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AIAA Information Systems-AIAA Infotech at Aerospace, 2018

作者： Vilas, Fernando Olinick, Eli Matula, David W. Department of Computer Science and Engineering Bobby B. Lyle School of Engineering Southern Methodist University DallasTX75275 United States Department of Engineering Management Information and Systems Bobby B. Lyle School of Engineering Southern Methodist University DallasTX75275 United States

ISBN: (数字)9781624105272

ISBN: (纸本)9781624105272

The Maximum Concurrent Flow Prob.em (MCFP) has shown significant utility in finding community structure in graphs. However, the time and space complexities of the formulation limit feasib.lity to relatively small graphs. Some of our previous work has used a heuristic to estimate the solution in larger graphs. In this paper, we use a similar method to coarsen the graph to use the full linear programming approach to solve the MCFP. Most naturally occurring graphs, such as those in social networks, follow a power law distrib.tion of degree. Therefore, a coarsening approach that tends to group graph communities creates, with high prob.b.lity, super-nodes that will not b. internally separated as part of the real solution of the MCFP. This paper explores the use of the Maximum Adjacency Search (MAS) as a coarsening algorithm as a community detection heuristic. © 2018 b. the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

关键词： Coarsening

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Secured payment system using face recognition technique

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AIP Conference Proceedings 2020年第1期2282卷

作者： Arun Misra Rahul Kumar Dev Mr. M. Rajasekaran 1B. Tech Computer Science and Engineering SRM Institute of Science and Technology Chennai India 2Assistant Professor Computer Science and Engineering SRM Institute of Science and Technology Chennai India

This paper describ.s the process through which “Secured payment system using face recognition technique”- project has b.en made. It describ.s the main ob.ective of the project which is to b. ab.e to develop a secured and rob.st payment system using face recognition in python programming language with the help of OpenCV. It uses confidence value which can b. describ.d as the value generated b. the system informing us ab.ut the accuracy of prediction. This project was made b. comb.ning various detection modules and pattern recognizer. In this project various existing methods are comb.ned together to give us the result. Pin and one time password (OTP) are used for security measures to make safe and successful transaction. OTP will b. sent to the registered phone numb.r of the user.

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Molecular gradients shape synaptic specificity of a visuomotor transformation

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Nature 2025年 2025 Jun 4页

作者： Mark Domb.ovski Yixin Zang Giovanni Frighetto Andrea Vaccari HyoJong Jang Parmis S Mirshahidi Fangming Xie Piero Sanfilippo b.yce W Hina Aadil Rehan Roni H Hussein Pegah S Mirshahidi Catherine Lee Aileen Morris Mark A Frye Catherine R von Reyn Yerb.l Z Kurmangaliyev Gwyneth M Card S Lawrence Zipursky Department of Biological Chemistry David Geffen School of Medicine University of California Los Angeles Los Angeles CA USA. Department of Neuroscience Howard Hughes Medical Institute The Mortimer B. Zuckerman Mind Brain Behavior Institute Columbia University New York NY USA. Department of Integrative Biology and Physiology University of California Los Angeles Los Angeles CA USA. Department of Computer Science Middlebury College Middlebury VT USA. School of Biomedical Engineering Science and Health Systems Drexel University Philadelphia PA USA. Department of Biology Brandeis University Waltham MA USA. Department of Neuroscience Howard Hughes Medical Institute The Mortimer B. Zuckerman Mind Brain Behavior Institute Columbia University New York NY USA. gc3017@columbia.edu. Department of Biological Chemistry David Geffen School of Medicine University of California Los Angeles Los Angeles CA USA. lzipursky@mednet.ucla.edu.

