Volume 12 | Issue 4

 Abstract

Abstract-- Confront discovery innovation has gotten to be progressively crucial in different security applications, especially in the distinguishing proof and following of offenders. This paper presents an upgraded approach to criminal confront discovery leveraging the Haar Cascade calculation. The proposed strategy points to make strides the exactness and effectiveness of recognizing criminal faces in observation symbolism. The Haar Cascade calculation is a well known strategy for confront location due to its vigor and speed. Be that as it may, ordinary usage frequently battle with precisely recognizing faces beneath challenging conditions such as shifting lighting, occlusions, and posture varieties. To address these restrictions, our upgraded approach consolidates a few key upgrades. Firstly, we present a refined preparing dataset particularly custom-made to capture a differing run of criminal facial characteristics. This dataset incorporates commented on pictures of people with known criminal records, guaranteeing the demonstrate is prepared on pertinent information for progressed execution in criminal confront location errands. Furthermore, we utilize highlight designing procedures to improve the discriminative control of the Haar Cascade classifier. By extricating more instructive highlights from the input pictures, our approach can superior separate between criminal and non-criminal faces, indeed in complex scenarios. Moreover, we coordinated post-processing steps such as non-maximum concealment to refine the discovery comes about and decrease wrong positives. This guarantees that as it were the most sure location are held, improving the unwavering quality of the framework in real-world applications. Test assessments conducted on benchmark datasets illustrate the adequacy of the proposed approach compared to pattern strategies. Our strategy accomplishes prevalent precision and vigor in identifying criminal faces over different challenging conditions, exhibiting its potential for arrangement in security frameworks and law requirement applications. Generally, the improved criminal confront location framework displayed in this paper offers a promising arrangement for moving forward open security and security through the exact recognizable proof and following of people with criminal records. This venture executes a confront acknowledgment framework which to begin with identifies the confront and then identifies the individual by comparing the identified confront with picture database. It will offer assistance to keep up a solid security in that environment. To begin with the information sets are made and prepared them with the offer assistance of calculations which experiences include extraction, normalization and at that point pre- handled. The prepared information sets are compared with the input facial picture, it to begin with identifies and perceives the individual and shows the title of the work force. We got confront acknowledgment rate of 77% and its false-positive rate is 28%. This framework is recognizing faces indeed when there are glasses or developed a whisker. Confront Acknowledgment of obscure people is about 60% for both with and without applying limit esteem. Its false-positive rate is 14% and 30% with and without applying limit respectively.

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LBPH Recognizer, Confront Datasets, Histogram, Haar Cascade Algorithm.

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The Business Process Outsourcing (BPO) sector has long grappled with the persistent challenge of insufficient salaries for its employees. This issue significantly impacts the lives of salaried individuals within this industry. Despite being an integral part of the global economy, BPO employees often face compensation packages that fail to match the demanding nature of their roles.The work in the BPO sector involves handling critical operations, customer service, and complex tasks requiring round-the-clock availability. However, the compensation structure frequently falls short in reflecting the skill set and dedication these employees bring to their roles. Low salaries often lead to financial stress, impacting the overall well-being and motivation of workers.

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Employees, BPO, Salary, Financial Stress

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Genomics has been revolutionized by DNA sequencing technologies, generating an avalanche of data that necessitates sophisticated analysis techniques. Machine learning (ML) has emerged as a powerful tool in harnessing this data deluge, unlocking new frontiers in our understanding of genomes and their role in genetics. This review delves into the transformative applications of ML across the DNA sequencing workflow, encompassing tasks like genome assembly, variant calling, and functional annotation. We explore how ML algorithms are employed to decipher genetic variations associated with diseases, paving the way for personalized medicine. Additionally, the potential of ML in drug discovery and accelerating research in various genetic disorders is investigated. We culminate by addressing the ethical considerations surrounding the use of genomic data and the future directions of this burgeoning field.

