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International Conference on Communication Systems and Network Technologies

作者： Amit Kumar Sharma Renuka Yadav Assistant Professor Department of Computer Science & Engineering The ICFAI University Jaipur Rajasthan India Associate System Engineer IBM India Pvt. Ltd. Pune Maharashtra India

ISBN: (纸本)9781479917983

The continuous growth of email users has resulted in the increasing of unsolicited emails also known as Spam. In current, server side and client side anti spam filters are introduced for detecting different features of spam emails. However, recently spammers introduced some effective tricks consisting of embedding spam contents into digital image, pdf and doc as attachment which can make ineffective to current techniques that is based on analysis digital text in the body and subject fields of email. Many of proposed working strategy provides an anti spam filtering approach that is based on data mining techniques which classify the spam and ham emails. The effectiveness of these approaches is evaluated on large corpus of simple text dataset as well as text embedded image dataset. But most of the filtering techniques are unable to handle frequent changing scenario of spam mails adopted by the spammers over the time. Therefore improved spam control algorithms or enhancing the efficiency of various existing data mining algorithms to its fullest extent are the utmost requirement. A comparative study is presented on various spam filtering techniques adopted on the basis of various attributes to find best among all to extract the best results.

关键词： Component Analysis Correlation Feature Selection PCA Bayesian Classifiers SVM J48 LMT Stemming TFIDF

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Clustering Software Components for Program Restructuring and Component Reuse Using Hybrid XNOR Similarity Function

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Procedia Technology 2014年 12卷 246-254页

作者： Chintakindi Srinivas Vangipuram Radhakrishna C.V. Guru Rao Associate Professor of CSE Kakatiya Institute of Technology and Science Warangal INDIA Department of Information Technology VNR Vignana Jyothi Institute of Engineering and Technology Hyderabad INDIA Professor of Computer Science and Engineering SR Engineering CollegeWarangal INDIA

Component based software development has gained a lot of practical importance in the field of software engineering from academic researchers and also from industry perspective. Finding components for efficient software reuse is one of the important problems aimed by researchers. Clustering reduces the search space of components by grouping similar entities together thus ensuring reduced time complexity as it reduces the search time for component retrieval. In this research, we instigate a generalized approach for clustering a given set of documents or software components by defining a similarity function called hybrid XNOR function to find degree of similarity between two document sets or software components. A similarity matrix is obtained for a given set of documents or components by applying hybrid XNOR function. We define and design the algorithm for component or document clustering which has the input as similarity matrix and output being set of clusters. The output is a set of highly cohesive pattern groups or components.

关键词： clustering similarity frequent item mining classification component

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Exploring the effects of virtual machine placement on the transmission of infections in cloud

Exploring the effects of virtual machine placement on the tr...

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International Symposium on Telecommunications, IST

作者： Farzaneh Abazari Morteza Analoui School of Computer Engineering Iran University of Science and Technology Tehran Iran Associate Professor of Computer Engineering Iran University of Science and Technology Tehran Iran

Cloud Computing has recently emerged as a computing paradigm for delivering IT resources as services over the internet. However, there still exist significant problems with regard to secure delivery of services using Cloud-based IT resources. As long as malicious virtual machines could affect its host and other machines, the virtual machine placement is an important issues. In this paper, we outline an approach based on a combination of graph theory and agent based simulations to study epidemics in the cloud computing and control the transmission of infections. We present our results on the graph properties of virtual machines graph, as well as simulation-based dynamic analysis of infection spread in such networks. We identify a number of measures that are significant for understanding epidemics and for developing new strategies in virtual machines placement algorithm.

关键词： Virtual machining Virtualization Cloud computing Virtual machine monitors Mathematical model computer crime

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Image Restoration Using IIST Algorithm

Image Restoration Using IIST Algorithm

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International Conference on Intelligent Computing Applications (ICICA)

作者： A. K. Kumaresh S. Kother Mohideen Associate Professor Department of Computer Science The MDT Hindu College Tirunelveli Professor and Research Convener National College of engineering Tirunelveli

The problem of restoration of digital images plays a central role in multitude important applications. A particularly challenging instance of this problem occurs in the case when the degradation phenomenon is modelled by ill-conditional operator. In such situation, the presence of noise makes it impossible to recover a valuable approximation of the image of interest without using some priori information called as simply priors is essential for image restoration, rendering it stable and robust to noise. Particularly, if the original image is known to be a piecewise smooth function, one of the standard priors used Rudin-Osher-Fatemi model which results in total variation (TV) based image restoration. We proposed an algorithm for unconstrained optimization problem where the objective function includes a data fidelity term and a nonsmooth *** Variation method is employed to find solution of the problem based on the improved iterative shrinkage thresholding algorithm (IITSA). IISTA is performed through a recursive application of two simple procedures linear filtering and soft thresholding. An experimental result shows that better performance of the algorithm when compared with the existing methods.

