Volume 12 | Issue 4

 Abstract

Numerous students apply yearly for undergraduate admission at various colleges in Maharashtra. Each institution uses a separate set of selection criteria to choose applicants, such as CET scores, gender, category. It is crucial for candidates to fill out the application form accurately, as it varies based on their academic standing and results from the entrance exam. Web applications and consulting services are available for recommending the best university based on a student's portfolio. These provide information on the universities that should be considered for admission. Numerous universities provide a wide range of engineering courses. Students find it difficult to arrange and identify the appropriate colleges for the courses they want to take based on their performance score. In this paper, we suggested a deep neural network (DNN) to forecast a student's likelihood of admission to a university based on their portfolio. The suggested model takes into account a number of student-related aspects, such as their CET Score and category.

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 Keywords

Admission, Deep Neural Network, Machine Learning, University Admission Prediction

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 Abstract

Financial literacy plays a crucial role in shaping individuals' financial behaviors and decision?making processes, particularly among undergraduate students who are transitioning into adulthood and assuming greater responsibility for managing their finances. This study examines the impact of financial literacy on investment decision-making among undergraduate students in India, with a focus on understanding investment preferences, factors influencing decision-making, and the relationship between financial literacy and investment outcomes. A sample of 120 undergraduate students from various educational institutions across India participated in the study, providing insights into their financial literacy levels, investment behaviors, and attitudes towards financial decision-making. The findings reveal a diverse range of financial literacy levels among undergraduate students, with the majority falling within the average range. Stocks and mutual funds emerged as the most preferred investment options, reflecting a preference for equity-based investments over traditional savings instruments. Factors such as financial goals, risk appetite, family influence, and information accessibility were found to significantly influence investment decision-making among students. Furthermore, the study confirms a positive relationship between financial literacy and investment decision-making, highlighting the importance of financial education in empowering students to make informed financial decisions. The study also identifies moderating and mediating factors that influence the relationship between financial literacy and investment decision-making, including individual characteristics, socio?economic factors, and psychological biases. These findings have important implications for policymakers, educators, and financial institutions seeking to promote financial literacy and improve investment outcomes among young adults in India. By understanding the factors influencing financial behaviors and attitudes and confirming the positive impact of financial education, stakeholders can design targeted interventions and policy initiatives to enhance financial literacy and foster financial well-being among undergraduate students

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 Keywords

Financial Literacy, investment decision making , investment preference

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 Abstract

Apart from Humanities and Science, Commerce is a fundamental academic stream in India. The field of commerce deals with trading things of economic value between two or more entities, in other words, exchange of services or goods from a producer to the final consumer. The field of commerce is the most influential and strongest social institution these days. As a branch of knowledge, Commerce education imparts the experience of the business world in all its manifestations. The growing phenomenon of privatization, globalization and liberalization has had an immense impact on the Commerce education. Commerce education imparts the experience of the business world in all its manifestations. It equips students with a number of specialized skills that help them excel in different functional areas of trade, industry and commerce. Commerce education is a living discipline and is totally different from other disciplines. Hence, it must charter new routes to service the aspirations of the nation. To man the economic development of the country and to meet the growing needs of the society, there is greater demand for sound development of commerce education in Indian Universities. The new National Education Policy 2020 will help in driving revolutionary change in the Indian educational system including commerce education. While giving impetus to India's vision to become the "Global Knowledge Superpower". The restructuring of higher education institutions that aims to become multi-disciplinary institutions will raise the standards of higher education in India by reassuring opportunities to deserved student community. The growing public sector of the country should also afford opportunities to the Commerce teachers on their boards and works council. If the teachers are trained in this manner the Commerce graduates would be automatically trained. The representation of Commerce teachers on the boards of private as well as public sectors of the industry, referring the problems of industry to the universities would make Commerce graduates more useful for the country.

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Skill, Career, Profession, Competency, Teaching, Trends.

