Volume 12 | Issue 4

 Abstract

In recent years, the power quality of the ac system has become a great concern due to the rapidly increased numbers of electronic equipment, power electronics, and high voltage power system. Most of the commercial and industrial installation in the country has large electrical loads which are more inductive in nature causing lagging power factor which gives heavy penalties to consumers by the electricity board. This situation is taken care of by PFC. Power factor correction is the capacity of absorbing the reactive power produced by a load. In the case of fixed loads, this can be done manually by switching capacitors. However in the case of rapidly varying and scattered loads it becomes difficult to maintain a high power factor by manually switching on/off the capacitors. This drawback is overcome by using an APFC panel. In this project, measuring of power factor from the load is done by using ATMEGA328 microcontroller and trigger required capacitors and extra synchronous condenser in order to compensate reactive power and bring power factor near to unity (1).

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 Keywords

Stepdown transformer , Diodes, Ac supply ,Dc supply, Op amp, XOR gate, Resisters, Lcd display, Arduino ,Relays ,Capacitor ,CRO

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 Abstract

Gas leakage is a critical safety concern in many industrial and domestic environments. This project involves the development of a gas leakage detection system utilizing Node MCU ESP8266 microcontroller and MQ5 gas sensor. The system is designed to detect the presence of harmful gases such as LPG, propane, and methane. Upon detection, the system triggers both visual and audible alarms through LED and a buzzer, at the respective levels of leakage, to alert occupants. Additionally, an exhaust fan is activated above the 80% of leakage to mitigate the gas concentration and enhance safety. The proposed system offers real-time monitoring capabilities through the Node MCU ESP8266 on ThinkSpeak open-source software, providing an effective solution for gas leakage detection and prevention.

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 Keywords

Esp8266, MQ-5 gas sensor, Buzzer, Led, Relay Module, Exhaust Fan, ThinkSpeak open-source .

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 Abstract

Innovations in transdermal delivery system (TDDS) have made important contributions to medical practice by providing advances in the delivery of treatment with existing and novel drugs. Today about 74%of drugs are taken orally and are found not to be as effective as desired. To improve such character's transdermal drug delivery system was emerged Drug delivery through the skin to achieve a systemic effect of a drug is commonly known as transdermal drug delivery system The study aimed to formulate a pure herbal transdermal patch and to evaluate its physicochemical properties. The Herbal transdermal patch was formulated by adding the extract of neem in the form of oil and ginger powder. Several test such as visual inspection, pH, thickness, weight variation, folding endurance etc. were performed to determine the physiochemical Properties of prepared transdermal patch. It showed clear appearance, standard surface ph and thickness. The result indicated the formulated transdermal patch is having excellent appearance and surface PH.

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Transdermal Patches, Ginger, Neem Oil

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 Abstract

Medical image fusion using different type of image fusion techniques like DWT and DRT. Image fusion can be done with two technologies, spatial domain and Transform Domain. Transform domain use Multi-Scaling and Multi-Resolution method. A new idea is presented in paper with combination of Multi resolution and multi scaling techniques which improves the result quality and get initial fused image. The Propose Image Block Method algorithm is improving initial fused image and quality of final fused image is improved. The performance of the fused image is evaluated using different parameters like PSNR, MSE, SSIM and ENTROPY.

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 Keywords

Medical Image Fusion, Multi-Scaling , Multi-Resolution, Block Matching

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 Abstract

ABSTRACT Across all income groups, coronary artery disease is the leading cause of death globally. Globalization has led to improvements in the health care system, but the indulgence in Western culture and sedentary lifestyles has increased the prevalence of cardiovascular risk factors. Elevated Cholesterol is one of the main causes of CAD. It is described as a disease where the body has higher than normal levels of lipids. Ayurveda takes a distinctive stance when diagnosing and treating high cholesterol. Elevated cholesterol is viewed as a sign of many different conditions rather than an illness in and of itself. The ailments are associated with Rasavaha sroto dushti rogas, which have been mentioned in ancient Ayurvedic texts. This illness results in a defect at the Agni level and is caused by diminished Agnis (Jatharagni, Dhatwagni, and Bhutagni). In light of this, we can arrange for the treatment of elevated cholesterol along the same lines as Rasavaha sroto dushti, necessitating the properties of Deepana, Pachana, and Kaphghana. One of the most widely used Ayurvedic formulations for a variety of uses is trimada. It is made up of three medications: Vidanga, Mustaka, and Chitraka. The purpose of this paper is to establish the relationship between high cholesterol and the role that taking Trimada's three medications can play in both preventing and treating high cholesterol.

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High Cholesterol, Rasavaha srotas, Trimada, Meda dhatu, Ayurveda, Agni, Oxidative stress.

