bluuebunny/crossref_metadata_2025 huggingface dataset:
An Exploration of the Teaching Mode of Civics and Politics in English Education Courses of Higher Vocational Colleges and Universities Based on Big Data Technology
Authors: Niu Xiaohong
Published: July 2024

Under the requirements of the educational background of the new era, establishing moral character has become the fundamental task of education, and at the same time, it also brings new challenges and opportunities for English education in higher vocational colleges and universities. Based on the core qualities of the curriculum Civics and Politics, we explore the point of fit between English education and it so as to deeply analyze the integration mechanism of the curriculum Civics and Politics in English education and complete the construction of the teaching model of the curriculum Civics and Politics in English education by combining with the big data technology. On this basis, taking S higher vocational colleges applying this model as an example, the expert scoring method is used to construct the teaching quality evaluation index system and assign weights, and the fuzzy comprehensive evaluation model is used to assess the quality of education. Core literacy and comprehensive ability have the highest weights of 0.2836 and 0.2866 respectively, respectively, which are key areas for cultivation. Finally, through the quality evaluation of the education model of this paper, it can be seen that the highest score of comprehensive ability is 90.21, which is at the excellent level, and the lowest score of values cultivation is 81.98. and the scores of each index are above 80. The average score of the education model of this paper is 85.13, which proves that the quality of teaching under the teaching model is good. It has an excellent performance in the cultivation of English talents. It is a good example of Big Data Technology, and the integration of the English education program Civics provides a feasibility with practical significance.
Practical Reflections on Enhancing Cultural Confidence in English Education in Colleges and Universities under the Big Data Platform
Authors: Wang Hongyang
Published: July 2024

Day by day, we are realizing the goal of the great rejuvenation of the Chinese nation, which necessitates the development of sufficient cultural self-confidence. The amalgamation of traditional culture and English learning is an essential prerequisite for us to effectively communicate the Chinese story to the world. This paper proposes an optimized ridge regression model with regularization constraints to enhance the preprocessing of cultural data. Subsequently, we propose a statistical model for analyzing the teaching styles of English texts from four perspectives, taking into account the characteristics of English language teaching and the cardinal text statistics algorithm based on word frequency optimization. This model’s analysis revealed that textbook articles reflecting traditional Chinese culture accounted for only 1.8% of all types, resulting in an uneven distribution of grades. Following the implementation of improvements to tackle this issue, 74.86% of the students expressed their belief that enhanced teaching could bolster their cultural confidence. Similarly, 86.6% of the teachers expressed their belief that incorporating Chinese culture into English teaching could enhance students’ cultural awareness, and 90% of the teachers believed it could boost students’ identification with Chinese culture and cultural confidence. It shows that the new teaching method optimized by conducting textual statistical analysis helps to bring into play the role of English education in colleges and universities in enhancing cultural self-confidence.
Optimizing bank credit risk assessment models using big data analytics
Authors: Yang Feiyu , Xu Jing
Published: July 2024

With the strong promotion of financial globalization and marketization and the rapid development of financial industry innovation, credit risk management is becoming an important work that banks need to pay more and more attention to. This paper focuses on the construction of the bank credit risk model to carry out research. First of all, according to the credit characteristics selection method, the optimal indicators are combined with the indicators for the correlation test of variables. On this basis, the sample data is calculated using the up-sampling method of SMOTE to complete the algorithm and sampling. After obtaining the data, data preprocessing is carried out using the MinMaxScaler scaler method, and the processed data is inputted into the improved momentum BP neural network to complete the credit risk assessment. Profiling with risk feature data, it is obtained that each feature is not a separate individual from the other. They are interdependent and connected and have obvious correlations. For example, there are 47 features in the dataset with sample missing ratios greater than 0.97, which is too high and indicates an invalid feature. The results of the study show that SMOTE’s up-sampling method and Momentum BP algorithm can quickly utilize big data to provide a more accurate decision basis for bank credit risk assessment.
Innovative Development Mode of Tourism and Culture Industry in the Era of Smart Tourism
Authors: Zhang Pingping
Published: July 2024

