Reviewerly/exHarmony huggingface dataset:
Mentoring Style, Self-Description, and Academic Achievement in English Class

The intention of the study was to examine student mentoring, self-description, and academic achievement in a selected private university in Jakarta, Indonesia. There were 150 respondents in the study. The 2 instruments used for collecting data were adopted from Cohen (1995) for identifying the mentoring style of the mentors of the students, and from Marsh (1999) for identifying self-description of the students. The analysis of data employed descriptive statistics (independent t-test) as well as Chisquare, One-way ANOVA, and Two-way ANOVA. The research inquiries focused on the following issues: (1) identifying the mentoring style, self-description, and academic achievement of the students; (2) the relationship of mentoring style, self-description, academic achievement, and demographic profiles; and (3) the interactive effects—individual and joint—of mentoring style, self-description, and student academic achievement. The findings of the study showed that 2 mentoring styles were predominant among their mentors: relationship emphasis and mentor model; students perceived themselves with a self-description focused on spiritual values; and students had high academic performance. Both male and female students perceived similar mentoring styles among their mentors, while, 1st year and 2nd year students perceived mentoring style to be different among their mentors. In self-description, differences were found between genders while there was no difference found between 1st and 2nd year students. There was no difference found between gender and year of study in the academic achievement, the students showed high performance. Mentoring style and self-description did not have a significant individual or joint difference on academic achievement. Since the students, as a whole had high academic achievement, this study seemed to suggest that the different mentoring style did not have a difference on their academic achievement. However, that did not mean that mentoring did not work. On the contrary, it seemed that mentoring, regardless of style—based on the high academic achievement scores—did work. However, there was also the possibility that high achieving students might not need mentoring for improving their academic achievement.&#x0D;
Simplified Hybrid Secure Algorithm for Mobile Banking Application

Abstract M-banking is one of the main divisions of m-commerce. It provides daily banking operations to the customer using his mobile with the supported application. But the current applications are facing security challenges due to the limitations of mobile resources. There are two major schemes. First, the public key infrastructure (PKI) but, suffers the scalability and certificate management problems. Second, the identity-based public key cryptography (IBPKC) but has key escrow problem. In this paper a modified algorithm to solve these problems by combining elliptic curve Signcryption with certificateless cryptography and enhance the security with lower computational time. From the results, the proposed algorithm has superior performance compared with earlier schemes. Also, it supports multiple types of messages (such as document and multimedia).
Imbalanced Data Classification with Deep Support Vector Machines

In recent years, deep learning has become increasingly popular in various fields. However, the performance of deep learning on imbalanced data has not been examined. The imbalanced data is a special problem in target detection and classification task, where the number of one class is less than the other classes. This paper focuses on evaluating the performance of the deep support vector machine (DSVM) algorithm in dealing with imbalanced human target detection datasets. Furthermore, we optimize the parameters of the DSVM algorithm to obtain better detection performance. It is compared with the stacked auto-encoder (SAE) and the support vector machine (SVM) algorithm. Finally, numerical experimental results show that the DSVM algorithm can effectively capture the minority class.
Hunting Cyber Criminals: A Hacker's Guide to Online Intelligence Gathering Tools and Techniques

Vinny Troia. Published by Wiley. ISBN: 9781119540922. Price £30.99, paperback and ebook. There are many how-to hacking books that seem remote from the reality of digital investigation. Many are little more than a list of well-known tools and a superficial introduction in how to apply them. This one is a little different.
Study on usability evaluation of medical software interface based on eye movement tracking technology

With the development of social economy, the acceleration of urbanization process and the acceleration of an aging society, the phenomenon of pet ownership is becoming more common, pet medical services and related products are gradually showing the development trend of personification, standardization and scale. However, there are still many problems in the interface design of veterinary X-ray machine software, such as operation interface layout, color matching and information architecture. Based on this, the study takes vetview console interface as the research object, through the eye tracking and comparing the data obtained from a questionnaire survey, and it is concluded that the software usability problems and combined the user requirement analysis, software function analysis, as well as interactive prototype design method. It puts forward the basic requirements of the software interface design. This paper tries to put forward the design principles and methods which have practical guiding significance for this kind of interface design.
TheNorth at HASOC 2019 : Hate Speech Detection in Social Media Data

The detection of hate speech in social media is a crucial task.The uncontrolled spread of hate speech can be detrimental to maintaining the peace and harmony in society. Particularly when hate spee ...
PENERAPAN METODE MIND MAP PADA PEMBELAJARAN TEKS BERITA DI SMPIT MNU TRUCUK

