Reviewerly/exHarmony huggingface dataset:
PERANCANGAN GAME PUZZLE HURUF HIJAIYAH MENGGUNAKAN CONSTRUCT 2 BERBASIS ANDROID

Hijaiyyah (Arabic letters) has been around for centuries, when the Al-Quran was first revealed using hijaiyyah, because the first time the Al-Quran was revealed was in Arabic. The importance of learning Arabic letters because these letters are used in writing the Koran. Muslims are obligated to learn the Koran. Educational games are a type of media that are used to teach, increase user knowledge through unique and interesting media. This type is usually intended for children. Construct 2 is a game creator made by Scirra, which is one of the games that game developers are interested in because construct 2 is easy to use and has many tutorials and templates available. in making this game the author uses the Game Development Life Cycle (GDLC) method because the stages are appropriate. The purpose of this research is to introduce the basic knowledge of Islamic religion, produce games with interactive 2D views and features that are interesting for players, this educational game is to encourage children to be more active in learning.
Perancangan Aplikasi Resepsionis Berbasis Web

The Sindang District Office is a government agency that has responsibility for data processing in the Sindang District area. To support effectiveness, efficiency and productivity in an agency in improving service quality, including providing services to the community in the Sindang District area at the reception. To overcome this problem, it is necessary to solve the problem by using a web-based application system so that it can easily find data and search for data. The method used by researchers is a waterfall which consists of several stages, namely requirements, design, implementation, verification and maintenance that have been successfully created and have succeeded in storing community data into a system.&#x0D; Keywords: Receptionist, Web Based, Waterfall.
PERANCANGAN SISTEM INFORMASI PENJUALAN PADA FJS STICKER BERBASIS WEB

In the present era, the implementation of IT has been carried out in various fields, including government, healthcare, military, education, economy, and others. All of this is done in order to boost results and facilitate work processes. In the field of economy or trade, IT is utilized to enhance performance and competitiveness with similar companies. This also has a positive impact on profit acquisition and product marketing expansion. E-commerce is one of the advancements in technology and the internet. It is an internet service used for online buying and selling. With e-commerce, many changes have occurred in the process of transactions. Unlike traditional commerce where sellers and buyers meet physically, e-commerce allows them to interact through the internet or communicate via telephone or chat. Trust becomes the main asset in this process.&#x0D; Therefore, the aforementioned issue necessitates the presence of an information system that can be used to search for information on ornamental plant locations. To address this issue, a web-based information system called "Design of Sales Information System for FJS Sticker" has been developed.
Conclusion

Tech companies bypass privacy laws daily, creating harm for profit. The information economy is plagued with hidden harms to people’s privacy, equality, finances, reputation, mental wellbeing, and even to democracy, produced by data breaches and data-fed business models. This book explores why this happens and proposes what to do about it. Legislators, policymakers, and judges are trapped into ineffective approaches to tackle digital harms because they work with tools unfit to deal with the unique challenges of data ecosystems that leverage AI. People are powerless towards inferences about them that they can’t anticipate, interfaces that manipulate them, and digital harms they can’t escape. Adopting a cross-jurisdictional scope, this book describes how laws and regulators can and should respond to these pervasive and expanding harms. In a world where data is everywhere, one of society’s most pressing challenges is addressing power discrepancies between the companies that profit from personal data and the people whose data produces profit. Doing so requires creating accountability for the consequences of corporate data practices—not the practices themselves. Laws can achieve this by creating a new type of liability that recognizes the social value of privacy, uncovering dynamics between individual and collective digital harms.
Regularity of Markov Process Sample Paths

In this chapter, Markov processes, having a locally compact, separable state space, are constructed with right-continuous sample paths having left limits, often referred to as Càdlàg paths càdlàg paths.
The influence of animated macros-based PowerPoint learning media on the learning outcomes

The objectives of this study are: (1) To determine the learning outcomes of students taught with animated macros-based PowerPoint learning media. (2) To determine the learning outcomes of students taught by conventional methods. (3) To analyze the influence of animated macros-based PowerPoint learning media on the learning outcomes of grade VII students of SMPN 2 Kalidawir. Quantitative research approach with Quasi-Experimental Design type. The population in this study is all grade VII students of SMP Negeri 2 Kalidawir for the 2022/2023 school year. The sample in this study was class VII A, an experimental class with a total of 20 students, and class VII B, a control class with 21 students with purposive sampling techniques. The data collection techniques used are tests and documentation. The data analysis technique used is an independent t-test. The results showed that (1) Student learning outcomes scores when using Macros Animation-based PowerPoint media obtained an average score of 86.00. (2) Student learning outcomes scores obtained an average score of 78.43 when using conventional methods. (3) Macros Animation-Based PowerPoint learning media influences the learning outcomes.
An Information Service Platform for Decision Support in Academic Admissions Using Data Fabrics and Artificial Intelligence

