bluuebunny/crossref_metadata_2025 huggingface dataset:
CORRELATES OF MAJOR DEPRESSIVE DISORDER AND HEALTH CARE UTILIZATION AMONG PATIENTS WITH SICKLE CELL DISEASE.
Authors: Yakubu Anas , KAREEM Yesiru , Umar Musa , Bakare Abdulfatai , Sani Abubakar , Ahmad Abubakar , Bello Amira , Abdullahi Uzairu , Bunza Habibu
Published: November 2024

BACKGROUND: The comorbidity between major depressive disorder (MDD) and sickle cell disease (SCD) has been documented in numerous literature sources, and there have been reports of an increase in both urgent and non-urgent healthcare utilization among individuals with both conditions compared to those with either of the conditions alone.
AIM: To determine the correlates of major depressive disorder and health care utilization among patients with sickle cell disease
MATERIALS AND METHODS: The study was conducted at the Usmanu Danfodiyo University Teaching Hospital (UDUTH) in Sokoto and involved SCD patients. A semi-structured questionnaire was used to gather data on sociodemographic, clinical, and healthcare utilization variables, at the same time the Patient Health Questionnaire-9 (PHQ-9) and the Mini International Neuropsychiatric Interview-7 (MINI) were employed to screen and diagnose MDD, respectively.
RESULTS: SCD patients with comorbid MDD reported significantly more visits to primary care physicians (P = 0.041), underwent more laboratory tests (P = 0.007), received fewer prescribed medications (P = 0.004), and had more visits to other hospitals (P = 0.005). However, no significant association was found with hospitalization (P = 0.476), daycare visits (P = 0.102), or emergency department visits (P = 0.315).
CONCLUSION: This study showed that comorbid SCD and MDD are associated with an increase in non-urgent healthcare utilization, such as outpatient visits, but did not find an increase in urgent healthcare utilization, including acute hospitalizations and emergency admissions.
Predictive signals in visual cortex
Authors:   , Seignette Koen
Published: November 2024

Our visual perception is not simply a continuous picture of the world. It is heavily influenced by context, prior experience and most importantly: predictions. We constantly predict the movements, actions and sensory information of everything around us and quickly detect any deviation from these predictions. In this thesis, I studied how visual processing is affected by experience and predictions and what happens in our brains when these predictions are violated. In Chapter 2, we developed a novel calcium imaging analysis toolbox that allowed us to extract high-quality neuronal signals from our calcium imaging datasets. Although not directly related to visual predictions, the work in this chapter was an important step to support the analytical work necessary for the other experimental chapters in this thesis, which both use calcium imaging as a main technique. In Chapter 3, we studied the role of chandelier cells in the primary visual cortex (V1) of mice in relationship to visuomotor predictive processing. We found that chandelier cells have unique connectivity with other neurons in the local network and that they are strongly activated by surprising visual stimuli, such as when these deviate from what is expected based on movement. Furthermore, we discovered that after repeated exposure to visual stimuli in a virtual tunnel, chandelier cells showed plasticity leading to reduced responses to visual input. We also found that in contrast to popular believe, chandelier cells in V1 have relatively little inhibitory control over the activity of nearby pyramidal cells. Finally, in Chapter 4 we describe the role of visual experience on predictive processing of visual information. We investigated how neurons in V1 responded to visual input and to the context of this information by showing mice several different natural scenes. By sometimes partially occluding the images, we were able to measure how neurons in V1 responded when contextual information, but no direct visual input, was presented. We discovered that when we showed partially occluded images, neurons in V1 responded to the occluded area with stimulus-specific activity: we could infer which image was shown based on their responses. These signals were strongly influenced by the extent to which the mouse was familiar with the images that we showed. We also found that separate populations of neurons in V1 responded to the occluded and not occluded pictures. Finally, we found that pictures that had not been shown during training of the mice, making them unexpected, induced stronger responses in V1. Taken together, the research described in this thesis provides a better understanding of the role of experience and predictions on visual processing.
"Toward Loving All Neighbors: Considering Ralph Waldo Emerson’s Theology, Philosophy, and the Idea of Shared Flourishing (Eudaimonia)"
Authors:   , Carlton Jeremiah
Published: November 2024

ABSTRACT

TOWARD LOVING ALL NEIGHBORS:
CONSIDERING RALPH WALDO EMERSON’S THEOLOGY, PHILOSOPHY, AND THE IDEA OF SHARED FLOURISHING (EUDAIMONIA)

Jeremiah L. Carlton

Vrije Universiteit, 2024

This dissertation argues that Ralph Waldo Emerson developed a unique theological and ethical worldview that emphasized the interconnectedness of all beings and advocated for an inclusive, nature-based spirituality aimed at human flourishing. Through close analysis of Emerson's writings, sermons, and personal journals, as well as examination of his influences and contemporaries, this study demonstrates how Emerson's theology evolved from traditional Unitarianism toward a more universal and transcendental philosophy.

The core claim is that Emerson's mature thought represents a coherent ethical and theological system grounded in several key principles:

First, the divine permeates all of nature and humanity, making direct spiritual experience accessible to all.

Second, self-reliance and cultivation of one's inner moral sense are paramount for ethical living.

Third, organized religion and dogma should be transcended in favor of personal spiritual insight.

