Reviewerly/exHarmony huggingface dataset:
Developing An Islamic Farayez System Applying Software Engineering

Distribution of deceased person’s wealth is a divine law in Islam. This distribution should be accurate; otherwise a gruesome punishment is waiting in hereafter. The combination of relatives of late person is diverse which makes the computation of distribution difficult. In order to ease the computation of shares of slain person, a software system can be designed for Islamic Farayez which is the premier concern of this article. The existing software systems cannot compute the distribution precisely always and furthermore have lack of proper explanation of the system. Having studied ‘Islamic Shariah’ for all possible combinations of relatives of dead person, a system has been modelled and developed which provides the knowledge of Islamic inheritance and distributes the wealth of deceased accurately through which user can be galvanized to follow. Here the Islamic Farayez has been analyzed and modelled using structured approach. After fixing different scenario of Islamic Farayez of a dead person, individual cases are analysed using three levels of Data Flow Diagram (DFD). Hence, DFD illustrated the organization of the functional components of the system; and as a consequence, based on this, the graphical form of algorithm or flow-chart of the overall Islamic Farayez system is developed. Finally, mathematical models are derived for all possible combination of relatives of late person and then developed the software for Islamic Farayez system. The reliability, accuracy, integrity and robustness of the proposed Islamic Farayez system are rigorously justified by comparing the proposed system generated results with manual results as well as other existing software generated results for various complex cases. It is recommended to use this proposed Islamic Farayez system as an expert assistant for distribution of deceased person’s wealth among his/her eligible relatives.
The Use of Electronic Frog VLE in Assisting Reading Comprehension Activities

the respondents were optimistic about the most challenging task, the high order thinking skills questions.The respondents were also positive about the implementation of reading comprehension activities through electronic Frog VLE web despite the challenges and obstacles perceived.The findings are hoped to provide insights in the integration of virtual learning environment in reading comprehension activities.
Evaluation and Geostatistical Study of Toxicological Risk by Water Ingestion with Al, Ba, Fe and Pb in Communities Close to Industrial Areas in the Brazilian Amazon

This study provides a risk assessment and risk maps related to the consumption of water contaminated by Al, Ba, Fe and Pb in an industrial area in the Brazilian Amazon.A total of 120 samples of drinking water were collected from 26 locations in the municipality of Barcarena, Pará State.Multiple elements were analyzed by inductively coupled plasma optical emission spectrometry.The quantifiable elements in the samples were Al, Ba, Fe and Pb.Risk assessment was performed according to U.S. Environmental Protection Agency (USEPA) procedures.Results indicate that the highest potential risk of non-carcinogenic adverse health effects for Al was in São João Island; for Ba, Fe and Pb (hazard quotient (HQ) > 1) were in Porto da Balsa community, in the city of Barcarena and Distrito Industrial community, respectively.Maps showed that areas located near Barcarena's industrial complex are the most affected by water contamination.Therefore, these populations are at higher risk of non-carcinogenic problems, especially children and the elderly, since the majority of the population resides in these areas.Geospatial analysis contributed to delimiting and analyzing risk-change trends in the region, expanding the scope of results to a decision-making process.
RULE BASED KANNADA NAMED ENTITY RECOGNITION

The Objective of this research is to determine the names of individuals in Kannada text documents. The Kannada text document includes various Named Entities like Name of a person, Place, Organization, Designation and various other entities shall be determined from it. The method divides the collection of Kannada sentences into different sentences in the pre-processing stage, then dividing the sentence into different words in the second stage of pre-processing. Further, the words are annotated and then the rule based feature extraction is done to recognize the Kannada Named Entities. The multi-class SVM classification is employed to determine the Kannada Named Entities. The Rule based approach focuses on identifying the names of a person by applying the rules formulated, place, and designation of a person has been identified by recognizing the names then the word prior to the names has been considered as a designation of a person. The Rule based Kannada Named Entity Recognition recognizes the various words of the Kannada text document. It has yielded a good results of 89.32% from a proposed Rule based Kannada Named Entity Recognition.
Developing English Learning Materials for Mechanical Engineering Students Using Padlet

