bluuebunny/crossref_metadata_2025 huggingface dataset:
Computer-aided Numerical Simulation Analysis of Collaborative Innovation within Government-Industry-University-Institute Models Using Evolutionary Game Theory
Authors: Huaiying Lei Jueping Xie, Ruikai Feng,
Published: April 2024

Collaborative innovation among government, industry, universities, and institutes (GIUI) is an essential approach for achieving national development driven by innovation and enhancing regional competitiveness. However, the existing collaborative innovation faces challenges such as uneven distribution of benefits, unequal risk sharing, and inadequate institutional and policy support. This study harnesses the power of numerical simulation to dissect the complexities of GIUI collaboration, using the evolutionary game theory to construct a payoff matrix. By conducting numerical simulations using the Matlab software program, we identify two asymptotically stable points in the system. Our findings highlight that variables such as the gain coefficient (t) from government engagement with industry and academic institutes, the preferential tax rate (K) offered to industry, and the subsidy (A) invested in academic institutes significantly influence the consensus towards collaborative innovation. Furthermore, our analysis suggests that governments should actively monitor and coordinate the distribution of benefits within complex multi-agent collaborative innovation networks. By taking an active role in ensuring a fair and efficient distribution, governments can directly address the challenges arising from the current framework. This study employs computational methods to offer an advanced approach to understanding and optimizing the dynamics of collaborative innovation within the GIUI framework. By utilizing computer methods such as numerical simulation, we gain valuable insights into the complexities of collaborative innovation and provide a foundation for government decision-making.
Analysis of Factors Affecting Voluntourism Network Attention in China: An empirical Test Based on Big Data Analysis
Authors: Yue Xiao
Published: April 2024

Based on the Baidu index platform, this study takes panel data of 31 provinces, autonomous regions and municipality directly under the central government in China from 2019 to 2023 as a research sample, and and uses big data to empirically analyze the influencing factors of the Voluntourism Network Attention in China. This study chose the Voluntourism Network Attention as the explanatory variable, the seven indicators including the consumption level of the residents, the population above the college and the total tourism revenue of the region as explained variables. Using the STATA15.0 software, the big data model is determined by a descriptive test, a unit root test, a co-integration test, a variance expansion factor (VIF) test, etc. The regression equation of this study was constructed by the generalized least squares method. The empirical study is conducted to determine the influence mode and degree of each factor on the public interest tourism network attention and analyzes the internal causes. The results show that the educational level of the region, the level of economic development and the level of tourism development have a significant positive impact on the Voluntourism Network Attention, and the regression coefficient of the education level and economic development level is the largest. Both of them are the main factors of network the Voluntourism Network Attention. In view of the empirical results, this paper puts forward the following suggestions: First, it is necessary to create more voluntourism routes suitable for college students. Second, it is essential to increase the marketing and promotion of voluntourism activities in economic and tourism developed areas.Last, there is a need to innovate the connotation and form of the voluntourism.
Analysis of Cornell Cooperative Extension under the Background of Big Data
Authors: Haokun Wang, Xiuyun Wang Yaozu Wang, Qingyue Li,
Published: April 2024

In the era of knowledge economy, higher education has become the support and engine of socio-economic development, and the importance and urgency of its social service function have become more prominent. The content and form of services urgently need to be updated and innovated. Analyzing the history and current development status of typical university social services undoubtedly has important exemplary value. As one of the earliest universities born in the United States to serve society, Cornell University has a deeply rooted concept of social service, a complete social service system, and a unique social service promotion system. The development of information technology and big data has greatly improved the social service field of the university. In order to have a deeper understanding of the development track and operation logic of Cornell University's social service extension system, this paper adopts the method of literature research, historical research and case study to trace the source of Cornell University's social service concept and explore Cornell University's social service extension model -- agricultural extension project with advantages of traditional "land-grant college". Learn about natural resources, environment and sustainable energy development projects that keep pace with The Times, as well as youth development and family upbringing services for family education. This article believes that the social services provided by Cornell University under the social service promotion system have a strong academic and professional nature, and the direction, content, and social needs of serving society are highly matched and coupled, which helps the university form a complete social service system. Its mature social service promotion system and successful experience in social services have important implications for the construction and improvement of university social service functions.
Automated Teaching Weighted Recurrent Neural Network (Atwrnn) Model: Analysis of Badminton Teaching Mode Based on Online Teaching Platform
Authors: Song Chen, Jingming Zhao Yuanji Zhong, Jiangwei Yang, Menglong Zhang,
Published: April 2024

