Infrared Face Recognition Using Distance Transforms

In this work we present an efficient approach for face recognition in the infrared spectrum. In the proposed approach physiological features are extracted from thermal images in order to build a unique thermal faceprint. Then, a distance transform is used to get an invariant representation for face recognition. The obtained physiological features are related to the distribution of blood vessels under the face skin. This blood network is unique to each individual and can be used in infrared face recognition. The obtained results are promising and show the effectiveness of the proposed scheme.

A Fuzzy Time Series Forecasting Model for Multi-Variate Forecasting Analysis with Fuzzy C-Means Clustering

In this study, a fuzzy integrated logical forecasting method (FILF) is extended for multi-variate systems by using a vector autoregressive model. Fuzzy time series forecasting (FTSF) method was recently introduced by Song and Chissom [1]-[2] after that Chen improved the FTSF method. Rather than the existing literature, the proposed model is not only compared with the previous FTS models, but also with the conventional time series methods such as the classical vector autoregressive model. The cluster optimization is based on the C-means clustering method. An empirical study is performed for the prediction of the chartering rates of a group of dry bulk cargo ships. The root mean squared error (RMSE) metric is used for the comparing of results of methods and the proposed method has superiority than both traditional FTS methods and also the classical time series methods.

Information Security Risk in Financial Institutions

The history of technology and banking is examined as it relates to risk and technological determinism. It is proposed that the services that banks offer are determined by technology and that banks must adopt new technologies to be competitive. The adoption of technologies paradoxically forces the adoption of other new technologies to protect the bank from the increased risk of technology. This cycle will lead to bank examiners and regulators to focus on human behavior, not on the ever changing technology.

An Assessment of Technological Competencies on Professional Service Firms Business Performance

This study was initiated with a three prong objective. One, to identify the relationship between Technological Competencies factors (Technical Capability, Firm Innovativeness and E-Business Practices and professional service firms- business performance. To investigate the predictors of professional service firms business performance and finally to evaluate the predictors of business performance according to the type of professional service firms, a survey questionnaire was deployed to collect empirical data. The questionnaire was distributed to the owners of the professional small medium size enterprises services in the Accounting, Legal, Engineering and Architecture sectors. Analysis showed that all three Technology Competency factors have moderate effect on business performance. In addition, the regression models indicate that technical capability is the most highly influential that could determine business performance, followed by e-business practices and firm innovativeness. Subsequently, the main predictor of business performance for all types of firms is Technical capability.

Characteristics of Hemodynamics in a Bileaflet Mechanical Heart Valve using an Implicit FSI Method

Human heart valves diseased by congenital heart defects, rheumatic fever, bacterial infection, cancer may cause stenosis or insufficiency in the valves. Treatment may be with medication but often involves valve repair or replacement (insertion of an artificial heart valve). Bileaflet mechanical heart valves (BMHVs) are widely implanted to replace the diseased heart valves, but still suffer from complications such as hemolysis, platelet activation, tissue overgrowth and device failure. These complications are closely related to both flow characteristics through the valves and leaflet dynamics. In this study, the physiological flow interacting with the moving leaflets in a bileaflet mechanical heart valve (BMHV) is simulated with a strongly coupled implicit fluid-structure interaction (FSI) method which is newly organized based on the Arbitrary-Lagrangian-Eulerian (ALE) approach and the dynamic mesh method (remeshing) of FLUENT. The simulated results are in good agreement with previous experimental studies. This study shows the applicability of the present FSI model to the complicated physics interacting between fluid flow and moving boundary.

Hybrid Neural Network Methods for Lithology Identification in the Algerian Sahara

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.

