Reviewerly/exHarmony huggingface dataset:
Research on Task Scheduling Optimi-Zation of Data Center Under Double Carbon Target

When a data center is running, the efficiency of task scheduling directly affects its operating efficiency. Aiming at the efficiency of scheduling operation, aiming at low-carbon operation, the optimization algorithm and resource allocation technology of task scheduling are studied. The traditional scheduling optimization algorithm is relatively lacking in the training speed and the state and motion capture ability in the face of complex environments. Therefore, a scheduling optimization learning model is proposed, which accelerates the model training through the experience knowledge base, and establishes a deep reinforcement learning model to obtain more effi-cient and accurate scheduling policy information, and design a coding scheme using idle nodes to speed up task scheduling. Simulation experiments show that it effectively reduces the turnaround time and delay parameters of task scheduling, maximizes the amount of parallel tasks, and has better scheduling efficiency and high-load coping capabilities.
Information and communication technologies in the educational process of Baranovichy State University and Derzhavin Tambov State University

The information and communication technologies used in the educational process of Baranovichy State University and Derzhavin Tambov State University are described. Wide methodological toolkit was used: general logical methods of cognition (analysis, synthesis, abstraction, deduction, induction, analogy, modeling); empirical methods (description, comparison, own observation of information and educational technologies of Baranovichy State University and Derzhavin Tambov State University); private scientific methods (cybernetic, axiological, synergetic, in particular, the method of content analysis of the content of the information and educational environment of the two universities); special methods (the method of comparative analysis, formal legal method, method of legal hermeneutics). It was established that the development of information and communication technologies is directly influenced by a complex of modern challenges and threats. The conclusion is made about the positive effect of the participation of universities in specialized support programs, the participation of Derzhavin Tambov State University in the Priority 2030 program is given as an example. Attention is focused on the development of information and communication technologies products in the context of expanding the conditions for the education of persons with disabilities. The application of the obtained results is assumed in three directions: theoretical (continuation of research), normative (development of proposals aimed at improving legislation) and utilitarian (application in the educational process). The originality and scientific novelty of the work are revealed in the results of the analysis and comparison of the content of information and educational technologies of two partner universities – Baranovichy State University and Derzhavin Tambov State University. Research data and its results can form the basis of individual transformations accompanying educational activities, as well as serve as a theoretical basis for further research in the field of information technology in the research and educational space.
Revisiting the fragility of influence functions

In the last few years, many works have tried to explain the predictions of deep learning models. Few methods, however, have been proposed to verify the accuracy or faithfulness of these explanations. Recently, influence functions, which is a method that approximates the effect that leave-one-out training has on the loss function, has been shown to be fragile. The proposed reason for their fragility remains unclear. Although previous work suggests the use of regularization to increase robustness, this does not hold in all cases. In this work, we seek to investigate the experiments performed in the prior work in an effort to understand the underlying mechanisms of influence function fragility. First, we verify influence functions using procedures from the literature under conditions where the convexity assumptions of influence functions are met. Then, we relax these assumptions and study the effects of non-convexity by using deeper models and more complex datasets. Here, we analyze the key metrics and procedures that are used to validate influence functions. Our results indicate that the validation procedures may cause the observed fragility.
Online Learning As a Tool for the Education System in the Context of Digitalisation

Online learning has tended to increase its use in the education system since the beginning of the pandemic. The article aims to empirically investigate the effectiveness of online learning as a tool for the education system in the context of digitalization. The study is based on the use of a structured interview technique and an analysis of the results of a survey of Ukrainian university students. To ensure organization and self-discipline, comprehension, learning, and assimilation of learning material, it is important to ensure a sufficient level of interactivity and teacher-student interaction, feedback, and guidance to students in an adequate time frame. A well-functioning feedback system is a supportive and essential element for student learning. Classical deadlines set by the teacher for assignments are also a valid method in online learning. Students noted the importance of creativity in the teacher's presentation of the task and the importance of the limitations of the methods by which the task can be solved. Timely revision, and evaluation by the teacher of the work, the task also encourage students to put a higher level of effort into their online learning. Online synchronous seminars in ZOOM are more impactful and motivating than recorded video lectures, and presentations which are available to students in asynchronous mode. An essential method of online learning was noted by the students to complete individual written assignments on the studied topic immediately after its presentation. The teacher's explanations and live synchronous conversation were also effective in online learning. Continuous, systematic educator monitoring of the progress and attendance at the online classes encouraged students to attend lectures but was not a major method for ensuring synchronous attendance.
Intelligent Multi-Lingual Cyber-Hate Detection in Online Social Networks: Taxonomy, Approaches, Datasets, and Open Challenges

