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SSRN 2023年

作者： Morand, Victor Müller, Nils Weightman, Ryan Keimer, Alexander Piccoli, Benedetto Bayen, Alexandre M. Ecole Polytechnique Palaiseau France Department of Electrical Engineering and Computer Science University of California BerkeleyCA United States Max Planck Institute for Software Systems Saarland Informatics Campus Germany Max Planck Institute for Intelligent Systems Germany Department of Mathematics Rutgers University NJ United States Department of Mathematics FAU Erlangen-Nürnberg Germany

In this contribution, we study the numerical approximation of scalar conservation laws by computational optimization of the numerical flux function in a first-order finite volume method. The cell-averaging inherent to finite volume schemes presents a challenge in the design of such numerical flux functions toward achieving high solution accuracy. Dense neural networks, as well as (piecewise) polynomials, serve as function classes for the numerical flux. Using a parametrization of such a function class, we optimize the numerical flux with respect to its solution accuracy on a set of Riemann problems for which we have closed-form solutions. By design, our resulting first-order finite volume schemes are *** show empirically that the proposed schemes can achieve higher accuracy than the Godunov and EnquistOsher method on a wide range of *** proposed method can be applied to the inverse problem, i.e., the data-driven synthesis of macroscopic physical laws for real-world flux phenomena. © 2023, The Authors. All rights reserved.

关键词： Finite volume method

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Don’t Forget the Exception! : Considering Robustness Changes to Identify Design Problems

Don’t Forget the Exception! : Considering Robustness Change...

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International Mining software Repositories, MSR

作者： Anderson Oliveira João Correia Leonardo Sousa Wesley K. G. Assunção Daniel Coutinho Alessandro Garcia Willian Oizumi Caio Barbosa Anderson Uchôa Juliana Alves Pereira Informatics Department – Pontifical Catholic University of Rio de Janeiro (PUC-Rio) Rio de Janeiro Brazil Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh United States Institute of Software Systems Engineering Johannes Kepler University (JKU) Linz Austria Federal University of Ceará (UFC) Itapajé Brazil

Modern programming languages, such as Java, use exception-handling mechanisms to guarantee the robustness of software systems. Although important, the quality of exception code is usually poor and neglected by developers. Indiscriminate robustness changes (e.g., the addition of empty catch blocks) can indicate design decisions that negatively impact the internal quality of software systems. As it is known in the literature, multiple occurrences of poor code structures, namely code smells, are strong indicators of design problems. Still, existing studies focus mainly on the correlation of maintainability smells with design problems. However, using only these smells may not be enough since developers need more context (e.g., system domain) to identify the problems in certain scenarios. Moreover, these studies do not explore how changes in the exceptional code of the methods combined with maintainability smells can give complementary evidence of design problems. By covering both regular and exception codes, the developer can have more context about the system and find complementary code smells that reinforce the presence of design problems. This work aims to leverage the identification of design problems by tracking poor robustness changes combined with maintainability smells. We investigated the correlation between robustness changes and maintainability smells on the commit history of more than 160k methods from different releases of 10 open-source software systems. We observed that maintainability smells can be worsened or even introduced when robustness changes are performed. This scenario mainly happened for the smells Feature Envy, Long Method, and Dispersed Coupling. We also analyzed the co-occurrence between robustness and maintainability smells. We identified that the empty catch block and catch throwable robustness smells were the ones that co-occurred the most with maintainability smells related to the Concern Overload and Misplaced Concern design problems. T

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The untold story of code refactoring customizations in practice

The untold story of code refactoring customizations in pract...

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International Conference on software engineering (ICSE)

作者： Daniel Oliveira Wesley K. G. Assunção Alessandro Garcia Ana Carla Bibiano Márcie Ribeiro Rohit Gheyi Baldoino Fonseca Informatics Department Pontifical Catholic University of Rio de Janeiro (PUC-Rio) Rio de Janeiro Brazil Institute of Software Systems Engineering - Johannes Kepler University (JKU) Linz Austria Computing Institute - Federal University of Alagoas (UFAL) Maceió Brazil Department of Computing and Systems Federal University of Campina Grande (UFCG) Campina Grande Brazil

