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Portable Blended MOOC Laboratory

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Portable Blended MOOC Laboratory

Learning With MOOCS (LWMOOCS)

作者： Pedro Plaza Elio Sancristobal German Carro Manuel Blazquez Antonio Menacho Felix García-Loro Clara Perez Javier Muñoz Edmundo Tovar JIm Sluss Russ Meier Manuel Castro Electrical and Computer Engineering Department (DIEECTQAI) UNED Madrid Spain Plaza Robotica Madrid Spain Languages Computer Systems and Software Engineering Department UPM Madrid Spain Dean Tuksa Graduate College School of Electrical and Computer Engineering Tulsa OK USA Electrical Engineering and Computer Science Department Milwaukee School of Engineering Milwaukee WI USA Director Electrical and Computer Engineering Department (DIEECTQAI) UNED Madrid Spain

Two types of teaching coexist today: traditional face-to-face methods and teaching based on self-learning where the student has ubiquitous access to course contents. This paper shows how tests have been made of a type of learning that is becoming more common in educational environments. This hybrid teaching method combines the Massively Open Online Course (MOOC) and students' face-to-face work. On the one hand, the advantages of face-to-face learning are taken advantage of: teacher in the classroom, social bonds and daily work sessions. On the other hand, the advantages of distance learning are integrated: flexibility, accessible material and wide variety. Also included in the paper is a description of the equipment and the way in which it has been used with students. Finally, the paper details the educational experience carried out with students and the outcomes obtained. These pilot tests are framed within the education of STEM topics and robotics.

关键词： computer aided instruction Robots Electronic learning Tools Light emitting diodes Training

Design of software Rejuvenation for CPS Security Using Invariant Sets

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Design of Software Rejuvenation for CPS Security Using Invar...

American Control Conference (ACC)

作者： Raffaele Romagnoli Bruce H. Krogh Bruno Sinopoli Dept. of Electrical and Computer Engineering Carnegie Mellon University (CMU) Pittsburgh PA USA CMU Software Engineering Institute Department of Electrical and Systems Engineering Washington University St. Louis MO USA

ISBN: (纸本)9781538679012;9781538679265

software rejuvenation has been proposed as a strategy to protect cyber-physical systems (CSPs) against unanticipated and undetectable cyber attacks. The basic idea is to refresh the system periodically with a secure and trusted copy of the online software so as to eliminate all effects of malicious modifications to the run-time code and data. This paper considers software rejuvenation design from a control-theoretic perspective. Invariant sets for the Lyapunov function for the safety controller are used to derive bounds on the time that the CPS can operate in mission control mode before the software must be refreshed. With these results it can be guaranteed that the CPS will remain safe under cyber attacks against the run-time system. The approach is illustrated using simulation of the nonlinear dynamics of a quadrotor system. The concluding section discusses directions for further research.

关键词： software Safety Cyberattack Clocks software algorithms Timing

Towards eliciting and analyzing security requirements using ontologies through use case scenarios (work-in-progress) 4

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Towards eliciting and analyzing security requirements using ...

4th International Conference on software Security and Assurance, ICSSA 2018

作者： Ochoa, Omar Steinmann, Jessica Lischuk, Yevgeniy Department of Electrical Computer Software & Systems Engineering Embry-Riddle Aeronautical University Daytona BeachFL32114 United States

ISBN: (纸本)9781538692103

As our reliance on large, complex and ubiquitous software system increases, so does the devastating consequences that a cyberattack can have to modern society. Building secure software systems requires a greater need for secure software engineering approaches that can detect and address security vulnerabilities at the earliest stages of the software development life cycle. This paper presents an approach to facilitate the elicitation of cybersecurity requirements based on enhancing the widely adopted technique of use case modeling by incorporating the use of an ontology. The ontology will model the semantic relationship of cybersecurity requirements. Utilizing this ontology, we propose an approach that can be used to reuse and share cybersecurity requirements, providing a potential for the rapid discovery and correction of software vulnerabilities in the development process. © 2018 IEEE.

