Reviewerly/exHarmony huggingface dataset:
AUTOMATIC CLASSIFICATION OF TOPICS POSTED AT SAUDI UNIVERSITIES IN TWITTER

Social media are the key venue of social interaction today. One such medium is Twitter whose characteristics and use has become the focus of various fields such healthcare, communications, and education. As education is the main field for the development of societies, educational institutions have paid attention to measuring their interaction with their students on Twitter to improve the performance of educational services by classifying tweets. Classifying tweets via machine learning algorithms is a viable means of evaluating the effectiveness of social media campaigns and communications. The present study is aimed at examining the field of social network mining through classifying the tweets in Arabic of various sectors of King Abdul-Aziz University, an educational institution in Saudi Arabia, through building a framework to classify the tweets into specific categories such as admission, exams, and libraries. This framework examines the power of stylometric features using three different classifiers of Arabic microblog. The stylometric features applied to the text in this framework are character, lexical, and syntactic. These features were extracted using the MADAMIRA tool and were used to build a features-based classification model. In this model, the features are combined with a different size set of data using three classification techniques, which are support vector machine (SVM), k-nearest neighbour, and random forests. The K-folds technique was used to evaluate the models, and the measures of precision, accuracy, recall, and f-measure were made regarding every machine-learning model. The study compared the three models to ascertain which models would offer the best performance in terms of accuracy. The findings show that SVM is the best performing classifier. While the random forest also proved to be a strong classifier, it did not perform as well as the SVM.
KECEMASAN MEMBACA DALAM PERSPEKTIF NEUROSCIENCE

This study aims to show the role of emotions in encouraging effective learning. The affective domain is always considered less significant in the learning process than the cognitive domain. The reader of this article is expected to understand how the role of emotions in the learning process, using cognitive psychology theory and neuroscience  analysis from this study. Next, examine the effect of the affective domain on learning in symbol interpretation. This paper concludes with analysis of reading anxiety and suggestions in reading exercises.
Optimization of Artifact Free Image Upscaling Using Genetic Algorithm

Creating an upscaled image from a low-resolution (LR) image to high resolution (HR) is very interesting. The nature and texture of an image should be maintained during upscaling of an image. This upscaling is also termed as “super-resolution”. It is related to both, statistical relationships between low-resolution and high-resolution. Several methods have been proposed to obtain better results, involving simple heuristics, edge modeling or statistical learning. The most powerful ones, however, present a high computational complexity, while fast methods, even if edge-adaptive, are not able to provide artifacts free images. In this paper, a simple and effective scheme for image upscaling is proposed. To balance visual quality and complexity, an optimal weight allocation using genetic algorithm is proposed which interpolates local pixel values along the direction where second order image derivative is lower. The scheme keeps the images as sharp as the original while avoiding magnifying noise and artifacts in the image. The high quality of the images enlarged with the new method is demonstrated with objective and subjective tests, while the computation time is reduced. Keywords: Super-resolution, image upscaling, low resolution, high resolution, genetic algorithm Cite this Article: Anishma MK, Shamna AR, Asmin MK, Asmin MK. Optimization of artifact free image upscaling using genetic algorithm. Journal of Web Engineering & Technology. 2020; 7(1): 21–29.
Content based Image Retrieval Method using Fuzzy Heuristics

Content based image retrieval (CBIR) refers to image content that is retrieved directly, by which the images with featuresor containing certain contents will be searched in an image database. The main idea of CBIR is to analyze imageinformation by low level features of an image, which includes colour, texture, shape and space relationship of objects etc.,and to set up feature vectors of an image as its index. A new CBIR search engine is proposed using three features andsimilarity is measured and controlled by fuzzy heuristics. CBIR Search Engine relies on the characterization of primitivefeaturessuchascolour,shapeandtexturethatareautomaticallyextractedfromtheimages.Thereareseveraltechniquesto deal with CBIR problems for retrieving the relevant images. CBIR proposed by using three methods. Colour feature isextracted by using histogram-based method, texture feature is extracted by using Gabor filter and shape feature is bymoment invariant algorithm. For searching the similar images with the database similarity measure is calculated and iscontrolled by using fuzzy. Fuzzy similarity measure is implemented by using Mamdani fuzzy inference method. The useof these three algorithms ensures that the image retrieval approach produces images which are relevant to the content ofanimagequery.
TWITTER SENTIMENT ANALYSIS

