bluuebunny/crossref_metadata_2025 huggingface dataset:
A Hybrid Logistic Scroll Chaotic Encryption Algorithm for Ensuring the Cloud Security to Counerfeiting the Attacks
Authors:   Department of Computer Science and Engineering, Vels Institute of Science, Technology and Advanced Studies (VISTAS), Chennai, admin admin ,   Department of Computer Science and Engineering, Vels Institute of Science, Technology and Advanced Studies (VISTAS), Chennai, Kathirvelu Kalaivani
Published: April 2024

Cloud computing is meant for storing the huge data using third party that ensures that confidential data cannot be accessed by the other users. But with rapid growth of technologies, data in the cloud normally increases which questions its security in storing in the cloud. Hence the protecting the cloud data seeks the strong security levels to counterfeit the different cloud attack. In order to achieve the highest level of security for cloud data, this study suggests a powerful encryption technique that combines chaotic scrolls and logistic maps. The proposed model exhibits the following advantages over the other algorithms: 1) High dynamic key generation 2) ability to counterfeit the multiple attacks 3) High randomness encrypted data which can provide more confusion of hacking from the intruder’s insight. To prove the strength of the proposed model, NIST National Institute of Science and Technology (NIST) is used for significant experiments. in which different statistical tests were carried out to prove the strength of the proposed model. The level of security of the suggested model is also evaluated and investigated using formal analysis using Burrows-Abadi-Needham Logic (BAN). The given model is thoroughly verified using both the Profverif tool and AVISPA. In terms of communication costs and unpredictability, the suggested model's randomness has also been contrasted with that of another existing algorithm. Results demonstrates that the proposed model shows its ability to provide more potent protection to the cloud data than the other existing encryption algorithms.
Sosialisasi dan Praktek Pengolahan Sampah Menjadi Eco-Enzyme pada Kegiatan Kuliah Kerja Nyata Kepada Masyarakat
Authors: Pangesti Deandra Anaya
Published: April 2024

Sampah kerap kali menjadi permasalahan yang dialami banyak negara. Seiring perkembangan zaman mendorong peningkatan laju pertumbuhan penduduk dan aktivitas produksi rumah tangga dan industri sehingga produksi sampah yang dihasilkan juga meningkat. Eco-enzyme merupakan hasil fermentasi limbah sampah organik seperti ampas buah, sayuran, buah, gula, dan air. Hasil fermentasi eco-enzyme dapat digunakan sebagai cairan pembersih rumah tangga yang bermanfaat bagi kehidupan sehari-hari. Pengabdian ini bertujuan untuk memberikan edukasi kepada masyarakat terkait pengolahan sampah organik melalui eco-enzyme. Munculnya kesadaran serta pengetahuan masyarakat terkait eco-enzyme diharapkan dapat meningkatkan Metode yang dilakukan adalah sosialisasi dan demonstrasi pembuatan eco-enzyme dengan sasaran warga sekitar serta kader sejumlah 30 orang. Kegiatan berlangsung dengan lancar dengan total kehadiran 30 peserta dan sebanyak 19 peserta menunjukkan antusias berupa mengajukan pertanyaan. Eco-enzyme berhasil dibuat dan dipantau selama 3 bulan setelah pengabdian selesai. Hasil pemantauan menunjukkan eco-enzyme terfermentasi dengan baik dan dapat digunakan.
Analysis of Islamic Religious Education (PAI) Problems and Solutions in Facing the Development of the 21st Century
Authors: Sulaiman Muhammad , Susanti Septiani Selly , Aini Nur , Wahyudi Fajar Satriyawan , Asy'arie Bima Fandi
Published: April 2024

In the development of the 21st century, Islamic religious education faces a number of challenges that need to be overcome. It can be seen that the lack of adequate facilities, such as reading books, causes students' disinterest in reading, the accuracy of using learning methods, and the like. The purpose of the study is (1) to find and describe the problems of Islamic religious education (2) analyze these problems, especially in Islamic religious education in the 21st century. Then, the type used in this study is using a qualitative approach with library research methods. The gains in this study from the forms of problems and solutions in Islamic religious education (PAI) in the development of the 21st Century are: First, internal problems (1) mastery of the material, (2) love the teaching profession, (3) skills in teaching, (4) evaluate student learning. Second, external problems (1) managing classes, (2) applying learning methods and models, (3) lack of teacher interaction with students, (4) utilization of learning media. So, to overcome these problems, a comprehensive and holistic approach is needed. Then it also takes strong collaboration between educational institutions, government, and other parties to be able to form a relevant curriculum in accordance with the times. Furthermore, the researcher provides suggestions for the next author to study more deeply and comprehensively about the problems of Islamic religious education in the 21st century. Especially on the causal factors and implications in learning through the use of technology.
Konjungsi Intrakalimat dalam Novel Mariposa Karya Luluk Hf
Authors: Safira Meliana , Charlina Charlina , Faizah Hasnah
Published: April 2024