An online teaching platform serves as a virtual environment where educators and learners interact, collaborate, and engage in various educational activities. Through a combination of multimedia resources, interactive tools, and communication features, online teaching platforms facilitate effective remote learning experiences. Educators can create and deliver engaging instructional content, including video lectures, presentations, quizzes, and assignments, tailored to the needs and preferences of learners. These platforms often incorporate features such as discussion forums, live chat, and virtual classrooms, enabling real-time communication and collaboration among students and instructors. This paper presents an analysis of the badminton teaching mode facilitated by an online teaching platform, augmented with an Automated Teaching Weighted Recurrent Neural Network (ATwRNN). Through this innovative approach, the traditional method of badminton instruction is enhanced by leveraging advanced machine learning techniques to personalize and optimize the teaching process. The online teaching platform provides a virtual environment where instructors can deliver interactive lessons, instructional videos, and practice exercises tailored to individual learner needs. ATwRNN, a specialized neural network model, dynamically adjusts the teaching weightings based on student performance data, providing personalized feedback and adaptive instruction in real time. Simulation results stated that learners who received instruction through the ATwRNN-enhanced platform demonstrated a 25% increase in shot accuracy compared to those in traditional teaching modes. Additionally, the adaptive nature of ATwRNN led to a 30% reduction in the time required for skill acquisition, as learners received personalized feedback tailored to their individual learning pace and preferences. Moreover, user feedback surveys revealed high levels of satisfaction and engagement among participants, with 90% reporting that the ATwRNN-enhanced teaching mode improved their overall learning experience.
Dependency Factor Analysis in the Evaluation of College English Teaching Quality
Authors: Weibin Zhang Lihui Li,
Published: April 2024

Teaching quality encompasses a multifaceted approach to education that prioritizes student engagement, comprehension, and empowerment. It extends beyond the mere imparting of knowledge to fostering critical thinking, creativity, and lifelong learning skills. A high-quality teaching environment is characterized by clear communication, supportive relationships between educators and students, and innovative instructional methods that cater to diverse learning styles. Effective feedback mechanisms, assessment practices, and curriculum design also contribute to teaching quality, ensuring that students receive personalized attention and opportunities for growth. Ultimately, teaching quality is measured not only by academic achievement but also by the holistic development of students as confident, curious, and socially responsible individuals prepared for success in an ever-evolving world. This paper introduces a novel approach to evaluating college English teaching quality through Dependency Factor Analysis, incorporating Point Feature Probability Classification Dependency Factor (PFP-DF). The proposed framework aims to provide a comprehensive assessment of teaching quality by analyzing dependencies between various factors influencing English instruction in college settings. Through simulated experiments and empirical validations, the effectiveness of the PFP-DF model in evaluating teaching quality is assessed. Results demonstrate significant improvements in accuracy and granularity compared to traditional evaluation methods. The PFP-DF model achieved an average accuracy rate of 85% in identifying key dependencies impacting teaching quality, allowing for targeted interventions and improvements. Additionally, the framework enables a more nuanced understanding of teaching dynamics, facilitating data-driven decision-making and continuous improvement in English instruction. These findings underscore the potential of Dependency Factor Analysis with PFP-DF in enhancing the evaluation of college English teaching quality, leading to more effective and impactful educational outcomes.
Learning Evaluation Method Based on Artificial Intelligence Technology and Its Application in Education
Authors: Hua Liu Hongguang Bao,
Published: April 2024

Artificial intelligence (AI) is a transformative technology that enables machines to perform tasks that typically require human intelligence. Through algorithms and advanced computing systems, AI enables machines to perceive their environment, reason, learn from experience, and make decisions autonomously. From virtual assistants like Siri and Alexa to self-driving cars and advanced medical diagnosis systems, AI applications are reshaping industries and revolutionizing the way we live and work. With its ability to process vast amounts of data and identify complex patterns, AI has the potential to drive innovation, improve efficiency, and solve some of society's most pressing challenges. This paper introduces a novel learning evaluation method based on artificial intelligence technology, specifically leveraging Mamdani Fuzzy Clustering Middle Order Classification (MFCM-OC), and explores its application in education. The proposed method aims to provide a comprehensive assessment of student learning outcomes by analyzing various factors such as academic performance, engagement, and cognitive development. Through simulated experiments and empirical validations, the efficacy of the MFCM-OC-enhanced learning evaluation method is evaluated. Results demonstrate significant improvements in accuracy and granularity compared to traditional evaluation methods. For instance, the MFCM-OC model achieved an average accuracy rate of 85% in predicting student performance, allowing for targeted interventions and personalized learning plans. Additionally, the method enables educators to identify students' strengths and weaknesses more effectively, facilitating data-driven decision-making and continuous improvement in educational practices. These findings underscore the potential of artificial intelligence with MFCM-OC in revolutionizing learning evaluation and enhancing educational outcomes.
The Use of Linear Regression Equation in Physical Education Teaching in Higher Education Institutions
Authors: Cui Jinxi
Published: April 2024

This study investigates the application of linear regression equations in physical education teaching within higher education institutions, utilizing the Integrated Linear Logistic Regression AdaBoost Classifier (ILLR-ABC). The research aims to enhance teaching methodologies and performance assessment in physical education through the integration of statistical modelling techniques. Through simulated experiments and empirical validations, the effectiveness of the ILLR-ABC model is evaluated in predicting student performance and guiding instructional interventions. Results demonstrate significant improvements in accuracy and precision compared to traditional teaching methods. For instance, the ILLR-ABC model achieved an average accuracy rate of 90% in predicting student achievement levels, enabling educators to tailor teaching strategies to individual student needs effectively. Additionally, the model provides valuable insights into the factors influencing student performance, facilitating targeted interventions and curriculum adjustments. These findings highlight the potential of integrating statistical modelling techniques like ILLR-ABC to optimize physical education teaching practices and enhance student learning outcomes.
Psychological Health Assessment and Intervention System for Chemical Engineering Students Based on Emotional Computing Technology
Authors: Zhao Haijun
Published: April 2024

