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检索条件"任意字段=18th International Conference on Software Engineering and Knowledge Engineering"

共 35587 条记录，以下是561-570 订阅

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Runtime Resolution of Feature Interactions through Adaptive Requirement Weakening 18

Runtime Resolution of Feature Interactions through Adaptive ...

引用

IEEE/ACM 18th international Symposium on software engineering for Adaptive and Self-Managing Systems (SEAMS)

作者： Chu, Simon Shedden, Emma Zhang, Changjian Meira-Goes, Romulo Moreno, Gabriel A. Garlan, David Kang, Eunsuk Carnegie Mellon Univ Pittsburgh PA USA Univ Michigan Ann Arbor MI USA Carnegie Mellon Univ Inst Software Engn Pittsburgh PA USA

ISBN: (纸本)9798350311921

the feature interaction problem occurs when two or more independently developed components interact with each other in unanticipated ways, resulting in undesirable system behaviors. Feature interaction problems remain a challenge for emerging domains in cyber-physical systems (CPS), such as the Internet of things and autonomous drones. Existing techniques for resolving feature interactions take a "winner-takes-all" approach, where one out of the conflicting features is selected as the most desirable one, and the rest are disabled. However, when multiple of the conflicting features fulfill important system requirements, being forced to select one of them can result in an undesirable system outcome. In this paper, we propose a new resolution approach that allows all of the conflicting features to continue to partially fulfill their requirements during the resolution process. In particular, our approach leverages the idea of adaptive requirement weakening, which involves one or more features temporarily weakening their level of performance in order to co-exist with the other features in a consistent manner. Given feature requirements specified in Signal Temporal Logic (STL), we propose an automated method and a runtime architecture for automatically weakening the requirements to resolve a conflict. We demonstrate our approach through case studies on feature interactions in autonomous drones.

关键词： feature interactions formal methods requirement engineering self adaptive systems signal temporal logic software engineering

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Impacts of Outdoor Vegetation on Indoor Residential Microbiomes 18

Impacts of Outdoor Vegetation on Indoor Residential Microbio...

引用

18th international conference on Indoor Air Quality and Climate, INDOOR AIR 2024

作者： Maestre, Juan P. Jarma, David Williams, Evan Wylie, Dennis Horner, Sharon Kinney, Kerry Department of Architectural Civil and Environmental Engineering UT AustinTX United States Center for Biomedical Research Support UT Austin TX United States School of Nursing The University of Texas at Austin AustinTX United States

ISBN: (纸本)9798331306816

the indoor microbiomes in homes are considered a reflection of their outdoor counterparts, which in turn are affected by global external factors such as latitude but also by more localized factors such as outdoor vegetation surrounding the home. the influences of outdoor vegetation on home microbiomes are still not fully understood. In this study, the microbial assemblages recovered from 100+ homes were analyzed to evaluate their relationship with features of their immediate surroundings such as vegetation types. Findings suggest that not all vegetation has the same effect, and that these effects can vary depending on the microbiome studied and the distance from the home to each type of vegetation. Crops and tree coverage showed strong relationships with indoor mycobiomes and other factors such as the land development are under further scrutiny to unveil the underlying specific determinants. © 2024 18th conference of the international Society of Indoor Air Quality and Climate, INDOOR AIR 2024 - conference Program and Proceedings. All rights reserved.

关键词： Filter forensics microbiome outdoor vegetation

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In vivo respiratory toxicology of Fine Particulate Matter Air Pollution and High relative humidity exposure: Evidence, mechanisms and prevention 18

In vivo respiratory toxicology of Fine Particulate Matter Ai...

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18th international conference on Indoor Air Quality and Climate, INDOOR AIR 2024

作者： Shu, Ziyu Yao, Runming Department of Civil Engineering Chongqing University China Department of Construction Management and Engineering Reading University United Kingdom

ISBN: (纸本)9798331306816

Exploring the main environmental factors that significantly increase the incidence of allergic asthma is the key and breakthrough point to effectively reducing and preventing allergic diseases. Fine particular matter (PM2.5), the ubiquitous indoor and outdoor air pollutants in mainland China, is closely associated with the onset and development of asthma with numerous vitro and vivo studies evidences. Epidemiological studies have also shown that the atmosphere's relative humidity(RH) and humidity-related pathogens may be an independent but enhanced factor associated with worsening respiratory diseases. From a practical perspective, the fluctuation in RH strongly correlated with the rise in PM2.5 concentration and was founded to affect the size and distribution characteristics. Moreover, due to the different water absorption properties of different components in the particles, humidity can accelerate the formation of secondary inorganic and organic aerosols, causing more severe air pollution. However, it is unclear about the adverse effect of humidity and/or PM2.5 combined exposure effect. therefore, a murine asthma model aimed to investigate the underlying mechanisms through Transient receptor potential (TRP) ion channels. the results show that combined exposure can enhance the activation of the TRPV ion channel in the lung, exacerbating inflammation and hypersecretion of mucus in the airways. this also pointed out that the RH variation is essential for studying air pollutants and allergens may have synergistic or additive effects on allergic asthma. © 2024 18th conference of the international Society of Indoor Air Quality and Climate, INDOOR AIR 2024 - conference Program and Proceedings. All rights reserved.

