bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Creativity on Emotional Intelligence, Self-Esteem and Resilience in Visual Arts and Engineering Students
Authors: - Isha Bhardwaj
Published: October 2024

This research looks into the complex interactions between creativity, emotional intelligence, resilience, and self-esteem, focusing on two distinct student groups: arts and engineering. Understanding the impact of creativity on these vital attributes becomes increasingly important as social needs grow, embracing both technological knowledge and emotional intelligence, resilience, and self-esteem. The study investigates the link between creativity and emotional intelligence, resilience, and self-esteem, offering light on how academic fields influence these vital characteristics. Purposive sampling was used in the research to sample 106 people from different colleges in North India. Self-report questionnaires such as the Emotional Quotient Test, Rosenberg Self-Esteem Scale, Nicholson McBride Resilience Questionnaire, and KDOCS 20 for creativity were used in the data collection process. With Jamovi, statistical studies such as regression, correlation, and t-tests were carried out. According to the findings, self-esteem, emotional intelligence, and resilience significantly correlate with creativity. Notably, students studying engineering and the arts showed different approaches to the scientific aspect of creativity. The scientific dimension was a significant predictor by regression analysis, indicating that it had a distinct impact on both student groups. Prioritizing ethical issues included obtaining participants' informed consent, managing data securely, and respecting participant autonomy.
AI in Neuromarketing: Understanding Consumer Emotions and Behavior through Machine Learning
Authors: - Tavishi Yadav
Published: October 2024

This paper explores the integration of artificial intelligence (AI) and machine learning in the emerging field of neuromarketing, which combines neuroscience with marketing strategies to decode consumer emotions and behaviors. By employing advanced techniques such as EEG, fMRI, and facial recognition, the research highlights how these technologies can analyze subconscious responses to marketing stimuli, providing deeper insights than traditional methods. The study emphasizes the transformative role of AI in enhancing predictive analytics, real-time personalization, and customer segmentation. Furthermore, it discusses the potential benefits of AI-driven insights for crafting effective marketing campaigns that resonate with consumers and improve engagement. The paper also addresses the challenges faced in this field and proposes future research directions to explore the intersection of AI and consumer behavior analysis.
Cultivation and Marketing Challenges in Growth of Herbal Plants in Garhwal Region, Uttarakhand
Authors: - Dr. Tulsi Bisht , - Dr. Poonam Rishishwar , - Dr. Sanjay Rishishwar , - Dr. Rakesh Dani
Published: October 2024

Evidence based on observation and conversation with the farmers played a major role in findings of this study. The study's main goal is to assess the current state of the market for medicinal plants in hilly region of Uttarakhand with a focus on easily accessible transportation, as well as storage facilities, threats and tactics associated with marketing these products in the region under proper supervision.
An Extension of the Theory of Planned Behavior to Predict the Purchase Intention of Millet
Authors: - G Jaison Sagayannathan , - Dr.D.P.Sudhagar
Published: October 2024

The demand and consumption of Millets are increasing across the globe, in particular during the International Year of Millets 2023. Unlike any other food product, Millet is considered unique in terms of nutrition, health benefits and taste. There is a growing need among the producers and marketers of Millets to understand how customers purchase millets. In this context, the purpose of the present study was to develop a comprehensive model to understand Millet's purchase intention using focus group discussion and literature review. Based on the proposed methodology, a model integrating critical variables influencing the purchase intention of millets was developed. The study used the theory of planned behaviour as the base model. The nine variables, such as environmentally friendly, information on millets, trust in millets, millet quality, millet safety, health consciousness, Knowledge of millets, health benefits of millets and environmental concerns, were identified as new variables influencing the attitude towards purchasing millets. The study contributes to developing a theory that predicts the purchase intention of millets. The model can be used in any geographical context to predict the purchase intention of millets and develop marketing strategies that will enhance the purchase and consumption of millets.
Prevalence Of Anemia, Its Diagnose, Causes and Treatment: - A Case Study of Faridabad District In Haryana
Authors: - Sweta Dash
Published: October 2024

Epidemiological information and disease prevalence studies have always been vital for planning control strategies and monitoring the impact of interventions to control such diseases. The present study is an outcome of a medical camp done under the aegis of PMGY an NGO model worldwide. Being assisted by hospitals and clinics run by the state and philanthropists, the NGO provides charitable medical services, free treatment, free medicines, and even free food and clothes to underprivileged sections of society. Keeping in view the mission of the NGO, and the poor mass of underprivileged people, this study has been devised to assess the prevalence, symptoms, causes and treatment of anemia in Faridabad mostly for two reasons. Firstly, because the locality is the operating field of the NGO and secondly, because anemia is at the highest prevalence, as found in our first observation of patients coming to the slum outreach camps and clinics under study. This will help make effective strategies of intervention, control and dissemination of health-related awareness & better preventative care and treatment to the target group i.e. the poor and underprivileged sections of the society. This cross-sectional study focuses on residents of the Faridabad district who were clinically assessed and treated for free. Seven rural and 19 urban clusters where nearly 750 people with underprivileged backgrounds came forward for the study. People with ongoing ailments were assessed alongside healthy individuals who required regular health checkups with utmost precaution to prevent community transmission. The treatment protocol revolved around palliative and curative treatment for symptomatic cases and preventative care only, when necessary, for asymptomatic cases.
A Study on Historical Context and Significance of Journalism in India
Authors: - Dr. Saibanna Eranna
Published: October 2024

