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International Conference on Advances in Computing, Communications and Informatics (ICACCI)

作者： R Ani Greeshma Sasi U Resmi Sankar O. S. Deepa Department of Computer Science and Applications Amrita school of Engineering Amrita Vishwa Vidyapeetham Coimbatore Tamil Nadu IN Department of Computer Science and Applications Coimbatore Amrita Vishwa Vidyapeetham Amrita University India

ISBN: (纸本)9781509020300

Chronic Renal Failure (CRF) is one of the major disease which affect the human life. The stages of CRF start with loss of renal functions and gradually it leads to complete failure of all kidney functions. This disease is fatal at its end stage unless a replacement of kidney or a dialysis process which is an artificial filtering mechanism is not done. So an early prediction of disease is very important to save the human life. Machine learning is a part of artificial intelligence that uses a variety of techniques to learn from complex dataset. Machine learning techniques are widely used in medical field for disease prediction and prognosis. The objective of this work is to develop a clinical decision support system using machine learning techniques. In this paper first the classification techniques like neural network based back propagation (BPN), probability based Naive Bayes, LDA classifier, lazy learner K Nearest Neighbor (KNN), tree based decision tree, and Random subspace classification algorithms are analyzed. The accuracy of each algorithm found is 81.5%, 78%, 76%, 90%, 93% and 94% respectively on a dataset collected from UCI repository which contains 25 attributes and 400 instances. From the results obtained, the algorithm which gave better result was used for the developing the Clinical Decision Support System.

关键词： Diseases Decision trees Kidney Decision support systems Training Prediction algorithms Biological neural networks

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Finding quadruply imaged quasars with machine learning. I. Methods

arXiv

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arXiv 2021年

作者： Akhazhanov, A. More, A. Amini, A. Hazlett, C. Treu, Tommaso Birrer, S. Shajib, A. Schechter, P. Lemon, C. Nord, B. Aguena, M. Allam, S. Andrade-Oliveira, F. Annis, J. Brooks, D. Buckley-Geer, E. Burke, D.L. Rosell, A. Carnero Kind, M. Carrasco Carretero, J. Choi, A. Conselice, C. Costanzi, M. Da Costa, L.N. Pereira, M.E.S. De Vicente, J. Desai, S. Dietrich, J.P. Doel, P. Everett, S. Ferrero, I. Finley, D.A. Flaugher, B. Frieman, J. García-Bellido, J. Gerdes, D.W. Gruen, D. Gruendl, R.A. Gschwend, J. Gutierrez, G. Hinton, S.R. Hollowood, D.L. Honscheid, K. James, D.J. Kim, A.G. Kuehn, K. Kuropatkin, N. Lahav, O. Lima, M. Lin, H. Maia, M.A.G. March, M. Menanteau, F. Miquel, R. Morgan, R. Palmese, A. Paz-Chinchón, F. Pieres, A. Malagón, A. A. Plazas Sanchez, E. Scarpine, V. Serrano, S. Sevilla-Noarbe, I. Smith, M. Soares-Santos, M. Suchyta, E. Swanson, M.E.C. Tarle, G. To, C. Varga, T.N. Weller, J. Department of Electrical and Computer Engineering University of California Los AngelesCA90095 United States Department of Electrical and Computer Engineering Nazarbayev University Nur-Sultan Kazakhstan Post Bag 4 Ganeshkhind Pune411007 India UTIAS The University of Tokyo Kashiwa Chiba277-8583 Japan Department of Statistics University of California Los AngelesCA90095 United States Department of Political Science University of California Los AngelesCA90095 United States Department of Physics and Astronomy PAB 430 Portola Plaza Box 951547 Los AngelesCA90095-1547 United States Graduate School of Education Stanford University 160 450 Serra Mall StanfordCA94305 United States Department of Astronomy & Astrophysics University of Chicago ChicagoIL60637 United States MIT Kavli Institute for Astrophysics and Space Research 37-664G 77 Massachusetts Avenue CambridgeMA02139 United States Observatoire de Sauverny VersoixCH-1290 Switzerland Fermi National Accelerator Laboratory P. O. Box 500 BataviaIL60510 United States Kavli Institute for Cosmological Physics University of Chicago ChicagoIL60637 United States Laboratório Interinstitucional de e-Astronomia - LIneA Rua Gal. José Cristino 77 RJ Rio de Janeiro20921-400 Brazil Instituto de Física Teórica Universidade Estadual Paulista São Paulo Brazil Department of Physics & Astronomy University College London Gower Street LondonWC1E 6BT United Kingdom Kavli Institute for Particle Astrophysics & Cosmology Stanford University P. O. Box 2450 StanfordCA94305 United States SLAC National Accelerator Laboratory Menlo ParkCA94025 United States Center for Astrophysical Surveys National Center for Supercomputing Applications 1205 West Clark St. UrbanaIL61801 United States Department of Astronomy University of Illinois at Urbana-Champaign 1002 W. Green Street UrbanaIL61801 United States The Barcelona Institute of Science and Technology Campus UAB Barcelona08193 Spain Center for Cos

