Reviewerly/exHarmony huggingface dataset:
Enhancing Students Motivation in Japanese Conversation (Online Course): through CM

This paper focuses on the study and teaching strategy of Japanese conversation. The goal of the paper is to analyze the motivation of the students learning experience through CM as a media source of the study, which can lead students to enhance their level of proficiency. The study used a qualitative method of the case study Japanese conversation lecture. Conversation lectures are usually done by memorizing text or role-play using existing text. The idea of this study is similar to role-play but, through CM students can learn pronunciation, articulation, and intonation from the native (actor) directly. This study represents the first stage of a research project aimed at raising student confidence and enhancing Japanese fluencies. The major finding was that a clear majority of students reported a considerably high motivation according to the use of terms ‘tanoshikatta’ and ‘omoshiroi’ on their feedback. It says that students were interested to do the assessment.
Locked Deduplication of Encrypted Data to Counter Identification Attacks in Cloud Storage Platforms

Deduplication of encrypted data is a significant function for both the privacy of stored data and efficient storage management. Several deduplication techniques have been designed to provide improved security or efficiency. In this study, we focus on the client-side deduplication technique, which has more advantages than the server-side deduplication technique, particularly in communication overhead, owing to conditional data transmissions. From a security perspective, poison, dictionary, and identification attacks are considered as threats against client-side deduplication. Unfortunately, in contrast to other attacks, identification attacks and the corresponding countermeasures have not been studied in depth. In identification attacks, an adversary tries to identify the existence of a specific file. Identification attacks should be countered because adversaries can use the attacks to break the privacy of the data owner. Therefore, in the literature, some counter-based countermeasures have been proposed as temporary remedies for such attacks. In this paper, we present an analysis of the security features of deduplication techniques against identification attacks and show that the lack of security of the techniques can be eliminated by providing uncertainness to the conditional responses in the deduplication protocol, which are based on the existence of files. We also present a concrete countermeasure, called the time-locked deduplication technique, which can provide uncertainness to the conditional responses by withholding the operation of the deduplication functionality until a predefined time. An additional cost for locking is incurred only when the file to be stored does not already exist in the server’s storage. Therefore, our technique can improve the security of client-side deduplication against identification attacks at almost the same cost as existing techniques, except in the case of files uploaded for the first time.
PEMANFAATAN METODE WAVELET PADA ROBOT SEPAKBOLA BERBASIS MACHINE LEARNING GOOGLE TENSORFLOW

Humanoid Football robot that will be investigated is a wheeled model developed with the ability to predict or prediction in a football field with high accuracy and image resolution. This robot is expected to be able to keep the goal for up to 25 minutes with a cruising reach of 100 m. Also, the robot can monitor or monitor the desired area so that it can keep the goal from attacks from the opposing robot. This robot is expected to complete prediction missions towards the ball and autonomous monitoring without being controlled by the pilot. Robot control is carried out by a Ground Control Station (GCS) computer. The goalkeeper's robot process uses Google TensorFlow's machine learning technology that is integrated with the wavelet method to enable this robot to keep the goalposts from the area effectively and efficiently. Keywords: robot, machine learning, prediction, Ground Control Station, wavelet method
Digital Gamification as a Leading Factor in the Educational and Learning Process of Law Students

The relevance and the leading role of gamification in the educational and learning process is caused by the fact that traditional teaching techniques are no longer as effective as they were considered previously.Moreover, the reduction of the contact hours in the master course content does not allow students to develop practical skills to their full extent.The intellectual status of students has also changed: the students of the 21 st century who grew up playing computer games and using social networks are bored by listening to the lectures and reading textbooks.They do not trust their own thinking but rely upon their gadgets' memory capacity and program codes.In this case, if they are not offered new interactive techniques, the quality of their knowledge will decrease irrevocably.One such technique is a game-based learning.The game aspect is only incentive to action and motivating to perform certain actions.It is aimed at increasing students' activity.At the same time, computer simulation activity, revealing the internal potential and abilities of a student, is aimed at mastering the level of practical skills that will be necessary for effective everyday practical activity.Actually, students imitate the process of their future professional activities.Our paper focuses on the digital gamification as a leading factor in the educational and learning process of law students.We offer some novel insights into this field and provide interesting suggestions and implications for the educators and the students alike.
UNIVERSITY TEACHERS’ PROFESSIONAL IDENTITY: A ROLE OF SELF-DETERMINATION THEORY