关键词： Ontology

ESFNet: Efficient network for building extraction from high-resolution aerial images

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arXiv 2019年

作者： Lin, Jingbo Jing, Weipeng Song, Houbing Chen, Guangsheng College of Information and Computer Engineering Northeast Forestry University Harbin HLJ China Department of Electrical Computer Software and Systems Engineering Embry-Riddle Aeronautical University Daytona BeachFL32114 United States

Building footprint extraction from high-resolution aerial images is always an essential part of urban dynamic monitoring, planning and management. It has also been a challenging task in remote sensing research. In recent years, deep neural networks have made great achievement in improving accuracy of building extraction from remote sensing imagery. However, most of existing approaches usually require large amount of parameters and floating point operations for high accuracy, it leads to high memory consumption and low inference speed which are harmful to research. In this paper, we proposed a novel efficient network named ESFNet which employs separable factorized residual block and utilizes the dilated convolutions, aiming to preserve slight accuracy loss with low computational cost and memory consumption. Our ESFNet obtains a better trade-off between accuracy and efficiency, it can run at over 100 FPS on single Tesla V100, requires 6x fewer FLOPs and has 18x fewer parameters than state-of-the-art real-time architecture ERFNet while preserving similar accuracy without any additional context module, post-processing and pre-trained scheme. We evaluated our networks on WHU Building Dataset and compared it with other state-of-the-art architectures. The result and comprehensive analysis show that our networks are benefit for efficient remote sensing researches, and the idea can be further extended to other areas. The code is public available at: https://***/mrluin/ESFNet-Pytorch. Copyright © 2019, The Authors. All rights reserved.

关键词： Deep neural networks

SAN: Scale-aware network for semantic segmentation of high-resolution aerial images

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arXiv 2019年

作者： Lin, Jingbo Jingy, Weipeng Songz, Houbing College of Information and Computer Engineering Northeast Forestry University Harbin HLJ China Department of Electrical Computer Software and Systems Engineering Embry-Riddle Aeronautical University Daytona BeachFL32114 United States

High-resolution aerial images have a wide range of applications, such as military exploration, and urban planning. Semantic segmentation is a fundamental method extensively used in the analysis of high-resolution aerial images. However, the ground objects in high-resolution aerial images have the characteristics of inconsistent scale, and this feature usually leads to unexpected predictions. To tackle this issue, we propose a novel scale-aware module (SAM). In SAM, we employ resampling method aimed to make pixels adjust their positions to fit the ground objects with different scales, and it implicitly introduce spatial attention by employing re-sampling map as weighted map. As a result, the network with the proposed module named scale-aware network (SANet) has a stronger ability to distinguish the ground objects with inconsistent scale. Other than this, our proposed modules can easily embed in most of the existing network to improve their performance. We evaluate our modules on International Society for Photogrammetry and Remote Sensing Vaihingen Dataset, and the experimental results and comprehensive analysis demonstrate the effectiveness of our proposed module. Copyright © 2019, The Authors. All rights reserved.

关键词： Remote sensing

Sharing of vulnerability information among companies - A survey of Swedish companies

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arXiv 2019年

作者： Olsson, Thomas Hell, Martin Host, Martin Franke, Ulrik Borg, Markus Software and Systems Engineering Lab RISE Research Institutes of Sweden Lund Dept. of Electrical and Information Technology Lund University Lund Dept. of Computer Science Lund University Lund Software and Systems Engineering Lab RISE Research Institutes of Sweden Kista

software products are rarely developed from scratch and vulnerabilities in such products might reside in parts that are either open source software or provided by another organization. Hence, the total cybersecurity of a product often depends on cooperation, explicit or implicit, between several organizations. We study the attitudes and practices of companies in software ecosystems towards sharing vulnerability information. Furthermore, we compare these practices to contemporary cybersecurity recommendations. This is performed through a questionnairebased qualitative survey. The questionnaire is divided into two parts: the providers' perspective and the acquirers' perspective. The results show that companies are willing to share information with each other regarding vulnerabilities. Sharing is not considered to be harmful neither to the cybersecurity nor their business, even though a majority of the respondents consider vulnerability information sensitive. However, the companies, despite being open to sharing, are less inclined to proactively sharing vulnerability information. Furthermore, the providers do not perceive that there is a large interest in vulnerability information from their customers. Hence, the companies' overall attitude to sharing vulnerability information is passive but open. In contrast, contemporary cybersecurity guidelines recommend active disclosure and sharing among actors in an ecosystem. Copyright © 2019, The Authors. All rights reserved.

