Reviewerly/exHarmony huggingface dataset:
Expert System Diagnosa Gangguan Autisme Secara Dini Pada Anak dengan Metode Forward Chaining

Autism is a developmental and behavioral disorder of children where social relationships are disrupted, namely children with autism cannot interact with other people, including their parents. Autistic children experience disorders such as communication disorders, social relationship disorders, and behavioral disorders, resulting in a child. Parents often do not realize the differences and abnormalities that appear in their children until they are three years old. They just realized that their child is different from other children. There are several basics of treating autism and there are some teachers who can help cure autism in children. The teacher treats autistic children with an approach that is adapted to the problem. Types of autism basically this child is divided into four categories, including social interaction disorders, behavioral generalized disorders, communication disorders, and self-stimulation disorders. This research designs and builds an expert system (expert system) for diagnosing Autism disorders in early childhood based on the web Method of Forward Chaining. This Forward Chaining is very good to use if the work starts with recording the initial information and wants to reach the completion or final goal. This expert system is considered capable of providing information and solutions for parents, about the types of autism disorders in early childhood, based on the symptoms entered and can provide solutions
A Study on the Cognitive Characteristics of Basketball Officials’ Fake Fouling

This study explores the identification of basketball officials on fake being fouled after a player falls.The experimental procedure adopted the paradigm of visual obscuration.After the officials watched the video for 5 seconds, the officials answered three questions in order of whether the player deliberately falls, how the player should be penalized for this action, and whether it would benefit the team.Records The officials reacts to the button.The research results show that when the officials judges whether a player deliberately falls, the role of the falling player has a significant interaction with the three options, and the main effect of the falling player's role is not significant; There is no significant interaction between the role of the falling player and the penalty result; The result of the official's penalty is significantly related to the official's analysis of the player's interests.The final conclusion is that the officials are biased in the information processing stage of the penalty, and the officials are more likely to deceive the foul when the defender falls.
Reality, information, and consciousness The universe as a cosmic quantum computer

uestions concerning reality have plagued human consciousness since the dawn of our existence.Philosophical and scientific researchers toy with questions such as 'what is real?' in a variety of ontological and epistemological manners, using a broad array of methods.Such questions, of course, only give rise to subsequent questions pertaining to the reality of consciousness itself.Is consciousness a product of the human body (ie, the brain), or is it perhaps a deeper, even spiritual, matter?
Flora Lexicon of Kaghati in Muna Speech Community

Diversity of the flora lexicon in the environment of Kaghati is part of the ethnic richness in the form of local knowledge that must be explored for the sake of environmental sustainability. This article intends to: (1) discover and portray the flora lexicon of kaghati; and (2) examine the dynamic of inter-generational comprehension. The researcher used qualitative method and upheld by quantitative method. The information required were gotten by perception, meeting, and poll strategies. At that point, the survey is directed upon 150 respondents. The extent of the respondentsâ€™ ages was from 15 to 65 years. In light of information examination, there were two discoveries discovered: (1) the flora lexicon of kaghati comprises of fifteen dictionaries as ostensible and biotic class. (2) There is an alternate degree of between generational comprehension on flora lexicon of kaghati. The old age (46-65 years) 84% (best), the middle generation (25-45 years) 74% (best), and the young generation (15-24 years) 55% (better).
Encouraging students' learning outcomes using the information search method

This study aims to determine the effect of the Information Search learning method on the learning outcomes of class VIII students in science subjects at SMP Negeri 9 Sorong City. The method used in this study was a quasi-experimental design with a non-equivalent control group design. Samples were Class VIII A1 (15 students) as the experimental group and class VIII D2 (15 students) as the control group. Before treatment, both classes were given a pre-test to see if there was a difference in learning outcomes between the experimental and control group. Both classes were given a post-test to see the effect of learning on learning outcomes. Data analysis in this study used statistical analysis consisting of three stages, namely normality test, homogeneity test, and hypothesis testing using a T-test. The calculation of gain from learning outcomes is also carried out. The results of this study indicate the effect of information search methods on improving student learning outcomes (sig. = 0.001 &lt; 0.05). The experimental class gain is 37.33, and the control class is 17.33. This research concludes that the information research method can encourage student learning outcomes.
Formation of professional competencies students and the modern labor market

The purpose of the study is to analyze the formation of students' professional competence, which allows them to carry out effective activities in their chosen specialty after graduating from a university in accordance with the requirements of the labor market. The conditions for effective training based on adaptation to market requirements are investigated, an example of interaction with an employer is shown. The scientific novelty of the work lies in the concretization of the concept of "professional competence of students", the development of a model for the formation of professional skills of students in an educational institution on the basis of a survey.
Challenges of Knowledge Component Modeling: A Software Engineering Case Study

