Reviewerly/exHarmony huggingface dataset:
Students’ Acceptance Level of Digital Newspaper Publication Performance Assessment Innovation

The alternative assessment was implemented in the Editing Course (AK20903) to analyze students’ group achievement in digital skills. This core course is compulsory for all second-year communication (UH6321001) students to prepare them with the skills of writing, analyzing, and copy editing. Students' digital skills are assessed through the publication of a digital newspaper that uses graphics applications provided by the university. However, this software can only be accessed within the campus area. The Covid-19 pandemic has changed the landscape of student locations where students are no longer within the coverage area where the software is accessible. To address this issue, the Canva application is being tried out. This study employs a quantitative approach with a sample of 124 respondents consisting of current students who are registered in the AK20903 (Editing) course. This study aims to analyze the acceptance level of the students of the introduced innovation. To collect the data a set of four parts questionnaire was used that included the demographic information, perception of user-friendly, perception of usability, and students’ satisfaction. The results showed that most of the respondents highly agreed that perception of usefulness, perception of usability, and users’ satisfaction are the factors that influenced their acceptance of the innovation performance assessment of digital newspaper publications. The findings of the study indicate that students’ acceptance of the innovation performance assessment of digital newspaper publishing is influenced by the benefits and usability gained from the use of Canva.
MANAJEMEN INFORMASI PERSEDIAN BAHAN BAKU PRODUKSI DENGAN METODE FIFO BERBASIS CLIENT SERVER

In conducting research, using descriptive methods, where the sources and types of data used are quantitative data and qualitative data. The research design used by the author is a primary data research design and a secondary data research design. The data collection technique used is a field research technique which includes interviews and observations, while a library research technique includes data collection techniques by studying, reviewing and understanding existing data sources. in several books related to the research.&#x0D; In the presentation of the raw material inventory report still using manual recording using inventory cards and Microsoft Office Excel 2003 software, then the new information system will be used to create a system that includes making DFD, ERD, Normalization, context diagrams and physical design, namely output design and databases.&#x0D; From the results of the study, it can be concluded that the existing system in CV. Adi Sejahtera Bandung there are several weaknesses, the system for recording transactions in and out of raw materials that is run manually is still not efficient, the occurrence of errors and the slow sales process is due to the slowness in receiving information on goods at this company. The author suggests using a computerized raw material inventory information system to help management control inventory transactions by improving the information structure in reports and making standardized reports to make work efficient and effective.
Comparative Analysis of the Speed of the Sorting Method on Google Translate Indonesian-English Using Binary Search

In Indonesia, English is a compulsory subject for students. This course is an uninteresting subject and tends to be difficult for students to understand. Meanwhile, on the other hand, international issues are often discussed, namely English which is Students must know and be fluent in reading, writing and communication. The basic idea of research objectives, comparing the sorting process using two different algorithms, namely bubble sort and Merge Sort. The basic model of the research method Comparative Analysis of the Speed of the Shorting Method on Google Translate Indonesian-English Using Binary Search. Sorting, Sorted (ordered according to certain rules/rules), and the data is presented in sorted form, as said in dictionaries, and files in a directory. The algorithm used for sorting is bubble sort, which is an element comparison operation that is exchanged for other elements until the end of the data series is reached, until no more elements are swapped. Results for find out how well the performance speed of the bubble sort algorithm is in sorting data.
Cyber attacks from the aspect of international and domestic law

There is no doubt that international as well as internal legal regulation of the use of cyber space will be one of the most important topics in the near future. Namely, the development of information technologies, as well as the solutions that these technologies offer, which are used in cyberspace, will significantly improve the quality of international life structures and thus the individual structure in the future As a proposal for comparison, we cite an example of the formation of joint investigative teams, due to the fact that very often the perpetrators are from several countries and act in co-perpetration. By forming such criminal-legal teams from several countries, the goal of identifying the perpetrators, obtaining the necessary evidence and prosecuting the perpetrators of criminal acts can be achieved. As we have already emphasized, the very speed of development of modern technology, as well as the possibility of its misuse, imposes the need for every state to develop a system of defense of institutions and citizens against this type of threats. High-tech crime knows no borders, and the target can be any country, institution or individual, which leads to the conclusion that in addition to the internal regulation of this area, international cooperation is also necessary in order to adequately oppose this type of crime. Also, the calming of tensions between the most developed countries in the world, which must happen at some point, will increase the interest in solving international legal restrictions on the use of cyberspace with the aim of increasing national security in cyberspace and creating conditions for the economic development of countries and the formation of world and regional markets. In the end, it can be concluded that the normative - legal international regulation of the use of cyberspace and the prevention of misuse of modern information and communication technologies is a prerequisite for the further progress of humanity. In the future, all this will lead to close cooperation of all internationally relevant factors in the development of common standards and rules, the definition of common response mechanisms to cyber attacks and the formation of a common security cyber infrastructure with the aim of preventing cyber attacks and increasing cyber security on a global level.
Inter-Model Interpretability: Self-Supervised Models as a Case Study

