Towards Big Data Electricity Theft Detection Based on Improved RUSBoost Classifiers in Smart Grid

The advent of the new millennium, with the promises of the digital age and space technology, favors humankind in every perspective. The technology provides us with electric power and has infinite use in multiple electronic accessories. The electric power produced by different sources is distributed to consumers by the transmission line and grid stations. During the electric transmission from primary sources, there are various methods by which to commit energy theft. Energy theft is a universal electric problem in many countries, with a possible loss of billions of dollars for electric companies. This energy contention is deep rooted, having so many root causes and rugged solutions of a technical nature. Advanced Metering Infrastructure (AMI) is introduced with no adequate results to control and minimize electric theft. Until now, so many techniques have been applied to overcome this grave problem of electric power theft. Many researchers nowadays use machine learning algorithms, trying to combat this problem, giving better results than previous approaches. Random Forest (RF) classifier gave overwhelmingly good results with high accuracy. In our proposed solution, we use a novel Convolution Neural Network (CNN) with RUSBoost Manta Ray Foraging Optimization (rus-MRFO) and RUSBoost Bird Swarm Algorithm (rus-BSA) models, which proves to be very innovative. The accuracy of our proposed approaches, rus-MRFO and rus-BSA, are 91.5% and a 93.5%, respectively. The proposed techniques have shown promising results and have strong potential to be applied in future.

Sources of Active Ingredients for Sustainable Corrosion Inhibitors

Metal corrosion is a grave problem, having deleterious effects on human health, the economy, the environment, and many engineering schemes, for example, automobiles, aircraft, naval vessels, and pipelines. For the confirmation of enduring reliability and stability of alloys and metals, corrosion-protective surfaces are of the greatest significance, for example, ions and water, through restraining their interactions with corrosive species. Though, their applied submissions are frequently bounded whichever through deprived mechanical robustness or else through the incapability to resist low surface tension liquids, for example, alcohols and oil. In this chapter, we have focused on diverse materials as sustainable corrosion inhibitors such as organic corrosion inhibitors, green corrosion inhibitors, and polymer-based corrosion inhibitors to protect materials from being corroded. Amongst them, we especially focus on green corrosion inhibitors as a consequence of simple manufacturing, easy availability, cost-effectiveness, and biodegradable nature.

Electronic Phenotyping to Identify Patients with Heart Failure Using a National Clinical Information Database in Japan

Heart failure (HF) is a grave problem in the clinical and public health sectors. The aim of this study is to develop a phenotyping algorithm to identify patients with HF by using the medical information database network (MID-NET) in Japan. Methods: From April 1 to December 31, 2013, clinical data of patients with HF were obtained from MID-NET. A phenotyping algorithm was developed with machine learning by using disease names, examinations, and medications. Two doctors validated the cases by manually reviewing the medical records according to the Japanese HF guidelines. The algorithm was also validated with different cohorts from an inpatient database of the Department of Cardiovascular Medicine at Tohoku University Hospital. Results: The algorithm, which initially had low precision, was improved by incorporating the value of B-type natriuretic peptide and the combination of medications related to HF. Finally, the algorithm on a different cohort was verified with higher precision (35.0% → 87.8%). Conclusions: Proper algorithms can be used to identify patients with HF.

Introduction

In 2014, a deadly epidemic of Ebola hemorrhagic fever ravaged three countries in West Africa. While the disease barely hit the United States, it caused widespread panic that sometimes threatened the safety of African immigrants in the United States. Five years later, a global pandemic of a novel coronavirus, later named COVID-19, quickly picked up speed around the world. In the face of a serious and very real threat, many Americans ignored the warnings and a vocal minority even insisted that the pandemic was not real. While the particulars of each of these examples might be quite different, they have something very important in common: science denial. This introductory chapter provides an overview of how such widespread science denialist views come into existence and how they spread. The authors outline the eight chapters of this book, which go into depth on different psychological mechanisms behind this phenomenon. Finally, they provide a preview of some of the solutions we have devised in response to this grave problem.