To improve instruction, educators require greater visibility into the learning gains of individual students and the ability to adapt to resolve any learning gaps. A prerequisite to achieving such instruction is decomposing knowledge into small components that function as gradual steps for the learner’s journey. However, decomposing a knowledge domain is not trivial, as instructors must overcome many practical challenges along the way. We report on our experience of knowledge component modeling for the clean code analysis and refactoring domain. We describe our method and list four challenges encountered during modeling and our solution for them. The resulting knowledge component inventory is a secondary contribution of the paper. These results can assist educators in planning and executing knowledge component modeling to refine their instruction and produce more significant learning gains in their students.
A Novel Method Considering Guesses and Slips for Item Ordering: Noise-Filter Ordering Theory and Item Relational Structure Theory

art's ordering theory algorithm and Takeya's item relational structure algorithm are the two classical ordering algorithms, but both of them have a common problem, that is, the item ordering results depend on the setting of threshold. The reason for this problem is that the ordering index fluctuates greatly due to guessing and slipping noise. This paper presents an improved algorithm, which can effectively filter out the noise of guessing and slipping. It is more effective than the two traditional methods. This paper also develops a computer program and carries out simulation experiments to prove the advantages of this method.
Absolute three-dimensional shape measurement combining digital image correlation and phase-shifting methods

Phase-shifting methods have been extensively employed in high-resolution and high-speed absolute three-dimensional (3D) measurements. In the process of 3D reconstruction, one of the important tasks is to recover the absolute phase pixel by pixel. In this paper, we propose an absolute 3D shape measurement method that combines the digital image correlation (DIC) algorithm with the phase-shifting method on a one-camera and one-projector structure light system. Comparing to the conventional multi-wavelength unwrapping method, the proposed method only needs one random binary pattern for phase unwrapping. Experimental results demonstrated the proposed method can successfully measure complex scenes with high quality.
Deep learning on time series laboratory test results from electronic health records for early detection of pancreatic cancer.

e16268 Background: Pancreatic cancer (PC) has a uniquely poor survival rate due to the absence of proven and effective methods for early detection. We thus aimed to leverage recent advances in deep learning towards the task of inferring early risk of PC from longitudinal laboratory test data contained within Electronic Health Records (EHR) data. Methods: In this study, we develop a novel deep learning framework for incorporating longitudinal clinical data from EHR to infer risk for PC. This framework includes a novel training protocol, which enforces an emphasis on early detection by applying an independent Poisson-random mask on proximal-time measurements for each variable. Data fusion for irregular multivariate time-series features is enabled by a “grouped” neural network (GrpNN) architecture, which uses representation learning to generate a dimensionally reduced vector for each measurement set before generating a final prediction. These models were evaluated using EHR data from Tripartite Request Assessment Committee (TRAC). Results: Our framework demonstrated better performance on early detection (AUROC 0.671, CI 95% 0.667–0.675, p &lt; 0.001) at 12 months prior to diagnosis compared to a logistic regression and a feedforward neural network baseline (black-box model). We demonstrate that our masking strategy results greater improvements at distal times prior to diagnosis, and that our GrpNN model improves generalizability by reducing overfitting relative to the feedforward baseline (Table). The results were consistent across reported race. Conclusions: Our study presents new approaches for integrating multimodal longitudinal clinical data with bias reduction strategies which results in improved early detection of PC. This study demonstrates for the first time the utility of multivariate time series laboratory test results for early detection of PC. Our proposed algorithm is potentially generalizable to improve risk predictions for other types of cancer and other diseases where early detection can improve survival. We split data into train set (80%) and hold-out set (20%) and presented mean AUROC and AUPRC with 95% confidence intervals.[Table: see text]
Procedurally generated simulated datasets for aerial explosive hazard detection

Recent advancements in signal processing and computer vision are largely due to machine learning (ML). While exciting, the reality is that most modern ML approaches are based on supervised learning and require large and diverse collections of well annotated data. Furthermore, top performing ML models are black (opaque) versus glass (transparent) boxes. It is not clear what they are doing and when/where they work. Herein, we use modern video game engine technology to better understand and help create improved ML solutions by confronting the real world annotated data bottleneck problem. Specifically, we discuss a procedural environment and dataset collection process in the Unreal Engine (UE) for explosive hazard detection (EHD). This process is driven by the underlying variables impacting EHD: object, environment, and platform/sensor (low altitude drone herein). Furthermore, we outline a process for generating data at different levels of visual abstraction to train ML algorithms, encourage improved features, and evaluate ML model generalizability. Encouraging preliminary results and insights are provided relative to simulated aerial EHD experiments.
Analisis Hasil Belajar Matermatika Dalam Pembelajaran Daring Menggunakan Aplikasi Whatsapp Group

