Medical Image Segmentation Using Deformable Model and Local Fitting Binary: Thoracic Aorta

This paper presents an application of level sets for the segmentation of abdominal and thoracic aortic aneurysms in CTA datasets. An important challenge in reliably detecting aortic is the need to overcome problems associated with intensity inhomogeneities. Level sets are part of an important class of methods that utilize partial differential equations (PDEs) and have been extensively applied in image segmentation. A kernel function in the level set formulation aids the suppression of noise in the extracted regions of interest and then guides the motion of the evolving contour for the detection of weak boundaries. The speed of curve evolution has been significantly improved with a resulting decrease in segmentation time compared with previous implementations of level sets, and are shown to be more effective than other approaches in coping with intensity inhomogeneities. We have applied the Courant Friedrichs Levy (CFL) condition as stability criterion for our algorithm.

Investigation of Effective Parameters on Annealing and Hot Spotting Processes for Straightening of Bent Turbine Rotors

The most severe damage of the turbine rotor is its distortion. The rotor straightening process must lead, at the first stage, to removal of the stresses from the material by annealing and next, to straightening of the plastic distortion without leaving any stress by hot spotting. The straightening method does not produce stress accumulations and the heating technique, developed specifically for solid forged rotors and disks, enables to avoid local overheating and structural changes in the material. This process also does not leave stresses in the shaft material. An experimental study of hot spotting is carried out on a large turbine rotor and some of the most important effective parameters that must be considered on annealing and hot spotting processes are investigated in this paper.

Adaptive Gaussian Mixture Model for Skin Color Segmentation

Skin color based tracking techniques often assume a static skin color model obtained either from an offline set of library images or the first few frames of a video stream. These models can show a weak performance in presence of changing lighting or imaging conditions. We propose an adaptive skin color model based on the Gaussian mixture model to handle the changing conditions. Initial estimation of the number and weights of skin color clusters are obtained using a modified form of the general Expectation maximization algorithm, The model adapts to changes in imaging conditions and refines the model parameters dynamically using spatial and temporal constraints. Experimental results show that the method can be used in effectively tracking of hand and face regions.

Heat transfer Characteristics of Fin-and-Tube heat Exchanger under Condensing Conditions

In the present work an investigation of the effects of the air frontal velocity, relative humidity and dry air temperature on the heat transfer characteristics of plain finned tube evaporator has been conducted. Using an appropriate correlation for the air side heat transfer coefficient the temperature distribution along the fin surface was calculated using a dimensionless temperature distribution. For a constant relative humidity and bulb temperature, it is found that the temperature distribution decreases with increasing air frontal velocity. Apparently, it is attributed to the condensate water film flowing over the fin surface. When dry air temperature and face velocity are being kept constant, the temperature distribution decreases with the increase of inlet relative humidity. An increase in the inlet relative humidity is accompanied by a higher amount of moisture on the fin surface. This results in a higher amount of latent heat transfer which involves higher fin surface temperature. For the influence of dry air temperature, the results here show an increase in the dimensionless temperature parameter with a decrease in bulb temperature. Increasing bulb temperature leads to higher amount of sensible and latent heat transfer when other conditions remain constant.

Bioconversion of Biodiesel Derived Crude Glycerol by Immobilized Clostridium pasteurianum: Effect of Temperature

Batch fermentation of 5, 10 and 25 g/L biodiesel derived crude glycerol was carried out at 30, 37 and 450C by Clostridium pasteurianum cells immobilized on silica. Maximum yield of 1,3-propanediol (PDO) (0.60 mol/mol), and ethanol (0.26 mol/mol) were obtained from 10 g/L crude glycerol at 30 and 370C respectively. Maximum yield of butanol (0.28 mol/mol substrate added) was obtained at 370C with 25 g/L substrate. None of the three products were detected at 45oC even after 10 days of fermentation. Only traces of ethanol (0.01 mol/mol) were detected at 450C with 5 g/L substrate. The results obtained for 25 g/L substrate utilization were fitted in first order rate equation to obtain the values of rate constant at three different temperatures for bioconversion of glycerol. First order rate constants for bioconversion of glycerol at 30, 37 and 45oC were found to be 0.198, 0.294 and 0.029/day respectively. Activation energy (Ea) for crude glycerol bioconversion was calculated to be 57.62 kcal/mol.

