Search results for: automatic CFD analysis
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9138

Search results for: automatic CFD analysis

8718 Improving Multi-storey Building Sensor Network with an External Hub

Authors: Malka N. Halgamuge, Toong-Khuan Chan, Priyan Mendis

Abstract:

Monitoring and automatic control of building environment is a crucial application of Wireless Sensor Network (WSN) in which maximizing network lifetime is a key challenge. Previous research into the performance of a network in a building environment has been concerned with radio propagation within a single floor. We investigate the link quality distribution to obtain full coverage of signal strength in a four-storey building environment, experimentally. Our results indicate that the transitional region is of particular concern in wireless sensor network since it accommodates high variance unreliable links. The transitional region in a multi-storey building is mainly due to the presence of reinforced concrete slabs at each storey and the fac┬©ade which obstructs the radio signal and introduces an additional absorption term to the path loss.

Keywords: Wireless sensor networks, radio propagation, building monitoring

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8717 Data-organization Before Learning Multi-Entity Bayesian Networks Structure

Authors: H. Bouhamed, A. Rebai, T. Lecroq, M. Jaoua

Abstract:

The objective of our work is to develop a new approach for discovering knowledge from a large mass of data, the result of applying this approach will be an expert system that will serve as diagnostic tools of a phenomenon related to a huge information system. We first recall the general problem of learning Bayesian network structure from data and suggest a solution for optimizing the complexity by using organizational and optimization methods of data. Afterward we proposed a new heuristic of learning a Multi-Entities Bayesian Networks structures. We have applied our approach to biological facts concerning hereditary complex illnesses where the literatures in biology identify the responsible variables for those diseases. Finally we conclude on the limits arched by this work.

Keywords: Data-organization, data-optimization, automatic knowledge discovery, Multi-Entities Bayesian networks, score merging.

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8716 State-Space PD Feedback Control

Authors: John Florescu

Abstract:

A challenged control problem is when the performance is pushed to the limit. The state-derivative feedback control strategy directly uses acceleration information for feedback and state estimation. The derivative part is concerned with the rateof- change of the error with time. If the measured variable approaches the set point rapidly, then the actuator is backed off early to allow it to coast to the required level. Derivative action makes a control system behave much more intelligently. A sensor measures the variable to be controlled and the measured in formation is fed back to the controller to influence the controlled variable. A high gain problem can be also formulated for proportional plus derivative feedback transformation. Using MATLAB Simulink dynamic simulation tool this paper examines a system with a proportional plus derivative feedback and presents an automatic implementation of finding an acceptable controlled system. Using feedback transformations the system is transformed into another system.

Keywords: Feedback, PD, state-space, derivative.

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8715 A Case Study of an Online Assignment Submission System at UOM

Authors: V. Ramnarain-Seetohul, J. Abdool Karim, A. Amir

Abstract:

Almost all universities include some form of assignment in their courses. The assignments are either carried out in either in groups or individually. To effectively manage these submitted assignments, a well-designed assignment submission system is needed, hence the need for an online assignment submission system to facilitate the distribution, and collection of assignments on due dates. The objective of such system is to facilitate interaction of lecturers and students for assessment and grading purposes. The aim of this study was to create a web based online assignment submission system for University of Mauritius. The system was created to eliminate the traditional process of giving an assignment and collecting the answers for the assignment. Lecturers can also create automated assessment to assess the students online. Moreover, the online submission system consists of an automatic mailing system which acts as a reminder for students about the deadlines of the posted assignments. System was tested to measure its acceptance rate among both student and lecturers.

