Reviewerly/exHarmony huggingface dataset:
ANXIETY AND DEPRESSION IN DIABETICS: A COMPARATIVE ANALYSIS BY GENDER

INTRODUCTION: Diabetes Mellitus is a group of metabolic diseases characterized by hyperglycemia resulting from defects in insulin secretion and/or action. Studies indicate that type 2 Diabetes Mellitus is related to the increased prevalence of mental health problems, especially depression and anxiety. Diagnosis is associated with an approximately 27% increase on the risk of developing depression, when compared with undiagnosed cases. OBJECTIVES: The objective of this study was to evaluate the prevalence of anxiety and depression in diabetics patients, to compare and correlate these aspects between men and women. METHODOLOGY: Participants were recruited at the Mutirao Diabetes, na event promoted in 2018 by the Municipal Health Secretariat of Goiânia/GO. After this first contact, volunteers were invited through phone calls for a blood exams and interviews. Patients with age between 40 and 60 years of both sexes were selected for the study. Symptoms related to depression were assessed by the Beck Depression Inventory (BDI), which discriminates the presence or absence of depressive behaviour. Anxiety was assessed by the State-Trait Anxiety Inventory (IDATE), which assesses symptoms related to anxiety. Blood glucose was measured and the adopted reference value was ≤99 mg/dL. Mean tests, standard deviation, Student’s t-test and Mann-Whitney tests were performed to compare means between groups and Pearson and Spearman bivariate correlation. RESULTS: The sample consisted of 96 individuals, with a mean age of 56.2 ± 9.6 years, 55.3% female and 42.7% male, and with a mean time of disease (diabetes) of 10.0 ± 7.6 years. The results showed that most of the subjects (66.7%) had their blood glucose above normal values (151.4 ± 76.6), and higher levels of trait anxiety than the reference values (43, 4 ± 6.9). When compared by gender, women had higher depression scores than men (10.4 ± 7.0; 7.8 ± 4.8; p <0.05). Stratifying the groups by the presence of depressive symptoms, it was found that both men and women had shown significant difference in trait anxiety, on the IDATE test, that being aggravated in the presence of depressive symptoms. Correlation analysis showed a weak and positive correlation between anxiety and glycemia rates (r = 0.220; p <0.05). CONCLUSIONS: It can be concluded that diabetes is directly related to biopsychosocial factors, especially depression scores and anxiety levels. The study also confirmed that diabetic women tend to have higher depression scores that diabetic individuals, despite the gender but that have depression, also have higher anxiety levels.
Evaluation of Big Data within the Context of the Protection of Personal Data and Competition Law

In order to sustain their presence in the market, personal data acquirers must obtain, store, and process personal data from sources that feed data such as social media shares, shopping records, and sensor networks. On the other hand, the problem of conformity of real and legal persons whose personal data are processed within the framework of personal data law brings about many legal problems and requires a profound research rather than a limited examination. The fact that a small number of enterprises create dominant power by using big data in market strategy has led to data-dependent companies or markets. Due to the effects that big data caused in the market, there is a need to address many problems in the field of competition law as well as the dimension of privacy and personal rights. In this context, the conflict of interest between the economic interest created by big data and the legal principles of personal data will be addressed and compared with regard to Turkish law and foreign law practices by discussing the relationship between big data and competition law.
Theory of Stochastic Objects: Probability, Stochastic Processes and Inference.

The task of writing a novel textbook on general probability theory seems virtually impossible nowadays. In Theory of Stochastic Objects, the author Athanasios Micheas aims to overcome this challeng...
Building Lptp Vpn Network and User Management Using Fuzzy Logic Based on Age and Utilization of The Dude for Network Monitoring

This study aims to build a VPN network, develop the use of The Dude as network monitoring and user management of bandwidth sharing using fuzzy logic and using MICROTIC ROUTERBOARD as process controller. The benefit of developing this tool is to facilitate the admin or business owner in the process of monitoring and monitoring on hotspots. This research was conducted by designing, making and implementing system components which include routerboard as process controller, access point as 2.4Ghz signal transmitter, The Dude application as network monitoring and user management as well as VPN as connecting media from public network to local hotspot network. The results of this study indicate that the tools made can function well and are developed on a larger scale.
Machine Learning Algorithms for Questing of Phishing URLs