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Machine learning(ML), DNA, Genome, genetics

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This study is aimed to examine the socio economic development of sugali tribe in Andhra Pradesh. The survey was conducted in ten villages spread over three Mandals of Anathapur district in Andhra Pradesh by using purposive random sampling method. Anathapur district has 63 Mandals, out of these mandals three rural mandals were selected purposively. They are Mudigubba, Gorantla, and Uravakonda Mandals. Four Villages were selected from each mandal and from each village selected 40 respondents. In the present study 400 sample sizes were selected randomly. Data were collected from respondents belonged to sugalies.

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Socio Economic, Development, Sugali Tribe, Andhra Pradesh.

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Special Economic Zones have been built to foster the economic growth of the country, attract foreign investment and promote international trade. These areas are governed by unique regulatory frameworks that catalyze economic growth, and technological advancement and create job opportunities. SEZs have evolved from Export Processing Zones(EPZs) and Free Trade Zones and have been tailored in such a way to meet the needs of the host country. These zones have played a pivotal role in shaping investment policies and enhancing the competitiveness of the country hosting them. The methodology used in this article is doctrinal research. The research gap in the topic is that a comparative analysis can be done to understand the shortcomings in the present regulatory system of India and will help in the effective implementation of SEZs. In the present article, a comparative study of SEZs in India and China has been conducted. A comparative analysis of SEZs in India and China within trade law has provided insights into the economic, trade, export dynamics of these two powerful nations. The analysis helps explore the legal framework, regulatory environments and trade law implications in India and China.

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Special Economic Zone(SEZ), Free-Trade Zones, Export Processing Zones, Industrial Parks, Specialised Zones.

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The integration of fake biometric detection using blockchain and thermal imaging technology presents a pioneering approach to bolstering the security and transparency of voting systems. By leveraging Convolutional Neural Networks (CNNs) in thermal image recognition, alongside the immutable ledger of blockchain, this innovative solution ensures the integrity of biometric data. Multi-CNNs use multiple channels as input, allowing the network to process different types of data or features simultaneously. Each thermal image, along with associated data, is securely stored on the blockchain, employing cryptographic hashes to link consecutive blocks, thereby preventing tampering or manipulation. The voting process becomes inherently transparent and traceable, fostering trust among stakeholders. Furthermore, smart contracts play a pivotal role in automating processes and enforcing predefined rules within the voting system. These self-executing contracts, encoded with the terms of the agreement, can trigger alerts or execute predetermined actions if anomalies are detected in the thermal image data, such as temperature breaches beyond acceptable limits. This proactive approach enhances the security posture of the voting system, mitigating potential risks and ensuring the authenticity of each vote cast. By combining fake biometric detection, thermal imaging technology, and blockchain-enabled transparency, this novel solution sets a new standard for secure and trustworthy electoral processes, safeguarding the democratic foundation of societies. SHA-256 is considered to be secure against collision attacks, where two different inputs produce the same hash output, and pre-image attacks, where the original input is derived from the hash output, when used correctly.

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Convolutional Neural Networks, Blockchain, Thermal Imaging, Cryptographic Hashes, Biometric Data,SHA-256.

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Technological advancements have significant implications for society and emphasizes the need for a well - rounded education that goes beyond technical skills. The focus on global awareness, environmental impact, social and political considerations, and professional ethics reflects the growing recognition of the interconnectedness between various disciplines and the need for a comprehensive understanding of the world's challenges. By incorporating these aspects into the curriculum, Dr. Vishwanath Karad MIT-World Peace University aims to prepare students to navigate complex societal issues and contribute to sustainable and inclusive progress. MIT WPU's vision of "Powering the future" through education, innovation, and culture indicates a commitment to creating a positive impact on society. By equipping students with the necessary knowledge and skills and fostering a sense of social responsibility, the university aims to drive sustainable and progressive transformation. The first part of the paper focuses on the teaching and learning of the core concept of Religious Harmony through Philosophy of Science and Religion / Spirituality. Statistics and components of the module being taught at UG and PG level at Dr. Vishwanath Karad MIT-World Peace University, Pune are presented. The quantitative analysis would be based on a questionnaire. This part focuses on collecting data, circulating the questionnaire to a minimum of 300 students who had studied the module in the recent past. The quantitative analysis of the data shows that the module's comprehension of religious correlations, instilment, and understandability is underscored by a significant positivity rate.