Learning methods are a set of strategies used in the learning process. learning methods are needed by teachers, to improve student competence in any particular sub-section or material. The use and use of learning methods must be adapted to the needs of the community and the suitability of the material to be taught. This research is included in the descriptive qualitative. Data collection techniques in this study are the measurement technique. Measurements were made on the ability of students to analyze the structure and elements of news text class VII SMP NU Trucuk, class VIII A, amounting to 12 students. The results showed that the application of the mind map method in learning to analyze the elements and structure of news text has benefits and obstacles in its application. The final results of applying this method can be said to be good. This can be seen from the final results of the calculation of the average value of 75.8.
Geochemical assessment of heavy metal pollution of river basin in Nigeria using stream sediment

Heavy metal pollution has been a source of health problems in humans. These metals are persistent, toxic, non-degradable and often take a long time to be eliminated from the body. This study is, therefore, designed to assess heavy metal pollution of River Basin in Nigeria. Seventy stream sediment samples were systematically collected from an area, approximately 400km2, latitude 7O 00’ and 7O 15’N and longitude 5O 11’ and 5O 19’E. The pollution status of the sediments by heavy metals were assessed by Enrichment Factor (EF), Pollution Load Index (PLI) and Geo-accumulation Index (Igeo). The concentrations of the heavy metals were also compared with United States Environmental Protection Agency (USEPA) Sediment quality guidelines (SQG). The samples were dried in the laboratory, disaggregated, sieved to minus 80 (&lt;177 microns) mesh size using nylon sieve. The sieved samples were, then, digested and the concentrations of As, Co, Fe, Mn, Ni, Pb, V and Zn were determined by Wavelength Dispersive X-ray Fluorescence Spectrometry (WD-XRFS). Results revealed that the mean concentrations of the heavy metals are in the order V&gt;Zn&gt;Pb&gt;As&gt;Ni&gt;Co&gt;Fe&gt;Mn. Furthermore, the mean concentration of lead exceeded both the average world shale and the USEPA SQG values. However, the mean concentration of cobalt, nickel, manganese and zinc were lower than the average world shale values for these elements. The Enrichment Factor (EF) revealed that cobalt was moderately enriched while arsenic and lead were significantly enriched in the sediments. On the basis of the geoaccumulation index, the stream sediments were largely uncontaminated except at some sites that were moderately to strongly contaminated by As and Pb.
Overview of the 2019 ALTA Shared Task: Sarcasm Target Identification

We present an overview of the 2019 ALTA shared task. This is the 10th of the series of shared tasks organised by ALTA since 2010. The task was to detect the target of sarcastic comments posted on social media. We intro- duce the task, describe the data and present the results of baselines and participants. This year’s shared task was particularly challenging and no participating systems improved the re- sults of our baseline.
DISASTROUS IMPACT OF CORRUPTION, POLITICAL INSTABILITY AND EXPROPRIATION RISK ON QUALITY OF EDUCATION: EVIDENCE FROM ASIAN COUNTRIES

The present study attempts to examine the impact of Civil Liberties, Regulatory Quality, Voice and Accountability along with Literacy rate and Population growth on quality of education.For this research, the panel data has been collected over the period of 28 years for 9 Asian countries from World Bank and Global Economy data base.The data is specific to employed variables.After the completion of data collection, several tests were applied in order to test the hypotheses using the system GMM approach.The tests include LLC unit root test, diagnostic tests of Heteroskedasticity, Autocorrelation, Cross-section dependence and Multicollinearity, and the estimation of static and dynamic GMM.The results show that, civil liberty, regulatory quality, literacy rate and population growth significantly impact the quality of education in Asian Countries.Whereas, the insignificant impact of voice and accountability was evidenced from outcomes of the research.Also, the study embraces several theoretical, practical and policy making implications for the government to improve the quality of education and devise the policies for its regulatory controls and the policies of civil liberties to its citizens along with the effective controls for accountability.In the last, various limitations have been given along with the recommendations for in-depth findings by the future researchers.
Comparison Of Classification Algorithms For The Detection Of Bone Weakness In Students Using Anthropometric Data

Low bone mineral density can lead to weak and fragile bones that lead to problems of osteoporosis and fractures in people, early detection can help their treatment. This research compares five data mining algorithms to predict bone weakness in students between 5 and 18 years of age. The methodology used for data processing is CRISP-DM. The accuracy of the algorithms applied in the referenced works with the results obtained with the WEKA data mining tool is discussed. After making the comparison, it was determined that the JRip algorithm was more precise.
Vessel enhancement of endoscopic image based on multi-color space