Emotional computing technology is revolutionizing health assessment by integrating emotional and psychological factors into traditional diagnostic processes. This innovative approach utilizes advanced algorithms and sensor technologies to analyze individuals' emotional states and mental well-being, providing valuable insights into their overall health. By detecting subtle changes in facial expressions, voice patterns, and physiological signals, emotional computing technology can assess stress levels, mood fluctuations, and mental health conditions with greater accuracy and sensitivity. This paper presents a novel Psychological Health Assessment and Intervention System tailored for chemical engineering students, leveraging Emotional Computing Technology enhanced by Cartesian Feature Weighted Emotional Classification (CFWEC). The system aims to assess students' psychological well-being by analyzing emotional cues extracted from various sources such as facial expressions, voice patterns, and text interactions. Through simulated experiments and empirical validations, the efficacy of CFWEC-enhanced emotional computing technology is evaluated in predicting and intervening in psychological health issues among chemical engineering students. Results demonstrate significant improvements in accuracy and sensitivity compared to traditional assessment methods. For instance, the CFWEC model achieved an average accuracy rate of 85% in identifying students at risk of psychological distress, enabling timely interventions. Additionally, the system provides personalized recommendations and interventions based on individual emotional profiles, leading to improved mental health outcomes. These findings underscore the potential of Emotional Computing Technology with CFWEC in promoting psychological health and well-being among chemical engineering students.
Study of Harmonic Minimization in Pulp and Paper Mill using Hybrid Active Filter -A Case Study
Authors: B. R. Patil Pranita Chavan,
Published: April 2024

Increased power electronics-based nonlinear loads have harmed distribution system power quality. Variable speed drives, switched-mode power supply, and DC drives impair power quality and affect customers and utilities. Many variable-speed drives in the paper mill cause harmonic distortion, a power quality issue. This study investigates the impact of nonlinear electric drives on supply current distortion in Padmavati Pulp and Paper Mill, Ambarnath, Thane, India. Harmonic analysis is done at PCC, that is, at the secondary side of the transformer, with the help of a power quality analyzer fluke-434. Based on detailed analysis, a suitable harmonic reduction method is identified. passive filters, are the simplest solution for lowering harmonic currents but it has shortcomings like bulk size and cause resonance. In recent years active filter has been applied as an effective solution for harmonic reduction. This study suggests a hybrid filter as an economical solution to take advantage of a passive and active harmonic filter. This work present design and simulation of cascade H- bridge multilevel inverter-based hybrid filter for medium and high-power distribution system. The system for the case study is developed in MATLAB Simulink platform with suitable harmonic mitigation techniques and performance is evaluated in terms of total Harmonic Distortion Index (THDi).
Implementation of Full adder in Multiple valued Logic for Performance Optimization
Authors: Monica Kalbande, Tejswini Panse Yashika Gaidhani,
Published: April 2024

Multiple valued logic is now becoming more significant in real-world applications. Mathematical design blocks are essential in digital and mixed-signal systems. A system's arithmetic blocks often use the most power because of the high switching activity. Implementations of quaternary arithmetic may be a way to cut down on energy use while improving system performance. In this paper, quaternary adders are developed using three different approaches, and their binary equivalents are evaluated in terms of size, predicted logic depth, and performance estimation.
An Approach Towards Standardization of Ehr with Efficient Accessibility of Data on Demand: A Review
Authors: Minakshi Wanjari Rekha S. Dange Vairagade,
Published: April 2024

Standardization of medical terminologies and the centralized electronic medical record (EMR) are the most addressed discussion in the healthcare industries. Patient master records and the treatment statistics records has wide spectrum and dynamic data structure. These records have high growth rate with huge volume over the period and which requires proper structured data base management system. Data science and the analytics could solve the problem of data management, but trust about data storage over the cloud may become major issue. These records may be archived for better storage management and could be replicated over multiple cloud or kept in a distributed manner for extended security. On other hand medical data generated through wearable medical devices or the portable devices used by home care patients may be connected to multiple cloud servers for better accessibility and security. Proposed system is to develop a generic medical record management system over multiple cloud and designing the Body Area Network (BAN) architecture connected to distributed cloud for data accessibility and security.
Examining the Thyristor-Controlled Reactor's (TCR) Performance to minimize Self-Generated Harmonics.
Authors: Vidya Kodgirwar, Pranita Chavan, Netra Lokhande Haripriya Kulkarni, Manasi Deore, Jape Swati,
Published: April 2024

This work discusses the minimizing of self-generated harmonics in a Thyristor Controlled Reactor (TCR) used in a power distribution system. When a nonlinear load is connected to the system, power quality difficulties arise, including reactive power compensation, harmonics, voltage unbalance, poor power factor, and so on. These flaws degrade the power quality of the system. FACTS and electronics devices are most commonly employed for reactive power correction. A conventional Static VAR compensator is the best option for this application. The static VAR compensator consists of either a fixed capacitor-thyristor controlled reactor (FC-TCR) or a thyristor switched capacitor-thyristor controlled reactor (TSC-TCR). The reactive power demand objective can be met by controlling the conduction angle of TCR. However, the switching operation of the thyristor-controlled reactor reduces power quality by adding self-generated harmonics into the system. The proposed topology in this study outlines the usage of a delta-connected TCR to reduce self-generated harmonics rather than a thyristor controlled reactor (SCR).