Abstract: Since an ever-increasing part of the population makes use of social media in their day-to-day lives, social media data is being analyzed in many different disciplines. The social media analytics process involves four distinct steps, data discovery, collection, preparation, and analysis. While there is a great deal of literature on the challenges and difficulties involving specific data analysis methods, there hardly exists research on the stages of data discovery, collection, and preparation. To address this gap, we conducted an extended and structured literature analysis through which we identified challenges addressed and solutions proposed. The literature search revealed that the volume of data was most often cited as a challenge by researchers. In contrast, other categories have received less attention. Based on the results of the literature search, we discuss the most important challenges for researchers and present potential solutions. The findings are used to extend an existing framework on social media analytics. The article provides benefits for researchers and practitioners who wish to collect and analyze social media data.[1]Index Terms: Social media Scraping Behavior economics Sentiment analysis Opinion mining NLP Toolkits Software platforms
[Telemedicine satisfaction of primary care patients during COVID-19 pandemics]./ Grado de satisfacción de los pacientes de la Unidad de Salud Familiar Vitrius con la teleconsulta durante la pandemia del COVID-19.

OBJECTIVES: To assess telemedicine satisfaction of patients from a primary health care center during COVID-19 pandemics. This work could bring information on its acceptance. MATERIALS AND METHODS: Transversal study with 253 individuals. A questionnaire was performed using Likert scale (1-very unsatisfied, 5-very satisfied) on patients with diabetes, hypertension and in subjects with other pathologies, whose consultations occurred between 01/04/2020 and 01/05/2020. Collected data included sociodemographics, previous telemedicine appointments, satisfaction levels of teleconsultation and doubt clarification, and interest in further telemedicine follow-up. In addition, a comparative analysis was performed between the periods January-February and April-May of 2020 in relation to age, sex, hypertension, diabetes and the type of contact (presential or remote). Statistics were performed using SPSS® and Excel®. RESULTS AND DISCUSSION: Diabetes follow-up appointments accounted for 34.4% of total consultations. Globally there was a high level of satisfaction and interest in future telemedicine follow-up. However, diabetic and older patients were less interested in this type of follow-up. Statistically significant differences about satisfaction were found in age, sex and presence/absence of diabetes. 70.6% of healthy patients preferred contact by e-mail over telephone. A selection bias is present because no randomization was made. The higher prevalence of diabetes consultations and the lack of adjustment for confounding factors can also affect results. Number of consults between January-February and April-May was compared and the main result was the significant reduction in the number of face-to-face consultations for diabetes (-50.1%) and hypertension (-94.1%). Presential consultations decreased by 72.6% and non-presential consultations increased by 61.9%. There was a selection bias because the sample was not random. The higher prevalence of diabetes consults and the lack of adjustment for confounders could affect results. CONCLUSIONS: This study allowed us to confirm the importance of telemedicine in primary health care, especially during pandemics. Participants recognized the usefulness of telemedicine and allowed future similar consultations.
NUIG-Shubhanker@Dravidian-CodeMix- FIRE2020: Sentiment Analysis of Code-Mixed Dravidian text using XLNet.