As mentioned earlier, the first newspaper in India, the Bengal Gazette, was launched in 1780 by James Augustus Hickey. The paper was published in English and had a circulation of only 400 copies. Despite its small readership, the Bengal Gazette paved the way for the growth of the Indian press. In the early years of Indian journalism, most newspapers were owned and operated by British colonizers. These newspapers mainly focused on the interests of the British ruling class and catered to their needs. However, as Indian nationalism grew, Indian journalists began to challenge British dominance in the media and started publishing newspapers that reflected the views and aspirations of the Indian people.
Impact of Mgnrega on Employment Generation in Karnataka
Authors: - Mareppa T , - Aleema
Published: October 2024

This study examines the impact of the Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) on employment generation in Karnataka. Using secondary data from official websites, the research highlights MGNREGA's significant role in providing wage employment and enhancing livelihood security for rural households. As of September 2024, over 80 lakh job cards have been issued, with a high employment fulfillment rate exceeding 98%. The program actively supports marginalized communities, with 18.15% of workers from Scheduled Castes and 10.71% from Scheduled Tribes. Overall, MGNREGA is a crucial mechanism for economic stability and poverty alleviation in rural Karnataka.
Revolutionizing Knowledge Synthesis: Introducing AI-Enhanced Collaborative Theory (AIECT)
Authors: - Rachid Ejjami
Published: October 2024

In an era of unprecedented data development, standard literature review approaches can result in information overload and missed chances for theoretical innovation. This paper introduces AI-Enhanced Collaborative Theory (AIECT), a paradigm for dynamic collaboration between artificial intelligence (AI) systems and human researchers to improve knowledge synthesis and theoretical progress. AIECT focuses on the intersection of human intuition and AI capabilities, including essential components like dynamic co-creation, iterative feedback loops, contextual intelligence, and ethical frameworks. Empirical experiments show that AIECT can significantly increase the efficiency and depth of literature reviews and theory creation, showing its potential to revolutionize research processes and address information overload concerns. While limitations such as sample size and the need for additional validation are acknowledged, the findings indicate that AIECT represents a transformative approach to academic inquiry, encouraging innovative, ethical, and nuanced research techniques. By safely integrating AI, AIECT sets the way for advances in knowledge synthesis and provides a systematic foundation for future scholarly endeavors in various domains.
Challenges Encountered by Police Officers During Crime Investigations
Authors: - Md. Imran Wahab, IPS
Published: October 2024

This study highlights the vital function of police officers involved in criminal investigations in maintaining the integrity of Indian society through effective law enforcement and fair justice. However, it identifies several obstacles that impede their efficiency, including heavy workloads, lack of adequate resources, shortage of officers, external pressures, and technological limitations, particularly when addressing serious crimes, cybercrimes, and offences involving cryptocurrency. These issues contribute to decreased morale among officers who investigate crimes and increase public distrust, especially amidst growing media scrutiny. Furthermore, the psychological strain of handling complex cases worsens these challenges. The study calls for comprehensive reforms to alleviate workloads, enhance the number of investigative officers, increase the sanctioned strength of police officers, improve resource allocation, integrate technology into investigations, and create a more efficient and culturally sensitive police system. Implementing these reforms is essential for strengthening investigative capabilities, adapting to the changing criminal landscape of the 21st century, and ensuring law enforcement's dedication to safeguarding the integrity of Indian society.
Balancing Progress and Protection: The Precautionary Principle in Global Environmental Governance
Authors: - Karan Raj Sachdeva
Published: October 2024

The precautionary principle is based on the premise that the lack of scientific proof does not justify ignoring potential environmental harm. It advocates for taking precautions to avoid damage rather than dealing with the consequences. Therefore, the precautionary principle is a useful guide when governments need to create policy and regulations in the face of scientific uncertainty. This is especially important with regards to sustainable development as it provides legislators with a framework to enact environmental protections even in the absence of scientific certainty regarding the harm caused by specific industrial activities.
Regulators across the world need to strike a balance between the economic benefits of some industrial activity and its social and environmental costs. Imprecise knowledge of health risks, inadequate data, lack of definitive proof, unclear priorities, and public debate all complicate the assessment and regulation of these costs.
This article draws attention to the ongoing discussion around particulate matter, specifically around the nature of the exposure-response relationship for different health endpoints, the underlying causal mechanisms of the health impacts caused by different types of particles, and the effects of these impacts on diverse populations. It could lead to different reactions from the judiciary. Due to this uncertainty, those in charge of making decisions about regulations and adjudications about health, well-being, and the environment face governance issues.
Ethical Artificial Intelligence Framework Theory (EAIFT): A New Paradigm for Embedding Ethical Reasoning in AI Systems
Authors: - Rachid Ejjami
Published: October 2024

