bluuebunny/crossref_metadata_2025 huggingface dataset:
SOROTAN AWAL FALSAFAH ILMU ISLAM: PERMASALAHAN, PENSEJARAHAN, DEFINISI DAN SUMBER ILMU DALAM ISLAM
Authors: Mohd Nasir Amar Ismat , Mohd Salleh Norsaleha , Yama Phayilah , Soroni Mohd Khafidz
Published: July 2024

The post-modern age has discarded great narratives such as knowledge and truth which led to crisis of thought such as atheism, agnosticism and liberalism among Muslims. Among the causes surrounding crisis is the epistemological issues. Knowledge that is acquired through scientific methods only is considered valid which causes olther knowledge such as religious knowledge to be seen as ancient, old-fashioned, unscientific and incompatible with the development of the times. This study aims to analyze the philosophy of knowledge according to the Islamic perspective from the aspects of problems, historiography, definitions and sources of knowledge. The Islamic philosophy of knowledge that is centered upon the unity of revelation and reason can be an initial guide in facing the epistemic crisis within the post-modern era. This study uses the of content analysis methods towards books that bring together aspects of the philosophy of science. The study founds that the Islamic philosophy of knowledge to be integrated, comprehensive, and combines religio-philosophy based on the framework of the Quran. In addition, the philosophy of Islamic knowledge also covers a wide field of knowledge including matters related to divinity and religion.
Transplante Fígado-Rim em Monobloco: Solução Técnica para Sítio Ilíaco com Aterosclerose Avançada
Authors: Veloso Luiz Fernando , Angeli Bianca De Marco , Veloso João Pedro Donato , Veloso Mateus Donato
Published: July 2024

Objetivos: Relatar o primeiro caso de transplante duplo – fígado e rim – em monobloco como alternativa cirúrgica em paciente com aterosclerose avançada e calcificação extensa de vasos arteriais aortoilíacos. Métodos: As informações foram obtidas por meio de revisão do prontuário, entrevista com a paciente, registro de imagem dos métodos diagnósticos aos quais a paciente foi submetida e revisão da literatura. Conclusão: A técnica descrita pode representar uma alternativa eficiente e segura em circunstâncias nas quais a anastomose vascular, arterial ou venosa é impossibilitada por desafios anatômicos em decorrência de doença vascular prévia.
The relationship between auditor diversity and audit quality
Authors: Jalagonia David , Kopaliani Kakhi , Khubua Marine , Papaskua Iuri , Osiqmishvili Ana
Published: July 2024

The article determines that within audit occupation there exists gender inequality, which can be explained by such professional requirements for an auditor as an analytical mindset and strong mathematical skills, which are stereotypically attributed to men solely. In the scientific literature, there are two diametrically opposed positions regarding the relationship between audit diversity and audit quality. The first position argues that a higher level of diversity among auditors corresponds to a higher level of audit quality, while the second one confronts it. The aim of this study is to examine these positions and prove or disapprove of them. The leading research methods in this article are surveys and questionnaires used to determine factors that influence the variables and the importance of considering these factors in order to improve audit quality in auditor groups. The authors sought to contribute to the existing body of knowledge on the topic by conducting a comprehensive analysis of the potential advantages and drawbacks of diverse audit teams. The paper presents the findings of the authors’ research, which examines the complex relationship between auditor diversity and audit quality. The conducted research yielded results that suggest that improving audit quality in auditor groups requires consideration of motivational and moral-ethical responsibility variables, rather than group characteristics such as diversity.
Assessment of methane emissions from landfills in five major cities of Algeria: comparative analysis of calculation models and study on methane-to-electricity conversion
Authors: Safia Abdelli Islam , Meriem Toumi , Fatiha Abdelmalek , Ahmed Addou
Published: July 2024

Landfills are commonly used for managing municipal solid waste and generating energy. However, accurate estimations of landfill gas, thorough analysis of its energy potential, and comprehensive economic assessments are essential for the successful implementation of a landfill project. The municipal solid waste (MSW) generation rate in Algerian cities is experiencing an exponential increase alongside the growth of urbanization and commercial activities. Various waste-to-energy technologies have been explored in the past, but anaerobic digestion stands out as the preferred option due to its eco-friendly nature and simple design. This article presents a study on the potential of generating electrical energy from methane produced in landfills in five major cities in Algeria. Using various models to assess methane quantities, the study highlights a rising trend in methane production over the years, with peaks expected between 2032 and 2047 depending on the regions. The findings suggest that methane can be harnessed as an economical energy source, providing a sustainable solution to meet the growing energy needs of these regions. Additionally, the article underscores the importance of effective landfill management to minimize environmental impacts and maximize the economic benefits of this renewable energy source. In conclusion, this study provides crucial insights to guide public policies and private initiatives aimed at promoting the capture and utilization of landfill methane as a solution to reduce greenhouse gas emissions and facilitate a transition to a greener economy in Algeria, also it will aid local authorities in incorporating considerations of the potential for energy recovery in the study regions, as well as in other areas of Algeria, into their long-term waste management plans.
On the qualitative study of solutions of a class of nonlinear abstract dynamic equations on time scales and applications
Authors: Bouaoud Safa , Neggal Bilel , Boukerrioua Khaled
Published: July 2024

