Occupancy Detection using Wireless Sensor Network in Indoor Environment

Occupancy detection plays an important role in many smart buildings such as reducing building energy usage by controlling heating, ventilation and air conditioning (HVAC) systems, monitoring systems and managing lighting systems, tracking people in hospitals for medical issues, advertising to people in malls, and to search and rescue missions. The global positioning system (GPS) is used most widely as a localization system but highly inaccurate for indoor applications. The indoor environment is difficult to handle because along with the loss of signals, privacy is a major concern. Indoor tracking has many aspects in common with sensor localization in Wireless Sensor Networks (WSN). The contribution of this work is the demonstration of a nonintrusive approach to detect an occupancy in a building using wireless sensor networks to detect energy from cell phones in a secure facility and perform indoor localization based on the minimum mean square error (MMSE). To estimate the occupancy, the detected cellular signals information such as signal amplitude, frequency, power and detection time is sent to a fusion server, matched the detected signals by time and channel information, performed localization to estimate a location, and finally estimated the occupancy of rooms in a building from the estimated locations

A Non-invasive Technique to Detect Authentic/Counterfeit SRAM Chips

Many commercially available memory chips are fabricated worldwide in untrusted facilities. Therefore, a counterfeit memory chip can easily enter into the supply chain in different formats. Deploying these counterfeit memory chips into an electronic system can severely affect security and reliability domains because of their sub-standard quality, poor performance, and shorter lifespan. Therefore, a proper solution is required to identify counterfeit memory chips before deploying them in mission-, safety-, and security-critical systems. However, a single solution to prevent counterfeiting is challenging due to the diversity of counterfeit types, sources, and refinement techniques. Besides, the chips can pass initial testing and still fail while being used in the system. Furthermore, existing solutions focus on detecting a single counterfeit type (e.g., detecting recycled memory chips). This work proposes a framework that detects major counterfeit static random-access memory (SRAM) types by attesting/identifying the origin of the manufacturer. The proposed technique generates a single signature for a manufacturer and does not require any exhaustive registration/authentication process. We validate our proposed technique using 345 SRAM chips produced by major manufacturers. The silicon results show that the test scores ($F_{1}$ score) of our proposed technique of identifying memory manufacturer and part-number are 93% and 71%, respectively.Comment: This manuscript has been submitted for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

Imposex study on Thais bitubercularis in Merambong shoal, Johor

Imposex in Thais bitubercularis was observed in Merambong Shoal. About 18% from female individuals of the species were found to have male sexual organs, which is imposex at various stages. Stage 2 is the highest level of imposex discovered. The imposex occurrence was determined by calculated the proportion of females with imposex to the total number of female in sample and the degree of imposex was assessed using the vas deference sequence index and the percentage of females possessing the imposex characteristics. There are no significant relationship between the shell height and the number of spines between the degrees of imposex occurrence in T. bitubercularis. The present study also provided an overview of the present condition of the population health of T. bitubercularis at Merambong Shoal. Based on the male to female ratio, the population in Merambong Shoal showed in normal ratio which is 5:7 and this ratio is closer to normal ratio condition which is 4:7. The imposex incidence in the population reveals that T. bitubercularis in Merambong shoals are no exception from being exposed with the pollutant that can promote imposex occurrence. Tributyltin (TBT) which was recorded as the most suspected pollutant causing imposex in gastropod is expected contaminating the Johor Straits. However, the low incidence of imposex can be explain as the sample was collected from a shoal that receive high water current. The condition causing very low suspended particles or organic matter in the sediment resulting low TBT deposition in the sediment, then automatically low uptake by the biota living in the shoal

Approximate MRAM: High-performance and Power-efficient Computing with MRAM Chips for Error-tolerant Applications

Approximate computing (AC) leverages the inherent error resilience and is used in many big-data applications from various domains such as multimedia, computer vision, signal processing, and machine learning to improve systems performance and power consumption. Like many other approximate circuits and algorithms, the memory subsystem can also be used to enhance performance and save power significantly. This paper proposes an efficient and effective systematic methodology to construct an approximate non-volatile magneto-resistive RAM (MRAM) framework using consumer-off-the-shelf (COTS) MRAM chips. In the proposed scheme, an extensive experimental characterization of memory errors is performed by manipulating the write latency of MRAM chips which exploits the inherent (intrinsic/extrinsic process variation) stochastic switching behavior of magnetic tunnel junctions (MTJs). The experimental results and error-resilient image application reveal that the proposed AC framework provides a significant performance improvement and demonstrates a maximum reduction in MRAM write current of ~66% on average with negligible or no loss in output quality