Reviewerly/exHarmony huggingface dataset:
A Proxy-Based Encrypted Online Social Network With Fine-Grained Access

When using Online Social Networks, users often share information with different social groups. When considering the backgrounds of the groups there is often no or little intersection within the members. This means that a user who shares information often has to share it with all members of all groups. It can be problematic that the user cannot decide which group sees which information. Our approach, therefore, allows users to decide for every bit of information who can access it. Further, protected circles can be created, where users can share information within. In contrast to other approaches, shared information and circles are encrypted in order to keep them secret from the social network provider. The necessary keys can be distributed via proxies.
PREDICTION OF EARTH ROTATION PARAMETERS WITH USING ADAPTIVE HARMONIC PATTERNS

The article discusses the methodology for predicting the Earth's rotation parameters (ERP), which differs from the generally accepted one's in that for constructing prognostic models, time series of initial data of various durations are used. At the same time, the estimation of the parameters of models of slow trend changes performed in the interval of the training sample of about 100 years. Intervals from 6 to 40 years are used to evaluate the parameters of the faster quasiperiodic and regular components. This method of dividing the time series into training sample intervals of different durations allows obtaining adaptive models of slow and fast changes in time series with their subsequent integration into a complete prognostic model. The practical implementation of the proposed methodology showed high stability of the forecasting results for all ERP regardless start date of the forecast, which was confirmed by the results of its testing in various international projects and programs.
Tunable and Robust Long-range Coherent Dipole Interactions Mediated by Weyl Bound States

We investigate the quantum optical behavior of quantum emitters coupled to a Weyl-like photonic environment. For the single emitter case, we will report on the formation of a novel photon-atom bound state featuring a tunable power-law localization of the excitation around the emitter. When two emitters are considered we show that the emergent bound state can mediate tunable and robust long-range coherent interactions.
Research on the Aging Evaluation System of Public Environment in Communities from the Perspective of Sustainability

Abstract The purpose of this study is to improve the quality of community-based care for the elderly, and to build an evaluation system for the aging of the community’s public environment. The research is carried out in two phases: the first phase is the policy specification and the literature statistics, the preliminary sampling of the appropriate aging evaluation indicators; the second phase is the questionnaire survey and exploratory factor analysis, extracting important evaluation factors.The research results showed that the evaluation system of community public environment suitable for aging people is composed of 4 dimensions and 24 indicators, the study suggested that construction standards and decision-making basis for the community’s public environment to be suitable for aging people when the community is under renewed and reconstructed situation.
THE PERCEIVED IMPACT OF SOCIAL MEDIA ACCESS ON RURAL COMMUNITIES IN AL-AHSA REGION, SAUDI ARABIA

Increasing penetration of smartphones in Saudi Arabia has increased access to social media. Smartphone ownership in Saudi Arabia is 87.34% and it is projected to further increase to 97.1% by 2025. This shows that smartphone penetration in the country is double the international average. The most notable use of the internet is for social interaction and this has enhanced the popularity of social media. Social media has greatly impacted the Saudi Arabian society that is largely defined by Islamic culture. Social media a force of change and it has transformed how people interact with friends. In this qualitative study, the data was collected through a survey method and an interview instrument is the research instrument employed. The purpose of this study is to evaluate the perceived impact of social media on the rural communities in Al-Ahsa, Saudi Arabia. The study used a sample of 17 students from King Faisal University and the study found that social media access enhances social interaction, attainment of freedom, and exchange of political ideologies. Also, social media access undermines personal privacy and dilutes a rich Islamic culture. The study also established that smartphone ownership is rapidly increasing in rural areas. Results of this study found the use of social media in rural areas is simultaneously beneficial and harmful. The findings will help leaders to develop policies that enhance the benefits of social media in rural areas but protect consumers from its harmful effects.
Nonlinear PI or PD Controller using Fuzzy Logic-Analytical Modelling, and Computational and Performance Analysis

This paper deals with analytical modelling of Mamdani type fuzzy PI or PD controller using Algebraic Sum (AS) OR operation. Smallest possible number of fuzzy sets (four input fuzzy sets and three output fuzzy sets) are chosen. L - type, Pi - type and Gamma - type membership functions, Algebraic Product (AP) and Minimum (Min) operators for performing AND operation, three linear fuzzy control rules, Larsen Product methodology (LP) for inferencing and Center of Sums (CoS) methodology for defuzzification are used for controller modelling. Two new models are obtained by using the combinations of these components of the fuzzy controller. The suitability of these models for control application is discussed by studying their properties. A numerical example is presented to analyze the performance of developed controller models.
An Empirical Evaluation Research on the Two-Dimensional Spatio-temporal Evaluation of the High-quality Development of Social Science Construction in Shandong Province from the Perspective of Input-Output