The theory of dynamic equations on time scale was introduced in [7, 8] whose main objective is to provide a unified approach to continuous and discrete analysis. The calculus on time scales and dynamic equations on time scales have applications in any field that requires simultaneous modeling of continuous and discrete processes, because they bridge the divide between continuous and discrete aspects of processes. Perturbation theory is a pertinent discipline for the applications of time scale dynamics which is a compilation of methods systematically used to evaluate the global behavior of solutions of dynamical systems with occurrence on non uniform domains. One of the analytic methods of the perturbation theory was referred to integral inequalities to quest some type of stability. In the last few years, the search on qualitative properties of dynamics was directed to the time scale integral inequalities using diverse techniques and some significant results were obtained. Some of the original references on this approach include [1,2,3,4,5,9,10,11,12,13,14,17,22,24]. In this work, we study the h-stability problems of some classes of dynamic equations as an extension of exponential stability. We derive some sufficient conditions that guarantee h-stability of perturbed dynamic equations using Grönwall- typ integral inequality approach and Lyapunov function approach. We prove under certain conditions on the linear and nonlinear perturbations that the resulting perturbed nonlinear abstract dynamic equation still acquired h stable, if the associated dynamic equation has already owned this property. Finally, an numerical example is introduced to illustrate the applicability of the main results.
Enhancing doubly-fed induction generator performance in wind energy systems using intelligent control
Authors: Chandad Abdelmoumen , Hamouda Messaoud , Bouzidi Mohammed , Ouledali Omar
Published: July 2024

This study investigates the optimization of doubly-fed induction generator (DFIG) performance in wind energy systems using intelligent control techniques. The research focuses on two primary control methods: fuzzy logic and artificial neural networks, complemented by neural space vector modulation (NSVM) for enhanced power quality. The paper presents a comprehensive model of the wind energy conversion chain and vector control of the DFIG, with particular emphasis on improving active and reactive power control. Simulation results demonstrate the effectiveness of both fuzzy logic and neural network systems in tracking power changes. However, the neural network-based control exhibits superior performance in reducing current and electromagnetic torque ripples. a key aspect of the study is the total harmonic distortion (THD) analysis of the source current. the neural network system achieves a lower THD value (0.11%) compared to the fuzzy logic system (0.32%), indicating better power quality. additionally, a robustness test involving alterations to generator parameters reveals the fuzzy logic system's greater adaptability to these changes. the research also explores the implementation of space vector modulation (SVM) based on neural networks (NSVM) to replace conventional switching pulse-width modulation (PWM) techniques. This approach significantly improves power quality and enhances performance in the presence of machine parameter variations. The study concludes by highlighting the potential of these intelligent control techniques in improving wind energy system performance. it provides valuable insights for developing more efficient and reliable control systems for DFIG in wind energy applications. The findings contribute to ongoing efforts to enhance renewable energy efficiency and reliability, potentially accelerating the adoption of wind power in the global energy mix.
Meta-Analysis: Impact of AMF Colonization on Allium Species
Authors: Pabitra Aryal
Published: July 2024

With available data, this meta-analysis assessed the effects of Arbuscular Mycorrhizal Fungi (AMF) inoculation on wellresearched Allium species related to the under-researched Allium tricocum species. The overarching goal was to synthesize findings from published research to develop hypotheses for future investigation into the role of AMF inoculation on Allium tricocum. Three Allium species were evaluated across ten studies. Four parameter categories were assessed. Parameter categories included a) plant mass, plant size, and yield b) mineral composition c) elemental composition d) phosphorus uptake Two treatment comparison categories were constructed for each parameter category: a) Allium species inoculated with AMF b) uninoculated (control). Data were presented for each parameter in % increase with control treatment. Allium species inoculated with AMF increased most parameter categories compared to uninoculated controls, except for a few element composition parameters (in a saline environment). They also had the highest average percent increase compared to uninoculated controls. The meta-analysis indicated that the inoculation of AMF on Allium species is closely related to Allium tricocum and generally increases growth, yield, and mineral composition, but it is dependent on the Allium species and AMF species used. Areas for future research of Allium tricocum identified through this analysis include whether AMF inoculation could help better growth of Allium tricoccum? if AMF inoculation helps in early maturation of Allium tricoccum? is the impact of AMF changes with the annual cycle for the growth and survival of Allium tricoccum? And does AMF inoculation help transplanted Allium tricoccum for adaptation to a new environment?
Comunidade de prática e a gestão do conhecimento no contexto escolar: pré-conselho de classe por meio de ferramentas Google
Authors: Periotto Tania Regina Corredato , Ortiz Sandra
Published: July 2024