This study aims to describe the results of learning mathematics during the online learning process and the obstacles in using the whatsapp group application in fourth grade elementary school students.This research is a qualitative research with the type of narrative research which was carried out in SD 2 Mlati Lor, Kota District, Kudus Regency. The subjects in this study were 6 students, 3 boys and 3 girls. Data collection techniques used observation, interviews and documentation. Data analysis used is data reduction, data presentation, and drawing conclusions. The results of the research obtained are that online learning using the Whatsapp Group application at SD 2 Mlati Lor runs well according to the applicable educational standards.The results showed that all educational units were on average in online learning using the Whatsapp Group Application. The results of learning mathematics at SD 2 Mlati Lor during online learning are good, as indicated by the complete score of all students. There are obstacles in the use of Whatsapp Group as a learning medium at SD 2 Mlati Lor, namely signal interference, lack of motivation, inadequate facilities, difficulty in understanding the material, full mobile memory and too many tasks.
Wireless and networking technologies for social distancing - indoor and outdoor

This chapter reviews the suitability of the most relevant wireless and networking communications technologies (e.g. GNSS, cellular, WiFi, Bluetooth and RFID) for the implementation of social distancing applications such as interpersonal distancing, real-time area monitoring, or geo-fencing.
Privacy in the Cloud Using ECC and DH

Individuals nowadays frequently save their data on distributed storage. When it comes to storing data on the cloud, security is a major concern. Cryptography processes are particularly useful for enforcing information security. To improve the security of information stored on distributed storage, a mixed cryptography architecture is presented. The proposed method employs Elliptic Curve Cryptography and Diffie Hellman (ECC and DH) and combines two types of computation to provide improved security on data before it is stored in the cloud. The suggested computation is implemented in JAVA and tested on a plain text sample. The project will be extremely beneficial for storing information on the cloud. It is verified that the proposed computing method is correct.
The Meanings of Publication in Open Access Journal: Experience of State Islamic University's Lecturers

The Indonesian Ministry of Research, Technology, and Higher Education always encourages lecturers to publish their scientific works in open access publications. This study explores the meaning of open access publications from the experiences of UIN lecturers. This study uses a qualitative method with a phenomenological approach to identify the interpretation and meaning of lecturers on open access journal publications. This study found that lecturers know about publishing in open access journals and their advantages. They choose reputable journals in their scientific field as their first reference because the journals that fall into this category have a high level of readability and citation. However, the informants stated that they were also pragmatic; they will reconsider the decision to publish in a reputable and open access journal if the publication fee is deemed too expensive. This study uses Hall's meanings concept, whose application is not only to explore the views of lecturers on open access publications but also to explore the actions they take so that their writings can be included in open access publications. Here, the researcher finds the emerging theme that is the importance of collaboration. It is as a way to overcome barriers to open access publishing and also as the key to the productivity of writing articles in academic journals. This study highlights several important themes related to collaboration. The integration of Islamic knowledge with scientific disciplines is an interesting issue when discussing the benefits of cooperation. The results of this study can provide insight into the meaning of open access journals published by lecturers and how they overcome the barriers in this matter. The researcher suggests using a quantitative approach based on our data for future research.
ANALISIS SENTIMEN TANGGAPAN MASYARAKAT TERHADAPBANTUAN SOSIALPEMERINTAH DI MASA PANDEMI COVID-19 PADA PLATFORM TWITTER

The study was conducted to analyze public opinion about the government's efforts in overcoming the Covid- 19 pandemic by providing social assistance (bansos) in the form of goods, money and or services. Through social media Twitter with the topic of social assistance, the classification of positive, neutral or negative sentiments will be carried out. The results of this classification will reveal what social assistance topics are often discussed on Twitter. This classification process uses the Naive Bayes method and uses the RapidMiner application. The data used in this analysis process is 747 Twitter comment text data with a data collection time span from October to November. The classification process is supported by the Term Frequency-Inverse Document Frequency feature as the word weighting stage. This classification produces 2,382 word attributes or word vectors from 747 data, with 370 sample data for model testing which produces an accuration value of 24.32%, a true neutral recall value of 100%, and a true neutral precision value of 24.32%. The word that most often appears from the results of this sentiment analysis is the word "bantuan".
Online deep learning for behavior prediction