Due to emergence of English for Specific Purposes where nowadays English not only a learning material for students but it has become a need for people. Mechanical Engineering graduates are expected to have English ability to compete in job profession. For that reason, it was important to develop English learning material based on the needs of Mechanical Engineering student. The aimed of this research was to develop appropriate English learning materials for the students of Mechanical Engineering Students by using Padlet. Padlet is a web-based interactive application that can be used for communication among students. This research was conducted by using research and development method which involves a preliminary stage and collects information, planning, develop of product and expert validation. The research result was feasible to use based on validation step which was 80% and categorized very good. The product of this research were six units of English learning materials in the form of spoken and written texts as well as grammar explanation. The activities encourage the students to actively participate in the classroom discussion and be involved in solving the task. This research is expected to give contribution to English learning especially English for Mechanical Engineering students.
Statistical Comparison of Architecture Driven Modernization with other Cloud Migration Frameworks and Formation of Clusters

<span lang='EN-US'>Corporations are migrating their legacy software systems towards the cloud environment for amelioration, to avail benefits of the cloud. Long term success of modernizing a legacy software depends on the characteristics of the chosen cloud migration approach. Organizations must think over how strategically imperative is the chosen cloud migration framework to their business? Thus, the Object Management Group (OMG) has defined standards for the modernization process based on Architecture Driven Modernization (ADM) framework. ADM serves as a vehicle for facilitating the arrangement of information technology with business stratagem and its architecture. Until now, it seems that there is no systematic mapping among ADM and other cloud migration frameworks, highlighting the demanding features. This research aims to give an in-depth study of similar cloud migration frameworks. Thus, the researchers introduced the clusters containing cloud migration frameworks having similar features to ADM. This systematic mapping can be seen as a valuable asset for those who are interested in choosing the best migration framework from the pool of cloud modernization frameworks, according to their legacy software requirements. The clustering technique is used to appraise and compare ADM with some of the other cloud migration frameworks for highlighting the similarities and key differences. The quality of clusters is evaluated by the Rand index and Silhouette measurements. The study distills the record and yields a sound and healthy catalog for essential events and concerns that are communal in cloud migration frameworks. This research offers the one-stop-shop convenience that the industry desperately desires. </span>
Usage of Social Networking Tools by Rural Youth in Transfer of Technology - An Overview

The utilization of social media tools is an integral part of rural youth lives today. Over some time utilization of social media has been changed the attention of rural youth. The development of rural youths on social media has reached at a different level, without social media, every individual of rural youth cannot think about the direction of their respective growth and futures. The research studies on the utilization of social media conducted across the world by different authors and review extensively for drawing constructive inference for future study and reference. The development of rural youth on social media is now leading to addiction. The major sources and several studies reported that it is widely accepted the overutilization of social media has a profound negative influence on the rural youths. This study highlights the main purposes of utilizing social media by rural youth and to attempt have been made to find out the time spent on surfing the various social networking sites. This study focuses on the major and the positive and negative effects of utilizing social media on the life of rural youths.
Group-Based Sparse Representation Based on <i>l<sub>p</sub> </i>-Norm Minimization for Image Inpainting

As a powerful statistical image modeling technique, sparse representation has been successfully applied in various image restoration applications. Most traditional methods depend on ℓ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> -norm optimization and patch-based sparse representation models. However, these methods have two limits: high computational complexity and the lack of the relationship among patches. To solve the above problems, we choose the group-based sparse representation models to simplify the computing process and realize the nonlocal self-similarity of images by designing the adaptive dictionary. Meanwhile, we utilize Ipnorm minimization to solve nonconvex optimization problems based on the weighted Schatten p-norm minimization, which can make the optimization model more flexible. Experimental results on image inpainting show that the proposed method has a better performance than many current state-of-the-art schemes, which are based on the pixel, patch, and group respectively, in both peak signal-to-noise ratio and visual perception.
Programming Theorems and Their Applications

One of the effective methodological approaches in programming that supports the design and development of reliable software is analogy-based programming. Within this framework, the method of problem reduction plays a key role. Reducing a given problem to another one whose solving algorithm is already known can be made more efficient by the application of programming theorems. These represent proven, abstract solutions – in a general form – to some of the most common problems in programming. In this article, we present six fundamental programming theorems as well as pose five sample problems. In solving these problems, all six programming theorems will be applied. In the process of reduction, we will employ a concise specification language. Programming theorems and solutions to the problems will be given using the structogram form. However, we will use pseudocodes as descriptions of algorithms resembling their actual implementation in Python. A functional style solution to one of the problems will also be presented, which is to illustrate that for the implementation in Python, it is sufficient to give the specification of the problem for the design of the solution. The content of the article essentially corresponds to that of the introductory lectures of a course we offered to students enrolled in the Applied Mathematics specialization.&#x0D; Subject Classification: D40
FairLedger: A Fair Blockchain Protocol for Financial Institutions.

