bluuebunny/crossref_metadata_2025 huggingface dataset:
Supply Chain Maturity Drives Successful Digital Transformation
Authors: Nassar Dr Shereen
Published: March 2024

Understanding supply chain digital transformation and the related concepts are core to its success. Global surveys showed that most businesses struggle to achieve the potential benefits of the implemented digital solutions. Focusing only on potential new technologies without understanding the level of business maturity at which digital technologies can be beneficial is the key cause of failure. This article reviews and differentiates various digital transformation terminologies and how they should be used. The article has a main focus on supply chain digital maturity and its impact on the success of digital transformation initiatives.
Fatores de risco para câncer endometrial: análise da distribuição de variáveis em mulheres atendidas em um centro integrado ambulatorial em Brasília
Authors: Lopes Carolina Figueiredo , Grespan João Pedro Borges Andrade , Grespan João Vitor Borges Andrade , Teixeira Edcley de Souza , Morales Neto Nicanor , Gomes Demétrio Antônio Gonçalves Silva
Published: March 2024

Introdução: O câncer endometrial uterino é a malignidade ginecológica mais prevalente em mulheres brasileiras e uma das principais causas de morbidade e mortalidade. Mais de 60.000 novos casos são esperados durante o próximo ano, devido à crescente exposição da população aos fatores de risco sabidamente associados à neoplasia, como obesidade e sedentarismo. O diagnóstico e tratamento da neoplasia de endométrio são complexos e onerosos do ponto de vista de saúde pública, portanto, a prevenção primária é um pilar fundamental do manejo da condição. Objetivo: Este estudo tem como objetivo conhecer a prevalência de fatores associados ao câncer de endométrio em mulheres na pré e pós menopausa atendidas em um Centro Integrado Ambulatorial em Brasília. Metodologia: Foi realizado um estudo transversal e descritivo entre as mulheres atendidas no setor de Ginecologia de um Centro Ambulatorial de Atenção Primária. Foram coletados dados relativos às variáveis sociodemográficas, gineco-obstétricas e exposição a fatores associados ao câncer endometrial. As participantes assinaram o termo de consentimento livre e esclarecido e o estudo seguiu as normas da resolução 196/96.  RESULTADOS: A população foi composta por 106 mulheres. Dentre os fatores de risco conhecidos para o desenvolvimento do câncer de endométrio, encontrou-se a prevalência aumentada de mulheres com sobrepeso (41,5% das amostras) ou obesidade (29,2%), primigestas (41,1%) e nuligestas (30,1%). CONCLUSÃO: A prevalência elevada de alguns fatores aponta para a necessidade da implementação de medidas de prevenção e promoção à saúde com o objetivo de se reduzir a exposição das pacientes da área atendidas aos fatores associados ao câncer.
Gestão da qualidade segundo registros de assistência técnica em edifícios
Authors: Figueiredo Chenia Rocha , Cavalcanti Mariana Silva Couto , Quintanilha Débora Santos Aires
Published: March 2024

O artigo investiga a eficácia dos sistemas de gestão da qualidade na construção civil, focando na detecção e prevenção de falhas comuns pós-obra. A pesquisa analisa detalhadamente oito edificações, utilizando a metodologia FMEA para identificar e analisar vícios construtivos recorrentes. Os dados coletados revelaram que as instalações hidrossanitárias e os revestimentos internos são as áreas com maior incidência de problemas, destacando-se nas solicitações dos clientes por assistência técnica. Através deste estudo, é possível compreender a dinâmica e a frequência das falhas mais comuns em construções, proporcionando uma base sólida para a implementação de melhorias nos processos produtivos. A pesquisa não apenas cataloga os problemas mais frequentes, mas também propõe soluções práticas para mitigá-los, enfatizando a importância de um sistema de gestão da qualidade robusto e adaptativo. Este sistema não apenas responde às necessidades imediatas de reparo, mas também atua preventivamente, refinando o processo construtivo para evitar a recorrência de falhas. Ao fazer isso, o estudo contribui significativamente para a elevação dos padrões de qualidade na construção civil, visando a satisfação do consumidor, a redução do retrabalho e a sustentabilidade dos projetos a longo prazo.
Estimativa de aporte de Nitrogênio e Fósforo na microbacia hidrográfica do rio Açu utilizando ferramentas de geoprocessamento
Authors: Luiz Junior Olavo José , Macedo Humberto Rodrigues , Werneck Pedro Rondon , Francisco Humberto Rodrigues , Feiden Aldi
Published: March 2024

A microbacia hidrográfica do rio Açu foi declarada área crítica quanto ao uso de recursos hídricos, em virtude da ação antrópica, caracterizando-se como área de potencial conflito por indisponibilidade hídrica e/ou risco de comprometimento de sistemas de abastecimento público de água, ou ainda pelo risco de contaminação de águas subterrâneas.  Este trabalho tem por objetivo avaliar as características geomorfológicas, e o impacto da piscicultura no aporte de Nitrogênio e Fosfóro Total na microbacia do rio Açu, utilizando-se de ferramentas de geotecnologias para realizar o mapeamento, classificação dos viveiros escavados. A microbacia do rio Açu possui uma área de 395,63 km² e 278 viveiros escavados, totalizando uma área de 169 hectares de lâmina d’água. Estimou-se que a piscicultura aporta cerca de 395 toneladas de Nitrogênio Total e 48 toneladas de Fósforo Total, durante o período de um ciclo de cultivo, os quais são os principais agentes eutrofizantes dos recursos hídricos. O uso das ferramentas de geoprocessamento podem ser úteis para dimensionar impactos ambientais e localizar pontos críticos, de forma a  planejar o uso racional dos recursos hídricos, evitar situações de crise, e assim promover o desenvolvimento rural sustentável.
A plataforma BIM na compatibilização de projetos de arquitetura e estrutura: estudos de casos
Authors: Praia Pedro , Pantoja João da Costa , Buzar Marcio Augusto Roma , Silva Lenildo Santos da
Published: March 2024