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Religious Harmony, Science, Spirituality, Seed thought

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This paper examines the factors that shape investment decisions, providing a comprehensive review of existing literature on investor behavior. Central to the review are the influences of financial goals, risk tolerance, and market knowledge on individual investment choices. While traditional finance theory posits rational decision-making, this paper highlights the role of emotions, biases, and heuristics in shaping investment decisions, drawing on insights from behavioral finance research. Additional factors, such as return on investment, financial literacy, social influences, and market conditions, are also found to impact investment behavior. Given the importance of informed decision-making for investors and financial institutions, a nuanced understanding of these factors is crucial for building prosperous economies. This paper acknowledges limitations, including reliance on secondary data, more in-depth analysis, and consideration of regional differences. Future research may explore specific factors using primary data and examine the impact of technological advancements on investment behavior.

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Keywords: Investment decision, factors influencing, individual investors.

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Artificial Intelligence (AI) is one of the most important innovations that has permeated both our daily lives and industrial processes. Its quick development portends revolutionary effects in a number of areas, from cutting-edge businesses to regular people's lives. AI is continuously improving human experiences by modifying interactions and enhancing capacities. For example, modern educational institutions use facial recognition technology to track attendance using AI algorithms. In the future, autonomous vehicles will be the ultimate application of AI, with cars depending solely on AI systems to navigate roads, detect traffic signals, and navigate.

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higher education, covid pandemic, virtual classrooms, and online communication tools

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Phishing assaults, which include content injection phishing, social engineering, online social networks, and mobile applications, employ advanced tactics and technologies to obtain sensitive information. To stop and reduce the chances of these attacks, a number of phishing detection methods were developed; deep learning algorithms were one of them that showed potential. The application of deep learning algorithms to phishing detection lacks a comprehensive overview, and the findings and related lessons are scattered throughout multiple publications. We carried out a systematic literature review (SLR) to find, assess, and condense the research results on deep learning algorithms for phishing detection as offered by the selected academic publications. The phishing website may be recognized in the final phishing detection rate depending on a number of important features, including the URL and Domain Identity, security and encryption specifications, and other elements. When a consumer completes an online transaction and pays through a website, our technology employs deep learning algorithms to identify whether or not the website is a phishing website.

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Detect Fake Urls

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The growth of Internet of Things (IoT) devices inside cyber-physical systems has brought in opportunities for technical improvements that are both encouraging and unprecedented in terms of the difficulties they provide to cybersecurity. This project intends to address the fundamental difficulties that are associated with the detection and attribution of cyberattacks within cyber-physical systems that are enabled by the Internet of Things (IoT). Increasing the capabilities of real-time detection is the key goal, and the primary objective focuses around the development and implementation of advanced algorithms and security protocols. In order to accomplish this, it is necessary to develop robust algorithms that are able to quickly recognize anomalies and potential dangers within the complex and interconnected landscape of Internet of Things environments. Additionally, the initiative will also investigate attribution, with the goal of identifying the origins of cyberattacks as well as the groups that are accountable for them. Utilizing cutting-edge technology like blockchain and forensic tools, we will investigate the possibility of establishing attribution systems that can be relied upon. By working on this project, the student hoping to earn a Bachelor of Technology degree hopes to make a significant contribution to the field of cybersecurity by developing workable solutions to strengthen cyber-physical systems that are enabled by the Internet of Things. It is predicted that the results of this research will bring to an improvement in the robustness of these systems, hence offering an increased level of protection against hostile activity. This endeavor highlights the significance of joint efforts among cybersecurity, Internet of Things, and related professionals in order to guarantee the effectiveness of complete detection and attribution tactics.

