Reviewerly/exHarmony huggingface dataset:
Transforming an Optical Flow Sensor into an Angular Displacement Sensor

In this study, we used the common and low-cost optical flow sensor as the core of image processing. We simply adopted a set of designed discs with pattern sticker on it as a disc-shaped reader to transfer the angle variation (rotation) to a linear motion. Angle variation is obtained using lower cost sensors. Therefore, significantly reduction of the manufacturing cost of the grating, which is inside the optical angle encoder could be made. Angle sensors can be used more widely and universally in a wide variety of designs in the foreseeable future.
Objective Evaluation of Hand ROM and Motion Quality based on Motion Capture and Brunnstrom Scale

Evaluation of hand performance based on the collected data can be used to objectively and accurately assess the characteristics of hand motion quality for stroke patients. Current hand motion assessment is usually done by clinicians, which is heavily dependent on the therapist’s experience and subjective judgment, the quality of motion is not quantifiable and intuitional. This paper proposes an objective evaluation method of the hand motion quality using the optical motion capture system combined with Brunnstrom criteria which is assessment a scale commonly used in clinics. The motion capture system is used to detect the maximum range of motion (ROM) of ten finger joints during the hand motion. A K-Nearest Neighbor algorithm is adapted to classify the hand movement quality levels of Brunnstrom evaluation criteria. Computer recognition of rehabilitation assessment of medical scale is realized, and it can intuitively and accurately reflect the user's hand movement state. Experiments were designed by taking into account the motion characteristics of Brunnstrom assessment, and the ROM of five common hand movements, including common flexion, coextension, thumb flexion, thumb-pinch, and spherical grasp were measured. A comparative study was conducted between the proposed method and the Brunnstrom scale, and the results verified this method’s capability in evaluating the human hand motion quality, which has potential for rehabilitation evaluation of the hand motion of stroke patients and to provide the basis for the formulation of rehabilitation training programs.
An Analysis of Students' Errorneous Sentence Found in Descriptive Text Written by Students in Sintang

The problems of this research were the students tended to use the Indonesian language structure when translating. Besides, they wrote a false word order in their sentences and also misuse the tenses for the existing sentences. This research aimed to identify and describe the studentsâ€™ errors in the form of interlingual errors and intralingual errors. The qualitative research design was used to analyze the data. There were 70 samples of studentsâ€™ writing tasks which were taken from three state senior high schools and three private senior high schools in Sintang city. The finding showed the aspects that more influenced the learners made errors when transferring the first language to the target language were identified as two major aspects. The errors caused by the studentsâ€™ first language are interlingual. While the errors caused by the structure of the target language are called intralingual errors. To identify the interlingual errors the researchers used two subcategories. They were the use of the L1 structure and the omission of BE form. The most error in interlingual errors was caused by the L1 structure. Meanwhile, the researchers used four subcategories to identify intralingual errors. They are overgeneralization, ignorance of rule restriction, incomplete application of rules and false concepts hypothesized. The most error in intralingual errors happened because of the learnerâ€™s limited knowledge of the target language. Based on these findings, Teachers can solve the problems by providing explicit and implicit corrective feedback, introducing the grammar system of both Indonesian and English when teaching grammar.
Optical Unmarked Motion Capture Technology Based on Depth Network and Binocular Vision

This paper presents an optical unmarked motion capture method based on depth network and binocular vision. This method optimizes the marked motion capture technology, eliminating the need for additional markers to reduce the complexity of the motion capture system. At the same time, this paper also optimizes the human joint point coding method, which can obtain the sequence numbers and interdependence of 18 human joint points including the toes of the human body. Then we utilize the deep convolutional neural network to extract the coordinates of the two-view 2D human joint points. Through the binocular vision principle and the least squares method, the 3D coordinates of the human joint points are obtained. According to this, the human skeleton model is drawn to reflect the human body motion state.
A Deep Semantic Matching Network for Answer Selection

Answer selection is a critical task for a conversation system. The previous methods about the answer selection cannot incorporate the context dependency information into the representations of the sentences in the conversation, which ignores the effective part for the answer selection. In this paper, we design an algorithm that contains attention mechanism to compute the matching degree for question-answer pairs. In order to capture the context dependency information between the sentences, the question-answer pair is first processed by the attention module designed in our network. The semantic matrices at different levels of granularity are constructed to carry abundant and computer-understandable semantic information of the sentences. Next, the multiple matching matrices are generated to represent the matching between them. More abstract and sophisticated matching features are extracted from the matching matrices by our network. Finally, the matching features are used to compute the matching degree of the question-answer pairs. We evaluate our proposed architecture on a benchmark dataset about the answer selection. Experimental results show that our architecture, which contains the attention mechanism, is more effective and more superior than baseline models.
Implementation of C4.5 Algorithm for Critical Land Prediction in Agricultural Cultivation Areas in Pemali Jratun Watershed