Refactoring is a common software maintenance practice. The literature defines standard code modifications for each refactoring type and popular IDEs provide refactoring tools aiming to support these standard modifications. However, previous studies indicated that developers either frequently avoid using these tools or end up modifying and even reversing the code automatically refactored by IDEs. Thus, developers are forced to manually apply refactorings, which is cumbersome and error-prone. This means that refactoring support may not be entirely aligned with practical needs. The improvement of tooling support for refactoring in practice requires understanding in what ways developers tailor refactoring modifications. To address this issue, we conduct an analysis of 1,162 refactorings composed of more than 100k program modifications from 13 software projects. The results reveal that developers recurrently apply patterns of additional modifications along with the standard ones, from here on called patterns of customized refactorings. For instance, we found customized refactorings in 80.77% of the Move Method instances observed in the software projects. We also investigated the features of refactoring tools in popular IDEs and observed that most of the customization patterns are not fully supported by them. Additionally, to understand the relevance of these customizations, we conducted a survey with 40 developers about the most frequent customization patterns we found. Developers confirm the relevance of customization patterns and agree that improvements in IDE's refactoring support are needed. These observations highlight that refactoring guidelines must be updated to reflect typical refactoring customizations. Also, IDE builders can use our results as a basis to enable a more flexible application of automated refactorings. For example, developers should be able to choose which method must handle exceptions when extracting an exception code into a new method.

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University Distributed Computer Network Vulnerability Assessment

University Distributed Computer Network Vulnerability Assess...

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Smart Information systems and Technologies (SIST), IEEE International Conference on

作者： Valerii Lakhno Volodimir Malyukov Bakhtyzhan Akhmetov Bagdat Yagaliyeva Olena Kryvoruchko Alona Desiatko Department of Computer Systems Networks and Cybersecurity National University of Life and Environmental Sciences of Ukraine Kyiv Ukraine Department of Informatics and Informatization of Education Abai Kazakh National Pedagogical University Almaty Kazakhstan Department of Computer Sciences Yessenov University Aktau Kazakhstan Department of Software Engineering and Cybersecurity State University of Trade and Economics Kyiv Ukraine

A methodology for evaluating information security (IS) for a distributed computer network (DCN) of a university (hereinafter referred to as UDCN) has been proposed. A mathematical model for calculating the UDCN vulnerability factor has been presented. The UDCN vulnerability coefficient makes it possible to assess its IS level at the UDCN design stage. The results of simulation modeling and virtualization of IS UDCN components have also been presented. In the course of simulation modeling, a model of a protected UDCN was designed and tested. In the experimental UDCN model, the network devices selected in the course of modeling the vulnerability coefficient were emulated on virtual machines (VMs). UDCN resources were reproduced using the Proxmox VE virtualization system. On the UDCN hosts running PVE, the Suricata Intrusion Detection System (IPS) was used. Splunk was used as SIEM.

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Energy Efficiency Improvement System for AC Circuits

Energy Efficiency Improvement System for AC Circuits

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IEEE NW Russia Young Researchers in Electrical and Electronic engineering Conference (EIConRusNW)

作者： Vladimir Kulagin Kirill Selivanov Andrey Vlasov Dmitrii Aminev Lyudmila Bunina Sergey Bikovsky Moscow technical university of communications and informatics Moscow Russian Federation Department of Design and Technology of Electronic Devices Bauman Moscow State Technical University BMSTU Moscow Russian Federation Department of Development of software solutions and system programming Russian Technological University – MIREA Moscow Russian Federation Department of Electrical Engineering Systems Russian Technological University – MIREA Moscow Russian Federation

The problem of the rational use of energy resources remains constantly relevant and requires the search for new approaches. One of them is power control. In AC circuits, the authors see the most promising method of phase AC power control. Based on it, a power control module was developed. The structural and circuit diagrams of the developed device are presented to implement the proposed solution. The authors produced its experimental prototype and conducted experimental testing at various levels of regulated power. Savings when using the proposed power control module were calculated using the example of energy consumption in various sectors of energy-intensive systems. According to the data obtained, the module allows saving energy consumption without significant discomfort to the energy user. The calculated results allow concluding that the proposed AC power control module is fully operational, and its widespread use will significantly reduce the need for electricity.

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Expert Evaluation of Main Measures Proposed for Human Resources Rational Usage for Region Competitiveness Improvement

Expert Evaluation of Main Measures Proposed for Human Resour...

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International Science and Technology Conference FarEastCon, 2021

作者： Kenzhin, Z.B. Zolkin, A.L. Aygumov, T.G. Poskryakov, I.A. West Kazakhstan Agrarian and Technical University Named After Zhangir Khan Uralsk090009 Kazakhstan Computer and Information Sciences Department Povolzhskiy State University of Telecommunications and Informatics Samara443010 Russia Department of Computer Engineering Software and Automated Systems Dagestan State Technical University Makhachkala367000 Russia Department of Transport Economic and Management Federal State Autonomous Educational Institution for Higher Education Russian Transport University Moscow127994 Russia

