Reviewerly/exHarmony huggingface dataset:
EVALUATING INFORMATION SECURITY AWARENESS AND COMPLIANCE IN SUB-SAHARAN AFRICA: AN INTERPRETIVIST PERSPECTIVE

Information security awareness and compliance are at low levels in Sub-Saharan African countries.The low level of awareness is partly because of several factors, including low Internet penetration rates, lack of adequate technological infrastructure, low levels of literacy, and high costs of acquiring new technology.However, there are other issues, including behavioral, social, cultural, and organizational issues that are often ignored.Most of the current literature on information security awareness and compliance is centered in developed countries and, to some extent, developing countries in Asia and the Middle East.There is limited literature on information security awareness and compliance, especially in Small and Medium-Sized Enterprises (SMEs) in Africa, and in particular in Sub-Saharan African countries.The purpose of this interpretivist study is to identify the significant challenges that SMEs in Nigeria, the most populous Sub-Saharan African country face concerning information security awareness and compliance.The purpose of this qualitative, multisite, exploratory case study will be to identify and explore the various social, cultural, organizational, and behavioral factors that influence the adoption and compliance with the information security policies in Nigerian SMEs.Results of this study could assist organizational leaders with maintaining higher levels of information security in their organizations and avoiding loss of brand equity and revenue because of information security breaches.Observations from audio recorded, in-depth personal interviews with 50 managers working in different departments in 20 different medium-sized companies in Nigeria will be used in this case study.The 20 medium-sized companies included two companies each from the ten key economic sectors forming the core of Nigerian economy.
Improved technique for hiding data in a colored and a monochrome image

Find a new way to hide the different types of confidential and important text files inside the images without noticing any change or distortion of the information in the images after the process of concealment or attempt to be detected by hackers. And then extract these texts and retrieved on demand without loss or loss or distortion of any of its content. The algorithm was used to hide the different text in different image formats using (256) elements, monochrome and color where about 4500 characters were hidden in a monochrome image and about 900 characters in a color image and with a hiding distance (S) where N = 3, key = 3. The overall error rate is low (0.05-0.17) and no distortions were observed on the resulting image
A Hybrid Aspect Based Latent Factor Model for Recommendation

Recommender system has been recognized as a superior way for solving personal information overload problem. More and more aspect-based models are leveraging user ratings and extracting information from review texts to support recommendation. Aspect-based latent factor model predicts user ratings relying on latent aspect inferred from user reviews. It usually constructs only a single global model for all users, which may be not sufficient to capture the diversity of users' preferences and leave some items or users be badly modeled. We propose a Hybrid aspect-based latent factor model (HALFM), which jointly optimizes the Global aspect-based latent factor model (GALFM) and the Local Aspect-based Latent Factor Models (LALFM), their user-specific combination, and the assignment of users to the LALFMs. HALFM makes prediction by combining user-specific of GALFM and many LALFMs. Experimental results demonstrate that the proposed HALFM outperforms most of aspectbased recommendation techniques in rating prediction.
EVALUASI GUIDELINE DAN E-LEARNING DIGITAL LITERACY MENGGUNAKAN MODEL CIPP

This study aims to evaluate digital literacy guidelines based on blended learning using the CIPP model (Contexts, Inputs, Processes, Products). The research method is simple experimental, namely by distributing questionnaires to users who have carried out trials on the system. The source of research data is librarians in the Center for Scientific Documentation and Information. Evaluation is measured by looking at the agreement and disagreement of users regarding the topic of training, completeness of the material, training time, and system quality. The results of the study show that the guidelines and e-learning are declared quite effective. However, there are still some disadvantages, among others, that there is still a small format of teaching material in applications, such as visual content, namely images, videos and audio to be used as reference for learning. In addition, an evaluation of the timing of training is needed.
ANALISIS TINGKAT KEPUASAN PEMUSTAKA TERHADAP LAYANAN DI PERPUSTAKAAN BALAI ARKEOLOGI DAERAH ISTIMEWA YOGYAKARTA DENGAN METODE LIBQUAL +TM

The purpose of this study was to determine the satisfaction of users of the quality of service in the Balai Arkeologi Daerah Istimewa Yogyakarta library using the LibQUAL +TM , in this method there are four indicators namely affect service, library as place, personal control, and information access. The research method used in this study is to use quantitative methods. The population in this study is the visitors who come to the library from April to December 2018. The sample used in this study amounted to 50 respondents. Gap analysis shows that the overall dimensions of LibQUAL +TM are negative. So there is a need for corrective actions to meet the user’s expectations. By using importance-performance analysis, it was found that subvariable personal control on modern equipment items (items 20) had a gap of -0.76. The user assumed that the photocopy machine facilities and infrastructure were needed by the user, but in fact the photo copy service was not provided by the library. Whereas the value of the User Satisfaction Index at the Balai Arkeologi Daerah Istimewa Yogyakarta library shows a number of 87.43%, which indicates the user satisfaction index is satisfied with the performance of library services.
Online video summarization with the Kohonen SOM in real time

