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International Conference on computer Theory and Applications (ICCTA)

作者： Youstina M. Halim Khaled A. Ismail Mohamed A. Abd El Ghany Sameh A. Ibrahim Youssef M. Halim Mixel Egypt. Electronics and Communications Engineering Dept. Faculty of Engineering Ain Shams University Cairo Egypt GSI Helmholtz Center for Heavy-Ion Research GmbH (GSI) Germany Electronics Department German University in Cairo Egypt. Integrated Electronic Systems Lab TU Darmstadt Germany Electronics and Communications Engineering Department Faculty of Engineering Ain Shams University Cairo Egypt Computer Engineering and Software Systems Dept. Faculty of Engineering Ain Shams University Cairo Egypt

Functional verification of digital designs is an increasingly complex and time-consuming endeavor. One of the major challenges in functional verification is achieving functional coverage closure in a timely manner. Verification experts have moved from using directed stimulus, towards constrained random stimulus and finally, towards using machine learning to direct stimulus. In this work, reinforcement learning (RL) was used, incorporating three different kinds of RL agents to direct stimulus generation for a traffic light controller system. Two of the agents are based on Q-learning (DQN and SARSA), and one is based on Monte-Carlo method (CEM). The maximum reduction in simulation time needed to achieve a targeted percent of coverage was 97%. The average reduction of simulation time across all testcases and agents used was 70%. The solution is highly reusable, the architecture was integrated with different agents and testcases.

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PatrIoT: IoT automated interoperability and integration testing framework

arXiv

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arXiv 2021年

作者： Bures, Miroslav Ahmed, Bestoun S. Rechtberger, Vaclav Klima, Matej Trnka, Michal Jaros, Miroslav Bellekens, Xavier Almog, Dani Herout, Pavel Dept. of Computer Science FEE Czech Technical University in Prague Prague Czech Republic Dept. of Math. & Computer Science Karlstad University Karlstad Sweden Red Hat Czech s.r.o. Brno Czech Republic Dept. of Electronic and Electrical Engineering University of Strathclyde Glasgow United Kingdom Software Engineering Dept. Shamoon College of Engineering Be'er Sheva Israel Dept. of CS and Engineering FAS University of West Bohemia Plzen Czech Republic

With the rapid growth of the contemporary Internet of Things (IoT) market, the established systems raise a number of concerns regarding the reliability and the potential presence of critical integration defects. In this paper, we present a PatrIoT framework that aims to provide flexible support to construct an effective IoT system testbed to implement automated interoperability and integration testing. The framework allows scaling from a pure physical testbed to a simulated environment using a number of predefined modules and elements to simulate an IoT device or part of the tested infrastructure. PatrIoT also contains a set of reference example testbeds and several sets of example automated tests for a smart street use case. Copyright © 2021, The Authors. All rights reserved.

关键词： Integration testing

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AGMI: Attention-Guided Multi-omics Integration for Drug Response Prediction with Graph Neural Networks

AGMI: Attention-Guided Multi-omics Integration for Drug Resp...

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2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021

作者： Feng, Ruiwei Xie, Yufeng Lai, Minshan Chen, Danny Z. Cao, Ji Wu, Jian Zhejiang University Coll. of Computer Science and Technology Hangzhou China Zhejiang University School of Software Technology Hangzhou China Zhejiang University Polytechnic Institute Hangzhou China University of Notre Dame Dept. of Computer Science and Engineering Notre Dame United States Zhejiang University Coll. of Pharmaceutical Sciences Hangzhou China Zhejiang University School of Public Health Hangzhou China

ISBN: (纸本)9781665401265

Accurate drug response prediction (DRP) is a crucial yet challenging task in precision medicine. This paper presents a novel Attention-Guided Multi-omics Integration (AGMI) approach for DRP, which first constructs a Multiedge Graph (MeG) for each cell line, and then aggregates multi-omics features to predict drug response using a novel structure, called Graph edge-aware Network (GeNet). For the first time, our AGMI approach explores gene constraint based multi-omics integration for DRP with the whole-genome using GNNs. Empirical experiments on the CCLE and GDSC datasets show that our AGMI largely outperforms state-of-the-art DRP methods by 8.3%-34.2% on four metrics. Our data and code are available at https://***/yivan-WYYGDSG/AGMI. © 2021 IEEE.

关键词： Graph neural networks

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Capturing the practices, challenges, and needs of transportation decision-makers

arXiv

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arXiv 2020年

作者： Sharbatdar, Nasim Lamine, Yassine Milord, Brigitte Morency, Catherine Cheng, Jinghui Dept. of Computer Engineering Polytechnique Montréal MontréalQC Canada Dept. of Civil Engineering Polytechnique Montréal MontréalQC Canada

Transportation decision-makers from government agencies play an important role in addressing the traffic network conditions, which in turn, have a major impact on the well-being of citizens. The practices, challenges, and needs of this group of practitioners are less represented in the HCI literature. We address this gap through an interview study with 19 practitioners from Transports Québec, a government agency responsible for transportation infrastructures in Québec, Canada. We found that this group of decision-makers can most benefit from research about data analysis tools and platforms that (1) provide information to support data quality awareness, (2) are interoperable with other tools in the complex workflow of the practitioners, and (3) support intuitive and customizable visual analytics. These implications can also be informative to the design of tools supporting other decision-making tasks and domains. Copyright © 2020, The Authors. All rights reserved.