ISBN: (纸本)9789811688287

A process of expert evaluation of actions based on complex methodology is reviewed in this article. The methods of questionnaire, expert evaluations, multi-variation problem of optimal alternative were used. Authors explained the methods of expert evaluations, e.g. Delphi method, as the good forecasting tool for region competitiveness improvement measures based on achievement of optimal balance of supply and demand of human resources. As a result of applied methodology, the main measures for rational usage of human resources in region competitiveness improvement were selected. Application of obtained results and proposed methodology allows to improve the region economic management. Authors came to the conclusion that measures for development of human resources as region competitive advantage are referred to quality education, healthcare, effective migration policy as base for labour efficiency improvement and reducing the shortage of skilled manpower. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Personnel

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Unleashing the Power of Multi-Task Learning: A Comprehensive Survey Spanning Traditional, Deep, and Pretrained Foundation Model Eras

arXiv

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arXiv 2024年

作者： Yu, Jun Dai, Yutong Liu, Xiaokang Huang, Jin Shen, Yishan Zhang, Ke Zhou, Rong Adhikarla, Eashan Ye, Wenxuan Liu, Yixin Kong, Zhaoming Zhang, Kai Yin, Yilong Namboodiri, Vinod Davison, Brian D. Moore, Jason H. Chen, Yong Department of Computer Science and Engineering Lehigh University United States Department of Biostatistics Epidemiology and Informatics University of Pennsylvania United States Department of Industrial and Systems Engineering Lehigh University United States Department of Statistics University of Missouri United States School of Software Shandong University China Department of Computer Science University of Hong Kong Hong Kong Department of Computer Science and Engineering South China University of Technology China Department of Community and Population Health Lehigh University United States Department of Computational Biomedicine Cedars-Sinai Medical Center United States

Multi-Task Learning (MTL) is a learning paradigm that effectively leverages both task-specific and shared information to address multiple related tasks simultaneously. In contrast to Single-Task Learning (STL), MTL offers a suite of benefits that enhance both the training process and the inference efficiency. MTL's key advantages encompass streamlined model architecture, performance enhancement, and cross-domain generalizability. Over the past twenty years, MTL has become widely recognized as a flexible and effective approach in various fields, including computer vision, natural language processing, recommendation systems, disease prognosis and diagnosis, and robotics. This survey provides a comprehensive overview of the evolution of MTL, encompassing the technical aspects of cutting-edge methods from traditional approaches to deep learning and the latest trend of pretrained foundation models. Our survey methodically categorizes MTL techniques into five key areas: regularization, relationship learning, feature propagation, optimization, and pre-training. This categorization not only chronologically outlines the development of MTL but also dives into various specialized strategies within each category. Furthermore, the survey reveals how the MTL evolves from handling a fixed set of tasks to embracing a more flexible approach free from task or modality constraints. It explores the concepts of task-promptable and -agnostic training, along with the capacity for zero-shot learning, which unleashes the untapped potential of this historically coveted learning paradigm. Overall, we hope this survey provides the research community with a comprehensive overview of the advancements in MTL from its inception in 1997 to the present in 2023. We address present challenges and look ahead to future possibilities, shedding light on the opportunities and potential avenues for MTL research in a broad manner. This project is publicly available at https://***/junfish/Awesome-Multi

关键词： Learning systems

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A Toolbox of Feminist Wonder: Theories and methods that can make a difference 26

A Toolbox of Feminist Wonder: Theories and methods that can ...

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26th ACM Conference on Computer-Supported Cooperative Work and Social Computing, CSCW 2023

作者： Hansson, Karin Bardzell, Shaowen Bhandari, Aparajita Boulicault, Marion Doyle, Dylan Thomas Erete, Sheena Cerratto Pargman, Teresa Lazem, Shaimaa Muller, Michael Normark, Maria Petterson, Adrian Rosén, Anton Poikolainen Taylor, Alex S. Thomas, Jakita O. Watson, Julia Södertörn University The School of Natural Sciences Technology and Environmental Studies Sweden Georgia Institute of Technology The School of Interactive Computing United States Cornell University Department of Communication United States University of Edinburgh Department of Philosophy United States University of Colorado Boulder Department of Information Science United States University of Maryland College of Information United States Stockholm University The Department of Computer and Systems Sciences Sweden City for Scientific Research and Technological Applications The Informatics Research Institute Egypt Ibm Research Human Centered Ai United States Uppsala University Department of Informatics and Media Sweden University of Toronto Faculty of Information Canada Aalto University The School of Arts Design and Architecture Finland City University of London The Centre for Human Computer Interaction Design United Kingdom Auburn University Department of Computer Science and Software Engineering United States University of Toronto Department of Computer Science Canada

ISBN: (纸本)9798400701290

This one-day hybrid workshop builds on previous feminist CSCW workshops to explore feminist theoretical and methodological approaches that have provided us with useful tools to see things differently and make space for change. Since its inception over a decade ago, feminist HCI has progressed from the margins to mainstream HCI, with numerous references in the literature. Feminist HCI has also evolved to incorporate other critical HCI practices such as Queer HCI, participatory design, and speculative design. While feminist approaches have grown in popularity and become mainstream, it is getting more difficult to distinguish the feminist emancipatory core from other attempts of developing and improving society in various ways. In this workshop, we therefore want to revisit our feminist roots, where theory is a liberatory and creative practice, motivated by affect, curiosity, and wonder. From this standpoint, we consider which of our feminist tools can make a significant difference today, in a highly datafied world. The goal of this workshop is to;1) create an inventory of feminist theories and concepts that have had an impact on our work as designers, educators, researchers, and activists;2) develop a feminist toolbox for the CSCW community to strengthen our feminist literacy. © 2023 Owner/Author.

