Reviewerly/exHarmony huggingface dataset:
Antecedent factors of violation of information security rules

Purpose This paper aims to investigate the influence of moral disengagement, perceived penalty, negative experiences and turnover intention on the intention to violate the established security rules. Design/methodology/approach The method used involves two stages of analysis, using techniques of structural equation modeling and artificial intelligence with neural networks, based on information collected from 318 workers of organizational information systems. Findings The model provides a reasonable prediction regarding the intention to violate information security policies (ISP). The results revealed that the relationships of moral disengagement and perceived penalty significantly influence such an intention. Research limitations/implications This research presents a multi-analytical approach that expands the robustness of the results by the complementarity of each analysis technique. In addition, it offers scientific evidence of the factors that reinforce the cognitive processes that involve workers’ decision-making in security breaches. Practical implications The practical recommendation is to improve organizational communication to mitigate information security vulnerabilities in several ways, namely, training actions that simulate daily work routines; exposing the consequences of policy violations; disseminating internal newsletters with examples of inappropriate behavior. Social implications Results indicate that information security does not depend on the employees’ commitment to the organization; system vulnerabilities can be explored even by employees committed to the companies. Originality/value The study expands the knowledge about the individual factors that make information security in companies vulnerable, one of the few in the literature which aims to offer an in-depth perspective on which individual antecedent factors affect the violation of ISP.
Tool-Aided Learning of Code Reasoning with Abstraction in the CS Curriculum

Computer science students often evaluate the behavior of the code they write by running it on specific inputs and studying the outputs, and then apply their comprehension to a more general understanding of the code.While this is a good starting point in the student's career, successful graduates must be able to reason analytically about the code they create or encounter.They must be able to reason about the behavior of the code on arbitrary inputs, without running the code.Abstraction is central for such reasoning.In our quest to help students learn to reason abstractly and develop logically correct code, we have developed tools that rely on a verification engine.Code involves assignment, conditional, and loop statements, along with objects and operations.Reasoning activities involve symbolic reasoning with simple assertions and design-by-contract assertions such as pre-and post-conditions as well as loop invariants with data abstractions.Students progress from tracing and reading code to the design and implementation of code, all relying on abstraction for verification.This paper reports some key results and findings from associated studies spanning several years.
Formation of Digital Competences of University Library Users

The paper presents various approaches to defining the concepts of ‘information competencies’ and ‘digital competencies’. The point of view of scientists on the essence, structure and ways of developing digital competencies are considered, the concept of students’ digital competence in modern conditions is clarified. The influence of this process on the development of the university library is emphasized. Digital competence is defined as the student’s high-level ability to communicate in the digital space (highly mobile intelligent devices, smart technologies, network professional communities) with the goal of self-realization and continuous innovative development. Among new challenges for the university library in digital environment the main ones are considered to be the emergence of new social and technological tasks, the specifics of working with users of the university library, and changing access to electronic resources while maintaining the invariability of main functional purpose of university library. The integrity and systemic development of digital competence of students in the conditions of the university library is reflected. The purpose of this paper is to unlock the potential of the university library as a subject of digital competencies development of students who will work in the digital age. The experience of the Scientific Library of the Siberian Federal University on developing digital competence of students is presented. Profiles of digital competencies of library users are proposed, which include two areas of responsibility: 1) information competencies and 2) digital competencies. The results of the study were refined and summarized, the results of the study were systematized, methodological recommendations were prepared to increase the effectiveness of libraries
Offline Handwritten Signature Authentication with Conditional Deep Convolutional Generative Adversarial Networks

Handwritten signature authentication systems are important in many real world scenarios to avoid frauds. Thanks to Deep Learning, state-of-art solutions have been proposed to this problem by making use of Convolutional Neural Networks, but other models in this Machine Learning subarea are still to be further explored. In this perspective, the present article introduces a Conditional Deep Convolutional Generative Adversarial Networks (cDCGAN) approach whose experimental results in a realistic dataset with skilled forgeries have Equal Error Rate (EER) of 18.53% and balanced accuracy of 87.91%. These results validate a writerdependent cDCGAN-based solution to the signature authentication problem in a real world scenario where no forgeries are available nor required in training time.
Analysis of Faecal Sludge Treatment Alternatives to Enhance the Treatment Performance of Wastewater Treatment Plant (WWTP) Denpasar Sewerage Development Project (DSDP) Suwung Denpasar City

