Reviewerly/exHarmony huggingface dataset:
Improved Deep Bi-directional Transformer Keyword Extraction based on Semantic Understanding of News

To address the problems of existing methods such as neglecting semantic information and the lack of diversity in extracted keywords. This paper proposes an improved deep bi-directional transformer model based on semantic understanding of news, combining pre-trained word vectors with K-Means algorithm. After extracting word vectors with rich semantic information based on contextual words through the bert pre-training model, then the K-Means clustering algorithm is used to form clusters of different topics. The extracted keywords semantically highlight the central theme and at the same time can better solve the problem that lack of the diversity of keywords. Experiments show that the improved deep bi-directional transformer model based on news language understanding proposed in this paper has significantly improved in accuracy, recall and F-value compared with RAKE, TF-IDF, LDA, RNN, LSTM models for extracting keywords and word2vec models for static extraction of word vectors.
Mining Diverse Clues with Transformers for Person Re-identification

Person Re-identification (ReID) is a challenging task due to the inherently large intra-class variation and subtle inter-class differences. Early works mainly tackle this problem by learning a discriminative pedestrian feature representation. Recently, vision transformer (ViT) has shown outstanding performance in many tasks, where the self-attention mechanism plays a key role that links every patch tokens with the class token. Intuitively, the class token could serve as a good global feature that captures local details naturally. Experiments demonstrate that the vanilla ViT can achieve impressive performance when directly applied to the ReID problem. Nevertheless, the class token may pay much attention to most salient patches while ignoring less salient but informative ones and missing some potential clues. To reduce this limitation, we propose a novel network MDCTNet to mine divers clues for person re-identification with transformers. Based on the cascaded architecture of transformer encoder, a Patch Suppression Module (PSM) is incorporated into the last several transformer layers, which aims to progressively discard some most salient patch tokens and make less salient ones passed to the next layer. Thus, the model is enforced to mine more potential useful clues in the remained patches and the resulting pedestrian representation can be more robust. Extensive experiments on three mainstream datasets including Market1501, DukeMTMC-ReID and MSMT17 validate the effectiveness of our method.
CO-EXPERIENCE AND DIGITAL INCENTIVES: UNDERSTANDING PURCHASE INTENTION IN THE P2E METAVERSE

The purpose of this study is to demonstrate the effects of co-experience and digital incentives, the main features of the Play to Earn (P2E)-type metaverse, on the successful operation of the metaverse.With consideration of the experience economy model, we propose a research model to elucidate participants' satisfaction, attitudes toward farming, and purchase intention for a P2E metaverse-type virtual farm.Analysis of data from questionnaires targeting real players confirmed the positive effects of co-experience and digital incentives on satisfaction and attitudes toward farming related to educational and entertainment experiences.We present theoretical and practical implications suggested by the results.
Good Practices of Witelon Collegium State University - creative activity for difficult times

At Collegium Witelon, the State University, a project entitled "Creative activity - possibilities of using free time also during a pandemic" was created. The idea of the project was to show young people the possibility of spending their free time also in a situation of isolation. The project focused on using the potential of creative activity. Creative activity is a chance for young people to realize themselves - regardless of gender, race, nationality, religion, belief, age. It is an opportunity to use your own skills and develop interests and passions, as well as, through specific actions, to make social changes that minimize the issue of mental threats. Various artistic, musical and theatrical forms constitute the most frequently undertaken creative activity, they are the possibility of expression accompanied by emotions through colors, sounds, words, gestures and movement. In this way, young people can satisfy their own needs while learning about the properties of the objects of the real environment. Creative activity is the best way for an individual to meet the need for knowing and experiencing the world. It should be treated as a priority used in the upbringing process, a fundamental value and a tool supporting development, especially in situations of isolation or social threats. All activities that show creative activity, especially in childhood, are valuable links influencing the effectiveness of the educational process. They develop cognitive curiosity, imagination and creativity, but also entertain and enjoy. They can be the basis of therapy or sociotherapy. Creative activity can be an alternative to confinement, isolation. It gives the opportunity for an interesting and creative way of spending free time - individually, together, also in a small group. It can give you a sense of your own fulfillment while achieving your own success. It can be an alternative to the pandemic - COVID -19. Therefore, it is worth focusing on the possibilities of creative activity and becoming interested in the method of activating children and youth, which is the project. Let good and proven practices inspire and undertake similar activities.
Safe Drone Flight with Time-Varying Backup Controllers

