Search results for: hierarchical segmentation

Authors: XueSong Yu, JiaFeng Liu, XiangLong Tang, JianHua Huang

Abstract:

For improving the efficiency of human 3D tracking, we present an algorithm to track 3D Arm Motion. First, the Hierarchy Limb Model (HLM) is proposed based on the human 3D skeleton model. Second, via graph decomposition, the arm motion state space, modeled by HLM, can be discomposed into two low dimension subspaces: root nodes and leaf nodes. Finally, Rao-Blackwellised Particle Filter is used to estimate the 3D arm motion. The result of experiment shows that our algorithm can advance the computation efficiency.

Keywords: Hierarchy Limb Model; Rao-Blackwellised Particle Filter; 3D tracking

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Authors: N. Lassouaoui, L. Hamami, N. Nouali

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The tracking allows to detect the tumor affections of cervical cancer, it is particularly complex and consuming time, because it consists in seeking some abnormal cells among a cluster of normal cells. In this paper, we present our proposed computer system for helping the doctors in tracking the cervical cancer. Knowing that the diagnosis of the malignancy is based in the set of atypical morphological details of all cells, herein, we present an unsupervised genetic algorithm for the separation of cell components since the diagnosis is doing by analysis of the core and the cytoplasm. We give also the various algorithms used for computing the morphological characteristics of cells (Ratio core/cytoplasm, cellular deformity, ...) necessary for the recognition of illness.

Keywords: Cervical cell, morphological analysis, recognition, segmentation.

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Authors: Abdel Rodríguez, Isis Bonet, Ricardo Grau, María M. García

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In this paper we designed and implemented a new ensemble of classifiers based on a sequence of classifiers which were specialized in regions of the training dataset where errors of its trained homologous are concentrated. In order to separate this regions, and to determine the aptitude of each classifier to properly respond to a new case, it was used another set of classifiers built hierarchically. We explored a selection based variant to combine the base classifiers. We validated this model with different base classifiers using 37 training datasets. It was carried out a statistical comparison of these models with the well known Bagging and Boosting, obtaining significantly superior results with the hierarchical ensemble using Multilayer Perceptron as base classifier. Therefore, we demonstrated the efficacy of the proposed ensemble, as well as its applicability to general problems.

Keywords: classifiers, delegation, ensemble

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Authors: M. Jarocka

Abstract:

The paper contains a review of the literature in terms of the critical analysis of methodologies of university ranking systems. Furthermore, the initiatives supported by the European Commission (U-Map, U-Multirank) and CHE Ranking are described. Special attention is paid to the tendencies in the development of ranking systems. According to the author, the ranking organizations should abandon the classic form of ranking, namely a hierarchical ordering of universities from “the best" to “the worse". In the empirical part of this paper, using one of the method of cluster analysis called k-means clustering, the author presents university classifications of the top universities from the Shanghai Jiao Tong University-s (SJTU) Academic Ranking of World Universities (ARWU).

Keywords: Classification, cluster analysis, ranking, university.

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Authors: Chih-Feng Chuang, Shih-Ching Shiu, Chao-Jen Cheng

Abstract:

The purpose of this study was to investigate the relationships among students- process of study, creative self-efficacy and creativity while attending college. A total of 60 students enrolled in Hsiuping Institute of Technology in central Taiwan were selected as samples for the study. The instruments for this study included three questionnaires to explore the aforesaid aspects. This researchers tested creative self-efficacy and process of study, and creativity with Pearson correlation and hierarchical regression analyses. The major findings of this research are (1) the process of study had direct positive predictability on creativity, and (2) the relationship between process of study and creativity is partially mediated by creative self-efficacy.

Keywords: Process of study, Creative self-efficacy, Creativity

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Authors: Seung-Jun Yu, Hwan-Jun Choi, Hyoung-Kyu Song

Abstract:

Among spatial diversity scheme, orthogonal space-time block code (OSTBC) and cyclic delay diversity (CDD) have been widely studied for the cooperative wireless relaying system. However, conventional OSTBC and CDD cannot cope with change in the number of relays owing to low throughput or error performance. In this paper, we propose a cooperative cyclic delay diversity (CDD) scheme that use hierarchical modulation at the source and adaptive modulation based on cyclic redundancy check (CRC) code at the relays.

Keywords: Adaptive modulation, Cooperative communication, CDD, OSTBC.