Este estudo objetiva uma investigação comparativa do processo tradicional de compatibilização em um escritório de arquitetura em contraste com a metodologia automatizada implementada através da tecnologia Building Information Modeling (BIM), com ênfase em projetos estruturais. O propósito é avaliar as implicações da sistematização e automatização no processo de compatibilização e discernir sua relevância e impacto no contexto operacional de firmas especializadas em Arquitetura, Engenharia e Construção (AEC) que empregam a plataforma BIM. A pesquisa envolve uma análise do procedimento corrente de compatibilização em uma firma de arquitetura, confrontando-o com um processo automatizado examinado por meio de dois estudos de caso concretos, executados pela referida firma. Tais estudos de caso foram empregados como instrumentos para evidenciar a superioridade, em termos de eficácia, do processo de compatibilização utilizando ferramentas de detecção automática em comparação com o método híbrido adotado atualmente pelo escritório. Os resultados obtidos indicam que a implementação exclusiva do BIM por um escritório de arquitetura não é suficiente para capitalizar plenamente as potencialidades oferecidas pelas funcionalidades avançadas de detecção de conflitos automáticos inerentes às ferramentas BIM. Este achado sublinha a necessidade de uma abordagem integrada e colaborativa no setor de AEC para maximizar os benefícios da compatibilização automatizada e promover uma maior eficiência e precisão nos projetos de construção.
The Influence Of Competence and Compensation On The Performance Of Army Polytechnic Teaching Staff: Mediated By Work Motivation
Authors: Rachmat Setiawibawa
Published: March 2024

This study aims to examine the influence of skills and rewards on the job performance of teaching staff at the Army Polytechnic Institute, considering the role of job motivation. The study population consists of 63 teaching staff members at the Army Polytechnic Institute, with samples selected using a saturated sampling technique. Data were analyzed through path analysis. The findings indicate that skills, rewards, job motivation, and job performance of teaching staff are at a good level. Skills and rewards directly contribute positively to job motivation and job performance. Moreover, job motivation also has a significant direct impact on job performance. The mediating results show that skills and rewards, through job motivation, indirectly influence the job performance of teaching staff at the Army Polytechnic Institute.
FIRST EVIDENCE OF PALAEO-TETHYAN UPPER TRIASSIC CALCAREOUS NANNOFOSSILS IN NORTH DOBROGEAN OROGEN (ROMANIA)
Authors: DEMANGEL ISALINE , GRĂDINARU EUGEN , LAZĂR IULIANA , SEGHEDI ANTONETA , MUNTEANU IOAN
Published: March 2024

This study presents the analysis of Upper Triassic sediments from five locations in North Dobrogea(Romania) and the Black Sea. Microfacies analyses on thin sections from the Frecăţei log reveal a shallowing trend and likely an increase in energy upward into the section. The oldest part of the log is characterised by deposition of mudstones transitioning to wackestones, with an increase of bivalves. Similar wackestones are observed in the Izvoarele and Rândunica logs, i.e. microfacies with abundant bivalves, some foraminifera and echinoderms. The offshore boreholes 816 and 817 Lebăda Vest (core CM 9 and CM 31) seem to have been deposited in a basinal or distal marine shelf environment indicated by the presence of mudstones with rare bioclasts. In contrast, sample CM 10 from borehole 816 LV is a micritised grainstone suggesting a deposition in a shallower, higher energy environment.Scanning electron microscope observations reveal a moderate diagenetic alteration in all studied samples, mainly due to dissolution. Two calcareous nannofossil species: Prinsiosphaera triassica triassica and Eoconusphaera zlambachensis were commonly observed in sample F of the Frecăţei log, allowing for assignment of the sediments to the Rhaetian age. Two coccoliths were also observed in sample F of Frecăţei log and sample CM 9 of the borehole 816 LV indicating the presence of coccolithophorids within the study region. This discovery constitutes the first confirmed record of well-preserved, determinable Upper Triassic calcareous nannofossils in the Palaeo-Tethys Ocean.
Research on the principle, performance, and application of UCB algorithm in multi arm slot machine problems
Authors: Huang Ruijie
Published: March 2024

As Internet technology continues to evolve, recommender systems have become an integral part of daily life. However, traditional methods are increasingly falling short of meeting evolving user expectations. Utilizing survey data from the MovieLens dataset, a comparative approach was employed to investigate the efficacy, performance, and applicability of the UCB (Upper Confidence Bound) algorithm in addressing the multi-armed bandit problem. The study reveals that the UCB algorithm significantly impacts the cumulative regret value, indicating its robust performance in the multi-armed bandit setting. Furthermore, LinUCBan enhanced version of the UCB algorithmexhibits exceptional overall performance. The algorithm's efficiency is not just limited to the regret value but extends to handling high-dimensional feature spaces and delivering personalized recommendations. Unlike traditional UCB algorithms, LinUCB adapts more fluidly to high-dimensional environments by leveraging a linear model to simulate the reward function associated with each arm. This adaptability makes LinUCB particularly effective for complex, feature-rich recommendation scenarios. The performance of the UCB algorithm is also contingent upon parameter selection, making this an important factor to consider in practical implementations. Overall, both UCB and its modified version, LinUCB, present compelling solutions for the challenges faced by modern recommender systems.
Investigating techniques to optimize data movement and reduce memory-related bottlenecks
Authors: Hu Yiyang
Published: March 2024