We implement online deep learning for target behavior prediction. Our online deep learning algorithm provides an autonomous agent the ability to train in real-time while also shaping the frequency of training based on its current performance level. The benefits of our algorithm are twofold: (1) to enable an autonomous agent to train in real-time and continue to learn to accurately predict target behavior even while its target changes the strategy guiding its behavior, and (2) to achieve more efficient usage of its computational resources by managing its training frequency. This trained predictive capability is leveraged in autonomous decision-making to influence a target’s behavior by selecting those actions that produce a predicted response from the target that supports the end goal of the autonomous agent. In our scenario, the goal of the autonomous agent is to influence its target to circle the perimeter of the environment. We test our online deep learning algorithm in environments of varying sizes to demonstrate that the time it takes for an autonomous agent to achieve the target level of accuracy is directly proportional to the size of the environment.
How leadership style creates an impact on job satisfaction level of employees in an organization

In this study, we tried to show how a good leader positively impacts employees, which leads to job satisfaction while working in an organization/business. Under this study, we are trying to examine the meaning and importance of Leadership towards job satisfaction of employees, how good leadership help in helping their employees, and they feel satisfied with their current working job. This study is based on two leadership styles: Responsible Leadership Style and Ethical leadership Style. A reliable leadership style shows a relationship between the leaders and their stakeholders; under this style, a leader must analyze stakeholders' needs and wants. Ethical leadership style is when a leader has to do their moral duties and work with honesty; under this style, the leader tries to make fair decisions in the organization and make a positive environment for employees. Based on this study, we are wanted to highlight how a leader is essential for every organization. If there is a good leader in the organization, employees can feel comfortable to share their views and problems related to their job.
COMPARATIVE ANALYSIS OF DIAGNOSTIC PERFORMANCE BETWEEN TWO ARTIFICIAL INTELLIGENCE-ASSISTED POLYP DETECTION SYSTEMS USING A SELECTED OPTIMAL FALSE POSITIVE THRESHOLDS.

Julalak Karuehardsuwan: NO financial relationship with a commercial interest | Kasenee Tiankanon: NO financial relationship with a commercial interest | Parit Mekaroonkamol: NO financial relationship with a commercial interest | Satimai Aniwan: NO financial relationship with a commercial interest | Phanukorn Sunthornwetchapong: NO financial relationship with a commercial interest | Peerapon Vateekul: NO financial relationship with a commercial interest | Rungsun Rerknimitr: NO financial relationship with a commercial interest
The Implementation of Personal Photograph as Media in Writing Descriptive Text at SMP Negeri 3 Sungguminasa

This research aims to find out whether personal photograph improve significantly the students’ skill in writing descriptive text and to find out students’ perception on the implementation of personal photograph in writing descriptive text. In this research, the population is the eighth-grade students. The research design used in this research was quasi-experimental design. The sample was taken two classes, one class as the experimental class, VIII C and the other class as the control class, VIII D. In collecting the data, the researcher used the instrument in the form of writing test for pre-test and post-test. The results of this research found that value of the t-test was 3.633 and the value of the t-table was 1.734 with significant level (P) = 0.05 and (df) = 20, then the value of t-test was higher than the value of t-table (3.633 &gt; 1.734). It means that H1 &gt; HO, the hypothesis was accepted. Then, the result questionnaire, question number 1-10 showed that almost all of students agree that personal photograph helps them in writing descriptive text.
Pengembangan Bahan Ajar Membaca Permulaan Dengan Menggunakan Media Pop Up Book di Kelas II Sekolah Dasar

The purpose of this research is to develop teaching materials for beginning reading using pop up book media that are valid, practical, and effective. The research method used is a 4D model including Define, Design, Develop, Disseminate. The teaching materials developed were analyzed by a team of experts. The research subjects were class II students. Practically, teaching materials are obtained through questionnaires for teacher and student responses. The effectiveness of teaching materials is seen from the control of student activities and learning outcomes. The results of the validation analysis are 86.84 very valid categories, the results of the practicality test are average and 91.64 are very practical categories and the effectiveness test results are obtained an average of 96 with very high categories Based on these results, it can be concluded that the initial reading teaching materials using pop up book media developed for Grade II Elementary School students are valid, practical, and effective.
Quantum teleportation between the narrow armchair graphene nanoribbons with zigzag ends

We study quantum teleportation between the narrow armchair graphene nanoribbons (GNRs) with zigzag ends. Several influences including Coulomb repulsion among electrons, temperature and ribbon length on the output state and teleportation fidelity are discussed in detail. Moreover, we derive the entanglement of the output state and corresponding fidelity as a function of the input and channel entanglement. For practical applications, we also propose a scheme for implementing the single-qubit gates (X, ZandHgates) and two-qubit controlled-NOT gate in GNRs, based on the Bang-Bang control strategy and synchronous step magnetic field.