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3rd International Conference on science in Information Technology, ICSITech 2017

作者： Lawi, Armin Wungo, Supriyadi La Manjang, Salama Department of Computer Science Post-graduate Program of Electrical Engineering Dept. Electrical Engineering Universitas Hasanuddin Makassar Indonesia

ISBN: (纸本)9781509058662

This study aims to implement a machine learning technique in identifying the irregularities of customer behavior on the use of prepaid electricity pulses. The methods used are Linear Discriminant Analysis and Logistic Regression. The performance of the classification system will be evaluated using the 10-fold cross-validation technique. Validation results are measured using accuracy, precision and recall values. In this research shows that the use of machine learning technique has a good performance in classification of electrical consumption behavior. Experimental results with the different amount of data testing indicate that Logistic Regression method has high accuracy, precision, and recall value when compared with Linear Discriminant Analysis that is 100%. This is due to Logistic Regression method can predict irregularities accurately because the addition of the amount of data does not affect the performance of the method. © 2017 IEEE.

关键词： Regression analysis

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Progressive cyber-human intelligence for social good

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Interactions 2018年第4期25卷 52-56页

作者： Rikakis, Thanassis Kelliher, Aisling Huang, Jia-Bin Sundaram, Hari Department of Bioengineering Virginia Tech United States Department of Computer Science Institute for Creativity Arts and Technology Virginia Tech United States Bradley Electrical and Computer Engineering Department Virginia Tech United States Computer Science and Advertising Departments University of Illinois at Urbana-Champaign United States

There is little doubt at this point that the growth and maturation of AI will be a major influence on the economy and society overall. Significant work is underway both on advancing AI and on combining human and artificial intelligence to improve the functionality and user experience of AI-based methods, tools, and services. Advanced AI is successfully reshaping many transactional contexts such as image search and purchase recommendations, as well as contexts that involve repetitive activity, such as manufacturing. However, AI is progressing much more slowly in contexts that involve rich experiences aimed at advancing human intelligence and the overall human condition -- for example, in education. A potentially unintended consequence of this is increased emphasis on the lower-hanging fruit of transactional and repetitive contexts, and less emphasis on the more complex human-development contexts that are critical for a healthy society. This article proposes a design approach for tackling the integration of AI into human-development contexts while promoting the development of new forms of cyber-human intelligence.

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Metasurfaces for next-generation wireless communication systems

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National science Review 2023年第8期10卷 17-19页

作者： Younes Ra'di Nikita Nefedkin Petar Popovski Andrea Alù Department of Electrical Engineering and Computer Science Syracuse University Photonics Initiative Advanced Science Research Center City University of New York Department of Electronic Systems Aalborg University Physics Program Graduate Center City University of New York

The pace of development in the world of 5G communication systems has proven to be much more demanding than previous generations, with 5G-Advanced seemingly around the corner [1]. Extensive research is already underway to structure the next generation of wireless systems(i.e. 6G), which may potentially enable an unprecedented level of human–machine interaction [2].

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A Flexible Renewal Process Simulator for Neural Spike Trains

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IEEE Transactions on Biomedical engineering 1976年第3期BME-23卷 262-266页

作者： Belanger, Barry F. Williams, William J. Yin, Tom C. T. Bioelectrical Sciences Laboratory Department of Electrical and Computer Engineering and the Bioengineering Program University of Michigan Ann Arbor MI 48109. United States

Certain neuronal spike trains may be viewed as stochastic, nonhomogeneous point process. Neuronal information may be encoded in the time-varying mean rate of the spike train in some cases. For this purpose the simulat... 详细信息

关键词： Humans Heart Bioelectric phenomena Testing Cardiology Myocardium Neurons Laboratories Thorax Signal analysis

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Optimal Placement of Software Monitors Aiding Systematic Testing

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IEEE Transactions on Software engineering 1975年第4期SE-1卷 403-411页

作者： Ramamoorthy, C.V. Kim, K.H. Chen, W.T. Computer Science Division Department of Electrical Engineering and Computer Sciences University of California Berkeley Calif 94720 United States Department of Electrical Engineering Systems and Computer Science Program University of Southern California Los Angeles Calif. United States

The usefulness of software monitors in testing large ‘programs is discussed. Several types of testing strategies based on the use of monitors are surveyed. Since there is a computational overhead involved in employing monitors, attempts are made to minimize the number of monitors employed. This optimization problem is formulated and analyzed in graph-theoretic terms. Implementation aspects are considered through both discussion and examples. Copyright © 1975 by The Institute of electrical and Electronics Engineers, Inc.