In the era of smart tourism, its emergence not only provides crucial technical support to meet the needs of tourists but also prompts the reform and improvement of the development mode of the tourism and culture industries. This study begins by examining the current state of smart tourism and the development of the tourism and culture industries. It then conducts a thorough analysis of the mechanisms driving these developments and establishes an industry analysis model based on the RMP theory. The study then employs fractional regression to identify the factors that influence the development of the smart tourism and culture industry. It then constructs a model for smart tourism and culture development, which includes government and industry support, economic and cultural support, digital information technology support, personnel support, talent cultivation, cultural participation, and social participation. Finally, it analyzes the impact of this model’s application using the RMP analysis model. This paper’s development model sees annual increases in tourism and culture industry indexes, rising from 105.85 to 145.79, with an average growth ratio of 17.35%. The overall satisfaction rating for the product experience stands at 4.152, suggesting that under the development mode of the smart tourism and culture industry in this paper, both the market economy and the product experience exhibit excellent phenotypes. This paper supports the construction of a smart tourism cultural industry development model using digital technology and provides references for the tourism cultural industry model.
Efficiency Assessment of Policy Instruments for Green Finance Management in the Context of Low Carbon Economy Based on Panel Vector Autoregressive Modeling
Authors: Zhu Chenyang
Published: July 2024

This paper takes green finance policy as the research object and collects local government policy texts about green finance so as to study its policy structure in depth. Then, it studies the theory of green finance to support the low-carbon economy, empirically analyzes it in terms of measurement using the panel vector autoregressive model, and tests its smoothness and covariance to explore the impact of green finance in the development of the low-carbon economy. According to the findings, the proportion of demand-based green financial policies is the lowest among the five provinces, with a mean value of 22%. The extreme differences in development levels of a low-carbon economy and green finance are 1.52 and 1.46, respectively, showing different characteristics. The model regression coefficient of the level of green financial development is 0.08, and the development of a low-carbon economy positively influences it. Although the effectiveness of green financial policies will fluctuate, the overall trend is upward. This paper analyzes the panel vector autoregressive model and the effectiveness of policy tools to provide suggestions for improving the policy system.
Speech Network Analysis and Spoken English Teaching for 6G Wireless Transmission Technology
Authors: Wu Meimei
Published: July 2024

Recent years have seen intensive research and widespread application of 6G wireless transmission technology, providing a technical bridge for the application of speech network analysis to spoken English teaching. Thus, this paper suggests a method for improving 6G technology. This paper primarily focuses on the following areas: First, to prevent overfitting, the dropout technique under 6G is added to the model, and the speech feature extracted from the data by the coding network is directly utilized. We then utilize the feature for either reconstruction or classification purposes. Initially, we perform unsupervised reconstruction using unlabeled data, and once we obtain the network parameters, we use the labeled data for classification. The next step involves feeding both data simultaneously into the model to calculate the error. Finally, we use gradient descent to minimize the error and optimize the parameters until the model converges. This model can convert sound-related symbols or information into visual symbols, and it can also convert speech into text. Comparative analysis shows that the improved method in this paper is far better than other methods in terms of noise reduction, and the signal-to-noise ratio of this paper is 3.76 dB higher than that of the LMS algorithm and 1.36 dB higher than that of the spectral subtraction method, which can stimulate the students’ interest in learning spoken English and increase the student’s interest in learning by 13.64% as a whole. It can be summarized through the comparison that this paper’s improved method increases the clarity of speech network analysis, which helps students teach spoken English.
Marxist Internet Communication and Youth Ideology Education
Authors: Yan Xiaoyu
Published: July 2024

Enhancing the mainstream ideological identity of young people is an unavoidable issue in the ideological construction of socialism with Chinese characteristics in the new era, which is closely related to strengthening the national identity and expanding the mainstream ideological positions. In this paper, we refer to the E-learning platform framework to design a Marxism online learning platform to achieve the online dissemination of Marxism and ideological education for youth. The HRNN model is utilized to extract and identify the behavioral traits of youth on the Marxism learning platform and investigate the link between youth behavior and ideological identity. The results of the study show that the Marxist online learning platform has a better communication effect and can improve the identification of the youth group with Marxist ideology. Meanwhile, the correlation analysis shows that there is a significant correlation between video viewing completion, quiz completion, and ideological identity (P=0.000), which is highly positive. The suggestions put forward in this paper regarding communication management, communication technology, and publicity provide a reference for further online communication of Marxism and lay the foundation for the enhancement of youth ideology education.
Practical Research on the Reform of Social Practice Teaching in Colleges and Universities under the Background of Big Data
Authors: Yang Yang
Published: July 2024