Phishing is being social engineering attack devastating the web users in terns of loss of information including login credentials and credit card numbers makes them to loose billions of dollars per annum.It is alluring fraudulent technique employed by thieves /intruders /phishers to fish for security or private data in the ocean of unsuspecting web users.Phishers uses spoofed-mails; phishing software is used to steal privacy data and financial details.This paper deals with the identification of phishing web sites by analyzing fraudulent features of benign and phishing URLs assessed by Machine learning techniques through proposed algorithms.The main aim of this (method) algorithm is to detect of phishing websites on the ground of lexical features, host properties and page importance properties.It emphasizes different data mining algorithms for evaluation of the features in order to get a better understanding of the structure of URLs that diffuse phishing.The fine-tuned parameters from URL, page rank and WHOIS query are being selected and used in the appropriate machine learning algorithms for decomposing the phishing sites.
A Preliminary Examination on the Development of Research Data Management (RDM) Policy

Data sharing is an important pre-requisite towards enhancing knowledge in science and technology in recent years. The need to systematically collect, collate and manage research data will further facilitate knowledge archiving for future reference and re-use.This paper describes the development of a policy framework for data repository in one of Malaysian public university with a focus onthe awareness of data sharing among researchers. Questionnaires were distributed to 164 respondents focusing on the benefit of data sharing, lack of data sharing requirement and types of data to be included in data repository management. From the finding, the respondents are willing to share and provide data to the other researchers provided there is a proper policy document. This research also discusses the recommended guidelines for the data repository policyand also on howto promote data sharing among researchers.
Research on the Training Mode of Applied Talents in Colleges and Universities for the Regional Development of Western Liaoning

At present, China's economic development is transforming to rely on innovation and talents. The development of national and regional economic society urgently needs colleges and universities to cultivate a large number of high-quality application-oriented talents to serve the society. The cultivation of Applied Talents in Colleges and universities is of great significance to the regional development of western Liaoning, which is conducive to the development of the important functions of higher education in serving the society and providing opportunities for the regional economic development of western Liaoning. To meet the demand of China's economic construction and socialist market economy for high-tech talents, and expand the employment channels of students, colleges and universities in western, the specific needs of application-oriented personnel training is explored in Liaoning province. The cultivation of application-oriented talents in western Liaoning universities should be based on application, deepen the reform of system and mechanism, build the system and mechanism of collaborative cultivation of application-oriented talents, and build the application-oriented curriculum system based on disciplines.
Percepciones del Profesorado de Educación Secundaria ante la Robótica Educativa como recurso didáctico en el enfoque STEM

Educational Robotics (RE) has more and more prominence in the secondary education classrooms and also the participation in the FIRST® LEGO® League championship. Its implication involves a globalizing approach to the different areas of the curriculum that generates a high degree of motivation in the students. In this article we intend to focus on the perception of Secondary Education teachers to know the strengths and difficulties of the implementation of the ER. To this end, a group of teachers who participated in the FIRST® LEGO® League championship in the 2018-19 school year were requested to collaborate. The research provides data on the experience of these teachers and their assessments of motivation and learning in students. The results obtained allow us to conclude that the RE project is well valued by teachers and highlights its potential as a motivational element committed to the students' competence achievement.
Fiturebot: CS Chatbot Application using Nazief-Adriani Algorithm

A company engaged in information technology, namely PT Fiture Teknologi Inovasi, has problems related to information.The absence of a system that can answer user questions automatically on the company's website, as well as the number of repetitive questions raises problems with the exchange of information between the company and the customer.One solution that can be done in overcoming this problem is by building and implementing chatbot applications as customer service.A Chatbot is an application based on artificial intelligence (AI) that can interact with customers automatically.The chatbot customer service application, Fiturebot, will be built using the AIML method as the knowledge base from the chatbot.The text preprocessing process will be implemented on the chatbot, and the Nazief-Adriani algorithm will be used as the stemming method to extract the basic word from the sentences that the customer has submitted.The application was successfully designed and built and has been tested using the Technology Acceptance Model (TAM) method by generating a number of 83.44% of respondents who agree that the application does not require much effort to use it, and 84.78% of respondents agree that the application can improve user performance in finding the information that they needed.
A STUDY ON FACTORS AFFECTING EMPLOYEE ENGAGEMENT IN IT INDUSTRY

In this decade of globalization, the IT industry is growing rapidly. Employees who work in this sector is comparatively high and there are many measures taken to increase the productivity as well as the growth of an employee and the organization simultaneously. This study aims to examine the effects of Cognitive Engagement Factors, Behavioral Engagement Factors, and Emotional engagement Factor on employee engagement in IT Industries in Bangalore. The Study result reviled the fact that Cognitive Engagement Factors, Behavioral Engagement Factors, and Emotional engagement Factor had impact on Employee Engagement. The results also showed that IT employee engagement had a significant impact on organizational efficiency. This study suggests that when employees are engaged, it will facilitate to improve their personal work performance, which will ultimately produce positive results for the Organization.
Missing Values Treatment and Feature Reduction Analysis to Enhance Classification

