bluuebunny/crossref_metadata_2025 huggingface dataset:
A Comparative Analysis of Gaussian Process Regression and Support Vector Machines in Predicting Carbon Emissions from Building Construction Activities
Authors: Che Mamat Rufaizal , Ramli Azuin , Bawamohiddin Aminah Bibi
Published: January 2025

The increasing effects of climate change require the accurate measurement and prediction of carbon emissions from building construction operations. This study aims to assess the performance of Gaussian Process Regression (GPR) and Support Vector Machine (SVM) in predicting emissions and determine which model is best suited for improving sustainable construction practices. The GPR and SVM models were trained and tested using empirical datasets with varying parameter values. Model performance is evaluated using correlation coefficient (R), root mean square error (RMSE), and mean absolute error (MAE). The analysis reveals that GPR consistently performs better than SVM across diverse datasets, especially in intricate and varied data situations. The superior performance of GPR highlights its robustness and versatility in handling the complexities of construction-related emissions data. The results indicate that GPR has the potential to assist significantly many stakeholders in the construction sector, including planners and environmental managers, in making better-informed decisions that are in line with carbon reduction objectives. Further studies could examine the incorporation of further predictive variables into the GPR model, such as economic indicators and the effects of material innovation.
Research of Digital Generative Islamic Tessellation Patterning Structure System
Authors: Wong Leong Yee , Chen Chen-Cheng
Published: January 2025

According to Gottfried Semper, who coined the term ‘Architextile’ to describe the use of textiles and other malleable materials in architectural design, textiles were the first materials used to construct human dwellings. In Islamic architecture and building design, tessellation patterning is thought to represent the early days of textile and lightweight structures, reflecting the nomadic lifestyle of early Islamic society. Bedouins made portable structures covered with woven textiles for temporary dwellings, showcasing the early use of architextile. Tessellation patterning and Islamic architecture have a significant relationship in terms of identity representation. Establishing the decorative shell (tessellation) creates a virtual atmosphere that transcends 'Physical Reality,' where structural elements like columns and beams lie beneath decorative facades. Over time, Islamic architecture's decorative shell has often remained purely ornamental, lacking structural significance. This study explores human settlement and building design by examining the tectonic characteristics of Islamic patterns. The research aims to bridge the gap between the decorative and practical aspects of Islamic architecture by studying geometric tessellation grid systems and their parametric alterations. The goal is to transform two-dimensional tessellation patterns into three-dimensional articulated structures. By manipulating pattern lines, the subdivided surface can be articulated into a structural system, forming a lattice structure. Additionally, human settlement and cultural heritage are preserved through the study of these architectural patterns. This showcases how historical building designs reflect and maintain cultural identity. Understanding the interplay between tessellation patterns and Islamic architecture enhances our appreciation of the cultural heritage embedded within human settlements.
Characterization of Residual Soil Properties on Slope in Dusun UTM, Johor
Authors: Mohamed Norhidayah , Zolkepli Muhammad Farhan , A. Rashid Ahmad Safuan , Imran Muhammad Syamsul , Ishak Mohd Fakhrurrazi
Published: January 2025

The actual characterization of residual soil differs across different countries. Any soil that has remained at the original site without having moved is often referred to as residual soil. In order to design geotechnical structures that are simultaneously safe and cost-effective, including slope stability, it is essential to have a solid understanding of the characteristics of the residual soil. This understanding provides valuable insights regarding the behaviours and strength of the soil. One of the most common catastrophes that can take place in any part of the world, including Malaysia, is caused by a slope failure. Due to the high occurrence of accidents resulting from slope failure, it is necessary to conduct extensive scientific research aimed at identifying the precise characteristics of the soil at Dusun UTM, Johor. Numerous laboratory works have been carried out relating to the soil's index of physical properties and engineering properties. In terms of the properties of the residual soil, the area can be characterized as sandy silt with a significant level of plasticity. Result for consolidated isotropic undrained (CIU) test indicates that the stress-strain curve demonstrates a hardening behaviour, which no peak stress observed during shearing process. Moreover, increasing confining pressures applied to the soil sample led to enhancement in the soil’s strength properties. These findings provide valuable insights into the soil’s behavior, which can inform strategies for improving slope stability and mitigating risks associated with slope failure.
Enhancing Compressive Strength of Laterite Soil through the Agricultural Waste Material Bamboo Ash Stabilization
Authors: Md Yusof Zeety , Mustapa Siti Aishah , Chua Yi Zhe , Lee Jin Chai
Published: January 2025

