Reviewerly/exHarmony huggingface dataset:
Enhanced shared experiences in heterogeneous network with generative AI

COVID-19 has made the immersive experiences such as video conferencing, virtual reality/augmented reality, the most important modes of exchanging information. Despite much advancement in the network bandwidth and codec techniques, the current system still suffers from glitches, lags and poor video quality, especially under unreliable network conditions. In this paper, we propose the method of a video streaming pipeline to provide better video quality under erratic network conditions. We propose an environment where the participants can interact with each other through video conferencing by only sending the audio in the network. We propose a Multimodal Adaptive Normalization (MAN)-based architecture to synthesize a talking person video of arbitrary length using as input: an audio signal and a single image of a person. The architecture uses multimodal adaptive normalization, keypoint heatmap predictor, optical flow predictor and class activation map-based layers to learn movements of expressive facial components and hence generates a highly expressive talking-head video of the given person. We demonstrate the effectiveness of proposed streaming that dynamically controls the Quality of Experience (QoE) as per the requirements.
Multi-level access using searchable symmetric encryption with applicability for earth sciences

Accessing the files remotely offers a rentable solution for file storage. If the files are sensitive these should be encrypted before they will be outsourced for assuring confidentiality. These being said, the searching process becomes a real challenging problem. Most of the schemes consider only the scenarios where the users can search entirely over the encrypted files or data. In practice, the sensitive data are classified using an access control policy and different users should have different rights. The current paper will examine and propose a scheme of a multi-level access control policy (MlACP) based on searchable symmetric encryption (SSE) for the software infrastructures that ensure the interoperability of the software applications that access and work with documents and files. The proof of MlACP is The accessibility of the documents is defined by an access control policy designed to take into consideration the applicability in a multitude of IT infrastructures’, such as maritime, environmental protection and ecology, physics analysis and statistics software applications.
O CONTROLE DA MOBILIDADE EM VARIÁVEIS LINGUÍSTICAS

Mobility has an important role on the mechanism of linguistic change in Brazilian Portuguese (BORTONI-RICARDO, 1985, 2011; OUSHIRO, 2016). Due to mobility, speakers come onto contact with linguistic variables that are not from their origin community, leading them to incorporate these variables in their repertoire and to disseminate them in other communities. In this paper, we aim to discuss studies related to mobility and language to understand how, from displacement and contact with different norms, speakers can change their linguistic behavior. We focus on studies based on the sample Deslocamentos (2019), from the Falares Sergipanos database (FREITAG, 2013), which considers the speech of university students at the Federal University of Sergipe regarding their region of origin and their insertion in the academic community in terms of time, such as Corrêa (2019), Ribeiro (2019) and Siqueira (2020). The results show that speakers of the sample present different patterns depending of their origin community.
Serious Game Design For Playful Exploratory Urban Simulation

The year 2020 has stricken humanities with the ferocious COVID-19.During this period, regulation and restriction are active to mitigate the spread while simultaneously causing massive behavioral change globally.While the post-pandemic situation has created new habits, rules, and limitations to restrict traveling, it also offers opportunities to introduce the citizens an interactive technology solution to explore their urban space and neighborhood effortlessly and risk-free.This paper proposes the use of Minecraft, a sandbox game, and its gameplay to design an interactive serious game-based platform for collaborative urban exploration in a playful, immersive approach.The prototype within this paper applies the digital twin concept and its principles for the realistic re-creation of a virtual Dihua Street of Dadaocheng, an old town and a tourist hotspot in Taipei, Taiwan.In a serious-game environment that is both a playground and a working platform, users can cooperate with others, create dynamic user-generated content.As they explore while sharing their knowledge and experience in the virtual open space, users are also engaged in serious urban planning tasks.This paper's main objective is to present the preliminary data of top priority users' satisfaction with game elements or features to develop a serious game-based urban exploration platform while demonstrating the proof-of-concept of the urban digital twin.
Assisted learning: cooperative AI with autonomy

The rapid development in data collecting devices and computation platforms produces an emerging number of agents, each equipped with a unique data modality over a particular population of subjects. While an agent’s predictive performance may be enhanced by transmitting others’ data to it, this is often unrealistic due to intractable transmission costs and security concerns. In this paper, we propose a method named ASCII for an agent to improve its classification performance through assistance from other agents, without sharing proprietary data and model information. The method is naturally suitable for privacy-aware, transmission-economical, and decentralized learning scenarios. The method is also general as it allows the agents to use arbitrary classifiers such as logistic regression, ensemble tree, and neural network, and they may be heterogeneous among agents. We demonstrate the proposed method with extensive experimental studies.
PERAMALAN BEBAN AIR PELANGGAN MENGGUNAKAN FUZZY LOGIC MODEL SUGENO (Studi Kasus : PDAM Tirta Taman Kota Bontang)

