Reviewerly/exHarmony huggingface dataset:
E-Farming: Digital generation of soil health card

The main objective of this project is building a website which will help Indian farmers to make effective cultivation by providing up-to-date information. As in this website, a farmer can see their SOIL HEALTH CARD anywhere and anytime. Secondly, it also helps the govt. to save their money by posting the cards to the farmer. This website will also help the farmers to know about the number of different chemicals they can use for their crops and to know about their soil fertility. This website will give farmers all kind of information about different crops. The E-FARMING system provides its users to get online information about, the crop, statistical details, and new tendencies. The main features of the information system include information retrieval facilities for users from anywhere in the form of obtaining statistical information about fertilizer, research institutes, and researches, suitable soil concentration for the corresponding crops and etc.
Expression Recognition with Appearance Based Features of Facial Landmarks

In this paper, Local Binary Patterns (LBP) is used for Facial Expression Recognition (FER). The concept of LBP is based on the information that is present in color images of face. Multi-linear image analysis can be done in different color spaces using LBP and it can be seen that the color content gives additional information about faces which can lead to an efficient FER. Using LBP, the components present in various color spaces such as RGB, YCbCr and CIELuv or CIELab, are made into two dimensional binary’s using multi-linear algebra and concepts of binary’s and then Log-Gabor filters are used to extract these features. For the selection of the features, mutual information quotients method is used. Multiclass linear discriminate analysis classifiers are used to classify the features that were extracted.
Interactive Search and Exploration in Online Discussion Forums Using Multimodal Embeddings

In this paper we present a novel interactive multimodal learning system, which facilitates search and exploration in large networks of social multimedia users. It allows the analyst to identify and select users of interest, and to find similar users in an interactive learning setting. Our approach is based on novel multimodal representations of users, words and concepts, which we simultaneously learn by deploying a general-purpose neural embedding model. We show these representations to be useful not only for categorizing users, but also for automatically generating user and community profiles. Inspired by traditional summarization approaches, we create the profiles by selecting diverse and representative content from all available modalities, i.e. the text, image and user modality. The usefulness of the approach is evaluated using artificial actors, which simulate user behavior in a relevance feedback scenario. Multiple experiments were conducted in order to evaluate the quality of our multimodal representations, to compare different embedding strategies, and to determine the importance of different modalities. We demonstrate the capabilities of the proposed approach on two different multimedia collections originating from the violent online extremism forum Stormfront and the microblogging platform Twitter, which are particularly interesting due to the high semantic level of the discussions they feature.
3D surface profile imaging based on time-encoded structured illumination

A novel 3D surface profile imaging method based on time-encoded structured illumination is proposed. With fast and arbitrary illumination pattern generation, low error 3D reconstruction of different objects can be obtained. © 2019 The Author(s)
Multi factor AKE protocol and key stroke authentication for secured communication

Authenticated Key Exchange (AKE) protocol permits a user and a server to authenticate each other for the first time. It generates a session key for the successive communications without any authentication. Many AKE protocols had been proposed to obtain person privateness and authentication for the duration of conversation. Other than secured consultation key established order, these AKE protocols offer a few other useful capability like two-thing user authentication and mutual authentication. But they have got few weaknesses along with vulnerability in opposition to loss of smart card, offline dictionary assault, de-synchronization attack, person anonymity or untraceability. Also, AKE scheme the usage of public key conversation doesn’t suite nicely for lightweight computational gadgets. In this work, a novel Multi-Factor AKE protocol is proposed to overcome all the above-mentioned weaknesses. This protocol supports revoked smart card transactions. The password that is available on the USB device will be overwritten once the user used it. Passwords can be updated without centralized storage. The average time to enter a password will be defined. The user has to type the password within the allocated time, failing which he/she has to enter it again. This security model of AKE supports user anonymity and resist a lost card attack. Elliptical Curve Cryptography algorithm is used for encryption and decryption of the session key. The computational cost and the bandwidth cost for this proposed model are low, which makes it useful in pervasive computing applications and mobile communications. The proposed AKE model is much secured when compared to the existing protocols.
Cloud Computing With Big Data Clustering Using Privacy Preserving High-Order Possibilistic C-mean Algorithm

