A dynamic mutation probability formula is utilized to optimize the model. In order to solve the logistics warehouse path problem, the ant colony optimization algorithm, optimized by a genetic... Show More

A dynamic mutation probability formula is utilized to optimize the model. In order to solve the logistics warehouse path problem, the ant colony optimization algorithm, optimized by a genetic algorithm, is employed to construct a logistics warehouse path optimization model. This model effectively optimizes the logistics warehouse paths. Test results comparing the convergence and distribution of non-inferior solutions demonstrated that the proposed model outperforms others in terms of convergence and non-inferior solution distribution. In practical logistics warehouse optimization, applying the proposed model to optimize cargo locations can significantly enhance the effectiveness of the objective function. The optimization resulted in improvements for all four objective functions related to cargo location, with reduction rates of 10.38%, 30.88%, 51.78%, and 88.49%, respectively. For the optimization of logistics warehouse paths, the original distance was 47.6m, which was reduced to 27.8m after optimization. Consequently, the picking distance decreased by 41.60%.

With the advent of the information age, the traditional pavement management technology of operating expressways can no longer meet the higher requirements for the improvement of engineering quality... Show More

With the advent of the information age, the traditional pavement management technology of operating expressways can no longer meet the higher requirements for the improvement of engineering quality in the information age. This paper proposes a method of integrated analysis based on BIM (building information modeling) and GIS (geographic information system), builds an intelligent platform for highway operation and maintenance, and solves the problem of data islands in highway maintenance and management.

ICAO has emphasized that aeronautical information agencies should provide digitized aeronautical data and information, and realize that aeronautical data exchanging internationally in AIM. The AIXM... Show More

ICAO has emphasized that aeronautical information agencies should provide digitized aeronautical data and information, and realize that aeronautical data exchanging internationally in AIM. The AIXM structured aeronautical information dataset will be the main source of aeronautical basic data in the aeronautical information exchange network. In this article, the authors first analyze the spatio-temporal attributes of AIXM dataset and design the query method of AIXM structured obstacle data based on the research of AIXM coding specification. Secondly, the helicopter path planning is taken as the research scenario. Using the AIXM obstacle dataset and route dataset, combining the helicopter performance constraints to construct the envelope frame for collision judgment, and a new path planning method with improving the classical A* algorithm based on the AIXM dataset is proposed. The proposed method is validated and visualized. The validation results show that the proposed method reduces the frequency of helicopter turning, and ensures the safe distance between the flight path and the obstacles.

The green credit policy has significantly influenced the growth of green industries in China. This study evaluates its impact on reducing bank credit risk using data from 26 Chinese banks from 2015... Show More

The green credit policy has significantly influenced the growth of green industries in China. This study evaluates its impact on reducing bank credit risk using data from 26 Chinese banks from 2015 to 2021. The authors discovered that the policy's primary effect is linked to banks' financial leverage. Notably, green credit's influence on insolvency risk is most evident in leverage risk. However, despite governmental support for green credit collaboration, prevalent information gaps between banks and green enterprises lead to misjudgments and subsequent credit losses. To address the balance between credit risk mitigation and privacy, the authors investigated vertical joint learning for a precise risk control model grounded in commercial banks' practices. Experiments revealed that this joint model outperforms the sole “bank internal model” in presenting green credit data, underscoring the potential of machine learning to refine green credit systems and bolster banks' credit risk management.

The Internet's rapid growth has led to information overload, necessitating recommender systems for personalized suggestions. While content-based and collaborative filtering have been successful... Show More

The Internet's rapid growth has led to information overload, necessitating recommender systems for personalized suggestions. While content-based and collaborative filtering have been successful, data sparsity remains a challenge. To address this, this article presents a novel social recommender system based on convolutional neural networks (SRSCNN). This approach integrates deep learning and contextual information to overcome data sparsity. The SRSCNN model incorporates user and item factors obtained from a neural network architecture, utilizing features from item titles and tags through a CNN. The authors conducted extensive experiments with the MovieLens 10M dataset, demonstrating that the SRSCNN approach outperforms state-of-the-art baselines. This improvement is evident in both rating prediction and ranking accuracy across recommendation lists of varying lengths.

