Volume 12 | Issue 12 |

 Abstract

A significant societal issue, particularly among youngsters, is cyberbullying. "The deliberate, repeated, and hostile use of information technology to harm or harass other people" is the definition of cyberbullying. It has increased in popularity since the creation of social media platforms like Twitter and Facebook. The Internet is the sole foundation of contemporary society. People today have a hard time imagining life without the internet. People have been utilizing social networking sites in recent years to exchange information, thoughts, and ideas. Different types of content, including text, images, audio, and video data, may be used in these exchanges. Giving users the opportunity to manage the messages posted on their own private space is a significant problem in today's online social networks (OSNs), since it prevents the broadcast of inappropriate information. As of right present, OSNs hardly support this need. As a result, social media academics are placing more and more emphasis on the automatic identification of messages that engage in cyberbullying. The use of rules and norms, human moderators, and blacklists based on offensive language are some of the traditional strategies for combating cyberbullying. In order to automatically identify cyberbullying behaviors, a principled learning framework must be created. A flexible rule-based system that enables users to tailor the filtering criteria to be factual to their walls and a soft classifier powered by machine learning that automatically labels messages in content-based filtering help achieve this. Server can learn the words and save them in the database based on this filtering. Before the message can be exchanged, the server might review the words at the moment of transmission and prohibit.

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 Keywords

Cyberbullying, social media, information technology, harassment, social networking sites, inappropriate content, content moderation, machine learning, rule-based system, soft classifier, offensive language, user control, filtering, human moderators, blacklists, automatic identification, server review, privacy.

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Creative Commons Attribution 4.0 and The Open Definition

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Cervical cancer is the fourth leading cause of cancer in women worldwide. Early detection of cervical intraepithelial neoplasia (CIN) can improve patient survival .This paper proposes a deep learning-based technique for determining whether a cervical cancer diagnosis is good or bad. By harnessing the power of transfer learning, the framework combines the benefits of pre-trained models like ResNet50, MobileNet, and DenseNet with the capabilities of CNNs. Our architecture is trained on a comprehensive database of cervical cancer images, comprising both online sources and magnification data-generated images. Using this model, our body can identify cervical cancer as positive or negative, which shows the effectiveness of CNNs and changes the study by checking medical images.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Cervical Cancer, Deep Learning, CNN, Transfer Learning, ResNet50, MobileNet, DenseNet

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In this project, a computerized greenhouse monitoring and control system is considered to control the environmental and climatic parameters for optimal plant growth. This system leverages sensor fusion of multiple sensors (temperature, humidity, soil moisture, and light intensity) for constant monitoring of the greenhouse environment. An embedded microcontroller reads the data and automatically controls devices such as fans, sprinklers, and lights (depending on the conditions needed for optimal plant growth). The automation minimizes the need for Human interference, saves water, and increases Energy efficiency. This system can be scaled for different greenhouse sizes and customized for various plant requirements.

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 Keywords

Greenhouse, Sensor, Actuator, Environmental Monitoring, Controlling, IoT etc

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Creative Commons Attribution 4.0 and The Open Definition

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Animal husbandry is a vital component of agriculture that faces mounting challenges due to increasing demand, climate change, and the necessity for sustainable practices. Artificial Intelligence (AI) offers innovative solutions to optimize operations, improve animal welfare, and promote environmental sustainability. This paper examines how AI can revolutionize animal husbandry, discussing key applications, benefits, and the challenges associated with its adoption.

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AI Artificial Intelligence Animal Husbandry

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This survey paper explores the progress made in using neural networks for diagnosing Autism Spectrum Disorder (ASD), a condition marked by challenges in social interaction, communication, and behavior. Timely diagnosis is crucial for effective intervention; however, traditional diagnostic methods can be subjective, lengthy, and may not provide the accuracy needed for early detection. As machine learning and artificial intelligence (AI) advance, neural networks present promising opportunities to automate and enhance the accuracy of ASD diagnosis, thereby reducing reliance on conventional assessment techniques. The paper systematically reviews recent studies on the use of neural networks for ASD, focusing on the analysis of data from behavioral assessments, speech patterns, and imaging data, including MRI and other imaging modalities. Key research is assessed based on the neural network architectures employed, the sources of datasets, and the performance metrics used, offering insights into the strengths and weaknesses of different approaches. Our analysis highlights significant challenges in current research, such as limited data availability, model overfitting, and the difficulty of translating complex neural network models into tools that can be easily interpreted in clinical settings. The importance of developing models that generalize effectively across diverse populations and provide reliable insights in real-world scenarios is underscored. Moreover, this survey points out critical gaps in the existing literature and proposes avenues for future research. It recommends the creation of self-updating datasets as a means to ensure that models remain relevant and accurate as new data emerges. Additionally, combining various data types--such as behavioral, speech, and imaging data--could improve diagnostic accuracy and offer a more comprehensive understanding of ASD characteristics. In summarizing the current landscape of neural network applications for ASD diagnosis, this survey seeks to inform future developments aimed at creating more robust, adaptable, and accessible diagnostic solutions.