A New Damage Identification Strategy for SHM Based On FBGs and Bayesian Model Updating Method

One of the difficulties of the vibration-based damage identification methods is the nonuniqueness of the results of damage identification. The different damage locations and severity may cause the identical response signal, which is even more severe for detection of the multiple damage. This paper proposes a new strategy for damage detection to avoid this nonuniqueness. This strategy firstly determines the approximates damage area based on the statistical pattern recognition method using the dynamic strain signal measured by the distributed fiber Bragg grating, and then accurately evaluates the damage information based on the Bayesian model updating method using the experimental modal data. The stochastic simulation method is then used to compute the high-dimensional integral in the Bayesian problem. Finally, an experiment of the plate structure, simulating one part of mechanical structure, is used to verify the effectiveness of this approach.

Robot Map Building from Sonar and Laser Information using DSmT with Discounting Theory

In this paper, a new method of information fusion – DSmT (Dezert and Smarandache Theory) is introduced to apply to managing and dealing with the uncertain information from robot map building. Here we build grid map form sonar sensors and laser range finder (LRF). The uncertainty mainly comes from sonar sensors and LRF. Aiming to the uncertainty in static environment, we propose Classic DSm (DSmC) model for sonar sensors and laser range finder, and construct the general basic belief assignment function (gbbaf) respectively. Generally speaking, the evidence sources are unreliable in physical system, so we must consider the discounting theory before we apply DSmT. At last, Pioneer II mobile robot serves as a simulation experimental platform. We build 3D grid map of belief layout, then mainly compare the effect of building map using DSmT and DST. Through this simulation experiment, it proves that DSmT is very successful and valid, especially in dealing with highly conflicting information. In short, this study not only finds a new method for building map under static environment, but also supplies with a theory foundation for us to further apply Hybrid DSmT (DSmH) to dynamic unknown environment and multi-robots- building map together.

A Tool for Modeling Slope Instability Triggered by Piping

The paper deals with the analysis of triggering conditions and evolution processes of piping phenomena, in relation to both mechanical and hydraulic aspects. In particular, the aim of the study is to predict slope instabilities triggered by piping, analysing the conditions necessary for a flow failure to occur. Really, the mechanical effect involved in the loads redistribution around the pipe is coupled to the drainage process arising from higher permeability of the pipe. If after the pipe formation, the drainage goes prevented for pipe clogging, the porewater pressure increase can lead to the failure or even the liquefaction, with a subsequent flow slide. To simulate the piping evolution and to verify relevant stability conditions, a iterative coupled modelling approach has been pointed out. As example, the proposed tool has been applied to the Stava Valley disaster (July, 1985), demonstrating that piping might be one of triggering phenomena of the tailings dams collapse.

The Effects of Feeding Dried Fermented Cassava Peel on Milk Production and Composition of Etawah Crossedbred Goat

Twelve lactating Etawah Crossedbred goats were used in this study. Goat feed consisted of Cally andra callothyrsus, Pennisetum purpureum, wheat bran and dried fermented cassava peel. The cassava peels were fermented with a traditional culture called “ragi tape" (mixed culture of Saccharomyces cerevisae, Aspergillus sp, Candida, Hasnula and Acetobacter). The goats were divided into 2 groups (Control and Treated) of six does. The experimental diet of the Control group consisted of 70% of roughage (fresh Callyandra callothyrsus and Pennisetum purpureum 60:40) and 30% of wheat bran on dry matter (DM) base. In the Treated group 30% of wheat bran was replaced with dried fermented cassava peels. Data were statistically analyzed using analysis of variance followed SPSS program. The concentration of HCN in fermented cassava peel decreased to non toxic level. Nutrient composition of dried fermented cassava peel consisted of 85.75% dry matter; 5.80% crude protein and 82.51% total digestible nutrien (TDN). Substitution of 30% of wheat bran with dried fermented cassava peel in the diet had no effect on dry matter and organic matter intake but significantly (P< 0.05) decreased crude protein and TDN consumption as well as milk yields and milk composition. The study recommended to reduced the level of substitution to less than 30% of concentrates in the diet in order to avoid low nutrient intake and milk production of goats.

Finding Sparse Features in Face Detection Using Genetic Algorithms

Although Face detection is not a recent activity in the field of image processing, it is still an open area for research. The greatest step in this field is the work reported by Viola and its recent analogous is Huang et al. Both of them use similar features and also similar training process. The former is just for detecting upright faces, but the latter can detect multi-view faces in still grayscale images using new features called 'sparse feature'. Finding these features is very time consuming and inefficient by proposed methods. Here, we propose a new approach for finding sparse features using a genetic algorithm system. This method requires less computational cost and gets more effective features in learning process for face detection that causes more accuracy.