Social practice teaching in colleges and universities combines theory and practice, transforms professional theory into practical behavior, and innovates students’ way of thinking, which can promote the teaching of colleges and universities as well as the cultivation of target talents. The big data era is innovating the traditional social practice teaching mode, and new opportunities are available for the development of social practice teaching. By analyzing the development form of social practice in colleges and universities in the era of big data, we propose to use the fuzzy C-mean clustering algorithm to deal with students’ social practice behaviors, to classify the type of students’ participation in social practice in colleges and universities, and to grasp the development status of the reform of social practice teaching in colleges and universities in the era of big data. The rating of dimensions of the social practice process in colleges and universities is used to determine the overall development level of social practice reform in colleges and universities. It also analyzes the differences in the process of carrying out social practice in colleges and universities, with the types of colleges and universities and categories of specialties as independent variables. When K is equal to 4, the contour coefficient is the largest, and the clustering effect is the best, so the students’ social practice participation can be reflected in four types: “need to improve”, “backward”, “hard-working” and “active”, combined with the overall score of social practice teaching reform in colleges and universities in the era of big data is 3.81±0.82 points, and the scores of all dimensions are above 3.75, and the overall development of social practice teaching reform in colleges and universities proposed in this paper is better.
Ideas for the construction of the curriculum system of calligraphy education in higher education institutions oriented to the future technology
Authors: Yuan Pingliang , Guo Dan
Published: July 2024

In view of the current situation that the curriculum construction of calligraphy education needs to be perfected, a more comprehensive and in-depth study is carried out for the curriculum setting and development of calligraphy education in higher teacher colleges and universities, starting from the core - curriculum system in calligraphy education. Based on information technology, this paper constructs a path of calligraphy education construction, from which the learning resources design, learning content design, learning activities design, and learning evaluation design of the practical calligraphy classroom are carried out. For the learning evaluation of the calligraphy education curriculum system, a calligraphy word evaluation model is proposed, which consists of three parts: overall structure, stroke form, and font layout. Ultimately, students can be scored according to the evaluation standard of calligraphy words. In the overall evaluation of the curriculum system constructed in this paper, 75%, 74%, and 72% of the students agreed strongly with the system in the cultivation of “knowledge”, “ability,” and “thinking and literacy,” respectively. The students indicated that they “strongly agree” with this system. With regard to the cultivation of “thinking and literacy”, this paper proposes corresponding improvement strategies to improve the calligraphy education program system.
RGB pixel information fusion segmentation of dense point cloud data for transmission and distribution 3D digital corridors
Authors: Li Duanjiao , Luo Jingbin , Zhang Jian , Liu Gao , Guo Qidi
Published: July 2024

Point cloud segmentation, as a key link in 3D point cloud data processing, can realize power transmission and distribution positioning, object identification, classification, and feature extraction, which helps to refine power grid management. In this paper, firstly, dense point cloud transmission and distribution 3D digital corridor modeling is carried out. Alignment splicing and noise reduction are carried out after obtaining the original dense point cloud. Contour line extraction, geometric modeling, and texture mapping are realized after processing the data to ultimately realize the transmission and distribution of 3D digitization. Then, the conversion formula for the pixel coordinate system and world coordinate system is derived to extract features from point clouds. Finally, a distance-based feature fusion method is designed to extract spatial features from point clouds and use the joint attention layer to segment them by fusing RGB pixel information. The original dense point cloud of a transmission and distribution digital corridor is segmented using the model presented in this paper for application after testing the dataset. It is found that the under-segmentation ratio of this paper’s algorithm is 0.96%, 3.44%, and 2.87% for the three scenarios of regular, irregular, and multi-targets, respectively, which is much lower than that of RANSAC+ECS with FCM + ECS. The intersection and concatenation ratios of this paper’s algorithm for the scenarios of irregular geometry as well as multi-target objects are 91.49% and 89.56%. It is much higher than 64.31% and 72.17% for RANSAC + ECS and 76.85% and 60.91% for FCM + ECS, which illustrates that this paper’s algorithm has a significant advantage in performance. In this study, the target point cloud can be segmented with high accuracy from the dense point cloud of a 3D model of power transmission and distribution with a large amount of data, effectively avoiding the phenomenon of under-segmentation and over-segmentation and contributing to the accurate control of power grid data.
Time domain analysis of catenary response characteristics caused by ambient wind
Authors: Gu Xuli , Liu Ting , He Yifan
Published: July 2024

The catenary system, as a framework within railway electrification projects, constitutes an exposed suspension structure deployed along railway lines. It serves the purpose of providing electrical power to electric locomotives through pantographs but lacks backup facilities and falls into the category of a specialized form of high-voltage transmission line. To ensure the safety and reliability of the catenary system and the stable current collection of the pantograph, thereby safeguarding railway operational safety, it is imperative to research the aerodynamic response of the catenary system induced by environmental winds. For this study, the catenary system in the 4m windbreak wall section of the Lanzhou-Xinjiang high-speed railway bridge has been selected as the research subject. To determine wind speed correction coefficients at the supporting cable and contact wire locations, a finite element model was created using wind tunnel experiments and numerical simulations. Samples of wind speed fluctuation have been obtained using the harmonic synthesis method. Based on quasi-steady aerodynamic theory, a temporal analysis has been conducted on the aerodynamic response of supporting cables and contact wires under the influence of both average and fluctuating winds. Temporal results, such as lift at positive and negative positioning locations and mid-span displacement, have been extracted to assess whether the existing structure complies with regulatory requirements. This study offers valuable insights for engineering applications that are similar.
Construction of Enterprise Green Accounting Information Disclosure System under the “Double Carbon” Goal
Authors: Xu Qian
Published: July 2024