Penelitian ini bertujuan untuk mendeskripsikan jenis dan makna konjungsi intrakalimat yang ada di dalam novel Mariposa Karya Luluk HF. Metode yang digunakan adalah metode kualitatif dengan teknik membaca dan Teknik mencatat. Metode analisis data yang digunakan adalah mereduksi data, kemudian dilanjutkan dengan penyajian data dan menarik kesimpulan dari analisis data yang telah dilakukan. Berdasarkan penelitian, data yang diperoleh sebanyak 850 data dari konjungsi intrakalimat yang terbagi menjadi konjungsi koordinatif yang memiliki lima makna, yaitu makna penjumlahan, makna pemilihan, makna perurutan, makna perlawanan dan makna lebih. Kemudian konjungsi subordinatif yang memiliki delapan makna, yaitu makna sebab, makna syarat, makna tujuan, makna kesewaktuan, makna penyungguhan, makna perbandingan, makna batas akhir dan makna pengandaian. Terakhir yaitu konjungsi korelatif yang tidak memiliki pembagian makna.
Vai trò điều tiết của giá trị xanh cá nhân tới tác động của quản trị nhân lực xanh đến hành vi xanh
Authors: Phạm Thu Trang
Published: April 2024

Nghiên cứu này tập trung vào việc đánh giá ảnh hưởng của quản trị nhân lực xanh đến hành vi xanh: cả hành vi xanh cá nhân trong nhiệm vụ và hành vi xanh ngoài nhiệm vụ của nhân viên, cũng như vai trò điều tiết của giá trị xanh cá nhân. Phương pháp khảo sát bằng bảng câu hỏi đã được sử dụng với 542 người tham gia từ các doanh nghiệp tại Việt Nam. Kết quả phân tích dữ liệu từ cuộc khảo sát cho thấy quản trị nhân lực xanh có ảnh hưởng tích cực đến cả hành vi xanh trong nhiệm vụ và hành vi xanh ngoài nhiệm vụ. Ngoài ra, nghiên cứu này cũng chỉ ra rằng giá trị xanh cá nhân có vai trò điều tiết mối quan hệ giữa quản trị nhân lực xanh và hành vi xanh trong nhiệm vụ, cũng như mối quan hệ giữa quản trị nhân lực xanh và hành vi xanh ngoài nhiệm vụ. Từ đó cung cấp những gợi ý thực tiễn cho các doanh nghiệp tại Việt Nam trong công tác quản trị nguồn nhân lực.
A Quantitative Study on the Intersection of Personal Competence and Classroom Efficiency in Dance Teaching: A Case of Middle and Primary Schools in Dongchangfu District, Liaocheng City, Shandong Province, China
Authors: Liu Shuangshuang
Published: April 2024

Dance education plays a vital role in fostering creativity, self-confidence, and overall well-being among students. Effective dance instruction requires a deep understanding of the intersection between personal competence and classroom efficiency among dance teachers. However, this intersection remains relatively unexplored, particularly in the context of Dongchangfu District, Liaocheng City, Shandong Province, China. To address this gap, this quantitative study examines how dance teachers' personal competence influences classroom efficiency in terms of student engagement, learning outcomes, and overall teaching effectiveness. A sample of 93 dance teachers from 45 primary and secondary schools in Dongchangfu District participated in the study. The findings reveal that dance teachers generally perceive themselves as competent and effective in their teaching practices, with high levels of technical skills, pedagogical knowledge, adaptability in teaching methods, communication effectiveness, and engagement in professional development activities. Moreover, teachers reported high levels of classroom efficiency, including student participation and engagement, achievement of learning objectives, effectiveness of teaching methods, classroom behavior management, and overall satisfaction with teaching outcomes. The study underscores the importance of continuous professional development, student-centered instructional strategies, effective classroom management, and support for novice teachers in enhancing dance education practices. The implications of the findings for practice, policy, and future research are discussed.
Assessing Stress Levels and Coping Mechanisms among Vocational and Technical College Students：A Case of XXX College, China
Authors: Wan Juhua
Published: April 2024

Stress is a prevalent issue among college students, exacerbated by academic demands, workload, time pressure, and future career concerns. Vocational and technical college students face additional stressors related to specialized programs, including technical skills training and industry expectations. This study focuses on stress levels and coping mechanisms among students at the XXX College in Guangdong, China, using a qualitative approach. In-depth interviews were conducted with 35 participants, revealing academic pressure, financial concerns, and personal/social challenges as significant stressors. Coping mechanisms included seeking social support, engaging in recreational activities, practicing mindfulness, and seeking professional help. The findings underscore the importance of targeted interventions and support systems to enhance student well-being and academic success in vocational and technical education.
Research on the development status, problems, and optimization path of green finance in commercial banks
Authors: Shang Jianhong
Published: April 2024

