Reviewerly/exHarmony huggingface dataset:
The Sun as the Energy Source for Human Beings from the Perspectives of Qu’ran and Science/ Matahari sebagai Sumber Tenaga untuk Manusia dari Perspektif Al-Qu’ran dan Sains

The sun is a great creation of Allah Almighty and a priceless gift for the benefit of mankind. The sun is a major source of energy for the earth’s creatures. Sunlight provides a source of direct radiation, stored radiation, and indirect radiation of energy. Direct radiation energy is the energy that is received directly from the sun. The stored radiation energy is the energy of fossil fuels, biomass, and biogas stored for later use. While indirect radiation energy is wind energy, hydro energy, and ocean thermal energy. These resources have been used from ancient times to the present day and are indispensable to drive the sustainable development of a country. This paper analyzes the information related to the source of energy from the sun and its relationship to the teaching of Islam as contained in the Holy Qu’ran. The resources given to us by God Almighty have no use if we do not use them optimally, efficiently and prudently. The analysis found that the Holy Qu’ran greatly encourages people to make full use of the benefits provided by the energy of the sun. It is hoped that the activities undertaken in utilizing this renewable energy source will not only be fully utilized but will also be used to look for the blessing of Allah Almighty.
Implementation of Web-Based Geographical Information System Mapping Recipients of Social Assistance in Giri Purno Village

Giri Purno Village is a village located in Rimbo Ilir District, Kab. Tebo. This village is one of the villages that receives social assistance from the government where the assistance will be passed on to people in need. The distribution of the location of the houses that receive assistance is still not available, so the coordinates of the houses receiving social assistance are needed. Therefore, we need a geographic information system in which the system contains information and the distribution of the location of houses that receive social assistance. This information system uses the Laravel framework, Laravel is a PHP framework for building a web-based system framework and uses the leafletjs library as a tool for displaying maps and Open Street Map as the base map used. The research method used is the waterfall method. The waterfall method is the earliest SDLC approach used for software development. This research resulted in a Geographic Information System that is capable of managing social assistance beneficiary data, RT data, social assistance beneficiary criteria and can visualize social assistance beneficiary location points on maps spread across Giri Purno Village. In addition, there are also details of recipients of social assistance as well as the route to the recipient's house.
Creating Virtual Field Trips for Education: A Comparison of Software and Tools for Creating Virtual Field Trips with 360° Images

Virtual Reality (VR) has gained more importance in the educational sector. A possibility of using VR in education can be Virtual Field Trips (VFTs). This work analyses the possibilities of creating VFTs with different software/tools, output devices, and 360° cameras in the educational sector. The preparatory work, with the recording of own 360° images, is described, including the involved time and comparison of 360° cameras. With a comparison, four categories of software/tools for creating a VFT are analyzed under the aspects of the needed technical equipment, the time effort, the needed skills to create the VFT and the level of immersion and interactivity, and the convey of technical content through the VFT. For the creation and use of a VFT a software/tool and an output device is necessary. The creation of 360° images requires a 360° camera, which is very time-consuming, concerning the everyday workload of teachers. Three of the tested software/tools require through a graphical user interface a low level of skills for creating a VFT. The created VFT with the different software/tools offers different levels of immersion and interaction. It is possible for teachers to create their own VFT, but the accompanying time and cost can limit the possibilities during the everyday work.
A Product of the Instructional Design Process Developed According to the Seels and Glasgow Model: Interactive Hologram-Supported Material Set

This study aims to design an educational process for teaching scientific concepts during the preschool period based on the instructional design model of Seels and Glasgow and to evaluate its effectiveness. For this purpose, a material set incorporating a teacher's manual and interactive holographic materials was developed. The teacher's manual developed has an inquiry-based approach according to which scientific concepts are structured in line with scientific information. Expert opinions were obtained regarding the developed material set. It was determined that the material set developed in line with expert opinions may be supportive in teaching scientific concepts in the preschool period. Moreover, it was found that the developed material set helped the concretization of abstract concepts that are difficult to observe and that require a process and assisted the children in constructing scientific information in their minds by way of generating realistic three-dimensional images. It is anticipated that, with the interactive holographic material set developed during the research, the lack of materials and scientific information in the preschool teaching process of scientific concepts may be prevented.
Modelling and Simulation of Semi-Autonomous Cars Undercarriage Cleaning Mobile Robot