Enterprises are the key participants in realizing the development of a green and low-carbon economy and are the main promoters of the environmental transformation and healthy development of the industry, and the green accounting information disclosure truly reflects the important indexes of green development of enterprises. In this paper, the relevant data of 15 listed companies in the paper industry from 2013 to 2023 are selected as samples to carry out empirical analysis, and their green accounting disclosure reports are used as the basis for calculating the GAID scores of the companies. A multiple linear regression model is created to test the disclosure-related research hypotheses, with the goal of discovering the factors that influence the current quality of enterprises’ green accounting disclosure. The fluctuation range of GAID scores of most of the fifteen listed enterprises in the paper industry is between 40 and 70, and there are also 20% of enterprises with GAID scores lower than 40. Enterprise size, proportion of outstanding shares, enterprise value, and enterprise development ability are significantly positively correlated with the quality of corporate green accounting disclosure at the 1% or 5% level, and the quality of disclosure increases by 0.151% for every 1% increase in enterprise size. In the enterprise green accounting information disclosure, enterprises need to be, based on their situation, reasonable and comprehensive information released in order to effectively enhance their corporate image and promote the green and sustainable development of enterprises.
Analysis of Strategies and Effectiveness of Big Data Technology for Business Decision Optimization
Authors: Wang Zhe , Xue Hongsong , Hu Junhua
Published: July 2024

Business decision-making is a decision-making process that relies heavily on business data, and with the continuous improvement of information technology, the level of intelligence of business decision-making has been increasing. The paper suggests relevant optimization strategies for business decision-making and creates an intelligent business decision-making process that utilizes big data. This paper mainly applies the association rule mining algorithm based on big data to business decision-making, extracting valuable information for business decision-makers from a large database of business information systems. In order to verify the operational efficiency of the improved algorithm, the traditional Apriori algorithm, FP-Growth algorithm, HBE-Apriori algorithm, and the improved algorithm are compared at the same time, and the results of the experiments show that the improved algorithm’s operational efficiency in the process of finding the maximal frequent itemset is significantly improved compared with the other three algorithms, which provides a basis for the analysis of the effectiveness of the optimization of business decision-making. The example of optimization of business decisions through big data technology found that after the optimization of business decision optimization, the asset quality and solvency of the enterprise are improved, and the operating capacity is unchanged due to the low operating capacity of the total assets of the enterprise. This paper’s method for optimizing business decisions based on association rules is shown to be feasible.
Future-oriented trends in intelligent building materials and applications
Authors: Xu Shifu
Published: July 2024

Nowadays, smart materials appear more and more frequently in people’s daily lives, and this paper investigates the development and current status of the application of smart materials in the construction industry in view of the high energy consumption status quo of the construction industry. The goal of the energy conversion mode of piezoelectric material is to be based on the basic principle of piezoelectric sensors. Study the monitoring function of buried piezoelectric sensors on the damage to the concrete main frame. The passive energy storage method of phase change material and its integration with the building are being investigated at the same time. The performance of these two materials is then tested by applying different forces to the piezoelectric sensors with the help of linear motors, and the output voltage of the piezoelectric materials is tested, which proves its good cyclic stability. The phase change material is split into multiple layers based on heat flow direction, and each layer’s temperature is calculated separately to analyze the thermal behavior inside the material in depth. Through experimental analysis, it has been found that the output voltage of the triangular piezoelectric transducer can reach 550 V, which can be applied to optimize pavement structure and pavement energy harvesting. The phase change material has excellent energy saving and thermal insulation effect in the summer, and the average heat flux decrease rate of the wall can reach 45.0%, which greatly reduces the energy consumption of air conditioners and other temperature-controlled appliances. The application of intelligent building materials is in line with the requirements of sustainable development planning, and there is ample room for growth.
Optimization study of anomaly detection algorithm in machine vision inspection technology
Authors: Zhou Guanghong , Wang Hairong , Zhuang Er-xing
Published: July 2024