With the green economy gradually becoming the trend of global economic development, green finance has also risen to China's national strategy and become a new blue ocean business for the future development of commercial banks. The development of green finance not only plays an obvious role in improving economic efficiency and realizing the transformation and upgrading of industrial structure, but also plays a great significance role in environmental protection, and realize the harmony and unity of man and nature, which is an important initiative to realize the progress and development of the country.The article firstly points out the problems in the process of green finance development, and analyzes the challenges faced in the process of green finance development. Finally, the article gives the optimized ways for commercial banks to develop green finance from four perspectives, such as learning international law governance experience, introducing the Equator Principles for project evaluation, improving policy support, strengthening government guidance, strengthening product research and development and innovation, and attaching importance to talent cultivation, so as to provide a reference for China to further promote green finance and achieve high-quality development.
Research Progress on Fog Cultivation Technology for Potato Seed Production
Authors: Ya Ru
Published: April 2024

The market demand for potato seed (minituber) is increasing with the progression and expansion of the potato industry, and the potato seed degeneration has become one of the important factors to restrict the yield and quality of potatoes in the actual development of potato industry. In recent years, the aeroponic cultivation of potato seed has the advantages of high yield and high efficiency as a newly developed virus-free production technology, which effectively solves the problems of soil-borne diseases and continuous cropping obstacles during the potato seed production, as well as opens up a new way for the scalization of potato seed production. In this thesis, the key points of potato seed aeroponic technology, the facility intelligentization development, the core nutrient solution and cultivation management and methods of automatic control of supply system were elaborated, the current problems and application prospects of this technology are summarized based on personal production experience, aimed to provide some foundations for the production as well as practical guidance of potato seed aeroponics cultivation.
The Current Situation and Enhancement of College Students' Mental Health
Authors: WANG XIAOWEI , LU JIHU , HU TINGTING , WANG YAN
Published: April 2024

The purpose of this study is to investigate college students and examine the current status of their mental health, so as to provide a basis for improving the mental health of college students. Three hundred and ninety-six college students were selected as the research subjects and their mental health was investigated by questionnaire method. The results showed that: 1. The mean scores of each dimension of SCL-90 and the mean scores of SCL-90 total scores ranged from 1.2654 to 1.7997, which were higher than the theoretical value of asymptomatic (1 point); the SCL-90 total scores were also higher than the theoretical value of asymptomatic (90 points). 2. The number of college students whose mean scores of each of the 10 dimensions of SCL-90, and whose mean scores of the total score of the scale reached the score of the positive symptom determinationranged from 9.09% to 31.06%; the proportion of college students whose total scores on the SCL-90 reached the positive symptom determination score was 16.41%, and the level of college students' mental health was relatively low.3. Effective and feasible methods to improve college students' mental health have been proposed. This study not only investigates the current situation of college students' mental health, but also provides empirical support and theoretical guidance for improving college students' mental health.
Consumer Perspectives on Commercial Pension Insurance Products: Insights and Implications
Authors: HUO XIUNING
Published: April 2024

This study delves into the consumer perspectives on commercial pension insurance products, aiming to uncover insights into awareness, understanding, preferences, and concerns among consumers. Through interviews with 50 participants from five prominent Chinese insurance companies, the study examines demographic characteristics, awareness levels, perceived benefits and risks, factors influencing purchase decisions, and satisfaction with current products. The findings reveal a nuanced landscape wherein participants recognize the importance of pension insurance for long-term financial security but express apprehensions regarding policy transparency, affordability, and reliability. Trust in insurance companies, reputation, and financial stability emerge as primary factors influencing purchase decisions, highlighting the need for flexible and affordable policy options aligned with individual retirement goals. Comparative analysis among companies underscores variations in consumer perceptions, emphasizing the importance of continual product evaluation and improvement to meet evolving consumer needs. The study concludes by advocating for enhanced consumer education initiatives and regulatory frameworks to foster transparency and consumer welfare within the competitive insurance market.
The Role of Continuing Education in Lifelong Learning: A Quantitative Study in Two Universities in China
Authors: QI JIANG
Published: April 2024

This quantitative study explores the role of continuing education (CE) in fostering lifelong learning among students in two universities in China: Hunan University of Science and Technology and Changsha University of Science and Technology. The research investigates students' attitudes, perceptions, and engagement levels towards continuing education, aiming to provide insights into the effectiveness of existing CE programs and identify areas for improvement. A structured questionnaire was administered to 300 undergraduate and graduate students, utilizing Likert scale responses. Results indicate a balanced representation across gender identities, with varying levels of engagement across academic years and fields of study. The majority of respondents report prior experience with CE, indicating proactive engagement in lifelong learning activities. Findings also reveal a generally positive outlook towards lifelong learning, with high levels of agreement on the importance of self-directed learning, adaptability, and openness to new ideas. Engagement with CE activities is predominantly positive, with strong participation in industry conferences, online courses, and additional certifications. Participants perceive CE as positively influencing academic performance, career prospects, and personal growth. The study underscores the significance of integrating CE initiatives into educational frameworks to support holistic student development and promote lifelong learning. It emphasizes the importance of addressing barriers to access and enhancing skills development within CE programs to empower students for success in today's dynamic job market.
Research on the Effect of Introducing Speeches in English Classes on Improving Oral English Ability under the Background of Digital Teaching
Authors: Lu Jiaxi
Published: April 2024

