Reviewerly/exHarmony huggingface dataset:
Role of Quantum Computing in Government and the Defence Sector

Quantum computing is a revolutionary technology that has the potential to transform various industries, including government operations, defence strategies, and national security. The chapter discusses its fundamental principles, advantages, limitations, and applications in cryptography, optimization, resource allocation, quantum sensing, and metrology. It highlights the need for quantum-resistant cryptography and post-quantum cryptographic algorithms to safeguard sensitive information. Quantum algorithms can improve decision-making processes, enhance efficiency, and address logistical challenges in defense strategy planning and disaster management. Quantum communication and secure networks are crucial for secure communication among government agencies, military units, and allied nations. Challenges include high costs, skilled personnel, and ethical and legal implications. The chapter concludes with a discussion on the future outlook of quantum computing in these sectors, emphasizing the need for continued research and investment.
A Blockchain-based Development Scheme of Digital Historical Material Databases

Digital Historical material databases are important for historical research. This article analyzes the current situation and problems of historical database construction and proposes a construction method based on blockchain technology to achieve secure storage and protection of digital historical data. The article also proposes a sharing and building mode of historical databases based on the blockchain architecture, which supports the co-building of historical material databases and encourages the exchange of digital historical materials.
A Secure Verifiable Computation Scheme for Matrix Determinants Based on Dual Perturbation Encryption and Multi-server Parallel Computation

With the development of cloud computing and IoT technologies, there is an increasing demand for timeliness in secure verifiable computing schemes. On one hand, the computation time can be reduced by improving the efficiency of client data encryption and decryption. On the other hand, the computation time of servers can be reduced by leveraging the advantages of multi-server parallel computing. The secure verifiable computing scheme for matrix determinant based on dual perturbation encryption and multi-server parallel computing achieves both reduced computation time for client matrix encryption and decryption, as well as decreased computation time for servers. In this scheme, a dual perturbation encryption algorithm is proposed based on specially constructed upper or lower triangular sparse matrices, which improves the efficiency of matrix encryption and decryption computation while meeting the same security goals. Additionally, a multi-server parallel computing algorithm is introduced based on matrix partitioning and matrix LU factorization techniques, which extends the available server quantity from two to multiple and enhances server parallel computing efficiency. Performance analysis indicates a 50% improvement in matrix encryption and decryption computation efficiency, and a 30% increase in parallel computing efficiency as the number of servers increases.
Research on Privacy Protection Technology for Data Mining

More and more sensitive data is being collected and processed by third parties for data mining and analysis, in order to solve the problem of how to achieve a certain balance between privacy protection and data analysis accuracy, in this thesis, a personalized local differential privacy protection method based on feature weights is proposed. The influence weight of feature attributes on data analysis is taken as the core basis of the whole perturbation method. The gradient response algorithm K-RR [1] is mainly used to realize random disturbance of data. However, in order to ensure the accuracy of subsequent data analysis as much as possible, the consideration of the influence of feature attributes on weight size, feature attribute dimension, and privacy budget allocation is introduced. In addition, the personalized privacy requirements of different data owners are fully considered. By setting the total privacy budget defined by data owners and constructing the sensitive attribute set defined by data owners, personalized local differential privacy protection is realized based on the influence weight of attributes. In addition, different privacy budget loss calculation methods are constructed for different attributes based on the influence weight of characteristic attributes to ensure data privacy.
Research on the Development of Dynamic E-book System for Physics Teaching

Under the background of education modernization, as an important teaching resources, books are gradually showing the characteristics of electronic. E-books have incomparable advantages in the convenience of dissemination and utilization compared to traditional paper-books. But these advantage come more from the digitization of the carrier than from the interactivity and dynamic simulation. In order to fully explore the application value of e-books, this paper takes physics teaching in lower grades as the application scenario, and studies an dynamic e-book system with simulation and interaction functions. This paper first introduces the characteristics of the system, then designs the logical architecture based on these characteristics, and finally analyzes the implementation method of each module. Due to the specific subject knowledge is embedded in the implementation, this kind of e-book system has great application value in the aspect of in-depth subject teaching.
Complexity-Adaptive Reversible Video Information Hiding Based on Motion Vectors