The rapid development of artificial intelligence (AI) has created several ethical issues, including bias, a lack of transparency, and privacy concerns, demanding the incorporation of ethical governance directly into AI systems. This study introduces the Ethical Artificial Intelligence Framework Theory (EAIFT), a novel approach to incorporating ethical reasoning into AI. It emphasizes real-time oversight, open decision-making, bias detection, and the ability to change ethical and legal norms. EAIFT advocates for establishing "ethical AI watchdogs" that automatically monitor and ensure the ethical operation of AI systems, together with dynamic compliance algorithms that can adapt to regulatory changes. The paradigm also encourages transparency and explainability to build user trust and detect and correct biases to ensure fairness. This paper employs a qualitative methodology that combines stakeholder interviews, content analysis, and expert commentary to evaluate EAIFT's potential to increase ethical accountability in various areas, including healthcare, banking, and criminal justice. The findings suggest that EAIFT outperforms existing ethical frameworks by proactively reducing biases, increasing transparency, and ensuring adherence to ethical standards. While presenting a comprehensive and adaptable technique, the study also acknowledges limitations in empirical testing and the need for additional research to widen EAIFT's applicability to future ethical challenges in artificial intelligence. The paper suggests future research subjects, such as empirical testing in different scenarios, a more in-depth examination of ethical risks, and the inclusion of the framework into new AI technologies to promote responsible AI governance by societal norms and values.
The Effect of Circuit Training and Plyometric Exercise on Agility and Core Strength in Karate Players
Authors: - Aditi Patil , - Vrushali Bhore
Published: October 2024

Since karate is one of the most well-known martial arts and the word "karate" means "empty hand" (kara = empty, te = hand), it refers to the practice of punches, kicks, and blocking moves without the use of weapons.
So the purpose of the study to find dose agility and core strength can can change by after undergoing the certain exercise which are plyometric exercise and circuit training in the male and female plyers
Dharma and Modern diplomacy: Lessons on peace-building from Buddhist philosophy
Authors: - Prashant Singh
Published: October 2024

Peace is the most sought after asset in today’s world. Everyone wants to be in a Harmonious relationship and environment But we are losing it to treachery, power conflicts and ego issues. In Today‘s age international conflicts and geopolitical tensions are very prevalent in the world, Buddha’s teachings can offer a profound and timeless wisdom for modern diplomacy and peace-building efforts that can provide sustainable insights and solutions to the problems. His Teachings primarily focused on individual peace and enlightenment that has now been interpreted and adapted to address the broader context of peace-building among nations and to seek valuable insights for modern diplomacy and peace-building efforts.He stated that Hatred does not cease by hatred, but only by love; this is the eternal rule . This research paper will explores the convergence of ancient wisdom of Buddha and present day cutting-edge international relations. This paper explores the principles of Dharma, particularly from Buddhist teachings, and their applicability to modern diplomatic practices. It will analyse how compassion, non-violence, and interconnectedness present in Buddhist philosophy can provide valuable insights for developing peace and resolving conflicts in today’s complex scenarios.In the linked world of today, these harmonious ties will be beneficial. It lowers the probability of war by facilitating amicable dispute settlement through discussion and negotiation. Additionally, it facilitates the formation and upkeep of multinational alliances, which promotes collaboration on world problems including trade, security, and climate change. Furthermore, modern diplomacy is more inclusive and efficient in tackling both established and new global concerns because of its flexibility in utilizing new platforms and technology to improve communication.. By analyzing the core principles of Dharma and applying as approaches by countries or organizations to manage international relations and achieve foreign policy goals. The purpose of this study is to offer a novel viewpoint on fostering peace and understanding in international relations.
Media Trial: Balancing Press Freedom and the Right to a Fair Trial
Authors: - Md. Imran Wahab, IPS
Published: October 2024

