Reviewerly/exHarmony huggingface dataset:
A Comprehensive Review of Access Control Mechanism Based on Attribute Based Encryption Scheme for Cloud Computing

Cloud computing is the most prevailing paradigm, which provides computing resources and services over the Internet. Due to immense development in services provided by cloud computing, the trend to share large-scale and confidential data on cloud has been increased. Though cloud computing provides many benefits, ensuring security of the data stored in cloud is the biggest challenge. The security concern about the data becomes main barrier for adoption of cloud. One of the important security aspects is fine grained access control mechanism. The most widely used and efficient access control scheme for cloud computing is Attribute Based Encryption (ABE). The Attribute Based Encryption (ABE) scheme provides a new technique for embedding access policies cryptographically into encryption process. The article presents an overview of various existing attribute-based encryption schemes and traditional access control models. Also, the comparison of existing ABE schemes for cloud computing, on basis of various criteria is presented in the article.
Protecting Commercial and Institutional Critical Infrastructure

This chapter focuses on protecting commercial and institutional critical infrastructure, specifically the Retail Subsector, Financial Services Sector, Educational Facilities Subsector, and the Healthcare and Public Health (HPH) Sector. These entities face a variety of vulnerabilities, and protection measures must be implemented. For the Retail Subsector, these subjects are explained: shrinkage, losses at the point-of-sale, electronic payments, e-commerce, fraud, counterfeiting, organized retail crime, shoplifting, robbery, and burglary. The Financial Services Sector content emphasizes government regulation of this industry and a variety of crimes against financial institutions and preventive measures. The Educational Facilities Subsector faces many unique challenges, especially the safety of people, that must be mitigated in grades K-12 and higher education. Content focuses on incidents such as assault, sexual assault, illegal drugs, and bullying. The HPH Sector is prone to violence in hospitals, especially in emergency rooms and mental health units. Departments also necessitating protection include the newborn nursery and pharmacy. All the entities covered in this chapter require cybersecurity and all-hazards protection.
A fast optimization method with the speed of light

By using purely resistive circuit, this paper proposes a fast optimization method that can obtain the optimal solution with the speed of light.
An interactive web-based visual analytics tool for detecting strategic eye movement patterns

In this paper we describe an interactive and web-based visual analytics tool combining linked visualization techniques and algorithmic approaches for exploring the hierarchical visual scanning behavior of a group of people when solving tasks in a static stimulus. This has the benefit that the recorded eye movement data can be observed in a more structured way with the goal to find patterns in the common scanning behavior of a group of eye tracked people. To reach this goal we first preprocess and aggregate the scanpaths based on formerly defined areas of interest (AOIs) which generates a weighted directed graph. We visually represent the resulting AOI graph as a modified hierarchical graph layout. This can be used to filter and navigate in the eye movement data shown in a separate view overplotted on the stimulus for preserving the mental map and for providing an intuitive view on the semantics of the original stimulus. Several interaction techniques and complementary views with visualizations are implemented. Moreover, due to the web-based nature of the tool, users can upload, share, and explore data with others. To illustrate the usefulness of our concept we apply it to real-world eye movement data from a formerly conducted eye tracking experiment.
A Study of Forensic Imaging to Evaluate “Unsanitized” Destination Storage Media

Best practices in digital forensics include a procedure to sanitize media on which forensic images will be stored, thus eliminating potential challenges that contamination of the evidence may occur due to data that exist on the media prior to storing forensic images. This article describes a research project to empirically evaluate the extent to which wiping destination storage media affects evidence. The authors specifically address whether the contents of forensic images differ in any way when written to a freshly wiped and formatted medium when compared to the images being written to a similar medium that had been populated with data and not wiped. They performed these experiments on different types of storage devices.
Application of Block Chain technology in Teaching

With the rapid development of high and new technology, especially information technology, modern education has entered the big data era under the condition of informatization. China’s education modernization 2035 points out that "promote the reform of education governance, accelerate the formation of modern education management and monitoring system, and promote accurate management and scientific decision-making". Using modern technology to promote the reform of decentralized teaching mode and the construction of a full chain education monitoring system to achieve accurate education and scientific management has become the basic trend of modern education development. Firstly, this paper analyzes the characteristics of Block Chain and the disadvantages of traditional teaching mode. According to the characteristics of Block Chain and integrating modern teaching mode, this paper puts forward new applications such as student achievement management, personnel management and teaching method management.
Character Recognition

