The double pass solar air heater or DPSAH is a device that is integrated with the solar air heater in order to facilitate the transfer of heart energy from one part of the device to another part of the device so that the heart's energy can be transferred efficiently. Solar air heaters with just one pass are said to have a lesser impact on the generation of thermal energy since they lose out on the energy during the transfer process and, as a result, they generate less thermal energy. On the other hand, DPSAH exhibits a superior thermal efficiency, as this is the result of doubling the area of heat transfer, which is attributed to its energy-efficient design that allows it to achieve better thermal efficiency. The absorber plate located behind the collector of a DPSAH helps in the collection of solar energy by absorbing the light from the sun. There are many situations where a part such as this will be painted black in order to increase the absorption of solar energy, as this colour has a direct impact on the generation of a higher absorption of solar energy. It is intended that as part of the study, the use of recycled materials will be observed in the construction of the absorber plate, as well as the efficiency that is generated from the use of such materials. It should be noted that the majority of absorber materials which are usually used for this application are semiconductors or dyes, which can come in both organic and inorganic forms.

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Self-compacting concrete (SCC) is a mixture that can be easily placed into formwork without the need for vibrating compaction, owing to its self-weight and high flowability. Unlike traditional concrete, SCC ensures that coarse aggregates remain uniformly distributed, eliminating the requirement for external or internal vibration during the compaction process while maintaining its engineering properties. Key properties of the new SCC include filling capacity, passing capacity, and strength, which are crucial considerations. Solidified mechanical properties of SCC with plastic fiber reinforcement are comparable to conventionally vibrated concrete. However, the disposal of waste plastics presents environmental challenges. Plastic is a non-biodegradable material, persisting in water and soil without degradation, leading to water and soil contamination. Incinerating plastic releases harmful gases, contributing to air pollution and posing health risks when inhaled. As a result, several countries have banned the use of plastics to address this pressing environmental issue. To tackle this problem, this research focuses on producing reinforced self-compacting concrete with waste plastic fibers (WPFRSCC) as a sustainable construction material. This approach offers a dual advantage, enhancing the properties of SCC while simultaneously addressing the disposal of waste plastics. In the study, a mix proportion for M40 concrete is determined using the IS: 10262:2009 method. Experiments are conducted to examine the flow characteristics of SCC with varying percentages of waste plastic fibers (0%, 0.50%, 1.00%, and 1.50%), along with different proportions of superplasticizer (1%, 0.90%, 0.80%, and 0.70%). After obtaining satisfactory mixes, cube, cylinder, and beam specimens are cast using different percentages of waste plastic fibers. Subsequent strength tests are performed on these specimens to evaluate the hardened properties of SCC with waste plastic reinforcement. The results demonstrate that waste plastic fiber reinforced SCC can be successfully developed without the need for consistency-modifying agents. Four distinct mixtures are formulated to meet the specific requirements of fresh SCC, considering different fiber percentages. From a strength perspective, it is found that an optimal combination is achieved with 1.0% of fiber content and 0.70% of superplasticizer.

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Digitalization has brought numerous advancements and benefits to India, transforming various aspects of society and the economy. However, along with the benefits, it has also introduced new challenges and opportunities for criminals. This research paper explores the criminal effects of digitalization in India, focusing on the rise of cybercrimes, financial frauds, data breaches, and other digital offenses. The paper analyzes the factors contributing to the increase in digital crimes, the impact on individuals and businesses, and the challenges faced by law enforcement agencies. It also highlights the importance of strengthening cybersecurity measures, enhancing law enforcement capabilities, promoting public awareness, and implementing effective legal frameworks to mitigate the criminal effects of digitalization.

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IoT devices are incomplete without a cloud server. Without cloud services, we cannot collect and process the data that is sent from each IoT sensor, then execute and send back the result. Implementation of a fog node near an IoT device results in storing and processing data at the fog node rather than sending it to the cloud. This study proposed multiple sensors for a smart home that is connected to a cloud server with a fog node and without a fog node. A smart home consists of 10 sensors like motion, gas, light, vibration, location, water leak, air, video, and humidity. The evaluation is done by comparing the energy consumption and network usage of sensors that are connected to the cloud with a fog node and without a fog node. The energy consumption and network usage of sensors with fog computing are lower than without fog computing, so these will lead to a green smart home. If more sensors are added, then also energy consumption and network usage of fog computing will be lower.

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This thesis presents a comparative study on the effects of moving loads on a reinforced concrete deck bridge, examining two distinct loading standards, namely IRC Class A and AASHTO HS-20. The study's primary objectives were to evaluate the structural behavior, assess the performance, and compare the stresses and deformations experienced by the bridge under both loading conditions. Additionally, the research aimed to analyze the safety implications and identify potential vulnerabilities for each loading scenario while investigating critical points influenced differently by IRC Class A and AASHTO HS-20 loadings. The investigation involved analyzing various parameters such as bending moment, deflection, stress, torsional moment, and shear force in the bridge structure. conclusions offer valuable insights into the structural behavior and performance of steel girder deck bridges under various loading conditions and deck thicknesses. The findings can serve as essential guidelines for bridge design and optimization, ensuring the safety, durability, and efficient performance of the bridge structure. Engineers and designers can leverage this research to make informed decisions when selecting appropriate loading standards, ultimately contributing to the overall improvement of bridge infrastructure.

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The rapid advancements in technology have led to the emergence of the Internet of Things (IoT) as a transformative paradigm in various domains, including home automation. This review paper aims to provide a comprehensive overview of IoT-based home automation systems, exploring their architecture, components, benefits, challenges, applications, and future prospects. With the increasing integration of IoT devices into our daily lives, a critical analysis of the current state of IoT-based home automation systems becomes crucial for understanding their potential impact on society, security concerns, and the path toward a smarter and more connected future.

