Reviewerly/exHarmony huggingface dataset:
Kampus Mengajar: Developing Literacy and Numeracy Skills of Elementary School Students

This research aims to determine the implementation of the Teaching Campus as an effort to grow the literacy ability of elementary school students. The method used is descriptive with a qualitative approach. The subjects of the research consisted of students of SD Budi Yakin Surabaya and students of SDN Langkap Madura. Data were collected using questionnaires, interviews, and documentation techniques. The results showed that students' literacy and numeracy skills have grown and developed. This can be seen from the increased understanding of the material learned, students can retell their reading results well. Students' dependence on teachers when working on LKS is reduced. The recommendation for campuses is that campuses must be able to prepare students' abilities as well as possible so that campus teaching programs provide benefits to schools.
Analyzing the Extent of Dollarization and Its Potential Impact on the Growth of Small and Medium Enterprises in Tanzania

The primary objective of this study was to investigate the prevalence of dollarization and its potential impact on the progress of Small and Medium Enterprises (SMEs) in Tanzania. To achieve this, an extensive review of literature was conducted to explore the various causes, types, trends, and global effects of dollarization. The research specifically focused on the Dar es Salaam region in Tanzania, employing a survey strategy that involved the distribution of questionnaires to gather data. A sample size of 160 SME representatives was chosen using stratified random sampling techniques.&#x0D; The collected data underwent analysis using the Statistical Package for Social Sciences (SPSS) software, and the findings were presented using tables, charts, figures, and percentages. The results indicated that more than 80% of the respondents were aware of dollarization and its potential implications on their businesses, expressing a predominantly negative perception towards it. However, around 20% of the participants exhibited a lack of comprehensive understanding regarding dollarization and remained uncertain about its benefits. Some respondents argued that dollarization contributes to currency instability, leading to fluctuations in prices for goods and services, as well as creating uncertainties in the foreign exchange market.&#x0D; Based on these findings, it is recommended to conduct further research and analysis to investigate the relationship between SMEs and dollarization within the context of development.
Motivation as a Factor for Enhancing Employees’ Satisfaction: A Case Study of Juba Teaching Hospital, South Sudan

Since issues of employees’ motivation are recorded to be emerging with the current and predicted increases in low salary, delayed salary encourages turnover rates marked that human resources got dehumanized and stopped happiness to people. This study was designed to examine the relationship between motivation and employees’ satisfaction, explore the factors influencing Motivation to enhance employees’ satisfaction and determine the factor structure of Motivation, enhancing employees’ satisfaction in Public Health Hospital. &#x0D; This research design was cross-sectional and descriptive, using quantitative approaches from a population of 838 persons. The purposive and simple random sampling technique was employed to select 260 respondents using The Likert scale. A set of attitude statements was presented as closed-end structure questionnaires and interview guides. SPSS version (20.0) and EPIDATA Program for coding (CSpro 7.5 version) were used to analyze the data. The results were presented using Spearman correlations coefficient, Regressions, ANOVA of variance and factor analysis structure loading to predict the variable relationship. &#x0D; The finding showed that there is a significant positive relationship between motivation and employees’ satisfaction (r=0.003, P-value &lt; 0.01). Enhancing and employees’ satisfaction (r=0.082, p-value &lt;0.01). Motivation is significantly correlated with employees’ satisfaction. However, motivation and employee’s satisfaction (r=0.128, p-value &lt; 0.01)), the staff with more opportunities for motivation are more likely to offer quality services. Indeed, employees with high motivation deliver quality services, indicating that employees’ satisfaction depends on motivation. The regression analysis shows the relationship between motivation, enhanced employees’ satisfaction (F= 1.984, sig=0.000) motivation and enhancing extremely explained employee’s satisfaction of (
PENGARUH E-RESOURCES TERHADAP PRESTASI AKADEMIK YANG DIMEDIASI OLEH PERCEIVED USEFULNESS

