Reviewerly/exHarmony huggingface dataset:
Relation Artefacts Type IV

This chapter is about relation artefacts Type IV which are socio-technical interventions in organizational and wider contexts. Three subtypes of these relation artefacts move the design from the technical to the social: interaction interoperability checkups, digital legacy interventions, and organizational strategy alignments. The HWID platform is shown to provide a massive push toward such interventions, through the continuous relations building between empirical work analysis and interaction design activities that aims to create new local sociomaterial realities for stakeholders involved. Ways of avoiding falling into a ‘techno-determinism’ trap and instead keeping the relations to the social, and vice versa, are introduced. The chapter ends with a summary of how to do socio-technical HCI design interventions.
A Method Out of the Madness: OhioLINK's Collaborative Response to the Serials Crisis

The downward spiral of increasing serial prices and decreasing subscriptions is well documented. Libraries’ efforts to minimize its impact by trying “just in time” rather than “just in case” solutions have most often attacked the periphery of the problem. Most libraries’ efforts have as an objective only to lose by closer scores rather than keep pace or even expand journal coverage. This paper examines ways in which the OhioLlNK community and individual libraries are trying to leverage their collective resources to dramatically reverse the spiral. [Article copies available for a fee from The Haworth Document Delivery Service: 1-800-342-9678. E-mail address: getinfo@haworth.com]
Deep Reinforcement Learning with Sparse Regularized Pruning and Compressing

Deep Reinforcement Learning (DRL) currently demonstrates distinguished performance in various fields of sequential decision tasks. Despite the great success, tremendous model size and large redundant parameters have become the major bottleneck on real-time deployments of DRL models. In this paper, we propose a novel model compression framework for DRL models with sparse regularized pruning method and policy shrinking technology, which can realize the superb balance be-tween the high sparsity and compression rate. In our framework, We first obtain the sparse student model by pruning method with the ℓ <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</inf> -norm. Then, the shrinking technology is proposed to gain the dense student model for further compressing DRL models. Experiments on Cartpole and Lunarlander environment demonstrate that the proposed algorithm for DRL leads to an improvement state-of-the-art in terms of model size, iteration cycles, and parameters reduction.
Mining Social-Network Graphs

Written by leading authorities in database and Web technologies, this book is essential reading for students and practitioners alike. The popularity of the Web and Internet commerce provides many extremely large datasets from which information can be gleaned by data mining. This book focuses on practical algorithms that have been used to solve key problems in data mining and can be applied successfully to even the largest datasets. It begins with a discussion of the MapReduce framework, an important tool for parallelizing algorithms automatically. The authors explain the tricks of locality-sensitive hashing and stream-processing algorithms for mining data that arrives too fast for exhaustive processing. Other chapters cover the PageRank idea and related tricks for organizing the Web, the problems of finding frequent itemsets, and clustering. This third edition includes new and extended coverage on decision trees, deep learning, and mining social-network graphs.
Cyber Security Crime and Punishment

Cyberspace and the existence of the internet allows different types of crimes to appear. Hence, there is a need for new laws to be set with a collective, comprehensive, view of crime and a global understanding. This article studies 5 different countries' laws pertaining to cybercrimes namely: Jordan, Oman, Kuwait, Qatar, and Saudi Arabia. These different countries issued different laws at different times, some in 2007 others are as new as 2015. The article looks at the laws from an academic definition of different crimes, and also describes the laws from a perspective of each country.
Virtual Reconstruction of Objects by Point Cloud Capture to Measurement of Density Parameters Using Low Cost Device

It is studied in this project the viability to implement an application to virtually rebuild objects using a low-cost device. A rebuilding application was developed using ReconstructMe SDK’s interfaces and a Kinect as a depth device. An analysis tool working on the Unity engine was also implemented, operating mainly as Editor Scripting with its C# API feature. This tool implements the capacity to obtain the measurement data of volumetric extremes of the virtual objects. The proposal is tested by rebuilding of some specific objects, which are the closest resource; by manually conducting the device. With results, the application faces some problems with the mesh fitting of some objects, however the mesh quality is relatively good. Based on data measured, it is achieved a good level of precision on the extreme measures besides that each rebuilding procedure can be made within a relatively fast time cost, around 25 s.
Introduction

This introductory chapter starts by describing the effects of uncertainty in intelligent systems and presents a brief history on the development of uncertain reasoning in artificial intelligence. Then it presents the basic approach for probabilistic reasoning, motivating the development of probabilistic graphical models. It gives an overview of probabilistic graphical models, the types of models and how these can be classified. It concludes with a description of the rest of the book.
Improved Secure Data Transfer Using Video Steganographic Technique