Keywords: Assignment, assessment, online, submission

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8714 Investigation on Feature Extraction and Classification of Medical Images

Authors: P. Gnanasekar, A. Nagappan, S. Sharavanan, O. Saravanan, D. Vinodkumar, T. Elayabharathi, G. Karthik

Abstract:

In this paper we present the deep study about the Bio- Medical Images and tag it with some basic extracting features (e.g. color, pixel value etc). The classification is done by using a nearest neighbor classifier with various distance measures as well as the automatic combination of classifier results. This process selects a subset of relevant features from a group of features of the image. It also helps to acquire better understanding about the image by describing which the important features are. The accuracy can be improved by increasing the number of features selected. Various types of classifications were evolved for the medical images like Support Vector Machine (SVM) which is used for classifying the Bacterial types. Ant Colony Optimization method is used for optimal results. It has high approximation capability and much faster convergence, Texture feature extraction method based on Gabor wavelets etc..

Keywords: ACO Ant Colony Optimization, Correlogram, CCM Co-Occurrence Matrix, RTS Rough-Set theory

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8713 A Case-Based Reasoning-Decision Tree Hybrid System for Stock Selection

Authors: Yaojun Wang, Yaoqing Wang

Abstract:

Stock selection is an important decision-making problem. Many machine learning and data mining technologies are employed to build automatic stock-selection system. A profitable stock-selection system should consider the stock’s investment value and the market timing. In this paper, we present a hybrid system including both engage for stock selection. This system uses a case-based reasoning (CBR) model to execute the stock classification, uses a decision-tree model to help with market timing and stock selection. The experiments show that the performance of this hybrid system is better than that of other techniques regarding to the classification accuracy, the average return and the Sharpe ratio.

Keywords: Case-based reasoning, decision tree, stock selection, machine learning.

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8712 Extracting Tongue Shape Dynamics from Magnetic Resonance Image Sequences

Authors: María S. Avila-García, John N. Carter, Robert I. Damper

Abstract:

An important problem in speech research is the automatic extraction of information about the shape and dimensions of the vocal tract during real-time speech production. We have previously developed Southampton dynamic magnetic resonance imaging (SDMRI) as an approach to the solution of this problem.However, the SDMRI images are very noisy so that shape extraction is a major challenge. In this paper, we address the problem of tongue shape extraction, which poses difficulties because this is a highly deforming non-parametric shape. We show that combining active shape models with the dynamic Hough transform allows the tongue shape to be reliably tracked in the image sequence.

Keywords: Vocal tract imaging, speech production, active shapemodels, dynamic Hough transform, object tracking.

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8711 Improving Taint Analysis of Android Applications Using Finite State Machines

Authors: Assad Maalouf, Lunjin Lu, James Lynott

Abstract:

We present a taint analysis that can automatically detect when string operations result in a string that is free of taints, where all the tainted patterns have been removed. This is an improvement on the conservative behavior of previous taint analyzers, where a string operation on a tainted string always leads to a tainted string unless the operation is manually marked as a sanitizer. The taint analysis is built on top of a string analysis that uses finite state automata to approximate the sets of values that string variables can take during the execution of a program. The proposed approach has been implemented as an extension of FlowDroid and experimental results show that the resulting taint analyzer is much more precise than the original FlowDroid.

Keywords: Android, static analysis, string analysis, taint analysis.

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8710 Multi-threshold Approach for License Plate Recognition System

Authors: Siti Norul Huda Sheikh Abdullah, Farshid Pirahan Siah, Nor Hanisah Haji Zainal Abidin, Shahnorbanun Sahran

Abstract:

The objective of this paper is to propose an adaptive multi threshold for image segmentation precisely in object detection. Due to the different types of license plates being used, the requirement of an automatic LPR is rather different for each country. The proposed technique is applied on Malaysian LPR application. It is based on Multi Layer Perceptron trained by back propagation. The proposed adaptive threshold is introduced to find the optimum threshold values. The technique relies on the peak value from the graph of the number object versus specific range of threshold values. The proposed approach has improved the overall performance compared to current optimal threshold techniques. Further improvement on this method is in progress to accommodate real time system specification.

Keywords: Multi-threshold approach, license plate recognition system.