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Authors: Tetsuya Furukawa, Masahiro Kuzunishi

Abstract:

Collected data must be organized to be utilized efficiently, and hierarchical classification of data is efficient approach to organize data. When data is classified to multiple categories or annotated with a set of labels, users request multi-labeled data by giving a set of labels. There are several interpretations of the data expressed by a set of labels. This paper discusses which data is expressed by a set of labels by introducing orders for sets of labels and shows that there are four types of orders, which are characterized by whether the labels of expressed data includes every label of the given set of labels within the range of the set. Desirable properties of the orders, data is also expressed by the higher set of labels and different sets of labels express different data, are discussed for the orders.

Keywords: Classification Hierarchies, Multi-labeled Data, Multiple Classificaiton, Orders of Sets of Labels

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Authors: Pairaya J., Buddhagarn R., Sukree S., Punthumadee K.

Abstract:

Application of Information Technology (IT) has revolutionized the functioning of business all over the world. Its impact has been felt mostly among the information of dependent industries. Tourism is one of such industry. The conceptual framework in this study represents an innovation of travel information searching system on mobile devices which is used as tools to deliver travel information (such as hotels, restaurants, tourist attractions and souvenir shops) for each user by travelers segmentation based on data mining technique to segment the tourists- behavior patterns then match them with tourism products and services. This system innovation is designed to be a knowledge incremental learning. It is a marketing strategy to support business to respond traveler-s demand effectively.

Keywords: Tourism, Innovation, Information Searching, Data Mining.

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Authors: A. Harifi, A. Aghagolzadeh

Abstract:

The main problem for recognition of handwritten Persian digits using Neural Network is to extract an appropriate feature vector from image matrix. In this research an asymmetrical segmentation pattern is proposed to obtain the feature vector. This pattern can be adjusted as an optimum model thanks to its one degree of freedom as a control point. Since any chosen algorithm depends on digit identity, a Neural Network is used to prevail over this dependence. Inputs of this Network are the moment of inertia and the center of gravity which do not depend on digit identity. Recognizing the digit is carried out using another Neural Network. Simulation results indicate the high recognition rate of 97.6% for new introduced pattern in comparison to the previous models for recognition of digits.

Keywords: Pattern recognition, Persian digits, NeuralNetwork.

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Authors: Endrick Barnacin, Jean-Luc Henry, Jimmy Nagau, Jack Molinié

Abstract:

Palynology is a field of interest in many disciplines due to its multiple applications: chronological dating, climatology, allergy treatment, and honey characterization. Unfortunately, the analysis of a pollen slide is a complicated and time consuming task that requires the intervention of experts in the field, which are becoming increasingly rare due to economic and social conditions. In this context, the automation of this task is urgent. In this work, we compare classical feature extraction methods (Shape, GLCM, LBP, and others) and Deep Learning (CNN and Transfer Learning) to perform a recognition task over 80 regional pollen species. It has been found that the use of Transfer Learning seems to be more precise than the other approaches.

Keywords: Image segmentation, stuck particles separation, Sobel operator, thresholding.

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Authors: Michela Lecca

Abstract:

System MEMORI automatically detects and recognizes rotated and/or rescaled versions of the objects of a database within digital color images with cluttered background. This task is accomplished by means of a region grouping algorithm guided by heuristic rules, whose parameters concern some geometrical properties and the recognition score of the database objects. This paper focuses on the strategies implemented in MEMORI for the estimation of the heuristic rule parameters. This estimation, being automatic, makes the system a highly user-friendly tool.

Keywords: Automatic object recognition, clustering, content based image retrieval system, image segmentation, region adjacency graph, region grouping.

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Authors: Huynh Quyet Thang, Le Hai Quan

Abstract:

Interaction Model plays an important role in Modelbased Intelligent Interface Agent Architecture for developing Intelligent User Interface. In this paper we are presenting some improvements in the algorithms for development interaction model of interface agent including: the action segmentation algorithm, the action pair selection algorithm, the final action pair selection algorithm, the interaction graph construction algorithm and the probability calculation algorithm. The analysis of the algorithms also presented. At the end of this paper, we introduce an experimental program called “Personal Transfer System".

Keywords: interface agent, interaction model, user model.