The weight, space, and power limitations of small aerial vehicles often prevent the application of modern control techniques without significant model simplifications. Moreover, high-speed agile behavior, such as that exhibited in drone racing, make these simplified models too unreliable for safety-critical control. In this work, we introduce the concept of time-varying backup controllers (TBCs): user-specified maneuvers combined with backup controllers that generate reference trajectories which guarantee the safety of nonlinear systems. TBCs reduce conservatism when compared to traditional backup controllers and can be directly applied to multi-agent coordination to guarantee safety. Theoretically, we provide conditions under which TBCs strictly reduce conservatism, describe how to switch between several TBC's and show how to embed TBCs in a multi-agent setting. Experimentally, we verify that TBCs safely increase operational freedom when filtering a pilot's actions and demonstrate robustness and computational efficiency when applied to decentralized safety filtering of two quadrotors.
Analysis on the Music Education Difficulties and Its Solutions in Higher Vocational Colleges

It has become the teaching goal of higher vocational colleges to cultivate qualified talents with high quality and skills that meet the needs of society and industrial development.The development of higher vocational colleges has been paid more and more attention by the state and society.Paying attention to the role of music education is becoming more and more important in the process of improving higher vocational education in the new era.As an important part of quality education, music education can improve students' comprehensive quality and promote students' all-round development.
A Meta-heuristic Algorithm for Global Numerical Optimization Problems inspired by Vortex in fluid physics

A Meta-heuristic Algorithm for Global Numerical Optimization Problems inspired by Vortex in fluid physics
Delay-Aware Cooperative Task Offloading for Multi-UAV Enabled Edge-Cloud Computing

Unmanned aerial vehicle (UAV) has received tremendous attention in the area of edge computing due to its flexible deployment and wide coverage accessibility. In weak infrastructure scenarios, multiple UAVs can form on-site edge computing clusters to handle the real-time tasks. Further, a multi-UAV enabled edge-cloud computing system is coined by cooperating the UAVs with remote cloud, which provides superior computing capability. However, the uneven distribution of tasks makes it difficult to meet the real-time requirements when load balancing is unavailable. To address above issue, a delay minimization problem for multi-UAV enabled edge-cloud cooperative offloading is investigated in this paper. The problem is formulated as a non-convex problem based on models that reflect characteristics of the system, such as ubiquitous network congestion, air-to-ground wireless channel and cooperative parallel computing. An efficient cooperative offloading algorithm is proposed to address the problem. Specifically, convex approximation is applied to make the original problem tractable, and Lyapunov optimization is utilized to make online task offloading decisions. Finally, the correctness of the models are verified through a practical UAV-edge computing platform. Simulations based on measurement results and real-world datasets indicate that, the proposed algorithm fully utilizes the available energy to significantly reduce the tasks' completion delay.
Intelligent Fall Detection and Notification System for IoT based Smart Home Environments

Throughout the history of technology, various mechanisms to support the elderly and the disabled have been introduced as a remedy for the inadequacy of caregivers to provide them with the required assistance in leading an independent and secure living. Among all those mechanisms, smart homes and social robotics appear to play a significant and effective role in assuring a comfortable and safe environment for the elderly and the disabled who prefer to live independently without causing an extra burden on their families.
Influence of Innovative Digital Technology on Healthcare Service Performance

This paper presents a study on innovative digital technology factors affecting UAE healthcare service practices performance. The innovative digital technology factors are clustered in four domains namely systemdevelopment; IT base innovation; technology services and process integration. Data collection was conducted through questionnaire survey among healthcare employees from managers to operational workers in Dibba Hospital, Masafi Hospital, and Fujairah Hospital in UAE. The selection of respondents was carried out in two sampling approaches which are stratified sampling random sampling technique methods. A total of 300 questionnaire sets were distributed but only 281 sets of completed questionnaire were returned for the analysis. This represents the responses rate of 94%. Before conducting the ranking analysis, the collected data was characterised for its reliability and normality patterns and found that the data has achieved the reliability and normality criteria. The ranking analysis found that the most influential innovative digital technology factor is TS2 of the technology services domain. TS2 is concerning the connectivity with an extranet.The second factor is TS3 in the technology services domain which is efficient human resource management system. The third rank is SD2 system development domain which is updates the technological features of existing system to improve healthcare services. The fourth rank is BIN1 in IT base innovation domain which is adds new capabilities to the existing system. Finally, the fifth rank is BIN2 in IT base innovation domain which isnew features are often added to the existing system.
Hydrogen Technologies in The Czech Republic