This study investigates how classroom speech training can boost English speaking skills within digital teaching contexts. It reveals that incorporating the ISAS teaching method with English speech training in vocational college courses can significantly enhance students' communication skills, particularly in oral expression. The research employed various methods to demonstrate that classroom speeches effectively elevate students' English speaking proficiency, diversify teaching content and methods, and foster innovation in English speaking education at vocational colleges. Integrating teaching materials with topics relevant to the software field, along with using a range of expressive forms and techniques, aids in broadening students' perspectives, making English classes more practical and engaging, and bolstering their English application skills and professional competencies. The study also highlights the crucial role of teachers' instructional abilities and personal qualities in enriching students' English learning and skill development. It suggests that teachers integrate more speech-focused activities into regular instruction to advance students' comprehensive English capabilities.
ANALYTICAL STUDY OF CREDIT CARD USAGE AND PAYMENT TRANSACTIONS (WITH REFERENCE TO STATE BANK OF INDIA)
Authors: Rao Dr. Wuppuluru Ramana
Published: April 2024

The study presents an analytical view of credit card payment transactions with special reference to one of the major giant in banking sector, the state bank of India. India is on its verge of going towards cashless economy and credit cards have emerges as one of the important tool in this directions. The research is focused on the statistics related to credit card payment transactions through PoS, Online (e-com) and other sources. The study is based on the quantitative analysis of transaction data with qualitative insights. Secondary data available on the official website of RBI is used to make the study authentic. The analysis will uncover the usage patterns and important reasons for using credit cards among the Indian consumers. Key findings also highlights about the challenges related to security concerns and customer dissatisfaction regarding certain aspects of credit card experience. Key words: Credit cards, Card payments, cashless transactions.
Literature Review: Skin Cancer Types Detection Using Deep Learning
Authors:   Department of CSE(AI &ML)  Vidyavardhaka College of Engineering Mysuru, India, D C Vinutha
Published: April 2024

Skin cancer ranks among the swiftly proliferating diseases globally, exacerbated by the limited resources. Timely recognition of skin cancer holds paramount importance for precise diagnosis and identification, facilitating a preventative approach overall. The incidence of melanoma, the most perilous type of cancer of the skin, is increasing. Identifying skin cancer in its initial phases poses a challenge for dermatologists. Over the past few years, both supervised and unsupervised learning assignments have extensively employed deep learning techniques. Among these, Convolutional Neural Networks (CNN) has outperformed its counterparts in tests related to object detection and classification. The algorithm used here relies on a bank of directional filters (difference of Gaussians) and explores color, directionality and topological properties of the network. Dull Razor algorithm has been used to remove artifacts such as hair as they cause difficulties in detecting pigments. Keywords— Deep learning, Convolutional Neural Networks (CNN), Color analysis, Data Augmentation, Artifacts removal, Pigment detection.
Generative Artificial Intelligence
Authors:   Department of Master of Computer Application  Trinity Academy of Engineering, Pune, Warankar Mayuri
Published: April 2024

Generative AI is a cool tech that helps machines create new stuff that looks a lot like what humans make. Think of it like a computer artist who can paint pictures, write stories, compose music, and even make videos. This paper is all about explaining generative AI: where it came from, what it's doing now, and how it's used. It works by using fancy computer programs and smart algorithms to understand patterns in data and then make new things that fit those patterns. It's super important because it's changing how we do things in fields like healthcare, entertainment, and education. But, it's not all fun and games. Generative AI also brings up some serious questions about privacy, fairness, and making sure we use it in good ways. This paper dives into all that, showing the good and the tricky parts of generative AI and how it's shaping our world. Key Words: Generative AI, technology, machine creativity, data patterns, applications, healthcare, entertainment, education, privacy, fairness, ethical use, societal impact.
Sign Language Interpreter
Authors:   Tulsiramji Gaikwad Patil College Of Engg , Mohgaon ,  Nagpur, Bopte, Mr.Vishal
Published: April 2024

Sign language serves as a vital mode of communication for millions of individuals worldwide who are deaf or hard of hearing. However, there exists a significant communication barrier between sign language users and those who do not understand sign language. To address this challenge, this project presents a Sign Language Interpreter, a software solution leveraging real-time image processing techniques.. Keywords — Machine Learning, Real time image processing, Hand tracking, Gesture Recognition, Adaptive learning, MERN development.
Advanced Vehicle Locking System Using Facial Recognition
Authors:   Electronics Engineering Yeshwantrao Chavan College of Engineering Nagpur, India, Dive Bhushan
Published: April 2024

