Reviewerly/exHarmony huggingface dataset:
A Survey on Design and Development of Flexibility and Controlling in Modern trend using Cloud Computing

Against the background of recent economic realities, certainly one of the bigger forces that is affecting businesses worldwide is cloud computing technology, whose advantages consist of agility, Cost savings, time to market, Competitive edge, time to capability, Flexibility, Sustainability, etc. The purpose of this study was to add to the body of knowledge that Might be implemented through researchers, IT organizations and businesses, alike to attain best results through focusing on factors of IT flexibility (connectivity, modularity, and compatibility) specific to cloud based services and solutions. The study findings provided statistical evidence that factors of IT flexibility (connectivity, modularity, and compatibility) specific to cloud computing have strong positive correlations on IT effectiveness. Also, the combination of three factors of IT flexibility, precise to cloud computing, explained 67% of the variance of IT effectiveness. The Connectivity factor predicted of IT effectiveness the most while the compatibility the less contribute to the prediction of IT effectiveness.
Understanding the Power of Evolutionary Computation for GPU Code Optimization

Achieving high performance for GPU codes requires developers to have significant knowledge in parallel programming and GPU architectures, and in-depth understanding of the application. This combination makes it challenging to find performance optimizations for GPU-based applications, especially in scientific computing. This paper shows that significant speedups can be achieved on two quite different scientific workloads using the tool, GEVO, to improve performance over human-optimized GPU code. GEVO uses evolutionary computation to find code edits that improve the runtime of a multiple sequence alignment kernel and a SARS-CoV-2 simulation by 28.9% and 29% respectively. Further, when GEVO begins with an early, unoptimized version of the sequence alignment program, it finds an impressive 30 times speedup–a performance improvement similar to that of the hand-tuned version. This work presents an in-depth analysis of the discovered optimizations, revealing that the primary sources of improvement vary across applications; that most of the optimizations generalize across GPU architectures; and that several of the most important optimizations involve significant code interdependencies. The results showcase the potential of automated program optimization tools to help reduce the optimization burden for scientific computing developers and enhance performance portability for domain-specific accelerators.
Use Mixed Precision Data Types to Speed up Computation for Ultrasound Imaging Software

Software-based ultrasound imaging systems send raw echo data acquired by the ultrasound transducer to a computer for processing and imaging. The computation is performed on Graphics Processing Units (GPUs) to process the enormous amount of streaming data, around 5GB/s, and generate images in real-time. Computation throughput is an important metric for such a system. In this paper, we have experimented the possibility of using mixed precision data types to speed up the computation for ultrasound imaging software on an Nvidia RTX 2060 GPU. Compared to using only single precision in the computation, the updated software can speed up imaging software by over 15% without sacrificing image quality. The benefit is from faster fused multiply-add (FMA) operations and reduced memory traffic. The improved computation capacity can also be used to improve the image quality.
Machine Learning Methods for Credit Card Fraud Detection

Machine learning is an innovative and efficient tool to prevent credit card fraud, however, given the variety of machine learning models, which model is the most suitable for fraudulent transaction predictions becomes a tough question to answer. In this research, a comprehensive evaluation method is borrowed to compare performances between different machine learning models. More precisely, this research uses the Area under the ROC Curve (AUC) metric to evaluate and compare performances between four different machine learning models with the same transaction information dataset. The four models are K Nearest Neighbor, Logistic Regression, Random Forest, and Support Vector Machine. In this research, a dataset that contains over one million credit card transaction data is processed and divided into training data and testing data. After preprocessing, the same training data are fitted into four different models and being test against the same testing data. After a series of hyperparameter tuning, the AUC score of each model is obtained and compared. The comparison result indicates that Random Forest makes the most accurate and consistent predictions on fraudulent transactions in this dataset, and thus can be recommended as the primary machine learning algorithm to prevent credit card fraudulent transactions.
Pelatihan Penyediaan Sabun Cuci Tangan Cair Bagi Warga RT 02 Dusun Rewulu Wetan, Godean, Yogyakarta

