Reviewerly/exHarmony huggingface dataset:
Measuring Security

The researchers have been focusing on embedding security from the early phases of software development lifecycle. They have researched and innovated a field of Security Engineering where security concerns are embedded during requirement, design, and testing phases of software development. Efforts were made in developing methods, methodologies, and tools to handle security issues. Various methods are present in the literature for eliciting, analyzing and prioritizing the security requirements. During the design phase based on prioritized requirements, environment parameters and attribute a suitable security algorithm mainly cryptography algorithms are identified. Then a question arises how to test the effectiveness of chosen algorithm? Therefore, as an answer to the issue in this paper, a process for Security Testing is presented that evaluates the selected security algorithms. Evaluation is done by generating the test scenarios for functionalities using sequence diagram representing the threats at vulnerable points. Then, checking the mitigation of potential threats at identified vulnerable points. A security index is generated which shows the effectiveness of deployed/ chosen security algorithm. The process ends with the generation of a test report depicting the testing summary. For a clear understanding of the process, the proposal is illustrated with a case study of the cloud storage as a service model.
Distributed System Implementation Based on “Ants Feeding Birds” Algorithm

Evolving technologies are intricately woven into the fabric of social and institutional systems. With the invent of “Internet of Everything (IoE)” concept it is realistic now to employ animals and or humans to transmit details electronically. IoE concepts with sensor technology can prove wonders in any domain for that matter starting from eFarming, eHealth, eCare and what not. Humans can transform electronics by using various eConnected gadgets also motivated due to or based on “Nature Inspired Algorithms”. The confluence of IT, psychology with non-IT systems will be part of new generation's life. Such collaborative concept can be implemented practically with the help of “Cloud-to-Dew-Computing” based technologies. To include so many concepts together, it is essential to concentrate also on Cyber Security and Risk associated with such conceptual implementation. Dew-Computing at root levels will take care of Cyber Security effectually. Dew-Computing being backend support of Distributed System, can process multiple entities resourcefully. “Animal Data Interchange Standards” are very well considered innovative business opportunity these days and for years to come. These standards have started their work focusing on the Dairy related animal standard. Every dairy animal should enjoy life to remain healthy and more productive. Incremental Learning about Animal Life Data and Animal Identification, behavior, seasonal-changes, health etc. can be easily achieved with IoE.
CommuniMents

Social media has revolutionized human communication and styles of interaction. Due to its effectiveness and ease, people have started using it increasingly to share and exchange information, carry out discussions on various events, and express their opinions. Various communities may have diverse sentiments about events and it is an interesting research problem to understand the sentiments of a particular community for a specific event. In this article, the authors propose a framework CommuniMents which enables us to identify the members of a community and measure the sentiments of the community for a particular event. CommuniMents uses automated snowball sampling to identify the members of a community, then fetches their published contents (specifically tweets), pre-processes the contents and measures the sentiments of the community. The authors perform qualitative and quantitative evaluation for a variety of real world events to validate the effectiveness of the proposed framework.
The Role of Feedback in Software Process Assessment

Processes encapsulate the way organizations are doing business. However, in many cases organization processes are not well defined, which leads to poor and unsystematic implementation. An organization that uses weak or misdirected processes will have weak products or services, and unpredictable outcomes of business activities. Process assessment can help software organizations to improve themselves through identification of critical problems and establishment of improvement priorities. Software process assessment includes feedback as a core activity that aims at feeding data back to relevant individuals or groups in an organization. Feedback is also used as a method for learning in software organizations based on the previous experience and identified issues in the assessment process. In addition, information included in the feedback can be used as the basis for decision making related to revealing the next activities in assessment and improvement project.
Quantum Cryptography

Quantum communication is the most advanced area of quantum information processing and quantum computing. This is where the most fundamental features of quantum mechanics are only a short step away from spectacular practical applications. We have already seen two such applications: Dense coding and teleportation. In this chapter we shall deal with what is arguably the most successful area of all of quantum information and quantum computing: Quantum cryptography.
Computing, Data Science and Other Skills For Managers

