Reviewerly/exHarmony huggingface dataset:
Constructing the Mode of "Four-in-One" Software Engineering Master Training Based on Artificial Intelligence

Building a "Four-in-One" software engineering master's cultivation model based on artificial intelligence is an inevitable requirement of the development of the times and the realization of industrial development. However, due to the outdated cultivation mode of the Master of Artificial Intelligence Software Engineering, there are few or no courses related to artificial intelligence in terms of curriculum setting, and the textbooks are not updated in time, which makes students lack of grasp of cutting-edge knowledge and scientific research methods. In terms of scientific research practice, it is simple in form and low in technology content, which leads to the insufficiency of students' comprehensive engineering application ability, and becomes the bottleneck of the cultivation of senior talents in software engineering under the background of artificial intelligence. With four modules of scientific selection system, multi-module curriculum system, practical training system and school-enterprise cooperation mechanism, the "Four-in-One" training mode is constructed to cultivate high-level, open, compound and international software talents.
Role of Security Mechanisms in the Building Blocks of the Cloud Infrastructure

This chapter describes how security plays a vital role in cloud computing, as the name itself specifies the data can be stored from any place and can be owned by anyone. Even though the cloud offers many benefits such as flexibility, scalability and agility, security issues are still backlog the cloud infrastructure. Much research is being done on cloud security equal to the scheduling problems in the cloud environment. The customers under the cloud providers are very concerned about their data, which has been stored in the cloud environment. In this regard, it is essential for a cloud provider to implement some powerful tools for security, to provide a secure cloud infrastructure to the customers. Generally speaking, there are some foundational needs to be attained and some actions to be combined to ensure data security in both cloud, as well as, non-cloud infrastructure. This book chapter concentrates only on the security issues, security measures, security mechanisms, and security tools of the cloud environment.
Mathematical Preliminaries

This chapter presents various mathematical preliminaries which are used for performing watermarking methods for different embedding and extraction processes. This chapter presents some commonly used terminologies used in watermarking, including basic types of audio signals, discrete cosine transform, discrete wavelet transform, singular value decomposition, fast discrete curvelet transform, finite ridgelet transform, non-subsampled contourlet transform, random noise generator, Arnold scrambling, compressive sensing (cs)-based encryption, audio watermarking attacks, and evaluation parameters for audio watermarking.
Long-term Electronic Archives: Modernization and Integration

Electronic archives are more than just “paper based” funds transferred into digital form. The task of forming a qualitative source base for historical research is solved in these projects on the basis of interdisciplinary interaction of computer science and humanities. One of the longterm projects at the IIS SB RAS is a creation of a methodology and technologies for the formation, use and support of electronic archives. Here are information systems of historical orientation that were created on the basis of the solutions described in this paper: the Electronic Archive of Academician A.P. Ershov, Photo Archive of the Siberian Branch of the Russian Academy of Sciences, Archive of the newspaper “Science in Siberia”, Open Archive of SB RAS, etc. Each of these resources has its own specifics, but in general, their documentary and information fund is based on the general social and territorial basis of scientific and social activities of the Siberian Branch of Academy of Sciences of the USSR/RAS and Novosibirsk Akademgorodok. In this report we will look into the general problems of creating electronic archives, relevant technologies, and architectural solutions. Some approaches to the integration/disintegration of isolated electronic resources are given on the examples of our electronic archives and on the basis of generally accepted and created tools. We will also examine the experience of using proprietary and open source software, their advantages and weaknesses.
Alignment Analysis of English Chinese Bilingual Corpora based on CRFS Model

Bilingual corpus alignment analysis, as an important research method of machine translation, is of great value as a source of translation knowledge. In view of this, this study carries out the research on English Chinese bilingual corpus alignment based on CRFs model. That is, on the basis of chunk aligned corpus, combined with the respective language characteristics of English and Chinese, the word alignment between chunks is realized with the help of CRFs model. The results show that the accuracy and recall of maximum entropy are 45.77% and 45.58% respectively, the accuracy and recall of log linear model are 45.73% and 45.68% respectively, while the accuracy and recall of CRFs model are 47.99% and 47.94%. It indicates that CRFs model can effectively alleviate the asymmetric problem of English and Chinese database alignment, also the alignment error rate of CRFs model is reduced accordingly. Therefore, it has a good effect on the alignment of English and Chinese bilingual corpora.
Prediction of Diabetic Patient Readmission Using Machine Learning

