Reviewerly/exHarmony huggingface dataset:
The Blockchain Framework for the Sharing of Data between Training Providers Based on the Internet of Things

Blockchain technology is recognised as being a key focus when it comes to modern-day studies and interest on a global scale, with the new block of transactions responsible for the continued growth and expansion of a distributed ledger that details transactional data, complete with immutable and verifiable structures. A greater degree of transparency, privacy, security, and traceability is provided by blockchain when a comparison is drawn with more conventional strategies. As a result of its secure and more progressive elements, blockchain is applied in a number of different arenas, including digital transactions, education, the healthcare industry, the Internet of Things (IoT), trade finance, and the training sector. Importantly, a notable effect on all applied fields has been witnessed as a result of blockchain technology, with data and transactional reliability, as well as privacy, recognised as the most important aspects when it comes to data-sharing in the training arena specifically. Very few models and frameworks are aligned with the guidelines put forth in this sector; as such, this report seeks to consider the pressing need to determine a model and framework to facilitate the sharing of data between training providers in line with the IoT. This study, therefore, centres on the creation of a blockchain model, with the creation of a sole recognition system for professionals seen to be advantageous for all such providers, specifically in the mind of providing a greater degree of clarity and simplification to the system in line with the IoT. The suggested model is focused on a number of different elements that have been identified as a result of studied theories, with consideration of the three different standpoints and professional assessments of 16 unique items.
Game of Life on Graphs

We consider a specific graph dynamical system inspired by the famous Conway's Game of Life in this work. We study the properties of the dynamical system on different graphs and introduce a new efficient heuristic for graph isomorphism testing. We use the evolution of our system to extract features from a graph in a deterministic way and observe that the extracted features are unique and the distance induced by that features satisfy triangle inequality for all connected graphs with up to ten vertices.
PROTOTYPE OF VACUUM FRYING OYSTER MUSHROOM CHIPS

Oyster mushroom is plant that is quite easy to cultivate because it only requires growing media for oyster mushrooms, oyster mushroom seeds and a humid place for cultivation. Oyster mushroom is a type of plant that is fibrous and contains a lot of water causing the shelf life of oyster mushrooms after harvest is very short. To increase the economic value of oyster mushrooms, it is necessary to process oyster mushrooms into something so that processed oyster mushrooms have a long shelf life, namely by processing oyster mushrooms into chips, but the manufacture of oyster mushroom chips still uses conventional or manual methods so that the quality of the resulting chips is still not good. By using innovative technology through a prototype design tool with the vacuum frying method, it produces chips that are of higher quality than conventional frying methods which are seen from the water content contained in oyster mushroom chips, which is less than 1% with an evaporated water content of 80%. The prototype of this vacuum frying fryer has an overall volume of 260,000 cm3 with an overall length of 100 cm, a width of 40 cm and a height of 65 cm and uses an electric motor of 2461.76 watts or 3.3012 HP
Hubungan Bimbingan Belajar dengan Hasil Belajar Matematika Siswa Sekolah Dasar

This study aims to determine whether there is a relationship between tutoring and student learning outcomes in mathematics in grade IV Elementary School, how much contribution is given and whether it has significance or not. This research was conducted in July-August at SDN Sumobito III. The research method used is correlational research with a quantitative approach. The sampling technique is purposive sampling. The research instrument used was a questionnaire and documentation of students' math scores. While the correlation technique used is the product moment. The results found in this study that there is a significant relationship between tutoring and student learning outcomes in mathematics. The results showed that the rcount or Pearson correlation was 0.923 and was included in the very strong category. While the value of the coefficient of determination in this study shows the figure of 85.2%. Thus, there is a very strong and significant relationship between tutoring and mathematics learning outcomes at SDN Sumobito III.Keywords: Tutoring, Mathematics Learning Outcomesutcomes
Pengaruh Penggunaan Metode Jarimatika Terhadap Kemampuan Berhitung Perkalian Anak Usia Sekolah Dasar

The purpose of this study was to find out and describe how the effect of the application of the Jarimatika method on the multiplication ability of high-grade students. The research method used is descriptive quantitative with data collection techniques using data recording with permanent products. Data retrieval using data recording with permanent products, observation and documentation with the research sample consisting of one student aged 4th grade. Data analysis used visual analysis method which consisted of visual analysis of graphs, analysis under conditions and analysis between conditions. The results of this study indicate that the multiplication arithmetic ability of students during the four phases is affected by the use of the Jarimatika method. This can be seen from the results obtained in the Baseline 1 phase, students got the highest score = 40, the Intervention phase 1 = 80, the Baseline 2 phase = 80, and the Intervention phase 2 = 100. The ability of students to count multiplications in the baseline phase is sufficient. good, in the intervention phase very good.
ONTOLOGY-BASED DATA WAREHOUSE VISUALIZATION USING PROTÉGÉ FOR CORONA VIRUS SPREAD INCIDENCES

