Volume 12 | Issue 5

 Abstract

Solar desalination has gained significant attention in recent years as an effective solution to address the global water scarcity problem. This paper presents a performance evaluation of a solar desalination prototype for treating seawater/brackish water. The prototype is designed to operate using low-cost materials and simple techniques, making it suitable for small-scale and remote areas. The system consists of a basin for water storage, a solar collector for heat absorption, and a condenser for water vaporization and condensation. The evaluation was conducted in the field under different weather conditions and feedwater salinities. The results show that the system was able to produce high-quality freshwater at a low cost, with an average production rate of 3.5 litters per day. The system performance was affected by the feedwater salinity, solar radiation, and ambient temperature, with higher production rates observed during sunny days with low salinity water. The prototype efficiency was evaluated using key performance indicators such as the daily solar energy input, the daily freshwater production rate, and the solar-to-water conversion efficiency. The results demonstrate that the solar desalination prototype achieved a high solar-to-water conversion efficiency of 70%, indicating its potential as an effective solution for treating seawater/brackish water in remote and arid areas. Overall, the performance evaluation of the solar desalination prototype presented in this paper provides valuable insights into the system potential for sustainable water production.

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 Keywords

Solar desalination, Seawater, Water scarcity, Freshwater production rate

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Wireless communication systems have become an essential part of our modern society, enabling a wide range of applications in fields such as entertainment, commerce, healthcare, and safety. The emergence of fifth-generation (5G) wireless systems and the ongoing development of sixth-generation (6G) networks underscore the growing significance of Artificial Intelligence (AI) and Machine Learning (ML) in the evolution of future wireless technologies. This paper offers a comprehensive overview of the changing landscape of wireless systems, with a special emphasis on the incorporation of ML techniques in 6G networks. We introduce a conceptual framework for 6G and explore the application of ML techniques across various layers of this framework, including the physical, network, and application layers. We delve into both classical and modern ML methods such as supervised and unsupervised learning, Reinforcement Learning (RL), Deep Learning (DL), and Federated Learning (FL), discussing their relevance in the context of wireless communication systems. Furthermore, we highlight potential future applications and research challenges in harnessing ML and AI to propel the progress of 6G networks.

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Machine Learning, Artificial Intelligence, Federated Learning, Deep Learning, Sixth Generation (6g) Network, Fifth Generation (5g).

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Chronic kidney disease (CKD) poses a significant global health challenge with profound morbidity and mortality rates, often leading to the onset of other ailments. Its asymptomatic nature in early stages underscores the importance of timely detection to initiate prompt treatment and mitigate disease progression. Machine learning models offer a promising avenue for achieving this objective owing to their rapid and accurate recognition capabilities. In this study, we present a machine learning framework for CKD diagnosis, utilizing a dataset sourced from KAGGLE, renowned for its comprehensive medical datasets albeit with numerous missing values. Employing mean imputation for numerical features and mode imputation for categorical features, we address the issue of missing data commonly encountered in real-world medical scenarios. Subsequently, four machine learning algorithms - Logistic Regression, Support Vector Machine (SVM), Random Forest Classifier, and Decision Tree Classifier - are employed to develop predictive models. Among these, Random Forest emerges as the top performer, demonstrating superior accuracy in CKD diagnosis. This study highlights the efficacy of machine learning in facilitating early CKD detection, thereby enabling timely interventions to alleviate its progression and improve patient outcomes.

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 Keywords

CKD Diagnosis,Kaggle Dataset,Machine Learning Algorithms,Logistic Regression,Support Vector Machine,Random Forest Classifier,Decision Trees.

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With the increased demand for agricultural production, there is a greater need for novel technology to assist farmers in the early identification and classification of plant leaf diseases. Computerised imaging technology has promise in this area, as it allows for the rapid identification and categorization of diseases affecting plant leaves. Unchecked illnesses can have a major impact on crop production quantity and quality, hence timely detection is critical. In agricultural contexts, many leaf diseases can develop and harm crops. Using modern image processing techniques including as segmentation, feature extraction, and classification provides a quick, dependable, and precise way for detecting and categorising leaf diseases. This study gives a thorough assessment of current research on leaf plant disease detection and classification using image processing techniques. We look at critical steps of the process, such as image acquisition, pre-processing, segmentation, feature extraction, and classification, using the work of many authors. By combining findings from various studies, we hope to provide agriculturists with useful tools and approaches for improving disease management procedures in the agriculture sector. Our review highlights the potential of deep learning technologies to revolutionise disease detection and classification, allowing farmers to make more informed decisions and reduce the impact of plant leaf diseases on agricultural production.