This chapter presents in detail the processes involved in character recognition. The segmented characters are corrected using skew detection and correction. The combined approach of template matching and contour analysis is used to recognize the character wherein error corrections and improved local binary pattern will be applied. The components of this algorithm and their functions are discussed. In addition, the experimental outcomes of the framed technique are presented and collated with related methods in terms of recognition accuracy which is a means to examine the accuracy of the proposed algorithm.
Trajectory reconstruction algorithm for powered landing of reusable rocket

Aiming to resolve the large trajectory deviation situation of the reusable rocket in the powered landing phase, a trajectory reconstruction algorithm is designed. First, using highways to recover the reusable rocket is proposed. Then, the highway landing trajectory optimization problem is constructed using the six-degree-of-freedom reusable rocket model. For rapidness, the successive convexification algorithm is utilized to attain the road landing trajectory. Finally, the landing performance indexes are designed to evaluate the obtained trajectory, based on which the trajectory reconstruction algorithm is designed. According to the numerical experiments, the algorithm can improve the success rate of landing in the presence of large-scale trajectory deviation.
Academic Examples

This chapter, closing the series of presentations of application cases of the reverse clustering paradigm, is devoted to the experiments, related to more academic datasets, as compared to those presented before. The purpose was to analyse the characteristics of the reverse clustering approach for the cases, whose properties are either well known, or they can be easily derived just by visual inspection. Some of the characteristics of the reverse clustering that we intended to assess could not be effectively analysed with the empirical and applied datasets, considered in the preceding chapters. One of those was the case of "nested clusters", in which we were interested in identifying the parameters of the procedure, for which the consecutive "levels of nesting" or "of resolution" could be recovered. The basic conclusion from the experiments, reported in this chapter is that the key features of the expected solutions were obviously effectively identified by the approach, but the parameterisation and the related capacity of fine-tuning, especially regarding the subsequent levels of resolution, have definite limitations.
An approach to the integration-balanced management of industrial complexes development in the space industry

The relevance of this research is due to the necessity to identify the interconnections between the development level of the industrial complex of the megaregional space industry and the factors, which influence the integration processes in these scientific and production systems, which are notable for industrial and regional components. The analysis of current development problems in the space industry is done. There are disclosed number of opportunities for the optimization of integration processes in the megaregion. These processes provide a synergistic effect under conditions of adequate strategic management and assessment tools. It is concluded that the mechanism of integration-balanced management would increase the development efficiency of the industrial complex of the space industry.
Relevance of Web 2.0 for Library Services in Digital Era

The chapter examined relevance of Web 2.0 for library services in digital era. it has been concluded that Web 2.0 tools play crucial role in effective service delivery of librarians. The chapter covers awareness, utilization; benefits and challenges that affect the use of Web 2.0 by librarians for effective service delivery. The concepts generally implied that Web 2.0 can be used by librarians as information acquisition tools that are used to gather information from sources outside libraries (for example, blogs and wikis), information dissemination tools that are used to distribute content and information to patrons (such as RSS feeds), information organization tools that facilitate storage and subsequent retrieval of information (social bookmarking and tagging), and information sharing tools that facilitate the bilateral flow of information between libraries and patrons (social networking and media sharing sites. It was concluded that Web 2.0 tools play crucial role in effective service delivery of librarians. Therefore, librarians should be proactive in the adoption and use of upgrade of web 4.0 which is more current than Web 2.0 to become relevant in the digital era.
Research in Agricultural and Environmental Information Systems

Information systems relate to diverse applications, but, until recently, the use of this technology in agriculture and environment has been relatively behind the applications in the industrial sector. The publication of IJAEIS started in 2010 in order to promote the new research advances in information systems applied to agriculture and environment. This paper presents an overview of the different scientific issues presented in the 50 papers published in IJAEIS between 2010 and 2013. The authors summarize the different contributions presented in IJAEIS and the authors identify the main trends in the field of agricultural and environmental information systems (ontologies, communication systems, spatial information processing, etc.).
Pseudorandom processes

Pseudorandom numbers turned out to be very widely applicable substitutes of real random number sequences. In this paper we introduce pseudorandom processes that appear to be random but they just imitate certain properties of random/stochastic processes. This paper is only the first step in replacing random coins of random walks by trigonometric functions. More general functions (“coins”) lead to unexpected new challenges, e.g. in case of Haar coins.
Instant Messaging Chat Bot

