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11th International Conference on Augmented Cognition, AC 2017, held as part of the 19th International Conference on Human-computer Interaction, HCI 2017

作者： Niu, Yafeng Xue, Chengqi Wang, Haiyan Tang, Wenzhe Zhang, Xinyu Jin, Tao Chen, Yingjie Victor School of Mechanical Engineering Southeast University Nanjing211189 China Science and Technology on Electro-Optic Control Laboratory Luoyang471023 China Mechanical and Electrical Engineering Institute China University of Petroleum Qingdao266580 China Department of Computer Graphics Technology Purdue University West LafayetteIN47907 United States

In order to explore the icon controlled digital interface for brain-computer interaction, we use Event-Related Potential technology, first of all, collect the icons from various digital interfaces, use the image processing software to process the icon images, the method comprises the following steps: communication between EEG and test computer, EEG experiment, off-line analysis of the original signal, time domain and frequency domain feature extraction of the group average EEG signal, microprocessor processing, and obtain the user computer function control command of the icon picture, then extract time domain and frequency domain characteristics of target icon picture EEG signal, and calculate the similarity between them, finally realize the triggering of control instruction of the target icon picture. This method can effectively realize icon brain-computer control of the digital interface, and provide the important reference for other elements to interact with the digital interface brain-computer interaction. © Springer International Publishing AG 2017.

关键词： Time domain analysis

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The interactive image: A media archaeology approach

The interactive image: A media archaeology approach

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ACM SIGGRAPH 2017 Art Gallery - International Conference on computer graphics and Interactive Techniques, SIGGRAPH 2017

作者： Bravo, Esteban García Burbano, Andrés Byrd, Vetria L. Forbes, Angus G. Purdue University Department of Computer Graphics Technology West LafayetteIN47907 United States Universidad de Los Andes Department of Design Cra 1 No. 18A-12 Bogotá111711 Colombia University of Illinois at Chicago Electronic Visualization Laboratory Department of Computer Science M/C 152 851 S Morgan Room 1120 ChicagoIL60607 United States

ISBN: (纸本)9781450349987

This paper examines the history of the influential Interactive Image computer graphics showcase, which took place at museum and conference venues from 1987 to 1988. The authors present a preliminary exploration of the historical contexts that led to the creation of this exhibition by the Electronic Visualization Lab (EVL), which included the integrated efforts of both artists and computer scientists. In addition to providing historical details about this event, the authors introduce a media archaeology approach for examining the cultural and technological contexts in which this event is situated. © 2017 Esteban García Bravo, Andr's Burbano, Vetria L. Byrd, Angus G. Forbes.

关键词： Exhibitions

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Smart Car Parking With Reservation System Using QR Generator

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IOP Conference Series: Materials science and Engineering 2018年第1期396卷

作者： Aswathy James Prince Abraham Department of Computer Science St.Josephs College Of Engineering And Technology Palai India Asst. Professor Department of Computer Science St.Josephs College Of Engineering And Technology Palai India

Nowadays parking has become an expensive resource in the almost any major city's in the world, and its limited availability is the concurrent cause of urban traffic congestion and air pollution. The common method of finding a parking space is manual where the driver usually finds a space on the street through luck and experience. This process takes time and effort and may lead to the worst case of failing to find any parking space if the driver is driving in a city with high vehicle density. In this paper, an attempt has been done to automate the car as well as the car parking system with a Smart Parking System (SPS) which is based on the integration of an Android app and QR Code reader. The introduction of a novel algorithm that increases the efficiency of the current smart-parking system and develops an android app to collect information about the occupancy state of parking spaces, and to inform the drivers to the nearest vacant parking spot. The entering into or leaving the parking slot is controlled by an Android-based application. The algorithm helps improve the probability of successful parking and minimizes the user waiting time.

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Systematic approach for enrichment of docking outcome using consensus scoring functions

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Journal of Physics: Conference Series 2019年第1期1228卷

作者： K Naga Madhavilatha G Rama Mohan Babu Research Scholar Department of Computer Science and Engineering University College of Engineering & Technology Acharya Nagarjuna University Nagarjuna Nagar GUNTUR - 522510 Andhra Pradesh India. Professor Department of Information Technology R.V.R. & J.C College of Engineering Chowdavaram GUNTUR- 522019 Andhra Pradesh India.

