bluuebunny/crossref_metadata_2025 huggingface dataset:
Unet retinal vessel image segmentation algorithm based on coordinate attention mechanism and Min-ASPP module optimisation
Authors: Ye Yiheng , Zhao Qichao , Bao Tiancheng
Published: July 2024

In this paper, the Unet image segmentation algorithm is optimised and improved by introducing the coordinate attention mechanism and integrating the Min-ASPP module, and compared with the traditional Unet model, targeting the segmentation of retinal blood vessel images, which is a key problem in the field of medical image processing. The experimental results show that the optimised Unet algorithm combining the coordinate attention mechanism and Min-ASPP module has a smoother performance in the loss curve, faster convergence speed, and lower final converged loss value, which has an obvious advantage compared with the traditional Unet algorithm. Meanwhile, the optimised Unet algorithm shows higher accuracy and stability in the prediction results, providing ophthalmologists with more reliable information about the retinal vascular structure. Therefore, the research results of this paper show that the Unet image segmentation algorithm optimised by combining the coordinate attention mechanism and Min-ASPP module has better application prospects and effects in the retinal blood vessel image segmentation task, which provides a useful exploration and practice for improving the level of medical image processing technology.
Mask detection using automated machine learning techniques: A response strategy to the COVID-19 pandemic
Authors: Cao Jinye
Published: July 2024

Amidst the global backdrop of the COVID-19 pandemic, the imperative of judicious mask usage has emerged as a pivotal facet of public health. Conventional monitoring methods, such as manual checks, prove inadequate in addressing the demands of a pandemic of this scale. Although traditional machine learning techniques offer a potential solution for mask detection, their time-consuming nature poses challenges for real-time applications. In response, this study delves into the realm of automated machine learning techniques, focusing on the EasyDL platform due to its user-friendly interface and robust algorithms. This study explores automated machine learning for efficient mask detection during the COVID-19 pandemic. Using the EasyDL platform, we achieved a 94.3% precision rate in mask detection with only 213 minutes of training on a 6006-image dataset. This approach proves more time-effective than traditional methods, making it suitable for real-time applications and large-scale monitoring. The combination of high accuracy and efficiency showcases the potential of automated machine learning in public health, enabling swift responses to health threats. To sum up, this research symbolizes a significant progress in terms of applying artificial intelligence to address the chanlleges of the public health. It could be estimated that these discoveries will stimulate further researches, and pave the way for developing more efficient and more effective mask detecting tools, which would be likely to contribute to the progress of public health management in the future.
Analysis of problems and countermeasures in computer network engineering security
Authors: Feng Xinyi
Published: July 2024

This paper analyzes the existing security issues in computer network engineering and proposes a series of countermeasures. To address the problems of hacker attacks and information leakage, it is recommended to strengthen network monitoring and the application of encryption technology. For the issues of malware and virus dissemination, it is advised to regularly update antivirus software and enhance employee security awareness training. Regarding network data leakage and privacy breaches, the use of secure transmission protocols and multi-factor authentication technology is advocated. For network security management and maintenance issues, establishing a sound security management system and emergency response plans is recommended to ensure the stable operation of network systems. Through the implementation of the above measures, the security level of computer network engineering can be effectively improved, ensuring the normal operation of network systems and the security of information.
Analysis of neural networks in text sentiment
Authors: Wang Xingyu
Published: July 2024

The proliferation of digital media and online platforms has led to a significant increase in the production and distribution of textual data. Consequently, the study of text sentiment analysis has emerged as a crucial area of research within the domain of natural language processing. The objective of sentiment analysis is to detect and categorize emotional inclinations in text, which has substantial practical importance in comprehending public sentiment, monitoring brand reputation, and other related areas. This research does a comprehensive investigation of the utilization of neural network models in text sentiment analysis using literature review methods. It examines the difficulties encountered and the approaches employed to overcome these difficulties. The research encompasses the fundamental principles and techniques of text sentiment analysis utilizing neural networks, as well as the utilization of convolutional neural networks (CNN), recurrent neural networks (RNN)/long short-term memory networks (LSTM), attention mechanisms, and pre-trained models in the field of sentiment analysis. Furthermore, this study delves into the complexities associated with data noise, the interpretability of models, the analysis of long text and multimodal sentiment, as well as the utilization of transfer learning and domain adaptation techniques. The study's importance is in establishing a theoretical basis and practical recommendations for the advancement of sentiment analysis technology, particularly in enhancing model precision, comprehensibility, and range of applications, thereby delivering useful insights.
Navigating business intelligence and data analytics: Trends, foundations, strategies, and future directions
Authors: Li Zetao
Published: July 2024

