bluuebunny/crossref_metadata_2025 huggingface dataset:
How to Retell the Chinese Myths in the Neo-Mysticism: The Analysis of the Chinese Mythology Game
Authors: Qin Jiayang
Published: February 2024

Under the cultural wave of "neo-mysticism" in the 1990s, countries began to carry out "myth retelling" activities. It subverts traditional mythological values, deconstructs and constructs the meaning of traditional mythology, and embodies the value of contemporary mythology. In the context of contemporary neo-mysticism, the retelling of myth has been inextricably linked with the cultural production focusing on content and creativity. As a new mass culture consumer goods after film and television and music, with the help of the communication advantages of new media, the scope of cultural radiation of games is increasing and its influence is becoming more and more extensive. It becomes a global popular culture phenomenon. And it is also coerced into the whirlwind of neo-mysticism that swept the world. The wedging of myth enriches the cultural meaning and content creativity of the game, and completes a cultural communication with its global entertainment consumption. Therefore, this study focuses on the emerging trend of neo-mysticism. Through participatory observation of role-playing games - Honor of Kings and Lady White Snake, in-depth interview and questionnaire survey of game users, this study deduces and summarizes the techniques of myth retelling involved in the game, in order to provide reference for the mythological retelling of other art forms, and promote the spread of Chinese mythological culture under the trend of neo-mysticism.
Study on Stress Intensity Factor of Girth Weld with Crack Defects
Authors: Yu Hao , Li Jun , Zheng Nenghong
Published: February 2024

In order to study the safety performance of the girth weld with cracks in the pressure vessel in use, based on fracture mechanics, this paper adopts ABAQUS and FRANC3D joint simulation to calculate the crack tip stress intensity factor(SIF). The influence of crack location, length and depth on the stress intensity factor of crack tip is analyzed. The results show that the crack SIF at different crack locations (inner crack > buried crack > outside crack) increases with the increase of crack length and increases with the increase of crack depth.
Development Path of Hotel Tourism Specialization in Vocational Schools based on the Integration of Industry-University-Research Integration
Authors: Wang Linlin
Published: February 2024

Accompanied by the booming development of the global tourism industry and the growing hospitality industry, the training demand for hotel tourism majors has become more and more significant. However, how to cultivate high-quality professionals who are adapted to the needs of the industry and have practical skills and innovative thinking has become an important challenge for hotel tourism majors in vocational schools. Based on this, the article launched a study on the development path of hotel tourism profession in vocational schools based on the integration of production, learning and research, analyzed the significance of the development of hotel tourism profession in vocational schools based on the integration of production, learning and research, elaborated the problems of the development of hotel tourism profession in vocational schools based on the integration of production, learning and research and gave effective measures to solve the problems, aiming to cultivate more professionals with practical operation ability and innovative spirit through the study.
Prediction of Atmospheric Carbon Dioxide Radiative Transfer Model based on Machine Learning
Authors: Duan Shiheng , Liu Yuxiang , Li Linxiao , Pan Yiming
Published: February 2024

Global warming is caused by the increasing amount of greenhouse gases in the atmosphere. The Kyoto Protocol to the United Nations Framework Convention on Climate Change defines carbon dioxide (CO), methane (CH:), nitrous oxide (N0) fluorocarbons (HFC), holocarbon (PFC), and sulfur hexafluoride (SF.) Six gases are divided into the main greenhouse gases, of which CO, the largest proportion of emissions, is an important man-made greenhouse gas." As the main gas affecting the global greenhouse effect (75%), the amount of CO in the atmosphere has increased from 315 ppm in 1958 to 417 ppm in 2022, and global annual CO emissions have increased from 27 Pg to 49 Pg% over the past 40 years. Therefore, under the background of deep reinforcement learning, it is a problem that all countries pay more attention to predict the concentration emission of carbon dioxide to cope with the severe situation of climate warming. In order to obtain the radiative forcing value under the influence of carbon dioxide concentration, a simplified net radiative flux model is established. Based on the radiative transfer equation, this model can calculate the net radiative flux and radiative forcing of each layer of the atmosphere due to changes in carbon dioxide concentration. The results are compared with the RRTMG-LW long-wave radiative transfer model of American Center for Atmospheric and Environmental Research (AER) under the same factor, and the error is less than 1%.
Milling Stability Prediction under Multi-effect Synergy
Authors: Liao Jing , Zheng Hualin
Published: February 2024

