Reviewerly/exHarmony huggingface dataset:
Speech generator for advanced embedded systems

This paper deals with a design and implementation of a speech generator for an advanced embedded system which converts written English text into synthetic speech.The first part describes the Atari 520ST Speech Synthesizer V2.0 program, which was the basis for the implemented speech generator.Then the design and implementation of the speech generator is described.
Building a Better Mouse App: New Modalities For Human-Computer Interaction

The rigid conventions for mouse and keyboard design are ripe for reinvention. We present a collection of new modalities for mouse and keyboard design, which explore possibilities that untether the user from the constraints of surfaces, both screens and tables, and investigate novel relationships to emerging HCI modalities that reconsider how we situate the user in physical and virtual space. We discuss our design process, and present a collection of prototypes that serve as provocations for this and future work. We conclude with a discussion about how these prototypes might provide new opportunities for HCI design in augmented and virtual reality, as well as their application to new possibilities for ubiquitous computing.
Effect of Nanomaterials Addition to Phase Change Materials on Heat Transfer in Solar Panels under Iraqi Atmospheric Conditions

It is common knowledge that phase-change materials are used for the purpose of thermal storage because of the characteristics that are exclusive to these materials and not found in others.These characteristics include a large capacity for absorbing heat and a large capacity for releasing heat when the phase changes; however, these materials have a low thermal conductivity.This paper presents the results of an experimental study that investigated the impact that nanoparticles of copper oxide had on reducing the temperature of solar panels.The phase change substance that was used was determined to be beeswax.The impact of adding nanoscale copper oxide at a concentration of 0.05% of the total mass of wax was investigated and compared to a reference solar panel that did not contain any nanoscale additions.The findings demonstrated that the incorporation of nanoscale copper oxide brought about a reduction of three °C in the plate's average temperature as well as a one percent improvement in its electrical efficiency.In cases where it seems that the use of nanoparticles might potentially enhance the performance of integrated solar energy systems that contain phase change.
Industrial data logger

This paper deals with the design of an ON-LINE diagnostic system named as "industrial data concentrator".The paper looks at the design itself in a comprehensive way and brings together parts such as defining useful process variables, and the actual design of the industrial data concentrator both in terms of hardware and software.
DIFFERENCES IN THE USE OF ROLE PLAYING METHODS AND LECTURE METHODS ON THEMATIC LEARNING OUTCOMES OF CLASS V SDN 9 BANYUWANGI

One of the efforts to improve the quality of education is through the introduction of contemporary curriculum development and role playing methods which are very suitable for elementary school thematic learners. In learning activities that use role play, the teacher can combine several subjects in one activity. This of course will make it easier and save the teacher's time to convey learning material. The purpose of this research is to find out whether the use of the role playing method has an effect on thematic learning outcomes. The research was conducted in class V of elementary school with a total of 70 students. Data collection techniques used questionnaires, tests and documentation. The data analysis technique uses multiple linear regression to test learning outcomes, using individual sample t-tests. The results showed that the t-test analysis of descriptive statistics on learning outcomes showed a significant difference between the average students who were treated with an average of 83.43 using the role playing method. This means that the role play method is very possible. While increasing student learning outcomes, students who were treated with the lecture method averaged 70.29. This means that the application of the lecture method has not been effective in improving student learning outcomes. In the t-test analysis using SPSS 23.00 the coefficient is less than 0.05 so the tcount is 12.179 which is significant. Furthermore, it can be said that there is a positive influence in the use of role playing learning on thematic learning outcomes of elementary school students
THE INFLUENCE OF COMIC MEDIA BASED ON ADOBE PHOTOSHOP CS ON WRITING SKILLS AND LEARNING INTEREST OF CLASS IV SDN SIDOMULYO STUDENTS 05

