Reviewerly/exHarmony huggingface dataset:
Accreditation document tracking system using Scrum approach

Document tracking which involves recording and monitoring the movement of documents has been a time-consuming task for staff. Dislocation and overlooking of the timeline have always been the problems in document control. An effective tool such as a web-based system is the easiest way to be implemented in the workplace. The Accreditation Document Tracking System (ADTS) is designed to monitor the movement and timeline of the document from a department to another department throughout the accreditation process efficiently. The main objective of this project is to develop a system that can track the location of a document and its status of submission at every stage. This advantageous system is developed through scrum approach, which is the most widespread agile methodology used in the industry. It offers flexibility and simplicity to the system developer in upgrading the system. Furthermore, the Unified Modelling Language (UML) is used to describe the interaction between user and proposed system. UML consists of three visual diagrams: (i) Use case diagram, (ii) activity diagram, and (iii) sequence diagram. By following each stage of the diagrams, the proposed system is able to be developed in order to achieve the objective of this project within within the university as well Malaysian Qualification Agency (MQA) and Ministry of Higher Education (MOHE).
Examination of the Conversations in a WhatsApp Group Created for Communication in a Bachelor’s Level Astronomy Course

The aim of this research on an astronomy course is to examine the situations that arose when WhatsApp, a social media application, was used as a tool for cooperation and interaction. In this work, a case study design was adopted. The WhatsApp group created for the research was composed of 87 participants and the messages exchanged in the WhatsApp group were used as research documents. Data were analyzed through descriptive and content analysis methods. The sharing in the WhatsApp group and the topics of the messages were revealed in the content analysis. The research results showed that the students used the WhatsApp group as an interaction tool in an extracurricular environment. It was also determined that they used this platform in order to inform each other about daily events and share and discuss information.
The impact of Local language Dialect toward the Teachers Language Attitude in EFL Class Room in South Sulawesi, Indonesia

The behavior that shows a misunderstanding of Standard English becomes an indicator of dialect prejudice (Devi & Kariko, 2017).This issue attracted the writer to observe the language attitude that arises due to the influence of local dialects on the use of English in speaking.In this case, the dialect prejudice of the English teachers toward English spoken by the students.Regarding the observation, the researcher investigated English teachers in some schools, a university and a course institution in South Sulawesi, to find out whether there is a language prejudice toward local dialect in EFL class.South Sulawesi is considered such a right location to conduct the investigation because there are many local dialects that still spoken by the society (including teachers and students) such as local dialects of Bugis, Toraja, Makassar, Mandar, and etc.There were 10 participants from a different area, and the teaching place had responded to nine items of questionnaire and two interview questions regarding the aims of the study.The data analysis shows that the English teachers misunderstand the standard English should be, and the dialect prejudice happens in the EFL classroom.
Exploration of Multidimensional Teaching Method Around Assembly Language Programming Course

Aiming at the problems existing in the teaching content and process of assembly language program designed for computer majors in colleges and universities, the key problems such as course motivations, teaching methods, practice teaching and course assessment reform were discussed in this paper, and the reform ideas and implementation plans were put forward.
Discusión teórica sobre las prácticas docentes como mediadoras para potencializar estrategias metacognitivas en la solución de tareas matemáticas

espanolUna de las expectativas de la educacion basica y media superior es lograr que los estudiantes sean sujetos activos y regulen sus aprendizajes. Aunque investigaciones recientes retoman el interes por discutir la metacognicion y su impacto en el aprendizaje de las matematicas, la discusion no profundiza en el papel del profesor. El objetivo de este articulo, es hacer una reflexion teorica sobre las acciones del docente que pueden potencializar estrategias metacognitivas en la ensenanza de las matematicas para un aprendizaje autorregulado, tomando como referente la metafora de andamiaje. En el documento se discute el concepto de metacognicion y su relacion con el aprendizaje autorregulado, se exponen las principales lineas de investigacion sobre las practicas docentes en torno a la metacognicion, y se analiza el papel del docente como un mediador necesario en la realizacion de tareas matematicas que los alumnos no lograrian por si mismos en una primera instancia. EnglishOne of the aims of basic and middle education is to enable students to become active learners and to regulate their learning processes. As a result of this, current research looks at metacognition and its influence on mathematics learning, but the role played by teachers in promoting metacognition has not been studied in depth. The purpose of this paper is to develop a theoretical discussion on the teaching actions that potentiate metacognitive strategies. This discussion is focused on mathematics teaching for self-regulated learning, and it takes as a reference the scaffolding metaphor. In order to achieve its purpose, the paper first examines the concept of metacognition and its relationship with self-regulated learning; afterwards the main research strands on metacognition are presented and the role of the teacher as a mediator in solving mathematical tasks is analyzed. The literature review shows that teachers build scaffoldings in order to potentiate metacognition in students, and these scaffoldings lead students to determine, execute and assess procedures in the course of solving mathematical tasks.
Mobile robot position control in environment with static obstacles