Strongly lensed quadruply imaged quasars (quads) are extraordinary objects. They are very rare in the sky - only a few tens are known to date - and yet they provide unique information about a wide range of topics, including the expansion history and the composition of the Universe, the distribution of stars and dark matter in galaxies, the host galaxies of quasars, and the stellar initial mass function. Finding them in astronomical images is a classic "needle in a haystack" problem, as they are outnumbered by other (contaminant) sources by many orders of magnitude. To solve this problem, we develop state-of-the-art deep learning methods and train them on realistic simulated quads based on real images of galaxies taken from the Dark Energy Survey, with realistic source and deflector models, including the chromatic effects of microlensing. The performance of the best methods on a mixture of simulated and real objects is excellent, yielding area under the receiver operating curve in the range 0.86 to 0.89. Recall is close to 100% down to total magnitude i ∼ 21 indicating high completeness, while precision declines from 85% to 70% in the range i ∼ 17 - 21. The methods are extremely fast: training on 2 million samples takes 20 hours on a GPU machine, and 108 multi-band cutouts can be evaluated per GPU-hour. The speed and performance of the method pave the way to apply it to large samples of astronomical sources, bypassing the need for photometric pre-selection that is likely to be a major cause of incompleteness in current samples of known quads. © 2021, CC BY.

关键词： Galaxies

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Privacy-preserving anomaly detection across multi-domain for software defined networks 7th

Privacy-preserving anomaly detection across multi-domain for...

引用

7th International Conference on the Theory, Technologies and applications of Trusted Systems, INTRUST 2015

作者： Bian, Huishan Zhu, Liehuang Shen, Meng Wang, Mingzhong Xu, Chang Zhang, Qiongyu Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications School of Computer Science Beijing Institute of Technology Beijing China Nanjing China University of the Sunshine Coast Queensland Australia

ISBN: (纸本)9783319315492

Software Defined Network (SDN) separates control plane from data plane and provides programmability which adds rich function for anomaly detection. In this case, every organization can manage their own network and detect anomalous traffic data using SDN architecture. Moreover, detection of malicious traffic, such as DDoS attack, would be dealt with much higher accuracy if these organizations shared their data. Unfortunately, they are unwilling to do so due to privacy consideration. To address this contradiction, we propose an efficient and privacy-preserving collaborative anomaly detection scheme. We extend prior work on SDN-based anomaly detection method to guarantee accuracy and privacy at the same time. The implementation of our design on simulated data shows that it performs well for network-wide anomaly detection with little overhead. © Springer International Publishing Switzerland 2016.

关键词： Denial-of-service attack

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Clustering of Words using Dictionary-Learnt Word Representations

Clustering of Words using Dictionary-Learnt Word Representat...

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International Conference on Advances in Computing, Communications and Informatics

作者： Remya R. K. Menon Gargi, S. Samili, S. Department of Computer Science and Applications Amrita School of Engineering Amrita Vishwa Vidyapeetham Amrita University

ISBN: (纸本)9781509020300

Language is the way of communication through words. This will help to get a better insight of the world. Natural Language Processing (NLP) mainly concentrate on expanding systems that allow computers to communicate with people using everyday language. One of the challenges inherent in NLP is teaching computers to recognize the way humans learn and use language. Word representations give rise to capture syntactic and semantic properties of words. So the main purpose of this work is to find out the set of words which have similar semantics by matching the context in which the words occur. In this work we explore a new method for learning word representations using sparse coding, a technique usually done on signals and images. We present an efficient sparse coding algorithm, Orthogonal Matching Pursuit to generate the sparse code. Based on the input given, sparse codes are generated for the input. The input term vectors are classified based on the sparse code by grouping the terms which have same sparse code into one class. K-Means algorithm is also used to classify the input terms vectors which have semantic similarities. Finally, this paper makes a comparison that gives the best representation from the sparse code and K-Means. The result shows an improved set of similar words using sparse code when compared to K-Means. This is because SVD is used as a part of dictionary learning which captures the latent relationship that exists between the words.