Sentiment Analysis, also known as opinion mining, is the area of Natural Language Processing that aims to extract human perceptions, thoughts, and beliefs from unstructured textual content. It has become a useful, attractive, and challenging research area concerning the emergence and rise of social media and the mass volume of individuals’ reviews, comments, and feedback. One of the major problems, apparent and evident in social media, is the toxic online textual content. People from diverse cultural backgrounds and beliefs access Internet sites, concealing and disguising their identity under a cloud of anonymity. Due to users’ freedom and anonymity, as well as a lack of regulation governed by social media, cyber toxicity and bullying speech are major issues that need an automated system to be detected and prevented. There is diverse research in different languages and approaches in this area, but the lack of a comprehensive study to investigate them from all aspects is tangible. In this manuscript, a comprehensive multi-lingual and systematic review of cyber-hate sentiment analysis is presented. It states the definition, properties, and taxonomy of cyberbullying and how often each type occurs. In addition, it presents the most recent popular cyberbullying benchmark datasets in different languages, showing their number of classes (Binary/Multiple), discussing the applied algorithms, and how they were evaluated. It also provides the challenges, solutions, as well as future directions.
Co-Speech Gesture Synthesis using Discrete Gesture Token Learning

Synthesizing realistic co-speech gestures is an important and yet unsolved problem for creating believable motions that can drive a humanoid robot to interact and communicate with human users. Such capability will improve the impressions of the robots by human users and will find applications in education, training, and medical services. One challenge in learning the co-speech gesture model is that there may be multiple viable gesture motions for the same speech utterance. The deterministic regression methods can not resolve the conflicting samples and may produce over-smoothed or damped motions. We proposed a two-stage model to address this uncertainty issue in gesture synthesis by modeling the gesture segments as discrete latent codes. Our method utilizes RQ-VAE in the first stage to learn a discrete codebook consisting of gesture tokens from training data. In the second stage, a two-level autoregressive transformer model is used to learn the prior distribution of residual codes conditioned on input speech context. Since the inference is formulated as token sampling, multiple gesture sequences could be generated given the same speech input using top-k sampling. The quantitative results and the user study showed the proposed method outperforms the previous methods and is able to generate realistic and diverse gesture motions.
Leveraging Foundation Models for Clinical Text Analysis

Infectious diseases are a significant public health concern globally, and extracting relevant information from scientific literature can facilitate the development of effective prevention and treatment strategies. However, the large amount of clinical data available presents a challenge for information extraction. To address this challenge, this study proposes a natural language processing (NLP) framework that uses a pre-trained transformer model fine-tuned on task-specific data to extract key information related to infectious diseases from free-text clinical data. The proposed framework includes three components: a data layer for preparing datasets from clinical texts, a foundation model layer for entity extraction, and an assessment layer for performance analysis. The results of the evaluation indicate that the proposed method outperforms standard methods, and leveraging prior knowledge through the pre-trained transformer model makes it useful for investigating other infectious diseases in the future.
Vocal Arrangement

Consumer acceptance of voice assistant devices depends in large measure on the performance of their voice recognition systems. HEAD acoustics reveals best practice for the testing and optimization of these technologies.
Challenge to create a new WAKUWAKU (Passion/Empathy/Agile) foundation by utilizing the concept of co-education and extending the idea of engineering to "the souls of engineers".

In recent years, there has been an "octopus pot" in the area of specialty that has become an issue. To address this issue, we aim to solve the problem by achieving "synthesis" (synthesis) that transcends specialized fields in order to acquire a bird's-eye view.The "purpose, ambition, and curiosity" originating from individual energy, "dialogue" with members of a group and different fields, and "fusion of intersubjectivity" are necessary, and these were understood as “the soul of engineers".The role of the manufacturing industry should be developed as a foundation for co-education. To do this, we would like to transform the company into a place where each engineer can create value, a place where “WAKU-WAKU” (Passion, Empathy, Agile) can take place, and a place where all people involved can grow, based on the concept of “the soul of engineers”.
Drone Visuals and Compliance with IHL

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Development of an Automatic Design System for Piping, Air Conditioning Ducts, and Cable Trays in a Nuclear Power Plant Using AI