Based on scientific literature, professional identity development of teachers in higher education leads to many positive work outcomes and is one of the essential elements of psychological well-being.This study investigated the role of Self-Determination theory (SDT) in the role of university teachers' sense of professional identity.SDT explains how its components play in producing highly motivated individuals, leading to the development of one's sense of self.Thus, the aim of this study is to identify the relationship between university teachers' professional identity and SDT.Sample consisted of 257 university teachers from Lithuania.Professional Identity Questionnaire (Kovalcikiene, 2014) was used to measure university teachers' identification with three professional roles: researcher, teacher and practitioner (or service provider).The SDT components (autonomy, competence and relatedness) were assessed using Basic Psychological Need Satisfaction and Frustration Scale -Work Domain (Chen et al., 2015).The results revealed that all components of self-determination, i.e. autonomy, competence and relatedness were related (p < .01, in all cases) with university teachers' identification with all three professional roles (researcher, teacher and practitioner) as well as overall professional identity.The regression analysis revealed that only competence of university teachers significantly associated with their professional identity: researcher, teacher, practitioner and overall (p < .001, in all cases).Scientific contribution of this research implies empirical study of the role of SDT in university teachers' professional identity.
USING SHADOWING TECHNIQUE TO IMPROVE STUDENTS’ ABILITY IN LISTENING COMPREHENSION

This study was aimed to observe the use of Shadowing technique to improve students’ ability in listening comprehension. This research was conducted by using classroom action research which is consist of two cycles. The sample of the research was one group out of four groups of the first semester students’ of English Department of Nommensen KHBP university which was selected by using random sampling technique. Listening test, observation sheets and diary notes were employed to collect the data. Quantitatively, it showed that there were an improvement of listening ability from the students since the first up to the last treatments. The result showed that in the first treatment there is no students who got the point up to 75. But it increased to 37.5% in the end of the second treatment and 94.28% in the end of the last treatment. Qualitatively, the result showed that the students felt better, easier, and interesting to learn listening that leading to the acquirement of more successful listening comprehension skill. Therefore, shadowing technique could be used to improve students’ ability in listening comprehension. &#x0D; Keywords: Listening comprehension, shadowing technique
MWSA Task at GlobaLex 2020: RACAI’s Word Sense Alignment System using a Similarity Measurement of Dictionary Definitions

This paper describes RACAI’s word sense alignment system, which participated in the Monolingual Word Sense Alignment shared task organized at GlobaLex 2020 workshop. We discuss the system architecture, some of the challenges that we faced as well as present our results on several of the languages available for the task.
Application of light microscopy tissue slices and digital slicing in experimental teaching of micromorphology

Histology teaching requires a combination of theory and experiment for a better understanding of microstructure and related functions of body. On the basis of the comparison and summary of the advantages and limitations of traditional light microscopy tissue slices and the emerging digital slicing, we combined them in the teaching of micromorphology experiments to achieve a better teaching results. Each experimental course (about 3 to 4 hours) was divided into four parts: teaching videos, observation of light microscopy tissue slices and digital slicing, discussion on course content and random quizzes. This teaching method contributed to the improvement of the students' interest and motivation in learning, the teachers' teaching efficiency and the overall teaching quality.Key words: Light microscopy tissue slices; Digital slicing; Micromorphology
Evaluation of the current situation of English courses in eight-year M.D. program and prospect of reform — taking Sichuan University as an example

ObjectiveTo investigate the current situation and underlying problems of English courses in general education for eight-year M.D. Program and to put forward possible solutions.Methods We investigated and interviewed teachers from West China Medical Center who teaches bilingual courses and teachers from College of Foreign Languages and Cultures along with faculty in Education Ministry of Sichuan University, analyzed the problems in English courses and explored measures for improvement.Results The emphasis students put on English course is satisfactory, but teachers still claim that few students participate actively in class. Therefore, the efficiency of English course should be improved.ConclusionThe current status of English course is not ideal, which can be attributed to both teachers and students, so future schemes should be based on these two perspectives.Key words: Eight-year M.D. program; English course; Underlying problems; Solutions
The Introduction of Local Culture as a Means of Learning Indonesian Language for Foreign Speakers

The teaching of Bahasa Indonesia to foreign speakers (BIPA) cannot be separated by local cultures.This condition is supported by the BIPA curriculum that includes the local culture.However, Indonesian language teaching for foreign speakers cannot be confused with Indonesian language instruction in native Indonesian students.This is due to differences in mother tongue and cultural background.This research is a qualitative descriptive study.Data collection is done through observation, recording, and documentation.The validity technique uses source triangulation to check the validity of the data.Based on the results of the research known that the local culture of Madiun, such as Dongkrek, Reog Ponorogo, Madiun tourism, and special food can be used as a means of Indonesian language recognition.Through the introduction of local cultures makes foreign learners easy to understand Indonesian vocabulary.Thus listening and speaking skills are easier to apply.
Rainfall Intensity and Evapotranspiration Patterns Nexus over Nigeria in Different Solar Cycles