Support vector data description (SVDD) inspires us in data analysis, adversarial training, and machine unlearning. However, collecting support vectors requires pricey computation, while the... Show More

Support vector data description (SVDD) inspires us in data analysis, adversarial training, and machine unlearning. However, collecting support vectors requires pricey computation, while the alternative boundary selection with O(N2) is still a challenge. The authors propose an indispensable edge pattern selection method (IEPS) for data description with direct SVDD model building. IEPS suggests a double local analysis to select the global edge patterns. Edge patterns belong to a subset of the target problem of SVDD and its variants, and neighbor analysis becomes pivotal. While an excessive number of participating data result in redundant computations, an insufficient number may impede data separability or compromise the model's quality. Consequently, a data-adaptive sampling strategy has been devised to ascertain an optimal ratio of retained data for edge pattern selection. Extensive experiments indicate that IEPS keeps indispensable edge patterns for data description while reducing the interference in the norm vector generation to guarantee the effectiveness for clustering analysis.

This paper aims to explore Kuwaiti users' perspectives and experiences with Shlonik, the mandatory contact tracing application that was used during the COVID-19 pandemic. A sample of 2,450 tweets... Show More

This paper aims to explore Kuwaiti users' perspectives and experiences with Shlonik, the mandatory contact tracing application that was used during the COVID-19 pandemic. A sample of 2,450 tweets about users' experiences was collected and thematically analyzed. The analysis used DeLone and McLean's information system success model to explore aspects of the degree to which this app can be judged a “success,” using parameters of system quality and service quality. A novel finding identified by this qualitative study was the significance of themes identified in the analysis such as social privacy (timing, privacy, and female privacy, which are related to the cultural and religious norms of Kuwait) and technical privacy (related to data protection). The research identified significant conflict with cultural and social norms in users' experience of the Shlonik app – factors not normally identified or discussed in existing literature. This research supports a need for improved strategies and designs in future m-government applications in developing countries.

In this article, we discuss the stagnation problem related to circulating digital course resources (DCRs) in China. Using information ecology theory, questionnaires and practical tests, we learn... Show More

In this article, we discuss the stagnation problem related to circulating digital course resources (DCRs) in China. Using information ecology theory, questionnaires and practical tests, we learn that universities in China are embodied with information isolation, and hence circulating the associated DCRs is inhibited. Our results show that the original simple mechanical construction no longer meets the current needs of teaching and learning. Consequently, coordination is essential among relevant subjects and circulating DCRs. In doing so, we further reoptimise the current circulating system of DCRs in Chinese universities through the use of information ecology theory and in turn provide a new solution for the sustainable construction and application of DCRs.

Traditional customer segmentation methods cannot obtain more effective information from massive customer data, which affects the formulation of marketing strategies. Based on this, this study... Show More

Traditional customer segmentation methods cannot obtain more effective information from massive customer data, which affects the formulation of marketing strategies. Based on this, this study constructs a customer segmentation marketing strategy model that integrates support vector machines and clustering algorithms. This model first utilizes support vector machines to segment existing customer data, and then integrates support vector machines and clustering algorithms to construct a customer segmentation model. Finally, simulation experiments are conducted using the dataset. The results show that the model algorithm obtains the optimal solution when the quantity of iterations is 50. Meanwhile, the average error rate of the model algorithm in the customer segmentation process is 6.82%, the average recall rate is 91.28%, and the average profit predicted by the impact strategy developed by the segmentation model is 29.88%, which is 2.53% different from the true value.

In the geographical field, the studies have been on service areas using the Voronoi diagram and its derived models is extensive, but there is a lack of effective methods to achieve a good... Show More

In the geographical field, the studies have been on service areas using the Voronoi diagram and its derived models is extensive, but there is a lack of effective methods to achieve a good area-weight proportionality between generators and their exclusive regions. As a famous visualizing method, adaptive multiplicatively weighted Voronoi diagrams are able to achieve it, but are limited to displaying non-spatial data. The approach of the area-weight proportional multiplicatively weighted Voronoi diagram is proposed to solve these problems by allowing for spatial division with a point-fixed iteration approach and a vector-based multiplicatively weighted Voronoi diagram construction method from point features with spatial coordinates and references in GIS environments. It enables one to create a set of regions that is proportional to the weights of the generators. The method is successfully tested on a series of cases. The approach aims to establish a kind of spatial data model to represent demand and supply situations in real life.