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 Keywords

Imaging Technology, Segmentation, Feature Extraction, Leaf Disease Classification

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Talent Management is a human resource management strategy that many organizations follow in order to retain staff for a long period of time. It is defined as the process of procuring talented employees, preparing them to move to higher positions, assessing and managing their performance and preventing them to leave the organization. The main focus of the study is to analyze the relationship between talent management and the organizational performance and also to suggest the ways of retaining effective talent in the organization for long run sustainability and growth of the company. For this a well designed questionnaire is used and data is collected from both primary and secondary sources. The sample size is 150 employees from various software companies located in Trichy city. For this study convenience, sampling technique is used and data is analyzed with the help of statistical tool like percentage analysis, chi square are used. The findings of the study include that talent management practices have positive impact on organizational performance. In order to retain talented employees organizations need to focus on learning and development initiatives for the employees and also career enhancement opportunities should be provided that ultimately improves organizations productivity and performance.

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Talent management, Importance of talent management, productivity and performance, career enhancement opportunities.

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This study investigates the creation of eco-bricks using construction and demolition waste (CDW) ash, waste foundry sand, and other waste materials. The primary objective was to determine the properties of the modified eco-bricks and compare them with traditional bricks. Additionally, the study aimed to identify the optimal ratios of waste materials for brick production. Specimens were cast and cured following conventional techniques, with varying proportions of CDW (10% and 20%), foundry sand (10%, 20%, 30%, 40%, and 50%), and sludge (10%, 20%, 30%, 40%, and 50%). After 28 days, the specimens were tested for water absorption, dry weight, and compressive strength. The results demonstrated that the modified eco-bricks had comparable properties to regular bricks and exhibited satisfactory performance characteristics.

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Construction And Demolition Waste, Foundry sand, Compression, Water absorption, Eco-Bricks

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Man, after all, is the child of the time and prisoner of his experiences. The contemporary stream of thought casts a great impact on the thought process of man. Examination of the contributions of Mahatma Gandhi seems necessary in view of the political and materialistic transformation of the modern world and the prevalence of ethical bankruptcy of the general masses due to growing materialism, progress of education and undue stress on physical well-being. Advance of Science and its sinister daughter technology has brought humanity and human values to stand nearer to the brink of total destruction. Concentration of power in the hands of a small minority whether in the field of Economics or politics leads to increase so many problems, as problems beget further problems. Forces are released that make each war the preamble to another and more devastating wars. The only consequence of war today is to enhance the impulse of revenge and retribution. The processes of change made the world much different from what it was in the early decades of the twentieth century. The explanation for this tragic paradox lies in the contradiction between the ends and means that characterizes the present age. "The wars of Liberation are becoming wars of annihilation". In this connection, Gandhiji showed us one of the ways of breaking this vicious circle for resolving the mounting tensions.

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Democracy , ideal, political view, state, classless society .

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The aim of this work is to formulate and evaluate an herbal face pack for glowing skin by using natural herbal ingredients. The natural herbal ingredients such as multani mitti, turmeric, sandalwood, saffron,milk powder, rice flour, orange peel were purchased from local market in the form of dried powder. The powder of banana peel was prepared by shade drying commercially, all powdered natural ingredients were sieved using #120 mesh, weighed accurately and mixed geometrically for uniform formulation and then evaluated for parameters including morphological, physicochemical, physical, phytochemical, irritancy along with stability examination. Thus, in the present work, we formulated aherbal face pack which can be easily made with the easily available ingredients. After evaluation, we found good properties for the face packs, free from skin irritation and maintained its consistency even after stability storage conditions. Results of the study scientifically verified that herbal face pack having enough potential to give efficient glowing effect on skin. The overall study is useful to substantiate product claims due its useful benefits on the human beings.