Information security using data hiding in video provides high embedding capacity and security. Steganography is one of the oldest data protecting methodologies deals with the embedding of data. Video Steganography hides secret information file within a video. Present day communications are treated to be “un-trusted” in terms of security, i.e. they are relatively easy to be hacked. The proposed technique is invented to hide secret information into a video file keeping two considerations in mind which are size and security of the cover video file. At the sender side, the secret information which is to be hidden is encoded into cover video file. Double layered security for the secret data can be achieved by encrypting confidential information and by embedding confidential information into cover video file frames using encrypted embedding technique.
Analysis on the Application Research of Intelligent Electronic Dictionary Search System in English Writing

With the rapid development of technology, smart phones have generally entered people's lives. The software industry is developing by leaps and bounds, and various mobile phone applications are emerging in the mobile market one after another. The wide variety and powerful functions of mobile apps have brought many conveniences to people's study and life. Among them, the intelligent electronic dictionary search system is widely used in foreign language learning, providing a lot of help for English learning. Based on this, this article studies the application of the intelligent electronic dictionary search system in English writing. This article takes H University English translation students as the research object, and explores the current situation of college students' use of the intelligent electronic dictionary search system through questionnaire survey and interview methods. The results of the survey showed that 68.77% of the students thought it was helpful to the question "the intelligent electronic dictionary search system is helpful for expanding vocabulary, removing obstacles to English writing, and improving English proficiency". Finally, this article describes the key functional modules and implementation process of the intelligent electronic dictionary search system through the demand analysis of the intelligent electronic dictionary search system.
U-control Chart-Based Differential Evolution Clustering for Determining the Number of Clusters in k-Means

Data are critical sources in several organizations and therefore the efficiency of access to it, sharing, extracting information and making use of that information has become an urgent necessity. Currently, data mining is one of the most recognized fields of research and application for carrying out such tasks. In general terms, data mining is the process of extracting useful information, previously unknown patterns and trends, from large databases. The data mining has received a great impulse in the last times motivated by different causes: (a) the development of efficient and robust algorithms for the processing of large volumes of data, (b) a cheaper computational power that allows the use of computationally intensive methods, and (c) the commercial and scientific advantages that have offered this type of techniques in the most diverse areas (Silva et al in Procedia Comput Sci 151:1219–1224 [1], Dianne and Deborah in Interactive and dynamic graphics for data analysis: with R and Gobi [2]). This paper presents an evaluation from different perspectives of a number of relevant nonsupervised quality measures.
Modal Logics

Abstract This chapter introduces normal propositional modal logics, then non-normal systems which invalidate the Necessitation rule (N). It shows how to model these logics using non-normal or impossible worlds, thought of as ‘logic violators’. This approach comes with non-uniform truth conditions: some operators are understood in one way at normal worlds, in another way at non-normal worlds. This may or may not be a problem. The specific case of non-adjunctive and non-prime worlds are then discussed, where conjunction and disjunction can behave in unusual ways.
Framework of the Tourism Comprehensive Service Platform Based on Blockchain Technology

Blockchain is considered to be one of the most promising transformational technologies in the era of digital economy, but it is still in the initial stage in tourism industry. Toward this end, in this paper, we put forward a systematic framework of tourism comprehensive service platform based on the blockchain technology. We first analyze the problems of the current tourism industry and the value of blockchain to it. Then, we introduce the proposed platform in detail, including its component modules and advantages. Lastly, we discuss the limitations and development trends of the platform. This paper is aimed at providing helpful guidance and reference for future research efforts.
Non-Traditional Intervention Strategies for Improving the Teaching Effectiveness of Graduate Teaching Assistants

Schon, 1983) all underscore the need to improve the quality of instruction, especially at the undergraduate level.Since graduate teaching assistants (T As) play significant roles in the teaching of undergraduate courses, many research universities have increased their efforts to train graduate students to become more effective teachers.Bassett and Browning (1978) maintain that the future of
Genome Sequence Analysis in Distributed Computing Using Spark

Integration of Computer Science with Bio Science has led to new field Computational Biology which created an opportunity in speeding up the process of analyzing the Bio-data. DNA sequence analysis especially finding the base pairs that helps in identifying the order of nucleotides present in all living beings, it also helps in forensics for DNA profiling and parenting testing. This sequence analysis has been a challenging task in Computational Biology due to large volumes of data and need of more computational resources. Using a distributed file system with distributed computation of tasks can be one of the solutions to above problem. In this paper, the authors use Spark a query engine for large-scale data processing in analyzing the DNA sequence and extracting the base pairs and also they try to improve base pair extraction with improvised algorithms.
A Novel Method for Secure Outsourced in Cloud through KAE Authentication