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Authors: Xingsheng Yuan, Zhengzhi Wang

Abstract:

Color constancy algorithms are generally based on the simplified assumption about the spectral distribution or the reflection attributes of the scene surface. However, in reality, these assumptions are too restrictive. The methodology is proposed to extend existing algorithm to applying color constancy locally to image patches rather than globally to the entire images. In this paper, a method based on low-level image features using superpixels is proposed. Superpixel segmentation partition an image into regions that are approximately uniform in size and shape. Instead of using entire pixel set for estimating the illuminant, only superpixels with the most valuable information are used. Based on large scale experiments on real-world scenes, it can be derived that the estimation is more accurate using superpixels than when using the entire image.

Keywords: color constancy, illuminant estimation, superpixel

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Authors: Yucel Ugurlu

Abstract:

This paper explains a novel approach to human interactive e-learning systems using head posture images. Students- face and hair information are used to identify a human presence and estimate the gaze direction. We then define the human-computer interaction level and test the definition using ten students and seventy different posture images. The experimental results show that head posture images provide adequate information for increasing human-computer interaction in e-learning systems.

Keywords: E-learning, image segmentation, human-presence, gaze-direction, human-computer interaction, LabVIEW

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Authors: Walid Aydi, Nouri Masmoudi, Lotfi Kamoun

Abstract:

Images of human iris contain specular highlights due to the reflective properties of the cornea. This corneal reflection causes many errors not only in iris and pupil center estimation but also to locate iris and pupil boundaries especially for methods that use active contour. Each iris recognition system has four steps: Segmentation, Normalization, Encoding and Matching. In order to address the corneal reflection, a novel reflection removal method is proposed in this paper. Comparative experiments of two existing methods for reflection removal method are evaluated on CASIA iris image databases V3. The experimental results reveal that the proposed algorithm provides higher performance in reflection removal.

Keywords: iris, pupil, specular highlights, reflection removal

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Authors: Aly Farag, Ayman El-Baz, Refaat Mohamed

Abstract:

In this paper we present a novel approach for density estimation. The proposed approach is based on using the logistic regression model to get initial density estimation for the given empirical density. The empirical data does not exactly follow the logistic regression model, so, there will be a deviation between the empirical density and the density estimated using logistic regression model. This deviation may be positive and/or negative. In this paper we use a linear combination of Gaussian (LCG) with positive and negative components as a model for this deviation. Also, we will use the expectation maximization (EM) algorithm to estimate the parameters of LCG. Experiments on real images demonstrate the accuracy of our approach.

Keywords: Logistic regression model, Expectationmaximization, Segmentation.

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Authors: Rongli Gai, Zhiyuan Chang, Xiaohong Wang, Jingyu Liu

Abstract:

In view of various situations in the interpolation process, most researchers use self-adaptation to adjust the interpolation process, which is also one of the current and future research hotspots in the field of CNC (Computerized Numerical Control) machining. In the interpolation process, according to the overview of the spline curve interpolation algorithm, the adaptive analysis is carried out from the factors affecting the interpolation process. The adaptive operation is reflected in various aspects, such as speed, parameters, errors, nodes, feed rates, random period, sensitive point, step size, curvature, adaptive segmentation, adaptive optimization, etc. This paper will analyze and summarize the research of adaptive imputation in the direction of the above factors affecting imputation.

Keywords: Adaptive algorithm, CNC machining, interpolation constraints, spline curve interpolation.

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Authors: Z. G. Wang, M. Rahman, Y. S. Wong, K. S. Neo

Abstract:

In this paper, a new hybrid of genetic algorithm (GA) and simulated annealing (SA), referred to as GSA, is presented. In this algorithm, SA is incorporated into GA to escape from local optima. The concept of hierarchical parallel GA is employed to parallelize GSA for the optimization of multimodal functions. In addition, multi-niche crowding is used to maintain the diversity in the population of the parallel GSA (PGSA). The performance of the proposed algorithms is evaluated against a standard set of multimodal benchmark functions. The multi-niche crowding PGSA and normal PGSA show some remarkable improvement in comparison with the conventional parallel genetic algorithm and the breeder genetic algorithm (BGA).

Keywords: Crowding, genetic algorithm, parallel geneticalgorithm, simulated annealing.