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Herbal Face pack, Skin, Natural Formulation, Herbal Remedies

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ABSTRACT: "Citizenship is the chance to make a difference to the place where you belong." - Charles Handy On the Month of 11th December 2019, The Citizenship (Amendment) Bill was passed by a majority of 125 lawmakers of the Parliament. It becomes Act in January 2022, known as the Citizenship (Amendment) Act or CAA. The core resolution of this Act was to bring amends to the Citizenship Act of 1955 and to grant Indian Nationality to those persons from Sikh, Buddhist, Jain, Parsi, Hindu, and Christian strict minorities, except Muslims, who had escaped exploitation or abuse before December 2014, from Bangladesh, Pakistan, and Afghanistan. However, many other lawmakers and like-minded public condemn and criticize the decision taken by the Ruling NDA Government and Parliament alleging an anti-Muslim prejudice. Many peaceful and violent protests have taken place across the Nation against the CAA passage in the Parliament, and no doubt it violates the principle of "secularism" enshrined in the Indian Constitution and other Fundamental rights conferred by the Constitution of India. The researcher delved into the evolution of the CAA, its current status of the Act and a comparison between the existing laws, its needs, issues, impact, and relevant judgments on the subject matter.

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Keywords: Citizenship (Amendment)Act, secularism, biases, discrimination, Indian Constitution, National Registration of Citizen

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In the real world, we can see that sharing documents and data is quite difficult, requiring significant time to communicate efficiently study or run a business. Cohesive Connect chat software is a team collaboration tool that allows direct and indirect communication as well as group creation. Cohesive Connect is available for Both Ios and Android as well as for windows user. As a result, we would like to demolish our proposal to integrate communication technologies for educational purposes. Cohesive Connect can be easily incorporated into workflows and populated by users with great efficiency to meet purposeful communication needs at businesses, colleges and health centers. Keywords- Document sharing, unified communications technology.

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communication and collaboration platform for teams to stay connected and work together seamlessly.oTarget User Persona: Small to medium-sized businesses looking for a user-friendly communication tool to streamline team collaboration.oUser's Pain Points to Solve:oFragmented communication across multiple platforms.oInefficient collaboration leading to project delays.oLack of centralized location for team interactions.oMain Value Propositions:oCentralized communication hub for team collaborati

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The rise of deepfake videos in recent years has raised significant concerns about the potential misuse of manipulated content for malicious purposes. To address this growing threat, this research introduces an enhanced Convolutional Neural Network (CNN) architecture specifically tailored for the detection of deepfake videos. The proposed model builds upon the DenseNet architecture, incorporating novel modifications to improve its performance in distinguishing authentic from manipulated visual content. The key enhancements include the integration of attention mechanisms and feature fusion strategies to capture complex patterns and subtle anomalies indicative of deepfake manipulations. Furthermore, a comprehensive dataset comprising a diverse range of authentic and manipulated videos is utilized for training and evaluation, ensuring the robustness and generalization of the proposed model. Experimental results demonstrate the superior performance of the proposed Dense CNN architecture compared to state-of-the-art deepfake detection models.

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D-CNN, GAN, Computer vision, Deep Learning, LSTM, ResNet

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ABSTRACT A study to assess the effectiveness of planned teaching program (PTP) on knowledge regarding self-awareness among nurses was conducted in selected psychiatric hospital in Goa with the objectives, to assess the level of knowledge regarding self- awareness among nurses using a structured knowledge questionnaire, to find out association between knowledge score of nurses with socio demographic variables and to develop and validate planned teaching program on self-awareness and to assess the effectiveness of Planned Teaching Program (PTP) regarding self-awareness among nurses by comparing the mean pre and post test knowledge scores. One group Pre-test Post-test pre-experimental research design was used. Convenience sampling technique was used for obtaining 30 nurses. The tools used for the study were self-structured questionnaire consisting of 36 items. Data was analyzed using inferential and descriptive statistics. The major findings of the study were: Majority of nurses were in the age group of 51-60 years (36%), 1male and 29 females, majority were from Hindu community 20 (66%), In relation to qualification, majority were GNM 21(70%), 30% BSc./PBBSc, majority of the nurses were permanent (28) 93.3%, around 9(30%) had 21 years of experience. Majority of the nurses 29(96.7%) had not attended any in-service education program. In the pre test majority of the nurses had average knowledge scores 25(83%) whereas 5(16.6%) had poor knowledge and none had good knowledge. While in post-test there was increase the level of knowledge. Around 83% (25) had good knowledge scores and 5(16.6%) had average knowledge scores. It was found that the planned teaching program effective as there was significant difference in knowledge scores of nurses pre and post- test. The study has implication for mental health nurses as self awareness is an important aspect of psychiatric nursing.