Although not really expected, activities in the field of hydrogen technologies date in The Czech Republic more or less 5 decades back to the history. It is true, this tradition was broken for substantial time in seventies and eighties of the past century, but there was a solid fundament to build up on. This, together with technical and technological skill of the people in the country, helped significantly when re-establishing activities in this field two decades earlier. And the same aspect hopefully helps also in the future development.
NormalityAssessment: An Interactive Classroom Tool for Testing Normality Visually

Many inferential and predictive statistical procedures possess underlying theoretical assumptions that should be met in order for the results of those procedures to be considered reliable. One assumption associated with methods for population means, including linear regression coefficients, is that of normality of a population(s). When assessing normality, two graphical tools that are often utilized are normal quantile-quantile (QQ) plots and histograms. However, while these tools are popular, they still present challenges for many who use them due to the subjectivity oftentimes involved when examining them. In this article, we describe a free, interactive Shiny application, downloadable as an R package, which implements two procedures recently developed for graphical inference with a specific emphasis on assessing normality. The application was created and designed with a focus on statistics education.
Hasil Validasi Ahli Materi, Bahasa, dan Media dalam Pengembangan Buku Ajar Belajar dan Pembelajaran yang Merujuk pada Kitab Ta’lim Muta’alim

Textbooks are an important element of learning. Therefore, the development of textbooks continues to improve the quality of content which has an impact on increasing overall output. One of the compulsory subjects on the education campus is study and learning courses. This subject is almost the same as the study of books in Islamic boarding schools, namely the ta'lim muta'alim book which specifically discusses how to learn and learn. This study aims to develop learning and learning textbooks that refer to the ta'lim muta'alim book. The outputs of this development include (1) producing printed textbooks that can be used in lectures; (2) produce scientific articles published in accredited national journals. While the long-term target is to improve the character of students (prospective teachers) in facing the 4.0 era and the next era. The development model used is the 4D model. which consists of the stages of define, design, develop, and disseminate. The results of the validation of material experts, linguists and media experts all show decent results with good predicates. Each validator also provides very specific suggestions for producing a quality product.&#x0D; &#x0D;
Evaluating SMR positioning with an autostigmatic microscope

An optical method of determining the location of the apex of a corner reflector mounted in a steel ball, commonly referred to as a Spherically Mounted Retroreflector (SMR), relative to the center of the ball to the 1-2 μm level was previously described by us. The method used an autostigmatic microscope focused on the apex and viewed the reflected spot image as the SMR was rotated about a normal to its entrance aperture. This measurement determined the lateral offset of the apex and tipping the SMR while viewing the spot gave an indication of the axial displacement. A related questions arose recently, could the distance between two SMRs be determined to the same level of precision if the SMRs were rigidly mounted in a fixture so they could not be moved. We show the answer is yes assuming the stage moving the pair of SMRs has the required precision. As a SMR is scanned under the autostigmatic microscope the spot motion seen by the microscope is identical to that seen when scanning a spherical ball under the microscope and we have already shown that balls centers can be found to 1 μm precision using a 10x objective. We show experimentally that we can determine the distance between 2 SMRs by repeated measurements with the balls in different azimuthal orientations, and show that by taking into account the orientation, the distance between SMRs remains the same within experimental errors.
Bibliometric Analysis of Research Papers on Blockchain Technologies

Blockchain is a database in which all transactions performed in a business network are recorded. It facilitates the tracking of tangible and intangible assets. Blockchain is a distributed and decentralized database. Recent studies in this area have attracted the attention of researchers. However, comprehensive bibliometric analysis studies on blockchain technologies are insufficient in the literature. In this study, a inclusive bibliometric analysis was performed on the blockchain technology by using the R programming language and the bibliometrix and biblioshiny libraries. Web of Science (WoS) database was used for data collection. Only the keyword blockchain was searched. Data are from 3927 Science Citation Index research papers published from 2016 to 2022. Predictable information was obtained by viewing key information about various tables such as annual scientific articles, top articles per citation, authors, countries, sources, and keywords. It is aimed to be a guide for new studies by determining the trends related to blockchain technology. As a result, it has been discovered that blockchain research will intensify on the axis of privacy and security of people, and the number of research studies will increase thanks to the collaborations to be made.
Fraud Prediction of Credit Card Customers Based on Xgboost Model and Multi-Layer Perception Model

