Research Paper Research Articles

Predicting power and solar energy using neural networks and PCA with meteorological parameters from Diass and Taïba Ndiaye

The excessive reliance on conventional fossil fuel-based resources poses a significant threat to our environment. To mitigate this impact, it has become increasingly crucial to increase the integration of intermittent and non-polluting energy sources into our electrical grids. However, while this higher penetration rate brings benefits such as improved producer satisfaction and reduced fossil fuel consumption, it also presents challenges for traditional non-smart electrical networks. To promote intermittent energy sources effectively and maintain a balance between consumption and production, accurate forecasting of these energy outputs plays a vital role. This research paper focuses on studying the application of artificial neural networks for predicting the power and energy output of the Diass solar power plant in the short and medium term. The proposed approach utilizes not only the meteorological data from the city where the power plant is located but also data from a nearby city with a data acquisition station. Principal component analysis (PCA) is employed to select the relevant variables for the prediction model. Furthermore, the results obtained from our approach are compared to existing literature that solely uses meteorological data from the power plant's location. The comparison shows that our method achieves more satisfactory results, with mean absolute errors and root mean square errors of 0.0223 KWh and 0.003 KWh, respectively, and a prediction accuracy of 94.57% in terms of energy and power. It is worth noting that the computational resource requirements for our approach are higher, with simulation times ranging between 1788 seconds and 2201 seconds. By utilizing a broader range of data sources and employing advanced techniques like artificial neural networks, this research contributes to improving the accuracy of solar power generation forecasts. The findings highlight the potential of incorporating additional data inputs and advanced modeling techniques to enhance the performance of renewable energy systems, paving the way for a more sustainable and efficient energy future.

The effect of blooket game towards students’ vocabulary mastery at the seventh-grade students of SMP-IT Mathla’ul Anwar Malingping in Academic Year 2023/2024

The research aims to know whether the use of Blooket Game significant effect towards students’ vocabulary mastery at the seventh-grade of SMP-IT Mathla’ul Anwar Malingping or not. The research paper used the quantitative research design with the characteristics of experimental method that is design into two classes. They are experimental and control class. The population of this research is class VII of SMP-IT Mathla’ul Anwar Malingping, they consist of 84 students. The sample of this research is VII-A as a control class consists of 28 students and VII-B as an experimental class consists of 28 students. The total of sample is 56 students. The instrument is a test and data of this research are collected by giving pre-test and post-test. The data is analysed using statistical SPSS 22 program including mean, standard deviation, and t-test. It could be seen from the result of the post-test of experimental and control class. Based on the result of data analysis and interpretation of the research, it is clear there is a significant effect of Blooket Game towards students’ vocabulary mastery at the seventh-grade students of SMP-IT Mathla’ul Anwar Malingping. It can be seen, the minimum score of pre-tests is 32, maximum is 72, mean 53.86, and standard deviation 11.339. while the minimum score of post-tests of experimental class is 68, maximum 96, mean 81.71 and standard deviation 8.105. furthermore, the minimum score of pre-tests of control class is 32, maximum 72, mean 52.71 and standard deviation 11.317. while the minimum score of post-tests of control class is 60, maximum 88, mean 72.57 and standard deviation 6.974. the result of t-test obtained sig.value 0.000 < 0.05. Ha is accepted and Ho is rejected. It can be concluded that there is a significant effect of Blooket Game towards students’ vocabulary mastery.

Quantitative analysis of the relationship between expressing gratitude and forgiveness and user sentiment on social media

Purpose The purpose of this study is to investigate how expressing gratitude and forgiveness on social media platforms relates to the overall sentiment of users, aiming to understand the impact of these expressions on social media interactions and individual well-being. Design/methodology/approach The hypothesis posits that users who frequently express gratitude or forgiveness will exhibit more positive sentiment in all posts during the observed period, compared to those who express these emotions less often. To test the hypothesis, sentiment analysis and statistical inference will be used. Additionally, topic modelling algorithms will be used to identify and assess the correlation between expressing gratitude and forgiveness and various topics. Findings This research paper explores the relationship between expressing gratitude and forgiveness in X (formerly known as Twitter) posts and the overall sentiment of user posts. The findings suggest correlations between expressing these emotions and the overall tone of social media content. The findings of this study can inform future research on how expressing gratitude and forgiveness can affect online sentiment and communication. Originality/value The authors have demonstrated that social media users who frequently express gratitude or forgiveness over an extended period of time exhibit a more positive sentiment compared to those who express these emotions less. Additionally, the authors observed that BERTopic modelling analysis performs better than latent dirichlet allocation and Top2Vec modelling analyses when analysing short messages from social media. This research, through the application of innovative techniques and the confirmation of previous theoretical findings, paves the way for further studies in the fields of positive psychology and machine learning.