关键词： Image restoration Mathematical model Equations Noise measurement Digital images Noise TV

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Selectively controlling the 2D organization of mammalian cells: Templated assembly by selective removal (TASR) for medical applications

Selectively controlling the 2D organization of mammalian cel...

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Annual Northeast Bioengineering Conference

作者： Gunjan Agarwal Carol Livermore Postdoctoral Associate: Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA USA Associate Professor: Department of Mechanical & Industrial Engineering Northeastern University Boston MA USA

This work presents the first ever size-selective sorting of single mammalian cells using a microfabrication-enabled assembly process known as templated assembly by selective removal (TASR). The selective placement and sorting of single mouse lung cancer cells into patterned hemispherical sites on rigid assembly templates using TASR was demonstrated. Nearly 100% of the assembly sites on the template were filled with matching cells (with assembly density as high as 900 sites/mm 2 ) within short assembly times of 3 minutes. Size selective sorting of mammalian cells holds promising potential for implementation in medical applications such as tissue engineering.

关键词： Assembly Sorting Lungs Cancer Silicon Cells (biology) Tissue engineering

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Surgical tool attributes from monocular video

Surgical tool attributes from monocular video

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Suren Kumar Madusudanan Sathia Narayanan Pankaj Singhal Jason J Corso Venkat Krovi Department of Mechanical Engineering University at Buffalo SUNY Buffalo NY USA Kaleida Health Western New York Buffalo NY USA Associate Professor in Department of Computer Science Engineering University at Buffalo SUNY Buffalo NY USA Associate Professor in Department of Mechanical Engineering and an Adjunct Professor in Department Obstetrics and Gynecology University at Buffalo SUNY Buffalo NY USA

HD Video from the (monocular or binocular) endoscopic camera provides a rich real-time sensing channel from surgical site to the surgeon console in various Minimally Invasive Surgery (MIS) procedures. However, a real-time framework for video understanding would be critical for tapping into the rich information-content provided by the non-invasive and well-established digital endoscopic video-streaming modality. While contemporary research focuses on enhancing aspects such as tool-tracking within the challenging visual scenes, we consider the associated problem of using that rich (but often compromised) streaming visual data to discover the underlying semantic attributes of the tools. Directly analyzing the surgical videos to extract more realistic attributes online can aid in the decision-making and feedback aspects. We propose a novel probabilistic attribute labelling framework with Bayesian filtering to identify associated semantics (open/closed, stained with blood etc.) to ultimately give semantic feedback to the surgeon. Our robust video-understanding framework overcomes many of the challenges (tissue deformations, image specularities, clutter, tool-occlusion due to blood and/or organs) under realistic in-vivo surgical conditions. Specifically, this manuscript performs rigorous experimental analysis of the resulting method with varying parameters and different visual features on a data-corpus consisting of real surgical procedures performed on patients with da Vinci Surgical System [9].

关键词： Streaming media Visualization Surgery Semantics Accuracy Feature extraction Support vector machines

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Conductance-based computational model of basal ganglia

Conductance-based computational model of basal ganglia

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Iranian Conference on Electrical engineering (ICEE)

作者： Mohammad Reza Mohagheghi-Nejad Fariba Bahrami Mahyar Janahmadi Graduate Student School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Associate Professor CIPCE College of Engineering University of Tehran Tehran Iran Professor Neurophysiology Research Center and Department of Physiology Shahid Beheshti University of Medical Science Tehran Iran

ISBN: (纸本)9781479944088

The basal ganglia play an important role in motor control and their malfunction is implicated in several disorders including Parkinson's disease (PD), in which dopamine concentration is greatly reduced. This is associated with changes in their firing patterns, evidenced by increase in firing rate of output nuclei of basal ganglia and synchronization between neurons of different micro-circuitry of basal ganglia. The most effective way to alleviate the symptoms of PD is to take Levodopa which replenishes dopamine storage in the brain. However, long-term use of Levodopa results in motor fluctuations and dyskinesia. Here, we developed a conductance-based computational model of basal ganglia which considers modulatory effects of dopamine on its target nucleus, that is on striatum. This model can be used to investigate the effect of variations of the dopamine levels on motor fluctuation. Moreover, the effect of applying deep brain electrical stimulation on different nuclei of basal ganglia can be investigated through the proposed model.

关键词： Neurons Computational modeling Synchronization Basal ganglia Brain modeling Biological system modeling Mathematical model

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Nonlinear Control of UAVs using Multi-Layer Perceptrons with Off-Line and On-Line Learning

Nonlinear Control of UAVs using Multi-Layer Perceptrons with...