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This research paper delves into the crucial role of forensic investigation in uncovering scams prevalent in both direct and indirect tax systems. In recent years, with the evolution of financial systems and the complexities therein, fraudulent activities have become more sophisticated, posing significant challenges to tax authorities worldwide. The paper explores the challenges and limitation faced by forensic experts in combating tax scams, including legal constraints, resource constraints, and the constantly evolving nature of financial crime. It also undersources the importance of collaboration between tax authorities, law enforcement agencies, and forensic professionals in effectively combating tax fraud.

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Fraud investigation, Forensic Role.

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This study looks at how personality traits affect how kind young people in India are. A cross-sectional study method was used to look at the 154 participants, whose ages ranged from 18 to 25. They were given self-report surveys that asked about their personality traits and how helpful they were to others. The Big Five Inventory (BFI) was used to test personality traits like agreeableness, extraversion, conscientiousness, neuroticism, and openness to experience. Items from well-known tests were used to measure kindness. The results showed that Agreeableness and Conscientiousness were linked to prosocial action in a good way. This means that these personality traits might be able to tell you about someone's tendency to work with others or help others. It wasn't very strong of a link between neuroticism and openness to experience, but it was stronger between extraversion and helping others. These results show how important it is to think about people's mental traits when coming up with ways to get them to be more altruistic. By recognising and capitalising on the effects of personality traits, educators, lawmakers, and practitioners can make personalised plans to build a community that works together and cares for each other. Important goals for future research include figuring out limitations like reaction biases, proving causation through longitudinal studies, and making sure the results can be used with different types of people.

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personality traits, prosocial behavior, young adults, India, Big Five Inventory, Agreeableness, Conscientiousness, Extraversion, Neuroticism, Openness to Experience.

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Implementing LoRa technology for emergency communication enhances penetration in remote areas, ensuring robust connectivity during crises. This system utilizes LoRa's long-range capabilities to transmit critical messages swiftly, bridging communication gaps in challenging terrains. With its reliable penetration and low-power consumption, LoRa-based emergency communication systems offer a resilient solution for effective crisis management

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Emergency Communication System, Long Range Network Technology, Low-power Wireless Capabilities, Real time Data, Penetrative Communication, Sensor network, Mesh Network

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Cataract, a common eye condition characterized by clouding of the lens, remains a leading cause of vision impairment worldwide. Timely detection and intervention are crucial for effective management of this condition. In this project, we propose a novel approach for cataract detection leveraging deep learning methods techniques.In this project, we introduce a novel method for detecting cataracts using deep learning. We utilize the EfficientNetB0 model for its efficiency and robustness in image classification tasks and implement parallel processing with a ThreadPoolExecutor to optimize computational resources. Using the ODIR-5K dataset, we train and evaluate the model, achieving an impressive 96.80 % accuracy in cataract detection. Our results demonstrate the model's efficacy in distinguishing between normal and cataractous retinal images, offering a promising solution for early detection and intervention in cataract-related visual impairments.

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Deep learning, EfficientNetB0, Convolutional neural network (CNN), Image classification, ThreadPoolExecutor

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 Abstract

Abstract: Agility in the fast eras bring the challenges but at the same time impacted several advantages in quality of education in terms of nowadays condition. The school principal remains the central source of leadership influence, Currently there are several skills need to be involved in school principal's leadership it is essentially lead to build professional growth in order to adapt to a new challenges and new purposes on curriculum, and solved school community issues before in this case is teacher intrinsic motivation. Nowadays the situations are more complex such fast eras in educational fields, so that the school principal orientation need to be directed into future leader skills that contain several skill, moreover this skills predicted can be enhancing school quality indicator. The aims of this study are to identify how school principal challenges on implementing future leader skills to the school community. Conducted by qualitative approach, study case, and using interview on collecting data, the subject of this study are school principal on duty and the previous decade from public and private school . The findings on this research are the school principal's challenges on implementing future leader skills generally are shifting paradigm, consistency, and fluctuated condition on implementing future leader skills caused by this leadership has a purpose to provide the internal core of awareness on changes to the school community. Specifically 1) strategic thinking, the school principal need to be able to be noticing efficiency on setting strategy while facing complex changing so that, it can build sense of optimism in school community 2) reflective thinking, the school principal need to be able reflecting on so many school concern 3) sense of sensitivity on school changes, school principal need to be able noticing appropriateness between school vision, mission, and the changes in order to build school on future perspective. The more willing principals are to spread leadership around, the better for the students.