Academic achievement directly or indirectly (through perceived usefulness mediation). influenced by the availability of electronic information sources (e-resources). This study aims to determine the significant value of probability: (1) The effect of electronic information sources (e-resources) on perceived usefulness: (2) The effect of perceived usefulness on academic achievement and (3) The direct or indirect influence of electronic information sources (e-resources) ) library on academic achievement. Furthermore, the results of this study are expected to be used as a recommendation material for conceptual formulation in improving student academic achievement through electronic information sources (e-resources) and perceived usefulness. This quantitative research consists of three variables including: electronic information sources (e-resources) as the independent variable, academic achievement as the dependent variable and functioning as an intervening variable, namely perceived usefulness. 100 samples of data were taken by probability from a population of 134. The data analysis used included the classic assumption test, the t hypothesis test and the Determinant (R2) test through path analysis. The results of the study show that: (1) Electronic information sources (e-resources) have a significant effect on perceived usefulness) as indicated by the probability p-value of 0.000 with a t-value of 6,757 which is less than 0.05 (p-value = 0.000 &lt; 0.05); (2) Perceived usefulness has a significant effect on academic achievement with a t-value of 4,579 and a probability of less than 0.05 (p-value = 0.000 &lt;0.05); (3) So directly electronic information sources (e-resources) have a significant effect on academic achievement by 24.2%. with a p-value probability of 0.000 with a t-count value of 6,757 less than 0.05 (p-value = 0.000 &lt;0.05) Likewise, indirectly (through perceived usefulness mediation) a significant effect on academic achievement is shown with a t value of 3.78294426 with a std error of 0.0812436 and a significant probability value of 0.00015498 p-value of 30.734%.
Qiagen DNA PowerWater DNeasy Extraction v1

These are instructions for using the Qiagen Power Water Kit for doing Extraction from drinking water samples
AI-Powered Smart Book: Enhancing Arabic Education in Palestine with Augmented Reality

The global outbreak of COVID-19 has had a major impact on the education of millions of children, hindering their involvement in educational settings and negatively affecting their academic progress. This situation highlights the need to reassess teaching methods and find ways to encourage student involvement in different learning scenarios. Specifically, elementary-level students studying the Arabic language have faced significant challenges in comprehending academic subjects. To tackle this issue, we propose a cutting-edge and creative proposed application called SBAR (Smart Book Augmented Reality), which leverages artificial intelligence (AI) to support students in their interaction with stories from their Arabic textbook curriculum in the State of Palestine. Our proposed application utilizes augmented reality to create a 3D environment featuring book characters that interact with students, inspiring them to learn in a unique and stimulating manner. The app can be run on smartphones and tablets and has been designed to maintain student engagement. It provides two key features: a 3D augmented reality representation of the story that presents the tale through voice and animation, and an interactive component that allows students to respond to questions through natural speech. The interactive component relies on AI and deep learning algorithms to analyze student answers, evaluate them, and provide feedback through interactive voice. Our proposed application is user-friendly, efficient, resource-friendly, and innovative compared to other interactive educational apps. It has been trialed in local schools in Palestine and received positive responses from both students and teachers.
Installing and Using the Perl Server

This chapter is brief, as there is only so much you need to know to install and use a Perl server. For the most part, most operations are simple and intuitively obvious.
Practical JavaScript Concepts and Projects

This chapter looks at some useful JavaScript concepts and projects that span everything from menus to links, coloring, and positioning concerns. I’ve provided about 50 individual code examples with detailed descriptions for each. Some are a little complicated, but for these, I’ve just included more explanations.
Installing and Using the MySQL Database Server

The MySQL database server has been around for years and as such is a robust and practical piece of software. Its features are many and are powerful. MySQL is the most oft-used database in the world. It has to be good to earn that designation. Quite the accomplishment. Even compared to giant database vendors like Oracle, MySQL stands up to the task. SQL (Structured Query Language) is a simple database language to learn, and the server is easy to install, use, and configure.
Structure of the Information-Measuring Complex for Determining the Mutual Position of the Master and Slave Vehicles and Its Calibration

The information-measuring complex for determining the mutual position of master and slave vehicles is necessary for the functioning of a robotic vehicle as a part of an autonomous convoy. The complex is based on a spatial array of ultrasonic receivers receiving periodically emitted signals by an active ultrasonic beacon with a built-in receiver of the global navigation satellite positioning system. The structure of information-measuring complex is designed to provide free connection of additional modules of ultrasonic wave receivers, included in the spatial array placed on the slave vehicle, without significant changes in the work of the complex as a whole. The number of required modules depends on the design features of the robotic vehicle, as well as on the required viewing angle of the complex. An active beacon, which is a portable device, is attached to its master, which can be another robotic vehicle, being a member of an autonomous convoy, or a human operator. The coordinates of each ultrasonic receiver in the local coordinate system of the slave robotic vehicle are needed to calculate the position and trajectory of the master by the Kalman filter with smoothing according to the Rauch-Thung-Strubel algorithm. To automatize the coordinate measurement process, a procedure for calibrating the spatial array of ultrasonic receivers has been developed. A distinctive feature of the calibration procedure is obtaining the coordinates of the ultrasonic receiver modules in the local coordinate system of the slave vehicle in automatic mode using a reference rangefinder mounted on the slave vehicle. In the course of experimental studies, it was found that the calibration of the information-measuring complex allowed to reduce the systematic component of the error in assessing the position of the master up to three times.
A comparative study of Korean children’s English pronunciation assessment: An AI-based speaking program vs. Korean elementary teachers