A Hybrid Deep Ranking Weighted Multi-Hashing Recommender System

In countries where there is a low availability of resources for language, businesses face the challenge of overcoming language barriers to reach their customers. One possible solution is to use collaborative filtering-based recommendation systems in their native languages. These systems employ algorithms that understand the customers’ preferences and suggest products or services in their native language. Collaborative filtering (CF) is a popular recommendation technique that simulates word-of-mouth phenomena. However, the accuracy of a CF recommendation can be affected by sparse data. In this research article, we present a novel hybrid weighted multi-deep ranking supervised hashing (HWMDRH) approach. Our method leverages both user-based and item-based CF by merging the item-based deep ranking weighted multi-hash recommender system prediction with the user-based deep ranking weighted multi-hash recommender system prediction to generate Top-N prediction. We conducted extensive experiments on the MovieLens 1M dataset, and our results show that the proposed HWMDRH model outperforms existing models and achieves state-of-the-art performance across recall, precision, RMSE, and F1-score metrics.

Modelling on COVID-19 control with double and booster-dose vaccination

COVID-19 vaccines have been illustrated to lessen the growth of sickness caused by the virus effectively. In any case, inoculation has consistently been controversial, with differing opinions and viewpoints. This has compelled some individuals to decide against receiving the vaccine. These divergent viewpoints have had a trivial impact on the epidemic’s dynamics and the disease’s development. In response to vaccinated individuals still falling ill, many countries have implemented booster vaccines to protect further.In this specific investigation, a mathematical model composed of seven compartments is employed to examine the effectiveness of a booster dose in preventing and treating the transmission of COVID-19. The principles of mathematics are employed to analyse and investigate the dynamics of the disease. Using a qualitative prototype analysis, we acquired valuable insights into its effectiveness. One essential aspect is the basic reproduction number, a critical determinant of the disease’s spread. This calculation is determined by studying the system’s equilibrium and evaluating its stability.Furthermore, we examined the balance from a local and global viewpoint, considering the possibility of bifurcation and the model’s reproductive number sensitivity index. Through numerical simulations, we have visually illustrated the analytical findings outlined in this research paper and presented a thorough examination of the efficacy of booster shots as a preventive and therapeutic measure in the spread dynamics of COVID-19.

Sufferings, Resilience, and Triumph over Despair in Linda Sue Park’s A Long Walk to Water

This research paper explores the plights of the refugees and their experiences in the place of origin, during the journey and in the host country, which are similar and caused by the same entity of state sovereignty and the use of state of exception in the text A Long Walk to Water. The civil war in Sudan compels Salva and many Sudanese people to leave their home country and live the very painful lives. Their plight is generally universal plight of every asylum seeker. In A Long Walk to Water, Salva starts facing a new set of obstacles after leaving his home country, Sudan and continues even in the host country. Despite the daunting obstacles, Salva's extraordinary resilience, determination, and willingness to adapt enables him to overcome his sufferings. This research paper finally argues that the problems of the right less/stateless people will have to be addressed by creating an unshakable framework by combining ideas of universal right to the political space with ethics of unconditional hospitality. Towards a creating an equal space for every individual, Hannah Ardent’s rights to have right, Kant’s universal hospitality and Derrida’s unconditional hospitality can be instrumental to minimize the sufferings of the refugees in this world. To improve and alleviate the sufferings of refugees, their rights will have to come from their equal access to the political space and legalization of their rights will have to be guided by humanitarian perspectives.

