Reviewerly/exHarmony huggingface dataset:
Identity Framing of South Korea in the Japanese Press: The 2019 Boycott Movement

The South Korean boycott movement of Japan that emerged over the summer of 2019 represents a drastic decline in Japan-South Korea relations. This thesis focused on how the boycott movement was framed in the five big national Japanese newspapers over a 50-day period in August and September 2019 in order to understand how the Japanese press constructs South Korean identity vis-avis Japan. Drawing on social constructivism and theories on Self-Other discursive representations in international relations, the thesis conducted a framing analysis by examining the identity frames and topic frames used by the newspapers. This illustrated how two opposing narratives of South Korea existed in the Japanese press relating to the boycotts: a negative, which constructed Korea as uncivilised/emotional, unlawful/untrustworthy, unreasonable, distinctively Asian, and responsible for the deterioration of Japan-Korea relations, and a positive where Korea was viewed as a valued partner who is just another country, not anti-Japanese, and not individually to blame for the declining relationship. These narratives were, however, represented differently between the newspapers, and the thesis thus argued against the claim that the Japanese press is homogeneous. (Less)
THE ANALYSIS OF STUDENTS ABILITY’ IN WRITING ADVERTISEMENT TEXT AT PRIVATE SCHOOL

The purpose of the research was to analyze the students’ ability in writing advertisement text using the format of Product and Service Advertisement. This research was qualitative research and the instrument was a written text. The research subject of this research were the ninth grade students at class IX SMP Swasta Bintan Tanjungpinang in the academic year of 2019/2020 which had been chosen using judgement sampling. The researcher adopted the technique of Bogdan and Biklen to conclude the students’ ability in writing the generic structure of the advertisement text. The result was all the students showed the ability in writing the generic structure and most of them got pretty decent outcome. Therefore, the students have to improve more their ability in writing the advertisement.
Enhancement on Edge and Reduction of Noise in Low Light Videos Using Discrete Wavelet Transform with JND Model

The low contrast videos captured by camera phone are not usually convincing due to theinappropriate illumination. The captivated videos under low light condition are of low contrast as well asextremely unpleasant by noise. Here both the contrast enhancement and noise reduction in low light videosusing wavelet coefficients is efficiently carried out. At first, normalization is functioned on the luminancecomponent taken from the frame to acquire its dynamic range. Then, the frame is decomposed into low-passand high-pass sub-bands using Discrete Wavelet Transform (DWT). The just noticeable difference (JND)based Contrast enhancement is obtained in the LL band and Edge enhancement and De-noising in high-passsub-bands HL, LH, HH. At last colour correction is attained in order to satisfy the colour distortionsrendered by contrast improvement. From the results we proved that an algorithm attains contrastimprovement, noise deduction for the dim light videos, which not only enhances the background luminancecapable for human visual recognition but also improves the contrast of the video frame.
Efficiency Comparison Between Curriculum Reinforcement Learning a Reinforcement Learning Using ML-Agents.

Efficiency Comparison Between Curriculum Reinforcement Learning & Reinforcement Learning Using ML-Agents.
Using ContextBased MicroTraining to enforce secure behavior among computer users

Abstract: While there are many technical security controls available, the research- as well as the practitionercommunity agrees that a key aspect of information security is user behavior(Bulgurcu, ...
Implementation of the competence approach: philosophical and methodological foundations

The core of the competence-based approach is the activity associated with the&nbsp;thinking processes of students. If the essence of mental activity is to reflect the essential properties and relations of things, first of all, the focus is on the con­nections between these objects, the establishment of which is impossible without the competent use of rational forms of thinking. It is noted that it is necessary to&nbsp;use the results of research in the field of thinking, which makes it possible to&nbsp;control and predict the desired result in the formation and development of&nbsp;the&nbsp;competences of modern man. Moreover, the success of solving practical problems, to the fulfillment of which the competence approach is oriented, is due to the qualitative characteristic of thinking from the standpoint of activity and communication. A special role is given to the elements of creativity that take place at the level of the expansion of cultural meanings and their focus, analysis, generation and filtering of ideas – both in the field of subject and ideal activity.
Dynamic Masking for Improved Stability in Online Spoken Language Translation.