In order to address the issue of the existing motion vector-based video reversible information hiding algorithms, which are unable to adaptively adjust the embedding capacity based on the visual characteristics of video frames and have limited capacity, a multi-channel vector sorting reversible video information hiding algorithm is proposed. This algorithm achieves adaptive information embedding for subsequent frames based on the complexity of reference frame texture and motion. Simultaneously, an improvement is made to the multi-pass pixel value ordering (multi-pass PVO) technique and applied to video information embedding, effectively enhancing the embedding capacity of the reversible hiding algorithm. Experimental results demonstrate that compared to similar algorithms, the changes in PSNR and SSIM are reduced by 14.5% and 8.5% respectively, while the embedding capacity is increased by 7.4%. This algorithm exhibits significant improvements in terms of visual quality and embedding capacity.
Analysis and design of teaching document management platform

With the vigorous development of information technology, the document management platform of colleges and universities is facing unprecedented challenges and opportunities, and a new digital management system of teaching documents is urgently needed. This paper uses a new design method to reconstruct the university teaching document management platform, and on the basis of investigating the current situation of teaching document information management in Shanghai University of Applied Technology, carries out relevant data analysis, and divides the management platform into scientific modules. The database adopts the design method of combining three different levels of administrators to make them perform their respective duties and arrange their responsibilities to be independent and connected with each other through the authorization mechanism. Finally, SQL language is used to set constraints on the integrity of the database, and the information management of teaching files is finally realized.
Research and Progress on 3D Face Recognition

3D face recognition technology has become a popular research direction in academia and industry because of its unique advantages such as naturalness, convenience, and friendly user experience. In recent years, 3D face recognition research has made great progress. Compared to 2D face recognition, 3D face recognition is more advantageous and the main feature is that 3D shape data is utilized in the recognition. We firstly classify 3D face recognition into 3D face recognition based on colour images, 3D face recognition based on high-quality 3D scanning data, and 3D face recognition based on low-quality RGB-D images based on the source of 3D shape data, and elaborate their representative methods and their advantages and disadvantages respectively; secondly, we analyse the way of applying deep learning in 3D face recognition; and then analyse the advantages and disadvantages of 3D face data compared with 2D images. The fusion method of 3D face data and 2D images in bimodal face recognition is then analyzed, and the commonly used 3D face databases are introduced; finally, the main difficulties faced by 3D face recognition and the development trend are discussed.
Research on the Application of financial Robot Automation under HRC

The era of big data leads the development of robots, the application of artificial intelligence is more and more widespread, and the application of robots has become very normal. Based on the background of intelligent finance, this paper studies the application design and application strategy of automation technology in financial robots, in order to improve the efficiency and effect of enterprise data information processing and promote the construction of intelligent. This paper puts forward a design framework, which reflects the man-machine combination hypothesis under the intelligent mode, and promotes the development of financial informatization. In addition, this paper proposes a financial robot risk prediction model based on graph convolutional networks for diagnosing risk information (R-GCN) in financial lending. Finally, the effectiveness of our proposed model was verified through experimental results.
Research on Recommendation Algorithms Based on User Interest Models

With the advent of the big data era, users are facing severe information overload problems. Information recommendation technology can help users extract useful information from massive network information, which has received widespread attention from researchers. In order to solve the problem of information overload and personalized recommendation for users, this article proposes a recommendation algorithm based on user interest models. By utilizing explicit user features and using linear regression algorithm to fit user interest and rating data, the fitted weight parameters are used to predict the user's interest value in a certain thing or service. Finally, the user information recommendation is completed based on the predicted interest value. Experiments have shown that the recommendation method proposed in this article can effectively grasp the potential interests of users and meet their application needs.
Research on Personalized Early Childhood Education Recommendation Model Based on Improved DeepFM

This study aims to explore how to utilize deep learning and recommendation system techniques to construct a personalized early childhood education recommendation model for recommending personalized early childhood education resources. Handling sparse and high-dimensional features is a challenge in personalized early childhood education resource recommendation. To address this challenge, we adopt the DeepFM model as the basis of our research. The DeepFM model utilizes feature embedding techniques to map discrete features into a low-dimensional dense vector space, effectively solving the issue of high-dimensional features. Our research objective is to improve upon the DeepFM model by considering the impact of cross-features and incorporating sequential information of user behavior. This improvement aims to accurately capture the interests and preferences of young children and provide precise personalized recommendations by learning the interaction relationships between features and high-order feature combinations. Through this study, we will train a personalized education resource recommendation model for young children to provide high-quality early childhood education experiences. The results of this study will provide valuable references for research and practice in the field of personalized early childhood education recommendation.
Service Model of Knowledge Integration Base on Automatic Text Summarization