Datasets may have large number of features which makes it hard and time consuming to classify.Additionally, they may have irrelevant and noise features too with missing values.The missing values should be treated in a proper way so that the classifier accuracy can be improved.There is also a need to reduce features and select only the features necessary to the classifier.Principal Component Analysis (PCA) is commonly considered for this process of reducing the number of features in a dataset.These reduced components can be applied as input to the classifiers.In this study, standard datasets are checked for missing values, classified using Support vector Machines (SVM) and Naive Bayes with and without reducing the features using PCA.Then, the proposed algorithm for missing value imputation is used on the datasets and the same analysis were carried out.The accuracy is evaluated using Confusion Matrix.The results are discussed with analysis based on the nature of features and missing values and how different datasets behave when used with machine learning algorithms.
PENGARUH PEMBELAJARAN SCRAMBLE TERHADAP HASIL BELAJAR ELEKTRONIKA KELAS X TKR SMKN 1 PALANGKA RAYA

The purpose of this study was to determine the effect of scramble learning model on automotive basic technology of electronics lesson on learning outcomes of class X TKR student of SMKN 1 Palangka Raya. This type of research uses true experiment design, the form of research design used in this study uses the form of the pretest and posttest control group design type wherein the initial test will be given before treatment is given and the final test will be given before treatment. The results of this study indicate that the calculation using the t test with a significance level of ? = 0.05 obtained a value of 6.24 while the value of 2.005. This means that H0 is rejected and H1 is accepted, so it can be concluded that there is an influence of student learning outcomes taught using the Scramble learning model on the basics of electronics lesson
FORMATION OF A POSITIVE IMAGE OF AN ENTREPRENEUR IN THE RUSSIAN SOCIETY

The formation of a socially-oriented market economy in Russia is possible only with the intensive development of entrepreneurship in each of the regions of the country.In 2018, in order to strengthen entrepreneurial activity and increase a number of small and medium-sized businesses, the Government of the Russian Federation adopted the National Project "Small and Medium-Sized Enterprises and Support for Individual Entrepreneurial Initiative".The National Project list of activities to promote entrepreneurship is not exhaustive and may be supplemented by a number of others borrowed from the practice of foreign countries.Developed by the author list of activities can contribute not only to formation of a positive image of an entrepreneur in the Russian society, but in general also lead to an increase in the efficiency of business activities in Russia.
GRAPHICAL USER INTERFACE DEVELOPMENT PROBLEM DESCRIPTION AND SOLUTIONS

This article is about graphical user interface development problem description and possible solution summary. The goal of this work is to delve into specifics of common graphical user interface development problems and controversies, and list possible solutions that can be used to overcome.
Fake calibration attack using a beam sampler in a continuous variable-quantum key distribution system

A Fake Calibration Attack process for a Continuous Variable-Quantum Key Distribution system using a Beam Sampler is presented. The Fake Calibration Attack allows a calibration that balances the Standard Quantum Limit for all the optical path in the experiment (differential Standard Quantum Limit is ≈ 0.39 dB) allowing Eve to acquire ≈ 0.0671 for a particular information quadrature which establishes a Quantum Bit Error Rate ≈ 5.8%. As a final result, the balancing of the Standard Quantum Limit for both states of polarization signals allows maintaining the overall Quantum Bit Error Rate at a particular value ≈ 3%, which implies an important basis for detecting a potential spy considering the minimum Quantum Bit Error Rate.
INTERPRETING LARGE SCALE NATIONAL LEVEL ASSESSMENT DATA IN MATHEMATICS BY USING RASCH ANALYSIS

Latvia is undergoing a nation-wide curriculum reform in general education, with an aim to help students to develop 21st century skills. In order to successfully implement reform, not only teacher performance in the classroom is important, but also the transformation of the school culture is of high priority. One of the key dimensions that is characteristic for a school as learning organization culture is whether it has data-driven culture and is using data on continuous basis to improve student achievement. Large scale national level assessment data is used for many different purposes, however, this data only rarely is recognised as useful data source for planning actions to improve student achievement at school level. Authors argue that in different grades average performance of students cannot be compared in a meaningful way to develop action plan and evaluate the impact of the initiatives at the school level. It is based on the issues rising from varying difficulty level of the tests and different skills, which are being assessed. The study design is based on in-depth analysis of items of large-scale national level assessment in mathematics, defining minimum level of competency of mathematics and calculating percentage of students in school with minimum level of competence in a cohort. This analysis is conveyed for the students of 3rd, 6th and 9th grade by using Rasch model, thus allowing to effectively monitor the student performance during the general education and use of data to make informed decisions.
Scheduling Mobile Robots in Flexible Manufacturing System by An Adaptive Large Neighborhood Search