Development of The cloud computing technology establishes a huge paradigm shift in the functional process of the IT industry. Since this new handling technology needs clients to believe in their useful information to reasoning providers, there have been enhancing security and comfort problems on shortened details. A few strategies using quality based security (ABE) have been prescribed for access administration of abbreviated subtle elements in thinking processing; be that as it may, the greater part of them experience from resoluteness in actualizing complex accessibility administration rules. The significant ones are capable of summing up with each other to develop vital variables and it could develop as traditional self-contained key, however covering the substantial number of keys being accumulated. In different terms, the key proprietor can discharge consistent size of separate key with proceedings of data for flexible alternatives of data that is composed of content set residing within the distributed storage space; however more significant and secured data documents which stay outside the set however kept classified. The lightly loaded overall key set could be the appropriate global pass to users which could be associated with a smart card with extremely confined safeguarded storage room. In our experiments evaluation official security examinations will provide to official cloud data storage events.
Introduction to Volume 13, Issue 1 of topiCS

We tend to talk about events, sort them, reason about them, and learn from them as if they were natural entities, endowed with a beginning and an end, with content, structure, and coherence. Yet how exactly do we recognize events as such and determine their boundaries? What allows us to carve them out from the continuous stream of sensorimotor experiences and turn them into meaningful units of conceptual thinking? If these questions are intriguing you, then this month's issue will be the place for finding answers and inspiration. For their topic “Event-predictive cognition: From sensorimotor via conceptual to language-based structures and processes,” Martin V. Butz (University of Tübingen, Germany), David Bilkey, and Alistair Knott (both at University of Otago, New Zealand) assembled a highly interdisciplinary set of amazing papers on our event-predictive abilities, ranging from their phylogenetic roots and their actual unfolding to the downstream implications for higher cognition, communication, and social interaction. Enjoy the reading! As I am taking over the responsibilities as Executive Editor, this topic is the first of several that I will be introducing, while the honor for having recruited these topics and following them through is due to Wayne Gray. My view and vision of topiCS is outlined in a welcome address in this issue; for Wayne's closing statement, see Gray (2020). We remind our readers that our publisher, Wiley, allows us to offer the Topic Editors' introduction to their topic to all of our readers as a free download. topiCS encourages letters and commentaries on all topics, as well as proposals for new topics. Letters are not longer than two published pages (ca. 400–1,000 words). Commentaries (between 1,000 and 2,000 words) are often solicited by Topic Editors prior to the publication of their topic, but they may also be considered after publication. Letters and commentaries typically come without abstract and with few references, if any. The Executive Editor and the Senior Editorial Board (SEB) are constantly searching for new and exciting topics for topiCS. Feel free to open communications with a short note to the Executive Editor ([email protected]) or a member of the SEB (for a list, see the publisher's homepage for topiCS: https://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1756-8765/homepage/EditorialBoard.html).
Curtailing the Threats to Cloud Computing in the Fourth Industrial Revolution

Cloud computing enables end users to make use of third party's resources to support their computing needs. The services offered by cloud computing make the technology very critical to the fourth industrial revolution. The benefits include cost minimization, scalability of services, speed, integration and higher data management, low innovation risk, and quicker response to organizational needs, among others. However, these benefits have been threatened by a number of security threats. This chapter seeks to curtail the effects of these threats by enlightening and educating users on the current ways to mitigate them. The chapter first defines cloud computing and highlights its relevance or benefits to businesses in the fourth industrial revolution. In addition, various security threats that are associated with cloud computing are brought to the fore. Thereafter, various measures that are used to mitigate the threats are discussed. The chapter concludes that with adequate enlightenment, the full benefits of cloud computing in industry 4.0 would be better enjoyed by users.
Mental Models

Creative problem solutions depend on how a person understands the performance domain at hand. Understanding of a performance domain is held to depend on peoples' mental models of how causes effect the outcomes observed in certain domains. This entry examines how mental models influence peoples' performance on creative problem-solving tasks. Included are descriptions of how people acquire viable mental models and how shared mental models contribute to the performance of teams working on creative projects. The implications of these observations for the assessment and development of creative potential are discussed.
RSN-GAN-Based Image Translation

