Automatic Classification of Initial Categories of Alzheimer's Disease from Structural MRI Phase Images: A Comparison of PSVM, KNN and ANN Methods

An early and accurate detection of Alzheimer's disease (AD) is an important stage in the treatment of individuals suffering from AD. We present an approach based on the use of structural magnetic resonance imaging (sMRI) phase images to distinguish between normal controls (NC), mild cognitive impairment (MCI) and AD patients with clinical dementia rating (CDR) of 1. Independent component analysis (ICA) technique is used for extracting useful features which form the inputs to the support vector machines (SVM), K nearest neighbour (kNN) and multilayer artificial neural network (ANN) classifiers to discriminate between the three classes. The obtained results are encouraging in terms of classification accuracy and effectively ascertain the usefulness of phase images for the classification of different stages of Alzheimer-s disease.

Automatic Microaneurysm Quantification for Diabetic Retinopathy Screening

Microaneurysm is a key indicator of diabetic retinopathy that can potentially cause damage to retina. Early detection and automatic quantification are the keys to prevent further damage. In this paper, which focuses on automatic microaneurysm detection in images acquired through non-dilated pupils, we present a series of experiments on feature selection and automatic microaneurysm pixel classification. We found that the best feature set is a combination of 10 features: the pixel-s intensity of shade corrected image, the pixel hue, the standard deviation of shade corrected image, DoG4, the area of the candidate MA, the perimeter of the candidate MA, the eccentricity of the candidate MA, the circularity of the candidate MA, the mean intensity of the candidate MA on shade corrected image and the ratio of the major axis length and minor length of the candidate MA. The overall sensitivity, specificity, precision, and accuracy are 84.82%, 99.99%, 89.01%, and 99.99%, respectively.

Numerical and Experimental Study of Flow from a Leaking Buried Pipe in an Unsaturated Porous Media

Considering the numerous applications of the study of the flow due to leakage in a buried pipe in unsaturated porous media, finding a proper model to explain the influence of the effective factors is of great importance.There are various important factors involved in this type of flow such as: pipe leakage size and location, burial depth, the degree of the saturation of the surrounding porous medium, characteristics of the porous medium, fluid type and pressure of the upstream.In this study, the flow through unsaturated porous media due to leakage of a buried pipe for up and down leakage location is studied experimentally and numerically and their results are compared. Study results show that Darcy equation together with BCM method (for calculating the relative permeability) have suitable ability for predicting the flow due to leakage of buried pipes in unsaturated porous media.

Physico-chemical Treatment of Tar-Containing Wastewater Generated from Biomass Gasification Plants

Treatment of tar-containing wastewater is necessary for the successful operation of biomass gasification plants (BGPs). In the present study, tar-containing wastewater was treated using lime and alum for the removal of in-organics, followed by adsorption on powdered activated carbon (PAC) for the removal of organics. Limealum experiments were performed in a jar apparatus and activated carbon studies were performed in an orbital shaker. At optimum concentrations, both lime and alum individually proved to be capable of removing color, total suspended solids (TSS) and total dissolved solids (TDS), but in both cases, pH adjustment had to be carried out after treatment. The combination of lime and alum at the dose ratio of 0.8:0.8 g/L was found to be optimum for the removal of inorganics. The removal efficiency achieved at optimum concentrations were 78.6, 62.0, 62.5 and 52.8% for color, alkalinity, TSS and TDS, respectively. The major advantages of the lime-alum combination were observed to be as follows: no requirement of pH adjustment before and after treatment and good settleability of sludge. Coagulation-precipitation followed by adsorption on PAC resulted in 92.3% chemical oxygen demand (COD) removal and 100% phenol removal at equilibrium. Ammonia removal efficiency was found to be 11.7% during coagulation-flocculation and 36.2% during adsorption on PAC. Adsorption of organics on PAC in terms of COD and phenol followed Freundlich isotherm with Kf = 0.55 & 18.47 mg/g and n = 1.01 & 1.45, respectively. This technology may prove to be one of the fastest and most techno-economically feasible methods for the treatment of tar-containing wastewater generated from BGPs.