Diante das constantes mudanças enfrentadas pela sociedade, na maioria das vezes ligadas aos avanços tecnológicos, a escola convive com o grande desafio de aprimorar as práticas pedagógicas para atender as demandas do contexto escolar. Como recurso para facilitar a gestão das atividades pedagógicas, têm-se as Comunidades de Prática (CoPs), que se apresentam como potencial ferramenta que podem ser incorporadas aos processos de compartilhamento e armazenamento do conhecimento. Nesse sentido, o objetivo deste trabalho é demonstrar como as CoPs, por meio do Google Drive, podem subsidiar o professor da Educação Básica no compartilhamento e armazenamento do conhecimento em sua atividade pedagógica, visando melhorar o desempenho dos estudantes e, consequentemente, o processo de ensino-aprendizagem. A pesquisa de natureza aplicada com caráter exploratório e descritivo, com abordagem mista, conta com levantamento bibliográfico e estudo de caso sobre a ocorrência do Pré-Conselho de Classe por meio do Google Drive, caracterizando-se como uma CoP. O universo da pesquisa envolveu o quadro de docentes de um colégio estadual da cidade Maringá/PR, Brasil, escola pública de referência na cidade.
Órfãos do feminicídio na escola: do luto ao acolhimento como forma de resistência
Authors: Amaral Thalita Fernanda Moreira Cardoso , Eduvirgens Jéssica Rodrigues Martins , Castro Raimundo Márcio Mota de
Published: July 2024

O objetivo do presente artigo é discorrer sobre a importância do acolhimento dos órfãos por feminicídio e apresentar a escola como possibilidade de discussão e acolhimento dos enlutados por morte decorrente do feminicídio. Sendo utilizado levantamento bibliográfico dos temas: feminismo, feminicídio, políticas públicas vigentes e o papel da escola frente a esta realidade. Tendo em vista que a especificidade de morte por feminicídio pode gerar grandes impactos nos sujeitos enlutados, destaca-se a importância de discutir sobre o papel essencial da escola de acolher os órfãos partícipes da escola. Os achados são apresentados ao longo do artigo e evidenciam a urgência de elaboração de políticas públicas eficazes para a proteção e garantia de direito à vida das mulheres, políticas públicas que sejam capazes de enxergar os sobreviventes do feminicídio: os órfãos e a necessidade da capacitação dos profissionais da educação para lidarem com estes sobreviventes que participam da escola e que necessitam do acolhimento especializado para a elaboração e integração do luto a sua história de vida. O presente artigo também possuí a finalidade de colaborar com o campo acadêmico, com os atuais e futuros estudos sobre as temáticas em questão.
Utilização do extrato de produtos naturais da região do Pantanal-MS para obtenção de inibidores de corrosão verde
Authors: Schmitzhaus Tobias Eduardo , Romão Kleiton de Mello , Santos Severino Teodoro dos , Schmitzhaus Wagner Cristiano , Simoni Leonardo
Published: July 2024

Os inibidores de corrosão são substâncias essenciais na mitigação dos efeitos nocivos da corrosão em ambientes industriais. No entanto, muitos desses agentes convencionais apresentam elevada toxicidade, resultando em sérios impactos ambientais e riscos para a saúde humana. Além disso, o custo associado ao uso desses inibidores pode ser significativo para as empresas. Diante desse contexto, a pesquisa tem se voltado cada vez mais para a busca de alternativas mais sustentáveis e seguras, como os inibidores de corrosão de origem natural, também conhecidos como inibidores "verdes". Os inibidores verdes são compostos por extratos vegetais que demonstram capacidade de reduzir a taxa de corrosão dos metais, principalmente pela diminuição da dissolução anódica. Esses extratos têm despertado interesse devido à sua eficácia em proteger os materiais metálicos contra a corrosão, ao mesmo tempo em que oferecem vantagens ambientais e de saúde pública. Neste estudo, foi investigado o potencial de um inibidor verde obtido a partir de extratos de óleo da amêndoa da palmeira bocaiuva (Acrocomia aculeata). A escolha desse extrato se baseou em sua disponibilidade, biodegradabilidade e possíveis propriedades inibidoras de corrosão. O principal objetivo foi avaliar a eficácia desse extrato como agente inibidor em meio ácido, especialmente em relação ao aço carbono, um material comum em muitas aplicações industriais. A análise da eficácia do inibidor foi realizada por meio de ensaios eletroquímicos, que incluíram a análise de curvas de polarização e do potencial de circuito aberto. Os experimentos foram conduzidos em uma solução corrosiva de ácido clorídrico 1 mol.L-1, e os resultados indicaram uma eficiência de inibição anódica considerável, atingindo cerca de 80% para uma concentração do extrato de 2 ml.L-1. Esses resultados destacam o potencial promissor dos inibidores de corrosão verdes, não apenas em termos de eficácia de proteção dos materiais metálicos, mas também em relação aos benefícios ambientais e de saúde associados à sua utilização. O desenvolvimento e a aplicação desses inibidores representam uma contribuição significativa para a busca por práticas mais sustentáveis na indústria.
Análise de ferramentas para auxiliar a fiscalização tributária a detectar fraudes estruturadas e monitorar real-time o trânsito de mercadorias: estudo de caso
Authors: Shidomi Vera Lucia Reiko Yoshida , Imoniana Joshua Onome
Published: July 2024

