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3rd International Conference on Information Management and Technology, ICIMTech 2018

作者： Sihombing, Harry Chandra Fajar, Ahmad Nurul Utama, Ditdit Nugeraha Mercu Buana University Master of Electrical Engineering Jakarta Indonesia Information Systems Management Department Bina Nusantara University BINUS Graduate Program-Master of Information Systems Management Jakarta11480 Indonesia Computer Science Department Bina Nusantara University BINUS Graduate Program-Master of Computer Science Jakarta11480 Indonesia

ISBN: (纸本)9781538658215

The use of instant messaging (IM) application is very communal among smartphone users, as it delivers ease in interaction and communication. The speed at which technologies, growth, and expansion of networks infrastructure for high-speed data networks (e.g. wifi, 4G, etc.) are changing and the high number of IM applications are available. IM application usage is significantly escalating, also for doing illegitimate purposes, particularly to organize and coordinate criminal acts. They are practically exploited by the criminality groups involved when they target and interact with the victims, or try to run away from criminal occurrences. By systematically conducting a review to understand and to investigate IM applications topic coming from a number of scientific sources (e.g. manuscripts, metadata, files, etc.), a broader picture and opportunity to regain the valuable evidence in the investigation is academically provided. © 2018 IEEE.

关键词： Smartphones

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Benchmark problems for transcranial ultrasound simulation: Intercomparison of compressional wave models

arXiv

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arXiv 2022年

作者： Aubry, Jean-Francois Bates, Oscar Boehm, Christian Pauly, Kim Butts Christensen, Douglas Cueto, Carlos Gélat, Pierre Guasch, Lluis Jaros, Jiri Jing, Yun Jones, Rebecca Li, Ningrui Marty, Patrick Montanaro, Hazael Neufeld, Esra Pichardo, Samuel Pinton, Gianmarco Pulkkinen, Aki Stanziola, Antonio Thielscher, Axel Treeby, Bradley Van't Wout, Elwin Physics for Medicine Paris INSERM U1273 ESPCI Paris PSL University CNRS UMR 8063 France Department of Bioengineering Imperial College London Exhibition Road LondonSW7 2AZ United Kingdom Institute of Geophysics ETH Zürich Sonneggstrasse 5 Zürich8092 Switzerland Department of Radiology Stanford University StanfordCA United States Department of Biomedical Engineering Department of Electrical and Computer Engineering University of Utah United States Department of Surgical Biotechnology Division of Surgery and Interventional Science University College London LondonNW3 2PF United Kingdom Earth Science and Engineering Department Imperial College London London United Kingdom Centre of Excellence IT4Innovations Faculty of Information Technology Brno University of Technology Bozetechova 2 Brno612 00 Czech Republic Graduate Program in Acoustics The Pennsylvania State University University Park PA16802 United States Joint Department of Biomedical Engineering University of North Carolina at Chapel Hill North Carolina State University NC United States Department of Electrical Engineering Stanford University StanfordCA United States Zurich Switzerland Laboratory for Acoustics / Noise control Empa Swiss Federal Laboratories for Materials Science and Technology Dubendorf Switzerland Zurich Switzerland Radiology and Clinical Neurosciences Departments Cumming School of Medicine University of Calgary Canada Department of Applied Physics University of Eastern Finland Kuopio70211 Finland Department of Medical Physics and Biomedical Engineering University College London Gower Street LondonWC1E 6BT United Kingdom Technical University of Denmark Denmark Danish Research Center for Magnetic Resonance Copenhagen University Hospital Hvidovre Denmark Institute for Mathematical and Computational Engineering School of Engineering and Faculty of Mathematics Pontificia Universidad Catolica de Chile Santiago Chile