Multistage Condition Monitoring System of Aircraft Gas Turbine Engine

Researches show that probability-statistical methods application, especially at the early stage of the aviation Gas Turbine Engine (GTE) technical condition diagnosing, when the flight information has property of the fuzzy, limitation and uncertainty is unfounded. Hence the efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the Fuzzy Logic and Neural Networks methods is considered. According to the purpose of this problem training with high accuracy of fuzzy multiple linear and non-linear models (fuzzy regression equations) which received on the statistical fuzzy data basis is made. For GTE technical condition more adequate model making dynamics of skewness and kurtosis coefficients- changes are analysed. Researches of skewness and kurtosis coefficients values- changes show that, distributions of GTE work parameters have fuzzy character. Hence consideration of fuzzy skewness and kurtosis coefficients is expedient. Investigation of the basic characteristics changes- dynamics of GTE work parameters allows drawing conclusion on necessity of the Fuzzy Statistical Analysis at preliminary identification of the engines' technical condition. Researches of correlation coefficients values- changes shows also on their fuzzy character. Therefore for models choice the application of the Fuzzy Correlation Analysis results is offered. At the information sufficiency is offered to use recurrent algorithm of aviation GTE technical condition identification (Hard Computing technology is used) on measurements of input and output parameters of the multiple linear and non-linear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The developed GTE condition monitoring system provides stageby- stage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine technical condition was made.

Autonomous Virtual Agent Navigation in Virtual Environments

This paper presents a solution for the behavioural animation of autonomous virtual agent navigation in virtual environments. We focus on using Dempster-Shafer-s Theory of Evidence in developing visual sensor for virtual agent. The role of the visual sensor is to capture the information about the virtual environment or identifie which part of an obstacle can be seen from the position of the virtual agent. This information is require for vitual agent to coordinate navigation in virtual environment. The virual agent uses fuzzy controller as a navigation system and Fuzzy α - level for the action selection method. The result clearly demonstrates the path produced is reasonably smooth even though there is some sharp turn and also still not diverted too far from the potential shortest path. This had indicated the benefit of our method, where more reliable and accurate paths produced during navigation task.

Diagnosing Dangerous Arrhythmia of Patients by Automatic Detecting of QRS Complexes in ECG

In this paper, an automatic detecting algorithm for QRS complex detecting was applied for analyzing ECG recordings and five criteria for dangerous arrhythmia diagnosing are applied for a protocol type of automatic arrhythmia diagnosing system. The automatic detecting algorithm applied in this paper detected the distribution of QRS complexes in ECG recordings and related information, such as heart rate and RR interval. In this investigation, twenty sampled ECG recordings of patients with different pathologic conditions were collected for off-line analysis. A combinative application of four digital filters for bettering ECG signals and promoting detecting rate for QRS complex was proposed as pre-processing. Both of hardware filters and digital filters were applied to eliminate different types of noises mixed with ECG recordings. Then, an automatic detecting algorithm of QRS complex was applied for verifying the distribution of QRS complex. Finally, the quantitative clinic criteria for diagnosing arrhythmia were programmed in a practical application for automatic arrhythmia diagnosing as a post-processor. The results of diagnoses by automatic dangerous arrhythmia diagnosing were compared with the results of off-line diagnoses by experienced clinic physicians. The results of comparison showed the application of automatic dangerous arrhythmia diagnosis performed a matching rate of 95% compared with an experienced physician-s diagnoses.

Application of Adaptive Neuro-Fuzzy Inference System in Smoothing Transition Autoregressive Models

In this paper we propose and examine an Adaptive Neuro-Fuzzy Inference System (ANFIS) in Smoothing Transition Autoregressive (STAR) modeling. Because STAR models follow fuzzy logic approach, in the non-linear part fuzzy rules can be incorporated or other training or computational methods can be applied as the error backpropagation algorithm instead to nonlinear squares. Furthermore, additional fuzzy membership functions can be examined, beside the logistic and exponential, like the triangle, Gaussian and Generalized Bell functions among others. We examine two macroeconomic variables of US economy, the inflation rate and the 6-monthly treasury bills interest rates.

