bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hints on the Multicore CPU Design for Personal Computers
Authors: İren Ecem , Akince Halil Can , Kantarci Aylin 
Published: December 2023

AbstractAbstract - Multi-core processors are created by combining multiple units, each called the core, containing the processing unit, registers and a cache. This study provides a detailed analysis on the performances of multicore CPUs for personal computers. We parallelized some cryptographic algorithms with OpenMP tool and tested one 2-core and one 4-core CPU with two cryptographic software one of which imposes high data load and the other one high work load. In the light of the experiments that stress the CPUs from these two different aspects, we present our hints and suggestions for designing multicore chips for the usage in personal computers.
Impact of Virtual Assistant on Programming Novices’ Performance, Behavior and Motivation
Authors: Biňas Miroslav , Pietriková Emília 
Published: December 2023

Abstract
In the following study, we deal with data-driven support for novice programmers – students, working in large groups. We introduce a virtual assistant, which aims to simplify communication and feedback, sending reports and advice during the programming course. We experiment with 134 students during one semester period, and we try to understand how the virtual assistant affects novices – students. In the introduction, we state 3 hypotheses, focusing on performance, behavior, and motivation. The experiment evaluation relies on data collected throughout the semester. The results reveal the impact of the virtual assistant on novice programmers in 2 of the studied aspects – performance and motivation. This can be perceived as potential towards efficient support in programming education, especially in large groups. We also believe the study is contributional to the areas of learning analytics and program comprehension.
Analysis of Reactions of Mobile Phone Users
Authors: Šatala Pavol , Ivančáková Juliana , Trella David , Butka Peter , Babič František 
Published: December 2023

Abstract
In this work, we analyze the aspects of user reactions during their work with a mobile phone. We tried to find the most crucial positions within the mobile screen, which provide essential information and stimulus. One of the main factors is to know which part of the screen is the first interest of the user and which part the user reacts to the fastest. Sixty-four persons participated in an experiment. We used the gamification approach to motivate users for the best results and created a game. Users competed with each other during the game, and they tried to react to the new point of the screen as soon as possible. The experiment showed that about a quarter of the screen below the centre was an area where users react the fastest. There were interesting differences between men and women and signs of background impact.
Decision Support System Improving the Interpretability of Generated Tree-Based Models
Authors: Klimonová Diana , Anderková Viera , Babič František , Majnaric Ljiljana Trtica 
Published: December 2023

Abstract
A decision tree represents one of the most used data analysis methods for classification tasks. The generated decision models can be visualized as a graph, but this visualization is quite complicated for a domain expert to understand in large or heterogeneous data. Our previous experience with medical data analytics related to the classification of patients with Metabolic Syndrome, Mild Cognitive Impairment, heart disease, or Frailty motivated us to evaluate the potential of new visualizations for this decision model in the medical domain. We managed a user study to design and implement a decision support system containing selected methods to improve the interpretability of the generated tree-based decision model. We hypothesized that this approach would result in more effective communication between data analysts and medical experts, reduce necessary time and energy and bring more comprehensive results. For this purpose, we selected two model-agnostic methods, LIME and SHAP, and one new interactive visualization called Sunburst. We used two data samples for design and evaluation: the publicly available heart disease dataset and the Metabolic Syndrome dataset the participating medical expert provided. We will use the collected feedback and experience for further improvements, like more evaluation metrics related to the usability of the decision models.
Analysis and Collection Data from IP Network
Authors: Hasin Martin , Chovanec Martin , Palša Jakub , Havrilla Martin 
Published: December 2023

Abstract
The rapid deployment of technologies that can share data brings, in addition to the positive aspects, also technologies that an attacker can use to misuse personal data. Vulnerabilities in the network can be divided according to the type of attack into horizontal attacks from the perspective of the attacker and vertical attacks from the perspective of the victim. An important goal of organizations is to successfully defend against such an attack. The search for attacks on the network infrastructure can be ensured by implementing machine learning that can capture the current attack. This work describes methods of searching for attacks using graphical representation of data and also using machine learning of the high count type at different sizes of the investigated segments.
IoT Anomaly Detection with 1D CNN Using P4 Capabilities
Authors: Altangerel Gereltsetseg , Tejfel Máté , Tsogbaatar Enkhtur 
Published: December 2023

