A Lightweight N-Cover Algorithm For Diagnostic Fail Data Minimization

The increasing design complexity of modern ICs has made it extremely difficult and expensive to test them comprehensively. As the transistor count and density of circuits increase, a large volume of fail data is collected by the tester for a single failing IC. The diagnosis procedure analyzes this fail data to give valuable information about the possible defects that may have caused the circuit to fail. However, without any feedback from the diagnosis procedure, the tester may often collect fail data which is potentially not useful for identifying the defects in the failing circuit. This not only consumes tester memory but also increases tester data logging time and diagnosis run time. In this work, we present an algorithm to minimize the amount of fail data used for high quality diagnosis of the failing ICs. The developed algorithm analyzes outputs at which the tests failed and determines which failing tests can be eliminated from the fail data without compromising diagnosis accuracy. The proposed algorithm is used as a preprocessing step between the tester data logs and the diagnosis procedure. The performance of the algorithm was evaluated using fail data from industry manufactured ICs. Experiments demonstrate that on average, 43% of fail data was eliminated by our algorithm while maintaining an average diagnosis accuracy of 93%. With this reduction in fail data, the diagnosis speed was also increased by 46%

Appraisal of Noise Level Dissemination Surrounding Mining and Industrial Areas of Keonjhar, Odisha: a Comprehensive Approach Using Noise Mapping

Noise mapping is a well-established practice among the European nations, and it has been following for almost two decades. Recently, as per guidelines of the Directorate General of Mines Safety (DGMS), India, noise mapping has made mandatory in the mining expanses. This study is an effort made to map the noise levels in nearby areas of mines in the northern Keonjhar district. The motive of this study is to quantify the existing A-weighted time-average sound level (LAeq,T) in the study area to probe its effects on the human dwellings and noise sensitive areas with the probability of future development of the mines, roads and industrial & commercial zone. The LAeq,T was measured at 39 identified locations, includes industrial, commercial, residential and sensitive zones, 15 open cast mines, 3 major highways and 3 haulage roads. With the utilization of Predictor LimA Software and other GIS tools, the worked out data is mapped and noise contours are developed for the visualization and identification of the extent and distribution of sound levels across the study area. This investigation discloses that the present noise level at 60% of the locations in silence and residential zone are exposed to significantly high noise levels surpasses the prescribed limit of Central Pollution Control Board (CPCB), India. The observed day and night time LAeq,T level of both the zone, ranged between 43.2 - 62.2 dB (A) and 30.5 – 53.4 dB (A) respectively whereas, the average Ldn values vary between 32.7 – 51.2 dB (A). The extensive mobility of heavy vehicles adjoining the sensitive areas and a nearby plethora of open cast mines is the leading cause of exceeded noise levels. The study divulges that the delicate establishments like school and hospitals are susceptible to high noise levels throughout the day and night. A correlation between observed and software predicted values gives R2 of 0.605 for Ld; 0.217 for Ln; and 0.524 for Ldn. Finally, the mitigation measure proposed and demonstrated using contour map showing a significant reduction in the noise levels by 0 – 5.3 dB (A)

Realizing modeling and mapping tools to study the upsurge of noise pollution as a result of open-cast mining and transportation activities

Introduction: In open-cast mines, noise pollution has become a serious concern due to the extreme use of heavy earth moving machinery (HEMM). Materials and Methods: This study is focused to measure and assess the effects of the existing noise levels of major operational mines in the Keonjhar, Sundergadh, and Mayurbhanj districts of Odisha, India. The transportation noise levels were also considered in this study, which was predicted using the modified Federal Highway Administration (FHWA) model. Result and Discussion: It was observed that noise induced by HEMM such as rock breakers, jackhammers, dumpers, and excavators, blasting noise in the mining terrain, as well as associated transportation noise became a major source of annoyance to the habitants living in proximity to the mines. The noise produced by mechanized mining operations was observed between 74.3 and 115.2 dB(A), and its impact on residential areas was observed between 49.4 and 58.9 dB(A). In addition, the noise contour maps of sound level dispersion were demonstrated with the utilization of advanced noise prediction software tools for better understanding. Conclusion: Finally, the predicted values at residential zone and traffic noise are correlated with observed values, and the coefficient of determination, R2, was calculated to be 0.6891 and 0.5967, respectively

Assessment of Heterogeneous Road Traffic Noise in Nagpur

The objective of the study is to assess the noise scenario and evaluate prediction model for heterogeneous traffic conditions. In the past few years, road traffic of Nagpur has increased significantly due to the rapid increase in the number of vehicles. Noise levels are monitored at six different squares, characterized as interrupted traffic flow due to traffic signals, high population density and heavy traffic where the major sources of noise are engines, exhausts, tires interacting with the road, horns, sound of gear boxes, breaks, etc. The A-weighted time-average sound levels (LAeq;T) are measured at the different time of day during peak and off-peak traffic hours. To assess the traffic noise more precisely, the noise descriptors such as L10, L50, L90, LAeq;T, TNI (Traffic Noise Index), NPL (Noise Pollution Level) and NC (Noise Climate) are used. In the present study, the Federal Highway Administration (FHWA) noise prediction model is used for prediction of noise levels and it is observed that one-hour duration measured LAeq;T ranged from 71 to 76 dB(A) and 71.6 to 76.3 dB(A) during peak and off peak hours respectively. Due to the heavy traffic the peak hour Sound Exposure Levels (LAE) at all locations are exceeding permissible limit of 70 dB(A) prescribed by the World Health Organization (W.H.O). Off-peak traffic hour noise levels are within permissible limit except at two locations, Jagnade and HB town square. Significant correlation was obtained when best fit lines generated between measured and predicted values gives R2 of 0.455 for all time intervals. Chi-Square test (χ2) was also computed to investigate the noise levels at different squares. The results show that the inhabitants of Nagpur city are exposed to high transportation noise during daytime