bluuebunny/crossref_metadata_2025 huggingface dataset:
Manajemen Pelatihan Dakwah Bagi Para Da’iyah pada Program Pendidikan Kader Ulama Mui Sumatera Utara
Authors: Simarmata Cindy Suci Aisyah , Misrah Misrah
Published: May 2024

Penelitian ini dilakukan untuk melihat manajemen pelatihan dakwah bagi para da'i perempuan pada program pendidikan kader ulama MUI Sumatera Utara dalam menyauti fenomena kelangkan dai’yah di wilayah tersebut. Tujuan dari penelitian ini ialah untuk mengetahui bagaimana perencanaan, pengorganisasian, pelaksanaan, pengawasan serta evaluasi pelatihan dakwah pada Program Pendidikan Kader Ulama MUI Sumatera Utara. Metode yang digunakan pada penelitian ini adalah metode kualitatif, data diperoleh melalui wawancara, observasi, dan menganalisis dokumen yang terkait. Hasil penelitian menunjukkan bahwa manajemen pelatihan dakwah bagi para da'iyah pada program pendidikan kader ulama MUI Sumatera Utara dalam menyauti adanya kelangkaan mubalighah di Sumatera Utara memperoleh data bahwa: (1) Perencanaannya: merumuskan tujuan pelatihan dakwah, sasaran pelatihan dakwah, penentuan materi pelatihan dakwah, penyeleksian peserta pelatihan dakwah, sumber dana. (2) Pengorganisasiannya: membentuk kepanitiaan, jabatan, pembagian tugas, membuat penjelasan tugas masing-masing. (3) Pelaksanaanya: peserta pelatihan, materi pelatihan dakwah, metode pelatihan dakwah, penilaian pelatihan dakwah. (4) Pengawasannya: Pengawasan pelatihan dilakukan setiap hari, dan pengevaluasian kinerja panitia serta pengukuran keadaan peserta dilakukan ketika semua kagiatan pelatihan selama tiga bulan penuh telah selesai.
Wireless Charging System for Electric Vehicles
Authors: G. Amudha. , . Srinivasulu , Narayanan A. J. Sooriya , M. Nishanth
Published: May 2024

This paper presents a comprehensive review of wireless electric vehicle (EV) charging technologies, focusing on the advancements, challenges, and prospects in this domain. With the increasing adoption of electric vehicles globally, the demand for efficient and convenient charging solutions has grown significantly. Wireless charging offers promising opportunities to enhance the user experience by eliminating the need for physical connections between the charger and the vehicle. This review discusses the underlying principles of various wireless charging technologies, including inductive charging, resonant charging, and capacitive charging. Furthermore, it examines the key components and system architectures involved in wireless EV charging systems. The paper also addresses the technical challenges such as efficiency, alignment, safety, and interoperability that must be overcome to realize the widespread deployment of wireless charging infrastructure. Additionally, the regulatory and standardization efforts governing wireless EV charging are discussed, along with their implications for market adoption. Finally, the review provides insights into future research directions and potential applications of wireless EV charging technology, including dynamic charging systems and integration with smart grid networks. Overall, this paper serves as a valuable resource for researchers, engineers, and policymakers interested in understanding the current state and future prospects of wireless electric vehicle charging.
Technology Communication and Firm Performance of Kenya Tea Producers Companies
Authors: Cherono Soi Judith , Nyang’au Paul Samson , Mwalili Tobias
Published: May 2024

The study sought to examine the role of Technology Communication on performance of Tea Producers companies in Kenya. The study reviewed theoretical and empirical literature relevant to the role of Technology Communication on performance of Tea Producers companies in Kenya. The conceptual framework was discussed to show the relationship between Technology Communication (independent variable) and firm performance (dependent variable). Positivism philosophy guided this study. The study used cross-sectional survey design to establish the role of Information Technology strategic alignment on performance of Tea Producers companies in Kenya. In this study, the target population was identified as tea producer companies that are members of the East Africa Tea Trade Association (EATTA) in Kenya. This choice was made on the premise that these entities are likely to possess pertinent and accurate information relevant to the research. Specifically, the population encompassed all 29 tea producer members of EATTA. Respondents’ population comprised of six top managers from each organization translating to 174 top managers. The sample size was 121 top managers. They were targeted because top managers of organizations mostly handle strategic management issues. Purposive sampling technique was used to select respondents. The study mainly relied on primary data. The study used a questionnaire with diverse set of questions for the respondent to answer. A pilot study was carried out in order to ascertain the validity and reliability of the questionnaire. Descriptive statistics in the form of means and standard deviations were computed on the Technology Communication and performance measurement scales to provide an initial outline of the distribution of the participants' responses. The study concluded that Technology Communication has a positive and statistically significant influence on performance of Tea Producers companies in Kenya. Based on the findings,this study recommends that the management of Tea Producer companies should ensure effectiveness in adopting information technology and using it in governance of their organization. In addition,the management of Tea Producer companies should ensure their employees are well equipped with information technology skills to improve their productivity.
Teaching Competence and Information and Communication Technology Integration (ICT) of Private Schools in Davao City
Authors: J. Septimo Vanessa , L. Cancio Bryan
Published: May 2024