This study aims to determine the effect of comic media based on Adobe Photoshop CS on writing skills and learning interest of fourth grade students of SDN Sidomulyo 05, Silo-Jember District.The phenomenon that exists in grade IV SDN Sidomulyo 05 is that there are several problems found in learning essay writing and a lack of interest in participating in learning activities. The problems encountered include: (a) there are still many students who have difficulty expressing their thoughts, feelings and ideas in writing in writing, (b) not being able to use solid sentences, (c) not being able to use correct spelling, (d) lack of interest in writing activities or tend to get bored easily because there are no more ideas that can be expressed in their writing, (e) students are not active in participating in essay writing activities and joke more with their friends.&#x0D; This study uses a causal quantitative research approach (cause and effect) in looking at the relationship of variables to the object under study, so that in this study there is an independent variable (X) namely comic media and two dependent variables, namely writing skills (Y1) and interest in learning (Y2). Techniques to determine a sample from a population that has certain characteristics to the desired quota. From this technique the researchers took a sample of class IV as many as 30 students.&#x0D; With the help of SPSS v.22 the results of the data obtained through the calculation of the SPSS test t-test, the t-count value of the conventional learning method has a value of -2.900 with a probability of 0.008 (sig). The mean difference in the conventional method is -2.30769 with a df of 25. Meanwhile, the t-count value in the comic media based on the Adobe Photoshop CS program is 6.325 with a probability of 0.001 (sig). The number of df is 25 with a mean difference of 4.61538. Meanwhile, from the results of the questionnaire data analysis of interest in learning obtained 0.535, this means that 53.5% of the data both have a positive effect.&#x0D; Based on the results of analysis and hypothesis testing, data obtained that Ho is rejected, which means that there is an effect of using adobe photoshop-based comic media on students' writing skills and interest in learning
Penerapan Sistem Informasi Pelayanan Pengaduan Pasien Sebagai Solusi Dalam Meningkatkan Kualitas Layanan

Excellent service or service excellence in hospitals is needed to provide trust and service according to standards. In an effort to improve services, a patient complaint service is needed to respond to each service and realize the rights received by patients. The availability of patient complaint services in Hermina Arcamanik Hospital is currently still using google form and sending complaints using whatsapp, the media used is still considered less effective and efficient so that it is vulnerable to data manipulation or errors when inputting data. Based on these obstacles, it is important that the complaint process can be resolved properly, appropriate data processing and ease of access to online services by patients can be fully and thoroughly. So a Patient Complaint Service Information System was made in the form of a web to facilitate access, this Information System was created using the PHP programming language and has an interface with Bootstrap and is equipped with Javascript, a storage database using MySQL and a local hosting server from Apache using the XAMPP program.The research results of designing a web-based complaint service information system in the form of service access that can be used easily and connected to the internet quickly and appropriate data processing.
THE INFLUENCE OF THE BLENDED LEARNING METHOD AND USAGE YOUTUBE VIDEO MEDIA ON STUDENT LEARNING OUTCOMES CLASS X OF SMAN PAKUSARI IN ENGLISH LESSON

Problem-based learning models can be combined with learning media to generate new desires and interests, generate motivation and stimulate learning activities and even bring psychological influences such as blended learning methods and YouTube video media that combine or mix face-to-face learning and computer-based learning.. This experimental research used a pre-test post-test control group design. Data collection tools used pre-test and post-test methods. Instrument analysis used: normality test and homogeneity test. Hypothesis analysis using t-test. The difference is clearly visible from the experimental class and control class as stated between learning using the Blended Learning method and youtube media and without youtube media. The value of sig 2 tailed is 0.00 where the value of sig is below the value of 0.005 which means that there are differences in student learning outcomes using the blended learning method without youtube media and with youtube media.Based on the results of research on the effect of the Blended learning method using YouTube video media on student learning outcomes in English subjects. Therefore, educational institutions are expected to make policies to improve the quality of learning, especially in developing a more student-centered learning model or better known as student-centered learning
Pengaruh Bermain Game Online Terhadap Perilaku Komunikasi Siswa Kelas XII Jurursan Mipa SMA Negeri 1 Andong

This study aims to determine and analyze the Effect of Online Game on Communication Behavior of Students SMA Negeri 1 Andong. This research is a quantitative study using primary data obtained from questionnaires and measured using a Likert scale. Data were analyzed using simple regression analysis. The population of this research is the XII grade field of mathematics and natural sciences students of SMA Negeri 1 Andong with a total of 300 students in which only 26% or 78 students were sampled for this study. The results of this study indicate that the online game have no effect on communication behavior.
Literature Review Visualisasi Data dan Sistem Informasi Geografis

In the past, statisticians, programmers, and data scientists handled data analytics, rarely interacting with companies directly. However, this "experts only" method of data analysis and display has been altered by more user-friendly data visualization, dashboards, and mashup technologies. With improvements that make it possible for people at all levels of an organization to analyze data in meaningful ways, data analytics is being pushed into business. The reporting and visualization tools that statisticians formerly used are now being improved by manufacturers of enterprise-grade analytics. This study describes how dashboards help businesses optimize their operations. And how business dashboards are developed using real-time data and people's innate capacity for visual thought.
FLOOD MODEL SIMULATION OF PURNAMA STREET AREA DUE TO INCREASE OF WATER LEVELS OF THE KAPUAS RIVER AND THE INTENSITY AND DURATION OF RAIN

