Fault-Tolerant Average Execution Time Optimization for General Purpose Multi-Processor System-on Chips

Fault-tolerance is due to the semiconductor technology development important, not only for safety-critical systems but also for general-purpose (non-safety critical) systems. However, instead of guaranteeing that deadlines always are met, it is for general-purpose systems important to minimize the average execution time (AET) while ensuring fault-tolerance. For a given job and a soft (transient) error probability, we define mathematical formulas for AET that includes bus communication overhead for both voting (active replication) and rollback-recovery with checkpointing (RRC). And, for a given multi-processor system-on-chip (MPSoC), we define integer linear programming (ILP) models that minimize AET including bus communication overhead when: (1) selecting the number of checkpoints when using RRC, (2) finding the number of processors and job-to-processor assignment when using voting, and (3) defining fault-tolerance scheme (voting or RRC) per job and defining its usage for each job. Experiments demonstrate significant savings in AET.

Is The Burden of Medical Education Affecting Ethics of Medical Treatment?

A substantial number of medical students in India have to bear an enormous financial burden for earning a bachelor's degree in medicine referred to as MBBS (bachelor of medicine and bachelor of surgery). This degree program lasts for four and one-half years followed by one year of internship. A postgraduate degree, such as MD, has to be pursued separately on completion of a MBBS. Every medical college in India is part of a hospital where the medical students get clinical exposure during the course of their study. All or at least a number of medical colleges in a given state are affiliated to a university that mainly plays a role of an overseeing authority. The medical colleges usually have no official interaction with other disciplines of education such as science and engineering, perhaps because of their independent location and absence of emphasis on medical research. However, many of the medical colleges are adept in imparting high-quality and sound training in medical practices including diagnostics and treatment. The medical colleges in India are generally of two types, i.e., government owned and private. Since only a limited number of seats are available across India in the former category of colleges, only a small fraction of aspiring candidates can find admission in these colleges after performing competitively in the relevant entrance tests. A major advantage of studying in these colleges is the nominal tuition fees that have to be paid. On the other hand, a large majority of would-be medical graduates have to seek admission in the privately run medical institutes in which the tuition and other related fees can be mind boggling when compared to their public counterparts. Except for candidates of exceptionally affluent background, the only alternative for fulfilling the dream of becoming a doctor is by financing one's study through hefty bank loans that may take years to pay back. It is often heard from patients that they are asked by doctors to undergo a plethora of diagnostic tests for apparently minor illnesses, which may financially benefit those prescribing the tests. The present paper attempts to throw light on the extent of disparity in cost of a medical education between state-funded and privately managed medical colleges in India; the average salary of a new medical graduate, which is often ridiculously low when compared to what is offered in entry-level engineering and business jobs; and the possible repercussions of this apparently unjust economic situation regarding the exploitation of patients.

FeatureMatch: A General ANNF Estimation Technique and its Applications

In this paper, we propose FeatureMatch, a generalised approximate nearest-neighbour field (ANNF) computation framework, between a source and target image. The proposed algorithm can estimate ANNF maps between any image pairs, not necessarily related. This generalisation is achieved through appropriate spatial-range transforms. To compute ANNF maps, global colour adaptation is applied as a range transform on the source image. Image patches from the pair of images are approximated using low-dimensional features, which are used along with KD-tree to estimate the ANNF map. This ANNF map is further improved based on image coherency and spatial transforms. The proposed generalisation, enables us to handle a wider range of vision applications, which have not been tackled using the ANNF framework. We illustrate two such applications namely: 1) optic disk detection and 2) super resolution. The first application deals with medical imaging, where we locate optic disks in retinal images using a healthy optic disk image as common target image. The second application deals with super resolution of synthetic images using a common source image as dictionary. We make use of ANNF mappings in both these applications and show experimentally that our proposed approaches are faster and accurate, compared with the state-of-the-art techniques.