Reviewerly/exHarmony huggingface dataset:
MobRec: Mobile Platform for Decentralized Recommender Systems

In this chapter, we develop a mobile platform for decentralized recommender systems—MobRec. The core concept is that everything runs on smartphones. Due to decentralization, MobRec does not exhibit the lock-in effects present in centralized service providers for recommender systems. In MobRec, ratings and preferences are captured locally. During daily life, these ratings and preferences are exchanged with users in proximity in a device-to-device manner. Locally running recommender systems or third-party service providers can then recommend items based on own data and data received from users met before. We implement the platform for off-the-shelf smartphones for both Android and iOS. We implement device-to-device data exchange that can run in the background on both platforms. In our evaluation, we show the feasibility of our approach. Our implementation can serve as a blueprint for future research and software development in this field.
Cognitive Visual Analytics of Multi-Dimensional Cloud System Monitoring Data

Hardware virtualization has enabled large scale computational service delivery models with high cost leverage and improved resource utilization on cloud computing platforms. This has completely changed the landscape of computing in the last decade. It has also enabled large–scale data analytics through distributed high performance computing. Due to the infrastructure complexity, end–users and administrators of cloud platforms can rarely obtain a full picture of the state of cloud computing systems and data centers. Recent monitoring tools enable users to obtain large amounts of data with respect to many utilization parameters of cloud platforms. However, they fail to get the maximal overall insight into the resource utilization dynamics of cloud platforms. Furthermore, existing tools make it difficult to observe large-scale patterns, making it difficult to learn from the past behavior of cloud system dynamics. In this work, the authors describe a perceptual-based interactive visualization platform that gives users and administrators a cognitive view of cloud computing system dynamics.
Design Methodology for Effective User Interface Design for E-Commerce Applications

There are many customers who shop online. Many of these users interact with the system using well-defined user interfaces only. So, there is a need to develop effective user interfaces that are more user friendly, minimize the keyboard operations, and maximize effective interaction with the system. This chapter focuses on designing effective user interfaces by considering human parameters for e-commerce applications.
Prerequisites and prospects for health-saving pedagogy development in the Murmansk Region

The paper briefly presents an analysis of students competences development at Murmansk Arctic State University: readiness to maintain the level of physical training, providing a full-fledged activity, as well as readiness to ensure students life and health protection within the Federal state educational standard of higher education. On the basis of the pedagogical research conducted among students of Murmansk Arctic State University, the authors propose prerequisites and prospects for health-saving pedagogy development in the Murmansk Region, define priorities of the health center, opened at the University, work out organizational and pedagogical recommendations for the educational process optimization, focusing on physical culture, preservation and strengthening of students health, taking into account climatic and geographical features of the region. The following tendency is revealed: introduction of the individual differentiated approach into the educational process of physical education taking into account the type of students constitution showed its efficiency in comparison with other approaches in physical education of students. The main thing is the use of this pedagogical method contributes to the development of young peoples motivational-value attitude to physical culture and a healthy lifestyle: as a result of pedagogical experiment, the majority of respondents expressed a desire to be engaged in physical training on a regular basis and showed interest in health-saving technologies.
Multi-source Heterogeneous Data Aggregation Method Based on Adversarial Domain Adaptation

In recent years, with the deployment of ubiquitous sensing, the aggregation method of massive multi-source heterogeneous data has become a hot research topic. At present, although the adversarial domain adaptation in transfer learning can achieve effective results in processing tasks such as data classification, there are few methods that can well apply the adversarial domain adaptation network to the scenario of multi-source heterogeneous data aggregation. The existing adversarial domain adaptation methods are mostly applied to the transfer of homogeneous features in single source domain. However, the samples in actual application scenarios are often heterogeneous data from multiple sources. To achieve feature alignment and the aggregation of multi-source heterogeneous data at the same time, a multi-source heterogeneous data aggregation method based on adversarial domain adaptation is proposed in this paper, by embedding a mapping neural network for heterogeneous data in the adversarial network, and adding weight parameters to measure the contribution of multiple source domains’ features and classes. The feasibility of the network structure is analyzed theoretically, and the effectiveness of the method is verified through experiments.
Mobile Embedded System

