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5th International Conference on Computational Intelligence and Multimedia Applications, ICCIMA 2003

作者： Liu, Zhi-Fang You, Zhi-Sheng Jain, A.K. Wang, Yun-Qiong Institute of Image and Graphic Dept. of Computer Science Sichuan University 610065 China Dept. of Computer Science and Engineering Michigan State University MI48824 United States

ISBN: (纸本)0769519571

Face detection and facial feature extraction plays an important role in video surveillance, human computer interaction and face recognition. Color is a useful piece of information in computer vision especially for skin detection. In this paper, we propose a novel approach for skin segmentation and facial feature extraction. The proposed skin segmentation is a method for integrating the chrominance components of nonlinear YCrCb color model. The goal of skin detection is to group pixels to form possible face candidate regions and then use connected components analysis for pixels grouping. In order to detect the facial feature in scale invariant, the possible face candidate regions will be normalized, and then texture information in these regions will be segmented by means of mean and variance of face region. Edge will be detected using the method based on multi-scale morphological. Eye will be located by the PCA edge direction. The others feature, such as nose and mouth, also located using the geometrical shape information. As all the above-mentioned techniques are simple and efficient, the proposed method is computational effective and suitable for practical applications. In our experiments, the proposed method has been successfully evaluated using two different test datasets. The detection accuracy is around 98%, the average run time ranged from 0.1-0.3 sec per frame. © 2003 IEEE.

关键词： Color

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SVASTHA: An effective solid waste management system for Thiruvalla Municipality in Android OS

SVASTHA: An effective solid waste management system for Thir...

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2013 IEEE Global Humanitarian Technology Conference: South Asia Satellite, GHTC-SAS 2013

作者： Issac, Roshan Akshai, M. Dept. of Computer Science and Engineering College of Engineering Kallooppara Kerala India Dept. of Electronics and Communication Engineering College of Engineering Kallooppara Kerala India

ISBN: (纸本)9781479910953

The rapid urbanization in Kerala has led to increased generation of municipal solid waste (MSW), which will seriously affect the society and the quality of life of people. Although some action has taken from the part of government against this, the poor management of waste has led to pollution and to the emission of greenhouse gases. The main issues with waste management are the high cost associated with no returns, lack of real time feedback from the people about unauthorized dumping and various transportation issues. For a case study, we have taken Thiruvalla Municipality situated between 9°23'06″ N to 76°34'30″E latitude and 9°38'2″N to 76.575°E longitude in Pathanamthitta district, Kerala. To address this issue we have introduced a system called SVASTHA which is a Sanskrit word which means 'be healthy and hygienic'. This effective management system with the help of RFID and GPS system can effectively manage the waste collection in Thiruvalla Municipality;this system can be adopted in other municipalities and corporations also. This system will actively monitor the waste collection process and will provide real time feedback such as waste collection status, live tracking of trucks and trash bins etc. The system can receive complaints from residents about uncollected wastes as well as the illegal disposal of wastes. one of the main feature of the system is the smart shortest path detection technique, so that vehicles need to travel only less distance to collect waste. This system is developed in android to support diverse class of mobile devices. © 2013 IEEE.

关键词： Municipal solid waste

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Modeling and handling duration constraints in BPMN 2.0 17

Modeling and handling duration constraints in BPMN 2.0

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32nd Annual ACM Symposium on Applied Computing, SAC 2017

作者： Combi, Carlo Oliboni, Barbara Zerbato, Francesca Dept. of Computer Science University of Verona Italy

ISBN: (纸本)9781450344869

When dealing with business processes, modeling and managing temporal aspects, either properties or constraints, is crucial. In this paper, we propose a set of structured BPMN process diagrams for specifying duration constraints at different levels of abstraction, starting from BPMN atomic tasks and up to consider the duration of selected process sub-regions. Moreover, we suggest suitable techniques for addressing their violation at process run-time. Copyright 2017 ACM.