For spoken language translation (SLT) in live scenarios such as conferences, lectures and meetings, it is desirable to show the translation to the user as quickly as possible, avoiding an annoying lag between speaker and translated captions. In other words, we would like low-latency, online SLT. If we assume a pipeline of automatic speech recognition (ASR) and machine translation (MT) then a viable approach to online SLT is to pair an online ASR system, with a a retranslation strategy, where the MT system re-translates every update received from ASR. However this can result in annoying flicker as the MT system updates its translation. A possible solution is to add a fixed delay, or to the the output of the MT system, but a fixed global mask introduces undesirable latency to the output. We show how this mask can be set dynamically, improving the latency-flicker trade-off without sacrificing translation quality.
LibGuides: Virtual Library Orientation: Archives Research Center

Welcome to the AUC Robert W. Woodruff Library Orientation LibGuide! You will find links and tutorials to get you started researching at the Library here.
Comparative Study of Naïve Bayes Algorithm and K-NN Algorithm in Predicting Timely Graduation

One indicator that shows an effective educational process is the student's timely graduation rate. In this study, timely graduation is predicted using Naive Bayes and k-Nearest Neighbor. Both algorithms are optimized using PSO . The results showed that the PSO-based k-Nearest Neighbor (k-NN) algorithm had better results than the Naive Bayes algorithm, with an Accuracy value of 76.69%. The accuracy value before and after the addition of the PSO feature is higher than the k-NN algorithm compared to the Naive Bayes algorithm. There are 6 attributes that have the same weighting value (value = 1,000) in the k-NN Algorithm, namely Gender, achievement index in Semester 2, achievement index in Semester 3, achievement index in Semester 4, achievement index in Semester 6 and Marriage Status. To find out which attributes are more influential than the 6 attributes, it can be helped by checking the weighting value on the comparison algorithm (Naive Bayes), finally 2 attributes are obtained that mostly influence on students' timely graduation. They are the Gender attribute and Achievement Index in semester 6. The smallest weighting lies in the Age Attribute (value = 0,000) for both the Naive Bayes Algorithm and the k-NN Algorithm. It means that the Age attribute does not have a strong influence on students' timely graduation.
Usability of Data Visualization Activity Worksheets in the Context of a Critical Data Visualization Workshop: Findings from a Usability Survey

This evidence-based practice paper presents outcomes on workshop participants' perception of the usability of data visualization worksheets utilized in a critical data visualization workshop.Training students to think critically about data is a process that takes practice.Thinking critically about data requires understanding the data, its provenance and context, and the best way to represent insights contained in the data.A 5-day workshop on teaching critical and ethical approaches to data visualization was hosted by the Center for Science of Information at Purdue University in June 2019.The motivation for the workshop was to provide an introduction to data science through the lens of critical data visualization.In addition to instruction and hands-on data visualization and data manipulation exercises supported by activity worksheets, workshop participants were exposed to small group discussion and active-learning focused team science and data visualization ethics modules.This three-prong approach provides the context in which the data visualization activity worksheets were utilized.This paper focuses solely upon the results of a usability survey of data visualization activity worksheets to introduce the data visualization process and reports students' perception of the worksheets to introduce the data visualization process to novice users.Overall participant perception of the worksheet method was positive: 61% thought the method was easy to use, felt most people would learn to use the method quickly, felt confident using the worksheet method after using the worksheets for multiple visualization challenges and indicated they would like to use the method frequently when applying the data visualization process.This work is funded by The National Science Foundation (Award #CCF-0939370).Next steps involve integrating team science and data visualization ethics activities into future iterations of the data visualization activity sheets and usability survey.
A Hybridization Approach based Semantic Approach to the Software Engineering

It is a major issue to measure semantic accuracy for determining the similarity between words, for developing a web and retrieving information thereby using natural language processing or mining of the text. There have been several proposals and adoption of methods for measuring the similarity by using WordNet and MeSH ontology. A new approach based on hybridization is proposed in this work. Feature based methodology and fuzzy set theory has been used here.
Discovering and Tracking-based Detection System for Optical Camera Communication

Detecting the transmitting source within a frame is fundamental in Optical Camera Communications (OCC). Until now, the detection techniques used today are discovery techniques, that is, in each frame or set of frames, the source is detected unequivocally. These techniques are expensive and may require learning (in case of using Deep Learning), which makes the implementation of receivers in users' end devices, such as smartphones, a new challenge to consider. In this article, we propose a detection system oriented to devices with limited hardware making use of basic operations, and also proposes to use the tracking technique. Since the tracking does not detect whether the source is within the region being tracked, this combination allows to obtain higher camera capture rates (FPS). This system may allow limited hardware devices to implement OCC technology.
Online Banking among Jamaicans during the 2020 COVID-19 Pandemic

