Reviewerly/exHarmony huggingface dataset:
THE USE OF PICTURE-CUED STORY SEQUENCE IN TEACHING WRITING SKILLS FOR THE FIRST GRADE STUDENTS AT MA MADANI ALAUDDIN GOWA

The aim of writing skills is to examine whether the Picture-cued Story Sequence improves students’ writing skills at the first grade of MA Madani Alauddin Gowa. The quasi experimental research with pre-test and post-test was implemented as the design of the research. The population of this research was the first grade at MA MAdani Alauddin Gowa. The population was 99 students. The research used purposive sampling. The research involved 66 students from the population. There were 33 students in class X MIA 3 as experimental class and 33 students in X MIA 1 as a controlled class. The instrument used to collect data was the writing text. The result of the research showed that the score of the students’ writing skills at the first grade of MA Madani Alauddin Gowa was improved. Score on pre-test was smaller than post-test. The students got “poor” classification in pre-test. After treatment, students got “good” classification. Based on the result of this research, the researcher suggest that Picture-cued Story Sequence may be used as alternative technique in teaching writing skills because it can help students easy to develop or organize their ideas in writing process.
On Two Information Quantities Relating Two Distortion Balls

This paper clarifies the relationship between two information quantities related to two distortion balls in variable-length lossy source coding. To show various fundamental limits in variable-length lossy source coding, the notion of distortion ball has been known to be useful. In the previous study by Kostina et al., it was shown that the fundamental limit of the minimum average codeword lengths under an excess distortion constraint is characterized by the information quantity related to the distortion ball centered at a source symbol. On the other hand, in our previous study, it was shown that the same fundamental limit is characterized by the information quantity related to the distortion ball centered at a reproduction symbol. Then, what is the relationship between these two information quantities? This paper gives an answer to this question.
Explainability Queries for ML Models and its Connections with Data Management Problems (Invited Talk).

In this talk I will present two recent examples of my research on explainability problems over machine learning (ML) models. In rough terms, these explainability problems deal with specific queries one poses over a ML model in order to obtain meaningful justifications for their results. Both of the examples I will present deal with “local” and “post-hoc” explainability queries. Here “local” means that we intend to explain the output of the ML model for a particular input, while “post-hoc” refers to the fact that the explanation is obtained after the model is trained. In the process I will also establish connections with problems studied in data management. This with the intention of suggesting new possibilities for cross-fertilization between the area and ML. The first example I will present refers to computing explanations with scores based on Shapley values, in particular with the recently proposed, and already influential, SHAP-score. This score provides a measure of how different features in the input contribute to the output of the ML model. We provide a detailed analysis of the complexity of this problem for different classes of Boolean circuits. In particular, we show that the problem of computing SHAP-scores is tractable as long as the circuit is deterministic and decomposable, but becomes computationally hard if any of these restrictions is lifted. The tractability part of this result provides a generalization of a recent result stating that, for Boolean hierarchical conjunctive queries, the Shapley-value of the contribution of a tuple in the database to the final result can be computed in polynomial time. The second example I will present refers to the comparison of different ML models in terms of important families of (local and post-hoc) explainability queries. For the models, I will consider multi-layer perceptrons and binary decision diagrams. The main object of study will be the computational complexity of the aforementioned queries over such models. The obtained results will show an interesting theoretical counterpart to wisdom’s claims on interpretability. This work also suggests the need for developing query languages that support the process of retrieving explanations from ML models, and also for obtaining general tractability results for such languages over specific classes of models.
근전도 기반 손동작 인식을 이용한 모바일 로봇의 원격 제어

In the present work, a novel method to control the motion of mobile robot remotely using hand gesture recognition technique is proposed. The mobile robot moves or performs a predefined action according to the recognized user’s hand gesture. For the training and test data of machine learning algorithm, electromyogram (EMG) signals for six kinds of hand gestures were measured by using a commercial wearable EMG measurement device. After signal processing, feature vectors were obtained from the measured EMG signals for hand gestures. One hundred measurements were conducted for each hand gesture and 80% and 20% of obtained data were used for training and test, respectively. The artificial neural network was designed for the gesture classification and the classification accuracies were evaluated according to numbers of hidden neurons. After assembling a mobile robot by miniaturizing industrial folk lift, the performance of the proposed method was evaluated in real-time environment. It is effectively demonstrated that the proposed method has a great potential for tele-manipulation of mobile robot with high classification accuracy.
Skeleton Based Sign Language Recognition Using Whole-body Keypoints