Flooding is a condition where water is not accommodated or the flow of water is obstructed in the sewer, so that it overflows to inundate the surrounding area. The area around the ditch on Purnama Street (the estuary of the Kapuas River) is affected by tides and the intensity and duration of rainfall. This study aims to simulate the flood model that occurred in the Purnama Street area. Data analysis was carried out using HEC-RAS software as a tool for modeling drainage flow. The research was conducted during no rain conditions, 5 and 10 year return periods of rain and the highest and lowest tidal conditions. The flood model simulations were carried out from Demang Ditch to the Lower Kapuas River. The results of the modeling using HEC-RAS show that the drainage channel from the Kapuas River to Purnama Street does not experience inundation/flooding, but in the area of Purnama Street to Demang Ditch during the 5 and 10 year return period rains and the highest tides experience inundation/flooding. which reaches the highway.
EVALUATION OF DRAINAGE CHANNEL CAPACITY ON JALAN BUDI KARYA, PONTIANAK SELATAN SUB-DISTRICT

Drainage is one of the most critical components to be maintained and developed in a strategically healthy and comfortable urban environment. There are often puddles of water on Budi Karya Street, especially at the Permai Reservoir Complex. In solving the existing inundation problem, primary and secondary data are needed. Primary data is in the form of longitudinal and transverse sections of the channel, while secondary data is in the form of location maps, tidal data, and rainfall data used to analyze hydrology. Based on the analysis of the capacity of Budi Karya's drainage channel using HEC -RAS software as a drainage channel flow modeling tool to view the water level profile along the channel, channel perspective drawing, or hydrograph, it was found that the Budi Karya drainage channel could not accommodate the planned discharge for return periods 2 and 5 Year. Therefore, it is necessary to improve drainage in the form of the normalization of drainage channels.
Leveraging Recommender Systems to Reduce Content Gaps on Peer Production Platforms

Peer production platforms like Wikipedia commonly suffer from content gaps. Prior research suggests recommender systems can help solve this problem, by guiding editors towards underrepresented topics. However, it remains unclear whether this approach would result in less relevant recommendations, leading to reduced overall engagement with recommended items. To answer this question, we first conducted offline analyses (Study 1) on SuggestBot, a task-routing recommender system for Wikipedia, then did a three-month controlled experiment (Study 2). Our results show that presenting users with articles from underrepresented topics increased the proportion of work done on those articles without significantly reducing overall recommendation uptake. We discuss the implications of our results, including how ignoring the article discovery process can artificially narrow recommendations on peer production platforms.
Deteksi Pornografi pada Karakter Animasi 2D dengan KNN (K-Nearest Neighbors) Menggunakan Fitur HSV

The development of animation technology is very rapid, both in 2D and 3D forms. Most animators often create female animated characters for various fields such as games, commercials or other anime. Along with the development of animation, there are also negative and positive impacts, where the negative impact is the presence of symbols that lead to pornography. Most of the animations containing negative symbols are spread through the internet, which can be accessed easily by anyone, regardless of age. Which can result in addiction to viewing pornography to other negative behaviors. Artificial intelligence, which is currently developing rapidly, also allows this research to aim at early detection of animated characters that contain pornographic elements. By classifying 2D female animation using the KNN algorithm method with HSV feature extraction. The HSV feature is quite good at detecting complex colors in 2D animated characters. Where the HSV feature can distinguish skin color from other colors in 2D animation. The dataset used consists of 3 categories, namely pornographic images, semi-pornographic images, and non-pornographic images. Using the KNN method, it is possible to classify pornographic, semi-pornographic and non-pornographic images. In this study, the results of HSV feature extraction using the KNN classification method obtained the highest accuracy value of 63.16%.
Network quantum steering enables randomness certification without seed randomness

Quantum networks with independent sources allow the observation of quantum nonlocality without inputs. Consequently, the incompatibility of measurements is not a necessity for observing quantum nonlocality when one has access to independent sources. Here we investigate the minimal scenario without inputs where one can observe any form of quantum nonlocality. We show that even two parties with two sources that might be classically correlated can witness a form of quantum nonlocality, in particular quantum steering, in networks without inputs if one of the parties is trusted, that is, performs a fixed known measurement. We term this effect as swap-steering. The scenario presented in this work is minimal to observe such an effect. Consequently, a scenario exists where one can observe quantum steering but not Bell non-locality. We further construct a linear witness to observe swap-steering. Interestingly, this witness enables self-testing of the quantum states generated by the sources and the local measurement of the untrusted party. This in turn allows certifying two bits of randomness that can be obtained from the measurement outcomes of the untrusted device without the requirement of initially feeding the device with randomness.
DARTS: Double Attention Reference-based Transformer for Super-resolution

