Fast Radial Symmetry for Detecting Points of Interest

A new transform is presented that utilizes local radial symmetry to highlight points of interest within a scene. Its lowcomputational complexity and fast runtimes makes this method well-suited for real-time vision applications. The performance of the transform is demonstrated on a wide variety of images and compared with leading techniques from the literature. Both as a facial feature detector and as a generic region of interest detector the new transform is seen to offer equal or superior performance to contemporary techniques at a relatively low-computational cost. A real-time implementation of the transform is presented running at over 60 frames per second on a standard Pentium III PC.


Vision-based eye-gaze tracking for human computer interface

Eye-gaze is an input mode which has the potential of an efficient computer interface. Eye movement has been the focus of research in this area. Non-intrusive eyegaze tracking that allows slight head movement is addressed in this paper. A small 2D mark is employed as a reference to compensate for this movement. The iris center has been chosen for purposes of measuring eye movement. The gaze point is estimated after acquiring the eye movement data. Preliminary experimental results are given through a screen pointing application.


An Empirical Exploration of Curriculum Learning for Neural Machine Translation

Machine translation systems based on deep neural networks are expensive to train. Curriculum learning aims to address this issue by choosing the order in which samples are presented during training to help train better models faster. We adopt a probabilistic view of curriculum learning, which lets us flexibly evaluate the impact of curricula design, and perform an extensive exploration on a German-English translation task. Results show that it is possible to improve convergence time at no loss in translation quality. However, results are highly sensitive to the choice of sample difficulty criteria, curriculum schedule and other hyperparameters.


Algorithms for Lipschitz Learning on Graphs

We develop fast algorithms for solving regression problems on graphs where one is given the value of a function at some vertices, and must find its smoothest possible extension to all vertices. The extension we compute is the absolutely minimal Lipschitz extension, and is the limit for large p of p-Laplacian regularization. We present an algorithm that computes a minimal Lipschitz extension in expected linear time, and an algorithm that computes an absolutely minimal Lipschitz extension in expected time Õ(mn). The latter algorithm has variants that seem to run much faster in practice. These extensions are particularly amenable to regularization: we can perform l0-regularization on the given values in polynomial time and l1-regularization on the initial function values and on graph edge weights in time Õ(m). Our definitions and algorithms naturally extend to directed graphs.


Tanzer group IIB constricted ear repair with helical advancement and superior auricular artery chondrocutaneous flap.

Constricted ear deformity was first described by Tanzer and classified it into 3 groups according to the degree of constriction. The group IIB deformity involves the helix, scapha, and antihelical fold. The height of the ear is sharply reduced, and the soft tissue envelope is not sufficient to close the cartilage framework after expansion and reshaping.This study describes expanding the cartilage and increasing the height by advancing the helical root superiorly and repairing the skin-cartilage defect with a superior auricular artery chondrocutaneous flap in Tanzer group IIB constricted ear deformity.Six ears of 6 patients were treated with this technique during the past 3 years. All patients were satisfied with the appearance of their corrected ears, and the increase in height was maintained through the follow-up period.The described technique does not have the disadvantages and possible complications of harvesting a costal cartilage graft. Moving and fixing the root of helix to a more superior position provide the auricle with additional length. The superior auricular artery chondrocutaneous flap not only provides adequate soft tissue for primary closure of the anterior portion of the auricle but also aids in repairing the cartilage defect resulting from the superior advancement of the helix as well.


Hand Gesture Recognition using Sign Language

Sign Language is mostly used by deaf and dumb people. In order to improve the man machine interaction, sign language can be used as a way for communicating with machines. Most of the applications which enable sign language processing are using data gloves and other devices for interacting with computers. This restricts the freedom of users. So to avoid this, this system we capture live video stream through normal webcam and pass it as input and process this video to detect human gestures . These gestures can be signs represented in any sign language like American Sign Language (ASL), Indian Sign Language(ISL) etc. By processing these signs, this system can make an efficient system for searching using signs. In future this method of searching can be implemented in many areas such as railway station for searching the details of any trains, etc. Searching uses signs can play a major role in searching technique because the latest existing technique of searching is based on voice. But this may not work properly because each person has a different pronunciation. This system can overcome the drawbacks of the current available searching technique and thus can make every person under an umbrella of searching.


Thermoplastic Forming of Bulk Metallic Glass— A Technology for MEMS and Microstructure Fabrication

A technology for microelectromechanical systems (MEMS) and microstructure fabrication is introduced where the bulk metallic glass (BMG) is formed at a temperature where the BMG exist as a viscous liquid under an applied pressure into a mold. This thermoplastic forming is carried out under comparable forming pressure and temperatures that are used for plastics. The range of possible sizes in all three dimensions of this technology allows the replication of high strength features ranging from about 30 nm to centimeters with aspect ratios of 20 to 1, which are homogeneous and isotropic and free of stresses and porosity. Our processing method includes a hot-cutting technique that enables a clean planar separation of the parts from the BMG reservoir. It also allows to net-shape three-dimensional parts on the micron scale. The technology can be implemented into conventional MEMS fabrication processes. The properties of BMG as well as the thermoplastic formability enable new applications and performance improvements of existing MEMS devices and nanostructures


Mobile Multimedia Recommendation in Smart Communities: A Survey

Due to the rapid growth of Internet broadband access and proliferation of modern mobile devices, various types of multimedia (e.g., text, images, audios, and videos) have become ubiquitously available anytime. Mobile device users usually store and use multimedia contents based on their personal interests and preferences. Mobile device challenges such as storage limitation have, however, introduced the problem of mobile multimedia overload to users. To tackle this problem, researchers have developed various techniques that recommend multimedia for mobile users. In this paper, we examine the importance of mobile multimedia recommendation systems from the perspective of three smart communities, namely mobile social learning, mobile event guide, and context-aware services. A cautious analysis of existing research reveals that the implementation of proactive, sensor-based and hybrid recommender systems can improve mobile multimedia recommendations. Nevertheless, there are still challenges and open issues such as the incorporation of context and social properties, which need to be tackled to generate accurate and trustworthy mobile multimedia recommendations.


Wireless Geophone Network for remote monitoring and detection of landslides

Recent years have shown an alarmous increase in rain fall induced landslides. This has facilitated the need for having a monitoring system to predict the landslides which could eventually reduce the loss of human life. We have developed and deployed a Wireless Sensor Network to monitor rainfall induced landslide, in Munnar, South India. A successful landslide warning was issued in June 2009 using this system. The system is being enhanced by incorporating a Wireless Geophone Network to locate the initiation of landslide. The paper discusses an algorithm that was developed to analyze the geophone data and automatically detect the landslide signal. A novel method to localize the landslide initiation point is detailed. The algorithm is based on the time delay inherent in the transmission of waves through the surface of the earth. The approach detailed here does not require additional energy since the geophones are self excitatory. The error rate of the approach is much less when compared to the other localization methods like RSSI. The proposed algorithm is being tested and validated, in the landslide laboratory set up at our university.


A compact, 37% fractional bandwidth millimeter-wave phase shifter using a wideband lange coupler for 60-GHz and E-band systems

A wideband 57.7–84.2 GHz Phase Shifter is presented using a compact Lange coupler to generate in-phase and quadrature signal. The Lange coupler is followed by two balun transformers that provide the IQ vector modulation with differential I and Q signals. The implemented Phase Shifter demonstrates an average 6-dB insertion loss and 5-dB gain variation. The measured average rms phase and gain errors are 7 degrees and 1 dB, respectively. The phase shifter is implemented in GlobalFoundries 45-nm SOI CMOS technology using a trap-rich substrate. The chip area is 385 μm × 285 μm and the Phase Shifter consumes less than 17 mW. To the best of authors knowledge, this is the first phase shifter that covers both 60 GHz band and E-band frequencies with a fractional bandwidth of 37%.


An innovative ontology-driven system supporting personnel selection: the OntoHR case

This paper describes the initial development of an HRM system that aims to decrease the gap between higher vocational education and the labour market for a specific job in the ICT sector. This paper focuses specifically on the delineation of a process model and the selection of a suitable job role (information system analyst) that is valid across organisational and cultural boundaries. The process model implies various applied uses of this ontology-based system, including mapping qualifications in vocational education to current and valid job roles, testing and evaluating the student applicant on the basis of labour market driven competencies, and providing ad-hoc support to educational institutions by elucidating the weaknesses of particular VET curricula.


A Balanced Filtering Branch-Line Coupler

A balanced filtering branch-line coupler is proposed for the first time. The proposed design is realized by coupled microstrip lines and coupled-line-fed coupling structures. Based on this, the proposed design not only exhibits the functions of power dividing and filtering for differential-mode signals, but also can suppress the common-mode noise/signal and be easily connected with other balanced circuits. The dimension of the proposed design is similar to that of the traditional single-ended design. A prototype of the balanced filtering branch-line coupler centered at 1.87 GHz with the size of 0.33 λg × 0.42 λg is fabricated, where λg is the guided wavelength at the center frequency. The measured results exhibit the maximum insertion loss of 1.4 dB with a 3-dB fractional bandwidth of 3.5%.


Identifying personal genomes by surname inference.

Sharing sequencing data sets without identifiers has become a common practice in genomics. Here, we report that surnames can be recovered from personal genomes by profiling short tandem repeats on the Y chromosome (Y-STRs) and querying recreational genetic genealogy databases. We show that a combination of a surname with other types of metadata, such as age and state, can be used to triangulate the identity of the target. A key feature of this technique is that it entirely relies on free, publicly accessible Internet resources. We quantitatively analyze the probability of identification for U.S. males. We further demonstrate the feasibility of this technique by tracing back with high probability the identities of multiple participants in public sequencing projects.