Robots play an important role in the production and processing of auxiliary products in flexible manufacturing systems. Mobile robots can quickly and easily transport goods from warehouses to individual production workshops. This paper studies the path planning problem of using mobile robots to provide goods. This problem is called mobile robot path planning (MRPP) problem. An improved algorithm based on adaptive large neighborhood search called ALNSI is proposed. This algorithm integrates the characteristics of this problem into the search framework and has designed various destroy and repair methods according to the problem. Both the destroy and repair methods include strategies for tasks and mobile robots. A path reconstruction algorithm for ensuring the feasibility of scheme is also included in neighborhood search framework. The algorithm proposed in this paper has better performance in experimental verification than comparison algorithms and can be better used in flexible manufacturing systems.
Demand Forecasting of Spare Parts of Automobiles using Gaussian Support Vector Machine

Reordering motor vehicle spare parts for the purposes of stock replenishment is an important function of the parts manager in the typical motor dealership. Meaningful reordering requires a reliable forecast of the future demand for items. Production planning and control in remanufacturing are more complex than those in traditional manufacturing. Developing a reliable forecasting process is the first step for optimization of the overall planning process. In remanufacturing, forecasting the timing of demands is one of the critical issues. The current article presents the result of examining the effectiveness of demand forecasting by time series analysis in auto parts remanufacturing. A variety of alternative forecasting techniques were evaluated for this purpose with the aim of selecting one optimal technique to be implemented in an automatic reordering module of a real time computerized inventory management system.
PRACTICAL STATUS OF VOCATIONAL TRAINING FOR FUTURE TEACHERS OF VOCATIONAL TRAINING AND TECHNOLOGY

The article presents the main results of the analysis of the practical status of vocationally oriented chemistry training for future teachers of vocational education and technology in higher education institutions. The main tasks of the study were aimed at studying the normative documents regulating the training of teachers in the specialty 014.10 Secondary education (vocational training and technology); finding out the need for studying chemistry and its professional teaching in the process of training future teachers of vocational training and technology in higher education institutions; determining the level of formation the chemical knowledge in future teachers of labor training and technology; exploring of the level of motivation to study chemistry by students. Based on the results of the ascertainment experiment, it is concluded that the problem of vocational training of future teachers of vocational training and technology in higher education institutions is not properly solved, as in the process of research revealed contradictions between: the importance of chemical knowledge for mastering the disciplines of professional training teachers of vocational training and technology and mostly low levels of academic achievement of students in chemistry; current requirements for the professional training of future teachers of vocational training and the current practical status of vocationally oriented chemistry training; the need to improve the vocational training of chemistry of future teachers of vocational training and the lack of training and methodological support for this purpose; the need to strengthen the professional orientation of the chemistry course and the lack of methodology for the formation of future teachers of work training and technologies of chemical knowledge, taking into account their professional direction.
Disaster Mitigation Study in School Prone to Earthquake and Tsunami Disaster (Case Study Of SMAN 4 Pariaman)

SMAN 4 Pariaman is located in an area prone to disasters, especially the earthquake and tsunami. SMAN 4 Pariaman is located on the coast of the West Coast of Sumatra, which belongs to the tsunami red zone in Pariaman City. Based on this, all school residents must be prepared to face the disasters that will occur, especially the earthquake and tsunami. This type of research is a combination of research (Mixed Methods). This research is a step of research by combining two pre-existing forms of research namely qualitative research and quantitative research. The results of the study found 5 main priorities, namely 1) Optimization of meeting the basic needs of disaster management with a value of (5,000), 2) Application of evacuation routes and zones of vulnerability to our position or presence (4,556), 3) Socialization through facilities and infrastructure prepared by parties BPBD with grades (4,412), 4) Make maps to the evacuation sites of schools with grades (4,200), 5) Facilitate evacuation route signs such as posters with grades (3,587). The results of the FGD and data processing by data processing with Bayes method obtained 5 main priorities, namely 1) Schools must incorporate knowledge about disasters into the curriculum or subjects with values ​​(5,100), 2) Improvement of earthquake resistant facilities (4,467), 3) Schools must enter disaster mitigation activities into extracurricular values ​​(3,933), 4) Making maps of tsunami evacuation routes to TES with values ​​(3,923), 5) Conduct TRC education and training with a value of 3,857.
Set-based Noise Elimination for Is-a Relations in a Large-Scale Lexical Taxonomy

As the significance of knowledge base has been widely accepted during the past decade, how to efficiently eliminate the noises in the knowledge base becomes a key problem since the automatically constructed knowledge base usually contains lots of noises that disturbs its application. Based on the observation for Is-a relations that the real entities of a concept A always share several same ancestors besides A, we come up with an Is-a relations noise elimination approach. In this paper, we will elaborate on this approach and explain the pseudocode of it. Our experimental results demonstrate that such an approach is capable of eliminating the noises in the knowledge base efficiently.