The Covid-19 pandemic has been going on since 2020. Efforts to improve health protocols are still being echoed. Washing hands with soap has become a new habit during this pandemic. There are many hand washing liquid soaps on the market, but it is relatively expensive. We need to find an effort to be able to get liquid soap at an economical price. This can be done by making your own hand washing liquid soap. Fulfilling the need for liquid hand washing soap is also important for residents of RT 02 in Rewulu Wetan, Sidokarto, Godean. Therefore, on March 28, 2021, a training was held on making hand-washing liquid soap for the residents of the hamlet. &#x0D; This training activity is to increase the knowledge of residents of RT 02, Rewulu Wetan about liquid hand soap and how to make it. Another goal is to get a cheaper liquid soap when compared to products on the market. This activity is expected to be a source of inspiration for participants to become entrepreneurs. The training was carried out by presenting the material by the resource persons. The activity continued with the practice of making liquid hand soap. The training closed with a discussion session with the trainees. The implementation of the training can run well and smoothly. The residents who attended were enthusiastic about receiving the material presented. This could be seen from the discussion about the training materials. The result of this training is an economical liquid hand soap.
A Contrastive Study of Hedges in COVID-19 Reports Selected from China Daily and The New York Times

Based on Jef Verschueren&amp;rsquo;s Adaptation Theory, Lakoff&amp;rsquo;s definition and Prince et al.&amp;rsquo;s classification of hedges, this paper takes New York Times and China Daily from January 23rd to April 8th, 2020 as corpus sources, randomly selects 39 COVID-19 reports, and makes a contrastive study of hedges among them, aiming at exploring the similarities and differences in the use of hedges in COVID-19 reports selected from Chinese and American mainstream newspapers and further revealing their influencing factors.
Corrections to “Pixel-Wise Ship Identification From Maritime Images via a Semantic Segmentation Model”

In the above article <xref ref-type="bibr" rid="ref1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[1]</xref> , we have found that the contents of <xref ref-type="table" rid="table1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Tables V</xref> and VI were same, while the detailed explanations (i.e., values used for evaluation model performance) for the two tables were correct. After carefully checking the final-accepted file uploaded to the submission system and the journal publication file, the abovementioned mix-up may be triggered by the incautious manuscript proof procedure. More specifically, the mix-up contents were only related with <xref ref-type="table" rid="table1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Table V</xref> , and did not affect other contents (e.g., Experiment and Conclusion sections) in the manuscript. The correct <xref ref-type="table" rid="table1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Table V</xref> content is provided as follows.
A software process improvement framework based on best practices

Abstract Software process improvement requires significant effort related not only to the identification of relevant issues and providing an adequate response to them, but also to the implementation and adoption of the changes. Best practices provide recommendations to software teams on how to address identified objectives in practice, based on aggregated experience and knowledge. In the paper, we present the GÉANT SPI framework based on best practices, together with the collected experience from the process of adopting the best practices.
Application of Population Data Collection in Padasuka Village, Bandung Regency, Based on Website

Padasuka Sub-region in Cimenyan District, Bandung Regency tries to give populace organization and common enlistment administrations to the local area as per the standards of the Service Standard Guidelines. To work on the nature of administration, it is important to have an assistance framework in the kelurahan so it can work with the presentation of specialist co-ops in sub-district and further develop the help nature of the mechanical assembly into a modernized framework and work with information assortment/chronicling of populace organization. information. The subsequent framework can be utilized to perform automated information assortment
Developing M-Learning Applications to Support Digital Literacy of Vocational High School Students

Abstrak:Â Literasi digital sangat penting untuk diterapkan saat ini karena pembelajaran telah mengarah pada pembelajaran yang mendukung teknologi. Literasi digital di Indonesia masih tergolong sangat rendah sehingga perlu upaya dalam meningkatkannya. Penelitian ini bertujuan untuk mengembangkan aplikasi m-learning berbasis Android yang tepat untuk mendukung literasi digital siswa SMK. Jenis metode yang digunakan yakni penelitian dan pengembangan (R&amp;D) dengan model ADDIE. Hasil penelitian ini menunjukkan bahwa pengembangan media sudah sesuai dengan kriteria baik materi maupun media yang menunjukkan hasil 3,67 yang kategori â€œbaikâ€, sementara hasil pada uji media sebesar 4,05 yang kategori â€œsangat baikâ€ dan pada uji coba kelas 3,92 yang kategorinya â€œbaikâ€. Aplikasi ini juga, terbukti efektif untuk digunakan dalam mendukung literasi digital siswa yang ditandai dengan meningkatnya hasil belajar siswa dari rata-rata pretest 66 menjadi 78 pada postestnya. Sehingga dapat disimpulkan dari hasil penelitian ini memberikan kontribusi dalam mendukung literasi digital peserta didik vokasi.Â Abstract:Â Digital literacy is very important to apply at this time because learning has led to learning that supports technology. Digital literacy in Indonesia is still very low, so efforts are needed to increase it. This study aims to develop appropriate Android-based m-learning applications to support digital literacy in vocational high school students. The type of method used is research and development (R&amp;D) with the ADDIE model. The results of this study indicate that media development is in accordance with the criteria for both material and media which shows a result of 3.67 which is in the "good" category, while the results in the media test are 4.05 which is in the "very good" category and in class trials 3.92 in the "good" category. This application has also proven to be effective for use in supporting students' digital literacy which is marked by increased student learning outcomes from an average pretest of 66 to 78 in the posttest. So it can be concluded from the results of this study that it contributes to supporting the digital literacy of vocational students.Â
Evaluasi User Experience Dalam Aspek Usability Pada Aplikasi Android Edukasi Literasi Matematika