In the ever-changing realm of computing, the importance of efficient data movement and the reduction of memory-related bottlenecks cannot be overstated. This research paper delves into a thorough examination of diverse methodologies and approaches aimed at optimizing data transfer and mitigating the constraints imposed by memory limitations. It offers an all-encompassing survey of pertinent literature, delving deep into techniques designed to enhance data movement efficiency, discussing effective strategies for alleviating memory bottlenecks, and presenting the outcomes of extensive experiments conducted. The findings of this study underscore the critical role played by these techniques in augmenting the performance, efficiency, and scalability of contemporary computing systems. In a world where the demand for computational power continues to grow, the ability to streamline data movement and overcome memory constraints is essential. By shedding light on these pivotal aspects of computing, this paper contributes to a more profound understanding of how to harness the full potential of modern computing systems, ultimately paving the way for groundbreaking advancements in the field.
Navigating the electronic landscape: Exploring FPGAs and MCUs architectures in electronic design
Authors: Zhao Deyu
Published: March 2024

Field-Programmable Gate Arrays (FPGAs) and Microcontroller Units (MCUs) are foundational pillars in electronic design, each possessing distinct attributes and applications. This paper embarks on an exploration of these components, delving deep into their unique architectures, performance characteristics, and practical uses. This study, through a comprehensive comparative analysis, examines the strengths and limitations inherent to each of these components. It seeks to serve as a guiding compass for technologists, aiding them in making informed decisions when embarking on electronic design projects. FPGAs emerge as the frontrunners in high-computation endeavors, flexing their computational muscles with finesse. Conversely, MCUs establish their dominance in real-time, low-power applications, where their unwavering reliability is paramount. As electronic systems continue to evolve and infiltrate various aspects of our lives, comprehending the intricacies of FPGA and MCU architectures assumes an increasingly pivotal role for engineers, designers, and researchers. Armed with this knowledge, they can confidently navigate the intricate landscape of electronics, strategically harnessing the power of these two fundamental building blocks to bring innovation and efficiency to the forefront.
A comparative study of large-scale and lightweight convolutional neural networks for ImageNet classification
Authors: Zhao Zepeng
Published: March 2024

In the field of convolution neural networks (CNNs), many impressive architectures have been published in recent years. These can be roughly divided into two groups: large-scale models and lightweight models. These large models are characterized by many trainable weights and complex network structures, offering them strong effectiveness in various computer vision tasks, and have become essential components of many modern visual recognition systems. These lightweight CNNs are designed to maintain high performance with limited memory and computational resources. They are highly efficient in terms of inference time and resource utilization, so that particularly suitable for mobile and edge computing devices. This work focuses on some prominent models based on the ImageNet database and explores the reasons for their frameworks success. By analyzing these models, a trend could be identified in the development of CNN models: Reasonably increasing the scale of the model and utilizing suitable frameworks can both improve accuracy and efficiency.
Advancing signal integrity and application analysis through data-flow mapping
Authors: Peng Yudong
Published: March 2024

Data-flow mapping is a crucial method in signal processing and optimization, managing data flow within systems. Its essential in signal compensation, particularly in telecommunications, audio processing, and biomedical signal processing. Four main algorithm categories underpin data-flow mapping: heuristics, meta-heuristics, Integer Linear Programming (ILP), and Constraint Satisfaction Problems (CSP). Heuristic and meta-heuristic methods like Genetic Algorithms (GA) and Ant Colony Optimization (ACO) provide approximate solutions, crucial for complex problems. ILP and Branch and Bound (B&B) methods offer precise solutions by exhaustive searches under constraints. CSP focuses on satisfying imposed conditions. These methodologies have practical applications, such as signal compensation in communication systems and improving medical imaging like MRI and ultrasound. Theyre also integrated with machine learning, quantum computing, and specialized hardware for 5G/6G communications and IoT. Real-time processing and noise reduction advancements enhance consumer audio and diverse sectors. In summary, data-flow mapping and its algorithms drive signal processing innovations across domains, with evolving technology integration ensuring their lasting importance.
Exploring the effect of depth and width of CNN models on binary classification of dogs and cats
Authors: Li Xu
Published: March 2024

Convolutional neural networks (CNNs), one of the trendiest study areas in recent years, have garnered a lot of interest. Their performance is particularly notable in speech recognition, target identification, and picture recognition. The performance of a convolutional neural network model is particularly crucial because convolutional neural networks deal with problems that demand enormous amounts of data and have strict standards for result correctness. The convolutional neural network model's depth and width are the first two parameters that are examined in this paper, which is built on the Tensorflow framework. Next, the impact of depth on the accuracy of model's prediction is examined. The model's accuracy and loss are then used as a benchmark to assess its quality; at the same time, the performance of the model can be discussed in relation to the impact of width by selecting a different number of neurons with various convolutional kernel sizes; Finally, A combinational convolutional, the experiments' result show that, with a classification accuracy of up to 95.4%, the combinatorial convolutional neural network outperforms a model with single depth or width.
An analysis of attention mechanisms and its variance in transformer
Authors: Chen Yuzhong , Pu Hongren , Qu Yang
Published: March 2024

Transformer is a machine learning model based on attention mechanism, which is widely used. When the Transformer model was first proposed, it gradually developed many variants and was promoted and applied in many fields, becoming an important research part in the areas of deep learning. However, the critical attention mechanism of Transformers has issues such as square complexity that affect computational speed and data processing efficiency. In order to meet the needs of data processing and related computing, there have been endless efforts to improve the attention mechanism in Transformers in different work areas. This article mainly provides a brief overview of the recent research progress on the attention mechanism in Transformers. Select representative studies from several directions of attention improvement work to introduce, in order to explore the latest research trends in its improvement work and lay a foundation for pointing out potential research directions for future research work and further improving the performance of Transformers.
A comparison of deep learning-based object detection for unmanned aerial vehicle
Authors: Li Tinghuan
Published: March 2024