关键词： Computation theory

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Practicable Paradigms for Semi-Automated Expert-User Post-Processing of Deep-Learning Segmentations in 3D Radiology 10

Practicable Paradigms for Semi-Automated Expert-User Post-Pr...

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10th International Workshop on Innovative Simulation for Health Care, IWISH 2021

作者： Jany, Julian Zwettler, Gerald Adam Department of Software Engineering School of Informatics Communications and Media University of Applied Sciences Upper Austria Softwarepark 11 Hagenberg4232 Austria Research Group Advanced Information Systems and Technology Research and Development Department University of Applied Sciences Upper Austria Softwarepark 11 Hagenberg4232 Austria

ISBN: (纸本)9788885741652

With recent improvements in deep-learning architectures and availability of GPU hardware, state of the art deep learning (DL) has already manifested as powerful image processing technology in the clinical routine to provide segmentation results of high accuracy. As a drawback, it's black-box nature does not naturally feature inspection and post-processing by medical experts. We present a Graph segmentation (GS) approach that derives it's fitness function from arbitrary DL results in a generic way. To allow for efficient and effective post-processing by the medical experts, various interaction paradigms are presented and evaluated in this paper. The trade-off of GS compared to the initial DL results is marginal (delta JI= 0.196%), yet potential DL segmentation errors can be corrected in a reliable way. The intuitive approach shows a high level of both, inter and intra user reproducibility. Change propagation of corrected slices keeps the demand for user-interaction to a minimum when successfully correction potential weaknesses in the DL segmentations. Thereby, the formerly error-prone slice mini-batches get corrected in an automated way with the JI being significantly increased. © 2021 The Authors.

关键词： Deep learning

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An Optimized Approach to Hourly Temperature and Humidity Setpoint Generation for Reducing Tomato Disease and Saving Power Cost in Greenhouses

SSRN

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SSRN 2024年

作者： Sánchez-Molina, Jorge Antonio Wang, Hui Laktionov, Ivan Díaz, Francisco Rodríguez Li, Ming BIPP Institute of Plant Protection Beijing Academy of Agriculture and Forestry Sciences Beijing100097 China Department of Computer Systems Software Dnipro University of Technology DniproUA49005 Ukraine Department of Informatics University of Almería ceiA3 CIESOL Almería04120 Spain Beijing Research Center for Information Technology in Agriculture National Engineering Research Centre for Information Technology in Agriculture National Engineering Laboratory for Agri-product Quality Traceability Key Laboratory of Agri-informatics Ministry of Agriculture Beijing100097 China

Grey leaf spot is a main leaf disease of tomato in Mediterranean greenhouses, characterized by warm temperatures and high humidity during the spring and winter seasons, hence suitable for pathogen infection and spore spread. Consequently, the utilization of automatic control and optimization algorithms has emerged as effective means to prevent chemical-oriented disease control and enhancing the overall quality and safety of food and crops. The aim of this work is to search an optimal strategy for precision management on greenhouse tomato growth environment. So, multi-objective optimization rises to an alternative to achieve this goal. While there were lots of research on determining trajectories to control a desired crop growth, and lacking works that optimize climate conditions for restraining the damage of disease on crop. Based on the multi-objective genetic algorithm optimization method (MOGA), the solution balances the conflict of two objectives: minimum power cost caused by climate control and maximum health leaves with few effects of grey leaf spot. This study also highlights disease and high temperature impact on tomato growth, which are as inequality constraints of the optimization problems. The results showed MOGA strategy performers good, the minimum power cost is only need 0.084€*day-1 in warm weather condition, as well as 3.74 €*day-1 in cold weather condition, the uninfected LAI (m2[Leaves](m-2[soils]*day-1)) is the range of [0.14 0.20]. The yearly power cost at least [308 1365]€.These are able to embed within a control scheme for achieving optimization purpose. The farmer receives the data necessary for decision-making to establish the setpoints during the crop cycle, modifying the control decisions, lowering production costs, reducing the use of pesticides and increasing the system efficiency to optimize crop growth. © 2024, The Authors. All rights reserved.

关键词： Crops

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