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8709 A Text Classification Approach Based on Natural Language Processing and Machine Learning Techniques

Authors: Rim Messaoudi, Nogaye-Gueye Gning, François Azelart

Abstract:

Automatic text classification applies mostly natural language processing (NLP) and other artificial intelligence (AI)-guided techniques to automatically classify text in a faster and more accurate manner. This paper discusses the subject of using predictive maintenance to manage incident tickets inside the sociality. It focuses on proposing a tool that treats and analyses comments and notes written by administrators after resolving an incident ticket. The goal here is to increase the quality of these comments. Additionally, this tool is based on NLP and machine learning techniques to realize the textual analytics of the extracted data. This approach was tested using real data taken from the French National Railways (SNCF) company and was given a high-quality result.

Keywords: Machine learning, text classification, NLP techniques, semantic representation.

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8708 On the Interactive Search with Web Documents

Authors: Mario Kubek, Herwig Unger

Abstract:

Due to the large amount of information in the World Wide Web (WWW, web) and the lengthy and usually linearly ordered result lists of web search engines that do not indicate semantic relationships between their entries, the search for topically similar and related documents can become a tedious task. Especially, the process of formulating queries with proper terms representing specific information needs requires much effort from the user. This problem gets even bigger when the user's knowledge on a subject and its technical terms is not sufficient enough to do so. This article presents the new and interactive search application DocAnalyser that addresses this problem by enabling users to find similar and related web documents based on automatic query formulation and state-ofthe- art search word extraction. Additionally, this tool can be used to track topics across semantically connected web documents.

Keywords: DocAnalyser, interactive web search, search word extraction, query formulation, source topic detection, topic tracking.

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8707 Neural Network Based Approach for Face Detection cum Face Recognition

Authors: Kesari Verma, Aniruddha S. Thoke, Pritam Singh

Abstract:

Automatic face detection is a complex problem in image processing. Many methods exist to solve this problem such as template matching, Fisher Linear Discriminate, Neural Networks, SVM, and MRC. Success has been achieved with each method to varying degrees and complexities. In proposed algorithm we used upright, frontal faces for single gray scale images with decent resolution and under good lighting condition. In the field of face recognition technique the single face is matched with single face from the training dataset. The author proposed a neural network based face detection algorithm from the photographs as well as if any test data appears it check from the online scanned training dataset. Experimental result shows that the algorithm detected up to 95% accuracy for any image.

Keywords: Face Detection, Face Recognition, NN Approach, PCA Algorithm.

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8706 Prediction Heating Values of Lignocellulosics from Biomass Characteristics

Authors: Kaltima Phichai, Pornchanoke Pragrobpondee, Thaweesak Khumpart, Samorn Hirunpraditkoon

Abstract:

The paper provides biomasses characteristics by proximate analysis (volatile matter, fixed carbon and ash) and ultimate analysis (carbon, hydrogen, nitrogen and oxygen) for the prediction of the heating value equations. The heating value estimation of various biomasses can be used as an energy evaluation. Thirteen types of biomass were studied. Proximate analysis was investigated by mass loss method and infrared moisture analyzer. Ultimate analysis was analyzed by CHNO analyzer. The heating values varied from 15 to 22.4MJ kg-1. Correlations of the calculated heating value with proximate and ultimate analyses were undertaken using multiple regression analysis and summarized into three and two equations, respectively. Correlations based on proximate analysis illustrated that deviation of calculated heating values from experimental heating values was higher than the correlations based on ultimate analysis.

Keywords: Heating value equation, Proximate analysis, Ultimate analysis.