Unmanned aerial vehicle (UAV) plays a critical role in the field of object detection, and machine learning techniques have significantly advanced the field in recent years. This paper provides a comprehensive overview of machine learning developments for UAV object detection. The process involves multiple steps. Firstly, deep learning and Convolutional Neural Network (CNN) are widely utilized to extract precise features and train object detection models for accurate classification and efficient recognition of target objects in images and videos. Secondly, classical object detection algorithms such as Faster R-CNN, You Only Look Once (YOLO), and Single Shot MultiBox Detector (SSD), have been enhanced to improve accuracy and real-time performance. In this review, we primarily focus on comparing the principles of CNN and YOLOv5 themselves, as well as their applications in object detection and image recognition. Ultimately, it becomes apparent that CNN is better suited for processing image data, automatically extracting features, and achieving more accurate classification and detection. On the other hand, YOLOv5 directly performs detection on large images, significantly reducing computation time compared to CNN.
Analysis of buying intension online based on decision tree and support vector machine
Authors: Zhang Linjing
Published: March 2024

With the development of the Internet, online shopping has gradually emerged and changed people's living habits. On this basis, the purchase intention of users has become a hot topic. In this study, the data set on Kaggle is used to train and analyse the model with decision tree as well as support vector machine (SVM). To be specific, 30% of the data is used for testing. According to the feature correlation analysis, one can see that some features, such as ExitRates and BounceRates, are highly correlated, and PageValue has a great impact on income. In addition, precision, recall, f1-score and other data were processed to evaluate the model, and its limitations and future development were explained. It is of great significance to forecast the income of online merchants and how merchants purchase goods and reduce inventory, and to understand and predict the intention of users to purchase online from the income of merchants.
APPL stock price prediction based on LSTM and GRU
Authors: Pang Tao
Published: March 2024

In particular, LSTM and GRU are two frequently used models in stock price prediction. With this in mind, this study will test these two useful tools from three aspects, actual using, limitations and possible future improving. Based on the stock price of (APPL), Apple company from 2022 to 2023. There are a lot of past research shows that LSTM and GRU are useful in forecasting stock price. However, one important part to notice is the rely on historical data. These two models may find difficult to address the correct prediction and make real profit. As a result, the usefulness of LSTM and GRU are tested by the unstable stock market. Additionally, overfitting can be a big problem. To make the models more useful and eliminate limitations. In this research, there will be some real examples of change in stock price based on graphs. There will be some future strategy to solve issues on LSTM and GRU, from possible improvements on the current reliability on historical data, and the easily influenced stock market. Overall, LSTM and GRU can provide useful details based on the past data of certain stock. However, the limitations of these two models are a big issue.
Investigation on task effect analysis and optimization strategy of multimodal large model based on Transformers architecture for various languages
Authors: Zhang Tianze
Published: March 2024

As artificial intelligence technology advances swiftly, the Transformers architecture has emerged as a pivotal model for handling multimodal data. This investigation delves into the impact of multimodal large-scale models utilizing the Transformers architecture for addressing various linguistic tasks, along with proposing optimization approaches tailored to this context. Through a series of experiments, this study scrutinized the performance of these models on multilingual datasets, engaging in a comprehensive analysis of the key determinants influencing their effectiveness. Firstly, several models of transformers architecture are pre trained on the same corpus, including ERNIE, GPT, ViT, VisualBERT, and a series of tests are carried out on these models in English, Chinese, Spanish and other languages. By comparing the performance of different models, it is found that these models show significant performance differences when dealing with tasks in different languages. Further, through analysis and experimental verification, this paper proposes a series of optimization strategies for different languages, including: annotation method for language specific datasets, incremental fine-tuning method for tuning, increasing the size of datasets, using multi task learning, etc. Experiments show that these methods have achieved remarkable results, and put forward the future research direction.
Movie genre prediction based on the bidirectional encoder representations from transformer
Authors: Li Lu , Lin Jin , Li Tongyu
Published: March 2024

The rapid expansion of digital media has underscored the growing significance of predicting genres to target audiences effectively and to enhance filmmakers' understanding of viewer preferences. In this study, we introduced a novel method for forecasting movie genres, leveraging the power of the Bidirectional Encoder Representations from Transformer (BERT) deep learning model. The research team employed a dataset sourced from Douban's website, which featured 5,000 movies, complete with cover images, titles, and genre information. This undertaking tackled several key challenges, including the extraction of features from textual data, the categorization of movie genres, and the incorporation of cultural nuances. BERT's bidirectional representation, especially its variant tailored for Chinese language tasks, 'bert-base-chinese', was employed to extract textual features. Meanwhile, the visual features from movie covers were processed using the Wide ResNet-50-2 architecture. The combined features underwent classification, and the resulting model achieved an accuracy of 34.67%, a recall rate of 74.5%, and an F1 score of 0.4755. The study validates the potential of the BERT model in predicting movie genres and offers significant insights for future research in multimedia content classification.
Analysis of diabetes based on Tree Decision, Logistic Regression and Artificial Neural Network
Authors: Shao Ziheng
Published: March 2024