Access control systems are crucial for vehicle security. This study presents an innovative method employing a Raspberry Pi-based system integrated with face-api.js, along with dlib libraries, to establish a secure vehicle access control system. Facial recognition algorithms are utilized for user authentication, adding an extra level of security. Any unauthorized access prompts an alert to the administrator, improving real-time monitoring and response capabilities.
BREAST CANCER DETECTION USING MACHINE LEARNING ALOGRITHM
Authors:   Department of Computer Science and Engineering, Raghu Engineering College, Visakhapatnam, Sagar Voolla. Vidya
Published: April 2024

Breast cancer is the most common and second most common cause of cancer in women. [3] Early diagnosis of breast cancer can provide better treatment and thus increase survival rates. Data classification using machine learning is widely used in cancer diagnosis and early cancer detection. The purpose of this literature review is to focus on the use of machine learning in classifying existing data in the early detection and diagnosis of breast cancer. When much scientific literature is examined, it is clearly seen that there are many methods for the diagnosis of breast cancer. The aim of this study is to provide a comprehensive review and recommendations on cancer screening and diagnosis. "Breast cancer type classification using machine learning."[1]Provides an overview of current research on multiple breast cancer cases using data mining techniques to improve breast cancer diagnosis and prognosis.. Key Words: breast cancer, machine learning, artificial neural networks, decision tree, support vector machine nearest neighbor, healthcare system, Wisconsin breast cancer database
Smart Eye : Empowering the Visually Impaired with Assistive Technology
Authors:   Department of ECE RVR & JC College of Engineering, Guntur, Andhra Pradesh, India, Nabi, D. Mahammad
Published: April 2024

According to the World Health Organization, an estimated 39 million people worldwide are visually impaired, underscoring the critical need for innovative solutions to assist blind individuals in navigating their environment independently. In response, this study introduces an intelligent and multipurpose bright blind stick leveraging Internet of Things (IoT) technology. The stick integrates components such as Arduino UNO, ultrasonic sensor, servo motor, Bluetooth module, GPS, and GSM modules to detect obstacles in real-time and provide audio feedback alerts to the user. Additionally, the technology enables remote monitoring by caregivers through GPS tracking and allows users to send location-based alert messages in emergencies. Through extensive research and comparative analysis of existing systems, including traditional white canes and other electronic aids, our solution has been designed to overcome common limitations such as high cost, limited functionality, and lack of portability. The intelligent multipurpose bright blind stick offers a cost-effective, portable, and intelligent tool aimed at significantly enhancing the independence and safety of blind individuals, fostering inclusivity and autonomy in their daily lives. This paper will provide insights into the design, implementation, and user testing of the solution, highlighting its effectiveness in real-world scenarios and its potential to make a meaningful impact on the lives of blind individuals worldwide. Index Terms - Arduino UNO, Servo Motor , Ultrasonic Sensor Bluetooth Module, GPS Module, GSM Module, Multi-functional Blind Stick and Internet of Things.
Optimizing Portfolio Construction Using Nifty India Manufacturing Index: A Risk-Return Analysis with Python
Authors:   CMS Business School, Jain Deemed to be University,  Bengaluru – 560009, R Dharshan
Published: April 2024

This paper presents a comprehensive analysis of portfolio construction strategies aimed at maximizing risk-adjusted returns for investors. Utilizing historical data on stock returns and risks, a meticulous selection process was employed to identify 15 stocks with superior risk-return profiles. These stocks were chosen based on their outperformance relative to the dataset's average measures, prioritizing returns higher than the dataset average and risks lower than average risk levels. The selected stocks, representing a diverse range of manufacturing-related businesses, formed the cornerstone of an optimal portfolio designed to minimize sector-specific risks while maximizing growth potential. Through rigorous portfolio optimization techniques, including Markowitz's mean-variance optimization, the study identified an optimal portfolio allocation with a return of 50.22% and volatility of 13.33%. Insights from the study offer valuable perspectives for investors seeking realistic and sustainable wealth accumulation strategies. The research also identifies avenues for future exploration, including the integration of alternative asset classes, behavioral finance insights, and advancements in risk management technologies. This study demonstrates the effectiveness of Python in financial analysis and portfolio optimization while furthering the theory of portfolios and providing valuable guidance for making investment decisions. Keywords: Returns, Risk, Volatility, Optimal Portfolio Construction, Manufacturing Sector, Markowitz Portfolio Theory,
GAS LEVEL MONITORING AND ALERTING WITH GAS LEAKAGE
Authors: Rao Prof.G.Raja
Published: April 2024