Abstract: This paper introduces and explains about precise planning and guiding methods for a car’s undercarriage cleaning mobile robot. The proposed semi-autonomous mobile robot makes use of Mecanum wheels, ESP-32, and IR sensors to effectively clean the entire undercarriage of the car. The mobile robot travels in horizontal and vertical directions and is controlled throughout the process. The robot guidance incorporates line follower algorithms as well as programmed motion commands. Line follower algorithm has been implemented via IR sensors. Modeling of the mobile robot is presented through the SolidWorks environment. The path planning is validated using MATLAB Simulink, V-REP and MATLAB as an API. We observed that the size factor hinders the process of adapting car cleaning to household purposes. We worked in that area and created a compact robot for cleaning. This job would serve as a cost-efficient yet time-saving solution to the present circumstances
Sequence Separation-Based Modeling of Denoised Implicit Feedback Behavior

This paper analyzes Click-through rate prediction (CTR), a critical component within recommender systems aiming to forecast the personalized probability of user-item click events. Recent advancements have shown that incorporating user behavior sequences into CTR prediction models can yield significant performance improvements. However, CTR prediction models primarily rely on implicit positive feedback, such as clicks, from user-item interactions while overlooking the negative feedback, such as unclicks. Moreover, the implicit feedback obtained from users often contains noisy data, which hampers the accuracy of user interest modeling. As a solution, we propose a novel framework for estimating click-through rates, leveraging the modeling of Denoised Implicit feedback Behavior (DIB). DIB integrates the complete implicit feedback behavior of users into the click-through rate estimation task and aims to mitigate the influence of noise in implicit feedback on the model’s accuracy. Through extensive experiments conducted on real-world, largescale datasets, we demonstrate that DIB outperforms state-of-the-art models by a substantial margin, resulting in an approximate 5% improvement in Area Under the Curve (AUC).
The Method of Making the Low-dimensional Map that Preserves the Distance Relationships from Selected Data Point

In recent years, data analyses have been conducted in various fields. If the data distribution is unknown before analysis, it is often necessary to determine it. Based on the obtained distribution, hypotheses are set up and the analysis is conducted according to the task. In general, data are high-dimensional with many elements. Therefore, dimensionality reduction is performed to determine the data distribution. Dimensionality reduction maps high-dimensional data onto a low-dimensional space of two or three dimensions while preserving the data features. This allows humans to easily grasp the data distribution. However, in a low-dimensional space, the number of dimensions that can be used for expression is reduced; thus, there will inevitably be gaps in the distance relationships between data in high-dimensional and low-dimensional spaces. As a result, the gaps lead to misinterpretation of the data distribution and analyses, based on incorrect hypotheses. To solve this problem, one possible method is to select a data point with a large gap in the distance relationships as a candidate and check the low-dimensional map that preserves the distance relationships from the candidate data point to the other data points, while preserving the distance relationships between noncandidate data points as much as possible. In this paper, we propose a method that creates a low-dimensional map in which the distance relationships from one selected data point to the other data points are preserved. As a result of the experiment, we confirmed that the proposed method preserves the distance relationships from the candidate data point to the other data points, while preserving the distance relationships between noncandidate data points as much as possible.
Integrating Sarcastic Language Datasets in Various Standards for Sarcasm Detection

Sarcastic language is a special kind of figurative language that involve misperception in the text. The ambiguity and specificity of sarcastic language affects the tasks related to natural language processing and sentiment analysis. These properties make sarcasm detection an important challenge. Different datasets give very different standard on sarcasm. In this paper, we study the “generalizability” of sarcastic datasets. We compare six sarcastic datasets annotated by different research teams. Based on the classification model trained by RoBERTa to investigate the generalizability among the datasets.
Pathfinding Visualizer: A Survey of the State-of-Art

This paper presents a guide to building a pathfinding algorithm visualizer using A* and Dijkstra's algorithms. It includes a background of the visualizer, guidance on building it with customization options, and a brief analysis of complexities. The paper also discusses features, applications, drawbacks, and future works of the visualizer, and provides a brief explanation of BFS and DFS algorithms. It serves as a valuable resource for anyone interested in building a pathfinding algorithm visualizer.
Implementing Runge-Kutta Method of Sixth-Order for Numerical Solution of Fuzzy Differential Equations

The article talks about the increasing importance of the practical use of fuzzy differential equations in modeling complex problems in various fields, such as science and engineering, as these differential equations allow for obtaining accurate results for systems that suffer from uncertainty or incomplete knowledge. Fuzzy differential equations are a suitable alternative to ordinary differential equations if nullity and ambiguity are present in the problem. The article presents a new method for solving fuzzy differential equations using Seikkala derivative techniques, which is based on the numerical approach used in Sixth's Rang-Kutta method. A comprehensive analysis of errors is presented, and the method is applied to solve some linear and nonlinear Cauchy problems using MATLAB program to obtain accurate numerical results close to the exact solution. The article hopes that it will help enhance the reader's understanding of these modern techniques in solving fuzzy differential equations, and improve the ability to apply them in practical solutions.
Communication Skill-Based Writing Instruction (Csbwi) To Promote Extrovert Students in Writing