This study compares AI PengTalk’s assessments of Korean children’s pronunciation with the assessments of Korean teachers. Sixty Korean sixth-graders participated as assessees, and four Korean elementary teachers participated as assessors. Both PengTalk and the teachers rated the children’s production of 10 English sentences on a five-point scale. They focused on segmentals, stress-rhythm, intonation, and speech rate. The findings were as follows: Firstly, PengTalk evaluated the children’s pronunciation in the four elements significantly lower than the teachers across all English proficiency levels. Secondly, teachers’ ratings of the students aligned more closely with their pre-evaluated English proficiency levels than the AI PengTalk’s assessments. The teachers rated students at the upper level significantly higher than those at the intermediate level, who were, in turn, assessed significantly higher than those at the lower level in all four elements. Furthermore, AI PengTalk and the teachers differed in the mean order of the four elements, particularly in segmentals. Based on the results of this study, suggestions were made for the development and implementation of AI-based English programs.
Drone Flight Path Architecture

This project was built from a pre-existing architecture that facilitates the planning and automatic execution of drone routes in a known space through a 3D virtual reality environment. Our work consisted in extending this architecture by integrating a new web component, making use of a 3D map API, to facilitate to people who do not have access to virtual reality hardware, the possibility of planning flight routes that have as parameters the <latitude, longitude> with respect to the globe and also a component in meters that represents the height at which the drone rises in a certain point. Additionally, the configuration possibilities of a route were extended in order to take advantage of one of the components that gives more value and potential to unmanned aircrafts: the use of the camera in multiple contexts and scenarios. The extension of this solution allows the user to assign different camera tasks along the route, see in real time what the camera is capturing and, after the flight, retrieve the multimedia content that was created
Frustrated with Code Quality Issues? LLMs can Help!

As software projects progress, quality of code assumes paramount importance as it affects reliability, maintainability and security of software. For this reason, static analysis tools are used in developer workflows to flag code quality issues. However, developers need to spend extra efforts to revise their code to improve code quality based on the tool findings. In this work, we investigate the use of (instruction-following) large language models (LLMs) to assist developers in revising code to resolve code quality issues. We present a tool, CORE (short for COde REvisions), architected using a pair of LLMs organized as a duo comprised of a proposer and a ranker. Providers of static analysis tools recommend ways to mitigate the tool warnings and developers follow them to revise their code. The \emph{proposer LLM} of CORE takes the same set of recommendations and applies them to generate candidate code revisions. The candidates which pass the static quality checks are retained. However, the LLM may introduce subtle, unintended functionality changes which may go un-detected by the static analysis. The \emph{ranker LLM} evaluates the changes made by the proposer using a rubric that closely follows the acceptance criteria that a developer would enforce. CORE uses the scores assigned by the ranker LLM to rank the candidate revisions before presenting them to the developer. CORE could revise 59.2% Python files (across 52 quality checks) so that they pass scrutiny by both a tool and a human reviewer. The ranker LLM is able to reduce false positives by 25.8% in these cases. CORE produced revisions that passed the static analysis tool in 76.8% Java files (across 10 quality checks) comparable to 78.3% of a specialized program repair tool, with significantly much less engineering efforts.
Eastern Africa

This chapter provides an overview of major political developments, socioeconomic trends, and issues of regional importance in Eastern Africa between January and December 2022. It describes the situation of the economy and macroeconomic challenges in the countries of the region. Overall, growth remained positive in the year under review; however, inflation pressure and debt sustainability became reasons for concern. The chapter also evaluates the state of democracy and elections, the state and causes of armed conflicts, and emerging regional tensions. Ecological issues and the impacts of prolonged drought and climate change on livelihoods and the humanitarian situation are analysed.
Consequence-based Axiom Pinpointing for Expressive Description Logic Ontologies