Unequal Error Protection of Facial Features for Personal ID Images Coding

This paper presents an approach for an unequal error protection of facial features of personal ID images coding. We consider unequal error protection (UEP) strategies for the efficient progressive transmission of embedded image codes over noisy channels. This new method is based on the progressive image compression embedded zerotree wavelet (EZW) algorithm and UEP technique with defined region of interest (ROI). In this case is ROI equal facial features within personal ID image. ROI technique is important in applications with different parts of importance. In ROI coding, a chosen ROI is encoded with higher quality than the background (BG). Unequal error protection of image is provided by different coding techniques and encoding LL band separately. In our proposed method, image is divided into two parts (ROI, BG) that consist of more important bytes (MIB) and less important bytes (LIB). The proposed unequal error protection of image transmission has shown to be more appropriate to low bit rate applications, producing better quality output for ROI of the compresses image. The experimental results verify effectiveness of the design. The results of our method demonstrate the comparison of the UEP of image transmission with defined ROI with facial features and the equal error protection (EEP) over additive white gaussian noise (AWGN) channel.

Hybrid Algorithm for Hammerstein System Identification Using Genetic Algorithm and Particle Swarm Optimization

This paper presents a method of model selection and identification of Hammerstein systems by hybridization of the genetic algorithm (GA) and particle swarm optimization (PSO). An unknown nonlinear static part to be estimated is approximately represented by an automatic choosing function (ACF) model. The weighting parameters of the ACF and the system parameters of the linear dynamic part are estimated by the linear least-squares method. On the other hand, the adjusting parameters of the ACF model structure are properly selected by the hybrid algorithm of the GA and PSO, where the Akaike information criterion is utilized as the evaluation value function. Simulation results are shown to demonstrate the effectiveness of the proposed hybrid algorithm.

Surveying the Environmental Biology Effects of Esfahan Factories on Zayandehrood Pollution

Water is the key of national development. Wherever a spring has been dried out or a river has changed its course, the area-s people have migrated and have been scattered and the area-s civilization has lost its brilliance. Today, air pollution, global warming and ozone layer damage are as the problems of countries, but certainly in the next decade the shortage and pollution of waters will be important issues of the world. The polluted waters are more dangerous in when they are used in agriculture. Because they infect plants and these plants are used in human and livestock consumption in food chain. With the increasing population growth and after that, the increase need to facilities and raw materials, human beings has started to do haste actions and wanted or unwanted destroyed his life basin. They try to overuse and capture his environment extremely, instead of having futurism approach in sustainable use of nature. This process includes Zayanderood recession, and caused its pollution after the transition from industrial and urban areas. Zayandehrood River in Isfahan is a vital artery of a living ecosystem. Now is the location of disposal waste water of many cities, villages and existing industries. The central area of the province is an important industrial place, and its environmental situation has reached a critical stage. Not only a large number of pollution-generating industries are active in the city limits, but outside of the city and adjacent districts Zayandehrood River, heavy industries like steel, Mobarakeh Steel and other tens great units pollute wild life. This article tries to study contaminant sources of Zayanderood and their severity, and determine and discuss the share of each of these resources by major industrial centers located in areas. At the end, we represent suitable strategy.

Between Policy Options and Technology Applications: Measuring the Sustainable Impacts on Distance Learning

This paper examines the interplay of policy options and cost-effective technology in providing sustainable distance education. A case study has been conducted among the learners and teachers. The emergence of learning technologies through CD, internet, and mobile is increasingly adopted by distance institutes for quick delivery and cost-effective factors. Their sustainability is conditioned by the structure of learners and well as the teaching community. The structure of learners in terms of rural and urban background revealed similarity in adoption and utilization of mobile learning. In other words, the technology transcended the rural-urban dichotomy. The teaching community was divided into two groups on policy issues. This study revealed both cost-effective as well as sustainability impacts on different learners groups divided by rural and urban location.

Delay Analysis of Sampled-Data Systems in Hard RTOS

In this paper, we have presented the effect of varying time-delays on performance and stability in the single-channel multirate sampled-data system in hard real-time (RT-Linux) environment. The sampling task require response time that might exceed the capacity of RT-Linux. So a straight implementation with RT-Linux is not feasible, because of the latency of the systems and hence, sampling period should be less to handle this task. The best sampling rate is chosen for the sampled-data system, which is the slowest rate meets all performance requirements. RT-Linux is consistent with its specifications and the resolution of the real-time is considered 0.01 seconds to achieve an efficient result. The test results of our laboratory experiment shows that the multi-rate control technique in hard real-time operating system (RTOS) can improve the stability problem caused by the random access delays and asynchronization.