In order to improve the contrast between the blood vessels and tissues of the images obtained by medical electronic endoscopes, a vessel enhancement method of non-linear contrast stretching in multi-color space is proposed according to the characteristics of endoscopic vascular images. Firstly, in RGB color space, stretching contrast adaptively of the green (G) component by using the nonlinear mapping function. Secondly, adjusting the gray value of the two components of red (R) and blue (B) according to the stretching result of the G component. Thirdly, converting the image to HSV color space, and stretching contrast adaptively of the saturation (S) component of the image. Finally, converting the image back to RGB color space, and the purpose of vessel enhancement is achieved. In this paper, the proposed algorithm is used to process several electronic endoscopic images with different contrast and brightness. The results show that the algorithm has better enhancement effect on small blood vessels which are not obvious in original features. Comparing to other enhancement methods, the detail variance (DV) of the enhanced image is significantly great. The algorithm is embedded in a resolution of 1280×800 endoscopic software, 26 frames can be processed per second.
A Classification of Visual Style for 3D Games

Graphic styles for 3D games can be designed in any direction as the designer desires. Graphic styles range from an abstract composing with a degree of independence from visual references to a realistic rendition of the real world. Cel shaded, voxel graphics, and photo-realism are terms that widely used to characterize the graphic style. Nevertheless, these designates are not systematically set and well prescribed since development techniques change rapidly due to hardware and software innovations. In order to visualize a chosen graphic style, numerous compositions, materials, and execution are required. The purpose of a game, as defined by developers, can be game experience goal, player enjoyment, market capitalization, or specific objectives such as cognitive improvement. Different graphic styles can be used to reach the same goal, but some of graphic styles may have longer production time than others. In this study, we survey a hundred and forty of popular 3D games in the mobile platform with a focus on their basic construction including forms, proportions, texture, and lighting, to propose an alternative classification of graphic styles for today’s technology.
Approximating V<scp>ertex</scp> C<scp>over</scp> using Structural Rounding

In this work, we provide the first practical evaluation of the structural rounding framework for approximation algorithms.Structural rounding works by first editing to a wellstructured class, efficiently solving the edited instance, and "lifting" the partial solution to recover an approximation on the input.We focus on the well-studied Vertex Cover problem, and edit to the class of bipartite graphs (where Vertex Cover has an exact polynomial time algorithm).In addition to the naïve lifting strategy for Vertex Cover described by Demaine et al. in the paper describing structural rounding, we introduce a suite of new lifting strategies and measure their effectiveness on a large corpus of synthetic graphs.We find that in this setting, structural rounding significantly outperforms standard 2-approximations.Further, simpler lifting strategies are extremely competitive with the more sophisticated approaches.The implementations are available as an open-source Python package, and all experiments are replicable.
3D Point Cloud Attribute Compression Based on Cylindrical Projection

With the rapid development of 3D acquisition technologies, there are mounting interests in representing real-world objects as 3D point clouds. However, nonuniform point positions and abundant photometry attributes of point cloud (i.e., colors, reflectance and normal directions) result in massive data volume, leading to the heavy overload of transmission. To address this issue, we propose an attribute compression method for static 3D point cloud by taking advantage of 2D video coding technology. The attribute is projected onto 2D images which are generated from cylindrical surface for several times. We require consistent angle for each projection to guarantee the spatial distribution of multiple projected images is similar, then we combine these images into video sequence. 2D video codec is utilized to perform compression. In this way, we benefit from both intra and inter prediction. Objective evaluation shows significant improvement in coding efficiency over reference technologies.
PRIVATE CLOUD STORAGE IN RURAL'S MANAGEMENT AND INFORMATION SYSTEM USING ROADMAP FOR CLOUD COMPUTING ADOPTION (ROCCA)

The draft Management Policy and Rural Information system are all articles with several articles governing all information security. In concerning Business Continuity Management it is written "The information system and security work unit backs up data periodically, to safer backing up data using Cloud computing facilities." Cloud computing has advantages as file management. Private cloud storage is a form of cloud computing that is intended for limited use in certain circles and one of its functions is used for backing up data or file management. On the other hand, there is software that can be used to implement private cloud storage, namely Owncloud. To run the Rural Information Security Policy Draft article on Business Continuity Management and for the provision of data centers, a study was conducted to implement private cloud storage using Owncloud. The method used in this study is the Roadmap for Cloud computing Adoption (ROCCA) with five stages, namely the stages of analysis, design, adoption, migration, and management. The results of this research are private cloud storage using Owncloud as a medium for storing, securing, and sharing files that are flexible and highly scalable that can be accessed via the internet by users.
How Robust is Your Automatic Diagnosis Model?

Automatic diagnosis based on clinical notes has become a popular research field recently, and many proposed deep learning models have achieved competitive performance in diseases inference. However, previous research reveals that deep learning models are susceptible to negligibly perturbed inputs named adversarial examples, which contradicts with the safety and reliability requirements of the medical domain. To analyze the vulnerability and robustness of current automatic diagnosis models, we investigate in the generation of adversarial text examples. The main challenges for generating adversarial text examples are divided into three parts. First, the word embedding space is discrete, which makes it hard to perturb as small as adversarial image examples generation. Second, previous adversarial example generation methods focus mainly on multi-class classification models, while automatic diagnosis is a multi-label classification task. Third, the semantic and medical meaning of clinical notes are vital in disease inference, and even small perturbations can change them to a large extent. In this paper, we address the three main challenges and propose Clinical-Attacker, a general framework for both white-box and black-box adversarial text examples generation against automatic diagnosis models. Experimental results on MIMIC-III dataset demonstrate that our framework can easily alter the predictions of automatic diagnosis models with the semantic and medical meaning preserved.
Recouping the missing web citations in Library Hi-Tech journal

The main purpose of the present study is to examine the trend and accessibility of web citations cited in the articles published in in Library Hi-Tech journal. It also intended to know the recovery of missing web citations using Time Travel. A total of 3912 web citations cited in 568 research articles published in Library Hi-Tech journal during 2006-2017. The study used W3C link checker to check the accessibility of web citations. Further, a list of missing web citations was separated. The study has also been made an attempt to recoup the missing web citations using Time Travel. The study found that the average web citations per article are 6.89. The study found that 23.29% of web citations were not accessible and remaining 76.71% of web citations are accessible. The use of Time Travel to recover missing web citations has shown that the Wayback machine was able to recover 60.92% of missing web citations followed by the Library of Congress Web Archive and Bib Alexandria. The findings of the study help authors, web masters, and librarians to understand the missing behavior of web citations cited in LIS scholarly articles and to use methods to recover those missing web citations
Preventing art forgery and fraud through emerging technology: application of a regulatory pluralism model

Art forgeries and fraud have occurred as long as art has been profitable. Art forgers study the methods of the masters to ensure that any traces marking their work as a copy are indiscernible to the most experienced expert authenticators. Galleries, auction houses and dealers often use detection technology to verify artworks in an attempt to separate the masterpieces from the fakes. In order to outsmart this technology, sophisticated criminals may alter their artistic modus operandi to mimic the age and techniques of the originals. Many scientific authentication tests are decades old and incremental improvements have been slow, enabling forgers to study the science to avoid interception. However, emerging technologies using scientific breakthroughs increasingly are able to differentiate between artists' methods and techniques to determine the authenticity of a work, supporting human experts’ opinions. Argued from the perspective of regulatory pluralism, this chapter examines emerging technologies and their usefulness in shifting the power against the criminals.
Evaluation of the effectiveness of the use of case-technology in teaching computer modeling of future teachers of informatics

Problem and goal. The article describes the problem of using case-technology in teaching computer modeling to future teachers of informatics. The relevance of solving this problem is determined by the need to find new approaches to combining the fundamental and applied training of future teachers in order to form a holistic competency that provides a solution to professional pedagogical problems. The purpose of this study was to design a model of training future teachers of informatics in the field of computer modeling using case-technology, as well as testing this model during a pedagogical experiment. Methodology. The basis of the developed methodological approach was the use of subject-oriented cases in teaching computer modeling to future teachers of informatics. This type of cases is considered as a set, which includes: 1) situational problem; 2) tasks, the implementation of which leads to the solution of the problem; 3) materials needed to complete tasks; 4) software tools for solving the problem. The model of training of future teachers of informatics using case-technology is considered as a set of target (formation of competence of the teacher of informatics in the field of computer modeling), content (the content of the course “Computer Modeling”) and process components (three stages of design, development and direct application of the subject-oriented case of computer modeling in the classroom). To assess the effectiveness of the case-technology application, a pedagogical experiment was conducted, involving the implementation of training in experimental and control groups. Results. The article presents the results of an experiment conducted at the Volgograd State Socio-Pedagogical University. During the experiment in the control and experimental groups, a course of computer modeling was implemented with the preservation of the content, but with the use of case-technology in the experimental group. Criterion evaluation of the effectiveness of the formation of competence of the teacher of informatics in the field of computer modeling was carried out in the subject and research aspects. The results of the experiment showed that in the experimental groups increased the number of students represented at high, as well as medium and high levels of formation of both the subject and research component of the competence. Conclusions. The study showed that the proposed approach to the use of case-technology provides high results. The obtained and statistically confi data of the experiment allow us to speak about the effectiveness of the use of case-technology as a means of teaching computer modeling to future teachers of informatics.