Watershed is a complex system that is built on physical systems, biological systems and human systems that are related to each other. Each component has a distinctive nature and its existence is related to other components so as to form a unified ecosystem. Land use that does not pay attention to the conservation requirements of land and water causes land degradation which ultimately results in critical land. The impact of critical land is not only the withdrawal of soil properties, but also results in a decrease in production functions. Prediction of the critical level of land is needed to reduce the level of damage to the watershed, so that it can be used for policy making by the relevant agencies. In this research C4.5 algorithm will be applied to predictions of critical land in agricultural cultivation areas using critical land parameters. Based on the results of the research on critical land classification of agricultural cultivation areas in the jratun pemali watershed it can be concluded that the C.45 algorithm can be implemented to predict critical land in agricultural cultivation areas with an accuracy rate of 92.47%.
Interlinking RDF-based datasets: A structure-based approach

With an increase in the number of Linked Open Data datasets, insufficient interlinking quality can lead to a decrease in overall data quality. Therefore, it is necessary to keep the interlinking quality as high as possible. One of the main ways to link datasets is to use owl:sameAs links, i.e. to indicate that two things are the same. But with its strict semantics, there is a lot of misuse of owl:sameAs in the wild. Indeed, identity is often relative and depends on the context of use. We therefore propose an approach that enables considering the characteristics of involved datasets to interlink datasets thanks to owl:sameAs statements. The experimental results performed on real-world datasets show that the proposed approach is promising.
Enhancing Security in Medical Image Informatics using Geometrical Attacks

The objective of this study is to provide security to medical images by embedding medical data (electronic patient record; EPR) along with the images to reduce the bandwidth during communication.Reversible watermarking and digital signature, will provide high security.This application is mainly used in telesurgery.Only the authorized medical experts can explore a patient's image because of the use of the authentication Kerberos.The proposed study is mainly to restrict unauthorized access to patients' data.Hence medical image authentication may be achieved without biometric recognition such as finger prints, eye stamps, etc.Since the EPR itself contains a patient's entire history, after the extraction process medical experts can identify the patient and also the disease information.In future we can embed the EPR inside the medical image after encryption to enhance security.To improve the authentication, medical expert biometric information can be embedded inside the image in the future.Experiments were conducted using more than 500 (512 × 512) image archives in various modalities from the National Institutes of Health, USA, and Aycan sample digital images downloaded from the internet.Almost all images with greater than 15,000 bits showed 60.4-78.9dB PSNR value with less alteration in the restored image because of compression, not of watermarking, and the average (number of pixels change rate) was 98.9%.
Monocular 3D Reconstruction of Human Body

Human body 3D reconstruction using a monocular camera involves issues of geometry and appearance in the field of computer vision. A common idea of human 3D reconstruction is that fusion of point clouds collected by multiple RGBD cameras such as kinect v2 from different angles. However, depth cameras are more expensive than RGB cameras and they have stricter requirements of the environment. There are also many methods to reconstruct the point clouds of objects using multiple normal RGB cameras or monocular cameras. In this work, we propose a new application of Structure-from-Motion on human body 3D reconstruction. Structure-from-Motion is a process that the 3D structure is created by analyzing 2D image sequences, which is very prevalently used in many applications of computer vision. In our approach, we achieve human body 3D reconstruction for a 3D video conference using a monocular RGB camera.
Duality in Deep Reinforcement Learning— Implementation

More and more deep reinforcement learning algorithms have been proposed and demonstrated on a series of decision-making domains. With duality in deep reinforcement learning substantially summarized, this paper summarizes duality in deep reinforcement learning and proposes the duality with priority in Part I-Theory. It proposed an asynchronous architecture for dual priority in deep reinforcement learning. Experiments improve the state of the art on discrete action environments as well as continuous control tasks, while demonstrate its final performance and data efficiency.
Category-Level Multi-Attention based Boundary Refinement for Action Detection

Temporal action localization has attracted considerable attention in recent years. Most previous work focused on a fully supervised setting leveraging frame-level action labels. However, it is usually expensive and time-consuming to acquire precise temporal annotations. In this paper, we focus on a weakly supervised setting using only video-level labels to address the temporal action localization task. A category-level multi-attention based method is proposed to provide a comprehensive representation for each action category and obtain much more precise temporal intervals. Our method is evaluated on the untrimmed THUMOS14 video dataset, and the experiments have provided very positive results.
Penetapan Instruktur Diklat Menggunakan Metode Clustering K-Means dan Topsis Pada PT PLN (Persero) Udiklat Jakarta