In this era, Pattern Recognition and Data Mining are widely used, because the size of data is increasing day by day.The Clustering of data's are commonly done by PCM but as the size of data increases PCM is not able to do the clustering of heterogeneous data.So the Fuzzy Clustering which allows C-mean clustering can be used.The Fuzzy Clustering uses multiple Clusters data points, with each of the data points degree is varying.The Method which uses Clustering processes and image analysis is PCM for C-mean.Mainly two type of Clustering is used, one is HOPCM for clustering of large heterogeneous data and other is Normal Clustering PCM.HOPCM used for very large amount of data based on the Map Reduce functionality.Algorithm used to protect private data is PPHOPCM on Cloud by applying BGV Encryption Scheme on HOPCM data.As the experiment we can say that the heterogeneous data Clustering can be done by PPHOPCM with securing the private data using Cloud Computing.In this Paper we are giving a huge data to process to HDFS.Applying Map Reduce algorithm to the data.Then it is clustered and applying double encryption.The spark is used a tool for clustering.The encryption using BGV and AES128 Encryption Algorithms [2].And Stored to Cloud.The encrypted data is Secure in the cloud.Using the same Encryption Key We can download the data.This improve the Security of data and Computing will be smoother.
DEVELOPING AUDIO-VISUAL MEDIA BY USING VIDEOPAD FOR TEACHING WRITING TO XI GRADE STUDENTS OF SMA N 11 MEDAN

This was a conducted Research and development (R & D) study which concerned with the using of appropriate teaching and learning media. The objectives of this study were to find out the existing teaching media used in XI grade students of SMA N 11 Medan and to develop Audio-Visual media by using VideoPad for teaching writing Analytical Exposition Text. The data was gathered in the preliminary data by using interview and questionnaire on XI grade students and the English teacher. Then need analysis was done through questionnaire and interview as well. This research described the existing media available in the school and how it is used in English teaching and learning process that a development should be done. According to the result of the need analysis there were only 18% of the students considered that the teaching and learning process was helpful. It also showed information about students‟ choice of method and media to learning writing. By considering the result of the need analysis, an Audio-Visual media then developed as a teaching and learning aid of writing Analytical Exposition text. The product had later been assessed by two experts to find out the eligibility of the media. Through the experts‟ assessment which was contained of 4 scoring criterias, it was known that the eligibility of the media was “Very Good” based on the scoring criteria. Keywords: Teaching and Learning Writing, Audio-Visual media, Analytical Exposition, VideoPad.
Special issue on the message passing interface

The simulation of the behavior of the human brain is one of the most ambitious challenges today with a non-end of important applications. We can find many different initiatives in the USA, Europe and Japan which attempt to achieve such a challenging target. In this work, we focus on the most important European initiative (the Human Brain Project) and on one of the models developed in this project. This tool simulates the spikes triggered in a neural network by computing the voltage capacitance on the neurons’ morphology, being one of the most precise simulators today. In the present work, we have evaluated the use of MPI+OpenMP tasking on top of this framework. We prove that this approach is able to achieve a good scaling even when computing a relatively low workload (number of neurons) per node. One of our targets consists of achieving not only a highly scalable implementation, but also to develop a tool with a high degree of abstraction without losing control and performance by using MPI+OpenMP tasking. The main motivation of this work is the evaluation of this cutting-edge simulation on multi-morphology neural networks. The simulation of a high number of neurons, which are completely different among them, is an important challenge. In fact, in the multi-morphology simulations, we find an important unbalancing between the nodes, mainly due to the differences in the neurons, which causes an important under-utilization of the available resources. In this work, the authors present and evaluate mechanisms to deal with this and reduce the time of this kind of simulations considerably.
Analysis of Research Articles on Effective Teaching in ESL/EFL Classrooms: Focusing on TESOL Quarterly

Much research has not been conducted on how classroom-based research articles concerning teaching effectiveness in the ESL/EFL classroom have changed over time, in spite of deep interest in the field. Therefore, this study aims to examine the characteristics of research articles on effective teaching in the ESL/EFL classroom, focusing specifically on articles from TESOL Quarterly. For this purpose, this study searched articles using three key terms; effective teaching, ESL/EFL, and activity. Articles which included those terms were investigated, depending on research topic and publication year, and four key facts were found; the importance of teachers’ input (older articles), a focus on group or peer work (newer articles), teachers’ education, and the use of students’ native languages. While students preferred teachers’ reliable and explicit input in the past, modern articles tended to recommend more frequent interactions among peer groups in the English learning classroom. Limited resources in teaching contexts asked for additional qualifications from ESL/EFL teachers, thus emphasizing teacher education as an important factor for effective teaching. Lastly, the use of students’ native language had a positive influence on learning English. The findings of this study suggest some implications for how effective teaching in Korean context could be implemented.
Bayesian Strategy for Group Decision Making and its Interval Generalization

An original approach to formalize the process of group decision making based on integration of private decisions of independent experts is developed. Mathematical models of collective decisions under risk conditions based on Bayesian strategy are proposed. Using the interval analysis methods there are constructed the suboptimal models providing with a given confidence probability the average risk minimum of the group decision on a set of possible situations.
Optimal Randomness in Swarm-Based Search