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KEY WORDS: Psychiatry, Self-awareness, Nurses, Planned Teaching Program, Knowledge.

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This paper presents a method for measuring strains and deflections using strain gauges. An Arduino Uno board is used for data acquisition due to its low cost and easy programming. The measured signals are conditioned using a Wheatstone bridge and then converted to digital form by an external Analog-Digital Converter. To validate the measurement system, experiments were conducted on beams, and the results were compared with analytical and finite element simulation findings. The results align with existing literature and demonstrate that the proposed system has satisfactory accuracy

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Strain Gauges, Arduino, Data acquisition, Wheatstone-Bridge, Beam

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Abstention rates are still rising today, partly because voters must travel to cast their ballots. For this reason, everyone will be able to vote remotely via electronic voting, increasing turnout by eliminating the need for travel. In addition, it will yield results more quickly and with less risk than a typical paper ballot vote. The advantages that these systems offer, such as the ability to vote remotely and expedited vote counting, can be used to explain this tendency. In fact, a remote e-voting system needs to be the best in terms of security, dependability, and transparency because elections carry such high stakes. Only then can citizens trust such a system. The immutable vote storage mechanism of blockchain technology increases the voting process's resilience, lowering the possibility of vote tampering and preserving the validity of elections. Several nations, including Germany, Russia, Estonia, and Switzerland, have included this technology into their electronic voting systems. This paper offers a thorough analysis of the blockchain-based electronic voting methods that are being adopted by numerous nations and businesses and that have been suggested for scholarly investigation.

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Blockchain, Electronic voting, Authentication, Privacy, Security, Transparency.

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Recent IT infrastructure now includes cloud computing heavily since it offers scalability and flexibility. However, the increasing reliance on cloud services also attracts malicious activities and cyber threats. To protect cloud environments in this situation, an efficient Intrusion Detection System (IDS) is important. So, In this proposed System a better Cloud Intrusion Detection System design that makes use of a machine learning classifier and a hybrid feature selection method. The suggested system improves both the accuracy and effectiveness of intrusion detection by utilizing label encoding, correlation analysis, and the Extra Tree algorithm. The suggested system has been verified by the UNSW-NB15 dataset Gather a diverse and representative dataset of cloud security incidents and non-incidents. Understand the characteristics of the dataset, including feature types (categorical, numerical) and potential challenges Exploratory data analysis (EDA) is used by data scientists to analyze and investigate data sets and list their primary attributes, frequently using data visualization. The UNSW-NB15 datasets have validated the proposed method, yielding accuracies of more than 98% and 99% in the multi-class classification scenario, respectively. It was found that an intrusion detection system would function better if it had less informative features.

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Intrusion Detection System, Machine Learning, Extra Tree Algorithm, UNSW-NB15 Dataset, Exploratory Data Analysis (EDA)

