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arXiv 2019年

作者： Bukal, Mario Muha, Boris University of Zagreb Faculty of Electrical Engineering and Computing Unska 3 Zagreb10000 Croatia University of Zagreb Faculty of Science Department of Mathematics Bijenička cesta 30 Zagreb10000 Croatia

We analyze a linear 3D/3D fluid-structure interaction problem between a thin layer of a viscous fluid and a thin elastic plate with the aim of deriving a simplified reduced model. Based on suitable energy-energy dissipation inequalities quantified in terms of two small parameters, thickness of the fluid layer and thickness of the elastic structure, we identify the right time scale and relation between small paramaters which eventually, on the vanishing limit of small parameters, provide a reduced model. The reduced model is given in terms of a linear sixth-order thin-film equation describing the out-of-plane displacement of the plate. The linear thin-film equation is rigorously justified in terms of weak convergence results relating its solution to the solutions of the original problem. Furthermore, error estimates for approximate solutions constructed from the reduced model are obtained, which provide even strong convergence results.35M30, 35Q30, 35Q74, 76D05, 76D08 Copyright © 2019, The Authors. All rights reserved.

关键词： Viscous flow

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TPTVer： A Trusted Third Party Based Trusted Verifier for Multi-Layered Outsourced Big Data System in Cloud Environment

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China Communications 2018年第2期15卷 122-137页

作者： Jing Zhan Xudong Fan Lei Cai Yaqi Gao Junxi Zhuang College of Computer Science Faculty of Information Technology Beijing University of Technology Beijing China Beijing Key Laboratory of Trusted Computing Beijing China National Engineering Laboratory for Critical Technologies of Information Security Classified Protection Beijing China

Cloud computing is very useful for big data owner who doesn't want to manage IT infrastructure and big data technique details. However, it is hard for big data owner to trust multi-layer outsourced big data system in cloud environment and to verify which outsourced service leads to the problem. Similarly, the cloud service provider cannot simply trust the data computation applications. At last,the verification data itself may also leak the sensitive information from the cloud service provider and data owner. We propose a new three-level definition of the verification, threat model, corresponding trusted policies based on different roles for outsourced big data system in cloud. We also provide two policy enforcement methods for building trusted data computation environment by measuring both the Map Reduce application and its behaviors based on trusted computing and aspect-oriented programming. To prevent sensitive information leakage from verification process,we provide a privacy-preserved verification method. Finally, we implement the TPTVer, a Trusted third Party based Trusted Verifier as a proof of concept system. Our evaluation and analysis show that TPTVer can provide trusted verification for multi-layered outsourced big data system in the cloud with low overhead.

关键词： big data security outsourced ser-vice security MapReduce behavior trustedverification trusted third party

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Practical Implications and Challenges of Multispectral Image Analysis

Practical Implications and Challenges of Multispectral Image...

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International Conference on computing, Mathematics and engineering Technologies (iCoMET)

作者： Syed Muslim Jameel Abdul Rehman Gilal Syed Sajjad Hussain Rizvi Mobashar Rehman Manzoor Ahmed Hashmani Department of Computer and Information Sciences Universiti Teknologi PETRONAS Seri Iskandar Malaysia High-Performance Cloud Computing Center (HPC3) Center for Research in Data Science (CERDAS) Universiti Teknologi PETRONAS Seri Iskandar Malaysia Faculty of Information and Communication Technology (FICT) Universiti Tunku Abdul Rahman Kampar Malaysia Faculty of Engineering Sciences and Technology Hamdard University Karachi Pakistan Department of computer science Sukkur IBA University Sukkur Pakistan

ISBN: (数字)9781728149707

ISBN: (纸本)9781728149714

Multispectral Image Analysis (MIA) is an exciting area of research and famous due to its utilization in geo monitoring, such as environmental change detection and region classification. Currently, many other areas are also emerging and are utilizing the multispectral imagery for improving the existing business processes and ensuring the reliability in the existing business methods. However, the process of generating and analyzing multispectral data needs more sophisticated techniques and methods. Also, the multispectral data possesses some temporal and structural inconsistencies, which make the existing multispectral analysis a more challenging task. Therefore, this study surveys the practical implication and possible issues in multispectral image analysis. For that reason, this study aims to investigate the two simple research questions and follow a structured analysis approach to achieve the research objectives. The rest of the paper is structured as; Section II briefly explains the systematic methodology adopted for this survey. Section III is relevant to research finding in response to the RQ1 and RQ2. Finally, Section IV presents the conclusion of this study. In future work, we will sharpen this study towards Skin Disease Analysis using Multispectral Imagery.

关键词： Image analysis Agriculture Diseases Machine learning Quality assessment Remote sensing

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Efficient AI-Driven Design of Microwave Antennas Using PSADEA

Efficient AI-Driven Design of Microwave Antennas Using PSADE...