In recent years, target detection algorithms based on machine vision have been a hotspot in computer vision research. The You Only Look Once (YOLO) algorithm, as an excellent target detection algorithm, has played an important role in improving detection speed and accuracy with the improvement of the network architecture in its development process. This paper introduces the concept of integrated learning to the YOLOv5 network architecture, incorporating deformable convolution and attention mechanisms. It also chooses the focal EIOU loss function to replace the GIOU loss function, thereby addressing the issue of localization loss, prioritizing abnormally detected targets, and enhancing the detection efficiency of these abnormal targets. Finally, we examine the practical value of the improved YOLOv5 algorithm by testing its performance and applying it to real-world anomaly detection. The results show that the improved YOLOv5 model outperforms the original YOLOv5 model in terms of performance and practical application advantages. In terms of performance, the classification accuracy of sea_person and earth_person in the improved YOLOv5 model is 37% and 26%, respectively, which is a significant performance gain overall. In actual application tests, the proposed method is more accurate than the traditional method. The accuracy is significantly higher.
Appreciation and Dissemination of Chinese Paintings from a Cross-cultural Perspective Based on Information Diffusion Modeling
Authors: Liu Ying , Liu Lin , Liu Zheqing
Published: July 2024

With a long history, profound cultural deposits, and diversified art types, Chinese painting is both an important part of traditional Chinese culture and a typical representative of traditional oriental art and culture. This article starts with the spirit of Chinese painting and aesthetic appreciation and then explores the significance of Chinese painting’s foreign dissemination and dissemination path. For the appreciation of Chinese paintings, the article designs an index system for assessing the appreciation ability of Chinese paintings, solves the weights of the indexes by using the optimal assignment method of distance estimation, and constructs a model for assessing the appreciation ability of Chinese paintings by combining with the cloud model. The Hidden Markov Model is used to establish an information diffusion model for Chinese painting dissemination, and the parameters of the model are estimated using the Great Likelihood Method. The quantitative analyses of Chinese painting appreciation ability, information diffusion effect, and satisfaction with communication effect were carried out with students from University S as the research subjects. The main factor of Chinese painting appreciation ability is emotional ability, which has a weight share of 26.74%. The comprehensive assessment cloud eigenvalue is (3.4714, 0.1462, 0.0348), which shows that the appreciation ability is good. When the state transfer probability is raised from 0.3 to 0.9, the increase in the number of Chinese painting communication nodes in 25s is 93.59%, and the satisfaction index of the audience for the communication effect of Chinese painting is 3.899. Combining with the information diffusion model, we can understand the change of communication nodes in Chinese paintings, which can provide a guide to enhance the communication effect of Chinese paintings.
Human Resource Management Informatization in Colleges and Universities in the Era of Artificial Intelligence
Authors: Luo Jing , Wang You
Published: July 2024

In the era of big data, informationization has been integrated into all walks of life, and all kinds of intelligent systems are constantly updated and iterated. Along with this, there is a constant change in people’s way of thinking, state of life, and working methods. This phenomenon is more obvious inside the general colleges and universities which are densely populated by teachers and students, which also brings new difficulties and challenges to the HR of colleges and universities to carry out the daily work of management services for teachers and students. The article analyzes the current situation of information construction and the problems faced, analyzes the necessity of information construction of HR work in colleges and universities around the HR business, and, on this basis, puts forward a network information system model adapted to HR management work in colleges and universities in the current era, and at the same time combines the hierarchical analysis method with the fuzzy comprehensive evaluation method, in order to think about optimizing the management of human resources data and analysis of colleges and universities and the implementation of HR After the informatization management, the system management approval links are shortened from 6 to 3, while the number of operators is reduced by half, and the time consumed is reduced to 5 hours. The proposed path to optimize the program to improve the quality of service is intended to explore innovative educational service forms. It is, at this moment, submitted to the industry for reference and exchange.
Analysis and Optimization of Learning Behavior of Music Students in Colleges and Universities Based on Big Data
Authors: Pan Xia
Published: July 2024

As digital education continues to progress, more and more scholars are focusing on the analysis and optimization of big data in the field of education. However, the analysis and optimization of students’ learning behaviors using big data has received less attention. Therefore, this paper uses the improved K-means algorithm to cluster the four aspects of learning, diet, exercise, and consumption behaviors of music majors in College Z. We use the Apriori algorithm to conduct a correlation analysis between the clustered students’ consumption, life, learning, and grades. This analysis summarizes the characteristics of the students’ various behaviors and habits, enabling school administrators to provide effective and reasonable advice to the students. We used the improved K-means algorithm to identify five clustering results related to students’ behaviors. The correlation analysis revealed that 10.98% of the students were regular and hardworking, and there was a 97.78% probability that these students would get “excellent” grades. The majority of students who live a more regular life, spend more time on the Internet and have a low to medium level of consumption have a probability of getting “good” and “medium” grades, which indicates that the results of the big data survey are basically consistent with their actual situation. Obviously, the use of big data can improve the analysis of the correlation between students’ behaviors and grades.
Behavioral Analysis and Educational Management of College Students in Universities by Integrating Multi-source Data
Authors: Xu Xiangpu
Published: July 2024