During the milling process, chatter vibration is prone to occur when the spindle, tool, and workpiece interact with each other under certain parameters, which seriously affects machining efficiency and reduces machining quality. Therefore, it is necessary to study the mechanism and influencing factors of chatter vibration, predict the stability of the milling system through a multi-effect synergistic dynamic model, and obtain the machining parameters of stable milling through analysis. Based on the traditional milling model, this article considered the regeneration effect, process damping effect, and modal coupling effect, and also considered the friction effect of the front cutting surface for friction-induced chatter, to make the model’s prediction range more accurate. Then, a milling dynamic model was established combining multiple effects, and its stability lobe diagrams were solved by the full-discretization method. The accuracy of the model was verified through milling stability experiments. The experimental results are basically consistent with the predicted stability lobe diagrams, indicating that the milling stability prediction model considering multi-factor coupling of the milling model is correct. Finally, the influence of various effects on milling stability was analyzed, with a focus on the influence of friction effects.
Research on the Path and Strategy of Basic Education Management Innovation
Authors: He Hao
Published: February 2024

With the continuous development of social economy, the status of education in the development of countries is getting higher and higher, and the basic education management also plays an important role in the education system. The Party and the government have always attached great importance to education, and have made a series of important arrangements for the cause of education. The education management department must constantly strengthen the innovation in the management of basic education, so as to improve the quality of basic education and promote the all-round development of students. Based on this, this paper starts with the importance of basic education management innovation, and discusses the difficulties of basic education management and the path and strategy of innovation, in order to provide a theoretical and practical basis for the innovation of education management system.
Research on Preventing Medical Information from Leaking based on Homomorphic Encryption
Authors: Rao Kangwei
Published: February 2024

The security and privacy protection of medical information is one of the important challenges facing today's society. Disclosure of medical information can lead to invasion of patient privacy, reputational damage to medical institutions, and potential legal liability. Therefore, it is very important to take effective measures to prevent the leakage of medical information. Information encryption is a common technical means, which can effectively protect the security and privacy of medical information. The purpose of this paper is to discuss how to prevent medical information leakage through information encryption. First, we describe the sensitivity and importance of medical information, as well as the current security challenges. Then, we discuss in detail the basic principles of information encryption and common encryption algorithms, including symmetric encryption and asymmetric encryption. Next, we explore the specific application scenarios of medical information encryption, such as electronic medical records, medical images and encryption protection during transmission. We also discuss the advantages and challenges of healthcare information encryption and propose some solutions such as key management and access control. Finally, we summarize the importance of information encryption in preventing medical information leakage and emphasize the need for further research and practice to ensure the security and privacy protection of medical information.
Design and Implementation of DDS Signal Generator Based on FPGA
Authors: Li Shun
Published: February 2024

With the rapid development of semiconductor technology, the digital circuit of the control chip gradually replaces the analog circuit of the traditional signal generator, which improves the performance of the signal generator and reduces the cost of research, development and production. This paper proposes a design scheme that takes FPGA chip as the control center. The signal generator system mainly includes DAC module, FPGA module and key module. The system uses Verilog language to develop the sine wave digital signal generation and key switching frequency control logic circuit on FPGA. The frequency control word circuit in the FPGA module provides multiple frequency sine wave selection, and the look-up table circuit realizes the reading of different phases by controlling the read address of the ROM. The 14-bit high-speed DAC module converts the digital signals sent by FPGA into analog signals. The DAC module integrates low-pass filter processing to increase the smoothness of the signal. After testing, the system meets the design requirements.
Research on Higher Education Management and the Cultivation of Innovation and Entrepreneurship Abilities in University Students
Authors: Lin Minyi
Published: February 2024

Educational management plays a crucial role in higher education, profoundly influencing the implementation of various educational initiatives. Despite widespread innovation and exploration in education reform across various institutions, the predominant focus often revolves around technological advancements and changes in teaching methodologies. There is relatively less attention given to innovations in teaching management, resulting in insufficient support for educational management. Given that higher education serves as a primary platform for cultivating future societal leaders and innovative talents, the close relationship between management research and the development of innovation and entrepreneurship abilities in university students becomes particularly significant. This paper aims to delve into the role of higher education management in fostering the cultivation of innovation and entrepreneurship abilities among university students, with the goal of providing more effective management strategies and training models for universities. Through an in-depth exploration of higher education management, this research aims to offer valuable insights to propel the education system toward better alignment with the demands of the contemporary era.
The Economic Impact and Application Challenges of IoT Technology in Smart Home and Infrastructure
Authors: Huang Changquan , Chen Qingle , Lin Zizhuo , Su Wangpeng , Zhang Zhiqi , Liu Suping
Published: February 2024