关键词： Decision making

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Defense Strategy against Byzantine Attacks in Federated Machine Learning: Developments towards Explainability

Defense Strategy against Byzantine Attacks in Federated Mach...

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Nuria Rodríguez-Barroso Javier Del Ser M. Victoria Luzón Francisco Herrera Dept. of Computer Science and Artificial Intelligence Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI) University of Granada Granada Spain TECNALIA Basque Research and Technology Alliance (BRTA) Derio Bizkaia Spain University of the Basque Country (UPV/EHU) Bilbao Bizkaia Spain Department of Software Engineering Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI) University of Granada Granada Spain

ISBN: (数字)9798350319545

ISBN: (纸本)9798350319552

The rise of high-risk AI systems has led to escalating concerns, prompting regulatory efforts such as the recently approved EU AI Act. In this context, the development of responsible AI systems is crucial. To this end, trustworthy AI techniques aim at requirements (including transparency, privacy awareness and fairness) that contribute to the development of responsible, robust and safe AI systems. Among them, Federated Learning (FL) has emerged as a key approach to safeguarding data privacy while enabling the collaborative training of AI models. However, FL is prone to adversarial attacks, particularly byzantine attacks, which aim to modify the behavior of the model. This work addresses this issue by proposing an eXplainable and Impartial Dynamic Defense against Byzantine Attacks (XI-DDaBA). This defense mechanism relies on robust aggregation operators and filtering techniques to mitigate the effects of adversarial attacks in FL, while providing explanations for its decisions and ensuring that clients with poor data quality are not discriminated. Experimental simulations are discussed to assess the performance of XI-DDaBA against other baselines from the literature, and to showcase its provided explanations. Overall, XI-DDaBA aligns with the need for responsible AI systems in high-risk collaborative learning scenarios through the explainable and impartial provision of robustness against attacks.

关键词： Fuzzy logic Training Privacy Data privacy Federated learning Filtering Robustness

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A Comprehensive Evaluation of Android ICC Resolution Techniques

arXiv

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arXiv 2021年

作者： Yan, Jiwei Zhang, Shixin Liu, Yepang Deng, Xi Yan, Jun Zhang, Jian Tech. Center of Software Engineering Institute of Software CAS China Univ. of Chinese Academy of Sciences Beijing China School of Software Engineering Beijing Jiaotong University Beijing China Dept. of Computer Science and Engr. Southern University of Sci. and Tech Shenzhen China State Key Lab. of Computer Science Institute of Software CAS China

Inter-component communication (ICC) is a widely used mechanism in mobile apps, which enables message-based control flow transferring and data passing between Android components. Effective ICC resolution requires precisely identifying entry points, analyzing data values of ICC fields, modeling related framework APIs, etc. Due to various control-flow- and data-flow-related characteristics involved and the lack of oracles for real-world apps, the comprehensive evaluation of ICC resolution techniques is challenging. To fill this gap, we collect multiple-type benchmark suites with 4,104 apps, covering hand-made apps, open-source, and commercial ones. Considering their differences, various evaluation metrics, e.g., number count, graph structure, and reliable oracle based metrics, are adopted on-demand. As the oracle for real-world apps is unavailable, we design a dynamic analysis approach to extract the real ICC links triggered during GUI exploration. By auditing the code implementations, we carefully check the extracted ICCs and confirm 1,680 ones to form a reliable oracle set, in which each ICC is labeled with 25 code characteristic tags. The evaluation performed on six state-of-the-art ICC resolution tools shows that 1) the completeness of static ICC resolution results on real-world apps is not satisfactory, as up to 38%-85% ICCs are missed by tools;2) many wrongly reported ICCs are sent from or received by only a few components and the graph structure information can help the identification;3) the efficiency of fundamental tools, like ICC resolution ones, should be optimized in both engineering and research aspects. By investigating both the missed and wrongly reported ICCs, we discuss the strengths of different tools for users and summarize eight common FN/FP patterns in ICC resolution for tool developers. © 2021, CC BY-NC-SA.

关键词： Graphic methods

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A New Hybrid Cipher based on Prime Numbers Generation Complexity: Application in Securing 5G Networks

A New Hybrid Cipher based on Prime Numbers Generation Comple...