In this paper, we propose an algorithm for the creation of an automatic video summary.It is based on the Kohonen's Self-Organizing Map as a method for training and clustering of frame features in online mode.The decision about whether the frame should be in summary depends on the stability of the last sequential clustering results.Three-way matching of images between automatic summary and corresponding user one is proposed and tested.Open Video and SumMe datasets were used for accuracy and performance comparison.It is shown, that the proposed approach can achieve real time summarization combining with its online properties without the requirement to see the whole video.The accuracy (measured by F1 scores) of the proposed approach can compete with batch processing methods.We also compared the performance to the state-of-the-art existing methods of online real time processing.
Development of an intelligent subsystem for operating system incidents forecasting

The object of research is a subsystem for prediction server platform’s incidents, which operates on the basis of the Windows OS family. One of the most problematic places when planning measures to prevent the harmful effects of network attacks such as dDOS, hardware failures etc for the server system is to obtain an effective model for predicting incidents of the operating system.In the course of the research, methods of formation and research of the time series, exponential smoothing, elements of the theory of machine learning based on the method of group accounting (GMDH) are used. To obtain accurate and reliable forecasts of the operation of the intellectual subsystem for forecasting incidents, elements of the theory of heuristic self-organization and a specific implementation of this theory, the GMDH, are used. An algorithm is obtained and a software implementation of an intelligent system for predicting incidents of operating system operation and the main characteristics of its operation is developed. This became possible as a result of the analysis of the constructed model of the intruder, the system log of security incidents and the use of the GMDH. A mechanism is proposed for generating a sample of OS incident events based on the Windows system event log. The testing of the proposed forecasting system based on test samples allows to state that the forecasting results obtained with various settings of the machine learning system and parameters (degree of the reference polynomial, number of variables in the characteristic polynomial model, number of selection series) are satisfactory. As a result of applying the created algorithm for forecasting incidents of OS operation, it is shown that the use of a large number of polynomial models in GMDH allows one to obtain a forecasting system that is qualitatively superior to systems based on classical regression models and methods. Due to this, a much more accurate forecast can be obtained than the classical regression methods or the method of exponential smoothing, compared with similar methods. The percentage of false calculations using GMDH is less than 4 %.
Penerapan Fuzzy SAW untuk Rekomendasi Penentuan Penerima Bantuan Pembangunan Rumah Tidak Layak Huni

Construction of Non-Habitable Homes (RTLH) is a government program managed by thesupervision of the Social Service (Dinas Sosial) in the form of housing construction assistancefunds for the poor. In its realization, assistance is still often found to be lacking on target. It isbecause the determination of beneficiaries is not correctly selected, and there are no standardmethods based on existing criteria. These problems require a system that can providerecommendations that conform to clear standards and use techniques that accounted. FuzzySimple Additive Weighting (SAW) method is one method used in decision making. This methodcalculates criteria to get ranking weights to support decision making. The process of selectingcriteria and determining fuzzy variables carried out as a primary process in this method. Afterthe fuzzification weight value obtained, ranking done to use as a reference in the decision makingof recipients. Based on the results of manual testing, the system made is under the effects ofmanual calculations with a level of accuracy reaching 100%, so that implemented as a basis formaking decisions. While testing, the black box system found that all the requirements tested canrun following the overall system functionality. With this recommendation system, it can help thedecision to find the recipients of the Fund for Non-Occupable Homes Construction Assistanceso that it is more targeted.
Cooperative Learning For First-Year Early Childhood Education Students

Cooperative learning is a transversal competence that has been applied specifically to university education since the creation of the European Higher Education Space. It is presented as an experience based on a retrospective study of the implementation of cooperative learning during the 2018–2019 academic year on a sample of 70 students enrolled in the first year of the Early Childhood Education at Zaragoza University and assessed by means of the questionnaire by González and García Ruíz. The results indicate that the skills perceived by students to be the most developed are autonomy, initiative, self-assessment and involvement, with a high overall score obtained for the use of this methodology (82.9% of students). Furthermore, aspects of communication and interaction with the group-class, skills of analysis and reflection, and the development of constructive criticism are given as positive aspects of its use. However, weaknesses are presented associated with social skills required to resolve difficulties related to team work, to the use of creativity, to the distribution of work, loads and acknowledgement in terms of involvement. Cooperative learning is perceived as a powerful tool for the development of transversal competences in higher education. Consideration is given to the possibility of enhancing basic instrumental, interpersonal and systemic skills, together with motivation and ethics as essential elements on which teaching staff should focus in order for cooperative learning to be effectively put into practice in university education
Bagging-based instance selection for instance-based classification