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IEEE Middle East and North Africa Communications Conference (MENACOMM)

作者： Mobayode O. Akinsolu Isah M. Danjuma Keyur K. Mistry Bo Liu Raed A. Abd-Alhameed Pavlos I. Lazaridis Zaharias D. Zaharis Peter Excell Faculty of Arts Science and Technology Wrexham Glyndŵr University UK Faculty of Engineering and Informatics University of Bradford Bradford UK School of Computing and Engineering University of Huddersfield UK Department of Electrical and Computer Engineering Aristotle University of Thessaloniki Thessaloniki Greece

Nowadays, artificial intelligence plays a very significant role in the optimal design of microwave devices such as antennas. In particular, antenna design automation via surrogate model-based optimization (SMBO) methods is attracting a lot of interest due to the efficiency improvement in terms of computational cost. The parallel surrogate model-assisted hybrid differential evolution for antenna optimisation (PSADEA) method is a state-of-the-art SMBO method. In this paper, PSADEA is used to synthesize a compact slotted monopole antenna for ultra wide band body-centric applications. The performance of PSADEA is compared with 2019 Computer Simulation Technology - Microwave Studio (CST-MWS) optimizers: trust region framework (TRF) and particle swarm optimisation (PSO). Results from the comparisons show that PSADEA obtains very satisfactory design solutions for the monopole antenna in all runs using an affordable optimization time in each, whereas the alternative optimizers fail to obtain a satisfactory design solution in all runs. A close agreement between the simulated and measured results for the fabricated prototype of a typical PSADEA synthesized design for the monopole antenna validates the design solution quality of PSADEA.

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Machine Learning Improves the Detection of Misplaced V1 and V2 Electrodes during 12-Lead Electrocardiogram Acquisition

Machine Learning Improves the Detection of Misplaced V1 and ...

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2019 computing in Cardiology, CinC 2019

作者： Rjoob, Khaled Peace, Aaron Bond, Raymond Finlay, Dewar McGilligan, Victoria Leslie, Stephen J. Iftikhar, Aleeha Guldenring, Daniel Rababah, Ali Knoery, Charles Faculty of Computing Engineering and Built Environment Ulster University NewtownabbeyBT37 0QB United Kingdom Faculty of Life and Health Sciences Ulster University United Kingdom Department of Diabetes and Cardiovascular Science University of the Highlands and Islands Centre for Health Science Inverness United Kingdom HTW Berlin Wilhelminenhofstr 75A Berlin12459 Germany Western Health and Social Care Trust C-TRIC Ulster University United Kingdom

ISBN: (纸本)9781728169361

Electrode misplacement during 12-lead Electrocardiogram (ECG) acquisition can cause false ECG diagnosis and subsequent incorrect clinical treatment. A common misplacement error is the superior placement of V1 and V2 electrodes. The aim of the current research was to detect lead V1 and V2 misplacement using machine learning to enhance ECG data quality to improve clinical decision making. In this particular study, we reasonably assume that V1 and V2 are concurrently superiorly misplaced together. ECGs for 450 patients were extracted from body surface potential maps. Sixteen features were extracted including: morphological, statistical and time-frequency features. Two feature selection approaches (filter method and wrapper method) were applied to find an optimal set of features that provide a high accuracy. To ensure accuracy, six classifiers were applied including: fine tree, coarse tree, bagged tree, Linear Support Vector Machine (LSVM), Quadratic Support Vector Machine (QSVM) and logistic regression. The accuracy of V1 and V2 misplacement detection was 94.3% in the first ICS, 92.7% in the second ICS and 70% in third ICS respectively. Bagged tree was the best classifier in the first, second and third ICS to detect V1 and V2 misplacement. © 2019 Creative Commons.

关键词： Support vector machines

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Effect of Different Treatment Methods on the Purification of Bacterial Cellulose Produced from OPF Juice by Acetobacter Xylinum

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IOP Conference Series: Materials science and engineering 2021年第1期1092卷

作者： Nurul Athirah Raihana Nor Aziz Hashim Junaidi Zakaria Shahril Mohamad Sharifah Fathiyah Sy Mohamad Mohd Hairul Ab. Rahim Faculty of Chemical and Process Engineering Technology College of Engineering Technology Universiti Malaysia Pahang Lebuhraya Tun Razak 26300 Gambang Kuantan Pahang Malaysia Faculty of Industrial Science and Technology College of Computing and Applied Sciences Universiti Malaysia Pahang Lebuhraya Tun Razak 26300 Gambang Kuantan Pahang Malaysia

Bacterial cellulose (BC) is a form of cellulose produced by Acetobacter xylinum via fermentation process. BC contains impurities such as medium broth or the cell biomass. This study aims to determine the effect of purification method on the BC produced from oil palm frond (OPF) juice. Three purification method was presented in this study; first, BC was treated with different NaOH concentration at constant temperature of 70°C. Second, the BC was treated with different temperature while the NaOH concentration was fixed at 0.1M. Lastly, the BC was further purified in distilled water at different temperature. Fourier transform infrared spectroscopy (FTIR) and field emission scanning electron microscope (FESEM) analysis revealed that chemical composition of BC is similar to the natural cellulose without the present of biomass impurities as no peak at 1800 – 1500 cm−1 can be detected. Higher percentage for loss of biomass, 22.03 % can be obtained when the BC was treated with 1.0 M NaOH at 90°C and further purified in distilled water at 90°C. As conclusion, pure BC which are free from any impurities can be obtained by using proposed method.