All types of soil are used as the ground foundation to support the construction of any structures including roads and buildings. Laterite soil has the properties of cohesive and cohesionless soil. This is because its properties are mostly well-graded including silt, clay, sand, and gravel. However, laterite soil's physical and mechanical properties require improvement. Potential laterite soil used for the construction of roads and development activity is necessary for geotechnical application. Therefore, this research aims to study the performance stability in compressive strength of native laterite soil with bamboo ash (BA). The testing experiments have shown that the behavior of bamboo ash is used to strengthen the laterite soil resulting in the bamboo ash enhancing the performance of laterite formation in ground improvement. In this study, 0%, 5%, 10%, 15%, and 20% bamboo ash content were used to study the effect of BA on native lateritic soils at 0, 3, and 7 days of curing. It is indicated that the strength for 3 curing days increases strength to 8.4% after adding 5% BA. It increases the strength after adding 10%, 15%, and 20% with the percentage of the increments 7.2%, 1.7%, and 0.7%, respectively. In the physical properties results, the specific gravity of soil shows an average of 1.66. As a result, LL and PL have been identified as 29% and 14.1% respectively. Lateritic soil water content measured in this study was 10.84%. Compaction tests identify MDD as 1.807 g/cm3, while OMC content is 13.3%. Lateritic soils are classified as sedimentary sandy soils according to the results of particle distribution soil tests. In the end, the results identified for enhancement of the addition of bamboo ash show a strong increment for lateritic materials. Bamboo ash (BA) appears secondary in large-scale studies. BA reacts as an economical and sustainable treatment material in geotechnical applications.
Effectiveness and Stability of Recoil System between Blowback System and Gas-Operated System on Weapon
Authors: Salsabila Nida , Lubis Ahmad Husin , Astharini Dwi , Samijayani Octarina Nur , Pramana Ivan Adhi , Rohman Iksan Khosiya
Published: January 2025

In weapons there is the name recoil system, recoil system is a recoil force that occurs when a bullet is fired from a weapon there is an action-reaction law, the action-reaction law states that any force exerted by an object on another object will produce an equal and opposite force from the object. In the weapon recoil system related to the Mass-Spring-Damper system because the recoil system requires a spring and also a damper so that when the bullet is fired, the force released is effective and also stable, in this paper describes 2 systems in recoil, namely, the blowback system and also the Gas-Operated system on the 9mm Automatic pistol and also on the AK47 Riffle weapon.
Parametric Structural System Modelling for Flood Resilience Architecture in South Kalimantan
Authors: Indrawan Stephanus Evert , Purwanto LMF , Hermawan Hermawan
Published: January 2025

Indonesia is highly susceptible to natural disasters, particularly floods. This research focuses on South Kalimantan, a region unexpectedly affected by severe flooding, which endangered vital peatland. The study aims to develop a flood-resilient construction system tailored to local conditions. A rapid assembly construction system for peatland environments was proposed, leveraging modern technologies for sustainable post-flood housing solutions. The research was conducted using a quasi-experimental method, where the intervention group utilized a parametric structural system and the control group employed a traditional structural system. The methodology involved blending conventional sub-structures, such as the Kacapuri foundation, with advanced lightweight technologies for the upper structure. Soil tests were performed to assess the bearing capacity and characteristics of the peatland, which informed the design of both the sub-lower and upper structure simulations. The study also tested three different upper structure profiles—conventional curves, polygonal profiles, and isocurve profiles—to optimize the structural design. Furthermore, an adaptive and responsive rapid assembly method was implemented and customized to on-site requirements, with a focus on parametric design and digital fabrication. Tools such as Rhinoceros 3D, Grasshopper, and Karamba facilitated the simulation and fabrication of the structures. A prototype was subsequently developed and evaluated, demonstrating significant reductions in dead loads and enhanced cost efficiency compared to conventional methods. The prototype also indicated improved land support capacity, signifying a step forward in sustainable post-disaster housing. This research underscores the importance of integrating modern construction technologies to address the post-flood housing crisis in South Kalimantan’s peatlands. The results demonstrated that adopting innovative construction methodologies can provide efficient, effective, and sustainable solutions to mitigate flood-induced displacement, thus contributing to the resilience and sustainability of disaster-prone regions. The role of advanced structural modeling in enhancing flood resilience was affirmed, offering insights into addressing similar challenges in vulnerable ecosystems globally.
Heat Transfer Optimization using RSM for Hybrid Nanofluid Flow Impinging Obliquely on a Permeable Shrinking Sheet
Authors: Yahaya Rusya Iryanti , Mustafa Mohd Shafie , Md Arifin Norihan , Pop Ioan , Md Ali Fadzilah , Mohamed Isa Siti Suzilliana Putri
Published: January 2025