Managers are required to have different skills and mindset in order to be successful nowadays. Business schools around the world contributed to the standardisation of knowledge and practices in the managerial environment, with MBA programmes being a must in every leader's curriculum. However, times are changing rapidly, and traditional knowledge around accounting or strategy models and tools need to be updated to consider the innovation brought in by technology. Concepts related to data, such as data science and big data, have intrigued a huge number of people around the world. Numbers are said to be an extensive source of knowledge, invaluable to those who want to improve processes, experiences, and efficiency in general. In this chapter, the authors discuss the new skills managers should learn to try have a better understanding of the subjects, fields, or abilities recruiters are looking for. Thus, we should still read this required expertise in conjunction with other soft skills linked to emotional intelligence and leadership techniques.
Association Rules

Association rules mining is an unsupervised machine learning method to discover interesting and unexpected patterns between attributes in datasets. Association rules—and its first step, frequent pattern mining—have been a popular data science technique for almost three decades. As it was originally popularized in retailing applications, it is often also referred to as market basket analysis. This chapter will introduce the concept of association rule mining and discuss potential applications to cryptocurrency blockchain data: what kind of pre-processing is necessary to transform the data to be compliant to typical inputs of association rules mining and what kinds of patterns could be found with this approach?
Grover Algorithm

The Grover algorithm is a quantum algorithm that provides a polynomial speedup compared to classical algorithms for searching a database. This algorithm could also be used to solve problems with NP complexity.
Awareness

Awareness is a term used to describe an individual's knowledge of a topic. One would expect that awareness of the cybersecurity threat is well understood because of the continual reports of cyber incidents and attacks impacting individuals, organizations, and cyber-attacks on communities and states. The CIAS found it was true that people understood cyber incidents and attacks were happening. They also understood they needed to protect their assets and information, and they needed to be able to respond and recover from incidents that might occur. The significant gap was they did not understand all the impacts that could occur from a cyber incident, and they didn't understand the cascading impacts that could domino from a single attack. The lessons learned regarding awareness are incorporated into the awareness dimension of the CCSMM and include what each member of a community needs to know based on their role in the community.
Frequentist Probability

Frequentist probability is historically presented as an attempt both to overcome the limitations of classical conception and to take into account the impressive development of experimental sciences and statistics. It is precisely because of this close link with the statistical sciences that it finds a significant place in teaching. It is also an area in which the use of IT tools is crucial. This approach also makes it possible to calculate the probability of events and from it we derive the same rules examined in the classical definition, since it is sufficient to replace the ratio between the number of favorable cases and the number of possible cases with the limit of the ratio when the repeated tests tend to infinity. One of the fundamental concepts appears in the chapter, that of a random variable capable of describing events and their distribution.
A Discussion of the Mapping from the Unified Search Space to the Search Space of the Optimized Task in Evolutionary Multitasking Optimization

Multitasking evolutionary algorithms enable the communication of information between different tasks and the mining of valuable knowledge by encoding all individuals into a unified search space. The mapping of decision variables of the same dimension for different tasks in the unified search space has the same dimensional index, i.e., the same encoded position. In this paper, we disrupt this mapping relationship so that decision variables of the same dimension for different tasks correspond to different encoded positions in the unified search space, to analyze and discuss the effect of this mapping relationship on the performance of the algorithm. A series of experimental results suggest that the mapping relationship between the decision variables of different tasks in a multitasking evolutionary algorithm has a significant impact on the performance of the algorithm.
Method of Feature Selection via the Feature Ensemble Clustering and Selecting

Clustering the feature into clusters and selecting the representative features from the clusters is often used in the method of feature selection. However, the current clustering ensembles cannot reduce the effects of certain base clustering, which would degrade the accuracy of the final result, and the feature information and redundancy between features are not fully considered for the existing method. The method of feature selection via the feature ensemble clustering and selecting is constructed to tackle the challenge. The ensemble clustering with adaptive weighted adjustment is developed to reduce the impact of the noise on the clustering ensemble, and centrality-entropy score is provided to help selecting the representative features in the obtained cluster. Extensive experiments on real data set are conducted to demonstrate the effectiveness and the superiority of the proposed method.
Surveillance Data Secure Transmissions

In this chapter, we will introduce fundamental knowledge of network communications including the infrastructure of computer networks as well as network security, monitoring, and forensics; we also analyze scrambling and descrambling techniques in data security; finally, we will review the technologies of data secure transmissions over the InternetInternet and IntranetIntranet. By the end of this chapter, we hope the major components of surveillance data transmission could be critically compared and evaluated.
The Cost of Managing Information