Big data technology has brought new opportunities for the development of the education industry and can play a positive role in the management of student campus education. In this paper, the behavioral features in the extracted multi-source behavioral data of college students are dimensionality reduced using principal component analysis, and the behavioral features are clustered using density peak clustering and undersampling methods. The Adaboost algorithm is used to identify and classify each behavioral feature to obtain behavioral analysis data for students. Finally, the university’s education management system is constructed based on this behavioral analysis model. The behavioral analysis of students in a university shows that both consumption behavior and book borrowing behavior cluster into three categories. Among them, the type of students who clocked into the library with a medium frequency and borrowed the most number of books had the highest percentage (39.25%) among the students in this university. And there is about a 79.3% probability that students of the university with a high number of absences seldom visit the library. The study also showed that there was a significant difference (p<0.05) in the study behavior of students in both experimental and control classes after the application of the educational management system. The student behavior analysis and management platform proposed in this paper effectively promotes the development and progress of education management in colleges and universities and improves the efficiency of student management work and the scientificity and reliability of the results.
Strategies for the Application of Emerging Information Technology in the Digital Recording of Cultural Heritage at Mingxi Nanshan Site
Authors: Yang Lin
Published: July 2024

Digging deep into the value of the cultural heritage of Mingxi Nanshan Ruins and continuing the historical lineage is a mission given by history to contemporary people. This paper chooses Mingxi Nanshan Ruins as the research object, combs through the specific framework of emerging information technology, and analyzes the application strategy for digitizing cultural heritage. The digital experience system of Nanshan Ruins in Mingxi is designed by combining emerging information technology with the guidance of immersive psychological experiences for users. The drone close photogrammetry technique is selected to acquire images of Mingxi Nanshan Ruins, and the measurement routes of the drone are carefully planned. Based on the imaging model of a pinhole camera, the reconstruction process of the three-dimensional model of Mingxi Nanshan Ruins is designed by combining the position optimization of the drone image with the geometric constraints of the pole. For the effectiveness of the UAV proximity photogrammetry technique, its positional measurement accuracy, model quantifiability, and positional accuracy were verified, and feasibility assessment and user digital interactive experience were designed to obtain a subjective evaluation of the digital experience system of the Nanshan Ruins in Mingxi. The RMSE-H obtained from the refined route planning is 0.3294cm, the mean value of the error in the plane of the 3D model of Mingxi Nanshan Ruins is 0.022m, and the mean value of the user’s subjective evaluation of the digital experience system is 4.39 points. Using emerging information technology as a guide, we can realize the digital reconstruction of the cultural heritage of Mingxi Nanshan Ruins and provide a new path for its digital protection.
Spatio-temporal correlation analysis of tourism urbanization patterns and high quality ecological services
Authors: Cui Yongqian
Published: July 2024

Exploring the development of tourism-based urbanization and improving the overall competitiveness of regional tourism is a major initiative to promote the development of tourism in countries in China. In this paper, we take the urbanization pattern of tourism as the background, water yield, soil retention, and habitat quality as the factors, and use a bivariate spatial correlation model to explore the spatiotemporal association between the urbanization pattern of tourism and ecosystem services, so as to provide a reasonable reference for the development of the urbanization pattern of tourism from the perspective of ecosystem services. It was found that the construction of tourism urbanization pattern increased water production and soil retention by 17.07% and 23.08%, respectively, compared with 2000. In addition, habitat quality contained the highest ecological service value of woodland, which provided 81% of water production and 470.79 g·m−2 of carbon storage. Throughout the period, the spatial distribution pattern of soil conservation and habitat quality remained largely unchanged, and the synergistic trade-off relationship between ecosystem services demonstrated spatial heterogeneity. The interaction relationship was dominated by synergistic relationships, with a small number of districts and counties existing as a trade-off. The study measures how ecosystem services change over time and space in Province A. It also explains how trade-offs and synergistic relationships between ecosystem services work. Finally, it gives a good scientific basis for the growth of high-quality ecological services and tourism in a region that is rapidly urbanizing.
Demand Forecasting and Project Development of Sports Tourism Based on User Behavior under the Perspective of Harmonious Coexistence of Human and Nature
Authors: Hu Yuhan
Published: July 2024