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8705 Hybrid Neural Network Methods for Lithology Identification in the Algerian Sahara

Authors: S. Chikhi, M. Batouche, H. Shout

Abstract:

In this paper, we combine a probabilistic neural method with radial-bias functions in order to construct the lithofacies of the wells DF01, DF02 and DF03 situated in the Triassic province of Algeria (Sahara). Lithofacies is a crucial problem in reservoir characterization. Our objective is to facilitate the experts' work in geological domain and to allow them to obtain quickly the structure and the nature of lands around the drilling. This study intends to design a tool that helps automatic deduction from numerical data. We used a probabilistic formalism to enhance the classification process initiated by a Self-Organized Map procedure. Our system gives lithofacies, from well-log data, of the concerned reservoir wells in an aspect easy to read by a geology expert who identifies the potential for oil production at a given source and so forms the basis for estimating the financial returns and economic benefits.

Keywords: Classification, Lithofacies, Probabilistic formalism, Reservoir characterization, Well-log data.

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8704 En-Face Optical Coherence Tomography and Fluorescence in Evaluation of Orthodontic Interfaces

Authors: R. O. Rominu, C. Sinescu, D.M. Pop, M. Hughes, A. Bradu, M. Rominu, A. Gh. Podoleanu

Abstract:

Bonding has become a routine procedure in several dental specialties – from prosthodontics to conservative dentistry and even orthodontics. In many of these fields it is important to be able to investigate the bonded interfaces to assess their quality. All currently employed investigative methods are invasive, meaning that samples are destroyed in the testing procedure and cannot be used again. We have investigated the interface between human enamel and bonded ceramic brackets non-invasively, introducing a combination of new investigative methods – optical coherence tomography (OCT), fluorescence OCT and confocal microscopy (CM). Brackets were conventionally bonded on conditioned buccal surfaces of teeth. The bonding was assessed using these methods. Three dimensional reconstructions of the detected material defects were developed using manual and semi-automatic segmentation. The results clearly prove that OCT, fluorescence OCT and CM are useful in orthodontic bonding investigations.

Keywords: Optical coherence tomography, Confocal Microscopy, Orthodontic Bonding.

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8703 Multidimensional Data Mining by Means of Randomly Travelling Hyper-Ellipsoids

Authors: Pavel Y. Tabakov, Kevin Duffy

Abstract:

The present study presents a new approach to automatic data clustering and classification problems in large and complex databases and, at the same time, derives specific types of explicit rules describing each cluster. The method works well in both sparse and dense multidimensional data spaces. The members of the data space can be of the same nature or represent different classes. A number of N-dimensional ellipsoids are used for enclosing the data clouds. Due to the geometry of an ellipsoid and its free rotation in space the detection of clusters becomes very efficient. The method is based on genetic algorithms that are used for the optimization of location, orientation and geometric characteristics of the hyper-ellipsoids. The proposed approach can serve as a basis for the development of general knowledge systems for discovering hidden knowledge and unexpected patterns and rules in various large databases.

Keywords: Classification, clustering, data minig, genetic algorithms.

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8702 Segmentation of Korean Words on Korean Road Signs

Authors: Lae-Jeong Park, Kyusoo Chung, Jungho Moon

Abstract:

This paper introduces an effective method of segmenting Korean text (place names in Korean) from a Korean road sign image. A Korean advanced directional road sign is composed of several types of visual information such as arrows, place names in Korean and English, and route numbers. Automatic classification of the visual information and extraction of Korean place names from the road sign images make it possible to avoid a lot of manual inputs to a database system for management of road signs nationwide. We propose a series of problem-specific heuristics that correctly segments Korean place names, which is the most crucial information, from the other information by leaving out non-text information effectively. The experimental results with a dataset of 368 road sign images show 96% of the detection rate per Korean place name and 84% per road sign image.

Keywords: Segmentation, road signs, characters, classification.

