Reviewerly/exHarmony huggingface dataset:
Development of Kahoot Application-Based Learning Evaluation Tool Using Smartphones in Civic Education Lessons for Class XI of Madrasah Students

The purpose of this study was to develop Kahoot-based learning evaluation tools where lately technology has developed in education.The researcher developed a Kahoot-based learning evaluation tool by utilizing the potential that exists in the Batam high school state Islamic senior high school with the availability of Wi-Fi networks.This research method uses the Research and Development (R & D) method with a 4D model.The instruments used were questionnaires and questions about the pretest and posttest.Pretest and posttest questions are used to evaluate student learning outcomes.As for the results of the material expert validation, the percentage of 86% criteria was very valid, the media expert was 81% with Valid criteria, the teacher of civic education was 88.6% with valid criteria, Language 81% with valid criteria and 89.25% development trial, the field test was 83.4%.The results of pretest data analysis on average were 62.76%, and the posttest average was 73.43%.As for the pretest normality test results obtained sig values 0.59 > 0.05 which are categorized as Normal, Homogeneity test results obtained sig 0.021> 0.05 which are categorized as not Homogeneity two pretest and posttest variables that do not get a difference.The t-test uses paired sample t-test, then the sig value is 0.000 value <0.05, then Ho is rejected H1 is accepted because there are differences in the two variables pretest and posttest.
Semantic Information Retrival for Scientific Experimental Papers with Knowlege based Feature Extraction

Abstrack -Along with the times, demands for information retrievals in scientific papers have also increased.Regarding experimental scientific papers, researchers have difficulty in searching for information on experimental scientific papers because information retrieval engines have limitations in the search process due to text mining-based feature extraction of the entire text, while experimental types of scientific paper have specific contents, which should have a different treatment in feature extraction.In this paper, we propose a new system for information retrieval on experimental scientific papers.This system consists of 4 main functions: (1) Specific content-based feature extraction, (2) Classification model, (3) Context-based subspace selection, and (4) Context-dependent similarity measurement.In feature extraction, our system extracts feature category in experimental scientific papers with specific content-based features, which are data, problem, method and result.To perform the applicability of our proposed system, we tested 77 papers in the dataset with the Leave-One-Out validation model with several classification algorithm (Nearest Neighbour, Naive Bayes, Support Vector Machine and Decision Tree) and on average performed 66.65% precision rate and accuracy of 76,18% precision rate.We also made the experiment on the similarity, our proposed system performed 79.17% accuracy rate
A Fast Non-Overlapping Multi-Camera People Re-Identification Algorithm and Tracking Based on Visual Channel Model

In this paper, a nonoverlapping multi-camera and people re-identification algorithm is proposed. It applies inflated major color features for re-identification to reduce computation time. The inflated major color features can dramatically improve efficiency while retaining high accuracy of object re-identification. The proposed method is evaluated over a wide range of experimental databases. The accuracy attains upwards of 40.7% in Rank 1 and 84% in Rank 10 on average, while it obtains three to 15 times faster than algorithms reported in the literature. The proposed algorithm has been implemented on a SOC-FPGA platform to reach 50 FPS with 1280×720 HD resolution and 25 FPS with 1920×1080 FHD resolution for real-time processing. The results show a performance improvement and reduction in computation complexity, which is especially ideal for embedded platform.
Sentim at SemEval-2019 Task 3: Convolutional Neural Networks For Sentiment in Conversations

In this work convolutional neural networks were used in order to determine the sentiment in a conversational setting.This paper's contributions include a method for handling any sized input and a method for breaking down the conversation into separate parts for easier processing.Finally, clustering was shown to improve results and that such a model for handling sentiment in conversations is both fast and accurate.
From Field Observations and Plant Specimens to a Trans-continental Knowledge Base: Efficient, semantically rich integration of highly heterogeneous plant phenological data

Ideally, an information system that automates the integration of disparate datasets should be able to minimize the loss of information from any one dataset, achieve computational complexity suitable for working with large datasets, be flexible enough to easily incorporate new data sources, and produce output that is easily analyzed and understood by data users. Achieving all of these goals within highly heterogeneous and highly complex data domains is a major challenge. In this talk, we present the results of our recent efforts to develop such a system for data about plant phenology. Our data integration system, which is built around the Plant Phenology Ontology, currently supports semantically fine-grained integration of phenological data from both field observations and herbarium specimens. We show that even with a heavily axiomatized ontology and sophisticated, machine-reasoning-based data analysis, it is possible to implement a high-throughput data integration pipeline capable of processing millions of individual records in a matter of minutes while running on modest, server-class hardware. Success requires careful ontology design and judicious application of machine reasoning techniques. We also discuss some of the many challenges that remain for designing efficient, general-purpose data integration systems.
Automatic Detection of Circulating Tumor Cells with Very Deep Residual Networks