Traditional drug discovery is an expensive and time consuming process. Pharmaceutical industry suffers from a huge attrition due to last stage failure in traditional drug discovery. Bioinformatics principles can be utilized to overcome this pressure and speedup the process of drug discovery. computer aided drug design is a remedy to avoid this loss. Drug design means designing the ligand that has high affinity towards target protein. This can be achieved by Virtual Screening. Ligand based virtual screening utilizes information from the ligand about the target. It is a ligand centric approach. The availability of three dimensional structures of protein targets and their possible ligands are utilized for identification and optimization of lead molecules (positive hits) in Structure based virtual screening. It is a target centric approach. To find out fit poses of ligand and its affinity at the active site of target Molecular Docking is done. Molecular docking is tool that contains search algorithm and scoring function. Search algorithms predict the binding modes of a target and fit ligand conformations towards the target. Scoring function is involved in prediction of the affinity of a ligand to bind to a protein target. There are various plat forms and scoring functions for predicting ligand – protein interactions. Consensus Scoring is a technique of combing information from multiple scoring functions and gives relatively accurate result when compared to single scoring function. It shows improvement in terms of quality of hit scores, false positive rate and enrichment. Consensus Scoring gives better, accurate and consistent results across the receptor systems when compared to individual or single scoring functions.

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A Novel Approach For Automatic Identification Of Psoriasis Affected Skin Area.

A Novel Approach For Automatic Identification Of Psoriasis A...

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International Conference on Emerging Computation and Information Technologies (ICECIT)

作者： T.R. Arunkumar H. S. Jayanna Research Scholar Department of Computer Science & Engineering Siddaganga Institute of Technology Tumkur India Professor Department of Information Science Siddaganga Institute of Technology Tumkur India

ISBN: (纸本)9781538610954

The paper presents the detection of psoriasis affected skin. Thecolor feature of the skin from RGB model, where the skin color is defined as redness, greenness, and blueness are analyzed. An algorithm is developed to differentiate affected area from non affected area. The color histogram analysis is carried out for more than fifty samples to analyse erythema in order to differentiate affected skin from non affected skin. Today dermatologists visually analyse the patients for the line of treatment which is biased by various external factors. The proposed model for diagnosis is not subjective where the decisions are based on various external factors such as emotions, part of the day and vary from dermatologist to dermatologist which may have a great impact on the treatment of the disorder. The algorithm is objective and minimizes the deviation in the line of treatment as it is not affected by intra and inter diagnosis by dermatologists. The RGB histogram is analyzed and a model is built based on mean and standard deviation to differentiate healthy skin and psoriasis disorder affected skin.

关键词： Skin Knowledge based systems Image color analysis Image segmentation Histograms Standards

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An Approach of RDD Optimization in Big Data Analytics

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IOP Conference Series: Materials science and Engineering 2018年第1期396卷

作者： V Athira Jeena Thomas PG Scholar Department of Computer Science St.Josephs College of Engineering and Technology Palai Kerala India Assistant Professor Department of Computer Science St.Josephs College of Engineering and Technology Palai Kerala India

We live in the information age and new information is produced in each and every second. The information can be worlds data which is responsible for major technological changes that can bring new ways in decision making. Keeping this data for further analysis and computation is a difficult task. Several studies are done in this arena, making it effective for future figuring. Processing or analysing such huge amount of data is a challenging task. All the existing technologies contain certain bottlenecks and performance overheads, diverse challenges like scalability. Spark is the commonly used data analysis framework. Map Reduce is a computing paradigm and a popular model for distributed data analysis. This paper gives a survey about some enormous information technologies, how it will deal with huge data, and the difficulties in existing advances, and has additionally learned about a portion of the execution bottlenecks and preventive techniques, and the concentration at that point moves to the Resilient Distributed Dataset (RDD), and how it is optimized.

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A Performance Improvement Inference Method For Link Prediction in Social Graphs

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IOP Conference Series: Materials science and Engineering 2018年第1期396卷

作者： Ashly Ann Jo Prince. V. Jose PG Scholar Department of Computer Science St.Joseph's College of Engineering and Technology Pala India Assistant Professor Department of Computer Science St.Joseph's College of Engineering and Technology Pala India

Social network analysis has turned into a conspicuous field in link prediction. The precise social network models are additionally address a few downsides. Since the link forecast in Social network analysis confront a few threats, for example, the in partially correct rules. An ideal inference mechanism should scale up towards vast scale information. The inference methods uses probabilistic evidence data since it can easily predict the vulnerabilities. There are diverse responses for Social network analysis have suggested over years. In this approach develop a model to predict the nearness of associations among nodes in broad scale casual groups, for example, informal organizations, which are exhibited by Markov Logic Networks (MLNs) and Bayesian Networks. This show gives a successful inference model which can deal with complex conditions and somewhat partially correct rules. The proposed system predicts the accuracy and efficiency of link prediction utilizing MAP Markov Logic induction technique and MPE Bayesian derivation strategy.

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Match Fixing Network Analysis to Verify Nearness among Internal Participants of a Cricket Match

Match Fixing Network Analysis to Verify Nearness among Inter...