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8701 Research on the Survivability of Embedded Real-time System

Authors: YongXian, JIN

Abstract:

Introducing survivability into embedded real-time system (ERTS) can improve the survivability power of the system. This paper mainly discusses about the survivability of ERTS. The first is the survivability origin of ERTS. The second is survivability analysis. According to the definition of survivability based on survivability specification and division of the entire survivability analysis process for ERTS, a survivability analysis profile is presented. The quantitative analysis model of this profile is emphasized and illuminated in detail, the quantifying analysis of system was showed helpful to evaluate system survivability more accurate. The third is platform design of survivability analysis. In terms of the profile, the analysis process is encapsulated and assembled into one platform, on which quantification, standardization and simplification of survivability analysis are all achieved. The fourth is survivability design. According to character of ERTS, strengthened design method is selected to realize system survivability design. Through the analysis of embedded mobile video-on-demand system, intrusion tolerant technology is introduced in whole survivability design.

Keywords: ERTS (embedded real-time system), survivability, quantitative analysis, survivability specification, intrusion tolerant

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8700 Sentiment Analysis: Comparative Analysis of Multilingual Sentiment and Opinion Classification Techniques

Authors: Sannikumar Patel, Brian Nolan, Markus Hofmann, Philip Owende, Kunjan Patel

Abstract:

Sentiment analysis and opinion mining have become emerging topics of research in recent years but most of the work is focused on data in the English language. A comprehensive research and analysis are essential which considers multiple languages, machine translation techniques, and different classifiers. This paper presents, a comparative analysis of different approaches for multilingual sentiment analysis. These approaches are divided into two parts: one using classification of text without language translation and second using the translation of testing data to a target language, such as English, before classification. The presented research and results are useful for understanding whether machine translation should be used for multilingual sentiment analysis or building language specific sentiment classification systems is a better approach. The effects of language translation techniques, features, and accuracy of various classifiers for multilingual sentiment analysis is also discussed in this study.

Keywords: Cross-language analysis, machine learning, machine translation, sentiment analysis.

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8699 Electromagnetic Field Modeling in Human Tissue

Authors: Iliana Marinova, Valentin Mateev

Abstract:

For investigations of electromagnetic field distributions in biological structures by Finite Element Method (FEM), a method for automatic 3D model building of human anatomical objects is developed. Models are made by meshed structures and specific electromagnetic material properties for each tissue type. Mesh is built according to specific FEM criteria for achieving good solution accuracy. Several FEM models of anatomical objects are built. Formulation using magnetic vector potential and scalar electric potential (A-V, A) is used for modeling of electromagnetic fields in human tissue objects. The developed models are suitable for investigations of electromagnetic field distributions in human tissues exposed in external fields during magnetic stimulation, defibrillation, impedance tomography etc.

Keywords: electromagnetic field, finite element method, humantissue.

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8698 Generalized Noise Analysis of Log Domain Static Translinear Circuits

Authors: E. Farshidi

Abstract:

This paper presents a new general technique for analysis of noise in static log-domain translinear circuits. It is demonstrated that employing this technique, leads to a general, simple and routine method of the noise analysis. The circuit has been simulated by HSPICE. The simulation results are seen to conform to the theoretical analysis and shows benefits of the proposed circuit.

Keywords: Noise analysis, log-domain, static, dynamic, translinear loop, companding.

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8697 A Hybrid Approach to Fault Detection and Diagnosis in a Diesel Fuel Hydrotreatment Process

Authors: Salvatore L., Pires B., Campos M. C. M., De Souza Jr M. B.

Abstract:

It is estimated that the total cost of abnormal conditions to US process industries is around $20 billion dollars in annual losses. The hydrotreatment (HDT) of diesel fuel in petroleum refineries is a conversion process that leads to high profitable economical returns. However, this is a difficult process to control because it is operated continuously, with high hydrogen pressures and it is also subject to disturbances in feed properties and catalyst performance. So, the automatic detection of fault and diagnosis plays an important role in this context. In this work, a hybrid approach based on neural networks together with a pos-processing classification algorithm is used to detect faults in a simulated HDT unit. Nine classes (8 faults and the normal operation) were correctly classified using the proposed approach in a maximum time of 5 minutes, based on on-line data process measurements.

Keywords: Fault detection, hydrotreatment, hybrid systems, neural networks.