Fourth, all beings are interconnected, necessitating an ethic of care and inclusion toward others and nature.

Fifth, human flourishing comes through aligning oneself with the moral law of the universe.

By tracing the development of these ideas in Emerson's life and work, this dissertation argues for understanding Emerson as a systematic theological and ethical thinker whose philosophy remains relevant for contemporary religious and moral discourse. His vision of inclusive spirituality and ethics aimed at shared human flourishing offers an important alternative to exclusivist religious tradition.
OPTIMIZING THE QUALITY OF SUPERIOR EDUCATION IN DARUL HUDA STIES' COLLEGES THROUGH HR MANAGEMENT STRATEGIES
Authors: Rahayu Puji
Published: November 2024

Improving the quality of education in the STIES Darul Huda Mesuji Lampung Sharia Economics study program is faced with human resource management (HR) challenges which include limited lecturer training, supporting infrastructure, and technological adaptation. This research aims to identify and analyze effective HR management strategies in improving the quality of education, with a focus on implementing competency-based recruitment, sustainable development through training, and integrating technology in the learning process. The research method used is a qualitative approach with a case study method, involving in-depth interviews, observation and document study. The research results show that although there are efforts in managing human resources, challenges such as uneven training and technological limitations are still the main obstacles. Implementation of a more structured HR management strategy, including transparent recruitment, continuous training, and application of sharia principles such as fairness and transparency, can significantly improve lecturer performance and education quality. Management support and investment in technology infrastructure is critical to support the sustainability of this strategy.
The Effects of Culture Shock on The Cultural Adaptation of Overseas Students in Thailand at King Mongkut’s University
Authors: Nguyen Duong Minh Quyen
Published: November 2024

This paper aims to examine the phenomenon of culture shock experienced by international students studying in Thailand for their master’s degree and explore their strategies for adapting to Thai culture. This research employed a semi-structured interview with eight international students at King Mongkut’s University of Technology in Bangkok, Thailand. The participants completed the open-ended questionnaires and provided responses via a Google Docs link. The writer will use Kalervo Oberg's four stages of culture shock to better understand culture shock and the adaptation process of overseas students studying in Thailand. The research illustrates the causes behind international students' desire to pursue educational institutions in Thailand and their experiences with culture shock across the four stages, along with their adaptation process. The findings suggest that overseas students suffer from culture shock in relation to their surroundings, language, cultural norms, and academic areas.
Bölgesel Güvenlik Kompleksi Teorisi Kapsamında Göç Olgusunun Orta Asya Güvenliğindeki Rolü
Authors: Temür Burcu , Bilgili Cihan
Published: November 2024

Göç olgusu, küreselleşmenin etkisiyle geçmişe kıyasla artış göstermektedir. Bu artış, Orta Asya'nın temel dinamiklerinden biri haline gelmiştir ve bölge ülkeleri için çeşitli anlamlar taşımaktadır. Orta Asya'daki devletlerin politik ve ekonomik kırılganlıkları ile coğrafi yapının geçirgenliği, göç olgusunu bölgenin güvenliğini olumsuz etkileyen faktörler arasına dahil etmektedir. Yasadışı göç, uluslararası düzeyde de etkili olup insan, uyuşturucu ve silah kaçakçılığı gibi sorunlara yol açmaktadır. Özellikle sınır güvenliğinin yetersizliği ve ülkeler arası iş birliğinin zayıflığı, Orta Asya'daki göç trafiğini artıran faktörler arasında yer almaktadır. Bu durum, sadece bölgedeki aktörlerin değil, aynı zamanda uluslararası kuruluşlar ve sivil toplum örgütlerinin de önemli roller üstlenmelerini gerektirmektedir. Bu çalışmada Orta Asya'nın göç sorunu, Kopenhag Okulu temsilcilerinden Barry Buzan ve Ole Waever’in geliştirmiş oldukları Bölgesel Güvenlik Kompleksi Teorisi (BGKT) çerçevesinde incelenmiştir. Bu teori çerçevesinde, aynı bölgede bulunan, coğrafi yakınlık içinde olan ülkelerin güvenlik sorunları bakımından birbirleriyle ilişki içinde oldukları savunulmaktadır. Çalışma, Türkçe, Rusça ve İngilizce literatürlerden derlenen verilerin analiziyle şekillenmiş ve medya haberleri ile uluslararası örgüt raporları da dâhil edilerek zenginleştirilmiştir. Bu araştırma, göç olgusunun Orta Asya'daki güvenlik dinamiklerini anlamak, BGKT’nin Orta Asya bölgesinde göç olgusu temelinde güvenlik kompleksi oluşturmak için elverişli olup olmadığını test etmek ve daha etkili güvenlik politikalarının geliştirilmesine katkı sağlamak amacıyla yapılmıştır. Göç olgusunun bölgenin güvenliği üzerindeki etkilerini daha derinlemesine anlamak, bölge ülkelerinin bu alandaki politika ve stratejilerini daha etkili bir şekilde yönlendirmelerine yardımcı olabilir.
Between coercion, conditionality and abandonment: A descriptive analysis of English mental health spending and provision under austerity
Authors: Kiely Ed
Published: November 2024