Currently, user experience has becomes an important thing in software development. Few users reportedly has left the application as a result of bad experience that occurs to them. Usability as one of the sub aspect of user experience that play role as a indicator level of how easy user using application is being evaluated in this study. Perceptual difference due to gender and character of children became the choosen topic, so this study aims to determine the significant effect of gender from elementary school students on the results of the usability evaluation that conducted. The application tested in this study is an android-based application called PrismaKu which is present as a smart solution to improve the mathematical literacy skills of elementary school students in Indonesia. This research method refers to previous method named research learning spiral method which is carried out in one cycle. Tests were conducted to measure the duration of each task and application ease of use assessment using the System Usability Scale (SUS). Based on the research results, there are no significant effect of gender from elementary school students on the results of usability neither duration of each task nor system usability scale score. Nevertheless, score and duration show difference as viewed from numerical and descriptive perspective.
Development and Testing of Performance Scale Application as an Effective Electronic Tool to Enhance Students’ Academic Achievements

Performance scale application (PSA) usage in the classroom is underutilized, despite the rapid progress of mobile phone and e-learning technology. Lack of self-learning, evaluation, satisfaction, and inability to choose appropriate specialties influence students’ academic achievement in secondary school. The objective of this study is to investigate the development and testing of PSA on students’ learning achievement in secondary school. The PSA was developed on the Android mobile operating system using the extra trees regression algorithm to predict student achievement in secondary school. Students in the 11th grade basic specialty were considered. Three specialties were used, namely scientific, literary, and industry. The variables examined include improving evaluation (IME), improving communication (IMC), improving scientific (IMSC), and satisfaction of learning (SOL). The findings demonstrated that the PSA accurately predicted the students’ choice of specialty, IMC, IMSC, SOL, personalized learning (L), distance L, mobile L, self L, and specialty L. The findings also indicated a positive and significant effect of the PSA on students’ learning achievement. This validates that the extra trees regression is an effective tool for the development of PSA. In conclusion, the PSA has efficiently predicted the choice of specialties and academic achievements of students in secondary schools.
Scientific discussion on the construction process of rammed earth walls of Hakka dwellings

The strength and construction influencing factors of rammed earth wall materials for Hakka dwellings are scientifically explored. Based on the research of improving the accuracy of the test, the working principle of rebound meter and the relationship between the strength of rammed earth walls in different periods and parts were fully considered, and the strength test curve of rammed earth walls was obtained by increasing the displacement of the elastic rod end of the rebound meter. Through field research and on-site measurement, the applicability of the improved rebound meter was verified, and it was also shown that the strength of rammed earth walls of Hakka traditional dwellings is low, ranging from 0.44 to 0.55 Mpa, and the strength and durability of the walls can be improved by improving the formula and increasing the number of plate rams on both sides. The method also provides a basis for the daily inspection of the protection of the walls of Hakka dwellings and helps to further improve the protection measures of the dwellings.
A Vietnamese benchmark for vehicle detection and real-time empirical evaluation

The current situation of traffic in Vietnam has many outstanding problems, especially traffic congestion, since the supply of infrastructure has often not been able to keep up with the growth in mobility. Thus, proposing monitoring plans to support authorities to make suitable and prompt decisions has always received large attention from the community. Meanwhile, applying information technology, especially advanced models which could process or analyze traffic data in real time is recently considered to be a priority solution due to the time, accuracy, and cost saving that it can potentially achieve. Therefore, this paper outlines research on three advanced real-time object detection methods: YOLOX, YOLOF, and YOLACT and the development of the newest Vietnamese traffic dataset named UIT-VinaDeveS22. The work contains both theoretical and empirical analysis, which are expected to create premises for further studies into addressing problems such as traffic density management, traffic separation, and traffic congestion.
Sensorimotor confidence for tracking eye movements

