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The malfunction variables of power stations are related to the areas of weather, physical structure, control and load behaviour. To predict temporal power failure is difficult due to their unpredictable characteristics. As high accuracy is normally required, the estimation of failures of short-term temporal prediction is highly difficult. This study presents a method for converting stochastic behaviour into a stable pattern, which can subsequently be used in a short-term estimator. For this conversion, K-means clustering is employed, followed by Long-Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) algorithms are used to perform the Short-term estimation. The environment, the operation and the generated signal factors are all simulated using mathematical models. Weather parameters and load samples have been collected as part of a data set. Monte-Carlo simulation using MATLAB programming has been used to conduct experimental estimation of failures. The estimated failures of the experiment are then compared with the actual system temporal failures and found to be in good match. Therefore, for any future power grid, there is a testbed ready to estimate the future failures.

One of the most neglected sources of energy loss is streetlights that generate too much light in areas where it is not required. Energy waste has enormous economic and environmental effects. In addition, due to the conventional manual nature of operation, streetlights are frequently seen being turned ‘ON’ during the day and ‘OFF’ in the evening, which is regrettable even in the twenty-first century. These issues require automated streetlight control in order to be resolved. This study aims to develop a novel streetlight controlling method by combining a smart transport monitoring system powered by computer vision technology with a closed circuit television (CCTV) camera that allows the light-emitting diode (LED) streetlight to automatically light up with the appropriate brightness by detecting the presence of pedestrians or vehicles and dimming the streetlight in their absence using semantic image segmentation from the CCTV video streaming. Consequently, our model distinguishes daylight and nighttime, which made it feasible to automate the process of turning the streetlight ‘ON’ and ‘OFF’ to save energy consumption costs. According to the aforementioned approach, geo-location sensor data could be utilised to make more informed streetlight management decisions. To complete the tasks, we consider training the U-net model with ResNet-34 as its backbone. Validity of the models is guaranteed with the use of assessment matrices. The suggested concept is straightforward, economical, energy-efficient, long-lasting and more resilient than conventional alternatives.

This chapter analyzes the construction of secrecy under the current U.S. export control regime for dual-use technologies and discusses its application for two technologies: research on a class of semiconductors used in military and civilian applications and biotechnology research on select agents. We argue that the assignment of technologies and countries to categories controlled under the export regime is an exercise in creating secret knowledge, in which the broad category of “the other” is subdivided between those who are forbidden to know and those who are not (and thus implicitly are qualified to become a party to the secret). We draw attention to the social cost of errors made in applying these categories, and point to some remaining issues.

Theories in the justice area have proliferated with little regard either to their interconnections or to the general scientific criterion of parsimony. Recently, there have been several attempts to integrate justice theories. However, there has been practically no discussion of theoretical method, that is, precisely what it means to integrate two or more theories and what must be done to accomplish it. This chapter advocates building integrated theories by developing smaller modularized theories that can be formulated and assembled for multiple purposes. To illustrate the process, we construct five modules addressing different areas connected to justice issues and show how they may be combined into a single integrated structure.