This article, titled "Media Trial: Balancing Press Freedom and the Right to a Fair Trial," explores the complications arising from media trials, where intense and often exaggerated media coverage can influence public opinion and alter legal results. While the media plays a crucial role as the "fourth estate" in fostering transparency and accountability, its involvement in judicial matters risks compromising the fairness of trials. The article explores how media trials can violate or uphold the right to a fair trial by referring to significant cases such as the O.J. Simpson trial and the Jessica Lal case respectively. It delves into the legal and moral dilemmas, the influence of social media, and the necessity of finding a balance between press freedoms and the integrity of the judicial process. The discussion underscores the significance of ethical journalism and legal protections to safeguard both public interest and the integrity of the justice system. Ultimately, the article recommends a cautious approach to reconcile these conflicting rights in today's media environment.
Real-time Flood Prediction using a Big Data Approach
Authors: - Kishor Yadav Kommanaboina
Published: October 2024

Floods have historically presented serious threats, putting infrastructure and lives in jeopardy throughout the world. There has never been a greater need for accurate and fast flood forecasts as climate change exacerbates existing situations. By using state-of-the-art algorithms and real-time integration to create a groundbreaking flood prediction platform, this research seeks to close important gaps. A comprehensive resource is created by combining a variety of datasets, including Internet of Things sensor streams, hydrological readings, and meteorological observations. For extremely accurate short-term flooding forecasts, advanced machine learning techniques—like deep neural networks and hybrid statistical methods—are trained on the live dataset. Pre-warnings from the suggested adaptive system are expected to become more and more dependable, enhancing readiness and reaction operations. Going forward, continually refining models with growing data repositories, exploring novel inputs, and extending the framework to other natural hazards will further strengthen resilience against these escalating threats.
The Role of Community Participation in the Tourism Development in Coastal Regions of Karnataka: an Analysis of Beach Households
Authors: - Nagaraja , - Abbokar Siddiq
Published: October 2024

The research explores the role of community participation in the tourism development of coastal regions in Karnataka, India, focusing on beach households as key stakeholders. Using a sample of 410 respondents, the study examines the influence of community involvement and participation on tourism development outcomes. The hypothesis was tested using One-way ANOVA and Regression in SPSS. The research investigates the extent to which local communities engage in tourism activities, their perceptions of the impacts of tourism, and the potential benefits and challenges associated with community participation. Results indicate a significant positive influence of community involvement on tourism development in coastal Karnataka. The findings shed light on fostering community participation in tourism planning and management to achieve sustainable development goals in coastal regions.
Legal Reforms Addressing Sexual Harassment in India: Examining the Role of Women’s Dress as a Contributing Factor
Authors: - Sinduja S
Published: October 2024

Women's clothing choice is mainly used as a reason for violence against them. The socially constructed aggression toward women is made to fit into the role the woman might be perceived to have in an attack. This shifts part of the responsibility for this violation onto the victim and the perpetrator. This paper discusses how the concept of "choice of dress" has emerged as one of the factors contributing to sexual violence against women. This paper discusses public opinion on this issue and attempts to enter into the perception that women's attire is being used as a justification for violating their rights. This paper has proceeded to analyze the role of law in preventing sexual harassment and considers public opinions on the possible introduction of legal regulations concerning women's dress codes, together with the probable impact such regulations may have on women's self-esteem. This research is based on both primary (convenient sampling and analysis through SPSS software) and secondary sources (books, articles, reports, legal commentaries, and case laws) dealing with sexual harassment laws. It attempts to provide reform proposals that shift attention away from women's clothing and instead focus on accountability on the part of the perpetrators in legal frameworks.
India's 1991 Liberalization Reforms, With Emphasis on Rising Out of Pocket Expenditure (OOPE)
Authors: - Bhumija Rishi
Published: October 2024

This research paper highlights why India was forced to liberalize its economy in 1991 and what sort of consequences it had for out-of-pocket medical expenditure.
The AI and Big Data Equitable Transformation Theory (ABETT): A Pathway to Inclusive Development and Technological Empowerment
Authors: - Rachid Ejjami
Published: October 2024

The rapid advancement of artificial intelligence (AI) and big data technology has created new potential for economic growth, social development, and creativity. However, their incorporation into local economies presents issues regarding ethical governance, skill development, access to infrastructure, and equitable benefit sharing. This paper presents the AI and Big Data Equitable Transformation Theory (ABETT), a comprehensive framework for guiding the responsible and inclusive use of AI and big data in various scenarios. The ABETT model has six basic constructs: policy and ethical governance, skills development and education, scalable and equitable infrastructure access, collaborative innovation and knowledge exchange, sustainable AI and data for development, and economic growth and competitiveness. The ABETT framework was created, validated, and enhanced using a qualitative research design that included a systematic literature assessment, expert interviews, and case study analysis. The results support the model's relevance and applicability, illustrating how its elements work together to generate ethical and sustainable technological innovation. Comparisons with previous theories show that ABETT adds value by proposing a comprehensive and customizable pathway for AI and big data adoption that emphasizes collaboration, equity, and sustainability. The paper discusses the model's policy and practical implications, limitations, and future research recommendations. ABETT provides a practical roadmap for stakeholders who want to use AI and big data to promote inclusive growth, sustainable development, and equitable technical advancement.
Unveiling the Dark Side: The Misuse of the Dowry Prohibition Act 2018 in Bangladesh
Authors: - Ruksana Akter , - Md. Khairul Anwar Robin , - Arshi Salehjee
Published: October 2024