While critical scholarship has demonstrated the harmful effects of austerity on public mental health, relatively little attention has been paid to austerity’s impacts on health services themselves. In response, this paper develops a descriptive analysis of mental health spending and provision in England during the austerity period, from 2009–10 to 2019–20. It examines spending patterns at the national and local level, highlighting a major growth in funding that has been overlooked by prior studies. Then it interrogates national trends in mental health provisioning, utilisation and treatment. The paper argues that austerity has divergent impacts on localities which are best understood as multiple localised austerities. Meanwhile, the overall mental health service landscape under austerity is characterised by three trends, all of which have the potential to harm public health. Inpatient services are utilising more coercion; community services are increasingly conditionalised; and a significant population – too ill for work but judged too healthy for treatment – has been abandoned by services. For critical scholars and practitioners of public health, these findings highlight the complexity of the political, economic and institutional dynamics which distribute spending cuts and therefore mediate austerity’s effects on health.
Reverse Sign Language Recognition System Using Machine Learning
Authors:   Department of Computer Engineering,Vidya Vikas Pratishthan Institute Of Engineering And Technology,Solapur., Mahindrakar Aaditya , Misal Anushka , Dyavarkonda Vaibhavi , Kadam Aishawarya , Shendge Prof. Smita
Published: November 2024

Deaf and hard-of-hearing people communicate with each other and their society by using sign language. As this is a very natural method for pupils to stay in touch with computers, many academics are working on it to make it less complex and more convenient for use. So the main objective of gesture recognition research is to make systems which can interact and communicate while understanding human gestures and use them. In simple words to communicate information. Fast and extremely accurate hand detection and realtime hand gestures. Identification should be possible with vision-based hand gesture circumstances and interfaces. Learning and knowing sign movements and gestures is the kick start in making words and sentences for computer assisted sign language interpretation. Both dynamic and static sign actions are open and available. Both ways of gesture recognition are crucial to human culture, even if static gesture recognition is much easier than dynamic gesture recognition. When a human enters the value of alphabets and numerical value as input, the system immediately displays or outputs the appropriate recognised character shows the gesture on the monitor screen. In the following, research projects that have led to a proper system that uses convolutional neural networks to identify handwriting on the basis of the depth pictures and Hand Languages (Brain lipi) the collects. Keywords- Convolutional neural network,Text recognition ,Convert to image,StackGAN,simultaneous Tracking text and converting to image, gesture recognition,display output as sign gesture,training machine to(A-z to 1-0).
Neural Style Transfer, Creating Art with Deep Learning
Authors: Duggal Bhanu , Khurana Dikshant , Rishabh Rishabh , Jain Rishabh , Kirti Kirti
Published: November 2024

Abstract—Neural style transfer is a deep learning technique that is the topic of study in this research paper. In NST two images are combined, a content and a style image. Where, while retaining the content image the artistic style of style image is imposed on the content image. In this research, a series of ways are explored to improve the efficiency and visual quality of the generated image. This research is about improvising and molding the existing losses, to improve the existing methodologies. Key contributions are dynamic weighting of content and style losses, multi scale loss computation for preserving the details in a better way. This kind of loss improvisation and changing is being used, so that not only the high-level structures and fine details are maintained in the image generated. These dynamic and multiple kind of losses will be implemented to retain the essence of the content in the content image. While generating a new image the content or style is overcompensated and most of the time one of these is having a stronger effect on the final image in most of the techniques, our motive is to eradicate the same and generate an excellent image. Along with this, various optimization techniques are studied in the underlying paper to compensate this computation cost of the newly introduced losses. The ways provide a framework for a neural style transfer with a higher quality and efficient combining of images. Index Terms—NST (Neural style transfer), dynamic weighting, multi-scale losses.
Machine Learning in Healthcare: Developing an AI Assistant Doctor for Symptom-Based Disease Prediction
Authors: Mondal Dr Dipannita , Shinde Harshad , Baghele Sarang , Kadam Pratham , Thengal Darshan
Published: November 2024

The rapid advancements in data science and machine learning have revolutionized various sectors, particularly healthcare. This research introduces an innovative AI Assistant Doctor system that utilizes machine learning techniques, specifically a Support Vector Classifier (SVC), to predict potential diseases based on user-reported symptoms. The system aims to bridge the gap between symptom recognition and understanding their significance, promoting early intervention and improved health outcomes. The AI Assistant Doctor offers a comprehensive healthcare tool that goes beyond disease prediction, providing users with detailed information about illnesses, preventive measures, drug recommendations, nutritional guidance, and personalized exercise suggestions. The SVC model is trained on a diverse dataset of symptoms and diseases, enabling accurate predictions. The system is designed to be accessible through a user-friendly web interface, allowing individuals to input their symptoms and receive immediate insights. In addition to disease prediction, the AI Assistant Doctor equips users with a thorough understanding of the predicted condition, including its symptoms, causes, and typical progression. It also offers preventive strategies, suggested medications, dietary advice, and customized physical activity recommendations to help users manage their health effectively. By leveraging machine learning algorithms and web-based frameworks, this research presents a cutting-edge approach to disease prediction and healthcare management, addressing the growing need for accessible medical information and timely interventions. The AI Assistant Doctor has the potential to alleviate pressure on healthcare systems, improve individual health outcomes, and support medical practitioners in delivering precise diagnoses and personalized treatment plans. Keywords: Machine learning, Disease Prediction, Support Vector Classifier (SVC), Healthcare, Symptoms, Prevention Personalized recommendations.
A Brief Study on Indian Startups- Analytic Research on the Success and Failure Factors of Swiggy, Boat, Doodhwala, And Shopx
Authors: Praveenadevi Dr.D , Nazia Mohammad , Srilekha Y.V , Meghana P , Snehitha B
Published: November 2024