关键词： Optimal placement overhead program testing software monitor test-input test-output test-path test-run

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All-optical image denoising using a diffractive visual processor

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Light(science & Applications) 2024年第3期13卷 429-445页

作者： Çağatay Işıl Tianyi Gan Fazil Onuralp Ardic Koray Mentesoglu Jagrit Digani Huseyin Karaca Hanlong Chen Jingxi Li Deniz Mengu Mona Jarrahi Kaan Akşit Aydogan Ozcan Electrical and Computer Engineering Department University of CaliforniaLos AngelesCA 90095USA Bioengineering Department University of CaliforniaLos AngelesCA 90095USA California NanoSystems Institute(CNSI) University of CaliforniaLos AngelesCA 90095USA University College London Department of Computer ScienceLondonUnited Kingdom

Image denoising,one of the essential inverse problems,targets to remove noise/artifacts from input *** general,digital image denoising algorithms,executed on computers,present latency due to several iterations implemented in,e.g.,graphics processing units(GPUs).While deep learning-enabled methods can operate non-iteratively,they also introduce latency and impose a significant computational burden,leading to increased power ***,we introduce an analog diffractive image denoiser to all-optically and non-iteratively clean various forms of noise and artifacts from input images–implemented at the speed of light propagation within a thin diffractive visual processor that axially spans<250×λ,whereλis the wavelength of *** all-optical image denoiser comprises passive transmissive layers optimized using deep learning to physically scatter the optical modes that represent various noise features,causing them to miss the output image Field-of-View(FoV)while retaining the object features of *** results show that these diffractive denoisers can efficiently remove salt and pepper noise and image rendering-related spatial artifacts from input phase or intensity images while achieving an output power efficiency of~30–40%.We experimentally demonstrated the effectiveness of this analog denoiser architecture using a 3D-printed diffractive visual processor operating at the terahertz *** to their speed,power-efficiency,and minimal computational overhead,all-optical diffractive denoisers can be transformative for various image display and projection systems,including,e.g.,holographic displays.

关键词： remove rendering holographic

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Motion tracked 3D Visualization system for Segmented ROI in medical imaging 2021

Motion tracked 3D Visualization system for Segmented ROI in ...

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7th International Conference on Arab Women in Computing, ArabWIC 2021

作者： Yaghi, Maha Zia, Huma Hajjdiab, Hassan El-Baz, Ayman Ghazal, Mohammed Electrical Computer and Biomedical Engineering Department Abu Dhabi University United Arab Emirates Computer Science Department Concordia University Bioengineering Department University of Louisville

ISBN: (纸本)9781450384186

computer-aided diagnosis systems are increasingly used in the detection and segmentation of abnormalities in medical imaging. However, in many borderline cases, radiologists and physicians need to analyze the images to confirm the diagnosis. This paper proposes a novel analysis system for visualizing the output of 3D segmented abnormalities and the associated computer diagnoses. We use motion trackers to localize the user's viewing device and estimate its 3D orientation. We then use this tracking data to slice the segmented and labeled volume showing the abnormalities in real-time. The user can switch between the labeled and raw views to analyze the abnormalities' boundaries. To test our visualization, we use our brain tumor segmentation pipeline using MRI scans to produce a labeled image and slice and visualize the tumor from all angles. Our system has a low latency of 0.01 seconds and can identify the viewing device's 3D location and orientation within a maximum of 0.2 cm and 2 degrees of error, respectively. The accuracy of our system depends on the segmentation pipeline. Our proposed system is also useful for medical training and as a visual feedback tool for computer-aided system's researchers and developers. © 2021 Association for Computing Machinery.

关键词： Magnetic resonance imaging

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Three-dimensional fourier-transform second-harmonic generation microscopy for quantification of collagen fiber organization in biological tissues

Three-dimensional fourier-transform second-harmonic generati...