In the current digital age, business intelligence (BI) and data analysis are rapidly evolving, but the driving force is in the progress of technology and exponential increase in data. In this paper, we consider a new trend, theoretical basis, implementation strategy, and the future direction of BI and data analysis. In this paper, we consider what innovative roles in artificial intelligence (AI), the Internet (IOT), and block chain technology reconstruct data analysis practices. In addition, this paper investigates ethical considerations and privacy issues related to data driven decisions, emphasizing the importance of responsible data management practices. In this paper, we introduce the strategy of implementing data analysis in business processes, overcoming challenges, and successful case studies. Finally, we emphasize the new trend and emphasize the essence of BI that will continue to evolve through advanced analysis.
Customer churn data analysis using data mining
Authors: Jiang Xingyuan
Published: July 2024

Churn is the phenomenon of a customer terminating their relationship or subscription with a company or service provider[1]. It represents the rate at which customers stop using a company's product or service during a specific period of time. Attrition rate is an important metric for businesses as it directly impacts revenue, growth and customer retention. In the context of the churn data set, the churn label indicates whether a customer has been churn. Lost customers are those who decide to stop buying the company's products. On the other hand, non-churn customers are those who continue to buy the company's products. Understanding customer churn is critical for businesses to identify the patterns, factors, and metrics that lead to customer churn. By analyzing churn behavior and its associated characteristics, companies can develop strategies to retain existing customers, improve customer satisfaction, and reduce customer churn. Predictive modeling techniques can also be applied to anticipate and proactively address potential customer churn, enabling companies to take proactive steps to retain at-risk customers[2].
Advances and future development prospects of the cross-fusion of computer graphics and artificial intelligence
Authors: Guo Yiling
Published: July 2024

The application of artificial intelligence is becoming increasingly widespread in today's society, and many fields are beginning to incorporate AI technologies. With the support of artificial intelligence, the processing of graphics and images is also being integrated with computer graphics. The cross-fusion of computer graphics and artificial intelligence is gradually becoming a new technological trend. This paper uses a comparative research method to explore the relevant technologies of the cross-fusion of computer graphics and artificial intelligence, aiming to elucidate its cutting-edge research and future development trends. The paper first introduces the background and significance of the cross-fusion of computer graphics and artificial intelligence and then provides a detailed introduction to the research methods and technologies. It then focuses on discussing cutting-edge technologies such as image generation and processing based on deep learning, as well as image-to-image translation and transformation. The paper also highlights the trends and challenges in this field and proposes possible solutions. Therefore, it can be concluded that the cross-fusion of computer graphics and artificial intelligence is becoming a trend in the development of image processing technologies. Investment should be increased to promote the rapid development of this process, which will undoubtedly lead to a better future.
Digital economy and entrepreneurial vitalityCausal inference based on double machine learning
Authors: Yin Niyuan
Published: July 2024

While digital economy provides entrepreneurs with convenient data elements, it also narrates their cognition due to its redundant information and data deluge. Based on the contradiction between the dilemma of information cocoon and the goal of wisdom sharing in the context of digital economy, this paper selects 248 prefecture-level cities in China from 2010 to 2019 as research samples and takes the policy of National Big Data Comprehensive Pilot Zone as the treatment variable, empirically analyzing the impact of digital economy on entrepreneurial vitality by the double machine learning model. The results indicate that: (1) Digital economy has a significant positive impact on entrepreneurial vitality; (2) Compared with the western region, the impact of digital economy on entrepreneurial vitality is more significant in the eastern and central regions, and there is heterogeneity among cities at different levels; (3) Optimizing the business credit environment and coordinating the digital infrastructure are two mechanisms between them.
Application of deep learning-based speech signal processing technology in electronic communication
Authors: Wu Yixuan
Published: July 2024

In recent years, the artificial intelligence boom triggered by deep learning is influencing and changing peoples lifestyles. People are no longer satisfied with human-computer interaction through simple text commands; instead, they look forward to more convenient and faster communication methods like voice interaction. Against the backdrop of innovative development, the application of speech signal processing systems is becoming increasingly widespread. Therefore, it is necessary to study the application of deep learning-based speech signal processing technology in electronic communication. This can provide more valuable references and assistance for future development, promoting the better development of deep learning-based speech signal processing technology in electronic communication. In this paper, we first review the application of deep learning in speech signal enhancement, speech recognition, and speech synthesis from a theoretical analysis perspective. Then, we discuss the application of deep learning-based speech signal processing in electronic communication, including the application of models such as Transformer, LAS (Listen, Attend and Spell), and GFT-conformer in speech signal processing. We also discuss some application scenarios of deep learning-based speech signal processing in electronic communication. Finally, we identify the need for deeper application of deep learning technology in speech signal processing and electronic communication, with continuous optimization and adjustment.
The development history and future prospects of artificial intelligence in facial recognition technology
Authors: Zhou Canbin
Published: July 2024