This study aims to discover the relationship between extrovert students' and their writing ability at the university level. The study was conducted from March to April 2023 at the Jinarakkhita Buddhist College Bandar Lampung. The population of the research was the second-semester Buddhist Education Department students in the academic year 2022-2023. The researchers used a rubric score to analyze and measure the students' recount text writing ability before and after treatment. The data were collected by administering essay writing pre-tests and post-tests. The data were collected from a writing test used to assess students' writing abilities, and a series of analyses were performed, beginning with examining the reliability of the questionnaire and the association between the score and students' personalities. The result showed increased pre-test and post-test average scores from 49.9 to 65.1. In addition, this study found that second-semester students' writing abilities have improved due to the use of communication skill-based writing instruction (CSBWI) to promote extrovert students' as they are more expressive in conducting ideas.
HDTSLR: A Framework Based on Hierarchical Dynamic Positional Encoding for Sign Language Recognition

Sign language is the basic way for people with hearing impairment to communicate, and sign language recognition (SLR) could effectively help in this regard. Mainstream Transformer-based SLR requires positional encoding to sense the positional information of the data. However, existing PE methods globally encode the sign data result in weaken or even ignoring the sequence variation within the gestures. This paper proposes HDTSLR: A Transformer-based SLR framework built on hierarchical dynamic positional encoding (HDPE) enhances individual gesture sequence features while preserving the sign overall temporal features. HDPE designs semantic positional encoding utilizing predefined scale functions with trainable biases to emphasize sign semantic relationships. The t-distribution is used by the designed lexical positional encoding to explore the unique variation of gestures. Before the HDPE operation, the sign language data is split into equal-length feature clips while feature extraction and chunking are performed by the autoencoder. The feature clips with significant changes in gesture chunk are further selected and aggregated with the remaining ones by deforming Gram matrix. In addition, HDTSLR is evaluated on the one-handed and two-handed datasets, achieving word error rates of 16.59% and 21.67%, respectively. Comparison experiments show that it outperforms known SLR methods in both accuracy and robustness.
Process Channels: A New Layer for Process Enactment Based on Blockchain State Channels

For the enactment of inter-organizational processes, blockchain can guarantee the enforcement of process models and the integrity of execution traces. However, existing solutions come with downsides regarding throughput scalability, latency, and suboptimal tradeoffs between confidentiality and transparency. To address these issues, we propose to change the foundation of blockchain-based process enactment: from on-chain smart contracts to state channels, an overlay network on top of a blockchain. State channels allow conducting most transactions off-chain while mostly retaining the core security properties offered by blockchain. Our proposal, process channels, is a model-driven approach to enacting processes on state channels, with the aim to retain the desired blockchain properties while reducing the on-chain footprint as much as possible. We here focus on the principled approach of state channels as a platform, to enable manifold future optimizations in various directions, like latency and confidentiality. We implement our approach prototypical and evaluate it both qualitatively (w.r.t. assumptions and guarantees) and quantitatively (w.r.t. correctness and gas cost). In short, while the initial deployment effort is higher with state channels, it typically pays off after a few process instances—considerably reducing cost. And as long as the new assumptions hold, so do the guarantees.
Zomato Data Analysis and Restaurant Recommendation

The main aim of this project is to develop an accurate model and compare different models to recommend restaurants to users. This is done by analyzing the impact of various factors that are obtained from the ’Bangalore Zomato dataset’ and affect the decision of a customer. Data pre-processing and visualization is performed to understand the attributes of the dataset and make decisions for building the model. TF-IDF is used for the vectorization of text data in the attributes and models with different distance measures are built and compared with each other. Keras Embedding Layer is used to create word embeddings for text data, therefore, generating continuous numeric data for every restaurant. This numeric data of each restaurant is compared with every other restaurant and ’k’ most similar restaurants are recommended
Experiences and Lessons Learned from Real-World Projects in Software Engineering Subject