This study had tried to investigate the misuse of the Dowry Prohibition Act 2018 in Bangladesh, a legislation designed to combat dowry-related abuses and promote gender equality. Through a thorough analysis of legal cases and socio-cultural data, it reveals the alarming trend of individuals exploiting the Act for personal gain. The law that was created to protect women from the oppression of the dowry system is now being used by some women to rule over males. This research, based on the misuse of dowry legislation in Bangladesh in 2018, will shed light on the causes of the rise in fake dowry cases in the Bangladesh. Second, a thorough comprehension of how to handle all bogus dowry case concerns gained through fieldwork Third, a thorough examination of the issue of defending and shedding light on the challenges faced by both victims and the accused.
Performance of Machine Learning Models to Predict Customer Satisfaction Scores for Lao National Convention Center
Authors: - Mr.Chansamone Senesouphab , - Phouthone Vongpasith , - Bouasoth Xayachak , - Chitnavanh Phonekhamma , - Bounmy Phanthavong
Published: October 2024

This research paper investigates the effectiveness of various machine learning (ML) models in predicting customer satisfaction scores for the Lao National Convention Center (LNCC). By utilizing a dataset containing customer feedback, demographic data, facilities, and service-related information, the study aims to identify the best performing model for predicting customer satisfaction. In this paper, the performance of ML to predict customer satisfaction scores from the questionnaire survey dataset is evaluated. The customer satisfaction score is categorized into five classes: strongly agree, agree, neutral, disagree and strongly disagree. The analysis will compare the performance of different models, including linear regression (LR), k-nearest neighbor (KNN), support vector machines (SVM), decision trees (DT) and random forest (RF). The results show that SVM model achieved the highest accuracy rate of 95.91%, followed by KNN and LR with an accuracy rate of 95.55% and 95.49%, respectively. The findings of this study have important implications for the use of ML in improving the service-related information for LNCC and providing valuable insights for decision-makers and developers.
Prevalence of Anemia among Adolescent School Girls of Bardoli Taluka, Surat, Gujarat
Authors: - Ms. Rinal Barad , - Dr. Rani Shetty
Published: October 2024

Introduction: Anemia is a serious public health challenge in India. It affects women, adolescents and children throughout the lifecycle. In boys and girls it limits their development, learning ability, reduce concentration in daily task, increases risk of infections, increases school dropout rates and reduces their physical activity. Anemia in girls can increase risk of pregnancy associated complications like premature births, low birth weight of baby and perinatal and maternal mortality.
Aims of the study: The aim of the present study was to identify the prevalence of anemia and its associated factors among adolescent school girls of Bardoli, Surat.
Material and methods: A cross sectional survey was carried out to identify the prevalence of anemia among 815 adolescent school girls from both Government and Private schools by using non probability purposive sampling technique and who fulfilled the inclusion criteria Digital hemoglobinometer was used to collect capillary blood for estimation of hemoglobin level.
Result: Study results showed that, 694 (85 %) girls were having anemia and 15% of them had normal hemoglobin level. 48% had mild anemia and 37% had moderate level of anemia. 2 (0.24%) girls had severe anemia. It was highly prevalent among 417 (60.15 %) girls of government schools than the private school. Majority 551 of them were under weight (BMI < 18.5). Level of anemia was significant with age, residence, dietary pattern, education and occupation of parents, family income. Menstruation related factors like regularity, amount of blood loss was significant.
Conclusion: Anemia is still a major health problem in our country. Anaemia among adolescent girls still continues to be a significant public health problem.
Factors Influencing the Location of Hotel Businesses Catering to International Travelers in Bangkok
Authors: - APHISAVADH SRILNG
Published: October 2024

Abstract:
This study investigates what makes international travelers pick hotel locations in Bangkok Thailand. The research tries to answer questions about location factors for international hotels and how these factors shape their decisions when choosing spots to serve international guests. The survey targeted select three to five-star hotels in Thailand's capital gathering just over 250 valid responses for analysis. Seven key factors came to light for international guests staying in Bangkok hotels: nearness to shopping centers, eateries, and tourist spots; ease of access; area wealth and appeal; rival hotels; hotel room size; and market focus. This study's results give us a deeper grasp of hotel placement in Bangkok. Looking at where top-tier hotels are, this paper points out some services that hotels in city centers should offer.
Treatment Strategies for Sigmoid Volvulus : A case series of 15 patients
Authors: - MANOJ KUMAR J , - SANTHI B
Published: October 2024