Understanding Farmers’ Intentions to Adopt Organic Farming in India

This research paper explores the dynamics of organic farming adoption among farmers in the Konkan region of India, focusing on the districts of Ratnagiri and Raigad. Against the backdrop of the pivotal role the agricultural sector plays in India's economy, the study employs an ex-post-facto research design to investigate the intentions, attitudes, and perceived capabilities of 150 organic farmers across diverse cropping systems. The findings reveal a nuanced landscape of motivations, ranging from a desire for toxin-free food to cultural preservation. Farmers' attitudes towards organic agriculture, influenced by health considerations and social networks, underscore the complex interplay between traditional practices and modern influences. Moreover, the study delves into the perceived marketability of organic products, highlighting factors such as consumer willingness to pay premiums and the competitive advantage of organic over conventional produce. As India grapples with the need for sustainable agricultural practices, the study sheds light on the multifaceted factors influencing the adoption of organic farming and provides insights essential for policy formulation and sustainable agricultural development.

Comparative Analysis of Nature-Inspired Metaheuristic Techniques for Optimizing Phishing Website Detection

The increasing number, frequency, and sophistication of phishing website-based attacks necessitate the development of robust solutions for detecting phishing websites to enhance the overall security of cyberspace. Drawing inspiration from natural processes, nature-inspired metaheuristic techniques have been proven to be efficient in solving complex optimization problems in diverse domains. Following these successes, this research paper aims to investigate the effectiveness of metaheuristic techniques, particularly Genetic Algorithms (GAs), Differential Evolution (DE), and Particle Swarm Optimization (PSO), in optimizing the hyperparameters of machine learning (ML) algorithms for detecting phishing websites. Using multiple datasets, six ensemble classifiers were trained on each dataset and their hyperparameters were optimized using each metaheuristic technique. As a baseline for assessing performance improvement, the classifiers were also trained with the default hyperparameters. To validate the genuine impact of the techniques over the use of default hyperparameters, we conducted statistical tests on the accuracy scores of all the optimized classifiers. The results show that the GA is the most effective technique, by improving the accuracy scores of all the classifiers, followed by DE, which improved four of the six classifiers. PSO was the least effective, improving only one classifier. It was also found that GA-optimized Gradient Boosting, LGBM and XGBoost were the best classifiers across all the metrics in predicting phishing websites, achieving peak accuracy scores of 98.98%, 99.24%, and 99.47%, respectively.

Factors influencing the research impact in cancer research: a collaboration and knowledge network analysis

BackgroundCancer is a major public health challenge globally. However, little is known about the evolution patterns of cancer research communities and the influencing factors of their research capacity and impact, which is affected not only by the social networks established through research collaboration but also by the knowledge networks in which the research projects are embedded.MethodsThe focus of this study was narrowed to a specific topic – 'synthetic lethality’ – in cancer research. This field has seen vibrant growth and multidisciplinary collaboration in the past decade. Multi-level collaboration and knowledge networks were established and analysed on the basis of bibliometric data from ‘synthetic lethality’-related cancer research papers. Negative binomial regression analysis was further applied to explore how node attributes within these networks, along with other potential factors, affected paper citations, which are widely accepted as proxies for assessing research capacity and impact.ResultsOur study revealed that the synthetic lethality-based cancer research field is characterized by a knowledge network with high integration, alongside a collaboration network exhibiting some clustering. We found significant correlations between certain factors and citation counts. Specifically, a leading status within the nation-level international collaboration network and industry involvement were both found to be significantly related to higher citations. In the individual-level collaboration networks, lead authors’ degree centrality has an inverted U-shaped relationship with citations, while their structural holes exhibit a positive and significant effect. Within the knowledge network, however, only measures of structural holes have a positive and significant effect on the number of citations.ConclusionsTo enhance cancer research capacity and impact, non-leading countries should take measures to enhance their international collaboration status. For early career researchers, increasing the number of collaborators seems to be more effective. University–industry cooperation should also be encouraged, enhancing the integration of human resources, technology, funding, research platforms and medical resources. Insights gained through this study also provide recommendations to researchers or administrators in designing future research directions from a knowledge network perspective. Focusing on unique issues especially interdisciplinary fields will improve output and influence their research work.