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 Abstract

This paper presents an innovative approach to enhancing tour package recommendations through the integration of various Machine Learning algorithms and vectorization methods for text processing. The proposed approach is designed to offer personalized tour package suggestions tailored to userspecified destinations and preferred travel styles. Leveraging the Machine Learning algorithms alongside different vectorization enables the system to analyze textual data efficiently and extract meaningful features for recommendation generation. Experimental evaluations conducted on real-world datasets demonstrate the efficiency of the proposed method in delivering pertinent and diverse tour recommendations. The results underscore the capability of our approach to enhance the user experience by providing personalized travel suggestions that align closely with individual preferences and interests. This research contributes to advancing the field of tour recommendation systems by offering a robust and effective framework for generating tailored tour packages.

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Random Forest, Count Vectorization, Tour Packages, Content-based Recommendation

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This study investigates the impact of medical clowning on the quality of life (QOL) and emotional regulation (ER) of pediatric oncology patients. A total of 56 participants aged 8-15 years were recruited from an onco-pediatric ward. Validated tools, including the Pediatric Quality of Life Inventory (PedsQL) and the Emotional Regulation Checklist, were utilized to assess QOL and ER, respectively. Statistical analysis, including paired sample t-tests, assumptions checking, and effect size calculation, were employed to analyze the data. The findings revealed significant improvements in both pediatric quality of life and emotional regulation following medical clowning interventions. Paired sample t-tests demonstrated a substantial increase in post-intervention pediatric quality of life scores, accompanied by a significant decrease in negative emotions. These results highlight the therapeutic benefits of medical clowning interventions in pediatric oncology care, emphasizing their role in enhancing patient well-being and promoting a supportive treatment environment. Furthermore, the findings underscore the importance of interdisciplinary collaboration and policy support in integrating medical clowning into comprehensive pediatric oncology care protocols. Overall, this study contributes valuable insights into the effectiveness of medical clowning as a psychosocial intervention in pediatric oncology settings, providing evidence to support its integration into standard care protocols. Moving forward, further research is needed to explore the long-term effects of medical clowning interventions and optimize their implementation in clinical practice.

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 Keywords

Medical clowning, Pediatric oncology, Quality of life, Emotional regulation, Psychosocial intervention.

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 Abstract

Culture is varied accordingly to different person depends upon their perspectives of life, behavior and environment. Culture deviation to a different outlook will change the entire perspective of ones life The attraction to a different culture would lead to a total different outcome of one's life as it hold the transition of downfall of the existing culture as well the upgradation of one's life as it holds an implication of vivid development of contra of individuals life. Cultural deviation is a wide aspect which has a interrelated and dimension of various aspects of life. The influence of cultural deviation has lot of in-depth analysis overall development in all the perspectives of the life. Those development have led to various positive and as well as the negative aspects of the entire perspectives of one's life. The culture variety great transition as it holds in life growth and development. Modern values like humanism, egalitarianism, secularism have entered Indian value systems and level of law has been reformed tremendously. We find that the traditional social organization exemplified by the caste system has undergone several changes yet continues to exist in Indian society performing some old and some new functions. During the last few decades, as a result of the forces of modernization, the ideology of caste has become less pervasive in an individual's day to day life.

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Key words: - culture, attraction, modernization ..

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 Abstract

Docker containers offer a decentralized approach, processing data closer to its source, reducing latency, and bandwidth usage. They are ideal for IoT environments due to their lightweight nature and ease of deployment. One major benefit of using Docker for IoT edge computing is scalability. Docker enables seamless scaling of applications across a network of edge devices, accommodating varying workloads efficiently. Deployment becomes simplified, thanks to Docker's standardized container format, which ensures consistent behavior across diverse environments. Moreover, Docker optimizes resource utilization by packaging applications and their dependencies into isolated containers. This minimizes overhead and maximizes the utilization of computational resources, crucial in resource-constrained edge environments. Practical implementations demonstrate Docker's effectiveness in streamlining edge computing workflows. For instance, Docker facilitates containerization of IoT workloads, enabling developers to encapsulate applications and dependencies into portable units, easily deployable across edge devices. Security remains a paramount concern in IoT deployments. Docker addresses this by providing built-in isolation between containers, ensuring that if one container is compromised, others remain unaffected. Additionally, Docker's image signing and verification features enhance security by guaranteeing the integrity of containerized applications. Container orchestration tools like Kubernetes complement Docker, enabling automated deployment, scaling, and management of containerized applications across edge environments. Integration with existing IoT frameworks is seamless, allowing organizations to leverage Docker's benefits without overhauling their infrastructure. Optimizing Docker-based deployments in resource-constrained environments involves minimizing container footprint and utilizing lightweight container runtimes. Techniques like multi-stage builds and Alpine Linux-based images help reduce container size, conserving resources and improving performance.