Man and nature are interconnected and interdependent. The naturalization of man reflects the scientific nature of the landscape, the development of ecotourism is to establish the development of man and nature in harmony and unity of the development of ideas. This paper proposes measures to enhance the tourism experience based on the above concept. After a series of operations, such as similarity calculation and data cleaning, the user category, consumption level, and geographic location preference are calculated to establish a user model and portrait based on behavioral analysis. Based on LASSO penalty regression, the link between covariates is incorporated into the penalty term to complete the optimization and improvement of the LASSO regression model. Associate the user preference degree model with the tourism demand prediction model based on user preference. The model is applied in practice, and the average error rate for the number of tourists predicted by the LASSO regression coefficient is about 9.9%, which is smaller than the average error rate of the comparison model. Based on the results of the demand prediction, strategies related to the development of sports tourism projects are proposed, and the impact of sports tourism projects on the environment is evaluated. Based on the IPA analysis method, the user’s tourism experience of the subject area is assessed, and the user is more concerned about the internal transportation of the tourist place, with I and P values of 12.455 and 1.457, respectively, and the performance effect of the subject area in this point is poor, which needs to be solved in time.
Unpacking Education as Migration Driver among Young Jordanian Women: A Study on Gender, Agency, and Sociocultural Transformations in Jordan
Authors: Cosmano Ivana
Published: July 2024

This paper explores young Jordanian women’s desire to migrate, uncovering often-unacknowledged factors influencing their decision to leave their home country. By delving into their dreams, aspirations, and expectations, this research uncovers why they firmly aspire and creatively plan to migrate, shedding light on the intricate interplay of agency and gender in shaping their migration choices. It theorizes that these women employ a co-optation strategy, whereby they reinterpret and leverage the inner meaning(s) of gendered expectations regarding education, to facilitate their journey abroad and enact more desired life trajectories. This paper argues that young Jordanian women’s desire to migrate stems from shifting sociocultural values and norms, mirroring evolving understandings of femininity, gender roles, and social hierarchies. Within this framework, migration emerges as a consequence of the country’s inability to address its young population’s aspirations for change. By addressing these dynamics, this research contributes to a deeper understanding of the underlying drivers behind the migration aspirations of a significant segment of Jordan’s youth—a pressing issue the country is facing. Ultimately, the insights offer a valuable perspective on migration as a lens through which ongoing sociocultural transformations can be comprehended.
DESIGNING 3D HORROR SURVIVAL GAME “SURVIVING THE NIGHT INVASION” IS AVAILABLE ON THE WINDOWS PLATFORM
Authors: Valerian Aldo , Pragantha Jeanny , Haris Darius Ardana
Published: July 2024

The game "Surviving the Night Invasion" is a 3D game with the Horror Survival genre developed on the Windows platform. This is a single player game that use keyboard and mouse controller. This game presents a dark environment and night scenery. The player will have the perspective of main character (first person). In the design process, this game was created using the C programming language and Unity Engine version 2022.1.15f1 (64-Bit). In this game the player is a person who stranded in an island full of zombies. The aim of this game is that the player has to find a vaccine before the infection rate reaches 100%. Beside that, the player have to turn on the generator so call for help and get out of the island. During the gameplay, the player must be aware of zombie’s attack and to find shelter and resources to survive
ENHANCING INTRUSION DETECTION SYSTEM PERFORMANCE WITH 1D-CNN AND BI -LSTM COMBINATION
Authors: Nurain Amalia , Satria M Vian , Navalino
Published: July 2024

Due to the ever-increasing network traffic, the demand for a system that contain Network Intrusion Detection systems have increased as cloud technology usage has become widespread. Recent research has shown that deep learning models are effective for a variety of applications involving natural language processing on a critical part of Network Intrusion Detection such as anomaly detection. The architecture of a deep learning model has two layers: a pattern-matching layer and a fully linked layer for training the label of attack. In this study, we use a deep learning model with a modified architecture that integrates pattern matching with convolutional neural networks (CNN) and bidirectional long short-term memories (Bi-LSTM). The results show that CNN and Bi-LSTM can classify attack categories in the UNSW-NB15 dataset with an accuracy of 82%.
Perlindungan Hukum Pekerja Harian Lepas di PT. Madina Agro Lestari Perspektif Undang-Undang dan Fiqih Siyasah
Authors: Hutabarat Yurliani , Hsb Putra Halomoan
Published: July 2024

The problem in this research is the legal protection for casual daily workers at PT. Madina Agro Lestari in Attitude Village, Muara Batang Gadis District, Mandailing Natal Regency. Because there are still many casual daily workers who do not get some rights.  Legal protection for casual daily workers is a work contract, work safety and welfare. The purpose of this study is to describe and analyze the legal protection for casual daily workers at PT. Madina Agro Lestari. The formulation of the research problem is how the legal protection for casual daily workers at PT. Madina Agro Lestari, what is the review of Fiqh siyasah regarding legal protection for casual daily workers at PT. Madina Agro Lestari, and what are the inhibiting and supporting factors for legal protection against casual daily workers at PT. Madina Agro Lestari. The method in this research is empirical normative with a sociological juridical approach, namely describing the conditions in the field as they are and the labor law which is the benchmark in this research. The data collection instrument used consisted of observation , interview , and documentation. The result of this research is legal protection for casual daily workers at PT. Madina Agro Lestari work agreements, worker wages, occupational safety and health, fiqh siyasa, view that humans are all the same and Islam is hostile to people who do not give the rights of others.  The obstacles faced are that there are still many casual daily workers who have not received perfect legal protection due to the low education of casual daily workers, and from companies.
Sociological Analysis of Restorative Justice in Rehabilitative Law Enforcement for Drug Abuse Cases
Authors: Hermawan Malsal Jajuli Haerudin , Wulansari Catharina Dewi
Published: July 2024