关键词： NLP Sparse Coding Dictionary Learning K-Means OMP K-SVD Terms PMI

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Harnessing the discriminatory strength of dictionaries

Harnessing the discriminatory strength of dictionaries

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International Conference on Advances in Computing, Communications and Informatics (ICACCI)

作者： Remya R K Menon Neethu V Kini G Athira Krishnan Department of Computer Science and Applications Amrita School of Engineering Amrita Vishwa Vidyapeetham Amritapuri Kollam

ISBN: (纸本)9781509020300

Over the past few years there are many developments in the area of classification in data mining. Classification is a supervised learning method, that maps data into predefined groups or classes. Nowadays classification techniques are extensively used in different applications. In this area most of the research works are done on text, image, signal etc. The main goal of this paper is to use a dictionary-based approach to learn, represent and classify documents. We consider dictionary as a collection of documents and each document in the dictionary is represented as a collection of vectors. An algorithm is also implemented to easily locate a class specific document in the dictionary and if it is not present, update the dictionary. The existing method is based on a dictionary learning algorithm which only improves the document representation based on Singular Value Decomposition (SVD) updation. Since SVD will not be helpful for discrimination of data, so our proposed algorithm is Linear Discriminant Analysis (LDA) for learning a discriminating dictionary. On applying the proposed algorithm on well known dataset, the overall results obtained shows 90% improvement in accuracy. The advantage is that it can be used for both representation as well as classification.

关键词： Dictionaries Algorithm design and analysis Classification algorithms Sparse matrices Matching pursuit algorithms Image coding Signal processing algorithms

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A novel PUF based on cell error rate distribution of STT-RAM 21

A novel PUF based on cell error rate distribution of STT-RAM

引用

21st Asia and South Pacific Design Automation Conference, ASP-DAC 2016

作者： Zhang, Xian Guangyu, Sun Zhang, Yaojun Chen, Yiran Li, Hai Wen, Wujie Di, Jia Center for Energy-Efficient Computing and Applications Peking University Beijing100871 China Collaborative Innovation Center of High Performance Computing NUDT Changsha410073 China Department of Electrical and Computer Engineering University of Pittsburgh PittsburghPA15261 United States Department of Electrical and Computer Engineering Florida International University MiamiFL33199 United States Computer Science and Computer Engineering University of Arkansas FayettevilleAR72701 United States

ISBN: (纸本)9781467395694

Physical Unclonable Functions (PUFs) have been widely proposed as security primitives to provide device identification and authentication. Recently, PUFs based on Non-volatile Memory (NVM) are widely proposed since the promise of NVMs' wide application. In addition, NVM-based PUFs are considered to be more immune to invasive attack and simulation attack than CMOS-based PUFs. However, the existing NVM-based PUF either shows the unreliability under environmental variations or need extra modifications to the IC manufacturing process. In this work, we propose err-PUF, a novel PUF design based on the cell error rate distribution of STT-RAM. Instead of using the distribution directly, we generate a stable fingerprint based on a novel concept called Error-rate Differential Pair (EDP) without modifications to the read/write circuits. Comprehensive results demonstrate that err-PUF can achieve sufficient reliability under environmental variations, which can significantly impact the cell error rates. Moreover, compared with existing approaches, err-PUF has a higher speed and lower power consumption with negligible overhead. © 2016 IEEE.

关键词： Hardware security

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Mean-field theory for the Nagel-Schreckenberg model with overtaking strategy

引用

Journal of Physics: Conference Series 2018年第1期1113卷

作者： Zhu Su Weibing Deng Jihui Han Wei Li Xu Cai National Engineering Laboratory for Technology of Big Data Applications in Education Central China Normal University Wuhan P. R. China Complexity Science Center Institute of Particle Physics Central China Normal University Wuhan P. R. China School of Computer and Communication Engineering Zhengzhou University of Light Industry Zhengzhou P.R. China

Based on the Nagel-Schreckenberg (NS) model with periodic boundary conditions, a modified model considered overtaking strategy (NSOS) has been proposed [1, 2]. In this paper, we focus on the theoretical analysis of traffic flow for NSOS model by using mean-field method. In the special case of vmax = 1 where vehicles can not overtake preceding ones, the features of stationary state can be obtained exactly. However, in the case of vmax > 1 where overtaking happens, some approximative methods have to be took into account. The main results are that we find the reason why traffic flow is increased in the regime where densities exceed the maximum flow density, and the influence of traffic flow on the transition density is dominated by the braking probability p.