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School Principal, Future, Leader.

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 Abstract

Adoption is a complex social, legal, and economic phenomenon that has existed in one form or another since ancient history. Adoption in some religions is allowed and in some other religions the practice of adoption is permitted but there are specific guidelines to follow, one such type of religion is the Muslim religion. With increasing numbers of abandoned and orphaned children and a growing number of hurdles, there is a need to tackle the issue. It is beyond the scope of this article to combat all of the nuances and issues raised by adoption in Islam. The main goal of this article is to understand the adoption of the Muslim religion and also an attempt to enlighten the readers regarding the verses of the Quran and the provisions of the Muslim Personal Law (Shariat) Application Act, of 1937. At the end of the paper, an attempt has been made to point out some existing flaws and the solutions to those flaws have been put forward by the researcher by referencing the recent Apex Court Judgement.

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Shariat law, Adoption, Quran, Drawbacks, Marham

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 Abstract

In this paper we aim to establish certain image formulas of H-Bar Function under Marichev- Saigo- Maeda fractional differential operators having Appell's function as a kernel. The results are expressed in terms of H? -function. A number of known and new results can also be obtained as special cases of these results.

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Marichev-Saigo-Maeda Fractional Differential Operators, -function, Appell function.

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This study focuses on creating a wireless charging system designed specifically for Electric Vehicles (EVs) to enable Vehicle-to-Vehicle (V2V) power transfer. The proposed solution operates on principles of Non-Radiative Wireless Charging, providing a safe and efficient method for transferring energy between vehicles. The primary motivation behind this project is the scarcity of traditional charging stations, leading to the exploration of more adaptable V2V solutions. Our approach utilizes resonant inductive charging technology, facilitating effective energy transfer without the need for physical contact. By carefully designing and implementing this V2V wireless charging system, we aim to improve the accessibility and convenience of charging for electric vehicles. The use of resonant inductive charging not only enhances efficiency but also contributes to creating a more sustainable and flexible charging infrastructure. This research represents a significant step towards advancing the practicality and scalability of V2V wireless charging solutions in the electric mobility sector, addressing key challenges in electric vehicle charging infrastructure.

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Inductive wireless charging, V2V charging, wireless transmission

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The proliferation of deepfake technology poses significant challenges to the integrity of digital content, necessitating robust detection mechanisms. In this study, we propose a hybrid approach that integrates ResNet, a convolutional neural network (CNN) architecture known for its feature extraction capabilities, with Long Short-Term Memory (LSTM) networks, specialized in capturing temporal dependencies. Our method aims to enhance the accuracy and effectiveness of deepfake detection by combining spatial and temporal information within a unified framework. We curate a diverse dataset containing authentic and deepfake videos, preprocess the data, and train the hybrid model using deep learning techniques. Evaluation on a separate test dataset demonstrates the superior performance of our approach, achieving high accuracy and precision in distinguishing between authentic and deepfake videos. Comparative analysis with baseline methods further validates the effectiveness of the proposed approach. Additionally, ethical considerations are carefully addressed throughout the research process, ensuring responsible development and deployment of the deepfake detection system. Through this study, we contribute to the advancement of techniques for combating deceptive visual media and preserving trust in digital content.

