  This report covers an intelligent decision support system (IDSS), which
handles an efficient and effective way to rapidly inspect containerized cargos
for defection. Defection is either cargo exposure to radiation, physical
damages such as holes, punctured surfaces, iron surface oxidation, etc. The
system uses a sorting array triangulation technique (SAT) and surface damage
detection (SDD) to conduct the inspection. This new technique saves time and
money on finding damaged goods during transportation such that, instead of
running $n$ inspections on $n$ containers, only 3 inspections per triangulation
or a ratio of $3:n$ is required, assuming $n > 3$ containers. The damaged stack
in the array is virtually detected contiguous to an actually-damaged cargo by
calculating nearby distances of such cargos, delivering reliable estimates for
the whole local stack population. The estimated values on damaged, somewhat
damaged and undamaged cargo stacks, are listed and profiled after being sorted
by the program, thereby submitted to the manager for a final decision. The
report describes the problem domain and the implementation of the simulator
prototype, showing how the system operates via software, hardware with/without
human agents, conducting real-time inspections and management per se.