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8696 Java Based Automatic Curriculum Generator for Children with Trisomy 21

Authors: E. Supriyanto, S. C. Seow

Abstract:

Early Intervention Program (EIP) is required to improve the overall development of children with Trisomy 21 (Down syndrome). In order to help trainer and parent in the implementation of EIP, a support system has been developed. The support system is able to screen data automatically, store and analyze data, generate individual EIP (curriculum) with optimal training duration and to generate training automatically. The system consists of hardware and software where the software has been implemented using Java language and Linux Fedora. The software has been tested to ensure the functionality and reliability. The prototype has been also tested in Down syndrome centers. Test result shows that the system is reliable to be used for generation of an individual curriculum which includes the training program to improve the motor, cognitive, and combination abilities of Down syndrome children under 6 years.

Keywords: Early intervention program (curriculum), Trisomy21, support system, Java.

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8695 Development of a Rating Scale for Elementary EFL Writing

Authors: Mohammed S. Assiri

Abstract:

In EFL programs, rating scales used in writing assessment are often constructed by intuition. Intuition-based scales tend to provide inaccurate and divisive ratings of learners’ writing performance. Hence, following an empirical approach, this study attempted to develop a rating scale for elementary-level writing at an EFL program in Saudi Arabia. Towards this goal, 98 students’ essays were scored and then coded using comprehensive taxonomy of writing constructs and their measures. An automatic linear modeling was run to find out which measures would best predict essay scores. A nonparametric ANOVA, the Kruskal-Wallis test, was then used to determine which measures could best differentiate among scoring levels. Findings indicated that there were certain measures that could serve as either good predictors of essay scores or differentiators among scoring levels, or both. The main conclusion was that a rating scale can be empirically developed using predictive and discriminative statistical tests.

Keywords: Analytic scoring, rating scales, writing assessment, writing performance.

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8694 Modeling and Simulating of Gas Turbine Cooled Blades

Authors: А. Pashayev, D. Askerov, R. Sadiqov, A. Samedov, C. Ardil

Abstract:

In contrast to existing methods which do not take into account multiconnectivity in a broad sense of this term, we develop mathematical models and highly effective combination (BIEM and FDM) numerical methods of calculation of stationary and quasistationary temperature field of a profile part of a blade with convective cooling (from the point of view of realization on PC). The theoretical substantiation of these methods is proved by appropriate theorems. For it, converging quadrature processes have been developed and the estimations of errors in the terms of A.Ziqmound continuity modules have been received. For visualization of profiles are used: the method of the least squares with automatic conjecture, device spline, smooth replenishment and neural nets. Boundary conditions of heat exchange are determined from the solution of the corresponding integral equations and empirical relationships. The reliability of designed methods is proved by calculation and experimental investigations heat and hydraulic characteristics of the gas turbine first stage nozzle blade.

Keywords: Modeling, Simulating, Gas Turbine, Cooled Blades.

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8693 A Visualized Framework for Representing Uncertain and Incomplete Temporal Knowledge

Authors: Yue Wang, Jixin Ma, Brian Knight

Abstract:

This paper presents a visualized computer aided case tool for non-expert, called Visual Time, for representing and reasoning about incomplete and uncertain temporal information. It is both expressive and versatile, allowing logical conjunctions and disjunctions of both absolute and relative temporal relations, such as “Before”, “Meets”, “Overlaps”, “Starts”, “During”, and “Finishes”, etc. In terms of a visualized framework, Visual Time provides a user-friendly environment for describing scenarios with rich temporal structure in natural language, which can be formatted as structured temporal phrases and modeled in terms of Temporal Relationship Diagrams (TRD). A TRD can be automatically and visually transformed into a corresponding Time Graph, supported by automatic consistency checker that derives a verdict to confirm if a given scenario is temporally consistent or inconsistent.

Keywords: Time Visualization, Uncertainty, Incompleteness, Consistency Checking.