The study investigated the relationship between teaching competence and ICT integration among private school teachers in Davao City for the 2022-2023 school year. Employing a descriptive correlation design with 100 teacher respondents, the analysis revealed consistently high levels of teaching competence, particularly emphasizing professional development, and a high level of ICT integration, showcasing positive attitudes and effective utilization of ICT. The study underscored the significance of educators having a strong teaching foundation for a moderate positive relationship between teaching competence and ICT integration. The significant impact of professional development on ICT integration highlighted the need for ongoing training and growth opportunities for teachers, emphasizing the role of continuous learning in adapting to technological advancements. These findings highlighted the close relationship between teacher competence and successful ICT integration, underscoring the importance of professional development in creating a technology-rich learning environment. Conclusively, the findings underscored the importance of professional development in shaping effective ICT integration. These recommendations aimed to foster a collaborative and supportive environment, enhancing educators' competence and ensuring effective ICT integration. These insights provided valuable guidance for educators, policymakers, and researchers aiming to enhance teaching competence and ICT integration in private schools in Davao City.
Review on Aerated Lightweight Concrete Challenges and Application
Authors: Badashah Nadaf Najir
Published: May 2024

This study explores the use of environmentally friendly Aerated Lightweight Concrete (ALC) in constructions, focusing on its versatility and adaptability to various densities. The growing demand for lightweight building materials with excellent strength-to-weight ratios has led to an expansion in the use of ALC over the past decade. The focus is on creating customized ALC for specific uses, rather than introducing novel materials. The article analyzes the primary variables affecting ALC use, such as raw materials, manufacturing processes, and anticipated density-based features. The review aims to demonstrate how ALC's physical and mechanical properties can be altered for building applications using new and alternative raw materials.
Creating Robust Expense Tracker Applications with Flutter: A Step-by-Step Guide
Authors: Victoire T. Amalraj , Karunamurthy A. , R Kiruthivasan.
Published: May 2024

This paper presents a comprehensive guide to developing a mobile expense tracker application using the Flutter framework. The demand for efficient financial management tools has propelled mobile apps to the forefront, catering to individuals and businesses alike. Flutter, with its cross-platform capabilities and rich feature set, provides an ideal framework for building robust and user-friendly expense tracker apps. This guide delves into the entire development process, from setting up the development environment to deploying the app on both Android and iOS platforms. Key components like user interface design, data management, and integration of essential features are meticulously explored, equipping developers with practical insights and best practices for crafting a successful expense tracker app.
Enhancements in Immediate Speech Emotion Detection: Harnessing Prosodic and Spectral Characteristics
Authors: Shah ZEWAR , Zhiyong SHAN , . Adnan
Published: May 2024

Speech is essential to human communication for expressing and understanding feelings. Emotional speech processing has challenges with expert data sampling, dataset organization, and computational complexity in large-scale analysis. This study aims to reduce data redundancy and high dimensionality by introducing a new speech emotion recognition system. The system employs Diffusion Map to reduce dimensionality and includes Decision Trees and K-Nearest Neighbors(KNN)ensemble classifiers. These strategies are suggested to increase voice emotion recognition accuracy. Speech emotion recognition is gaining popularity in affective computing for usage in medical, industry, and academics. This project aims to provide an efficient and robust real-time emotion identification framework. In order to identify emotions using supervised machine learning models, this work makes use of paralinguistic factors such as intensity, pitch, and MFCC. In order to classify data, experimental analysis integrates prosodic and spectral information utilizing methods like Random Forest, Multilayer Perceptron, SVM, KNN, and Gaussian Naïve Bayes. Fast training times make these machine learning models excellent for real-time applications. SVM and MLP have the highest accuracy at 70.86% and 79.52%, respectively. Comparisons to benchmarks show significant improvements over earlier models.
Conversational Fashion Outfit Generator Powered by GenAI
Authors: Gupta Deepak , Ranjan Jha Harsh , Chhallani Maithili , Thakar Mahima , Dhakne Amol , Parit Prathamesh , Kachgunde Hrushikesh
Published: May 2024

The convergence of artificial intelligence and fashion has given rise to innovative solutions that cater to the ever-evolving needs and preferences of fashion enthusiasts. This report delves into the methodology behind the development of a "Conversational Fashion Outfit Generator powered by GenAI," an advanced application that leverages the capabilities of Generative Artificial Intelligence (GenAI) to create personalized fashion outfits through natural language interactions. The model outlines the essential elements of the methodology, including data collection, natural language understanding, computer vision integration, and deep learning algorithms. Data collection forms the bedrock, as access to a diverse dataset of fashion-related information is critical for training and fine-tuning AI models. Natural Language Understanding (NLU) is instrumental in comprehending user input and generating context-aware responses, ensuring meaningful and engaging conversations. Computer vision technology is integrated to analyze fashion images, recognizing clothing items, styles, and colors, thus aiding in outfit recommendations. Deep learning algorithms, particularly recurrent and transformer-based models, form the backbone of the system, generating personalized and contextually relevant fashion suggestions. This methodology not only underpins the "Conversational Fashion Outfit Generator" but also reflects the evolving landscape of AI in the fashion industry, where personalized, interactive experiences are becoming increasingly paramount in the realm of fashion and e-commerce.
A Study on Natural Dye Application on Cotton Fabric using Clitoria Ternatea
Authors: Sangeetha K. , Manonmani G. , Janani K. I.
Published: May 2024