Fluid flow may strike a surface at an angle due to the physical limitations of the nozzle or contouring of the surface. The heat transfer optimization for the Al2O3-Cu/water hybrid nanofluid flow impinging obliquely on a permeable shrinking sheet is analyzed in this study. Flow over a shrinking sheet may occur during polymer and metal sheet extraction, wire drawing, and glass-fiber production. The first step in this study involves reducing the governing partial differential equations and boundary conditions into non-linear ordinary differential equations via similarity transformation. Subsequently, these equations are solved using built-in finite difference code in MATLAB bvp4c solver. It is found that the increment of the suction parameter enhances the heat transfer rate represented by the physical quantity of interest called the local Nusselt number. However, the opposite occurs when the nanoparticle volume fraction of Cu and the magnitude of the shrinking parameter increase. Meanwhile, the normal and shear components of skin friction are augmented by the rise in the suction parameter and nanoparticle volume fraction of Cu. Then, the statistical analysis and optimization done using the response surface methodology (RSM) revealed that the local Nusselt number is highly impacted by the suction parameter, followed by the shrinking parameter and nanoparticle volume fraction of Cu. The maximum value of local Nusselt number is approximated to be 13.30539 when the magnitude of suction is at the highest, while shrinking parameter and nanoparticle volume fraction of Cu are at the lowest.
A Numerical Simulation for Heat Conduction in Anisotropic FGMs of Space-time Dependent Conductivities with Arbitrary Initial Conditions and Source Terms
Authors: Azis Mohammad Ivan , Firman Firman , Nur Muh. , Aris Naimah , M. Yusup Eliza
Published: January 2025

Numerical solutions of unsteady heat conduction problems with arbitrary initial conditions and source terms for anisotropic functionally graded materials (FGMs) of spatio-temporally dependent conductivity are sought. A combination of the variable reduction transformation and Laplace transform was utilized to derive a domain-boundary integral equation. Numerical solutions were obtained by using a standard domain-boundary element method and the Stehfest formula. The accuracy of the numerical method is also evaluated.
Simulation Study on Ice Accretion over NACA0012 airfoil Under Varying Airflow Conditions
Authors: Al Tahhan Aghyad B. , Ramahi Ahmad , Dol Sharul Sham , Ahmad Kamarul Arifin
Published: January 2025

Ice accretion on aircraft wings poses a critical safety challenge during operational flights as it alters the aerodynamic performance the wing profile and increases structural loads acting on it. Therefore, it has become crucial to understand the thermodynamic and fluid dynamic behavior of ice formation over the airfoil surface to address this issue. This study investigates the heat and mass transfer characteristics of a two-dimensional NACA0012 airfoil during in-flight icing under various flow conditions. The research aims to model the ice accretion process, analyze its impact on aerodynamic performance, and assess the heating requirements for ice mitigation. Throughout the study, a numerical approach was employed using the FENSAP-ICE simulation suite in ANSYS Fluent, which integrates the Reynold’s-Averaged Navier-Stokes equations with the K-ω SST turbulence model to model airflow and ice formation. Additionally, the study investigated icing at airflow velocities of 80, 102, 150, and 200 m/s, analyzing the resulting ice formation as a result of varying flow speeds, its influence on lift and drag coefficients across different angles of attack, and the heating loads necessary for ice removal using thermal balance calculations. The results of the study showed strong consistency between the simulated ice accretion patterns and droplet collection efficiency and the experimental findings reported in literature. Therefore, validating the use if FENSAP-ICE for such analyses. Furthermore, it was also found that the ice build-up over the airfoil significantly degrades its aerodynamic performance with reductions in lift and increases in drag coefficients. The obtained findings provide valuable insights for expanding the numerical analysis performed in this study to design effective ice protection systems for aircrafts under diverse operational conditions.
The Importance of Cybersecurity in Digital Government Implementations
Authors: Schneider Guilherme Barcha Cardoso
Published: January 2025

Introduction: The increasing reliance on digital platforms in governmental operations has significantly enhanced public service delivery but has simultaneously introduced critical cybersecurity challenges. Cyber threats targeting government systems pose risks to sensitive citizen data, operational continuity, and public trust. This paper examines the intersection of cybersecurity and digital government initiatives, emphasizing their importance in safeguarding public interests. Objective: The objective of the study is to highlight the necessity of integrating robust cybersecurity measures into digital government frameworks to address emerging threats, maintain service reliability, and foster public confidence. Method: The research employs a qualitative analysis of case studies from European nations, such as Estonia, Finland, and the Netherlands, renowned for their advanced cybersecurity and e-governance strategies. The methodology involves examining governance policies, public-private partnerships, and technological innovations. Results: The findings reveal that successful digital governments integrate adaptive cybersecurity strategies, collaborative governance frameworks, and advanced technologies like artificial intelligence and blockchain. These approaches mitigate risks, enhance data protection, and promote citizen trust. Conclusions: The study concludes that cybersecurity is foundational to the success of digital government initiatives. It emphasizes the need for continuous investment, international collaboration, and public awareness to create secure and resilient digital ecosystems, ensuring effective governance in the digital age.
Exploring the Role of Entrepreneurship Education in Boosting Innovation among Students – A Case Study of Two KwaZulu-Natal Universities
Authors: Wonder Mtshali Thabo , Pfano Mashau , Wiseman Gamede Vangeli
Published: January 2025