A new image translation method is proposed to solve the problems existing in the current image translation models, such as the detail loss in the generated images and training instability. In this paper, ResNet is added to the generator network to solve the degradation problem in the process of deep network training through residual learning. After each convolution layer in the discriminator network, a spectral normalization layer is added to make the training of the network model more stable and improve the quality of the generated image. Experimental results show that, compared with other methods, the image generated by this model has better effect and lower FID.
Feature-Aided Tracking Techniques for Active Sonar Applications

Feature-aided tracking techniques seek to improve tracking performance by utilizing additional feature information from detections in combination with the typical kinematic measurements such as bearing, range, and Doppler. In this paper, we explore three techniques primarily based around measured signal-to-noise ratio and target strength: single-ping scoring, state augmentation, and composite confirmation logic. Through simulated active sonar scenarios, we demonstrate tracking performance improvements through these techniques which include both improvement in both target and track completeness.
Signature primitives

In cryptography, a ring signature is a type of digital signature, which can be used by any member of a user's group that each have keys. Therefore, a message signed with a ring signature is endorsed by someone in a particular group of people. To enhance the privacy and anonymity of transactions, some advanced signature primitives such as ring signature and multisignatures are widely used. In this chapter, we discuss the ring signatures, one-time signatures, multisignatures, Borromean ring signatures in detail. The detailed working and functionality of these signature primitives are described.
Advance GA Operators and Techniques in Search and Optimization

Genetic algorithms (GAs) are the latest technique to solve problems. A huge amount of research work is available but still there are a lot of newer avenues which have to be explored. In this chapter, the authors discuss variations in the GA operators that can be done and various other background operators that can be use to improve the efficiency and efficacy of GAs. It is not just like a mathematical or statistical technique. In this chapter, the authors discuss various procedural variations, twists and turns, and special meaning they could give to the GA operators in order to improve the solution quality. These newer operators and variations might be useful for researchers in the implementation of GAs to find better solutions.
Multi-objective Optimal T-S fuzzy Controller of Nonlinear Permanent-Magnet Synchronous Motor for Speed Tracking

This paper investigates the multi-objective control of the nonlinear permanent magnet synchronous motor (PMSM) system. To this end, the T-S fuzzy approach is introduced to tackle the synthesis of the speed control under nonlinear dynamics. Then, a novel multi-objective bat algorithm (NMOBA) is proposed for optimizing the constructed T-S fuzzy controller. Specifically, the virtual desired variables are utilized for developing the fuzzy tracking control to trace the desired speed profiles. Theoretical analyses demonstrate that the proposed control strategy can simplify the nonlinear controller design. Furthermore, the challenge in the optimization of the T-S fuzzy controller is addressed, that is, complex adjustable parameters usually lead to multiple local optima. To avoid premature convergence without losing efficiency, the hybrid mechanism is designed for the proposed NMOBA to enhance convergence and diversity of the swarm. Experimental results on a real-world PMSM system illustrate that the proposed controller has a significant advantage over the traditional LMI-based T-S fuzzy controller.
Uncertainties in Galilean Spacetime

State estimation plays an important role in various types of systems, such as moving object tracking in the field of robotics and autonomous driving. The correct and accurate representation of the state has a huge impact on the estimation results in terms of accuracy and reliability. An elegant way for the encapsulation of the Euclidean state vector is the use of Lie groups, which allows appropriate handling of the associated uncertainties. Although better results are obtained compared to working in the Euclidean space, the commonly used representations such as the special Euclidean group exclude one important part: uncertainty in time. In this paper, we investigate this aspect and look at the problem of state estimation of moving objects from a different perspective. We propose the Galilei group as an elegant way of state representation and analyze the effect of uncertainties of the separate parameters on an object’s state represented as an event in spacetime. To show the practical applicability, we derive the necessary equations for the integration of our novel representation into an extended Kalman filter to serve as the basis of an object tracking scenario.
Exploring the Role of Mobile Learning in Global Education

This chapter describes the current trends of mobile devices in education, the applications of mobile technologies in learning, the overview of Mobile Learning (m-learning), and the importance of m-learning in global education. M-learning encourages both blended learning and collaborative learning, thus allowing the learners at different locations to get in touch with their peers or others teams to discuss and learn. The m-learning environment is about access to content, peers, experts, portfolio artifacts, credible sources, and previous thinking on relevant topics. Given the convenience of m-learning, there is less time spent getting trained, and the overall costs are lowered as a results. With m-learning, learners are able to learn in their own style at their own pace. M-learning provides easy access to the learning at any place and any time, which is more convenient to the learners.