In this fast fashion era dyeing is considered as a major cause for the textile pollution. It is also a cause for many deadly diseases due to the poor usage of synthetic dyes and most of the textile industry does not care about the workers and their protective wears and the workers suffer from health hazardous due the emitted effluents that gets emitted from the dyeing process. During the dyeing the synthetic dyes produce strong fumes, and these are highly carcinogenic and while disposing the dye there are proper treatment for the disposal otherwise this will create a huge damage to the environment. The present study focuses on colour ant that is extracted from clitoriaternatea flower on cotton fabric has been studied using alum. The wash, rub, light, and perspiration fastness of the dyed samples have been tested. It is discovered that clitoriaternatea dye can be successfully used for the dyeing of cotton to obtain a wide range of colours by using various mordant. In regard to colour fastness test samples exhibit excellent fastness to sunlight, washing, crocking, perspiration, and saliva.
Star Formation and Dust in the Cosmic Web
Authors: Parente Massimiliano , Ragone-Figueroa Cinthia , López Pablo , Martínez Héctor J. , Ruiz Andrés N. , Ceccarelli Laura , Coenda Valeria , Rodriguez Facundo , Granato Gian Luigi , Lapi Andrea , van de Weygaert Rien
Published: May 2024

The large-scale environment of the cosmic web is believed to impact galaxy evolution, but there is still no consensus regarding the mechanisms. We use a semi-analytic model (SAM) galaxy catalog to study the star formation and dust content of local galaxies in different cosmic environments of the cosmic web—namely voids, filaments, walls, and nodes. We find a strong impact of the environment only for galaxies with M
stars ≲ 1010.8
M
⊙: the less dense the environment, the larger the star formation rate and dust content at fixed stellar mass. This is attributed to the fact that galaxies in less dense environments typically feature younger stellar populations, a slower evolution of their stellar mass, and delayed star formation compared to galaxies in denser environments. As for galaxies with M
stars ≳ 1010.8
M
⊙, the differences among environments are milder, due to the disk-instability-driven supermassive black hole (SMBH) growth implemented in the SAM, which makes SMBH growth, and thus galaxy quenching, environment-insensitive. We qualitatively test our predictions against observations by identifying environments in Sloan Digital Sky Survey Data Release 16 using dust masses derived from the GAMA survey. The agreement is encouraging, particularly at

log

M

stars

/

M

⊙

≳
10.5
–
11

, where the specific star formation rates and dust masses appear quite environment-insensitive. This result confirms the importance of in situ growth channels of SMBHs.
Temperature Intermittent Structures in the Fast Solar Wind
Authors: Wang Xin , Wang Yuxin , Song Dongze , Yuan Haochen
Published: May 2024

In the solar wind turbulence, proton temperature fluctuations are highly intermittent, especially at small scales in the inertial range. This phenomenon may contain information about solar wind intermittent heating. However, the physical nature of the temperature intermittency is not yet clear. Based on the measurements from Solar Orbiter between 2020 September and 2022 September, we identify 185 temperature intermittent structures at the scale of 24 s with well-defined minimum variance direction in the fast solar wind and study the nature and kinetic effects of them. According to the variations of proton temperature, the intermittent structures are classified into four types, including temperature bump, step, dip, and chain. When considering the magnetic field configuration together with other plasma properties, we find that, among the bump cases, 46 of them are linear magnetic holes (LMHs) that are mainly related to mirror-mode (MM) instability, and 43 of them are current sheets (CSs) with local temperature enhancement. The step cases are found to be associated with shock-like structures (13 cases) and tangential discontinuities (eight cases) that separate two different parcels of plasma. For the dip cases, 21 of them could be associated with the MM instability, and the rest of the 16 ones may prefer soliton scenario. The 38 chain cases are identified as compressive vortex-like structures and a mixture of LMHs and CSs. These results will help to further understand the intermittent dissipation process in the solar wind turbulence.
Impact of Planetary Parameters on Water Clouds Microphysics
Authors: Yang Huanzhou , Komacek Thaddeus D. , Toon Owen B. , Wolf Eric T. , Robinson Tyler D. , Chael Caroline , Abbot Dorian S.
Published: May 2024