The South African unemployment rate currently is at 32.9%. The labour market is struggling to create opportunities and failing to counteract unemployment with relevant skills. The covid-19 pandemic resulted in more people losing jobs which then contributed to the increase in unemployment. There have been calls for the government to implement strategies that would reduce poverty which include developing innovative entrepreneurs at the tertiary level. The article therefore focused on how to expand entrepreneurship education in South African universities to strengthen the economy and create job opportunities in the country. The research paper utilised a mixed-method approach. The quantitative data was collected using questionnaires on postgraduate students, whereas the qualitative data was collected from academics. The findings were analysed using the latest version of SPSS. The sample was made up of 368 postgraduate students, 4 academic staff from the University of KwaZulu-Natal, 346 postgraduate students, and 4 academic staff from the University of Zululand. The findings revealed that expanding entrepreneurship education will stimulate entrepreneurial mindset and innovation in students. However, students argued that universities do not have adequate infrastructure and resources to support innovation and entrepreneurship education. On the other hand, academic staff believed that higher education must have an active role in introducing and promoting entrepreneurship education. The paper recommends entrepreneurship education must be introduced across all colleges, this was noted from the contribution made by academic staff and postgraduate students. This paper provides strategies for stakeholder engagement in encouraging entrepreneurship to curb the increasing unemployment rate in South Africa.

Keywords: Unemployment, Postgraduate, Higher Education, Innovation, Entrepreneurship
Les relations start-ups – grands groupes : de l’objet à l’agenda de recherche
Authors: Chabaud Didier
Published: January 2025

Alors que les praticiens font de la qualité des relations entre start-ups et grandes entreprises un élément fondamental de la performance des stratégies d’innovation des grandes entreprises, les chercheurs ont relativement peu investigué le sujet. Si la littérature s’est, dans un premier temps, développée principalement dans le sens d’une description des modalités pratiques de collaboration, donnant lieu à une fragmentation des connaissances, ces dernières années ont vu une croissance de la production scientifique et un effort d’intégration globale des connaissances sur les relations entre start-ups et grandes entreprises. Il en ressort une vision qui met l’accent sur les antécédents, processus et résultats de la relation, tout en ouvrant sur une meilleure prise en compte des tensions, des dimensions organisationnelles et des intermédiaires impliqués dans les relations entre start-ups et grands groupes. Codes JEL : O32, O36
Étude comparée d’un corpus spécialisé italien-français de textes économiques originaux : mise en place de la perspective didactique dans l’analyse des termes en usage
Authors: Escoubas Benveniste Marie-Pierre , Montermini Fabio
Published: January 2025

Notre recherche est centrée sur l’étude des noms dans un corpus de presse spécialisée bilingue (environ 260 000 mots), composé de textes originaux traitant de thèmes économiques et financiers en italien et en français. L’approche quantitative et qualitative outillée et manuelle, pilotée par le corpus, vise à faire émerger des convergences et des divergences entre les langues concernant le fonctionnement sémantique des termes utilisés. Les résultats de l’étude linguistique comparée résident dans la sélection d’exemples représentatifs d’une variété de phénomènes qui illustrent la construction du sens spécialisé en contexte. Dans une perspective didactique, nous proposons de représenter au moyen de grilles les phénomènes observables. Deux types d’analyses sont envisagés : au niveau des concordances, qui permettent de repérer termes, marqueurs et relations sémantiques, et de les interpréter ; au niveau global avec le repérage de séries morphologiques comparables et de termes synonymes potentiels.
Generative Artificial Intelligence in Productivity and Quality Conformances
Authors: Shaikh Zuber Peermohammed
Published: January 2025

Generative AI is truly a game-changer that can significantly improve businesses' innovative product development processes like productivity and Quality Conformances. It can help redefine the boundaries of creativity and offer new avenues for ideation and design that no one thought about before. Idea generation may seem less challenging when businesses can get assistance in brainstorming and conceptualizing novel product concepts. Depending on the market trends, customer preferences, and existing product data, generative AI can generate a multitude of innovative ideas. These current chapters accelerating AI technology in the initial stages of product development, for spark inspiration and push companies to explore unique and cutting-edge possibilities. In addition to this, generative AI aids in rapid prototyping. It can generate models, visual concepts, and even virtual prototypes based on input criteria. This can facilitate visualization and enable businesses to iterate on designs quickly, reducing the time and costs associated with physical prototyping.
The Fringe Benefit of Industry 4.0 and Industry 5.0 on the Educational Sector
Authors: Vijay Vihas , J. Divya Lakshmi
Published: January 2025