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American Control Conference

作者： Subodh Bhandari Amar Raheja Daisy Tang Kevin Ortega Ohanes Dadian Ajay Bettadapura Cal Poly Pomona Pomona CA 91768 Professor Department of Aerospace Engineering AIAA Senior Member Cal Poly Pomona Pomona CA 91768 Professor Department of Computer Science Cal Poly Pomona Pomona CA 91768 Associate Professor Department of Computer Science Cal Poly Pomona Pomona CA 91768 Graduate Student Department of Computer Science Cal Poly Pomona Pomona CA 91768 Graduate Research Assistant Department of Computer Science Cal Poly Pomona Pomona CA 91768 Undergraduate Research Assistant Department of Aerospace Engineering AIAA Student Member

ISBN: (纸本)9781479932757

This paper presents the research on the development of neural network based non-linear controllers for an airplane UAV. Multi-layer perceptrons are used for the training of networks, both off-line and on-line. The data required for off-line training is generated from a validated non-linear flight dynamics model of the Cal Poly Pomona 12' Telemaster UAV. The off-line trained network using multilayer perceptrons replaces the inverse transformation required for feedback linearization. On-line training is then accomplished to account for the inversion and modeling error. The controllers are tested in the software-in-the-loop simulation environment using FlightGear Flight Simulator. Simulation results compared with flight data are shown. Also shown are the results in the presence of sensor noise.

关键词： UAV Nonlinear Control using Multi-Layer Perceptrons nonlinear control Unmanned Aerial Vehicle drone honey bees OFF LINE Neural Networks (computer) IN-LINE Simulated Environment Multilayer perceptrons flight data

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Investigation of Mechanical Properties, Microstructure and Wear Rate of High Leaded Tin Bronze after Multidirectional Forging

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Procedia Materials science 2014年 5卷 1081-1089页

作者： Rahul Gupta Sanjay Srivastava G.V. Preetham Kumar Sanjay K. Panthi Ph.D Research Scholar Department of Material Science & Metallurgical Engineering Maulana Azad National Institute of Technology Bhopal 462003 India Associate Professor Department of Material Science & Metallurgical Engineering Maulana Azad National Institute of Technology Bhopal 462003 India Assistant Professor Department of Metallurgical & Materials Engineering National Institute of Technology Karnataka Surathkal Mangalore 575025 India Scientist Computer Simulation & Design Center Advanced Materials and Processes Research Institute (AMPRI) Near Habibganj Naka Hoshangabad Road Bhopal 462064 India

In this work, the change in mechanical properties, microstructure and wear rate of high leaded tin bronze material was studied after multidirectional forging (MDF) process. The total equivalent strain of 0.75 was applied during MDF process result in the improvement of ultimate tensile strength, yield strength, hardness and wear rate along with maintained ductility with the increase in the number of MDF pass. The initial average grain size of 120 nm was refined to the final grain size of 37 nm. The transmission electron microscope, scanning electron microscope and optical microscope was used for the microstructure study of the undeformed, MDForged and wear worn surfaces.

关键词： Multidirectional forging high leaded tin bronze mechanical properties microstructure wear

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Feature based Summarization of Customers’ Reviews of Online Products

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Procedia computer science 2013年 22卷 142-151页

作者： Kushal Bafna Durga Toshniwal M. Tech. Computer Science Electronics and Computer Engineering Department IIT Roorkee-247667 India Associate Professor Electronics and Computer Engineering Department IIT Roorkee-247667 India

With the growing availability and popularity of opinion-rich resources such as review forums for the product sold online, choosing the right product from a large number of products have become difficult for the user. For trendy product, the number of customers’ opinions available can be in the thousands. It becomes hard for the customers to read all the reviews and if he reads only a few of those reviews, then he may get a biased view about the product. Makers of the products may also feel difficult to maintain, keep track and understand the customers’ views for the products. Several research works have been proposed in the past to address these issues, but they have certain limitations: The systems implemented are completely opaque, the reviews are not easier to perceive and are time consuming to analyze because of large irrelevant information apart from actual opinions about the features, the feature based summarization system that are implemented are more generic ones and static in nature. In this research, we proposed a dynamic system for feature based summarization of customers’ opinions for online products, which works according to the domain of the product. We are extracting online reviews for a product on periodic bases, each time after extraction, we carry out the following work: Firstly, identification of features of a product from customers’ opinions is done. Next, for each feature, its corresponding opinions’ are extracted and their orientation or polarity (positive/negative) is detected. The final polarity of feature-opinions pairs is calculated. At last, feature based summarizations of the reviews are generated, by extracting the relevant excerpts with respect to each feature-opinions pair and placing it into their respective feature based cluster. These feature based excerpts can easily be digested by the user.

关键词： Opinion Mining Summarization Sentiment Classification Feature Based Clustering and Reviews

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