A fiscalização tributária é um assunto conhecido, porém pouco se fala sobre a atuação do auditor fiscal do ICMS no trânsito de mercadorias e de que forma são concebidas e implementadas as ferramentas tecnológicas para mitigar riscos de controle evitando assim fraudes fiscais de apropriação indébita de tributos. Esse estudo tem como objetivo apresentar a narrativa de como ocorreu o processo de desenvolvimento de ferramentas específicas para implantar controles visando munir o fiscal de informações efetivas no combate à sonegação. Considerando a Teoria da Legitimação, existe um acordo entre os contribuintes e o fisco sobre o adequado atendimento a legislação do ICMS, porém para garantir que esse acordo seja atendido é fundamental a utilização dos controles sistêmicos. O estudo de caso é exploratório utilizando como fonte de evidência a observação do participante (auditor fiscal). O resultado da parceria entre auditores experientes na área fiscal e um auditor experiente em tecnologia da informação já trouxe diversos benefícios palpáveis. A integração entre todos os auditores (experientes ou não) na utilização de uma única ferramenta desenvolvida de acordo com suas necessidades gerou uma forma padronizada na forma de trabalho, trazendo maior agilidade ao trabalho, pois as informações necessárias para análise e tomada de decisão agora estão a seu alcance no celular e não mais do outro lado da estrada em aplicações cliente-servidor ou mainframe. As informações possuem maior acurácia e tempestividade, pois antes de realizar a abordagem, o auditor já está munido das informações que ele precisa para tomada de decisão. A contribuição desse estudo é apresentar mecanismos tecnológicos desenvolvidos para garantir a legitimidade de que a legislação, no caso do ICMS, está sendo atendida através de controles sistêmicos. É o início do processo da automatização dos controles, agora é possível evoluir e mitigar as fraudes de apropriação indevida de tributos e a concorrência desleal.
PRIMARY BREAST LYMPHOMA: A CASE REPORT
Authors: HAFEEZ T , ATTA MB , IMTIAZ K , AQEEL S , AHMED M , ASHRAF A , RUBEET A , RANDHAWA I
Published: July 2024

Hematological malignancies, such as lymphomas, rarely involve breast tissues, comprising only 0.04% to 0.7% of all breast neoplasms. This rarity may be attributed to the scarcity of lymphoid tissue in the breast. Primary breast lymphomas pose a diagnostic challenge due to nonspecific imaging findings that can overlap with other breast tumors. This article provides a case study and literature review on primary breast lymphoma.
Physical Exercise at High Altitudes Increases Erythropoietin Hormone Secretion: A Systematic Review
Authors: Ayubi Novadri , Wibawa Junian Cahyanto , Aljunaid Mohammed
Published: July 2024

Objective: To investigate and quantify the mechanism by which exercise at high altitude increases the release of the erythropoietin hormone. Methods: This study examines many journal databases, such as Pubmed, Embase, Web of Science, and Scopus. Among the criteria considered in this study were articles published within the last five years, as well as those on erythropoietin, physical activity, and high-altitude training. We only rejected publications published in anonymous journals for inclusion in this analysis. We successfully identified 2510 papers in total using the Embase, Web of Science, Pubmed, and Scopus databases. We have looked at and reviewed approximately ten papers that address the requirements for this systemic breakthrough. We developed standard operating procedures for the current investigation using the Preferred Reporting Items for Systematic and Meta-Analysis (PRISMA). Results: The systemic analysis reveals that physical activity at altitude elevates the hormone erythropoietin, leading to an increase in erythrocyte count. Furthermore, it can improve physical performance by increasing oxygen delivery to cells, thereby potentially triggering energy system function. Conclusions: Anaerobic physical exercise at an altitude of 4000-5000 m for a minimum of four weeks can have a real impact on increasing levels of the hormone erythropoietin. For further research and analysis, it is advisable to find out what genes trigger the release of the hormone erythropoietin.
ANALISIS FAKTOR-FAKTOR YANG MENENTUKAN KINERJA PERUSAHAAN MANUFAKTUR YANG TERDAFTAR DI BURSA EFEK INDONESIA PERIODE 2016-2021
Authors: Marsana Marsana , Karyawati Danik , Sunarya Sunarya
Published: July 2024

This research aims to investigate the influence of the Current Ratio (CR) on the performance of manufacturing companies listed on the Indonesia Stock Exchange (IDX). The study was conducted on manufacturing companies listed on the IDX for the period 2016-2021. The data used in this research were obtained from the Indonesia Stock Exchange office, located at Jalan P. Mangkubumi Number 111, Cokrodiningratan, Jetis, Yogyakarta City, along with supporting websites such as www.idx.co.id and finance.yahoo.com. The research was conducted from January 2022 until completion. The analysis results indicate that the CR variable has a probability rounded to 0.05 and a regression coefficient of 0.007062. The CR variable influences the 5% significance level, with a probability value of CR being 0.05, which is equal to 0.05. This indicates that the CR variable individually has a significant influence on the performance of manufacturing companies listed on the IDX. The regression coefficient value indicates that CR has a positive effect on company performance. This means that an increase of 1% in CR will lead to a 0.007% increase in the performance of manufacturing companies listed on the IDX.
STRATEGI PEMASARAN TERHADAP K-STREET BYUNDONG DALAM MENGHADAPI PASAR DI ERA PANDEMI COVID-19 DI KOTA PURBALINGGA
Authors: Yeristha Asrillia Auriel , Rohmah Fitri Nur , Mawarni Mita , Prasetyani Oki Dwi
Published: July 2024