Automatic web spreadsheet data extraction

Spreadsheets contain a huge amount of high-value data but do not observe a standard data model and thus are difficult to integrate. A large number of data integration tools exist, but they generally can only work on relational data. Existing systems for extracting relational data from spreadsheets are too labor intensive to support ad-hoc integration tasks, in which the correct extraction target is only learned during the course of user interaction.
 This paper introduces a system that automatically extracts relational data from spreadsheets, thereby enabling relational spreadsheet integration. The resulting integrated relational data can be queried directly or can be translated into RDF triples. When compared to standard techniques for spreadsheet data extraction on a set of 100 random Web spreadsheets, the system reduces the amount of human labor by 72% to 92%. In addition to the system design, we present the results of a general survey of more than 400,000 spreadsheets we downloaded from the Web, giving a novel view of how users organize their data in spreadsheets.


Analysis of waveguide slot-based structures using wide-band equivalent-circuit model

Analysis of geometrically complicated waveguide-based slotted arrays and filters is performed using a simple equivalent-circuit model. First, the circuit parameters (inductance and capacitance) of a simple waveguide slot-coupler problem are obtained through moment-method (MoM) analysis. The values of the lumped LC elements are virtually constant over the frequency range of interest (the X-band) for specific waveguide and slot dimensions. Based on the equivalent-circuit model of a single slot of two coupled waveguides, more complicated structures are then analyzed, such as slot coupler arrays and slot-based waveguide filters. The scattering parameters of these structures are obtained through circuit analysis, and are verified using the MoM and finite-difference time-domain method. Excellent agreement is observed over a wide band of frequencies and is confirmed by experimental results.


A Wearable Inertial Measurement System With Complementary Filter for Gait Analysis of Patients With Stroke or Parkinson’s Disease

This paper presents a wearable inertial measurement system and its associated spatiotemporal gait analysis algorithm to obtain quantitative measurements and explore clinical indicators from the spatiotemporal gait patterns for patients with stroke or Parkinson’s disease. The wearable system is composed of a microcontroller, a triaxial accelerometer, a triaxial gyroscope, and an RF wireless transmission module. The spatiotemporal gait analysis algorithm, consisting of procedures of inertial signal acquisition, signal preprocessing, gait phase detection, and ankle range of motion estimation, has been developed for extracting gait features from accelerations and angular velocities. In order to estimate accurate ankle range of motion, we have integrated accelerations and angular velocities into a complementary filter for reducing the accumulation of integration error of inertial signals. All 24 participants mounted the system on their foot to walk along a straight line of 10 m at normal speed and their walking recordings were collected to validate the effectiveness of the proposed system and algorithm. Experimental results show that the proposed inertial measurement system with the designed spatiotemporal gait analysis algorithm is a promising tool for automatically analyzing spatiotemporal gait information, serving as clinical indicators for monitoring therapeutic efficacy for diagnosis of stroke or Parkinson’s disease.


Preparation of Personalized-dose Salbutamol Sulphate Oral Films with Thermal Ink-Jet Printing

To evaluate the use of thermal ink-jetting as a method for dosing drugs onto oral films. A Hewlett-Packard printer cartridge was modified so that aqueous drug solutions replaced the ink. The performance of the printer as a function of print solution viscosity and surface tension was determined; viscosities between 1.1 and 1.5 mm2 s-1 were found to be optimal, while surface tension did not affect deposition. A calibration curve for salbutamol sulphate was prepared, which demonstrated drug deposition onto an acetate film varied linearly with concentration (r2 = 0.9992). The printer was then used to deposit salbutamol sulphate onto an oral film made of potato starch. It was found that when doses were deposited in a single pass under the print head, then the measured dose was in good agreement with the theoretical dose. With multiple passes the measured dose was always significantly less than the theoretical dose. It is proposed that the losses arise from erosion of the printed layer by shearing forces during paper handling. The losses were predictable, and the variance in dose deposited was always less than the BP limits for tablet and oral syrup salbutamol sulphate preparations. TIJ printing offers a rapid method for extemporaneous preparation of personalized-dose medicines.


From big smartphone data to worldwide research: The Mobile Data Challenge

This paper presents an overview of the Mobile Data Challenge (MDC), a large-scale research initiative aimed at generating innovations around smartphone-based research, as well as community-based evaluation of mobile data analysis methodologies. First, we review the Lausanne Data Collection Campaign (LDCC) – an initiative to collect unique, longitudinal smartphone data set for the MDC. Then, we introduce the Open and Dedicated Tracks of the MDC; describe the specific data sets used in each of them; discuss the key design and implementation aspects introduced in order to generate privacypreserving and scientifically relevant mobile data resources for wider use by the research community; and summarize the main research trends found among the 100+ challenge submissions. We finalize by discussing the main lessons learned from the participation of several hundred researchers worldwide in the MDC Tracks.


ESUR prostate MR guidelines 2012

The aim was to develop clinical guidelines for multi-parametric MRI of the prostate by a group of prostate MRI experts from the European Society of Urogenital Radiology (ESUR), based on literature evidence and consensus expert opinion. True evidence-based guidelines could not be formulated, but a compromise, reflected by “minimal” and “optimal” requirements has been made. The scope of these ESUR guidelines is to promulgate high quality MRI in acquisition and evaluation with the correct indications for prostate cancer across the whole of Europe and eventually outside Europe. The guidelines for the optimal technique and three protocols for “detection”, “staging” and “node and bone” are presented. The use of endorectal coil vs. pelvic phased array coil and 1.5 vs. 3 T is discussed. Clinical indications and a PI-RADS classification for structured reporting are presented. Key Points • This report provides guidelines for magnetic resonance imaging (MRI) in prostate cancer. • Clinical indications, and minimal and optimal imaging acquisition protocols are provided. • A structured reporting system (PI-RADS) is described.


An overview of pricing models for revenue management

This publication contains reprint articles for which IEEE does not hold copyright. Full text is not available on IEEE Xplore for these articles.


Recommendation Systems in Software Engineering

Software engineering is a knowledge-intensive activity that presents many information navigation challenges. Information spaces in software engineering include the source code and change history of the software, discussion lists and forums, issue databases, component technologies and their learning resources, and the development environment. The technical nature, size, and dynamicity of these information spaces motivate the development of a special class of applications to support developers: recommendation systems in software engineering (RSSEs), which are software applications that provide information items estimated to be valuable for a software engineering task in a given context. In this introduction, we review the characteristics of information spaces in software engineering, describe the unique aspects of RSSEs, present an overview of the issues and considerations involved in creating, evaluating, and using RSSEs, and present a general outlook on the current state of research and development in the field of recommendation systems for highly technical domains.


Relationship Between Visual-Motor Integration , Eye-Hand Coordination , and Quality of Handwriting

If the influence of visual-motor integration (copying forms) on the quality of handwriting has been widely investigated, the influence of eye-hand coordination (tracing item) has been less well analyzed. The Concise Assessment Scale for Children’s Handwriting (BHK), the Developmental Test of Visual Perception (DTVP-2), and the section “Manual Dexterity” of the Movement Assessment Battery for Children (M-ABC) were administered to a group of second grade children (N = 75; 8.1-year-olds). The association of visual-motor integration and eye-hand coordination are predictive of the quality of handwriting (p < . 001). These two skills should be taken into consideration when children are referred to occupational therapy for difficulties in handwriting.


The research and implementation of metadata cache backup technology based on CEPH file system

Based on research and analysis of the Ceph file system, the log cache backup scheme is proposed. The log cache backup scheme reduces metadata access delays by caching logs and reducing the time of storing logs to server clusters. In order to prevent the loss of cached data in metadata servers, a cached data backup scheme is proposed. Compared to the metadata management subsystem of the Ceph, the log cache backup scheme can effectively improve the access performance of metadata. Finally, based on open source codes of the Ceph file system, the log cache backup scheme is implemented. Compared to the performance of the Ceph metadata management subsystem, experiment results show that performance improvements of the log cache backup scheme are up to 11.5%.


A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects

We conducted a quantitative meta-analysis of previous research on the technology acceptance model (TAM) in an attempt to make well-grounded statements on the role of subjective norm. Furthermore, we compared TAM results by taking into account moderating effects of one individual-related factor (type of respondents), one technology-related factor (type of technology), and one contingent factor (culture). Results indicated a significant influence of subjective norm on perceived usefulness and behavioral intention to use. Moderating effects were found for all three factors. The findings yielded managerial implications for both intracompany and market-based settings. # 2006 Elsevier B.V. All rights reserved.


Triangular Tile Pasting P Systems for Pattern Generation

-In the area of membrane computing, a new computability model, called P system, which is a highly distributed, parallel theoretical computing model, was introduced by G.H. Păun [1], inspired from the cell structure and its function. There are several application areas of these P systems. Among these one area deals with the problem of picture generation. Ceterachi et al. [2] began a study on linking the two areas of membrane computing and picture grammars, which were not very much linked before, by relating P system and array-rewriting grammars generating picture languages and proposing array rewriting P systems. Iso-Triangular picture languages were introduced in [3], which can also generate rectangular and hexagonal picture languages. Tile pasting P system model for pattern generation was introduced in [4]. In this paper we propose a theoretical model of a P system using triangular tiles called Triangular tile pasting P system, for generating two dimensional patterns that are generated by gluing triangular tiles and study some of its properties. Keywords--Triangular Tiles, Array Grammars, Pasting System, Tile Pasting P Systems


Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers

We present a unifying framework for studying the solution of multiclass categorization problems by reducing them to multiple binary problems that are then solved using a margin-based binary learning algorithm. The proposed framework unifies some of the most popular approaches in which each class is compared against all others, or in which all pairs of classes are compared to each other, or in which output codes with error-correcting properties are used. We propose a general method for combining the classifiers generated on the binary problems, and we prove a general empirical multiclass loss bound given the empirical loss of the individual binary learning algorithms. The scheme and the corresponding bounds apply to many popular classification learning algorithms including support-vector machines, AdaBoost, regression, logistic regression and decision-tree algorithms. We also give a multiclass generalization error analysis for general output codes with AdaBoost as the binary learner. Experimental results with SVM and AdaBoost show that our scheme provides a viable alternative to the most commonly used multiclass algorithms.