Potentially habitable exoplanets are targets of great interest for the James Webb Space Telescope and upcoming mission concepts such as the Habitable Worlds Observatory. Clouds strongly affect climate and habitability, but predicting their properties is difficult. In Global Climate Models (GCMs), especially those aiming at simulating Earth, cloud microphysics is often crudely approximated by assuming that all cloud particles have a single, constant size or a prescribed size distribution and that all clouds in a grid cell are identical. For exoplanets that range over a large phase space of planetary properties, this method could result in large errors. In this work, our goal is to determine how cloud microphysics on terrestrial exoplanets, whose condensable is mainly water vapor, depend on aerosol properties and planetary parameters such as surface pressure, surface gravity, and incident stellar radiation. We use the Community Aerosol and Radiation Model for Atmospheres as a 1D microphysical model to simulate the formation and evolution of clouds including the processes of nucleation, condensation, evaporation, coagulation, and vertical transfer. In these 1D idealized experiments, we find that the parameters that determine the macrophysical thermal structure of the atmospheres, including surface pressure and stellar flux, impact cloud radiative effect (CRE) most significantly. Parameters such as gravity and number density of aerosols working as cloud condensation nuclei affect the microphysical processes of cloud formation, including activation and vertical transfer. They also have a significant, though weaker effect on CRE. This work motivates the development of more accurate GCM cloud schemes and should aid in the interpretation of future observations.
Exogenous Carbon is Unlikely to be the Source of Methane Microseepage Emissions on Mars
Authors: Moores John E. , Sapers Haley M. , Schuerger Andrew C.
Published: May 2024

A complete understanding of methane in the atmosphere of Mars requires information on putative sources. Organic carbon derived from meteoritic sources, such as interplanetary dust particles (IDPs), over geologic time is the best-defined source of organic carbon on the surface of Mars. Here we examine two different mechanisms for degrading this material to produce methane (1) Ultraviolet photolysis and (2) thermal decomposition. Neither of these mechanisms can produce sufficient methane under realistic assumptions to explain observed methane at Gale Crater, suggesting that IDPs are not the primary source material producing methane on Mars.
Not in the countryside please! Investigating UK residents’ perceptions of an introduced species, the ring-necked parakeet (Psittacula krameri)
Authors: Pirzio-Biroli Alessandro , Crowley Sarah L. , Siriwardena Gavin M. , Plummer Kate E. , Schroeder Julia , White Rachel L.
Published: May 2024

Wildlife management can generate social conflict when stakeholder perceptions of the target species are not considered. Introduced Ring-necked Parakeets (RNP) are established in the UK and have been added to the ‘general licence’ of birds that can be killed to prevent serious economic damage. We aimed to better understand perceptions of RNPs on a nationwide scale to inform mitigation actions for potential future conflict over RNP management. We surveyed 3,947 UK residents to understand awareness of, knowledge of and attitudes towards the RNP across the UK.

We found that most respondents (90.2%) were aware of the RNP. Almost half of respondents (45.9%) held negative opinions, particularly against the RNP in rural areas (64.7%), suggesting landscape contexts influence attitudes. Respondent preference for the RNP was low in local neighbourhoods (7.80%) although the species was considered aesthetically pleasing by most (83.0%). Many respondents knew the species’ name (54.9%), but underestimated current population numbers in the UK (82.6%) and few knew its full native range (10.0%). We identified respondents’ ecological interest, age, education, preference for, awareness of and knowledge of the RNP as significant factors associated with perceptions.

Our findings suggest that the RNP presents a complex socio-environmental challenge, with respondent awareness, knowledge and attitudes each forming an important component of perceptions towards this species. We recommend that wildlife managers utilise our findings and cohesive approach to enhance future RNP perception research in the UK and abroad and towards the success of any proposed management initiatives under the UK general licence.
Type specimens, taxonomic history, and genetic analysis of the Japanese dancing mouse or waltzer, Mus wagneri variety rotans Droogleever Fortuyn, 1912 (Mammalia, Muridae)
Authors: Cruz Mónica , Bergmans Wim , Takada Toyoyuki , Shiroishi Toshihiko , Yoshiki Atsushi
Published: May 2024

In the present paper, the existence and location of the type series of the Japanese dancing mouse or waltzer, Mus wagneri variety rotans Droogleever Fortuyn, 1912, are established, and a lectotype is designated. Available type specimens are measured, and some morphological parameters, sex, and general condition of the specimens are recorded. A literature survey was conducted, and an attempt is made to clarify the position of M. wagneri variety rotans in the taxonomy of Mus. A genetic analysis suggests that the type series of the Japanese dancing mouse represent a crossbred, or derivation of a crossbred, between the original Japanese dancing mouse of Mus musculus molossinus Temminck 1844 origin and European fancy or laboratory mice of Mus musculus domesticus Schwarz & Schwarz, 1943 origin. Much of their genome was replaced and occupied by Mus musculus domesticus type genome, probably through extensive breeding with European mice.
Une nuit à Troie
Authors: Goya Michel
Published: May 2024

La guerre décrite dans le cycle troyen, et notamment par Homère dans l’ Iliade , se déroule bien sur la Terre, mais pas dans notre monde. Les héros se battent et se débattent dans un univers avec ses lois propres, y compris ses lois physiques. Ils donnent l’impression d’agir dans une petite arène entourée d’un brouillard que l’on appelle la nuit. Pour Achille, Hector, leurs compagnons et leurs adversaires, ce brouillard est une force contre laquelle ils ne peuvent rien et dont l’arrivée dans l’arène signifie le repos ou la mort. C’est un monde de cauchemar.
Combattre dans le vert
Authors: Erbland Brice
Published: May 2024