关键词： Systems engineering

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Escape probability based routing for ad hoc networks

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Journal of Systems engineering and Electronics 2006年第4期17卷 927-930,937页

作者： Zhang Xuanping Qin Zheng Li Xin Dept. of Computer Science Xi'an Jiaotong Univ. Xi'an 710049 P. R. China

Routes in an ad hoc network may fail frequently because of node mobility. Stability therefore can be an important element in the design of routing protocols. The node escape probability is introduced to estimate the lifetime and stability of link between neighboring nodes and the escape probability based routing （EPBR） scheme to discover stable routes is proposed. Simulation results show that the EPBR can discover stable routes to reduce the number of route rediscovery, and is applicable for the situation that has highly dynamic network topology with broad area of communication.

关键词： ad hoc networks escape probability routing path stability.

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Content based retrieval and classification of cultural relic images

Content based retrieval and classification of cultural relic...

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Second International Symposium on Neural Networks: Advances in Neural Networks - ISNN 2005

作者： Wei, Na Celebi, M. Emre Geng, Guohua Dept. of Computer Science Northwest University at Xi'an Shaanxi 710069 China Dept. of Computer Science and Engineering University of Texas at Arlington Arlington TX 76019 United States

In this paper we present a novel system for content-based retrieval and classification of cultural relic images. First, the images are normalized to achieve rotation, translation and scaling invariant similarity retrieval. After normalization, a combination of color and shape features is extracted from the images. In order to improve the retrieval efficiency, a modified version of principal component analysis is used to reduce the dimensionality of the feature space. Retrieval performance of the system is evaluated for three different distance functions using the normalized recall measure. A multi-class support vector machine (SVM) classifier is used for classification. The results demonstrate that the system is both effective and efficient. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Information retrieval

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Text Filtering Insignificant Word (TFIW) Readability Framework Model to Explain NLP in Sentiment Analysis Using Reinforcement Machine Learning 2

Text Filtering Insignificant Word (TFIW) Readability Framewo...

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2nd International Conference on Recent Trends in Microelectronics, Automation, Computing, and Communications Systems, ICMACC 2024

作者： Kandakatla, Rajesh Kumar, V Dhilip Vel Tech Rangarajan Dr. Sagunthala R & D Institute of Science and Technology Dept. Computer Science and Engineering Chennai India BVRIT HYDERABAD College of Engineering for Women Dept. Computer Science and Engineering Hyderabad India

ISBN: (纸本)9798350366570

Reading of a text in a given sentence have lot of parameters to consider for expressing an opinion on a given text to conclude nature of the text. The data which need to be formed in the form of data sets based on specific constrains. The Natural Language Processing (NLP) will always presume that Text readability made as the considerable measure for better round spread of any newspaper. The data related to these documents must be collected and store them in data sets. During this process of measuring text readability at the granular level of the text reading is a cumbersome task. This will always implicate a problem of machine readability of the text and explainability of the text taken from the documents mentioned above. In this context human readability will act an important role in predicting the text reading at granular level where the text-based sentiment analysis have been predicted through a machine learning model. The text reading has been evaluated in order to improve the readability through explainable system. The explainable systems will capture and explain the predictions of text reading. In this technical work an explainable system Text Filtering Insignificant Word (TFIW) is introduced where it improves the textual reading at the granule level based on sentiments by prediction the words which need to be filtered. This will improve the explainability of text and text reading and improve the fast text and explainability of the document. © 2024 IEEE.

关键词： Reinforcement learning

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21st International Parallel and Distributed Processing Symposium, IPDPS 2007

作者： Shi, Xiaoqiu Han, Jinsong Liu, Yunhao Ni, Lionel M. Wenzhou University Dept. of Computer Science Wenzhou Zhejiang 325035 China Hong Kong University of Science and Technology Dept. of Computer Science and Engineering Clear Water Bay Kowloon Hong Kong

ISBN: (纸本)1424409101

In a hybrid peer-to-peer (P2P) system, flooding and DHT are both employed for content locating. The decision to use flooding or DHT largely depends on the population of desired data. Previous works either use local information only, or do not consider dynamic factors of P2P systems. In this paper, we propose a Popularity Adaptive Search method for Hybrid (PASH) P2P systems. By dynamically detecting the content popularity, PASH properly selects search methods and efficiently saves query traffic cost and response time. We comprehensively evaluate PASH through synthetic and trace-driven simulations. The results show that PASH outperforms existing approaches and it also scales well. © 2007 IEEE.