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 Keywords

Keywords - Autism Spectrum Disorder (ASD) - Neural Networks - Deep Learning - Automated Diagnosis - Artificial Intelligence in Healthcare - Medical Imaging - Neuroimaging - Neural Network Architectures - Convolutional Neural Networks (CNNs) - Recurrent Neural Networks (RNNs) - Multimodal Data Analysis - Feature Extraction - Diagnostic Tools - Machine Learning Algorithms - Behavioral Analysis - Early Diagnosis - Precision Medicine - Data-driven Approaches - Medica

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Creative Commons Attribution 4.0 and The Open Definition

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As cloud computing becomes the backbone of modern digital infrastructure, ensuring data privacy and security in cloud environments has emerged as a critical concern for enterprises and individuals alike. This paper provides a comprehensive review of the current landscape of data privacy and security in the cloud, highlighting the key challenges, emerging threats, and advanced techniques designed to mitigate risks. With the exponential growth of cloud services, sensitive data faces diverse vulnerabilities, including data breaches, insider threats, and compliance challenges. The study explores state-of-the-art encryption methods, including encryption for data-at-rest, data-in-transit, and data-in-use, as well as innovative privacy-preserving technologies like homomorphic encryption and confidential computing. The discussion extends to the role of regulatory frameworks--such as GDPR, HIPAA, and CCPA--and their impact on data sovereignty and access control. Additionally, the paper examines the principles of Zero Trust Architecture and its application in enforcing stringent security measures in cloud-native environments. Best practices for incident response, data loss prevention, and secure DevOps (DevSecOps) are analysed to provide a holistic approach to cloud security. Finally, the review addresses the evolving landscape of threats and anticipates future advancements in privacy-preserving technologies, emphasizing the need for a proactive and adaptive security posture. This paper aims to offer a nuanced understanding of data privacy and security dynamics, equipping researchers and practitioners with the knowledge to navigate the complexities of cloud security and contribute to building a more secure cloud ecosystem.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Cloud Computing, Data Privacy, Data Security, Encryption, Homomorphic Encryption, Zero Trust Architecture, Regulatory Frameworks

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Menopause is the end of menstruation.Menopause is the permanent cessation of menstruation at the end of reproductive life due to loss of ovarian follicular activity. A comparative study was designed to assess the problems faced and coping strategies adopted by women with natural and surgical menopause residing in selected villages of Bardoli Taluka With the objectives to 1) assess the problems faced and coping strategies adopted by women with natural and surgical menopause 2) compare the problems faced and coping strategies adopted by women with natural and surgical menopause 3) find out the correlation between problems faced and coping strategies adopted by women with natural and surgical menopause 4)find out the association of mean score of problems faced and coping strategies adopted by women with natural and surgical menopause with their selected demographic variables.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Problems faced, Coping strategies adopted, Women, Natural and surgical menopause.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In the recent time, Polylactic acid is used in fused deposition modeling for making drug carriers, medical tools, cups, automotive parts, packaging, bottles, outdoor applications in purpose of medical, automotive, textile, constructions fields. The limitations of polylactic acid (PLA) is low melting point, not the hardest or toughest plastic, high production cost. To overcome the above problem, ABS is the best suitable polymer. The ABS material normally used in unconventional method. It has the limitations of less dimensional stability, poor surface finish, low hardest property. So, ABS polymer is used in additive manufacturing method. Because, good dimensional stability, very high surface finish, light weight and suitable for vast range applications. Now a days, polymer parts made by additive manufacturing methods (AM) have multiple applications in various industries. Additive manufacturing has the many techniques, but we are using fused deposition modeling (FDM). FDM is a procedure that uses thermoplastic filament that has been parched to its melting point and then thrust out layer to form a 3D object. The aspects associated with 3D printing such as less material wastage, ease of manufacturing, less human involvement, less post processing and energy efficiency makes the process sustainable for industrial use. In this study investigate the effects of Fused Deposition Modeling (FDM) process parameters of material the tensile strength, impact strength and hardness test of three-dimensional (3D) printed Acrylonitrile butadiene styrene (ABS) test parts were determined using the ASTM D638, ASTM D256 and ASTM.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

ABS polymer, Fused Deposition Modeling, Binder Jetting and Manufacturing.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The impact of the COVID-19 pandemic on people's lives and communities has been profound. Given the extraordinary times that the entire world is currently experiencing, it is especially critical to address concerns about crime, violence, and justice in general. Current studies have demonstrated that the COVID-19 pandemic has affected crime in part due to alterations in people's daily routines and their exposure to stressful situations. The investigation has also connected a number of previously developed theories to the modifications in crime trends that occurred during COVID-19 pandemic lockdown.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Crime, COVID-19, and Lockdown.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