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Authors: Mohammed Fethi Khalfi, Malika Kandouci

Abstract:

Over the past decade, mobile has experienced a revolution that will ultimately change the way we communicate.All these technologies have a common denominator exploitation of computer information systems, but their operation can be tedious because of problems with heterogeneous data sources.To overcome the problems of heterogeneous data sources, we propose to use a technique of adding an extra layer interfacing applications of management or supervision at the different data sources.This layer will be materialized by the implementation of a mediator between different host applications and information systems frequently used hierarchical and relational manner such that the heterogeneity is completely transparent to the VoIP platform.

Keywords: TOIP, Data Integration, Mediation, informationcomputer system, heterogeneous data sources

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Authors: Abdullah H. Özcan, Dilara Hisar, Yetkin Sayar, Cem Ünsalan

Abstract:

In this study, an automated building and tree detection method is proposed using DSM data and true orthophoto image. A multiscale matched filtering is used on DSM data. Therefore, first watershed transform is applied. Then, Otsu’s thresholding method is used as an adaptive threshold to segment each watershed region. Detected objects are masked with NDVI to separate buildings and trees. The proposed method is able to detect buildings and trees without entering any elevation threshold. We tested our method on ISPRS semantic labeling dataset and obtained promising results.

Keywords: Building detection, tree detection, matched filtering, multiscale, local maximum filtering, watershed segmentation.

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Authors: Michela Lecca

Abstract:

System MEMORI automatically detects and recognizes rotated and/or rescaled versions of the objects of a database within digital color images with cluttered background. This task is accomplished by means of a region grouping algorithm guided by heuristic rules, whose parameters concern some geometrical properties and the recognition score of the database objects. This paper focuses on the strategies implemented in MEMORI for the estimation of the heuristic rule parameters. This estimation, being automatic, makes the system a self configuring and highly user-friendly tool.

Keywords: Automatic Object Recognition, Clustering, Contentbased Image Retrieval System, Image Segmentation, Region Adjacency Graph, Region Grouping.

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Authors: Won-Ho Kim, Nuwan Sanjeewa Rajasooriya

Abstract:

In this paper, a simple moving human detection method is proposed for video surveillance system or access monitoring system. The frame difference and noise threshold are used for initial detection of a moving human-object, and simple labeling method is applied for final human-object segmentation. The simulated results show that the applied algorithm is fast to detect the moving human-objects by performing 95% of correct detection rate. The proposed algorithm has confirmed that can be used as an intelligent video access monitoring system.

Keywords: Moving human-object detection, Video access monitoring, Image processing.

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Authors: Rahma Souli-Jbali, Minyar Sassi Hidri, Rahma Ben Ayed

Abstract:

Grid of computing nodes has emerged as a representative means of connecting distributed computers or resources scattered all over the world for the purpose of computing and distributed storage. Since fault tolerance becomes complex due to the availability of resources in decentralized grid environment, it can be used in connection with replication in data grids. The objective of our work is to present fault tolerance in data grids with data replication-driven model based on clustering. The performance of the protocol is evaluated with Omnet++ simulator. The computational results show the efficiency of our protocol in terms of recovery time and the number of process in rollbacks.

Keywords: Data grids, fault tolerance, chandy-lamport, clustering.

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Authors: Hermenegilde Nkurunziza, Albrecht Gebhardt, Juergen Pilz

Abstract:

The focus in this work is to assess which method allows a better forecasting of malaria cases in Bujumbura ( Burundi) when taking into account association between climatic factors and the disease. For the period 1996-2007, real monthly data on both malaria epidemiology and climate in Bujumbura are described and analyzed. We propose a hierarchical approach to achieve our objective. We first fit a Generalized Additive Model to malaria cases to obtain an accurate predictor, which is then used to predict future observations. Various well-known forecasting methods are compared leading to different results. Based on in-sample mean average percentage error (MAPE), the multiplicative exponential smoothing state space model with multiplicative error and seasonality performed better.

Keywords: Burundi, Forecasting, Malaria, Regressionmodel, State space model.

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Authors: M. Vivodík, Ž. Balážová, Z. Gálová

Abstract:

The aim of this work was to detect genetic variability among the set of 40 castor genotypes using 8 RAPD markers. Amplification of genomic DNA of 40 genotypes, using RAPD analysis, yielded in 66 fragments, with an average of 8.25 polymorphic fragments per primer. Number of amplified fragments ranged from 3 to 13, with the size of amplicons ranging from 100 to 1200 bp. Values of the polymorphic information content (PIC) value ranged from 0.556 to 0.895 with an average of 0.784 and diversity index (DI) value ranged from 0.621 to 0.896 with an average of 0.798. The dendrogram based on hierarchical cluster analysis using UPGMA algorithm was prepared and analyzed genotypes were grouped into two main clusters and only two genotypes could not be distinguished. Knowledge on the genetic diversity of castor can be used for future breeding programs for increased oil production for industrial uses.