Automatic detection of circulating tumor cells (CTCs) in microscopic images is a very challenging task due to the variable artificial and environmental factors, such as inconsistency of light intensity and staining, cell adhesion, multiple impurities and so on. In order to meet these challenges, we propose a novel deep multiscale residual network (DMRN) for CTCs detection. Compared with existing methods either low-level hand-crafted features or CNNs with shallower architectures, our deep networks can acquire more discriminative features for more accurate detection. To train very deep networks more efficiently, we propose a set of schemes to ensure effective training and learning under limited training data. First, we apply the residual learning to generate more discriminative features and overcome the overfitting problem when a network goes to deeper. Then, a fully residual convolutional network (FRCN) is proposed to produce the prediction maps of CTCs. Finally, we propose to integrate multi-scale contextual information in proposed FRCN and fuse these prediction maps both global and local features of CTCs, making the prediction more accurate and robust. We built three DMRN models to study the impact of network depth on model performance. Each model was tested on our own dataset containing complex jamming information. The DRMN-50 model which has a depth of 50 layers performs best among three models with Jaccard-index of 0.810 (with a pixel accuracy of 99.8% as a reference index) and its performance outperform other existing state-of-art methods such as U-Net in other domain. The result also depicts the accurate and robust performance of proposed method in complex environment.
Geospatial Distribution and Analysis of Trace Element Geochemistry along the lower Reaches of Kassa River System Younger Granite Province, North Central Nigeria

A study was conducted to investigate the Geospatial distribution of trace elements including Iron along the lower reaches of theKassa river system within the Younger granite province of North Central Nigeria. A total of thirty sediment sample were collectedto investigate the concentration and potential environmental effects of trace elements within the area of study. The X-Ray fluorescence spectroscopy was used to determine the concentration of the trace elements including Iron while geographicinformation system technique of interpolation was used to interpolate not the element present but their ambient concentration as well. Results showed that the relative concentration of trace elements in the lower reaches of the Kassa river sediments is in the order Fe˃Ze˃Pb˃Th˃Rb˃Nb. Pollution Load Index values of studied area ranged from 0.596-1.476ppm which testify that theriver sediments are mostly unpolluted except for two of the sampling sites. However, the Igeo values indicate that anthropogenicactivities in the study area contribute to the distribution and concentration of the trace elements within the area of study.
Identification of Constitutive Parameters from Full Thermal and Kinematic Fields: Application to Hyperelasticity

In this paper, a new inverse identification method is developed from full kinematic and thermal field measurements. It consists in reconstructing the heat source from two approaches, a first one that requires the measurement of the temperature field and the value of the thermophysical parameters, and a second one based on the measurement of the kinematics field and a thermo-hyperelastic model that contains the parameters to be identified. The identification does not require any boundary conditions since it is carried out at the local scale. In the present work, the method is applied to the identification of hyperelastic parameters from a heterogeneous heat source field. Due to large deformation undergone by the rubber specimen tested, a motion compensation technique is developed to plot the kinematic and thermal fields at the same points before reconstructing the heat source.
DIGITAL TECHNOLOGIES IN HIGHER AND SECONDARY-SPECIAL EDUCATION: BLOCKCHAININ TARGET TRAINING OF INNOVATIVE PERSONNEL

The development of digital technology has lead to new opportunities for the organization of the educational process.The absence of scientifically -based advanced research methodology development of higher and secondary special education does not permit effective use of all the possibilities that digital technologies offer today.The most promising are the possibilities of working with big data (BigData); deep learning in a professional environment (Deep Learning); cloud and blockchain technologies (Cloud).It is likely that in the context of the development of virtual machines (VR), a number of previously unexplored educational opportunities will be implemented, which will complement the range of previously known teaching methods.Thus, modern didactics of vocational education for the successful realization of digital technology opportunities should be focused on the formation of a professional information culture for graduates.Formation of the methodology of smart didactics allowsthe expanding of the range of classification for approaches to teaching methods.Training specialists in terms of implementing the blockchain will allow the integration of the interests of employers, learners and the state, making it more open and focused.A special feature of preparation for the blockchain is the possibility of targeted training, for which a student in the first year knows about his future workplace and also an employer knows about his future specialist andis ready to provide the necessary practice on promising technologies.
Info-MIMBARDIK-Edutainment, Issue of March 2019