India’s startup ecosystem has witnessed unprecedented growth in recent years, emerging as one of the most dynamic and fast-paced environments globally. This research paper examines the primary factors leading to the high failure rate of Indian startups, focusing on familiar challenges such as inadequate business models, poor product-market fit, cash flow problems, regulatory hurdles, and inefficient management. Through case studies of successful ventures like Swiggy, and BoAT, this paper highlights critical success factors that have enabled these companies to thrive, including data-driven decision-making, customer-centric strategies, adaptability, and strong strategic partnerships. The study also explores the pivotal role of venture capitalists (VCs) in shaping startup trajectories, from early seed funding to advanced growth stages. Additionally, the paper delves into the influence of Indian government initiatives, such as Startup India and the Atal Innovation Mission, in fostering a supportive ecosystem that encourages entrepreneurship and innovation. Keywords: Entrepreneur, Start-up, Economy, Future market, Challenges
Culinary Tourism and its Role in Diversifying Punjab Tourism Offerings
Authors:   PCTE group of Institute, Baddowal, Ludhiana, Jain Tanya , Priyadarshi Sudhanshu , Das Manoj , Gupta Anirban
Published: November 2024

Culinary tourism, a rapidly growing niche within the tourism industry, encompasses travel experiences focused on exploring local food and drink, connecting visitors with a region’s unique culinary traditions. This paper examines culinary tourism in Punjab, India, a region known for its rich flavors, traditional cooking techniques, and vibrant food culture. Punjab’s culinary offerings, especially in cities like Amritsar, Jalandhar, and Patiala, have the potential to diversify and enhance its tourism appeal beyond religious and cultural tourism, attracting food enthusiasts and promoting cultural exchange. Through a descriptive analytical approach, this study explores how culinary tourism can serve as a driver for local economic development, supporting small businesses and local farmers while preserving Punjab’s cultural heritage. By highlighting local food festivals, traditional dishes, and farm-to-table experiences, the paper addresses how Punjab can leverage its culinary heritage to position itself as a premier destination for food tourism. Furthermore, this research emphasizes the role of culinary tourism in supporting sustainable economic development, underlining its potential to create jobs, preserve traditions, and diversify Punjab’s tourism market. The findings suggest that a robust culinary tourism strategy in Punjab can not only elevate the region's tourism profile but also contribute to a more resilient local economy. Keywords: Culinary Tourism, Cultural Heritage, Sustainable Economic Development, Food Tourism Punjab
Medi-Cliq (A Drug Dispenser) - A Survey Paper
Authors: Journal IJSREM
Published: November 2024

In this paper, the concept of automated drug dispensing is summarized, and its significance in the healthcare sector is illustrated. MediCliq is designed to efficiently dispense prescribed medication, is researched in detail, focusing on the integration of mechanical design with IT-based control systems. Key technologies, including prescription scanning, prescription validation, and user interac- tion interfaces, are explored to enable seamless dispensing and user authentication. This paper also conducts a formal review of interdisciplinary methodologies, combining mechanical engineering with IT for developing an effective, secure, and user-friendly automated drug dispensing solution. Keywords: Automated drug dispensing, Prescription scanning, Secure dispensing solution, Prescription validation
Big Data and Blockchain Integration Enhancing Data Management and Security
Authors:   SCSVMV(Deemed to be University), Saraswathi Dr.M , Bhargava R. Saketh ,   SCSVMV(Deemed to be University)
Published: November 2024

Big Data and blockchain are two of the most transformative forces shaping the faces of industries around the world in this digital age. Where Big Data allows organizations to exploit vast pools of information to make informed decisions, blockchain gives one a decentralized and highly secure way of handling and sharing data. Based on the integration of the two technologies, several of the existing challenges in data security and transparency together with its management could be resolved. This paper looks at the advantages, technical details, practical applications, and challenges when big data meets blockchain and through this synergy, a more efficient, secure, and transparent data ecosystem can be developed.
Despite Contradictions, Artificial Intelligence and Block Chain Technology are Composing the Future Together
Authors:   Arni University, Rani Neha , Thakur Minakshi ,   Arni University
Published: November 2024

