Reviewerly/exHarmony huggingface dataset:
Implementation of Fuzzy Logic Controller Algorithms with MF optimization on FPGA

In this work, we propose the design and implementation of a parallel-structured fuzzy logic controller with integral action and anti-windup. The Grey Wolf Optimization (GWO) optimization technique is used to optimize fuzzy rules, which allows for the complicated algebraic ideas of type 1 fuzzy logic algorithms to be reduced to straightforward numerical equations for FPGA target implementation. The techniques for operating a geared DC motor are optimized by the membership function structure of our controller's data propagation. Our proposed controller was implemented in Xilinx System Generator (XSG) and co-simulated on hardware and software with VIVADO and XSG tools.
Ethnomathematics Comics of Al-Akbar Mosque Surabaya to Improve Numeracy and Literacy in Reading and Writing

The numeracy and reading and writing literacy of elementary school students in Indonesia is still not satisfactory. Need the existence of innovative teaching materials that suit students' cognitive levels, increasing interest in reading, and accommodate students' numeracy and literacy skills. Culture in the form of the Al-Akbar Mosque building in Surabaya can be used as a student learning resource with the hope that learning will be more meaningful for students. Ethnomatematics comics can used as an alternative learning media to improve numeracy and reading literacy write. The purpose of this research is to describe the comic development process ethnomathematics of al-akbar mosque and knowing the validity of ethnomathematics comics. The research method uses Borg and research and development methods Gall. The research subjects were fifth grade students at Bahrul Ulum Elementary School, Surabaya. This research uses a type of development research or commonly known as Research and Development (R&amp;D). Using the ADDIE model (Analysis, Design, Development, Implementation, Evaluation). However, it is limited to the Analysis, Design and Development stage. Data collection methods use questionnaires and documentation. Development research instruments used to assess the feasibility of interaktif digital modules are in the form of product feasibility questionnaires. Data analysis techniques use descriptive data analysis techniques for product processing and quantitative analysis to determine product feasibility. The results of this research are products of development results through three stages, namely Analysis (needs analysis, student analysis, content analysis), Design (the stage used to create an Ethnomatematics comics and Development in the form of product development results. Ethnomathematics comic at the Al Akbar Mosque in Surabaya has achieved 83.93% feasibility in the feasible category. Feasibility is obtained from the results of an assessment by 2 expert validators media and material experts, as well as 2 practitioners. So, it can be concluded that ethnomathematics comics are suitable for use in learning and are expected to become reference learning resources by educators to improve literacy and numeracy for elementary school students.
The Importance of User Education As An Effort to Maximize the Use of Library At SMKN 1 Bandung

User education is material about libraries that are given to users. Libraries provide user education so that users know how to use the library. There are still users who do not understand using the library, which makes the writer interested in researching the importance of user education to maximize the use of the library at SMKN 1 Bandung. This study uses a descriptive method with a quantitative approach, where data is obtained using a questionnaire distributed using google forms. The population in this study were users of SMKN 1 Bandung, which amounted to 30 users. The study results revealed that user education in the library of SMKN 1 Bandung was carried out by providing various methods of user education for school residents. Pustaka revealed that user education provided by the library of SMKN 1 Bandung is considered essential and helps users use or utilize various library services and facilities.
Phenomena of Child Involvement in Literacy Practices in the Province of Yogyakarta Special Region: A Communication Study

Literacy hegemony is currently formed by the cultural practices of the dominant social group, in this case, adult humans. The whole practice is seen from the eyes of adults as a form of the legitimacy of power. Since 2017 the phenomenon of children's involvement in literacy practices has increased. Even though children work together with adults in their operations, they are able to accommodate their needs well. This article tries to look at communication activities that occur in the phenomenon of children's involvement in literacy practices in the Province of the Special Region of Yogyakarta. The writing of this article is based on the theory of symbolic and sociocultural interaction with a constructivist approach. The research informants consisted of 5 elementary school children in the Special Region of Yogyakarta Province who had a consistent and measurable literacy trajectory and were involved in various literacy practices from 2017 to 2019. The results showed that communication activities in children involved in literacy practices partially begin early, intensely, and in a conducive communication environment. The presence of parents or adults around the child is decisive. Creating space for discussion and children's participation through play activities and text media forms interactions that help children's cognitive and affective development, encouraging children's involvement in literacy practices
Enhancing Classification of Low-Quality Text Documents through Multimodal Approach