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8692 Region-Based Image Fusion with Artificial Neural Network

Authors: Shuo-Li Hsu, Peng-Wei Gau, I-Lin Wu, Jyh-Horng Jeng

Abstract:

For most image fusion algorithms separate relationship by pixels in the image and treat them more or less independently. In addition, they have to be adjusted different parameters in different time or weather. In this paper, we propose a region–based image fusion which combines aspects of feature and pixel-level fusion method to replace only by pixel. The basic idea is to segment far infrared image only and to add information of each region from segmented image to visual image respectively. Then we determine different fused parameters according different region. At last, we adopt artificial neural network to deal with the problems of different time or weather, because the relationship between fused parameters and image features are nonlinear. It render the fused parameters can be produce automatically according different states. The experimental results present the method we proposed indeed have good adaptive capacity with automatic determined fused parameters. And the architecture can be used for lots of applications.

Keywords: Image fusion, Region-based fusion, Segmentation, Neural network, Multi-sensor.

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8691 A Data Mining Model for Detecting Financial and Operational Risk Indicators of SMEs

Authors: Ali Serhan Koyuncugil, Nermin Ozgulbas

Abstract:

In this paper, a data mining model to SMEs for detecting financial and operational risk indicators by data mining is presenting. The identification of the risk factors by clarifying the relationship between the variables defines the discovery of knowledge from the financial and operational variables. Automatic and estimation oriented information discovery process coincides the definition of data mining. During the formation of model; an easy to understand, easy to interpret and easy to apply utilitarian model that is far from the requirement of theoretical background is targeted by the discovery of the implicit relationships between the data and the identification of effect level of every factor. In addition, this paper is based on a project which was funded by The Scientific and Technological Research Council of Turkey (TUBITAK).

Keywords: Risk Management, Financial Risk, Operational Risk, Financial Early Warning System, Data Mining, CHAID Decision Tree Algorithm, SMEs.

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8690 Modeling and Analysis of a Cruise Control System

Authors: Anthony Spiteri Staines

Abstract:

This paper examines the modeling and analysis of a cruise control system using a Petri net based approach, task graphs, invariant analysis and behavioral properties. It shows how the structures used can be verified and optimized.

Keywords: Software Engineering, Real Time Analysis andDesign, Petri Nets, Task Graphs, Parallelism.

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8689 Landcover Mapping Using Lidar Data and Aerial Image and Soil Fertility Degradation Assessment for Rice Production Area in Quezon, Nueva Ecija, Philippines

Authors: Eliza. E. Camaso, Guiller. B. Damian, Miguelito. F. Isip, Ronaldo T. Alberto

Abstract:

Land-cover maps were important for many scientific, ecological and land management purposes and during the last decades, rapid decrease of soil fertility was observed to be due to land use practices such as rice cultivation. High-precision land-cover maps are not yet available in the area which is important in an economy management. To assure   accurate mapping of land cover to provide information, remote sensing is a very suitable tool to carry out this task and automatic land use and cover detection. The study did not only provide high precision land cover maps but it also provides estimates of rice production area that had undergone chemical degradation due to fertility decline. Land-cover were delineated and classified into pre-defined classes to achieve proper detection features. After generation of Land-cover map, of high intensity of rice cultivation, soil fertility degradation assessment in rice production area due to fertility decline was created to assess the impact of soils used in agricultural production. Using Simple spatial analysis functions and ArcGIS, the Land-cover map of Municipality of Quezon in Nueva Ecija, Philippines was overlaid to the fertility decline maps from Land Degradation Assessment Philippines- Bureau of Soils and Water Management (LADA-Philippines-BSWM) to determine the area of rice crops that were most likely where nitrogen, phosphorus, zinc and sulfur deficiencies were induced by high dosage of urea and imbalance N:P fertilization. The result found out that 80.00 % of fallow and 99.81% of rice production area has high soil fertility decline.

Keywords: Aerial image, land-cover, LiDAR, soil fertility degradation.

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