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IEEE International Conference on Recent Trends in Electronics, Information & Communication technology

作者： K. Ananthapadmanabha K. Udayakumar Research Scholar PP COMP.SCI.ENG.025 Computer Science &EngineeringRayalaseem University Kurnool India Principal & Professor Dept of Computer Science & Engineering Adarsha Institute of Technology Bangalore India

ISBN: (纸本)9781509037056

Match fixing in cricket is a fraudulent activity involving captain of the team, few key players, umpires, officials, bookies, middle men and gangsters. To perform match fixing in cricket, they form a criminal network with each of them acting as a node and association between these nodes acting as edges. To analyze this network concepts like using graph mining, link mining, community mining and algorithmic design notation like greedy technique are applied. Participants in a cricket match like captain, umpires, players, officials are called internal participants share vital game plan information from dressing room with bookies, middlemen and gangsters. Participants like bookies, middlemen and gangsters who perform match fixing with the support of internal participants are called external participants and they use information given to them by internal participants to conduct betting and fixing activities. Some important game plan information are pitch report, weather report, team composition, team batting strategy, field placement, and team bowling strategy. In this paper we focus our attention on match fixing network analysis using internal participants.

关键词： Cricket Match fixing Internal participants Graph mining Link mining Community mining Greedy technique Scapteriscus Cricket Fixed Captains,Ship Network analysis Gambling Refereeing and umpiring

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Feature Based Sentiment Analysis of Compound Sentences

Feature Based Sentiment Analysis of Compound Sentences

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International Conference on Emerging Computation and Information Technologies (ICECIT)

作者： Sandhya R Savanur R Sumathi Research Scholar Siddaganga Institute of Technology Tumakuru India Professor and Head Department of Computer Science and Engineering Siddaganga Institute of Technology Tumakuru India

ISBN: (纸本)9781538610954

Sentiment analysis is the study that analyzes people's opinions, sentiments, attitudes and emotions towards entities such as products, services, organizations, individuals and events. The rise of blogs and social networks has fueled bull market in personal opinions, reviews, ratings, recommendations and other forms of online expressions. Sentiment analysis is accomplished by examining this large amount of data on the basis of positive, negative and neutral views of the end user. Feature based sentiment analysis focuses on different aspects or features of any entity under analysis. The reviews, attitudes, opinions and emotions are available on the web in the form of simple and compound sentences. Feature based sentiment analysis of simple sentences is easy compared to the analysis of compound sentences which contain multiple clauses. In this paper, we propose rules for analyzing different conjunctions and propose an algorithm to perform feature based sentiment analysis of compound sentences. Rules are defined for the different conjunctions used to form compound sentences. The algorithm analyses different conjunctions used in the compound sentences based on the rules and provides a feature based summary of different attributes of the entity under analysis.

关键词： Streaming media Text recognition Image recognition Automobiles Lighting computer vision Cameras

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Speckle reduction with trained nonlinear diffusion filtering

arXiv

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arXiv 2017年

作者： Feng, Wensen Chen, Yunjin School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing100083 China Institute for Computer Graphics and Vision Graz University of Technology Inffeldgasse 16 GrazA-8010 Austria

Speckle reduction is a prerequisite for many image processing tasks in synthetic aperture radar (SAR) images, as well as all coherent images. In recent years, predominant state-of-the-art approaches for despeckling are usually based on nonlocal methods which mainly concentrate on achieving utmost image restoration quality, with relatively low computational efficiency. Therefore, in this study we aim to propose an efficient despeckling model with both high computational efficiency and high recovery quality. To this end, we exploit a newly-developed trainable nonlinear reaction diffusion(TNRD) framework which has proven a simple and effective model for various image restoration problems. In the original TNRD applications, the diffusion network is usually derived based on the direct gradient descent scheme. However, this approach will encounter some problem for the task of multiplicative noise reduction exploited in this study. To solve this problem, we employed a new architecture derived from the proximal gradient descent method. Taking into account the speckle noise statistics, the diffusion process for the despeckling task is derived. We then retrain all the model parameters in the presence of speckle noise. Finally, optimized nonlinear diffusion filtering models are obtained, which are specialized for despeckling with various noise levels. Experimental results substantiate that the trained filtering models provide comparable or even better results than state-of-the-art nonlocal approaches. Meanwhile, our proposed model merely contains convolution of linear filters with an image, which offers high level parallelism on GPUs. As a consequence, for images of size 512 × 512, our GPU implementation takes less than 0.1 seconds to produce state-of-the-art despeckling performance. Copyright © 2017, The Authors. All rights reserved.

关键词： Computational efficiency

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