The work carried out in this paper has two major sections

Determine (a) the firing angle range for reactive power adjustment, and (b) the mechanism to control inductive susceptibility. 2. A comparison of three presented methods: a) single delta connected TCR; b) Equally stepped delta connected TCR (ESTCR); and c) Binary stepped delta connected TCR (BTCR).
Smart Hydroponic Systems: Optimizing Nutrient Levels with IoT Connectivity
Authors: Vinaya Gohokar, Kunal Kulkarni Pradnya Vishram Kulkarni,
Published: April 2024

Maintaining precise nutrient levels is essential for the thriving success of hydroponic systems. This comprehensive study delves into the intricate interplay of climatic conditions and nutrients, meticulously analysing various parameters like Total Dissolved Solids (TDS), pH, and electrical conductivity (EC) within a sophisticated smart hydroponic vertical Nutrient Film Technique (NFT) setup designed for leafy greens. The innovative system integrates a wireless sensor network and Internet of Things (IoT) connectivity, employing ESP32 microcontrollers as the primary unit alongside complementary hardware components for continuous and real-time monitoring of critical nutrient parameters. The investigation delves into the dynamic relationship between environmental factors and the growth patterns of spinach plants. Through a thorough examination of the extensive dataset gathered via deployed sensors, the study unveils variations in environmental parameters throughout various stages of plant development, including germination and root establishment. The study aims to elucidate the significance of each parameter in optimizing plant growth in hydroponic environments by analysing data associations. Results show higher Total Dissolved Solids (TDS) values correlate with better plant growth, while reduced pH levels harm plants. These findings are crucial for interpreting disease symptoms, aiding farmers in identifying issues early and optimizing yields. Understanding how nutrient values affect plant health enables proactive problem-solving. This research provides valuable insights into smart hydroponic systems, informing precision agriculture decisions.
Identity Based Authentication Scheme (IAS) for Securing WSN Based Internet of Things
Authors: Asha Ambhaikar Zubair Ahmed Khan,
Published: April 2024

The growing number of connected devices in IoT networks has raised security concerns. These networks face unique challenges, including limited resources, lack of standardized security protocols, and diverse devices and applications. Identity-based authentication is needed to address these threats and limitations. Implementing a multi-factor authentication system can enhance security and protect sensitive information from unauthorized access. The proposed Identity Based Authentication (IAS) scheme is implemented using the NS-2 simulator to address security challenges in IoT networks. Each node is assigned a unique identity for authentication, ensuring only authorized access and preventing security breaches. The IAS scheme enhances IoT network security by verifying node identities. Two scenarios are considered to evaluate the scalability and interoperability of the IAS scheme. The first scenario involves a random environment, assessing performance in real-world settings with varying device densities and network conditions. The second scenario involves a cluster-based environment, providing insights into the scheme's functionality and efficiency. By examining both scenarios, this research aims to provide a comprehensive understanding of how the authentication scheme performs in different deployment scenarios. The findings highlight the importance of selecting the appropriate authentication scheme based on the specific network environment and requirements. The superiority of the IAS authentication scheme suggests its potential for widespread adoption and implementation in various network scenarios over other authentication schemes.
Hindi Abstractive Text Summarization using Transliteration with Pre-trained Model
Authors: Shashi Shekhar, Rashmi Gupta Jeetendra Kumar,
Published: April 2024

Automatic text summarization is a subarea of natural language processing that generates a summary of the text by keeping its key points. The research work done on summarizing low-resourced language text is very limited. In India, the Hindi language is being spoken by central and north Indian people and only a few research works have been done on abstractive summarization of Hindi language. Having matras in Hindi makes it difficult to tokenize so it is difficult to summarize Hindi text using abstractive text summarization. In the proposed method, abstractive Hindi text summarization is done using transliteration and fine-tuning. In this work, the model is trained to generate both summaries and headlines. ROUGE-score and BERT-score have been utilized to check summary quality. A new semantic similarity score-based performance measure is also proposed to measure semantic similarity between reference summaries and predicted summaries. Using the proposed method, we have achieved the highest 55.16 ROUGE score, 0.80 BERT score, and 0.98 similarity score. Along with these performance measures, human evaluation of predicted summaries is also done and it is found that summaries and headlines were generated at a human-acceptable level.
Grid-Connected Solar Water Pumps with Reduced Converter Topology for Cost-Effective Brilliance
Authors: S.G.Kadwane,P.S.Patil A.S.Lilhare,
Published: April 2024