Sigmoid volvulus, a condition characterized by the twisting of the sigmoid colon, is a frequent cause of large bowel obstruction. This study aims to review and evaluate the treatment strategies applied to 15 patients diagnosed with sigmoid volvulus at our institution. The outcomes, complications, and long-term results were analyzed to identify the most effective management approaches. The treatment modalities ranged from conservative management to surgical interventions. Our findings indicate that a multidisciplinary approach, timely intervention, and appropriate patient selection are key determinants of successful outcomes.
Improvement of Properties Jet Mechanics in A3S High Strength Steel
Authors: - Ramazani Mulenda Lens , - Mulimbi Mutoke Aguethan
Published: October 2024

The objective continued in this work is to improve the characteristics mechanical properties of high- strength A3S steel produced at the Panda Central Workshops of Gecamines. The steel grade studied contains quantities​ important manganese​ in proportions ranging from 2 to 4.6%. Various treatments thermal has summer realized in view to improve machinability while​ designing properties​ mechanics that meet the requirements of their use.Samples in the raw casting state have presented a hardness of 407.8 HB and a resilience of 4.3 J/cm 2. Annealing at 773°C followed by holding for 4 hours and slow cooling in the furnace to a speed of 20°C per hour helps to reduce hardness​ up to 200HB with increased resilience up to 28.3 J/cm 2. A quench was then carried out and made it possible to retain a heating temperature of 900°C and water as a cooling medium; which allowed to increase hardness and resilience until values respective of 343 HB and 19.7 J/cm 2. The final result obtained after tempering leads to a hardness of 217 HB and a resilience of 19.7 J/ cm2.It emerges from the tests realized that it is possible to modify and improve the hardness and resilience of the studied grade using thermal cycles appropriate.
Exploring the Properties, Synthesis, and Applications of Magnesium Aluminate Nanoparticles
Authors: - Deepa Rani
Published: October 2024

Magnesium aluminate (MgAl2O4) is a synthetic ceramic compound, characterized by a spinel structure and comprised of magnesium oxide (MgO) and aluminum oxide (Al2O3). Magnesium aluminate is esteemed for its distinctive combination of thermal, mechanical, and optical characteristics, making its role remarkable for various applications. Hence this review, focuses mainly on magnesium aluminate nanoparticles, a subject that is gaining prominent attention in the current research scenario. There are several methods available for the synthesis of MgAl2O4 nanoparticles (MANPs), including sol-gel and co-precipitation techniques, along with those that incorporate green methodologies. The high melting point, substantial hardness, and excellent thermal shock resistance of the host material suggest that MANPs could hold a significant place in the field of nanotechnology. Numerous studies have demonstrated that the introduction of different ions into MANPs through doping effectively altered their characteristics, thereby improving their functional capabilities. Thus, this review gives a comprehensive examination of the properties of magnesium aluminate, the synthesis methods utilized, impacts of doping, and various applications of magnesium aluminate nanoparticles.
Effect of Motivation on Employee Performance: A Case of Tanzania Fire and Rescue Force, Kigoma Region
Authors: - Jacob Simon Chacha , - Nasra Kara , - France A. Shayo
Published: October 2024

This study sought to determine the effect of motivation on employee performance at the Tanzania Fire Rescue Force. The study was specifically designed to identify the effects of salary, fringe benefits, recognition, training & development on the employees' performance using a case of the Tanzania fire rescue force in Kigoma Region. The study employed a quantitative approach and cross-sectional research design. 50 structured questionnaires were distributed to 50 employees and the collected data were analyzed using descriptive statistics, principal component factors, correlation and simple linear regression analysis. The findings indicated the moderate effect of salary, Recognition & Appreciation on employee performance. The findings also revealed that personal commitments and job satisfaction are two fringe benefit factors influencing employee performance. Moreover, it was reported that Training & Development have contributed to 63% of the variation in employees' performance among workers. Additionally, the overall finding indicated that salary, fringe benefits, training, development, Recognition & Appreciation are seen as job-motivating factors that significantly impact employee performance. The study recommended that by nurturing a motivational work environment and supporting skill development and feedback mechanisms, the organization can further enhance employee performance and contribute to its overall success.
Patient Satisfaction in In-Patient Department in Tertiary care Hospital in Odisha
Authors: - Durgadatta Das
Published: October 2024

Patient satisfaction is a crucial factor in determining the overall Quality of services proved in the Hospital setting. It includes a collaborative and scientific inspection of the various departments associated with the patient that are being admitted to the Hospital.
It gives an insight to the areas that need to be improved and increase the overall patient experience.
Regeneration of Moses' Leadership Based on the Book of Numbers 27:15-23 for GKJW Ministers in the Three Sub-districts of Pacet, Gondang and Dlanggu Mojokerto East Java
Authors: - Vinus Zai , - Sri Wahyuni , - Hana Suparti , - Srini M. Iskandar
Published: October 2024