The alarming rise in diabetes cases globally, particularly amongst the aging population, underscores a pressing need for innovative, accurate, and early diagnostic tools. Amidst this health crisis, the present study delves into the evaluation of three prominent machine learning in predicting diabetes using the Pima Indians Diabetes Database. A comprehensive analysis, considering metrics such as accuracy, precision, recall, F1 score, and ROC curve, revealed Decision Trees as the most efficacious, exhibiting adeptness in balancing precision and recall. Artificial Neural Networks displayed a remarkable ability to identify true positive cases, making it a notable contender in medical diagnostics. In terms of accuracy, Decision Trees led with a rate of 76.19%, followed by Logistic Regression at 74.03%, and Artificial Neural Networks trailing at 72.64%. The findings suggest Decision Trees' potential utility in offering both a nuanced and comprehensive approach to diabetes prediction. However, the constraints imposed by the dataset, and the inherent limitations and sensitivities of the machine learning models, call for a judicious interpretation of the results. This research illuminates the prospective integration of machine learning in healthcare for enhanced, personalized, and timely diabetes management, paving the way for improved patient outcomes and a substantial reduction in global health disparities attributed to diabetes.
Creating a credit card anti-fraud detection sytem using machine learning
Authors: Zhang Jia
Published: March 2024

With the increasing prevalence of online transactions, fraudulent cases involving credit cards have also been on the rise. Therefore, the primary objective of this research is to create an effective fraud detection system that benefits both financial companies and their cardholders. The research work began with a thorough analysis of the dataset, which helped to provide a better understanding of the data. In order to enhance the performance of the machine learning models, new features were created by combining previous transaction features to identify clients and credit cards. To mitigate the problem of imbalanced data, a minority oversampling method was utilized. Machine learning techniques such as XGboost and Random Forest were then employed to evaluate the model performances based on AUC, recall and F1-score. The results demonstrated that the models improved significantly after incorporating the combined features to identify clients and users.
Impelementasi Metode SQ3R untuk Meningkatkan Maharah Al-Qiro’ah di Madrasah Tsanawiyah
Authors: Adawiyah Yayah Robiatul , Wulandari Sri
Published: March 2024

Siswa dan siswi MTs Ar riyadlah mengalami kesulitan dalam memahami teks bacaan dalam bahasa arab kesulitan ini terjadi karna kurangnya semangat dari siswa untuk mempelajari bahasa arab sehingga menimbulkan beberapa permasalahan dalam mempelajari bahasa arab di antaranya: banyak nya siswa yang tidur didalam kelas dan kurangnya ketertarikan siswa dalam mempelajari teks bacaan bahasa arab. Penelitian ini bertujuan untuk mengetahui langkah-langkah maharah al qiro’ah dengan menggunakan metode SQ3R di MTs Ar Riyadlah dan perkembangan siswa dalam mempelajari maharah al-qiro’ah dengan menggunakan metode SQ3R. Peneliti menggunakan metode penelitian kualitatif dimana penelitian ini dilakukan dengan cara berwawancara kepada guru dan murid, observasi dengan mengikuti pembelajaran di dalam kelas serta melakukan beberapa dokumentasi. Peneliti tertarik dengan metode ini karna dengan menggunakan metode SQ3R ini memberikan inovasi serta ketertarikan siswa dalam mempelajari bahasa arab khususnya pada maharoh Al-Qiro’ah sebelum adanya metode SQ3R disekolah tersebut banyak siswa yang kurang memahami maksud dari teks bacaan tersebut sehingga membuat siswa bosan dan kurang tertarik dalam mempelajari bahasa arab dan sejak diterapkan nya metode SQ3R ini siswa semakin tertarik serta mudah memahami teks bacaan bahasa arab. Data yang diperoleh selanjutnya berdasarkan alur analisis milles dan hubermain yaitu berupa reduksi data, Penyajian data, dan kesimpulan.
Main processes of bone formation and regeneration through molecules and cells as biostimulators in buccomaxillofacial surgery: a systematic review
Authors: Inada Luís Fernando , Beneti Igor Mariotto
Published: March 2024

Introduction: At a cellular and molecular level, tissue engineering offers numerous advantages that meet the needs of the injured tissue or organ for the bone regeneration process in buccomaxillofacial surgeries. To achieve this, it is necessary to understand the chemical, physical, and biological processes of both the biological material and the target biological niche. Objective: It was to carry out a concise systematic review of the main processes of bone formation and regeneration using molecules and cells as biostimulators in buccomaxillofacial surgeries. Methods: The PRISMA Platform systematic review rules were followed. The search was carried out from December 2023 to February 2024 in the Scopus, PubMed, Science Direct, Scielo, and Google Scholar databases. The quality of the studies was based on the GRADE instrument and the risk of bias was analyzed according to the Cochrane instrument. Results and Conclusion: A total of 182 articles were found, 60 articles were evaluated in full and 36 were included and developed in the present systematic review study. Considering the Cochrane tool for risk of bias, the overall assessment resulted in 12 studies with a high risk of bias and 20 studies that did not meet GRADE and AMSTAR-2. Most studies did not show homogeneity in their results, with X2=54.7%>50%. The bone regeneration process occurs through the activation of osteoblasts and vascular control guided by PDGFs and TGF-β. These growth factors also promote matrix formation and osteoblast differentiation. Some biodegradable natural polymers (chitosan®) associated with inorganic materials such as tricalcium phosphate were tested as spongy carriers for PDGF-BB. Chitosan® has been attributed to hemostatic properties, inducing bone formation and regulating the release of bioactive agents. The use of platelet-rich plasma and mesenchymal stem cells (exosomes and microRNAs) has been indicated and used in other areas of oral and buccomaxillofacial surgery, accelerating a process of bone regeneration that normally already occurs and this process continues its path until the formation of bone mature.
STRATEGY FOR THE DEVELOPMENT OF FREE ECONOMIC ZONES IN UZBEKISTAN
Authors: Sabirov Khasan Nusratovich  , Akbarova Asidakhan
Published: March 2024

