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arXiv 2018年

作者： Zamli, Kamal Z. Din, Fakhrud Ahmed, Bestoun S. Bures, Miroslav IBM Centre of Excellence Faculty of Computer Systems and Software Engineering Universiti Malaysia Pahang Lebuhraya Tun Razak Kuantan Pahang Darul Makmur 26300 Malaysia Department of Computer Science Faculty of Electrical Engineering Czech Technical University Karlovo nam. 13 Praha 2121 35 Czech Republic

The sine-cosine algorithm (SCA) is a new population-based meta-heuristic algorithm. In addition to exploiting sine and cosine functions to perform local and global searches (hence the name sine-cosine), the SCA introduces several random and adaptive parameters to facilitate the search process. Although it shows promising results, the search process of the SCA is vulnerable to local minima/maxima due to the adoption of a fixed switch probability and the bounded magnitude of the sine and cosine functions (from-1 to 1). In this paper, we propose a new hybrid Q-learning sine-cosine-based strategy, called the Q-learning sine-cosine algorithm (QLSCA). Within the QLSCA, we eliminate the switching probability. Instead, we rely on the Q-learning algorithm (based on the penalty and reward mechanism) to dynamically iden-tify the best operation during runtime. Additionally, we integrate two new operations (Lvy ight motion and crossover) into the QLSCA to facilitate jumping out of local minima/maxima and enhance the solution diversity. To assess its performance, we adopt the QLSCA for the combinatorial test suite minimization problem. Experimental results reveal that the QLSCA is sta-tistically superior with regard to test suite size reduction compared to recent state-of-the-art strategies, including the original SCA, the particle swarm test generator (PSTG), adaptive particle swarm optimization (APSO) and the cuckoo search strategy (CS) at the 95% confidence level. However, con-cerning the comparison with discrete particle swarm optimization (DPSO), there is no significant difference in performance at the 95% confidence level. On a positive note, the QLSCA statistically outperforms the DPSO in certain configurations at the 90% confidence level. Copyright © 2018, The Authors. All rights reserved.

关键词： Cosine transforms

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Artificial Intelligence Powered MOOCs: A Brief Survey

Artificial Intelligence Powered MOOCs: A Brief Survey

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IEEE International Conference on Agents (ICA)

作者： Simon Fauvel Han Yu Chunyan Miao Lizhen Cui Hengjie Song Liang Zhang Xiaoming Li Cyril Leung Joint NTU-UBC Research Centre of Excellence in Active Living for the Elderly (LILY) Nanyang Technological University Singapore School of Computer Science and Engineering Nanyang Technological University Singapore School of Software Engineering Shandong University Jinan China School of Software Engineering South China University of Technology Guangzhou China Institute of Network Computing and Information Systems Peking University Beijing China Department of Electrical and Computer Engineering University of British Columbia Vancouver Canada

Massive Open Online Courses (MOOCs) have gained tremendous popularity in the last few years. Thanks to MOOCs, millions of learners from all over the world have taken thousands of high-quality courses for free. Artificial intelligence (AI) has played an important role in making MOOCs what they are today. By exploiting the vast amount of data generated by learners engaging in MOOCs, AI techniques have been proposed to improve our understanding of MOOC participants and enable MOOC practitioners to deliver better courses. These approaches have also greatly improved student experience and learning outcomes through constructing intelligent and personalized learning trajectories. In this paper, we first review the state-of-the-art AI research making an impact on MOOCs education, emphasizing on works which aim to enhance our understanding of student learning behaviours, improve student engagement, and improve learning outcomes. We then offer an overview of important future research to carry out in sub-fields of AI to enable MOOCs to reach their full potential.

关键词： Videos Artificial intelligence Tools Navigation Computational modeling Trajectory Education

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Dynamical Sampling with Additive Random Noise

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Sampling Theory, Signal Processing, and Data Analysis 2018年第2期17卷 153-182页

作者： Akram Aldroubi Longxiu Huang Ilya Krishtal Akos Ledeczi Roy R. Lederman Peter Volgyesi Department of Mathematics Vanderbilt University Nashville USA Department of Mathematics Northern Illinois University DeKalb USA Department of Electrical Engineering and Computer Science Vanderbilt University Nashville USA Department of Statistics and Data Science Yale University New Haven USA Institute for Software Integrated Systems Vanderbilt University Nashville USA

Dynamical sampling deals with signals that evolve in time under the action of a linear operator. The purpose of the present paper is to analyze the performance of the basic dynamical sampling algorithms in the finite dimensional case and study the impact of additive noise. The algorithms are implemented and tested on synthetic and real data sets, and denoising techniques are integrated to mitigate the effect of the noise. We also develop theoretical and numerical results that validate the algorithm for recovering the driving operators, which are defined via a real symmetric convolution.