Sign language is a visual language that is used by deaf or speech impairedpeople to communicate with each other. Sign language is always performed byfast transitions of hand gestures and body postures, requiring a great amountof knowledge and training to understand it. Sign language recognition becomes auseful yet challenging task in computer vision. Skeleton-based actionrecognition is becoming popular that it can be further ensembled with RGB-Dbased method to achieve state-of-the-art performance. However, skeleton-basedrecognition can hardly be applied to sign language recognition tasks, majorlybecause skeleton data contains no indication of hand gestures or facialexpressions. Inspired by the recent development of whole-body pose estimation\cite{jin2020whole}, we propose recognizing sign language based on thewhole-body key points and features. The recognition results are furtherensembled with other modalities of RGB and optical flows to improve theaccuracy further. In the challenge about isolated sign language recognitionhosted by ChaLearn using a new large-scale multi-modal Turkish Sign Languagedataset (AUTSL). Our method achieved leading accuracy in both the developmentphase and test phase. This manuscript is a fact sheet version. Our workshoppaper version will be released soon. Our code has been made available athttps://github.com/jackyjsy/CVPR21Chal-SLR
The Effects of Consciousness-raising Tasks on EFL Learners' Grammar Acquisition and Flow

The current study examines the effects of consciousness-raising tasks on L2 learners grammar competence and their flow experiences. The participants consisted of 77 Korean college students who were assigned to two consciousness-raising task groups the hypothesis building/checking and classification and one control group. The study used a background questionnaire, pre-, post-, and delayed English grammar tests, and also pre-, and post-flow perceptions questionnaires. The results indicate that the hypothesis building/checking and classification task groups showed significant improvement in terms of immediate learning effects, while the performance of hypothesis building/checking task was much greater than the control group in terms of long-term retention. As for the flow experiences, learners in the hypothesis building/checking group rated themselves as having a faster flow state than the other groups. Based on the findings, pedagogical implications and suggestions for L2 grammar classrooms have been made.
A Style-Shifting Analysis of Rumpletiltskin Speech In ‘Once Upon A Time’ Drama Series

This research aimed to identify and describe the style-shifting used by Rumpletiltskin in the drama series and the frequency he used in the drama. Benefit of this research is to give deeper knowledge for students or theater members in making a theater dialogue or deepening roles when playing a drama character in the Play performance course of English Department UIN Antasari Banjarmasin.Researcher used a descriptive technique and qualitative research type for the method of this research. Researcher used document and record analysis techniques to collect the data.The result of this research showed that there were 8 types of style-shifting used by Rumpletiltskin in his dialogue, totaling 22 style-shifting items from 59 items of Rumpletiltskin's speech style in his dialogue. The 8 types of style-shifting are: (1) Casual or Informal to Formal totaling 1 item; (2) Formal to Consultative amounting to 1 item; (3) Casual or Informal to Intimate, amounting to 4 items; (4) Casual or Informal to Consultative, amounting to 3 items; (5) Intimate to Formal amounting to 1 item; (6) Intimate to Casual or Informal, amounting to 4 items; (7) Intimate to Consultative amounting to 1 item; and (8) Consultative to Casual or Informal totaling 7 items.
Visualization for vibration mode of CFRTP plate by time averaged digital holographic interferometry

Resent 3D printer can make a CFRTP (Carbon Fiber Reinforced Thermo Plastics) plate with continuous fiber reinforcement. The 3D printed CFRTP plate has various vibration modes depended on its anisotropy characteristic by carbon fiber direction. This paper deals with visualization of vibration mode and make a FEM model of 3D printed CFRTP plate to calculate the vibration mode. The time averaged digital holographic interferometry can visualize vibration modes of the plate on resonance situation. This method can visualize also high order mode of the plate. The FEM model of the 3D printed CFRTP plate is made used anisotropic elements with orientation angles same with fiber direction. The bended fiber part located at the plate diagonal is modeled 45deg direction elements. This FEM model can indicate almost same vibration mode with experimental results at some modal orders. But the result has indicated different natural frequencies with the experimental results.
Effect of Non-Gaussian Noise Due to Beam Wandering on Error Performance of Quantum Measurement

In the efforts to apply quantum communication to atmospheric channels and on an intercontinental scale, a diverse range of inherent effects in the quantum channel have been attracting research attention in recent years. Beam wandering is an inherent effect that is known to occur when wireless communication methods such as satellite-based global communications are considered, and a previous study on these terms provides a good example of non-Gaussian noise. In our study, we present and consider the error performances for optimum quantum measurement, suboptimal measurement, and optimum classical measurement approaches using an M -ary phase-shift keying modulation scheme when beam wandering occurs.
Implementation of Fisher Yates Shuffle Algorithm In Making Learning Animations: Implementation of Fisher Yates Shuffle Algorithm In Making Learning Animations