This paper presents the architecture of an information service platform for decision support in academic admissions, utilizing data fabrics and artificial intelligence. The factors affecting students’ further education can be classified into four main types: (1) the course, (2) image, (3) personal reasoning of the student, and (4) public relations. The process of providing information for decision support in academic admissions can be divided into six stages: (1) collecting information, (2) matching study guidance, (3) recommending appropriate education, (4) confirming information, (5) assessing student admissions, and (6) providing feedback. Data fabric is an increasingly popular technology application for data management. The data fabric architecture consists of six layers: (1) an augmented data catalog, (2) a knowledge graph enriched with semantics, (3) metadata activation, (4) a recommendation engine for active metadata, (5) data preparation and integration, and (6) orchestration and data operations. A smart decision support system (DSS) technology is used to assist in decision-making. The results showed that this architecture has an excellent level of suitability (mean = 4.56, standard deviation = 0.35). It can be applied to a university to help it become a digital university and align with its mission.
Research on High Performance Hybrid Model for Text Sentiment Analysis

Long short-term memory (LSTM) neural networks and attention mechanisms have been widely used in the field of sentiment analysis. However, in the existing research, sentiment analysis has always had large deviations in experimental results due to incomplete feature mining. Therefore, in this paper, a hierarchical multi-attention model is proposed, which uses LSTM and Transformer encoder structures to analyze text information step by step. Firstly, convolutional feature extraction is carried out on the preprocessed text vector, then the upper-lower text correlation feature is captured by LSTM. In addition, we use the multi-head attention mechanism for further analysis, and finally the sentiment classification is output, in which the existence of multi-attention makes the model improve the model efficiency on the basis of perfect feature extraction. The proposed LSTM-Transformer framework is evaluated on datasets such as the Sentiment Corpus: Yelp13 and IMDB. Experiments show that this method has good performance.
JS-11 Estimation of stress resilience from eye-gaze data collected by a tablet terminal when performing a dot- probe task

In recent years, the number of patients with mental disorders due to mental health problems has been increasing, and interest in resilience has been growing. In this study, we investigated whether resilience can be estimated even when only affective pictures are used as emotional stimulus images estimated by eye gaze measurement. The results showed that the coefficient of determination of the regression equation using eye gaze indices as explanatory variables was R*2=0.852 when the responce variable was ARS and R*2=0.477 when the responce variable was BRS, which was higher than the previous study. Among the gaze indices, First Fixation was negatively correlated with ARS (R = -0.801) and BRS (R = -0.349), and Frequency was negatively correlated with ARS (R = -0.680) and BRS (R = -0.695). Viewing Time was positively correlated with ARS (R=0.357) and BRS (R = 0.346). Since the results differed from those of previous studies, the characteristics of the attentional bias for the facial expression and affective pictures may be modelled differently.
Application of Augmented Reality Technology in a Custom Car Ride Selection Application (Case Study: Impala Auto Fashion)

The use of augmented reality technology as an auxiliary medium in the wheel selection process is proof of the very rapid development of technology. An effective way to make work easier is by utilizing augmented reality technology, namely combining two-dimensional objects or three-dimensional objects that are applied to the real world. In other words, augmented reality is a combination of two or three-dimensional objects with the real world. A lot of time and energy is simply spent during the process of replacing car rims because the car owner does not feel comfortable with how to disassemble the rims, therefore the augmented reality application is a breakthrough to simplify and speed up the process of selecting rims, the method used is concept, design, assembly, testing, and distribution. The result of the research is an augmented reality application to simplify the process of selecting and replacing car rims on Impala auto fashion.
NEH announces major new AI research initiative

Federal Grants & ContractsVolume 47, Issue 24 p. 1-1 Article NEH announces major new AI research initiative First published: 15 November 2023 https://doi.org/10.1002/fgc.33353Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume47, Issue2416 November 2023Pages 1-1 RelatedInformation
Two Twin Extreme Learning Machines for Regression and Their Applications in Industry