Traditional document classification relies on text-based Natural Language Processing (NLP), limiting its effectiveness with visually complex or Optical Character Recognition (OCR)-sensitive documents. Indeed, the result of text recognition from an image directly influences the outcomes of classification traditionally based on NLP techniques. This paper introduces a novel multimodal approach that integrates textual and visual information to enhance accuracy, particularly in challenging OCR scenarios. We showcase practical applications highlighting the potential of our approach to improve document classification. The results to be presented in this paper seem interesting and appealing, demonstrating an improvement of accuracy.
A Comparative Study on MMSE Approaches to Speckle Noise Reduction in SAR Images

Speckle noise in the satellite image can cause a decrease in image quality and make it less informative about the target/features in the image under study. Denoising SAR images is a challenging task for researchers due to the difficulty of identifying and recognizing images that are affected by speckle noise. Hence, it is crucial to reduce the speckle in the image before implementing any image processing technique. There have been numerous filtering techniques developed to denoise SAR images to date. The primary purpose of denoising is to eliminate speckle noise while keeping the essential features of the images intact. In this study, we will discuss the MMSE-based filter and his enhanced versions. In fact, many researches were made to prove the effectiveness of this based filter and their alternative versions for that the author made a brief analysis of different techniques used for speckle noise reduction, along with their advantages and disadvantages, in a comparative manner. The evaluation of each filter is based on its capacity to smooth the homogeneous areas, its aptitude to preserve contours, and its capacity to preserve spatial detail. Airborne synthetic aperture radar SAR data is used for validation.
An improved learning algorithm for training neural network based lattice equalizer

In nonlinear channel equalization, artificial neural networks (ANN) have attracted a significant interest. The ANN's primary drawback is their intensive training. We propose suggestions for enhancing their training capacities. The first involves applying a whitening technique to the input data by employing a lattice structure as the equalizer. Lattice equalizer therefore becomes insensitivity to the inputs correlation matrix. In the second strategy, we suggest modifying the slope of the activation function. Combining the two methods increases the ANN's nonlinear capabilities and adaptability. Through simulation tests, the offered methodologies efficacy is verified. The results demonstrate that the performance of the neural network-based lattice equalizer is greatly improved by whitening the received data using adaptive lattice channel equalization techniques in conjunction with an adjustable slope activation function.
MODERN PEDAGOGICAL TECHNOLOGIES USE IN TECHNOLOGICAL EDUCATION AS A CONDITION FOR IMPROVING THE QUALITY OF EDUCATION

The traditional content of education today serves as a reliable foundation for implementing new, yet unfamiliar pedagogical ideas. Rapidly advancing modern education offers new approaches aimed at enhancing its effectiveness, encompassing the theory and practice of teaching, upbringing, and education, defining them as systematic and purposeful actions directed toward organizing and refining educational processes.The aim of the article is to examine and analyze the impact of modern pedagogical technologies on the process of technological education with the objective of improving the efficiency and quality of the educational process. The primary focus of the article is directed towards revealing the advantages and opportunities of utilizing these technologies in shaping key skills among students, stimulating their creative thinking, and preparing them for the challenges of the modern world.During the research, groups of technology teaching methods were identified. The study focuses on exploring and analyzing key pedagogical technologies such as: information and communication technologies – facilitating not only access to knowledge but also encouraging active information exchange; critical thinking technology – aimed at fostering studentsʼ analytical and critical skills; project-based technology – emphasizing practical application of acquired knowledge and fostering creative thinking; developmental learning technology –aimed at stimulating active creative engagement among students; health-promoting technologies – supporting studentsʼ physical and psychological well-being; problem-based learning technology – aiding in solving complex tasks and stimulating analytical thinking; game-based technologies – fostering student interest and engagement in learning.The diversity of pedagogical technologies enhances studentsʼ comprehension of both theoretical and practical materials, positioning them among the forefront in contemporary didactics within general secondary education institutions. Implementing modern pedagogical technologies in classrooms creates an environment conducive to improving the quality of studentsʼ learning experiences in technological education.&#x0D; Keywords: teaching technologies; formation; learning effectiveness; practical work; modernisation of education; quality of education; technological education; critical thinking; lesson.
Quantum Annealing-Based Machine Learning for Battery Health Monitoring Robust to Adversarial Attacks

