Reviewerly/exHarmony huggingface dataset:
A Metagraph Model оf Cyber Protection оf аn Information System

The aim of this article is to present a developed metagraph model which serves to verify the minimum requirements for cyber security in web-based student information management systems. The model presents the correlation between cyber attacks and cyber defense of the system. The protection is based on a created model for cybersecurity 3-12 and is divided into 3 categories – software, server and information system users. The most common 9 cyber attacks on automated information systems have been selected. Twelve countermeasures to these attacks have been selected. The application of the metagraph model is used to check whether the system meets the requirements of the model 3-12. The developed information system has been tested in foreign language training of students at Nikola Vaptsarov Naval Academy. The developed metagraph model can be applied to other information systems.
Understanding Phenomena: Investigating Structure-Function Relationships

As Simon (1981) has pointed out, coming to characterize phenomena as functional systems is fundamental for our understanding of the natural and man-made worlds. Yet little is known about people’s propensities for making such characterizations. In contrast to previous research that has focused on unfamiliar, opaque systems, the study reported here investigated experts and novices relative use of structure-function relationships to understand a familiar, inspectable system–a bicycle. As the study shows, the experts, but not the novices, spontaneously and consistently utilized a systems approach to characterize this familiar object.
Development and Effectiveness Evaluation of Mindfulness-Cognitive Schema Therapy Program for Decreased Alcohol Craving, Increased Abstinence Self-Efficacy, Mindfulness and Self-compassion of Alcohol Use Patients

본 연구는 알코올 사용 장애 환자의 음주 갈망 감소와 금주 자기효능감, 마음챙김, 자기자비 증진을 위해 정신건강의학과 병원에 입원치료 중인 알코올 사용 장애 환자를 대상으로 마음챙김-인지도식 프로그램을 개발하고 그 효과를 검증하였다. 본 프로그램은 8회기로 구성하였고, 처치 집단에 12명, 통제 집단에 12명을 할당하였으며, 사전-사후 검사를 실시하였다. 연구 결과, 사전-사후 검사에서 처치 집단의 경우, 음주 갈망, 금주 자기효능감, 마음챙김, 자기자비 수준의 유의한 차이가 있었고, 통제 집단은 차이가 없는 것으로 나타났다. 집단 간 분석에서 처치 집단이 통제 집단보다 금주 자기효능감, 마음챙김, 자기자비 수준이 통계적으로 유의하게 증가하였고, 음주 갈망은 유의하게 감소되었다. 이는 기존의 치료 프로그램의 한계점을 보완하는 효과적인 치료 프로그램으로서 기능할 수 있음을 시사한다.The purpose of this study was to develop a mindfulness-cognitive schema therapy program and evaluate the effectiveness of the program for the alocholics and for the purpose of reducing the alcohol craving and improving the abstinence self-efficacy, mindfulness and self-compassion. In the pre and post treatment, the patients performed the Mindfulness Scale, the Self-Compassion Scale, the Drinking Craving Scale, and the Abstaining Self-Efficacy Scale. The treatment group experienced total of 8 sessions of program. As a result of this study, first, there was a significant mean differences in alcohol craving, abstinence self-efficacy, mindfulness and self-compassion between pre and post test in treatment group. Second, there were statistically significant increase in mindfulness, self-compassion, abstinence self-efficacy score in the treatment group compared to the control group and a significant decrease in the alcohol craving score. These results suggest the possibility of functioning as an effective treatment program that complements the limitations of existing treatment programs.
Learning temporal regularized and weighted surrounding-aware correlation filter for unmanned aerial vehicle object tracking

Correlation filter (CF)-based trackers have demonstrated promising performance in the field of unmanned aerial vehicle (UAV) tracking, benefiting from their high computational efficiency. However, model degradation and the boundary effect remain two major obstacles for CF-based trackers. We present an innovative temporal regularized and weighted surrounding-aware CF for UAV object tracking. First, we considered the consistency of response between the current frame and the previous frame of an object in a time series, which effectively enhances the discriminability and generalization capability of CF-based trackers to abrupt appearance variations. Second, we developed an innovative weighted context learning strategy that is able to enlarge the visual field of trackers to cope with the boundary effect. Specifically, we extract weighted surrounding patches with the same size and shape of the object to empower the discriminating ability of the CF. Finally, to validate the effectiveness of our proposed method, substantial comparison experiments with other state-of-the-art algorithms were conducted on three UAV standard data sets. The experimental results demonstrate that the algorithm proposed has good robustness for occlusion, deformation, fast motion, and other challenging disturbances in complex scenes and effectively tracks the target on the platform of a UAV.
BioCatch and CyberLink tackle security risk