L\'{e}vy flights is a random walk where the step-lengths have a probability distribution that is heavy-tailed. It has been shown that L\'{e}vy flights can maximize the efficiency of resource searching in uncertain environments, and also movements of many foragers and wandering animals have been shown to follow a L\'{e}vy distribution. The reason mainly comes from that the L\'{e}vy distribution, has an infinite second moment, and hence is more likely to generate an offspring that is farther away from its parent. However, the investigation into the efficiency of other different heavy-tailed probability distributions in swarm-based searches is still insufficient up to now. For swarm-based search algorithms, randomness plays a significant role in both exploration and exploitation, or diversification and intensification. Therefore, it's necessary to discuss the optimal randomness in swarm-based search algorithms. In this study, CS is taken as a representative method of swarm-based optimization algorithms, and the results can be generalized to other swarm-based search algorithms. In this paper, four different types of commonly used heavy-tailed distributions, including Mittag-Leffler distribution, Pareto distribution, Cauchy distribution, and Weibull distribution, are considered to enhance the searching ability of CS. Then four novel CS algorithms are proposed and experiments are carried out on 20 benchmark functions to compare their searching performances. Finally, the proposed methods are used to system identification to demonstrate the effectiveness.
Students’ Experiences in Higher Education With Virtual and Augmented Reality: A Qualitative Systematic Review

Virtual reality involves 3-D computer graphics that are experienced using a desktop computer or advanced tools including head-mounted displays. Augmented reality is usually experienced on a mobile phone and involves combining real and computer-generated digital information. These platforms have been introduced into higher education settings, however, little is known about their impact on student learning. This meta-synthesis examines the experiences of higher education students with virtual and augmented reality. A thematic synthesis integrating qualitative evidence was undertaken where eight electronic databases were searched. Twenty-three articles met the inclusion criteria (n = 1,334 students) and were examined by two reviewers using a constant comparative approach. Four themes emerged: technological factors, student characteristics, learning outcomes and recommendations. Our findings indicate there are factors to consider with these platforms as well as with the learners themselves when incorporating this technology in higher education.
THE IMPLEMENTATION OF E-LEARNING IN TEACHING WRITING AT THE FOURTH SEMESTER OF ENGLISH DEPARTMENT OF UIN ANTASARI BANJARMASIN

Educational materials that have been effectively designed will facilitate the achievement of desired learning outcomes for students. The student, need to practice their English not only in classrooms but also outside the classroom to improve their English skills. This study explains about the implementation of e-learning in teaching writing at the fourth semester in English Department of UIN Antasari Banjarmasin. The problem statements of this study are (1) how is the implementation of e-learning in teaching writing and (2) what are the problems of the implementation of e-learning in teaching writing. The objectives of this study are to find out the implementation of e-learning in teaching writing and the problem in the implementation of e-learning in teaching writing. This study used descriptive analysis. For data collection, the writer classified type of data after collect data appropriate with the procedures, then the writer analyzed the data descriptive qualitatively. The findings of this study concluded that (1) The implementation of e-learning in teaching writing consists of four phases; they are a) The teacher’ explanation in using e-learning; b) The learning materials provided by the lecturer; c) The students’ activity on the use of e-learning; d) The effectiveness of application. (2) The most common problem in the implementation of e-learning in teaching writing is internet connection. This is the lack of Learning Management System that we will meet if we implement e-learning.
SOA-Based Photonic Integrated Deep Neural Networks for Image Classification

We successfully demonstrate classification of three classes of Iris flowers by implementing a trained neural network on an SOA-based InP cross-connect chip. Classification accuracy of 91.6% is achieved after a fine optimization procedure.
PENINGKATAN MUTU PEMBELAJARAN MEMBACA DAN MENULIS PERMULAAN SEBAGAI UPAYA PENINGKATAN LITERASI DI SD NEGERI INPRES PERUMNAS I WAENA JAYAPURA

The activities of this community service were gaven training to the teachers at SDN Inpres Perumnas I Waena. The aimed of this training were to provide the teachers with the ability to : 1) understand MMP methode; 2) create a curriculum based on local knowledge; 3) innovate variety of learning media; 4) construct evaluation tools; 5) construct RPP and 5) conduct real teaching. CBSA method with complex approach such as lecturer, questions and answer session, task response, discussion and teaching, practice has been used on this training. The trainers were very enthustiastic and recognized their weakness in conducting MMP method during the class.Keywords: Jayapura, Literasi, MMP Methode, Profesionalisme guru
Framework Based on a Fuzzy Inference Model for the Selection of University Program Applicants