This study addresses the problem of efficiently navigating a differential drive mobile robot to a target pose in a region with obstacles, without explicitly generating a trajectory. The robot is assumed to be equipped with an omnidirectional range sensor, while the region may or may not be a priori known. Given the known obstacles in each iteration of the controller, the shortest path connecting the robot and the target point provides a raw desired movement direction. Considering the unobstructed area in that direction, the size of the robot and the obstacle contours in its visibility range, the reference direction is determined. Finally, respecting the velocity and acceleration constraints of the robot, the angular velocity is properly selected to rotate the robot towards the reference direction, while the linear velocity is chosen to efficiently minimise the distance to the final target, as well as to avoid collisions. After the robot has reached the target, the controller switches to orientation mode in order to fix the orientation. Experimental studies demonstrate the effectiveness of the algorithm.
Relationship of associated clusters degree with metal ionization according to the cluster-associate model

Relationship of associated clusters degree with metal ionization according to the cluster-associate modelThis article deals with a cluster-associate model of kinematic viscosity of liquid metals.This model was derived from the concept of chaotized particles.According to the proposed model, the authors calculated average values clusters association degree contained in liquid metal.28 metals of the secondsixth periods of D.I. Mendeleyev element table were studied for calculation.The authors compare the first potential of metal ionization with the obtained values of clusters association degree.This comparison showed a regular change in clusters association degree closely connected with the change in the first ionization potential.In combination with the Fraenkel equation, an approximate equation was obtained to calculate activation energy.The obtained equation for the cluster-associate pattern of viscosity temperature dependence is used in calculating the activation energy of viscous melt flow for twenty-eight metals.The obtained results on activation energy were compared to experimental data.This comparison showed that the activation energy data obtained from the proposed model is described better by the approximating dependence.Tables and figures are given in the work for visual confirmation of the obtained results.Thus, in the process of comparing the first potential of metal ionization for all periods of D.I. Mendeleyev element system with clusters association degree, their regular connection was revealed.This connection makes it possible to assert the functional aspect of the cluster-associate pattern.
Numerical analysis of least squares and perceptron learning for classification problems

This work presents study on regularized and non-regularized versions of perceptron learning and least squares algorithms for classification problems.The Fréchet derivatives for least squares and perceptron algorithms are derived.Different Tikhonov's regularization techniques for choosing the regularization parameter are discussed.Numerical experiments demonstrate performance of perceptron and least squares algorithms to classify simulated and experimental data sets.
Study of a Code Comment Decision Method Based on Structural Features

Code comment is one of the most effective ways to help programmers to understand the source code. High-quality comment decisions can not only cover the core code snippets in the software system but also avoid generating redundant code comments. However, in actual development, there is no uniform comment specification, and most of the comment decisions depend on personal experience and domain knowledge. This paper has learned a common comment decision specification from a large number of code comment examples to assist programmers in making appropriate comment decisions during code development. This paper proposes a method to extract the code structure from the context code of the current code line, and use the machine learning algorithm to determine the possibility that the current code needs to add comments. The proposed method was evaluated on 8 well-known open-source Python projects in GitHub and the experimental results show the feasibility and effectiveness of the method in some code types.
It Doesn’t Have to Be So Hard: Efficient Symbolic Reasoning for CRCs

Cyclic redundancy check functions (CRCs) are commonly used as checksums in hardware and software systems.Though some previous work has treated CRCs as if they would be difficult for automated reasoning or proposed using them for obfuscation, we argue that CRCs need not be difficult for symbolic execution.CRCs have a strong algebraic structure, and the key to efficient reasoning about them is exposing this structure.Common CRC implementation techniques use perbit branching or lookup tables, but these code structures can be compactly summarized by symbolic execution engines that perform path merging or create formulas reflecting the contents of a table, respectively.To evaluate the effectiveness of these techniques, we test the binary symbolic execution tools angr and FuzzBALL, and the Java bytecode tool Java Ranger, on symbolically finding CRC preimages for output sizes of 32 and 64 bits and input sizes up to 8192 bytes.The best configurations can find short CRC preimages in just a fraction of a second and long ones in under 10 seconds, demonstrating that constraint solving with CRCs is not difficult.
Effectiveness of Using 2D Animation Video with Live Shoot Motion Graphic

