Reviewerly/exHarmony huggingface dataset:
The development of a clustering technique-based blended learning model: Preliminary study in the department of fine arts education

This research is a preliminary study that is used as a guide to develop a blended learning model based on the clustering technique in Universitas Negeri Padang.This research was conducted through a literature study.Students' and lecturers' expectations regarding the implementation of learning the history of Indonesian art during COVID-19 pandemic is studied.Based on literature study, three dominant factors need to be considered in designing the clustering techniquebased blended learning, namely: (1) connectivism learning, (2) the ability to read quickly, and (3) self-efficacy.The results of the needs analysis and feasibility study show that the facilities and infrastructure needed are adequate to conduct the model.Reading ability is still at a moderate level, and self-efficacy is lacking.It is necessary to develop blended learning based on compounded discovery or clustering techniques.From these findings, at least it can be concluded that it is true that a blended learning model based on clustering techniques is needed.This consideration is based on the department's need to produce graduates who are ready to become art teachers, art critics, or fine arts entrepreneurs who master the history of the development of fine arts in the archipelago, while online or face-to-face learning alone is considered insufficient to equip students' knowledge and skills.It involves a combination of online and face-to-face methods in a structured manner so that maximum learning outcomes are achieved.
Online Examination System

Abstract: Online Examination System is an on-line test simulator that allows you to take an online exam, test quickly, and without wasting time physically examining the test paper. The major goal of this web-based online assessment system is to completely evaluate students using a fully automated approach that not only saves time but also provides quick and accurate results. Students give papers at their leisure from any location using the internet and their time, with no requirement for supplementary items such as paper, pen, and so on. Students benefit from the online examination system since it allows them to take the test quickly and easily. It also delivers 100 percent accurate and secure results instantly after the test. Students can only enter to take an exam if they have a valid username and password. This test has multiple choice questions with a sufficient number of options. There are no restrictions on the amount of options available, and they can be randomized so that the same set of questions does not appear in front of all students, preventing manipulation. Although more than one option may be correct, the user can only choose one. This establishes a time limit.
The Relationship of Food Addiction With Emotional Control and Socio-Cultural Factors in University Employees

BACKGROUND/AIMS:The aim of this study was to examine the relationship between food addiction in university employees with emotion control, sociodemographic and sociocultural factors and social media use. MATERIALS AND METHODS:The study was conducted on 213 administrative and academic staff working at a foundation university.The data was collected by a demographic fact sheet, the Social Media Addiction Scale-Adult Form (SMAS-AF), the Courtauld Emotion Control Scale (CECS) and the Yale Food Addiction Scale (YFAS). RESULTS:The average age of the participants was 36±10 years and 65.7% of them were women.Of all the participants, 4.7% (n=10) were found to be addicted to food and 80% (n=8) of these were women.A significant inverse relationship was found between SMAS-AF and CECS total scores.As social media addiction increases, emotion control decreases.Among those with food addiction, the proportion of those with a low-income levels was greater compared to any other income group.There was no significant relationship between food addiction and gender, age, social media addiction, or emotion control.A significant negative correlation was found between age and the total score of social media addiction. CONCLUSION:In our study, the prevalence of food addicts among university employees was low.The fact that the rate of the food addicts was higher in women and those who were single and those who had low-income levels reveals that gender, marital status and income levels are important socio-cultural factors.While no relationship was found between food addiction and emotion control or social media addiction, higher scores of SMAS-AF were noted in single and low-income users.
Meningkatkan Kemampuan Siswa dalam Menemukan Ide Pokok Paragraf Melalui Pendekatan Saintifik di Kelas VI SD Negeri 1 Bumi Harjo

The purpose of this study is to find out: 1. A scientific approach can improve students' ability to find the main idea of a paragraph in Class VI Semester 1 of the 2019/2020 Academic Year of SD Negeri 1 Bumi Harjo. 2. Using a scientific approach can improve students' ability to find the main idea of a paragraph in Class VI Semester 1 of the 2019/2020 Academic Year at SD Negeri 1 Bumi Harjo. Research Methods: This research was conducted at SDN 1 Bumi Harjo with 26 students as the subject. The procedure of this research is through planning, action, observation, and reflection. The technique of collecting data is through tests, observations, and documentation, while the data is analyzed through data reduction, data display, and data consolidation.
Optimization model analysis and its application in mathematical modeling