The project aims in designing a Gas cylinder level monitoring and Gas leakage detection also alerting system using GSM technology. This system capable of detecting the Gas in the cylinder according to weight and display onLCD. Also, this system will activate the buzzer and sensing the alert SMS to the predefine mobile number through GSM if the cylinder weight crosses the set limit or if the system detects the gas leakage.This project makes a use Arduino NANO Microcontroller which is used to interface with input and output modules. Continuous weight monitoring of Gas cylinder using load cell and will be display on LCD. LOW level Gas alerts using Buzzer and SMS. GSM module is used to send the alert SMS to the user mobile. GAS sensor is used to detect the GAS.The main controlling device of the project is ARDUINO NANO Microcontroller.
Design and Implementation of Women Auspice System with GPS Tracking
Authors:   Siddam Vasuki Abhirami, Dept of ECE,  Guru Nanak Institute of Technology, Hyderabad, Rao r. Ch. Rama Koteswara
Published: April 2024

The project, named "Design and Implementation of Women Auspice System with GPS Tracking. aims to enhance the safety of women. Despite many advances in technology, many women still feel worried about their safety. Despite the rapid advancement of technology in the 21st century, many women still feel unsafe venturing outside alone during late hours or at unusual times. While technology has evolved, concerns over their safety persist. The solution proposed here is a wearable device, something like a small gadget that can be carried easily or worn, which doesn't rely on having a smart phone or being able to operate one in a stressful moment. This project aims to create a small, easy-to-use device that women can carry with them to feel safer when they're out and about. If they feel threatened, they can quickly press a button to call for help, without needing to fumble with a phone. Keywords- Arduino UNO R3, GPS, GSM, Buzzer, Safety.
Impact of Electric Vehicles in Logistics Operations in Establishing Green Supply Chain
Authors: Tiwari Shashwat
Published: April 2024

Electric vehicles (EVs) in the logistics are being adopted for more sustainable and nature friendly supply chain. This paper examines the impact of EVs in supply chain mainly logistics and its role in the green supply chain. The paper focuses on a comprehensive review of the benefits, challenges, and prospects associated with the integration of EVs into the logistics process. Through a combination of literature review, case studies, and case studies, this paper explores how EVs contribute to reducing carbon emissions, reducing operating costs, improving overall productivity better in supply chain management and moreover, it is important for the successful integration of EV in the logistics industry The findings of the study examining the regulatory framework, technological developments and industry needs highlights the particularly positive impact of EVs on logistics, including reduced environmental footprint, improved last-mile delivery and moving reputation forward by providing sustainable services but low margins, initial and high cost problems Challenges remain barriers to high adoption In conclusion, this paper highlights the transformation that electric vehicles have in the logistics industry and highlights the need for strategic planning, ongoing collaboration between stakeholders and infrastructure another ongoing process to achieve a greener and more sustainable supply chain.
WEB MINING TO DETECT ONLINE SPREAD OF TERRORISM
Authors:   Department of Information Technology, Shrimati Kashibai Navale  College of Engineering, Pune, India, Kadam Aishwarya
Published: April 2024

To fight online terrorism, integrating web mining techniques with data mining algorithms is crucial. Various algorithms like Logistic Regression, K-Nearest Neighbors (KNN), Support Vector Machines (SVM), Naive Bayes (NB), Decision Trees (DT), Random Forests (RF), and Gradient Boosting (GB) are studied for detecting terrorist activities online, extracting data, identifying patterns, and relevant information. Logistic Regression provides a probabilistic framework, KNN uses similarity metrics, SVM constructs hyper-planes, NB assumes feature independence, DT builds decision trees, RF applies ensemble learning, and GB boosts weak learners' performance. These algorithms aid in proactive monitoring and prevention of online terrorism through efficient analysis of structured and unstructured web data. By combining web mining and data mining strengths, this study emphasizes a comprehensive approach to combatting online terrorism dissemination, helping security agencies anticipate evolving threats and prevent terrorist propagation effectively. Key Words: Terrorism, Naive-bayes, random forest, web mining, Gradient boosting
MULTIPLE BRAIN DISEASE PREDICTION WITH DIAGNOSTIC REPORT USING DEEP LEARNING
Authors:   Head, Department of Computer Science & Engineering, Dhirajlal Gandhi College of Technology, Salem,  Tamilnadu, India, J Ms.Vaijayanthimala
Published: April 2024

The prevalence of brain diseases such as Alzheimer's disease, brain tumor, and strokes poses significant challenges to public health worldwide. Early detection and accurate diagnosis of these conditions are crucial for timely intervention and improved patient outcomes. In this context, the development of a deep learning-based system for brain disease prediction represents a promising approach to address these challenges. This project aims to create a web application that utilizes a Convolutional Neural Network (CNN) algorithm to predict the three main brain diseases affecting humans: Alzheimer's disease, brain tumor and stroke. Users can upload MRI or CT scan images of their brain to the web application, which then analyzes the images using the trained CNN model to determine whether the individual is affected by any of the targeted brain diseases. If a brain disease is detected, the application generates a detailed diagnostic report, specifying the type of disease and providing relevant information such as disease severity. Users have the option to view the report within the application interface and download it in A4 sheet format for future reference. In future, Extending the system to predict a broader range of brain diseases beyond the initial four main diseases. This expansion would require additional training data and fine-tuning of the deep learning model to recognize a diverse set of disease patterns. Exploring opportunities for personalized medicine by integrating clinical data with medical imaging data to tailor treatment plans to individual patients' needs and genetic profiles. Key Words: Brain Disease, Deep Learning Model, CNN, Alzheimer's disease, brain tumor, stroke, Accurate Diagnosis
HR Automation: Enhancing Candidate Onboarding Processes
Authors:   Artificial Intellegence and Data Science Department, Shah and Anchor Kutchhi Engineering College, Pazare Shital
Published: April 2024

