Reviewerly/exHarmony huggingface dataset:
TBM Karya Mulya Development through the application of technology and the Information Literacy

The development of community reading parks through the application of technology and Information Literacy concepts has become a significant effort in promoting literacy and access to knowledge within the community at large. This effort is necessary to utilise the principles of technology and information literacy to improve reading experience and knowledge dissemination. This research discusses the implementation of information literacy in the library of Karya Mulya community reading park. The purpose of this study is to describe the development of Taman Baca Masyarakat (TBM) Karya Mulya through the application of technology and the concept of Information Literacy through an activity programme created by academic supervisors of lecturers and students. This research was conducted using a qualitative approach with a case study method. Data collection was done through observation and interviews with TBM managers. The results of this study indicate that the development of TBM Karya Mulya through the application of technology and the concept of Information Literacy is designed in addition to supporting one of its parent programmes, namely TBM Karya Mulya, also to introduce the concept of information literacy to TBM managers. The implementation of the programme consists of several types of activities such as the installation of SLiMS, E-DDC, and the classification of unnumbered books for stored books as well as introducing the concept of information literacy to students. This activity has enriched the understanding of information literacy among visitors to Taman Bacaan Masyarakat Karya Mulya, especially students and lecturers who were previously unfamiliar with the concept of information literacy.
RFID BASED SMART SYSTEM FOR STORING DATA

The main functionality of this project is to access the passport details of a passport holder through RFID technology. For this purpose the authorized person is given an RFID card. This card contains an integrated circuit that is used for storing, processing information through modulating and demodulating of the radio frequency signal that is being transmitted. Thus, the data stored in this card is referred as the passport details of the person.Passport verification and checking is a very time consuming process. This proposed system simplifies the process by giving the authorized person an RFID tag containing all the passport details like name, passport number and nationality etc. Once, the person places the cardin front of the RFID card reader, it reads the data and verifies it with that data present in the system and if it matches then it displays the details of the passport holder. Here we use microcontroller from 8051 family. For display a 16X2 LCD is used. The status also can be retrieved from this system by pressing the status button interfaced to a microcontroller.&#x0D; &#x0D; Further the project can be enhanced by using finger printer module. This overcomes thedrawbacks of RFID and provides high level of security in the system.
OA-721 Leveraging digital platforms to support a sustainable national research information management system for research ethics and regulation in Uganda

<h3>Background</h3> In Uganda, complex clinical research projects that require regulatory oversight are a growing phenomenon. Although there are functional national regulatory agencies (NRAs) to provide oversight, various constraints, including the lack of a robust digital platform to facilitate their work make them inefficient. This scenario has necessitated the establishment of a sustainable digital system to support the work of the NRAs and research ethics committees (RECs). Against this background, the EDTCP-II grants supported a project on Scaling up the Capacity of RECs in Uganda (SCRECU), 2019–2022, and facilitated further development of a National Research Information Management System (NRIMS) which had been developed with support from an earlier EDCTP grant. The overarching objective of SCRECU was to build sustainable capacity for the NRIMS with capabilities of facilitating multi-REC ethical reviews, national registration of research protocols, and their subsequent monitoring by NRAs and RECs. <h3>Methods</h3> We trained RECs personnel on the use of NRIMS for online protocol submissions and management; post-approval processes and enrolment of RECs. We provided the RECs with ICT equipment and followed them up to ensure utilization. We tested the effectiveness of the NRIMS, evaluated its adoption, and developed guidelines for its operationalization. <h3>Results</h3> We trained the chairperson, an administrator, and an IT officer from each of the 26 RECs in Uganda on the use of NRIMS and equipped them with Internet services and other relevant tools. Our study demonstrated the affordability of NRIMS and how digital tools can be leveraged to strengthen ethics and regulatory capacity in resource-constrained settings. The study also generated an inventory of equipment required for the operationalization of an NRIMS. The NRIMS has registered over 13,000 users, received over 6,000 applications, and granted 2,500 approvals online. The NRIMS has enhanced institutional workflows, reduced paperwork by over 95%, and turnaround time for protocol approvals by 50%. It has enhanced research ethics regulatory capacity in Uganda. <h3>Conclusion</h3> The NRIMs has revolutionized and strengthened research ethics and regulation in Uganda. It provides a secure, web-based solution for efficient submission, review, approval, and monitoring of research projects. Its success in Uganda provides a paradigm shift for other NRAs in sub-Saharan Africa.
Pentingnya Pendidikan Bahasa Dalam Membangun Karakter Yang Berbudaya Di SMP PGRI 9 Sidoarjo