Hospital readmissions pose additional costs and discomfort for the patient and their occurrences are indicative of deficient health service quality, hence efforts are generally made by medical professionals in order to prevent them. These endeavors are especially critical in the case of chronic conditions, such as diabetes. Recent developments in machine learning have been successful at predicting readmissions from the medical history of the diabetic patient. However, these approaches rely on a large number of clinical variables thereby requiring deep learning techniques. This article presents the application of simpler machine learning models achieving superior prediction performance while making computations more tractable.
Fraud threat to biometrics: shedding light on the dark web

The encrypted and anonymous nature of the dark web makes it an ideal host for fraudulent activities for one simple reason: it can't be accessed by standard browsers or search engines. To effectively combat the threat fraudsters pose to biometric-based and related authentication systems, researchers need to understand hackers' tactics and their mindsets. And to do this, they need to be where the fraudsters are – in the dark web. Here we interview Ido Rozen, from biometrics fraud detection specialists SecuredTouch, to find out how white-hat researchers can infiltrate the dark web, and the key threats they are finding. On page 7 Noa Benari of SecuredTouch explains how behavioural biometrics can mitigate these threats.
Introduction

This chapter presents the motivation, objective, and structure of the book. This book sheds light on the progress made in empowering women in Africa over the last decade and the challenges that remain. It contributes to the discourse on women’s empowerment in Africa by providing a fresh perspective and strong multidisciplinary research evidence on diverse, timely, and relevant gender issues in various (and contextually different) African countries. The book is a collection of literature reviews, empirical studies, and policy discussions that inform policymakers and academics who are interested in the fifth Sustainable Development Goal. The chapters focus on the following issues: (1) climate change and gender, (2) women’s land rights and agricultural productivity in East Africa, (3) maternal health and education, (4) labour market participation and unpaid care work, (5) women’s bargaining power and their households’ well-being, and (6) women in politics and society. Crosscutting issues such as domestic violence, migration, discriminatory social norms, and harmful practices are also addressed in some of the chapters.
A Taxonomy of Data Mining Problems

Much of the research in data mining and knowledge discovery has focused on the development of efficient data mining algorithms. Researchers and practitioners have developed data mining techniques to solve diverse real-world data mining problems. But there is no single source that identifies which techniques solve what problems and how, the advantages and limitations, and real-life use-cases. Lately, identifying data mining techniques and corresponding problems that they solve has drawn significant attention. In this paper, the author describes the progress made in developing data mining techniques and then classify them in terms of data mining problems taxonomy to help assist practitioners in using appropriate data mining techniques that solve business problems. This will allow researchers to expand the body of knowledge in this discipline. This article proposes a data mining problems taxonomy based on data mining techniques being used. Prominent data mining problems include classification, optimization, prediction, partitioning, relationship, pattern matching, recommendation, ranking, sequential patterns and anomaly detection. The data mining techniques that are used to solve these data mining problems in general fall under top 10 data mining algorithms.
Emergent Pathways for the Future of Instructional Design

This monogram aims at providing an overview of the entire field of instructional design, starting with a brief historical account of the field but focusing on current and promising trends for the future of instructional design based on advances in instructional technology and human-computer interaction capabilities. The discussion encompasses several parallel trending areas, such as adaptive learning, digital storytelling, gamification, simulation technologies, augmented reality, cybernetics, the xAPI standard, mobile and ubiquitous learning, as well as implications of these trends for the field from both the theoretical and practical point of view. Even though this discussion is by no means an exhaustive account of these trends, it is the aim of this monogram to provide a centralized literature review of multiple paths currently being carved in the field and a glimpse to a multiplicity of potential futures for all those involved in designing and delivering learning or effecting human behavior and performance change.
Errors in Figure Label and Caption

in 2017 1 and 2018, 2 in which I declared nothing to disclose.In my previous reporting, I included disclosures of potential conflicts of interest that seemed "reasonably related" to the topic of the article, as suggested in guidance by the International Committee of Medical Journal Editors (ICMJE).Consequently, I included my status as an independent board member of Johnson & Johnson in articles that focused on drug or device payment or regulation, and I included my activities related to accountable care organizations and other specific provider payment reforms in articles that focused on those topics.These activities are publicly known.To promote transparency, I also provide information on my activities on my web page. 3 For completeness and to avoid confusion, I
Quantum mechanical four-dimensional non-polarizing beamsplitter