Accurate and precise eye movements are important for visual perception. Yet, both saccades and smooth-pursuit are affected by sensory and motor noise, and are constrained by limited processing time. Can observers report the degree of accuracy in their eye movements, despite typically being unaware of the eye’s constant movement? To investigate this question, we measured sensorimotor confidence for tracking of unpredictably moving targets that elicited both saccades and smooth-pursuit behaviour. We define sensorimotor confidence as the subjective evaluation of task performance that should take into account sensory and motor uncertainty as well as the sensorimotor goal (e.g., maximise tracking accuracy). We asked human observers to track the centre of a noisy dot cloud with their eyes as it moved horizontally. The trajectory followed a sum of sinusoids (average speed: 9 deg/s). There were 20 unique trajectories, repeated 12 times each, half with direction reversed, presented in a randomised order. After 6 seconds of tracking, observers reported if they thought their tracking performance was better or worse than their estimated average performance in the task. From these sensorimotor confidence judgments, we computed their metacognitive sensitivity, the ability to classify objectively better from objectively worse performance, using an ROC-style analysis (Locke et al., 2020, Cognition). Metacognitive sensitivity was significantly above chance-level (area-under-the-curve of 0.50) for the group, however only marginally so (mean and SEM: 0.56 ± 0.02, n = 7). Investigating the individual repeated trajectories by performing a median-split of the objectively better versus worse repeats, all observers were on average more likely to report “better” for the better half of repeats. Together these results suggest humans have marginal metacognitive sensitivity for tracking eye movements. This limited access to sensorimotor uncertainty may be the cost for humans to make fast and accurate eye movements.
The role of expectations in embodiment and presence

Virtual reality (VR) became an influential tool in vision science. One challenge is to create virtual environments that are experienced as realistic. This depends on two key factors: The experience of oneself as spatially belonging to the virtual environment (presence) and of being represented by an avatar (embodiment). It is commonly believed that visuospatial asynchrony of body movements diminishes embodiment. Embodiment and presence have frequently been assessed by the participants’ reaction to threat against the avatar. The validity of such measures has recently been questioned showing that participants can become aware of the research hypotheses, termed demand characteristics. This can lead to changes in participants’ experiences, which are in accordance with researcher’s expectations. Here, we conducted an experiment to test this claim by comparing participants’ ratings in an online experiment to the responses in a VR experiment. In the online experiment, participants watched a video of a person performing the VR experiment combined with the virtual scene they saw. Participants rated their expected embodiment and presence sensations on the same questionnaire in the online and VR experiment. We manipulated movement synchrony (synchronous, asynchronous) and avatar visibility (visible, invisible), and introduced a threat to the avatar (height exposure, control) after each condition. If ratings in both experiments are equivalent, then demand characteristics contribute to the results. As shown in previous studies, participants correctly judged the direction of expected experimental effects. However, ratings in the online and VR experiment differed in size. As compared to the online experiment, ratings in the VR experiment were higher for synchronous movements (only for embodiment), and lower when an avatar was visible. Our results suggest that demand characteristics can only partly explain embodiment and presence as assessed by questionnaires. Additionally, they show the need to control for demand characteristics in future studies examining embodiment and presence.
Combining Services Computing Systems Engineering Framework and Scrum for Agile Development

Services Computing Systems Engineering (SCSE) Framework is an engineering framework or methodology for building service computing systems based on Service Oriented Architecture (SOA). Flexibility and ease of making changes are the advantages offered by SOA. It is also provided by the software development process with the Scrum framework in Agile software development. By using the SCSE framework, the service computing development process runs sequentially from the beginning to the end of the process in one cycle timeline. These guides are excellent for developing systems with obvious requirements and are released in one cycle. However, for services computing that requires fast release, following the guidelines in the SCSE Framework is hard to achieve. Modifications are needed to use the framework in agile system development so that development can be carried out quickly and with multiple releases. This research will be a starting point for combining SCSE with Scrum to produce a new framework that takes advantage of both. The main objective of this research is to determine how SCSE can be used in an agile development environment to produce a service computing system with fast delivery. The research methodology we use is Design Science Research Methodology (DSRM). A system development project has been tested using the proposed framework for one initial release with good results. A survey with the quantitative result has also been conducted among several stakeholders in system development to evaluate the proposed framework. As a result of this study, a framework is proposed to guide system development in an agile manner for creating services computing systems.