Now times, Block Chain technology and enhancements in Artificial Intelligence paradigm are facing more attention in the field of research with new advancements in many security techniques in all the sectors of IT and business. One cannot deny from the fact that the adoption of Artificial Intelligence paradigms and block-chain technology is shaping the new face of market. Beyond their contradictions both are proceeding at lightning speed. Both of them are aimed at providing something new to the world but the degree of complexity of each is quite different. With a secure, decentralized, and trustworthy system, block-chain technology did automate the bit-coin payments and provide the users an access to a shared ledger of records, transactions and data. With the useof smart contracts, a block-chain can also regulate the user interactions without the need for any central authority. In the contradiction, AI provides agents with the ability of reasoning, decision making and human-level intellect. At bottom one can say, block chain is concerned with keeping correct records, authentication and implementation while AI deals in conducting assessments, examining, and coming to a decision analyzing certain patterns and datasets, eventually giving rise to a self- directed interaction. Artificial Intelligence along with block chain allocates several descriptions which will make a seamless communication prospect certainly. AI and Block-Chain need sharing of data. The decentralized approach of database focuses on the significance of data sharing among various clients on a meticulous network. In the same way, AI depends very much on Big-Data, exclusively, for data distribution. The first section in the proposed article offers the Introduction part. The second section focuses on the majorly emphasized topics and domains about block chain technology indulging Artificial Intelligence into it, presents a detailed literature-review of many of the contributions by eminent research analysts. The third section describes the challenges in the collaborating AI with block-chain. The last section expresses a brief conclusion of the research work. Keywords- Block Chain Technology, Artificial Intelligence, AI, Machine Learning
Smart Park: Innovating the Future of Vehicle Parking
Authors:   Department of Electronics and Telecommunication, GHRCEM Nagpur., Ugale Dr. Shubhangini
Published: November 2024

Effective parking solutions become increasingly important as urban areas increase because of wasted space, time-consuming searches, and traffic congestion. By utilizing cutting edge technologies to improve parking management and user experience, the Smart Vehicle Parking System (SVPS) tackles these issues. To deliver dynamic solutions, SVPS combines sophisticated algorithms, sensor networks, and real-time data. Parking space sensors track occupancy and transmit data to a central system, where machine learning maximizes space distribution and directs vehicles to open spaces. This smart parking system is software and hardware based. Different algorithms are used to find vacant slots using machine learning and deep learning. IR sensors, RFID, Servomotors and ESP 32 microcontrollers and Internet of things are useful to find vacant slots in real time signal processing. In traditional method it is difficult to search free space, and this method is time consuming, Smart parking system overcome this problem with new technology and improve parking management system. The SVPS not only improves urban mobility but also contributes to reducing vehicle emissions and enhanced overall efficiency. Keywords— smart parking, integration, secure payment,advanced technologies, convenient.
Forecasting Cryptocurrency Market Movements Based on Bitcoin, Ethereum, and Ripple Returns
Authors: V Neha , R Ravi Shankar , N Aarthi
Published: November 2024

Cryptocurrency has transformed from a niche interest to a significant investment domain, attracting diverse investors globally. However, the cryptocurrency market is marked by extreme price volatility and risk, particularly for major digital currencies like Bitcoin (BTC), Ethereum (ETH), and Ripple (XRP). This analysis dives deeply into the historical behavior of these cryptocurrencies, examining their volatility, returns, interdependencies, and potential predictability using advancedmodeling approaches.
Analysis of ABSL Multicap Fund and Textile sector with Innerwear and Hosiery as a Subsector with reference to Lux Industries Ltd
Authors: Kolhapure Rohan , Pol Prof. Mahesh
Published: November 2024

The internship project entitled "Analysis of ABSL Multicap Fund and Textile Sector with Innerwear and Hosiery as a subsector with reference to Lux Industries Ltd." was taken up at Aditya Birla Sun Life Ltd. by Rohan Ganesh Kolhapure. The project would involve assessing the performance, strategies, and market positioning of the ABSL Multicap Fund for the period between June-August 2024. This also included assessing the textile sector dynamics, with special inward titude toward the innerwear hosiery subsector, using Lux Industries Ltd as a case study. The main tasks were related to the assessment of historical performance of ABSL Multicap Fund and its investment strategies, as well as the analysis of sectoral trends influencing the innerwear market. Specific methodologies included quantitative analysis of financial statements, asset allocation, and risk management practices, in addition to strategic frameworks like SWOT, PESTEL, and Porter's Five Forces.
Online Voting System Using Blockchain: A Secure and Transparent Approach
Authors: Madke Nilesh B. , Prajapati Arvindkumar , Chaudhari Gaurav , Sonawane Sanket , Patil Vaibhav
Published: November 2024

Blockchain technology has emerged as a viable solution for secure and transparent digital voting systems. Traditional voting systems, particularly online voting mechanisms, are often vulnerable to security risks such as hacking, tampering, and vote manipulation. Furthermore, maintaining voter anonymity and ensuring data integrity are significant challenges. Blockchain, with its distributed and immutable ledger, offers potential solutions by providing a secure and decentralized approach to recording votes. This paper explores the architecture, implementation, and advantages of a blockchain-based online voting system that leverages the security features of blockchain technology to improve the voting process. By utilizing cryptographic principles and decentralized data storage, the system enhances transparency, reduces fraud risks, and ensures that votes remain immutable. The proposed system includes mechanisms for voter registration, vote casting, and result verification, all of which are secured by smart contracts. Experimental results demonstrate that blockchain can maintain voter anonymity, resist tampering, and provide an auditable voting trail. Additionally, the study discusses challenges in scalability, latency, and regulatory compliance, offering insights into potential improvements and future work. Overall, the research indicates that blockchain based voting has the potential to transform electoral processes, providing a trusted digital voting alternative that aligns with democratic principles. Key Words: Blockchain Technology, Digital Voting, Online Voting Systems, Data Integrity, Transparency, Security, Cryptography, Smart Contracts, Voter Anonymity, Tamper-Resistance, Immutable Ledger, Scalability, Decentralization.
Exploring the Potential of Agritourism: A Gateway to Sustainable Development in Kumaun Region of Indian Central Himalayas
Authors: Joshi Arti , Lohani Dr. Jitendra Kumar , Upadhyay Govinda Raj
Published: November 2024