Since early machine learning models, metrics such as accuracy and precision have been the de facto way to evaluate and compare trained models. However, a single metric number doesnâ€™t fully capture the similarities and differences between models, especially in the computer vision domain. A model with high accuracy on a certain dataset might provide a lower accuracy on another dataset, without any further insights. To address this problem we build on a recent interpretability technique called Dissect to introduce inter-model interpretability , which determines how models relate or complement each other based on the visual concepts they have learned (such as objects and materials). Towards this goal, we project 13 top-performing self-supervised models into a Learned Concepts Embedding (LCE) space that reveals proximities among models from the perspective of learned concepts. We further crossed this information with the performance of these models on four computer vision tasks and 15 datasets. The experiment allowed us to categorize the models into three categories and revealed for the first time the type of visual concepts different tasks requires. This is a step forward for designing cross-task learning algorithms.
Information Theory–based Compositional Distributional Semantics

Abstract In the context of text representation, Compositional Distributional Semantics models aim to fuse the Distributional Hypothesis and the Principle of Compositionality. Text embedding is based on co-ocurrence distributions and the representations are in turn combined by compositional functions taking into account the text structure. However, the theoretical basis of compositional functions is still an open issue. In this article we define and study the notion of Information Theory–based Compositional Distributional Semantics (ICDS): (i) We first establish formal properties for embedding, composition, and similarity functions based on Shannon’s Information Theory; (ii) we analyze the existing approaches under this prism, checking whether or not they comply with the established desirable properties; (iii) we propose two parameterizable composition and similarity functions that generalize traditional approaches while fulfilling the formal properties; and finally (iv) we perform an empirical study on several textual similarity datasets that include sentences with a high and low lexical overlap, and on the similarity between words and their description. Our theoretical analysis and empirical results show that fulfilling formal properties affects positively the accuracy of text representation models in terms of correspondence (isometry) between the embedding and meaning spaces.
Big Data Privacy Preservation Using Principal Component Analysis and Random Projection in Healthcare

With the rising usage of technology, a tremendous volume of data is being produced in the current scenario. This data contains a lot of personal data and may be given to third parties throughout the data mining process. Individual privacy is extremely difficult for the data owner to protect. Privacy-Preservation in Data Mining (PPDM) offers a solution to this problem. Encryption or anonymization have been recommended to preserve privacy in existing research. But encryption has high computing costs, and anonymization may drastically decrease the utility of data. This paper proposed a privacy-preserving strategy based on dimensionality reduction and feature selection. The proposed strategy is based on dimensionality reduction and feature selection that is difficult to reverse. The objective of this paper is to propose a perturbation-based privacy-preserving technique. Here, random projection and principal component analysis are utilized to alter the data. The main reason for this is that the dimension reduction combined with feature selection would cause the records to be perturbed more efficiently. The hybrid approach picks relevant features, decreases data dimensionality, and reduces training time, resulting in improved classification performance as measured by accuracy, kappa statistics, mean absolute error and other metrics. The proposed technique outperforms all other approaches in terms of classification accuracy increasing from 63.13 percent to 68.34 percent, proving its effectiveness in detecting cardiovascular illness. Even in its reduced form, the approach proposed here ensures that the dataset's classification accuracy is improved.
Electronic Human Nutrition Analyzer for Managing Obesity (EHNAMO)