Financial institutions are currently looking into technologies for permissioned blockchains. A major effort in this direction is Hyperledger, an open source project hosted by the Linux Foundation and backed by a consortium of over a hundred companies. A key component in permissioned blockchain protocols is a byzantine fault tolerant (BFT) consensus engine that orders transactions. However, currently available BFT solutions in Hyperledger (as well as in the literature at large) are inadequate for financial settings; they are not designed to ensure fairness or to tolerate selfish behavior that arises when financial institutions strive to maximize their own profit. We present FairLedger, a permissioned blockchain BFT protocol, which is fair, designed to deal with rational behavior, and, no less important, easy to understand and implement. The secret sauce of our protocol is a new communication abstraction, called detectable all-to-all (DA2A), which allows us to detect participants (byzantine or rational) that deviate from the protocol, and punish them. We implement FairLedger in the Hyperledger open source project, using Iroha framework, one of the biggest projects therein. To evaluate FairLegder's performance, we also implement it in the PBFT framework and compare the two protocols. Our results show that in failure-free scenarios FairLedger achieves better throughput than both Iroha's implementation and PBFT in wide-area settings.
Heuristic technologies of training in professional education

The changed educational paradigm has identified new educational goals expressed in the form of competencies of students, which they must master to carry out future professional activities at a high level and ensure their competitiveness in the labor market. Within the framework of the competence approach, practice-oriented education is developing, so higher education institutions seek to implement technologies that actively support this direction. The purpose of the article is to analyze the experience of implementing heuristic technologies as one of the most effective in the preparation of a teacher of vocational training. Features and essence of heuristic technologies, their value in modern preparation of students are revealed. The article presents a study that reflects the use of heuristic methods to improve the preparedness of students to perform their professional activities. In the formation of the ability to analyze professional and pedagogical situations-one of the most important professional competencies of future teachers of vocational training, the method of organized strategies (the method of strategies for working with information) was applied. Heuristic teaching methods bring positive results in the formation of the ability to analyze professional and pedagogical situations. The ability to work with information is an important part of the formation of this competence. We performed an analysis of the experience in implementing heuristic technologies, as one of the most effective in training a teacher of vocational training, revealed the features and essence of heuristic technologies, their significance in modern student training. Heuristic teaching methods bring positive results in the formation of the ability to analyze professional and pedagogical situations. Our methods of working with information contribute to more rapid training of teachers of vocational training. The results of testing students ' skills to work with information showed that after the introduction of heuristic methods, the results became much better, which contributes to the formation of this competence. The obtained data can be used in the preparation of students in other areas of teaching pedagogical university.
A Systematic Review on Bilingualism and Language Processing from 2015-2019

Over the past few decades, research on bilingualism has been extensively covered but still leaves room for much to be discovered especially in the context of language processing. There is a lack in systematic review on studies that examine the trends, effects, methodological approaches, challenges and limitations on bilingualism in relation to language processing. Therefore, this article aims to offer current understanding on bilingualism and language processing through a process of a critical analysis and synthesis. A total of 20 articles published from 2015-2019 in peer-reviewed journals both abroad and locally were selected to be included in this review for content analysis. Hence, this paper attempts to give a systematic report on the findings categorized by trends, effects, methodological approaches, challenges and limitations. Few main findings emerged: (a) An increasing trend in the study on internal language processing and individual factors affecting bilingualism; (b) The existence of inconsistent effects; (c) The need to re-evaluate methodological approaches; and (d) The lack of research conducted in Malaysia. This review also provides suggestions and opportunities for future research in bilingualism and language processing. Keywords: systematic review; bilingualism; language processing; qualitative method; challenges
Automatic Reading Analog gauge with Handheld device

In general, people use measurement devices which have analog gauge such as speedometer, barometer, and etc. to measure various values. However, analog gauges can cause problems with accuracy and reliability, since people measure the values directly through the needle of gauge. To solve these problems, we propose an ADC system to improve measurement accuracy and reliability more than analog devices. The system can extract measured value through image processing using OpenCV libraries. And, we increased user access to the implanting system in a portable device.
Painting image browser applying an associate-rule-aware multidimensional data visualization technique