On Enhancing Robustness of an Evolutionary Fuzzy Tracking Controller

This paper presents three-phase evolution search methodology to automatically design fuzzy logic controllers (FLCs) that can work in a wide range of operating conditions. These include varying load, parameter variations, and unknown external disturbances. The three-phase scheme consists of an exploration phase, an exploitation phase and a robustness phase. The first two phases search for FLC with high accuracy performances while the last phase aims at obtaining FLC providing the best compromise between the accuracy and robustness performances. Simulations were performed for direct-drive two-axis robot arm. The evolved FLC with the proposed design technique found to provide a very satisfactory performance under the wide range of operation conditions and to overcome problem associated with coupling and nonlinearities characteristics inherent to robot arms.

Synchronization of Chaos in a Food Web in Ecological Systems

The three-species food web model proposed and investigated by Gakkhar and Naji is known to have chaotic behaviour for a choice of parameters. An attempt has been made to synchronize the chaos in the model using bidirectional coupling. Numerical simulations are presented to demonstrate the effectiveness and feasibility of the analytical results. Numerical results show that for higher value of coupling strength, chaotic synchronization is achieved. Chaos can be controlled to achieve stable synchronization in natural systems.

Fuzzy PID based PSS Design Using Genetic Algorithm

This paper presents PSS (Power system stabilizer) design based on optimal fuzzy PID (OFPID). OFPID based PSS design is considered for single-machine power systems. The main motivation for this design is to stabilize or to control low-frequency oscillation on power systems. Firstly, describing the linear PID control then to combine this PID control with fuzzy logic control mechanism. Finally, Fuzzy PID parameters (Kp. Kd, KI, Kupd, Kui) are tuned by Genetic Algorthm (GA) to reach optimal global stability. The effectiveness of the proposed PSS in increasing the damping of system electromechanical oscillation is demonstrated in a one-machine-infinite-bus system

Sliding Joints and Soil-Structure Interaction

Use of a sliding joint is an effective method to decrease the stress in foundation structure where there is a horizontal deformation of subsoil (areas afflicted with underground mining) or horizontal deformation of a foundation structure (pre-stressed foundations, creep, shrinkage, temperature deformation). A convenient material for a sliding joint is a bitumen asphalt belt. Experiments for different types of bitumen belts were undertaken at the Faculty of Civil Engineering - VSB Technical University of Ostrava in 2008. This year an extension of the 2008 experiments is in progress and the shear resistance of a slide joint is being tested as a function of temperature in a temperature controlled room. In this paper experimental results of temperature dependant shear resistance are presented. The result of the experiments should be the sliding joint shear resistance as a function of deformation velocity and temperature. This relationship is used for numerical analysis of stress/strain relation between foundation structure and subsoil. Using a rheological slide joint could lead to a decrease of the reinforcement amount, and contribute to higher reliability of foundation structure and thus enable design of more durable and sustainable building structures.

Roundness Deviation Measuring Strategy at Coordination Measuring Machines and Conventional Machines

Today technological process makes possible surface control of producing parts which is needful for product quality guarantee. Geometrical structure of part surface includes form, proportion, accuracy to shape, accuracy to size, alignment and surface topography (roughness, waviness, etc.). All these parameters are dependence at technology, production machine parameters, material properties, but also at human, etc. Every parameters approves at total part accuracy, it is means at accuracy to shape. One of the most important accuracy to shape element is roundness. This paper will be deals by comparison of roughness deviations at coordination measuring machines and at special single purpose machines. Will describing measuring by discreet method (discontinuous) and scanning method (continuous) at coordination measuring machines and confrontation with reference method using at single purpose machines.

Determination of Electromagnetic Properties of Human Tissues

In this paper a computer system for electromagnetic properties measurements is designed. The system employs Agilent 4294A precision impedance analyzer to measure the amplitude and the phase of a signal applied over a tested biological tissue sample. Measured by the developed computer system data could be used for tissue characterization in wide frequency range from 40Hz to 110MHz. The computer system can interface with output devices acquiring flexible testing process.