In recent decades, with the fast development of various algorithms and the rapid improvement of computer hardware performance, the development of facial recognition technology has been very rapid. This technology used to only appear in science fiction movies, but now it has been widely used in mobile payments, identity recognition, and other fields, and it also has very reliable performance. This article introduces the different facial recognition methods used in different periods of facial recognition technology from the 1960s and 1970s to the present day, to help people understand the development process of facial recognition technology. Among them, the focus is on early methods based on geometric features, grayscale information, and feature extraction, as well as recent applications based on deep learning and convolutional neural networks. In response to some challenges faced by current technology, some speculations on possible future development directions are proposed.
The effect of players' ability to resist monsters on immersion and fear in survival horror games
Authors: Yan Qiheng
Published: July 2024

Horror survival games, as a crucial segment of the video game industry, are highly regrded for their ability to evoke excitement, suspense and the challenge of overcoming obstacles and fears through wit and skill. This study delves into the impact of players' ability to confront monsters in horror survival games on their level of immersion and fear, and how these two psychological states mutually enhance the gaming experience. This research applies Python for natural language processing analyses, including sentiment analysis, keyword frequency analysis, Latent Dirichlet Allocation (LDA) topic modeling, and K-Means clustering to uncover the main trends in player feedback, which is based on 5,000 user comments scraped from the Steam platform on two famous horror games, "Resident Evil 7" and "Outlast 2." Additionally, data on players' personal experiences of fear and immersion in the games are collected through surveys. The results show that the sensation of fear and successfully confronting monsters significantly enhances players' immersion of being completely engaged in the game, highlighting the importance of balancing challenge and player's ability to make choices in game design. This study provides valuable insights into understanding the psychological dynamics of players in horror survival games, guiding game designers and developers on how to create more engaging and satisfying gaming experiences that meet players' requirements.
Exploring the horizon of AI development: Navigating constraints of chips and power in the technological landscape
Authors: Hou Wenwen
Published: July 2024

With the proliferation of AI technology, machine learning has emerged as a cornerstone of AI systems, facilitating pattern recognition and decision-making through robust data analysis. This encompasses various learning paradigms such as supervised, unsupervised, and reinforcement learning, all of which are indispensable for the advancement of artificial intelligence. Nevertheless, the development of AI necessitates substantial computational resources, with specialized chips serving as the linchpin, particularly in demanding tasks such as deep learning. Dedicated chip development, exemplified by GPUs and TPUs, plays a pivotal role in enhancing the performance of AI systems, notwithstanding challenges related to costs and market monopolies. Moreover, AI systems require significant power support, especially during the training of large-scale models. To address these challenges, this paper reviews the existing literature on modeling techniques aimed at enhancing the efficiency of machine learning and reducing energy consumption. This review encompasses optimal algorithm design, hardware optimization, and spatial modeling. Through the implementation of these approaches, the challenges posed by resource constraints in machine learning scenarios can be effectively mitigated, thereby fostering the continued development and application of AI technology.
Microleakage and depth of penetration of different materials used as pit and fissure sealants under wet conditions: An Invitro study
Authors: Karthika Vijay , Varghese Chacko , Sobha Kuriakose , Soumya Rajan , Suprasidh Suprakasam
Published: July 2024

Objectives: To compare the effectiveness of 3 types of pit and fissure sealants namely, glass ionomer sealants (GC FUJI VII), high viscosity GIC used as ART sealant (GC Fuji IX EXTRA), and hydrophilic resin sealant (Embrace Wet Bond) when placed under salivary contamination in terms of marginal leakage and depth of penetration.
Kepemimpinan Kepala Madrasah dalam Meningkatkan Budaya Organisasi Kondusif di MTsN 3 Sijunjung
Authors: Turrohma Mitra , Hendriani Suswati
Published: July 2024

This research is to examine how the role of the madrasa head plays an important role in creating a good organizational culture at MTsN 3 Sijunjung. A good organizational culture is very important to create an effective and productive educational environment. This case study was carried out using a qualitative approach, and data was collected through observation, documentation, and in-depth interviews. Studies show that madrasa heads have a strategic role in building a good organizational culture by using leadership strategies such as effective communication, staff empowerment, and continuous professional development. It has been proven that inspirational and participative leadership can increase employee involvement and motivation and create a harmonious and collaborative work environment. This research shows how important it is for madrasa heads to establish a good organizational culture, which helps improve education in madrasas
Pengaruh Metode Lattice Terhadap Hasil Belajar Operasi Perkalian Bilangan Cacah dengan Menggunakan Model PBL di Kelas IV Sekolah Dasar
Authors: Ahmad Syafri , Siregar Julinda Khoirunnisa
Published: July 2024