Abstract Exploration of artworks is enjoyable but often time consuming. For example, it is not always easy to discover the favorite types of unknown painting works. It is not also always easy to explore unpopular painting works which looks similar to painting works created by famous artists. This paper presents a painting image browser which assists the explorative discovery of user-interested painting works. The presented browser applies a new multidimensional data visualization technique that highlights particular ranges of particular numeric values based on association rules to suggest cues to find favorite painting images. This study assumes a large number of painting images are provided where categorical information (e.g., names of artists, created year) is assigned to the images. The presented system firstly calculates the feature values of the images as a preprocessing step. Then the browser visualizes the multidimensional feature values as a heatmap and highlights association rules discovered from the relationships between the feature values and categorical information. This mechanism enables users to explore favorite painting images or painting images that look similar to famous painting works. Our case study and user evaluation demonstrates the effectiveness of the presented image browser.
DIGITALIZATION OF TAMIL HANDWRITTEN CHARACTERS RECOGNITION USING CONVOLUTIONAL NEURAL NETWORKS(CNN)

Now-a-days digitalization becomes an important one for documents preservation. Some Tamil Handwritten characters need preservation, like land documents etc. So we try to overcome the difficulty of paper preservation by digitalizing it. The aim of this Project is to require Handwritten set of Tamil Characters as input within the format of image to process the character, train the Convolution Neural Network algorithm to acknowledge the pattern and convert the recognized characters to a Printed document. Convolutional Neural Network then attempts to work out if the computer file matches a pattern that the Neural Network has memorized. Optical Character Recognition deals with a crucial concern issue of handwritten character classification. To beat the difficulty of knowledge recognition among similarities, Convolutional Neural Network will provide more accuracy of character recognition. Convolutional Neural Networks (CNN) are playing an important role nowadays in every aspect of computer vision applications. The art of CNN is used in recognizing Tamil handwriten characters in offline mode. CNNs differ from traditional approach of Tamil Handwritten Character Recognition (THCR) in extracting the features by the methods of preprocessing ,normalization, feature extraction and classification .we've developed a CNN model from scratch by training the model with the Tamil characters in offline mode and We have achieved good accuracy results on obtained datasets. This work is for digitalizing offline THCR using deep learning technique.
Fusing Logical Relationship Information of Text in Neural Network for Text Classification

With the development of computer science and information science, text classification technology has been greatly developed and its application scenarios have been widened. In traditional process of text classification, the existing method will lose much logical relationship information of text. The logical relationship information of a text refers to the relationship information among different logical parts of the text, such as title, abstract, and body. When human beings are reading, they will take title as an important part to remind the central idea of the article, abstract as a brief summary of the content of the article, and body as a detailed description of the article. In most of the text classification studies, researchers concern more about the relationship among words (word frequency, semantics, etc.) and neglect the logical relationship information of text. It will lose information about the relationship among different parts (title, body, etc.) and have an influence on the performance of text classification. Therefore, we propose a text classification algorithm—fusing the logical relationship information of text in neural network (FLRIOTINN), which complements the logical relationship information into text classification algorithms. Experiments show that the effect of FLRIOTINN is better than the conventional backpropagation neural networks which does not consider the logical relationship information of text.
Pedagogical approaches to problem solving in higher education

One of the most often mentioned competence in the surveyed literature is problem solving.It is also one of the key skills for the sustainable development of society.The article includes analysis of pedagogical approaches like project-based, problem-based learning and enquiry-based learning, as well as describes the use of design thinking as one of the problem solving approaches in higher education.As mathematics studies at universities play an important role in developing problem solving skills, an empirical study was carried out to identify the pedagogical approaches used by mathematics teachers and to illustrate the development of problem solving skills in mathematics studies at universities in Latvia.It includes a survey of mathematics teachers in Latvia aimed at identifying their experience in implementing different pedagogical approaches to mathematics and assessing the extent to which these methods help develop problem solving skills.The answers of mathematics teachers show that problem solving skills are developed at the middle level, which means only for the use in a certain situation (that is slightly different from previously known).The most effective approach to promoting problem-solving skills is the so-called context approach, which means focusing on the practical task related to a specialty.In the empirical study self-assessment method is used and the results are based only on respondents' opinion.