关键词： Indoor air pollution

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Design and Experimental Study of Novel Controllable Attenuator Systems for Constant Temperature Air-Conditioning 18

Design and Experimental Study of Novel Controllable Attenuat...

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18th international conference on Indoor Air Quality and Climate, INDOOR AIR 2024

作者： Weichen, Guo Yusong, Hong Zeng, Wang Xuejin, Zhu Zhe, Zhu Wei, Ye School of Mechanical Engineering Tongji University Shanghai China Shanghai Architectural Design and Research Institute Co. LTD Shanghai China Key Laboratory of Performance Evolution and Control for Engineering Structures of Ministry of Education Tongji University Shanghai China

ISBN: (纸本)9798331306816

High-end manufacturing and fundamental physics research require the provision of indoor air environments with ultra-high precision constant temperature. therefore, the chilled water system, which is the main source of cooling, also requires strict temperature control. Current closed-loop control loops are mainly used to overcome low-frequency disturbances, and attenuators are usually used to overcome high-frequency fluctuations. In this study, two high-precision controlled attenuator systems based on two typical attenuators, i.e., plate heat exchanger and water mixing pump, were proposed, which combined PID control and attenuator through flow control to achieve full-frequency fluctuation control of fluid temperature. Experiments on controlled attenuator operation under two schemes were carried out. And the Fourier transform was used to calculate the fluctuation spectrum and to analyse the sources of disturbances. the control and attenuation processes of the system were analysed in the frequency domain and the fluctuating perturbations caused by the pump were highlighted. © 2024 18th conference of the international Society of Indoor Air Quality and Climate, INDOOR AIR 2024 - conference Program and Proceedings. All rights reserved.

关键词： Air conditioning

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software engineering for Data Intensive Scalable Computing and Heterogeneous Computing

Software Engineering for Data Intensive Scalable Computing a...

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IEEE/ACM international conference on software engineering - Future of software engineering (ICSE-FoSE)

作者： Kim, Miryung UCLA Los Angeles CA 90095 USA

ISBN: (纸本)9798350324969

With the development of big data, machine learning, and AI, existing software engineering techniques must be re-imagined to provide the productivity gains that developers desire. Furthermore, specialized hardware accelerators like GPUs or FPGAs have become a prominent part of the current computing landscape. However, developing heterogeneous applications is limited to a small subset of programmers with specialized hardware knowledge. To improve productivity and performance for data-intensive and compute-intensive development, now is the time that the software engineering community should design new waves of refactoring, testing, and debugging tools for big data analytics and heterogeneous application development. In this paper, we overview software development challenges in this new data-intensive scalable computing and heterogeneous computing domain. We describe examples of automated software engineering (debugging, testing, and refactoring) techniques that target this data and compute intensive domain and share lessons learned from building these techniques.

关键词： data-intensive scalable computing heterogeneous computing big data analytics debugging testing refactoring software development tools

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Holistic Cyber threat Modeling for Machine Learning-Based Systems: A Case Study in Healthcare

Holistic Cyber Threat Modeling for Machine Learning-Based Sy...

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18th international Joint conference on Biomedical engineering Systems and Technologies, BIOSTEC 2025

作者： Jaal, Janno Bahsi, Hayretdin Department of Software Science Tallinn University of Technology Tallinn Estonia Cybernetica AS Tallinn Estonia School of Informatics Computing and Cyber Systems Northern Arizona University United States

Considering the immense pace in machine learning (ML) technology and related products, it may be difficult to imagine a software system, including healthcare systems, without any subsystem containing an ML model in the near future. However, ensuring the resiliency of these ML-based systems against cyber attacks is vital for more seamless and widespread technology usage. the secure-by-design principle, considering security from the early stages of development, is a cornerstone to achieving sufficient security at a reasonable cost. the realization of this principle starts with conducting threat modeling to understand the relevant security posture and identify cyber security requirements before system design. Although threat modeling of software systems is widely known, it is unclear how to apply it to software systems with machine learning models. Although adversarial machine learning is a widely studied research topic, it has yet to be thoroughly researched how adversarial and conventional cybersecurity attacks can be holistically considered to identify applicable cyber threats at the early stage of a software development life cycle. this paper adapts STRIDE, a widely-known threat modeling method, for the holistic cyber threat analysis of an ML-based healthcare system. © 2025 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： Adversarial machine learning

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Evaluation and Validation of Design Metrics in Machine Learning for Depression Detection 18

Evaluation and Validation of Design Metrics in Machine Learn...