The study employed Mass – Transfer Model (MTM) to estimate evapotranspiration (ET) from 12 selected locations spread across three climatic zones over Nigeria at intervals of 30 years (1988 and 2018) depicted by different solar cycles. Based on this finding the impacts of rainfall intensity on evapotranspiration patterns over Nigeria were investigated. Daily averaged values of wind speed at 2 m from soil, air temperature and relative humidity for 12 selected stations across Nigeria were employed for 1988 and 2018. The actual vapour pressure and saturated vapour pressure were estimated. A correlation between evapotranspiration with rainfall intensity was established to determine impacts of rainfall intensity on evapotranspiration patterns over Nigeria in solar maxima and minima scenarios. The results showed that ET was higher in 2018 than 1988 in 3 out of 4 stations in tropical monsoon; in tropical savannah and only Ibadan and Akure had a reduction in these values when 1988 was compared with 2018. Lowest values of ET was observed between August and October corresponding to the peak of rainy season. 7 stations out of 12 were influenced by solar minima phenomenon namely Port Harcourt, Owerri, Enugu, Ibadan, Minna, Borno and Gusau. The lowest values of ET were recorded at Calabar and Port Harcourt for both 1988 and 2018 while the highest values were observed at Borno for 1988 and Sokoto for 2018. Rainfall intensity had greater impacts on ET values in tropical monsoon than any other climatic zone in Nigeria.
Leading Opportunities for Fighting Cyberterrorism Using Blockchain Technology

This paper focuses on the leading opportunities of applying the blockchain technology for tackling cyberterrorism.Originally developed for the digital currency called Bitcoin, blockchain technology created a platform for a new segment of Internet, influenced the decentralization of the network by the principle of a distributed registry, and began to be used in all kinds of combinations and combinations for various purposes, including cybersecurity.The use of blockchain technology for ensuring cybersecurity and its leading potential in that is unlimited, thanks to such unique properties as reliability, accessibility, high adaptability, economic efficiency, and profitability.Our results show that the use of blockchain technologies in combating cybercrime, including cyber terrorism, can extend to the control of financial services, transport, or any other industry.However, the growth of criminal activity using blockchain technologies will also intensify if law enforcement agencies cannot technologically competently, at a faster pace, detect these developing centres, determine their actions, and destroy illegal plans.
PROTOTYPE APLIKASI GENERATE BARCODE BERBASIS WEB PADA PT. BIMASAKTI KARYAPRIMA

PT. BimasaktiKaryaprima is a medium-sized company engaged in the shoe industry. In this company, there is a system to create barcode shoe data that still uses Libre Office, where in the implementation of the system there are several things that become obstacles, which includes the effectiveness and time efficiency in the process of inputting barcode shoes data, the form of manufacture which is still typing one by one the data that must be printed in making a barcode. With the above reasons, the author tries to provide an alternative problem solving by creating a barcode making system application where the user can input large amounts of data and can also process data import with CSV file extension, so that it will eliminate the way of making barcode data with the Libre Office which has been running at PT. Bimasaktikaryaprima. At this writing the method used for collecting data through observation, interviews, literature studies and software design methods using the waterfall method.
Pain Facial Expression Recognition from Video Sequences Using Spatio-temporal Local Binary Patterns and Tracking Fiducial Points

Monitoring the facial expressions of patients in clinical environments is a necessity in addition to vital sign monitoring. Pain monitoring of patients by facial expressions from video sequences eliminates the need for another person to accompany patients. In this paper, a novel approach is presented to monitor the expression of face and notify in case of pain using tracking fiducial points of face in video sequences and spatio-temporal Local Binary Patterns (LBPs) for eyes and eyebrows. The motion of eight fiducial points on facial features such as mouth, eyes, eyebrows are tracked by Lucas-Kanade algorithm and the movement angles are recorded in a feature vector which along with the spatio-temporal histogram of LBPs creates a concatenated feature vector. Spatio-temporal LBPs boost the proposed algorithm to capture minor deformations on eyes and eyebrows. The feature vectors are then compared and classified using the Chi-square similarity measure. Experimental results show that leveraging spatio-temporal LBPs improves the accuracy by 12% on STOIC database.
A Load Balancing Per Connection Classifier Dengan Pengukuran Quality of Service Pada Jaringan LAN Lingkup Universitas