With the advent of the era of big data, the number of various knowledge resources has exploded. A series of problems, such as information redundancy and knowledge overload, bring trouble to users ' reading and use. The generation of text knowledge summary can improve the efficiency of user knowledge acquisition and knowledge reuse rate, and realize knowledge integration and orderly organization. This paper integrates automatic text summarization technology into knowledge service. Firstly, a knowledge summary generation method based on improved TextRank algorithm is proposed. Then, the knowledge integration service elements based on automatic text summarization are defined. Finally, a knowledge integration service model based on automatic text summarization is constructed. It provides new methods and new perspectives for the research of knowledge service model.
ACDO: An Ant Colony Dynamic Optimization Framework for Tourism Route Planning

Aiming at selecting the optimal tourism route planning, this problem is abstracted into a traveling salesman problem (TSP) for research, and an Ant Colony Dynamic Optimization (ACDO) is proposed. Firstly, ACDO improves the pheromone initialization method to ensure the diversity of the population, and improves the state transfer rule so that it can be dynamically adjusted with the evolution of the population to accelerate the convergence rate of the algorithm, and then the ACDO expands the searching space of the solution through the improvement of the local updating and global updating rules of the pheromone, and finally dynamically adjusts the volatility factor of the global pheromone through the setting of an iterative threshold, so as to avoid falling into local optimal solution or premature stagnation. Combined with the hand-drawn map of Jingdezhen culture and tourism, the simulation operation of different scale TSP problems shows that the ACDO is very effective for the optimal selection problem of tourism routes.
Research on Blockchain-Based Aviation Supply Chain Management

As businesses steadily advance in their digital transformation efforts, the integration between internet technology and traditional enterprises has become increasingly tight. One specific manifestation of this phenomenon is the widespread application of blockchain technology. Thanks to its broad adoption, the value and potential of blockchain technology in the field of collaborative manufacturing are gradually being unearthed. Blockchain's core technologies, including smart contracts, decentralization, and information sharing, play a unique role and offer advantages in collaborative manufacturing. Traditional supply chains often involve vertical and serial management structures, leading to information silos that make companies less responsive to supply chain issues, less efficient in tracing and tracking problems, and less capable of effectively guarding against malicious data tampering by suppliers. The application of blockchain technology in supply chains can enable multi-tiered and flattened management structures, helping aviation companies establish new collaborative manufacturing mechanisms and prevent the aforementioned issues. This article constructs a supply chain management model based on blockchain technology tailored to the specific circumstances of aviation companies. The aim is to achieve systematic, digitized, and information-driven supply chain management. It involves assessing and admitting suppliers based on management requirements, ultimately optimizing the overall supply chain. In the end, this leads to the establishment of an aviation supply chain management system based on blockchain.
Analisis Data Human Resources Untuk Pengambilan Keputusan: Penggunaan Analisis Data Dan Artificial Intelligence (AI) Dalam Meramalkan Tren Sumber Daya Manusia, Pengelolaan Talenta, Dan Rentensi Karyawan

Purpose-The main orientation of this article is to recognize the pattern of digitalization's impact on the current development of Artificial Intelligence (AI) and human resource management and how it affects the skills needed by HR professionals for decision-making through talent management and employee retention to ensure employee capabilities by aligning work at the right time based on the company's business priority goals. Methodology-This study uses a qualitative methodology that uses descriptive research. This research focuses on decisions made by leaders to improve the quality of human resources and seeks to identify areas of knowledge that have not been explored in research. Findings-Research results show that the company's strategy of using Artificial Intelligence (AI) provides many benefits, such as improving operational efficiency, developing innovative products or services, and making better business decisions based on better forecasting and analysis. Practical Implications-Through the implications of HR data analysis as decision-making in forecasting human resource trends using AI, talent management, and employee retention. This is applied to the recruitment and selection process that provides benefits such as rewards to employees who can achieve targets. Therefore, a supportive work culture by honing the talents and potential of employees to create maximum and efficient performance can have a good impact on the company.
PKM MEDIA PEMBELAJARAN BERBASIS ANIMASI (POWER POINT) PADA SMKN 1 JENEPONTO