PDF HTML XML Export Cite reminder Consequence-based Axiom Pinpointing for Expressive Description Logic Ontologies DOI: 10.21655/ijsi.1673-7288.00304 Author: Affiliation: Clc Number: Fund Project: Article | Figures | Metrics | Reference | Related | Cited by | Materials | Comments Abstract:Axiom pinpointing has attracted extensive interest in Description Logics (DLs) due to its effect of exploring explicable defects in the DL ontology and searching for hidden justifications for logical implication. Balancing the expressive power of DLs and the solving efficiency of reasoners has always been the focus of axiom pinpointing research. This study, from both glass-box and black-box perspectives, proposes a consequence-based method for axiom pinpointing. The glass-box method uses modified consequence-based rules (pinpointing rules) to trace the specific process of inference and introduces the concept of pinpointing formula to establish the correspondence between the label of the Boolean formula and all the minimal axiom sets. The black-box method directly calls the reasoner based on the unmodified consequence-based rules and further uses the Hitting Set Tree (HST) to compute all justifications of logical implication. Finally, a reasoning tool is designed based on the two axiom pinpointing algorithms for expressive DL ontologies. Its feasibility is verified theoretically and experimentally, and its solving efficiency is compared with that of existing axiom pinpointing tools. Reference Related Cited by
Detecting Adversarial Attacks on Distribution System State Estimation with Feature Attributions

&lt;p&gt;This paper presents a novel targeted adversarial attack based on the fast gradient sign method on data-driven distribution system state estimation. In this attack, malicious sensor data are crafted such that the state estimator’s output moves away from the latent state of the system in a direction specified by the attacker. Through extensive simulation on a test distribution system, we expose the vulnerability of a state-of-the-art data-driven state estimation technique to the proposed adversarial attack. We also show that the bad data detection method that is commonly used to safeguard state estimation is ineffective against this attack, and this can have deleterious effects on a voltage regulation scheme that incorporates state estimates. To address this vulnerability, we analyze the dispersion of perfeature attribution scores and argue that this dispersion can be used be to detect adversarially crafted data. We corroborate the efficacy of this detection method by comparing it with the conventional bad data detection method and two other baselines.&lt;/p&gt;
Coq Formalization of ZFC Set Theory for Teaching Scenarios

PDF HTML XML Export Cite reminder Coq Formalization of ZFC Set Theory for Teaching Scenarios DOI: 10.21655/ijsi.1673-7288.00303 Author: Affiliation: Clc Number: Fund Project: Article | Figures | Metrics | Reference | Related | Cited by | Materials | Comments Abstract:Discrete mathematics is a foundation course for computer-related majors, and propositional logic, first-order logic, and the axiomatic set theory are important parts of this course. Teaching practice shows that beginners find it difficult to accurately understand abstract concepts, such as syntax, semantics, and reasoning system. In recent years, some scholars have begun introducing interactive theorem provers into teaching to help students construct formal proofs so that they can understand logic systems more thoroughly. However, directly employing the existing theorem provers will increase students' learning burden since these tools have a high threshold for getting started with them. To address this problem, we develop a prover for the Zermelo-Fraenkel set theory with the axiom of Choice (ZFC) in Coq for teaching scenarios. Specifically, the first-order logical reasoning system and the axiomatic set theory ZFC are formalized, and several automated proof tactics specific to reasoning rules are then developed. Students can utilize these automated proof tactics to construct formal proofs of theorems in a textbook-style concise proving environment. This tool has been introduced into the teaching of the course of discrete mathematics for freshmen. Students with no prior theorem-proving experience can quickly construct formal proofs of theorems including mathematical induction and Peano arithmetic with this tool, which verifies the practical effectiveness of this tool. Reference Related Cited by
The study on categorizing scaffolding types of AI chatbots for primary English learning-oriented assessment.

The purpose of this study is to explore the types of scaffolding that AI chatbots can&#x0D; provide through systematic feedback based on learners' individual utterances during&#x0D; elementary English learning-oriented assessment. For the study, the researcher designed&#x0D; an English speaking task and implemented an learning-oriented speaking assessment&#x0D; using an AI chatbot for 25 learners in the 6th grade. Subsequently, individual interviews&#x0D; were conducted to analyze the learners' responses to the scaffolding. By analyzing&#x0D; learner responses and transcripts of conversations between learners and chatbots, the&#x0D; researcher categorized the types of scaffolding that AI chatbots can provide during&#x0D; the learning-oriented assessment. As a result, first, the scaffolding can be categorized&#x0D; into three areas: linguistic, cognitive, and affective. Linguistically, the chatbots&#x0D; provided scaffolding for conveying meaning, language forms, and pronunciation&#x0D; aspects. In the cognitive aspect, the scaffolding assisted learners in their thinking&#x0D; processes, while in the affective aspect, it helped regulate frustration. Second, through&#x0D; scaffolding using various strategies, learners demonstrated the ability to self-correct&#x0D; erroneous utterances and gradually complete sentences on their own. In addition,&#x0D; cognitive scaffolding helped learners solve challenging tasks at their current cognitive&#x0D; level, and affective scaffolding contributed to improving confidence in speaking&#x0D; English. The study offers implications and recommendations based on the findings.