This study consisted in the construction of an integrated framework based on a fuzzy inference model for evaluating the competencies in the entry profile of applicants to university programs in order to evaluate the process and make it more efficient. This framework was designed to systematize the method for evaluating the applicant profiles based on specific requirements and to improve performance indicators in the evaluation process. This architecture framework has two components: (a) the evaluation system and (b) the fuzzy model; where the system collects input information from knowledge assessment tests and applicant interviews, which are processed by a web service and delivered as parameters to libraries embedded in the fuzzy model, which was designed in Matlab SDK, and as a result the level of the applicant is returned. Furthermore, the system can be configured to add linguistic variables to the fuzzy model and set membership functions, as well as other modifications. This study is important because it facilitates the evaluators and improves the efficiency of the process to evaluate competencies in a profile as well as the efficiency of results which serve as input for process improvements. Finally, the results of the implementation of the framework based on indicators improved time efficiency (80.3%), use of resources (45.7%) and increased evaluator satisfaction (25.7%) with a value of p < 0.05 for all cases.
Hybrid Algorithm of Mobile Position-Trajectory Control

The paper describes a hybrid algorithm of position-trajectory control of a moving object, based on the integration of the wave and ant algorithms. The process of tracing the trajectory is carried out step by step. At each step relative to the current position of the moving object, a zone is formed within which all the obstacles are localized with the help of the radar, after which a separate trajectory section is constructed which is a continuation of the previously constructed section. And the entire trajectory is a collection of individual sections. The time complexity of this algorithm depends on the ant colony lifetime l (the number of iterations), the number of vertices of the graph n, and the number of ants m, and is defined as O(l∙n2∙m).
Uniqueness of Four Covering Arrays Equivalent to Error-Correcting Codes

A covering array CA(N;t,k,v) is an N × k array over v symbols where every N × t subarray contains as a row each t-tuple over v symbols at least once. Two covering arrays are isomorphic of one can be obtained from the other by permutations of rows, columns, and symbols in the columns. Isomorphic covering arrays form equivalence classes in the set of all CA(N;t,k,v). The problem of classifying covering arrays consists in generating one element of each isomorphism class; if there is only one isomorphism class, then CA(N;t,k,v) is unique. This work introduces two parallel versions of a previously reported algorithm to classify covering arrays. By using these algorithms we determine the uniqueness of the covering arrays CA(32;4,13,2), CA(64;5,14,2), CA(128;6,15,2), and CA(256;7,16,2). We also AƒÂ¯A‚Â¬A‚Ând that these four covering arrays are equivalent respectively to the unique error-correcting codes (13,32,6), (14,64,6), (15,128,6), and (16,256,6), where (n,M,d) denotes a code with word length n, M code words, and minimum distance d.
PENGARUH MEDIA INTERNET TERHADAP PRESTASI SISWA-SISWI DI SMA NEGERI 17 MEDAN

This study was conducted by using quantitative correlational method which tests certain theories of methods. This study aims at examining the extent to which variations in a factor are related to others. it was conducted to find whether there is influence between variables and if there are, how close the relationship is close and whether the relationship is meaningful or not. technique in getting the sampling in this study is by total sampling technique in which all the members of population are taken as sampling. In collecting data, researchers used a questionnaire as a data collection tool in this study. Data collected was analyzed using small table analysis, cross table and hypothesis testing using rank spearman. The results show that the influence of internet media on student achievement, this influence was a significant relationship, obtained based on the guilford scale is on a scale that shows a significant relationship. Thus it can be seen that the influence of internet media on student behavior and student achievement is very significant.
Implementation of Electronic Industrial Training Application for Industrial Training Management Based on Netbeans and Android

The research builds a management information system software that can be used by organizer and trainees in the industry. Training information system that aims to improve the effectiveness of managing industrial training and improve employee access to competency information and industry training. It is expected that there will be an increase in employee competencies so that it has an impact on increasing industrial production. The e-IndT application is designed in the form of applications for organizer and training participants. The design of e-IndT application was tested using the balckbox method and questionnaire. Testing on the e-IndT training application for training organizer in the form of time to search for data access, enter data, update data, delete data, and send data via e-mail and SMS then compared with classical systems. Testing on the e-IndT application for training participants in the form of a questionnaire with a quantitative approach. The results of the study stated that the effectiveness of the management of industrial training increased with the processing time in e-IndT applications faster than classical systems. Increasing training participants' access to competency and industry training information is achieved as evidenced by more than 95% of respondents stating the ease of accessing training information.