The use of smartphone is pervasive. With device pocketability driving user engagement throughout the day, it is highly probable that smartphones will replace daily items (e.g., keys and credit cards) that people now carry around. The idea presented here is a significant step in this direction. This chapter details the authors' design and development of a smartphone access control system using Near Field Communication (NFC) Encrypted Steganography Graphical Password (ESGP). The primary objective is to leverage the technical capability of NFC-enabled smartphones in developing a two-factor authentication system connecting physical resources (i.e., premises) and virtual resources (i.e., password knowledge). This involves a novel integration of token-based, graphical-password authentication, cryptography and steganography. The second objective is to evaluate users' behavior intention to use the system. New insights for researchers and business world interested in the unified solutions for NFC-compatible smartphone, access control and mobile security are provided.
Research on the Live Teaching Effect Based on Multimodal Data Fusion

In the intelligent education era, multimodal data fusion analysis becomes a trend and a key method to address issues in education and teaching. As live teaching grows rapidly, the analysis of teaching effect is facing challenges of dynamic data collection, as well as multimodal data fusion analysis. Based on analyzing the connotation of multimodal data as well as research status-quo of live teaching, and with the assistance of EEG identification and facial expression identification among other technologies, the article carried out the analysis and experiment on live teaching performance based on multimodal data fusion, and discussed the role that multimodal data fusion played in the analysis of live teaching performance with respects to knowledge retention, students satisfaction, sense of presence, and interaction, etc., and eventually came with an optimization strategy for lives teaching activities with the support of multimodal data fusion and analysis. The research concluded that multimodal data fusion analysis enabled the all-round multidimensional recording of the live teaching process, brought about more comprehensive performance analysis of different teaching periods, and provided data support to tutoring.
Measuring Text Readability Using Reading Level

Reading grade level calculations have been in use for over a century in the United States and have guided the selection of texts used in school programs. Government agencies at all levels, the military in its various branches, and editors of publications have found such formulas of use in setting policy or determining who can participate in programs. As readership is now a worldwide phenomenon with English as the primary language of the internet, reading grade level calculations can also be useful in creating web pages and assigning reading texts to large multi-user classes (MOOCs) run over the internet. In this regard, it is possible for faculty to be assured that the material is reachable to a wide audience by checking reading grade level and providing additional guidance for the more difficult items in the form of discussion or focused questions. Authors can use the formulas as a tool to check the quality of their own writing and improve sections which are unnecessarily complex.
A Socio-Technical Perspective on Threat Intelligence Informed Digital Forensic Readiness

In this article, a DFR framework is proposed focusing on the prioritization, triaging and selection of Indicators of Compromise (IoC) to be used when investigating of security incidents. A core component of the framework is the contextualization of the IoCs to the underlying organization, which can be achieved with the use of clustering and classification algorithms and a local IoC database.
Imitation of multiposical collective messaging in individual thinking

The variety of varieties (implementation technologies) of the method of “brain storming” or “brain attack”, used in the process of collective generation of ideas and solutions in such areas as design and management, is known. This diversity includes: reverse, shadow and combined brainstorming, brain write on paper, individual brainstorming, brainstorming on the board, brainstorming in the style of «Solo», visual brainstorming, brainstorming as japanese, the morphological method and method of analyzing the range of problems, analogy method, random impulse, «635» method, moderation method. The inclusion of “brain storming” of the variety “individual brainstorming” into such a mix raises some doubts among a number of researchers, since the brainstorming method was originally and in essence intended for the collective generation of ideas and solutions. World science studied and known the specific differences of individual (personal) and collective (group-wise) consciousness, behavior and mental activity. The author of the article considers the possibility of generating “new” information in the process of imitation multi-position collective activities in individual thinking, considering such an approach to be different from the variety of technologies of the “brain storming” method.
Quantum Fourier Transforms

Quantum Fourier transform (QFT) plays a key role in many quantum algorithms, but the existing circuits of QFT are incomplete and lacking the proof of correctness. Furthermore, it is difficult to apply QFT to the concrete field of information processing. Thus, this chapter firstly investigates quantum vision representation (QVR) and develops a model of QVR (MQVR). Then, four complete circuits of QFT and inverse QFT (IQFT) are designed. Meanwhile, this chapter proves the correctness of the four complete circuits using formula derivation. Next, 2D QFT and 3D QFT based on QVR are proposed. Experimental results with simulation show the proposed QFTs are valid and useful in processing quantum images and videos. In conclusion, this chapter develops a complete framework of QFT based on QVR and provides a feasible scheme for QFT to be applied in quantum vision information processing.
Think Events: From Signals to Events