In today’s society, mathematical modeling has attracted more and more attention due to its wide application, and optimization model is one of the most commonly used models. In this paper, linear programming, integer programming and nonlinear programming in the optimization model are taken as examples, combined with the three problems in the national college students ' mathematical modeling competition, the application of three optimization methods in mathematical modeling is briefly analyzed. Finally, the methods of solving optimization problems are summarized.
Survey Paper on Content Moderation

With the growth and accessibility of the internet to everyone, recognizing pornographic images is of great significance for protecting children's physical and mental health. It’s common for children to surf the internet and they are just one click away from getting access to pornographic images. It is the desire of all parents to protect their children from online pornography, cyberbullying, and cyber predators. Several existing methods analyze a limited amount of information from a child's interaction with the respective online section. Some restrict access to sites based on blacklists known as banned URLs, others attempt to scan and analyze media content being exchanged between two parties. However, new URLs can be used to bypass blacklists, and images, videos, and text appear to be safe individually but should be evaluated together. Due to the vast size of social media- generated content, these approaches are insufficiently accurate. Furthermore, the approaches are not discriminative enough on a variety of image properties. The Colour, shadow, and frequency features of the images can vary, even the context is the same according to lumination features. The problem can be solved more accurately with deep learning techniques. Notably, the specific type of deep learning architecture called convolutional neural network is suitable for the problem space. Having a potential solution becomes even more important than detecting and recommending NSFW (Not Safe For Work) content that may be present to the user. Keywords: adult content, deep learning, NSFW, cyberbullying, pornographic,
Level of Compliance with the Brigada Eskwela Implementation to DO No. 66 S. 2018 in Selected Public Junior High Schools in Laguna: Basis for an Action Plan

In May 2003, the Department of Education launched National Schools Maintenance Week (DepEd Memorandum 79, s. 2003) to promote the Adopt-A-School Program. Every third week of May, teachers, parents, and community members gathered to repair and prepare public schools for the start of classes. In the spirit of “bayanihan”, private institutions or individuals joined forces with local governments to achieve the DepEd Memorandum's goals and objectives. Brigada Eskwela (BE) is the DepEd's response to the problem of inadequate school maintenance and ensures school preparedness and competency before classes begin. Since it is difficult to involve stakeholders including parents, the private sector, community organizations, and non-governmental organizations, not all schools participate in this endeavor Thus, this study analyzed the level of compliance of the BE implementation guidelines matrix among the Junior High school focal persons in selected schools in Laguna province. It involved 200 respondents and utilized a researcher-made questionnaire for this descriptive study. Frequency, weighted mean, and t-test were employed to determine the level of each BE dimension and significant differences in the demographic profile of the respondents. Results revealed that the responders' compliance with BE is inferred as Complied, with no significant differences in its dimensions. Conferring to the outcomes of the surveys, the bulk of BE Focal Persons were trainees; a minimum amount of service as a BE Focal Person is suggested. In conclusion, it has statistically significant positive correlations with DepEd Memorandum No.24 S.2008 so a plan to close the gap was recommended.
Implementasi Algoritma Apriori untuk Mendapatkan Pola Kelulusan Mahasiswa

Data transactions that occur every day will become chunks of data in an institution's database. These chunks of data have no value if mining is not carried out in obtaining interesting knowledge and information. The purpose of this study was to analyze chunks of graduation data for STIE-Graha Karya Muara Bulian students, in order to obtain patterns formed from predetermined variables. The method used is the Apriori Algorithm. This is in accordance with the main function of this algorithm, which is to analyze the frequent itemset. The results showed that for the 2-itemset data the highest support value was the combination of Female Gender and Work with a value of 34%, while the highest confidence value was in the combination of a Grade Point Average above 3.5 and Work with a score of 85%. As for the 3-itemset, the highest support value is in the combination if the GPA is above 3.5, gender is female and the work status reaches 14% and confidence is 90%.
Property modelling in the AECO industry