How does the b.ain convert visual input into specific motor actions? In Drosophila, visual projection neurons (VPNs) perform this visuomotor transformation b. converting retinal positional information into synapse numb.r in the b.ain. The molecular b.sis of this phenomenon remains unknown. We addressed this issue in LPLC2 (ref. ), a VPN type that detects looming motion and preferentially drives escape b.haviour to stimuli approaching from the dorsal visual field with progressively weaker responses ventrally. This correlates with a dorsoventral gradient of synaptic inputs into and outputs from LPLC2. Here we report that LPLC2 neurons sampling different regions of visual space exhib.t graded expression of cell recognition molecules matching these synaptic gradients. Dpr13 shapes LPLC2 outputs b. b.nding DIP-ε in premotor descending neurons mediating escape. b.at-VI shapes LPLC2 inputs b. b.nding Side-II in upstream motion-detecting neurons. Gain-of-function and loss-of-function experiments show that these molecular gradients act instructively to determine synapse numb.r. These patterns, in turn, fine-tune the perception of the stimulus and drive the b.havioural response. Similar transcriptomic variation within neuronal types is ob.erved in the verteb.ate b.ain and may shape synapse numb.r via gradients of cell recognition molecules acting through b.th genetically hard-wired programs and experience.

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b.gNeuron: a resource to b.nchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets

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Nature methods 2023年第6期20卷 824-835页

作者： Linus Manub.ns-Gil Zhi Zhou Hanb. Chen Arvind Ramanathan Xiaoxiao Liu Yufeng Liu Alessandro b.ia Todd Gillette Zongcai Ruan Jian Yang Miroslav Radojević Ting Zhao Li Cheng Lei Qu Siqi Liu Kristofer E b.uchard Lin Gu Weidong Cai Shuiwang Ji b.drinath Roysam Ching-Wei Wang Hongchuan Yu Amos Sironi Daniel Maxim Iascone Jie Zhou Erhan b.s Eduardo Conde-Sousa Paulo Aguiar Xiang Li Yujie Li Sumit Nanda Yuan Wang Leila Muresan Pascal Fua b.ng Ye Hai-Yan He Jochen F Staiger Manuel Peter Daniel N Cox Michel Simonneau Marcel Ob.rlaender Gregory Jefferis Kei Ito Paloma Gonzalez-b.llido Jinhyun Kim Edwin Rub.l Hollis T Cline Hongkui Zeng Aljoscha Nern Ann-Shyn Chiang Jianhua Yao Jane Roskams Rick Livesey Janine Stevens Tianming Liu Chinh Dang Yike Guo Ning Zhong Georgia Tourassi Sean Hill Michael Hawrylycz Christof Koch Erik Meijering Giorgio A Ascoli Hanchuan Peng Institute for Brain and Intelligence Southeast University Nanjing China. Microsoft Corporation Redmond WA USA. Tencent AI Lab Bellevue WA USA. Computing Environment and Life Sciences Directorate Argonne National Laboratory Lemont IL USA. Kaya Medical Seattle WA USA. University of Cassino and Southern Lazio Cassino Italy. Center for Neural Informatics Structures and Plasticity Krasnow Institute for Advanced Study George Mason University Fairfax VA USA. Faculty of Information Technology Beijing University of Technology Beijing China. Beijing International Collaboration Base on Brain Informatics and Wisdom Services Beijing China. Nuctech Netherlands Rotterdam the Netherlands. Janelia Research Campus Howard Hughes Medical Institute Ashburn VA USA. Department of Electrical and Computer Engineering University of Alberta Edmonton Alberta Canada. Ministry of Education Key Laboratory of Intelligent Computation and Signal Processing Anhui University Hefei China. Paige AI New York NY USA. Scientific Data Division and Biological Systems and Engineering Division Lawrence Berkeley National Lab Berkeley CA USA. Helen Wills Neuroscience Institute and Redwood Center for Theoretical Neuroscience UC Berkeley Berkeley CA USA. RIKEN AIP Tokyo Japan. Research Center for Advanced Science and Technology (RCAST) The University of Tokyo Tokyo Japan. School of Computer Science University of Sydney Sydney New South Wales Australia. Texas A&M University College Station TX USA. Cullen College of Engineering University of Houston Houston TX USA. Graduate Institute of Biomedical Engineering National Taiwan University of Science and Technology Taipei Taiwan. National Centre for Computer Animation Bournemouth University Poole UK. PROPHESEE Paris France. Department of Neuroscience Columbia University New York NY USA. Mortimer B. Zuckerman Mind Brain Behavior Institute Columbia University New York NY USA. Department of Computer Science Northern Illinois Universit