The quantity of piping, air conditioning ducts, cable trays in a Nuclear Power Plant is extremely large and currently takes a huge amount of time and cost to plan for the layout. In order to efficiently do the work, Hitachi is developing the AI Automatic Design System, that automatically designs the route of piping, air conditioning ducts, and cable trays in 3D model of an actual plant. The AI Automatic Design System enables automated design even with a small amount of learning data by applying a hybrid method that combines a program-based design rules, a route search program by Genetic Algorithm (GA), and AI by deep learning. Hitachi also studied the automatic mutual arrangement of piping, air conditioning ducts and cable trays to reduce the work of adjusting its arrangement. As a result, by using the system in the actual plant model, it was confirmed that the piping, air conditioning ducts, and cable trays were properly arranged according to the design rules. It is confirmed that applying AI Automatic Design System to actual plant model is possible.
From Commitment to Action: Filipino College Students' Involvement in Agriculture in Selected Provinces in the Philippines

This study determined which knowledge sharing and learning (KSL) intervention best fits agriculture and non-agriculture students in the Philippines, and documented each of the student groups' commitments to be intermediaries to farmers. Six months after the data had been gathered through survey method, the research team documented which KSL intervention each student group shared to others. The study also determined whether the students’ expressions of commitment had been concretized into action. Samples were randomly selected from higher education institutions in the Philippines, namely, Central Mindanao University in Bukidnon, Central Bicol State University of Agriculture in Camarines Sur, Father Saturnino Urios University in Agusan del Norte, and Camiguin Polytechnic State College. A total of 44 agriculture students and 59 non-agriculture students were compared. The study found that agriculture students involved themselves using their technical knowledge of information and communications technology (ICT)-based tools, whereas the other group of students employed nontechnical and practical ways to help their communities—specifically by encouraging people to save rice. Agriculture students reached more farmers than the non-agriculture students did. The results of this study could guide policymakers in developing policies that would enhance students’ involvement in agriculture.
The comparison of solar irradiance assessment at different terrain in west Malaysia

Solar energy is one of the renewable energies that is emerging in our country&apos;s development, in conjunction with the developing green technology effort. Environmental difficulties and the costly price of energy are two of the most concerning aspects of electrical power production. The primary goal of this study is to determine the optimal solar panel angle. The objectives are to achieve the goal to determine the maximum azimuth angle for solar panels in hilly and flat locations in Ampang, Malaysia, as well as to calculate the sun irradiance of solar panels at the chosen location. To maximise the overall output of electrical energy, the tilt angle of the fixed structure solar module was carefully analysed for various locations and periods. Two different locations in Ampang were analysed for observing the maximum input of solar irradiance which were in a hilly area of 3°10&apos;25.1&apos;&apos; N 101°47&apos;28.7&apos;&apos; E and a flat area of 3.1491° N, 101.7625° E. This study identified the maximum solar irradiance for generating solar energy at hilly area projected at 1333.56 W/m2 compared to a flat area that received at 942.67 W/m2. It gives a review of the critical indicators that the solar industry looked forward to when dealing with site selection or the potential for the development of new solar power plants. Ampang receives between 1273.43 W/m2 and 1333.56 W/m2 at hilly area, suggesting that the sky is clear, and the sun is shining brilliantly for a significant portion of the year.
Disparity map algorithm using census transform and hierarchical segment-tree from stereo image

This article presents a disparity map algorithm to improve the depth map estimation based on Census Transform and hierarchical segment tree on each block. Essentially, the framework applied is based on reconstructed through a series of consecutive techniques. The process produces the disparity map or depth map as a result. To generate a disparity or depth map, a four-stage taxonomy has been used. Technically, the generated map contains essential information that will be used in a variety of usage such as drone navigation, autonomous vehicle exploration and navigation, virtual reality and surface reconstruction. To produce an appropriate depth map, the structure need resilient to low texture, bare colour, and repetitive pattern regions in the input stereo image. The stereo matching algorithm presented in this study comprises of four steps: Cost Computation, Cost Aggregation, Optimization, and Post-Processing, all of which will refine the final disparity map. Based on the research and results analysed using the existing benchmarking evaluation method which is Middlebury Benchmark, the disparity produced indicates a relatively low inaccuracy of 5.61% for nonocc error and 8.92% for all error pixels. On average, it outperforms and has a greater impact or equivalent to other proposed work.
Brain capillary geometry development for multiscale modelling study