Enterprise resource planning (ERP) implementations often encounter multifaceted challenges, leading to failures. Success relies on technical competence, management support, and user engagement.... Show More

Enterprise resource planning (ERP) implementations often encounter multifaceted challenges, leading to failures. Success relies on technical competence, management support, and user engagement. Unique organizational processes significantly influence outcomes. Failures can disrupt operations, highlighting the need to identify critical success factors (CSFs) for effective ERP implementation. This study employed analytic hierarchy process (AHP) methodology to analyze CSFs. Data collection involved surveys administered to a social insurance company's ERP project team in Indonesia. This study revealed 15 success factors, categorized into organization, process, and technology dimensions. Organization emerged as the most crucial, followed by technology and process. Among these, five CSFs stood out: project team competence, vendor and consultant quality, ERP fit, top management support, and hardware and software selection.

When a cyber incident occurs, organizations need to identify the attack's impacts. They have to investigate potentially infected devices as well as certainly infected devices. However, as an... Show More

When a cyber incident occurs, organizations need to identify the attack's impacts. They have to investigate potentially infected devices as well as certainly infected devices. However, as an organization's network expands, it is difficult to investigate all devices. In addition, the cybersecurity workforce shortage has risen, so organizations need to respond to incidents efficiently with limited human resources. To solve this problem, this paper proposes a tool to assist an incident response team. It can visualize ATT&CK techniques attacker used and, furthermore, detect lateral movements efficiently. The tool consists of two parts: a web application that extracts ATT&CK techniques from logs and a lateral movement detection system. The web application was implemented and could map the collected logs obtained from an actual Windows device to the ATT&CK matrix. Furthermore, actual lateral movements were performed in an experimental environment that imitated an organizational network, and the proposed detection system could detect them.

In the realm of physical education in college, the traditional classroom teaching approach primarily relies on paper textbooks and demonstrations by the teacher. However, in today's physical... Show More

In the realm of physical education in college, the traditional classroom teaching approach primarily relies on paper textbooks and demonstrations by the teacher. However, in today's physical education classrooms, there is a need to change these traditional teaching methods. Utilizing multimedia technology and interactive interfaces, teachers can demonstrate the essential actions and intricate details through multimedia videos and other formats such as push-pull and shaking. This chapter introduces a multi-segment human body tracking algorithm that focuses on real-time tracking. The human body target is divided into multiple segments, and an online learning method based on Hough Forests is used to learn the overall appearance of the human body and the appearance model of each segment. The research findings indicate that when the merged area exceeds 82.36% of the pre-segmentation area using watershed analysis, smaller areas lead to faster segmentation speed, while larger areas result in slower segmentation speed. Compared to other methods, this approach yields better recognition results.

Implementing mental health education (MHE) in schools is vital for students' psychological well-being. Subject infiltration integrates psychological factors into subject learning, promoting healthy... Show More

Implementing mental health education (MHE) in schools is vital for students' psychological well-being. Subject infiltration integrates psychological factors into subject learning, promoting healthy development. However, English learning can introduce issues like self-confidence and language anxiety. Early identification of mental health problems (MHP) is crucial. This study, rooted in humanistic psychology and constructivism, explores affective factors, strategies, teaching, and English listening. The algorithm, based on the DeepPsy model, shows promise, identifying 75% of students with MHP. This research aids universities in offering timely support to high-risk students, minimizing long-term harm. The algorithm contributes to a healthier learning environment by enhancing English teaching and addressing mental health issues early.

This article conducts a series of research on computer network courses based on “flipped classroom.” Teaching reform will be carried out for computer networks, but the results are mediocre. The... Show More

This article conducts a series of research on computer network courses based on “flipped classroom.” Teaching reform will be carried out for computer networks, but the results are mediocre. The author of this article has carefully considered and summarized computer network teaching based on his years of teaching experience and has put forward suggestions for widespread application. This article discusses the application of translation. The necessity and connotation of transitioning to classroom mode were emphasized, and the design of this teaching method was emphasized, adopting a three-step approach of “consolidating and improving knowledge after class.” Therefore, teachers should start from their own perspective, based on process preview, in class learning, and after class review, find the connection point between flipped classroom and computer network courses, reflect on the problems in teaching, and adopt targeted teaching methods to solve problems. This article provides guidance for improving teachers' teaching level.