Corona Virus (Covid-19) is an infectious disease caused by a newly discovered coronavirus. At this time, there are no specific vaccines or treatments for COVID-19. death rates due Covid-19 in Indonesia reach 8,9%. The presence of differences between data released by the Covid-19 complaint website of West Java Province and data released by Subang Government indicates that’s still difficult to obtain accurate information. We need to build data warehouse and create ontology of Covid-19 incidences data to figure out the important information in Covid-19. we are using Protégé to build and visualize ontology of Covid-19 data.&#x0D; &#x0D; Keywords : ontology, Protégé, Covid-19
Evaluation of Online Communities for Technology Foresight: Data-Driven Approach Based on Expertise and Diversity

This study proposes a framework for selecting and validating data sources for public-based technology foresight. In other words, it finds out which of the many online communities have valuable data sources. Specifically, we evaluate the usefulness of text data from online communities for technology foresight in terms of expertise and diversity. To this end, not only is a bibliographic analysis using metadata conducted, but also, topic modeling techniques for a semantic analysis of texts are utilized. As a case study, we selected 20 candidate communities where discussions and predictions related to technology are made and applied newly proposed metrics. As a contribution of this study, it is expected that it will provide a basis for public participation in technology foresight, not only leaving it to a few experts.
On the Reusability of Machine Learning Models in Edge Computing: A Statistical Learning Approach

The adoption of Edge Computing continues to grow with edge nodes recording increasingly more data, which inevitably requires that they should be processed through Machine Learning (ML) models to speed up the production of knowledge. However, training these models requires an increased amount of resources, which are limited, thus, the reuse of ML models becomes of paramount importance. Given that we do not have a pool of models to choose from, is it possible to determine which nodes in the network require distinct models and which of them could be reused? In this paper, we propose a solution to this question, an online model reuse framework which is evaluated for its precision and speedup. The framework considers all possible combinations of pairs in the network to determine which are good reusability pairs, by adopting statistical learning methods. Then for each pair, the node model is chosen that has the highest data space overlap. Our comprehensive experimental analysis in the context of both regression and classification shows the feasibility our solution in model reusability in Edge Computing environments.
RANCANG BANGUN SISTEM INFORMASI PENGAWASAN PEMASANGAN JARINGAN LISTRIK PADA PT.PLN (Persero) AREA PALEMBANG

Installation of electrical network at PT. PLN (Persero) is done by a vendor that works with the agency. Before the installation of the electricity network the vendors must fill the data first to know the responsibility of each job in the installation of electrical networks. The problem in this research is that there is no specific system used in the collection of vendors. This research aims to design and build an application that can help PT. PLN (Persero) in supervising the electrical network installation conducted by the Vendor. The research method used is the Development research method, which is a research activity aimed at and develop or complete knowledge that is already know. The development system used is web Engineering. The results of the research is the information system of installation control electrical network that can help PT. PLN (Persero) in data and supervise the work that is done by the vendor so that the performance produced better and increase customer satisfaction.&#x0D; Keywords: Sistem Informasi, Pengawasan, Web Engineering, Berbasis Web
Persuasive Dialogue Corpus: Graph-Based Approach Combining Persuader and Persuadee Perspectives

Persuasion is omnipresent in our daily communication. As a mechanism for changing or forming one’s opinion or behavior, persuasive dialogues and their strategies have gained interest for developing intelligent conversational systems. Given the complexity of this task, persuasion systems, especially dealing in conversations that require ‘no action’ by the user but rather a change in opinion or belief, require specialized annotated corpora and the understanding of logical structure, natural language, and persuasive strategies. The sparsity of available annotated data and a wide range of proposed models make it challenging for developing strategic chatbots specific to user needs. To address these issues, this study introduces a novel framework combining a replicable data collection tool and a topic-independent annotation schema for designing an argument-graph corpus and incorporating both persuader and persuadee perspectives, essential for building smart conversational agents.
Impact of Digital Marketing on Customer Buying Behavior (Residential Real Estate)