Agritourism, a fusion of agriculture and tourism, is a new ray of hope for the sustainable development of rural regions livelihoods, economies, and other related sectors. This concept combines both aspects, with the potential to provide economic benefits to rural livelihoods and enrich the experience for tourists who visit the place. Agritourism has potential as a catalyst for sustainable development in the Kumaun region of Uttarakhand state, which is the eastern part of the state, boasts rich scenic natural beauties, cultural heritage, diverse landscapes, and all above organic and traditional agricultural practices. The paper explores existing agritourism initiatives in the Kumaun region, ranging from farm stays to culinary experiences. and analyzes the economic benefits, challenges, and prospects of agritourism. This abstract underscore the transformative power of agritourism in encouraging sustainable development in rural areas of the Kumaun region while preserving cultural heritage, promoting environmental conservation, and enhancing socio- economic well-being. Keywords: agritourism, agriculture, Kumaun, economic development.
SOCIAL MEDIA FAKE ACCOUNT IDENTIFICATION USING ML
Authors: Dalvi Shraddhesh , Gholap Shubham , Jadhav Piyush , Baviskar Prof. Pallavi
Published: November 2024

The proliferation of social media platforms has led to an increase in the creation of fake accounts. These accounts are used for various malicious activities, such as spreading false information, phishing, and identity theft. As a result, there is a growing need for effective methods to identify and eliminate fake accounts. This paper proposes a machine learning-based approach for social media fake account identification. This paper proposes a machine learning-based approach to identify fake accounts on social media platforms. Our method leverages a combination of feature extraction techniques and supervised learning algorithms to classify accounts as genuine or fake. We collect a large dataset of labeled social media accounts, including both genuine and fake profiles, and extract features from various sources such as profile information, network behavior, and content analysis. We experiment with multiple machine learning models, including Support vector machines(SVM),K-Nearest Neighbors Algorithm(KNN),Random forest, Logistic Regression & Artificial Neural Network(ANN) to evaluate their performance in identifying fake accounts. Our proposed method has significant implications for social media platform operators, policymakers, and researchers seeking to combat fake accounts and maintain online trust. The approach can be integrated with existing social media moderation tools to enhance the accuracy and efficiency of fake account identification. Key Words: Support vector machines(SVM),K-Nearest Neighbors Algorithm(KNN),Random forest, Logistic Regression & Artificial Neural Network(ANN),Python.
Dye-Sensitized Solar Cells: Unveiling Barriers to Enhanced Performance
Authors: Nemade Savita Rambhau , Khare Purnima Swarup , Nemade Kailash
Published: November 2024

Global energy consumption is steadily increasing, and the world's reliance on non-renewable energy sources such as hydroelectric and thermoelectric power is unsustainable due to their diminishing availability. The photovoltaic (PV) devices have been developed through various methods for various applications, and among these, Dye- Sensitized Solar Cells (DSSCs) have emerged as a cost-effective and easily implementable technology. This comprehensive review paper offers an in-depth overview of DSSCs, aiming to provide insights into their construction, working principles, applications, and the significant challenges they face, primarily related to their low efficiency and stability. To fully commercialize DSSCs and compete with existing energy technologies, it is imperative to continue addressing and overcoming the efficiency challenges outlined in this review. KEYWORDS: TiO2, Dye Sensitized Solar Cell, Electrolyte, Photoanode, Counter Electrode
Innovative Discovery Studies of Anti Lungs Cancer Active Drug Substances in Medicinal Chemistry
Authors:   Department of Chemistry, Master of Philosophy in Chemistry  Arignar Anna Govt. Arts College, B Narayanamoorthy , Ravichandran Dr. CT ,   Department of Chemistry, Master of Philosophy in Chemistry  Arignar Anna Govt. Arts College
Published: November 2024

The discovery study of anti cancer active drug substance of (2S,2′S)-2,2′-[[2,2′- Diamino-4,4′,6-trioxo-1,4,4′,6,7,7′-hexahydro-1′H,5H-5,6′-bipyrrolo[2,3-d]pyrimidine-5,5′- diyl]bis(ethylenebenzene-4,1-diylcarbonylimino)] dipentanedioic acid was synthesized and characterized by medicinal chemistry bath way, also this product was obtained via the associated with the synthesis of pemetrexed disodium was performed. The possibility of (2S,2′S)-2,2′-[[2,2′-Diamino-4,4′,6-trioxo-1,4,4′,6,7,7′- hexahydro-1′H,5H-5,6′-bipyrrolo[2,3-d]pyrimidine-5,5′-diyl]bis(ethylenebenzene-4,1-diylcarbonylimino)] dipentanedioic acid forming has been mentioned in literature, but no study on this structure has been published yet. This paper describes the development of the synthesis methods and preclinical studies for this compound and discusses their structure elucidation on the basis of NMR experiments and MS data. The identification of anti cancer drug activity of this compound by preclinical test, it should be useful for identify the new anticancer drug in pemetrexed generation.
Impact of Cloud Computing in Finance Graphs
Authors: Journal IJSREM
Published: November 2024