Human Resources (HR) departments are faced with the problem of effectively managing a variety of activities, from talent acquisition to legal compliance, in the dynamic workforce landscape of today. This study explores the ground breaking integration of Artificial Intelligence (AI), with an emphasis on Natural Language Processing (NLP), as a transformative force in reimagining Human Resources (HR) management methodologies." The pivotal role of two cutting-edge AI tools, the Legal Language Model (LLM) and the Language Model for Attribute-based Matching (LAMA), is examined in addressing key HR challenges. LLM employs sophisticated NLP techniques to automate and refine the interpretation of complex legal documents, ensuring compliance and reducing legal risks. Concurrently, LAMA transforms the recruitment paradigm by facilitating a nuanced, attribute-based alignment of candidates' profiles with job requirements, thereby optimizing the talent acquisition process. We explore the integration of these models within an interactive framework provided by Streamlit, a Python tool for creating user-engaging web applications. This integration offers HR professionals an intuitive platform for accessing, visualizing, and interacting with model-generated insights, fostering informed decision-making and enhanced operational efficiency. Our analysis reveals significant improvements in the precision of recruitment processes, efficacy in legal document handling, and overall workflow streamlining. The findings advocate for the adoption of these AI-driven tools in HR, highlighting their potential to revolutionize traditional practices and contribute to the strategic growth of organizations in the contemporary digital landscape. Key Words: Human Resources Management, Legal Language Model (LLM), Language Model for Attribute-based Matching (LAMA), Streamlit, HR Technology Integration, HR Automation.
REAL TIME WIRELESS FIRE FIGHTING ROBOT
Authors:   Assistant Professor, Dept. Of Mechanical Engineering, Gurunanak Institute Of Technology, Khanapur, India., sriram T. Jaya
Published: April 2024

The Real-time Wireless Firefighting Robot is an innovative autonomous robotic system designed for effective fire response in hazardous environments. This robot integrates advanced technologies such as wireless communication, sensors, and real-time data processing to enhance firefighting capabilities. Equipped with a high-resolution camera, the robot can navigate through smoke-filled areas and transmit live video feeds to the control center. The wireless communication system enables seamless remote operation, allowing firefighters to assess the situation and make informed decisions. The robot's robust design and fire-resistant materials ensure its durability in high-temperature environments. Overall, the Live Wireless Firefighting Robot presents a cutting-edge solution for improving firefighting efficiency and reducing risks to human responders. This robot is equipped with advanced sensors for real-time fire detection and localization. Its wireless connectivity enables remote control and monitoring, allowing firefighters to operate it from a safe distance. The robot's mobility and agility enable it to navigate challenging environments, reaching areas that may be hazardous for humans. With a built-in water or foam spraying system, the robot can effectively suppress fires. Additionally, it incorporates live video streaming to provide a comprehensive view of the situation. The use of wireless technology not only facilitates seamless communication but also ensures quick response times, making this robot a valuable asset in firefighting scenarios, minimizing risks to human lives. Key Words: Fire Fighting Robot, Mobility, Live video feeds.
RELATIONSHIP BETWEEN OIL PRICES, EXCHANGE RATES AND STOCK INDICES
Authors:   MBA Student, Mittal School of Business, Lovely Professional University, India, Singh Ayush
Published: April 2024

This research examines the connections between oil prices, exchange rates, and stock indices in India. It examines correlations and causal effects between these key financial variables. The Granger causality tests fail to detect any significant causal effects between exchange rate returns and either crude oil returns or stock returns. These findings are valuable for long-term decision-making, and further research is needed to fully understand the impact of oil prices on stocks. This study adds to our knowledge of these relationships in the Indian market. Keywords: Oil prices, exchange rates, market, relationships, stock indices
Review Paper on Study and Analysis on Low-Cost Housing
Authors:   ATMA MALIK INSTITUTE OF TECHNOLOGY AND RESEARCH , SHAHAPUR, JADHAV Mr . AMOL .A.
Published: April 2024