Introduction : The information era began in the mid-20 th century with the coming of the third industrial revolution, characterized by the emergence and usage of computer technology and peripheral devices and equipmentin conducting business and personal transactions.This was amplified with the ushering in of the fourth industrial revolution: the emergence of the internet and digital networking of computers. The benefits and advantages of digital banking include the ease of use and access and explains greater volume of transactions unlike in other eras. However, people fear technology in banking because of the high prevalence of internet banking frauds. Objectives : This study seeks to: 1) evaluate perceived usefulness of technology and ascertain whether this facilitates greater acceptance of online banking, 2) assess perceived ease of use of technology and whether this determines  acceptance of online banking, 3) determine whether security and confidentiality of information facilitate acceptance of online banking, and 4) evaluate the quality of internet connectivity and whether this affects acceptance of online banking. Methods and materials : A correlational research design was used for this study. The researchers examined how six variables (security and privacy, perceived enjoyment, perceived ease of use, perceived usefulness, internet connectivity, and amount of information) were likely to influence a single dependent variable (use of online banking). Using a population of 1,091,336, a 95% confidence interval, and a 3 % margin, the actual sample size for this research is 1,067 respondents. Findings :The study found a positive statistical correlation (r xy > 0) among perceived usefulness, perceived ease of use, perceived enjoyment, amount of information, and internet connectivity. Of the six variables examined in this study, online/internet banking is influenced by three correlates (amount of information, perceived ease of use, and perceived usefulness). People’s decision to use internet banking is positively influenced by perceived ease of use which has the most influence on using internet banking (Adjusted R 2 = 15.1%).  Conclusion :The issue of COVID-19 pandemic has reiterated the importance and value of internet/online banking to transact economic/financial businesses because of the promulgated social distancing which is to reduce the spread of the virus.
Remote health monitoring: fall detection

Abdulhamid, M., Peter, D. (2020). Remote health monitoring: fall detection. Technical sciences and technologies, 1 (19), 199-205.
Penerapan Pembelajaran Daring Dragonlearn pada Era Pandemic Covid-19(Studi Kasus di MI Ma’had Islam Kopeng)

The purpose of this study was to determine the optimization of mathematics learning during the New Normal due to the impact of the Covid-19 pandemic. In addition, to find out the implementation process, advantages, and obstacles of online learning with Dragonlearn. This type of research uses a qualitative approach. Data collection techniques using the method of observation, interviews, and documentation. The data analysis stage includes: data reduction, data presentation, and drawing conclusions. The results showed that: 1) optimizing mathematics learning during the New Normal period at MI Ma'had Islam Kopeng using the home visit learning method as an alternative to learning. Before using the home visit learning method, the school conducted online or online learning. However, this method cannot run smoothly and cannot be enjoyed by some students, especially those whose home addresses are remote and do not have supporting facilities to obtain material through online learning. 2) The process of implementing Dragonlearn Era New Normal online learning has been going well, by carrying out careful planning students can carry out learning smoothly so that teachers can evaluate through the available statistics page. 3) The advantage of using dragonlearn is that students are more active and more confident in asking questions, they can access it anytime and anywhere. However, learning like this has obstacles that lie in the network. This learning also has disadvantages, namely that there are convoluted types of questions and the learning cannot be face-to-face so that the teacher cannot convey the material optimally.
LibGuides: Streaming Video Sources: Copyright and video

This guide is designed to facilitate the search for multidisciplinary streaming videos. Resources include both Dalhousie subscriptions and sources from the open web.
Metodología de Navegación de robots móviles para detección de vanos y discontinuidades en su trayectoria

In this master thesis, intends to present the study and implementation of 2 autonomous navigation strategies that lead to a robotic platform to fulfilling the task assigned in normal indoor environments, including work with some discontinuities, such as Corridor or hallways. The first strategy to be evaluated will be a hybrid system, taking into account a neuronal-fuzzy system, where the part of neuronal networks in combination with reactive behaviors estimate a decision on orientation, and the fuzzy logic part delivered through the use of rules , The speed to be followed by the platform, taking into account the physical and mechanical constraints of the robot, the second method to analyze will be based on statistical and / or probabilistic strategies, where it will focus on Bayesian networks. Tests will be developed in different environments and each with different levels of complexity, where representative data can be compared with performance metrics and thus be able to establish to some extent the best option
THE CORRELATION BETWEEN EXTRACURRICULAR SCORE AND SCORE IN ENGLISH AT KARYA YOSEF ELEMENTARY SCHOOL

Karya Yosef elementary school is one of the schools that include English lesson in their curriculum. This is helpful for students in order to understand English as a foreign language. Karya Yosef elementary school provides English extracurricular program beside English lesson in the formal class to help students develop their abilities and skills in English. The writer would like to find out the correlation between English extracurricular score and students’ scores in English class. This research uses a quantitative method to find the correlation between the variables. The population were students who joined the English club with samples were students in grade 1-3 at SD Karya Yosef Pontianak by using purposive sampling method. Data analysis used is Pearson product-moment in SPSS. The result shows no correlation between English extracurricular score and students’ score in grade 1 English class. However, there was a positive correlation between English extracurricular score and students’ score in grade 2 and 3 English class at Karya Yosef elementary school Pontianak.
IntersectGAN: Learning Domain Intersection for Generating Images with Multiple Attributes