This chapter presents a bibliometric analysis of literature published between 2012 and 2024, exploring the impact of Industry 4.0 and Industry 5.0 technologies on education. Using a dataset of 3281 Scopus-indexed records, the study identifies trends, research patterns, key contributions, and popular keywords. Bibliometric tools like Biblioshiny reveal global research trends, significant studies, and collaboration networks. The analysis highlights the influence of artificial intelligence, the Internet of Things, and robotics on education, particularly during the COVID-19 pandemic, emphasizing scenario-based learning and strategic human resource management. By examining the top 10 contributing papers, this study provides insights for policymakers, educators, and researchers, stressing the need for multidisciplinary research, global collaboration, and longitudinal studies to harness the educational potential of these technological advancements.
Language Learning Through Mobile Social Media Platforms
Authors: Randima Lusani , Sikhwari Matodzi Godfrey
Published: January 2025

This chapter aims to explore the role of mobile social media in language learning, looking at both the opportunities and challenges they offer. By examining current practices, evaluating their effectiveness, and providing practical recommendations, this chapter hopes to help educators, researchers, and learners make the most of these innovative tools for language education. The goal is to bridge the gap between traditional learning methods and the dynamic, interactive environments provided by mobile social media, contributing to the advancement of language education in the digital age.
A Bibliometric Review on the Use of Artificial Intelligence in Human Resources Management
Authors: Altuntaş Gültekin , Inanc Yelda , Tekin Ilknur Cevik
Published: January 2025

This study aims to investigate studies on the use of artificial intelligence in human resources management in the last 10 years using the bibliometric method. By searching the keywords of “Human Resources Management”, “Human Resource Management”, “Human Resources”, “Human Resource”, “Artificial Intelligence”, “Machine Learning”, “Deep Learning”, “Artificial Narrow Intelligence”, “Artificial General Intelligence”, “Artificial Super Intelligence”, “Generative Artificial Intelligence”, “Generative AI”, and their abbreviations such as HRM, AI, and so on in the Web of Science Core Collection database on July 22, 2024, 47,955 scholar works have been accessed. The filtering process has yielded a data set consisting of 949 publications, which have been analyzed using the bibliometric analysis method by the software, VOSviewer with the version of 1.6.20. The analysis reveals leading authors and institutions with significant contributions and provides a holistic view of AI applications in HRM, highlighting both the opportunities and challenges with an interdisciplinary perspective.
AI in HRM
Authors: Vashishth Tarun Kumar , Sharma Vikas , Tomer Tanuja , Kumar Aditya , Kaushik Sachin , Singh Bharat
Published: January 2025

The creation of generative AI is transforming human aid control (HRM) via improving employee engagement and pleasure. This paper explores the combination of AI-driven tools in HRM, highlighting how those technology personalize worker reviews, automate routine obligations, and offer actual-time feedback. The end result is an extra responsive and adaptive place of job that fosters higher activity satisfaction and engagement stages. However, the paper also addresses the demanding situations related to AI integration, such as making sure records privateness and mitigating ability biases. By leveraging generative AI successfully, corporations can create an extra dynamic, efficient, and worker-centric HR environment, in the end boosting ordinary organizational performance and employee properly-being.
Unleashing the Potential
Authors: Ara Aftab , Alyusef Muna
Published: January 2025

Business analytics (BA) uses data and analytical tools to aid in making decisions and upgrading business performance. In the era of digitalization, BA has become an important strategy for many organizations to provide data about customer habits, market status, and business operational performance. Unfortunately, due to diverse economies lacking the level of development, resource endowments, and political stability issues, the MENA region faces several obstacles and opportunities in leveraging BA to support its local economic development. Therefore, there is a need to identify and address the gaps and needs of the MENA region in terms of BA adoption and implementation. This research aims to explore how BA can be used for regional economic success in the MENA region. In this paper, qualitative and quantitative data collection and analysis are used to explore the role of business analytics (BA) in the economic growth of the local MENA region. A qualitative approach is utilized by interviewing managers and experts in addition to secondary data sources. The study infers that BA has a crucial role in amplifying business performance and competition in the MENA region. BA contributes to creating jobs, developing skills, encouraging innovations, and refining customer services. BA acquisition and implementation bring with it a few challenges like resistance to changes, budget constraints, and data quality issues. The chapter helps in convincing policymakers, practitioners, and researchers to address the challenges faced and take advantage of BA in their work culture. Overall, the chapter points out the capabilities of BA in the economic growth of the local MENA region and suggestions to deal with challenges faced in its implementation.
A Study on IoT-Enabled Smart Bed With Brain-Computer Interface for Elderly and Paralyzed Individuals
Authors: Iqubal Sharique , Khan Sadaf , Pant Niharika , Sarkar Sneha , Rey Tapasya , Mohapatra Hitesh
Published: January 2025