Analysis of Emotionally Salient Aspects of Fundamental Frequency for Emotion Detection

During expressive speech, the voice is enriched to convey not only the intended semantic message but also the emotional state of the speaker. The pitch contour is one of the important properties of speech that is affected by this emotional modulation. Although pitch features have been commonly used to recognize emotions, it is not clear what aspects of the pitch contour are the most emotionally salient. This paper presents an analysis of the statistics derived from the pitch contour. First, pitch features derived from emotional speech samples are compared with the ones derived from neutral speech, by using symmetric Kullback-Leibler distance. Then, the emotionally discriminative power of the pitch features is quantified by comparing nested logistic regression models. The results indicate that gross pitch contour statistics such as mean, maximum, minimum, and range are more emotionally prominent than features describing the pitch shape. Also, analyzing the pitch statistics at the utterance level is found to be more accurate and robust than analyzing the pitch statistics for shorter speech regions (e.g., voiced segments). Finally, the best features are selected to build a binary emotion detection system for distinguishing between emotional versus neutral speech. A new two-step approach is proposed. In the first step, reference models for the pitch features are trained with neutral speech, and the input features are contrasted with the neutral model. In the second step, a fitness measure is used to assess whether the input speech is similar to, in the case of neutral speech, or different from, in the case of emotional speech, the reference models. The proposed approach is tested with four acted emotional databases spanning different emotional categories, recording settings, speakers and languages. The results show that the recognition accuracy of the system is over 77% just with the pitch features (baseline 50%). When compared to conventional classification schemes, the proposed approach performs better in terms of both accuracy and robustness.


The role of voice quality in communicating emotion, mood and attitude

This paper explores the role of voice quality in the communication of emotions, moods and attitudes. Listeners reactions to an utterance synthesised with seven different voice qualities were elicited in terms of pairs of opposing affective attributes. The voice qualities included harsh voice, tense voice, modal voice, breathy voice, whispery voice, creaky voice and lax–creaky voice. These were synthesised using a formant synthesiser, and the voice source parameter settings were guided by prior analytic studies as well as auditory judgements. Results offer support for some past observations on the association of voice quality and affect, and suggest a number of refinements in some cases. Listeners ratings further suggest that these qualities are considerably more effective in signalling milder affective states than the strong emotions. It is clear that there is no one-to-one mapping between voice quality and affect: rather a given quality tends to be associated with a cluster of affective attributes. 2002 Elsevier Science B.V. All rights reserved.


Emotion recognition in human-computer interaction

In this paper, we outline the approach we have developed to construct an emotion-recognising system. It is based on guidance from psychological studies of emotion, as well as from the nature of emotion in its interaction with attention. A neural network architecture is constructed to be able to handle the fusion of different modalities (facial features, prosody and lexical content in speech). Results from the network are given and their implications discussed, as are implications for future direction for the research.


New Support Vector Algorithms

We propose a new class of support vector algorithms for regression and classification. In these algorithms, a parameter lets one effectively control the number of support vectors. While this can be useful in its own right, the parameterization has the additional benefit of enabling us to eliminate one of the other free parameters of the algorithm: the accuracy parameter in the regression case, and the regularization constant C in the classification case. We describe the algorithms, give some theoretical results concerning the meaning and the choice of , and report experimental results.


RNN-based sequence prediction as an alternative or complement to traditional recommender systems

The recurrent neural networks have the ability to grasp the temporal patterns within the data. This is a property that can be used in order to help a recommender system better taking into account the user past history. Still the dimensionality problem that raises within the recommender system field also raises here as the number of items the system have to be aware of is susceptibility high. Recent research have studied the use of such neural networks at a user’s session level. This thesis rather examines the use of this technique at a whole user’s past history level associated with techniques such as embeddings and softmax sampling in order to accommodate with the high dimensionality. The proposed method results in a sequence prediction model that can be used as is for the recommender task or as a feature within a more complex system.


Developing multiple hypotheses in behavioral ecology

Researchers in behavioral ecology are increasingly turning to research methods that allow the simultaneous evaluation of hypotheses. This approach has great potential to increase our scientific understanding, but researchers interested in the approach should be aware of its long and somewhat contentious history. Also, prior to implementing multiple hypothesis evaluation, researchers should be aware of the importance of clearly specifying a priori hypotheses. This is one of the more difficult aspects of research based on multiple hypothesis evaluation, and we outline and provide examples of three approaches for doing so. Finally, multiple hypothesis evaluation has some limitations important to behavioral ecologists; we discuss two practical issues behavioral ecologists are likely to face.


The Sixth PASCAL Recognizing Textual Entailment Challenge

This paper presents the Fifth Recognizing Textual Entailment Challenge (RTE5). Following the positive experience of the last campaign, RTE-5 has been proposed for the second time as a track at the Text Analysis Conference (TAC). The structure of the RTE-5 Main Task remained unchanged, offering both the traditional two-way task and the threeway task introduced in the previous campaign. Moreover, a pilot Search Task was set up, consisting of finding all the sentences in a set of documents that entail a given hypothesis. 21 teams participated in the campaign, among which 20 in the Main Task (for a total of 54 runs) and 8 in the Pilot Task (for a total of 20 runs). Another important innovation introduced in this campaign was mandatory ablation tests that participants had to perform for all major knowledge resources employed by their systems.


Mindfulness-Based Cognitive Therapy and the Adult ADHD Brain: A Neuropsychotherapeutic Perspective

Attention-deficit/hyperactivity disorder (ADHD) is a recognized serious mental disorder that often persists into adulthood. The symptoms and impairments associated with ADHD often cause significant mental suffering in affected individuals. ADHD has been associated with abnormal neuronal activity in various neuronal circuits, such as the dorsofrontostriatal, orbitofrontostriatal, and frontocerebellar circuits. Psychopharmacological treatment with methylphenidate hydrochloride is recommended as the first-line treatment for ADHD. It is assumed that medication ameliorates ADHD symptoms by improving the functioning of the brain areas affected in the condition. However, side effects, contraindications, or non-response can limit the effectiveness of a psychopharmacological treatment for ADHD. It is therefore necessary to develop non-pharmacological interventions that target neuronal mechanisms associated with the condition in the same way as pharmacological treatment. We think that mindfulness meditation employed as a neuropsychotherapeutic intervention could help patients with ADHD to regulate impaired brain functioning and thereby reduce ADHD symptoms. In this paper, we highlight the mechanisms of such mindfulness meditation, and thus provide a rationale for further research and treatment development from a neuropsychotherapeutic perspective. We conclude that mindfulness meditation employed as a neuropsychotherapeutic intervention in therapy is a promising treatment approach in ADHD.


Image-based reconstruction of wire art

Objects created by connecting and bending wires are common in furniture design, metal sculpting, wire jewelry, etc. Reconstructing such objects with traditional depth and image based methods is extremely difficult due to their unique characteristics such as lack of features, thin elements, and severe self-occlusions. We present a novel image-based method that reconstructs a set of continuous 3D wires used to create such an object, where each wire is composed of an ordered set of 3D curve segments. Our method exploits two main observations: simplicity - wire objects are often created using only a small number of wires, and smoothness - each wire is primarily smoothly bent with sharp features appearing only at joints or isolated points. In light of these observations, we tackle the challenging image correspondence problem across featureless wires by first generating multiple candidate 3D curve segments and then solving a global selection problem that balances between image and smoothness cues to identify the correct 3D curves. Next, we recover a decomposition of such curves into a set of distinct and continuous wires by formulating a multiple traveling salesman problem, which finds smooth paths, i.e., wires, connecting the curves. We demonstrate our method on a wide set of real examples with varying complexity and present high-fidelity results using only 3 images for each object. We provide the source code and data for our work in the project website.


On the Semantics of Self-Unpacking Malware Code ∗

The rapid increase in attacks on software systems via malware such as viruses, worms, trojans, etc., has made it imperative to develop effective techniques for detecting and analyzing malware binaries. Such binaries are usually transmitted in packed or encrypted form, with the executable payload decrypted dynamically and then executed. In order to reason formally about their execution behavior, therefore, we need semantic descriptions that can capture this self-modifying aspect of their code. However, current approaches to the semantics of programs usually assume that the program code is immutable, which makes them inapplicable to self-unpacking malware code. This paper takes a step towards addressing this problem by describing a formal semantics for self-modifying code. We use our semantics to show how the execution of self-unpacking code can be divided naturally into a sequence of phases, and uses this to show how the behavior of a program can be characterized statically in terms of a program evolution graph. We discuss several applications of our work, including static unpacking and deobfuscation of encrypted malware and static cross-phase code analysis.