The existence of a leader is important in an organization because a leader is a person who can show the way to step, guide, direct the way of members both before and after the business is completed. Numbers 27: 15-23 is a process that should be used as a reference in preparing, selecting, assigning and submitting leaders in the service of God. Numbers 27: 15-17 clearly describes the preparation, selection, appointment and submission of leaders who could head the Israelites to go out and enter the Promised Land. In this case Moses asked God to appoint a leader over God's people, the Israelites, saying: “Let the Lord, The God of the spirit of all creation, appoint over this people a person (verse 16). Regeneration in the leadership of Moses is something very important. Before this regeneration process was carried out, God had first prepared the prospective leader of the Israelites, Joshua.
Relation in preparing the servant of God GKJW in three districts Pacet, Gondang and Dlanggu Mojokerto which are considered less important and only focus on Bible study but now there has begun a process of regeneration through the direction of catechization candidates involved in the ministry and further church responsibilities in terms of the election of leaders or ministers of God because in the established procedures that the election is the right and duty of every perform service duties. Another problem faced in the determination of GKJW leaders in the three districts of Pacet, Gondang and Dlanggu Mojokerto is that at the time of the selection of candidates to be appointed as God's servants, more people withdrew than were willing, on the grounds of 1) work that could not be left, 2) Did not have the ability to serve 3). No knowledge of Theology 4. No sense of belonging to the church, so in the process of handing over the leadership is faced with a serious problem, namely the refusal to be a servant of God on the grounds of feeling unable to carry out the task entrusted. Rejection is done by sending a letter to the committee that has been assigned by the church on the grounds of inability or lack of confidence in leading the church. Research Methodology hhis study uses a quantitative approach (positivist) on qualifications in data collection and analysis to test the hypothesis applied. So, in this study found that the dominant background category that determines the confirmation of regeneration in the leadership of Moses based on the book of Numbers 27:15-23 for GKJW servants of God in the three sub-districts of Pacet, Gondang and Dlanggu Mojokerto East Java is the type of service, not education, thus providing uniqueness and novelty in the research process conducted on the research locus.
Flood Risks Analysis in Upton Upon Severn: Assessing the Baseline Conditions and Future Scenarios for 100 and 1000-year Flood Events with a 2050 Climate Change Perspective.
Authors: - Tasneem Haider Khan
Published: October 2024

This paper investigates the flood risks in Upton upon Severn, a town in Worcestershire, England, which is prone to fluvial flooding from the River Severn. Historical events, such as the significant floods of 1947 and 2007, highlight the town’s vulnerability and underscore the importance of analysing current and future flood risks. This research uses a one-dimensional hydraulic model, using Flood Modeller and QGIS software, to assess baseline flood conditions and predict the potential impacts of severe and extreme flood events, including 1 in 100-year and 1 in 1000-year flood scenarios. Additionally, it examines the projected effects of climate change by incorporating a 20% increase in flood risk estimates for the year 2050. The model results reveal that the baseline scenario poses limited flood risks, with only 17 properties affected, and key infrastructure like the A4104 road remains passable. However, under the 1 in 100-year event, approximately 336 properties are at risk, with significant road blockages and a flooded area of 5.09 Km2. The 1 in 1000-year flood scenario predicts a peak flow of 1807 m3/s, threatening more properties and covering a larger area of land. When climate change is factored into the 1 in 100-year scenario, the risks become similar to those of the 1 in 1000-year event, with 500 properties and key infrastructure, including the fire station and primary school, at risk and the A4104 road becoming impassable. These findings provide vital insights for flood risk management, especially given the possible effects of climate change, and stress the need for long-term solutions to flooding.
Site Suitability Analysis for Urban Development: A Case of Ranikhet, Uttrakhand
Authors: - Shyam Gunjal , - Dr. Mohd. Khalid Hassan , - Er Mohsin Anees
Published: October 2024