Computational models of acoustic wave propagation are frequently used in transcranial ultrasound therapy, for example, to calculate the intracranial pressure field or to calculate phase delays to correct for skull distortions. To allow intercomparison between the different modeling tools and techniques used by the community, an international working group was convened to formulate a set of numerical benchmarks. Here, these benchmarks are presented, along with intercomparison results. Nine different benchmarks of increasing geometric complexity are defined. These include a single-layer planar bone immersed in water, a multi-layer bone, and a whole skull. Two transducer configurations are considered (a focused bowl and a plane piston), giving a total of 18 permutations of the benchmarks. Eleven different modeling tools are used to compute the benchmark results. The models span a wide range of numerical techniques, including the finite-difference time-domain method, angular-spectrum method, pseudospectral method, boundary-element method, and spectral-element method. Good agreement is found between the models, particularly for the position, size, and magnitude of the acoustic focus within the skull. When comparing results for each model with every other model in a cross comparison, the median values for each benchmark for the difference in focal pressure and position are less than 10% and 1 mm, respectively. The benchmark definitions, model results, and intercomparison codes are freely available to facilitate further comparisons. Copyright © 2022, The Authors. All rights reserved.

关键词： Bone

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Observation of topological polaritons and photonic magic angles in twisted van der Waals bi-layers

arXiv

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arXiv 2020年

作者： Alù, Andrea Krasnok, Alex Dai, Zhigao Wu, Jing Qiu, Cheng-Wei Wu, Yingjie Bao, Qiaoliang Si, Guangyuan Ou, Qingdong Hu, Guangwei Mazor, Yarden Zhang, Qing Department of Electrical and Computer Engineering National University of Singapore Singapore Singapore Photonics Initiative Advanced Science Research Center City University of New York New YorkNY United States Monash University ClaytonVIC Australia Melbourne Centre for Nanofabrication Victorian Node of the Australian National Fabrication Facility ClaytonVIC Australia Singapore Singapore Faculty of Materials Science and Chemistry China University of Geosciences 388 Lumo Road Wuhan430074 China Department of Electrical and Computer Engineering University of Texas at Austin AustinTX United States Physics Program Graduate Center City University of New York New YorkNY United States

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Ensembling Handcarafted Features to Representation Learning for Content Based Image Classification

Ensembling Handcarafted Features to Representation Learning ...

引用

IEEE Punecon

作者： Rik Das Khushbu Kumari P.K. Manjhi Sudeep D. Thepade Dept.of Post Graduate Program-Information Technology Xavier Institute of Social Service Ranchi Jharkhand India Dept.of Computer Applications Yogoda Satsanga Mahavidyalaya Ranchi Jharkhand India Dept.of Mathematics Vinoba Bhave University Hazaribag Jharkhand India Computer Engineering Dept. Pimpri Chinchwad College of Engineering Maharashtra India

ISBN: (数字)9781728119243

ISBN: (纸本)9781728119250

Content Based Image Classification (CBIC) has garnered massive interest within research community for it's applications and significances in multiple areas. This paper has explored a robust feature vector definition scheme based on fusion of handcrafted features to neural network based feature extraction, popularly known as representation learning. The extracted handcrafted features are primarily evaluated with classification results to identify the best color space for significant descriptor definition. Further, feature vector extraction using pre-trained Convolution Neural Network is exercised for evaluating classification performance with representation learning features. Finally, an early fusion of handcrafted feature and representation learning feature is accomplished to examine the classification performance of the model. The test bed is prepared using Wang dataset having 10 different categories of 1000 images. Six different color spaces are explored to finalize the best fit for feature extraction with the proposed handcrafted technique. Performance analyses of the proposed model have turned out to be superior compared to state-of-the-art techniques and have established the importance of fusion based approach in enhancing the accuracy of content based image classification.

关键词： Colour Intervals Color Space Hand-Crafted Features Representation Learning Fusion Classification color spaces Image classification Fusion reactions Fusion, biological Taxonomy FUSION fusion (melting) Feature extraction Learning based test bed Neural network Eigenvector

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Big Data Governance for Building A Smart Cities

Big Data Governance for Building A Smart Cities

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International Conference on ICT For Smart Society (ICISS)

作者： Novan Zulkarnain Raymond Kosala Benny Ranti Suhono Harso Supangkat Computer Science Department BINUS Graduate Program Doctor of Computer Science Information Systems Department Bina Nusantara University Jakarta Indonesia Computer Science Department Bina Nusantara University Jakarta Indonesia Computer Science Department Universitas Indonesia Depok Indonesia School of Electrical and Informatics Engineering Institute of Technology Bandung Bandung Indonesia

There have been many studies conducted related to Smart City, IT Governance and Big Data. In this study aims to find out how the relationship between the three and how to form a framework to explain it. The methodology used is qualitative by looking for some literature on smart city framework, IT Governance framework, and a Big Data framework. From these results, an overall picture of the relationship between the three is concluded, where Big Data has a role in IT Governance. and also the relationship of IT Governance to the realization of Smart City. And the final results of this study produce a framework to explain the relationship between Smart City, IT Governance and Big Data.