Implementing Adaptive Steganography by Exploring the Ycbcr Color Model Characteristics

Stegnography is a new way of secret communication the most widely used mechanism on account of its simplicity is the use of the least significant bit. We have used the least significant bit (2 LSB and 4 LSB) substitution method. Depending upon the characteristics of the individual portions of cover image we decide whether to use 2 LSB or 4 LSB thus it is an adaptive stegnography technique. We used one of the three channels to behave as indicator to indicate the presence of hidden data in other two channels. The module showed impressive results in terms of capacity to hide the data. In proposed method, instead of using RGB color space directly, YCbCr color space is used to make use of human visual system characteristic.

Secret Communications Using Synchronized Sixth-Order Chuas's Circuits

In this paper, we use Generalized Hamiltonian systems approach to synchronize a modified sixth-order Chua's circuit, which generates hyperchaotic dynamics. Synchronization is obtained between the master and slave dynamics with the slave being given by an observer. We apply this approach to transmit private information (analog and binary), while the encoding remains potentially secure.

Application of a Novel Audio Compression Scheme in Automatic Music Recommendation, Digital Rights Management and Audio Fingerprinting

Rapid progress in audio compression technology has contributed to the explosive growth of music available in digital form today. In a reversal of ideas, this work makes use of a recently proposed efficient audio compression scheme to develop three important applications in the context of Music Information Retrieval (MIR) for the effective manipulation of large music databases, namely automatic music recommendation (AMR), digital rights management (DRM) and audio finger-printing for song identification. The performance of these three applications has been evaluated with respect to a database of songs collected from a diverse set of genres.

Dual-Response Approach to Work Stress: An Investigation of Stressors and Wellbeing Outcomes

This study sought to uncover the complex role of stress in the workplace by investigating both positive (eustress) and negative (distress) stress responses. In particular, the study tested a mediation model in which organisational stressors (person-job fit and role overload) influence employee affective wellbeing, both directly and indirectly through stress responses. Participants were recruited from retail and finance organisations in Australia and New Zealand, and asked to complete an anonymous online questionnaire. A total of 140 individuals returned completed questionnaires. The results show that person-job fit influenced eustress, which in turn had a positive effect on employee affective wellbeing; and role overload impacted distress, which in turn held a negative influence on affective wellbeing. These findings indicate that different organisational stressors have unique relationships with eustress and distress responses. Limitations and implications of the study are discussed.

Effectiveness of Cellular Phone with Active RFID Tag for Evacuation - The Case of Evacuation from the Underground Shopping Mall of Tenjin

The underground shopping mall has the constructional problem of the fire evacuation. Also, the people sometimes lose their direction and information of current time in the mall. If the emergencies such as terrorist explosions or gas explosions are happened, they have to go out soon. Under such circumstances, inside of the mall has high risk for life. In this research, the authors propose a way that he/she can go out from the underground shopping mall quickly. If the narrow exits are discovered by using active RFID (Radio Frequency Identification) tags and using cellular phones, they can evacuate as soon as possible. To verify this hypothesis, the authors design the model and carry out the agent-based simulation. They treat, as a case study, the Tenjin mall in Fukuoka Prefecture in Japan. The result of the simulation is that the case of the pedestrian with using active RFID tags and cellular phones reduced the amount of time to spend on the evacuation. Even if the diffusion of RFID tags and cellular phones was not perfect, they could show the effectiveness of reducing the time of evacuation.

Real-Coded Genetic Algorithm for Robust Power System Stabilizer Design

Power system stabilizers (PSS) are now routinely used in the industry to damp out power system oscillations. In this paper, real-coded genetic algorithm (RCGA) optimization technique is applied to design robust power system stabilizer for both singlemachine infinite-bus (SMIB) and multi-machine power system. The design problem of the proposed controller is formulated as an optimization problem and RCGA is employed to search for optimal controller parameters. By minimizing the time-domain based objective function, in which the deviation in the oscillatory rotor speed of the generator is involved; stability performance of the system is improved. The non-linear simulation results are presented under wide range of operating conditions; disturbances at different locations as well as for various fault clearing sequences to show the effectiveness and robustness of the proposed controller and their ability to provide efficient damping of low frequency oscillations.