Studying and analyzing low-cost housing involves examining various aspects such as design, construction materials, location, affordability, sustainability, and social impact. Here's a breakdown of some key considerations: 1. Design: Low-cost housing often requires innovative designs that maximize space utilization while minimizing costs. This may include modular construction, tiny homes, or efficient layouts that reduce the need for excessive materials. 2. Construction Materials: The choice of materials significantly impacts the cost of housing. Analyzing alternative, locally-sourced materials that are both affordable and durable is essential. This might involve using materials like bamboo, recycled materials, or compressed earth blocks. 3. Location: The location of low-cost housing projects is crucial for accessibility to job opportunities, transportation, and essential services. Analyzing the availability of land and infrastructure in suitable locations can influence the feasibility of such projects. 4. Affordability: True low-cost housing must be affordable not only in terms of initial construction but also in terms of ongoing maintenance and utilities. Analyzing the total cost of ownership over time is essential to ensure that housing remains accessible to its intended occupants. 5. Sustainability: Sustainable practices should be integrated into low-cost housing projects to minimize environmental impact and reduce ongoing costs. This may involve energy-efficient design, renewable energy sources, water conservation, and waste management strategies. 6. Social Impact: Low-cost housing projects should consider the social impact on communities, including issues like inclusivity, community engagement, and empowerment of residents. Analyzing the social dynamics and potential benefits Key Words: Affordability, Construction material , House technique , Urbon Planning
IoT Based Smart Irrigation System
Authors:   Asst Prof Department of Computer Engineering & IETE’S Bharat College of Engineering, Athawale Deepak
Published: April 2024

In recent years, the integration of Internet of Things (IoT) technology into agriculture has shown great potential for enhancing irrigation practices, thereby improving crop yield and water efficiency. This paper presents the design, implementation, and performance evaluation of an IoT-based smart irrigation system tailored for agricultural applications. The proposed system employs various sensors to monitor soil moisture levels, weather conditions, and crop water requirements in real time. Data collected from these sensors are transmitted wirelessly to a central control unit, which utilizes an intelligent algorithm to optimize irrigation scheduling and water distribution. The system also incorporates remote monitoring and control capabilities, allowing farmers to access and manage irrigation operations from anywhere via a web or mobile interface. Experimental results demonstrate the effectiveness of the IoT-based smart irrigation system in conserving water, reducing energy consumption, and enhancing crop productivity. Moreover, the scalability, reliability, and cost-effectiveness of the proposed solution make it suitable for deployment in both small-scale and large- scale agricultural settings. Key Words: IoT, smart irrigation, agriculture, soil moisture sensor, wireless communication, optimization, remote monitoring
COMPARATIVE ANALYSIS ON DEEP LEARNING METHODS FOR BOT DETECTION
Authors:   Professor, Department of Computer Science and Engineering, Tirumala Engineering College, Naik Dr.R.Lalu
Published: April 2024

Social bots are automated accounts on social media that are managed by software and overseen by people behind the scenes. While some bots are created for positive reasons, like sharing news updates or offering assistance in crises, others have been misused to spread false information, rumors, or influence political events. There are tools in place to identify and eliminate harmful bots automatically, but creators are continually evolving their techniques to evade detection. Hence, there is a pressing need for improved ways to differentiate between genuine and automated bot accounts. In recent years, several research studies have delved into the realm of social media bot detection, offering an extensive overview of different detection strategies, including advanced approaches such as machine learning (ML) and deep learning (DL) techniques. To the best of our knowledge, this study stands out as the first to solely focus on DL techniques, evaluating their efficacy and rationale in comparison to each other and to conventional ML methods. In this research, we offer a comprehensive classification of the characteristics utilized in deep learning research and provide information on the necessary preprocessing methods for creating appropriate training data for a deep learning model. We highlight the gaps identified in review papers discussing deep learning and machine learning studies, offering insights into future developments in this area. In general, deep learning methods have proven to be efficient in terms of computation and time for detecting social bots, demonstrating superior or comparable performance compared to traditional machine learning techniques. Key Words: Bot Detection, Social Media, Deep Learning, Computation, Automation
Evaluating the Efficacy of Remedial Measures under the Competition Act: A Critical Study
Authors: Bhardwaj Kanupriya
Published: April 2024

The Competition Commission of India (CCI) plays a crucial role in evaluating and regulating mergers, acquisitions, and amalgamations that may have an adverse effect on competition. The CCI has reviewed over 1,000 filings since 2011, requiring modifications in approximately 40 cases to mitigate competition concerns. These modifications range from structural remedies like divestitures to behavioral commitments addressing issues such as access, discriminatory practices, and information sharing. The CCI follows distinct procedures during Phase I and Phase II reviews. In Phase I, parties propose voluntary modifications, which the CCI assesses. There is also an intermediary period for modifications before Phase II. During Phase II, the CCI can suggest and negotiate modifications, which parties must implement within a specified timeframe to secure approval. The CCI adopts a flexible, case-by-case approach when crafting remedies tailored to address specific competition issues. Structural remedies like divestitures are preferred for significant horizontal overlaps, while behavioral remedies tackle vertical concerns. The CCI engages extensively with parties to ensure effective mitigation of competitive harm. Aligning with global best practices, the CCI collaborates with international regulators on cross-border mergers. However, it maintains a strong focus on India-specific impacts. Parties are advised to propose timely, proportionate remedies, ideally in Phase I, and maintain contingency plans.