The escalating trend in drug abuse, particularly among the youth, necessitates a unified approach from all law enforcement entities to address this shift in paradigm. It is essential to view drug addicts and victims of drug abuse not only as perpetrators but also as victims, warranting the incorporation of rehabilitation as an alternative form of punishment. The severity of narcotics crime in Indonesia poses a profound threat not only to individual health both physical and mental but also to societal well-being and national development, potentially compromising state security and sovereignty. This paper explores the enforcement of narcotics law in Indonesia as dictated by Law Number 35 of 2009 and examines the application of restorative justice, a concept often referred to in criminal law enforcement, which emphasizes recovery and atonement for the perpetrator or their family towards the victim, facilitating out-of-court reconciliatory efforts. By examining the legal sociological perspective, this research advocates for resolving narcotics-related criminal cases through means that prioritize restoration over retribution. It argues for a restorative justice approach, where the focus shifts from imprisonment to alternatives like medical and social rehabilitation, aiming for a resolution that restores harmony and agreement between involved parties, thereby aligning legal outcomes with societal values and needs.
STRATEGI KOMUNIKASI MELALUI METODE NLP (NEURO LINGUSTIC PROGRAMMING) DALAM PENYULUHAN PENYALAHGUNAAN NARKOBA KEPADA REMAJA DI DENPASAR SELATAN
Authors: Putu Soni Kurniawan  , I Dewa Ayu Hendrawathi Putri  , I Nyoman Alit Putrawan
Published: July 2024

Permasalahan narkoba semakin memprihatinkan, angka prevalensi menunjukan dari tahun ke tahun angka penyalahguna narkoba cenderung mengalami peningkatan. Data BNN RI menyebutkan, pada tahun 2022 pengguna narkoba di Indonesia sebanyak kurang lebih 5 juta orang. Upaya pencegahan dengan penyuluhan telah dilaksanakan secara masiv, tapi masih dirasa kurang maksimal karena metode yang digunakan penyuluh kurang menarik sering membuat audience bosan. NLP merupakan sebuah teknik untuk mengkodekan bagaimana manusia mengorganisasikan pikiran, perasaan, bahasa dan prilaku mereka agar memberikan hasil sesuai keinginannya. Penelitian ini bertujuan untuk mengetahui penerapan strategi komunikasi melalu metode NLP (neuro linguistic programing), hambatan dalam penerapan strategi komunikasi melalu metode nlp, dan dampak implementasi strategi komunikasi melalu metode NLP dalam penyuluhan penyalahgunaan narkoba kepada remaja di Denpasar Selatan. Teori yang digunakan dalam penelitian ini adalah, teori komunikasi persuasif, teori interaksionisme simbiolik dan teori persepsi. Penelitian ini menggunakan pendekatan kualitatif. Sumber data didapatkan melalui observasi, wawancara dan dokumentasi. Hasil penelitian menemukan 1) Penerapan strategi komunikasi melalui metode NLP dalam penyuluhan penyalahgunaan narkoba kepada remaja di Denpasar Selatan, dapat diketahui bahwa strategi yang diterapkan menggunakan teknik anchoring, analogue marking, dan building rapport dapat dijalankan dengan baik 2) Hambatan yang ditemukan adalah, volume peserta penyuluhan yang banyak sehingga cenderung menghasilkan kegaduhan yang menyulitkan terciptanya suasana penyuluhan yang kondusif dan kurangnya keinginan masyarakat secara umum untuk membantu dalam penyuluhan penyalahgunaan narkoba karena dirasa tidak memberikan feedback kepada masyarakat 3) Strategi komunikasi yang diterapkan melalui metode NLP dapat terlaksana dengan baik. Oleh karena itu, strategi yang telah diterapkan dapat lebih dikembangkan dan melakukan percepatan pada perkembangan strategi komunikasi yang diciptakan dengan memanfaatkan strategi analisis SWOT sehingga tercipta strategi komunikasi yang semakin baik dalam penyuluhan penyalahgunaan narkoba.