Surface Defects Detection for Ceramic Tiles UsingImage Processing and Morphological Techniques

Quality control in ceramic tile manufacturing is hard, labor intensive and it is performed in a harsh industrial environment with noise, extreme temperature and humidity. It can be divided into color analysis, dimension verification, and surface defect detection, which is the main purpose of our work. Defects detection is still based on the judgment of human operators while most of the other manufacturing activities are automated so, our work is a quality control enhancement by integrating a visual control stage using image processing and morphological operation techniques before the packing operation to improve the homogeneity of batches received by final users.

Multiple-Points Fault Signature's Dynamics Modeling for Bearing Defect Frequencies

Occurrence of a multiple-points fault in machine operations could result in exhibiting complex fault signatures, which could result in lowering fault diagnosis accuracy. In this study, a multiple-points defect model (MPDM) is proposed which can simulate fault signature-s dynamics for n-points bearing faults. Furthermore, this study identifies that in case of multiple-points fault in the rotary machine, the location of the dominant component of defect frequency shifts depending upon the relative location of the fault points which could mislead the fault diagnostic model to inaccurate detections. Analytical and experimental results are presented to characterize and validate the variation in the dominant component of defect frequency. Based on envelop detection analysis, a modification is recommended in the existing fault diagnostic models to consider the multiples of defect frequency rather than only considering the frequency spectrum at the defect frequency in order to incorporate the impact of multiple points fault.

Numerical Analysis of Turbulent Natural Convection in a Square Cavity using Large- Eddy Simulation in Lattice Boltzmann Method

In this paper Lattice Boltzmann simulation of turbulent natural convection with large-eddy simulations (LES) in a square cavity which is filled by water has been investigated. The present results are validated by finds of other investigations which have been done with different numerical methods. Calculations were performed for high Rayleigh numbers of Ra=108 and 109. The results confirm that this method is in acceptable agreement with other verifications of such a flow. In this investigation is tried to present Large-eddy turbulence flow model by Lattice Boltzmann Method (LBM) with a clear and simple statement. Effects of increase in Rayleigh number are displayed on streamlines, isotherm counters and average Nusselt number. Result shows that the average Nusselt number enhances with growth of the Rayleigh numbers.

Design A Situated Learning Environment Using Mixed Reality Technology - A Case Study

Mixed Reality (MR) is one of the newest technologies explored in education. It promises the potential to promote teaching and learning and making learners- experience more “engaging". However, there still lack of research on designing a virtual learning environment using MR technology. In this paper, we describe the Mixed Reality technology, the characteristics of situated learning as instructional design for virtual environment using mixed reality technology. We also explain a case study that implemented those design and also the system overview.

Semantic Markup for Web Applications

In this paper we would like to introduce some of the best practices of using semantic markup and its significance in the success of web applications. Search engines are one of the best ways to reach potential customers and are some of the main indicators of web sites' fruitfulness. We will introduce the most important semantic vocabularies which are used by Google and Yahoo. Afterwards, we will explain the process of semantic markup implementation and its significance for search engines and other semantic markup consumers. We will describe techniques for slow conceiving RDFa markup to our web application for collecting Call for papers (CFP) announcements.

A Method under Uncertain Information for the Selection of Students in Interdisciplinary Studies

We present a method for the selection of students in interdisciplinary studies based on the hybrid averaging operator. We assume that the available information given in the problem is uncertain so it is necessary to use interval numbers. Therefore, we suggest a new type of hybrid aggregation called uncertain induced generalized hybrid averaging (UIGHA) operator. It is an aggregation operator that considers the weighted average (WA) and the ordered weighted averaging (OWA) operator in the same formulation. Therefore, we are able to consider the degree of optimism of the decision maker and grades of importance in the same approach. By using interval numbers, we are able to represent the information considering the best and worst possible results so the decision maker gets a more complete view of the decision problem. We develop an illustrative example of the proposed scheme in the selection of students in interdisciplinary studies. We see that with the use of the UIGHA operator we get a more complete representation of the selection problem. Then, the decision maker is able to consider a wide range of alternatives depending on his interests. We also show other potential applications that could be used by using the UIGHA operator in educational problems about selection of different types of resources such as students, professors, etc.