As the hacking threat to biometric technology rises – Experian calls biometrics one of 2019's biggest cyber-targets – more defence products are coming to market. BioCatch has launched a new behavioural biometrics offering to combat bank fraud, and CyberLink has partnered with Altek to improve the anti-spoofing capabilities of smart security systems.
Session details: Theme: Software design and development: RE - Requirements engineering track

This editorial gives details of the 13th edition of [email protected], including an update of a previous analysis for the first nine editions of the track.
SportsStore: Orders and Checkout

In this chapter, I continue adding features to the SportsStore application that I created in Chapter 7 . I add support for a shopping cart and a checkout process and replace the dummy data with the data from the RESTful web service.
IMPLEMENTASI DATA MINING UNTUK MENENTUKAN KELAYAKAN PEMBERIAN KREDIT DENGAN MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBORS (K-NN)

The banking world in terms of lending to customers is routine activities that are at high risk. In its execution, the problematic credit or bad credit is often due to the lack of careful credit analysis in the process of granting credit, as well as from poor customers. The purpose of this study is to implement data mining to assist in conducting credit analysis process in order to produce the right information whether the customer who will apply for the credit is worthy or not to be able to see the potential payment by the customer. The attributes used in this study consist of 11 attributes i.e. marital status, number of liabilities, age, last education, occupation, monthly income, home ownership, warranties, loan amount, length of loan and description as a result attribute. The methods of data collection used are observation, interviews, and documentation. The method used in this study is K-Nearest Neighbor (K-NN). From the results of evaluation and validation using the K-5 fold that has been done using the RapidMiner tools obtained the highest accuracy results from the K-Nearest Neighbor (K-NN) method of 93.33% in the 5th test.
Model Innovation and Scheme of Music Online Open Course

With the opening of "listening to music" course by Yale University to the whole world in 2009, China has also initiated the relevant reform of music course standard.In November 2017, "music online open course construction and education teaching reform seminar for colleges and universities" was successfully held in capital normal university.This meeting is aimed at music online open course construction and education teaching reform and other core issues to exchange and discuss, which indicates that music online open courses in China will become one of the main directions in the future.This paper is mainly divided into three aspects.First, analyzing the demand of music online education.Second, thinking about the construction of online courses.Third, studying the reform of education teaching.This paper is expected to help students learn to explore, create, cooperate and share music, so as to improve their learning ability.
A Mediator Leadership Practices for Organisational Development Through Data Screening

This paper explored the data collected regarding the study on mediating effect of organizational innovation in the relationship between leadership practices and organisational performance. Seventy universities operating in Saudi Arabia participated in the study. The survey was completed by 248 principal officers on behalf of their respective universities. The results were then analysed using version 22 of the software package of the Statistical Package for the Social Sciences (SPSS). An initial data testing and preliminary review were conducted to ensure that the multivariate analysis assumptions were not broken. The analysis was carried out in this study explicitly with the missing values, outliers, regular test and multilinearity testing. We concluded that the data were sufficient for further study.
Neural Networks

This chapter introduces a subfield of machine learning frequently recognized as deep learning. First, it introduces different artificial neural networks. Second, we cover back propagation and forward propagation. Third, it presents different activation functions. Last, it builds and test a Restricted Boltzmann Machine and a multilayer perceptron using the SciKit-Learn package, followed by deep belief networks using the Keras package. To install Keras on the Python environment, use pip install Keras and on the conda environment use conda install -c conda-forge keras
Automatic service abstraction through data, information and knowledge prioritisation

Web service is a popular solution to integrate components when building a software system, or to allow communication between a system and third-party users, providing a flexible and reusable mechanism to access its functionalities. Scientists have been proposing numerous models for defining anything 'as a service (aaS)', including discussions of products, processes, data and information management, and security as a service. Various web service-based systems are prevailing in health service, personalised recommendation provision. We propose a framework towards constructing and searching typed resources in terms of data, information and knowledge through a hierarchy composing data graph, information graph and knowledge graph in order to improve performance in accessing and processing resources. We use cases to illustrate the mechanism of the framework.
Frequency Adding Singular Value Decomposition Algorithm and Its Application in Fault Feature Extraction

Abstract：For the frequency separation of singular value decomposition(SVD), the separation condition of SVD for single frequency is studied.It is found that the effect of SVD to separate a single frequency depends on the amplitude difference of the frequencies.If the amplitudes of different frequencies are very close, then SVD cannot separate these frequencies.Based on this characteristic, a frequency adding SVD algorithm is proposed.In order to extract the feature frequency of the original signal, the ideal sinusoidal signal of this frequency is added to the original signal, which makes the amplitude of this feature frequency different from the ones of other frequencies, so that this frequency can be separated by SVD.The feasibility of frequency adding SVD is proved theoretically.The simulation signal example shows that for the frequencies with very close frequency values, the frequency adding SVD algorithm can also separate them accurately, and the defects of the traditional SVD frequency separation algorithm is overcome.Finally, this algorithm is applied to extract the vibration features of a rotor system and the high-order harmonics of the vibration signal are extracted separately, which reveal the periodic fluctuation characteristic of the amplitudes of high-order harmonics, and the cause of periodic fluctuation of the amplitudes is analyzed.
Internet of Things (IoT): Towards A Better Healthcare