Abstract
Although the Internet of Things (IoT) is a rapidly developing technology, it also brings a number of security challenges, such as IoT attacks. Currently, research on IoT anomaly detection in Software-Defined Networking (SDN) relies only on the control plane. In this study, we aim to detect IoT anomalies by covering the advantages of the control and data plane. First, we collected real-time network telemetry data from the data plane based on the capabilities of the P4. Then, using this telemetry data, we built different anomaly detection models and compared their performance. Among them, the one-Dimensional Convolutional Neural Network (1D CNN) model classified our data best and showed the highest performance, so we proposed this model for IoT anomaly detection on the control plane. To our knowledge, our approach is the first solution that integrates the control plane and data plane for IoT anomaly detection. Finally, when evaluating the performance of our proposed 1D CNN model, the accuracy, F1 score, and Matthews correlation coefficient (MCC) are the same or better than existing studies.
Innovative Paths of Modern Fiscal and Financial Systems to Assist the Coordinated Development of Regional Economy
Authors: Gu Ruipeng 
Published: December 2023

Abstract
The coupling and coupling coordination degree model is used in this paper to classify the coupling coordination degree level of industry and regional economic development. According to the correlation between the fiscal, taxation, and financial system and regional economic development, the coupling driving mechanism algorithm is selected to analyze the degree of assistance of the fiscal, taxation, and financial systems to the coordinated development of the regional economy. Taking the analysis of the Chongqing tourism industry and regional economic development level as an example, the coupling degree relationship between fiscal, tax and financial policies on regional economic development is analyzed according to the coupling coordination degree. The degree of financialization in the northern coastal economic zone is the highest at 4.4885, and the degree of financial deepening in the southern coastal integrated economic zone is 3.7621 lower than that in the northern region, but the coefficient of its β1′ is 0.0207, which indicates that it has a positive regulating effect on the development of the regional economy.
Residual life prediction of bearings based on RBF approximation models
Authors: Zhen Qiang , Shen Ling 
Published: December 2023

Abstract
Once the failure of rotating machinery occurs, it may cause the whole system to paralyze and cause great economic losses, or it may cause casualties. Therefore, the prediction of the remaining life of bearings is of great significance. The purpose of this paper is to analyze the approximate modeling technology and develop a framework for combined approximate modeling technology. A multi-strategy radial-based approximate model optimization model is proposed based on the limitations of radial-based approximate model technology. Utilizing the weight coefficient solving technique, the variable confidence RBF model, i.e., RBF-LSTM model, is established. Propose the remaining methods for life prediction using the bearing life prediction process. The RBF-LSTM combined approximation model is used to construct the evaluation index for rolling bearing remaining life prediction. Using the empirical analysis method, the optimization effects of different models and the accuracy of bearing remaining life prediction are analyzed, respectively. Experiments show that the data range of the RBF-LSTM combined approximation model is between [23,52], the overall fluctuation range of the data is not large, and the time taken is only 31 s. After 230 calculations, the model optimization effect is better. In the remaining life validation, the starting values of 132h and 148h are less different from real life, only 1.53h and 1.3h, respectively, and the model prediction accuracy is high.
Informatization Integration Strategy of Modern Vocal Music Teaching and Traditional Music Culture in Colleges and Universities in the Era of Artificial Intelligence
Authors: Zhang Ni 
Published: December 2023

Abstract
This paper utilizes deep learning algorithms to informally integrate modern vocal music teaching with traditional music culture and extracts audio time-domain features and frequency-domain features through neural network self-learning. Secondly, a large number of music tracks are decomposed into music patterns, which constitute a music pattern library, and a music training model is generated through the automatic music audio synthesis algorithm based on a recurrent neural network, and the GRU model is used for music training and model prediction. The strategy of integrating artificial intelligence and modern vocal music teaching mode through traditional music culture in modern vocal music teaching is informatized, and a controlled experiment is carried out with H Music Academy as an example. The results show that the average degree of completion of the learning objectives of the students in the two experimental classes is 89.32 and 87.16, respectively, which is 14.15 and 11.99 higher than the average degree of completion of the control class. This study demonstrates that the teaching mode of traditional music culture integration in modern vocal music teaching can enhance the student’s ability of vocal music skills and practically improve the students’ artistic literacy, which can improve the degree of completion of the student’s learning objectives and in turn, improve the overall level of vocal music teaching.
Study on the Dissemination Path of Chinese Modern and Contemporary Literature in the Background of the Internet
Authors: Hu Dihui 
Published: December 2023

