Face Localization Using Illumination-dependent Face Model for Visual Speech Recognition

A robust still image face localization algorithm capable of operating in an unconstrained visual environment is proposed. First, construction of a robust skin classifier within a shifted HSV color space is described. Then various filtering operations are performed to better isolate face candidates and mitigate the effect of substantial non-skin regions. Finally, a novel Bhattacharyya-based face detection algorithm is used to compare candidate regions of interest with a unique illumination-dependent face model probability distribution function approximation. Experimental results show a 90% face detection success rate despite the demands of the visually noisy environment.

Subpixel Detection of Circular Objects Using Geometric Property

In this paper, we propose a method for detecting circular shapes with subpixel accuracy. First, the geometric properties of circles have been used to find the diameters as well as the circumference pixels. The center and radius are then estimated by the circumference pixels. Both synthetic and real images have been tested by the proposed method. The experimental results show that the new method is efficient.

Designing of Multi-Agent Rescue Robot: Development and Basic Experiments of Master-Slave Type Rescue Robots

A multi-agent type robot for disaster response in calamity scene is proposed in this paper. The proposed grouped rescue robots can perform cooperative reconnaissance and surveillance to achieve a given rescue mission. The multi-agent rescue of dual set robot consists of one master set and three slave units. The research for this rescue robot system is going to detect at harmful environment where human is unreachable, such as the building is infected with virus or the factory has hazardous liquid in effluent. As a dual set robot, with Bluetooth and communication network, the master set can connect with slave units and send information back to computer by wireless and monitor. Therefore, rescuer can be informed the real-time information in a calamity area. Furthermore, each slave robot is able to obstacle avoidance by ultrasonic sensors, and encodes distance and location by compass. The master robot can integrate every devices information to increase the efficiency of prospected and research unknown area.

Study on Nitrite Accumulation Characteristics and Nitrifying Population Dynamics at Different Growth Environments

Novel nitrogen removal technologies via nitrite pathway attract increasing interest in recent years. In this study, batch experiments were performed to investigate nitrite accumulation characteristics and shifts in nitrifying community structure at different growth environments including ammonia concentration, pH and alkalinity. It was found that nitrite accumulation ratios were maintained at around 95% at studied conditions, and the optimum pH and Alk/N (ratio between alkalinity and nitrogen) for ammonium oxidization were 8.5 and 8.33, respectively. Fluorescence in situ hybridization analysis of nitrifying bacteria showed that high free ammonia (from influent ammonium or caused by high pH) significantly altered the structure of nitrifying community, leading to abundance of ammonia-oxidizing bacteria (AOB), especially Nitrososmonas, and inhibition of nitrite-oxidizing bacteria (NOB). The results suggest that free ammonia plays more important role than other studied conditions on nitrite accumulation.

Microscopic Analysis of Welded Dental Alloys

Microplasma welding is a less expensive alternative to laser welding in dental technology. The aim of the study was to highlight discontinuities present in the microplasma welded joints of dental base metal alloys by visual analysis. Five base metal alloys designated for fixed prostheses manufacture were selected for the experiments. Using these plates, preliminary tests were conducted by microplasma welding in butt joint configuration, without filler material, bilaterally and with filler material, proper for each base metal. Macroscopic visual inspection was performed to assess carefully the irregularities in the welds. Electron microscopy allowed detection of discontinuities that are not visible to the eye and revealing details regarding location, trajectory, morphology and size of discontinuities. Supplementing visual control with microscopic analysis allows to detect small discontinuities, which escapes the macroscopic control and to make a detailed study of the weld.

Performance and Emission Study of Linseed Oilas a Fuel for CI Engine

Increased energy demand and the concern about environment friendly technology, renewable bio-fuels are better alternative to petroleum products. In the present study linseed oil was used as alternative source for diesel engine fuel and the results were compared with baseline data of neat diesel. Performance parameters such as brake thermal efficiency (BTE) and brake specific fuel consumption (BSFC) and emissions parameters such as CO, unburned hydro carbon (UBHC), NOx, CO2 and exhaust temperature were compared. BTE of the engine was lower and BSFC was higher when the engine was fueled with Linseed oil compared to diesel fuel. Emission characteristics are better than diesel fuel. NOx formation by using linseed oil during the experiment was lower than diesel fuel. Linseed oil is non edible oil, so it can be used as an extender of diesel fuel energy source for small and medium energy needs.

ZMP Based Reference Generation for Biped Walking Robots

Recent fifteen years witnessed fast improvements in the field of humanoid robotics. The human-like robot structure is more suitable to human environment with its supreme obstacle avoidance properties when compared with wheeled service robots. However, the walking control for bipedal robots is a challenging task due to their complex dynamics. Stable reference generation plays a very important role in control. Linear Inverted Pendulum Model (LIPM) and the Zero Moment Point (ZMP) criterion are applied in a number of studies for stable walking reference generation of biped walking robots. This paper follows this main approach too. We propose a natural and continuous ZMP reference trajectory for a stable and human-like walk. The ZMP reference trajectories move forward under the sole of the support foot when the robot body is supported by a single leg. Robot center of mass trajectory is obtained from predefined ZMP reference trajectories by a Fourier series approximation method. The Gibbs phenomenon problem common with Fourier approximations of discontinuous functions is avoided by employing continuous ZMP references. Also, these ZMP reference trajectories possess pre-assigned single and double support phases, which are very useful in experimental tuning work. The ZMP based reference generation strategy is tested via threedimensional full-dynamics simulations of a 12-degrees-of-freedom biped robot model. Simulation results indicate that the proposed reference trajectory generation technique is successful.