This study aims to determine the effect of using the lattice method on the learning outcomes of multiplication operations of integers in class IV elementary school. This research is experimental research in the form of Quasi Exsperimental Type Nonequivalent Control Group Design. The sampling technique used cluster random sampling. In hypothesis testing, simple linear regression test, correlation analysis, and t test were used. Based on correlation analysis, the experimental class obtained rxy 0.825 which is categorized as very strong. The coefficient determination value obtained is 68.06%, so it can be interpreted that the use of the lattice method has an effect of 68.06% on the learning outcomes of multiplying small numbers in class IV. Through the t-test in the form of an independent t-test based on the posttest scores of the experimental and control classes, a tcount of 2.04613 was obtained with a ttable of 2.014 at a significance level of 0.05. When the tcount and ttable are compared, 2.04613> 2.014. This means that Ho is rejected, and Ha is accepted, so it can be concluded that there is a significant effect of using the lattice method with the PBL model on the learning outcomes of multiplication operations of small numbers in class IV elementary schools
Pengaruh Kurikulum Merdeka Terhadap Pembentukan Karakter di SMP Islam Al-Azhar Cairo Palembang
Authors: Nisa Nurul Hidayahtun , Niswah Choirun , Ibrahim Ibrahim
Published: July 2024

This research aims to determine whether the implementation of the independent curriculum (kurikulum merdeka) has an impact on character development at SMP Islam Al-Azhar Cairo Palembang. The research population consists of 140 seventh-grade students at SMP Islam Al-Azhar Cairo Palembang. The instruments used for data collection are questionnaires and documentation. Data collection took place from April 25 to May 29, 2024. The data analysis technique used is simple linear regression analysis. The research results indicate, first, that there is an impact of the independent curriculum implementation on the character development of students at SMP Islam Al-Azhar Cairo Palembang. This is evidenced by the data analysis results, showing that the calculated r value of 0.712 is greater than the product moment table r value, which is 0.312 at a 5% confidence interval and 0.403 at a 1% confidence interval for N = 40. Second, the implementation of the independent curriculum has a high impact on the character development of students at SMP Islam Al-Azhar Cairo Palembang, as the calculated r value of 0.712 falls within the range of 0.600 to 0.800, indicating a high/strong interpretation
Tokoh-Tokoh Utsmani Muda dan Ide-Ide Modern dalam Islam
Authors: Mulyani Sri , Dahlan M , Rahmawati Rahmawati
Published: July 2024

This article aims to find out a brief history of the birth of the Ottoman Empire, young Ottoman figures and modern ideas in the Islamic world. This research method is a literature review using a qualitative approach. Data is obtained from articles published through google scholar. Data from selected articles were then analyzed using a descriptive approach to describe key findings, identify patterns and trends, and summarize key conclusions from the reviewed literature. The data analysis technique uses qualitative data analysis consisting of data reduction, data presentation, and conclusion drawing. The main finding of this article is that the Ottoman Empire was founded by the Oghuz Turkish tribe, with Ertugrul as its original founder, and then continued and strengthened by his son, Uthman bin Ertugrul, who is considered the main founder of the Ottoman Empire. The ideas put forward by the Young Ottoman leaders were influential in the period of renewal after the Tanzimat period. The Young Ottomans were originally a secret group founded in 1865 with the aim of overthrowing the absolute rule of the Ottoman Empire and pushing for a constitutional government. The Young Ottoman figures were active in carrying out secret movements. Their interactions with liberal thinkers from France and England exerted a significant influence on the Young Ottoman movement. Therefore, some of the changes they propose tend to be liberal in nature
Analisis Pembelajaran 4 Gerakan Tari Payung untuk Siswa Tunarungu Kelas VI di SLB Negeri Tamansari Kota Tasikmalaya
Authors: Rafifah Rifa , Ahmad Wakih Agus , Heris Mahendra Hatma
Published: July 2024

Dance arts are related to movement and musical rhythm, with a strong connection to hearing. This research is motivated by the researcher’s interest in the abilities of deaf students who can synchronize their movements with musical rhythms to achieve excellence. The purpose of this study is to describe the teaching methods, the four movements of Tari Payung, and the interest of deaf students in dance arts at SLB Negeri Tamansari in Tasikmalaya City. This research uses a qualitative method with a descriptive approach. Data collection techniques use triangulation to combine various data sources and techniques. Qualitative research aims to understand phenomena related to behavior, motivation, perception, and actions of subjects holistically. The research findings indicate that deaf students have a good interest in learning dance arts. Students demonstrate interest, enjoyment, attention, active participation, and good awareness. This is evident from their consistent attendance, enthusiasm during practice, and the achievements they have attained in dance arts education.
Dynamic Scheduling of Assembly Line Using Neural Networks for SARIA Industrial Complex-Sudan
Authors: Bukkur Khalid , Ahmed Khalil , Shukri Mohamed
Published: July 2024

In this paper, neural network was developed to improve the dynamic scheduling of SARIA industry complex. This work implemented into two modules: modeling system by time calculation, the main purpose of this modeling is to calculate the total manufacturing times of the products. The second module is the neural network model architecture, constructed to hold a real-time optimization schedule to solve dynamic scheduling problems. Analytical model was built, included collection and manipulation of data, time calculations and the neural networks model was formulated. Several training tests were carried out, then the dynamic scheduling formulated. To assess the validity of the system and to investigate the efficiency and robustness of the system, the results were compared with those obtained from SARIA. The results reveal that the total time of products demand is easy calculated, and the system agile to scheduling any change occur in the demand, also the proposed system reduces 4 shift days for one demand. So the developed neural network leads to minimize the total costs.
Pairing Relative Gain Array (RGA) and System Stability in Distillation Column
Authors: Mervat Abdo Ahmed  , Salma Omer Alhag  , Gurashi Gasm alssed
Published: July 2024

