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International Conference on Applied System Innovation (ICASI)

作者： Wen-Chuan Wu Ming-Han Lee Dep. of Computer Science and Information Engineering National Ilan University Yilan City Taiwan R.O.C. Master Program of E-Learning for Multimedia and Network Communications National Ilan University Yilan City Taiwan R.O.C.

ISBN: (数字)9798350394924

ISBN: (纸本)9798350394931

Digital content industry, encompassing areas such as digital games, computer animation, digital audio-visual applications, and digital art, plays a pivotal role in today's and future developmental trends. Maya 3D software stands out as a crucial development tool in these domains. However, the multitude of built-in tools in Maya 3D can lead to overly complex interfaces, impacting development efficiency for software developers. To address this issue, this paper designs a digital toolkit for Maya 3D software, presented in a Menu Bar format. This toolkit offers features like naming, sorting, categorization, and automatic saving to JSON files for future use. Through a crossover experimental design, this paper investigates the impact of this proposed toolkit on 3D software developers' individual work performance, work engagement, and stress perception. Results shows a significant positive influence of that toolkit on software developers, particularly in enhancing work performance. It means that the proposed digital toolkit effectively improves the performance of software developers' work and reduces their stress during the software development process.

关键词： Industries Technological innovation Three-dimensional displays Market research Software Stress Software development management

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Energy-efficient Trajectory Planning with Media Transition for a Hybrid Unmanned Aerial-Underwater Vehicle

Energy-efficient Trajectory Planning with Media Transition f...

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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Pedro M. Pinheiro Armando Alves Neto Douglas G. Macharet Paulo L. J. Drews NAUTEC Center for Computational Science Universidade Federal do Rio Grande - FURG Rio Grande Brazil Dept. of Electronics Engineering Univ. Federal de Minas Gerais Belo Horizonte Brazil Dep. of Computer Science Computer Vision and Robotics Laboratory (VeRLab) Univ. Federal de Minas Gerais Belo Horizonte Brazil

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Vehicles capable of operating in more than one environment have been developed to solve real problems. Among them, the hybrid unmanned aerial-underwater vehicle (HUAUV) is receiving attention from the robotics community, mainly with a quadrotor-like configuration. However, this vehicle presents high energy consumption because of the larger mass required compared to the only aerial vehicle, limiting its autonomy. This work addresses the trajectory planning problem for a HUAUV. The method is based on Rapidly-exploring Random Trees (RRTs), a highly customizable planning technique. In addition, we propose two new heuristics to increase the energy efficiency of the hybrid vehicle. The first consists of biasing the tree expansion towards the environment with the lowest navigation cost, while the second one assigns estimated costs to nodes in the tree and chooses the least expensive trajectories. These techniques are evaluated in physically realistic simulation experiments performed in 135 scenarios. A comparative analysis of their performances is presented relative to the state of the art. We show that using efficient heuristics can significantly contribute to reducing energy consumption and even increase the average velocity in the missions performed by these vehicles.

关键词： Energy consumption Costs Limiting Trajectory planning Navigation Media Energy efficiency Trajectory Planning Intelligent robots

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An Analysis of Haskell Parallel Programming Model in the HaLVM 4

An Analysis of Haskell Parallel Programming Model in the HaL...

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4th International Conference on Computing and Applied Informatics 2019, ICCAI 2019

作者： Cheon, Junseok Kim, Yeoneo Hur, Taekwang Byun, Sugwoo Woo, Gyun Dep. of Electrical and Computer Engineering Pusan National University Korea Republic of Dep. of Computer Science Kyungsung University Korea Republic of Smart Control Center of LG Electronics Korea Republic of

Recently, cloud computers are widely used due to the development of computing environment and network speed. Unikernel is considered to be an attractive operating system in the manycore environment that effectively provides cloud computers. HalVM is a unikernel coded in Haskell. In this paper, we analyze the performance of Haskell running in a unikernel, which has shown good parallel programming performance in a manycore environment. In this paper, we analyze the performance of Haskell running in a unikernel, while Haskell has shown good performance in a manycore environment. To do this, we select HaLVM as the target operating system and analyze the performance by testing various Haskell parallel programming models. Test result shows that HaLVM is scalable only on IVC. We also implement a library to make programming with IVC more convenient, and use this library to compare extensibility experiments. Our test shows HaLVM's scalability is 112.42% higher than Linux environment. © Published under licence by IOP Publishing Ltd.

关键词： computer operating systems

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SSAM: A Haskell Parallel Programming STM Based Simple Actor Model 4

SSAM: A Haskell Parallel Programming STM Based Simple Actor ...