An Information Retrieval Approach For Automatically Constructing Software Libraries

Although software reuse presents clear advantages for programmer productivit.y and code reliability, it is not practiced enough. One of the reasons for the only moderate success of reuse is the lack of software libr'lries that facilitate the actual locating and understanding of reusable components. This paper dpscrihes II technology for automatically I\Ssembling large softwar~ libraries that promote softwarp rpuse by helping the user locate the components closest to hfO'r/his neeels Softwarp libraries are aut.omatically assemblfO'd from a set. of Ilnorganizpd component.s by using informat.ion rptripval techniques. The constrllction of the library is done in !.wo steps. First, attribut.es ;up alJtornal.ically pxtracted from nat.urlll language docllmpntat.ion by IIsing a npIV inJexing scheme ba~fO'd an t.he nntinns of lexical affinities anci quantity of inforrnllt.ion. Then, a hierarchy for browsing is alJtomat.iclllly generaterl using a clustering techniq1le that draws only nn the informlltion provided by the attribulps. Thanks to the frfO'p-!.pxt inrlexing se-heme, tools following this approach can accept free-style nat'Jral language 'luprips. This tpChllOlogy h1\.S bfO'en impll"ment .. d in the GURU ~ystpm, whirh h<l5 bpen applied 1.0 construct an organized library of Alx utilities. An exppriment. was rondllrtpd in orrlpr to pvalullte the n·t.rievll\ effectivl"nfO'ss of GURU 1\.5 compl\red to INFOExPLORER a hypprt.pxt lihrary syslplll for Alx 3 on the IBM RISe System/6000 series. We followpr\ Ihe usual evaluation prOf"pr\lJr!' us .. .! in informat.ion rptrifO'vl\l, hased upon recall and precision ml"a5IJrPS, and d"t.erminpd t 1111 I. nllr syst.f'Tll pr>rforms l!i% better on a random test set, while being milch le~s pxpensive to build than INFOEXl'LORF.R.


NOSEP: Nonoverlapping Sequence Pattern Mining With Gap Constraints

Sequence pattern mining aims to discover frequent subsequences as patterns in a single sequence or a sequence database. By combining gap constraints (or flexible wildcards), users can specify special characteristics of the patterns and discover meaningful subsequences suitable for their own application domains, such as finding gene transcription sites from DNA sequences or discovering patterns for time series data classification. Due to the inherent complexity of sequence patterns, including the exponential candidate space with respect to pattern letters and gap constraints, to date, existing sequence pattern mining methods are either incomplete or do not support the Apriori property because the support ratio of a pattern may be greater than that of its subpatterns. Most importantly, patterns discovered by these methods are either too restrictive or too general and cannot represent underlying meaningful knowledge in the sequences. In this paper, we focus on a nonoverlapping sequence pattern mining task with gap constraints, where a nonoverlapping sequence pattern allows sequence letters to be flexibly and maximally utilized for pattern discovery. A new Apriori-based nonoverlapping sequence pattern mining algorithm, NOSEP, is proposed. NOSEP is a complete pattern mining algorithm, which uses a specially designed data structure, Nettree, to calculate the exact occurrence of a pattern in the sequence. Experimental results and comparisons on biology DNA sequences, time series data, and Gazelle datasets demonstrate the efficiency of the proposed algorithm and the uniqueness of nonoverlapping sequence patterns compared to other methods.


A CMOS Transceiver for a Multistandard 13.56-MHz RFID Reader SoC

A CMOS transceiver for a multistandard 13.56-MHz radio-frequency identification reader system-on-a-chip (SoC) is designed and fabricated. The SoC consists of an RF/analog part for modulation/demodulation and a digital part for controlling the transceiver functionality. Prior to designing the integrated circuit, pre-experiments using discrete components and commercial tags are performed. With the results, overall functions and specifications are determined. For supporting multistandard, several blocks are designed with digital controls according to the standards. In the transmitter, a digitally controlled amplitude modulator for various modulation indexes and a power control circuit are adopted. In the receiver, a variable gain amplifier and a level-controllable comparator, which are also controlled digitally according to the standard, are introduced. The full transceiver SoC is implemented in the Chartered 0.18-¿m CMOS technology. The measurement results of the implemented chip indicate that the designed transceiver operates in a multistandard mode.


The contagious leader: impact of the leader's mood on the mood of group members, group affective tone, and group processes.

The present study examined the effects of leaders' mood on (a) the mood of individual group members, (b) the affective tone of groups, and (c) 3 group processes: coordination, effort expenditure, and task strategy. On the basis of a mood contagion model, the authors found that when leaders were in a positive mood, in comparison to a negative mood, (a) individual group members experienced more positive and less negative mood, and (b) groups had a more positive and a less negative affective tone. The authors also found that groups with leaders in a positive mood exhibited more coordination and expended less effort than did groups with leaders in a negative mood. Applied implications of the results are discussed.


A 3-Month, Randomized, Double-Blind, Placebo-Controlled Study Evaluating the Ability of an Extra-Strength Marine Protein Supplement to Promote Hair Growth and Decrease Shedding in Women with Self-Perceived Thinning Hair

An oral marine protein supplement (MPS) is designed to promote hair growth in women with temporary thinning hair (Viviscal Extra Strength; Lifes2good, Inc., Chicago, IL). This double-blind, placebo-controlled study assessed the ability of MPS to promote terminal hair growth in adult women with self-perceived thinning hair associated with poor diet, stress, hormonal influences, or abnormal menstrual cycles. Adult women with thinning hair were randomized to receive MPS (N = 30) or placebo (N = 30) twice daily for 90 days. Digital images were obtained from a 4 cm(2) area scalp target area. Each subject's hair was washed and shed hairs were collected and counted. After 90 days, these measures were repeated and subjects completed Quality of Life and Self-Assessment Questionnaires. MPS-treated subjects achieved a significant increase in the number of terminal hairs within the target area (P < 0.0001) which was significantly greater than placebo (P < 0.0001). MPS use also resulted in significantly less hair shedding (P = 0.002) and higher total Self-Assessment (P = 0.006) and Quality of Life Questionnaires scores (P = 0.035). There were no reported adverse events. MPS promotes hair growth and decreases hair loss in women suffering from temporary thinning hair. This trial is registered with ClinicalTrials.gov Identifier: NCT02297360.


Digital Advertising: An Information Scientist's Perspective

Digital online advertising is a form of promotion that uses the Internet and World Wide Web for the express purpose of delivering marketing messages to attract customers. Examples of online advertising include text ads that appear on search engine results pages, banner ads, in-text ads, or Rich Media ads that appear on regular web pages, portals, or applications. Over the past 15 years online advertising, a $65 billion industry worldwide in 2009, has been pivotal to the success of the World Wide Web. That being said, the field of advertising has been equally revolutionized by the Internet, World Wide Web, and more recently, by the emergence of the social web, and mobile devices. This success has arisen largely from the transformation of the advertising industry from a low-tech, human intensive, “Mad Men” way of doing work to highly optimized, quantitative, mathematical, computerand data-centric processes that enable highly targeted, personalized, performance based advertising. This chapter provides a clear and detailed overview of the technologies and business models that are transforming the field of online advertising primarily from statistical machine learning and information science perspectives.


Design on the low-leakage diode string for using in the power-rail ESD clamp circuits in a 0.35-/spl mu/m silicide CMOS process

A new design of the diode string with very low leakage current is proposed for use in the ESD clamp circuits across the power rails. By adding an NMOS-controlled lateral SCR (NCLSCR) device into the stacked diode string, the leakage current of this new diode string with six stacked diodes at 5 V (3.3 V) forward bias can be reduced to only 2.1 (1.07) nA at a temperature of 125/spl deg/C in a 0.35 /spl mu/m silicide CMOS process, whereas the previous designs have a leakage current in the order of mA. The total blocking voltage of this new design with NCLSCR can be linearly adjusted by changing the number of the stacked diodes in the diode string without causing latch-up danger across the power rails. From the experimental results, the human-body-model ESD level of the ESD clamp circuit with the proposed low-leakage diode string is greater than 8 kV in a 0.35 /spl mu/m silicide CMOS process by using neither ESD implantation nor the silicide-blocking process modifications.


Zero-bias autoencoders and the benefits of co-adapting features

Regularized training of an autoencoder typically results in hidden unit biases that take on large negative values. We show that negative biases are a natural result of using a hidden layer whose responsibility is to both represent the input data and act as a selection mechanism that ensures sparsity of the representation. We then show that negative biases impede the learning of data distributions whose intrinsic dimensionality is high. We also propose a new activation function that decouples the two roles of the hidden layer and that allows us to learn representations on data with very high intrinsic dimensionality, where standard autoencoders typically fail. Since the decoupled activation function acts like an implicit regularizer, the model can be trained by minimizing the reconstruction error of training data, without requiring any additional regularization.


Global prevalence of glaucoma and projections of glaucoma burden through 2040: a systematic review and meta-analysis.

PURPOSE
Glaucoma is the leading cause of global irreversible blindness. Present estimates of global glaucoma prevalence are not up-to-date and focused mainly on European ancestry populations. We systematically examined the global prevalence of primary open-angle glaucoma (POAG) and primary angle-closure glaucoma (PACG), and projected the number of affected people in 2020 and 2040.

DESIGN
Systematic review and meta-analysis.

PARTICIPANTS
Data from 50 population-based studies (3770 POAG cases among 140,496 examined individuals and 786 PACG cases among 112 398 examined individuals).