Battery health monitoring methods including machine learning (ML) models rely on trustworthiness of battery sensor data and features. As more battery systems require network connectivity for intelligent health monitoring, cyberattacks become a serious threat. A notable attack is an adversarial attack that generates stealthier input data misleading the ML results. This paper introduces an adversarial attack targeting battery health monitoring system and explores a quantum annealing (QA)-based machine learning method to mitigate the adversarial attacks. In this paper, a Quantum Boost (QBoost)-based state of health (SOH) estimation algorithm for electric vehicles is developed and trained by D-Wave QA processor and the performance is compared with a state-of the art random forest (RF)-based SOH estimation method. The experimental results show that the proposed QBoost method is more robust to the adversarial attack than the RF method, while the RF method provides better accuracy during normal operation.
Emerging Computing Architectures: Simulation of Power Electronics in Power Grids

As the penetration of power electronics increases in power grids, new computing architectures needed to be evaluated for the simulation of high-fidelity models of power electronics in power grids in operations. In this paper, emerging computing architectures such as quantum processing units are evaluated for the simulation of power electronics in power grids. A hybrid algorithm based on classical computing and quantum computing is developed and tested for different use cases of electromagnetic transient (EMT) simulation of power electronics (PE)-based systems and simple circuits. The algorithms needed to simulate power electronics in emerging computing architectures are discussed and thereafter, simulation results are shown.
Improving Stage II Dementia Patient Outcomes with Robotics

This paper presents the preliminary investigation into using low-cost robots to improve or slow down dementia in aged patients living in the community.
The Impact of Google Translate Syntactic Strategies on Translation Quality: Translating Journal Articles from Indonesian to English

The prevalent use of Google Translate as a tool for academic translations, despite concerns regarding its quality, frames the core issue of this research. This research aims to classify syntactic strategies used by Google Translate in translating from Indonesia to English. It also aims to analyze the quality of the translation produced and how the syntactic strategies affected the translation quality. The data were collected from a journal article entitled “Pengaruh Bahasa Indonesia dan Bahasa Inggris sebagai Bahasa Pengantar dalam Pendidikan Formal” which was presented using a descriptive qualitative method. The findings of this research reveal there are several types of different syntactic strategies used by Google Translate. The result of this research shows that, out of 273 data collected, there are 123 (45.05%) data of literal translation, 2 (0.73%) data of loan and calque, 53 (19.41%) of transposition, 17 (6.23%) data of unit shift, 45 (16.48%) data of phrase structure change, 1 (0.37%) data of clause structure change, 18 (6.59%) data of sentence structure change, 1 (0.37%) data of cohesion change, 13 (4.76%) data of level shift, and no data found for scheme change. In addition, there are several different classifications found for translation quality. Out of 194 data analyzed, the results show that 163 (84.02%) data are accurate, 30 (15.46%) data are less accurate, and 1 (0.52%) data is not accurate. For acceptability, there are 179 (92.27%) acceptable, 14 (7.22%) data are less accurate, and 2 (1.03%) data are not acceptable. Finally, there are 180 (92.78%) data with high readability, 15 (7.73%) data are medium readability, and no data found for low readability.
Infrared image interest point detector for few samples Based on Superpoint

Aiming at the problems of poor robustness and many misselected points when extracting interest points from a small number of infrared images, an interest point detection algorithm based on improved Superpoint for infrared images with few samples is proposed. First, self-supervised methods are used in the data annotation phase to reduce the cost of manual annotation and the problem of defining points of interest caused by individual subjectivity. The improved Superpoint algorithm is then used to train the optical remote sensing images to enhance the performance of the detector. Finally training on a small number of infrared images by transfer learning. The improved algorithm is evaluated against different algorithms on a small number of infrared image datasets and a generic Haptches datasets, The results show that the improved algorithm maintains some generality and achieves excellent performance, has better robustness in processing images with low resolution and high noise, and can provide more reliable points of interest for subsequent image matching tasks.
Dynamic Link State Routing Scheme for Quantum Key Distribution Network

Quantum key distribution, as a physical principle-based encryption scheme, can circumvent the encryption risks associated with increased arithmetic power. With the gradual completion of hardware architecture, key relaying and distribution between nodes over long distances can be achieved, thus it becomes possible to implement quantum key encryption in large scale complex networks. In this paper, an adaptive link overhead routing algorithm for enhanced networks based on quantum key distribution is proposed, combined with a shortest path-based routing scheme that jointly determines link overheads according to link capacity and key generation rate, and simulation under 7-node and 10-node network topologies are completed.
Investigating The Effectiveness of Various Convolutional Neural Network Model Architectures for Skin Cancer Melanoma Classification