The stability of distillation system has always been difficult to determine due to the nonlinear natural of the unit operation. In this work the Relative Gain Array RGA of MIMO were obtained to pair the loops that give minimum interaction in a distillation column. Wood and Berry 2X2 and Ogunnaike and Ray 3X3 were taken as case studies. the procedure is to compute the Relative Gain Array RGA by firstly getting the matrix at s=0. From the matrix obtained the inverse was calculated, from the inverse the transposed was made and the Relative Gain Array RGA was calculated by multiplying elements of transposed by elements of the matrix, from Relative Gain Array RGA the loops that gave minimum interaction were specified. The loops selected were subjected to stability analysis; which were plotted using MATLAB software. The results show that the systems are unconditionally stable. RGA can easily be used to select loops with minimum interactions; they are the tools to be applied wherever complex control MIMO systems are applied.
Study Performance of Floating Columns Subjected to Vertical Loads
Authors: Abdelrahim Abdalla Bashir  , Mohammed Kamal Satti , Mahgoub Elhaj Mahgoub Kambal
Published: July 2024

In many cases, we need large areas in the building that are free of columns, especially on the lower floors, such as the ground floor and the basement, in order to use them as car parking or otherwise. The load path will change and new terms will appear, including the term ”floating column”, which is the column above the removed column, and the term Transfer beam, is the beam that the floating column is based on it as a concentrated load and then transfers the loads to the adjacent columns. In this paper, the effect of vertical load on a concrete building containing a floating column has been studied and compared to another one without a floating column. Also, the results of the Transfer beam were compared in a number of parameters such as moment, shear force, and deflection. A building consisting of G+4 was studied and analyzed using ETABS, SAFE, and Midas programs, A number of results were reached, the most important is the concept of load path redistribution, also this paper concluded that in normal buildings case all beams have an approximately equal result of bending, shear, and deflection but in floating column building the beams above the Transfer beam have different values which decrease when going upward.
Evaluation of Hazards and Operability Study for Optimization Operation of Industrial Processes
Authors: Eljack Eltieeb Abuzar Abbas , Abdalla Babiker , Elamin Nagmeldin
Published: July 2024

Nitrocellulose is a substance that ignites easily when exposed to a hot or humid environment. It is widely used in the military as well as civil industries, most notably the production of explosives and films. Therefore, it was selected as a case study in order to assess the risks in the seven production stages using HAZOP (Hazards and Operability) technology. In this study, the raw material preparation stage investigated. This stage was divided into five identified nodes. The deviation from the design intention for 16 critical parameters for this process was studied.The findings of the study were as follow: Nitric acid and sulfuric acid are stored for a long time under process shutdown resulting in the corrosion of the tank and acids decomposition, Acids measurement depend on operator competence in the process of preparation of the acid mixture, which leads to inappropriate operating conditions, the temperature of the acid mixture increases due to endothermic mixing process resulting in decomposition of the mixture, in the process of feeding RC to the reactor, the flow increases due to the increase in the speed of the belt affecting the degree of nitration. Recommendations are; It should not be turned off until the end of the acids, thermoneutral process was wanted and Adjust the RC flow speed every 10 operations.
ANN Based Location of Fault for 500KV Transmission Line in Sudan from Merowe to Atbara
Authors: Alnour Mustaffa Mohammed , Mohamed Hussein Eltahir , Ishag Ahmed
Published: July 2024

Today, transmission lines have become one of the important core components in systems of electrical power that are used to transport energy. Since transmission lines are prone in nature, the probability of failures in transmission lines is generally higher than that of other major components. This paper presents the fault of the transmission line from Merowe to Atbara in northern Sudan using artificial neural networks. A transmission line model was created in MATLAB R2014a using SIMULINK and SIMSCAPE with the SIMPOWERSYSTEM toolbox. The current and voltage values obtained from the transmission line model have been used as an entry for artificial neural networks. The results obtained from the proposed artificial neural networks were acceptable and the networks were found to be practically practicable for implementation. The significance of picking the most proper artificial neural network, to get the best performance from the neural networks.
Effects of Ferromagnetic Cores in Wireless Power Transfer System for Charging Electric Vehicles
Authors: Kamal Eldin Idris Elnail , Kamal Eldin Idris Elnail
Published: July 2024