MIMBAR PENDIDIKAN: Jurnal Indonesia untuk Kajian Pendidikan (Indonesian Journal for Educational Studies). This journal, with ISSN 2527-3868 (print) and 2503-457X (online), was firstly published on March 11, 2016, by UPI (Indonesia University of Education) Press in Bandung and orgnized by the Lecturers of UPI Journal Developer Team. The MIMBAR PENDIDIKAN is a new version journal from the old journal with the similar name that was published since 1995 to 2005. This journal is dedicated not only for Indonesian scholars who concern about educational studies, but also welcome to the scholars of Southeast Asian countries and around the world who care and share related to the educational studies in general. The MIMBAR PENDIDIKAN journal is published twice a year i.e. every March and September.Bandung, West Java, Indonesia: March 30, 2019.Andi Suwirta, M.Hum.Managing Editor of MIMBAR PENDIDIKAN Journal; and Senior Lecturer at the UPI, Indonesia University of Education, Bandung, Indonesia. E-mail: suciandi@upi.edu
Sistem Informasi Just in Time Berbasis Markerless Mobile Augmented Reality

&lt;div&gt;&lt;p&gt;&lt;em&gt;Information related to tourist attractions is needed by tourists. The information can be seen through brochures and internet that has been provided by the government, the manager of the object or by a third party. Information technology is very helpful in memeberikan information needed by tourists. Augmented Reality (AR) has many advantages that can make the information provided to users more effective and efficient. Among them is by using a markerless method that can extend the detection range of AR applications so that tourists can search information from all tourist objects just by doing the scanning process. Like just in time philosophy, AR applications can be used to get the information as needed. Both of the desired tourist attraction information and in terms of connectivity required. In this research has resulted AR application with markerless method that can detect tourist object like monument from several side. In addition AR applications are created to recognize different objects so there is no error in providing information. No internet connectivity is needed in the early detection process and can use internet connectivity when needed, such as when looking for hotel room availability information.&lt;/em&gt;&lt;/p&gt;&lt;/div&gt;
High Voltage Circuit Breaker Fault Diagnosis Based on Reasoning chain and Bayes

Abstract In order to find the reason of the high voltage circuit breaker rejection quickly, an fault diagnosis method based on reasoning chain and Bayesian network (BN) is presented in the paper. Firstly, the concept of event set is introduced. A fault symptom set is constructed based on the measured circuit breaker characteristic parameters and warning signals. And the direct cause of circuit breaker failure, such as a part of the circuit breaker components or mechanism failure constitute the fault cause set. After that, when the high voltage circuit breaker fails, a subset of fault symptoms and fault causes is obtained according to the information. Then an reasoning chain is constructed according to the causal relationship between the two. Finally, a corresponding Bayesian network model for reasoning chain is built. The probability of fault causes is obtained by Bayesian backward reasoning, so as to realize the rapid analysis of circuit breaker faults. And the effectiveness of the method is verified by the result of practical fault diagnosis examples.
Specificity of Electronic Documents in the System of Library Funds

The purpose of the article is to reveal the specifics of electronic documents in the system of modern library funds. The methodology of the research is based on general scientific methods of knowledge, including a systematic approach that helped to analyze the electronic document as an integral part of the library business, funds and electronic document space as general systems; theoretical-empirical, abstraction, analogy, analysis, deduction, induction, reduction and synthesis methods have been used. Scientific novelty. The specificity of electronic funds in the context of domestic and world tendencies in the development of library activity is investigated; various aspects of the formation of funds of electronic documents and electronic libraries as an integral part of the library fund of the 20th century have been analyzed; The concept of «electronic document», «electronic fund», as well as differences of electronic library fund from electronic library is specified. Conclusions. The specifics of electronic documents as forms, which appeared as a result of the synthesis of documentary diversity and computer technologies, were determined, and possessed the properties of a document, combined with a class of technetronic documents, with specific general characteristics, and at the same time personal characteristics. It is revealed that replenishment of the electronic library of the library at the present stage is one of the priority directions of domestic libraries activity, both at the local and national level, taking place within the framework of creation of a single information space and provision of information in national and international information systems, according to the state target national-cultural program for the creation of a unified information library system «Library XXІ».
Curriculum Design: Implementations and Challenges (Case Study of the English Language Center in Indonesia)