Combattre de nuit est l’un des savoir-faire les plus complexes pour une unité militaire moderne, qui nécessite un entraînement spécifique. Le soldat est depuis toujours habitué à dompter la nuit, depuis ses classes jusqu’aux veilles dans les centres opérations. Mais il découvre en y combattant des particularités insoupçonnées. Même si la technologie permet aujourd’hui de percer les nuits les plus noires, les dangers liés à cet environnement particulier s’ajoutent à la menace de l’ennemi.
Voyage au bout de ma nuit
Authors: Cohn Sarina
Published: May 2024

Malvoyante de naissance, Sarina est aveugle depuis ses seize ans. Pour la première fois elle raconte dans un article son parcours, sa façon d’appréhender le monde qui l’entoure, ce qui fait sa vie. Alors, ne pas voir, est-ce vivre dans la nuit ?
De midi à minuit…
Authors: Trêve Jean
Published: May 2024

Il est impossible de parler de la nuit sans évoquer l’alternance du jour et de la nuit, mouvement pendulaire de la vie. La franc-maçonnerie, dans la diversité de ses formes, s’inscrit dans ce mouvement en adoptant le patronage des deux saints Jean, associés aux deux solstices. Mais la nuit terrestre n’est pas obscurité totale, car le monde reste éclairé par la lumière réfléchie de la Lune. Le perfectionnement de l’Homme auquel aspirent les frères les conduit par la métaphysique à connaître la véritable nuit qui est au-delà du cosmos, qui se révèle à la fois comme chaos primordial et retour à l’unité du Principe.
Tâtonnements
Authors: Butel Nelly , El Khoury Ghada
Published: May 2024

Il s’agit d’une rencontre, dans la nuit des mots et des idées, pour parler de la nuit, avec un langage qui ne cherche pas à définir, mais qui se laisse porter par le courant de ce qui se dit dans une écoute et une interpellation mutuelles. On découvre au fur et à mesure que la nuit peut durer ; que dans la durée elle agit comme révélatrice ; que nous avons à lui survivre, en posant simplement un premier pas ; que d’autres fois nous gagnerions plutôt à l’écouter et à recevoir d’elle notre mission, à la laisser nous dépouiller du faux et de ce qui nous encombre, d’une protection qui ne protège plus que la mort en nous, pour nous conduire vers l’aimé. Chacun peut raconter ses nuits, sa nuit.
Role of AI in Academic Research
Authors: Kondaveeti Hari Kishan , Kumar Samparthi V. S. , Manusree Atchuta Venkata Naga , Vatsavayi Valli Kumari , Ananthachari Preethi
Published: May 2024

Artificial intelligence (AI) is rapidly transforming academic research, accelerating discovery, improving efficiency, and opening up new avenues across various disciplines. This chapter introduces AI and discusses its broad range of applications, both within and outside of academia. The chapter then presents the applications of AI in academic research. It covers various AI tools, such as Scite, Elicit, etc., and a comparative analysis of their capabilities and limitations. The chapter also discusses some ethical issues that must be considered when using AI in academic research. It concludes with a discussion on the future of AI in academic research and the potential benefits and challenges that lie ahead. This chapter is intended for a broad audience, including academic researchers, students, and those who are interested in learning more about the role of AI in academic research.
The Researcher's Sidekick
Authors: Gupta Minisha , Bhaskar Preeti
Published: May 2024

This research aims to delves into the perspectives of researchers in unleashing ChatGPT's potential in academic research. The researchers are encouraged to extensively discuss their perspectives on perceived benefits, limitations of ChatGPT in academic research, as well as share insights into potential strategies for enhancing ChatGPT's effectiveness in academic research. The study uses interpretative phenomenological analysis (IPA) as the research methodological framework to gain insights into the perspectives of researchers, aligning with the objectives of the study. The study was carried out in the Uttarakhand region of India. Semi-structured in-depth interviews were carried out to collect data from the researchers. The authors(s) always maintained respect, privacy concerns, and a non-judgmental outlook towards the research participant during sample selection and interview. Semi-structured in-depth interviews were carried out to collect data from the researchers.
Efficient Software Cost Estimation Using Artificial Intelligence
Authors: Juneja Sonia
Published: May 2024

Accurate cost estimation is desired for efficient budget planning and monitoring. Traditional approach for software cost estimation is based on algorithmic models expressing relationship among different project parameters using mathematical expressions. Algorithmic models are parameter-based models and produce the best accuracy when these parameters are well defined and predictable. The fundamental factor governing project cost within algorithmic models is the software size, quantifiable either in lines of code or function points. Analogy based estimation and expert judgment-based estimation falls under the category of non-algorithmic models. Both algorithmic and non-algorithmic models can estimate project cost and effort required but are unable to face challenges arising due to dynamic user requirements, latest technological trends, and impact of cost drivers on estimation process. Different machine learning based approaches like fuzzy modelling, regression models, optimization techniques, and ensemble methods can be used to predict an estimate nearest to the real cost of the project.
Test Data Generation for Branch Coverage in Software Structural Testing Based on TLBO
Authors: Jaiswal Updesh Kumar , Prajapati Amarjeet
Published: May 2024