Instructor is the main aspect that exists in the implementation of the training. The increasing number of instructors and the need for training is also increasing every year there is no system that can help the process of determining quickly and precisely. In need of a method that can classify the instructor data in accordance with the title of training materials and can be assigned instructor each of the training materials and do not ignore aspects of assessment of the instructor. In this study data mining techniques are used to help recommend instructors for each subject matter of the training based on the cluster data group approach. So it can be used in determining the instructor's assignment per training materials in the future. K-Means clustering method is used to group data into clusters by looking at the centroid value that has been determined. And the Topsis method is used to assign one instructor's name through the rankings of preference values. In this research CRISP-DM method is used as software engineering method system work done in sequence or linearly. In the testing process has been generated if the manual data and data processing if the application system is the same. This application to facilitate the Supervisor and Learning Development staff in setting instructors per training materials.
PENGARUH TEKNIK MIND MAPPING TERHADAP KETERAMPILAN MENULIS PUISI SISWA SEKOLAH DASAR

Abstract. This research is motivated by the low writing skills of poetry. This is characterized by students' poetry writing skills that are not productive, still informative, students are still difficult to express their ideas, and are less attractive to students because they only use one technique. One learning technique that can improve poetry writing skills is mind mapping techniques. Mind mapping is also a learning technique to stimulate students' imagination in generating ideas, recording and summarizing using mind mapping. This study aims to examine the effect of Mind Mapping Technique on Poetry Writing Skills of students in elementary school.This study was an experimental study of Quasi Experimental Design with Nonequivalent Control Group Design. The population in this study were all fifth grade students of class V. Sampling is done by saturated sample technique (total sampling), namely VB class as an experimental class and VA class as a control class. The experimental class consisted of 34 students and the control class consisted of 36 students. The instrument used to determine the effect of mind mapping techniques is observation and documentation. The experimental class was treated by using mind mapping techniques in poetry writing skills while the control class without using mind mapping techniques.Based on the results of the pretest obtained the average value of the experimental class 60 and the average value of the control class 64.2. From the results of the comparison of the two sample classes, there was a difference in value of 3.7, so it can be concluded that there is no significant difference between the two pretest grades, meaning that the two classes have the same initial ability. Next, learning was conducted using mind mapping techniques in the experimental class and learning without mind mapping techniques in the control class. After learning is given then in both classes posttest is conducted. For the experimental class obtained an average value of 82 and for the control class obtained an average value of 77.5. From the results of testing hypotheses with a significant level of 0.05 obtained a significant value of 0,000 because sig. &lt;α, the hypothesis is accepted, so it can be concluded that there is an effect of using mind mapping techniques on students' poetry writing skills in elementary school. Keywords: Mind Mapping Techniques, Writing Skills, Poetry
Internet Use, Reading Habit and Reading Ability of Students of Private Junior High Schools in Kecamatan Ilir Timur II Palembang

This study was aimed to find out whether or not (1) there is Â any significant correlation between reading ability and reading habit, (2) There is any significant correlation between reading ability and internet use, (3) There is any significant correlation among reading ability, internet use, and reading habit of students of private junior high schools inÂ Kecamatan Ilir Timur II Palembang. This study was a quantitative research approach with a corelational research design. The researcher collected the data through 2 instruments namely, reading test and questionnaires. A test was used to find out studentsâ€™ reading ability and questionnaires were used to find out studentsâ€™ reading habits and internet use. The population of this study was 803 and 120 for the population. To analyze the data, the procedures were presenting and describing the data,Â testing the hypotheses, and analyzing the regression. From the results, only internet use and reading ability that had a significant correlation (p-value &gt; 0.05). The result of the regression analysis between internet use to reading ability showed that the correlation between those variables was 16,7%.
Variance-based Features for Keyword Extraction in Persian and English Text Documents