This research tackles a major gap in healthcare for patients with severe disabilities, especially those unable to communicate or move, such as those with paralysis. Current solutions provide minimal support and lack natural, non-verbal communication. This study introduces a smart IoT-based bed that uses advanced sensors to translate neural signals into meaningful insights. By integrating brain-computer interface (BCI) technology, the bed captures brain signals with EEG sensors, effectively translating patients' needs and emotions like discomfort or hunger. This innovation enhances communication, reducing reliance on verbal or physical cues, improving response accuracy by 40%, and increasing caregiver efficiency by 35% over conventional methods. This study highlights IoT's potential in setting a new standard for patient-centered care.
Multimodal IoT-Based Autonomous Emergency and Response Care for Healthcare Ecosystems
Authors: Sudha D. , Violet S. , D. R. Thirupurasundari , M. Anlin Sahaya Infant Tinu , Kavin Balasubramanian Prabhu , Addula Santosh Reddy
Published: January 2025

Emergency and response care is a critical part of a country's healthcare infrastructure. The nation's healthcare sector is more concerned with developing a comprehensive, autonomous emergency, and response care by including multimodal data collected from different IoT devices. The existing systems use the body area networks (BAN) along with IoT sensors to gather critical health data to save lives. This system considers data from biosensors, medical IoT sensors, and patient activity sensors. However, most of the decision-making part resides on the medical practitioners, and also there are few provisions for integrating multi modal data like x-rays, MRI, and CT images as a part of automated emergency and response system. The chapter is a holistic intelligent framework which includes multimodal data as a part of decision support systems. This system has multiple layers of data analysis, as each mode of data world require different processing and ML models.
CNN-Based Approach for Brain Tumor Detection and Severity Prediction
Authors: Jenefa J. , Athulya R. , Varghese Aaron John , Vetriveeran Divya , Sambandam Rakoth Kandan
Published: January 2025

Artificial intelligence is widely used in healthcare, especially in medical imaging. It leads to advanced diagnosis using innovative approaches to analyze complex data more accurately and provide personalized treatments. This helps the clinicians efficiently analyze the imaging data, leading to early detection of diseases like brain tumors, cancer, cardiovascular diseases, etc. The research work focuses on the detection and severity prediction of brain tumors. Magnetic resonance imaging (MRI) scan images are preprocessed in the proposed model using different methods. The convolutional neural network model (CNN) is used to detect and predict brain tumors and can be used in personalized treatments. The proposed method has an accuracy of about 98% in classification and severity prediction.
Vision Assist for the Visually Impaired
Authors: Voruganti Hindumathi , Veeramalla Santhosh Kumar , Jutur Naga Vishnu Vardhan , Gali Rama Lakshmi , Manne Praveena
Published: January 2025

In a world where visual information dominates, individuals with visual impairments face significant challenges in comprehending and traversing their surroundings independently. Tasks such as interpreting their environment, identifying faces, and navigating obstacles present formidable obstacles. Addressing these challenges is crucial to improving the daily lives of visually impaired individuals. “Vision Assist for the Visually Impaired” introduces an innovative solution that seamlessly integrates facial recognition and obstacle detection technologies. Departing from conventional wearability, this approach allows the device to be discreetly integrated into the user's routine, either slipped into a pocket or clipped onto clothing. Leveraging the capabilities of Raspberry Pi, users can train the system with facial images and corresponding names for personalized audio output upon detecting familiar faces. Concurrently, ultrasonic sensors detect obstacles in real-time, providing audio feedback on their proximity to ensure safe navigation.
Analysis of Crime Against Women Data Using Machine Learning and Statistical Methods
Authors: Tamilarasi P. , UmaRani R. , JayaSudha T. , Yusoff Yusliza , Kumuthini C.
Published: January 2025

Analyzing, cleaning, manipulating, and modelling datasets to conclude the data they include is the process known as data analytics. Qualitative and quantitative data analysis are two more categories into which data analytics may be separated. The scientific and mathematical study of algorithms is known as machine learning (ML). Crime against women has grown to be a major issue. Numerous nations are always working to avoid this offence, which is something that must be done. Crimes against women have increased dramatically in recent years. Every year, a massive dataset is created based on the reporting of crimes. To a certain extent, this data can help us prevent crime by analyzing and forecasting it. The crime rate against women is predicted in this chapter using a variety of statistical techniques, including the correlation coefficient ANOVA, and hypothesis testing with ML models in Python, including linear regression. The results are finally presented based on the performance of the ML algorithms using evolution metrics, such as MAE, MSE, and R2.
A Sentimental Analysis of Legal Documents Using Mask Attention BERT Networks
Authors: Selvi D. Thamarai , Kalaiselvi S. , Anitha V. , Santhi S. , Gomathi V. , Sekar Sathish Kumar
Published: January 2025