Test data generation is forever a core task in automated software testing (AST). Recently, some meta-heuristic search-based techniques have been examined as a very effective approach to facilitate test data generation in the structural testing of software. Although the existing methods are satisfactory, there are still opportunities for further improvement and enhancement. To solve, automate, and assist the test data generation process in software structural testing, a teaching learning based optimization (TLBO) algorithm is adapted in this chapter. In this proposed method, the branch coverage convention is taken as a fitness function to optimize the solutions. For validation of the proposed method, seven familiar and benchmark software programs from the literature are utilized. The experimental results show that the proposed method, mostly, surpasses simulated annealing, genetic algorithm, harmony search, particle swarm optimization, ant colony optimization, and artificial bee colony.
Comparative Evaluation of Tocolytic Efficacy on Oral Nifedipine Tablet vs. Transdermal Nitroglycerine Patch in Preterm Labor
Authors: Kshirsagar N. S. , Laddad Manisha , Patil Sanjay Kumar S. , Alatawi Abeer
Published: May 2024

Because preterm labour is linked to poor outcomes for newborns, it is a major concern in obstetrics. Tocolytic medicines are used to improve foetal outcomes and delay preterm birth. Oral nifedipine and transdermal nitroglycerine are compared for tocolytic efficacy, safety, and cost-effectiveness in premature labour control. A randomised controlled trial included 200 preterm-risk pregnant women. One group received transdermal nitroglycerine and the other oral nifedipine. Minimum 48-hour delivery delay was the main consequence. Secondary outcomes included neonatal outcomes, mother side effects, cost analysis, and adverse events. Oral nifedipine and transdermal nitroglycerine had similar effective delivery delay (p = 0.076). Adverse events, side effects, and neonatal outcomes were similar between groups. The cost investigation found no significant differences in direct medical expenses. The data suggest oral nifedipine and transdermal nitroglycerine are viable tocolytics. Clinicians can choose a treatment strategy based on each patient's individual traits and preferences. These drugs' safety and efficacy emphasise the importance of maternal monitoring. Its cost-equivalency allows healthcare institutions to prioritise patients without economic constraints. The findings contribute to the debate over preterm labour management and emphasise the necessity for patient-centered care in pregnant women.
Impact of Cultural Diversity on Employee Performance
Authors: Arman Abdelfatah , Sohaib Osama , Begum Vazeerjan , Alkharman Aaesha Aaesha
Published: May 2024

The purpose of this study was to investigate the influence of cultural diversity on job satisfaction and its effect on expatriate work performance. Structured interviews were conducted to collect qualitative data from a sample group of expatriates five participants from mixed nationalities in a private sector organization based in the United Arab Emirates. Thematic analysis identified three emergent themes of culture that negatively impacted expatriates' job satisfaction, causing reduced employee performance, and two themes were identified that increased expatriate performance at work (enhanced creativity and innovation). This research contributes to the body of academic knowledge about the effect of cultural diversity on expatriate employee performance. The value for praxis from this study are recommendations for managerial action to improve expatriate work performance.
Analysis of Competencies Required for Teachers According to the Kingdom's Vision 2030
Authors: Alenezi Abdullah
Published: May 2024

This study examines digital technology integration in Saudi Arabian schools from the viewpoints of teachers and administrators. The research employed a mixed-methods approach, involving surveys for 346 teachers and 155 administrators, as well as in-depth interviews with a subgroup of 12 teachers and 12 administrators. The findings reveal that both teachers and administrators acknowledge the significance of digital technology in education, with most indicating access to and utilization of digital tools. Challenges identified encompass technical issues, inadequate training, and bureaucratic obstacles. Qualitative insights delve into subjects like digital skills, infrastructure needs, integration's prospects and hurdles, and the influence of Vision 2030 on tech adoption. The study emphasizes advancements in digital integration while recognizing areas for enhancement, including more teacher training, addressing bureaucratic impediments, and harnessing digital technology to align with Vision 2030's educational objectives.
Developing Measurement of Collaboration Between the Supplier and Client Firms
Authors: Mohiuddin Muhammad , Karuranga Egide , Cao Yuliang
Published: May 2024

This study recommends a suitable model for evaluating supply chain collaboration in the natural forest products industry. We follow a two-step analysis: The first-order measurement model is leveraged to assess collaboration level, and the second-order confirmatory factor analysis develops the collaboration level by using four indicators representing customer and supplier firms as well as two specific indicators for each of them. Four items are common practices for both sides: joint sales forecasting, exchange of basic information, joint planning, and joint delivery improvement. Two practices are highly oriented toward customers: resource sharing of logistics assets and exchange of performance evaluation. Business-to-business practices engaged mostly with suppliers include the implementation of replenishment systems and joint new product development. Collaboration measurement between suppliers and client firms contributes to effectively manage the relationship between the supplier and client firms and can improve the competitiveness of participating firms in the network.
Pleural mesothelioma from fluoro-edenite exposure: PACAP and PAC1 receptor. A preliminary report
Authors: Lombardo Claudia , Maugeri Grazia , D'Amico Agata Grazia , Broggi Giuseppe , Caltabiano Rosario , Filetti Veronica , Matera Serena , D'Agata Velia , Loreto Carla
Published: May 2024