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This research paper investigates the relationship between parenting styles and two crucial psychological factors affecting the development of adolescents: self-esteem and academic motivation. A sample of 150 adolescents aged between 13 and 19 years participated in this study. The study employed three standardized psychometric tools to measure parenting styles, self-esteem, and academic motivation: the Parental Authority Questionnaire, Rosenberg's Self-Esteem Scale, and the Academic Motivation Scale. The findings revealed significant associations between parenting styles and adolescents self-esteem and academic motivation. Specifically, authoritative parenting demonstrated a positive correlation with higher levels of self-esteem and intrinsic academic motivation, while authoritarian and permissive parenting styles showed negative correlations. Adolescents raised in authoritative households showed to have greater self-esteem and intrinsic motivation to excel academically, attributed to the balance of warmth and structure provided by authoritative parents. Conversely, authoritarian parenting, characterized by high control and low warmth, was associated with lower self-esteem and motivation, potentially due to restricted autonomy and harsh disciplinary practices. Similarly, permissive parenting, marked by low control and high warmth, exhibited negative effects on adolescents self-esteem and academic motivation, possibly stemming from the lack of clear boundaries and expectations. These findings underscore the critical role of parenting style in shaping adolescents psychological well-being and academic outcomes. Understanding the influence of parenting practices on self-esteem and academic motivation is vital for designing effective interventions and support systems aimed at promoting positive youth development. Future research should explore additional contextual factors and longitudinal effects to further understand the complex interplay between parenting, self-esteem, and academic motivation among adolescents.

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PARENTING STYLE, SELF-ESTEEM, AND ACADEMIC MOTIVATION

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This research paper analyzes how ESG ratings impact the market capitalisation of the top firms in India. Thus, the purposes of the study are to assess the relationship between ESG performance and the stock market value and determine leaders and laggards in ESG companies. In this case, the companies under consideration are five selected and operate in the FMCG industry, namely Hindustan Unilever, ITC, Tata Consumer Products, Nestle India, and Britannia Industries. In addition, the research uses both quantitative and qualitative data whereby the ESG score from the companies is evaluated based on the environmental, social and Governance indicators as well as comparing the three sets of ESG scores to the market capitalization of the respective companies. Classification of the variables Multiple linear regression analysis is carried out to compare the performance of the ESG scores (IV's) and market capitalization (DV). Based on these results, it may be seen that some firms excel in particular ESG issues that have to do with their business activities, however, the authors do not disclose the statistically significant correlation between ESG scores and market capitalization for the analyzed sample. Accordingly the paper concludes CSR scores are insignificant in this dataset insofar as an impact on market capitalization is concerned.

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Environmental, Social, and Governance (ESG), Market Capitalization, Corporate Social Responsibility (CSR), Sustainability, Regression Analysis, FMCG Industry.

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In recent months, free software tools based on deep learning have made it easier to create reliable facial transformations in videos that appear out of nowhere without control effects, so-called "DeepFake" (DF) videos. Digital video management has been proven for many years using the view.Recent advances in deep learning have led to major improvements in the accuracy and accessibility of false content where possible . created. These are called AI Synthetic Media (often called DF). However, this represents a significant challenge when it comes to the discovery of these DFs. Because training the algorithm to find DF is not easy. We take a step forward in DF detection by using neural networks and recurrent neural networks. The system uses a convolutional neural network (CNN) to extract phase models. These features are used to train a Recurrent Neural Network (RNN) that can detect inconsistencies between, which learns to determine whether videos have been modified and physical disparities between frames represented by DF Design. tool. Expected results for many fake videos collected from the dataset. We show that our system achieves competitive results on this task using a simple reference model.

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Deepfake video detection, recurrent neural network (RNN), convolutional neural network (CNN).

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Education is the fundamental right of every children. But this fundamental right cannot be achieved without availability of quality education. Schooling has directed effects on children's Psycho social development. According to Solomon (1960), the school classroom has the second important place after home Foso human development. School provides first face to face interaction with reality to children. In school child get format education as well as learns so many informal things. This happens because teachers, peons and other students affect their personality in many ways. There are so many stimulating materials present in school premises that affect children's personality intelligence, emotions, motivation, sociolisation etc.

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Impact of Private and Government School's Education on Children's Psycho-Socio Development

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Efficient project management is indispensable in today's digital age, especially in educational institutions. This paper introduces TRIAD, a comprehensive project management system designed specifically for higher education. TRIAD inte grates project planning, task assignment, progress tracking, and communication features tailored for academia. Moreover, it incor porates advanced plagiarism detection algorithms and meeting facility coordination to ensure academic integrity and streamline collaboration. This paper outlines the system's architecture, func tionalities, related works, proposed enhancements, and future scope, highlighting its transformative potential in revolutionizing education and preparing students for the professional world.

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Project Management system, Plagiarism Detection, Meeting Facility Coordination, Academic Integrity, Higher Education

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