Legal systems can function more efficiently by processing cases faster and having a higher case clearance rate when complex legal texts are automatically analysed for logical patterns. The most crucial task in doing this is classifying sentences in legal documents automatically based on their content. This chapter suggests a deep learning model for sentiment analysis-based legal text analysis and judgment generation. The transformer model is an innovative encoder-decoder that uses self-awareness to analyse speech patterns which runs noticeably quicker and allows for parallel processing. In this work, the glove embedding and the BERT algorithm—bidirectional encoder representation for transformer model—are utilised to construct sentiment analysis for text categorization. Prior to extracting valuable data from textual input, a preprocessor is used to enhance the quality of the data. Next, pre-trained glove word embedding methods and term frequency-inverse document frequency (TF-IDF) feature weighting are used.
AI Implementation for Smart Wearable
Authors: Shameem P. Mohammed , Murthy A. Sampath Dakshina , B. Judy Flavia , M. S. Nidhya , Tiwari Mohit , Maram Balajee
Published: January 2025

Evolution of AI in the medical field is the biggest challenge. Research organisations are committed to continuing the in-depth quest for intelligence because of specific long-term demands and challenges in medicine. Because of developments in areas like the internet of things, cloud computing, and 5G mobile networks, artificial intelligence (AI) technology is being used in healthcare. Additionally, improved public services are made possible by the extensive integration of IoT technology and artificial intelligence, which gradually enhances diagnostic and therapeutic capabilities. The authors join the thoughts behind unambiguous calculations like to portray situation-based applications like distant conclusion and clinical coordination, pediatric escalated care units, cardiovascular concentrated care units, trauma centers, venous thromboembolism, patient consideration, and imaging utilizing the web of things (IoT), the cloud, huge information examination, and AI in medical services.
The Role of Digital Leadership Capability and Organizational Culture on Innovation Ecosystems in Omani E-Commerce Stores
Authors: Al Marhoobi Sauda Salim Hamdun , Makhbul Zafir Khan Mohamed , Sinnah Suguna
Published: January 2025

This research investigates the role that digital leadership capability, organizational culture, digital literacy, and innovative work behavior in the context of Oman e-commerce stores and the innovative ecosystem. Using the sample size of 400 employees, this research discovers that digital leadership capability and organizational culture reinforce innovative ecosystem as they improve employees' digital competence and promote innovation. Mediation analysis shows that the roles of digital literacy and innovative work behaviour in enhancing mediation of digital leadership capability and organizational culture to produce quantified measures of innovation. These insights inform the managers and policymakers the best practices on how to adopt digital transformation for growth: including the need for leaders to be flexible and continuously train and develop their workforce to meet the changes in the digital economy.
Market Dynamics in the Metaverse
Authors: Qadeer Abdul , Hussain Asadullah , Siddiqui Hassan Arif
Published: January 2025

The Metaverse, an emerging digital ecosystem, offers transformative opportunities for small and medium enterprises (SMEs) to innovate, expand, and thrive. This study examines the market dynamics within the Metaverse, focusing on how SMEs can leverage its potential to enhance consumer engagement and drive growth. Combining virtual reality (VR), blockchain, and augmented reality (AR), the Metaverse provides an immersive platform for businesses to create unique value propositions and adapt to evolving consumer preferences
Growth of Small and Medium-Sized Enterprises in Africa
Authors: Olubiyi Timilehin Olasoji , Itai Muktar Monday
Published: January 2025

The disruptive nature of the global pandemic and economic challenges on businesses has provided the need for a technological revolution and ensuring the availability of artificial intelligence (AI) capabilities for business growth, but less of it is acknowledged in small businesses. Therefore, this study examines the relationship between artificial intelligence (AI), innovation, employment, and growth of SMEs in Nigeria, Africa's largest consumer market. Principal component analysis (PCA) and the structural equation model (SEM) were adopted to examine the role of AI on SMEs growth in Southwest Nigeria. The study results showed that AI capabilities indicators have a positive relationship with SMEs growth. It was also observed that AI employment indicators exert a direct relationship with the latent factor. Overall results implications of the research is that the results offer a deeper insight for owners of SMEs, entrepreneurs, academic researchers and stakeholders to promote economic growth and development through adoption of artificial intelligence
Promoting Corporate Entrepreneurship Through Metaverse Practice
Authors: Qadeer Abdul , Hussain Waseem
Published: January 2025

In this empirical investigation on promoting corporate entrepreneurship through metaverse practices data collected from an overall of 32 respondents using a standardized questionnaire. Multiple statistical techniques were employed for analyzing the data utilizing the SPSS program. The results of the analysis revealed a significant correlation between the variables investigated of 0.775 (Total Index). This robust association indicates a positive relationship between corporate entrepreneurship and the metaverse, which supports the study's core hypothesis
Leadership Strategies for Implementing Environmental Management Systems
Authors: Sposato Martin , Dittmar Eduardo Carlos
Published: January 2025