The task of reducing marked large size samples for building diagnostic and recognizing models by precedents is considered.The method allowing to reduce essentially the size of a training sample increasing at the same time its efficiency, through removal of irrelevant and redundant instances is proposed.The given method provides an opportunity to estimate each instance of a training sample by synthesis of an ensemble of weak classifiers using a bagging model, and to create a reduced sample of the most significant instances by estimations.Software is developed to implement the proposed method.This software has been experimentally investigated in solving the task of reducing synthetic and real world data.The results of the conducted experiments allow recommending the use of the developed method and its software realization for solving the task in the sphere of technical diagnostics.
Android Based Mobile Attendance System Application Online for on Site Engineers at PT. ZYX Indonesia

As the development of technology almost everythingcan be done to use android, android is a linux-based operatingsystem with a system of opensoruce. To develop an androidapplication is also less because there have been many tools alreadyfull code or guide. PT. ZYX Indonesia on all Site engineers havealready complimented Android smartphone. Attendance Systemnow still use web base and need more time to do the attendance,such as the need to open the laptop, web browser login, enterthe page absent recently could do absent. In this case studyattendance system will be designed with the android application.On this application will facilitate engineer for absent because theuser interface is very easy, when directly connected to the logintimeout page attendance.
A Novel Method to Encrypt-Decrypt Digital Speech Signal (EDDSS)

Digital speech signal is very famous and important data type; it is used in many important vital applications such as banking systems, protection and security systems, so speech protection is required.In this research paper we will introduce a simplified method of digital speech signal image encryption-decryption; the method will be tested and implemented using various digital speech signals.The proposed EDDSS will change the frequency and amplitude of the original signal, the issues of security, efficiency and accuracy will be discussed; the obtained experimental results will be analysed in order to raise some judgments.
PELATIHAN MENGELOLA DAFTAR PUSTAKA MENGGUNAKAN APLIKASI MENDELEY PADA MUSYAWARAH GURU MATA PELAJARAN (MGMP) BAHASA INDONESIA SMA/SMK KOTA BENGKULU

The Mendeley application training at the MGMP Bahasa Indonesia SMA/SMK in Bengkulu City aims to improve the knowledge and skills of the teacher using the Mendeley application, as well as facilitate management and library writing. This activity is carried out using several methods, namely observation/monitoring, interviews, and questionnaires. The results of this training activity can be used as one of the learning media for the preparation of bibliography, so this activity is not only useful for teachers, but also students taught by teachers in their respective work units. In addition, this activity can increase the ability of teachers to write scientific articles, especially in compiling and managing bibliography. Based on the data, this training adds to the insights of teachers in managing libraries and is able to apply this application in teaching and learning in their respective schools.
Analysis of voice signal phase data informativity of authentication system user

Directions of improving the quality characteristics specific to voice authentication systems in various access systems are analyzed and explored in the article.One of the main directions for improving the quality characteristics of the user authentication systems is the use of phase information of a voice signal.The urgent scientific task of studying new procedures is being solved to refine the estimates of the pitch frequency obtained on the basis of the amplitude-frequency spectrum analysis.The estimates were refined using phase data of the voice signal, as well as estimates of the pitch frequency in the process of obtaining cepstral coefficients.The results are obtained in the course of statistical analyzing the simulation results using experimental voice data of the authentication system user.Phase data of a voice signal allows obtaining adequate and reliable estimates in the process of spectral analysis.However, if there are errors associated with gross errors, for example, when taking the first or second formants for estimating the pitch frequency, preference should be given to the estimate obtained in the process of calculating cepstral coefficients.The presented research results should be used in voice authentication systems, improving speech recognition systems, as well as in solving speaker identification problems.
Effect of Naikan cognitive therapy intervention on psychosomatic symptoms of female compulsory drug abuse addicts