In the actual industrial production process, due to the uncertainties and disturbances caused by measurement errors, abnormal events and other factors, the single-value exact prediction models for key indicators usually fail to guarantee high prediction accuracy. The adoption of prediction interval regression can effectively improve this problem. In this paper, two twin extreme learning machines for interval regression, TELMR and K-TELMR, are proposed. Specifically, TELMR aims to find two non-parallel hyperplanes passing through the origin that approach the sample points from the upper and lower bounds, respectively. The regression error is minimized in each hyperplane without exceeding the sample points as much as possible, and slack variables and a penalty term are introduced to balance the underfitting and overfitting problems. K-TELMR is based on TELMR with kernel mapping instead of random mapping, which saves the step of optimizing the number of hidden layer neurons and makes the model further simplified and lightweight. Numerical computation results on several UCI regression problems and a practical industrial regression problem validate the effectiveness of the proposed models.
Rumah Ramah Apps: Supporting English Learning for Low Vision Students in Higher Education

This research aims to elaborate the use Rumah Ramah Apps by English teachers for low vision student in supporting English learning. The data was obtained through in-depth interviews with five lecturers who and a low vision student who implemented rumahramah.id Apps in English language teaching and learning.The research method adopted in this research is Research and Development (R&amp;D). The findings of the study revealed that (1) Developing English language learning services through the 'Rumah Ramah' application for 'Low Vision' students at Universitas Muhammadiyah Makassar focused on activities ranging from signing in to the Rumah Ramah page to comprehending the use of features on the instructor dashboard and course dashboard to the process of entering learning material, which focuses on general and content drip settings. (2) Implementing English language learning services through the 'Rumah Ramah' Apps for 'Low Vision' students at Universitas Muhammadiyah Makassar focused on the way to access Rumah Ramah Apps and utilize of Rumah Ramah Apps for low vision student. As a result, Rumah Ramah is extremely practicable for usage as an English learning media in assisting lecturers in designing material for low vision students.
A New, Reconfigurable Circuit Offering Functionality of AND and OR Logic Gates for Use in Algorithms Implemented in Hardware

The paper presents a programmable (using a 1-bit signal) digital gate that can operate in one of two OR or AND modes. A circuit of this type can also be implemented using conventional logic gates. However, in the case of the proposed circuit, compared to conventional solutions, the advantage is a much smaller number of transistors necessary for its implementation. Circuit is also much faster than its conventional counterpart. The logic gate was implemented in the 180nm CMOS technology and verified using Hspice simulations. There are many possible applications for this gate, mostly in artificial intelligence and pattern recognition algorithms implemented at the transistor level.
Relevance Search over Knowledge Graph with User-entity Interaction Data

Relevance search is to find a list of entities in a knowledge graph (KG), which are associative to a query entity. However, many entities are not linked in KG but are actually associated by user interactions. To this end, we propose a joint weighting function to evaluate the entity associations from both KG and user-entity interaction data simultaneously. Upon the subgraph extracted from KG w.r.t the query entity, we obtain the associative entities by calculating their association degrees. Experimental results show that the effectiveness of our method outperforms other competitors.
Exploring 2D, 3D and Spatial Audio User Interfaces in VR for Reminiscence Therapy

Reminiscence Therapy (RT) is a non-pharmacological treatment focused on helping individuals with dementia recollect memories through their senses. Traditionally, RT therapy has relied on multimedia, where caregivers choose videos, pictures, and audio files. Since cross-sensory stimuli play an important role during RT, the adoption of Virtual Reality (VR) has spiked as the technology becomes commonplace. Our previous work has focused on prototyping a VR RT tool through co-design and usability testing, utilizing hand tracking for ease of use. In this research, we aim to further understand usability, presence, and cognitive load effects by comparing a 2D Graphical User Interface (GUI), a radio-style 3D User Interface (3DUI), a curved-style 3DUI, and a spatial audio User Interface UI that allows playing, stopping, and adjusting the volume of an audio file. Our preliminary study indicates that a traditional 2D GUI has higher usability, and lower cognitive load, while a curved-style 3DUI with 3D push buttons and a slider for volume around the user has a higher presence than the radio-style 3DUI and the spatial audio UI.
Practical Analysis of Digital Technology in an Electronic Education Platform in PE Training