What brings you to our humble abode? Tourist motivation for visiting rural destinations: The case of Nqileni village, South Africa

Rural areas, especially in developing countries, have considered using rural tourism to advance economic and social development. Many authors have conducted academic research focusing on tourism to develop rural areas. However, more clarity is needed on what constitutes rural tourism. While several studies have investigated the reasons for rural tourism development, more is needed to understand what attracts visitors to rural areas. This research paper aims to enhance understanding of rural tourism by examining rural tourists' motivations for places such as Nqileni village, Eastern Cape Province, South Africa. The authors identified the motivational factors that push tourists to rural areas and the activities that tourists prefer at the destination. Finally, the research determined the tourists' overall satisfaction during their stay at the destination. Numerous research studies have been conducted to investigate the factors influencing the growth of rural tourism, but more is needed to determine what attracts tourists to rural destinations. The study adopted a quantitative research approach, using questionnaires to collect data. The results conclusively show that tourists were motivated to visit the area for relaxation, visit family and relatives, and enjoy a feeling of freedom in the countryside.

From blocks to bridges: navigating the globalization-blockchain nexus through bibliometrics analysis

Purpose This study aims to comprehensively inspect the impact of blockchain technology in the context of globalization, focusing on the most influential research works, scientific production by countries, commonly used keywords, trending topics and the conceptual and intellectual structure of this field. Design/methodology/approach A bibliometric analysis was conducted in R Studio, involving the review and scrutiny of 194 research papers indexed in the Scopus database. This analytical approach allowed for a systematic examination of the literature and the identification of key patterns and trends in blockchain and globalization research. Findings The analysis revealed the most influential research contributions, highlighted countries with significant scientific production, identified frequently used keywords and unveiled emerging trends and areas of focus in the field of blockchain and digitization. Additionally, the study explores prospective research directions. Research limitations/implications This research provides insights into the current state of blockchain and globalization research, offering valuable information for scholars, policymakers and industry professionals. The recognized themes provide a systematic structure for upcoming inquiries, directing studies toward vital domains like supply chain management and sustainable development. Moreover, the analysis emphasizes the significance of interdisciplinary collaboration and provides practical insights, enabling businesses and policymakers to enhance transparency, counteract fraud and adjust to the digital era for societal and economic advancement. Originality/value The study contributes to the prevailing literature by steering a comprehensive analysis of the interplay between blockchain technology and globalization, shedding light on influential works and emerging trends. It adds value by providing a structured overview of the field's intellectual landscape.

A high-efficiency poly-input boost DC–DC converter for energy storage and electric vehicle applications

This research paper introduces an avant-garde poly-input DC–DC converter (PIDC) meticulously engineered for cutting-edge energy storage and electric vehicle (EV) applications. The pioneering converter synergizes two primary power sources—solar energy and fuel cells—with an auxiliary backup source, an energy storage device battery (ESDB). The PIDC showcases a remarkable enhancement in conversion efficiency, achieving up to 96% compared to the conventional 85–90% efficiency of traditional converters. This substantial improvement is attained through an advanced control strategy, rigorously validated via MATLAB/Simulink simulations and real-time experimentation on a 100 W test bench model. Simulation results reveal that the PIDC sustains stable operation and superior efficiency across diverse load conditions, with a peak efficiency of 96% when the ESDB is disengaged and an efficiency spectrum of 91–95% during battery charging and discharging phases. Additionally, the integration of solar power curtails dependence on fuel cells by up to 40%, thereby augmenting overall system efficiency and sustainability. The PIDC’s adaptability and enhanced performance render it highly suitable for a wide array of applications, including poly-input DC–DC conversion, energy storage management, and EV power systems. This innovative paradigm in power conversion and management is poised to significantly elevate the efficiency and reliability of energy storage and utilization in contemporary electric vehicles and renewable energy infrastructures.

Nature-Young Adult Relationship in Anderson’s Speak: An Ecofeminist Reading

This paper explores ecofeminism through a connection to the nature and a sexually assaulted young adult girl in Laurie Halse Anderson’s novel Speak. This study argues that adolescents suffer from the effects of rape. It also contends that aside from abusing teenagers, sexual assaulters also damage the victim’s ability to interact with the outside world. The rapists prevent the female protagonist from having healthy relationship with the nature. Therefore, it is crucial to re-establish connections with oneself, other people, and the natural environment in order to escape the horrible act of physical violation. For that purpose, this research paper employs the perspectives of Roberta S. Trites about young adults; and opinions of Carlos J. Adams and Greta Gaard about ecofeminism. In conclusion, this study hopes to pave the path for future research into the comprehensive interaction between a young adult’s (female) body and nature.