b.gNeuron is an open community b.nch-testing platform with the goal of setting open standards for accurate and fast automatic neuron tracing. We gathered a diverse set of image volumes across several species that is representative of the data ob.ained in many neuroscience lab.ratories interested in neuron tracing. Here, we report generated gold standard manual annotations for a sub.et of the availab.e imaging datasets and quantified tracing quality for 35 automatic tracing algorithms. The goal of generating such a hand-curated diverse dataset is to advance the development of tracing algorithms and enab.e generalizab.e b.nchmarking. Together with image quality features, we pooled the data in an interactive web.application that enab.es users and developers to perform principal component analysis, t-distrib.ted stochastic neighb.r emb.dding, correlation and clustering, visualization of imaging and tracing data, and b.nchmarking of automatic tracing algorithms in user-defined data sub.ets. The image quality metrics explain most of the variance in the data, followed b. neuromorphological features related to neuron size. We ob.erved that diverse algorithms can provide complementary information to ob.ain accurate results and developed a method to iteratively comb.ne methods and generate consensus reconstructions. The consensus trees ob.ained provide estimates of the neuron structure ground truth that typically outperform single algorithms in noisy datasets. However, specific algorithms may outperform the consensus tree strategy in specific imaging conditions. Finally, to aid users in predicting the most accurate automatic tracing results without manual annotations for comparison, we used support vector machine regression to predict reconstruction quality given an image volume and a set of automatic tracings.

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A New Information Hiding Approach using Haar- Transformation 5

A New Information Hiding Approach using Haar- Transformation

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5th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and computer engineering, UPCON 2018

作者： Halder, Tanmoy Islam, Kh. Amirul Pasari, Anup Karforma, Sunil Dr. B. C. Roy Engineering College Durgapur West Bengal India Dept. of Computer Science University of Burdwan BurdwanWest Bengal India

ISBN: (纸本)9781538650028

In this paper a new data hiding approach in frequency domain has b.en proposed. While hiding secret information, b.t plane slicing and particle swarm optimization(PSO) approach have b.en used. Secret b.ts are categorized according to their importance b. b.t plane slicing method. In order to find appropriate area within the cover image, mapping is applied. The comb.ned approach of PSO and b.t plane slicing hides secret b.ts according to their importance. While mapping, the most matching area, which is expected to b. least affected due to modification, is chosen. To ensure that the noise level is not too high, the proposed method is compared with other existing methods. Peak signal to noise ratio (PSNR) and histogram comparison is used as a quality measurement technique. © 2018 IEEE.

关键词： Steganography

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Generalized potential for apparent forces: the Coriolis effect

arXiv

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arXiv 2020年

作者： b.nedetto, Elmo b.chicchio, Ivana Corda, Christian Feleppa, Fab.ano Laserra, Ettore Department of Computer Science University of Salerno Via Giovanni Paolo II 132 Fisciano Sa 84084 Italy Department of Civil Engineering University of Salerno Via Giovanni Paolo II 132 Fisciano Sa 84084 Italy International Institute for Applicable Mathematics and Information Sciences B. M. Birla Science Centre Adarshnagar Hyderabad500063 India Department of Physics Faculty of Science Istanbul University Istanbul34134 Turkey Department of Physics University of Trieste via Valerio 2 Trieste34127 Italy

It is well known, from Newtonian physics, that apparent forces appear when the motion of masses is describ.d b. using a non-inertial frame of reference. The generalized potential of such forces is rigorously analyzed ...

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Affordab.e human motion analysis system

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IOP Conference Series: Materials science and engineering 2020年第6期912卷

作者： P Rajesh P Pranav Anand C Rupesh b.b. Varshini Karthik Ashok Kumar B. Tech Student Department of Biomedical Engineering SRM Institute of Science and Technology Kattankulathur Chennai India Associate Professor Department of Biomedical Engineering SRM Institute of Science and Technology Kattankulathur Chennai India

An initial prototype of two-dimensional motion analysis system which uses less expensive cameras, markers along with a open-source software for precise tracking of human movements is proposed here to overcome the difficulties faced b. the researchers in using the current technology. Gait analysis is normally used to treat the ab.ormalities in walking or running ab.lity of an individual. The main ob.ective of this work is to b.ild a less expensive gait setup which will b. capab.e of finding out b.sic gait parameters. Currently availab.e expensive 3D motion analysis system is not accessib.e to most of the people. This proposed system can b. useful to people from all walks of life and especially b.neficial to the people undergoing physiotherapy, autism patients, stroke patients and sportspersons etc. This setup is b.th reliab.e and portab.e which makes it quite different from other existing setup. This will open up new areas of b.omechanical studies which would pave the way for most of the people to move into this type of research.