To improve the practical effect of digital technology (DT) in electronic education platform (ECP) in sports training, this study proposes using OpenPose as the main method of posture matching in sports teaching. MobileNet was introduced to replace the backbone network in OpenPose to improve the efficiency of the model. At the same time, self-attention mechanism (SAM) is introduced to improve the accuracy of the model. In the performance verification results, the proposed algorithm has a mean mean absolute error (MAE) of 0.793 and a root mean square error (RMSE) of 0.628. The accuracy of the proposed algorithm reached a maximum of 0.893 in the test set. The accuracy of the proposed algorithm exceeds 90% in the training set. In the practice of physical education (PE) and training, the absolute error between the actual value and the predicted value does not exceed 1.5 cm, while the relative error does not exceed 1.2%. The minimum absolute error and relative error are 0.01 cm and 0.2%, respectively. The proposed algorithm has high prediction effect and performance, and can be applied to PE training.
PENGARUH MODEL PEMBELAJARAN KOOPERATIF TIPE TTW (THINK TALK WRITE) TERHADAP KETERAMPILAN MENULIS KARANGAN NARASI PESERTA DIDIK KELAS V DI SEKOLAH DASAR

This research was motivated by problems found in class V at SDN Budhi Karya, namely the lack of students' ability to write narrative essays. The type of research used by researchers is a quantitative approach with quasi-experimental or experimental research like an experiment focuses on designnonequivalent control group design. The population used by researchers is all class V students at SDN Budhi Karya, and the sample used by researchers is class VA which is the experimental class and class VB is the control class. The sample in this study used techniques sampling purposive. The instruments used in data collection were tests, namely pretests and posttests to measure students' essay writing skills after being given treatment. The results of the research show that the use of the think talk write type cooperative learning model has an influence with an effect size value of 0.37 in the medium category.
School Administrators’ Support for Teachers’ Training and Maintenance of Digital Literacy Devices, in the Implementation of Digital Literacy Programme in Public Primary Schools in Kitui County-Kenya

Purpose: This study sought to assess the school administrators’ support to implementation of digital literacy program in public primary schools in Kitui County. The study sought to find out whether school administrators had facilitated teachers for digital literacy trainings and to examine whether school administrators had provided for maintenance of the digital literacy devices.&#x0D; Methodology: Descriptive survey research design was used. The target population comprised of 3280 school administrators, who comprised of both head teachers and deputy head teachers and 328 classroom teachers making a total of 3608 respondents. A sample of 10% of the total population was taken making a sample size of 361 respondents, comprising of 328 school administrators and 33 classroom teachers. Self-administered questionnaires were used for data collection. A test- retest was carried out in four public primary schools to establish the reliability of the research instrument. Data collected were analyzed descriptively with help of Statistical Packages of Social Sciences (SPSS) version 28.&#x0D; Findings: The findings revealed that a large number of teachers were supported by their school administrators to attend digital literacy training sessions. It was further noted that very few administrators always facilitated for repair of the broken parts of the computers 16(9.8%).&#x0D; Unique Contribution to Theory, Policy and Practice: The findings of the study will guide the leadership in effective delivery of flagship programs like the digital literacy program through multi-agency approaches.
A Collaborative Filtering Recommendation Algorithm Model Based on User Feature Transfer

The quality of teaching resources and recommended practices in flipped classrooms determine the advantages and disadvantages of this educational model. However, current teaching resource recommendation platforms suffer from issues such as cold startup and sparse data. In order to address these issues, a collaborative filtering recommendation algorithm based on user feature transfer was proposed and utilized to examine the correlation between students’ preference behavior and the recommendation of teaching resources in flipped classes for tourism management. The aim was to enhance the quality of teaching in current classes. Using this algorithm, a transfer by user feature (TUF) model is constructed. In this model, a soft embedding method is employed to accurately extract user feature information in the auxiliary space. This method addresses the challenge of filling large-scale missing matrices in the auxiliary space. Additionally, singular value decomposition is performed to obtain more precise user features. Finally, an optimized Wiberg algorithm with rapid convergence is designed to solve the constructed model. The performance of this algorithm is measured and compared using two common datasets. Compared to other algorithms, the proposed algorithm demonstrates superior performance and a lower mean absolute error value. In summary, the recommendation algorithm can enhance the quality of resource organization and provide more suitable personalized recommendations for the recommendation platform. This is beneficial for improving the quality of students’ learning.