The bad eating habits in the Nigeria society is increasing and the Obesity rate is constantly increasing but to monitor the Nutritional status simply means booking an appointment with a nutritionist with long hours of waiting time to get answers. Another important factor is cost of getting an appointment this could be high to an average Nigerian giving the fact that seeing a nutritionist is not one-time bargain as one would continuously need to book an appointment on the long run. The developed is capable of allowing users to enter personal details such as height, weight, age, gender and other factors to efficiently monitor the user nutritional status. By calculating the B.M.I (Body mass index) the system easily identifies the nutrition status of the user and proceeds to recommend appropriate profile for the user such as gaining weight, maintaining weight and losing weight and also likewise calculating B.M.R (Basal Metabolic rate) of the user the system automatically knows the amount of calories needed to be present in the individual nutritional status based on the users profile. The web application was developed using Php7 and Mysql which can be deployed on to any web server for the application to be accessible to users. This web based nutrition analyzer allows users to generate their own diet/Nutritional Food-time table which can be followed to achieve a healthy Nutritional Status. The study gives room for nutritionist to user interaction in order to help boost user satisfaction, the system has the capabilities of generating reminder, alerts, exercise routines and constantly motivates the user to use the application and improve their nutritional habits. Keywords: Obesity, Body Mass Index (BMI), Basal metabolic rate (BMR), Diet, Nutrition Journal Reference Format: Adepegba, O. A., Adepegba S. A., Longe O. B. &amp; Adesiyan A. P. (2022): Electronic Human Nutrition Analyzer for Managing Obesity (EHNAMO). Journal of Behavioural Informatics, Digital Humanities and Development Research. Vol. 8.No. 1, Pp 15-26. Available online at https://www.isteams.net/behavioralinformaticsjournal dx.doi.org/10.22624/AIMS/BHI/V8N21P2
TRABALHADORES (AS) DA SAÚDE E DESGASTE NO TRABALHO: REFLEXÕES SOBRE O IMPACTO DA PANDEMIA NOS HOSPITAIS DE REFERÊNCIA DA COVID-19 NO SERTÃO DA PARAÍBA

This article discusses the role of the social worker in the Social Assistance Policy, seeking a critical reflection on the possibilities of implementing the political ethics of the profession design, evaluating the limits and potentialities within an environment marked by the ideology capitalist.For this we intend to analyze a specific workspace professional, Social Duty, unveiling their instrumentality action alternatives and the possibilities of contributing to realization of the rights of the trainees.The base analysis Social Duty in the municipality of Ponte Nova-MG, located in the Zona da Mata region of Minas Gerais.
Beyond Traditional Characterizations in the Age of Data

What are data and network models? What are efficient algorithms? What are meaningful solutions? Big Data, Network Sciences, and Machine Learning have fundamentally challenged the basic characterizations in computing, from the conventional graph-theoretical modeling of networks to the traditional polynomial-time worst-case measures of efficiency:
Visualization in Data Science VDS @ KDD 2022

Data science is the practice of deriving insight from data, enabled by modeling, computational methods, interactive visual analysis, and domain-driven problem solving. Data science draws from methodology developed in such fields as applied mathematics, statistics, machine learning, data mining, data management, visualization, and HCI. It drives discoveries in business, economy, biology, medicine, environmental science, the physical sciences, the humanities and social sciences, and beyond. Machine learning and data mining and visualization are integral parts of data science, and essential to enable sophisticated analysis of data. Nevertheless, both research areas are currently still rather separated and investigated by different communities rather independently. The goal of this workshop is to bring researchers from both communities together in order to discuss common interests, to talk about practical issues in application-related projects, and to identify open research problems. This summary gives a brief overview of the ACM KDD Workshop on Visualization in Data Science (VDS at ACM KDD and IEEE VIS), which will take place virtually on Aug 14-18, 2022 (Held in conjunction with KDD'22). The workshop website is available at http://www.visualdatascience.org/2022/
Enseñar y evaluar las competencias transversales (key skills) en programas de educación superior mediados por la tecnología

In this paper, the authors will talk about the development of technological platforms and tools that will support the creation and implementation of techno-pedagogical paradigms to tech the XXI Century generations. By proving how the innovative model of the open and distance learning universities (UNAD, for its Spanish acronym) is not run out and can be renewed, taking as an example the COVID-19 pandemic and analyzing the carriers that provide change to a new education, where the need of innovation in higher education in open and distance modalities is an urgent matter. Undoubtedly, learning is one of the human capacities that has most influenced their development and evolution. Thus, the e-education concept is presented as an effort to develop talents and human capacities using the Internet and new information and communication technologies (ICT). This will allow introducing a generalized remote mode, which will create a different culture adjusting the school curriculum to an online strategy, and not a rigid one, that involves technological improvements, so general and specialized knowledge are combined to the needs of scientific, technological, and social development. Teachers work with students differently and provide help through more knowledge and experience. Recent studies are showing that there are more open and online options for teacher professional development and teachers access the Internet to expand their development opportunities through social media platforms. In this sense, the non-attendance process of education has improved its relevance globally. Although, the COVID-19 pandemic caused an accelerator effect on the digital transformation of the educational institutions.
La formación en habilidades blandas un desafío para la educación abierta, a distancia y en línea