引用

18th IEEE international conference on Emerging Technologies, ICET 2023

作者： Ajmal, Sahar Usman, Muhammad Javed, Abqa National University of Computer and Emerging Sciences Dept. of Software Engineering Chiniot Faisalabad Pakistan National University of Computer and Emerging Sciences Dept. of Computer Science Chiniot Faisalabad Pakistan Univ. of Engineering and Technology Dept. of Computer Science Lahore Pakistan

ISBN: (纸本)9798350328172

Depression is a medical syndrome that is often neglected and considered not as significant as physical illness due to lack of awareness and knowledge, but it should be treated in early stages to avoid extreme cases such as suicide. therefore, Machine Learning Algorithms (MLA) are used to detect depression primitively to avoid extreme hazards. In-ternational Organization for Standardization (ISO) standards are essential for designing metrics in MLA as they ensure global consistency, quality assurance, and objective benchmark, enhancing credibility and reliability of the model. Although there is no proper standard design level quality metric is defined for MLA. therefore, in this study, ISO 9126 standard is used to make as a quality standard considering functionality parameter of MLA design. these metrics are used to evaluate at the design level of MLA such as evaluation of dataset, preprocessing, MLA, and results. We have provide comparative analysis of MLA with partial functionality compliance with full ISO functionality conformance. In this study, MLA with ISO have significance compliance which is promising, where the raw data added to MLA to get the output and or the other hand all the steps are performed. the results clearly show that proposed model of MLA design metrics are out-performed provides 28% better results in terms of evaluations. Furthermore, the proposed design quality metrics can be used as the standard for the MLA domain. © 2023 IEEE.

关键词： Quality assurance

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A python software development for dynamic simulation of mobile elevating work platform 31

A python software development for dynamic simulation of mobi...

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31st international conference on Noise and Vibration engineering, ISMA 2024 and 10th international conference on Uncertainty in Structural Dynamics, USD 2024

作者： Cangi, G. Angeletti, A. Baldinucci, M. Palmieri, M. Cianetti, F. University of Perugia Department of Engineering Via G. Duranti 93 Perugia06125 Italy Terex Italia Via Portella delle Ginestre 5 Umbertide Perugia06019 Italy

ISBN: (纸本)9789082893175

Understanding since the initial stages of designing new products (such as work machinery) the dynamic loads (forces and moments) acting at critical points of structures, leads to significant time to market reduction and cost savings. However, the adoption of commercial capable of simulating the dynamic behavior of various physical systems, remains limited due to the specialized knowledge required to operate with such software. Consequently, many companies forego using these programs, compromising the efficiency of new product development and falling into the iterative design-test loop. the Python-based tool developed in this study, used here to simulate the dynamics of an aerial work platform, aims to make such simulations accessible with relative ease. © 2024 Proceedings of ISMA 2024 - international conference on Noise and Vibration engineering and USD 2024 - international conference on Uncertainty in Structural Dynamics. All rights reserved.

关键词： Product design

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Expert Initialized Reinforcement Learning with Application to Robotic Assembly 18

Expert Initialized Reinforcement Learning with Application t...

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IEEE 18th international conference on Automation Science and engineering (IEEE CASE)

作者： Langaa, Jeppe Sloth, Christoffer Univ Southern Denmark Maersk McKinney Moller Inst Odense Denmark

ISBN: (数字)9781665490429

ISBN: (纸本)9781665490429

this paper investigates the advantages and boundaries of actor-critic reinforcement learning algorithms in an industrial setting. We compare and discuss Cycle of Learning, Deep Deterministic Policy Gradient and Twin Delayed Deep Deterministic Policy Gradient with respect to performance in simulation as well as on a real robot setup. Furthermore, it emphasizes the importance and potential of combining demonstrated expert behavior with the actor-critic reinforcement learning setting while using it with an admittance controller to solve an industrial assembly task. Cycle of Learning and Twin Delayed Deep Deterministic Policy Gradient showed to be equally usable in simulation, while Cycle of Learning proved to be best on a real world application due to the behavior cloning loss that enables the agent to learn rapidly. the results also demonstrated that it is a necessity to incorporate an admittance controller in order to transfer the learned behavior to a real robot.

关键词： Training Robotic assembly Computer aided software engineering Automation Service robots Cloning Reinforcement learning

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VeriCombTest: Automated Test Case Generation Technique Using a Combination of Verification and Combinatorial Testing 18

VeriCombTest: Automated Test Case Generation Technique Using...

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18th international conference on Evaluation of Novel Approaches to software engineering, ENASE 2023

作者： Godboley, Sangharatna Department of Computer Science and Engineering National Institute of Technology Telangana Warangal India

ISBN: (纸本)9789897586477

We propose VeriCombTest which is the combination of Verification and Combinatorial Testing. We experimented with 38 C-Programs from the RERS challenge repository. Verification (CBMC) produced 940 test cases and Combinatorial Testing (PICT) populated a total of 42053 test cases. the good point is that for 40 programs, PICT consumed only 2.6 Minutes to populate the test inputs, however, CBMC which is a Static Symbolic Executor consumed 546.99 Minutes to generate the test inputs. We performed mutation analysis for this work. VeriCombTest has 355 extra killed mutants as compared to the baseline. VeriCombTest is a fully automated tool. Copyright © 2023 by SCITEPRESS - Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

关键词： C (programming language)

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