Keywords: Dendrogram, polymorphism, RAPD technique, Ricinus communis L.

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Authors: Al-Amin Bhuiyan, Chang Hong Liu

Abstract:

This paper addresses the development of an intelligent vision system for human-robot interaction. The two novel contributions of this paper are 1) Detection of human faces and 2) Localizing the eye. The method is based on visual attributes of human skin colors and geometrical analysis of face skeleton. This paper introduces a spatial domain filtering method named ?Fuzzily skewed filter' which incorporates Fuzzy rules for deciding the gray level of pixels in the image in their neighborhoods and takes advantages of both the median and averaging filters. The effectiveness of the method has been justified over implementing the eye tracking commands to an entertainment robot, named ''AIBO''.

Keywords: Fuzzily skewed filter, human-robot interface, rmscontrast, skin color segmentation.

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Authors: Salam K. Al-Nasri, SM Holmes

Abstract:

Composite of Celatom-ZeoliteY (Cel-ZY) was used to remove cobalt ion from an aqueous solution using batch mode. ZeoliteY has successfully superimposed on Celatom FW-14 surface using hydrothermal treatment .The product was synthesized as a novel of hierarchical porous material. It was observed from the results that Cel-ZY has higher ability to remove cobalt ions than the pure ZeoliteY powder (PZY) synthesized under the same conditions. Several parameters were studied in this project to investigate the effect of removal cobalt ion such as pH and initial cobalt concentration. It was clearly observed that the uptake of cobalt ions was affected with increase these parameters. The results proved that the product can be used effectively to remove Co2+ ions from wastewater as an environmentally friendly alternative.

Keywords: Adsorption, Celatom-Zeolite, Cobalt ions, Isotherm models.

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Authors: Seung-Jun Yu, Yong-Jun Kim, Jung-In Baik, Hyoung-Kyu Song

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In this paper, a dual-hop relay based on channel state is studied. In the conventional relay scheme, a relay uses the same modulation method without reference to channel state. But, a relay uses an adaptive modulation method with reference to channel state. If the channel state is poor, a relay eliminates latter 2 bits and uses Quadrature Phase Shift Keying (QPSK) modulation. If channel state is good, a relay modulates the received symbols with 16-QAM symbols by using 4 bits. The performance of the proposed scheme for Symbol Error Rate (SER) and throughput is analyzed.

Keywords: Adaptive transmission, channel state, dual-hop, hierarchical modulation, relay.

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Authors: Alka Obadić

Abstract:

The research concentrates on the role of tourism in generating female employment and on impact of gender discrimination in tourism sector. Unfortunately, in many countries there are still some barriers to the inclusion of women at all hierarchical levels of tourism labor market. Research analysis focuses on EU countries where tourism is a main employer of women. The analysis shows that women represent over third persons employed in the non-financial business economy and almost two thirds in core tourism activities. Women's gross hourly earnings in accommodation and food services were below those of men in the European Union and only countries who recorded increase of gender pay gap from the beginning of crisis are Bulgaria and Croatia. Women in tourism industry are still overrepresented in lower status jobs with fewer opportunities for career progression and are often treated unequally.

Keywords: Employment, gender discrimination, tourism, women’s participation.

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Authors: Ae Hee Park, So Hyun Park, Hee Yong Youn

Abstract:

Multi-agent system is composed by several agents capable of reaching the goal cooperatively. The system needs an agent platform for efficient and stable interaction between intelligent agents. In this paper we propose a flexible and scalable agent platform by composing the containers with multiple hierarchical agent groups. It also allows efficient implementation of multiple domain presentations of the agents unlike JADE. The proposed platform provides both group management and individual management of agents for efficiency. The platform has been implemented and tested, and it can be used as a flexible foundation of the dynamic multi-agent system targeting seamless delivery of ubiquitous services.

Keywords: Agent platform, container, multi-agent system, services, ubiquitous computing

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