Tirta Taman Bontang City, a water treatment company, has played an importand role inproducing raw water to prosper Bontang residents. Therefore, the performance of water use should bemonitored and controlled by its company. The forecasting of customer’s water load is in anytimepredicted to full fill one of the part of customer’s excellence and the needs to raw water. Forecastingsystem of customer’s water load and customer database which hasn’t been performed will be effected tothe un optimal Administration system performance toward the operation and reporting the customer’swater use Thus there should be designal an application to ease the prediction of forecasting of thecustomer’s water load by using Sugeno Methode. The aim of the application is to increase workeffectiveness. The variables used to predict are the amount of user and the amount of income. The Sugenofuzzy model is using linier equation (zero ordo of Sugeno’s model). The examination toward fuzzy SugenoMethod shows that the value which is provided through this method creates the analysis of truth based onthe actual production by 99.87 % in determining the forecasting of customer water use load thereforeSugeno Method can be used to fill the needs of predicting the water use of Tirta Taman water treatmentcompany’s customer in Bontang.Key Words : Water Load, Database, Fuzzy Logic, Sugeno Method, Forecasting
Early Detection of Post-Surgical Complications using Time-series Electronic Health Records

Models predicting health complications are increasingly attempting to reflect the temporally changing nature of patient status. However, both the practice of medicine and electronic health records (EHR) have yet to provide a true longitudinal representation of a patient's medical history as relevant data is often asynchronous and highly missing. To match the stringent requirements of many static time models, time-series data has to be truncated, and missing values in samples have to be filled heuristically. However, these data preprocessing procedures may unconsciously misinterpret real-world data, and eventually lead into failure in practice. In this work, we proposed an augmented gated recurrent unit (GRU), which formulate both missingness and timeline signals into GRU cells. Real patient data of post-operative bleeding (POB) after Colon and Rectal Surgery (CRS) was collected from Mayo Clinic EHR system to evaluate the effectiveness of proposed model. Conventional models were also trained with imputed dataset, in which event missingness or asynchronicity were approximated. The performance of proposed model surpassed current state-of-the-art methods in this POB detection task, indicating our model could be more eligible to handle EHR datasets.
Machine and Deep Learning Techniques in IoT and Cloud

Rapid advancements in communication technology have supported the invention of various internet-based devices. These devices communicate with one another and provide data from the physical world. Nowadays, the internet connected devices are used in various fields to make things easier. A great number of devices has been used, depending upon requirements. At the same time, the data produced by such devices is gradually increasing. To process the collected data, machine learning and deep learning techniques are applied. The Internet of Things (IoT) produces big datasets with multiple modalities but also a range of data with different quality standards. It is an important but also a challenging task to process all of the data within a certain time-frame. In this scenario, cloud computing gives us the optimal solution since the data generated is sent to distant cloud infrastructures. In addition to the cloud technology, machine learning (ML) and deep learning (DL) techniques are integrated with cloud computing to improve the effectiveness. In ML technique, the training data is given for learning to generate a set of rules from inferences on the data. Huge amounts of data that has been stored in the cloud gives input to DL techniques. DL architecture has been derived from the Artificial Neural Network (ANN) that uses multiple layers of nonlinear processing and transformation. The deep learning approach uses unknown elements in the input data to group objects, generate features and find new data patterns to build the model.
Network Game of Student Training Quality Assessment System Based on KOHONEN Neural Network

Objectives: In recent years, with the continuous improvement of the requirements of student training quality, the evaluation results of the existing evaluation system of student training quality are mostly unsatisfactory. Therefore, by integrating c-mean algorithm and Kohonen clustering algorithm, a non-sequential artificial neural network is obtained, a student training quality evaluation system based on KOHONEN neural network is designed by automatically adjusting the size of the objective function nodes of the non-sequential artificial neural network. Then the evaluation system is applied to the expected evaluation of the training quality of students in two science classes of Xinghua Middle School in Shenyang, Liaoning Province. The comparison between the test result data and the expected results of the model after the experiment confirms that the evaluation results obtained by using the evaluation system based on KOHONEN neural network have high accuracy.
Applying "assessment for learning" strategies in teaching mathematics education courses at pedagogical universities