Abstract
This paper first establishes a literary communication SICR model on the basis of the communication SICR model. It adopts cultural communication state transfer to construct a social network composed of N-closed individuals. Secondly, the dissemination threshold when the model reaches a stable state is discussed from the beginning and end of the literary work dissemination process. Finally, numerical simulation research using MATLAB software is used to analyze the propagation process of modern Chinese literary works, with examples provided. The results show that the number of literary ignoramuses (I) transformed into literary propagators (S) gradually rises when the initial values are S(t)=8915, I(t) =3414, C
0 =5288, and R
0 =850 in the dissemination process of X novels in Fictum, a Chinese online literature, and reaches the dissemination threshold when the dissemination rate reaches 0.856. This paper aims to provide a guide for advancing the advancement of modern and contemporary Chinese literature to the outside world and advocating for cultural dissemination.
The Role of English Language and Literature in the Cultivation of Students’ Language Proficiency in the Context of Deep Learning
Authors: Jia Manli 
Published: December 2023

Abstract
In this paper, the PSO-LSTM algorithm is used to construct a model for evaluating students’ language proficiency, and the improvement of the acceleration factor and inertia weights is used to adjust the influence of the individual optimal position and the global optimal position in the speed update. For model performance judgment after optimization of LSTM hyperparameters, the PSO fitness function is replaced by MAPE and MSE functions. Finally, the student’s English composition texts were used as experimental parameters and input into the language proficiency evaluation model to verify the model performance and analyze the influence of English language literature on language proficiency. The results show that English language literature is effective in predicting 18.55% of the variance in English proficiency level for self-efficacy, 8.17% of the variance in English proficiency level for language attitude, and 0.47% of the variance in English proficiency level for learning anxiety, which indicates that English language literature has a significant effect on students’ English proficiency. This paper investigates the role mechanism of the English language and literature in the cultivation of student’s English proficiency, which provides a theoretical reference for the reform of English teaching in colleges and universities.
Research on Talent Cultivation and Industry-Education Integration Path Construction of College Education under the Perspective of Informatization
Authors: Li Cong , Li Hui 
Published: December 2023

Abstract
This paper extracts the basic elements of the integration of industry and education under the perspective of symbiosis theory and builds a symbiosis model in the communication and cooperation between symbiosis units according to the symbiosis units in the system of integration of industry and education. Influential factors were screened from different levels, and the DEMATEL method was used to determine the importance degree of system factors in combination with the explanatory structural model so as to construct the structural framework of influential factors. The weights of the influencing factors were finally confirmed through analysis, and empirical research was conducted on three colleges and universities, S1, S2, and S3. The overall performance level of S1 college and university integration is excellent, and the comprehensive judgment value of the college and university integration performance of this college and university is 85.342. The overall performance level of the two colleges and universities, S2 and S3, is good, and the comprehensive judgment value of the college and university integration performance of the two colleges and universities is 77.933 and 81.930, respectively. The evaluation study on the integration of industry and education can provide better recommendations for the integration path.
Preparation of cross-linked chitosan magnetic microspheres and immobilization of pectinase
Authors: Wu Hao , Zong Zhimin 
Published: December 2023

Abstract
In this paper, the kinetic model under the influence of each factor is given by investigating the effects of distribution effect, external diffusion effect and internal diffusion effect on the immobilized pectinase reaction system. The magnetic chitosan microspheres were prepared by the reversed-phase suspension cross-linking method, and the effects of the type and amount of cross-linking agent and the ratio of chitosan to magnetic core incorporation on the performance of the magnetic spheres were investigated. Then, the immobilized pectinase was prepared by using cross-linked chitosan magnetic microspheres as a carrier, and an orthogonal test was used to determine the conditions of immobilized enzyme preparation and to study the enzymatic properties and operational stability of immobilized pectinase. The results showed that the transmittance of the magnetic microspheres of this test increased from 32% to 90.79% in 10 min in a magnetic field, but in a gravity field, the transmittance increased from 32.12% to 46.44% in 50 min. The experimentally prepared microspheres exhibit good magnetic responsiveness. The optimum temperature of immobilized pectinase was 50°C, and the remaining enzyme activity was still 61.24% after 6 repetitions. The immobilized pectinase made by crosslinking glutaraldehyde with chitosan magnetic microspheres has a high recovery of enzyme activity and good operational stability, as indicated by this.
Construction of a Visual Platform for Higher Vocational Financial Education Combining Gaussian Hybrid Networks
Authors: Xu Lu 
Published: December 2023