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4th International Conference on Computing and Applied Informatics 2019, ICCAI 2019

作者： Kim, Y. Cheon, J. Hur, T. Byun, S. Woo, G. Dep. of Electrical and Computer Engineering Pusan National University Korea Republic of Dep. of Computer Science Kyungsung University Korea Republic of Smart Control Center of LG Electronics Korea Republic of

As computers with manycore architecture are being widely spread, parallel programming becomes a pending issue. While parallel programming has been a challenging issue, Haskell is known to be of the best available one. The immutability and declarative nature of Haskell suit well the need for parallelism. In our previous work, we implemented the SAM, a parallel programming model based on Haskell. In this paper, we propose the SSAM, an updated version of SAM, by solving the performance overhead of SAM socket. We discuss the architecture of SSAM and its major functions and show the 14% scalability upgrade in a performance test. © Published under licence by IOP Publishing Ltd.

关键词： Parallel programming

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Vegetation and Drought Trends in Sweden's Mälardalen Region-Year-on-Year Comparison by Gaussian Process Regression

Vegetation and Drought Trends in Sweden's Mälardalen Region...

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2020 Swedish Workshop on Data science, SweDS 2020

作者： Paszkowsky, Nuria Agues Brannvall, Rickard Carlstedt, Johan Milz, Mathias Kovacs, Gyorgy Liwicki, Marcus Unit for Data Center Systems and Applied Data Science Research Institutes of Sweden Sweden Luleå University of Technology Dep. of Computer Science Electrical and Space Engineering Sweden

ISBN: (纸本)9781728192048

This article describes analytical work carried out in a pilot project for the Swedish Space Data Lab (SSDL), which focused on monitoring drought in the Mälardalen region in central Sweden. Normalized Difference Vegetation Index (NDVI) and the Moisture Stress Index (MSI)-commonly used to analyse drought- A re estimated from Sentinel 2 satellite data and averaged over a selection of seven grassland areas of interest. To derive a complete time-series over a season that interpolates over days with missing data, we use Gaussian Process Regression, a technique from multivariate Bayesian analysis. The analysis show significant differences at 95% confidence for five out of seven areas when comparing the peak drought period in the dry year 2018 compared to the corresponding period in 2019. A cross-validation analysis indicates that the model parameter estimates are robust for temporal covariance structure (while inconclusive for the spatial dimensions). There were no signs of over-fitting when comparing in-sample and out-of-sample RMSE. © 2020 IEEE.

关键词： Remote sensing

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Using Hybrid Scheduling Algorithms For Solving Blockchain Allocation On Cloud

arXiv

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arXiv 2021年

作者： El-Dosuky, Mohammed A. Eladl, Gamal H. Computer Science Dep Faculty of Computer and Info Mansoura University Egypt Computer Science Dep. Arab East Colleges Riyadh Saudi Arabia Information Systems Dep Faculty of Computer and Info Mansoura University Egypt

Companies are rushing to deliver their services and solutions through the cloud. The scheduling process is very critical in reducing delays. Scheduling also has a role in accessing resources without excessive waiting time. All this in context of modern advances in infrastructure and the emergence of Blockchain-as-a-service. What if integration is done between a hybrid scheduling algorithm and blockchain technology via the cloud. This integration aims to enhance and provide the service uninterruptedly. This method is distinguished, compared to other scheduling algorithms such as shortest-job-first and priority scheduling, that it does not suffer from starvation and it has a balanced load on resources. Based on analytical performance, the proposed hybrid scheduling has the markable result. © 2021, CC BY.

关键词： Scheduling

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TAXINOMISIS: A cloud – based platform for risk profiling and patient specific management of the carotid artery disease

TAXINOMISIS: A cloud – based platform for risk profiling an...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Vassilis D. Tsakanikas Panagiotis K. Siogkas Vassiliki T. Potsika Antonis I. Sakellarios Dimitris S. Pleouras Vassiliki I. Kigka Themis P. Exarchos Igor B. Koncar Dimitrios I. Fotiadis Dep. of Materials Science and Engineering Unit of Medical Technology and Intelligent Information Systems University of Ioannina Ioannina GR Greece Unit of Medical Technology and Intelligent Information Systems University of Ioannina Ioannina Greece Biomedical Research Institute Foundation for Research and Technology Hellas (FORTH)

Carotid Artery Disease is a complex multi-disciplinary medical condition causing strokes and several other disfunctions to individuals. Within this work, a cloud - based platform is proposed for clinicians and medical doctors that provides a comprehensive risk assessment tool for carotid artery disease. It includes three modeling levels: baseline data-driven risk assessment, blood flow simulations and plaque progression modeling. The proposed models, which have been validated through a wide set of studies within the TAXINOMISIS project, are delivered to the end users through an easy-to-use cloud platform. The architecture and the dep.oyment of this platform includes interfaces for handling the electronic patient record, the 3D arterial reconstruction, blood flow simulations and risk assessment reporting. TAXINOMISIS, compared with both similar software approaches and with the current clinical workflow, assists clinicians to treat patients more effectively and more accurately by providing innovative and validated *** Relevance - Asymptomatic carotid artery disease is a prevalent condition that affects a significant portion of the population, leading to an increased risk of stroke and other cardiovascular events. Early detection and appropriate treatment of this condition can significantly reduce the risk of adverse outcomes and improve patient outcomes. The development of a software tool to assist clinicians in the assessment and management of asymptomatic patients with carotid artery disease is therefore of great clinical relevance. By providing a comprehensive and reliable assessment of the disease and its risk factors, this tool will enable clinicians to make informed decisions regarding patient management and treatment. The impact of this tool on patient outcomes and the reduction of healthcare costs will be of great importance to both patients and the healthcare system.