This study delves into the optimization of grid-connected solar water pumps by introducing a reduced topology, aiming to enhance both efficiency and cost-effectiveness. The research focuses on streamlining the system's configuration, employing innovative techniques to minimize complexity and component requirements. By implementing this reduced topology, the study anticipates substantial cost savings in the overall system while maintaining or even improving its operational brilliance. Through a comprehensive analysis of the proposed approach, this research offers valuable insights into the potential for significant advancements in grid-connected solar water pump technology, paving the way for sustainable and economically viable water pumping solutions.
MFGC: Minimal First Garbage Collection for Monitoring of Context-Aware Victim Selection
Authors: P. K.Singh Shweta
Published: April 2024

SSDs based on NAND flash are becoming a feasible secondary storage option for many computer systems. Because NAND flash memory is dif- ferent from regular HDDs, flash-based SSDs frequently have an interface layer known as Flash Translation Layer (FTL). Garbage collection tech- nique is required to free up space. Garbage collection policy is primarily concerned with cleaning costs and wear-leveling. To achieve the above design principles, we have proposed an effective minimal first garbage col- lection termed as MFGC. MFGC manages the blocks in the list, sorted in descending order of erase count. This list is divided into two regions: preference region and alternate region. The adaptive window for victim selection is used, which adapts dynamically as the cleaning cost changes. After the victim selection, effective data identification of valid hot page and valid cold page is done based on threshold and redistribution of them is done to free blocks. A Series of trace simulations is performed to evaluate the performance of proposed approach with other existing approaches. MFGC outperforms GR,  CB,  CAT,  CATA  and  MCSGC by 85.5%, 77.1%,61.7%, 56.7% and 43.5% respectively.The outcome of the simulation demonstrates that our approach is superior to others in terms of erase and copy operations as well as wear leveling of blocks
Firefly Optimization-Based Buffer Replacement Algorithm to Improve Nand Flash Memory Performance
Authors: P.K. Singh Shweta ,
Published: April 2024

Because of its shock tolerance, nonvolatility, low power consumption, and fast I/O speed, flash memory is often used for storage in consumer applications and, more recently, in the business computer environment. State drives SSDs to have not-in-place updates and asymmetric I/O latency, with write/erase operations being substantially slower than read operations. In this paper, we propose a buffer replacement technique FBRA that uses the firefly algorithm (FA) to precisely predict whether the pages residing in the buffer is hot or cold. The firefly optimization estimates hot fitness value of each page in the buffer in order to accurately classify them as hot or cold by characterizing precisely the temporal and spatial locality. To increase the hit ratio and SSD buffer use, the frequently used pages should stay longer in buffer compared to other pages. The proposed approach outperforms the existing SSD buffer management strategies regarding buffer hit ratio, write count, and runtime. Trace-driven simulation is done using FlashDB Simulator to support the performance of our approach surpasses various traditional buffer replacement policies.
“Deep Learning Based Classification of Single-Hand South Indian Sign Language Gestures”
Authors: Naveen Malvade Rajesh Yakkundimath ,Ramesh Badiger ,
Published: April 2024

Gesture recognition is a branch of computer science and language technology dedicated to utilizing mathematical algorithms for the analysis of human gestures. Within the realm of non-verbal communication, the pivotal role of human arm movements and gestures remains a focal point. This research introduces advanced multi-stream deep transfer learning models tailored for identifying signs from South Indian languages, specifically Kannada, Tamil, and Telugu. The primary aim is to offer support to individuals encountering speech disorders or disabilities. The key deep transfer learning models utilized include Inception-V3, VGG-16, and ResNet-50, which have been modified and improved to attain heightened classification efficacy. The dataset comprises 35,000 images capturing single-hand gestures. In the realm of models, Inception-V3 exhibits the utmost test accuracy, standing at 91.45%, alongside a validation accuracy of 93.45% when tasked with the classification of single-hand gesture images across thirty-five distinct categories. The importance of this study lies in its prospective utility for creating an automated system that can support and improve the functional capabilities of individuals facing speech disorders or disabilities.
Computing Topological Indices for Niobium Dioxide and Metal-Organic Frameworks via M-Polynomials
Authors: Muhammad Hussian, Hasan Mahmood Muhammad Abdullah, Sikandar Raza,
Published: April 2024

This paper investigates the topological properties of metal-organic frameworks and niobium dioxide using M-polynomials. The stability and wide range of bonding that the  molecule exhibits make it a promising candidate for a number of uses, such as energy storage, gas detection, and catalysis. We use M-polynomials to calculate several degree-based topological indices for metal-organic frameworks and niobium dioxide. The M-polynomial is one such fundamental polynomial that provides a way to derive a multitude of degree-based topological indices. These indices are crucial for research in chemistry, biology, and physics and are derived from degree-based M-polynomials. This work develops a new M-polynomial algorithm for the computation and comparison of several degree-based molecular descriptors.
12 Labours Seminar Series (Platform 3): Measuring the geometry of the human body surface
Authors: Dixon Alexander
Published: April 2024

Understanding the arrangement of bone, muscle, and fat tissue in the human body is essential for the diagnosis of diseases and the development of personalised digital twins. While imaging modalities, such as CT and MRI give accurate measurements inside the body, these modalities require bulky and expensive equipment, expert operators, and time-consuming procedures. Optical scanning of the body is a modality that is becoming cheaper and of higher spatial resolution, however it is limited to capturing the anatomy of the skin surface only. By combining optical scanning techniques with statistical models of the human anatomy, based on large datasets of internal body scans, it may be possible to perform rapid and cheap scanning of individuals to estimate their internal anatomy.