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Internet of Things (IoT), Cyber Security, Blockchain, Detection, Cyber attack

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We report the design and implementation of an affordable bedside device, Neo is capable of acquiring vital data in real time by integrating with diverse devices connected to newborns in neonatal intensive care units (NICUs). NICUs are equipped with multiple vital sign monitoring devices that are connected to the premature newborn. An NICUs is a device consisting of a rigid box-like enclosure in which an infant may be kept in a controlled environment for medical care. An infant incubator provides stable levels of temperature, relative humidity and oxygen concentration The relative humidity should follow set values according to the number of incubation days. In this smart NICUs an infant's data will be sent through via Phone or PC by doctor/care taker.

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Neo, vital data, networks in intensive care units (NICUs), monitoring devices, premature newborn, few gigabytes of data.

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: Barbara Kingsolver as an author has mastered the art of writing political stories about human's plight and nature's exploitation. Her life in Kentucky and career as a biologist has opened doors to new ecofeminist perspectives. This paper aims to analyse The Bean Trees and Flight Behaviour from ecofeminist perspective, highlighting every issue ecofeminism aims to analyse. Anthropocentrism gives priority to human needs and Androcentrism narrows down the discrimination by treating men as the representatives of human condition. In both cases nature and women receive the shorter end of the stick as they are exploited to cater to the needs of entitled men. The prevalence of this entitlement can be seen through Bear Turnbow's actions in The Flight Behaviour and Turtles assault in The Bean Trees. Kingsolver unearths different layers of Anthropocentrism in her narrative by highlighting the moral dilemmas which come with using natural resources for one's own gain. While the women in her novels feel trapped in their world due to social conventions, nature is also given very little regard by the same people. The predicament of women and the exploitation of nature interweave to create a compelling narrative which advocates the liberation of both.

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Key Words : Ecofeminism, Anthropocentrism, Androcentrism, Women, Nature

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Abstract. Word sense disambiguation is the method of believing out what an expression'splannedimportiswhenitlooksinalinguistic.Thenetworksamong the many parts of linguistics, most notably words, expressions, and routes, are highlyunclearanddeeplyentwined. Theplannedsensesofwordsare,parenthe- tically,easyforpeopletorealizeanddecode. Becauseofmistiness,itistoughto create a highly accurate material retrieval scheme or machine version system. Plentifuldeviceshavebeendevisedtoresolveambiguity,buttheyhaverelatively low success rates. Relative factors may have substantially impacted how well people could decipher the meaning ofpolysemic words. Announcing the Multi- Sensedatasetincludes9,000picturesofEnglishverbs,amachinetranslationsys- tem, or both as of ambiguity. Several methods have been developed to resolve ambiguity but have relatively low success rates. Associated factors may have greatly impacted how well people could interpret the meaning of polysemic words. Introducing the Multi-Sense dataset, which includes 9,000 pictures of Englishverbs.Theoutcome is low accuracy. Thepresentqueryexpansion algo- rithmsdonottakeintoversiontheframeworkoftheworker'squestion'spuzzling terms.Themethodforcausalthecorrectsenseofambiguousphrasesisprovided in this work. It contains likening the import of the unclear term to the senses of the other terms in the question and then giving weight to the contrast. Weights aregiventothelikenessmeasuresofthephrasesindecreasingorderofproximity to the ambiguous term. An overall likeness score is resolute by the supplied weights.

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WordSenceDisambiguation,MachineLearning,Multi-Sence words, Natural Language Processing.