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Asymmetrical Multilevel Inverter Topology with Reduced Number of Components

Asymmetrical Multilevel Inverter Topology with Reduced Numbe...

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International Conference on Power Electronic Drives and Energy systems for Industrial Growth

作者： Marif Daula Siddique Saad Mekhilef Noraisyah Mohamed Shah Adil Sarwar Mudasir Ahmad Memon Mehdi Seyedmahmoudian Ben Horan Alex Stojcevski Koki Ogura Muhyaddin Rawa Hussain Bassi Power Electronics and Renewable Energy Research Lab (PEARL) University of Malaya Kuala Lumpur Malaysia Department of Electrical Engineering Aligarh Muslim University Aligarh India School of Software and Electrical Engineering Swinburne University Victoria Australia School of Engineering Deakin University Victoria Australia Department of Electrical Engineering Kyushu Sangyo University Fukuoka Japan Center of Research Excellence in Renewable Energy and Power Systems King Abdulaziz University Jeddah Saudi Arabia Department of Electrical and Computer Engineering King Abdulaziz University Rabigh Saudi Arabia

ISBN: (纸本)9781538693179;9781538693162

A new hybrid structure of multilevel inverter topology is recommended in this paper. It is designed with the aim of reducing the number of components with more number of levels at the output. Proposed topology uses three dc voltage sources along with 10 power semiconductor devices to achieve 13 levels at the output. A comparative study is given with other similar topologies which proves the lower number of components. In order to achieve good-quality output voltage, selective harmonic elimination technique is used with the elimination of lower order harmonics. Different simulation results have been provided to validate the proposed topology.

关键词： Topology Switches Harmonic analysis Inverters Modulation Stress Switching circuits

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Fuzzy adaptive tuning of a particle swarm optimization algorithm for variable-strength combinatorial test suite generation

arXiv

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arXiv 2018年

作者： Zamli, Kamal Z. Ahmed, Bestoun S. Mahmoud, Thair Afzal, Wasif Faculty of Computer Systems and Software Engineering University Malaysia Pahang Gambang Malaysia Department of Computer Science Faculty of Electrical Engineering Czech Technical University Karlovo ńam. 13 Praha 2121 35 Czech Republic School of Engineering Edith Cowan University 270 Joondalup Dr JoondalupWA6027 Australia School of Innovation Design and Engineering Mälardalen University Sweden

Combinatorial interaction testing is an important software testing technique that has seen lots of recent interest. It can reduce the number of test cases needed by considering interactions between combinations of input parameters. Empirical evidence shows that it effectively detects faults, in particular, for highly configurable software systems. In real-world software testing, the input variables may vary in how strongly they interact;variable strength combinatorial interaction testing (VS-CIT) can exploit this for higher effectiveness. The generation of variable strength test suites is a non-deterministic polynomial-time (NP) hard computational problem [1]. Research has shown that stochastic population-based algorithms such as particle swarm optimization (PSO) can be efficient compared to alternatives for VS-CIT problems. Nevertheless, they require detailed control for the exploitation and exploration trade-off to avoid premature convergence (i.e. being trapped in local optima) as well as to enhance the solution diversity. Here, we present a new variant of PSO based on Mamdani fuzzy inference system [2, 3, 4], to permit adaptive selection of its global and local search operations. We detail the design of this combined algorithm and evaluate it through experiments on multiple synthetic and benchmark problems. We conclude that fuzzy adaptive selection of global and local search operations is, at least, feasible as it performs only second-best to a discrete variant of PSO, called DPSO. Concerning obtaining the best mean test suite size, the fuzzy adaptation even outperforms DPSO occasionally. We discuss the reasons behind this performance and outline relevant areas of future work. Copyright © 2018, The Authors. All rights reserved.