This article aims to discuss in detail the importance of language education in building a cultured character at the PGRI 9 SIDOARJO Junior High School level. Language education has a very important role in shaping the character of students, especially during adolescence which is a crucial period in the formation of their personality. Language education at Junior High School PGRI 9 SIDOARJO provides opportunities for students to develop language skills, both in speaking, writing, reading and listening. Students learn grammar, vocabulary, and language skills needed in everyday life. Language education is also important in building a cultured character. Students are exposed to literary works that represent diverse cultural values, develop empathy, tolerance and understanding of cultural diversity. Language education teaches good communication ethics, respect for the opinions of others, courtesy, and honesty. Students learn to respect and understand the perspectives of others and communicate effectively by taking into account social and cultural contexts. Good language skills open doors for students to acquire new knowledge and access broader information. Language education provides a strong foundation for students in studying other subjects, developing interests and talents, and facing challenges in an increasingly global world of work. This article emphasizes the importance of language education in building cultured character at Junior High School PGRI 9 SIDOARJO. Language education improves language skills, understands culture, and develops inclusive, empathetic, and communicative characters
PELATIHAN TEKNIK MUDAH PEMBUATAN GAME PADA MICROSOFT POWERPOINT PADA SMK AL-WASLIYAH HAMPARAN PERAK

Reativity and skills in the field of technology are a unit that go hand in hand and are indispensable in the world of work. For this reason, it needs to be instilled early on in directing and developing the skills and creativity of a student. Given the large number of companies engaged in graphic design, advertising and multimedia, it affects the development of the times and everyone's knowledge. In the very rapid development of technology like now we are required to be able to become people who have more creativity. This Community Service is carried out at the Al-Wasliyah Hamparan Perak Vocational School, where the author will help younger siblings to be able to make simple games from power point. But it doesn't demand the possibility for them to recreate it into games that are more creative, innovative and useful.
K-means Optimization Method Based On Adaptive Parallel Hierarchical Clustering

The two key steps of the K-means algorithm are the selection of the clustering number and the selection of the initial clustering center, which will seriously affect the classification accuracy and efficiency of K-means, and need further optimization. Aiming at the selection of the number of clusters, a K-means optimization method based on adaptive parallel hierarchical clustering is proposed. In the merging process of hierarchical clustering, the optimal number of clusters is selected adaptively by improving the clustering effect evaluation function, and the Parallel computing method is used instead of the serial computing method to improve the computing speed. Aiming at selecting cluster centers more accurately, an optimized data density model is proposed to make full use of potentially related information between samples, which improves the classification accuracy of the algorithm. More importantly, it overcomes the problem of the strong subjectivity of super-parameter selection. The improved algorithm was tested with the ablation experiment method and compared to other traditional algorithms on iris and seed data sets. The results showed that the optimization algorithm could accelerate the calculation speed and improve the classification accuracy.
Sentiment-aware Content Recommendation using LSTM-based Collaborative Filtering

The need for this work arises from the ever-growing demand for more precise and efficient content recommendation systems. Existing methods, while serving their purpose, are not without limitations. They often struggle to capture the intricate nuances of user sentiment, which is crucial for personalized content recommendations. This limitation results in suboptimal precision, accuracy, recall, and speed, ultimately leading to less satisfying user experiences. To address these shortcomings, this paper introduces a novel approach, leveraging the fusion of Bidirectional Long Short-Term Memory (BiLSTM) with BERT, combined with a Graph Convolutional Network (GCN). This innovative model brings together the power of natural language processing and graph-based techniques, enhancing the efficiency of sentiment-aware content recommendation and filtering. The use of BiLSTM and BERT allows our model to grasp the contextual intricacies of user preferences, making it more adept at discerning sentiment in textual data samples. The incorporation of GCN further enriches our model's capabilities by leveraging the underlying connections between users and content, enabling it to provide more personalized recommendations. The advantages of our proposed approach become evident through rigorous testing on multiple contextual datasets. Compared to existing methods, our model exhibits notable improvements, with an 8.3% boost in precision, an 8.5% increase in accuracy, a 5.9% rise in recall, and a 4.5% enhancement in speed. Moreover, our model achieves a 7.5% better Area Under the Curve (AUC), solidifying its effectiveness in sentiment-aware content recommendation.&#x0D; In conclusion, this work fills a crucial gap in the realm of content recommendation by introducing a sophisticated model that excels in capturing user sentiment and delivering more precise and efficient recommendations. These advancements pave the way for improved user experiences and hold significant implications for a wide range of applications, from e-commerce to personalized content delivery platforms.
Impact Of Agricultural Loans by Deposit Money Banks on Agricultural Output In Nigeria