The significance of Internet of Things (IoT) makes different objects connected and it has also been known as the tech revolution. One of the many applications of IoT is in healthcare to examine the patient’s health report, internet of things makes medical technology more efficient and less complicated by giving access to real-time analysis of the patient’s health, in which it focuses on acquiring the data regarding the patient’s health and eliminate the possible human flaws. In the internet of things, a patient’s health statistics get transmitted through various medical equipment through a gateway, where they are stored and monitored. The main challenges in the implementation of the internet of things for healthcare services are checking all patients from different places. Therefore, the internet of things in the healthcare field gives the basic solutions for effective patient monitoring at less cost and also reduces the tensions between patient outcomes and disease management. This paper gives emphases on the different techniques used to monitor the patients while working for the healthcare department.
Organizational and Methodological Proposals for Optimizing the Process of Creating а Board of Trustees in a Russian School

Studying the experience of the formation of boards of trustees in educational organizations, the authors presented the draft recommendations for the creation of a board of trustees of a secondary school, pointing out the key problems and offering options for their optimal solutions.Among the key problems of creating boards of trustees and their initial activities, the authors see: determining the organizational and legal form of the board of trustees and the official registration of the latter, forming the composition of the board and the functional structure of its management, determining the procedure for making managerial and executive decisions in the council.The authors prove that the modern regulatory framework for the activities of the boards of trustees is insufficiently formalized, which complicates their activities.
Correction to: Software engineering whispers: The effect of textual vs. graphical software design descriptions on software design communication

To fulfill the contractual requirement of the Sweden Compact agreement, the following funding note has to be added and placed in the Funding section of the original article: Open access funding provided by University of Gothenburg .
Design &amp; Development of IoT Based Rehabilitation Outdoor Landscape for Gait Phase Recognition

Over a few decades, there is a steady accretion of life expectancy in many countries. Significant advances in modern healthcare technologies, medicines and overall health care awareness gave many to lead a prolonged healthy life. Over the past few years, there has been a huge demand for unobtrusive health monitoring systems from both medical professionals and the general populace to use these technologies for understanding the general health well being in order to improve life longevity. However, most of the available technologies for health monitoring are difficult for the general populace to access and most of the developed health monitoring systems are either deployed in a controlled environment or in healthcare facilities, thus severely limiting the ease of access to many, especially the elderly people. For effective health management of elderly people, evidence-based decision making, continuously monitoring the health status of the elderly demographic is paramount. In order to address these issues, we developed an innovative smart IoT based outdoor health monitoring system. The proposed system collects information about the mobility, posture, and overall gait of the person in an easy to access public outdoor setting such as parks, supermarkets etc. It is quite evident from multiple studies, that analysing the gait can be a useful tool in early detection of the declining health of individuals, as mobility is a key factor in any individual's well being. Also, detecting gait disorders earlier will allow for functional relief to the health care system with the possibility of reducing the number and severity of gait disorders through early intervention.
Prediction of Breast Cancer by Segmenting the Image from Mammography using Neural Network Classifier

An automated identification system to enable early identification of breast cancer which is one of the most familiartypes of cancer amidst females which is identified using a diagnostic technique called mammography. This identification ideologybanks on multiple instance learning (MIL) paradigms which demonstrate an aid in therapeutical assistance. Within the projected framework, breasts area unit is first divided adaptively into regions. The GLCM options are extracted from wavelet sub bands. A classification of diagnostic examination procedure as normal or abnormal is revealed from lesions which are masses or small calcifications and the textural options. To arrive at the final results the abovefactors are interpreted from all parts and analysed.In the event of an anomaly found in thereport, the parts that are detected by the machine driven identification will be displayed. Dual evaluation methodology is undertaken to outline this deviation. A neural network has to be trained before utilization; it is done by segmenting the lesions and feeding it to NN. The NN assigns an anomaly index to them and then the combination of local and global anomaly index takes place.
An Evaluation of English-to-Yoruba Translations of Some Concepts by Selected Radio News Bulletins in South-Western Nigeria