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Frontiers in Optics, FIO 2012

作者： Lau, Tung-Yuen Ambekar, Raghu Toussaint, Kimani C. United States Department of Mechanical Science and Engineering United States Department of Electrical and Computer Engineering United States Departments of Electrical and Computer Engineering and Bioengineering University of Illinois Urbana-Champaign IL 61820 United States

Fourier transform-second harmonic generation imaging has previously been shown to be useful in quantifying collagen fiber organization in 2D. Here, we generalize this approach to 3D and calculate preferred fiber orien... 详细信息

ISBN: (纸本)9781557529565

关键词： Harmonic generation

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Machine learning for improved current-density reconstruction from two-dimensional vector magnetic images

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Physical Review Applied 2025年第3期23卷 034035-034035页

作者： Niko R. Reed Danyal Bhutto Matthew J. Turner Declan M. Daly Sean M. Oliver Jiashen Tang Kevin S. Olsson Nicholas Langellier Mark J.H. Ku Department of Physics University of Maryland College Park Maryland USA Quantum Technology Center University of Maryland College Park Maryland USA Joint Quantum Institute University of Maryland College Park Maryland USA Department of Biomedical Engineering Boston University Boston Massachusetts USA A. A. Martinos Center for Biomedical Imaging Massachusetts General Hospital Charlestown Massachusetts USA Department of Electrical and Computer Engineering University of Maryland College Park Maryland USA The MITRE Corporation McLean Virginia 22102 USA Intelligence Community Postdoctoral Research Fellowship Program University of Maryland College Park Maryland 20742 USA Department of Physics Harvard University Cambridge Massachusetts USA Present address: VideaHealth Inc. Boston MA. Department of Materials Science and Engineering University of Delaware Newark Delaware 19716 USA Department of Physics and Astronomy University of Delaware Newark Delaware 19716 USA Present address: Northrop Grumman Mission Systems Linthicum Maryland 21090 USA.

The reconstruction of electrical current densities from magnetic field measurements is an important technique with applications in materials science, circuit design, quality control, plasma physics, and biology. Analytic reconstruction methods exist for planar currents, but break down in the presence of high-spatial-frequency noise or large standoff distance, restricting the types of systems that can be studied. Here, we demonstrate the use of a deep convolutional neural network for current density reconstruction from two-dimensional images of vector magnetic fields acquired by a quantum diamond microscope . Trained network performance significantly exceeds analytic reconstruction for data with high noise or large standoff distances. This machine learning technique can perform quality inversions on lower-signal-to-noise-ratio data, significantly reducing the data collection time and permitting reconstructions of weaker and three-dimensional current sources.

关键词： Signal to noise ratio

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Effect of electrolyte anions on the cycle life of a polymer electrode in aqueous batteries

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escience 2022年第1期2卷 110-115页

作者： Ye Zhang Lihong Zhao Yanliang Liang Xiaojun Wang Yan Yao Department of Electrical and Computer Engineering Materials Science and Engineering ProgramUniversity of HoustonHoustonTX77204USA Texas Center for Superconductivity at the University of Houston HoustonTX77204USA

Redox polymers are a class of high-capacity, low-cost electrode materials for electrochemical energy storage, butthe mechanisms governing their cycling stability are not well understood. Here we investigate the effect of anionson the longevity of a p-dopable polymer through comparing two aqueous zinc-based electrolytes. Galvanostaticcycling studies reveal the polymer has better capacity retention in the presence of triflate anions than that withsulfate anions. Based on electrode microstructural analysis and evolution profiles of the cell stacking pressure, theorigin of capacity decay is ascribed to mechanical fractures induced by volume change of the polymer activematerials during repeated cycling. The volume change of the polymer with the triflate anion is 61% less than thatwith the sulfate anion, resulting in fewer cracks in the electrodes. The difference is related to the different anionsolvation structures—the triflate anion has fewer solvated water molecules compared with the sulfate anion,leading to smaller volume expansion. This work highlights that anions with low solvation degree are preferablefor long-term cycling.

关键词： Aqueous batteries Polymer electrode Anions Volume chang

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