In the semantic representation and documentation of our built environment, properties of building elements, spaces, and concepts in general play a tremendously important role. Such properties – e.g. thermal transmittance, door height, fire resistance classification according to specifications – capture the state of the built environment at a given moment and place. In a global world with very diverse stakeholders and contexts, a multitude of property definitions are made, leading to diverse ways in which properties can be defined and exchanged and handled. In order to avoid misunderstandings, confusion, and continuous redefinition of properties of elements, there is a need to distinguish between those diverse methods for describing properties and using them in a connected World Wide Web environment. In this chapter, we therefore look into diverse property modelling approaches on the web and their associated functionality and limitations. We focus particularly on a Linked Data and Semantic Web context, yet parallels are made with general property modelling approaches as applied in relational databases, custom JSON and XML formats and IFC-SPFF (Industry Foundation Classes in STEP Physical File Format). This includes explicit parallels with international standardisation initiatives in CEN, ISO, W3C, and buildingSMART. These property modelling approaches are compared, diverse implementations are documented, and guidelines are presented on when to use which property modelling approach – applied to the Architecture, Engineering, Construction and Operations (AECO) (Architecture, Engineering, Construction and Operations) industry. The resulting framework can be used to easily distinguish between property modelling approaches and make corresponding agreements for an information exchange.
A Covid-19 Sentiment Analysis on Twitter Using K-Nearest Neighbours

In December 2019, an outbreak named Corona Virus (SARS-CoV-2) occurred in the city of Wuhan, China which was later known as COVID-19. News of the development of the virus spread through various media, one of which was through the well-known platform Twitter. Twitter is one of the widely used media platforms to communicate about Covid-19. Information related to Covid-19 circulating in the community can be in the form of news or opinions or opinions. Then, the circulating information will be classified into three classes, namely positive, negative or neutral. The method used to calculate the prediction of text classification on Twitter is K-nearest neighbors (KNN). The dataset used in grouping on twitter by using the account name Covid19. Firstly, the dataset by crawling data or information on twitter. Secondly, the text mining stage to determine the class distance value and calculate the Euclidean distance formula based on all the training data to be tested. After the training process is complete, the evaluation model used will be used, the Euclidean results are taken based on the value of the closest distance. The accuracy of the model will be calculated using the previous Euclidean method. The results of this study he obtained with the highest value, one of which was 78% using a 50:50 sample comparison with k-5 and k-9 values.
A GAN based approach for inferring progression trajectories of costal cartilage calcification from cross-sectional data at image level

Costal cartilage calcification (CCC) increases with age and presents differently for men and women. In individuals, however, the cross-sectional studies that show such trends do not reveal the geometric trajectories through which calcification might accumulate across a lifetime. Generative adversarial networks have the potential to reveal such trajectories from cross-sectional data by learning population trends and synthesizing individualized images at progressive levels of calcification.Chest wall mid-surface CT images with normalized cartilage morphologies were produced for 379 subjects aged 6 to 90, and labeled by sex and calcification severity. A conditional GAN with added loss terms to favor one-way accumulation of CCC was trained using organized image batches. GAN performance was assessed by comparing the distributions of images between the training and synthetic groups.Synthetic images generated from a common seed for a given sex and at successive calcification severity levels showed incremental and regional growth of calcification sites. CCC patterns for synthetic male and female images matched known sex-based differences, and individual CCC growth in synthetic images was consistent with previously observed population trends. These trends in the synthetic images were also quantified by structural similarity scores. Synthetic images generated from different input seeds further showed individual variance in specific regions and trajectories of CCC accumulation.This study inferred individual progression of CCC accumulation from uncalcified to severely calcified using cross-sectional image data. This information can inform computational models of the changing chest wall biomechanics with age, and the GAN-based technique shows potential for inferring longitudinal data from population trends in other clinical areas.
Affect Expression: Global and Local Control of Voice Source Parameters

This paper explores how the acoustic characteristics of the voice signal affect.It considers the proposition that the cueing of affect relies on variations in voice source parameters (including f0) that involve both global, uniform shifts across an utterance, and local, within-utterance changes, at prosodically relevant points.To test this, a perception test was conducted with stimuli where modifications were made to voice source parameters of a synthesised baseline utterance, to target angry and sad renditions.The baseline utterance was generated with the ABAIR Irish TTS system, for one male and one female voice.The voice parameter manipulations drew on earlier production and perception experiments, and involved three stimulus series: those with global, local and a combination of global and local adjustments.65 listeners judged the stimuli as one of the following: angry, interested, no emotion, relaxed and sad, and indicated how strongly any affect was perceived.Results broadly support the initial proposition, in that the most effective signalling of both angry and sad affect tended to involve those stimuli which combined global and local adjustments.However, results for stimuli targeting angry were often judged as interested, indicating that the negative valence is not consistently cued by the manipulations in these stimuli.
Technology in Mental Health and Education: Applications, perspectives and challenges in the Colombian Caribbean