With the introduction of the philosophy and social science concepts with Chinese characteristics in the new era of prosperity and development, the construction of social sciences in all regions of the country has attracted much attention. In order to clarify the current situation of social science construction in Shandong Province and better provide reference and reference for the policy formulation of social science construction, the article constructs a DEA-based Malmquist index model to carry out a space-time dual dimension on the high-quality development level of social science construction in 17 cities in Shandong Province Empirical evaluation, through the calculation and decomposition of the total factor productivity of social science construction, it is found that the current social science construction in Shandong Province is showing a good development trend in time series, but the overall social science construction level still needs to be improved, from both time and space dimensions. It is concluded that the high-quality development level of social science construction is closely related to changes in the rate of technological progress; from the perspective of the "two circles and four districts" pattern, the efficiency of social science construction in the Qingdao metropolitan area ranks first, so it is necessary to improve the high-quality development level of social science construction. It can start from the aspects of technological progress rate, technological efficiency, and the agglomeration and diffusion of regional social science construction. The article research can provide a basis for relevant departments to understand the level and stage of social science construction in each city, and provide a reference for determining the policy formulation of social science development in each city. It has certain theoretical guidance and practical reference value.
WITHDRAWN: REHC: Reduction through exclusive homogeneous clusters for imbalance dataset

This article has been withdrawn: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/our-business/policies/article-withdrawal). This article has been withdrawn as part of the withdrawal of the Proceedings of the International Conference on Emerging Trends in Materials Science, Technology and Engineering (ICMSTE2K21). Subsequent to acceptance of these Proceedings papers by the responsible Guest Editors, Dr S. Sakthivel, Dr S. Karthikeyan and Dr I. A. Palani, several serious concerns arose regarding the integrity and veracity of the conference organisation and peer-review process. After a thorough investigation, the peer-review process was confirmed to fall beneath the high standards expected by Materials Today: Proceedings. The veracity of the conference also remains subject to serious doubt and therefore the entire Proceedings has been withdrawn in order to correct the scholarly record.
MOTIONS: Exploring Human-Information Interactions Beyond Clicks

During the last decades, the way people interact with information has drastically changed as a result of the rapid proliferation of new technologies and the arrival of the World Wide Web. This technological evolution has propitiated a transition from physical information objects such as books to their digital and ethereal versions. As a result, an interaction gap between individuals and information objects has emerged. As new technologies appear, alternative possibilities to interact with information can be envisioned, however, little is known about the benefits and costs of such interaction forms (e. g. body-based, virtual and augmented reality, among others). Furthermore, the complexity and cost of conducting studies with technologies such as the above mentioned can be particularly high. To address these problems, we introduce MOTIONS (huMan-infOrmation inTeractION System), a system to conduct evaluations and experiments on human-information interactions with multiple types of interfaces. Additionally, we present a synthesis of case studies conducted using MOTIONS with the aim to compare different types of interactions with digital information objects. On the one hand, these studies demonstrate MOTIONS' utility as a research tool. On the other hand, results suggest that state-of-the-art interaction technology, while appealing, may not be necessarily cost-effective in terms of performance and user experience. These results shed light not only about potential uses of MOTIONS, but also about design decisions when developing new interfaces to interact with information objects in the digital realm.
Joint Estimation of Depth and Pose with IMU-assisted Photometric Loss

Estimation of depth and pose is of research significance. Photometric loss, which can jointly take depth and pose into consideration, is widely used in this field. However, photometric loss jointly estimates depth and pose only based on visual information, which is of difficulty in optimization phase. Considering that IMU (Inertial Measurement Unit) can measure motion status, which has a close relationship with pose, we introduce IMU, named as Pose Hints in this paper, into photometric loss in monocular depth and pose estimation process. Pose Hints provide pose suggestions during optimization phase, so to fuse the two heterogeneous data, we embed a nonlinear optimization module in Convolutional Neural Networks (CNNs) [15,16]. The nonlinear optimization module jointly optimizes depth and pose according to the fused visual-inertial information by minimizing photometric loss. And during the nonlinear optimization process, we get the pseudo-IMU from consecutive poses, which will be compared with Pose Hints to measure the accuracy of pose estimation and then promote the optimization process based on this measurement. We show that using Pose Hints, we can get better estimation results when compared with our baseline.
Design of the educational process of course "Programming fundamentals" in accordance with the CDIO ideology