ObjectiveTo evaluate the intervention effect of Naikan cognitive therapy (NCT)on psychosomatic symptoms of female compulsory drug addicts.MethodsSeventy drug addicts who met the inclusion criteria and volunteered to participate in the study were selected and randomly divided into intervention group(n=35) and control group(n=35) with random number table method.The intervention group received 10 consecutive days of NCT, while the control group received the same period of mental health education.Before and after treatment, the two groups were assessed with symptoms check list-90(SCL-90), preceived social support scale(PSSS), simple coping style scale(SCSQ) and inclination of relapse questionnaire of drug rehabilitated addicts.ResultsThere was no significant difference between the two groups before the intervention (all P>0.05). Compared with pre-intervention, the total score of SCL-90((176.49±40.85) vs (152.60±31.17)), somatization, compulsion, interpersonal sensitivity, depression, anxiety, terror, paranoid and psychiatric factors were significantly decreased and the total scores of PSSS((59.09±14.60) vs (64.43±10.42)) family support, friend support and other support subscales increased significantly post-NCT intervention in the intervention group (all P 0.05).ConclusionNaikan cognitive therapy can significantly improve the psychosomatic symptoms perceive social support and positive coping styles, and reduce the tendency of negative coping and relapse of female compulsory drug addicts.Key words: Naikan cognitive therapy; Compulsory drug addicts; Physical and psychological symptoms; Relapse tendency
Augmented Reality in Environmental Humanities Education

Environmental humanities is an emerging multidisciplinary field of research focused on identifying the impact of modern human (including cultural) activities on the environment, as well as of environmentally friendly solutions. Environmental damage can have serious consequences for the present, as well as for the past, as in the case of archaeological sites, whose investigation becomes difficult and whose process of decay is accelerated. As these issues have not yet been addressed through effective and systematic educational solutions, this chapter proposes, as part of the environmental humanities strategy a digital humanities educational solution centred on the technology of Augmented Reality (AR). The IT application proposed aims to identify the areas of ecological risk and provide detailed information on the destruction processes, as well as the ability to connect with networks of specialists. The authors’ aims are to stimulate critical thinking focused on environmental issues, provide a solution for continuous learning for both specialists and the public, thus contributing to the protection of the environment and of archaeological subjects, and to further the development of sustainable activities through education and awareness.
ESP/ EMP: ARE STUDENTS PREPARED FOR IT?

ESP is considered the best choice in tertiary education context as it meets the students’ needs and consequently boosts motivation. However, the results of needs analysis applied while designing the course and the students’ awareness of their needs when using the language in professional communication may differ. The survey of 1st year students conducted at Sechenov University (Moscow, Russia) between 2014 and 2019 revealed only partial awareness of the needs. The possible solution may be either creating ‘first-hand’ experience (students’ exposure to the situations where they have to use respective ESP skills), or ‘second-hand’ experience (students’ exposure to communication with professionals in their prospective sphere of employment who are regularly using ESP skills).
Supercharacter theory for the Borel contraction of the group GL(n, Fq)

The notion of a supercharacter theory was proposed by P. Diaconis and I.M. Isaacs in 2008. A supercharacter theory for a given finite group is a pair of the system of certain complex characters and the partition of group into classes that have properties similar to the system of irreducible characters and the partition into conjugacy classes. In the present paper, we consider the group obtained by the Borel contraction from the general linear group over a finite field. For this group, we construct the supercharacter theory. In terms of rook placements, we classify supercharacters and superclasses, calculate values of supercharacters on superclasses
Blockchain for Mobile Health Applications Acceleration with GPU Computing

Blockchain is a linearly linked, distributed, and very robust data structure. Originally proposed as part of the Bitcoin distributed stack, it can be applied in a number of fields, most notably in smart contracts, social media, secure IoT, and cryptocurrency mining. It ensures data integrity by distributing strongly encrypted data in widely redundant segments. Each new insertion requires verification and approval by the majority of the users of the blockchain. Both encryption and verification are computationally intensive tasks which cannot be solved with ordinary off-the-shelf CPUs. This has resulted in a renewed scientific interest in secure distributed communication and coordination protocols. Mobile health applications are growing progressively popular and have the enormous advantage of timely diagnosis of certain conditions. However, privacy concerns have been raised as mobile health applications by default have access to highly sensitive personal data. This chapter presents concisely how blockchain can be applied to mobile health applications in order to enhance privacy.
Active Defense Against Social Engineering: The Case for Human Language Technology

We describe a system that supports natural language processing (NLP) components for active defenses against social engineering attacks. We deploy a pipeline of human language technology, including Ask and Framing Detection, Named Entity Recognition, Dialogue Engineering, and Stylometry. The system processes modern message formats through a plug-in architecture to accommodate innovative approaches for message analysis, knowledge representation and dialogue generation. The novelty of the system is that it uses NLP for cyber defense and engages the attacker using bots to elicit evidence to attribute to the attacker and to waste the attacker’s time and resources.