Most of the wastewater generated from domestic activities in Denpasar city is treated in an off-site treatment plant located in WWTP DSDP Suwung. This includes faecal sludge that originates from on-site treatment plants. The existing treatment facilities can only treat wastewater that has a maximum biochemical oxygen demand (BOD) concentration of around 225 mg/l while the disposed faecal sludge’s BOD concentration reaches 3,394 mg/l. Therefore, an additional faecal sludge treatment plant needs to be established in order to separate the solid phase from the liquid phase. According to the treatment performance calculation, some alternative treatments can achieve BOD5 and TSS removal of up to 97% and 98% respectively. The selection of the alternative treatment was decided from weighting results of several aspects, such as economic, land use, technological and environmental aspects. The weighting method that was used in this research was Simple Additive Weighting (SAW). The advantage of SAW is its ability to do the assessment highly precisely because it is based on predetermined criteria and preference weights. Based on the weighting result, the treatment technology selected was a Solid Separation Chamber as primary treatment, combined with an Anaerobic Baffled Reactor as a secondary treatment. A Belt Filter-Press was applied to reshape the sludge into a recyclable cake. The required cost is approximately 16 billion rupiahs.
Integrating Channel Context Attention and Regional Association Attention for Kidney and Tumor Segmentation

Automatic segmentation of the kidney and tumor from computed tomography (CT) images is an essential step in precision oncology and personalized treatment planning. Due to the irregular shapes and vague boundaries of kidney and tumor, this is a challenging task. Most of existing methods focused on local features without fully considering the associations between regions and contextual relationships between features. We propose a new segmentation method, CR-UNet, to extract, encode and adaptively integrate multiple layers of relevant features. Since the semantic features of different channels contribute differently to the segmentation of kidney and tumor, we introduce semantic attention mechanism of channels. The regional association attention mechanism is established to integrate the semantic and positional connections between different regions. Ablation studies demonstrate the contributions of semantic associations between deep learning channels, and regional relation modelling. Comparison results with state-of-the-art methods over public dataset demonstrated improved tumor and kidney segmentation performance.
Ensemble Techniques for Credit Card Fraud Detection

Credit card fraud is a problem that has grown by great danger and has a huge impact on the financial sector.The challenges of credit card fraud are the availability of public data, high imbalance in data, and volatility of the fraud nature.Over the years ensemble learning has gained more importance and proved to give better performance.Here we try to do a comparative study of various ensemble approaches using various learning algorithms on the credit card fraud data and to understand multiple models based on various evaluation and performance metrics using the SMOTE balancing technique.
Correction to “Fluorinated Compounds in North American Cosmetics”

ADVERTISEMENT RETURN TO ISSUEPREVCorrectionNEXTORIGINAL ARTICLEThis notice is a correctionCorrection to “Fluorinated Compounds in North American Cosmetics”Heather D. WhiteheadHeather D. WhiteheadMore by Heather D. Whitehead, Marta VenierMarta VenierMore by Marta Venierhttps://orcid.org/0000-0002-2089-8992, Yan WuYan WuMore by Yan Wuhttps://orcid.org/0000-0001-7876-261X, Emi EastmanEmi EastmanMore by Emi Eastman, Shannon UrbanikShannon UrbanikMore by Shannon Urbanik, Miriam L. DiamondMiriam L. DiamondMore by Miriam L. Diamondhttps://orcid.org/0000-0001-6296-6431, Anna ShalinAnna ShalinMore by Anna Shalin, Heather Schwartz-NarbonneHeather Schwartz-NarbonneMore by Heather Schwartz-Narbonnehttps://orcid.org/0000-0003-4776-0974, Thomas A. BrutonThomas A. BrutonMore by Thomas A. Bruton, Arlene BlumArlene BlumMore by Arlene Blum, Zhanyun WangZhanyun WangMore by Zhanyun Wanghttps://orcid.org/0000-0001-9914-7659, Megan GreenMegan GreenMore by Megan Green, Meghanne TigheMeghanne TigheMore by Meghanne Tighehttps://orcid.org/0000-0002-8930-892X, John T. WilkinsonJohn T. WilkinsonMore by John T. Wilkinson, Sean McGuinnessSean McGuinnessMore by Sean McGuinness, and Graham F. Peaslee*Graham F. PeasleeMore by Graham F. Peasleehttps://orcid.org/0000-0001-6311-648XCite this: Environ. Sci. Technol. Lett. 2021, 8, 12, 1104–1105Publication Date (Web):December 3, 2021Publication History Received10 November 2021Accepted16 November 2021Published online3 December 2021Published inissue 14 December 2021https://doi.org/10.1021/acs.estlett.1c00903Copyright © 2021 The Authors. Published by American Chemical SocietyRIGHTS & PERMISSIONSACS AuthorChoiceCC: Creative CommonsBY: Credit must be given to the creatorNC: Only noncommercial uses of the work are permittedND: No derivatives or adaptations of the work are permittedArticle Views2272Altmetric-Citations-LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InReddit PDF (574 KB) Get e-AlertsSupporting Info (1)»Supporting Information Supporting Information SUBJECTS:Calibration,Cell signaling,Fluorine,Metabolism,Organic compounds Get e-Alerts
A new class of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="d1e1162" altimg="si346.svg"><mml:mi>α</mml:mi></mml:math>-transformations for the spatial analysis of Compositional Data