This chapter focuses on budgets, financial decisions, and costs to support your information strategy. The chapter explains the basic types of costs to consider and how costs are treated from a cost accounting perspective.
Aspect-Based Sentiment Analysis of Online Product Reviews

Sentiment analysis is a part of computational linguistics concerned with extracting sentiment and emotion from text. It is also considered as a task of natural language processing and data mining. Sentiment analysis mainly concentrate on identifying whether a given text is subjective or objective and if it is subjective, then whether it is negative, positive or neutral. This chapter provide an overview of aspect based sentiment analysis with current and future trend of research on aspect based sentiment analysis. This chapter also provide a aspect based sentiment analysis of online customer reviews of Nokia 6600. To perform aspect based classification we are using lexical approach on eclipse platform which classify the review as a positive, negative or neutral on the basis of features of product. The Sentiwordnet is used as a lexical resource to calculate the overall sentiment score of each sentence, pos tagger is used for part of speech tagging, frequency based method is used for extraction of the aspects/features and used negation handling for improving the accuracy of the system.
The Hidden Costs of Cross-Cultural Documentation

A way to reduce translation costs, as suggested by localization service providers, is using Machine Translation and Translation Memory Software (TMS). Based on experience in editing localized documentation, this study shows some localization pitfalls and their indirect costs. TMS tools reduce some translation costs by identifying and reusing already translated text. Saving 30% of the costs apply to the whole localization cost but exclusively to the translation costs, that is, to 50% of the localization budget. Running a PP only saves translation costs because it translates in only one language and then fixes the bugs before launching the translation in other languages, it also saves a large number of expensive engineering hours. Apart from the translation costs of its site and the pertinent documentation, the ISP was faced with legal costs both in the United States and in Europe, not to mention loss of image.
Security Analysis

Proving the security of a quantum key distribution protocol is crucial with regard to using the protocol in any practical application. Without a security proof one cannot be sure that the created key can safely be used for communication tasks. The security analysis of a quantum key distribution protocol involves several steps: the final goal is to make a security claim about the protocol. For this purpose, it is necessary to first give a precise definition of what we mean by “security”. To arrive at the security claim, we first clarify the assumptions that we make for the protocol in question. There are some assumptions we have to make independent of the protocol (e.g., that quantum mechanics is correct), but others are very specific, such as a claim about the efficiencies of the included detectors. Furthermore, we need to clarify what kind of attacks Eve can perform. A general security proof should take into account the most powerful attacks that she can do. Starting from these assumptions we can formulate the security proof. This proof can take different forms, depending on the assumptions we make, the protocol we use, and what kind of techniques are applicable.
ELECTRONIC COLLECTION «VILLAGE DOVOLNOE IN PRESS» AS A MEANS OF PRESERVING AND PROMOTING LIBRARY LOCAL-LORE RESOURCES

The article justifies the need to create an electronic collection «Village Dovolnoe in press» to ensure preservation and promotion of local culture heritage as a part of historical and cultural heritage of the country. It examines the descriptions of the most important project solutions for the creation of the collection. It presented a description of functions performed by the collection.
Association Rule Mining II

This chapter is concerned with a special form of Association Rule Mining known as Market Basket Analysis, the most common application of which is to relate the purchases made by the customers in a shop. An approach to finding rules of this kind, with support and confidence measures above specified thresholds, is described. This is based on the idea of supported itemsets. The Apriori algorithm for finding supported itemsets is described in detail. Further rule interestingness measures, lift and leverage, which can be used to reduce the number of rules generated are introduced.
Efficient Energy Saving Cryptographic Techniques with Software Solution in Wireless Network

To reduce communication costs, to protect our data from eavesdropping and from unauthorized users, cryptographic algorithms are used. Cryptographic module has to be developed for combining the operation of compression and encryption synchronously on the file. The information file is preliminary processed and then converts into one intermediary form so that it can be compressed with better efficiency and security. In this paper an optimized approaching coding technique which deals with both the issues of size and security is introduced and characterized experimentally using the performance measurement approach java in which file of any data length can be practically compressed and encrypted using new encryption technique and a novel energy saving technique in wireless communication network with efficient hardware solution is presented. To improve the strength and capability of algorithms and to compress the transmitted data an intelligent and reversible conversion technique is applied.
Integrating Residual Network and Channel Attention Mechanism for Tire Pattern Image Retrieval