Identifying potential sites for urban development in hilly regions is a crucial aspect of planning. Conducting site suitability analysis is essential for determining appropriate locations for various developmental projects, particularly in the challenging terrain of hills. Unregulated and disorganized urban expansion, driven by population pressure, is a widespread issue in many cities within developing countries, leading to urban sprawl that encroaches on natural environments. As a result, selecting suitable areas for urban development while maintaining ecological balance has become a critical component of effective urban planning. This work demonstrates the application of Geographic Information System (GIS) and the Multi-Criteria Analysis (MCA) technique for identifying appropriate sites for urban development in Ranikhet, Uttarakhand. The aim is to identify optimal locations for future urban growth that minimize impacts on natural features. The work also calculates the potential transfer of land suitability from various land use and land cover categories, a unique aspect of this research. Eight criteria distance from roads, land use/cover, distance from water bodies, slope, elevation, soil, geological formation, and population density were used for land evaluation. The thematic maps generated for these criteria were standardized using the Analytical Hierarchy Process (AHP), which involved creating a pairwise comparison matrix. Each criterion was assigned a weight based on its relative importance, leading to the creation of a final site suitability map with five categories: very high suitable, high suitable, moderately suitable, less suitable, and restricted or not suitable. The study highlights the potential zones within the study area and offers valuable insights for sustainable urban development planning. The results are expected to assist planners, stakeholders, and policymakers in identifying the most suitable locations for future intensive development projects.
AI-driven Predictive Analytics for Enhancing Cybersecurity in a Post-pandemic World: a Business Strategy Approach
Authors: - S A Mohaiminul Islam , - Ankur Sarkar , - A J M Obaidur Rahman Khan , - Tariqul Islam , - Rakesh Paul , - Md Shadikul Bari
Published: October 2024

Due to heightened technological advancement that has been ignited by the COVID-19 pandemic, the use of technology in running businesses has surged and therefore making businesses prone to cybersecurity threats. The present paper explores the potential of AI as a tool for advancing cybersecurity in the world after a pandemic, and how business organizations can organize its application for protection against new emerging forms of threats. The research draws on secondary industry data and primary case studies of the businesses with AI-based cybersecurity in place. The outcome demonstrates that emerging AI technologies, including machine learning and neural networks, have cut threat detection time by 40% and enhanced the precision of recognizing potential security threats by 30%, beyond conventional cybersecurity solutions. The new and distinct feature of this paper is to elucidate that new threats can be predicted with the help of AI, while there is a continuous need for new training for AI in relation to cyber threats. Drawing from the literature, this paper, therefore, posits that incorporation of AI-based predictive analytics into business cybersecurity models and systems is not only vital for the defense of data and infrastructure against hackers but equally important for the achievement of sustainable, long-term business continuity during the current day, age of technology and globalization.
Artificial Intelligence in Fraud Detection and Financial Risk Mitigation: Future Directions and Business Applications
Authors: - Tariqul Islam , - S A Mohaiminul Islam , - Ankur Sarkar , - A J M Obaidur Rahman Khan , - Rakesh Paul , - Md Shadikul Bari
Published: October 2024

AI in fraud detection and financial risk management has taken this role of prevention and combating fraud closely related to organizations and the losses they incur a next level. This paper aims to discuss the use of artificial intelligence models in the process of detecting frauds and preventing and reducing financial risks in such markets as banking, insurance, and fintech. Today, through machine learning algorithms, deep learning techniques, and data analysis, the AI improves the speed, accuracy and effectiveness of fraud detection. This paper discusses the current AI models and business use incorporating the success story and the business outcomes which has encountered sometime to have the best result. Furthermore, the paper examines other important issues of AI application management such as data security and liberation, and complete fairness control. Using examples as well as statistical data in this AI for business article, we show how corporations have managed to minimize their risks while lowering their expenses with the use of artificial intelligence technology. This research outlines ideas on how organizations can implement AI into fraud detection systems and what can be done in future to enhance the solutions. This paper adds to the emerging body of knowledge on AI’s impact on finance and security, and demonstrates AI’s ability to influence the future of the industry.
Real-time Predictive Health Monitoring using Ai-driven Wearable Sensors: Enhancing Early Detection and Personalized Interventions in Chronic Disease Management
Authors: - A J M Obaidur Rahman Khan , - S A Mohaiminul Islam , - Ankur Sarkar , - Tariqul Islam , - Rakesh Paul , - Md Shadikul Bari
Published: October 2024

The use of artificial Intelligence in wearable health sensor has brought a great change in the way chronic diseases are being managed since it monitors the health and gives prompt prediction of diseases coupled with recommendations. This paper seeks to investigate the part played by AI wearables in augmenting early detection & proactive plans relating to chronic illnesses, including diabetics, cardiovascular diseases, and hypertension. Implicitly, the purpose of this study is to update the current understanding of the subject by examining the effect that predictive analytics has on patient outcomes and cost. Technologically, the concepts of the research rely on the data collected from different kinds of wearable devices and analyze by machine learning and real time analytic to examine the abnormal of vital signs before symptoms occur. Analysis is carried out on the outcomes which reveals a 25 percent decrease in hospitalization incidences per early diagnosis of chronic diseases and a 30 percent enhancement in the adherence to treatment provided formed by precautions embraced from various sensors data. This research also increases the stock of knowledge on the role of artificial intelligence in healthcare by presenting empirical evidence regarding the use of wearable devices in chronic diseases. The uniqueness of this concept is in the synchrony of monitoring processes with the application of the predictive model in providing proactive health care solutions. Some potential future research and development considerations in AI-assisted technologies in healthcare are also described.