chapter Share on Think Events: From Signals to Events Authors: Laleh Jalali University of California, Irvine (UCI), Hitachi America Ltd. University of California, Irvine (UCI), Hitachi America Ltd.Search about this author , Ramesh Jain University of California, Irvine (UCI) University of California, Irvine (UCI)Search about this author Authors Info & Claims Event Mining for Explanatory ModelingMay 2021 https://doi.org/10.1145/3462257.3462260Published:20 May 2021Publication History 0citation8DownloadsMetricsTotal Citations0Total Downloads8Last 12 Months3Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my Alerts New Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Application of BP Neural Network Algorithm in Campus Sports and Health Management

Sports are beneficial to people's physical and mental health, and improving people's physical and mental health is one of the hot issues that sports researchers and human society generally pay attention to. The BP neural network algorithm is used in the evaluation research of sports and health management, which theoretically enriches and expands the use and evaluation scope of sports and health evaluation. In the research method, the neural network BP is introduced into the sports health evaluation. In this process, it has certain theoretical guiding significance for the complete application of the neural network method BP and other research issues. The purpose of this article is to study the application of BP neural network algorithm in campus sports and health management. This paper uses the improved Hu unique moments to describe human motion behavior. In order to describe the characteristics of human motion behavior more accurately, this paper selects 4 Hu moments to represent behavior characteristics. This work proposes a BP neural network structure optimized by genetic algorithm to determine human motion behavior. This work uses BP neural network to evaluate health management. Experimental studies have shown that the GA-BP neural network algorithm used in this article has a significantly higher recognition rate of 20%-30% than the recognition rate of the BP neural network for the five human gaits. A large number of simulation experiments have also verified the feasibility of this method.
The Backbone of Decision Support Systems

Understanding the current situation is critical in every natural disaster or crisis. Therefore, there is a need for accurate and up-to-date information about the scope, extent and impact of a disaster. The basis for this information is data that is available through a variety of sensors. Decision Support Systems (DSSs) support decision makers in disaster management, response, and recovery by providing early warnings, insights into the current situation and recommendations for mitigation actions. For this purpose, raw sensor data needs to be collected, analyzed, integrated, and its semantics need to be automatically understood by the system. This series of processes forms a generic sensor to decision chain. In this paper, we present solutions and technologies to integrate those steps seamlessly, also demonstrating how each step of the pipeline can be visualized.
Independent Training of Students for Seminars on the Discipline Regional Folk Singing Styles

The article considers the key aspects of individual work performed by undergraduate students of Russian institutions of higher education of creative orientation educated in training direction “Art of Folk Singing”, as a part of preparation for workshop (seminar) sessions run within the frames of the academic discipline “Regional Styles of Folk Singing”. On the author’s view, one of the most important condition for today’s undergraduate students’ good self-education and fostering of a further folk singing culture specialist’s professionally valuable qualities is appreciation of significance of a role of a modern student’s individual work in general structure of pedagogical process running in the Russian higher school. The author of the paper briefly describes a typical structure of a workshop (seminar), its key management tasks and principles. Steps of an algorithm of information search and analysis of education materials by students are disclosed. The article outlines the author’s opinion on content peculiarities of issue-related calendar plan of academic discipline “Regional Styles of Folk Singing” that discloses particularly through a workshop (seminar) form. Also, the specifics of management of a workshop (seminar) are given; the author notices importance of a workshop (seminar) in the context of training students’ ability to apply received knowledge, skills practically.
Blockchain in Food and Agriculture Supply Chain

Agriculture is one of the most important and largest sectors in Indonesia and creates jobs for at least 38.7 million workers. Although the number of workers in agriculture is relatively high and the sector contributes 14% to Indonesian GDP, many challenges still remain hampering growth. One of the key issues is the limited data availability in the agriculture sector causing imperfect and incomplete information on agriculture products. Data can provide the information about the quality of the product to the consumer to create transparency between producer and consumer. In order to facilitate data access, a big data base is needed in which all stakeholders can access the near-time data. A technology that can help to support this database is called blockchain. Blockchain is an immutable, transparent, public and append-only ledger. It is a peer-to-peer network that can maintain updates and verifies those updates to the ledger in a way that it is impossible to alter the data. This paper discusses HARA, a use-case of blockchain implementation in the food and agriculture sector.
APPENDIX E: On Behalf of Edwards’ Complete Representation Exemplarism