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In this paper, we present a novel approach utilizing recent advancements in embedded processing to enhance fire detection capabilities in surveillance systems, specifically tailored for forested areas. Our proposed system utilizes the YOLO-v8 algorithm, optimized for efficiency and accuracy, to detect wildfires in their early stages, crucial for mitigating potential impacts and facilitating swift responses. Through fine-tuning the model with fire-specific data and considering the unique characteristics of the target problem, we achieve a balance between efficiency and accuracy. The framework's effectiveness is validated through rigorous testing in CCTV surveillance environments. Upon detection of a fire, the system promptly notifies relevant personnel via email alerts and buzzer notifications, ensuring timely intervention and minimizing potential damages. It uses a sensor that detects the heat by using the temperature sensors which can differentiate the heat levels of the sunlight from the actual forest fire.

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Fire detection, Surveillance systems, Yolo-v8 algorithm, Sensors, Temperature sensor.

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The purposes and goals of competition law and intellectual property law appear to be at odds with one another. These disagreements have resulted in the formation of a long-debated issue that must be resolved. Anti-competitive practices in the market are prohibited by the Competition Law, which serves to facilitate market expansion. IPRs, on the other hand, give the owner an exclusive monopoly over the product or service. Economic efficiency is increased when there is healthy and fair competition. The goal of putting the competition law into effect was to reduce monopolies and promote competition. In contrast to the goal of establishing competition legislation, intellectual property laws are intended to prevent ideas developed through research and development by inventor firms from being copied and sold by companies that produce comparable items and profit from the sale of those products. Competition rules are drafted in order to prevent a dominant corporation from abusing its market position. Its goal is to eliminate monopolisation of the manufacturing process, hence stimulating the entry of new enterprises into the marketplace. Some of the primary objectives of competition law include the enhancement of consumer welfare and the increase in the value of production. However, intellectual property laws offer monopolistic legal rights to the producers and owners of works that are the outcome of human intellectual creation. When this dominant/monopoly position is abused, it is in violation of intellectual property rights and competition law. The IPR may result in a situation in which substitutes are no longer available on the market. Consequently, a dominant position in the market may be established, which may later be exploited by the dominant enterprises, thereby defeating the primary goal of the Competition Act of 2002. Research Objectives o LINKING PATENT AND COPYRIGHT WITH COMPETITION LAW o BALANCING IPR AND ANTITRUST o UNREASONABLE CONDITIONS IMPOSED BY IP HOLDER THAT COULD LEAD TO ANTI-COMPETITIVE PRACTISES o UNDERSTAND EFFECTS OF IPRs ON COMPETITION AND WELFARE

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legal view on interplay between competition laws and intellectual property right

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Diabetes mellitus is a chronic disorder that is widely prevalent and requires careful management that includes diet, lifestyle, and health parameters. This research describes a novel mobile application that provides individualized meal advice and monitoring for people with diabetes. The application uses machine learning algorithms to provide personalized food recommendations based on dietary restrictions, personal tastes, and health data like blood glucose levels. The application seeks to enable users to achieve optimal glycemic control while partaking in a varied and fulfilling diet by combining user input with real-time data. This manuscript outlines the intended mobile application's characteristics, developmental trajectory, and possible benefits in enhancing diabetes self-management. The application aims to transform nutritional support for people with diabetes by utilizing an innovative method that promotes informed decision-making and improved well-being.

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Diabetes Management, Mobile Application, Personalized Recommendations, Machine Learning, Dietary Monitoring, Blood Sugar Levels.

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Cestrum nocturnum Linn is a medicinal plant, found as weed throughout India. The plant is native to tropical regions such as the West Indies, India and other South Asian Countries. It has been extensively used in Indian traditional medicine for wound healing, such as antioxidant, antibacterial, anticancer, antifungal, analgesic, anti-inflammatory. Cestrum nocturnum is the most valuable drug which is used in compound preparation included in Ayurveda literature. From leaves to the roots, the whole Parijat plant is very useful for various healing properties. It is known to improve the function of insulin and reduce the symptoms of diabetes.

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Cestrum nocturnum Linn , Wound healing, Anti-cancer, Antioxidant, Analgesic

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False Job Prediction, Machine Learning, Data Mining.

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