Social media has penetrated into multilingual societies, however most of them use English to be a preferred language for communication. So it looks natural for them to mix their cultural language with English during conversations resulting in abundance of multilingual data, call this code-mixed data, available in todays' world.Downstream NLP tasks using such data is challenging due to the semantic nature of it being spread across multiple languages.One such Natural Language Processing task is sentiment analysis, for this we use an auto-regressive XLNet model to perform sentiment analysis on code-mixed Tamil-English and Malayalam-English datasets.
Problems of Mass Media and Society Interactions

The article examines the role of the mass media in the life of the modern information society, examines the features and functions of mass communication as a form of social interaction. The author analyses the theories of foreign scientists who study the means of influence of mass media and the problems of modern mass media.
Traffic Gesture Classification for Intelligent Vehicles

Self-driving vehicles have shown rapid development in recent years and continue to move towards full autonomy. For high or full automation, self-driving vehicles will have to be able to address and solve a broad range of situations, one of which is interaction with traffic agents. For correct and save maneuvering through these situations, reliable detection of agents followed by an accurate classification of the traffic gestures used by agents is essential. This problem has received limited attention in literature to date. The objective of this work is to establish and investigate a working traffic gesture pipeline by leveraging the latest developments in the fields of computer vision and machine learning. This work investigates and compares how well state-of-the-art methods translate to traffic gesture recognition and what application specific problems are encountered. Multiple configurations based on skeletal features, estimated using OpenPose, and classified using recurrent neural networks (RNN) were investigated. Skeleton estimation using OpenPose and feature representations were evaluated using an action recognition dataset with motion capture ground-truth. Three RNN network architectures, varying in complexity and size, were evaluated on traffic gestures. The robustness of the developed system regarding viewpoint variation is explored, combined with the viability of transfer learning for traffic gestures. To train and validate these methods, a new traffic gesture dataset is introduced, on which an mAP of 0,70 is achieved. The results show that the proposed methods are able to classify traffic gestures within reasonable computation time and illustrate the value of transfer learning for gesture recognition. These promising results validate the methodology used and show that this direction warrants further research.
Turning transformer attention weights into zero-shot sequence labelers.

We demonstrate how transformer-based models can be redesigned in order to capture inductive biases across tasks on different granularities and perform inference in a zero-shot manner. Specifically, we show how sentence-level transformers can be modified into effective sequence labelers at the token level without any direct supervision. We compare against a range of diverse and previously proposed methods for generating token-level labels, and present a simple yet effective modified attention layer that significantly advances the current state of the art.
Early childhood teachers’ perceptions of storytelling activities storied by storytellers: focusing on their interests and the performances of the activities

본 연구의 목적은 이야기선생님이 들려주는 이야기에 대한 유아교사의 관심도를 살펴보고, 이야기선생님이 들려주는 이야기 프로그램을 운영하고 있는 기관에서의 운영 실태를 조사하는 것이다. 이야기선생님이란 유아교육기관에 방문하여 유아들에게 옛 이야기를 들려주는 외부전문가를 의미한다. 본 연구는 충청남도 내의 유치원 및 어린이집에 근무하는 유아교육기관을 대상으로 단순임의표집을 통해 312명의 유아교사를 표집하여 연구를 실시하였고 성실하게 응답한 246명의 설문지를 사용하였다. 이야기선생님이 들려주는 이야기에 대한 교사들의 관심도를 ‘관심도 측정 설문지’를 사용하였다. 이야기선생님이 들려주는 이야기 운영 실태에 대한 설문지는 정현숙(1995), 조일영(1998), 박혜경(2001)의 연구에서 유아교사를 대상으로 동화지도 실태를 묻기 위해 제작하고 사용된 설문지를 기초로 본 연구의 목적에 맞게 수정, 보완하여 사용하였다. 본 연구 결과는 이야기선생님이 들려주는 이야기에 대한 유아교사의 관심도가 결과적 관심, 무관심, 협력적 관심, 정보적 관심, 대안적 관심, 개인적 관심, 운영적 관심의 순서로 나타났다. 이야기선생님이 들려주는 이야기프로그램의 운영 실태에 대해 알아본 결과, 이야기선생님이 들려주는 이야기의 가장 우선적 목적으로 유아교사들은 인성교육이라고 생각하고 있는 반면 언어교육이라고 생각하는 경우는 가장 낮은 것으로 나타났고 이야기선생님이 들려주는 이야기의 종류를 살펴보면 우리나라 전래동화와 창작동화가 가장 높은 비중을 차지했고 외국의 전래동화와 창작동화가 비교적 낮은 비중을 차지했다. 본 연구에서 나타난 결과에 근거할 때, 이야기선생님이 들려주는 이야기는 교육현장에서 교사가 들려주는 이야기와 더불어 영유아들에게 긍정적 의미를 제공할 수 있음을 알 수 있었다. 이는 앞으로 이야기선생님이 들려주는 이야기 사업의 활성화를 모색하는데 중요한 기초자료를 제공할 것이다.The purpose of this study is to examine early childhood teachers’ interests in storytelling activities storied by storytellers and the performances of the activities in Kindergartens. A storyteller in this study refers to an expert who visits a preschool and tells old stories to children. With a simple random sampling, a total of 312 early childhood teachers working in Kindergartens and day care centers in Chungcheongnam-do Province had participated in a survey and 246 questionnaires were used for analysis. Using ‘Interest measurement questionnaire’, teachers interests in stories told by a storyteller was measured. The questionnaire about the performances of the activities in Kindergartens(Chung, 1995, Joe, 1998, and Park, 2001) was revised and used for the purpose of this study. The results of this study showed that early childhood teachers were interested in the storytelling activities storied by storytellers in order of effective interests, indifference, cooperative interests, informative interests, alternative interests, personal interests, and managerial interests. The results of performances of the activities in Kindergartens presented that early childhood teachers seemed to think that the first priority of storytelling was to achieve children’s personal development whereas language learning was not the activities’ main purpose. Furthermore, the most widely-read stories that the storytellers read to children were Korean traditional fairy tales and creative fairy tales while stories related to foreign countries were relatively low. It is discussed how storytelling activities storied by storytellers can give positive and encouraging messages for children’s development and how teachers can utilize the storytelling programs in Kindergartens.
Cepu Double Pitch Sport Center Dengan Pendekatan Arsitektur Kontekstual