The financial sector, which serves as the backbone of the global economy, has undergone significant transformation with the adoption of cloud computing. This paper presents a detailed analysis of the connection between cloud computing and finance, drawing insights from an in-depth review of scholarly articles in the Scopus database. As financial institutions navigate evolving customer demands, regulatory challenges, and the need for innovation, cloud computing has emerged as a dominant force. It has ushered in a new era where competition is reshaped and operational efficiency is prioritized. The introduction highlights the critical role cloud computing plays in enhancing the financial landscape. Traditionally, financial institutions have been complex and resource-heavy systems, but they now face the pressing need for digital transformation. Cloud technology's scalability, flexibility, and cost-efficiency offer a guiding light for organisations aiming to reimagine their operations in this digital era. This paper examines not just the evolution but the profound shift in which cloud technology becomes a key driver in redesigning the way financial services are developed, delivered, and experienced. Keywords—cloud computing, AWS, machine learning, finance.
Financial Ratio Analysis of Tata Motors Limited
Authors:   Indira School of Business Studies,PGDM, Kadbhane Rudranksh , Pol Prof. Mahesh
Published: November 2024

This report presents a comprehensive financial ratio analysis of Tata Motors Limited, focusing on its performance in the automobile industry. The analysis aims to evaluate the company's financial health and operational efficiency through various financial ratios. The findings are based on data collected during a summer internship at Tata Motors, providing insights into the company's strengths and weaknesses in the competitive market.
File Compression System Using Huffman Coding
Authors: Journal IJSREM
Published: November 2024

Abstract—File compression, which minimizes file sizes without significantly compromising the quality of information contained in the file, is among the most critical aspects of data management since it facilitates fast flow and storage of data. Storage manage- ment has become more challenging due to the exponential growth of digital data; hence, efficient file compression has been an issue of great importance to help in decreasing storage expenses and increasing data transfer rates. This paper presents a web interface for the file compression system that is based on lossless data compression known as Huffman coding to reduce the size of the files without changing their content. A standard internet portal allows the users to upload their files to the system and get back resized files within the shortest time possible. The technique employed in the compression is astute in that it uses Huffman codes which give characters codes depending with their frequencies in the file. It then follows that since most of the file will have short codes; the file will take up less space. To safeguard the compressed information, the system generates a data structure called a Huffman tree in which no code is a sub- string of any other. This application does seize to be usable from a few selected devices such as desktops and laptop computers but can also be accessed from projectors and cell phones because of the effective design. The file compression system is also versatile and accommodates various file categories such text, image and binary among others providing users with convenience in a number of sectors. Index Terms—Data Compression, Hoffman Coding, HTML( Hypertext Markup Language), CSS ( Cascading Styling Sheet ), JavaScript.
Adaptive Random Early Detection Using Deep Reinforcement Learning for Enhanced Congestion Control in Dynamic TCP/IP Networks
Authors: Matrood Mohammed Q. , Ali Majid H.
Published: November 2024

AQM is used to meet targets for congestion control and low delay, high throughput in TCP/IP networks. But methods developed for AQM like Random Early Detection (RED) work strictly on the control parameters pre-set on them and thus may not respond very well to changing network conditions. Thus, this paper presents a composite AQM model using DRL based on DQN, and the ability to learn independently regarding the AQM weight parameter of the queue. The fact that DRL is adaptive means the effectiveness of the proposed system is also assured. As it is observed in implementing traditional model-based approach, the stability and performance degrade when tested in different network conditions; however, DRL’s ability to learn independently enables ML to solve network congestion as it happens. Consequently, more stability is achieved, the delay is lesser, more bandwidth is used and the overall packet drop rate is low; the proposed DRL-RED model is ideal for dynamic network environments. The proposed DRL-RED model is compared with the regular RED algorithm for both low density and high-density networks. This proposed model has achieved sustained throughput of up to 49.9 Mbps with 0.949 % reduction on delay and very low PLR of 8.38043%. From the comparative analysis, it is clear that the employment of DRL with RED improves the stock of network throughput, the reduction on packet drop frequency, and the general delay in network situations. There are two main disadvantages of this approach: first, it cannot reach the heavy-traffic, the problem partly solved by model-based approach; second, the values of the congestion-control parameters cannot be reset, an issue eradicated by DRL as a result of its inherent adaptiveness. Consequently, new stability and increased performance can be achieved under various network conditions.
The Effect of Training and Work Environment on Employee Performance through Employee Engagement as an Intervening Variable
Authors: Kurahman Muhammad Taufik , Tyas Ari Anggarani Winadi Prasetyoning
Published: November 2024