Abstract
In this paper, a Gaussian mixture network distribution finance has been carried out to assess the risk, which is used as a risk assessment tool for the visual platform of higher vocational financial education. Financial data is quantified and determined by determining the cumulative expected loss amount to establish the financial investment risk assessment function. The Activiti open-source workflow engine was utilized to remove complex financial data and configure the K-line as the platform’s data visualization tool. Finally, the financial education visualization platform was used to analyze the Gaussian distribution and K-line data of X stock, which verified the practicality of the platform, and the effectiveness of the platform was verified by taking the students of H higher vocational college as the sample of the teaching experiment. The results show that the influence coefficient of the platform teaching on the quality of the course is 0.856, and the influence coefficient on the learning interest is 0.887, which indicates that the visual platform teaching makes students interested and strengthens their cognitive level. The visual digital reform of teaching finance majors in colleges and universities is provided with a new reference direction by this paper.
Analysis of Strategies for Enhancing Informatization Teaching Ability of College Teachers Combined with Mathematical Statistics Multiple Regression Models
Authors: Li Yang 
Published: December 2023

Abstract
In this paper, from the perspective of education informatization, for the problem of teachers’ informatization teaching ability in colleges and universities, the loss function of the analysis of teachers’ informatization teaching ability in colleges and universities can be calculated by using a Logistic regression algorithm. In order to prevent the overfitting problem of multiple regression analysis, it is necessary to optimize the multiple regression analysis by regular transformation, and then construct the model of teachers’ informatization teaching ability based on multiple linear regression, and determine the research variables and regression equations in the model. Starting from the research objectives, the research objects and problems are determined, and two analysis methods, simulation analysis and statistical analysis, are used to empirically analyze the informatization teaching ability of college teachers. The results show that on the analysis of model instances, the correlation coefficients between the factors and the overall teacher educators’ informatization teaching ability range from 0.671 to 0.829, and there is a certain correlation between each factor and teacher educators’ informatization teaching ability. On the analysis of differences in teachers’ informatized teaching competence, the five competence constructs of Guangzhou college teachers’ education in technological literacy (P=0.653>0.05), instructional design (P=0.133>0.05), instructional implementation (P=0.584>0.05), evaluation development (P=0.287>0.05), and informatized teaching competence (P=0.413>0.05) do not significant differences exist. This study comprehensively analyzes the strategies for improving teachers’ informatization teaching ability in order to play some role in promoting the development of education informatization.
The Innovative Model of Higher Education Management and Student Training Mechanism in the Internet Era
Authors: Jiang Mingsi 
Published: December 2023

Abstract
With the goal of improving the ability of higher education management and student cultivation, this paper applies face recognition technology to higher education management and student cultivation and proposes a new model of digital management and cultivation. By analyzing the recognition process of the face recognition algorithm in face detection and combining the data to describe the deformability of the face, a neural network-based face recognition algorithm is constructed. After inputting the face image data, it passes through several convolutional layers, a linear rectification layer and a pooling layer and finally connects to the fully connected layer so as to achieve the effect of face recognition. The results show that the face recognition technology training state accuracy rate in the 0~3000th generation rises sharply, which can be seen in the neural network in 3500 generations around the rise has gradually leveled off in 5000 generations to reach convergence. Strengthening digital management thinking can improve the management effect to a certain extent and improve the management content so as to achieve the specific management effect.
Research on the Application of Traditional Sports Culture in College Physical Education Teaching under the Background of Deep Learning
Authors: Meng Xuezhi , Li Jiangnan 
Published: December 2023

Abstract
In this paper, the transformer target detection algorithm is established by combining deep learning technology, and the Deep algorithm is added on the basis of SORT to optimize and improve SORT and overcome the problems of SORT. After the DeepSORT model is constructed, YOLOv5 is introduced into the model, and finally, the YOLOv5-DeepSORT model for sports element detection and tracking is constructed and completed. The ATT-BERT sports culture element entity recognition model is constructed from four levels: the BERT layer, the BiLSTM layer, the attention layer, and the CRF layer, which results in an application framework for the integration of traditional sports culture into teaching. The influence factors of sports culture perception and sports teaching, as well as the integration of traditional ethnic sports culture into sports teaching in Z, were empirically examined. The study shows that the correlation coefficient between the two is around 0.465, and there is a positive and strong correlation between the two. The correlation coefficients of the dimensions for physical education students and non-physical education students were 0.513, 0.483, 0.485, and 0.462, respectively. The most common teaching methods used by teachers in physical education classrooms integrating traditional sports culture were explanation, demonstration, and complete decomposition, with ratios of 0.78 and 0.7, respectively. The integration of sports culture into physical education has resulted in good results. The outcome was satisfactory.