METHODS
We searched PubMed, Medline, and Web of Science for population-based studies of glaucoma prevalence published up to March 25, 2013. Hierarchical Bayesian approach was used to estimate the pooled glaucoma prevalence of the population aged 40-80 years along with 95% credible intervals (CrIs). Projections of glaucoma were estimated based on the United Nations World Population Prospects. Bayesian meta-regression models were performed to assess the association between the prevalence of POAG and the relevant factors.

MAIN OUTCOME MEASURES
Prevalence and projection numbers of glaucoma cases.

RESULTS
The global prevalence of glaucoma for population aged 40-80 years is 3.54% (95% CrI, 2.09-5.82). The prevalence of POAG is highest in Africa (4.20%; 95% CrI, 2.08-7.35), and the prevalence of PACG is highest in Asia (1.09%; 95% CrI, 0.43-2.32). In 2013, the number of people (aged 40-80 years) with glaucoma worldwide was estimated to be 64.3 million, increasing to 76.0 million in 2020 and 111.8 million in 2040. In the Bayesian meta-regression model, men were more likely to have POAG than women (odds ratio [OR], 1.36; 95% CrI, 1.23-1.52), and after adjusting for age, gender, habitation type, response rate, and year of study, people of African ancestry were more likely to have POAG than people of European ancestry (OR, 2.80; 95% CrI, 1.83-4.06), and people living in urban areas were more likely to have POAG than those in rural areas (OR, 1.58; 95% CrI, 1.19-2.04).

CONCLUSIONS
The number of people with glaucoma worldwide will increase to 111.8 million in 2040, disproportionally affecting people residing in Asia and Africa. These estimates are important in guiding the designs of glaucoma screening, treatment, and related public health strategies.


Fuzzy Logic Based-Map Matching Algorithm for Vehicle Navigation System in Urban Canyons

With the rapid progress in the development of wireless technology, Global Positioning System (GPS) based vehicle navigation systems are being widely deployed in automobiles to serve the location-based needs of users and for efficient traffic management. An essential process in vehicle navigation is to map match the position obtained from GPS (or/and other sensors) on a road network map. This process of map matching in turn helps in mitigating errors from navigation solution. GPS based vehicle navigation systems have difficulties in tracking vehicles in urban canyons due to poor satellite availability. High Sensitivity GPS (HS GPS) receivers can alleviate this problem by acquiring and tracking weak signals (and increasing the availability), but at the cost of high measurement noise and errors due to multipath and cross correlation. Position and velocity results in such conditions are typically biased and have unknown distributions. Thus filtering and other statistical methods are difficult to implement. Soft computing has replaced classical computing on many fronts where uncertainties are difficult to model. Fuzzy logic, based on fuzzy reasoning concepts, is one of the most widely used soft computational methods. In many circumstances, it can take noisy, imprecise input, to yield crisp (i.e. numerically accurate) output. Fuzzy logic can be applied effectively to map match the output from a HS GPS receiver in urban canyons because of its inherent tolerance to imprecise inputs. This paper describes a map matching algorithm based on fuzzy logic. The input of the system comes from a SiRF HS XTrac GPS receiver and a low cost gyro (Murata ENV-05G). The results show an improvement in tracking the vehicle in urban canyon conditions.


Automatic design of low power CMOS buffer-chain circuit using differential evolutionary algorithm and particle swarm optimization

PSO and DE algorithms and its variants are used for the optimization of a buffer-chain circuit and the results of all the algorithms are compared in this literature. By testing these algorithms on different mathematical benchmark functions the best parameter values of buffer chain circuit are obtained in such a way that it reduces the error between simulated output and optimized output, hence giving the best circuit performance. Evolutionary algorithms are better in performance and speed than the classical methods. 130nm CMOS technology has been used in this work. With the help of these parameter values the circuit simulator gives the values of power consumption, symmetry, rise time and fall time, which are almost closer to the desired specification of the buffer chain circuit.


Memory Interference as a Determinant of Language Comprehension

The parameters of the human memory system constrain the operation of language comprehension processes. In the memory literature, both decay and interference have been proposed as causes of forgetting; however, while there is a long history of research establishing the nature of interference effects in memory, the effects of decay are much more poorly supported. Nevertheless, research investigating the limitations of the human sentence processing mechanism typically focus on decay-based explanations, emphasizing the role of capacity, while the role of interference has received comparatively little attention. This paper reviews both accounts of difficulty in language comprehension by drawing direct connections to research in the memory domain. Capacity-based accounts are found to be untenable, diverging substantially from what is known about the operation of the human memory system. In contrast, recent research investigating comprehension difficulty using a retrieval-interference paradigm is shown to be wholly consistent with both behavioral and neuropsychological memory phenomena. The implications of adopting a retrieval-interference approach to investigating individual variation in language comprehension are discussed.


Sentiment analysis is the procedure by which information is extracted from the opinions, appraisals and emotions of people in regards to entities, events and their attributes. In decision making, the opinions of others have a significant effect on customers ease in making choices regards to online shopping, choosing events, products, entities. In this paper, a rule based domain independent sentiment analysis method is proposed. The proposed method classifies subjective and objective sentences from reviews and blog comments. The semantic score of subjective sentences is extracted from SentiWordNet to calculate their polarity as positive, negative or neutral based on the contextual sentence structure. The results show the effectiveness of the proposed method and it outperforms the machine learning methods. The proposed method achieves an accuracy of 87% at the feedback level and 83% at the sentence level for comments. [Aurangzeb khan, Muhammad Zubair Asghar, Shakeel Ahmad, Fazal Masud Kundi, Maria Qasim, Furqan. Sentiment Classification through Semantic Orientation Using SentiWordNet. Life Sci J 2014; 11(10):309-315] (ISSN: 1097-8135). http://www.lifesciencesite.com. 44


Radar Signal Processing for Jointly Estimating Tracks and Micro-Doppler Signatures

The aim of the radar systems is to collect information about their surroundings. In many scenarios besides static targets there are numerous moving objects with very different characteristics, such as extent, movement behavior or micro-Doppler spread. It would be most desirable to have algorithms that extract all information on static and moving object automatically, without a system operator. In this paper, we present measurements conducted with a commercially available high-resolution multi-channel linear frequency-modulated continuous-wave radar and algorithms that do not only produce radar images but a description of the scenario on a higher level. After conventional spectrum estimation and thresholding, we present a clustering stage that combines individual detections and generates representations of each target individually. This stage is followed by a Kalman filter based multi-target tracking block. The tracker allows us to follow each target and collect its properties over time. With this method of jointly estimating tracks and characteristics of each individual target in a scenario, inputs for classifiers can be generated. Which, in turn, will be able to generate information that could be used for driver assistance or alarm trigger systems.


The medial patellofemoral ligament: location of femoral attachment and length change patterns resulting from anatomic and nonanatomic attachments.

BACKGROUND
Incompetence of the medial patellofemoral ligament (MPFL) is an integral factor in patellofemoral instability. Reconstruction of this structure is gaining increasing popularity. However, the natural behavior of the ligament is still not fully understood, and crucially, the correct landmark for femoral attachment of the MPFL at surgery is poorly defined.

PURPOSE
To determine the length change pattern of the native MPFL, investigate the effect of nonanatomic femoral and differing patellar attachment sites on length changes, and recommend a reproducible femoral attachment site for undertaking anatomic MPFL reconstruction.

STUDY DESIGN
Descriptive laboratory study.

METHODS
Eight cadaveric knees were dissected of skin and subcutaneous fat and mounted in a kinematics rig with the quadriceps tensioned. The MPFL length change patterns were measured for combinations of patellar and femoral attachments using a suture and displacement transducer. Three attachments were along the superomedial border of the patella, and 5 femoral attachments were at the MPFL center and 5 mm proximal, distal, anterior, and posterior to this point. Reproducibility of attachment sites was validated radiographically.

RESULTS
The femoral attachment point, taking the anterior-posterior medial femoral condyle diameter to be 100%, was identified 40% from the posterior, 50% from the distal, and 60% from the anterior border of the medial femoral condyle. This point was most isometric, with a mean maximal length change to the central patellar attachment of 2.1 mm from 0° to 110° of knee flexion. The proximal femoral attachment resulted in up to 6.4 mm mean lengthening and the distal attachment up to 9.1 mm mean shortening through 0° to 110° of knee flexion, resulting in a significantly nonisometric graft (P < .05).

CONCLUSION
We report the anatomic femoral and patellar MPFL graft attachments, with confirmation of the reproducibility of their location and resulting kinematic behavior. Nonanatomic attachments caused significant loss of isometry.

CLINICAL RELEVANCE
The importance of an anatomically positioned MPFL reconstruction is highlighted, and an identifiable radiographic point for femoral tunnel position is suggested for use intraoperatively.


The Spatial Orienting paradigm: How to design and interpret spatial attention experiments

This paper is conceived as a guide that will describe the very well known Spatial Orienting paradigm, used to explore attentional processes in healthy individuals as well as in people suffering from psychiatric disorders and brain-damaged patients. The paradigm was developed in the late 1970s, and since then, it has been used in thousands of attentional studies. In this review, we attempt to describe, the paradigm for the naïf reader, and explain in detail when is it used, which variables are usually manipulated, how to interpret its results, and how can it be adapted to different populations and methodologies. The main goal of this review is to provide a practical guide to researchers who have never used the paradigm that will help them design their experiments, as a function of their theoretical and experimental needs. We also focus on how to adapt the paradigm to different technologies (such as event-related potentials, functional resonance imaging, or transcranial magnetic stimulation), and to different populations by presenting an example of its use in brain-damaged patients.