Recently there has been a resurgence of chat bot use among businesses, which employ them as part of their marketing strategy. To provide better insight into instant messaging chat bots as a marketing tool, the present research focuses on mobile users' current understanding and perceptions of chat bots. This study examines what mobile consumers think of instant messaging chat bots, and whether consumers are willing to use the new chat bots. This study employs focus group interviews and online surveys to examine consumers' perceptions. The results indicate that a majority of mobile users have employed chat bots for customer service and for entertainment. Mobile users found instant messaging chat bots easy to use and useful, but not necessarily entertaining.
MSBiNN: Multi-scale Bipartite Graph Neural Network for Recommender System

In this paper, we propose a network structure called Multi-scale Bipartite Graph Neural Network(MSBiNN), which can make full use of the neighborhood information of nodes without scale (order). For the bipartite graph in the recommender system, we propose the Bipartite graph multi-scale residual block. We combine the convolution kernel and GAT (Graph Attention Network) technology in GCN (Graph Convolutional Network) reasonably and effectively, so that the learned representation vector can maintain the heterogeneity of the bipartite graph and integrate the information of neighbor nodes of different orders. Using attention mechanism, we perform weight distribution and feature aggregation on the output of each Bipartite graph multi-scale residual block. From the perspective of linear space, we explained the rationality of the attention mechanism used with the residual network. Multi-scale Bipartite graph neural network can effectively prevent feature disappearance and excessive smoothing. We have conducted experiments on different test sets of recommender systems. Through comparison with baselines, we have proved that our model has better results. At the same time, we explored the performance of each module of our model.
Is Ethereum better explained by Bitcoin and Ripple prices An ECM approach on the covid-19 episode price data

Bitcoin, Ethereum and Ripple are the three major cryptocurrencies with market capitalisation exceeding 70% of all the cryptos. The covid-19 threats since the beginning of the 2020 are disturbing the financial markets all around the world. This study is an enquiry to model the fluctuations among the three cryptocurrencies with the hypothesis that whether a combination of two coins could explain the changes in the other coin. The study found that Bitcoin and Ripple are better explaining the Ethereum returns in the short-run. The negative error correction coefficient found in the regression indicates that if the daily log returns of ETH is above that of the daily log return of BTC by one point, the daily log return of ETH fall by 1.11 point. On the other hand, the positive error correction coefficient indicates that if the daily log return of ETH is above that of the daily log return of XRP by one point, the daily log return of ETH increases by 0.14 point.
Energy and SLA Efficient Virtual Machine Placement in Cloud Environment Using Non-Dominated Sorting Genetic Algorithm

To increase the availability of the resources and simultaneously to reduce the energy consumption of data centers by providing a good level of the service are one of the major challenges in the cloud environment. With the increasing data centers and their size around the world, the focus of the current research is to save the consumption of energy inside data centers. Thus, this article presents an energy-efficient VM placement algorithm for the mapping of virtual machines over physical machines. The idea of the mapping of virtual machines over physical machines is to lessen the count of physical machines used inside the data center. In the proposed algorithm, the problem of VM placement is formulated using a non-dominated sorting genetic algorithm based multi-objective optimization. The objectives are: optimization of the energy consumption, reduction of the level of SLA violation and the minimization of the migration count.
Selection and implementation of a consortial e-resource management system: The University of Missouri System’s experience

Implementing effective Electronic Resource Management Systems (ERMS) is a continuing challenge for library consortia. The E-Resources Cooperative Office of the University of Missouri System identified a need to implement an ERMS to manage its consortially-licensed electronic resources more effectively, transparently and cooperatively. The author details the experience of selecting and implementing an ERMS to better meet the current e-resource management needs of member libraries and the consortium office. Leveraging the capabilities of an ERMS will also allow the consortium to more proactively engage in special projects and additional e-resources endeavors to benefit its members.
Privacy Preserving Feature Selection for Vertically Distributed Medical Data Based on Genetic Algorithms and Naïve Bayes