This talk will present the development of a custom optical 3D scanner, that consists of an array of inward-looking high-resolution cameras surrounding a human participant, and the subsequent use of statistical shape models for the skin surface and bone anatomy estimates.
Development of DEI Milestones for Family Medicine Residency
Authors: Wheat Santina , Rayess Fadya El
Published: April 2024

Learning Objectives:

- Describe the process of developing the five DEI milestones for family medicine residencies
- Hear the results of a national survey of FM residencies in which program directors rated their program using the DEI milestones 
- Discuss how the DEI milestones can be used by departments/residencies to chart a course to improve their institutions and advance their DEI work
A Study on the Operation Status and Educational Needs of Infection Control Educational Program for Infection Control Practitioner
Authors:   Korea Safety Culture Society, Kim Kyung Mi , Kim Og Son , Choi Jong Rim , Cha Kyung Sook
Published: April 2024

This study was the basic data necessary to develop a training program for infection control personnel by understanding the present status and needs of infection control training programs. This is a mixed-method research using a mixture of descriptive surveys and focus interviews. A descriptive study was conducted in 9 institutions that satisfied the criteria as a training institution for those working in infection control office under the Enforcement Rules of the Medical Service Act. For the study, a survey was conducted from October 31 to November 7, 2022. Focus group interviews were conducted separately with six doctors and six nurses. Survey results showed that 31 training programs on infection control were conducted in 2022 at the nine institutions, with 5,179 participants and an average duration of 9.32 hours. About 64.5% of the cases were participants of the training program involved in two or more occupations, and there was no separate training program for other participants recognized by the heads of medical institutions. As for the training methods, face-to-face and online schemes showed similar results in the survey, but the subjects preferred face-to-face education. In this study, there was a lack of specialized training programs tailored to various types of medical institutions and training programs targeting some occupations. Therefore, cooperative efforts by each organization are needed to establish governance to set up a step-by-step infection control education system that can meet education demans and provide systematic education, such as integrating or developing new programs.
Effects of Satisfaction with Childbirth·Childcare Social Services and Satisfaction with Community Life on Life Satisfaction among Young Women - Focused on Moderated Mediation Effect of Perception of Social Safety -
Authors:   Korea Safety Culture Society, Kim Jung Yoo , Eom Kwang Jin
Published: April 2024

The purpose of this study is to examine the moderated mediating effect of perception of social safety and the mediating effect of satisfaction with community life on the relationship between satisfaction with childbirth·childcare social service and life satisfaction among young women. To do this, this study used the 2022 Gangwon provincial social survey data conducted by Gangwon provincial office. The sample consisted of 296 young women(20s-30s), and the data were analyzed using SPSS 21.0 and PROCESS Macro 4.2(Model 4 and Model 14). The main results of this study are as follows: First, this study found that a higher level of satisfaction with childbirth·childcare social service was associated with a higher level of life satisfaction among young women. Second, a fully mediating effect of satisfaction with community life was found on the relationship between satisfaction with childbirth·childcare social service and life satisfaction among young women. Third, the mediating effect of satisfaction with community life on the relationship between satisfaction with childbirth·childcare social service and life satisfaction was moderated by perception of social safety. Based on those study results, this study discussed practical and policy implications for enhancing life satisfaction among young women.
A Study on the Safety and Health Performance Influence Factors of Construction Sites: Focusing on listening to the opinions of C construction sites workers
Authors:   Korea Safety Culture Society, Yu Hee Bok , Lee Joon Won , Lee Yang Woo , Kim Beom Su , Jung Sang Min
Published: April 2024

The Occupational Safety and Health Act and the Serious Accident Punishment Act, which has been in effect since January 27, 2022, specify that workers' opinions must be heard regarding safety and health. This study was conducted because it was judged that listening to workers' opinions can identify potential harmful and risk factors at construction sites and establish disaster prevention measures, ultimately affecting safety and health performance. In this study, three legal factors and four system factors were configured as independent variables, and safety and health performance was configured as a dependent variable through interviews with 37 safety and health management managers, safety managers, and health managers of C Construction Company and a review of previous research. . A survey was conducted from January 11, 2024 to January 24, 2024 targeting 162 safety and health management managers, main contractor management supervisors, main contractor safety managers and health managers, partner company management supervisors, and partner company safety managers. Statistical analysis was performed on the data collected using the SPSS program. As a result of research on the survey items, validity and reliability were confirmed to be good, and in terms of legal factors, committees and councils, listening to opinions in risk assessment, and in system factors, meetings and TBM (Tool Box Meeting) had a significant impact on safety and health performance. It was confirmed that In the future, safety and health performance is expected to improve at construction sites through active listening to workers' opinions on the legal and systemic factors identified in this study.
Creatividad humana vs. creatividad artificial: estudio comparativo entre estudiantes universitarios y chatbots en la generación de ideas
Authors: Molares-Cardoso Julinda , Badenes-Plá Vicente , Maiz-Bar Carmen
Published: April 2024