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Arbitrary order 2D virtual elements for polygonal meshes: Part II, inelastic problem

arXiv

引用

arXiv 2017年

作者： Artioli, E. Beirão da Veiga, L. Lovadina, C. Sacco, E. Department of Civil Engineering and Computer Science University of Rome Tor Vergata Via del Politecnico 1 Rome00133 Italy Department of Mathematics and Applications University of Milan Bicocca Via Roberto Cozzi 55 Milan20125 Italy Department of Mathematics University of Milano Via Cesare Saldini 50 Milano20133 Italy Civil Engineering and Mechanical Engineering University of Cassino and Southern Lazio Via Di Biasio 43 Cassino03043 Italy

The present paper is the second part of a twofold work, whose first part is reported in [3], concerning a newly developed Virtual Element Method (VEM) for 2D continuum problems. The first part of the work proposed a study for linear elastic problem. The aim of this part is to explore the features of the VEM formulation when material nonlinearity is considered, showing that the accuracy and easiness of implementation discovered in the analysis inherent to the first part of the work are still retained. Three different nonlinear constitutive laws are considered in the VEM formulation. In particular, the generalized viscoplastic model, the classical Mises plasticity with isotropic/kinematic hardening and a shape memory alloy (SMA) constitutive law are implemented. The versatility with respect to all the considered nonlinear material constitutive laws is demonstrated through several numerical examples, also remarking that the proposed 2D VEM formulation can be straightforwardly implemented as in a standard nonlinear structural finite element method (FEM) framework. Copyright © 2017, The Authors. All rights reserved.

关键词： Plasticity

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Application-layer clock synchronization for wearables using skin electric potentials induced by powerline radiation

arXiv

引用

arXiv 2017年

作者： Yan, Zhenyu Li, Yang Tan, Rui Huang, Jun School of Computer Science and Engineering Nanyang Technological University 50 Nanyang Avenue Singapore639798 Singapore Advanced Digital Sciences Center Illinois at Singapore Connexis North Tower 1 Fusionopolis Way #08-10 Singapore138632 Center for Energy Efficient Computing and Applications Peking University 5 Yiheyuan Road Haidian Beijing100871 China

Design of clock synchronization for networked nodes faces a fundamental trade-off between synchronization accuracy and universality for heterogeneous platforms, because a high synchronization accuracy generally requires platform-dependent hardware-level network packet timestamping. This paper presents TouchSync, a new indoor clock synchronization approach for wearables that achieves millisecond accuracy while preserving universality in that it uses standard system calls only, such as reading system clock, sampling sensors, and sending/receiving network messages. The design of TouchSync is driven by a key finding from our extensive measurements that the skin electric potentials (SEPs) induced by powerline radiation are salient, periodic, and synchronous on a same wearer and even across different wearers. TouchSync integrates the SEP signal into the universal principle of Network Time Protocol and solves an integer ambiguity problem by fusing the ambiguous results in multiple synchronization rounds to conclude an accurate clock offset between two synchronizing wearables. With our shared code, TouchSync can be readily integrated into any wearable applications. Extensive evaluation based on our Arduino and TinyOS implementations shows that TouchSync's synchronization errors are below 3 and 7 milliseconds on the same wearer and between two wearers 10 kilometers apart, respectively. Copyright © 2017, The Authors. All rights reserved.

关键词： Synchronization

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Object verification in two views using Sparse representation 23

Object verification in two views using Sparse representation

引用

23rd International Conference on Pattern Recognition, ICPR 2016

作者： Hsu, Shih-Chung Chang, I-Cheng Huang, Chung-Lin Department of Electrical Engineering National Tsing-Hua University Hsin-Chu Taiwan Department of Computer Science and Information Dong-Hwa University Hua-Lien Taiwan Department of M-Commerce and Multimedia Applications Asia University Tai-Chung Taiwan

ISBN: (纸本)9781509048472

This paper proposes an object verification method by using sparse representation (SR) which has been applied for object representation and recognition. However, SR dictionary does not show sufficient compactness. Our method comprises three major modules. First, we train the sparse matrix by using boost K-Singular Value Decomposition (boost K-SVD) to obtain a sparse vector set. Second, we combine two training sparse vector sets of the same and different objects from two views to generate a positive/negative combined sparse vector set. Finally, a Support Vector Machine (SVM) classifier is applied for verification. Our contributions are (1) obtaining a sparser vector set using K-SVD, (2) demonstrating the SR matrix with better Restricted Isometry Property (RIP), and (3) applying the SR matrix to the object verification process with high accuracy. The experimental results prove that our method has higher accuracy than the other methods. © 2016 IEEE.

关键词： Singular value decomposition

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