This symposium will focus on the emerging field of technology applied to mental health and education in the Colombian Caribbean, a region with great needs in science, technology, innovation, health and education.Speakers will address the future prospects, applications and challenges of introducing technological innovation in intervention for these fields.Throughout the presentations, the speakers will discuss creation opportunities, perspectives in development or future application, and ethical challenges in the framework of this progressive field that is beginning to consolidate in this region.Topics to be discussed include: (1) technological prototype for the study of sustained attention in educational settings; (2) preliminary perspectives of the study of an application for university students aimed at preventing gender violence and promoting mental health; (3) bases for the application of a virtual reality environment for intervention in ADHD; and (4) implications and ethical challenges inherent to this technological field, especially in the health care area.These topics were included as they provide a glimpse into the challenges that are developing in the region, as well as the ethical issues of considering the use of technological tools to address them.This symposium aims to highlight the opportunities of technology research in the domains of health and education in this region to promote science, innovation and social development, but also aims to make a critical analysis of this progress in the interests of establish the limitations and challenges that cannot be set aside only by the novelty and the boom of the technological revolution.
Person re-identification network based on weight-driven saliency hierarchical utilization

The purpose of person re-identification (ReID) is to retrieve a person of interest from a set of images taken by multiple cameras. In the person ReID task, the use of global-local features and attention mechanisms to construct robust pedestrian features has been shown to be effective. However, in these methods, the models only focus on extracting pedestrian features with strong discrimination while ignoring the potential features, which are equally valuable and can play an important role in person ReID tasks. To extract these potential features, which are hidden by salient features, we propose a person ReID network based on weight-driven saliency hierarchical utilization. Three improvements are exploited to extract more comprehensive and diverse information of pedestrians. First, we use the non-local module to enhance the feature extraction ability of the model. To mine potential features, we use a saliency enhancement and suppression operation in the non-local module. Second, we employ a new multi-stage global feature fusion module to increase the diversity of features. Third, we use the multi-branch attention module to extract more fine-grained part features to improve the model performance. Extensive experiments show that our model achieves excellent performance on the Market-1501, duke multi-tracking multi-camera re-identification, and multi-scene multi-time person ReID datasets.
PRIVACY-PRESERVING REAL TIME TRACING SYSTEM FOR COVID-19 PATIENT USING GPS TECHNOLOGY

The new normal condition in Indonesia does not mean that Indonesia is completely free from infection with the Covid 19 virus. Individuals exposed to the Covid 19 virus have symptoms like mild, moderate, to severe condition. Most individuals who have mild symptoms are self isolating at their home until tested negative for the Covid 19 virus. The impact of Covid 19 has led to an increase in the use of gadgets to access all the information needed. The purpose of this study is to provide information regarding patients infected with Covid 19 in a certain area through a tracing application. The application can help public to find out how many individuals are infected with Covid 19 in the surrounding environment by prioritizing privacy-preserving in a real time. The method used in this study is a combination of graph theory and GPS tracing system on a gadget. The initial stage of this study was carried out through tracing Covid 19 patients based on their position of residence. The final stage of the study was carried out using a graph approach based on distance and percentage of transmission. The result of this study obtained privacy-preserving real-time tracing with the predicted precentage of Covid 19 transmission susceptibility within the scope of danger or vulnerability, quite safe, and secure. Furthermore, individuals can take precautions by maintaining a safe distance.
Analysis, Performance Monitoring and Tracking System for Employees

Abstract: Every organization, whether big or small, has human resource challenges to overcome. Every organization has different employee management needs; therefore we design exclusive employee management systems that are adapted to the managerial requirements. This is designed to assist in strategic planning, and will help to ensure that the organization is equipped with the right level of human resources for the future goals. Also, for the busy executive who are always on the go, our systems come with remote access features, which will allow you to manage your work force anytime, at all times. These systems will ultimately allow you to better manage resources. One of the main features in this system is performance tracking and analysis, sales verification for employees. Effective time tracking mechanism saves both time and money for the organization. The purpose of the Analysis, Performance Monitoring and Tracking System for employee is to automate the existing manual system by the help of computerized equipment’s and full-fledged computer software, fulfilling their requirements, so that their valuable data/information can be stored for a longer period with easy accessing and manipulation of the same. The required software and hardware are easily available and easy to work with. Analysis, Performance Monitoring and Tracking System, as described above, can lead to error free, secure, reliable and fast management system. It can assist the user to concentrate on their other activities rather to concentrate on the record keeping. Thus it will help organization in better utilization of resources. The organization can maintain computerized records. Keywords: Information system, Database system, DBMS, employee table, table fields, primary key, foreign key, relationship, sql queries, controls.