Teamwork in software development life cycle (SDLC) and Software Engineering (SE) is a cooperative process that all Computing Science (CS) undergraduates need to undergo.It is a critical skill for the industry and is usually trained through group projects in Higher Education.Due to the nature of software development, most software projects involve collaborative efforts of a group of developers.Although teamwork has been studied in many prior works, it is still considered as a dynamic element in SDLC.As the level of complexity, type of deliverables and range of stakeholders in software projects can vary widely, prior experience cannot be applied directly to new projects.The current implementation of SE education in the Professional Software Development (PSD) and Team Project (TP) subjects contains elements to promote teamwork.Students are required to work in groups on real-world problems.This paper examines the current teamwork simulating real-world software projects through an evaluation with the existing and previous cohorts of students, who have experienced the PSD and TP subjects.Several improvements are then proposed by this study.Based on the results, the majority of the respondents agree that our proposed methods such as selfselection of groups, pair programming, and prototyping model will bring about improved teamwork in their group projects.
Multi-Mode AI Accelerator Architecture for Thermal-Aware 3D Stacked Deep Neural Network Design

Deep Neural Networks (DNN) find its prominent presence in the AI world. The properties of its algorithms are very well exploited to make its computations power faster and more efficient. One such adaptation requires reduction in the bit width of the operations for DNN. This paper deals about a DNN architecture design with reconfigurable bitwidth accelerator without affecting the accuracy. This proposed architecture is a modified version of Bit Fusion architecture dealing with dynamic bit-level decomposition for accelerating complex DNN computations. The design make computations with less power consumption, and it is more suitable for the trade-offs among the latency, power, and temperature. The micro architecture design of the modified BitFusion using RTL simulations is carried out to evaluate the functionality.
On Evidence-based Feedback Practices in Software Engineering for Continuous People Improvement

Poor feedback practices for professional development can stall, or even reverse, the professional growth of software engineering professionals. Yet, when setting up feedback systems, organizations often rely on experience or “anecdotal evidence” due to a lack of empirically-grounded guidelines that support those who give and those who receive feedback. Based on responses from a web-based survey, we describe initial challenges and strategies for professional feedback specifically in software engineering. We then explore how software engineering practice can progress towards more evidence-based feedback systems to ensure the continuous growth of professionals. We also present new directions for future research.
Photonics by Four Bosons Electromagnetism

Maxwell is extended based on two electric charge phenomenologies: mutation and conservation law. Three charges {+, −, 0} transformations physics succeeds. It is processed by a Four Bosons Electromagnetism. Photonics is proposed. Self-interacting photons appear at tree level. © 2023 The Author(s).
Underwater laser positioning of targets outside the field of view based on a binocular vision

An underwater laser positioning scheme based on a binocular camera is introduced. In spite of the scattering, the underwater laser light path can be clearly captured by a camera within an appropriate range depending on the water turbidity. For an emitting laser with a fixed position, the three-dimensional information of the laser source can be calculated from the beam images captured by a binocular camera, even if the laser is out of the camera’s field of view (FOV). This method can break through the FOV limitation of traditional camera positioning and perform a 3D spatial positioning for the target even outside the FOV of the camera. We simulate and analyze the scattering light imaging and find that the laser propagation direction can be recognized from the scattering image. The experimental results show that the proposed underwater positioning scheme achieves an average 3D positioning error of 5.53 cm within a range of 5 m when the underwater attenuation is 0.325m −1 .
Enhanced Sharp-Gan for Histopathology Image Synthesis

Histopathology image synthesis aims to address the data shortage issue in training deep learning approaches for accurate cancer detection. However, existing methods struggle to produce realistic images that have accurate nuclei boundaries and less artifacts, which limits the application in downstream tasks. To address the challenges, we propose a novel approach that enhances the quality of synthetic images by using nuclei topology and contour regularization. The proposed approach uses the skeleton map of nuclei to integrate nuclei topology and separate touching nuclei. In the loss function, we propose two new contour regularization terms that enhance the contrast between contour and non-contour pixels and increase the similarity between contour pixels. We evaluate the proposed approach on the two datasets using image quality metrics and a downstream task (nuclei segmentation). The proposed approach outperforms Sharp-GAN in all four image quality metrics on two datasets. By integrating 6k synthetic images from the proposed approach into training, a nuclei segmentation model achieves the state-of-the-art segmentation performance on TNBC dataset and its detection quality (DQ), segmentation quality (SQ), panoptic quality (PQ), and aggregated Jaccard index (AJI) is 0.855, 0.863, 0.691, and 0.683, respectively.
Research on video sensor networks coverage optimization method in obstacle scene

Abstract Aiming at the presence of obstacles when monitoring wild animals in the forest, an obstacle avoidance method is introduced, and a video sensor networks coverage optimization algorithm for virtual force affected by obstacles fused to an immune clone particle swarm is proposed. The algorithm adjusts locally through virtual forces to reduce the overlapping area and then uses the immune cloning particle swarm algorithm to optimize the global nodes to improve the coverage of nodes in the obstacle scene. The simulation results show that the algorithm proposed in this paper can improve the coverage of nodes.