This study examines translations of selected official names/titles contained in news broadcasts in the Yorubaspeaking part of Nigeria, interrogating their adequacy and appropriateness.Sixty-five concepts/titles extracted from one hundred news bulletins presented by five radio stations across the Yoruba-speaking states of Nigeria are examined.The study is prompted by an intuitive feeling of inaccuracy and inappropriateness of important words in news broadcasts in Yoruba and predicated upon the fact that misinformation can be as pernicious as lack of information.The renderings of the concepts in Yoruba are compared with their original versions in English, revealing translation weaknesses such as semantic narrowing, expansion, wordiness, sometimes even unwitting distortions.It concludes by emphasising the adoption of appropriate translation strategies and a more rigorous engagement with the texts as a way of guarding against unintended distortions and misinformation.
SUDANESE GRADUATES PERCEPTIONS: WILL THE METHODS OF TEACHING PROFESSIONALISM STRENGTHEN AND FOSTER LEARNING?

Medical professionalism is context-specific; however, most studies on professionalism were conducted in Western countries.This study aimed to assess medical students' perceptions of professionalism and to determine whether the teaching of professionalism has been introduced in Sudanese medical schools.Additionally, it aimed to determine how medical students conceptualize professionalism and how appropriate and effective they judge the teaching of professionalism to be, based on their experience.To meet these objectives, questionnaires were distributed to medical students enrolled in 23 medical schools across Sudan.Of the 483 students surveyed, 257 (51.3%) reported receiving lectures on professionalism during their training.Of these, 83 had received lectures on professionalism during their training but in an informal way.
JavaScript Primer, Part 1

Effective TypeScript development requires an understanding of how JavaScript deals with data types. This can be a disappointment to developers who adopt TypeScript because they found JavaScript confusing, but understanding JavaScript makes understanding TypeScript easier and provides valuable insights into what TypeScript offers and how its features work. In this chapter, I introduce the basic JavaScript type features, continuing with more advanced features in Chapter 4.
Python Programming

Python is a large and complex language that I cannot hope to cover in one chapter. There are simply too many functions and structures and programming constructs that need to be detailed to make you into a decent Python user. What I will try to do however is apply the 80/20 rule here, also called the Pareto principle. Since we are learning Python for the purpose of programming microcontrollers with CircuitPython, I can omit a lot of things and still have you understand just enough to follow along with this book.
A new Modified method of Cryptography using Caesar Cipher

Nowadays the modern world depends on connections through the internet brings different teams together.The essential components of communication are sender, medium, and receiver.Data transmission over the internet is not possible without any encryption method due to security issues.Different types of areas like corporate sectors, banking sectors, government sectors, and many other sectors share their data through the internet.Hackers always try to attack the transmitted data and try to recover the data.Various techniques are developed for providing data security.Cryptography is used for the safe transmission of data.Encryption is done at the sender side in cryptography, and decryption is done at the receiver side.In the encryption technique, Caesar cipher is one of the best examples.The analysis of Basic Caesar cipher, Delta formation Caesar cipher, and XOR Caesar cipher is done based on many parameters like Avalanche Effect, Frequency Test, and Brute force attack.The authors of this paper have tried to modify the caesar cipher method, which produces ciphertext that can be read.After that with the new ciphertext that can be read, then cryptanalysis not suspicious of the ciphertext.
Message from the SEIS Chairs of ICSE 2019

The scope of the Software Engineering in Society (SEIS) track at ICSE is bold and ambitious in that it focuses on the impact of the accelerating pervasiveness of software technologies in society.Specifically we would like to discuss how software engineering can address the opportunities and challenges posed by the rapidly accelerating pace of technological advances that are impacting the economic, political, environmental, social and technical aspects of society.Equally, the SEIS track is the forum to share success stories, failures and lessons learned from working in highly complex problem spaces such as climate change, public health, cyber security and sustainability.
Do News Headlines matter in the Cryptocurrency Market?

The paper examines the influence of investor sentiment based on news headlines on the cryptocurrency market index and ten individual cryptocurrency returns. We capture investors' sentiment from cryptocurrency-specific news headlines. We use a lexicon-based Natural Language Processing (NLP) technique to construct a unique sentiment indicator, and the sentiment scores are generated using two financial dictionaries: Henry (2008) (HE) and Loughran and Mcdonald (2011) (LM). The findings of the study show that news sentiment has a significant impact on cryptocurrency returns. When the investors' sentiment is optimistic or bullish, the cryptocurrency market experiences herding behavior, leading to an increase in prices. The diverse and heterogeneous nature of the various cryptocurrencies causes each individual cryptocurrency to respond differently to sentiment. Further, we see that sentiment has a more pronounced impact on young, small, and volatile cryptocurrencies. Our study is among the few studies that use cryptocurrency-specific news headlines rather than news bodies to build a news sentiment indicator.