This study examines the impact of agricultural loan by deposit money bank credit on agricultural output in FCT Abuja, Nigeria. The study employed the Demand-following theory to explain the relationship between agricultural loan applicant access to deposit money bank credit and agricultural output. A sample of 295 (5 Agricultural loan desk officer from the five selected banks and 200 agricultural loan applicants) respondents were sampled using Multistage Cluster sampling technique. Data were analysed using descriptive statistic (mean Score) and logit regression analysis for inferential statistics. The results show that agricultural loan applicants' access to bank credit for deposits has a large direct impact on Nigerian agriculture. Based on the outcome of data analysis, the study recommends that the Apex bank should direct the deposit money banks to make credits available for agricultural loan applicants and upsurge the agricultural credits monetary base to farmers. This can be done by expanding and encouraging more farmers and also increasing the sum allotted to individual/cooperative units.&#x0D;
Decision Support System Direct Cash Assistance Of Village Funds (Blt Dd) Using Weighted Aggregated Sum Product Assement Waspas Method (Case Study Of Padang Pandan Village)

The problems found in this study are how to make a Decision Support System application for direct cash assistance to BLT DD village funds by applying the Waspas method to Padang Pandan Village. Decision Support System is an information system that provides information, modeling and data manipulation. Decision support systems provide specific interactive support for the decision-making process of managers and other business practitioners. The purpose of the Decision Support System is to make it easier to collect data on the implementation of BLT village funds.The WASPAS method is a combination of two methods, namely the WSM (Weight sum model) and the Weight product model (WPM). WSM is a weighted quantity, while WPM is a weighted product model. So it can be defined that WASPAS is an assessment of the weighted aggregate amount product. The results of the study that the waspas method can collect data on the value of the results of information calculations about direct cash assistance for BLT DD village funds in Padang Pandan village
Development of Interactive Multimedia to Foster Students' Information Literacy Ability on Salt Hydrolysis Topic

This study aims to produce and determine the feasibility of interactive multimedia salt hydrolysis to grow students' information literacy skills. This research is a development research which includes 10 stages of implementation, namely potential and problems, collecting information, product design, design validation, design revision, product trial, product revision, usage trial, product revision, and bulk product. However, this study only reached the stage of product revision. The interactive multimedia produced was then validated by 2 expert lecturers in the field of chemistry education, and for practitioner tests by 1 chemistry teacher and then a limited group trial was carried out involving 15 students of SMA Negeri 1 Batulayar. Based on the assessment of two lecturers as validators getting an average of 91,2% with a very decent category, the practitioner test results got a percentage of 94.3% with a very decent category, and the results of a limited group trial by 15 students got an average percentage of assessments for ease, readability, display, material, and motivation of 88.6% with good categories. So it can be concluded that the product of interactive multimedia development of salt hydrolysis has met the feasibility aspect and this medium can be used in learning on salt hydrolysis material.
Grammatical Evolution based Controller Design for Vehicle Robot Action Learning

Compared to humans that naturally learned to accomplish a task by learning from psychomotor skills, robots perform a complete task by dividing tasks into smaller executable tasks and run in sequence. Creating a control program for robots needs explicit definition of each action to handle inputs from sensors and produce outputs to actuator. This project aims to analyze Grammatical Evolution(GE), a naturally inspired evolutionary algorithm derived from Genetic Programming (GP) to automate the process of producing controller instructions for Vehicle Robot. The advantage of this algorithm is the ability to separate searching space and generated program, thus eliminating human criteria bias when creating a robot controller while able to find more optimized and complex skills learning. The evaluation is done through partially observed maze problem which objective to find goal without defining starting orientation and discoverable path along the way. Several Evolutionary parameters are compared to find the optimized value that suits the application of robot. Then, several paths generated from the program are compared and discussed to determine the efficacy of the algorithm in locating the optimal program. The proposed method is more pragmatic as it focusses on the actual actions sequences on how the program is developed automatically to solve the problem.
The Effect of Process Skills Approach Using Picture Stories on Reading Comprehension and Interest in Reading in Elementary School Students

This study aims to describe the effect of the process skills approach using picture stories on reading comprehension and reading interest of Aisyiyah Muhammadiyah 3 Elementary School Makassar fifth-grade students. This research is a quasi-experimental study with a nonequivalent control group design. The research population was all fifth-grade students at Aisyiyah Muhammadiyah 3 Makassar Elementary School, totaling 30 students. Sampling was done through the saturated sampling technique. Data was collected through tests and questionnaires and then analyzed descriptively and differentially using the Independent T-Test and the Manova Test. Based on the study's results, it can be concluded that the process skills approach using picture stories positively affects reading comprehension and reading interest in fifth-grade students of Aisyiyah Muhammadiyah 3 Makassar Elementary School.
Fine metal-rich waste stream characterization based on RGB data: Comparison between feature-based and deep learning classification methods