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Deepfake, Hybrid Resnet

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 Abstract

ABSTRACT This research paper delves into the critical role of employer branding in fostering employee retention within educational institutions. While the concept of employer branding itself is relatively new, with much of the research conducted in the last two decades (Ambler & Barrow, pioneering works), its application to the education sector offers a unique perspective. The Power of Employer Branding in Education: Employer branding bridges the gap between two crucial organizational areas: branding and human resources. This synergy allows educational institutions to develop a comprehensive strategy for attracting and retaining top-tier faculty and staff (Backhaus & Tikoo, 2004). A Competitive Advantage Through Employer Branding: An effective employer brand positions an educational institution as a desirable employer, offering a superior work experience compared to competitors. This strategic approach fosters a competitive advantage in the talent market, attracting and retaining high-caliber individuals (Love & Singh, 2011). Building a Strong Employer Brand in Education: This research explores the key components of a strong employer brand within the educational landscape. These components may include, but are not limited to, competitive compensation and benefits packages, clear pathways for career progression, and opportunities for professional development and value creation. A Changing Educational Landscape: The educational landscape is undergoing a significant transformation. The rise of online learning platforms, coupled with an increasing emphasis on research and innovation, has intensified competition among educational institutions. This competitive environment directly impacts an institution's ability to attract and retain qualified faculty and staff. The Importance of Employee Retention in Education: Retaining a talented workforce is crucial for educational institutions to achieve their strategic goals. A highly qualified faculty and staff are essential for maintaining high-quality education, fostering a positive learning environment for students, and ultimately ensuring the institution's continued success and growth. Expanding the Scope of the Research: Building upon the existing research on employer branding, this paper aims to provide a more detailed understanding of its specific application within the educational sector. By analyzing the unique challenges and opportunities faced by educational institutions, the research will explore how employer branding strategies can be tailored to effectively retain faculty and staff, ultimately contributing to the success of the institution itself. Additional Considerations: The abstract concludes by hinting at the potential for the research to address a broader and more professional audience. This could be elaborated on by mentioning the intended readership, such as university administrators, human resource professionals in education, or researchers focused on talent management in educational institutions.

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Employers, Corporate branding , Organizational culture , employee branding , employee retention

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 Abstract

The use of artificial intelligence for data access optimization is becoming increasingly important in the field of data science. AI algorithms can be used to create complex data structures that can be used to facilitate faster and more efficient access to data. Additionally, AI can be used to create frameworks capable of handling large amounts of data and optimizing the speed and accuracy of query results. This paper presents a framework for utilizing AI for data access optimization. In this framework, AI algorithms are used to create a structure for data storage and user interfaces that allow users to interact with the data more efficiently. Data mining techniques are used to identify patterns in the data that can be used to generate optimized queries. Additionally, the framework includes tools and libraries to automate processes and enable easy implementation of the developed framework. The proposed framework has been evaluated using a case study, and results show that the AI-based query optimization proposed in this framework can significantly reduce the query result time compared to traditional methods

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Data, Artificial Intelligence, Optimization, Accuracy, Mining

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Contact dermatitis is common skin problem occurring in 15% to 17% of people. Contact dermatitis is an inflammatory process in the skin caused by an exogenous allergen or an agent that directly or indirectly injures the skin. It may be allergic (ACD) or irritant (ICD). Irritant contact dermatitis is a nonspecific response of skin to direct chemical damage that releases inflammatory mediators predominantly from epidermal cells. Available treatment protocols in modern are identification and avoidance of causative agent or irritant, antihistamines, systemic or topical steroids and moisturizers. In this case report, a female presented to hospital with diagnosis ,Irritant Contact Dermatitis Acute. She was treated with modern as well as ayurvedic medicines, after two weeks of treatment ,the improvement was noticed in symptoms like itching, redness and burning sensation in the skin. The line of treatment in this case was to treat provoked pitta dosha, vitiated twaka, mamsa, vasa and ras ,rakta dhatu.

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Dermatitis; irritants; kshudrakushtha; pittapradhana tridoshaj vyadhi; etc.