We present DARTS, a transformer model for reference-based image super-resolution. DARTS learns joint representations of two image distributions to enhance the content of low-resolution input images through matching correspondences learned from high-resolution reference images. Current state-of-the-art techniques in reference-based image super-resolution are based on a multi-network, multi-stage architecture. In this work, we adapt the double attention block from the GAN literature, processing the two visual streams separately and combining self-attention and cross-attention blocks through a gating attention strategy. Our work demonstrates how the attention mechanism can be adapted for the particular requirements of reference-based image super-resolution, significantly simplifying the architecture and training pipeline. We show that our transformer-based model performs competitively with state-of-the-art models, while maintaining a simpler overall architecture and training process. In particular, we obtain state-of-the-art on the SUN80 dataset, with a PSNR/SSIM of 29.83 / .809. These results show that attention alone is sufficient for the RSR task, without multiple purpose-built subnetworks, knowledge distillation, or multi-stage training.
Curriculum Learning for Graph Neural Networks: A Multiview Competence-based Approach

A curriculum is a planned sequence of learning materials and an effective one can make learning efficient and effective for both humans and machines. Recent studies developed effective data-driven curriculum learning approaches for training graph neural networks in language applications. However, existing curriculum learning approaches often employ a single criterion of difficulty in their training paradigms. In this paper, we propose a new perspective on curriculum learning by introducing a novel approach that builds on graph complexity formalisms (as difficulty criteria) and model competence during training. The model consists of a scheduling scheme which derives effective curricula by accounting for different views of sample difficulty and model competence during training. The proposed solution advances existing research in curriculum learning for graph neural networks with the ability to incorporate a fine-grained spectrum of graph difficulty criteria in their training paradigms. Experimental results on real-world link prediction and node classification tasks illustrate the effectiveness of the proposed approach.
Examining the Effects of Degree Distribution and Homophily in Graph Learning Models

Despite a surge in interest in GNN development, homogeneity in benchmarking datasets still presents a fundamental issue to GNN research. GraphWorld is a recent solution which uses the Stochastic Block Model (SBM) to generate diverse populations of synthetic graphs for benchmarking any GNN task. Despite its success, the SBM imposed fundamental limitations on the kinds of graph structure GraphWorld could create. In this work we examine how two additional synthetic graph generators can improve GraphWorld's evaluation; LFR, a well-established model in the graph clustering literature and CABAM, a recent adaptation of the Barabasi-Albert model tailored for GNN benchmarking. By integrating these generators, we significantly expand the coverage of graph space within the GraphWorld framework while preserving key graph properties observed in real-world networks. To demonstrate their effectiveness, we generate 300,000 graphs to benchmark 11 GNN models on a node classification task. We find GNN performance variations in response to homophily, degree distribution and feature signal. Based on these findings, we classify models by their sensitivity to the new generators under these properties. Additionally, we release the extensions made to GraphWorld on the GitHub repository, offering further evaluation of GNN performance on new graphs.
Federated Large Language Model: A Position Paper

Large scale language models (LLM) have received significant attention and found diverse applications across various domains, but their development encounters challenges in real-world scenarios. These challenges arise due to the scarcity of public domain data availability and the need to maintain privacy with respect to private domain data. To address these issues, federated learning (FL) has emerged as a promising technology that enables collaborative training of shared models while preserving decentralized data. We propose the concept of federated LLM, which comprises three key components, i.e., federated LLM pre-training, federated LLM fine-tuning, and federated LLM prompt engineering. For each component, we discuss its advantage over traditional LLM training methods and propose specific engineering strategies for implementation. Furthermore, we explore the novel challenges introduced by the integration of FL and LLM. We analyze existing solutions and identify potential obstacles faced by these solutions within the context of federated LLM.
Sharpness-Aware Graph Collaborative Filtering

Graph Neural Networks (GNNs) have achieved impressive performance in collaborative filtering. However, GNNs tend to yield inferior performance when the distributions of training and test data are not aligned well. Also, training GNNs requires optimizing non-convex neural networks with an abundance of local and global minima, which may differ widely in their performance at test time. Thus, it is essential to choose the minima carefully. Here we propose an effective training schema, called {gSAM}, under the principle that the \textit{flatter} minima has a better generalization ability than the \textit{sharper} ones. To achieve this goal, gSAM regularizes the flatness of the weight loss landscape by forming a bi-level optimization: the outer problem conducts the standard model training while the inner problem helps the model jump out of the sharp minima. Experimental results show the superiority of our gSAM.