Wireless Power Transfer (WPT) technology for charging Electric Vehicle (EV) batteries is promising technology. System performance improvement and reducing Electromagnetic field (EMF) leakage are the key factors in designing an optimum charger. In this paper, adding ferrite disk to the WPT resonator is intensively studied. Three case studies are proposed, including coils only without ferrite, ferrite disk is used to the transmitting coil, and ferrite disks are used with the two coils. Finite Element Method (FEM) software is used for designing 3 kW-class, 20cm transfer distance, 85 kHz charger. The simulation results are recorded andcompared with regard to the system coil-to-coil efficiency and the EMF levels above the receiving coil and inside the air-gap. The results show that adding ferrite disks is significantly enhanced the system performance as well as reduced the EMF surrounding the charger.
An error Prevention using Deep learning to Solve Disassembly Line Balancing Problem
Authors: Damos Nadir A.Siddig , Damos Zeqiang Zhang , Damos Abdallah mokhtar , Damos Ahmed Abualno
Published: July 2024

The disassembly line has issues with balancing the disassembly, including worker errors and the influence of these errors on worker productivity, disassembly idle time, loss of smooth work, accumulation and blockage of some work stations, and the lack of effectiveness of other work stations. In this paper, a new novel technique for balancing the waste products disassembly line is proposed, and this method depends on the machine’s vision to assist workers in performing the essential tasks. The findings of comparing the performance of workers with and without assistance with the proposed method were as follows: Worker productivity increased by 50%, idle time was reduced by 77.8%, the number of workstations was reduced by 33.3%, and the error rate was reduced by 81.5%
Counter: A Novel Scheme Ensuring Compliance and Privacy in Cryptocurrency-Based Blockchain
Authors: ELFADUL ISSAMELDEEN , Wu Lijun , Egide Nkurunziza , Ahmed Mohamed
Published: July 2024

An extremely secure cryptocurrency, commonly known as the Decentralized Anonymous Payment System (DAP), stands as one of the most innovative and widely embraced applications in the field of blockchain. Although the DAP provides a strong degree of transaction privacy and user anonymity, it has been utilized illegally in criminal activities, constituting security challenges to governments and financial institutions. In this paper, we propose a solution known as Counter: A Novel Scheme Ensuring Compliance and Privacy in Cryptocurrency-Based Blockchain, which aims to preserve transaction privacy while providing governments with supervision and enforcing regulations over transactions. Our suggested counter imposed limitations on the transfer of large amounts of cryptocurrencies and also imposed a restriction on the trading of cryptocurrencies during specific time periods. The principal feature of our proposed system involves employing the Order-Preserving Encryption (OPE) and Pedersen Commitment to implement a financial policy ensuring that the transferred amount remains within the allowed range and does not exceed the limit. Besides, we utilized the Unix timestamp to guarantee that the transaction is carried out within the allowed date and time frame. We utilized the RSA accumulator to provide government supervision and enforce regulations. Our suggested counter employs the combination of the ring signature, Pedersen Commitment, and stealth address to protect transaction privacy. Our system fulfills all the security requirements for organizing digital assets that have been defined by international financial institutions and authorities. Finally, the assessment shows that our system is effective and efficient compared to other systems.
Prediction of Global Solar Radiation across the Region of Northern Sudan
Authors: Wageiallah Mohammed Osman , Ahmed Elmahi Fathelrahman
Published: July 2024

Available data for solar resources indicates that northern Sudan has solar potentials among the highest in world. However, in this vast area (about 471×103 km2) only two stations, at Hudeiba and Dongola, have records for global solar radiation. Four other stations (at Atbara, Karima, Abu-Hamed and Wadi-Halfa) in this region have records for sunshine duration. In this study, recorded data at Hudeiba and Dongola stations have been used to develop 15 models for estimation of monthly average daily global solar radiation on a horizontal surface in northern Sudan. The developed models have been extensively evaluated by using 14 statistical indicators. All developed models revealed good performance (percentage errors within ±4.5%). Then, the most accurate regional model (Model M3) has been used to predict the global solar radiation at Atbara, Karima, Abu-Hamed and Wadi-Halfa stations. Results showed that the whole region receives abundant solar energy throughout the year. The yearly average of daily global solar radiation over the entire region is 23.16 MJ/m2. Furthermore, the developed models can be used to predict global radiation at adjacent places that lack such data.
Factors Affecting Domestic Violence against Rural Educated and Uneducated Women in Bangladesh: A Sociological Analysis
Authors: Mahmuda Sayda , Mazumder Subarna , Rahman Sk. Naimur
Published: July 2024