Generative adversarial networks (GANs) have demonstrated great success in generating various visual content. However, images generated by existing GANs are often of attributes (e.g., smiling expression) learned from one image domain. As a result, generating images of multiple attributes requires many real samples possessing multiple attributes which are very resource expensive to be collected. In this paper, we propose a novel GAN, namely IntersectGAN, to learn multiple attributes from different image domains through an intersecting architecture. For example, given two image domains $X_1$ and $X_2$ with certain attributes, the intersection $X_1 \cap X_2$ denotes a new domain where images possess the attributes from both $X_1$ and $X_2$ domains. The proposed IntersectGAN consists of two discriminators $D_1$ and $D_2$ to distinguish between generated and real samples of different domains, and three generators where the intersection generator is trained against both discriminators. And an overall adversarial loss function is defined over three generators. As a result, our proposed IntersectGAN can be trained on multiple domains of which each presents one specific attribute, and eventually eliminates the need of real sample images simultaneously possessing multiple attributes. By using the CelebFaces Attributes dataset, our proposed IntersectGAN is able to produce high quality face images possessing multiple attributes (e.g., a face with black hair and a smiling expression). Both qualitative and quantitative evaluations are conducted to compare our proposed IntersectGAN with other baseline methods. Besides, several different applications of IntersectGAN have been explored with promising results.
Library Guides: Masters of Science in Law Resources: Cybersecurity Concentration

A guide designed to assist current and potential students obtaining a Master of Science at NSU Law.
LibGuides: Blackface Minstrelsy Resources: Blackface in Other Cultures

This guide has been developed by The Center for American Music to provide resources for researching blackface minstrelsy and other demonstrations of blackface performance.
Webinar: Jadu AWS Intelligent Services Integration with Live Demo

Technology is the enabler to better services, particularly in Local Government. More and more users are moving online to find help from their Local Council, even more so recently due to the pandemic. With demand being so high, more Local Authorities are moving towards Artificial Intelligence (AI) to help assist Customer Service Centres. Think of a chatbot, it can provide information easily to a user while the Customer Service Staff focus on the more important, or urgent services.
Effects of threatening pictures on encoding behavior of subsequent stimuli.

Research regarding episodic memory and emotion shows that emotion has a modulatory effect on memory. The aim of the present study is to investigate if exposure to emotionally loaded images could potentially change the way future neutral images are encoded, and if this exposure also modulates the memory experience of these images. In addition to this, data resulting from questionnaires regarding participants anxiety levels are also recorded and incorporated in follow -up analysis which examines the potential relationship between this exposure and individual’s anxiety levels. To investigate the relationship between prior emotional experiences and memory encoding, the present study examines how a sequence of neutral and emotionally loaded images are encoded and how these images are subsequently recalled from memory. To capture the memory encoding process, eye-tracking is used to monitor participants' gaze behavior when they inspect and encode different images. Results of the present study offer novel insights into the relationship between emotion and memory and show that (a) memories of emotionally charged and neutral images were experienced differently; (b) that participants looked back to locations where a previous image was presented during encoding and that such gaze behavior had an effect on the subsequent memory experience; (c) a relationship between higher levels of anxiety and the tendency to look back at positions where emotionally charged stimuli were encoded. (Less)
STUDENTS’ PROBLEMS OF READING COMPREHENSION DURING ONLINE LEARNING IN THE PERIOD OF COVID-19 PANDEMIC

Abstract The aims of this research were finding out the students’ problem in learning reading and the source of problem in learning reading in period of Covid-19 pandemic. This research used qualitative research use survey method. The researcher used quota sampling technique to determine the sample. The instrument used in this research was questionnaire. This research took 75 students as respondents at non TBI department of UIN Sultan Maulana Hasanuddin Banten on second semester in Academic year 2019/2020. The researcher used three categories to analyze the data. The result of this research found that the students problem during the Covid-19 in learning reading as follow : Students do not understand what the teacher explain; it’s hard to find the main idea in a paragraph, lack of vocabulary, lack of more detail information, from a text and the students were hard to make a summary or making inference. The source of the problem in comprehending English reading text in period of Covid-19 pandemic are learners’ background and students environment. Keywords: Learning Problems, Reading Comprehension, Online Learning, Pandemic Era