Pleural mesothelioma is a devastating malignancy primarily associated with asbestos exposure. However, emerging evidence suggests that exposure to fluoro-edenite fibers, a naturally occurring mineral fiber, can also lead to the development of pleural mesothelioma. In this study, based on the hypothesis that pituitary adenylate cyclase-activating polypeptide (PACAP) and PACAP-preferring receptor (PAC1R) expressions could be dysregulated in pleural mesothelioma samples and that they could potentially act as diagnostic or prognostic biomarkers, we aimed to investigate the immunohistochemical expression of PACAP and PAC1R in pleural biopsies from patients with pleural mesothelioma exposed to fluoro-edenite fibers. A total of 12 patients were included in this study, and their biopsies were processed for immunohistochemical analysis to evaluate the expression of PACAP and its receptor. The study revealed a correlation between the overexpression of PACAP and PAC1R and shorter overall survival in patients with malignant mesothelioma. These findings suggest that PACAP and PAC1R expression levels could serve as potential prognostic biomarkers for malignant mesothelioma. Furthermore, the immunohistochemical analysis of PACAP and PAC1R may provide valuable information for clinicians to guide therapeutic decisions and identify patients with poorer prognosis.
Oral isotretinoin versus acitretin in the treatment of plantar warts in adults
Authors: Nofal Ahmad A.E. , Najah Samar M. , ElShafy Ahmed S.A.
Published: May 2024

Background

Plantar warts are benign epithelial tumors that are forced inward due to pressure on the toes or sole of the foot and may become very painful if not treated. Many treatment options are available including topical treatments, lasers, and immunotherapy. However, data about systemic therapies are lacking.

Objective

To compare the efficacy and safety of acitretin versus oral isotretinoin in the treatment of multiple plantar warts.

Patients and methods

This randomized comparative double-blinded study included 80 adult patients with multiple plantar warts. The cases were divided into two groups: acitretin group (40 cases with a dose of 0.5 mg/kg/day) and isotretinoin group (40 cases with a dose of 0.5 mg/kg/day). The reduction in wart size and photographic comparisons at the beginning and every 2 weeks for 3 months were used to assess the treatment efficacy in the two groups. After therapy ended, a follow-up was conducted every month for 6 months to observe any recurrence.

Results

Complete response was observed in 30%, partial response in 55%, and no response in 15% of patients of acitretin group while complete response was achieved in 15%, partial response in 45%, and no response in 40% of patients of isotretinoin group with statistically significant difference in favor of acitretin (P=0.03). Compared with acitretin, oral isotretinoin was associated with a shorter duration to a complete response (83.3% of cases achieved complete response in <2 months compared with only 16.7% in acitretin group) (P=0.006).

Conclusion

Acitretin is superior to oral isotretinoin as a therapeutic option for plantar warts, but both are effective and safe. Since they are resistant to other traditional therapy techniques, they can be seen as valuable therapeutic choices for multiple plantar warts.
Evaluation of Turmeric, Ashwagandha, and Aloe Vera in the Management of Oral Lichen Planus Lesion
Authors: Shivu ME , Gupta Neha , Mulla Mushir , Mulla Munaz , Anand Bajoria Atul , Varshney Anchal
Published: May 2024

ABSTRACT

Objectives:

This study was conducted to evaluate the efficacy of turmeric, ashwagandha, and aloe vera in the management of oral lichen planus (OLP) lesion.

Materials and Methods:

Thirty patients with histologically confirmed symptomatic OLP with gingival presentation were included in this comparative investigation. Three groups of participants were created: Group I consisted of turmeric; group II included ashwagandha; and group III included aloe vera. For 3 weeks in a row, they were told to apply topical treatments twice a day. The patients were recalled for 4 to evaluate the cessation of symptoms.

Result:

The participants in all the groups showed a considerable improvement in the burning lesion size and pain after 4 months of follow-up.

Conclusion:

For the treatment of OLP, turmeric, ashwagandha, and aloe vera can be useful as substitute topical medications, particularly for those who are not responsive to topical corticosteroids.
Realization of Urban Perception Art: Painting Expressions of Internet of Things Technologies in Urban Environments
Authors: Zhu Hong , Yao Lu
Published: May 2024