This paper takes an in-depth look at the Internet of Things (IoT) and its transformative impact on smart homes and infrastructure. It delves into the evolution of IoT technology, its economic impact, the challenges it poses, and strategies to overcome them, supported by real-world case studies. The paper begins with an overview of the historical development of the IoT, tracing its roots from basic automation to complex connected systems in homes and cities. The paper highlights how the IoT is evolving, integrating into our daily lives and reshaping the way we interact with our living and working environments. The report takes a broad look at the economic impact of the IoT, revealing how it is revolutionizing market dynamics by increasing efficiency, reducing costs and creating new business opportunities. The analyses include data-driven insights into smart home energy efficiency and smart city infrastructure operational efficiency. In addition, the report discusses the impact that the proliferation of IoT will have on the job market and skills requirements. Addressing the challenges faced by IoT, the paper identifies key areas, including technical barriers such as interoperability and security, social issues such as privacy and digital divide, and environmental issues such as e-waste and sustainability. The paper proposes comprehensive strategies and solutions involving policy reforms, technological advances, and co-operation between the public and private sectors. The paper presents practical examples of IoT applications through a series of case studies that illustrate successes and challenges in different regions and sectors. These case studies provide valuable insights into the real-world applications and outcomes of IoT technologies. Finally, the paper summarises the discussion on IoT, highlighting its potential to significantly improve the quality of life and the efficiency of urban systems. It emphasises the need for a balanced approach to address the complexities and responsibilities associated with IoT advances to ensure a sustainable and equitable technological future.
Digitization, the Free Flow of Factors and the Coordinated Regional Development
Authors: Zhang Mingrui
Published: February 2024

In recent years, the digitization with the big data and information technologies as the core has effectively changed the flow mode of production factors, and increasingly shows the kinetic energy and potentials of affecting the coordinated development of regions. How does data and digitization affect the flow of factors, and what paths and mechanisms are used to promote the regional coordinated development? The answers to these two questions are increasingly becoming the underlying logic of relevant academic research and policy making. Based on this, relying on the spatial configuration model (SMM), this paper establishes the digital factor flow model, which proves the "inverted U-shaped" development trend of digitization - expanding the regional development gap in the short term and bridging the gap in the long term. Subsequently, in this paper, three empirical models are established to verify the "inverted U-type" conclusion, and to further discuss the relationship between digitization, free flow of factors and the coordinated regional development. Finally, this paper puts forward that local governments should scientifically understand the role of digital factors in promoting the free flow of factors, rationally perceive potentials of digitization in bridging regional development gaps, and give full play to the role of macroeconomic regulations and guidance to improve the underdeveloped digital infrastructure, promote the inclusive development of digital economy, better serve the underdeveloped western regions in China, and finally, to promote the coordinated regional development.
Implementation of an AI-based MRD Evaluation and Prediction Model for Multiple Myeloma
Authors: Chen Jianfeng , Xiong Jize , Wang Yixu , Xin Qi , Zhou Hong
Published: February 2024

With the application of hematopoietic stem cell transplantation and new drugs, the progression-free survival rate and overall survival rate of multiple myeloma have been greatly improved, but it is still considered as a kind of disease that cannot be completely cured. Many patients have disease recurrence after complete remission, which is rooted in the presence of minimal residual disease MRD in patients. Studies have shown that positive MRD is an independent adverse prognostic factor affecting survival, so MRD detection is an important indicator to judge the prognosis of patients and guide clinical treatment. At present, multipa-rameter flow cytometry (MFC), polymerase chain reaction (PCR), positron emission tomography (positron emission) Several techniques, such as PET/computer tomography (CT), have been used for MRD detection of multiple myeloma. However, there is still no cure for the disease. "IFM2013-04" four clinical studies confirmed for the first time that proteasome inhibitors (PIs) and immunomodulatory drugs, The synergism and importance of the combination of IMiDs in the treatment of MM, the large Phase 3 clinical study SWOG SO777 compared the combination of bortezomib plus lenalidomide and dexamethasone. The efficacy of VRD and D established the status of VRD first-line treatment of MM, and due to the good efficacy of CD38 monoclonal antibody in large clinical studies, combination therapy with VRD has been recommended as the first-line treatment of MM. However, to explore the clinical value and problems of applying artificial intelligence bone marrow cell recognition system Morphogo in the detection of multiple myeloma minimal residual disease (MRD).
An evaluation of the impact of ChatGPT on network security
Authors: Zheng Qizhong
Published: February 2024

ChatGPT, a very advanced natural language generation model, represents a momentous paradigm shift inside the realm of the internet. ChatGPT, which was made available to the public by OpenAI on November 30, 2022, is an enhanced version of OpenAIs GPT-3.5 model. It has been further developed through the implementation of fine-tuning methods that combine both supervised and reinforcement learning approaches. Furthermore, it provides a client interface that is easy to use, allowing users to actively participate in interactive question-and-answer exchanges with the model. Nevertheless, the utilization of these chatbots likewise presents noteworthy cybersecurity concerns that necessitate attention. The primary objective of this research study is to examine the cyber dangers that are inherent in the utilization of ChatGPT and other comparable AI-driven chatbots. This investigation will encompass an analysis of potential vulnerabilities that may be susceptible to exploitation by individuals with malevolent intent. Additionally, the paper proposes strategies for mitigating the aforementioned cyber risks and vulnerabilities.
Asynchronous Federated Learning: Methods and applications
Authors: Liu Yifan
Published: February 2024