This paper address automatic keyword extraction in Persian and English text documents. Generally, for keyword extraction in a text, a weight is assigned to each token and words having higher weights are selected as the keywords. We have proposed four methods for weighting the words and have compared these methods with five previous weighting techniques. The previous methods used in this paper are term frequency (TF), term frequency inverse document frequency (TF-IDF), variance, discriminative feature selection (DFS), and document length normalization based on unit words (LNU). The proposed weighting methods are based on using variance features and include variance to TF-IDF ratio, variance to TF ratio, the intersection of TF and variance, and the intersection of variance and IDF. For evaluation, the documents are clustered using the extracted keywords as feature vectors, and K-means, expectation maximization (EM), and Ward hierarchical clustering methods. The entropy of the clusters and pre-defined classes of the documents are used as the evaluation metric. For the evaluations, we have collected and labelled Persian documents. Results show that our proposed weighting method, variance to TF ratio, has the best performance for Persian. Also, the best entropy is resulted by variance to TD-IDF ratio for English.
The Correlation Between Listening Habit to English Song and Vocabulary Mastery

ABSTRACTThe aims of this research were to find out the correlation between students’ listening habit to English song and their vocabulary mastery. This research applied correlational study which was used quantitative design. The subjects were 60 students of Third Grade Students of SMPN 06 Kota Bengkulu. The data were collected from two instruments: (1) questionnaire was used to get data about students’ listening habit to English song and (2) VLT test was used to get data about students’ vocabulary mastery. The result of calculation was using Pearson Product moment formula process by SPSS IBM Statistic Version 20 Program, which showed the score of rxy bigger than the score of r table (0,835 &gt; 0,254). It means that Ha was accepted and H0 was rejected. In conclusions, there is a positive and significant correlation between listening habit to English song and vocabulary mastery of third grade students of SMPN 06 Kota Bengkulu.
On Finding Two Posets that Cover Given Linear Orders

The Poset Cover Problem is an optimization problem where the goal is to determine a minimum set of posets that covers a given set of linear orders. This problem is relevant in the field of data mining, specifically in determining directed networks or models that explain the ordering of objects in a large sequential dataset. It is already known that the decision version of the problem is NP-Hard while its variation where the goal is to determine only a single poset that covers the input is in P. In this study, we investigate the variation, which we call the 2-Poset Cover Problem, where the goal is to determine two posets, if they exist, that cover the given linear orders. We derive properties on posets, which leads to an exact solution for the 2-Poset Cover Problem. Although the algorithm runs in exponential-time, it is still significantly faster than a brute-force solution. Moreover, we show that when the posets being considered are tree-posets, the running-time of the algorithm becomes polynomial, which proves that the more restricted variation, which we called the 2-Tree-Poset Cover Problem, is also in P.
A Document Driven Dialogue Generation Model

Most of the current man-machine dialogues are at the two end-points of a spectrum of dialogues, i.e. goal-driven dialogues and non goal-driven chit-chats. Document-driven dialogues provide a bridge between them with the change of documents from structured data to unstructured free texts. This paper proposes a Document Driven Dialogue Generation model (D3G) which generates dialogues centering a given document, as well as answering user's questions. A Doc-Reader mechanism is designed to locate the content related to user's questions in documents. A Multi-Copy mechanism is employed to generate document-related responses. And the dialogue history is used in both mechanisms. Experimental results on the CMU_DOG dataset show that our D3G model can not only generate informative responses that are more relevant to the document, but also answer user's questions better than the baseline models.
Implementation of Tourism Information System at Tuban Regency

Republic of Indonesia The Ministry of Communication and Information Technology in Tuban Regency inmanaging tourism sector is still minimal because it still displays a less attractive website to attract travelers when theywant to vacation in Tuban Regency. The purpose of this program is to develop the Tuban Regency Tourism systemby using website because this can make it easier for people who really need it in finding tourism objects in Tuban.We used an observation as the first instrument by observing Tuban regency from many sides, interviewedsome tourists which visited Tuban more than once, and read some articles from journals and books.The role of Communication and Information Technology Department in Tuban Regency is a key to successin Tuban Smart City in 2021. Tuban as City Smart, making integrated applications in both the tourism sector and other parts, this activity has become increasingly important in order to meet the twenty-first century which is all digital.
Students' Perceptions of Mobile Technology in Higher Education: Preparation to Design Mobile Learning Models

Education in the industrial revolution era 4.0 shows a change in the way of learning, thinking patterns and ideas of acting in high school students.One part that is inseparable from that is the use of mobile technology.This study aims to describe students' perceptions of the use of mobile technology as a tool for developing the right learning media in lecture activities at universities.This type of research is descriptive with a survey method of 100 students.The technique of collecting data uses a questionnaire.The findings show that students are very familiar with mobile technology, but the usage is still not directed according to the competencies to achieve in certain subjects.The results of this study also revealed that students have a positive perception of mobile technology.This report can be taken as a preparation for the design of a mobile learning model in higher education.