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A Real-time and Online Multiple-Type Object Tracking Method with Deep Features

A Real-time and Online Multiple-Type Object Tracking Method ...

引用

Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)

作者： Yi-Hsuan Hsu Jiun-In Guo Graduate Degree Program of College of Electrical and Computer Engineering National Chiao Tung University 1001 University Road Hsinchu City Taiwan R.O.C. Pervasive Artificial Intelligence Research Labs (PAIR Labs)

ISBN: (数字)9781728132488

ISBN: (纸本)9781728132495

Object tracking is one of the most important things in intelligent vision system. Meanwhile, the most challenging issue in object tracking is how to keep the target's identity unchangeable with limited power consumption. In this paper, we propose a real-time and online tracking method to track multiple types of objects (e.g. pedestrian and car). Furthermore, to handle the ID switching problem, we provide a lightweight deep learning model which can recognize the similarity of objects. It can effectively solve the ID switching problem resulted from occlusion. Finally, we do some experiments to demonstrate that the proposed method achieves the state-of-the-art performance with less power consumption. The proposed method can solve the problem of high computation of tracking and keep the high accuracy of counting results with low ID switching rate. The experimental result shows that the average counting accuracy of the proposed method can reach more than 93% on pedestrian and vehicle counting applications. Also, it shows that the proposed method improves 68.2% on average of ID switching rate than previous works.

关键词： Target tracking Switches Machine learning Computational modeling Detectors Object tracking Feature extraction

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Guaranteed methods based on constrained zonotopes for set-valued state estimation of nonlinear discrete-time systems

arXiv

引用

arXiv 2019年

作者： Rego, Brenner S. Raffo, Guilherme V. Scott, Joseph K. Raimondo, Davide M. Graduate Program in Electrical Engineering Federal University of Minas Gerais Belo Horizonte MG 31270-901 Brazil Department of Electronics Engineering Federal University of Minas Gerais Belo Horizonte MG 31270-901 Brazil Department of Chemical and Biomolecular Engineering Clemson University ClemsonSC United States Department of Electrical Computer and Biomedical Engineering University of Pavia Italy

This paper presents new methods for set-valued state estimation of nonlinear discrete-time systems with unknown-but-bounded uncertainties. A single time step involves propagating an enclosure of the system states through the nonlinear dynamics (prediction), and then enclosing the intersection of this set with a bounded-error measurement (update). When these enclosures are represented by simple sets such as intervals, ellipsoids, parallelotopes, and zonotopes, certain set operations can be very conservative. Yet, using general convex polytopes is much more computationally demanding. To address this, this paper presents two new methods, a mean value extension and a first-order Taylor extension, for efficiently propagating constrained zonotopes through nonlinear mappings. These extend existing methods for zonotopes in a consistent way. Examples show that these extensions yield tighter prediction enclosures than zonotopic estimation methods, while largely retaining the computational benefits of zonotopes. Moreover, they enable tighter update enclosures because constrained zonotopes can represent intersections much more accurately than zonotopes. Copyright © 2019, The Authors. All rights reserved.