In this paper, the authors will talk about the development of technological platforms and tools that will support the creation and implementation of techno-pedagogical paradigms to tech the XXI Century generations. By proving how the innovative model of the open and distance learning universities (UNAD, for its Spanish acronym) is not run out and can be renewed, taking as an example the COVID-19 pandemic and analyzing the carriers that provide change to a new education, where the need of innovation in higher education in open and distance modalities is an urgent matter. Undoubtedly, learning is one of the human capacities that has most influenced their development and evolution. Thus, the e-education concept is presented as an effort to develop talents and human capacities using the Internet and new information and communication technologies (ICT). This will allow introducing a generalized remote mode, which will create a different culture adjusting the school curriculum to an online strategy, and not a rigid one, that involves technological improvements, so general and specialized knowledge are combined to the needs of scientific, technological, and social development. Teachers work with students differently and provide help through more knowledge and experience. Recent studies are showing that there are more open and online options for teacher professional development and teachers access the Internet to expand their development opportunities through social media platforms. In this sense, the non-attendance process of education has improved its relevance globally. Although, the COVID-19 pandemic caused an accelerator effect on the digital transformation of the educational institutions.
Heutagogy-Based Didactic Design of Indonesian Language Online Learning

This study aims to describe the didactic design of Indonesian online learning based on a heutagogical approach. The research design used is a qualitative research design using the Design-Based Research (DBR) method. The research subjects were students, lecturers, and learning experts. The data collection methods used were observation and interview and data analysis techniques with four stages of analysis. The results showed that the didactic design consisted of the stages of preparation and implementation of learning. The learning preparation stage is carried out by providing scaffolding consisting of seven stages, namely (1) essential study analysis, (2) precondition, (3) orientation and discussion, (4) topic determination, (5) assessment discussion, (6) technical discussion, learning, and (7) reflection. Meanwhile, the stages of learning implementation consisted of four stages, namely (1) exploration, (2) connection and reflection, (3) material comprehension, and (4) final reflection of learning. The design provides support for the concepts of learning agents, efficacy and ability, metacognition and reflection, nonlinear learning, and learning how to learn.
A Density-Based Spatial Clustering of Application with Noise Algorithm and its Empirical Research

With the rapid development and wide popularization of information technology, a large amount of data also follows. It is very important to use data mining tools to screen valuable information from complex data. As one of the widely used density clustering algorithms, density- based spatial clustering of application with noisy (DBSCAN) algorithm is an important data mining method. It can find the multi-dimensional relationship between data elements from the data set, complete the clustering of arbitrary shape and noisy data sets when the number of cluster classes is unknown, and support spatial database. Therefore, based on the example of judging the correctness of the relationship between the user's meter and the substation transformer, and supported by the clustering technology of DBSCAN, this paper finally verifies that the density-based clustering method has a good classification effect on the data with high complexity.
Analisis Sentimen Opini Masyarakat Terhadap Keefektifan Pembelajaran Daring Selama Pandemi COVID-19 Menggunakan Naïve Bayes Classifier

Since Indonesia was affected by the Covid-19 pandemic, one of the sectors affected was Education. The government makes an online learning system policy where the system is run with an online process. Not a few of them complained about the limitations of activities issued by the government. Twitter social media is often used to express opinions about concerns about programs issued by the government. The Twitter data crawling process was carried out using the hashtag "learning from home" to get as many as 1,000 datasets, followed by the process of removing duplicates which left 524 datasets and then carrying out the implementation stage of the Naïve Bayes Classifier Algorithm. The purpose of this study was to determine the number of positive and negative sentiments from the dataset labeling classification and to determine the accuracy results of using the Naïve Bayes Classifier method as well as the results of evaluation tests on positive and negative sentiment datasets. Based on the experiment, positive sentiment was obtained as many as 480 and negative sentiment as many as 44 out of 524 datasets. The accuracy results in the evaluation test process get results of 88.5% where negative sentiments get a precision value of 12%, recall 17%, and f1-score 14%, while positive sentiments get a precesion value of 95%, recall 93%, and f1 -score 94%.
CAPÍTULO 02: PANDEMIA, COVID 19 UM NOVO NORMAL NAS ESCOLA

This article aims to investigate what mathematical notions children from four to six years old manifest through play, with a problem: if hopscotch used in a playful way can become a teaching-learning tool?Because children build their own knowledge, through interactions with people, through play they build new meanings.To obtain this analysis, a bibliographic research was carried out.For theoretical support, it is mainly based on: