Reviewerly/exHarmony huggingface dataset:
BdSL36: A Dataset for Bangladeshi Sign Letters Recognition

Bangladeshi Sign Language (BdSL) is a commonly used medium of communication for the hearing-impaired people in Bangladesh. A real-time BdSL interpreter with no controlled lab environment has a broad social impact and an interesting avenue of research as well. Also, it is a challenging task due to the variation in different subjects (age, gender, color, etc.), complex features, and similarities of signs and clustered backgrounds. However, the existing dataset for BdSL classification task is mainly built in a lab friendly setup which limits the application of powerful deep learning technology. In this paper, we introduce a dataset named BdSL36 which incorporates background augmentation to make the dataset versatile and contains over four million images belonging to 36 categories. Besides, we annotate about 40,000 images with bounding boxes to utilize the potentiality of object detection algorithms. Furthermore, several intensive experiments are performed to establish the baseline performance of our BdSL36. Moreover, we employ beta testing of our classifiers at the user level to justify the possibilities of real-world application with this dataset. We believe our BdSL36 will expedite future research on practical sign letter classification. We make the datasets and all the pre-trained models available for further researcher.
Measurement of emotional variables through a brain-computer interface in the interaction with books with augmented reality in higher education

Abstract This article aims to describe the process of measuring mental state variables through a brain-computer interface in the interaction of humans with books with augmented reality; specifically, it seeks to analyze the variables commitment, stress, interest, relaxation, excitement, concentration in the interaction of students with a book with augmented reality compared with the measurement of the same variables when reading a traditional text. For the process of measuring emotional signals, two texts were designed for the data structure subject of the systems engineering program, the first in traditional format and the second with augmented reality applications. Subsequently, the mental state measures were taken through the brain-computer interface to the sample of students of the subject interacting with the traditional book and the book with augmented reality. Finally, through the interface software application, the results of the variables of each student interacting with the mentioned texts were downloaded and comparatively analyzed. Through comparative analysis, it is shown that the variable of mental state interest increases in the interaction of higher education students with books with augmented reality compared to reading a traditional text. Brain-computer interface systems have become an effective strategy for the measurement of emotional variables in the incorporation of emerging technologies such as augmented reality into teaching-learning processes in higher education.
A Study on Efficiency, Accuracy and Document Structure for Answer Sentence Selection

An essential task of most Question Answering (QA) systems is to re-rank the set of answer candidates, i.e., Answer Sentence Selection (AS2). These candidates are typically sentences either extracted from one or more documents preserving their natural order or retrieved by a search engine. Most state-of-the-art approaches to the task use huge neural models, such as BERT, or complex attentive architectures. In this paper, we argue that by exploiting the intrinsic structure of the original rank together with an effective word-relatedness encoder, we achieve the highest accuracy among the cost-efficient models, with two orders of magnitude fewer parameters than the current state of the art. Our model takes 9.5 seconds to train on the WikiQA dataset, i.e., very fast in comparison with the 18 minutes required by a standard BERT-base fine-tuning.
Rules as Code

“Rules as Code” is a label adopted by people in governments working on the idea of encoding (or just marking up) legislation while it is being drafted, so that the logic of the resulting legislation can be “read” (and checked) by a computer, to improve the manner in which legislation is produced and the way in which it is available digitally. The idea is currently attracting attention in the legal community, particularly on the question of whether it will lead to automation replacing human interpretation of the law. This note briefly describes Rules as Code, at least as conceived by a legislative drafter. It argues that this conception of Rules as Code does not have the over-reaching ambitions that it may sometimes appear to harbour, and in particular does not trespass into removing key interpretative functions.&#x0D; &#x0D;
The Influence of Service Marketing Mix on Customer Loyalty towards Islamic Banks: Evidence from Jordan

This study aimed to conduct an analysis of the influence of service marketing mix on customer loyalty, with customer satisfaction as the mediating variable in the context of Islamic banks in Jordan.Banks generally require catering to distinct needs and preferences of customers in order to sustain their long-term relationship.The study collected the required data from 344 respondents using a structured questionnaire, with the sample obtained through convenience sampling approach.Based on the research results, all the elements of service marketing mix, namely price, product, place, promotion, process, people and physical evidence significantly and positively affected customer satisfaction and customer loyalty.This study contributes to the Jordanian Islamic banks knowledge and information concerning the marketing mix strategies that they can adopt in order to sustain and maintain long-term customer relationships.The study supported the importance of customer satisfaction for the creation of customer loyalty.The study findings have implications to literature and practice when it comes to understanding the marketing mix pattern, customer satisfaction and customer loyalty relationship.
Information Security Awareness among youth in Klang Valley: A Focus Group Discussion