All societal and economic strata are negatively impacted by the problem of domestic violence. Although the government of Bangladesh is making efforts to address the problem of domestic violence, the nation is ranked fourth worldwide for violence against women. Thus, the purpose of this study is to explore the pattern and causes of domestic violence against rural educated and uneducated women in Bagerhat district of Bangladesh. In this study, district and upazila were selected purposively whereas union, village and respondents were selected using simple random sampling technique. Using random sample procedures, a total of 100 rural women were chosen. The data was analyzed using tabular, graphical, and descriptive statistics. It is found from the socioeconomic analysis of the study that the mean age of the rural women in the study area is 29.05 years. In terms of educational status, it is seen that 13% respondents had primary education while 19% had secondary education with the average years of schooling of women is 6.23 years. It is observed that 35% women were housewife, 15% were NGO worker and10% health worker. Findings of the study reveal that husband was the main culprit for committing domestic violence against women in 64% cases while sister-in-law are responsible for committing violence in 16% cases. Findings of the study indicate that 28% educated women experienced physical violence whereas 78% uneducated women experienced physical violence in their life. In case of women affected by psychological violence, it is seen that 58% educated women affected by psychological violence while 64% uneducated women affected by physical torture violence. In terms of women affected by economic violence, it is seen that uneducated women (86%) are more affected than educated women (42%). Result of the study shows that 38% educated women and 56% uneducated women believe that poverty is responsible for committing domestic violence against women. Considering media violence as a cause of domestic violence, it is observed that 56% educated women and 55% uneducated women believe media violence is responsible for domestic violence against women. In addition, 57% educated women and 59% uneducated women believe that marital conflict is a main factor which are contributing domestic violence against women.
Mławski Obwód Armii Krajowej (wybrane zagadnienia)
Authors: Arent Leszek Andrzej
Published: July 2024

Mławski Obwód Związku Walki Zbrojnej, a następnie Armii Krajowej był jednymz wielu podstawowych elementów wielkiej organizacji wojskowej, jakąbyło konspiracyjne wojsko polskie w okupowanym kraju. Armia Krajowa stanowiłapodstawę Podziemnego Państwa Polskiego, a jej głównym celem byłoprzygotowanie podstawowych ogniw do przeprowadzenia powstania powszechnego,w końcowej fazie niemieckiej okupacji. Równolegle prowadzonebyły także systematyczne działania wywiadowcze, służące do osiągnięciazakładanych celów i dywersja przeciwko okupantom. Obwód mławski prowadziłdziałalność z polecenia władz zwierzchnich wojska konspiracyjnego,działającego z rozkazu konstytucyjnych władz polskich na emigracji. Podobniejak w innych regionach niemieckiej okupacji, w obwodzie mławskim nieudała się próba wcielenia innych związków bojowych, działających z inicjatywyposzczególnych ruchów niepodległościowych: Batalionów Chłopskich zeStronnictwa Ludowego „Roch” czy Narodowych Sił Zbrojnych z Obozu Narodowego.Obwód mławski pomimo niezrealizowania podstawowego celuw ramach akcji „Burza” spełnił swoje zadanie przez samo funkcjonowanie.Była to organizacja, która w świadomości lokalnej społeczności swoją obecnościązapewniała względne bezpieczeństwo, podtrzymywała chwiejnychludzi od współpracy z okupantem, a niebezpiecznych współpracownikówwładz okupacyjnych likwidowała na mocy wyroków sądów podziemnych.
Poziom partycypacji publicznej mieszkańców Siedlec
Authors: Niewęgłowska Aneta , Niewęgłowski Marek , Niewęgłowski Maciej
Published: July 2024

Przedmiotem opracowania jest przedstawienie zagadnienia zaangażowaniamieszkańców Siedlec w życie społeczne. Starano się określić, jaki modelpartycypacji był realizowany przez Siedlczan. W badaniach ankietowych,przeprowadzonych w 2019 r. wśród stu mieszkańców Siedlec, pytano respondentówo trzy formy działań realizowanych w mieście, czyli informowanie,konsultowanie i delegowanie, a te rozważano w odniesieniu do gotowości,oczekiwań i oceny władz przez obywateli. Artykuł prezentuje wybranebadania przeprowadzone w ramach pracy dyplomowej podejmującej tematpartycypacji publicznej na przykładzie miasta Siedlce, napisanej na WydzialeAdministracji i Nauk Społecznych Politechniki Warszawskiej.
Artificial Intelligence in Education World: Opportunities, Challenges, and Future Research Recommendations
Authors: 'Alam Ghasa Faraasyatul , Wiyono Bambang Budi , Burhanuddin Burhanuddin , Muslihati Muslihati , Mujaidah Ani
Published: July 2024

Artificial Intelligence (AI) is revolutionizing various aspects of life, including education. AI in education (AIEd) fosters teachers' understanding of students' learning processes, offers personalized and adaptive learning, and provides instantaneous feedback. It has the potential to improve academic performance and reduce educational disparities. This study aims to engage researchers, policymakers, teachers, students, and engineers in a dialogue about AIEd. It provides an overview of studies on opportunities, challenges, and recommendations for future research, focusing on specific educational outcomes. A comprehensive perspective is needed to understand the function of AIEd. This research utilizes bibliometric analysis and systematic literature review to analyze AIEd, presenting results as a specific bibliometric network using the VOSviewer tool. Research findings that AIEd-based environments are enhancing student learning, but their personalized learning is still in its experimental stage. Challenges include a lack of resources and ethical concerns. AI chatbots and interactive books aid language learning, but they also have advantages and disadvantages. The humanities must balance these advantages and disadvantages.
Synthetic Classification of Provinces and Cities in Vietnam as a Guide for Regional Policy
Authors: Bondarenko Ksenia A. , Afonina Angelina Gennadievna
Published: July 2024