Programming is not just about writing programs that are "as long as they are", "as long as they can run", "as long as they can deliver the results they expect".Programming requires good methods, techniques, and methodologies so that the written program is an effective program.It is true that many people can make programs, but only a few can program properly.In current technological developments, Algorithms play an imperative part in the field of programming.Especially in the lectures of the Department of Informatics, its relationship is strong with its specific algorithmic programming for students of Multimedia Engineering and Network Study Program.An understanding of algorithms is needed so that it can make the program more effective and efficient.To be able to help students understand the Algorithm and programming material, suitable learning media are important.Media that can be used are 2D Animation Video and Live Shoot Motion Graphic.Given the development of learning media in the form of 2D Animation Video and Live Shoot Motion Graphic that can help students understand the concepts of Algorithms and Programming, it is necessary to conduct research related to testing the effectiveness of learning.This study compares the effectiveness of the use of 2D Animation Video with Live Shoot Motion Graphic on the first-semester student of Multimedia Engineering and Network, Politeknik Negeri Batam.The results of this study indicate that learning using 2D video with live shoot motion graphics is relatively better than learning using power-point.
Parental Motivation and Achievement

The motivation that parents provide to their students can have a significant impact on achievements in school. The study intends to assess the level of parental motivation and achievers of junior high and senior high. Parental motivation is given by the parents towards their students to make them work harder or being determine their studies that leads them to have better achievements in school. The checklist is made up of two parts, parental motivation and the level of achievement. The research was a quantitative correlation design. The respondents are the achievers from junior high and senior high and consist of overall respondents of 145 respondents. To treat the data, the researcher used a statistical test the weighted mean, chi – square to determine the relationship of the two variables. The study revealed that parents do not always provided a motivation to their students most of the parents sometimes give a motivation to their student. However, the achievements of students are still in high level. The achievements of students do not always depend on their parents’ motivation yet their achievement is based on their personality of being determined and consistent in their studies. Not all the time that the motivation of parents can enhance the educational achievements of students.
Detection of Threat Situation for UAV Collision Avoidance Based on Sliding Window Polynomial Fitting Prediction Method

The detection of air threat situation is the key to the early warning for UAV flight collision avoidance. For this reason, a detection method of air threat situation based on sliding window polynomial fitting prediction is proposed. Firstly, the sliding window polynomial fitting method is used to dynamically predict the track of the intruder. Then, on the basis of the track prediction, using the flight information of UAV and intruder, the detection and alarm for flight conflict trend between UAV and intruder is carried out in a specific flight scenario. Simulation validates the effectiveness of the proposed method and the feasibility of application in the early warning for UAV flight collision avoidance.
ELT Comparison: Increasing Students Speaking Ability in Indonesia, South Korea, Russia, and Poland

English as a global language facilitates the people to communicate with each other despite different lingua-cultures or accent. Communication will be something important to build the socio condition of civilians in every single country. This background of research leads to get to know about English Language Teaching (ELT) to the people whose first language is not English. Each country in Asia or Europe whose English is not their first language has its differences in teaching and learning about English. The four basic things of English, such as reading, writing, and speaking will be the challenges that they need to be faced. According to the basics of four skills, speaking is the hardest one for most non-native speakers. Therefore, the teachers need to have particular ways to teach about speaking to increase students’ skill ability in EFL countries. This research is aimed to show the differences and comparisons among Indonesian and South Korea as the representatives of Asia, also Russia and Poland as the representatives of Europe whose first language is not English. This purpose means that people can distinguish among different types in each country for teaching and learning English, moreover for speaking skills.
Building FL-Vocabulary Transferability through Semantic Boggle

The purpose of this study was to investigate the effectiveness of the Semantic Boggle Game on building vocabulary transferability in foreign language students. The study was conducted in SMPN 177 Jakarta. The population in this study was all seventh-graders of which 7E of 35 students as the sample representative. The method used in this study was a quantitative method with a pre-experimental research design. In collecting the data, the writer used the students' pre-test and post-test. The data result indicates that the total students' pre-test scores are 2085 with an average score of 59,57. The total student's post-test score is 2745 with an average of 78,68. The results of the pre-test and post-test were calculated using a t-test. The calculation of the data result indicates that the t-count was 2,26 with t-table is 1,69 at the 0,05significance level. Therefore, this implies that the alternative hypothesis (H1) is accepted and the null hypothesis (H0) is rejected. The writers then concluded that using Semantic Boggle Game in teaching vocabulary is effective to build students’ vocabulary transferability.
The Application of Intersection in the Set Theory for Instagram Hashtags