The Effect of Pyridoxine and Different Levels of Nitrogen on Physiological Indices of Corn(Zea Mays L.var.sc704)

One field experiment was conducted on corn (Zea mays L.Var. SC 704) to study the effect of three different basic levels of nitrogen (90, 140and 190 Kg/ha as urea) with 0.01% and 0.02% pyridoxine pre-sowing seed soaking for 8 hours. Water-soaked seeds were treated as controled. biomass production was recorded on 45, 70 and 95 days after sowing. Total dry material (TDM), leaf area index (LAI), crop growth rate (CGR), relative growth rate (RGR) and net assimilation rate (NAR) was calculated form 45until 95 days after sowing. Yield and its components such as kernel yield, grain weight, biologic yield, harvest index and protein percentage was measured at harvest. In general, 0.02% pyridoxine and 190 Kg pure nitrogen/ha was shown gave maximum value for growth and yield parameters. N190 + 0.02 % pyridoxine enhanced seed yield and biologic yield by 57.15% and 62.98% compared to 90kg N and water – soaked treatment.

An Improved Illumination Normalization based on Anisotropic Smoothing for Face Recognition

Robust face recognition under various illumination environments is very difficult and needs to be accomplished for successful commercialization. In this paper, we propose an improved illumination normalization method for face recognition. Illumination normalization algorithm based on anisotropic smoothing is well known to be effective among illumination normalization methods but deteriorates the intensity contrast of the original image, and incurs less sharp edges. The proposed method in this paper improves the previous anisotropic smoothing-based illumination normalization method so that it increases the intensity contrast and enhances the edges while diminishing the effect of illumination variations. Due to the result of these improvements, face images preprocessed by the proposed illumination normalization method becomes to have more distinctive feature vectors (Gabor feature vectors) for face recognition. Through experiments of face recognition based on Gabor feature vector similarity, the effectiveness of the proposed illumination normalization method is verified.

Transient Stress Analysis on Medium Modules Spur Gear by Using Mode Super Position Technique

Natural frequencies and dynamic response of a spur gear sector are investigated using a two dimensional finite element model that offers significant advantages for dynamic gear analyses. The gear teeth are analyzed for different operating speeds. A primary feature of this modeling is determination of mesh forces using a detailed contact analysis for each time step as the gears roll through the mesh. ANSYS software has been used on the proposed model to find the natural frequencies by Block Lanczos technique and displacements and dynamic stresses by transient mode super position method. The effect of rotational speed of the gear on the dynamic response of gear tooth has been studied and design limits have been discussed.

Effects of Polymers and Alkaline on Recovery Improvement from Fractured Models

In this work, several ASP solutions were flooded into fractured models initially saturated with heavy oil at a constant flow rate and different geometrical characteristics of fracture. The ASP solutions are constituted from 2 polymers i.e. a synthetic polymer, hydrolyzed polyacrylamide as well as a biopolymer, a surfactant and 2types of alkaline. The results showed that using synthetic hydrolyzed polyacrylamide polymer increases ultimate oil recovery; however, type of alkaline does not play a significant rule on oil recovery. In addition, position of the injection well respect to the fracture system has remarkable effects on ASP flooding. For instance increasing angle of fractures with mean flow direction causes more oil recovery and delays breakthrough time. This work can be accounted as a comprehensive survey on ASP flooding which considers most of effective factors in this chemical EOR method.

Performance Evaluation of Improved Ball End Magnetorheological Finishing Process

A novel nanofinishing process using improved ball end magnetorheological (MR) finishing tool was developed for finishing of flat as well as 3D surfaces of ferromagnetic and non ferromagnetic workpieces. In this process a magnetically controlled ball end of smart MR polishing fluid is generated at the tip surface of the tool which is used as a finishing medium and it is guided to follow the surface to be finished through computer controlled 3-axes motion controller. The experiments were performed on ferromagnetic workpiece surface in the developed MR finishing setup to study the effect of finishing time on final surface roughness. The performance of present finishing process on final finished surface roughness was studied. The surface morphology was observed under scanning electron microscopy and atomic force microscope. The final surface finish was obtained as low as 19.7 nm from the initial surface roughness of 142.9 nm. The outcome of newly developed finishing process can be found useful in its applications in aerospace, automotive, dies and molds manufacturing industries, semiconductor and optics machining etc.