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On the usage of average hausdorff distance for segmentation performance assessment: hidden bias when used for ranking

arXiv

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arXiv 2020年

作者： Aydin, Orhun Utku Taha, Abdel Aziz Hilbert, Adam Khalil, Ahmed A. Galinovic, Ivana Fiebach, Jochen B. Frey, Dietmar Madai, Vince Istvan Charité Lab for AI in Medicine Charité Universitätsmedizin Berlin Germany Research Studio Data Science Research Studios Austria Salzburg Austria Centre for Stroke Research Berlin Charité Universitätsmedizin Berlin Germany Department of Neurology Max Planck Institute for Human Cognitive and Brain Sciences Leipzig Germany School of Computing and Digital Technology Faculty of Computing Engineering and the Built Environment Birmingham City University United Kingdom

Average Hausdorff Distance (AVD) is a widely used performance measure to calculate the distance between two point sets. In medical image segmentation, AVD is used to compare ground truth images with segmentation results allowing their ranking. We identified, however, a ranking bias of AVD making it less suitable for segmentation ranking. To mitigate this bias, we present a modified calculation of AVD that we have coined balanced AVD (bAVD). To simulate segmentations for ranking, we manually created non-overlapping segmentation errors common in cerebral vessel segmentation as our use-case. Adding the created errors consecutively and randomly to the ground truth, we created sets of simulated segmentations with increasing number of errors. Each set of simulated segmentations was ranked using AVD and bAVD. We calculated the Kendall-rank-correlation-coefficient between the segmentation ranking and the number of errors in each simulated segmentation. The rankings produced by bAVD had a significantly higher average correlation (0.969) than those of AVD (0.847). In 200 total rankings, bAVD misranked 52 and AVD misranked 179 segmentations. Our proposed evaluation measure, bAVD, alleviates AVDs ranking bias making it more suitable for rankings and quality assessment of segmentations. Copyright © 2020, The Authors. All rights reserved.

关键词： Geometry

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Innovative Developments in HCI and Future Trends

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International Journal of Automation and computing 2017年第1期14卷 10-20页

作者： Mohammad S.Hasan Hongnian Yu Faculty of Computing Engineering and Sciences Staffordshire University Faculty of Science and Technology Bournemouth University

The recent developments in technology have made noteworthy positive impacts on the human-computer interaction （HCI）. It is now possible to interact with computers using voice commands, touchscreen, eye movement, hand gesture, etc. This paper compiles some of the innovative HCI progresses in various areas, e.g., specialised input/output devices, virtual or augmented reality, wearable technology, etc. It also identifies some future research directions.

关键词： Human-computer interaction （HCI） virtual reality augmented reality haptic feedback controller smart-home.

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Identifying topology in power networks in the absence of breaker status sensor signals 19

Identifying topology in power networks in the absence of bre...

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19th IEEE Mediterranean Eletrotechnical Conference, MELECON 2018

作者： Oliveira, Rui Bessa, Ricardo Iranda, Vladimiro M. INESC TEC Portugal Faculty of Engineering University of Porto Porto Portugal INESC TEC Institute for Systems and Computing Engineering Technology and Science Porto Portugal INESC TEC Faculty of Engineering University of Porto Porto Portugal

ISBN: (纸本)9781538637388

This paper presents the concept of a tapered deep neural network, subject to unsupervised training layer by layer, under a criterion of maximum entropy, to perform the estimation of breaker status in the absence of a specific sensor signal. The almost perfect prediction power of the model confirms the conjecture that the knowledge of the topology of a network is hidden in the electric measurement values in the network. A test case is presented with computing speed accelerated by using a GPU (graphics processing unit). The comparison with a previous model illustrates the superiority of the novel approach. © 2018 IEEE.

关键词： Topology

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CFRP-wrapped hollow steel tubes under axial impact loading 16th

CFRP-wrapped hollow steel tubes under axial impact loading

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16th International Symposium on Tubular Structures, ISTS 2017

作者： Batuwitage, C. Fawzia, S. Thambiratnam, D.P. Tafsirojjaman, T. Al-Mahaidi, R. Elchalakani, M. Science and Engineering Faculty Queensland University of Technology Brisbane Australia Department of Civil and Construction Engineering Swinburne University of Technology Australia School of Civil Environmental and Mining Engineering Faculty of Engineering Computing and Mathematics University of Western Australia Australia

ISBN: (纸本)9780815381341

CFRPs are widely used in the automobile industry and civil engineering applications. However, the structural behaviour of CFRP-wrapped steel hollow sections under axial impact loading is not yet fully understood. This paper evaluates the effect of impact mass on the axial impact behaviour of CFRP-wrapped steel hollow square sections. FE models were developed using LS-DYNA explicit finite element code and validated using existing experimental data. The axial impact behaviour of the tubes was evaluated by studying the responses to peak impact force, axial deflection and energy absorption. Appropriate results are presented and the trends discussed. © 2018 Taylor & Francis Group, London.

关键词： Automotive industry

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