Abstract: The study is to examine the impact of digital marketing on the customer buying behavior and to find out the customers are sensible of digital marketing and the digital channel’s impact on their purchase decision. The study is carried out through checks from 148 respondents and Responses from the client. The rating scale was used to get the respondents' final results from the questionnaire. The questionnaires were distributed to 180+ and got 148 responses from respondents. The Rate scale will be used to measure a person's perception and attitude or opinion. The results are interpreted to show the impact of digital marketing on customer buying behavior. The findings revealed that customers are apprehensive of digital marketing and prefer to book site visits through digital channels in their buying actions. The study is performed in a particular geographical area, particularly residential real estate customers or leads and this may be considered as a limitation to judge the purchase opinion of varied regions. As the world moves towards a digital period, the various digital channels play a vital place in the increase of sales of any company’s products or generating leads for the Business. So, the present study attempted to reveal the impact of digital marketing on customer buying behavior- Residential Real Estate. This result helps us to change the Digital Marketing Strategy plan Developed for the Residential Real Estate (Vue Residences).
SM3D portal’s founder as a science-wide top scientist

In the 2022 updated database, one of the founders of SM3D Portal – Dr. Quan-Hoang Vuong – appears in the list of career-long impact (ranked at 240,933th) and single-year impact (ranked at 22,704th). Last year, he also appeared in the 2021 lists of top-career-long-impact scientists (ranked at 294,101th) and top-single-year-impact scientists (ranked at 46,350th). If we only consider the career-long and single-year impacts within the fields of Social Sciences and Humanities, he is ranked at 12,703th and 2,989th, respectively.
Application of Doppler Radar in Short-Term Near-Term Weather Forecast

Application of Doppler radar in short-term near-term weather forecast is the focus of this paper. Short-term now weather forecast can effectively improve the ability of meteorological disaster forecast and early warning. Conditional provinces or counties and cities can realize real-time update of the meteorological information and real-time insertion of sudden and severe weather warning information through public media. The application of modern meteorological methods provides the possibility for the production and timely broadcasting of the short-term and the near-term weather forecasting. This paper gives the combination of the Doppler radar to enhance the general model.
Job Autonomy and Employee Performance in Kampala Capital City Authority in Uganda

The empirical study investigated the association between job autonomy and employee performance in Kampala Capital City Authority (KCCA) in Uganda. The scientific research study utilized a survey descriptive research design with mixed approaches in nature (qualitative and quantitative paradigms). A sample of 235 participants out of 3051 study population was chosen employing a table advanced by Morgan &amp; Krejcie (1970). Data was gathered utilizing self-administered questionnaires and interview guides; and examined applying Descriptive dimensions and Pearson Linear Correlation Coefficient (PLCC) for quantitative indicators and content examination was used for analyzing qualitative information .The inquiry study outcomes yielded a significant correlation between job autonomy and employee performance in Kampala Capital City Authority (KCCA) in Uganda. It was thus concluded that giving administrators greater autonomy at work place is itself motivation to the employees and the Heads of Departments of an organization in KCCA in Uganda and in the whole world at large. The systematic study recommended that the political leadership or management of KCCA should embrace the process of management by objectives whereby the major focus must be oriented towards putting in place activities that shoot into achievement of the objectives of the organization of KCCA. Such a scenario can engender an environment of development in KCCA in Uganda.
PCSERVE – ND-POINTCLOUDS RETRIEVAL OVER THE WEB

Abstract. We investigate how PCServe, a web service for disseminating massive point clouds, performs for read-only access (i.e. a visualization application). PCServe is backed by a database model based on Space Filling Curves. By adding a virtual hierarchy of blocks to the database, we can support different visualization applications for retrieval of point cloud data over the web without having to store the data multiple times. This makes expressive access to point clouds over the web possible. We investigate the amount of processing that is needed to create the database model and how well PCServe handles requests from the visualization application. Some suggestions are provided how the current approach can be improved.
A comparative analysis of metadata structures and attributes of Samsung smartphone voice recording files for forensic use*

Due to the popularization of smartphones, most of the recorded speech files submitted as evidence of recent crimes are produced by smartphones, and the integrity (forgery) of the submitted speech files based on smartphones is emerging as a major issue in the investigation and trial process.Samsung smartphones with the highest domestic market share are distributed with built-in speech recording applications that can record calls and voice, and can edit recorded speech.Unlike editing through third-party speech (audio) applications, editing by their own builtin speech applications has a high similarity to the original file in metadata structures and attributes, so more precise analysis techniques need to prove integrity.In this study, we constructed a speech file metadata database for speech files (original files) recorded by 34 Samsung smartphones and edited speech files edited by their built-in speech recording applications.We analyzed by comparing the metadata structures and attributes of the original files to their edited ones.As a result, we found significant metadata differences between the original speech files and the edited ones.
Development of artificial neural networks for breast histopathological image analysis