Issues on the lack of understanding on the awareness of information security among the Internet user has become central debate now a day.User's ignorance and negligence towards awareness of information security, may lead to being the victim of cybercrime syndicates.This can be clearly seen through the increase of number in cybercrime statistics in Malaysia.Internet users has been scammed, cyberbullying and faced loss amount of money due to their unawareness of information security.The purpose of this study is to look at the youth understanding of information security awareness.Based on the focus group discussion with a total of 20 informants among youth, this research try to obtain the youth perspective and understanding on information security awareness.Using convenience sampling, youth were chosen as informants since they are mostly engaged with new media compared to other age groups.Discussions were audio-recorded, transcribed verbatim, and analyzed using thematic analysis.Results show that there were few themes emerge on the awareness of information security, such as secure password usage, information sharing, safe online shopping website, and safe online banking website.Generally, most of the youth have a basic knowledge on information security awareness, particularly on having a secure password usage and information sharing.This study on the other hand, creates awareness on the important of information security, thus educated them to become a safe Internet user.Future study emphasizing on the government's role in regulating the cybercrime issues and educating smart device users towards safe Internet usage is recommended.
Augmented Reality Application for Teaching Basic Operations with Fractions of the Same Denominator

In this study, an Augmented Reality (AR) application for the teaching of basic operations with fractions of the same denominator was made.Prototype Methodology was used for its develop.In the application striking figures designs are visualized in three-Dimensional (3D), to the students' perspective, those help to represent the explanation in the best way with the process of the basic operations with fractions: Addition, subtraction, multiplication, division and an exercises section.All this is to the students comprehend the fractions topic totally, using computational technology as a support in the teaching-learning process in a dynamic, friendly, creative and innovate way, also easy to manipulate by the users, catching students attention to learn this kind of topics or even another in a significate way.The application was focused to fourth grade elementary students, it is important to say that nowadays an application like that do not exist.Once the application develop finished a demonstration of the application was done in a group of fourth grade students and a questionnaire was applied them, obtaining satisfactory results in their learning.
The Mobile Learning Adoption Model Tailored to the Needs of a Private University

The mission of today’s universities is to prepare the students properly to live and work in the 21st century. International research demonstrates the positive impact of using iPads in teaching. Successful deploying of mobile learning (m‑learning) is not a matter of accident, but depends on users’ acceptance of the technology. The purpose of this article is to create a mobile learning adoption pre‑model tailored to the needs of a private university. To achieve this goal, valued adoption models were analyzed and, on their basis, the new model was created. The pre‑model has been tested with a questionnaire. A paper‑based survey was conducted among 640 students representing 25 countries. The questionnaire was grouped into sections: specifications of mobile devices owned by students and mobile internet access, expectation from mobile education application and attitudes towards current and future use of mobile devices in education. We computed all data with The Statistical Package for the Social Sciences – IBM SPSS Statistics version 25. The results of the research showed that the students from a central‑eastern European University are technologically ready for mobile learning. Moreover, there appears to be no cause for concern regarding students from post‑Soviet countries with respect to their competency to meet the demands of modern teaching in the form of mobile learning. Students have shown that they have clearly defined expectations for educational materials for mobile devices, which will be a challenge for the university when creating m‑learning materials. Furthermore, students must feel the university's support in using mobile applications. That is why the teachers face a serious task: teachers must be prepared to show students the benefits of mobile learning, so they not only need to be trained but also convinced that it is worth using mobile learning.
Study on security risks of e-banking system

&lt;p&gt;Online banking and other e-banking modes are a very convenient way to banking in terms of speed, convenience and delivery costs, but they have brought many risks alongside them. Online banking has created a new risk orientation and even new forms of risk. Technology plays an important role as both a source and a tool for risk control. The purpose of this research is to identify the security situation of the e-banking application and to analyze the risks and attacks that could occur to the customers that, although it’s an e-banking application attacks could happen. Several mitigations were mentioned to overcome attacks like, access control is to mitigate eavesdropping this means that, restricting access to sensitive data is mandatory. Another way to mitigate is, update and patch which is for SQL injection meaning, it's vital to apply patches and updates when it’s available. These attacks may attack the whole application or target an individual where private information is stolen or changed. This research also shows how to apply several more different protections measures to protect oneself and organization from being targets of cybercrime. &lt;/p&gt;
Analysis of Expert System for Early Diagnosis of Disorders During Pregnancy Using the Forward Chaining Method

Nowadays technological developments are increasingly having a positive influence on the development of human life, including in the health sector. One of them is an expert system that can transfer an expert's knowledge into a computer application to simplify and speed up the diagnosis of a disorder or disease in humans. The purpose of this final project is to design an application to diagnose diseases that occur during pregnancy which is caused by the existence of these pregnancies to simplify and speed up the diagnosis of diseases experienced by pregnant women. This study uses the forward chaining method. By involving experts in this expert system analysis according to current needs. Users are given easy access to information on several types of pregnancy disorders and their symptoms, as well as consultation through several questions that the user must answer to find out the results of the diagnosis. While experts are facilitated in system management, both the process of adding, updating and, deleting data.
Reversible Data Hiding Using Hybrid Method of Difference Expansion on Medical Image

Data hiding in the image can cause permanent distortion (irreversible), in other applications such as medical images, distortion can cause misdiagnosis. To overcome these problems, a special scheme is required for the embedding data on medical image. Reversible data hiding is a scheme that can restore the image to original image without distortion after the embedded information is extracted. Difference Expansion (DE) is one of the schemes in reversible data hiding that is simple and easy to implement. In this paper, we propose two schemes based a hybrid combination of DE to increase on capacity and visual quality. Medical image has characteristics is the large of smooth block areas, in which DE method is applied to the non-smooth areas image. We used four different medical images to evaluate the proposed scheme. The results showed that the proposed scheme has a high capacity and better visual quality than the original scheme and similar schemes have been proposed previously. Embedding capacity of the proposed scheme is up to 0.66 bpp with visual quality of PSNR value is up to 48 dB.
Perbedaan Motivasi Belajar Antara Siswa Laki-Laki dan Siswa Perempuan

The problem in this research is the low motivation to learn students, especially male students. This objective of the research is to find out to find out the differences in learning motivation between male and female students of SMAN 1 Bayang Academic Year 2017/2018. This research is comparative research. This research was conducted at SMAN 1 Bayang. This sampling technique is in proportionate stratified random sampling of 150 people. Data analysis techniques are using the t test (independent sample t test). The results of the analysis show that the average learning motivation of male students (Study at Senior High School 1 Shadow) 2017/2018 Academic Year is 88,613. The average learning motivation of female students (Study at SMAN 1 Bayang) 2017/2018 Academic Year is 94,493. There are differences in learning motivation between male and female students (Study at Senior High School 1 Shadow) Academic Year 2017/2018, where the motivation of female students is better than the motivation of male study
How EFL Teachers Deal with Pedagogical Competence Development for the Teaching of Writing: A Study on Higher Educational Level in Indonesian Context

This study investigates what has been done by EFL teachers in higher education level or EFL lecturers in the teaching of writing. This study involves seven research subjects who have taught writing for English Department students for at least three years. The data were collected through in-depth interview. The data were then analyzed through open, axial, and selective coding. In relation to development of teaching techniques for teaching writing, the most frequent activity done by the research subjects is to attend workshop and seminar/conference on writing and TEFL (Teaching English as a Foreign Language). The most frequent activity conducted to improve pedagogical competence on material development for writing class is to read literature or article on materials development for writing class from textbook or the internet. As an addition, the most frequent activity the lecturers conducted to develop their pedagogical competence in classroom management is conduct sharing session with fellow and/or senior lecturers. Finally, the most frequent activities the lecturers conducted to improve their pedagogical competence in assessment/evaluation for writing are to read literature or article on ‘assessment/evaluation for writing class’ from textbook, journal, thesis, dissertation, and the internet, and conduct sharing session with fellow and senior writing lecturers and expert in writing. FFuture researchers can develop this study into pedagogical competence in the other English skills (reading, speaking, listening) or other types of competence pivotal for English lecturers (personal, social, and professional). These will have a positive contribution toward development of English as Foreign Language in Indonesian context.
Secure Data Collaborative Computing Scheme Based on Blockchain

With the rapid development of information technology, different organizations cooperate with each other to share data information and make full use of data value. Not only should the integrity and privacy of data be guaranteed but also the collaborative computing should be carried out on the basis of data sharing. In this paper, in order to achieve the fairness of data security sharing and collaborative computing, a security data collaborative computing scheme based on blockchain is proposed. A data storage query model based on Bloom filter is designed to improve the efficiency of data query sharing. The MPC contract is designed according to the specific requirements. The participants are rational, and the contract encourages the participants to implement the agreement honestly to achieve fair calculation. A secure multiparty computation based on secret sharing is introduced. The problem of identity and vote privacy in electronic voting is solved. The scheme is analyzed and discussed from storage expansion, anticollusion, verifiability, and privacy.
Image Boundary, Corner, and Edge Detection: Past, Present, and Future

This paper presents a thorough review of image processing tasks such as boundary, corner, and edge detection.A clear introduction of these topics is provided for a new researcher, which is followed by a description of the technical details that have been implemented for these topics.In addition, the database list used in the experimentations is also provided.Further, all the techniques are classified and listed in a tabular format.Finally, the open challenges in this field of research are discussed and concluded with the future scope and directions.The authors of this paper expect that this review paper will help new researchers to find an approach to conduct further studies in this topic and also identify some of the unsolved problems.The latter will assist them in solving and reaching close to this research topic.
Yapay Zeka Yöntemleri İle Kuzularda İmmünoglobulin G Tahmini

The health, mortality and morbidity rates of neonatal ruminants depend on colostrum quality and the amount of Immunoglobulin G (IgG) absorbed.Computer-aided estimates are important as measuring IgG concentration with conventional methods is costly.In this study, artificial neural network (ANN), multivariate adaptive regression splines (MARS), support vector regression (SVR) and fuzzy neural network (FNN) models were used to predict the serum IgG concentration from gamma-glutamyl transferase (GGT) enzyme activity, total protein (TP) concentration and albumin (ALB).The correlation between parameters was examined.IgG positively correlated with GGT and TP and negatively correlated with ALB (R = 0.75, P<0.001; R = 0.67, P<0.001; R = -0.17,P<0.01, respectively).IgG, GGT, and TP cut-off values were determined for mortality, healthy, and morbidity in neonatal lambs by decision tree method.IgG ≤113 mg/dL (P<0.001),GGT ≤191 mg/dL (P=0.001), and TP ≤45 g/L (P<0.001) were determined for mortality.IgG >575 mg/dL (P=0.02),GGT >191 mg/dL (P<0.001), and TP >55 g/L (P<0.001) were determined for healthy.It has been observed that the FNN is the most successful method for the prediction of IgG value with a correlation coefficient (R) of 0.98, root mean square error (RMSE) of 234.4,and mean absolute error (MAE) of 175.8.
Correlation Image Sensor for Algebraic Solution of Optical Flow

In this article, we describe several enhancements of a three-phase correlation image sensor (3PCIS) toward its uses for a direct algebraic method of optical flow detection, i.e., determining velocity field of image patterns for detecting, tracking, and three-dimensional recovery of objects in a scene. A recent theoretical study has provided an exact closed-form solution of the velocity from temporal Fourier integral measurements of a time-varying intensity distribution. An accurate analog multiplication and integration of incident light and reference signals required for this type of measurements is the inherent advantage of a 3PCIS. We fabricate and compare several types of correlation detection block. As continuous-value inputs of the algebraic solution, compensation operations of systematic sources of error are so designed to realize a near shot-noise-limited performance. For random telegraph noise and interference reduction, we show that a p-epi channel, deep p-well structure is the best 3P multiplier. Several experimental results of optical flow detection including an accuracy evaluation and the dense motion capture of a traffic scene are given.
Proposed Design of a Real-Time COVID-19 Pandemic Contact Tracing Using Mobile Phone

As the virus that causes COVID-19 continues to spread from person to persons in communities and rampaging the world, the need for an effective real-time surveillance system becomes paramount. Advance contact tracing and detection of the persons with the virus represents one of the main strategies to prevent transmission. Although COVID-19 surveillance systems such as contact tracing mobile apps have improved the administration and management of virus, there are still challenges such as privacy, cost and ethical issues, the adoption of new technologies, standardized cases, and validly diagnosed case and validity. However, the current mobile apps contact tracing system adopted by different nations has complemented conventional tracing effort in fighting the virus. This proposal is a model for an interactive computer system using mobile phones and the internet for real-time collection and transmission of events related to COVID19. It will aid the administration and presumptive management of COVID-19 in the world, especially in rural areas. This proposal shows that a sophisticated COVID-19 surveillance system can be build using mobile phones with the right telecommunication technology partner.
Generation of unstructured tetrahedral meshes for flow past flight vehicles based on open packages

The open packages Gmsh and Salome are used for automatic generation of unstructured tetrahedral meshes in aircraft flow problems.These packages allow you to quickly and efficiently build spatial grids for geometric models defined in the OpenCascade geometric core or in STEP format.It provides mechanisms for thickening the grid, adapting the grid to the solution, generating the grid in interactive mode, command-line mode, and using the program library.In this paper, the possibilities of grid generation algorithms in terms of speed and quality of the resulting grid are investigated.Examples of creating a geometric model and generating a grid are given, as well as examples of calculations on the resulting grids.