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In the digital era, providing a safe and respectable online society is a top priority. Cyberbullying, an epidemic that presents a considerable danger to one's mental and social life, is impossible to avoid. This study addresses the issue of cyberbullying classification in Twitter data. We use the simple measures of sentiment analysis to do so in tandem with machine learning. In our project, we employ an SVM to classify tweets as cyberbullying or non-cyberbullying. The sentiment analysis pipeline produced by the sentiment analysis includes text preprocessing, transforming and weighting vectorization, and model training. Moreover, the system employs an interactive widget interface that allows the operators to infiltrate a tweet, and the system processes their input tweets to clean them up using usual expression extraction from URLs and non-alphanumeric characters before passing them to the pre-trained TF-IDF model for training and predicting if it's cyberbullied. Performance evaluation is performed through a classification report which provides precision, recall, F1-score, and support of each class metric. This system has the potential to enable users and administrators to intervene in cyberbullying cases in a preventative manner, making the online community a safer and more inclusive place.

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Cyberbullying detection, Sentiment analysis, Machine learning, Support Vector Machines (SVM), TF-IDF vectorization, Text preprocessing.

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A mental ailment that affects millions of individuals worldwide is depression. Improving results and averting long-term disability depend on early detection and treatment of depression. In this article, we present a machine learning-based method for detecting depression using two distinct approaches: sentiment analysis using Twitter data and a quiz based on the PHQ-9 questionnaire. For the quiz-based strategy, we employed a random forest algorithm; for the sentiment analysis technique, we utilized TF-IDF. Responses from people who completed the quiz and Twitter data from people who discussed depression were included in our dataset. According to our findings, the random forest model was the most accurate in predicting the depression phase from the quiz scores, with a 96.5 percent accuracy rate.

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Treatment, Detection, Depression, Mental Health, Disorders, Complexity, Patient Health Questionnaira

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 Abstract

the use of AI in statistics gets entry to techniques has recently emerged as a critical topic in the discipline of the information era. AI and gadgets gaining knowledge of strategies can enhance the performance and accuracy of facts to get entry to strategies. Also, they can offer extra blessings, including advanced scalability, privacy, and protection. This paper examines the feasibility of incorporating AI for efficient information entry techniques. An in-depth review of present studies inside the place of AI for statistics gets entry is supplied, highlighting the challenges and possibilities related to its use. The paper also examines the practical factors of incorporating AI for information get entry to techniques and assesses the price, scalability, and complexity of such procedures. We concluded that incorporating AI for records access techniques is viable and might benefit information customers significantly. However, similar studies are wanted to decide the most incredible layout and implementation of such techniques

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Data, Artificial Intelligence, Optimization, Accuracy, Privacy

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 Abstract

Human face having the different emotions. The emotion has varied forms like Happy, Surprise, Angry, Neutral, Sad, Fearful. The emotions are taken as the input from the inbuilt camera. We have used the Convolutional Neural Networks for emotion detection of the image taken from inbuilt camera and for implementing CNN we use Python, HTML, CSS, Django. Automatically Music playlist as well as Video is generated by identifying the current emotion of the user. The user can choose either music or video for their capability. The Music is useful for the people having audible sense and video is useful for the deaf and dumb people. Here it works by using the Spotify dataset for song recommendation and animation video for the visible outcome.

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Python, Django, CSS, HTML, CNN.

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 Abstract

The project focuses on a solar-based wireless charger utilizing inductive capacitance to transfer power wirelessly. It combines a solar panel, inductive capacitance coils, and a battery storage system. The solar panel harnesses sunlight to generate electrical energy, which is then wirelessly transmitted to devices through inductive capacitance coils. This technology eliminates the need for physical charging cables, streamlining the charging process and reducing clutter. Moreover, a battery storage unit stores surplus energy for use during low-light or nighttime conditions, ensuring a continuous power supply. By efficiently transferring power wirelessly, the system minimizes energy loss and contributes to a more sustainable and convenient charging solution for various electronic devices. This innovation represents a significant step towards eco-friendly and user-friendly charging technologies, merging the advantages of solar energy with wireless charging for a cleaner and more efficient power ecosystem.

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 Keywords

wireless charger, solar power, cords, TAM, photovoltaic cells, AC to DC, inductive charging, thermoelectric

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Creative Commons Attribution 4.0 and The Open Definition