Georeferenced compositional data are prominent in many scientific fields and in spatial statistics. This work addresses the problem of proposing models and methods to analyze and predict, through kriging, this type of data. To this purpose, a novel class of α-transformations, named the Isometric α-transformation (α-IT), is proposed, which encompasses the traditional Isometric Log-Ratio (ILR) transformation. Similarly to other α-transformations existing in the literature, it is shown that the ILR is the limit case of the α-IT as α tends to 0 and that α=1 corresponds to a linear transformation of the data. Unlike the ILR, the proposed transformation accepts 0s in the compositions when α>0. Maximum likelihood estimation of the parameter α is established. Prediction using kriging on α-IT transformed data is validated on synthetic spatial compositional data, using prediction scores computed either in the geometry induced by the α-IT, or in the simplex. Application to land cover data shows that the relative superiority of the various approaches w.r.t. a prediction objective depends on whether the compositions contained any zero component. When all components are positive, the limit cases (ILR or linear transformations) are optimal for none of the considered metrics. An intermediate geometry, corresponding to the α-IT with maximum likelihood estimate, better describes the dataset in a geostatistical setting. When the amount of compositions with 0s is not negligible, some side-effects of the transformation gets amplified as α decreases, entailing poor kriging performances both within the α-IT geometry and for metrics in the simplex.
Confirmation of Personality Types Using Visual Evoked Potential with User Interface Design Stimulus

After obtaining the consistency of Visual Evoked Potential (VEP) by using a stimulus with data-entry user interface design.This study tries to confirm whether an individual's VEP will be classified according to personality type, which results from the proceeds of conventional personality tests usually carried out by the organization that is the place of this research.The results of this study will be an attempt to complement the needs of particular organizations for the elicitation stage to show user personas by using personality types as something to consider in software development in organizations.The recording of 20 participants whose personality types were known from the results of personality tests at the organization was completed.Each individual has a unique VEP. to confirm personality types and it is necessary to prove the similarity of VEP between individuals of the same type.93.75% of VEP is classified according to personality type.Therefore it is necessary to consider that personality type can be used as user persona for user classification at the stage of user needs.To identify personality types at the personality test stage, it is still necessary to add more participants involved to get more convincing results.
Sistem Pelatihan Jarak Jauh (PJJ) Balai Diklat Keagamaan Medan Berbasis Web Menggunakan Learning Management System (LMS) Moodle

The training process held by the Medan Religious Education and Training Center (BDK) is still carried out using the classical method, it means that training process can be established on the condition that there is a meeting between committee, participants and lecturers in a class. The Covid-19 pandemic, which has not ended until now, means that using classical training cannot be done optimally. Therefore, distance training method (E-Learning) was developed as a solution to the that problem. To support the successful implementation of the training, a web-based system for distance training process is needed as a media between committee, participants and lecturers. The Web-based system using Learning Management System (LMS) Moodle version 3.10.7. The method of system design uses the System Development Life Cycle (SDLC) approach with the Waterfall method. It is recommended that a Distance Training System be provided with technical instructions for using the system.
ANALYSIS OF SOLAR ENERGY POTENTIAL BY REMOTE SENSING TECHNIQUES IN VARAŽDINSKA COUNTY, CROATIA

Abstract. Renewable energy becomes more and more considered as energy production due to great benefits and less environmental impact then traditional energy sources. As a part of the European Union, Croatia agreed upon certain energy efficiency goal that need to be achieved during certain period. In this paper we analyse solar energy potential in northern part of Croatia, Varaždinska county. Remotely sensed data, CORINE land cover, digital elevation model, is used to perform multicriteria analysis. There are different solar panels considered: mono-crystalline silicon panels, poly-crystalline silicon panels, amorphous silicon panels, gallium arsenide panels and cadmium tellurium panels. Based on remote sensing data estimated yearly production of electric energy from solar potential could be from 8.40*107 to 2.43*1010 kWh depending on different slope of solar panels. Gallium arsenide panels shows best usability depending on slope estimated energy production is from 2.52*1010 to 7.30*1010 kW.
Extension of Deep Learning Based Feature Envy Detection for Misplaced Fields and Methods