English is a foreign language that is difficult for most Indonesian children to learn because the pronunciation is different from the language in which it is written. English is an international language used by various countries in the world. This makes it important to introduce English to children from an early age. The basic English that can be learned by children is the introduction of the pronunciation of the alphabet and numbers and general vocabulary in English. One way of learning that can be adjusted according to the level of children's development so that it is interesting and not easily bored is using learning animations. Animated learning is one of the interactive multimedia-based learning media whose use involves interaction with users so that it can increase the involvement of students in the learning process and can improve the results of learning objectives. The implementation of the fisher yates shuffles algorithm is used to randomize the order of the questions in the quiz practice so that the randomized questions will produce different permutations so that users will get unequal question sequences and it is not easy to remember the quiz answers from the given practice questions. The assessment of the feasibility test for this learning animation will be measured using a questionnaire.
GOLD PRICE PREDICTION USING AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA)

Gold was first used as a standard means of exchange in 643 B.C when it was used to create coins. During this ear, wealth was then defined as a function of the amount of gold possessed by individuals or countries. The impact of gold on the economy of any nation has a direct correlation with the safety and security of most related investments in the economy. Whenever other investment instruments look risky or filled will a high level of uncertainty, gold almost automatically assumes the place of a good hedge. Information on the speculation and trading of this metal abounds. Investors are attracted to moving their funds to gold as guaranteed storage of wealth, while traders capitalize on the dynamism of the market to build capital. The ups and downs in the price of gold and other precious metals can be predicted with proven mathematical and artificial intelligent algorithms. The researchers conducted a study using a machine learning algorithm in the price prediction of gold over a 10year period. Autoregressive Integrated Moving Average (ARIMA) model was used in the experiment, while Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) evaluation metrics were used in the evaluation of the performance of the various ARIMA models. The results obtained in the study proved that ARIMA could achieve high prediction performance over the entire period of prediction. The best prediction outcome of 98.23% was obtained during the 52 weeks period.
LibGuides: Drop-In Library Support Sessions: Week 2

Resources on search strategies, doing a literature review, getting the most out Google Scholar and APA 7 Referencing from library support drop-in sessions in November 2020.
LibGuides: eBook Collections at UVic Libraries: eBooks: General & Multidisciplinary

A guide to the eBook collections at UVic Libraries Best bets! An overview of the major e-book collections to which UVic Libraries provides access.
COVID-19 AND BUSINESS BEHAVIOR: A STUDY IN THE LIGHT OF THE THEORY OF STAKEHOLDERS IN THE FASHION SECTOR IN BRAZIL

On March 11, 2020, the World Health Organization declared Pandemic status by Covid-19, a disease that had its first notification in China Since then, several countries have adopted restrictive measures to prevent the spread of the virus that causes the disease Such actions have led to the suspension of several commercial activities, and the fashion sector has been cited among those most affected The objective of the study was to verify the stakeholders with which companies in the fashion sector in Brazil sought to approach the imminent Covid-19 and what the institutions' attitude towards this pandemic is Data collection was carried out on the conference calls for the last quarter of 2019, held after the day on which the pandemic state had already been decreed It was found that companies have five groups of stakeholders: Employees, customers, suppliers, government, and investors However, the biggest target of companies at the time of the survey was being employees, aiming at the health of the worker and the maintenance of employment;as well as customers focusing on maintaining sales and contact with this group The research clarified how some companies are behaving and with which groups they have tried to relate at the critical moment The study allows interested parties in the analyzed sector to have access to systematized information about what actions have been taken by the institutions to mitigate the negative results in both the financial and public health fields
Heuristic approaches for porting deep neural networks onto mobile devices

Deep Neural Networks (DNNs) although promising for image processing, have significant computational complexity. This impedes implementation in resource-constrained systems. This paper presents effective heuristic approaches for porting DNNs onto mobile devices. Four sets of heuristics are studied: (1) heuristics based on the reuse of transferred weight matrices and weight pruning; (2) heuristics based on parameter reduction, network acceleration and non-tensor layer improvements; (3) a suite of heuristics for low power acceleration of DNNs based on dataflow, near memory and in-memory processing, transform schemes and analog based approaches; and (4) heuristics based on feature and feature map pruning utilizing cosine distances. These sets of heuristics achieve significant complexity, memory and power reductions with minimal reduction of accuracy across an assortment of state-of-the-art DNNs and applications.
침술 훈련 시스템을 위한 경혈점 컨텐츠 및 인체모형 설계