Technology is developing rapidly with the advent of social media, which paper messages are substitutes for electronic messages that make someone is easier to communicate with others. Many social media exist. The famous ones are Facebook, Instagram, Twitter, and others. With so many social media emerging, every social media must have differences with other social media. Instagram has quite a lot of users, especially in student organizations on campus. The hashtags feature of Instagram makes it is easy to search what to find for people, and group them according to the hashtags used. This paper studies an implementation of intersection operators and applies the intersection operator to classification of Instagram’s hashtags.
Research and Application of Image Edge Detection Algorithm Based on FOA

Traditional differential-based edge detection algorithms have shortcomings such as inaccurate edge point positioning and corner point missing detection. This paper presents an application of FOA (Fruit Fly Optimization Algorithm) for establishing an image edge tracking model. Firstly, the prior knowledge of edge points is obtained by Canny edge detection operator. Then the corner points are extracted by Hilbert transform, and the edge tracking is accomplished by the coordination of the two mechanisms of randomness and positive feedback; Finally, a single pixel edge is obtained by using the forward movement mechanism and the loop termination condition. Compared with the original Canny edge detection algorithm, the precision and accuracy of image detection are better
Generation of 3D Tumor Models from DICOM Images for Virtual Planning of its Recession

Medical images are essential for diagnosis, planning of surgery and evolution of pathology. The advances in technology have developed new techniques to obtain digital images with more details, in return this has also led to disadvantages, such as: the analysis of large volumes of information, long time to determine an affected region and difficulty in defining the malignant tissue for its later extirpation, among the most relevant. This article presents an image segmentation strategy and the optimization of a method for generating three-dimensional models. A prototype was implemented in which it was possible to evaluate the segmentation algorithms and 3D reconstruction technique, allowing to visualize the tumor model from different points of view through virtual reality. In this investigation, we evaluate the computational cost and user experience, the parameters selected in terms of computational cost are the time and consumption of RAM, we used 140 MRI images each with dimensions 260x320 pixel, and as a result, we obtained an approximate time of 37.16s and consumption in RAM of 1.3GB. Another experiment carried out is the segmentation and reconstruction of a tumor, this model is formed by a three-dimensional mesh made up of 151 vertices and 318 faces. Finally, we evaluate the application, with a usability test applied to a sample of 20 people with different areas of knowledge. The results show that the graphics presented by the software are pleasant, they also show that the application is intuitive and easy to use. Additionally, it is mentioned that it helps improve the understanding of medical images.
DIAGNOSA DEPRESI PADA MAHASISWA MENGGUNAKAN METODE CERTAINTY FACTOR DAN FORWARD CHAINING

Many person are not aware of the dangers of depression. It's hard to know the symptoms and overcome depression early on. In this case adolescents are the most vulnerable to the disease because at that time humans are in a transition phase from childhood to adulthood. WHO says every second there is a case of suicide due to severe depression. Based on these cases the researchers aimed to make an application to help the community, especially students, to be able to recognize and diagnose depression from an early age. The system in this application is an expert system using the Certainty Factor and Forward Chaining method. Inputs received by this application are biodata and psychological questions about the symptoms experienced by the user. The resulting output is the diagnosis, as well as the percentage of possible diseases suffered by user.
Using Mind Mapping Strategy to Improve 8th Graders’ Abilities to Summarize and Retell Stories

This research aimed at investigating whether or not there were significant differences in summarizing and retelling achievements between the eighth graders who were exposed with Mind Mapping strategy and those who were not. The population was the eighth graders of one of the Junior High Schools in Palembang. Sixty students were taken as the sample and were put into control and experimental groups. Both control and experimental groups were given pre and post tests, but only the experimental group was given the exposure of Mind Mapping strategy. To collect the data, writing and speaking tests were given and then analyzed by using paired sample t-test and independent sample t-test. The results showed that there were significant improvements in the students’ summarizing and retelling achievements in the experimental group after the treatment given. There were also significant improvements in summarizing and retelling achievements between the experimental and control groups.