Volume 12 | Issue 4 |

 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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 Keywords

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

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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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 Keywords

Comprehensive, Scaffold, Accommodation, Domain.

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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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 Keywords

Digital India, Cybercrime, Cyber victim

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Creative Commons Attribution 4.0 and The Open Definition

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

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Creative Commons Attribution 4.0 and The Open Definition