Modeling the ecological footprint and assessing its influential factors: A systematic review.

Various factors have been found responsible for the increment in ecological footprint resulting difficulties in maintaining environmental sustainability. This has been noticed through a modeling perspective. Identifying the factors affecting Ecological Footprint helps policymakers to formulate policies regarding sustainability. However, studies conducted based upon systematic reviews on Ecological Footprint through modeling are still limited. This study intends to identify influential factors associated with ecological footprint through a systematic review. ProQuest, Science Direct, Scopus, and Web of Science databases were used to search literature systematically. Particular keywords and Boolean operators were applied to dig out relevant studies for the review. Peer-reviewed research articles published in the English language till September 13, 2023, were incorporated for the analysis. Following the guidelines of Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA), 1011 articles were identified from four different databases and only 37 research papers were eligible for this study. These articles were assessed and relevant information was extracted and then amalgamated into the systematic review. Gross domestic product, urbanization, energy consumption, renewable energy, non-renewable energy, natural resources, bio-capacity, human capital, foreign direct investment, trade openness, and financial development were observed as key factors of the ecological footprint. Factors known to influence ecological footprint need to be addressed properly for environmental sustainability including widespread use of renewable energy.

SOCIAL STOCK EXCHANGE: A WAY FORWARD TO MAKE INDIA A VIKSIT BHARAT (DEVELOPED NATION) @ 2047

This research paper delves deep into the mechanisms of the Social Stock Exchange, unravelling its potential to shape a sustainable future, where economic growth seamlessly integrates with social well-being, guiding India towards its visionary goal to become developed nation by 2047. This qualitative research study attempts to give comprehensive view on Social Stock Exchange (SSE) proposed in India by providing information on Framework, Global outlook, Significance, Challenges & Limitations of SSE. The study also shows that how this revolutionary concept will significantly contribute to attain United Nations Sustainable Development Goals (SDGs) by 2030 and in the development of India to become Viksit Bharat by 2047.

EVALUATING THE PSYCHOLOGICAL EFFECTS OF VEHICULAR HONKING ON INDIVIDUALS

This research paper rigorously examines the psychological effects of vehicular honking on individuals within urban environments. By employing a comprehensive mixed-methods approach, encompassing both surveys and interviews, the study uncovers a compelling connection between honking exposure and adverse mental effects such as stress, annoyance, and emotional disturbances. This impact on psychological well-being subsequently influences overall life satisfaction. The findings underscore the pressing need for tailored interventions, including public awareness campaigns to promote responsible honking behaviour and the enforcement of stricter regulations during peak hours. Technological innovations, such as noise reduction systems, are proposed as potential solutions to mitigate the psychological toll of honking noise. Ultimately, the research highlights the urgency of addressing the psychological fallout of vehicular honking and offers a path toward creating more harmonious and mentally supportive urban environments.

A Study on the Socio-Economic Status and Income Levels in Rural Regions

This research paper explores the socio- economic status of the rural population with a primary focus on income level analysis. By examining various factors influencing income levels in rural areas, this study aims to provide a comprehensive understanding of the economic challenges and opportunities faced by rural communities. The paper includes a review of existing literature, analysis of income distribution, identification of key determinants of income levels, and policy recommendations to enhance the socio-economic status of rural populations.