Assessment for learning is the assessment that the first priority is to improve students' learning. It is the process of exploring and explaining the evidence for use by learners and teachers to determine where the learners are in their learning, where they need to go, and how best to get there. To adapt to the innovations of assessments in teaching school mathematics, the purpose of "assessment for learning" needs to be considered in educational courses in pedagogical universities, especially in teaching "mathematics education courses." This paper makes clear what "assessment for learning" is, proposes the process of designing and organizing assessment activities for teacher students, and applies "assessment for learning" strategies in teaching "mathematics education courses."
Influence of Interest in Learning, Parents Attention, and Learning Motivation Toward Achievement of Students in Class Xi Smk in Jakarta

This research was made to find out and analyze the factors that influence student achievement in the form of interest in learning, parents' attention, and interest in learning. The techniques used in sampling in this study were SPSS version 22.0 and Amos version 23.0, with a sample of 200 respondents. Tests conducted are test requirements tests, classic assumptions test and hypothesis testing. Researchers also conducted EFA, CFA and SEM tests. The results and discussion of the study indicate that there is an influence of the independent variables on the dependent variable. The results of this study are 1) Learning Interest has an influence of 2,060 on Student Learning Achievement. 2) Parents' attention have an influence of 1,998 on Student Learning Achievement. 3) Learning motivation has an effect of 2, 485 on Student Achievement. The conclusion of this study is the influence of Degrees of Interest, Parents' Attention and Learning Motivation affects Student Learning Achievement.
Scientific Reviews in Web of Science Core Collection Data Base

Scientific reviews are a publications type, which is very important for the world scientific community. This article considers reviews positions in the world publication flow (within the database «Wed of Science Core Collection» (WoS CC) array) for six natural sciences research areas (physics, chemistry, mathematics, geology, biology, computer science) during the period 2010–2019 for the leading countries of the world and Russia. The article considers additionally this type documents citation specialties depending on the research area. By means of the WoS CC database, bibliometric parameters of publication flows of scientific reviews for the six mentioned research natural sciences areas were determined: the number of records, it’s percentage in the total publication flow, the place of Russian reviews in the world flow, the average citation rate, the proportion of not cited records, the period of active citation. The dynamics of changes for these parameters over time (2010–2019) is considered. The article establishes the following features of scientific reviews, as a specific publication type: the percentage of reviews in both the world and Russian information flow is relatively small, it significantly depends on the research area, but over time it increases for all research areas; the trends of changes for the Russian reviews flow over time and in all research areas, follows world trends; Russian reviews occupy places, in terms of quantity, from 6–9 to a place in the fifth ten in the world array of WoS CC documents (depending on the year and research area), but they show a large spread in average citation terms. Sometimes, Russian reviews average citation is approaching and even exceeds the world average citation for some years and some research areas (and sometimes significantly); the non-cited reviews publications share is significantly lower than even for articles (the most cited type of publications); the reviews active citation period reaches 9–10 years and is significantly longer than (from some publications opinion) for scientific publications in general.
DEVELOPMENT OF A REGION-CENTRIC WEBSITE TO SUPPORT DATA TRACKING OF COVID-19 PATIENTS IN KELURAHAN GUNUNG

The deadly Coronavirus, SARS-COV-2, which is known as COVID-19 has caused global panic as it has affected multiple countries and millions of people around the world. Despite the existence of vaccines, every country in the world is trying their best to limit the spread of the virus. However, as the active cases starts multiplying each day, keeping track of the data of each person living in the world is becoming a much difficult task. The management of the subdistrict “Gunung” in Jakarta, Indonesia had mentioned that there is a lack of automated systems to maintain data. Therefore, with Information Systems and the technology we have nowadays, we are able to develop something that could aid us in keeping accurate and detailed information of the patients and unaffected citizens. Using PHP, HTML, JavaScript and MySQL, a website was developed to keep track of the citizen of Kelurahan Gunung, while also keeping track of the swab test results. The aim of proposed solution to the problem can be described as to present additional information support regarding the pandemic for population data and to present an information system for government and residents in Kel. Gunung regarding the assistance services available during the pandemic.&#x0D;
UPAYA MENINGKATKAN PEMAHAMAN SISWA PADA PEMBELAJARAN TEMATIK MENGGUNAKAN STRATEGI PEMBELAJARAN JIGSAW DAN EKSPERIMEN BAGI SISWA KELAS VI SDN 200405 HUTAIMBARU PADANGSIDIMPUAN