Code smells (CS) are a severe symptom in software source code that leads to a serious problem in software maintenance and evolution.Feature Envy (FE) is a type of CS that refers to methods that are misplaced in the source code.Many tools like infusion, JDeodorant and JspIRIT have been used to identify the CS.The conversion of source code measurements into predictions is based on manually constructed heuristics.But, manually selecting good features and constructing optimal heuristics is a challenging issue.So, automatic detection of CS is required.The Deep Learning (DL) methods play an important role in achieving the automatic detection of FE(DLFED).The FE detection approach based on DL is intended to discover misplaced methods.The DL technique automatically identifies the source code characteristics for FE identification as well as automatically improves the difficult mapping structure between the features and their prediction.But, a DL-based automatic detection of CS requires a significant number of features with labeled training datasets to provide better prediction results.Therefore, an extension of the DL-based FE detection technique (EDLFED-FM) is proposed in this article to detect both misplaced methods and fields.The semantic relationship between identifiers in the source code program is used to extract the features of misplaced fields and methods.The new decomposition slice method is proposed to convert the extracted features of misplaced methods and fields into the slicing vector composition.This sliced feature helps deep learners understand the relationship between misplaced methods and fields.This automated method is capable of producing labeled training data for DL techniques-based classifiers without the requirement for human intervention.Finally, the experimental outcomes proved that precision rate of suggested method outperforms the JDeodorant and DLFED methods by 14.49% and 10.29 % for free plane, 14.72 % and 12.2 % for Junit, and 21.84% and 14.68 % for JExcelapi applications.Hence, it has been demonstrated that the predicted misplaced methods and fields are moved to the refactoring class for positive testing of source code program with less training data.
Disbursal of Text Steganography in the Space of Double-Secure Algorithm

Hackers reveal sensitive information from encrypted conversations as the globe has become one community. As a result, steganography and cryptography are used together to safeguard sensitive data more effectively than previous approaches and newly developed algorithms. A double-secure algorithm for text steganography (DSTS) is the safest approach compared to the paragraph hiding method (PHM) and capital alphabet shape encoding (CASE) method. In this context, the paragraph hiding method uses ASCII coding, which is not a standard method, and the CASE method has a security issue that if someone understands its applicability, it can be easily attacked. DSTS algorithm overcomes its limitations by using UTF-16 coding and enhances the security of CASE with a one-time pad (OTP). The one-time pad is a theoretically unbreakable cryptographic method. Still, it is not feasible for long messages, however, it is usable for short messages such as a password or intelligence agency’s more secure messages. DSTS degrades the average hiding capacity in a PHM from 2.06% to 1% due to UTF-16 coding. Using the UTF-8 method, the authors have improved MDSTS and the CMPHM by 6.49% and 7.76% hiding capacity, which outperforms in existing procedures; in the CMPHM, there is one reason for the improvement in hiding capacity is using the LZW compression method. CMHPM algorithm optimization standard deviation is less than that of the HPM, DSTS, and MDSTS, ultimately increasing speed.
Integrating Cloud with Self Service Kiosk: An Impact Study on Society Evolution

Self-Service Kiosks is the invention of moving technologies with improving the services into a new era of rapid development to society. Using Self-Service Kiosks changing the lifestyle schedule of the day, no need to make free time during the working hours to accomplish the services you need, as it's available 24/7. Public sectors are adopting SSKs at a high rate knowing its potential in revolutionizing how services are offered by improving work efficiency, work experience, relieving human workloads and reducing service cost. The integration of cloud technologies with SSK is an emerging tendency. The survey conducted in the form of questionnaire indicates that cloud enabled SSKs are aesthetically appealing and its implementation would assist in offering right content to a right person at the right time. As several industries adopted SSKs technology to provide their services, this study aims to understand the impact of the self-service kiosk on society and explain the association between self-service kiosk and cloud- computing.
Features of Management Decisions by the Head of an Educational Institution, Their Assessment in the Conditions of Crisis

The innovative and socio-economic preconditions of the state growth process make it urgent to develop education and modernise education management, to improve the competence of administrators at all levels and to model the mechanisms of human interaction, psychology and educational philosophy. The purpose of the study is to examine the characteristics and conditions of management decisions determined by the head of an educational institution, his competence to make and implement them in a crisis situation to achieve high results. An urgent need for management decisions may arise due to external or internal circumstances. It is a kind of response to indirect influences, which aims at solving a particular problem and getting as close to the goal as possible. The practical significance lies in finding the best methods and forms of managerial decision-making that will help the rational implementation of the educational process at school in crisis.
COVID-19 Highlights a Critical Need for Efficient Health Information Systems for Managing Epidemics of Emerging Infectious Diseases

OPINION article Front. Public Health, 10 December 2021Sec. Infectious Diseases – Surveillance, Prevention and Treatment https://doi.org/10.3389/fpubh.2021.767835