Abstract&#x0D; In the use of internet networks that are general in nature need to implement an appropriate network configuration to maximize the use of internet connections provided by service providers. This is important for the optimal use of internet services and in accordance with utilities that are basically general and shared can be achieved. Per Connection Classifier is a load balancing method for distributing traffic loads to more than one network connection point in a balanced way, so that traffic can run optimally.&#x0D; This research focuses on network configuration methods to maximize internet usage for all users. Quality of Service is used to see the performance of network traffic which is indicated by the value of the parameter delay, throughput, and packet loss.&#x0D; Based on the results of testing and research that have been carried out before and after using load balancing per connection clasifier, the delay value is decreased from 180.26 ms to 148.36 ms and throughput increased from 1.76% to 2.03%, then packet loss decreased from 25.37% to 18.59% according to the TIPHON standard.&#x0D; Keywords: Quality of Service, Per Connection Classification, load balancing, delay, throughput, packet loss
A Study of Quantum Computing

Quantum computing is a locale of figuring focused on making PC development reliant on the norms of quantum speculation, which explains the direct of imperativeness and material on the atomic and subatomic levels.Conventional PCs that we use today can simply encode information in bits that take the estimation of 1 or 0. This confines their ability.Quantum enlisting, on the other hand, uses quantum bits or qubits.It handles the unique limit of subatomic participles that licenses them to exist in more than one state for instance a 1 and a 0 at the same time.Superposition and trap are two features of quantum material science on which these supercomputers are based.This empowers quantum PCs to manage exercises at speeds exponentially higher than common PCs and at significantly lesser imperativeness usage.
Anti-Phishing Game Framework to Educate Arabic Users: Avoidance of URLs Phishing Attacks

Objectives:The main objective of this study is to address poor security awareness regarding phishing attack in Middle East by developing anti-phishing educational game to educate Arabic users about phishing URLs.Methods/statistical analysis: We start by identifying phishing site URL attributes that help identify phishing sites.Then, we followed a well-established game design framework (EDPE) to develop our anti-phishing game.We performed a study on 56 participants using pretest and post-test technique to assess the level of phishing awareness among participants before playing the game and after playing the game.We used paired t-test and one-way analysis of variance (ANOVA) statistical analysis to identify to what extent anti-phishing game could help users identify and avoid phishing attacks.Findings: The results obtained from pretest proved the clam that security awareness in Arabic region is still immature.While the results obtained from post-test prove that serious educational games in Arabic language could be used to educate Arabic users about security concepts and increase security awareness.In addition, the results reflect that employees need more training (as their performance were the lowest among different demographic participants) to help them correctly identify phishing sites.Moreover, by inspecting participants' responses, we identified that similar and deceptive domains, is the hardest URL phishing category to be correctly identified by users.So, we should pay more attention to this category while performing users training.Application/improvements: Our anti-phishing game is the first security educational game in Arabic language.It proves the effectiveness of serious games as a training tool.It is a step towards raising security awareness in Arabic region.
Subconcept Based One Class Classification Method with Cluster Updating

One class classification is an effective way to perform anomaly detection or outlier detection. Previous work has empirically shown that complexity in the background (also known as target) class degrades the performance of one-class classifiers, and one source of data complexity is the presence of subconcepts in that class. Learning over subconcepts individually can mitigate the effects of domain complexity and improve one class classification performance. Unless a clustering could be derived from domain knowledge, the approach used to search for subconcepts is unsupervised clustering. However, in some cases, the examples belonging to some of the clusters may be too scattered, while, in others, clusters may be affected by the small disjunct problem where some clusters comprise only of a few examples that cannot be used to train a robust classifier. To handle these problems, this paper presents a method to update the clusters obtained by the clustering process prior to learning over them. In addition, it introduces the c-Nearest-Cluster (c-NC) method for combining the individual classifiers derived from each subconcept. Our experiments on classical outlier detection datasets and on cyber security datasets show that our method can improve upon the classification performance obtained by the recently proposed subconcept based one class classification method.
Building a Sentiment Analysis System Using Automatically Generated Training Dataset

In this paper, we describe a methodology to develop a large training set for sentiment analysis automatically. We extract Arabic tweets and then annotates them for negativeness and positiveness sentiment without human intervention. These annotated tweets are used as a training data set to build our experimental sentiment analysis by using Naive Bayes algorithm and TF-IDF enhancement. The large size of training data for a highly inflected language is necessary to compensate for the sparseness nature of such languages. We present our techniques and explain our experimental system. We use 200 thousand annotated tweets to train our system. The evaluation shows that our sentiment analysis system has high precision and accuracy measures compared to existing ones.
Comparative Study of Requirements Traceability in Facing Requirements Change: Systematic Literature Study and Survey

Context: Requirements change commonly occurs during the software development lifecycle. Requirements traceability is one of the important techniques to support requirement change management and ana ...