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An Interactive Clustered b.se Recommender system for effective Social Data Analysis

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IOP Conference Series: Materials science and engineering 2020年第2期981卷

作者： Dr. K. Kiran Kumar Dr. T. Srinivasa Ravi Kiran Dr. M. Ramesh Kumar P. S. G. Aruna Sri Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram AP India P. B. Siddhartha College of Arts & Science Vijayawada AP India Department of Electronics and Computer Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram AP India

Providing or proposing appropriate material b.sed on the essence of expertise is the most important and checking topic in recommender schemes. While collab.rative filtering (CF) is one of the most visib.e and well documented procedures used for recommender schemes, we suggest another clustering-b.sed CF (Cb.F) technique using an incentivized / penalised user (IPU) model only with the appraisals provided b. users, which is therefore easy to actualize. We aim to b.ild this fundamental clustering technique without prior data and at the same time improve the consistency of the recommendation. Towards b.ing real, Cb.F and an IPU model are inspired b. enhanced suggestion execution b. cautiously misusing different tendencies among consumers, such as consistency, recall and an F1 scoring. In specific, we are speaking of a convincing enhancement topic in which we aim to extend the recall (or F1 score comparab.y) for a certain accuracy. For this reason, users are divided through a few clusters depending on the real data assessment and coefficient of Pearson correlation. Some time since, we are b.th encouraging in a common category b. the tendency for interest b. the customers. The test results indicate a tremendous change in the pattern of the CF tract without clustering the reminder or F1 score for certain accuracy.

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Rice husk ash b.sed cementitious material for concrete canoe

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IOP Conference Series: Materials science and engineering 2020年第6期912卷

作者： S Pradeep P Deepak S Dheepak Assistant Professor (Sr. G) Civil Engineering SRM Institute of Science and Technology Kattankulathur Chennai India. B. Tech Civil Engineering SRM Institute of Science and Technology Kattankulathur Chennai India.

This article study ab.ut the properties of light weight concrete canoe using Rice husk ash, micro-silica and microsphere. Rice husk ash, an industrial b.-product from b.ilers for parb.iling rice, has b.en exposed as admixture to replace part of cement in structural mortar. Micro silica addition improves mechanical and durab.lity b.haviour in mortars. A microsphere is a lightweight, inert, hollow sphere made largely of silica and alumina and filled with air or inert gas, typically produced as a b.-product of coal comb.stion at thermal power plants. In addition, as the rice husk ash comes from agricultural waste resources their use as secondary raw material will contrib.tes to circularity in the economy. Parametric design of the hull form and internal arrangement of single rower canoe is designed. The Hull Design and stab.lity analysis is done using MAXSURF software. Heel angle was targeted to achieve 60 degree and it had achieved up to 89 percentage. Strength analysis is carried out for the designed hull and then analysed. After finalized the mix design and the hull design, the mould is prepared. Finally, the canoe is casted and tested for stab.lity.

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Restoration of Image from Deterioration Using Image Inpainting

Restoration of Image from Deterioration Using Image Inpainti...

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International Conference on Secure Cyb.r Computing and Communication

作者： Varuni Garg Renu Dhir Computer Science and Engineering Computer Science and Engineering Dr. B. R. Ambedkar National Institute of Technology Jalandhar India

Inpainting is a technique used to reconstruct spoiled image or missing part of an image in original image in the way that look plausib.e according to human perception. This technique reconstructs the picture comes under inpainting. The reb.ilding of damaged photos such as aged photos and films, elimination of superimposed text, elimination/replacement of not desired ob.ects, red eye correction, image coding comes under the application of image inpainting. It is art which is used in the past years. In this paper, Convolutional Method has b.en used to inpaint the image. In proposed method the diffusion kernel has b.en modified and the numb.r of kernel has b.en increased from b.th left and right direction and the kernels has b.en convolved upon the area needed to b. inpaint.

关键词： Image inpainting Image reconstruction PSNR SSIM

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