The current trend in the education is developed with the e-learning system, which has the real-world learning effects even in virtual space with the development of advanced digital technologies. However, the lack of a system to train and evaluate acupuncture has led to an education that is not objective in Korea. In this paper, the dummy and MR contents are proposed for the increase of the effectiveness of the education of the acupuncture point, which requires the most mastery at the oriental medical college in universities of Korea. It presents the convergence between the proposed dummies and contents, rendering speed of the contents, the matching rate of the proposed dummy and the data of the acupuncture points.
A Study on Effects of Pre-reading Activities on Online Reading Comprehension for EFL Learners

The purpose of this study is to investigate the effects of three types of pre-reading activities (providing visual materials, drawing semantic maps, vocabulary pre-teaching) on online reading comprehension. Participants consisted of 120 non-English major students enrolled in a English Reading and Writing course at a university. They were assigned into four groups: one control group and three experimental groups for each of the three types of pre-reading activities. A test of reading comprehension ability was conducted before and after the treatment, and a questionnaire was carried out to explore the participants’ interest in English reading and pre-reading activities. According to the statistical analysis of the data, three pre-reading activities proved to be useful in facilitating participants’ reading comprehension and attracting participants’ interest to read. The most appropriate pre-reading activities for participants’ level were not observed. Pedagogical implication and suggestions for future studies follow.
The time-adaptive statistical testing for random number generators

Currently, there are dozens of random number generators (RNGs) and hundreds of statistical tests designed to test the generators. These tests are often combined into so-called batteries, each of which contains from a dozen to more than a hundred tests. When a battery test is used, it is applied to a sequence generated by the RNG, and the calculation time is determined by the length of the sequence and the number of tests. Generally speaking, the longer the sequence, the smaller deviations from randomness can be found by a specific test. So, when a battery is applied, on the one hand, the better tests are in the battery, the more chances to reject a bad RNG. On the other hand, the larger the battery, the less time can be spent on each test and, therefore, the shorter the test sequence. In turn, this reduces the ability to find small deviations from randomness. To reduce this trade-off, we propose an adaptive way to use batteries (and other sets) of tests that can be used in such a way as to increase the testing power.
Gait Training Support Based on Arm-Holding Mobile Robot

Recently, needs of robot technology specialized for locomotive rehabilitation and gait assistance are expected increasingly. In gait and locomotive assistance, appropriate recognition of walking patterns and navigation are required; however, most of supporting devices are directly intervening in movements of lower limbs and therefore they let walking patterns be unnatural. In order to solve this problem, we propose a method to estimate walking patterns from movement of lower limb movements and force/contact interaction with upper libs. Step length and velocity can be measured from the movement of lower limbs by a laser-based sensor, and the dependency on the assistance can be measured from the upper limb by a force and tactile sensors, aiming in the optimal control of intervention in walking support for gait navigation. In this paper, we focus on a detection algorithm of walking patterns from the lower limbs.
Perception Analysis Of Teachers And Students Towards Online Learning During The Covid 19 Pandemic

Abstract. Covid 19 is a pandemic outbreak that occurs in the world and is the leading cause of death during 2020. Indonesia is one of the countries that has had a big impact with this outbreak. One of the impacts that occurs is in the educational aspect where the learning process has changed from face-to-face learning in class (conventional) to virtual or online classes. This learning change was carried out as an effort to prevent the transmission of the covid 19 virus. This study aims to conduct an analysis to determine the perceptions of teachers and students regarding online learning during the Covid 19 pandemic. The type of research used in this study is quantitative research that describes the perceptions of teachers and students online learning from various aspects. Perceptions of online learning are indicated by the existence of interpretations or interpretations, reactions or responses, beliefs and expectations of using the internet to be applied in learning. Teachers in rural and urban areas will be the research samples. There are several similarities and differences in perceptions regarding online learning between teachers in rural areas and teachers in urban areas. They agree that online learning is very useful during the current Covid 19 pandemic. Keywords: perception, online learning, covid19
The Effect of COVID-19 on Intraregional Tourism of Gulf Cooperation Council Countries

Little information is known about the impact of pandemic/epidemic on a tourist’s choice of destination. To fulfill this gap, Conservation of Resources Theory and Fear Appeal Theory are used. The current study aims to get first-hand information regarding people’s perception of tourism services, perception of susceptibility, perception of travel risk, and self-efficacy on travel following COVID-19 pandemic. Besides, revealing the impacts of visitors’ gender and nationality on all these dimensions. Drawing on a sample of 1,112 valid questionnaires from the Gulf Cooperation Council (GCC) countries, which had a domestic or international travel experience, was utilized to collect the data throughout an online survey. The data were analyzed using factor analyses, mean comparison, standard deviation, Mann-Whitney Test & Kruskal-Wallis Test to check the aim and validity of the study. The findings revealed that COVID-19 pandemic influences GCC potential tourists significantly in many ways. Finally, this paper provided some practical implications for reopening the tourism and hospitality business after the COVID-19.