Volume 12 | Issue 4 |

 Abstract

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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 Keywords

Inductive wireless charging, V2V charging, wireless transmission

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Deepfake, Hybrid Resnet

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Creative Commons Attribution 4.0 and The Open Definition

 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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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

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

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Creative Commons Attribution 4.0 and The Open Definition

 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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 Keywords

Data, Artificial Intelligence, Optimization, Accuracy, Mining

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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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 Keywords

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

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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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 Keywords

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

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

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

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Creative Commons Attribution 4.0 and The Open Definition

 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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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Data, Artificial Intelligence, Optimization, Accuracy, Privacy

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Creative Commons Attribution 4.0 and The Open Definition

 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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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Python, Django, CSS, HTML, CNN.

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Creative Commons Attribution 4.0 and The Open Definition

 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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Creative Commons Attribution 4.0 and The Open Definition

 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