关键词： Surveys

Security of the Internet of Things: Vulnerabilities, Attacks and Countermeasures

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arXiv 2019年

作者： Butun, Ismail Österberg, Patrik Song, Houbing Department of Computer Science and Engineering Chalmers University of Technology Gothenburg Sweden Mid Sweden University Sundsvall Sweden Department of Electrical Computer Software and Systems Engineering Embry-Riddle Aeronautical University FL United States

Wireless Sensor Networks (WSNs) constitute one of the most promising third-millennium technologies and have wide range of applications in our surrounding environment. The reason behind the vast adoption of WSNs in various applications is that they have tremendously appealing features, e.g., low production cost, low installation cost, unattended network operation, autonomous and longtime operation. WSNs have started to merge with the Internet of Things (IoT) through the introduction of Internet access capability in sensor nodes and sensing ability in Internet-connected devices. Thereby, the IoT is providing access to huge amount of data, collected by the WSNs, over the Internet. However, owing to the absence of a physical line-of-defense, i.e. there is no dedicated infrastructure such as gateways to watch and observe the flowing information in the network, security of WSNs along with IoT is of a big concern to the scientific community. More specifically, for the application areas in which CIA (confidentiality, integrity, availability) has prime importance, WSNs and emerging IoT technology might constitute an open avenue for the attackers. Besides, recent integration and collaboration of WSNs with IoT will open new challenges and problems in terms of security. Hence, this would be a nightmare for the individuals using these systems as well as the security administrators who are managing those networks. Therefore, a detailed review of security attacks towards WSNs and IoT, along with the techniques for prevention, detection, and mitigation of those attacks are provided in this paper. In this text, attacks are categorized and treated into mainly two parts, most or all types of attacks towards WSNs and IoT are investigated under that umbrella: "Passive Attacks" and "Active Attacks". Understanding these attacks and their associated defense mechanisms will help paving a secure path towards the proliferation and public acceptance of IoT technology. Copyright © 2019, The Aut

关键词： Internet of things

Emotion Recognition From Gait Analyses: Current Research and Future Directions

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arXiv 2020年

作者： Xu, Shihao Fang, Jing Hu, Xiping Ngai, Edith Wang, Wei Guo, Yi Leung, Victor C.M. School of Information Science and Engineering Lanzhou University Gansu730000 China Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China School of Intelligent Systems Engineering Sun Yat-sen University Guangdong Shenzhen518107 China Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong Second Clinical Medical College Jinan University Shenzhen518055 China College of Computer Science and Software Engineering Shenzhen University Shenzhen518055 China Department of Electrical and Computer Engineering The University of British Columbia VancouverBCV6T 1Z4 Canada

Human gait refers to a daily motion that represents not only mobility, but it can also be used to identify the walker by either human observers or computers. Recent studies reveal that gait even conveys information about the walker’s emotion. Individuals in different emotion states may show different gait patterns. The mapping between various emotions and gait patterns provides a new source for automated emotion recognition. Compared to traditional emotion detection biometrics, such as facial expression, speech, and physiological parameters, gait is remotely observable, more difficult to imitate, and requires less cooperation from the subject. These advantages make gait a promising source for emotion detection. This article reviews current research on gait-based emotion detection, particularly on how gait parameters can be affected by different emotion states and how the emotion states can be recognized through distinct gait patterns. We focus on the detailed methods and techniques applied in the whole process of emotion recognition: data collection, preprocessing, and classification. At last, we discuss possible future developments of efficient and effective gait-based emotion recognition using the state of the art techniques in intelligent computation and big data. Copyright © 2020, The Authors. All rights reserved.

关键词： Emotion Recognition

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Preface

Studies in Big Data

Studies in Big Data 2021年 73卷 v-vii页

作者： Chakraborty, Chinmay Banerjee, Amit Kolekar, Maheshkumar H. Garg, Lalit Chakraborty, Basabi Department of Electronics and Communication Engineering Birla Institute of Technology Ranchi Mesra India Department of Electrical Engineering Indian Institute of Technology Patna Patna India Faculty of Software and Information Science Iwate Prefectural University Takizawa Japan Department of Electrical and Computer Engineering National University of Singapore Singapore Singapore Department of Computer Information Systems Faculty of Information and Communication Technology University of Malta Msida Malta