Tire pattern image retrieval is important in obtaining useful clues for criminal case solving and traffic accident control. For complex deep learning models, the increase of the number of hidden layers can improve the model performance to a certain extent, but complex network architecture may cause the difficulty in network training, resulting in low retrieval efficiency. The use of residual blocks in residual networks can relieve this problem. To further improve the accuracy of tire pattern image retrieval, this paper combines a modified residual network with attention mechanism and proposes a novel tire pattern image retrieval model. A modified residual network is used for feature extraction, and a channel attention mechanism is added in the four convolution blocks (conv2-conv5) for feature selection. This method not only reduces the training parameters and make the model simpler, but also facilitates the extraction of more accurate tire pattern image features. Simulation results demonstrate the effectiveness of the proposed algorithm.
Object-Based Surveillance Video Synopsis Using Genetic Algorithm

Video synopsis provides representation of the long surveillance video, while preserving the essential activities of the original video. The activity in the original video is covered into a shorter period by simultaneously displaying multiple activities, which originally occurred at different time segments. As activities are to be displayed in different time segments than original video, the process begins with extracting moving objects. Temporal median algorithm is used to model background and foreground objects are detected using background subtraction method. Each moving object is represented as a space-time activity tube in the video. The concept of genetic algorithm is used for optimized temporal shifting of activity tubes. The temporal arrangement of tubes which results in minimum collision and maintains chronological order of events is considered as the best solution. The time-lapse background video is generated next, which is used as background for the synopsis video. Finally, the activity tubes are stitched on the time-lapse background video using Poisson image editing.
Enhanced Knowledge Graph for True-false Question Generation: A Case Study in Computer Networks Course

Knowledge graph provides an ideal technical means to automatic question generation. The classical knowledge graph contains direct relationship between entities and their attributes, but it is difficult to contain implicit logical relationships, like evolution, analogy and causality. This is not conducive to the generation for logical questions. In this paper, we analyzed true-false question features in computer networks course and classified questions into three types: fact discrimination(FD), conception discrimination(CD) and logic discrimination(LD). In order to generate these three types of question, we propose an enhanced knowledge graph (E-KG). By upgrading model layer and data layer, we can use inheritance relationship to describe knowledge points from the same knowledge domain. This helps to find analogical knowledge more conveniently. We label the implicit logical relationships between entities and use reference sentence to support and explain these logical relationships. Finally, we construct an E-KG by using computer networks knowledge and analysis the true-false question generated by our E-KG to verify the help of E-KG with question generation.
Path Planning in a Mobile Robot

This chapter presents the development and implementation of three approaches that contribute to solving the mobile robot path planning problems in dynamic and static environments. The algorithms include some items regarding the implementation of on-line and off-line situations in an environment with static and mobile obstacles. A first technique involves the use of genetic algorithms where a fitness function and the emulation of the natural evolution are used to find a free-collision path. The second and third techniques consider the use of potential fields for path planning using two different ways. Brief descriptions of the techniques and experimental setup used to test the algorithms are also included. Finally, the results applying the algorithms using different obstacle configurations are presented and discussed.
Application of Multimedia Technology and Remote Online Video in Interactive Practice System through Computer Internet

The article is based on the computer Internet technology and uses the Struts framework technology to design and implement the system design and implement a set of supporting systems for college English classroom teaching. The article presents requirements analysis, overall design, database design, source code and running results. The system test results show that the system can well adapt to the actual characteristics of college English open teaching and meet the needs of college English teaching auxiliary functions.
The Ions

The typical choice of ion for trapped ion quantum computing are earth-alkalis, volatile metals or lanthanides with a full s-orbital. Thus, after single ionization, one loosely bound electron remains in the outermost shell in a hydrogen-like configuration. Further criteria are fundamental limits for errors and technical constraints. When using several species in one trap the compatibility of the species is also relevant.
An Improved C<sup>2</sup>oDE based on Stochastic Ranking: A Further Study

Constraint Handling Techniques plays an important role when solving Constrained Optimization Problems. In the previous paper, an improved constrained composite differential evolution (C <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> oDE) based on stochastic ranking (SR) is proposed with the aim to check if some other combinations of CHTs can be more effective during the two phases of C <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> oDE. This paper further studies the effect of the selection probability P <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">f</inf> in SR with problem characteristics considered. Experimental results confirm the corresponding relationship between problem characteristics and P <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">f</inf> , which can give some inspiration when designing new algorithms.