As the crucial foundation of teaching learning process, curriculum should be well-designed by the curriculum developers.English curriculum in this language center has been developed years by years to find out an appropriate framework in order to provision students with certain abilities on English and the government pedagogical requirements.This study aims to seek the answers from purposive participants toward the three research questions; does the implemented curriculum meet the students' needs?, how are the curriculum of English certification programs designed?, what challenges do the curriculum developers face with in designing the curriculum?.A focus group discussion was used as the research approach to get in depth-data from participants.It was conducted for 12 hours.The research results illustrate that the designed-curriculum has met the students' need, internal institution policy and the development of other International tests.Likewise, the curriculum was designed by conducting need analysis, though the team encountered many challenges in designing it, for instance assessment and scoring.
A micro-task model for user-oriented semantic service description

SOA (Service-Oriented Architecture) has become a popular technology for developing network application. However, the current problem is new service cannot be quickly discovered, orchestrated and composed to match customer needs for insufficient capacity of semantic description of Web services. There is thus a need for an efficient way to describe services from users' perspective, instead of only realization-oriented description, to make web service the most widely used. This paper proposes a user-oriented semantic service description method which combines task model with semantic service to find a novel way that is suitable and intuitive for a service consumer. A micro-task model is proposed to enhance the capacity of semantic service description from four dimensions: user goal, context, displayed variable, activity; simultaneously, a services description framework based on micro-task model is proposed to accurately map user task into services.
REKAYASA PERANGKAT LUNAK PADA DATA NASABAH KREDIT PERMAISURI BERBASIS WEB

As part of the banking system under the supervision of the OJK.Bank Sumut Branch Rantauprapat always have to give maximum contribution in moving the economy as a whole.However, for the operation of loan financing products specially for SSI Credit (Sumut Sejahtera I) loan or commonly known as Permaisuri loan (Mandiri Suri Tauladan Women) the operational system still uses manual system, which is in need of operational system that can work quickly, effectively and efficiently.So to provide services in handling borrower customers with various financing system.Bank Sumut Branch Rantauprapat need a fast, efficient, and easy operation system for bank employees in passing lending procedures / financing to customers.There are several stages in the process of designing applications As for Programming Language used in making the System in question is Using PHP and MySQL.Application Database creation using MySQL and Xampp, Localhost Phpmyadmin.Preparation of this Final Project begins by formulating problems, Identifying problems, Destination Determination, Benefits and Collecting data on the History of the establishment of the Agency.Hopefully with this information system, can improve Performance in lending process / financing to customers.
DIAGNOSA PENYAKIT KULIT WAJAH MENGGUNAKAN METODE DECESSION TREE DAN ALGORITMA C4.5

Today's face is something that is very much considered by both women and men. Women and men do facial treatments so often because the face is the first thing to see when meeting someone. However, there are those that often interfere with the face, one of which is a skin disease that is very diverse ranging from acne, dullness, blackheads to cancer. In fact, to overcome this, many people always consult with doctors, especially face problems. One thing that can be done is to diagnose facial skin diseases using the decession tree method and the c 4.5 algorithm. The existence of this system is expected to be a solution in conducting consultations for women and men for facial problems. By using the decession tree method and the c 4.5 algorithm and by using a number of data mining, it will give results that can be used as guidelines in treating facial skin diseases. In addition, the existence of this system will also be very helpful in the field of services to consumers, both women and men, especially for facial care to avoid facial skin diseases, which has been a problem so far.
Detection and Content Retrieval of Object in an Image using YOLO

It is easy for human beings to identify the object that is in an image.Even if the task is complex, human beings require only a minimal effort.Since computer vision is actually replicating human visual system, the same thing can be achieved in computers when they are trained with large amount of data, faster GPUs and many advanced algorithms.In general terms, Object detection can be defined as a technology that detects instances of object in images and videos by mimicking the human visual system functionalities.The motivation of the paper is making the search process easier for the user i.e., if the object is very new for the user and he has no idea about it, he can upload a picture of that object and the algorithm will detect the object and gives a description about it.The objective of the paper is to detect the object in an image, once the object is detected, the label i.e., the name of the detected object is searched in Wikipedia and few lines of description about that object is retrieved and printed.Also, the label is searched in google and the URL of the top pages with content related to the label are also displayed.The detection of object in an image is done using YOLO (You Only Look Once) algorithm with pre-trained weights.Previous methods for object detection, like R-CNN and its variations, used a pipeline to perform this task in multiple steps.This can take some time for execution, complex optimization may be involved because individual training of components is required.YOLO, does it all fastly with a single neural network.Hence, YOLO is preferred.