MSMEs are trading businesses managed by individuals who have economic businesses with criteria that have been applied by law. Even in terms of management, it still has a close relationship with the community's economy. However, around the beginning of March 2020, Indonesia was hit by an outbreak of a disease called Covid-19 (Corona Virus). Corona virus is a contagious disease. The global Covid-19 pandemic certainly has an impact on various sectors, especially in the economic sector. This study aims to examine the strategy of K-Street ByungDong in dealing with the market in the era of the Covid-19 pandemic and find out the efforts made by K-Street ByungDong in overcoming marketing constraints during the Covid-19 pandemic. The research method used in this study is a descriptive qualitative method. In this study, the object of research is the strategy of K-Street ByungDong in dealing with the market in the era of the Covid-19 pandemic. Data analysis methods used are interviews and documentation. Based on the results of the study, it shows that digital marketing is effectively carried out as a marketing strategy in dealing with the market in the era of the covid-19 pandemic
PENGARUH PENJUALAN DAN HARGA POKOK PENJUALAN TERHADAP LABA BERSIH
Authors: Priyadi Joko , Michael  , Wardana Aditya Wisnu
Published: July 2024

This study aims to determine, explain, and analyze the effect of Sales and Cost of Goods Sold on Net Profit in manufacturing companies in the basic and chemical industrial sectors of the wood and processing sub-sectors listed on the Indonesia Stock Exchange in 2018-2020. The number of samples taken is 4 (four) wood and processing sub-sector companies from 5 populations of wood and processing companies that have published complete annual financial reports during the study period. The sampling technique used is purposive sampling. The research method used in this study is a quantitative verification method. Based on the results of the research data analysis, the results obtained where; sales have a significant positive effect on net income. and Cost of Goods Sold in the partial test has a positive effect on net income, in the simultaneous or concurrent test, Sales and COGS are known to have a significant effect on net income.
Enhancing Healthcare Data Classification: Leveraging Machine Learning on ChatGPT-Generated Datasets
Authors: Basheer Basheer ,   Al-Imam Al-Kadhum College for Islamic Science University, Iraq,   Mustansiriah University, Department of Mathematics, Iraq, Obaidi Murhaf
Published: July 2024

With the large-scale language methods namely ChatGPT, there is a chance to explore the use of machine learning (ML) methods on ChatGPT-generated data for classifying healthcare data. Healthcare data classification gains more significance in extracting and organizing useful insights from the huge volume of medical data available. The ChatGPT-generated data has realistic and different healthcare-based text datasets that can be applied to training classification methods. ML approaches include supervised learning methods as support vector machines (SVMs), and random forests (RF), which can be implemented for classifying the healthcare data. The methods were trained on the ChatGPT-generated data that can be carefully validated and labelled with suitable classes related to the healthcare field. With this motivation, this article presents an automated healthcare data classification-using barnacles mating optimizer with a pyramid neural network (AHDC-BMOPNN) technique. The presented AHDC-BMOPNN technique examines the healthcare data effectually using an ML model with a feature selection process. Primarily, the AHDC-BMOPNN technique exploits min-max data normalization for scaling the input dataset. In addition, the butterfly optimization algorithm-based feature selection (BOA-FS) method is deployed for the selection of optimum feature subset. In this work, the PNN algorithm was utilized for the classification of medical data. Ultimately, the BMO-based hyperparameter tuning process takes place to boost the overall classifier results of the PNN technique. The empirical findings of the AHDC-BMOPNN approach was validated on ChatGPT generated dataset. The simulation values highlight that the AHDC-BMOPNN method and the diverse healthcare text data generated by ChatGPT enhance the ability to extract valuable insights and organize medical information effectively.
Quantum Sparrow Swarm Optimization with Deep Learning Enabled Deception Detection on Facial Micro Expressions
Authors: admin admin ,   Umm Al-Qura Univerity, Mekka, Saudi Arabia
Published: July 2024

Deception detection means finding whether an individual is lying or being deceptive depending on cognitive cues, and various behavioural, or physiological. It is a significant domain of research with applications in social psychology, law enforcement, and security. Deception detection relevant to microexpressions includes examining these subtle facial cues for determining whether an individual is being deceptive or lying. Microexpressions can deliver significant cues to detect deception. Deep learning (DL) and Machine learning (ML) models were utilized for finding micro-expressions and are trained for differentiating deceptive statements from genuine ones. Still, it necessitates a diverse and large dataset of video recordings in addition to careful tuning and pre-processing of the DL approach. So, this article presents an Automated Deception Detection on Facial Microexpressions using Improved Sparrow Swarm Optimization with Deep Learning (ADDFM-ISSODL) method. The proposed ADDFM-ISSODL algorithm examines facial micro-expressions effectively for detection of deceptive behaviour. To complete this, developed ADDFM-ISSODL model uses a Gaussian filtering (GF) approach for pre-processing. Besides, ADDFM-ISSODL technique employs MobileNetv3 model for feature extraction and the hyper parameter tuning procedure performed using ISSO algorithm. The ISSO approach was designed by the integration of the standard SSO approach with the quantum evolutionary algorithm (QEA). For deception detection, a probabilistic neural network (PNN) classifier was employed. At last, grasshopper optimization algorithm (GOA) was implemented for parameter tuning of PNN method. The performance validation of ADDFM-ISSODL system tested utilizing facial expression dataset. The simulation outcome stated the greater results of ADDFM-ISSODL algorithm over other methodologies.
Optimal Deep Learning-Based Image Classification for IoT-Enabled UAVs in Remote Sensing Applications
Authors: Sanjar Sanjar ,   Tashkent State University of Economics, Tashkent, Uzbekistan,   Tashkent State University of Economics, Tashkent, Uzbekistan, Sulaym Samandarboy
Published: July 2024