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Edge computing, Docker technology, Containerization, Deployment simplicity, Container isolation.

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Intelligent Traffic Management Systems (ITMS) play a vital role in enhancing the efficiency, safety, and sustainability of urban transportation networks. This paper presents a comprehensive review of various components, technologies, challenges, and advancements in ITMS. The research explores the integration of artificial intelligence, IoT, and data analytics in traffic management, highlighting their impact on congestion reduction, accident prevention, and environmental sustainability. Additionally, it discusses the future directions and potential avenues for further research in this domain.

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traffic,reinforcement, data,analysis

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 Abstract

The theory of attachment offers significant understanding into the ways in which people establish and preserve relationships throughout their lives. This study examines how adult attachment styles influence the on quality of relationship. It is essential to comprehend the ways in which attachment to parents and other caregivers influences attachment and trust in adult relationships. This study specifically looks at how avoidant, ambivalent, and secure attachment styles affect codependent behaviors and relationship satisfaction. Examining these factors is crucial because codependency and its negative effects on relationships are a growing source of concern. In order to evaluate attachment style, codependent behaviors, and relationship satisfaction, participants filled out screening questionnaires and scales with a sample of 150 married women who were selected through interviews. The purpose of the study is to find out how people with various attachment styles differ in terms of codependent behaviors and relationship satisfaction. According to theories, people with avoidant and ambivalent attachment styles would be more likely to exhibit codependent behaviors and report feeling less satisfied in their relationships. There were negligible variations between attachment styles in terms of codependent behaviors and relationship satisfaction, according to data analysis that included a one-way ANOVA. These results underline the significance of addressing attachment patterns in interventions aimed at improving adult relationships and advance our knowledge of the applicability of attachment theory to those relationships.

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Attachment theory, attachment styles, relationship satisfaction, Quality codependency, adult relationships

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Assessment is resource intensive and needs careful evaluation and response to a learner's objectives and details of how the target was achieved. Although in medical training, assessment is largely conducted in offline mode, except for some computer-based formative assessment in certain specific areas. Online assessment provides computer rich, comprehensive, formative feedback that can scaffold the learning process and helps the learner to self-evaluate and enhance their learning outcome while preparing for summative assessment. It also eliminates the inconvenience due to rudimentary, traditional clinical assessments, for example, the need for examination halls, printed paper, and accommodation, travel and subsistence for both invigilator and candidate. The bottom line of using e-assessment tools in the field of medical education is that it offers substantial potential benefits but needs to be carefully managed to minimize potential risks. This article seeks to revisit basic concepts of e-assessments and the ways in which it can support learners to develop domain knowledge and professional skills with the hope of encouraging thought and reflection among medical educators.

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Comprehensive, Scaffold, Accommodation, Domain.

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 Abstract

Purpose- The purpose of this paper is to identify the level of awareness towards internet security measures, cyber security, and cybercrimes in the digital era. Research Methodology- This research starts with the conceptual framework of digitalization in India and it mainly focuses on cyber security. Both primary and secondary data are used and convenience sampling has been done with a total sample size of 320. Findings- The study disclosed that the awareness level among the respondents is very low and only a few respondents have knowledge about internet security measures that help them from cybercrimes. So that the govt can work on these factors and the appropriate measures can be taken by them. Research Limitations- The study area is limited to the Durg district only due to lack of time. In future the researchers may explore each type of cyber fraud separately. Implication- This research paper highlights the awareness among people towards cyber security and the way they deal with cybercrimes. As we know "Innovation creates the potential for exploitation." "People trust when they shouldn't."

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Digital India, Cybercrime, Cyber victim

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 Abstract

Due to middlemen who set low prices when buying from farmers and then sell the same at higher prices to consumers, farmers have experienced problems while trying to sell their food crops on the market. So we are going to made a platform which is only accessible to farmers who have a farmer's ID and registered farmer phone number. Farmers can establish their own prices for their products through a web-based programme, which also enables purchasers to participate in an online auction. The farmer determines the initial beginning price by consulting the dashboard's demand page. To verify that the price mentioned reflects the current market value of agricultural items, a machine learning system was used to make the prediction. Farmers are guaranteed to receive the highest price for their goods because to the fair competition that the bidding procedure promotes among buyers. Before participating in an online auction, farmers can choose the opening bid amount depending on the products' quality, lifespan, and current market price. Since the dashboard is updated often, buyers can see the highest bid amount listed there. Once the validity of the bid has expired and the matching buyer and seller have been alerted by SMS, the choices are locked. Customers can put their questions on the interface and receive assistance from agricultural experts using it as a decision support system. It is a user-friendly website that was exclusively created with farmers'