Abstract Some quantum optics researchers might not realize that classical electromagnetism predicts a $$\mathbf {\pi }$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>π</mml:mi> </mml:math> phase shift between S- and P-polarized reflection and might think the reflection coefficients of the transverse modes are independent, or that such a phase shift has no measurable consequences. In this paper, we discuss theoretical grounds to define elements of a 4x4 matrix to represent the beamsplitter, accurately accounting for transverse polarization modes and phase relations between them. We also provide experimental evidence confirming this matrix representation. From a scientific point of view, the paper addresses a non-trivial equivalence between the classical fields Fresnel formalism and the canonical commutation relations of the quantized photonic fields. That the formalism can be readily verified with a simple experiment provides further benefit. The beamsplitter expression derived can be applied in the field of quantum computing.
Differential Privacy Approach for Big Data Privacy in Healthcare

This chapter presents a survey of the most important security and privacy issues related to large-scale data sharing and mining in big data with focus on differential privacy as a promising approach for achieving privacy especially in statistical databases often used in healthcare. A case study is presented utilizing differential privacy in healthcare domain, the chapter analyzes and compares the major differentially private data release strategies and noise mechanisms such as the Laplace and the exponential mechanisms. The background section discusses several security and privacy approaches in big data including authentication and encryption protocols, and privacy preserving techniques such as k-anonymity. Next, the chapter introduces the differential privacy concepts used in the interactive and non-interactive data sharing models and the various noise mechanisms used. An instrumental case study is then presented to examine the effect of applying differential privacy in analytics. The chapter then explores the future trends and finally, provides a conclusion.
The Dynamic Data Privacy Protection Strategy Based on the CAP Theory

With the rapid development of cloud storage technology, the cloud storage platform has gradually been used to store data. However, the privacy protection strategy provided by public cloud storage platform is hard to be trust by users. Moreover, they are unable to customize their own storage strategy according to their demands. This study proposed a consistency-availability-partition tolerance (CAP) theory -based data privacy protection strategy, which firstly employed CAP theory to provide privacy data protection for users and then offer users with choice to select corresponding privacy strategy to store data. Moreover, a total of three privacy protection strategies were put forward, focusing on the balance between data consistency and response time, data consistency and data availability, as well as response time and availability respectively.
Robust Steganography over Noisy Channel

Steganography is accomplished by frequency or spatial domain. In spatial domain method, the important data are inserted directly into the image's pixels. Alternatively, the coefficients of the image frequency transform like DCT are used to carry the important data. Robustness in the presence of a noise is important. In this paper, the robustness over a noisy channel with noise like Added White Gaussian Noise (AWGN), salt and pepper noise and Speckle noise is investigated. The bit error rate is used for system evaluation. Simulation outcomes demonstrate that the frequency based model is stronger than spatial method against channel noise. Moreover, robustness is enhanced via using error correction.
Derivatives

In this chapter, derivatives as a product class are discussed. After explaining why derivative product knowledge and a derivative mindset is beneficial to anyone working in a sales, trading or research environment, the main derivative types are covered: forwards, futures, swaps and options. The main focus is set on developing an intuitive understanding of the functioning and the practical use of derivatives.
METHODOLOGY OF DEVELOPMENT OF MATHEMATICAL MODELS OF INFORMATION PROCESSING SYSTEMS

Modeling as a research method is a powerful cognitive tool throughout the history of human development. The article describes the methodology for the development of mathematical models of information systems, based on materials from various literary sources, author's developments on the system approach, mathematical modeling and programming. The mathematical model of the information system is described and all the characteristics of the IS are given.
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Nowadays the digital is on the basis of our daily life. Digital services are found in almost every area of public life: finance, industry, telecommunications, trade, security, as well as education with its entire system. It may be noted that the digital has led to a profound modernization of practice in the world of social sciences. The article highlights the potential strategic features of the digital in higher education, the role that the digital service plays in students' lives, and the success of student integration in that world. The article focuses on the digital as a teaching tool, as a key tool for future development. The article finally highlights the idea that the role of digital services is invaluable internationally.
Deep Neural Network for Speaker Identification Using Static and Dynamic Prosodic Feature for Spontaneous and Dictated Data

We can recognize a person by his voice alone. In principle, the sound has a tone (pitch) that is different for each person. This study aims to measure a Deep Neural Network (DNN) performance with static and dynamic prosodic features. Prosodic is information about sound related to tone, intonation, pressure, duration, and rhythm of a person's pronunciation. The data is dictated and spontaneous voice data that taken from YouTube. The data consists of three male voices and one female voice. The data is segmented into various duration, 3 seconds,5 seconds, and 10 seconds. After the data has been segmented, extracted static prosodic features with 103 dimensions and dynamic prosodic features with 13 dimensions. Each feature and feature combination are trained and tested using DNN with a ratio of 90:10. The result shows that the 10 seconds segmented data has higher accuracy than the others. Accuracy of static prosodic features is better than dynamic prosodic features. The average accuracy of DNN for static prosodic features is 87.02%. The average accuracy of DNN for dynamic prosodic features is 72.97%. The average accuracy of DNN for combined static and dynamic prosodic features is 87.72 %.
Opponent-Restricted Response Solving on Texas Hold’em Poker