Design and Performance of Adaptive Polarized MIMO MC-SS-CDMA System for Downlink Mobile Communications

In this paper, an adaptive polarized Multiple-Input Multiple-Output (MIMO) Multicarrier Spread Spectrum Code Division Multiple Access (MC-SS-CDMA) system is designed for downlink mobile communications. The proposed system will be examined in Frequency Division Duplex (FDD) mode for both macro urban and suburban environments. For the same transmission bandwidth, a performance comparison between both nonoverlapped and orthogonal Frequency Division Multiplexing (FDM) schemes will be presented. Also, the proposed system will be compared with both the closed loop vertical MIMO MC-SS-CDMA system and the synchronous vertical STBC-MIMO MC-SS-CDMA system. As will be shown, the proposed system introduces a significant performance gain as well as reducing the spatial dimensions of the MIMO system and simplifying the receiver implementation. The effect of the polarization diversity characteristics on the BER performance will be discussed. Also, the impact of excluding the cross-polarization MCSS- CDMA blocks in the base station will be investigated. In addition, the system performance will be evaluated under different Feedback Information (FBI) rates for slowly-varying channels. Finally, a performance comparison for vehicular and pedestrian environments will be presented

A Constrained Clustering Algorithm for the Classification of Industrial Ores

In this paper a Pattern Recognition algorithm based on a constrained version of the k-means clustering algorithm will be presented. The proposed algorithm is a non parametric supervised statistical pattern recognition algorithm, i.e. it works under very mild assumptions on the dataset. The performance of the algorithm will be tested, togheter with a feature extraction technique that captures the information on the closed two-dimensional contour of an image, on images of industrial mineral ores.

A CFD Study of Sensitive Parameters Effect on the Combustion in a High Velocity Oxygen-Fuel Thermal Spray Gun

High-velocity oxygen fuel (HVOF) thermal spraying uses a combustion process to heat the gas flow and coating material. A computational fluid dynamics (CFD) model has been developed to predict gas dynamic behavior in a HVOF thermal spray gun in which premixed oxygen and propane are burnt in a combustion chamber linked to a parallel-sided nozzle. The CFD analysis is applied to investigate axisymmetric, steady-state, turbulent, compressible, chemically reacting, subsonic and supersonic flow inside and outside the gun. The gas velocity, temperature, pressure and Mach number distributions are presented for various locations inside and outside the gun. The calculated results show that the most sensitive parameters affecting the process are fuel-to-oxygen gas ratio and total gas flow rate. Gas dynamic behavior along the centerline of the gun depends on both total gas flow rate and fuel-to-oxygen gas ratio. The numerical simulations show that the axial gas velocity and Mach number distribution depend on both flow rate and ratio; the highest velocity is achieved at the higher flow rate and most fuel-rich ratio. In addition, the results reported in this paper illustrate that the numerical simulation can be one of the most powerful and beneficial tools for the HVOF system design, optimization and performance analysis.

Video-based Face Recognition: A Survey

During the past several years, face recognition in video has received significant attention. Not only the wide range of commercial and law enforcement applications, but also the availability of feasible technologies after several decades of research contributes to the trend. Although current face recognition systems have reached a certain level of maturity, their development is still limited by the conditions brought about by many real applications. For example, recognition images of video sequence acquired in an open environment with changes in illumination and/or pose and/or facial occlusion and/or low resolution of acquired image remains a largely unsolved problem. In other words, current algorithms are yet to be developed. This paper provides an up-to-date survey of video-based face recognition research. To present a comprehensive survey, we categorize existing video based recognition approaches and present detailed descriptions of representative methods within each category. In addition, relevant topics such as real time detection, real time tracking for video, issues such as illumination, pose, 3D and low resolution are covered.