Federated Learning (FL) is a distributed alternative to traditional machine learning frameworks that computes a global model on a centralized aggregation server according to the parameters of local models, which can address the privacy leakage problem caused by collecting sensitive data from local devices. However, the classic FL methods with synchronous aggregation strategies, in many cases, shall suffer from limitations in resource utilization due to the need to wait for slower devices (stragglers) to aggregate during each training epoch. In addition, the accuracy of the global model can be affected by the uneven distribution of data among unreliable devices in real-world scenarios. Therefore, many Asynchronous Federated Learning (AFL) methods have been developed on many occasions to improve communication efficiency, model performance, privacy, and security. This article elaborates on the existing research on AFL and its applications in many areas. The paper first introduces the concept and development of FL, and then discusses in detail the related work and main research directions of AFL, including dealing with stragglers, staleness, communication efficiency between devices, and privacy and scalability issues. Then, this paper also explores the application of AFL in different fields, especially in the fields of mobile device edge computing, Internet of Things devices, and medical data analysis. Finally, the article gives some outlook on future research directions and believes that it is necessary to design efficient asynchronous optimization algorithms, reduce communication overhead and computing resource usage, and explore new data privacy protection methods.
Face recognition technology based on ResNet-50
Authors: Liu Jingyu
Published: February 2024

Face recognition technology is progressively finding its place across diverse domains. In pursuit of enhancing the efficacy of face recognition systems, this study employs a ResNet-50 deep convolutional neural network. The dataset is meticulously gathered and processed via OpenCV, thus amplifying the precision and utility of face recognition. ResNet, an advanced convolutional neural network, incorporates the concept of residual connections, bridging convolutional layers through shortcut connections. These connections facilitate the addition of input to output, forming residual blocks. Consequently, ResNet-50 efficiently tackles the vanishing gradient issue, enabling the training of exceptionally deep networks. With 49 convolutional layers and a fully connected layer, ResNet-50 boasts a robust architecture. To emulate varying brightness conditions, post-collection image adjustments are applied randomly. This strategy curbs the impact of divergent lighting scenarios on recognition accuracy, bolstering the models practical applicability. Notably, experimental outcomes underscore the commendable performance of the trained ResNet-50 model in face recognition trials. This substantiates the broad-spectrum viability of face recognition technology in domains such as security surveillance, human-machine interaction, identity verification, and beyond.
Echo cancellation using Artificial Intelligence technique
Authors: Lin Ziyang , Xu Jincheng , Yang Yuxuan , Zeng Yichen
Published: February 2024

To improve the audio quality in telecommunication, echo cancellation was proposed to prevent signals from re-appearing. Generally speaking, the echo canceler first recognizes the original transmitted signal that appears again due to delay in the transmitted or recieved signal. Then, the echo canceler subtracts the echo in the signals. Commonly, echo cancelers are calledacoustic echo cancellation (AEC) in general, whether they aim for acoustic echo, line echo, or both. However, in modern times, new problems have been emerging which require more innovative, more advanced methods to tackle the echo issue. Thus, the paper reviews methods regarding Artificial Intelligence (AI) to improve the current means for echo cancellation. In this paper, we mainly discuss the approaches to echo cancellation, the identification of echo using adaptive AI and the usage of adaptive filters and neural network for echo cancellation. For instance, deep learning approaches can facilitate the issues of AEC (active echo control) and ANC (active noise control),the optimization of LMS algorithm can be achieved by combining Swarm Intelligence (SI), combining adaptive digital filter and recurrent neural network for acoustic echo cancellation etc. Using AI in echo cancellation can help us achieve high-quality, full-duplex telecommunication in modern telephony system.
Thematic classification of ancient Chinese poetry using TwinEmbedAttentionNet
Authors: Chang Haoxiang , Li Beitong , Wang Fengwei , Bin Yue
Published: February 2024

Ancient Chinese poetry, a reflection of Chinas rich cultural and philosophical fabric, encapsulates the evolving socio-cultural nuances of its historical epochs. Despite its cultural significance, there remains an evident lacuna in comprehensively classifying its recurring themes, due in part to the conciseness and polysemy intrinsic to the language and the essentiality of embedded cultural and historical contexts. Addressing this challenge, this study introduces TwinEmbedAttentionNet, a pioneering method tailored for the thematic classification of ancient Chinese poetry. This approach synergistically integrates pretrained word and sentence embeddings with an attention mechanism, ensuring the nuanced representation of the poetrys intricate details. Our results showcase its superior performance over existing models. Furthermore, an in-depth examination of model components offers insights into their respective thematic categorization efficacies. This research not only advances the academic understanding of ancient Chinese poetry but also underscores the potential of innovative neural networks in processing historically rich textual data.
Street view imagery: AI-based analysis method and application
Authors: Song Haoyang
Published: February 2024