Vietnam is a country with a relatively high level of regional inequality. The General Statistics Office of Vietnam groups the provinces based on their geographic location. This article presents the classification of the provinces and cities of Vietnam based not only on geography, but also on their socio-economic characteristics, economic structure, and the membership in free economic zones (FEZs). The analysis identifies four groups of provinces and cities: i) highly developed (FEZ members with high GRP per capita and a developed technological industry) ii) developed (FEZ members with high untapped economic growth potential and a highly diversified economic base), iii) moderately developed (with a vast primary sector and high potential for the development of the tourism sector) and iv) less developed (the poorest regions). The article highlights individual provinces, the level of socio-economic development of which (ceteris paribus) will allow them to transfer towards the group of more developed provinces in the near future. In order to reduce inequality in other provinces, we propose to use approaches, which have been successfully implemented in highly developed and developed regions, such as incentives for foreign investors or tax preferences for the development of significant industries in individual provinces.
National Heroes of Vietnam through the Lens of State Myth-making
Authors: Terskikh Mikhail A.
Published: July 2024

The elevation by the state of certain historical characters to the rank of national heroes is always myth-making, which pursues its own goals. To understand such goals in relation to Vietnam, it seems important to consider its national heroes, especially since their list is actually determined at the state level.
An analysis of the “official” national heroes of Vietnam allows us to draw a number of conclusions. The choice of characters is largely «Sino-centric», which generally reflects the role of the northern neighbor in the history of the Vietnamese state and its worldview in the modern period. Most of the heroes are military leaders and heads of state (mainly who went down in history because the resistance to the Chinese), and not cultural figures, science or art. At the same time, their official biographies are always close to the image of an ideal person, regardless of actual actions. Here one can see the Confucian basis of Vietnamese society, in which history is always positive. Noteworthy is the apparent lack of figures from the last two centuries (with the exception of Ho Chi Minh), which seems to reflect the following peculiarity of the political culture of Vietnam: power usually avoids personification. Also interesting is the modest number of characters associated with Buddhism and religion in general, which may be a consequence of the course taken in the last century to build socialism, which presupposes an atheistic view of the world.
The Impact of Climate Changes on Environmental Conservation in Coastal Tourism and Beach Resort
Authors: Alhemimah Arej , Agina Mohamed Fathy , Alotaibi Salman , Semlali Yahdih , Aliane Nadir , Abdou Maha Y.K. , Hassan Thowayeb H. , Ahmed Mohamed
Published: July 2024

Coastal tourism and beach resorts are considered the most vulnerable tourism activities to climate change. This paper seeks to achieve two objectives: first, to examine climate change's impact on the value of tourists' experience in coastal tourism and beach resorts; Secondly, to identify the adaptation strategies applied to coastal tourism and beach resort hotels to reduce the negative effects of climate changes. A quantitative approach was adopted in this research to test the study hypotheses. Hurghada was selected as a case study. A convenience sample technique was chosen in this research to collect data from visitors of coastal tourism and beach resort hotel guests. A total of 250 questionnaires were distributed, and only 175 were returned and valid for analysis with a response rate of 70%. The findings showed that coastal tourism and beach resort hotels on the Red Sea are highly vulnerable to potential climate change risks such as floods, rising sea levels and rising temperatures. Also, the findings showed that climate changes negatively affect coastal tourism and beach resort hotels, affecting the value of the tourist experience. In addition, the results indicated that coastal tourism and beach resort hotels on the Red Sea coast in Hurghada are exposed to significant financial losses due to the threats of climate change. Beach resort hotels must be able to adapt to climate changes and mitigate their effects.
The Beginnings of Steroid Chemistry in The Czech Lands
Authors: Drašar Pavel
Published: July 2024

Steroid research in the Czech Republic has a long tradition, and this article takes the liberty of summarizing the most important details and information that the author remembers and that he managed to find.
Production of Steroid Hormones in Galena Opava
Authors: Cvak Ladislav
Published: July 2024

The drug product Antigest of the company Spofa was launched as soon as in 1965 and Czechoslovakia thus became forth country in the world where oral anticonception was introduced. The gestagen component of Antigest was methenmanidon acetate (superlutin), an original substance developed in the Research Institute of Natural Drugs. Superlutin and some other steroid drugs were produced in the Galena Opava plant. In the article, all the syntheses utilized in the manufacture of steroid drugs in Galena are described and the reasons why the manufacture of steroid drugs was terminated at the beginning of eighties are explained.