Knowing the enemy and yourself, you can fight a hundred battles and win them all. For an unknown opponent, nash equilibrium may be a useful strategy to not lose on a worst-case situation. However, when we have opponent’s estimated model, developing an exploitive counter-strategy wins far beyond an nash equilibrium. But how to take performance maximizing strategy and keep least opponent’s best response value, is critical to compute a robust counter strategy. In this paper, we try to achieve higher expected payoff by modeling stationary opponent and developing an exploitive counter-strategy, instead of cautiously trying to consider worst-case to avoid lose, increasing winnings far beyond what a NE would win. In order to tradeoff between exploitability and exploitation, we combine explicit opponent model and CFR to develop a online robust counter strategy, and then evaluate on significant larger imperfect information game of no-limit Texas Holdem poker.
PVD Steganography Based on Correlation and Maximum Pixel Value Difference

In this chapter, the author describes the pixel value correlation-based steganography techniques and maximum pixel value difference-based steganography techniques. The pixel value-based correlation steganography techniques utilize the relationship among the pixel values of a block, whereas the maximum pixel value difference steganography techniques utilize the largest pixel value difference among different pairs of pixels in the block. Although the PSNR values of these techniques are better as compared to the traditional PVD schemes, the hiding capacity is not improved.
GPAS - Graphical Password Authentication System for Software Privacy Protection

Now daily's larger part of PC frameworks, passwords is the technique for decision for validating clients. A procedure by which a framework confirms the personality of a client is known as 'Confirmation'. Confirmation may likewise be summed up by saying that "to validate" signifies "to approve". Confirmation is the main line of resistance against trading off classification and uprightness. The most generally and normally utilized confirmation is conventional "Username" and "Secret phrase". For such verification by and large content (alphanumeric) is utilized. It is outstanding, in any case, that passwords are defenseless to assault: clients will in general pick passwords that are anything but difficult to recollect, and regularly this implies they are likewise simple for an assailant to get via hunting down hopeful passwords. Token and biometric based validation frameworks were presented as an option for those plans. Be that as it may, these plans are all around expensive. Consequently, Graphical plan was acquainted as a variety with the login/secret key plan. In this paper we investigate a way to deal with client confirmation that sums up the idea of a literary secret key and that, as a rule, improves the security of client verification over that given by printed passwords. In this proposed framework we have utilized another system for confirmation. It is a variety to the login/secret phrase plan utilizing graphical secret phrase utilized in a graphical way. We have presented a structure of our proposed Graphical Password Authentication System (GPAS), which is resistant to the basic assaults endured by other confirmation plans.
Design Challenges of Cloud Computing

Cloud computing has recently emerged as a new paradigm of computing for hosting and delivering services over the Internet. It replaces computing as a personal commodity by computing as a public utility. It is attractive solution to business owners as it eliminates the requirement for users to plan ahead for provisioning, and allows enterprises to start from the small and increase resources only when there is a rise in service demand. However, despite the significant benefits, these technologies present many challenges including lack of security. The chapter presents an advanced survey focusing on cloud computing concept. It highlights its key concepts and presents a physical architecture of this environment. Finally, the chapter defines virtualization technology as a factor for cloud computing surge and discuses security issues that damage these systems. The aim of this chapter is to provide a better understanding of the design challenges of cloud computing.
Optimized Test Case Generation for Object Oriented Systems Using Weka Open Source Software

Detection of fault proneness classes helps software testers to generate effective class level test cases. In this article, a novel technique is presented for an optimized test case generation for ant-1.7 open source software. Class level object oriented (OO) metrics are considered as effective means to find fault proneness classes. The open source software ant-1.7 is considered for the evaluation of proposed techniques as a case study. The proposed mathematical model is the first of its kind generated using Weka open source software to select effective OO metrics. Effective and ineffective OO metrics are identified using feature selection techniques for generating test cases to cover fault proneness classes. In this methodology, only effective metrics are considered for assigning weights to test paths. The results indicate that the proposed methodology is effective and efficient as the average fault exposition potential of generated test cases is 90.16% and test cases execution time saving is 45.11%.