The essence of this article is that the role, activities, advantages and disadvantages of free economic zones in Uzbekistan today, the changes of free economic zones over the years, the emergence of an understanding of strategic activities and free economy, and free economic zones, which are considered the main factor for the socio-economic development of the country. zones, their attractiveness and evaluation criteria, as well as theoretical bases of their necessity are emphasized. This, in turn, requires the deployment and development of production forces in each region based on its mineral and resource wealth. Especially small business and private entrepreneurship, increase and strengthening of export potential, regional economy stability and the current situation in our country are highlighted.
OZIQ-OVQAT SANOAT KORXONALARI FAOLIYATINI BOSHQARISH HAMDA KORXONALAR IQTISODIY SAMARADORLIGINI OSHIRISH YO‘LLARI
Authors: Rasulоva Sharifa G‘aybullayеvna
Published: March 2024

Ushbu maqоlada bugungi kunda mamlakatimizning milliy iqtisоdiyоtida qurilish sоhasining о‘rni va ahamiyati, Prеzidеntimiz tоmоnidan kо‘zlangan yuqоri iqtisоdiy о‘sish sur’atlarni saqlab qоlish ham qurilish sоhasidagi оlib bоrilayоtgan islоhоtlar bilan chambarchasi bоg‘liqligi, hamda statistika bоshqarmasi tоmоnidan О‘zbеkistоn Rеspublikasida qurilish ishlari bajarilish bо‘yicha ma’lumоtlar kеltirib о‘tilgan.
ҲУДУДЛАР САНОАТИНИ КОМПЛЕКС-ИНОВАЦИОН РИВОЖЛАНТИРИШ МОДЕЛИ
Authors: Ҳусанова Гулчеҳра Сайфуллаевна
Published: March 2024

Ушбу мақолада Наманган вилояти   саноат салоҳиятини ошириш бўйича ишлаб чиқилган  саноатни  ривожланиш цикли  модели таклиф этилган.. Наманган вилоятини комплекс-инновацион ривожлантиришга қаратилган илмий таклиф ва амалий тавсияларни ишлаб чиқилган. Саноат  ва минтақанинг ижтимоий-иқтисодий ривожланиши ўртасидаги боғлиқлик, унинг иқтисодий ўсиш ва аҳоли фаровонлигига таьсири илмий асосланган. Вилоятда ижтимоий-иқтисодий ривожланиш тенденциялари тараққиётининг ҳозирги холати бахоланган. Мавжуд табиий иқтисодий салоҳиятни чуқур таҳлил қилган ҳолда иқтисодий ўсиш ва аҳоли даромадларини оширишни ривожлантиришнинг асосий омиллари ва хусусиятлари тавсифланган.
A COMPREHENSIVE ANALYSIS OF THE IMPACT OF GLOBALIZATION ON AUDITING STANDARDS
Authors: Abduhamidov Abdurahmon Abdulatif o‘g‘li
Published: March 2024

This article examines the profound impact of globalization on auditing standards, unraveling the complexities faced by auditors in an increasingly interconnected global economy. As businesses extend their operations across borders, auditors grapple with diverse regulatory frameworks, cultural nuances, and evolving business practices. The literature review reveals a compelling narrative, highlighting the imperative for harmonized auditing standards in the face of globalization. The International Auditing and Assurance Standards Board (IAASB) plays a pivotal role in formulating and updating standards to align with the intricacies of a borderless economy. Technological advancements, particularly in data analytics and artificial intelligence, are transforming audit methodologies, enhancing efficiency, and addressing global financial challenges. Challenges emerge in adapting to local variations, requiring auditors to strike a delicate balance between standardization and cultural adaptability. Collaboration and communication among auditors, regulators, and standard-setting bodies emerge as critical elements for success in this dynamic global auditing landscape.
MOLIYAVIY TEXNOLOGIYALAR TARIXI VA RIVOJLANISHI: OʻZBEKISTON MISOLIDA
Authors: A.Abduhamidov  , D.Xoʻjamurodov
Published: March 2024

Ushbu maqolada moliyaviy texnologiyalar, moliyaviy xizmatlar toʻg‘risida ma'lumotlar keltirilgan.
MAMLAKATIMIZDA YASHIL IQTISODIYOTNI JORIY ETISH HOLATI VA ASOSIY YOʻNALISHLARI
Authors: J.A.Turgʻunov
Published: March 2024

Ushbu tadqiqotda mamlakatimizda yashil iqtisodiyotni rivojlantirishning nazariy asoslari koʻrib chiqilgan. Yashil iqtisodiyot va “yashil oʻsish”ni ta’minlashning ustuvor yoʻnalishlari tahlil qilingan. Tadqiqotning maqsadi mamlakatimizda yashil iqtisodiyotni joriy etish jarayonini tahlil qilish, uning hozirgi holati, istiqbollarini koʻrsatib oʻtishdan iborat. Shuningdek, tadqiqotda mamlakatimiz iqtisodiyotini “yashil iqtisodiyot” tamoyillari asosida rivojlantirishning ustuvor yoʻnalishlari oʻrganilgan.
SPECIFIC CHARACTERISTICS OF TOUR OPERATOR ACTIVITY MANAGEMENT
Authors: Mamadaliev Ulugbek Toxirjon ugli
Published: March 2024

The distinctive features of tour operator management include several important strategic, operational and customer-oriented services. This will further develop the field of activity of tour operators in the industry, moving between technology and innovation and consumer preferences. In this article, we will look at the specifics of tour operator management, strategic positioning, organizational needs, and key aspects of customer engagement within the tour operator business.
IQTISОDIY ISLОHОTLAR SHARОITIDA KОRXОNALARNI BОSHQARISH
Authors: Umarova Z.O
Published: March 2024