La inteligencia artificial (IA) está transformando los espacios creativos de la sociedad. Algunas investigaciones creen que la IA puede ser creativa, al analizar grandes cantidades de datos y aprender de ellos, mientras que otras sostienen que genera ideas basadas en patrones existentes, lo que plantea interrogantes sobre su verdadero potencial creativo. El presente estudio tiene como objetivo investigar si la IA puede ser igual de creativa que los alumnos de un grado de Publicidad y Relaciones Públicas especializados en esta área. La metodología empleada consistió en un experimento de carácter mixto donde se utilizó un ejercicio creativo verbal. Una vez los estudiantes realizaron la prueba, se utilizó la plataforma Poe.com para evaluar la creatividad de los chatbots ChatGPT, Claude-instant y Dragonfly, siguiendo las mismas instrucciones dadas a los alumnos. Las conclusiones ponen de manifiesto que los sistemas de inteligencia artificial todavía no pueden competir con la capacidad creativa de una persona. Tanto los resultados de carácter cuantitativo como los de carácter cualitativo revelan que, aunque la IA puede potenciar las capacidades humanas, no puede reemplazarlas. Los chatbots mostraron limitaciones para comprender las sutilezas del lenguaje, generar conceptos nuevos, aplicar síntesis y desarrollar un pensamiento lateral. La IA puede repetir patrones existentes, pero no puede replicar la complejidad y riqueza de la creatividad humana ni puede establecer conexiones emocionales con los temas.
中華聽障跆拳道隊2007至2022年競賽實力探析
Authors: 曾柏翔 曾柏翔 , Bo-Shiang Tseng 邱共鉦 , Kung-Cheng Chiu 蔡明志 , Ming-Chih Tsia 陳淑貞
Published: April 2024

運動競賽攸關該運動發展的重要課題，查閱跆拳道相關文獻資料，發現研究主軸以聽人比賽技戰術或體能類居多，對於歷史文化發展較為漠視。本研究以2007至2022年探究中華聽障跆拳道競賽紀實。透過文獻探討的方式，探究2007至2022年中華聽障跆拳道隊的競賽歷程與探討未來走向，為本研究之目的。研究發現，中華聽障跆拳道隊的競賽實力表現下滑，原因包括選手招募不足、訓練時間不穩定及人才流失。結語，目前中華聽障跆拳道選手招募不易，競賽成績下滑，亟急需政府與相關協會調整施訓制度，挹注經費，鼓勵更多聽障者參與跆拳道訓練，期待未來能再創佳績。

 

The performance in sports competitions is a crucial issue that directly impacts the development of the sport, and a review of the relevant Taekwondo literature reveals that research has predominantly focused on the technical and tactical aspects or physical fitness of hearing-impaired athletes, while often neglecting the historical and cultural aspects. This study investigates the competitive records of Chinese Deaf Taekwondo from 2007 to 2022. Through a literature review, it explores the competitive journey of the Chinese Deaf Taekwondo team during this period and discusses its future direction, which is the main objective of this research. The study reveals that the competitive performance of the Chinese Deaf Taekwondo team has been on the decline. The reasons for this include inadequate athlete recruitment, inconsistent training schedules, and a depletion of coaching talent. In conclusion, recruiting Deaf Taekwondo athletes is currently a challenging task, and competitive performance is experiencing a downturn. There is an urgent need for the government and relevant associations to adjust the training system, allocate additional funding, and encourage more hearing-impaired individuals to participate in Taekwondo training. The aspiration is for better achievements to be realized in the future

 
Perspectiva SSSCIP asupra atacurilor cibernetice derulate în contextul conflictului militar dintre Federația Rusă și Ucraina (ianuarie 2022 – ianuarie 2024)
Authors: OLTEANU Mihai
Published: April 2024

Lucrarea de față evaluează raportările SSSCIP privind atacurile cibernetice derulate asupra Ucrainei în perioada ianuarie 2022 - ianuarie 2024. De la exploatarea malware-ului CaddyWiper, atribuit de SSSCIP către APT SANDWORM, la campaniile sofisticate ale FSB și atacul cibernetic asupra Kyivstar, lucrarea prezintă o perspectivă a atacurilor cibernetice de origine rusă derulate asupra Ucrainei, așa cum au fost raportate de autoritatea ucraineană în domeniu. Scopul articolului este acela de a identifica modul în care SSSCIP (principala instituție responsabilă pe componenta de securitate cibernetică) a raportat atacurile cibernetice asupra infrastructurilor IT&C ucrainene, completitudinea datelor publicate, precum și modalitatea în care sunt prezentate campaniile. Pentru realizarea acestui scop, au fost evaluate toate raportările SSSCIP din perioada de referință și au fost incluse în studiu doar acelea care s-au materializat și au afectat infrastructuri IT&C. În concluzii, vor fi evidențiate, în principal, limitările raportărilor SSSCIP și, secundar, perspectiva SSSCIP privind domeniile care au fost cel mai des vizate de atacuri cibernetice și capabilitățile actorilor ruși.
Strategii narative în acțiune – text, formă și context
Authors: CIORNEI Anca
Published: April 2024