关键词： Enclosures

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Erratum: Total variation superiorized conjugate gradient method for image reconstruction (2018 Inverse Problems 34 034001)

引用

Inverse Problems 2020年第8期36卷

作者： Marcelo V W Zibetti Chuan Lin Gabor T Herman Graduate Program in Electrical Engineering and Computer Science Federal University of Technology—Paraná Curitiba 80230-901 Brazil School of Electrical Engineering Southwest Jiaotong University Chengdu Sichuan 610031 People's Republic of China Department of Computer Science The Graduate Center City University of New York NY 10016 United States of America

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engineering chirality at wafer scale with ordered carbon nanotube architectures

引用

Nature communications 2023年第1期14卷 7380页

作者： Jacques Doumani Minhan Lou Oliver Dewey Nina Hong Jichao Fan Andrey Baydin Keshav Zahn Yohei Yomogida Kazuhiro Yanagi Matteo Pasquali Riichiro Saito Junichiro Kono Weilu Gao Department of Electrical and Computer Engineering Rice University Houston TX USA. Applied Physics Graduate Program Smalley-Curl Institute Rice University Houston TX USA. Department of Electrical and Computer Engineering The University of Utah Salt Lake City UT USA. Carbon Hub Rice University Houston TX USA. Department of Chemical and Biomolecular Engineering Rice University Houston TX USA. J.A. Woollam Co. Inc. Lincoln NE USA. Smalley-Curl Institute Rice University Houston TX USA. Department of Physics Tokyo Metropolitan University Tokyo Japan. Department of Chemistry Rice University Houston TX USA. Department of Materials Science and NanoEngineering Rice University Houston TX USA. Department of Physics Tohoku University Sendai Japan. Department of Physics National Taiwan Normal University Taipei Taiwan. Department of Physics and Astronomy Rice University Houston TX USA. Department of Electrical and Computer Engineering The University of Utah Salt Lake City UT USA. weilu.gao@utah.edu. Carbon Hub Rice University Houston TX USA. weilu.gao@utah.edu.

Creating artificial matter with controllable chirality in a simple and scalable manner brings new opportunities to diverse areas. Here we show two such methods based on controlled vacuum filtration - twist stacking and mechanical rotation - for fabricating wafer-scale chiral architectures of ordered carbon nanotubes (CNTs) with tunable and large circular dichroism (CD). By controlling the stacking angle and handedness in the twist-stacking approach, we maximize the CD response and achieve a high deep-ultraviolet ellipticity of 40 ± 1 mdeg nm. Our theoretical simulations using the transfer matrix method reproduce the experimentally observed CD spectra and further predict that an optimized film of twist-stacked CNTs can exhibit an ellipticity as high as 150 mdeg nm, corresponding to a g factor of 0.22. Furthermore, the mechanical rotation method not only accelerates the fabrication of twisted structures but also produces both chiralities simultaneously in a single sample, in a single run, and in a controllable manner. The created wafer-scale objects represent an alternative type of synthetic chiral matter consisting of ordered quantum wires whose macroscopic properties are governed by nanoscopic electronic signatures and can be used to explore chiral phenomena and develop chiral photonic and optoelectronic devices.

关键词：

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cytoNet: Network Analysis of Cell Communities

SSRN

引用

SSRN 2019年

作者： Mahadevan, Arun S. Long, Byron L. Hu, Chenyue Wendy Ryan, David T. Britton, George L. Ligeralde, Andrew Robinson, Jacob T. Warmflash, Aryeh Qutub, Amina Ann Department of Biomedical Engineering University of Pennsylvania Department of Biomedical Engineering University of Texas San Antonio United States Department of Bioengineering Rice University Systems Synthetic and Physical Biology Program Rice University Department of Electrical and Computer Engineering Rice University The Department of Biosciences Rice University Biophysics Graduate Program University of California Berkeley United States

We introduce cytoNet, a method to characterize multicellular topology from microscopy images. Accessible through a web-based interface, cytoNet quantifies the spatial relationships in cell communities using principles of graph theory, and evaluates the effect of cell-cell interactions on individual cell phenotypes. We demonstrate cytoNet’s capabilities in two applications relevant to regenerative medicine: quantifying the morphological response of endothelial cells to neurotrophic factors present in the brain after injury, and characterizing cell cycle dynamics of differentiating neural progenitor cells. The framework introduced here can be used to study complex cell communities in a quantitative manner, leading to a deeper understanding of environmental effects on cellular behavior. © 2019, The Authors. All rights reserved.

关键词： Endothelial cells

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