Unmanned Aerial Vehicles (UAVs), together with Internet of Things (IoT) technology, have emerged as robust tools for remote sensing (RS) and data collection in different sectors, including environmental monitoring, agriculture, and disaster management. The incorporation of data from UAVs with IoT sensors on the ground can provide a holistic view of the environment, improving the quality of input for image classification. Deep learning (DL) models-based image classification is a key component of IoT-assisted UAVs, transforming them from data collection tools into intelligent decision-making platforms. Especially, Convolutional Neural Networks (CNNs) can automatically recognize objects, patterns, and anomalies in images captured by UAVs. Therefore, the study presents an automated image classification with the Tyrannosaurus optimization algorithm using deep learning (AIR-TROADL) method on the IoT-aided UAV network. The AIR-TROADL technique aims to examine the UAV images for the identification and classification of images into distinct categories. In the projected AIR-TROADL method, an enhanced ShuffleNet model is exploited for feature extraction. Besides, the hyperparameter tuning of enhanced ShuffleNet model can be performed by using TROA, which in turn boosts the classification performance. Finally, the classification of images takes place using the attention-based gated recurrent unit (AGRU) model. A series of simulations have been conducted to exhibit the promising outcome of the AIR-TROADL technique. The comparative outcomes highlighted that the AIR-TROADL method reaches high efficiency over its recent approaches in terms of distinct measures.
Harnessing Single-Valued Linguistic Complex Neutrosophic Set based Arabic Sentiment Classification on Natural Language Processing
Authors: Aigul Aigul ,   Department of English Philology and Intercultural Communication of Elabuga Institute, Kazan Federal University, Kazan, 420008, Russia,   Department of English Philology and Intercultural Communication of Elabuga Institute, Kazan Federal University, Kazan, 420008, Russia,   Department of English Philology and Intercultural Communication of Elabuga Institute, Kazan Federal University, Kazan, 420008, Russia,   Department of Sports Activities, Urgench State University, Urgench, 220100, Uzbekistan,   Department of Information Technology, VR Siddhartha Engineering College(A), Siddhartha Academy of Higher Education (Deemed to be University), Vijayawada, India, Yarullina Alfiya , Akhmetova Leysan , Shamuratova Barno , Lydia E. Laxmi
Published: July 2024

Neutrosophic logic (NL) goes further by introducing a third component: indeterminacy. Each logical proposition in NL belongs to three degrees: truth (T), indeterminacy (I), and false (F), each taking value within the range of zero and one. This allows the processing and representation of uncertain, incomplete, and inconsistent data in a superior way. NL finds it beneficial in partially contradictory, partially known, and partially unknown scenarios, it becomes an effective instrument for applications in fields such as information fusion, artificial intelligence, and data analysis, where logical framework might be unsuccessful in handling the nuances and complexities of real-time data. Recently, Arabic sentiment analysis has become a hot research topic, which mainly intends to recognize sentiments that exist in Arabic social media. Therefore, this study introduces a Single-Valued Linguistic Complex Neutrosophic Set based Arabic Sentiment Classification (SVLCNS-ASC) technique on NLP applications. The presented SVLCNS-ASC technique undergoes Arabic data pre-processing and Glove word embedding process. For sentiment recognition, the SVLCNS-ASC technique applies the SVLCNS model, which enables to identification of various kinds of sentiments. At last, the performance of the SVLCNS model can be boosted by the use of artificial bee colony (ABC) based parameter-tuning approach. The results of the SVLCNS-ASC system has been studied on Arabic database. The experimental values indicate the supremacy of the SVLCNS-ASC approach compared to recent models.
Integrating Transfer Learning with Neutrosophic Weighted Extreme Learning Machine for Violence Detection in Smart Cities
Authors: Nigora Nigora ,   Department of Management and Marketing, Urgench State University, Urgench, 220100, Uzbekistan,   Department of Economics and Management of Elabuga Institute, Kazan Federal University, Kazan, 420008, Russia,   Institute of Digital Technologies and Law, Kazan Innovative University named after V. G. Timiryasov, Kazan, 420111, Russia,   Department of Industrial Electronics and Lighting Engineering, Kazan State Power Engineering University, Kazan, 420066, Russia, Bakhvalov Sergey , Denisovich Veronika , Zakieva Rafina
Published: July 2024