Iqtisоdiy islоhоtlar sharоitida kоrxоnalarni bоshqarishni o‘rganish hamda kоrxоnalar amaliyоtida strategik bоshqarishning ahamiyati haqidagi ma’lumotlar va tavsiyalar keltirilgan.
АN ОVERVIEW ОF THE FUNСTIОN ОF HUMАN RESОURСE MАNАGEMENT IN EMPLОYEE PERFОRMАNСE АND MОTIVАTIОN
Authors: Melibаevа Gulxоn Nаzrullаevnа
Published: March 2024

The present study shows the crucial relationship that exists between Human Resource Management (HRM) and company success. Specifically, HRM is vital to aligning human resources with strategic objectives. In order to effectively coordinate human resources, HRM must move from administrative duties to a strategic partner role. A motivated workforce and HRM methods are examined in this article, with a focus on hiring, training, and performance reviews. A deeper understanding of employee pleasure is achieved by integrating psychological theories like Maslow's hierarchy and McClelland's wants.
AN OVERVIEW OF GREEN BANKING PRACTICES IN UZBEKISTAN
Authors: Gulomkodirova Mamura Saydumarxon qizi
Published: March 2024

The research draws on existing literature on green banking practices, as well as case studies of banks in Uzbekistan. This approach allowed for a thorough and comprehensive understanding of the topic. The main purpose of this paper is to provide an overview of green banking practices in Uzbekistan, with a focus on mobile banking, online banking, green financing, and guidelines for green banking practices.  This paper will also explore the role of green banking in promoting CSR (Corporate Social Responsibility) and will discuss the importance of green banking in Uzbekistan, and the challenges that need to be overcome in order to implement it effectively. The literature review revealed a number of important findings, including the lack of standardized definitions for green banking practices, the challenges faced by banks in implementing these practices, and the benefits that can be gained by doing so. These findings will be further explored in the main body of the paper.
FOND BOZORI VA UNDA TIJORAT BANKLARINING TUTGAN OʻRNI
Authors: Sultonov Mansur G‘aniyevich
Published: March 2024

Ushbu maqolada fond bozori va unda tijorat banklarining hozirgi kundagi oʻrni, tijorat banklari fond bozorining eng muhim ishtirokchilaridan biri ekanligi, Respublikamiz banklarining fond bozoridagi faoliyatini takomillashtirish zarurligi haqida ma’lumotlar va tavsiyalar keltirilgan.
SIYOSIY MOJAROLARNING TURIZMGA TA’SIRI
Authors: Hamidjon Rasulov
Published: March 2024

Ushbu maqolada mamlakatlar o‘rtasidagi siyosiy mojorolar va turli xil kelishmovchiliklarning turizm sanoatiga ta’siri haqida so‘z yuritiladi. Bir necha yillar oldin va ayni hozirgi davrda bo‘lib turgan bir necha davlatlar, masalan Rossiya va Ukraina, Falastin va Isroil kabi mamlakatlarinig siyosiy inqirozdan oldingi turizm holati o‘rganib chiqilib, topilgan ma’lumotlar hozirgi turizm holati haqidagi ma’lumotlar bilan qiyosiy tahlil qilindi. Undan tashqari ma’lum vaqt o‘tkandan keyin yani siyosiy mojorolar tugagandan so‘ng turizm sanoati eski davrdagi holatiga kelgunicha qancha vaqt ketishligi, uning uchun qanday chora tadbirlar qilinishi haqida fikrlar ilgari surildi va takliflar berildi.
UNLOCKING KNOWLEDGE: KEY PEDAGOGICAL ASPECTS OF THE STUDY OF PHILOLOGY
Authors: Ganiyeva Muborak Odilovna  , Ergasheva Durdonakhon Gayratkhuja kizi
Published: March 2024

The educational foundations of philology - a field of study devoted to interpreting the linguistic complexity of historical written sources—are explored in this abstract. With a focus on interdisciplinary approaches, we investigate how language analysis, literary analysis, historical study, and cultural discovery may all be integrated as vital elements of a successful philological education. Language competency, which goes beyond fluency in one's mother tongue, is vital and calls for students to learn not only syntax and vocabulary but also the subtle changes that languages undergo over time. One of the most important aspects of philological education is helping students to traverse the socio-cultural environments in which languages flourish by helping them to comprehend historical contexts. Textual analysis is emphasized as a crucial method for gaining access to knowledge, including the understanding of ancient languages, the identification of linguistic patterns, and the interpretation of cultural. The main conditions as a result of the research modernization and introduction of innovative methods in foreign systems philology of university students was analyzed.
O‘ZBEKISTONDA PISA TESTI NATIJALARI VA BOSHLANG‘ICH TA’LIM O‘QUVCHILARINI BU TESTGA TAYYORLASH ISTIQBOLLARI
Authors: Jumanova Shaxnozaxon Ikromjonovna  , Abdullayev Axrorjon Axadjon o‘g‘li  , Odilova Maxliyoxon Doniyorjon qizi
Published: March 2024