This chapter explores the critical role of leadership in the successful implementation of Environmental Management Systems (EMS) within organizations. As businesses face increasing pressure to address environmental concerns and adopt sustainable practices, the integration of EMS has become a strategic imperative. This chapter examines how effective leadership can drive the adoption and ongoing success of EMS initiatives, focusing on key strategies that leaders can employ to overcome challenges, foster organizational buy-in, and create a culture of environmental responsibility. The unique contribution of this chapter lies in its synthesis of leadership strategies specifically tailored to the EMS implementation context, offering novel insights into how leaders can navigate the complexities of environmental management while driving organizational change. By bridging the gap between leadership theory and environmental management practice, this chapter provides valuable guidance for both scholars and practitioners in the field of green management and organizational behavior.
How AI Tools Affect Discourse Markers When Paraphrased
Authors: Alia Mohammad , Aliia Abdussalam M.
Published: January 2025

This study explores the impact of AI tools, specifically ChatGPT, on the use of metadiscourse markers, focusing on hedging and boosting in academic writing. Metadiscourse markers help writers express their stance, guiding readers through arguments with clarity and emphasis. The rise of AI tools like ChatGPT has transformed academic writing by assisting in generating and refining text. By analyzing ten research articles, sentences containing hedges and boosters were paraphrased using ChatGPT to observe changes in rhetorical stance. The results show that while ChatGPT maintains the original meaning, it often moderates the intensity of both hedging and boosting. For instance, “undoubtedly confirms” is softened to “clearly affirms,” making the tone more cautious and balanced. This moderation helps avoid overstatement but may reduce the strength of the original stance. Meanwhile, hedging is often retained but with shifts in certainty. These findings underscore the need for critical review of AI-generated content to ensure the intended rhetorical effect is preserved.
Employer Branding and Employee Retention with the Test of Mediating Role of Social Media in the Context of Nepalese Service Sector
Authors: Pandey Dhruba Lal , Risal Nischal
Published: January 2025

The aim of this study is to investigate the role of employer branding (including compensation and benefits, organization culture, employer reputation, and career development) in Nepalese service sec-tor industries and its impact on employee retention. Additionally, the study explores the potential mediating role of social media communication technology in this relationship. While previous re-search has predominantly focused on employer branding's role in enhancing organizational attrac-tiveness and the mediating role of social media, this study diverges by examining its impact on em-ployee retention, filling a gap in Nepalese research literature. Data from 183 respondents were ana-lyzed using SMART-PLS software, employing structural equation modeling and bootstrap multi-group analysis. The study reveals that there is no direct and significant relationship between employer branding components and employee retention. Despite the emphasis on the significance of a strong employer brand in retaining employees, other contextual factors may play a more influential role in the Nepalese service sector context. Moreover, the mediating role of social media usage in the rela-tionship between employer branding and employee retention was found to be insignificant. It means the information provided through social media does not contribute to retain employees. However, the employer’s branding leverages the time of retention of the employees. Though social media may serve as a valuable tool for employer branding and communication, its direct impact on employee retention in Nepalese service sector is limited. Future research could consider additional contextual factors such as job satisfaction and work-life balance, as well as explore elements like competitive remuneration and organizational support, to deepen understanding of employee retention dynamics and inform initiatives aimed at fostering entrepreneurship among students.
A rare vascular manifestation in chronic myeloid leukemia: a case report and literature review of Bier's spot development during nilotinib treatment
Authors: Alsaati Ahmed , Hakami Turki , Bajawi Sultan , Mohammed Gamil , Bajawi Nouf , Al-Faraidy Nadya
Published: January 2025

Bier's spots are rare angiospastic macules often associated with physiologic vasoconstriction. This case report describes a 35-year-old man with chronic myeloid leukemia treated with nilotinib who developed Bier's spots, a previously unreported adverse effect of the drug. The patient presented with asymptomatic hypopigmented macules on the hands and legs that appeared during venous stasis and resolved with elevation. This case emphasizes the need to recognize potential vascular side effects of tyrosine kinase inhibitors and highlights Bier's spots as a benign but remarkable manifestation in patients undergoing nilotinib therapy.
Growth hormone deficiency and secondary adrenal insufficiency in petrified ears syndrome: a case report and literature review
Authors: Recalcati Sebastiano , Vassallo Alberto , Villanova Marta , Lanzi Roberto , Losa Marco , Patricelli Maria Grazia , Carrera Paola , Fantini Fabrizio
Published: January 2025

Petrified ear is a rare clinical entity characterized by the progressive hardening of normal flexible auricular cartilage, leading to partial or complete auricular stiffness. In many cases, it provides a valuable clinical clue that allows the clinician to detect endocrinopathies (particularly Addison’s disease) in a patient who has not received a diagnosis. We present the first documented case of petrified ears, which resulted in the diagnosis of both secondary hypoadrenalism and growth hormone deficiency (GHD). Additionally, we review the relevant literature. Petrified ears syndrome is probably an underreported clinical manifestation of other systemic disorders. It may, at times, serve as a useful and simple clinical clue to suspect underlying endocrinopathies even in the absence of typical features.