INTRODUCTION: With the continuous progress of urbanization, people's perceptions and experiences of the urban environment are increasingly concerned. Traditional forms of artistic expression can no longer fully meet people's needs for urban perception. Therefore, it is especially important to explore new possibilities of urban perception art with the help of modern technology, especially intelligent technology.OBJECTIVES: The main purpose of this study is to explore the feasibility and effectiveness of utilizing advanced technology for urban perception art expression. Through an in-depth understanding of the urban environment and the perceptual needs of urban residents, as well as existing technological means, artistic expressions that can present urban perceptions more intuitively and vividly are developed.METHODS: This study adopts a combination of field research and art practice. Through urban observation and questionnaire surveys, the subjective experience and needs of urban residents for urban perception were collected. Then, using digital painting and video technology, combined with the principles of perception psychology, urban perception works with artistic and technological senses were designed.RESULTS: A series of urban perception artworks were designed in this study, covering all aspects of urban life, including architectural landscapes, transportation scenes, and humanistic customs. These works enable viewers to perceive the urban environment in a more intuitive and immersive way through digital painting and video technology, as well as real-time data and perceptual feedback.CONCLUSION: By exploring new ways of artistic expression of urban perception, this study provides urban residents with a richer and deeper experience of urban perception. The application of digital painting and video technology, as well as the interaction and feedback with urban residents, opens up new possibilities for the development of urban perceptual art.
Analysis of Employment Competitiveness of College Students Based on Binary Association Rule Extraction Algorithm
Authors: Guo Lixia
Published: May 2024

Today, assessing competition among college students in the job search is extremely important. However, various methods available are often inaccurate or inefficient when it comes to determining the level of their readiness for work. Conventional techniques usually depend on simplistic measures or miss out on crucial factors responsible for employability. The challenging characteristics of such competitive employment of college students are the lower levels of perceived stress, financing my education, and crucial professional skills. Hence, in this research, the Internet of Things Based on Binary Association Rule Extraction Algorithm (IoT-BAREA) technologies have improved college students' employment competitiveness. IoT-BAREA addresses this situation using a binary association rule extraction algorithm that helps detect significant patterns and relationships in large amounts of data involving student attributes and employment outcomes. IoT-BAREA positions itself as capable of providing insights into features that highly mediate the employability levels among students. This paper closes this gap and recommends a new IoT-BAREA method to help increase accuracy and efficiency in evaluating student employment competitiveness. Specifically, this study uses rigorous evaluation methods such as precision, recall and interaction ratio to determine how well IoT-BAREA predicts students' employability.
Research on Fault Diagnosis Method of CNC Machine Tools Based on Integrated MPA Optimised Random Forests
Authors: Wang Xiaoyan
Published: May 2024

INTRODUCTION: Intelligent diagnosis of CNC machine tool faults can not only early detection and troubleshooting to improve the reliability of machine tool operation and work efficiency, but also in advance of the station short maintenance to extend the life of the machine tool to ensure that the production line of normal production.OBJECTIVES: For the current research on CNC machine tool fault diagnosis, there are problems such as poorly considered feature selection and insufficiently precise methods.METHODS: This paper proposes a CNC machine tool fault diagnosis method based on improving random forest by intelligent optimisation algorithm with integrated learning as the framework. Firstly, the CNC machine tool fault diagnosis process is analysed to extract the CNC machine tool fault features and construct the time domain, frequency domain and time-frequency domain feature system; then, the random forest is improved by the marine predator optimization algorithm with integrated learning as the framework to construct the CNC machine tool fault diagnosis model; finally, the validity and superiority of the proposed method is verified by simulation experiment analysis.RESULTS: The results show that the proposed method meets the real-time requirements while improving the diagnosis accuracy.CONCLUSION: Solve the problem of poor accuracy of fault diagnosis of CNC machine tools and unsound feature system.
Design of Intelligent Political Test Paper Generation Method Based on Improved Intelligent Optimization Algorithm
Authors: Wan Qing
Published: May 2024

With the development of artificial intelligence, computer intelligent grouping, as a research hotspot of political ideology examination paper proposition, can greatly shorten the time of generating examination papers, reduce the human cost, reduce the human factor, and improve the quality of political ideology teaching evaluation. Aiming at the problem that the current political ideology examination paper-grouping strategy method easily falls into the local optimum, a kind of intelligent paper-grouping method for political ideology examination based on the improved stock market trading optimisation algorithm is proposed. Firstly, by analyzing the traditional steps of political thought grouping, according to the index genus of the grouping problem and the condition constraints, we construct the grouping model of political thought test questions; then, combining the segmented real number coding method and the fitness function, we use the securities market trading optimization algorithm based on the Circle chaotic mapping initialization strategy and adaptive t-distribution variability strategy to solve the grouping problem of the political thought test. The experimental results show that the method can effectively find the optimal strategy of political thought exam grouping, and the test questions have higher knowledge point coverage, moderate difficulty, and more stable performance.
Improved Convolutional Neural Network Algorithm for Student Behavior Detection in the Classroom
Authors: Liu Yihua , Wang Weirong
Published: May 2024

The performance of the existing student classroom behavior detection model is affected by various aspects such as dataset, algorithm and height as well as the differences between different classrooms, and there are problems such as a single dataset, low accuracy and low efficiency. In order to improve the accuracy of student classroom behavior detection algorithm, this paper proposes a student classroom behavior detection method based on improved convolutional neural network algorithm. Firstly, the student behavior detection dataset is constructed, and the student classroom behavior detection technology scheme is designed; secondly, in order to improve the detection accuracy, the features are extracted by using the new jumping bi-directional paths, and the attention mechanism module is added at different positions to improve the path aggregation network; weekly, the embedding positions of the attention mechanism strategy are determined by analyzing multiple sets of experiments, and the proposed student classroom behavior detection algorithm's effectiveness and superiority.