Ushbu maqolada O‘zbekistondagi PISA testi natijalari chuqur tahlil qilinadi va boshlang‘ich ta’lim o‘quvchilarining ushbu xalqaro baholashga tayyorgarligini oshirish bo‘yicha istiqbolli strategiyalar bayon etilgan. O‘zbekistonning so‘nggi PISA testlaridagi ko‘rsatkichlarini o‘rganilar ekan, maqolada kuchli tomonlar va e’tibor talab qilinadigan sohalar aniqlangan. Natijalarga ta’sir etuvchi omillar, jumladan, o‘qitish metodologiyasi, o‘quv dasturlarini muvofiqlashtirish va ijtimoiy-iqtisodiy masalalar o‘rganiladi. O‘zbekistonning boshlang‘ich ta’lim tizimini har tomonlama ko‘rib chiqish o‘quv dasturini PISA tizimiga moslashtirish va tanqidiy fikrlash ko‘nikmalarini integratsiyalash bo‘yicha munozaralar uchun zamin yaratadi. Maqolada uzluksiz o‘qituvchilar malakasini oshirish, ta’limga texnologiya integratsiyasi va qulay ta’lim muhitini yaratishda jamoatchilik ishtirokining ahamiyati ta’kidlangan. Muvaffaqiyatli taʼlim modellari haqida tushunchaga ega boʻlish uchun xalqaro hamkorlikni qoʻllab-quvvatlaydi va ota-onalarni oʻquvchilarni PISA testiga tayyorlashga faol jalb qilish yoʻllarini taklif qiladi. Ta’lim infratuzilmasiga investitsiyalarning ahamiyati barqaror takomillashtirishning asosiy omili sifatida ta’kidlangan. Boshlang‘ich ta’lim o‘quvchilarini tayyorlash istiqbollari ana shu ko‘p qirrali strategiyalar bilan chambarchas bog‘liq.
BOSHLANGʻICH SINF OʻQUVCHILARIDA MATEMATIK KOMPETENSIYASINI RIVOJLANTIRISH YOʻLLARI
Authors: Valiyeva Nargiza Athamboyevna
Published: March 2024

Ushbu maqolada boshlangʻich sinf oʻquvchilarida kompetensiyaviy yondashuv asosida oʻqitish, matematik kompetensiya tushunchasi oʻzi nima va uni darslarda qanday qoʻllanishi haqida bayon qilingan. Shuningdek, matematik kompetensiyani boshlangʻich sinflarda rivojlantirish uchun turli metodlar va takliflar keltirilgan.
OʻQUVCHILARNING INDIVIDUAL OʻQUV NATIJALARINI BAHOLASHGA ZAMONAVIY YONDASHUVLAR
Authors: Pardayev Sherzod Mamasharipovich
Published: March 2024

Ushbu maqolada oʻquvchilarning individual oʻquv yutuqlarini baholashning zamonaviy  texnologiyalari  sifatida  formativ va summativ   baholashlar mohiyati toʻgʻrisida soʻz yuritiladi, shuningdek, formativ va summativ baholashning asosiy farqlari bayon etilgan. Oʻquvchilarning oʻquv natijalarini baholashning an’anaviy baholash tizimining afzalliklari hamda yutuqlari, shuningdek, baholashga mezonli yondashuvning amaliy ahamiyati haqida fikr yuritilgan.
IIV AKADEMIYASI KURSANT QIZLARINI ZAMONAVIY KROSSFIT SPORT TURI ORQALI JISMONIY TAYYORGARLIGINI TAKOMILLASHTIRISH
Authors: Mirzakulov Akrom Gafurjanovich
Published: March 2024

Respublikada bugungi kunda xodima ayollarga boʻlgan talab, qolaversa, ularning sportga qiziqishlari tobora ortib bormoqda. Ichki ishlar vazirligi akademiyasida kursant yigit va qizlarni kasbiy tayyorlashda jismoniy tayyorgarlikka alohida oʻrin qaratiladi. Shu bois, “Akademiyada ta’lim tizimi kadrlarni maqsadli kasbiy tayyorlashga qaratiladi hamda 1-kursdan boshlab jangovar va jismoniy jihatdan tayyorlash chuqurlashtirilgan holatda amalga oshirilishi ustuvor vazifa etib belgilangan”. Ushbu maqolada kursant qizlarning jismoniy tayyorgarligi, hozirgi kunda zamon talabiga javob beradigan, yangi sport turlaridan boʻlmish krossfit vosita va usullari yordamida rivojlantirilganligi ilmiy asoslab berilgan.
TALIM JARAYONLARINI RAQAMLI TEXNOLOGIYALAR ASOSIDA SAMARADORLIGINI OSHIRISH
Authors: Akbarova Husnidaxon Kamoldin qizi
Published: March 2024

Bu maqolada, ta’lim jarayonlarini raqamli texnologiyalar asosida samaradorligini oshirish haqida ma’lumot beriladi. Raqamli texnologiyalar, masofaviy ta’lim, onlayn darslar va interaktiv darsliklar kabi vositalar orqali ta’lim jarayonlarini oʻrganish va oʻqitishni samaradorligini oshirishda qanday rol oʻynashi aytib oʻtilgan. Maqolada ta’lim jarayonlarini raqamli texnologiyalar orqali tashkil etishning oʻziga xos afzalliklari, bu usullarning talabalarga va oʻqituvchilarga qanday foyda keltirishi, shuningdek, bu texnologiyalarning ta’lim jarayonlarini samaradorligini qanday darajada oshirishi haqida ma’lumotlar mavjud. Maqola ilmiy tadqiqotlarga asoslanib tuzilgan boʻlib, raqamli texnologiyalar asosida ta’lim jarayonlarining samaradorligi va uning muhim ahamiyati haqidagi soʻzlashishlarni ham oʻz ichiga oladi.
HOW DOES A PERSON BECOME MULTILINGUAL?
Authors: Mamatqulova Marhabo
Published: March 2024

This article, based on case study, presents information about the process of becoming multilingual of a female. This research is investigated focused on different types of methodologies like interviewing, questionnaire. Today, knowing one particular foreign language is not enough. One should know at least two or three languages in order to communicate or collaborate without any barriers. Several studies suggest that bilingual education has cognitive, social and health benefits, so it is beneficial that many schools integrate bilingual instructions. Also acquiring multiple languages have benefits not only inside the classroom. In addition, it is clear that, learning a second (or third) language is an investment in learners’ future achievements.