关键词： Particle swarm optimization (PSO)

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Guest Editorial Special Issue on Security and Privacy in Cyber-Physical systems

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IEEE Internet of Things Journal 2017年第6期4卷 1798-1800页

作者： Yu, Wei Fu, Xinwen Song, Houbing Economides, Anastasios A. Jo, Minho Zhao, Wei Department of Computer and Information Sciences Towson University TowsonMD21252 United States Department of Computer Science University of Central Florida OrlandoFL32816 United States Department of Electrical Computer Software and Systems Engineering Embry-Riddle Aeronautical University Daytona BeachFL32114 United States Computer Networks and Telematic Applications Laboratory University of Macedonia Thessaloniki546 36 Greece Department of Computer Convergence Software Korea University Seoul Korea Republic of University of Macau China

A typical cyber-physical system (CPS) refers to a system that features a tight integration of computation, networking, and physical elements for interactions between cyber and physical spaces. The Internet of Things (IoT) is considered to be the networking infrastructure of CPS. Applications of CPS cover numerous smart-world research areas that our daily life depends upon, including smart transportation, smart electrical power grid, smart cities, smart medical systems, smart manufacturing systems, and others. While major research on improving the efficiency and reliability of CPS by using advanced information and communication technologies has been conducted, the risks of cyberspace security and privacy breaches in CPS need to be seriously investigated before a massive deployment of CPS technologies can or should be realized.

关键词： Special issues and sections Cyber-physical systems Smart cities Smart grids Manufacturing processes

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From LTL to rLTL Monitoring: Improved Monitorability through Robust Semantics

arXiv

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arXiv 2018年

作者： Mascle, Corto Neider, Daniel Schwenger, Maximilian Tabuada, Paulo Weinert, Alexander Zimmermann, Martin ENS Paris-Saclay Cachan France Safety and Explainability of Learning Systems Group Carl von Ossietzky University of Oldenburg Germany The Max Planck Institute for Software Systems Kaiserslautern Germany Reactive Systems Group Saarland University Saarbrücken Germany Department of Electrical and Computer Engineering UCLA Los Angeles United States Cologne Germany University of Liverpool Liverpool United Kingdom

Runtime monitoring is commonly used to detect the violation of desired properties in safety critical cyber-physical systems by observing its executions. Bauer et al. introduced an influential framework for monitoring Linear Temporal Logic (LTL) properties based on a three-valued semantics for a finite execution: the formula is already satisfied by the given execution, it is already violated, or it is still undetermined, i.e., it can still be satisfied and violated by appropriate extensions of the given execution. However, a wide range of formulas are not monitorable under this approach, meaning that there are executions for which satisfaction and violation will always remain undetermined no matter how it is extended. In particular, Bauer et al. report that 44% of the formulas they consider in their experiments fall into this category. Recently, a robust semantics for LTL was introduced to capture different degrees by which a property can be violated. In this paper we introduce a robust semantics for finite strings and show its potential in monitoring: every formula considered by Bauer et al. is monitorable under our approach. Furthermore, we discuss which properties that come naturally in LTL monitoring - such as the realizability of all truth values - can be transferred to the robust setting. We show that LTL formulas with robust semantics can be monitored by deterministic automata, and provide tight bounds on the size of the constructed automaton. Lastly, we report on a prototype implementation and compare it to the LTL monitor of Bauer et al. on a sample of examples. Copyright © 2018, The Authors. All rights reserved.

关键词： Semantics

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Using measurement and simulation for understanding distributed development processes in the cloud 17

Using measurement and simulation for understanding distribut...

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27th International Workshop on software Measurement and 12th International Conference on software Process and Product Measurement, IWSM Mensura 2017

作者： Lunesu, Ilaria Marchesi, Michele Münch, Jürgen Kuhrmann, Marco University of Cagliari Department of Electrical and Electronic Engineering Italy University of Cagliari Department of Mathematics and Computer Science Italy Reutlingen University Business Informatics and Herman Hollerith Center Germany Clausthal University of Technology Institute for Applied Software Systems Engineering Germany

ISBN: (纸本)9781450348539

Organizations increasingly develop software in a distributed manner. The Cloud provides an environment to create and maintain software-based products and services. Currently, it is widely unknown which software processes are suited for Cloud-based development and what their effects in specific contexts are. This paper presents a process simulation to study distributed development in the Cloud. We contribute a simulation model, which helps analyzing different project parameters and their impact on projects carried out in the Cloud. The simulator helps reproducing activities, developers, issues and events in the project, and it generates statistics, e.g., on throughput, total time, and lead and cycle time. The aim of this simulation model is thus to analyze the tradeoffs regarding throughput, total time, project size, and team size. Furthermore, the modified simulation model aims to help project managers select the most suitable planning alternative. Based on observed projects in Finland and Spain, we simulated a distributed project using artificial and real data. Particularly, we studied the variables project size, team size, throughput, and total project duration. A comparison of the real project data with the results obtained from the simulation shows the simulation producing results close to the real data, and we could successfully replicate a distributed software project. By improving the understanding of distributed development processes, our simulation model thus supports project managers in their decision-making. © 2017 Association for Computing Machinery.