This Community Service Research, which was funded by the Makassar Dipa University Foundation, is intended as a form of approach offered to overcome the problems that exist in the UMKM assisted group of Vena Energi. The problem that is often faced by MSMEs is in the process of introducing and marketing their products. MSME actors have taken several ways to introduce their products to the public, namely by posting their products to social media such as Facebook, Instagram or via WhatsApp status. However, this did not have an impact on increasing sales of their MSME products, this was because the posts of MSME actors on social media had not yet targeted social media user criteria such as age criteria, location, hobbies, and many other criteria. This can only be done when MSME actors post it in the form of advertisements known as Facebook ads and Instagram ads. For this reason, we, from the team implementing the community service program activities at Dipa Makassar University, have held community service in the form of training for MSME actors in the Vena Energi Jeneponto fostered group, so that they have the skills and ability to advertise and target potential buyers based on criteria that match their MSME products in facebook ads and also Instagram Ads.The result is the creation of MSME actors who are able to utilize Adsense social media to optimize MSME product advertisements so that they are more targeted and able to increase the number of MSME product sales for the Vena Energi Jeneponto fostered group
PELATIHAN PEMBUATAN MEDIA PEMBELAJARAN BERBASIS ANIMASI SEBAGAI UPAYA PENINGKATAN PROFESIONALISME GURU PADA SMK NEGERI 1 JENEPONTO

Community service is a series of tridharma at tertiary institutions, so that activities at SMKN I Jeneponto are the implementation of training activities for making Animation-Based Learning Media as an effort to increase teacher professionalism. However, the problem that is often faced by subject teachers in carrying out their activities within the scope of SMK Negeri 1 Jeneponto is making teaching materials and materials using methods that are not optimal, there is still a lack of understanding about the use of Information Technology and the Use of Software Applications that support learning media, especially in applications presentation processing and application software for animation creation. For this reason, training on making animation-based learning media was held to meet their needs. This activity was carried out in four stages, namely the pre-activity stage, the preparation stage, the training implementation stage, and the activity evaluation stage. This activity was attended by 25 Jeneponto Vocational School 1 teachers who were directly accompanied by speakers from the Undipa PKM team. The result of the activity is an increase in the ability of all teachers. This is evidenced by the results of a user satisfaction survey. In addition, from the design of the animated learning media designs that were made, the best and most interactive ones were selected and had an increase in the quality of the animation designs
PELATIHAN MENELUSURI SUMBER REFERENSI DAN MENGGUNAKAN APLIKASI REFERENCE MANAGER UNTUK MENINGKATKAN KESIAPAN PENULISAN TUGAS AKHIR MAHASISWA

Research activities are generally carried out by students as part of the completion of the final project (thesis) which is one of the graduation requirements for obtaining a bachelor's degree. There are several reference sources that can be used as references in conducting research, including textbooks, previous research journal articles, data and information published by official institutions, as well as results of observations or preliminary research. With a complete reference source, it is expected that students can easily conduct research and write their final project. This community service activity seeks to provide training and practical instructions in accessing national and international journal articles, as well as the process of writing final assignments and publishing scientific articles. This community service activity aims to accelerate students' ability to complete their final project, as an implementation of a cooperation agreement that has been agreed upon by the Faculty of Economics, Jakarta State University with several universities in Indonesia. The time for implementing this community service activity is October 15th 2022. The training was be carried out via media zoom, bearing in mind that currently, Indonesia is still in a pandemic period so there are limitations to conducting face-to-face learning. For this reason, various tips will be explained through this training on how to access various research reference sources that can be carried out by optimizing the use of digital applications. It is hoped that through this training, FE UNJ can actively collaborate with other tertiary institutions in Indonesia in improving capabilities and accelerating the completion of student final assignments in Indonesia
Junior Highschool Library Automation System Solution and Implementation

A high school library is a crucial part of educational infrastructures. Textbooks, e-books, and other collections in a library need to be recorded for circulation and administrative support needs. To provide data for statistical analysis, users of the library must tracked and recorded. Several library activities can be supported by a library automation system (SLiMS). East Jakarta's SMP Negeri 174 Jakarta is a public junior high school with a library. This project to install and implement SLiMS along with configuring the local network and library server. As a result, the library's infrastructure has been properly set up to support the library management system. Data entry for books and library members is currently underway. A guestbook option has also been added, and it is now switching from a manual guestbook to an electronic one to in order to precisely record library visitors.