Massive Lesions Classification using Features based on Morphological Lesion Differences

Purpose of this work is the development of an automatic classification system which could be useful for radiologists in the investigation of breast cancer. The software has been designed in the framework of the MAGIC-5 collaboration. In the automatic classification system the suspicious regions with high probability to include a lesion are extracted from the image as regions of interest (ROIs). Each ROI is characterized by some features based on morphological lesion differences. Some classifiers as a Feed Forward Neural Network, a K-Nearest Neighbours and a Support Vector Machine are used to distinguish the pathological records from the healthy ones. The results obtained in terms of sensitivity (percentage of pathological ROIs correctly classified) and specificity (percentage of non-pathological ROIs correctly classified) will be presented through the Receive Operating Characteristic curve (ROC). In particular the best performances are 88% ± 1 of area under ROC curve obtained with the Feed Forward Neural Network.

Physiological and Biochemical Responses to Drought Stress of Chickpea Genotypes

The experimental design was 4 x 5 factorial with three replications in fully controlled research greenhouse in Department of Soil Sciences and Plant Nutrition, Faculty of Agriculture, University of Selcuk in the year of 2009. Determination of tolerant chickpea genotypes to drought was made in the research. Additionally, sophisticated effects of drought on plant growth and development, biochemical and physical properties or physical defense mechanisms were presented. According to the results, the primary genotypes were Ilgın YP (0.0063 g/gh) for leaf water capacity, 22235 70.44(%) for relative water content, 22159 (82.47%) for real water content, 22159 (5.03 mg/l) for chlorophyll a+b, Ilgın YP (125.89 nmol H2O2.dak-1/ mg protein-1) for peroxidase, Yunak YP (769.67 unit/ mg protein-1) for superoxide dismutase, Seydişehir YP (16.74 μg.TA-1) for proline, Gökçe (80.01 nmol H2O2.dak-1/ mg protein-1) for catalase. Consequently, all the genotypes increased their enzyme activity depending on the increasing of drought stress consider with the effects of drought stress on leaf enzyme activity. Chickpea genotypes are increasing enzyme activity against to drought stress.

Rule-Based Message Passing for Collaborative Application in Distributed Environments

In this paper, we describe a rule-based message passing method to support developing collaborative applications, in which multiple users share resources in distributed environments. Message communications of applications in collaborative environments tend to be very complex because of the necessity to manage context situations such as sharing events, access controlling of users, and network places. In this paper, we propose a message communications method based on unification of artificial intelligence and logic programming for defining rules of such context information in a procedural object-oriented programming language. We also present an implementation of the method as java classes.

An Evaluation of Digital Elevation Models to Short-Term Monitoring of a High Energy Barrier Island, Northeast Brazil

The morphological short-term evolution of Ponta do Tubarão Island (PTI) was investigated through high accurate surveys based on post-processed kinematic (PPK) relative positioning on Global Navigation Satellite Systems (GNSS). PTI is part of a barrier island system on a high energy northeast Brazilian coastal environment and also an area of high environmental sensitivity. Surveys were carried out quarterly over a two years period from May 2010 to May 2012. This paper assesses statically the performance of digital elevation models (DEM) derived from different interpolation methods to represent morphologic features and to quantify volumetric changes and TIN models shown the best results to that purposes. The MDE allowed quantifying surfaces and volumes in detail as well as identifying the most vulnerable segments of the PTI to erosion and/or accumulation of sediments and relate the alterations to climate conditions. The coastal setting and geometry of PTI protects a significant mangrove ecosystem and some oil and gas facilities installed in the vicinities from damaging effects of strong oceanwaves and currents. Thus, the maintenance of PTI is extremely required but the prediction of its longevity is uncertain because results indicate an irregularity of sedimentary balance and a substantial decline in sediment supply to this coastal area.