Neutrosophic logic extends conventional and fuzzy logic (FL) by integrating the concepts of indeterminacy, truth, and falsity, enabling for a further extensive management of uncertainty. In classical binary logic, a statement can be either true or false. FL extends this by adding degree of truth, where a statement is partially true or false. The smart city technology shown to be an effective solution to the problems regarding improved urbanization. The practical applications of a smart city technology to video surveillance relies on the ability of processing and gathering large quantities of live urban data. Violence detection is considered as a major challenge in smart city monitoring. The required computational power is substantial due to the large volume of video data gathered from the extensive camera network. As a result, the algorithm based on handcrafted features utilizing video and image processing fails to provide a promising solution. Deep Learning (DL) and Deep Neural Networks (DNNs) models are more reliable to handle these data. In this study, we introduce a Transfer Learning with Neutrosophic Weighted Extreme Learning Machine for Violence Detection (TL-NWELMVD) technique in smart cities. The TL-NWELMVD technique aims to recognize the presence of the violence in the smart city environment. In the TL-NWELMVD technique, the features can be extracted using SE-RegNet model. To enhance the performance of the TL-NWELMVD technique, a hyperparameter optimizer using monarch butterfly optimization (MBO) is involved. Finally, the NWELM classifier is applied for the identification of violence in the smart city environment. To investigate the accomplishment of the TL-NWELMVD technique, a widespread investigational outcome is involved. The simulation results portrayed that the TL-NWELMVD technique gains better performance compared to other models.
Knowledge of Risk Factors Related to Osteoporosis among Women in Hospitals
Authors: Hanaa Hussein Mukhlif
Published: July 2024

The study aims to determine women's knowledge of some risk factors contributing to osteoporosis and determine the connection between the knowledge and the women's demographic data. A descriptive study design was used. One hundred thirty women participants were selected as convenience samples from Mosul city hospitals. Data was collected from 15th January to 20th March 2024. A questionnaire was constructed from two parts six as demographic information and ten questions about women's knowledge of risk factors of osteoporosis. The study results were found through descriptive statistics and inferential statistical. Most women (63.1%) know osteoporosis risk factors. With a significant relationship between women's knowledge and level of education (0.048), while no significant with other variables. The study concludes that the participating women's understanding of the risk factors for osteoporosis was acceptable, and there related to their educational level. The study recommended increasing women's risk factors for osteoporosis and prevention strategies.
Knowledge of Therapeutic Communication among Nurses in Maternal Wards at Hospital
Authors: Hanaa Hussein Mikhlif
Published: July 2024

The study aimed to assess nurses' knowledge of therapeutic communication in maternal wards at Mosul Hospitals. A descriptive study was designed and selected of a purposive sample of 100 nurses. The tool consists of demographic data from six variables and therapeutic communication from twelve questions with three answers. The study was performed in four hospitals from November 2023, April 2024. A statistical analysis uses the SPSS (26) to determine nurses' knowledge of therapeutic communication among nurses.the study results were found through descriptive statistics. Most of nurses (65%) represented moderate knowledge among nurses. A study finds a relationship between age, experience years, with their knowledge. More than half of nurses have an average knowledge of therapeutic communication. There is need to increase nurses' knowledge about therapeutic communication by providing educational program according therapeutic communication with patients.
Assessment of Health Behaviors Related to Nutrition of Pregnant Women in Hospitals
Authors: Hanaa Hussein Mukhlif
Published: July 2024

This study aims to assess the behaviors of pregnant women regarding their nutritional status in hospitals within Mosul City to promote optimal nutrition during pregnancy. The study used a descriptive design from December 2023 to April 2024. A purposive sample of pregnant women who visited hospitals in Mosul was collected. The study tool consisted of demographic data about pregnant women, six questions about women's health histories, and seven questions about health behaviors related to nutrition, with four choices for each question. And eating meat during one week. Seven experts measured the tool and its reliability (0.81). Most of the women (63.6%) reported taking supplements, and (66.4%) were in the third trimester. A small percentage of women (15.6%) reported having a deformity. The majority of women (81.6%) reported having visited a healthcare center. The majority of women (72.8%) had 1-3 pregnancies. Most pregnant women never eat meat, fish, or dairy during the week. The study revealed that a significant number of pregnant women in the sample reported taking supplements and eating meat types and dairy are lower. The study recommended appropriate nutritional guidance be provided to pregnant women in health centers.
Peran Sistem Informasi dalam Transformasi Bisnis Digital
Authors: Nugroho Mahendra Adhi , Mirani Erna , Arianisari Septiningdyah
Published: July 2024

Digital transformation is a must for companies in facing the competitive business era. Information Systems has a role in Digital Business Transformation by emphasizing the importance of efficient information system integration. This study uses a qualitative method with an analytical approach and literature study. Data is taken from various source searches such as books, scientific journal articles, and research reports The appropriate sources will be analyzed against discussions related to the role of information systems in the digital transformation of businesses in companies. Data analysis was carried out qualitatively consisting of data reduction, data presentation, and conclusion drawn. The results of the analysis show that information systems play a key role in managing operations, improving individual performance, and supporting the company's strategic decisions. In the context of digital transformation, the integration of people/employees, business, and technology components is an important factor in optimizing the benefits of digitalization. Strong leadership is needed to change the company's culture to be customer-oriented and able to adapt to changing market needs. By understanding the role of information systems and the integration of digital transformation components, companies can improve operational efficiency, respond to market changes more dynamically, and create added value for customers
Strategi Digital Leadership untuk Mendorong Innovation Work Behaviour di Lembaga Keuangan Koperasi Simpan Pinjam
Authors: Reni Reni , Renaldi  , Amri  , Akhmad Dahlan  , Ahmad Muktamar
Published: July 2024