Melanoma is one of the most dangerous types of skin cancer. Since 2018, the number of skin cancer cases in the US has increased and exceeded 100,000. Melanoma is the third most common cancer in Indonesia, following womb cancer and breast cancer. Standard detection of melanoma skin cancer biopsy is costly and time-consuming. The purpose of this research is to build and compare melanoma skin cancer detection using various Convolutional Neural Network method. This research used four CNN model architectures methods, VGG-16, LeNet, Xception, and MobileNet. The dataset for this research is image data that consists of 9605 data divided into benign and malignant classes. The data will be augmented to increase its quantity. After that, the data will be trained using four CNN architecture models and evaluated using the confusion matrix. The result of this study is that Xception model has the best accuracy and the lowest loss, with 93% accuracy and 19% loss, with precision 93%, recall 93,5%, and f1-score 93%. Whereas the other model, VGG-16 gives 90 % accuracy, 27% loss, LeNet 89,7% accuracy, 28% loss, and mobileNet 90,8% accuracy and 22,5% loss.
Melukis dengan teknik tarikan benang pada pembelajaran Seni Budaya dan Keterampilan (Studi Deskriptif di kelas II SDN 87 Kota Bengkulu)

This type of research is qualitative descriptive research, with participant observationtechniques. The purpose of this study is to describe the process of making and painting artwork with yarn pull techniques in class II Culture and Skills SBK study were all class II students of SDN 87 Bengkulu city, totaling 26 people. The research instrument was a human instrument, using observation guidelines, interview guidelines and documentation guidelines. Data collection techniques in the form of observation, interviews and documentation. Data analysis of the process of making the work is done by analyzing the data then reducing, displaying, and drawing conclusions. The results of the study are (1) The process of making painting works with the technique of pulling thread begins with the distribution of tools and materials in the form of newsprint, mattress yarn, dyeing place, HVS paper and coloring. Followed by folding the paper in two. Next dip the yarn into the dye. Then the thread is put on paper and the last is the pulling of the thread. (2) All works of art in painting with the technique of pulling threads made by students contain elements and principles of fine art. Elements of art on the results of painting with yarn pull techniques have all been applied. Keywords: art works, yarn pull technique, SBK
Privacy-Preserving Frequency Estimation Method

Differential privacy is one of the methods used to protect personal data by adding noise to personal data and its analysis results, so that the statistics obtained from the data can be safely disclosed. In this paper, we propose a new frequency estimation method by applying differential privacy to frequent itemset mining, which analyzes the frequencies of items owned by individuals in a dataset. Existing differential privacy mechanisms for frequency estimation have shown high usefulness when the privacy budget is large, i.e., when the privacy protection strength is low, but have been less useful when the privacy budget is small. Our proposed method uses a mechanism that does not change the distribution of the original dataset and anonymized one regardless of the size of the privacy budget, so that the proposed method is highly useful even when the privacy budget is small.
A Novel Ciphertext-Policy Attribute-Based Encryption Supporting Dual Membership

Attribute-based encryption (ABE), which was first conceptualized by Sahai and Waters in 2005, has been applied to many different environments nowadays. Various variants of ABE has been designed and proposed in literature. Recently, Lu et al. proposed a new ABE supporting dual membership predicates. Unfortunately, we found that Lu et al.’s scheme fails to achieve non-membership. In this manuscript, we design a new ABE scheme supporting dual membership. As we will show in the manuscript, our scheme is the only ABE scheme realizing membership and non-membership predicates for access structures.
IMPLEMENTATION OF WORDWALL AS A LEARNING MEDIA TO IMPROVE STUDENTS' WRITING SKILL

This study examines the effectiveness of Wordwall as a learning media in enhancing the writing skill of students. The Wordwall is an innovative and interactive tool that utilizes technology to engage students in writing activities. A review of related literature suggests that Wordwall as a learning media has been successfully implemented in various contexts to enhance students' writing skill. This study utilized a pre-experimental design known as a one-group pretest-posttest design. This design involved a single group of participants who underwent two measurements: a pretest was conducted prior to the intervention and then followed by a posttest. By comparing the participants' performance on the pretest and posttest, the study aimed to evaluate the impact of the intervention on the measured variable. The results showed that the group taught using Wordwall had a significant improvement in their writing skill. The results of this study have practical implications for language teachers to consider using Wordwall as a learning media to enhance their students' writing skill.&#x0D; Keywords: wordwall as a learning media, writing skill, interactive learning, technology-based learning