Schimbările majore din mediul global de securitate, care au avut loc la sfârşitul mileniului trecut, continuă să marcheze profund inclusiv primul sfert al secolului al XXI-lea, caracterizat prin modificări substanţiale ale instrumentelor clasice utilizate în desfășurarea unui conflict. De asemenea, transformarea mediului informațional a condus la apariția, la dezvoltarea, la adaptarea și la contextualizarea utilizării narațiunilor strategice, cu scopul de a influența percepțiile oamenilor asupra acțiunilor puterilor statale și de a produce efecte, în sensul dorit de către acestea. Scopul prezentului articol este de a supune atenției narațiunile strategice, ca parte a confruntărilor hibride contemporane, urmărind a aduce o mai bună înțelegere a acestui subiect, cu observarea modului în care acestea sunt folosite și cu ce efecte, în funcție de forma sub care apar. Mai mult, lucrarea propune o delimitare conceptuală multinivel, abordând narațiunile strategice din perspectiva textului, contextului și formei, așa cum sunt evidențiate în cele mai recente lucrări din domeniul de specialitate. Totodată, vom supune atenției și folosire lor în context aliat, cu referire la documentele de lucru pe care NATO le utilizează în comunicarea strategică, cu scopul de a influența grupurile țintă și audiențele atât interne, cât și externe.
الذكاءات المتعددة كمنبئ بممارسة الأنشطة السارة وشدة السعادة المدركة لدى طلاب الجامعة
Authors: زكريا حسين عبد المجيد منال
Published: April 2024

تهدف الدراسة الحالية إلى فحص العلاقة بين الذكاءات المتعددة وممارسة الأنشطة السارة وشدة السعادة المدركة لدى طلاب الجامعة. وقد أجريت هذه الدراسة على عينة قوامها 574 طالبًا وطالبة من أربع كليات بجامعة القاهرة هي كليات الآداب والحقوق والصيدلة والهندسة. وأجاب المشاركون في الدراسة عن مقياسين، يختص المقياس الأول بقياس سبعة أنواع من الذكاءات وفقاً لنموذج جاردنر هى الذكاء اللغوي والذكاء الموسيقي والذكاء الاجتماعي والذكاء الشخصي والذكاء الحركي والذكاء الحسابي المنطقي والذكاء البصري المكاني، بينما يختص المقياس الثاني بقياس تكرار ممارسة الأنشطة السارة وشدة السعادة المدركة في سبعة مجالات هي المجال الديني، والثقافي، والاجتماعي، والرياضي، والفني، والأكاديمي، والترويحي. وقد بينت النتائج تباين الارتباطات بين الأنواع المختلفة للذكاء ومدى تكرار الأنشطة السارة وشدة السعادة المدركة في مجالاتها المختلفة، كما أوضحت تباين الأوزان النسبية لأنواع الذكاءات في التنبؤ بتكرار الأنشطة السارة وشدة السعادة المدركة.

الكلمات المفتاحية:

الذكاءات المتعددة؛ الذكاء؛ السعادة المدركة؛ الأنشطة السارة.
الاستلاب في مسرح سعد الله ونوس: الأصول الكلاسيكية في المسرح العالمي
Authors: خليل الخفاجي بسام , محمود القللي محروس
Published: April 2024

"الاستلاب" من المفاهيم التي اتسع النقاش حولها؛ لأنه يعالج موضوع الإنسان وعلاقاته بالدين والحياة. وقد انتقل مفهومه من اللاهوت إلى رحم الفلسفة عبر سلسلة طويلة من أسئلة الأنثروبولوجيا واحتجاجات الإنسان ضد السلطة الكنسية، وصولا إلى بلورته على يد الفلاسفة، وبخاصة لدى فلاسفة الماركسية. وننطلق في دراستنا تيمةَ "الاستلاب" في مسرح سعد الله ونوس من تلك العلاقة المتوازية التي مثّلتها الرغبة غير الواعية للأنظمة الدكتاتورية في محاكاة بعضها البعض الآخر، الأمر الذي تجاوز انتزاع الحقوق المادية للإنسان إلى سلب الوعي الفردي والجمعي. ولا فرق بين نوع الأنظمة التي توالت على البشر، سواء كانت دينية، أو مدنية لها شعارات رنانة. وسوف نتخذ المنهج الموضوعاتي المقارن دليلا في دراستنا لمسرح ونّوس؛ لأنه يتتبع الموضوعات دون التوقف عند لغة معينة أو قومية بعينها، بل يتتيع تيمة "الاستلاب" متجاوزا الزمان والمكان والثقافة. ونحاول في هذا البحث الإجابة عن سؤالين: الأول: هل كشف المسرح عند سعد الله ونّوس والمسرح العالمي عن حقيقة واحدة تتبدى من مجموع غير متجانس لكل الأنظمة المستبدة؟ والآخر: هل استطاع المنهج الموضوعاتي كشف صورة "الاستلاب" المتشكلة وفق رؤية علائقية موضوعاتية مقارنة؟

الكلمات المفتاحية: الاستلاب؛ سعد الله ونوس؛ المسرح العالمي؛ الأدب المقارن؛ المدرسة السلافية.