Supervised and Unsupervised Machine Learning Methodologies for Crime Pattern Analysis

Crime is a grave problem that affects all countries in the world. The level of crime in a country has a big impact on its economic growth and quality of life of citizens. In this paper, we provide a survey of trends of supervised and unsupervised machine learning methods used for crime pattern analysis. We use a spatiotemporal dataset of crimes in San Francisco, CA to demonstrate some of these strategies for crime analysis. We use classification models, namely, Logistic Regression, Random Forest, Gradient Boosting and Naive Bayes to predict crime types such as Larceny, Theft, etc. and propose model optimization strategies. Further, we use a graph based unsupervised machine learning technique called core periphery structures to analyze how crime behavior evolves over time. These methods can be generalized to use for different counties and can be greatly helpful in planning police task forces for law enforcement and crime prevention.

Incidence of Malignant Diseases in Punjab: A Retrospective Study in a Tertiary Level Government Hospital in Punjab

Introduction: Cancer is a grave problem with increase in incidence of various malignancies at an alarming rate in Punjab. Crude annual incidence rate of all cancers in Punjab has increased from 58.0 in 1990 to 85.5 in 2016 while crude mortality incidence ratio of all cancers in Punjab is 0.61 in females and 0.81 in males. Not only it is increasing mortality and morbidity, but it is also increasing the economic burden on a state already facing financial crisis. The exact burden of malignancies is not well known, although many local surveys have been done. Aim: To know the accurate burden of malignant diseases in patients presenting to a tertiary level government hospital in Punjab. Materials and Methods: A retrospective observational study in which data of all cases diagnosed to have malignant disease on histopathology at Government Medical College and Rajindra Hospital, Patiala, Punjab, from January, 2006 to December, 2015. The data was retrieved on yearly basis and total of each malignant disease was done to know the exact incidence of various malignancies over the decade by the measure of relative frequency. Results: A total of 4270 patients (41.65% in age group 41 to 70 years) were diagnosed to have malignant disease on histopathology out of which 2341 (54.82%) were females and 1929 (45.18%) were males. Leading causes of malignancy were the cancers of the f emale genital organs i.e., 20.05%, followed by breast cancer i.e., 1 8.17% and cancers of lip, oral cavity and pharynx i.e., 15.36%. Conclusions: Maximum incidence was seen in Carcinoma Breast followed by carcinoma cervix and carcinoma larynx. Early screening, timely diagnosis and management along with regular scrutiny of records should be done in routine to know the actual burden of cancer in the society.

Balloon Dilatation of Laryngotracheal Stenosis: Hospital Ampang Experience

The upper airway is a crucial structure. It becomes a grave problem should it be narrowed. Several methods of treatment were rendered for patients with laryngotracheal stenosis. We share our experience with the combination total intravenous anaesthesia and apneic pause technique with or without steroid injection. Four cases of laryngotracheal stenosis were observed in Hospital Ampang: two adult and two paediatric cases. Age, gender, causative factor, stenosis segment length, grade or severity were observed before and after dilatation, number of dilatation were observed and compared. The outcome measures are decannulation and avoidance of tracheostomy. All cases had improvement of symptoms. Half or 50% of the patient required repeated balloon dilatations. The paediatric cases successfully avoided tracheostomy while the adult cases successfully decannulated with no complication from the procedure. Balloon dilatation by total intravenous anaesthesia coupled with apneic method is a safe and effective method of treatment for the narrowed airway.