This research aims to examine the influence of Training and Work Environment through Employee Engagement on Employee Performance at PT. Coway International Indonesia. This research was motivated by employee performance which was not mentioned, so research was carried out to find out which training, work environment and Employee Engagement variables would have the most influence on employee performance at PT. Coway International Indonesia. The population in the study were employees of PT. Coway International Indonesia. Meanwhile, the research sample was taken using a purposive sampling technique and then using a saturated sampling technique, namely all members of the population were used as samples with a total of 100 respondents. This research is quantitative research using the Structural Equation Model - Partial Least Square (SEM-PLS) method. The results of the research show that Training and Work Environment have a positive effect on Employee Engagement, Training and Work Environment have a positive effect on Employee Performance, Employee Engagement has a positive effect on Employee Performance, Training has no positive effect on Employee Performance through Employee Engagement, finally the Work Environment has a positive effect on Performance Employees through Employee Engagement. After conducting research, the author suggests expanding the population to other branches, so that it can represent more answers from Coway International Indonesia employees. Coway International Indonesia throughout Indonesia. Apart from that, you can also add other supporting variables, such as Work Motivation, Job Satisfaction, Reward and Punishment and other variables that are relevant to the novelty of the research.
Women’s Dilemma and Social Reflection in Film Narrative: A Case Study of Kim Ji-young, Born 1982
Authors: Wang Yunning
Published: November 2024

Kim Ji-young, Born 1982 portrays the life experiences of an ordinary woman navigating family, work, and society, exposing the patriarchal structures, female discipline, and reproductive oppression in South Korean society. Adapted from Cho Nam-joo’s novel, the film recounts Ji-young’s struggles in childhood and marriage, along with the mental distress caused by the pressures of balancing career and family. It powerfully illustrates how societal expectations lead women to lose their sense of self, highlighting the exploitation of emotional labor and unpaid housework. Ji-young’s story transcends individual experience, reflecting the broader structural gender inequality embedded in society. Upon release, the film sparked intense social debate, particularly from South Korean men, some of whom petitioned the Blue House to block the screening, accusing it of fueling gender conflict. This opposition reveals the patriarchal structure’s defensive response to challenges and men’s anxiety over losing status and privilege. This paper explores how government pro-natalist policies, under the guise of preserving family structures, further entrench the oppression of women’s reproductive and labor value.
Peningkatan Kesadaran dan Keterampilan Masyarakat dalam Pengelolaan Sampah Organik Melalui Pelatihan Pembuatan Pupuk Kompos di Desa Sindanglaya
Authors: Darmaraja Aji Putih , Casini Casini , Jalilah Dini Nurul , Aropah Siti Syadiyatul
Published: November 2024

Latar Belakang: Pengelolaan sampah rumah tangga menjadi isu yang krusial, terutama di daerah pedesaan seperti Desa Sindanglaya yang tidak memiliki fasilitas  pembuangan sampah yang disediakan oleh pemerintah setempat. Tujuan: Program kuliah kerja NYATA (KKN) di Dusun Nanggela mengajarkan warga setempat cara mengubah sampah organik menjadi kompos. Metode: Metode yang diambil dalam penelitian ini menggunakan Partisipatory Action Reasearch di mana, penulis melibatkan masyarakat secara langsung dalam proses penelitian dan pemecahan masalah. Terlepas dari tantangan termasuk kesadaran masyarakat yang rendah,  Hasil: Hasil kegiatan ini menunjukkan bahwa dengan pengelolaan sampah yang baik, masyarakat dapat memanfaatkan sampah rumah tangga secara lebih efektif, sehingga tidak hanya menjaga kebersihan lingkungan, tetapi juga memperbaiki kualitas hidup mereka. Kesimpulan: Tujuan dari program ini menunjukkan bahwa pelatihan secara efektif meningkatkan pengetahuan dan kemampuan masyarakat dalam pengelolaan sampah organik.
Pelatihan Pembuatan Batik Berbasis Ecoprint di Desa Blimbing, Kecamatan Gatak, Kabupaten Sukoharjo
Authors: Sukatiman Sukatiman , Krisna Listi Murnita , Faturrohman Muhammad Aldy , Pramudita Aisyah , Handoko Yohanes Tri , Lestari Putri , Rossa Annisa Al Sakinah , Sadewi Zakia Inti , Rahmadhani Madhu Bates , Pratama Febryan Krishna , Pratama Pandu Satria
Published: November 2024

Latar Belakang: Desa Blimbing di Kecamatan Gatak, Kabupaten Sukoharjo, memiliki potensi besar untuk mengembangkan batik ecoprint, yaitu teknik pewarnaan kain yang ramah lingkungan dengan menggunakan bahan alami. Namun, masyarakat menghadapi beberapa masalah, seperti kurangnya pengetahuan dan keterampilan tentang teknik ini. Tujuan: Untuk mengatasi masalah ini, diadakan pelatihan pembuatan batik berbasis ecoprint dengan tujuan meningkatkan keterampilan dan pengetahuan warga setempat, sekaligus mengukur tingkat kepuasan peserta terhadap pelatihan tersebut. Metode: Pendekatan yang digunakan dalam pelatihan ini adalah Participatory Action Research (PAR), yang memberdayakan masyarakat dengan melibatkan mereka secara aktif dalam setiap tahap pelatihan. Hasil: Hasil evaluasi menunjukkan bahwa tingkat kepuasan peserta berada pada angka 63%, yang menunjukkan bahwa mayoritas peserta merasa puas dan berhasil memahami teknik ecoprint. Kesimpulan: Pelatihan ini terbukti efektif dalam meningkatkan keterampilan dan pengetahuan masyarakat Desa Blimbing, serta memberikan dampak positif terhadap pemahaman mereka terkait ecoprint.