The purpose of this research was to determine whether the Jigsaw Learning Strategy and Experimentation could improve students' understanding in grade VI of SD Negeri 200405 Hutaimbaru Padangsidimpuan. The tools used in data collection in this study were tests and observations. This research is a classroom action research. Subjects in the study were grade VI students of SD Negeri 200405 Hutaimbaru Padangsidimpuan with a total of class VI students totaling 19 people. and the object of this research is the understanding of students through Jigsaw Learning Strategies and experiments in SD Negeri 200405 Hutaimbaru Padangsidimpuan. The results of this study indicate the level of success that is marked by the achievement of indicators of research success, namely students who have the ability to master the material and an excellent understanding of at least 75%. Meanwhile, based on the data obtained, it was shown that students who mastered the material were already above 70% ie 90.47%. According to the results obtained from the first cycle and second cycle. Difficulties faced by students can be overcome after applying the Jigsaw Learning Strategy and experimentation.
An Overview of Bladeless Drone

The aim of the study project to design the blades drone by using bladeless technology.The motivation in this overview to eliminate the problems created by propellers on conventional multirotor.The bladeless propulsion system serve as alternative to propellers of drone The concept of bladeless drone inspired by dyson bladeless fan.
Modeling Heterogeneous Hierarchies with Relation-specific Hyperbolic  Cones

Hierarchical relations are prevalent and indispensable for organizing human knowledge captured by a knowledge graph (KG). The key property of hierarchical relations is that they induce a partial ordering over the entities, which needs to be modeled in order to allow for hierarchical reasoning. However, current KG embeddings can model only a single global hierarchy (single global partial ordering) and fail to model multiple heterogeneous hierarchies that exist in a single KG. Here we present ConE (Cone Embedding), a KG embedding model that is able to simultaneously model multiple hierarchical as well as non-hierarchical relations in a knowledge graph. ConE embeds entities into hyperbolic cones and models relations as transformations between the cones. In particular, ConE uses cone containment constraints in different subspaces of the hyperbolic embedding space to capture multiple heterogeneous hierarchies. Experiments on standard knowledge graph benchmarks show that ConE obtains state-of-the-art performance on hierarchical reasoning tasks as well as knowledge graph completion task on hierarchical graphs. In particular, our approach yields new state-of-the-art Hits@1 of 45.3% on WN18RR and 16.1% on DDB14 (0.231 MRR). As for hierarchical reasoning task, our approach outperforms previous best results by an average of 20% across the three datasets.
Pelatihan Merancang Sistem Informasi Akuntansi Accurate Pada PT. Mahatani Kota Bogor

MSMEs (Micro, Small and Medium Enterprises) in Indonesia are one of the most dominant business sectors run by business actors. Processing of data related to financial statements is carried out using an excel data manual system in Microsoft office, this causes obstacles in calculating financial transactions, both in the form of cash turnover on sales and at the same time merchandise inventory turnover, also experiencing delays in making financial reports. Management of financial data and inventory in the preparation of financial statements, requires accuracy and accuracy of data data in every decision making. In accordance with current technological developments, it is hoped that MSMEs that already have a turnover of the upper middle class will already use a computer accounting information system. &#x0D; To assist in preparing financial reports using an accurate accounting information system, through this training, it is hoped that data results are updated, accurate, and quickly provide information to management. Training on Designing Accurate Accounting Information Systems at PT. Mahatani in Bogor City, can provide an overview of how it works and design concepts that are easily understood by system users/users to help make it easier to prepare financial reports. The required transactions have been provided for accurate activities, starting from creating a new account with the name of the company, along with the chart of account number, updating the chart of account according to the needs of the account number designed by management to facilitate account classification. The accurate accounting information system can be done with multi users, so that all departments can input transaction data together with the aim of providing financial information for management.&#x0D; The ultimate goal of accounting records is to produce a good and accurate report that is expected to provide an actual picture of the company's financial activities. Accurate, which is an integrated program, provides financial reporting facilities that make it very easy for users. Especially the Accurate database system which allows every financial activity that occurs and is recorded in the system to be extracted when it is summarized into a report&#x0D; &#x0D; Keywords: Designing Accurate Accounting Information System at PT. Mahatani.
Pengaruh Self Regulated Learnıng Terhadap Kemampuan Lıterası Saıns Sıswa Sekolah Dasar

Literacy Sains is an ability that must be possessed to become the expected future generation. Self-regulated learning is the ability to self-regulate in learning mathematics that plays a role in improving the quality and quantity of self in literacy sains. This study aims to examine the relationship between students' self-regulated learning and literacy sains. This research is a quantitative correlation study. The research was conducted at elementary Student, SDN Kepuh Kiriman Sidoarjo. To get result data The research used an instrument in the form of a literacy sains ability test and self-regulated learning scale questionnaire. Data analysis using correlation analysis with product moment correlation. The results showed that there was no relationship between students' self-regulated learning with students' literacy sains ability. This research can be used as a consideration for Elementary Student in the field of mathematics that can be used as a consideration in improving literacy sains ability.