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A heuristic model to identify organizational collaborative critical success factors (CSFs) 5

A heuristic model to identify organizational collaborative c...

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5th International Young Engineers Forum in Electrical and computer engineering, YEF-ECE 2021

作者： Nunes, Marco Abreu, Antonio Bagnjuk, Jelena D’Onfrio, Vanessa Saraiva, Celia Dep.of Mechanical Engineering University of Beira Interior Covilha Portugal Center of Technology and Systems CTS Uninova Costa da Capatica Portugal Health Management UKE Hamburg Germany Dep.of Project Management Life Science Nord Hamburg Germany Dep. of Digital Services NMQ Digital Lisbon Portugal

ISBN: (纸本)9781665412643

It is often argued that efficient inter and intra organizational collaboration is a major critical success factor to drive organizational performance and innovation. However, according to several research, isn’t always clear to organizations to identify and distinguish which factors really drive to success, namely in the collaborative dimension, where the myriad of hidden dynamic interactions between organizational entities triggered by the mix of formal and informal relationships, more often than not, may lead to misinterpret of the reality. Furthermore, organizations often argue that the lack of proper models to guide and support collaborative partnerships, is the major unbreakable barrier that shifts them from engaging more frequent in such collaborative initiatives. In this work is proposed a heuristic model developed under three key organizational areas ((1) collaborative networks, (2) project management, and (3) social network analysis), that in a holistic way identifies and quantitatively measures the myriad of organizational dynamic interactions (collaborative behaviors) to identify organizational collaborative critical success factors (CSFs), by analyzing collaborative data generated by organizations as they execute projects tasks and activities. A case study is illustrated to show the modeĺs implementation and application, and the benefits for organizations. © 2021 IEEE.

关键词： Project management

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Machine Learning Approach to Detection of Offensive Language in Online Communication in Arabic 1

Machine Learning Approach to Detection of Offensive Language...

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1st IEEE International Maghreb Meeting of the Conference on sciences and Techniques of Automatic Control and computer engineering, MI-STA 2021

作者： Alakrot, Azalden Fraifer, Muftah Nikolov, Nikola S. The College of Medical Technology Department of Information Technology Yefren Libya The College of Industrial Technologies-CIT Department of Electronic Engineering Misurata Libya University of Limerick Dep. of Computer Science and Information System Limerick Ireland

ISBN: (纸本)9781665418560

This paper presents the results of several machine learning experiments, conducted with a dataset of YouTube comments in Arabic. The experiments aim at studying the impact of various text preprocessing, feature-extraction and feature-selection techniques on the accuracy of a document classifier for detection of offensive language in online communication in Arabic. Regarding data pre-processing, our experiments focus on filtering out noisy characters and normalising inconsistencies present in casual online writing in Arabic. The combined effect of these data preprocessing techniques and a few feature-extraction and feature-selection methods is then evaluated by training document classifiers. Our results give evidence that it is possible to train a classifier for the detection of offensive language on Arabic social media with reasonable overall accuracy of 0.84, and precision, recall and F1-score of 0.89, 0.76 and 0.81, respectively. © 2021 IEEE.

关键词： Support vector machines

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Trust your neighbors: A comprehensive survey of neighborhood-based methods for recommender systems

arXiv

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arXiv 2021年

作者： Nikolakopoulos, Athanasios N. Ning, Xia Desrosiers, Christian Karypis, George Amazon Seattle United States Biomedical Informatics Computer Science and Engineering Dep. The Ohio State University Columbus United States Software Engineering and IT Dep. École de Technologie Supérieure Montreal Canada Computer Science & Engineering Dep. University of Minnesota Minneapolis United States

Collaborative recommendation approaches based on nearest-neighbors are still highly popular today due to their simplicity, their efficiency, and their ability to produce accurate and personalized recommendations. This chapter offers a comprehensive survey of neighborhood-based methods for the item recommendation problem. It presents the main characteristics and benefits of such methods, describes key design choices for implementing a neighborhood-based recommender system, and gives practical information on how to make these choices. A broad range of methods is covered in the chapter, including traditional algorithms like k-nearest neighbors as well as advanced approaches based on matrix factorization, sparse coding and random walks. Copyright © 2021, The Authors. All rights reserved.

关键词： Recommender systems

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