Influence of Heat Treatment on Fretting Wear Behavior of Laser Powder Bed Fusion Inconel 718 Alloy

Abstract This research paper focuses on the fretting wear characteristics of self-mated laser powder bed fusion (L-PBF)-produced Inconel 718 alloy, with the primary aim of characterizing its distinct wear rate in relation to fretting cycles. This study investigates both the as-built and heat-treated Inconel 718 Superalloy. Experiments were conducted under aggressive contact conditions, involving a flat-on-flat contact pressure of 100 MPa (1645 N) and a temperature of 650 °C sustained over a million cycles. From the preliminary observation, the microstructure reveals that the heat-treated L-PBF alloy has denser and harder precipitates than its as-built counterpart. This indicates that heat-treated alloy is much harder (470 HV0.3) than the as-built Inconel 718 (275 HV0.3). The heat treatment process resulted in the precipitation of beneficial strengthening phases like γ′ and γ″, along with maintaining stable carbides (NbC). Notably, the heat-treated material displays an approximately two-fold lower wear rate (0.103 μm/cycle at the end of 1000k cycles) compared to the as-built material (0.238 μm/cycle), attributed primarily to its high strength characteristics. Additionally, the heat-treated material demonstrates a reduced steady-state friction coefficient (0.34) in contrast to the as-built material (0.37), owing to its inherent capability to form a uniform lubricious glaze layer. Both as-built and heat-treated systems show dominant adhesive wear mechanisms along with localized abrasion resulting from the combination of oxidation and cyclic wear processes.

Standard Classroom Capacity: Effective of Learning Activities in Malaysian Primary School Buildings

The teaching and learning process needs to be carried out formally in the classroom, which is the main learning space in the school system. This should be implemented effectively to achieve a level of comfort for students. The capacity of a classroom can affect the way the teacher teaches and the level of student understanding. Classroom capacity needs to be emphasized to encourage and maintain student motivation for continuous learning, especially at the primary school level. This study aims to analyse classroom capacity in order to improve student comfort in the primary school building and thus enhance the effectiveness of learning. The qualitative method used for conducting the study is the method used in this research to measure the predicted findings. The present area of 15 randomly chosen classrooms was measured (Width X Length) using a qualitative method that also included semi-structured interviews. The findings of the study show that 50 percent of classroom capacity in primary school buildings comply with existing guidelines, established design rules and classroom area requirements. The current classroom size is 2.25 m2 per student with a significant increase in student satisfaction during the teaching and learning process. However, the findings from the semi-structured interviews highlight interesting points in relation to the appropriateness of classroom capacity. Teachers think that classroom capacity affects students' level of comfort. Respondents agreed that the capacity of a classroom is effective with a maximum of 26 students. This research paper emphasizes the importance of compliance with classroom physical performance standards in primary school buildings to increase the comfort level of students in the classroom. The research presented here provides current information, knowledge, and findings regarding actual classroom capacity in primary school buildings data that could have an impact on students' comfort. During the formative learning phase, very little meaningful attention is paid to the areas where students spend the majority of their weekdays. As a result, this can support experts in the fields of school building management, building facilities, and other related fields in determining and implementing the right classroom capacity in schools generally.

A Study of Citations: Bibliometric Analysis of the 100 Top-cited Publications on Panic Disorder

Background: The number of times a publication is cited in scientific research papers is often considered to estimate its contribution to biomedical literature. Although extensive research has been conducted on panic disorder over time, attempts at a citation analysis have yet to be made to the best of our knowledge. Aim: The aim of this study was to understand the trends of research on panic disorder from the top 100 most-cited publications worldwide. Materials and Methods: A citation analysis of the top 100 panic disorder publications was conducted, using Harzing’s Publish or Perish to identify articles from Google Scholar. The study analyzed citation patterns, authorship, publication types, and themes. Exclusions comprised non-scientific materials. No ethics approval was needed as it involved published data, not human subjects. Results: Publications with more than 500 citations were 11, and those with more than 400 citations, known as citation classics, were 27. Fifty-nine publications were funded, of which 14 (23.8%) were clinical trials and 24 (40.7%) were observational studies. The maximum number of articles was published between 1990 and 1999 ( n = 45), followed by 2000 and 2009 ( n = 26). The h-index of the first author showed a significant positive correlation with the number of citations of the paper (Spearman’s ρ = 0.480, P = 0.02). Among research papers, the maximum were observational studies ( n = 44), followed by 19 randomized controlled trials (RCTs) and eight non-randomized clinical trials. Additionally, among RCTs ( n = 19), 17 were focused on the management theme. Conclusion: This bibliometric analysis is an invaluable resource for scholars and students who might be interested in learning about the developments and patterns in the field of panic disorder research.