关键词： Throughput

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Architecture-aware design and implementation of CNN algorithms for embedded inference: the ALOHA project

Architecture-aware design and implementation of CNN algorith...

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International Conference on Microelectronics, ICM

作者： Paolo Meloni Daniela Loi Gianfranco Deriu Andy D. Pimentel Dolly Saprat Maura Pintort Battista Biggio Oscar Ripolles David Solans Francesco Conti Luca Benini Todor Stefanov Svetlana Minakova Bernhard Moser Natalia Shepeleva Michael Masin Francesca Palumbo Nikos Fragoulis Ilias Theodorakopoulos Department of Electrical and Electronic Engineering University of Cagliari Italy Institute of Informatics University of Amsterdam The Netherlands Pluribus One Italy CA Technologies Spain Integrated Systems Laboratory ETH Zurich Switzerland Institute of Advanced Computer Science Leiden University The Netherlands Software Competence Center Hagenberg Austria IBM Research - Haifa Israel IDEA Lab University of Sassari Italy IRIDA Labs Computer Vision Systems Greece

ISBN: (纸本)9781538681688;9781538681671

The use of Deep Learning (DL) algorithms is increasingly evolving in many application domains. Despite the rapid growing of algorithm size and complexity, performing DL inference at the edge is becoming a clear trend to cope with low latency, privacy and bandwidth constraints. Nevertheless, traditional implementation on low-energy computing nodes often requires experience-based manual intervention and trial-and-error iterations to get to a functional and effective solution. This work presents a computer-aided design (CAD) support for effective implementation of DL algorithms on embedded systems, aiming at automating different design steps and reducing cost. The proposed tool flow comprises capabilities to consider architecture-and hardware-related variables at very early stages of the development process, from pre-training hyperparameter optimization and algorithm configuration to deployment, and to adequately address security, power efficiency and adaptivity requirements. This paper also presents some preliminary results obtained by the first implementation of the optimization techniques supported by the tool flow.

关键词： Tools Inference algorithms Engines computer architecture Computational modeling Microelectronics Training

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Scenario challenges for next generation aviation technology demonstrations

Scenario challenges for next generation aviation technology ...

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AIAA Modeling and Simulation Technologies Conference, 2018

作者： Moallemi, Mohammad Jafer, Shafagh Chhaya, Bharvi Castro, Carlos A. Embry-Riddle Aeronautical University Daytona BeachFL32114-3900 United States Next Generation Applied Research Lab Embry-Riddle Aeronautical University Daytona Beach Campus Sim Bldg 127 600 S Clyde Morris Blvd Daytona BeachFL32114-3900 United States Department of Electrical Computer Software and Systems Engineering Embry-Riddle Aeronautical University Daytona Beach Campus Lehman 343 600 S Clyde Morris Blvd Daytona BeachFL32114-3900 United States

ISBN: (纸本)9781624105289

The Federal Aviation Administration’s (FAA) Next Generation Air Transportation System (NextGen) program is a long-term modernization and transformation of the current National Airspace System (NAS) into a more efficient and coordinated decision-making system. In order to test the key concepts and methods proposed by FAA and affiliated standard organizations such as RTCA (Radio Technical Commission for Aeronautics), Modeling and Simulation (M&S)-based demonstration of the solutions are employed in the early stages for the verification and validation of concepts and their technologies. With the help of model-based and simulation-based engineering, large-scale systems integration and demonstrations take place seamlessly. This demands for common understanding of simulation scenarios, allowing for cross-platform interoperability. A major challenge facing the development and testing of the demonstrations is the lack of standard scenario definition language bridging the gap between the operational team (controllers, pilots, and dispatchers) and the engineering community. This paper will tackle aviation scenario generation challenges using the recently proposed Aviation Scenario Definition Language (ASDL). ASDL aims at providing a standard scenario specification that leads to a common mechanism for verifying and executing aviation scenarios, effective sharing of scenarios among various simulation environments, improve the consistency among different stakeholders and entities and enable the reuse of scenario specifications. Based on Domain-Specific Language (DSL) design methodologies, current version of ASDL provides a well-structured definition language to define various flight operations scenarios. In this paper, a number of scenarios that have been implemented in previous FAA funded projects, including scenarios of 4 Dimensional trajectory operations as well as unmanned aerial system operations will be presented and an equivalent ASDL generated scenario script will be pro

关键词： Decision making

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