A gesture-free geometric approach for mid-air expression of design intent in 3D virtual pottery

The advent of depth cameras has enabled mid-air interactions for shape modeling with bare hands. Typically, these interactions employ a finite set of pre-defined hand gestures to allow users to specify modeling operations in virtual space. However, human interactions in real world shaping processes (such as pottery or sculpting) are complex, iterative, and continuous. In this paper, we show that the expression of user intent in shaping processes can be derived from the geometry of contact between the hand and the manipulated object. Specifically, we describe the design and evaluation of a geometric interaction technique for bare-hand mid-air virtual pottery. We model the shaping of a pot as a gradual and progressive convergence of the pot’s profile to the shape of the user’s hand represented as a point-cloud (PCL). Thus, a user does not need to learn, know, or remember any gestures to interact with our system. Our choice of pottery simplifies the geometric representation, allowing us to systematically study how users use their hands and fingers to express the intent of deformation during a shaping process. Our evaluations demonstrate that it is possible to enable users to express their intent for shape deformation without the need for a fixed set of gestures for clutching and deforming a shape.


A comparative study of differential evolution variants for global optimization

In this paper, we present an empirical comparison of some Differential Evolution variants to solve global optimization problems. The aim is to identify which one of them is more suitable to solve an optimization problem, depending on the problem's features and also to identify the variant with the best performance, regardless of the features of the problem to be solved. Eight variants were implemented and tested on 13 benchmark problems taken from the specialized literature. These variants vary in the type of recombination operator used and also in the way in which the mutation is computed. A set of statistical tests were performed in order to obtain more confidence on the validity of the results and to reinforce our discussion. The main aim is that this study can help both researchers and practitioners interested in using differential evolution as a global optimizer, since we expect that our conclusions can provide some insights regarding the advantages or limitations of each of the variants studied.


An AES Smart Card Implementation Resistant to Power Analysis Attacks

In this article we describe an efficient AES software implementation that is well suited for 8-bit smart cards and resistant against power analysis attacks. Our implementation masks the intermediate results and randomizes the sequence of operations at the beginning and the end of the AES execution. Because of the masking, it is secure against simple power analysis attacks, template attacks and first-order DPA attacks. Due to the combination of masking and randomization, it is resistant against higher-order DPA attacks. Resistant means that a large number of measurements is required for a successful attack. This expected number of measurements is tunable. The designer can choose the amount of randomization and thereby increase the number of measurements. This article also includes a practical evaluation of the countermeasures. The results prove the theoretical assessment of the countermeasures to be correct.


Approximating Kinematics for Tracked Mobile Robots

In this paper we propose a kinematic approach for tracked mobile robots in order to improve motion control and pose estimation. Complex dynamics due to slippage and track–soil interactions make it difficult to predict the exact motion of the vehicle on the basis of track velocities. Nevertheless, real-time computations for autonomous navigation require an effective kinematics approximation without introducing dynamics in the loop. The proposed solution is based on the fact that the instantaneous centers of rotation (ICRs) of treads on the motion plane with respect to the vehicle are dynamics-dependent, but they lie within a bounded area. Thus, optimizing constant ICR positions for a particular terrain results in an approximate kinematic model for tracked mobile robots. Two different approaches are presented for off-line estimation of kinematic parameters: (i) simulation of the stationary response of the dynamic model for the whole velocity range of the vehicle; (ii) introduction of an experimental setup so that a genetic algorithm can produce the model from actual sensor readings. These methods have been evaluated for on-line odometric computations and low-level motion control with the Aurigaα mobile robot on a hard-surface flat soil at moderate speeds. KEY WORDS—tracked vehicles, kinematic control, mobile robotics, parameter identification, dynamics simulation


Practical Stabilization of a Skid-steering Mobile Robot - A Kinematic-based Approach

This paper presents kinematic control problem of skid-steering mobile robot using practical smooth and time-varying stabilizer. The stability result is proved using Lyapunov analysis and takes into account both input signal saturation and uncertainty of kinematics. In order to ensure stable motion of the robot the condition of permissible velocities is formulated according to dynamic model and wheel-surface interaction. Theoretical considerations are illustrated by simulation results


Experimental kinematics for wheeled skid-steer mobile robots

This work aims at improving real-time motion control and dead-reckoning of wheeled skid-steer vehicles by considering the effects of slippage, but without introducing the complexity of dynamics computations in the loop. This traction scheme is found both in many off-the-shelf mobile robots due to its mechanical simplicity and in outdoor applications due to its maneuverability. In previous works, we reported a method to experimentally obtain an optimized kinematic model for skid-steer tracked vehicles based on the boundedness of the instantaneous centers of rotation (ICRs) of treads on the motion plane. This paper provides further insight on this method, which is now proposed for wheeled skid-steer vehicles. It has been successfully applied to a popular research robotic platform, pioneer P3-AT, with different kinds of tires and terrain types.


Adaptive Trajectory Tracking Control of Skid-Steered Mobile Robots

Skid-steered mobile robots have been widely used for terrain exploration and navigation. In this paper, we present an adaptive trajectory control design for a skid-steered wheeled mobile robot. Kinematic and dynamic modeling of the robot is first presented. A pseudo-static friction model is used to capture the interaction between the wheels and the ground. An adaptive control algorithm is designed to simultaneously estimate the wheel/ground contact friction information and control the mobile robot to follow a desired trajectory. A Lyapunov-based convergence analysis of the controller and the estimation of the friction model parameter are presented. Simulation and preliminary experimental results based on a four-wheel robot prototype are demonstrated for the effectiveness and efficiency of the proposed modeling and control scheme


Trajectory Tracking Control of a Four-Wheel Differentially Driven Mobile Robot

We consider the trajecto ry tracking control problem for a 4-wheel differentially driven mobile robot moving on an outdoor terrain. A dynamic model is presented accounting for the effects of wheel skidding. A model-based nonlinear controller is designed, following the dynamic feedback linearization paradigm. A n operational nonholonomic constraint is added at this stage, so as to obtain a predictable behavior for the instantaneous center of rotation thus preventing excessive skidding. The controller is then robustijied, using conventional linear techniques, against uncertainty in the soil parameters at the ground-wheel contact. Simulation results show the good performance in tracking spline-type trajectories on a virtual terrain with varying characteristics.


Impact of probing procedure on flip chip reliability

Probe-after-bump is the primary probing procedure for flip chip technology, since it does not directly contact the bump pad, and involves a preferred under bump metallurgy (UBM) step coverage on the bump pads. However, the probe-after-bump procedure suffers from low throughputs and high cost. It also delays the yield feedback to the fab, and makes difficult clarification of the accountability of the low yield bumped wafer between the fab and the bumping house. The probe-before-bump procedure can solve these problems, but the probing tips may over-probe or penetrate the bump pads, leading to poor UBM step coverage, due to inadequate probing conditions or poor probing cards. This work examines the impact of probing procedure on flip chip reliability, using printing and electroplating bumpings on aluminum and copper pads. Bump height, bump shear strength, die shear force, UBM step coverage, and reliability testing are used to determine the influence of probing procedure on flip chip reliability. The experimental results reveal that bump quality and reliability test in the probe-before-bump procedure, under adequate probing conditions, differ slightly from the corresponding items in the probe-after-bump procedure. UBM gives superior step coverage of probe marks in both probe-before-bump and probe-after-bump procedures, implying that UBM achieves greater adhesion and barrier function between the solder bump and the bump pad. Both printing and electroplating bump processes slightly influence all evaluated items. The heights of probe marks on the copper pads are 40–60% lower than those on the aluminum pads, indicating that the copper pad enhances UBM step coverage. This finding reveals that adequate probing conditions of the probe-before-bump procedure are suited to sort flip chip wafers and do not significantly affect bump height, bump shear strength, die shear force, or flip chip reliability. 2002 Elsevier Science Ltd. All rights reserved.


Anomaly Detection with Attribute Conflict Identification in Bank Customer Data

In commercial banks, data centers often integrates different data sources, which represent complex and independent business systems. Due to the inherent data variability and measurement or execution errors, there may exist some abnormal customer records (data). Existing automatic abnormal customer detection methods are outlier detection which focuses on the differences between customers, and it ignores the other possible abnormal customers caused by the inner features confliction of each customer. In this paper, we designed a method to identify abnormal customer information whose inner attributes are conflicting (confliction detection). We integrate the outlier detection and the confliction identification techniques together, as the final abnormality detection. This can provide a complete and accurate support of customer data for commercial bank's decision making. Finally, we have performed experiments on a dataset from a Chinese commercial bank to demonstrate the effectiveness of our method.


Subcutaneous penile vein thrombosis (Penile Mondor's Disease): pathogenesis, diagnosis, and therapy.

OBJECTIVES
In international studies, only a few data are available on subcutaneous penile vein thrombosis. The pathogenesis is unknown, and no general recommendation exists regarding therapy.

METHODS
A total of 25 patients with the clinical picture of a "superficial penile vein thrombosis" were treated at our policlinic. All patients had noted sudden and almost painless indurations on the penile dorsal surface. The extent of the thrombosis varied. Detailed anamnesis, ultrasonography, and routine laboratory tests were performed for all patients, knowing that primary therapy was conservative.

RESULTS
No patient indicated any pain. Some reported a feeling of tension in the area of the thrombosis. In all patients, the thrombosis occurred in the dorsal penis shaft. It was close to the sulcus coronarius in 21 patients, near the penis root in 3, and in the entire penis shaft in 1 patient. The length of the thrombotic vein was between 2 and 4 cm. The ultrasound results were similar for all patients. The primary treatment was conservative for all patients. Recovery was achieved in more than 92% of cases (23 of 25 patients) using conservative therapy, which consisted of local dressing with heparin ointment (10,000 IU) and oral application of an antiphlogistic for 14 days. In 2 cases, thrombectomy was necessary.