Geospatial Dynamics of Cropping pattern and Agricultural Efficiency in Kashmir Valley-A Northwestern Himalayan Region, India

Food (in)security and agricultural efficiency is a major challenge in many of the world’s mountain ranges. The particular physical characteristics of mountains and associated socioeconomic factors, mountain regions all over the world face challenges in terms of food security and cropping pattern, although at different levels. Mountains in developing countries are sites of poverty. About 40 percent of the mountain population or nearly 300 million people are estimated to be vulnerable to food insecurity, of these, nearly 90 percent live in rural areas and almost half of those are likely to be chronically hungry. The present study also focuses on the regional disparities in agricultural efficiency and cropping pattern across different tehsils of Kashmir Valley-A north-western part of Himalayas. The study was carried out across thirty-nine spatial units (Tehsils) among different districts of Kashmir valley in GIS and remote sensing environment. Both primary and secondary data was employed. The study shows that the productivity of paddy, maize, and wheat is showing an increasing trend among all tehsils of Kashmir valley from 2011 to 2017 but the area under these crops is decreasing at an alarming rate leading a food deficit of 21.70 percent. So, agriculture planning is badly needed to curb this grave problem and impose restrictions to land conversion a burning issue nowadays

Sleeping in Church: Preaching, Boredom, and the Struggle for Attention in Medieval and Early Modern Europe

The word “boredom” was not used in English before the eighteenth century. Does this mean that pre-eighteenth-century people did not experience boredom? Or did their experience of boredom differ from ours? This article approaches these questions by exploring the history of people falling asleep in church, and asking whether boredom played a role in their slumber. Across the confessional spectrum in premodern Europe, religious somnolence was depicted as a common and grave problem. The preoccupation with this problem went hand in hand with longstanding ecclesiastic concerns about deficient attention among the flock. Probing medieval and early modern controversies about somnolence and boredom offers insight on two levels: First, it helps to correct the problematic presentism that identifies boredom as a quintessentially modern condition. Second, exploring the long history of boredom adds nuance to our understanding of premodern culture and mentalities, revealing—in the case of religious audiences—a struggle for attention that we would not expect to find in a world in which religion reigned supreme. The article also touches on other social and institutional contexts (such as court life) in which boredom was both endogenous and endemic.

Sustainable Development

Sustainable development was famously defined in the 1987 Brundtland Report as “development that meets the needs of the present without compromising the ability of future generations to meet their needs.” In the decades that followed, anthropologists have made clear that the term requires a more specific redefinition within its context of late capitalism. For anthropologists, sustainable development evokes the effort of extending capitalist discipline while remaining conscious of economic or environmental constraints. Yet they have also found that sustainable development discourses frequently pitch certain forms of steady, careful capitalist extension as potentially limitless. Anthropologists have broadly found “sustainable” to be used by development workers and policy experts most widely in reference to economic rather than environmental constraints. Sustainable development thus presents as an environmentalist concept but is regularly used to lubricate extraction and energy-intensive growth in the name of a sustained capitalism. The intensifying impacts of climate change demonstrate the stakes of this choice. Anthropological interruptions and interrogations of the sustainable development concept within the unfolding logic of late capitalism range from the intimate and local realm of economic lives, to the political ecology of resource extraction, to the emerging ethnography of climate change. Anthropologists investigate sustainable development at these three scales. Indeed, scale is an effective analytic for understanding its spatial and temporal effects in and on the world. Anthropologists approach sustainable development up close as it has been utilized as a short-term disciplinary instrument of transforming people identified as poor into entrepreneurs. They can zoom out to see large extractive industries as, themselves, subjects and drivers of a larger-scale, longer-term framework of sustainable development. They also zoom out even further, intervening in emergent responses to climate change, a problem of utmost urgency that affects the globe broadly and far into the future, but unevenly. The massive environmental changes wrought by energy-intensive growth have already exceeded the carrying capacity of many of the world’s ecosystems. Climate change is at once a grave problem and a potential opportunity to rethink our economic lives. It has been an impetus to redefine mainstream approaches to sustainable development within a fossil-fueled capitalism. However, a deliberate program of “neoliberal adaptation” to climate change is emerging in sites of sustainable development intervention in a way that promises a consolidation of capitalist discipline. Anthropologists should thus engage a more robust ethnographic agenda rooted in environmental justice.