Abstract The article offers the working program for course "Programming fundamentals " of "Information systems and technologies" direction. Pedagogical technologies for implementing seven modules that are contained in course are listed. There is the list of competencies to be formed in the educational process in the context of CDIO standards as well as features of the forms of using active learning methods during classes are given. The developed curriculum contains related disciplines and includes a clear plan for integrating personal and interpersonal skills as well as skills for creating products, processes and systems.
Text Sentiment Analysis based on Parallel TCN Model and Attention Model

Aiming at the problem that the traditional single convolutional neural network cannot completely extract comprehensive text features, this paper proposes a text sentiment classification based on the parallel TCN model of attention mechanism. First, obtain the comprehensive text features with the help of parallel Temporal Convolutional Network (TCN). Secondly, in the feature fusion layer, the features obtained by the parallel TCN are fused. Finally, it combines the attention mechanism to extract important feature information and improve the optimized text sentiment classification effect. And conducted multiple sets of comparative experiments on the two sets of Chinese data sets, the accuracy of the model in this paper reached 92.06% and 92.71%. Proved that the proposed model is better than the traditional single convolutional neural network.
Developing Efficient Implementation of Label Propagation Algorithm for Modern NVIDIA GPUs

Systems equipped with modern NVIDIA GPUs nowadays are capable of solving many real-world problems, including large-scale graph processing. Efficiently implementing graph algorithms on GPUs is a challenging task, since modern real-world graphs have irregular structure. Current paper describes approaches, which can be used for developing efficient implementation of label propagation algorithm, frequently used to solve graph clustering and community detection problems. Compared to already existing GPU-based implementations, new optimization techniques have been proposed, including graph preprocessing, efficient load-balancing, using unified memory for out-of-core graph processing, and several others. The performance of the developed implementation has been evaluated on synthetic and medium-scaled real-world graphs, resulting in up to 2 times better results compared to existing approaches.
Preface: Research Progress of the Middle‐Lower Yangtze River Valley Metallogenic Belt

Acta Geologica Sinica - English EditionVolume 94, Issue 6 p. I-VI Preface Preface: Research Progress of the Middle-Lower Yangtze River Valley Metallogenic Belt Taofa ZHOU, Corresponding Author Taofa ZHOU tfzhou@hfut.edu.cn School of Resources and Environmental Engineering, Hefei University of Technology, Hefei, 230009 China Anhui Province Engineering Research Center for Mineral Resources and Mine Environments, Hefei, 230009 ChinaCorresponding author. E-mail: tfzhou@hfut.edu.cnSearch for more papers by this authorYu FAN, Yu FAN School of Resources and Environmental Engineering, Hefei University of Technology, Hefei, 230009 China Anhui Province Engineering Research Center for Mineral Resources and Mine Environments, Hefei, 230009 ChinaSearch for more papers by this author Taofa ZHOU, Corresponding Author Taofa ZHOU tfzhou@hfut.edu.cn School of Resources and Environmental Engineering, Hefei University of Technology, Hefei, 230009 China Anhui Province Engineering Research Center for Mineral Resources and Mine Environments, Hefei, 230009 ChinaCorresponding author. E-mail: tfzhou@hfut.edu.cnSearch for more papers by this authorYu FAN, Yu FAN School of Resources and Environmental Engineering, Hefei University of Technology, Hefei, 230009 China Anhui Province Engineering Research Center for Mineral Resources and Mine Environments, Hefei, 230009 ChinaSearch for more papers by this author First published: 15 December 2020 https://doi.org/10.1111/1755-6724.14594Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Volume94, Issue6Special Issue: Special Issue in Honor of Professor CHANG Yinfo's 90th BirthdayDecember 2020Pages I-VI RelatedInformation
System View of Requirements Engineering for IT Professionals

Requirements Engineering teaching for new and experienced Information Technology professionals is a challenge. The pressure of the short-term development culture forces IT professionals to dedicate less time than necessary to both learning and executing the whole Requirements Engineering process. As a way of enabling training these professionals in Requirements Engineering, considering both agile and traditional approaches, this paper presents an innovative approach, which combines cases, discussion, and real experiences. The training contributes to enabling IT professionals to develop a system view of the requirements concerns, promoting a single vision of the different parts of a software system.
Learning Environments of Ingushetia: Archaism and Modernity