This study aims to identify digital leadership strategies that are effective in improving employees' work innovation behavior at Sinar Murni Banten Savings and Loan Cooperative. Using a quantitative approach with survey techniques, data was collected from 100 cooperative employees who have at least one year of work experience and are involved in the use of digital technology in their daily work. The results showed that digital leadership has a significant influence on employees' creativity, proactivity, and ability to implement new ideas. Regression analysis revealed that digital leadership strategies contributed 37% to the variability of employees' innovative work behavior. Leaders who integrate digital technology in their managerial strategies can encourage employees to be more creative and proactive in completing their tasks. In conclusion, an effective digital leadership strategy can improve operational efficiency and create added value for cooperatives through the development of employee work innovation behavior. This research suggests that cooperatives should continue to develop technological infrastructure, initiatives to face challenges and capitalize on opportunities in the digital era
The Role of Human Resource Education: An Essential Driver in Advancing Economic Progress through Entrepreneurship Exploration
Authors: Hanif Muh , Ukar Kurweni , Permana Budi
Published: July 2024

Education is considered the primary foundation for economic development. Through education, individuals acquire the skills and knowledge necessary to effectively participate in the global economy. Entrepreneurship plays a crucial role in driving the economy through job creation, enhanced competition, and innovation. Entrepreneurship education can enhance individuals' abilities to start and manage their own businesses. This research aims to explore how human resource education can serve as an essential driver in advancing economic progress through entrepreneurship exploration. This study is a literature review using a qualitative approach with descriptive analysis. Data were gathered from articles published on Google Scholar between 2013 and 2024 through keywords HR Education, Economic Progress, Entrepreneurship. The study results indicate that human resource education plays a crucial role in driving a country's economy through harnessing entrepreneurial potential. Education is not only about transferring knowledge but also shaping character, skills, and attitudes that support innovation and competitiveness. In an increasingly interconnected global context, education also serves as a bridge between local innovation and the global market, creating an inclusive and sustainable environment for economic growth
Dampak Model Pembelajaran Kooperatif Think, Pair and Share (TPS) Terhadap Hasil Belajar Matematika Siswa Kelas VII SMP PGRI 3 Larangan Kota Tangerang
Authors: Jannah Miftahul , Somawati Somawati
Published: July 2024

The purpose of this study is to determine the impact of the Think Pair and Share (TPS) cooperative learning model on the mathematics learning outcomes of Grade VII junior high school students at PGRI 3 Larangan Junior High School, Tangerang City. This type of research is a pseudo-experiment using a purposive sampling technique. The data collection technique used is a test technique. The collected data was analyzed using a t-test with a significance level of α = 0.05. Based on the results of data analysis, it is known that the calculation of the t-test post-test can be concluded that t calculates > t table, which is 2.281 > 1.67 which has an impact on the mathematics learning outcomes of students given the TPS learning model. This shows that the learning outcomes of the TPS learning model are higher than the Student Team Achievement Devision (STAD) learning model.
Problem Based Learning Berbantuan Domino untuk Pembelajaran Numerasi Sekolah Dasar
Authors: Yustitia Via , Kusmaharti Dian
Published: July 2024

Numeracy is very important for students to master in the 21st century. Numeracy means applying numerical and mathematical concepts. The fact that the applied learning is still not effective at SDN Gayungan II/423 Surabaya. The purpose of this study was to find out that there was no effect of domino card-assisted Problem Based Learning on student numeracy. This type of research uses quantitative research with experimental methods. The design of this study was a nonequivalnt posttest-only control design. The population in this study were all grade III students at SDN Gayungan II/423 Surabaya, totaling 44 students. Through cluster random sampling, a sample of class III B was selected as the experimental class and class III A as the control class. Data collection techniques through tests. The data analysis technique used is a statistical test consisting of a normality test, homogeneity test, and hypothesis testing using the t-test.  The results of the study showed that there was an influence of Problem Based Learning assisted by domino cards on the numeracy of class III SDN Gayungan II/423 Surabaya.
Evaluasi Efektivitas Program Pembelajaran Jarak Jauh di Sekolah Menengah Atas pada Masa Pandemi Covid-19
Authors: Iqbal Muhammad , Marsyela Marsyela , Marsyeli Marsyeli , Hasanah Uswatun , Br Lubis Melati , Khofifah Siregar Nur
Published: July 2024

This research aims to describe and explain literature studies regarding the concepts of evaluation, effectiveness, and distance learning during the COVID-19 pandemic. Evaluating the effectiveness of distance learning programs in high schools during this period is particularly relevant due to the significant changes in teaching methods. This study employs a library research method, involving a comprehensive review of books and journal articles. The research process includes collecting articles, reducing and analyzing them, and drawing conclusions. Findings indicate that assessing the effectiveness of distance learning programs is crucial to determine the extent to which learning objectives were achieved during the COVID-19 pandemic. The goal of this research is to enhance the effectiveness of distance learning programs in high schools during the pandemic