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This study examines new trends, problems, and solutions in cybersecurity. This review study has importance because it provides an overview of major cybersecurity types, discusses recent cyberattacks, and analyses the properties, purpose, and motivations of cyberattacks, solutions and specific tools that can be used to mitigate the cyber-attack useful for individuals, businesses, and governments worldwide who want to understand the current state of cybersecurity and how to protect themselves against cyber threats. combination of literature review, and case study analysis is used to write this review research paper. The report begins with a summary of the key results from the Cybersecurity Ventures Report, emphasising the frequency and sophistication of cyberattacks that are becoming more common. Then, a case study is used to evaluate the roles played by the FBI in the USA in battling cybercrime. Prominent recent cyber incidents, such as the 2020 Microsoft Exchange Server and SolarWinds Hack, are examined. By scrutinizing cybersecurity through diverse lenses, the study investigates its fundamental framework, potential remedial measures, and specific tools that hold promise in mitigating cyber threats. It underscores the pivotal importance of devising a comprehensive cybersecurity strategy that encompasses the human element, robust procedural protocols, and cutting-edge technological fortification. The study's conclusion reveals a tapestry of insights into the changing cybersecurity scene and culminates in practical advice for preventing cyberattacks. It emphasises cybersecurity as a major issue that transcends national boundaries and has a big influence on people, businesses, and countries on a worldwide scale, going beyond the bounds of academia.

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This study focuses on Magnetic Refrigeration, a solid-material-based cooling technique employing the magneto-caloric effect. The paper explains this phenomenon's mechanism, contrasts it with conventional methods, assesses diverse magneto-caloric materials, and highlights magnetic refrigeration's advantages and applications. This method offers cost-effectiveness, durability, reduced weight, and enhanced efficiency, utilizing a solitary moving part: a rotating disc with magneto-caloric material. Unlike traditional systems, it avoids compressors, pumps, working fluids, and harmful substances. Potential applications span electronics, superconducting components, residential/commercial refrigerators, and air conditioning for various settings, promising a breakthrough in cooling technology.

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Lubricant oils, essential for minimising friction between moving parts, find application across diverse industries such as automotive, industrial, marine, aviation, and energy production. The automotive sector primarily drives lubricant oil consumption, while the industrial domain follows suit. The global lubricants market, valued at USD 128.51 billion in 2020, demonstrates a growing trend, emphasising the escalating significance of lubricant oils. Traditionally derived from crude oil, the depletion of this source raises concerns. Moreover, disposal practices involving incineration and landfill contribute to environmental issues. Consequently, the pursuit of environmentally sustainable methods for disposal and reuse has become critical. "Re-refining" emerges as a rising technique, involving the removal of contaminants from used lubricant oils to restore their utility. This approach is not only eco-friendly but also conserves resources by reducing the need for fresh oil production. Moreover, re-refined lubricant oils often surpass industry standards, driven by advanced refining technologies. However, this method also produces potentially hazardous by-products, necessitating regulatory scrutiny. The study undertakes a comprehensive analysis of available methods, primarily focusing on engine oil, to determine an environmentally viable and economically feasible approach to re-refine used lubricant oils. The research presents a methodological exploration of re-refining used lubricant oils, driven by the urgency of sustainable development. The vacuum distillation-based approach, involving sequential operations of Dehydration, Vacuum Distillation, and Lube Oil Distillation and Condensation, emerges as a promising solution. This approach effectively removes water and contaminants, precisely fractionates components, and employs MEK (Methyl Ethyl Ketone) to enhance lubricating oil quality. The advantages include resource efficiency, waste minimisation, and high-quality re-refined products. While re-refining mitigates environmental concerns, certain challenges, including by-product hazards, necessitate careful consideration. This review underscores the need for and viability of re-refining as a path toward sustainable development, addressing environmental concerns while fostering economic growth in the lubricant industry.

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The goal of this paper is to compare the predictive performance of several machine learning algorithms in their capability to predict in loans. This is done to come up with valuable information about which algorithms are most suitable for this task. Such information is required before machine learning can be implemented in practice to predict loan. To determine the performance, several algorithms that can be used to classify samples have been implemented. Those are used to predict the loan and the performance of each of the algorithms is measured. The loans used in this paper come from data sets Data collection- we collect data from kaggle repository. Samples used for prediction is 614 samples and column names are loan ID, Gender, Married ,Dependent, Education, Self-employed, Applicant Income, Coapplicant income, loan Amount etc. Finally, data set has been split according to certain characteristics. The goal of such a modification is to find differences in performances on specific parts of the data set. The proposed technique is based on gradient boosting (GB) technique and applied to load data. The proposed GB ML technique provides in 93.13% training accuracy and 93.13% testing accuracy. The proposed technique is 11.10 improvement accuracy compared to LR and 14.66% improvement accuracy compared RF.

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Wireless Sensor Networks (WSNs) consists of huge number of sensor nodes deployed in the region for the purpose of gathering information about the its environment and transfer that information to the base station. Because of the advancement in micro electrical-mechanical system (MEMS) and digital electronics the tiny sensors have capabilities of low-cost, low-power, multifunctional for different types of environment conditions, processing, and communication within short range. But with these features comes the biggest problem of WSNs that it has limited source of energy for data collection, processing, storing, and transmission due to its harsh environment condition in most of the cases. Also, sensor nodes are prone to security threats by the insider as well as outsider attackers due to distributed nature, random deployment and environment of WSNs. In this paper, we discuss clustering and routing approach energy efficiently so that there will be proper utilization of energy resulting in enhancement of overall networks lifetime. We will also discuss various threats at different layers of the network, mechanisms incorporated with different soft computing techniques to deal with such threats.

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