ABSTRACT INTRODUCTION "We must protect families, we must protect children, who have inalienable rights and should be loved, should be taken care of physically and mentally, and should not be brought into the world only to suffer" Mrs. Indira Gandhi. The 21st century is known as the era of information technology, when technology advancement hits civilization, parental care, and guidance slowly replaced by variety of technological innovations. The term "smartphone" was used in 1997 by Ericson. Smatphone is providing integrated services from communication, computing and mobile sectors such as voice communication, messaging, personal information management applications and wireless communication capability. The internet fuels the smartphone uses and is useful for a variety of purposes, such as convenient, rapid sharing of information, and contact with other cultures, emotional and feasibility and an easy charring of a smartphone makes it possible to use it anywhere, Because Smartphone's currently include all the features of a laptop, including web browsing, Wi-Fi, a bundle of apps. All over the world, adolescents are the more vulnerable group for the smartphone usages and abuse. According to WHO, Adolescents are defined as young people between the ages of 10 and 19 years. Today 20% of the world population is of adolescents, constituting 1.2 billion people worldwide. Nearly 243 million adolescents live in India.4 A UN report has raised concerns about the increased use of Smartphone in schools all over the world. This report shows the impact of technology shared objectives of on teaching and learning. And also abuse of technology for non-educational activities like entertainment and commercial use. UN also warned and suggested the whole countries to maintain the human -centred use of technology only to support the education, not to supplement the teachers led instructions. The Adolescents should know and use only the relevant content and ignore the unnecessary and irrelevant content. The technology has a double edge sword so adolescents should select only the use of technology to enhance their knowledgeand growth , not to replace the human relationship. 1 RESEARCH PROBLEM: Effectiveness of a nurse led educational package regarding smart phone addiction and associated health problems among adolescents in selected schools at Patiala, Punjab. BACKGROUND OF THE STUDY: It is often stated that children are the world's most valuable resources and assets, but their rights throughout the world are largely ignored often resulting into tragic outcomes. AIM OF THE STUDY: To assess the effectiveness of a nurse led educational package regarding smart phone addiction and associated health problems among adolescents in selected schools at Patiala, Punjab. METHODOLOGY: A quantitative approach with two group experimental research design was used for this study. A sample size of 560 adolescents 280 in each, from experimental and control group at selected schools of Patiala Punjab was selected using probability stratified sampling technique. Structured questionnaire and SAS scale was administered to assess knowledge regarding smartphone addiction and the prevalence of smartphone addiction among adolescents at selected schools of Patiala, Punjab. RESULTS: As the result of analysis of Section A In this study among 560 subjects , the pre- test knowledge score was only 2 (0.37%) had adequate knowledge followed by 165(29.23%) had moderate knowledge score with the remained 293 (70.50%) had shown the inadequate knowledge score regarding smartphone addiction . The Mean knowledge score of pre-test of the experimental group was 9.37(31.23%) and the Mean knowledge score of the pre-test of the control group was 9.40 (31.35%). After intervention there was a substantial gain in knowledge compared to the pre-test scores was seen with the significant difference in the adequate knowledge score of experimental group) that mean score was 21.91(73.5%) but the post test knowledge score in the control group was almost the same as pre- test with mean score of 9.55 (3.31.85%). As reported in the post test knowledge score of experimental group 189 (67.5 %) subjects have adequate knowledge score, followed by 89 (31.8%) shown moderate knowledge score, where only 2 (0.7%) subjects had reported the inadequate knowledge score. On the other hand reported in the post- test knowledge score, the subjects of the control group shown the score almost same with pre test effect that is 5(1.8%) subjects had adequate knowledge , followed by 87(31.1%) had moderate and 188(67.1%) had shown the inadequate knowledge score . In the analysis report of Section -B, Out of total 560 subjects (Experimental group, N=280 +Control group, N= 280), the majority 183 (32.67%) subjects (experimental 92 and control 91) had severe Smartphone addiction followed by 193(34.46%) subjects from both groups had reported with the moderate addiction score while the remaining 184 (32.85%) had been found at the risk or in the low addiction score. An notable effectiveness of a nurse led educational package regarding smartphone addiction among adolescents on severe addiction score of experimental group had been reported with the post- test addiction score of 4 (1.4%) that was shifted from a higher pre-test mean score of severe addiction 92 (32.5 %) of experimental group . The moderate addiction score was raised up to mean score 140(50%) from 99(35.4%) Followed by the low addiction mean score 136 (48.6%) from the 94 (33.6%) of the addiction score of experimental group .The pre-test mean percentile addiction score was 114.35 %which decreased up to post -test score of 94.71%after the intervention On the other hand the addiction score among the adolescents of the control group had remained same that was as severe 85(30.4%), moderate, 107(38.2%) and mild 88(31.4%) with the pre -test addiction score as 91(32.5%), 99(35.4%) and 90(32.1%) respectively. The post -test mean score of control group was found almost the same as 115.78% and 115.29 % of the pre test and post test respectively CONCLUSION: It was concluded in this study, that there is a noticeable effectiveness of the intervention 'A nurse led educational package regarding smartphone addiction among adolescents at selected schools of Patiala, Punjab, which had shown a substantial gain in knowledge compared to the pre-test scores as a significance difference in the pre-test and post test knowledge score among adolescents of experimental group. There is also seen a significance difference in the prevalence score of Smartphone addiction among the adolescents of the experimental group, after intervention that was shifted from severe to moderate and low addiction score .

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 Keywords

KEY WORDS: knowledge, Effectiveness, Smartphone, Smartphone addiction, adolescents.

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Creative Commons Attribution 4.0 and The Open Definition