Due to low spatial resolution of functional magnetic resonance imaging (fMRI), mathematical modelling of human brain is usually developed in ischaemic stroke study in order to enhance the understanding of ischaemic stroke mechanism so that proper treatment plan can be decided to a particular stroke patient. A 3D brain geometry is developed in this project using AutoLISP, which is a programming language within AutoCAD. The objective of this project is to re-create the geometry developed by El-Bouri et al. by replacing the 1-dimensional line with 3-dimensional capillary which can be meshed for the simulation. Simulation of blood flow using Stokes&apos; cell equation is done in the 3D geometry in order to obtain effective hydraulic conductivity, K. Finally, the hydraulic conductivity obtained from the simulation is analysed and compared with previous work done by El-Bouri et al. Based on result in section 3, the initial geometry developed is further modified by adding few small cylinders and also bigger volume of the geometry with 15.21% percentage difference. Non-diagonal elements obtained in matrix K show non-zero values due to small voxel size used for the simulation (180µm), which should be increased to more than 250µm. The percentage difference of diagonal elements K 11, K 22, and K 33 are 8.05%, 2.65% and 21.43% respectively. The large percentage differences are probably due to additional volume added to the 3D geometry to maintain its periodicity with neighbouring voxels. Besides, meshing process and mesh size chosen are also contributing factor to the large percentage difference between both hydraulic conductivity values.
Sequential Monte Carlo in sequence

Reliability evaluation is one of the most needed in the reliability world, especially in the utility world. A stable network system needs to plan wisely to meet user demands. To make it to reality, it needs to check the reliability of the network system. In this research, Sequential Monte Carlo is part of the Monte Carlo Simulation and one of the most used techniques to check the reliability by including variance reduction in the simulation. There will be two cases present in this paper, Case A and Case B, and the simulation for each case set with a different number of sequences with a comparable percentage of variance reduction. The importance of the sequence will determine the accuracy of the simulations. The reliability indices SAIFI, SAIDI, and CAIDI can be used to compare simulation accuracy. The best simulation is when the reliability indices recorded small values, however the size of sample should be larger to get high accuracy. Thus, it shows that the variance reduction with five sequences has a more efficient simulation than the two sequences.
Literature Review: Teachers’ and Students’ Language Attitude Towards the Use of Indonesian Language in the Japanese-Speaking Classroom

This study aims to discover the variety and research trends for L1 language use in the L2 classroom. This study used library research or literature review to collect and process the data. The data originated from national and international articles, journals, and documents. Many sources have shown the result of the study stating that using a first language in learning a foreign language, especially in the speaking classroom, has made teachers and students get several positive attitudes. According to some research, the three characteristics of positive attitudes toward using the Indonesian language in the speaking classroom-language involve loyalty, language pride, and language awareness of norms that both teachers and students highlight. The two methodologies most commonly used in linguistic attitude studies are direct and indirect measures. The results of a survey of linguistic attitudes indicate whether or not students are effective at learning a language. Attitude is known, not innate. Students can improve their favourable language attitudes toward other languages through specific educational activities&#x0D; Keywords :&#x0D; Jurnal Pendidikan Bahasa Jepang Japanese Education JournalJapanese Speaking ClassroomJapanese Literature ReviewJapanese Studies
Poster Presentation: A Project-Based Integrated Language Learning to Enhance Soft Skills of Japanese Language Learners

This study investigates how Japanese language students view group poster presentations as a project-based integrated language learning process. Japanese language students in higher education must possess both the hard and soft skills necessary for the workplace in the twenty-first century. Therefore, developing Japanese language learning methods is necessary to enhance both learners' soft skills and Japanese proficiency. The project-based learning (PjBL) approach was carried out through a project assigned in the Speaking course, namely in group poster presentations. This research investigated students' perceptions after implementing poster presentation activities to develop their soft skills. The research data were collected using questionnaires, interviews with selected students, and observations during the 8-week project. The results of this study show that the Japanese language students respond favourably to the implementation of the group poster presentation project. Poster presentation activities encourage the students to practice their four Japanese language skills (listening, speaking, reading, and writing) in realistic communication. At the same time, these group project activities help the students understand the value of interpersonal skills, project management, critical thinking and problem-solving, teamwork, and communication skills in completing a project.&#x0D; Keywords :&#x0D; Jurnal Pendidikan Bahasa Jepang Japanese Education JournalJapanese Language LearningJapanese Poster PresentationJapanese Vocational Education