Background: Material compositions in the recycling industry are currently determined by manual sorting, which is time intensive and shows subjective influences. For an automated, sensor-based material flow characterization a particlebased material classification is necessary. Aim: The classification of metal-containing fine-fractions based on RGB images with different machine learning (ML) techniques is investigated on two created datasets A (12,480 images) and B (19,498 images). Method: Two approaches are compared: In approach I, images are firstly pixel- and then object-based classified with six different ML models on three color spaces. In approach II, images are classified by six different convolutional neural networks (CNNs). Results: The classification of dataset A was possible with high accuracy (&gt; 99.8 %) for both approaches and chosen ML algorithms were of minor importance. For dataset B, approach I achieved an accuracy of 78.2 % ± 2.0 %, and chosen ML algorithms were of higher importance for object-based classification. In approach II, the best-performing CNN achieved an accuracy of 80.4 % ± 4.2 % and a top-3 score of 94.2 % ± 2.6 %. Conclusion: Results from existing studies for coarser particle sizes can be transferred to fine fractions. Further research is needed to improve the classification of dataset B, e. g. by adding instances to less frequent classes and applying deeper CNNs.
Promoting ELT through Mobile Assisted Language Learning – MALL

In this qualitative, descriptive, and case study research, the effect of applying Mobile Assisted Language Learning strategies (MALL) in the development of communicative skills in teachers at Universidad Santo Tomás (USTA) was analyzed. To achieve this goal, the following moments were defined: first, some applications focused on the development of language skills in English such as reading, grammar, listening and writing were characterized to define their contribution to the learning process. Second, a mobile learning strategy was implemented to guide and control the use of the applications in order to motivate learning and to encourage the development of different language skills. Along this stage, data was obtained from three varied sources: surveys, workshops and open interviews with a focus group that provided specific information to determine the outcome of the strategy implementation. Finally, the information was analyzed to determine the findings and conclusions. The results showed that teachers maintained their motivation during the process and were willing to learn English with the mediation of mobile learning strategies. Likewise, the participants’ performance improved along the whole process. As a final result, the implementation of this strategy helped to consolidate an ICT proposal for the Foreign Language and Cultures International Center (CILCE) at Universidad Santo Tomás (USTA).
Exploring the Impact of Training Data Distribution and Subword Tokenization on Gender Bias in Machine Translation

Bar Iluz, Tomasz Limisiewicz, Gabriel Stanovsky, David Mareček. Proceedings of the 13th International Joint Conference on Natural Language Processing and the 3rd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (Volume 1: Long Papers). 2023.
Are Machine Reading Comprehension Systems Robust to Context Paraphrasing?

Yulong Wu, Viktor Schlegel, Riza Batista-Navarro. Proceedings of the 13th International Joint Conference on Natural Language Processing and the 3rd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (Volume 2: Short Papers). 2023.
Data from Comparison of Performance Between a Short Categorized Lifestyle Exposure-based Colon Cancer Risk Prediction Tool and a Model Using Continuous Measures

&lt;div&gt;Abstract&lt;p&gt;Risk prediction models that estimate an individual's risk of developing colon cancer could be used for a variety of clinical and public health interventions, including offering high-risk individuals enhanced screening or lifestyle interventions. However, if risk prediction models are to be translated into actual clinical and public health practice, they must not only be valid and reliable, but also be easy to use. One way of accomplishing this might be to simplify the information that users of risk prediction tools have to enter, but it is critical to ensure no resulting detrimental effects on model performance. We compared the performance of a simplified, largely categorized exposure-based colon cancer risk model against a more complex, largely continuous exposure-based risk model using two prospective cohorts. Using data from the Nurses’ Health Study and the Health Professionals Follow-up Study we included 816 incident colon cancer cases in women and 412 in men. The discrimination of models was not significantly different comparing a categorized risk prediction model with a continuous prediction model in women (c-statistic 0.600 vs. 0.609, &lt;i&gt;P&lt;/i&gt;&lt;sub&gt;diff&lt;/sub&gt; = 0.07) and men (c-statistic 0.622 vs. 0.618, &lt;i&gt;P&lt;/i&gt;&lt;sub&gt;diff&lt;/sub&gt; = 0.60). Both models had good calibration in men [observed case count/expected case count (O/E) = 1.05, &lt;i&gt;P&lt;/i&gt; &gt; 0.05] but not in women (O/E = 1.19, &lt;i&gt;P&lt;/i&gt; &lt; 0.01). Risk reclassification was slightly improved using categorized predictors in men [net reclassification index (NRI) = 0.041] and slightly worsened in women (NRI = −0.065). Categorical assessment of predictor variables may facilitate use of risk assessment tools in the general population without significant loss of performance.&lt;/p&gt;&lt;/div&gt;