Machine learning is a powerful tool to mine useful knowledge from vast databases. Many establishments in the medical area such as hospitals, laboratories want to join their efforts with the ambition to extract models that are more accurate. However, this approach faces problems. Due to the laws protecting patient privacy or other similar concerns, parties are reluctant to share their data. In vast amounts of data, which are useful and pertinent in constructing accurate data mining models? In this article, the researchers deal with these challenges for vertically distributed medical data. They propose an original secure wrapper solution to perform feature selection based on genetic algorithms and distributed Naïve Bayes. Contrary to the previous solutions, the original data is not perturbed. Therefore, the data utility and performance are preserved. They prove that the proposed solution selects relevant attributes to increase performance, preserving patient privacy.
A Maturity Model for Understanding and Evaluating Digital Money

As the internet and e-commerce expands, individuals will seek ways to earn and spend currency in the digital economy. Furthermore, faith in the fiat money systems of some countries is eroding and investors are searching for alternative ways to invest and store their wealth. Digital currencies (DC) are filling the demand for an alternative to government-based currency. Currently there are over 1,500 DCs with a market capitalization of over 450 billion (in US dollars) that are traded in thousands of markets. This chapter reviews the literature and history of DCs. Then the authors explain the related risks and benefits. Next, they add to the literature by proposing a model for judging the maturity of a DC. The digital currency maturity model (DCMM) will help individuals and organizations evaluate the safety and reliability of DCs given the investor's risk tolerance. Finally, the authors summarize their findings and suggest future research.
Privacy Preserving Distributed K-Means Clustering in Malicious Model Using Verifiable Secret Sharing Scheme

In this article, the authors propose an approach for privacy preserving distributed clustering that assumes malicious model. In the literature, there do exist, numerous approaches that assume a semi honest model. However, such an assumption is, at best, reasonable in experimentations; rarely true in real world. Hence, it is essential to investigate approaches for privacy preservation using a malicious model. The authors use the Pederson's Verifiable Secret Sharing scheme ensuring the privacy using additively homomorphic secret sharing scheme. The trustworthiness of the data is assured using homomorphic commitments in Pederson's scheme. In addition, the authors propose two variants of the proposed approach - one for horizontally partitioned dataset and the other for vertically partitioned dataset. The experimental results show that the proposed approach is scalable in terms of dataset size. The authors also carry out experimentations to highlight the effectiveness of Verifiable Secret Sharing scheme against Zero Knowledge Proof scheme.
A Reliable Data Provenance and Privacy Preservation Architecture for Business-Driven Cyber-Physical Systems Using Blockchain

Cyber-physical systems (CPS) including power systems, transportation, industrial control systems, etc. support both advanced control and communications among system components. Frequent data operations could introduce random failures and malicious attacks or even bring down the whole system. The dependency on a central authority increases the risk of single point of failure. To establish an immutable data provenance scheme for CPS, the authors adopt blockchain and propose a decentralized architecture to assure data integrity. In business-driven CPS, end users are required to share their personal information with multiple third parties. To prevent data leakage and preserve user privacy, the authors isolate and feed different information retrieval requests using tokens specifically generated for each type of request. Providing both traceability of data operations, and unlinkability of end user activities, a robust blockchain-based CPS is prototyped. Evaluation indicates the architecture is capable of assured data provenance validation and user privacy preservation at a low overhead.
Secure Data Transmission with Access Control for Smart Home Devices

Smart home is a good exemplification of the Internet of Things (IoT). Many researchers study how to make smart home systems (SHS) smarter. However, the security of SHS is also worth studying as user's information is collected from the devices and security-sensitive data are communicated through an open network. Therefore, how to guarantee the security of the data transmission in SHS is an important problem. In this paper, we propose a new secure data transmission scheme with access control to protect the data transmission in SHS. In our scheme, data transmission is secured by a new cryptographic primitive called access control encryption (ACE). Different from other existing solutions in SHS, our scheme controls not only which messages smart devices can receive, but also which messages they can send. Our experimental results demonstrate the effectiveness and efficiency of our proposed mechanism.
Open Source Software Usage in Education and Research

Information technology and telecommunication is considered a new and quickly evolving branch of science. New technologies and services in IT and telecommunications impose successive changes and updates on related engineering majors, especially in practical qualification that includes using software facilities. This chapter aims to join the efforts to spread the use of open source software in academic education. The chapter consists of two main sections. The first presents the trend of using open source software in higher education and discusses pros and cons of using open source software in engineering education. The second section presents network traffic analysis as an example of recent effective research topics and provides a set of open source tools to perform the research's practical steps. The research example with the suggested tools is valid as practical lab work for telecommunication and IT-related majors.