No AccessAPPENDIX E: On Behalf of Edwards’ Complete Representation Exemplarismhttps://doi.org/10.13109/9783666564864.290SectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinkedInRedditEmail About Previous chapter Next chapter FiguresReferencesRelatedDetails Download book coverNew Directions in Jonathan Edwards StudiesVolume 6 1st editionISBN: 978-3-525-56486-8 eISBN: 978-3-666-56486-4HistoryPublished online:January 2020 PDF download
Homomorphic Encryption

Shortly after the original RSA paper [1], a question was posed by Rivest, Adleman, and Dertouzos [2]: would it be possible to have a database of encrypted information (such as financial or health data), stored in an external location, that would nonetheless allow computations on the encrypted data without decrypting it? This would permit, for example, external storage, and computation on the encrypted data stored at the external site, without having to trust the owner or operator of the external site. $$\mathbb {R}^{3}$$
Access Control Framework Using Multi-Factor Authentication in Cloud Computing

The most challenging issues in cloud computing are access control and data security because users of the cloud outsource sensitive data and information to cloud provider servers, which are not within the same trusted domain as the data owner. Within cloud computing, various services and resources need protection from unauthorized use as a part of the security. Authentication is a key technology for information security. In recent years, a lot of research has been carried out throughout the world and several schemes have been proposed to improve authentication in the cloud. Remote authentication is the commonly used method to determine the identity of the remote client. In this article, the authors have proposed a systematic method for authenticating clients, namely by using a password, biometrics, and out-of-band-based access control mechanisms that are suitable for access control. The proposed system involves user ID/password, biometrics characteristics, and a mobile phone as a software token for one-time password generation.
Light Weight Landmark Detection Method

Detecting landmarks in images is an important and challenging task for intelligent driving. The difficulty of this task is to locate and classify the landmarks accurately under the limited resources of intelligent driving platform. In this paper, we propose a method of filter pruning for deep neural networks for the real-time landmark detection. The network is based on yolov3 and improved for feature extraction. Then we conduct filter pruning based on the attention mechanism, resulting in the final lightweight model. The experiment on landmark detection datasets shows that the proposed lightweight landmark detection method can achieve high performance in accuracy with fast speed.
Understanding the Hand-Gestures Using Convolutional Neural Networks and Generative Adversial Networks

In this paper, it is introduced a hand gesture recognition system to recognize the characters in the real time. The system consists of three modules: real time hand tracking, training gesture and gesture recognition using Convolutional Neural Networks. Camshift algorithm and hand blobs analysis for hand tracking are being used to obtain motion descriptors and hand region. It is fairy robust to background cluster and uses skin color for hand gesture tracking and recognition. Furthermore, the techniques have been proposed to improve the performance of the recognition and the accuracy using the approaches like selection of the training images and the adaptive threshold gesture to remove non-gesture pattern that helps to qualify an input pattern as a gesture. In the experiments, it has been tested to the vocabulary of 36 gestures including the alphabets and digits, and results effectiveness of the approach.
Novel Trust Model to Enhance Availability in Private Cloud

The benefitsDamera, Vijay Kumar of cloud computing for companies are numerous.Nagesh, A. However, among all the advantages, high availability in the cloud is one of the factors that draws the attention of most of cloud users.Nagaratna, M. High availability, as the name suggests, ensuring that IT resources are available at all times. For this, it is necessary to implement processes to detect single points of failure in your system and reduce the chances of their occurrences through strategies such as redundancy and/or replication. Widely accepted solution for enhancing availability in cloud is replication. However, deciding on minimum number of replicas and where to place replica is a major research concern in cloud. Hence, where to keep replicas in the system to satisfy availability requirement is a matter of concern. To address above issue, this paper proposes a novel trust model which helps in selecting appropriate node for replica placement.
Research on a Graph Reachability Algorithm Based on Block Optimization

The traditional Floyd Warshall algorithm can be used to compute the transitive closure of a graph with <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$O \boldsymbol{(\mathrm{n}^{\wedge}3)}$</tex> time complexity. In this paper, a new directed graph reachability calculation algorithm based on topological sorting and block optimization is proposed. The performance of the new algorithm is verified by simulation experiments under different conditions. The experimental results show that the new algorithm is more effective than the traditional algorithm when calculating the reachability of directed graphs with different sparsity.