The study is devoted to learning environments of Ingushetia. The development of the Ingush national and regional educational space was accompanied by combination and competition of three learning environments: the environment of secular Russian-language education, this of religious Arabic-language education and the environment of folk pedagogy. They made and still make an impact on nurture and education of pupils. Besides, in the context of the emergence and development of the information society and information technology in the educational space of Ingushetia, the fourth new learning environment appeared, that is a digital environment. The study describes these learning environments and their influence on the educational process. The results of the study can be used by education institutions.
Application of 3D Animation Technology in the Making of MOOC

Information technology is gradually developing and progressing with the entire society. At the same time, it is also an indispensable part of the education industry. With the advancement of science and technology, multimedia teaching has become common in modern education. While enhancing students’ interest in learning, it creates a broader teaching space. Among them, 3D animation technology is also a cutting-edge technology in the development of information technology. The introduction of animation technology into the classroom plays a very important auxiliary role in improving the quality of teaching, and also greatly improves students’ interest in learning and learning efficiency. The application of 3D animation technology in the current MOOC production can greatly improve the current teaching ability. 3D animation technology can break the limitations of time and space, and make the MOOC production classroom more realistic. In this regard, the purpose of this article is to study the application of 3D animation technology in MOOC production. This article uses a questionnaire survey method to design an experiment with 200 students, and applies the case design to educational practice. The experimental conclusions show that 3D animation technology is very important for MOOC production. In the process of MOOC production, 3D animation technology can be beneficially used to improve teaching methods and classroom efficiency.
Three Class Classification of Digital Mammograms using Chebyshev Moments and Convolutional Neural Network

Two approaches for effective classification of digital mammograms for early detection of breast cancer are proposed in this work. Detection of breast cancer at an early stage is an effective way for reducing the mortality. Biopsy is the ultimate solution for detection of breast cancer. However, it is invasive and costly too. Digital mammograms are non invasive and assist the radiologist for a preliminary assessment of the disease at an early stage. In the literature most of the works on digital mammogram analysis are based on two class classifications, i.e., whether the image is a normal image or abnormal image. Further, if it is abnormal, the tumor present is malignant or benign. So, the classification is easy as the problem is divided into two binary classification problems. However, there are some works on three class classification of digital mammograms. In this work, publicly available mini MIAS database is used to assess the performance of the proposed algorithms. The first work uses Chebyshev moments for calculating the features and Support Vector Machine with fine tuned hyper parameters is used as a classifier. The second work proposes a simple and compact convolution neural network for the classification. 10 fold cross validation is used in both the approaches for the model preparation. The MIAS dataset is highly imbalanced and hence a misclassification cost is assigned for the underrepresented classes. Performance measures i.e, accuracy, and balanced accuracy are used to demonstrate the usefulness of the proposed algorithms. Results are compared with the state of the art existing works in the literature and superiority of the proposed approaches is justified.
Interval Optimization Based on Hybrid Optimization Algorithm

By combining the genetic algorithm (GA) with the artificial neural network (ANN), this chapter establish two hybrid optimization algorithms to solve the nested optimization problem after transformation, based on which two efficient nonlinear interval optimization methods are developed.
Color Recognition of Vehicle Based on Low Light Enhancement and Pixel-wise Contextual Attention

At present, as a direction of intelligent transportation, the research results of car body color detection are still relatively lacking, and the current car body color detection is still easy to be affected by light, shielding, pollution and other factors. This paper proposes a color recognition of vehicle based on low light enhancement and Pixel-wise Contextual Attention, including low light intensity enhancement based on dual Fully Convolutional Networks (FCN), vehicle body detection based on Pixel-wise Contextual Attention Networks (PiCANet), and color classification of vehicle based on Convolutional Neural Network (CNN). The method of low light enhancement has better robustness and adaptability, and can better process the dark image. We use Pixel-wise Contextual Attention Networks, which better identify main area of vehicle with context information. Experiments show that our method is more accurate than the state-of-the-art method with 0.6% under insufficient light.
Comparative Analysis of Optimal Path Search Algorithms

This article discusses widely used algorithms for finding optimal paths. Currently, there is a fairly wide list of algorithms for the problem of finding the shortest path, and is actively used in mobile robotics to find the optimal route. The article offers a two-level system that performs traffic planning. Comparative analysis of various search methods was carried out: their length, complexity, and a number of turning points. The purpose of the article is to study and compare algorithms from the field of artificial intelligence for finding the shortest path in a maze and a hexagonal grid. Algorithms under study: A* (star), Dijkstra algorithm, BFS, DFS, and Greedy algorithm. Algorithms are compared based on two criteria: the length of the found path and the time it takes to find the path. The results, presented analytically and graphically, show the application of five algorithms for mazes with different size and number of obstacles.