Cepu Double Pitch Sport Center is a sports building that can be used as a center fororganizing various sporting activities in Cepu. Equipped with international standardfacilities and infrastructure which has a double arena floor design. This sports buildingfacility will be built on Ronggolawe Main Street, Bulansawahan, Balun, Kec. Cepu, BloraRegency, Central Java. Apart from being equipped with a volleyball game arena,basketball, tennis, badminton, Sepak Takraw and also a swimming pool, Cepu DoublePitch Sport Center is also equipped with a sports park that can be used for sports andrecreation. It was created to accommodate the enthusiasm of the Blora community forsports and can also be useful as a means of physically and mentally healthy. The overalldesign of the building is inspired by the concept of a contextual architectural approachwith the hope of elevating and introducing the local culture and arts of Blora Regencyoutside of Blora, especially crafts made from teak wood.
LibGuides: Murphy Memorial Library: Course Reserves

Information on accessing and using Clarks Summit University's library resources and so much more! Find out where you can view what books are on reserve in the library for each of your classes.
USE OF GOOGLE MEET IN TEACHING AND LEARNING PROCESS IN DEPARTMENT OF INFORMATION &amp; COMMUNICATION TECHNOLOGY, POLITEKNIK SULTAN MIZAN ZAINAL ABIDIN

The spread of the Covid19 pandemic in Malaysia has a profound impact on all sectors, including the education sector. Following the government's move to announce PKP throughout Malaysia, it has forced the PdP process to be implemented online either in schools or IPTs. In relation to that, most of the PdP process at JTMK, PSMZA is also conducted online. Various platforms are used and one of them is Google Meet. This study was conducted to identify three aspects, namely in terms of accessibility, user interface design, and Google Meet user-friendly level from the perspective of students. This study was conducted by distributing 1 set of questionnaires to respondents. The respondents of this study consisted of 80 students in semesters 3 and 4 taught by the researcher. The results showed that the respondents agreed that Google Meet is easy to achieve where the average value of the mean score is 3.94 in addition to having a simple and attractive user interface design with an average value of a mean score of 3.90. Respondents also agreed that Google Meet has a good and pleasant level of user-friendliness with an average mean score of 3.92. So, Google Meet is a great PdP process platform to use.
Implementasi Extreme programming Pada Website Marketplace Lapak Petani Online