CONCLUSIONS
Extended imaging diagnosis does not improve the evaluation of the extent of a superficial penile vein thrombosis. Conservative primary therapy consisting of heparin ointment and oral application of antiphlogistics is sufficient. If the thrombosis persists after conservative therapy, surgery is indicated.


Control of Inertial Stabilization Systems Using Robust Inverse Dynamics Control and Adaptive Control

This paper presents an advanced controller design for an Inertial stabilization system. The system has a 2-DOF gimbal which will be attached to an aviation vehicle. Due to dynamics modeling errors, and friction and disturbances from the outside environment, the tracking accuracy of an airborne gimbal may severely degrade. So, an advanced controller is needed. Robust inverse dynamics control and the adaptive control are used in the inner loop or gimbal servo-system to control the gimbal motion. An indirect line of sight (LOS) stabilization will be controlled by the outer loop controller. A stabilizer is mounted on the base of the system to measure base rate and orientation of the gimbal in reference to the fixed reference frame. It can withstand high angular slew rates. The experimental results illustrate that the proposed controllers are capable enough to overcome the disturbances and the impact of LOS disturbances on the tracking performance.


How well developed are altmetrics? A cross-disciplinary analysis of the presence of ‘alternative metrics’ in scientific publications

In this paper an analysis of the presence and possibilities of altmetrics for bibliometric and performance analysis is carried out. Using the web based tool Impact Story, we collected metrics for 20,000 random publications from the Web of Science. We studied both the presence and distribution of altmetrics in the set of publications, across fields, document types and over publication years, as well as the extent to which altmetrics correlate with citation indicators. The main result of the study is that the altmetrics source that provides the most metrics is Mendeley, with metrics on readerships for 62.6 % of all the publications studied, other sources only provide marginal information. In terms of relation with citations, a moderate spearman correlation (r = 0.49) has been found between Mendeley readership counts and citation indicators. Other possibilities and limitations of these indicators are discussed and future research lines are outlined.


Deep Recurrent Regression for Facial Landmark Detection

We propose a novel end-to-end deep architecture for face landmark detection, based on a deep convolutional and deconvolutional network followed by carefully designed recurrent network structures. The pipeline of this architecture consists of three parts. Through the first part, we encode an input face image to resolution-preserved deconvolutional feature maps via a deep network with stacked convolutional and deconvolutional layers. Then, in the second part, we estimate the initial coordinates of the facial key points by an additional convolutional layer on top of these deconvolutional feature maps. In the last part, by using the deconvolutional feature maps and the initial facial key points as input, we refine the coordinates of the facial key points by a recurrent network that consists of multiple long short-term memory components. Extensive evaluations on several benchmark data sets show that the proposed deep architecture has superior performance against the state-of-the-art methods.


Adaptive hypertext navigation based on user goals and context

Hypertext systems allow flexible access to topics of information, but this flexibility has disadvantages. Users often become lost or overwhelmed by choices. An adaptive hypertext system can overcome these disadvantages by recommending information to users based on their specific information needs and preferences. Simple associative matrices provide an effective way of capturing these user preferences. Because the matrices are easily updated, they support the kind of dynamic learning required in an adaptive system. HYPERFLEX, a prototype of an adaptive hypertext system that learns, is described. Informal studies with HYPERFLEX clarify the circumstances under which adaptive systems are likely to be useful, and suggest that HYPERFLEX can reduce time spent searching for information by up to 40%. Moreover, these benefits can be obtained with relatively little effort on the part of hypertext authors or users. The simple models underlying HYPERFLEX's performance may offer a general and useful alternative to more sophisticated modelling techniques. Conditions under which these models, and similar adaptation techniques, might be most useful are discussed.


Unfriending on Facebook: Friend Request and Online/Offline Behavior Analysis

Objectives: Determine the role of the friend request in unfriending decisions. Find factors in unfriending decisions and find differences in the perception of online and offline behaviors that vary depending on the unfriending decision. Method: Survey research conducted online. 690 surveys about unfriending were analyzed using exploratory statistical techniques. Results: The research results show that the initiator of the friend request has more than their expected share of unfriends compared to those who receive the friend request. There are online and offline factors for unfriending decisions; the research identified six constructs to evaluate unfriending decisions. There are 4 components for online behaviors (unimportant/frequent posts, polarizing posts, inappropriate posts and everyday life posts) and 2 offline components (disliked behavior and changes in the relationship). Survey respondents who said they unfriend for online reasons were more likely to agree that the person posted too frequently about unimportant topics, polarizing topics, and inappropriate topics compared to those who unfriended for offline reasons.


Semantics of context-free languages

“Meaning” may be assigned to a string in a context-free language by defining “attributes” of the symbols in a derivation tree for that string. The attributes can be defined by functions associated with each production in the grammar. This paper examines the implications of this process when some of the attributes are “synthesized”, i.e., defined solely in terms of attributes of thedescendants of the corresponding nonterminal symbol, while other attributes are “inherited”, i.e., defined in terms of attributes of theancestors of the nonterminal symbol. An algorithm is given which detects when such semantic rules could possibly lead to circular definition of some attributes. An example is given of a simple programming language defined with both inherited and synthesized attributes, and the method of definition is compared to other techniques for formal specification of semantics which have appeared in the literature.


TweetCred: A Real-time Web-based System for Assessing Credibility of Content on Twitter

During large scale events, a large volume of content is posted on Twitter, but not all of this content is trustworthy. The presence of spam, advertisements, rumors and fake images reduces the value of information collected from Twitter, especially during sudden-onset crisis events where information from other sources is scarce. In this research work, we describe various facets of assessing the credibility of usergenerated content on Twitter during large scale events, and develop a novel real-time system to assess the credibility of tweets. Firstly, we develop a semi-supervised ranking model using SVM-rank for assessing credibility, based on training data obtained from six high-impact crisis events of 2013. An extensive set of forty-five features is used to determine the credibility score for each of the tweets. Secondly, we develop and deploy a system–TweetCred–in the form of a browser extension, a web application and an API at the link: http://twitdigest.iiitd.edu.in/TweetCred/. To the best of our knowledge, this is the first research work to develop a practical system for credibility on Twitter and evaluate it with real users. TweetCred was installed and used by 717 Twitter users within a span of three weeks. During this period, a credibility score was computed for more than 1.1 million unique tweets. Thirdly, we evaluated the real-time performance of TweetCred , observing that 84% of the credibility scores were displayed within 6 seconds. We report on the positive feedback that we received from the system’s users and the insights we gained into improving the system for future iterations.


Monte-Carlo Tree Search: A New Framework for Game AI

Classic approaches to game AI require either a high quality of domain knowledge, or a long time to generate effective AI behaviour. These two characteristics hamper the goal of establishing challenging game AI. In this paper, we put forward Monte-Carlo Tree Search as a novel, unified framework to game AI. In the framework, randomized explorations of the search space are used to predict the most promising game actions. We will demonstrate that Monte-Carlo Tree Search can be applied effectively to (1) classic board-games, (2) modern board-games, and (3) video games.


Low-Cost Wideband and High-Gain Slotted Cavity Antenna Using High-Order Modes for Millimeter-Wave Application

A novel single-fed low-cost wideband and high-gain slotted cavity antenna based on substrate integrated waveguide (SIW) technology using high-order cavity modes is demonstrated in this paper. High-order resonant modes (TE130, TE310, TE330) inside the cavity are simply excited by a coaxial probe which is located at the center of the antenna. Energy is coupled out of the cavity by a 3 × 3 slot array etched on the top surface of the cavity. Two antennas with different polarizations are designed and tested. Measured results show that the linearly polarized prototype achieves an impedance bandwidth (|S11| <; -10 dB) of > 26% (28 to 36.6 GHz), and a 1-dB gain bandwidth of 14.1% (30.3 to 34.9 GHz). In addition, a measured maximum gain of 13.8 dBi and radiation efficiency of 92% are obtained. To generate circularly polarized radiation, a rotated dipole array is placed in front of the proposed linearly polarized antenna. Measured results show that the circularly polarized antenna exhibits a common bandwidth (10-dB return loss bandwidth, 3-dB axial ratio bandwidth, and 1-dB gain bandwidth) of 11%.


Medical Concept Embeddings via Labeled Background Corpora

In recent years, we have seen an increasing amount of interest in low-dimensional vector representations of words. Among other things, these facilitate computing word similarity and relatedness scores. The most well-known example of algorithms to produce representations of this sort are the word2vec approaches. In this paper, we investigate a new model to induce such vector spaces for medical concepts, based on a joint objective that exploits not only word co-occurrences but also manually labeled documents, as available from sources such as PubMed. Our extensive experimental analysis shows that our embeddings lead to significantly higher correlations with human similarity and relatedness assessments than previous work. Due to the simplicity and versatility of vector representations, these findings suggest that our resource can easily be used as a drop-in replacement to improve any systems relying on medical concept similarity measures.


Exploring Ways To Mitigate Sensor-Based Smartphone Fingerprinting

Modern smartphones contain motion sensors, such as accelerometers and gyroscopes. These sensors have many useful applications; however, they can also be used to uniquely identify a phone by measuring anomalies in the signals, which are a result from manufacturing imperfections. Such measurements can be conducted surreptitiously in the browser and can be used to track users across applications, websites, and visits. We analyze techniques to mitigate such device fingerprinting either by calibrating the sensors to eliminate the signal anomalies, or by adding noise that obfuscates the anomalies. To do this, we first develop a highly accurate fingerprinting mechanism that combines multiple motion sensors and makes use of (inaudible) audio stimulation to improve detection. We then collect measurements from a large collection of smartphones and evaluate the impact of calibration and obfuscation techniques on the classifier accuracy.