In this chapter, we present an introduction to breast histopathological image analysis (BHIA) algorithms based on artificial neural networks. In the first part, we divide the BHIA architectures into two groups used for intensive and deep research, namely classical and deep neural networks. Second, we describe related research which is associated with BHIA architectures. Finally, we compare the prevalent models to find the more effective frameworks.
DEVELOPMENT OF AUGMENTED REALITY BASED GEOMETRY LEARNING MEDIA ORIENTED TO BALINESE ARCHITECTURE TO IMPROVE ABILITY STUDENT MATHEMATICS SPATIAL

Media Augmented Reality is very relevant for student learning based on information and communication technology. However, learning using AR has not been widely used, especially when learning mathematics. This study aims to determine the quality of augmented reality media oriented towards Balinese architecture and the implementation characteristics when using the media in learning. AR media packaged in an android mobile application is included with a marker to scan 3D objects to improve students' mathematical spatial abilities in geometry learning. This research is design research using the Plomp model. The research subjects were students of class X SMA. So, the data collection methods of this research are observation, interviews, tests, and questionnaires. The validity test results show that the media is very valid, scoring 3.68. The practicality test showed that the development included AR media in the efficient category with a score of 3.5. Finally, the effectiveness test indicates that the AR media developed effectively increases spatial ability with an average score of 85, reaching the completeness criteria. This result shows that AR media is oriented to Balinese architecture with valid, practical, and effective quality. One of the characteristics of the media developed is that AR media can display 3D objects so that students are given space to explore, imagine and conclude the material obtained. Then, the characteristics of using the media, namely AR media, can be used as an alternative to spatial geometry media in overcoming the limitations of presenting material in schools.
VIZPLAN: A VISUAL ANALYTICS PLATFORM FOR THE ASSESSMENT OF MULTIDIMENSIONAL INDICATORS OVER TIME

Abstract. In this paper, we introduce VizPlan, a new platform to support the assessment of multidimensional indicators over time. VizPlan includes a visualisation scheme based on a radial visual structure that allows the direct comparison of indicator values over time, a search tool to support the identification of entities whose indicators are similar to each other, and a clustering tool to group entities according to their indicator scores. VizPlan was designed and implemented to be flexible; it can be easily tailored to the visualization and analysis of any multidimensional temporal data. In this paper, the use of VizPlan is illustrated in the context of three case studies concerning the analysis of sustainability indicators to support urban planning: key performance indicators related to the sustainable development goals, walkability analysis, and bus service availability assessment. All case studies refer to real data related to Norwegian cities, especially Ålesund. VizPlan is available as an open source software at https://github.com/Rylern/VizPlan – As of May 2022.
Academic research for implementation of python language programs for information measurement and coding for data compression

This article presents the expanded abstract containing information about the academic research for implementation of programs in Python language for information measures and coding for data compression. The research was conducted, at the Amazonas State University, by the student of Electronic Engineering course Williams Cavalcante Oliveira, under the guidance of Professor Paulo Cesar de Souza Cavalcante, and had its abstract presented in the 1st Amazon Stem Academy Conference 2021. The content of the presented abstract, transcribed in this paper, exposes brief theoretical review of information measurement calculation methods and methods for statistical and dictionary-based data compression encoding. Besides other information concerning the research, it also presents, as its final product, the Python language modules developed for the execution of the algorithms of the methods studied, for performing the calculations and encodings that were the object of the research.
Telehealth as a tool to strengthen and expand the overweight and obesity care line

The objective of this study is to train the multiprofessional team of primary and secondary care about the management of overweight and obese patients. In addition, to share the knowledge of the multiprofessional team of a bariatric and metabolic surgery program about the management of pre and postoperative patients in all related areas (nutrition, psychology, medicine, social work, nursing, physical education, and physical therapy) within the network of care for obese individuals.
Risk prioritization methodology for decision makers

Changes in regulatory standards, especially NR-01 with the obligation to prepare a Risk Management Program (RMP) has increased pressure on organizations to manage occupational risks. Companies need to establish mechanisms to protect the health and safety of their employees to meet legal obligations and reduce the damage caused to their employees and society. Organizations need to recognize the risks that make up their activities and establish measures to eliminate or reduce the potential damage that these risks can cause , and the proposed methodology seeks to solve this problem.