Street view imagery is an emerging form of geographic big data. It presents urban visual environments from the perspective of urban residents and also contains non-visual environment of cities, such as urban human activities and socio-economic development. However, traditional digital image processing has its limitations, and the continuous development of artificial intelligence, especially computer vision and deep learning, provides strong technical support for exploring the rich semantic information in street view imagery. This paper reviews the related research on street view imagery and its artificial intelligence analysis methods and applications. It outlines the acquisition, storage, and common data sources of street view imagery. Then it introduces computer vision, deep learning, and commonly used open-source datasets in street view imagery analysis. It also detailed three aspects of AI-based street view imagery applications, namely quantification of the physical space, urban perception, and spatial semantic speculation. Finally, issues like data acquisition, domain adaption and deep learning black box are discussed. The hotspots and prospects for the development of this research topic are also prospected.
Breast cancer prediction based on the machine learning algorithm LightGBM
Authors: Zhu Jiayu
Published: February 2024

Nowadays, the idea of Artificial Intelligence (AI) medical detection has aroused great interest around the world. AI has the potential to strengthen medicine in both observation and operation. For instance, AI could catch crucial details that are not intuitive to humans. Robots controlled by AI could also do micro-operations that are extremely hard on human hands. In this study, the author utilizes one of the most focused traditional machine-learning methods, that is the Light Gradient Boosting Machine (LightGBM) algorithm for breast cancer prediction. The LightGBM performs both well on accuracy and speed in the studys experiment. The study applies the bootstrap aggregating (Bagging) method to cope with the over-fitting problem. As the significance of the study, the study shows that the LightGBM can be utilized in designing accurate, fast and cheap medical detection devices. Nevertheless, programmers should handle the over-fitting problem cautiously while building models based on LightGBM. This could help doctors in impoverished areas realize accurate medical detection. People could also do accurate self-diagnosing with a cheap, portable device at home.
AutoML-based neural network for the detection of keratoconus
Authors: Li Daimin
Published: February 2024

For many years, the diagnosis of Keratoconus (KCN) has heavily relied upon the expertise and subjective judgment of clinicians. However, this study represents a pioneering effort to revolutionize KCN identification through the integration of Convolutional Neural Network (CNN) classification. In this innovative approach, the model is specifically designed to process corneal images as its primary input data, categorizing them into one of three distinct classes: KCN, suspect, or normal. Remarkably, this CNN model, meticulously implemented on the Edge Impulse platform, has achieved an astounding accuracy rate of 98.2% in correctly identifying KCN cases. Nevertheless, there remains substantial potential for improvement in the accurate classification of the suspect and normal categories. In conclusion, this study exemplifies the vast potential of CNNs to transform the diagnosis of keratoconus. With ongoing refinements, including enhanced data preprocessing, attention mechanisms, and quantitative integration, this approach could herald a transformative era in KCN identification and management.
The recognition and analysis of fake images based on deep neural network
Authors: Luo Qihang
Published: February 2024

The generation of fake images and the process of technology is developing quickly, which has generated great concern about its impact on society. To effectively identify the fake image, this article introduces a deep learning-based identification method. This article uses a convolutional neural network (CNN) neural network to construct a model for machine learning image recognition and lets it learn a dataset of hundreds of real and fake pictures to let it complete tasks that are difficult for humans to complete. the use of deep learning to solve this problem has the following advantages: the results can be observed after data input, which is conservative and fast, and there is no need to manually design rules as Deep learning methods can optimise the loss function to learn the rules, mining potential features of data, with strong representation ability. Using this method, the accuracy result is over 60%. This paper proves a machine can learn and recognise real and fake pictures, which is specifically inspiring that learning-based methods can also solve the challenging problem of images.
DIVORCE AND REMARRIAGE WITHIN THE EVANGELICAL CONTEXT: A CONCISE REEVALUATION
Authors: R. Burgos Michael
Published: February 2024

This study articulates the various evangelical views on divorce and remarriage. Following a critique of these views, a biblical substantiation of a modified Erasmian approach is provided. It is argued that a modified Erasmian viewpoint best accounts for the explicit testimony of Scripture regarding the permissibility of divorce and remarriage within the context of adultery or spousal abandonment while affording divorce and remarriage in extraordinary situations wherein a spouse has engaged in sin that is deserving of capital punishment.
Rural tourism development path under the perspective of industrial integration—Case study of Tangwan township, Guixi City
Authors: Wang Chenjian , Zhou Huimin , Zhao Fang , Zhang Yuansuo
Published: February 2024

With the improvement of people’s economic income and the upgrading of tourism consumption demand, rural tourism is becoming more and more popular. Although the rural tourism industry is emerging all over the world, how to realize the high-quality development of the rural tourism industry is still a complex systemic issue. The integrated development of the industry is an important way to realize the high-quality development of the industry; therefore, this study tries to discuss the path of the integrated development of the rural tourism industry by analyzing the micro-case study. For the case study, the authors chose Tangwan Town, a rural tourism town in Guixi City, Jiangxi Province, China. We collected relevant qualitative and quantitative data through questionnaires, field research, and interviews, based on which we analyzed the SWOT and the obstacles to industrial development at the case site and gave suggestions on the path of integration development at two levels. Through the empirical study of the case study, we summarize the four priorities in the integrated development of the rural tourism industry, which are capital, operation, resources, and talents. This study further provides management implications for tourism management, visitor experience, and the further development of the rural tourism industry.
In Vitro Head-to-Head Comparison of Flow Reduction between Fibered and Non-Fibered Pushable Coils
Authors: Yoon Jong-Tae , Kwon Boseong , Choi Joon Ho , Hwang Sun Moon , Kim Mihyeon , Hwang Sungbin , Song Yunsun , Lee Deok Hee
Published: February 2024

Purpose: To compare the embolization effects of a non-fibered pushable coil with a conventional fibered pushable coil in an in vitro bench-top experiment.Materials and Methods: A simplified vascular phantom with 4 channels (1 for the non-fibered coil, 1 for the fibered coil, and 2 for continuous circuit flow) was used. A single coil of the longest length was inserted to evaluate the effect of single-coil embolization, and 3 consecutive coils were inserted to assess the effect of multiple-coil embolization. Post-embolization angiography was performed to obtain flow variables (time to peak [TTP], relative peak intensity [rPI], and angiographic flow reduction score [AFRS]) from time density curves. The packing densities of the two coil types were calculated, and the AFRS of each channel was determined by dividing the TTP by the rPI.Results: When inserting a single coil, the conventional fibered coil demonstrated better flow reduction, as indicated by a higher AFRS (25.6 vs. 17.4, P=0.034). However, the non-fibered coil exhibited a significantly higher packing density (12.9 vs. 2.4, P=0.001). Similar trends were observed with multiple coils.Conclusion: The conventional fibered pushable coil showed better flow reduction efficiency, while the non-fibered pushable coil had a higher packing density, likely due to the flexibility of the coil loops. A better understanding of the distinct characteristics of different pushable coils can enhance the outcomes of various vascular embolization.
The role of representations constructed by students in learning how to solve the transportation problem
Authors: Stankov Gordana , Pap Zoltan , Maravić Čisar Sanja
Published: February 2024

The purpose of the research presented in this paper was to study the role of concrete and table representations created by students in learning how to solve an optimization problem called the transportation problem. This topic was learned in collaborative groups using table representations suggested by teachers in 2021. In 2022, the researchers decided to enrich the students’ learning environment with concrete objects and urged the students to use them to present the problem to be solved. The students did it successfully and, to be able to record it in their notebooks, they constructed a table representation by themselves without any help from their teacher. After that, they managed to solve the problem by manipulating the objects. At the same time, each step in the solution was presented with changes in the table. The students were assessed before (pre-test) and after collaborative learning (test) in both academic years. The pre-test results were similar, but the test results were better in 2022. Therefore, it can be concluded that using concrete and table representations constructed by students in learning how to solve transportation problems makes collaborative learning more constructivist and more effective than when they use only table representations suggested by their teachers.
Subject Classification: 97M10, 97M40
Teaching correlation and regression in three European countries
Authors: Boller Balázs
Published: February 2024

In this article, we compare the presence of correlation and regression analysis in secondary education of Ireland, the Netherlands and Luxembourg, through the analysis of final-exam tasks and curricula based on the Anthropological Theory of Didactics (ATD). It points out that the same topic can appear in different ways and extent in curricula, even if the mathematics teaching goals are similar. This article is a kind of introduction to the research that explores the possibilities for the appearance of these concepts in the Hungarian mathematics education. Therefore, in the second part of the article, Hungarian curricular goals are included, and it is shown which methodology of the three studied countries has the greatest curricular basis in Hungary.
Subject Classification: 97xxx
The Effect of Tax Avoidance, Profitability, and Firm Size on Firm Value (Case Study of Pharmaceutical Companies listed on the IDX 2018-2022)
Authors: Al Hazmi Raldin Alif
Published: February 2024

A company is established to earn profits and in the long run to maximize the value of the company. Satisfactory company performance in the market will attract investors and potential investors and will increase company value. This study aims to determine and examine the effect of tax avoidance, profitability and company size on firm value in pharmaceutical sub-sector companies listed on the Indonesia Stock Exchange for the period 2018-2022. Data obtained from www.idx.com, the company's official website, and www.finance.yahoo.com. Sample data based on purposive sampling, using 8 companies listed on the IDX with a total sample of 40 sample data. Hypothesis testing is done with multiple linear regression analysis for panel data. The test results conducted in this study found that tax avoidance has no effect on firm value, profitability affects firm value, and company size has no effect on firm value. This research is expected to add to the literature for users of financial statements and investors and to be able to better utilize their resources and further maximize company profits.
Simulation-Based Evaluation of Sliding Mode Control with Washout Filter for Power Balancing in Battery Energy Storage Systems
Authors: Journal IJSREM
Published: February 2024

This research paper presents a simulation-based evaluation of a novel sliding mode control (SMC) approach with a washout filter for power balancing in battery energy storage systems (BESS). Unlike traditional proportional-plus integral control methods, the proposed SMC technique is specifically tailored for charging and discharging BESS units. The primary objective of this study is to investigate the efficacy of the proposed SMC-based scheme in achieving optimal power balancing at the DC bus of the BESS. A comparative analysis is conducted to assess the performance of the developed SMC strategy against the conventional proportional-plus integral controller. MATLAB simulations utilizing Simulink and the Sim Power System toolbox are employed to obtain comprehensive results. The findings of this study provide valuable insights into the effectiveness of the SMC with washout filter for enhancing power balancing in BESS applications, thereby contributing to advancements in energy storage system control methodologies. Keywords: Sliding Mode Control (SMC), Washout Filter, Power Balancing, Battery Energy Storage Systems (BESS), Simulation-based Evaluation, MATLAB Simulation
Antibiotic knowledge and practices of students attending in Medical Institute / Southern Technical University
Authors: Hameed Assistant Lecturer Ahmad Shandookh , Falih Hayder yousif , Taher Assistant lecturer Ruqayah
Published: February 2024

Antibiotic resistance is now a major a medical and financial burden that affects healthcare globally. Insufficient undergraduate instruction on antibiotic management may be a factor in antibiotic-related clinical malpractice, which could have detrimental effects on patient wellness. The study's objective was to evaluate undergraduate medical students at the Medical Institute in Al-Nasiriyah understanding, beliefs, and behaviors regarding resistant antibiotics. Methodology: A cross-sectional investigation was making in the University of the Medical Institute in Al-Nasiriyah. (133) undergraduate medical students who were chosen at random were given a structured questionnaire. The statistical package for social sciences and SPSS, version 22.0, was used to analyze the data. A Chi-square test was used to examine relationships between the independent and dependent variables.
Results:  133 of 188 medical students (71%) had good understanding about the use and resistance to antibiotics, according to the study. Regarding antibiotics and antibiotic resistance, the students' knowledge is good; however, their understanding of antibiotic usage is below average. Knowledge is influenced by a number of variables, such as program, academic level, gender, and awareness of resistance to antibiotics.  Based on the results, it is recommended that students' understanding of these topics be enhanced. Conclusions: There are a lot of common misconceptions in some fields, like the usage of antibiotics. Immediately interventions are necessary to enhance students' understanding of antibiotics and resistance in light of the findings. Although they were less practiced, the students' knowledge and attitudes were higher.
Myśliwi Władysława Terleckiego
Authors: Warońska-Gęsiarz Joanna
Published: February 2024

Artykuł jest analizą sztuki Władysława Terleckiego, która powstała zarówno w wariancie radiowym, jak i telewizyjnym. Koncentrując się na opublikowanej w „Dialogu” wersji telewizyjnej, autorka omawia sposób budowania akcji i tworzenia atmosfery niesamowitości, relacje między postaciami oraz ich dążenie do odkrycia prawdy wojennych wydarzeń. Pytanie o to, co wydarzyło się w czasie drugiej wojny światowej w lesie, w którym toczy się akcja sztuki, dręczy zarówno Pryszcza – dowódcę rozbitego oddziału partyzantów – jak i Małego, jego antagonistę. Zamiast odpowiedzi pojawi się jednak sceptyczne: „nie wiem”. Terlecki zastanawia się nad możliwościami dotarcia do prawdy z przeszłości nad użytecznością wykorzystanych dokumentów (wspomnień, map) i relacjami świadków, a ponadto nad możliwością zamknięcia swojego doświadczenia w tekście.
Wokół bohaterów Mateczki Władysława Terleckiego
Authors: Wróbel Elżbieta
Published: February 2024

Przedmiotem niniejszej analizy jest jeden z ostatnich dramatów Władysława Terleckiego – Mateczka – opublikowany w 1995 roku. Autorka przypomina autentyczne wydarzenia, które zainspirowały pisarza do napisania tego utworu. W artykule odwołuje się do licznych relacji dokumentarnych i naukowych poświęconych Stanisławie Umińskiej, będącej pierwowzorem tytułowej bohaterki. Umińska była początkującą i zdolną aktorką. W 1924 roku w paryskim szpitalu zabiła swojego ciężko chorego narzeczonego, ulegając jego prośbom o ukrócenie cierpienia. Po uniewinniającym ją procesie wstąpiła do zakonu i przyjęła imię Benigna. Szczególnie istotne dla autorki artykułu stały się ustalenia historyków teatru – jeden z ważniejszych wątków dramatu Terleckiego jest bowiem związany z osobą Leona Schillera. Postać Leona w Mateczce zyskuje biografię zbieżną z życiorysem Schillera. Wielki reżyser podczas drugiej wojny światowej wystawił w domu zakonnym dla młodocianych przestępczyń, w którym matką przełożoną była siostra Benigna, między innymi Pastorałki. Refleksja nad piątym przykazaniem dekalogu: „Nie zabijaj”, stała się najważniejszym problemem, który Terlecki rozważa w swoim dramacie. W analizie utworu wskazano typowy dla pisarza sposób konstruowania postaci. Przypomniano również, że Terlecki zainteresował się biografią Stanisławy Umińskiej już wcześniej, wygłaszając na antenie Radia Wolna Europa esej biograficzny Paryski proces, podwarszawskie jasełki (1991). Autorka ukazuje także związek poruszanej tematyki z życiorysem pisarza i jego przeżyciami wojennymi z okresu dzieciństwa spędzonego w rodzinnym mieście – Częstochowie.
Rancang Bangun Alat Pendeteksi Formalin Pada Makanan dan Minuman Berbasis Arduino Uno
Authors: Hamid Helson , Hasiri Ery Muchyar , Megawati Megawati
Published: February 2024

Makanan merupakan kebutuhan primer jasmani untuk makhluk hidup yang dikonsumsi untuk menghasilkan tenaga dan energi, sehingga komponen makanan harus sehat dan terbebas dari kontaminasi bahan berbahaya. Maraknya isu kecurangan pedagang dalam menjual makanan di pasaran yang mengandung zat makanan berbahaya seperti formalin yang dijadikan bahan pengawet agar makanan lebih tahan lama dengan mencegah atau menghambat proses rusak atau pembusukan makanan dan membuat masyarakat resah karena kesulitan dalam mengidentifikasi ciri keberadannya secara kasat mata dan efek buruk yang dialami masyarakat saat mengonsumsi zat berbahaya ini menjadi kerugian yang besar karena mampu merusak kesehatan manusia baik dalam jangka pendek maupun jangka panjang bahkan menyebabkan kematian. Oleh karena itu dibutuhkan inovasi yang dapat membantu mendeteksi formalin pada makanan dan minuman berbasis arduino uno, penelitian ini menggunakan metode pengumpulan data observasi, studi pustaka. Adapun tujuan pada penelitian ini adalah untuk merancang dan membuat alat pendeteksi foramlin pada makanan dan minuman berbasis arduino uno. Penelitian ini menggunakan komponen berupa Sensor HCHO,Buzzer, Lcd 16×2, Arduino Uno. Hasil penelitian Pendeteksi Formalin pada Makanan dan Minuman maka dapat di peroleh kesimpulan di antaranya dapat mendeteksi makanan dan minuman yang berormalin dan penggunaan sensor HCHO bekerja dengan Membaca data dari gas/aroma sampel yang berada pada tempat pengujian sampel.
АНАТОМИЧЕСКОЕ ОБОСНОВАНИЕ УПРАВЛЯЕМОГО ОСТЕОСИНТЕЗА ФРАГМЕНТАРНЫХ ПОВРЕЖДЕНИЙ ТАЗА
Authors: Лобанов Г.В. , Вертыло Н.А. , Агарков А.В. , Боровой И.С.
Published: February 2024

Для определения оптимальных морфо-анатомических условий введения различных типов фиксаторов в кость, проведены механические и морфологические экспериментальные исследования на трупном материале по устойчивости соединения «фиксатор-кость» в зависимости от места введения и типа фиксатора, а также механической жесткости связи и репозиционно-механические возможности различных видов фиксаторов
Gender Differences in Chinese EFL Learners’ Comprehension When Reading Across Mediums
Authors: Tian Xiufeng , Samat Norhanim Abdul , Zainal Zaidah
Published: February 2024

As the reading medium shifts from paper to digital devices, there is a notable change in readers’ habits, moving from traditional printed formats to electronic forms. While extensive research has been conducted on gender differences in traditional print reading, studies focusing on gender disparities in mobile reading comprehension are rather limited. This research employed cross-sectional quantitative methods to explore gender differences in comprehension through both print and smartphone-based reading tests. Data was gathered from 190 undergraduates at a local university in China through reading comprehension tests. Participants’ reading results were analyzed using SPSS software for comparison. The findings indicate no significant difference in reading achievements between male and female participants on both paper and smartphone platforms. However, the study found positive trends in female students’ performance on both mediums. The disparity in the mean difference between male and female students’ reading scores was larger in smartphone-based tests, which indicates that digital mediums could either enhance reading performance in female students or potentially have a negative impact on male students.
Repair or not? Face-saving in EFL Classes in an Elementary School in Japan
Authors: Shino Ayano
Published: February 2024

This study examines how face is protected for smoothly conducting English classes and building good relationships among class teachers (CTs), native English teachers (NETs), and students in EFL classes in an elementary school in Japan. In this study, interactions among the CTs, the NETs, and the students in English lessons were recorded for about 50 hours in total, and the transcribed data were analyzed partially on the basis of existing research on classroom discourse, conversation, and classroom-based conversation analytic approaches. The results show that the CTs, the NETs, and the students manage an irregular usage of Japanese by the NETs and of English by the CTs and the students in EFL classrooms by protecting interlocutors’ face in various ways, such as indirect repair and silence.