Yelp Dataset Challenge: Review Rating Prediction

Review websites, such as TripAdvisor and Yelp, allow users to post online reviews for various businesses, products and services, and have been recently shown to have a significant influence on consumer shopping behaviour. An online review typically consists of free-form text and a star rating out of 5. The problem of predicting a user’s star rating for a product, given the user’s text review for that product, is called Review Rating Prediction and has lately become a popular, albeit hard, problem in machine learning. In this paper, we treat Review Rating Prediction as a multi-class classification problem, and build sixteen different prediction models by combining four feature extraction methods, (i) unigrams, (ii) bigrams, (iii) trigrams and (iv) Latent Semantic Indexing, with four machine learning algorithms, (i) logistic regression, (ii) Näıve Bayes classification, (iii) perceptrons, and (iv) linear Support Vector Classification. We analyse the performance of each of these sixteen models to come up with the best model for predicting the ratings from reviews. We use the dataset provided by Yelp for training and testing the models.


Prospects of encoding Java source code in XML

Currently, the only standard format for representing Java source code is plain text-based. This paper explores the prospects of using Extensible Markup Language (XML) for this purpose. XML enables the leverage of tools and standards more powerful than those available for plain-text formats, while retaining broad accessibility. The paper outlines the potential benefits of future XML grammars that would allow for improved code structure and querying possibilities; code extensions, construction, and formatting; and referencing parts of code. It also introduces the concept of grammar levels and argues for the inclusion of several grammar levels into a common framework. It discusses conversions between grammars and some practical grammar design issues. Keywords—XML, Java, source code, parsing, code formatting


Semantic integration of UML class diagram with semantic validation on segments of mappings

Recently, attention has focused on the software development, specially by different teams that are geographically distant to support collaborative work. Management, description and modeling in such collaborative approach are through several tools and techniques based on UML models. It is now supported by a large number of tools. Most of these systems have the ability to compare different UML models, assist developers, designers and also provide operations for the merging and integration, to produce a coherent model. The contribution in this article is both to integrate a set of UML class diagrams using mappings that are result of alignment and assist designers and developers in the integration. In addition, we will present a detail integration of UML models with the validation of mappings between them. Such validation helps to achieve correct, consistent and coherent integrated model.


On partial least squares in head pose estimation: How to simultaneously deal with misalignment

Head pose estimation is a critical problem in many computer vision applications. These include human computer interaction, video surveillance, face and expression recognition. In most prior work on heads pose estimation, the positions of the faces on which the pose is to be estimated are specified manually. Therefore, the results are reported without studying the effect of misalignment. We propose a method based on partial least squares (PLS) regression to estimate pose and solve the alignment problem simultaneously. The contributions of this paper are two-fold: 1) we show that the kernel version of PLS (kPLS) achieves better than state-of-the-art results on the estimation problem and 2) we develop a technique to reduce misalignment based on the learned PLS factors.


Reinforcement Learning and Approximate Dynamic Programming for Feedback Control

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Toward a Rational Choice Process Theory of Internet Scamming: The Offender's Perspective

Internet fraud scam is a crime enabled by the Internet to swindle Internet users. The global costs of these scams are in the billions of US dollars. Existing research suggests that scammers maximize their economic gain. Although this is a plausible explanation, since the idea of the scam is to fool people to send money, this explanation alone, cannot explain why individuals become Internet scammers. An equally important, albeit unexplored riddle, is the question of what strategies Internet scammers adopt to perform the act. As a first step to address these gaps, we interviewed five Internet scammers in order to develop a rational choice process theory of Internet scammers’ behavior. The initial results suggest that an interplay of socioeconomic and dynamic thinking processes explains why individuals drift into Internet scamming. Once an individual drifts into Internet scamming, a successful scam involves two processes: persuasive strategy and advance fee strategy.


Catfish Binary Particle Swarm Optimization for Feature Selection

The feature selection process constitutes a commonly encountered problem of global combinatorial optimization. This process reduces the number of features by removing irrelevant, noisy, and redundant data, thus resulting in acceptable classification accuracy. Feature selection is a preprocessing technique with great importance in the fields of data analysis and information retrieval processing, pattern classification, and data mining applications. This paper presents a novel optimization algorithm called catfish binary particle swarm optimization (CatfishBPSO), in which the so-called catfish effect is applied to improve the performance of binary particle swarm optimization (BPSO). This effect is the result of the introduction of new particles into the search space (“catfish particles”), which replace particles with the worst fitness by the initialized at extreme points of the search space when the fitness of the global best particle has not improved for a number of consecutive iterations. In this study, the K-nearest neighbor (K-NN) method with leave-oneout cross-validation (LOOCV) was used to evaluate the quality of the solutions. CatfishBPSO was applied and compared to six classification problems taken from the literature. Experimental results show that CatfishBPSO simplifies the feature selection process effectively, and either obtains higher classification accuracy or uses fewer features than other feature selection methods.


Powering 3 Dimensional Microrobots : Power Density Limitations ∗

Many types of electrostatic and electromagnetic microactuators have been developed. It is important to understand the fundamental performance limitations of these actuators for use in micro-robotic systems. The most important consideration for micro mobile robots is the effective power density of the actuator. As inertia and gravitional forces become less significant for small robots, typical metrics for macro-robots, such as torque-to-weight ratio, are not appropriate. A very significant problem with micro-actuators for robotics is the need for efficient transmissions to obtain large forces and torques at low speeds from inherently high speed low force actuators.


FPGA based Time-to-Digital Converter

High-resolution Time-to-Digital converter (TDC) is one of the crucial blocks in Highenergy nuclear physics time of flight experiments. The contemporary time interval measurement techniques rely on employing methods like Time-to-Amplitude Conversion, Vernier method, Delay Locked Loops (DLL), Tapped Delay Lines (TDL), Differential Delay Lines (DDL) etc. Recently, FPGA based TDC designs with merits of low cost, fast development cycle and re-programmability are reported [1]. The TDC implementation in FPGA have design challenges and issues like, lack of direct control over the propagation delays, unpredictable Place & Route (P&R) delays and delay variations due to Process, Voltage & Temperature (PVT) variations. In the TDC design presented here, the resolution below the minimum gate delay is achieved by employing differential (Vernier oscillator) technique. The predictable P&R is achieved by manual P&R of the critical elements and avoiding the use of digital synthesis tools. Further, in order to compensate for the delay variations due to PVT, a calibration methodology is developed and implemented. By implementing the design in a Flash-based FPGA, the low power design objective is achieved.


Looking good: factors affecting the likelihood of having cosmetic surgery

The present study examined various factors associated with the likelihood of having cosmetic surgery in a community sample of Austrian participants. One-hundred and sixty-eight women and 151 men completed a questionnaire measuring how likely they were to consider common cosmetic procedures. The results showed that women were more likely than men to consider most cosmetic procedures. Path analysis revealed that personal experience of having had cosmetic surgery was a significant predictor of future likelihood, while media exposure (viewing advertisements or television programs, or reading articles about cosmetic surgery) mediated the influence of vicarious experience and sex. These results are discussed in relation to previous work examining the factors associated with the likelihood of having cosmetic surgery.


A Case for NOW (Networks of Workstations) - Abstract

In this paper, we argue that because of recent technology advances, networks of workstations (NOWs) are poised to become the primary computing infrastructure for science and engineering, from low end interactive computing to demanding sequential and parallel applications. We identify three opportunities for NOWs that will benefit endusers: dramatically improving virtual memory and file system performance by using the aggregate DRAM of a NOW as a giant cache for disk; achieving cheap, highly available, and scalable file storage by using redundant arrays of workstation disks, using the LAN as the I/O backplane; and finally, multiple CPUs for parallel computing. We describe the technical challenges in exploiting these opportunities – namely, efficient communication hardware and software, global coordination of multiple workstation operating systems, and enterprise-scale network file systems. We are currently building a 100-node NOW prototype to demonstrate that practical solutions exist to these technical challenges.


Discriminative Embeddings of Latent Variable Models for Structured Data

Kernel classifiers and regressors designed for structured data, such as sequences, trees and graphs, have significantly advanced a number of interdisciplinary areas such as computational biology and drug design. Typically, kernels are designed beforehand for a data type which either exploit statistics of the structures or make use of probabilistic generative models, and then a discriminative classifier is learned based on the kernels via convex optimization. However, such an elegant two-stage approach also limited kernel methods from scaling up to millions of data points, and exploiting discriminative information to learn feature representations. We propose, structure2vec, an effective and scalable approach for structured data representation based on the idea of embedding latent variable models into feature spaces, and learning such feature spaces using discriminative information. Interestingly, structure2vec extracts features by performing a sequence of function mappings in a way similar to graphical model inference procedures, such as mean field and belief propagation. In applications involving millions of data points, we showed that structure2vec runs 2 times faster, produces models which are 10, 000 times smaller, while at the same time achieving the state-of-the-art predictive performance.


Searching for processes and threads in Microsoft Windows memory dumps

Current tools to analyze memory dumps of systems running Microsoft Windows usually build on the concept of enumerating lists maintained by the kernel to keep track of processes, threads and other objects. Therefore they will frequently fail to detect objects that are already terminated or which have been hidden by Direct Kernel Object Manipulation