The use of information technology to improve people’s welfare has been implemented in various lines of life, including selling agricultural products through the marketplace to expand marketing and increase sales figures. Marketplace built based on the website using extreme programming (XP) method. The selection of extreme programming for marketplace development is tailored to all user needs and system requirements because website development is done in a relatively short time and many changes occur during website development. The stages of the extreme programming method are carried out in several iterations to get feedback from the end-users who are used in the website improvement process so that at the end of the iteration process the website developed is in accordance with the needs of the end-user. The output generated from this research is the farmer’s stall marketplace website that is used to market agricultural products from the Cilacap Holtikultura Farmers Association (PHC).
شناسایی مؤلفه ها و مهارت های مدیریت دانش شخصی کتابداران

Purpose: The purpose of this study was to identify the dimensions of personal knowledge management and to evaluate the status of personal knowledge management skills of librarians in central libraries of public libraries in Tehran. Methodology: This is purpose-based research and is qualitative-quantitative research based on the method and how to obtain the required data. The statistical population of this research in the qualitative section is individuals who have had a background in personal knowledge management and research, and in the quantitative section, it is the staff and librarians of central libraries of public universities in Tehran. A researcher-made questionnaire consisting of seven components of retrieval, evaluation, organization, collaboration, analysis, information provision, and information security was used to evaluate personal knowledge management. Cronbach's alpha reliability was 0.8. Findings: Among the elements of librarians’ personal knowledge management in central libraries of state universities in Tehran, the component analysis has been at the relatively desired level, and other studied components were at the desired level. There is a significant relationship between personal knowledge management skills, but there is no significant difference between gender, age, and background with personal knowledge management skills. Conclusion: Personal knowledge management serves as a viable tool for academic libraries, through which they can improve their services and retain their capacity. Personal knowledge management skills seem to need instruction. Because librarians, as well as other people with no personal knowledge management skills, are unable to improve their position in the library, they need to learn the basics of personal knowledge management. Learning and identification of librarians’ personal knowledge management skills will help them learn more about improving those skills; and library officials and academic community will be persuaded to pay more attention to the tools and techniques of personal knowledge management. Therefore, library managers and universities must be planned to be trained in this case.
An Operational Responsibility and Task Monitoring Method: A Data Breach Case Study

As a result of digitalization, services become highly dependent on information systems thus increasing the criticality of security management.However, with system complexity and the involvement of more human resources, it becomes more arduous to monitor and track tasks and responsibilities.This creates a lack of visibility hindering decision making.To support operational monitoring, we propose a method composed of i) a core of security concepts from International Standard Organization (ISO) standards ii) a graphical modeling language iii) a guiding process and iv) a tool that provides verification through formal Object Constraint Language (OCL) queries.Applying this method to the case of the Capital One data breach showcases incident prevention through task supervision.The resulting work product is a formal comprehensive map of assets, actors, tasks and responsibilities.The SysML formalism allows different actors to extract information from the map using OCL queries.This allows for regular task and responsibility verification thus closing any window of attack possible.
ALGORITMA GENETIKA PADA APLIKASI PENJADWALAN MATAKULIAH PROGRAM STUDI TEKNIK INFORMATIKA

The design of course schedules is a complex matter that is still done conventionally. Because it requires more time and energy if designing a schedule that has a lot of data. This will become an obstacle when faced with an increase in the number of components and conditions determined by the informatics engineering study program. To solve the problem an algorithm is needed. One of the algorithms was inspired by genetic theory and natural selection. The application of the algorithm is used to provide recommendations in the preparation of course schedules. In this study, the design used is using Data Flow Diagrams (DFD). And testing the system using a blackbox. The genetic algorithm is quite good to use as an algorithm that is able to meet the algorithm requirements in designing college course schedules. Because the resulting fitness value is 1 which indicates the optimal fitness value, then the resulting course schedule does not occur at the same time.