With the boom in mobile web applications and the electronic payment industry, the use of credit cards for fraudulent purposes is increasing. How to handle credit card fraud in a timely manner is now the pressing challenge for financial institutions and operators to overcome. To address this problem, this paper conducts experiments using the credit card public dataset available on Kaggle. For the uneven distribution of data samples in the dataset, this paper uses the down sampling method, followed by feature filtering by ranking the importance of the features in the dataset, and finally using XGoost and the multilayer perceptron to analyse and predict credit card fraud in the dataset. This study tests the performance of the two models using accuracy, recall, and f1-score in order to fairly assess how well they perform on this issue. Empirical evidence shows that the XGBoost model outperforms the multilayer perceptron model in the credit card fraud problem.
The role of VINITI in the advance of the national system of sci-tech information

The new and traditional vectors in the activities of the RAS All-Russian Institute of Scientific and Technical Information (VINITI) are reviewed. The Institute’s potency and its role in the development of the system of sci-tech information are demonstrated. The VINITI RAS acts as a polyfunctional information center with diverse characteristics; it applies modern information and telecommunication technologies and digital information resources. The key types of information products and services to provide information support in science, technology and industries, are reviewed.
Quantitative Analysis of China's Artificial Intelligence Technology Patents

Traditional patent statistics cannot accurately reflect the real development level of technology. In order to overcome this deficiency, this study adopts quantitative research methods to conduct empirical research on global artificial intelligence technology-related patent applications, and on this basis, provides suggestions for the government and enterprises on how to improve my country's innovation capabilities in the field of artificial intelligence. First, this paper analyzes patent application trends, technology application areas and innovation trends using the incoPat patent search database and information visualization tools. On this basis, the Herfindahl-Hirschman index is further used to measure and analyze the patent concentration of artificial intelligence technology patent applicants in various regions of my country. The analysis results show that my country has the largest number of patent applications in the area of artificial intelligence technology, but the proportion of high-value patents is relatively low, which needs to be further improved. Patents in the eastern region are relatively scattered, while patents in the western region are relatively concentrated. The government should introduce policies according to local conditions to avoid excessive concentration and dispersion of patents.
"Anime + Virtual" Analysis of the New Fusion of Metaverse Variety Shows——Taking "2060" as an Example

In recent years, the concept of the metaverse has appeared in people's field of vision.2021 is called "the first year of the metaverse", and the virtual image that came into being with the era of Z has also begun to integrate into our world.At the end of last year, Jiangsu Satellite TV launched an animation image stage competition program "2060", which combined virtual technology to create a 26-bit twodimensional image V-life.The guests formed their favorite teams based on their debut and other performances.Win the audience's favorite value to decide the winner."2060" has changed the traditional competitive variety show mode, using the concept of the metaverse and virtual images, making the audience refreshing.Analyze the ingenious integration of "2060" from the perspective of program content, technology application, and visual experience, and why the Metaverse variety show can enter the mainstream platform.
PERANCANGAN SISTEM INFORMASI CUSTOMER RELATIONSHIP MANAGEMENT BERBASIS WEB UNTUK MENINGKATKAN LOYALITAS PELANGGAN PADA LAUNDRY XYZ

With more laundry outlets being opened, the competition is getting tighter where customer satisfaction is a top priority as a strategy to retain old customer and get new customer. Today’s customer satisfaction does not only cover the quality of the laundry results but also covers the service from beginning to the end of the transaction, including the information on laundry time and information about the information on laundry completiontime. Customer Relationship Management (CRM) is a strategy used by business people in managing relationships with customers so that they can maximize communication in order to gain customer trust and loyalty. Web E-CRM has been successfully built using the waterfall system development method through 5 stages, namely planning, analysis, desing, implementation and system stages. The E-CRM web implementation phase is done by testing the system. Testing e-crm using black box testing where the method test the input and output functionality of a software.
On Discrimination Power of Image Feature Vector

Image Analysis using systems like Content based Image Retrieval is the information retrieval system which helps in retrieving similar images, found very useful in many areas. Feature vectors are the compact and precise representation of Images which effectively needs to be used in Image Retrieval System. The performance of Image Retrieval is majorly dependent on the quality of feature vectors. Many intelligent algorithms are proposed in literature to retrieve the features of images and represent it in an optimal way. Feature Vectors with reduced dimensions are always preferred for image retrieval systems. Quality of Feature Vectors is always checked using the output of image retrieval. There has always been a trade-off between the size of the feature vector and retrieval performance. Common measures used for checking retrieval system performance are precision, recall. This paper discusses the important measure: “discrimination power” of Image feature vector to check feature vector quality in context of image matching and retrieval. The discrimination power of Image Feature Vector, and its use-case with our feature extraction method is discussed here.