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ACS/IEEE International Conference on computer Systems and Applications

作者： Adda Boualem Abdelkader Berrouachedi Marwane Ayaida Hisham Kholidy Elhadj Benkhelifa Department of Computer Science Ibn Khaldoun University Tiaret Algeria Paragraphe Lab University of Paris 8 Paris France Polytechnique Hauts-de-France CNRS Univ. Lille UMR 8520 - IEMN France CReSTIC EA 3804 Univ. Reims Champagne Ardenne France Dept. of Networks and Computer Security College of Engineering SUNY Polytechnic Institute Utica New Yourk USA Smart Systems AI and Cybersecurity Research Centre Staffordshire Univ UK

Today’s cellular networks (known as 2G, 3G, and 4G) provide a solid foundation for connecting things. The Internet of Things (IoT) is helping people live and work smarter and take full control of their lives. In addition to providing smart devices for home automation, IoT is also critical for businesses. The security of classical cryptosystems is characterized by their simple arithmetic complexity. This type uses; shifts, arrangements, permutations, and substitutions of letters, words, or phrases to encrypt a given message. Moreover, this kind of cryptosystem is easy to break, because the complexity of their scheme is convergent. On the other hand, the security of modern cryptosystems is characterized by complex arithmetic, using the concept of keys; private keys to encrypt and public keys to decrypt. This type is hard to break because of the complexity of their scheme being divergent. This paper aims to secure the 5G networks with a new variant of the classical Polybius Checkerboard Cipher (HPCC). The system of letter substitution is based on the complexity and the divergence of private key generation. Filling a magic square with primes is an NP-hard task, which shows the complexity and divergence of the strategy adopted in this variant.

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A QoE Evaluation of an Immersive Virtual Reality Autonomous Driving Experience

A QoE Evaluation of an Immersive Virtual Reality Autonomous ...

引用

International Workshop on Quality of Multimedia Experience, QoMEx

作者： Guilherme Daniel Gomes Ronan Flynn Niall Murray Dept. Of Computer & Software Engineering Athlone Institute of Technology Athlone Ireland

ISBN: (数字)9781728159652

ISBN: (纸本)9781728159669

The driver/passenger role in autonomous driving experiences is an important subject that is concerned with how these systems will interact and communicate with the human stakeholder. Even though self-driving technologies have made rapid progress in recent years, their success will depend on ethics, safe capabilities and user acceptance. The overall satisfaction resulting from the interaction between humans, these technologies and their evaluation in simulators can help industry to improve their design. Such evaluations can be based on user's perceived Quality of Experience (QoE). The impact of the quality features that compound VR environments is an important factor to understand. Sense of dept., texture quality and resolution are some examples that influence the perceived quality of the simulation and immersion levels. This demonstration promotes a VR autonomous driving experience in one street of Athlone, Ireland. The application will be presented in two different formats: photogrammetry, a technique that uses photos to provide realistic 3D content, and secondly non-photorealistic simulated environment. Further investigations will be carried out to understand factors that enable the highest immersive experience in autonomous vehicles considering feedback modalities between the car and its users.

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The concordia NLG surface realizer at SR'19 2

The concordia NLG surface realizer at SR'19

引用

2nd Workshop on Multilingual Surface Realisation, MSR@EMNLP-IJCNLP 2019

作者： Farahnak, Farhood Rafiee, Laya Kosseim, Leila Fevens, Thomas Dept. of Computer Science and Software Engineering Concordia University Montreal Canada

ISBN: (纸本)9781950737765

This paper presents the model we developed for the shallow track of the 2019 NLG Surface Realization Shared Task. The model reconstructs sentences whose word order and word inflections were removed. We divided the problem into two sub-problems: reordering and inflecting. For the purpose of reordering, we used a pointer network integrated with a transformer model as its encoder-decoder modules. In order to generate the inflected forms of tokens, a Feed Forward Neural Network was employed. © 2019 Association for Computational Linguistics.

关键词： Feedforward neural networks

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Web Service-Based Turkish Automatic Speech Recognition Platform

Web Service-Based Turkish Automatic Speech Recognition Platf...

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Human-computer Interaction, Optimization and Robotic Applications (HORA), International Congress on

作者： Saadin Oyucu Hüseyin Polat Hayri Sever Dept. of computer engineering University of Gazi Ankara Tukey Dept. of software engineering University of Cankaya Ankara Tukey

ISBN: (数字)9781728193526

ISBN: (纸本)9781728193533

In response to the similar challenges in building large-scale distributed applications and platforms on the Web, microservice architecture has emerged and gained a lot of popularity in recent years. Therefore, both for the use of microservices and for the provided of the necessary interface for Automatic Speech Recognition (ASR), a web-based platform has been developed. Within firstly the scope of the study, a Turkish ASR system was developed. A web service structure was created to facilitate access to the ASR system. The access of methods and data in the web service structure was provided through Representational State Transfer (REST) web services and service layer. An interface was developed to enable interaction with the web service. The platform was developed using a combination of different technologies such as ASR, web services, microservices, and interface technologies. The developed platform can be used via a standard web browser or an Application Programming Interface (API). In this study, Docker packages were used to improve system performance instead of using different virtual machines on a single server. In the experiments performed, it was shown that the Turkish ASR system had a word error rate of 24.70%. In web service performance tests, it was shown that the platform responded in an average of 9.6 seconds for a 59-second speech recording. The developed user interface was tested in both mobile and desktop web browsers and was shown to function properly. Applications and other services were given access to the platform without the need to use an interface via API support provided by the platform. As a result, a web service-based Turkish ASR platform working seamlessly on the ever-increasing number of mobile devices, the Internet of Things ecosystem, or other access devices was developed.

关键词： Web services Hidden Markov models Maximum likelihood decoding Testing Speech recognition Tools Browsers

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