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 Keywords

Agriculture , Auction, Middlemen, Farmers, Consumers, Crop, Goods

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 Abstract

Employee morale is a critical factor in organizational success, influencing job satisfaction, productivity, and overall work culture. This article explores the impact of monetary rewards and other forms of recognition on employee morale, with a focus on their significance in fostering a positive work environment. Drawing upon a comprehensive review of existing literature and case studies, the research delves into the multifaceted nature of employee morale and how various incentive systems contribute to its enhancement. The findings reveal that while monetary rewards, including bonuses, salary increases, and incentives, hold undeniable appeal for employees, they are not the sole determinants of morale. Equally vital are non-monetary recognition methods such as verbal appreciation, public acknowledgment, and opportunities for professional growth. The study underscores that a balanced approach, combining both financial incentives and non-monetary recognition, is essential for nurturing high levels of employee morale.

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KEYWORDS: Employee morale, monetary rewards, undeniable appeal, balanced approach

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 Abstract

Abstract-- The technique presented in this paper uses a stereo camera system based on structural light to measure item size automatically and accurately. The four steps of the approach are depth interpolation, object detection, preprocessing, and key point extraction prior to size calculation. Initially, during the preprocessing stage, the RGB and depth frames are matched.

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KEYWORDS: Index terms: tracking-by detection, you only look once (yolo), simple online and realtime tracking (SORT), tools operated: python IDLE shell/ pychram programming language: python programming language.

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 Abstract

Women's power and struggle in Hindi Stories of the last decade of the 20th century

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Women's power and struggle in Hindi Stories of the last decade of the 20th century

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Creative Commons Attribution 4.0 and The Open Definition

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This paper presents an approach to recognition of traffic signs using Convolutional Neutral Networks (CNNs) and You Only Look Once (YOLOv4) networks. Traffic sign recognition is a crucial aspect of autonomous driving systems, aiding in navigation, safety, and compliance with traffic regulations. In this project, proposal to a novel approach to traffic sign recognition utilizing a combination of Convolutional Neural Networks (CNNs) and the You Only Look Once version 4 (YOLOv4) object detection framework. The integration of YOLOv4 allows for efficient real-time detection of traffic signs in complex scenes, while CNNs enable accurate classification of detected signs. The proposed system involves preprocessing input images, followed by training the YOLOv4 framework to detect traffic signs. Subsequently, the detected signs are extracted and classified using a CNN model trained on a labeled dataset of traffic signs. The synergy between YOLOv4 and CNNs enhances the robustness and accuracy of traffic sign recognition, even in challenging scenarios with varying lighting conditions and occlusions. Experimental evaluations on benchmark datasets demonstrate the effectiveness and efficiency of the proposed approach compared to existing methods. The developed system holds significant promise for integration into autonomous vehicles and intelligent transportation systems, contributing to enhanced road safety and traffic management.

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 Keywords

DEEP LEARNING, CNN, YOLO, IMAGE PROCESSING

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Text to image synthesis refers to the method of generating images from the input text automatically. Deciphering data between picture and text is a major issue in artificial intelligence. Automatic image synthesis is highly beneficial in many ways. Generation of the imageis one of the applications of conditional generative models. For generating images, GAN(Generative Adversarial Models) are used. Recent progress has been made using Generative Adversarial Networks (GAN). The conversion of the text to image is an extremely appropriate example of deep learning.

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GAN algorithm

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This review paper provides a comprehensive analysis of Windows Security, covering its components, strategies, technologies, built-in features, third-party tools, and emerging trends. With the continuous evolution of cyber threats, understanding and implementing effective security measures in Windows environments are paramount. The paper explores the foundational components of Windows Security, such as antivirus software, firewalls, encryption tools, access controls, and security patches. It discusses strategies for Windows Security, including defence-in-depth, least privilege access, network segmentation, and regular security audits. Additionally, it examines technological advancements driving Windows Security, such as machine learning, behavioural analytics, and cloud-based security services. Probably the best way to protect a PC from harmful programming is to provide security updates promptly [1].The review highlights built-in security features within Windows operating systems, such as Windows Defender Antivirus, Windows Firewall, BitLocker Drive Encryption, and Windows Update. Without these models, it is difficult for consumers to understand what is happening just as much as how it is managed [4]. Furthermore, it delves into the role of third-party security tools in augmenting Windows Security, such as endpoint protection platforms, threat intelligence solutions, and vulnerability management tools. Finally, the paper explores emerging trends shaping the future of Windows Security, including zero-trust security models, secure access service edge (SASE), and identity-centric security frameworks. By understanding and leveraging these elements, organizations can enhance the security posture of their Windows environments and mitigate evolving cyber threats effectively.

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 Keywords

Keywords: Secure Access Service Edge (SASE), and identity-centric security frameworks

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Creative Commons Attribution 4.0 and The Open Definition