关键词： Distributed computer systems

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Graph Convolutional Networks for Predicting State-wise Pandemic Incidence in India 2

Graph Convolutional Networks for Predicting State-wise Pande...

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2nd International Conference on Artificial Intelligence and Signal Processing, AISP 2022

作者： Sriraman, Siddharth Manjunathan, R. Sivakumar, Nethraa Pooja, S. Viswanath, Nikhil Dept. of Computer Science and Engineering SSN College of Engineering Kalavakkam India Dept. of Electronics and Communication Engineering SSN College of Engineering Kalavakkam India

ISBN: (纸本)9781665442909

In this paper, we analyze the performance of graph convolutional networks (GCNs) in predicting COVID-19 incidence in states and union territories (UTs) in India as a semi-supervised learning task. By training the model with data from a small number of states whose incidence is known, we analyze the accuracy in predicting incidence levels in the remaining states and UTs in India. We explore the effect of pre-existing factors such as foreign visitor count, senior citizen population and population density of states in predicting spread. To show the robustness of this model, we introduce a novel method to choose states for training that reduces bias through random sampling in five regions that cover India’s geography. We show that GCNs, on average, produce a 9% improvement in accuracy over the best performing non-graph-based model and discuss if the results are feasible for use in a real-world scenario. © 2022 IEEE.

关键词： Graphic methods

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Deep Learning based Chatbot Architecture for Medical Diagnosis and Treatment Recommendation 3

Deep Learning based Chatbot Architecture for Medical Diagnos...

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3rd International Conference on Advanced Computing Technologies and Applications, ICACTA 2023

作者： Rajani, Girish Ruparel, Khushi Thadomal Shahani Engineering College Dept. of Artificial Intelligence and Data Science Mumbai India

ISBN: (纸本)9798350348347

With the exponential growth and rapid development in the fields of deep learning and neural networks, chatbots have gained a lot of popularity and have become a proven, and efficient tool to interact and provide service to users. Healthcare is one of the most promising fields where chatbots can be used more efficiently. This has become important, especially in the current medical landscape, where there is a shortage of doctors, and patients often have to wait long periods before getting any medical guidance. By using the power of transformer models and machine learning algorithms chatbots can help patients with personalized diagnoses and treatment recommendations, efficiently at ease and convenience. This helps the patients to access medical services anywhere, at any point in time. This paper proposes a well-planned systematic architecture for a medical chatbot that utilizes the potential of transformers, classification algorithms and machine-learning models. The architecture includes three main components: a Naïve Bayes Classifier, a Binary Tree classifier along with a Support Vector Classifier, and a sequence-to-sequence model. These algorithms are used to classify symptoms and determine the severity of a medical condition to provide patients with accurate medical diagnoses and treatment recommendations. Overall, the proposed architecture is built and designed to bridge the gap between doctors and patients by providing immediate access to medical advice, making it a promising tool for improving the quality and accessibility of healthcare services. © 2023 IEEE.

关键词： Diagnosis

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Demo: RecDroid- an android resource access permission recommendation system 15

Demo: RecDroid- an android resource access permission recomm...

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16th ACM International Symposium on Mobile Ad Hoc Networking and Computing, MobiHoc 2015

作者： Rashidi, Bahman Fung, Carol Bond, Gerrit Jackson, Steven Pare, Marcus Vu, Tam Dept. of Computer Science Virginia Commonwealth University RichmondVA United States Dept. of Computer Science and Engineering University of Colorado Denver DenverCO United States

ISBN: (纸本)9781450334891

Nowadays, it is prohibitive for apps market places, such as Google App Store, to thoroughly verify an app’s resource permission requests to be legitimate or malicious. As a result, mobile users are left to decide for themselves whether an app is safe to use or not. To assist users to make correct decisions as for whether to accept a permission request or not, we propose RecDroid. RecDroid is a crowdsourcing recommendation framework that collects apps’ permission requests and users’ responses to those requests, from which an experts ranking algorithm is used to seek expert users in the system and a recommendation algorithm is used to suggest appropriate responses to permission requests (accept or reject) based on experts’ responses. In this demo, we demonstrate a user case to show how the RecDroid system assists users in permission control. We also explain the major principles and processes behind that support the RecDroid recommendation system. Copyright © 2015 ACM.

关键词： Recommender systems

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