Study of Water Relations, Chlorophyll and their Correlations with Grain Yield in Wheat(Triticum aestivum L.) Genotypes

The objective of this experiment was to study of water relations and chlorophyll in different wheat genotypes and their correlations with grain and biological yields. 21 genotypes of bread wheat were compared in a field experiment as randomized complete blocks design with four replications. The results showed that relative water deficit, relative water loss, excised leaf water retention, cell membrane stability, chlorophyll-a, chlorophyll-b, total chlorophyll, grain yield and biological yield were different significantly among wheat genotypes, but SPAD-chlorophyll index, relative water content and chlorophyll florescence were not. Significant correlations were not observed among above mentioned water relations and chlorophyll characteristics with grain yield, but there was a positive and significant correlation between biological yield and grain yield.

An Experimental Study of a Self-Supervised Classifier Ensemble

Learning using labeled and unlabelled data has received considerable amount of attention in the machine learning community due its potential in reducing the need for expensive labeled data. In this work we present a new method for combining labeled and unlabeled data based on classifier ensembles. The model we propose assumes each classifier in the ensemble observes the input using different set of features. Classifiers are initially trained using some labeled samples. The trained classifiers learn further through labeling the unknown patterns using a teaching signals that is generated using the decision of the classifier ensemble, i.e. the classifiers self-supervise each other. Experiments on a set of object images are presented. Our experiments investigate different classifier models, different fusing techniques, different training sizes and different input features. Experimental results reveal that the proposed self-supervised ensemble learning approach reduces classification error over the single classifier and the traditional ensemble classifier approachs.

Improving Water Productivity of Chickpea by the Use of Deficit Irrigation with Treated Domestic Wastewater

An experiment was performed in the south of Morocco in order to evaluate the effect of deficit irrigation by treated wastewater on chickpea production. We applied six irrigation treatments on a local variety of chickpea by supplying alternatively 50 or 100% of ETm in a completely randomized design. We found a highly significant difference between treatments in terms of biomass production. Drought stress during the vegetative period showed highest yield with 6.5 t/ha which was more than the yield obtained for the control (4.9 t/ha). The optimal crop stage in which deficit irrigation can be applied is the vegetative growth stage, as the crop has a chance to develop its root system, to be able to cover the plant needs for water and nutrient supply during the rest of cycle, and non stress conditions during the flowering and seed filling stages allow the plant to optimize its photosynthesis and carbon translocation, therefore increase its productivity.

Data Placement in Heterogeneous Storage of Short Videos

The overall service performance of I/O intensive system depends mainly on workload on its storage system. In heterogeneous storage environment where storage elements from different vendors with different capacity and performance are put together, workload should be distributed according to storage capability. This paper addresses data placement issue in short video sharing website. Workload contributed by a video is estimated by the number of views and life time span of existing videos in same category. Experiment was conducted on 42,000 video titles in six weeks. Result showed that the proposed algorithm distributed workload and maintained balance better than round robin and random algorithms.

Microwave Dehydration Behavior of Admontite Mineral at 360W

Dehydration behavior gives a hint about thermal properties of materials. It is important for the usage areas and transportation of minerals. Magnesium borates can be used as additive materials in areas such as in the production of superconducting materials, in the composition of detergents, due to the content of boron in the friction-reducing additives in oils and insulating coating compositions due to their good mechanic and thermal properties. In this study, thermal dehydration behavior of admontite (MgO(B2O3)3.7(H2O)), which is a kind of magnesium borate mineral, is experimented by microwave energy at 360W. Structure of admontite is suitable for the investigation of dehydration behavior by microwave because of its seven moles of crystal water. It is seen that admontite lost its 28.7% of weight at the end of the 120 minutes heating in microwave furnace. 

Comparison of Proportional Control and Fuzzy Logic Control to Develop an Ideal Thermoelectric Renal Hypothermia System

In this study, a comparison of two control methods, Proportional Control (PC) and Fuzzy Logic Control (FLC), which have been used to develop an ideal thermoelectric renal hypothermia system in order to use in renal surgery, has been carried out. Since the most important issues in long-lasting parenchymatous renal surgery are to provide an operation medium free of blood and to prevent renal dysfunction in the postoperative period, control of the temperature has become very important in renal surgery. The final product is seriously affected from the changes in temperature, therefore, it is necessary to reach some desired temperature points quickly and avoid large overshoot. PIC16F877 microcontroller has been used as controller for both of these two methods. Each control method can simply ensure extra renal hypothermia in the targeted way. But investigation of advantages and disadvantages of every control method to each other is aimed and carried out by the experimental implementations. Shortly, investigation of the most appropriate method to use for development of system and that can be applied to people safely in the future, has been performed. In this sense, experimental results show that fuzzy logic control gives out more reliable responses and efficient performance.

Mechanism of Damping in Welded Structures using Finite Element Approach

The characterization and modeling of the dynamic behavior of many built-up structures under vibration conditions is still a subject of current research. The present study emphasizes the theoretical investigation of slip damping in layered and jointed welded cantilever structures using finite element approach. Application of finite element method in damping analysis is relatively recent, as such, some problems particularly slip damping analysis has not received enough attention. To validate the finite element model developed, experiments have been conducted on a number of mild steel specimens under different initial conditions of vibration. Finite element model developed affirms that the damping capacity of such structures is influenced by a number of vital parameters such as; pressure distribution, kinematic coefficient of friction and micro-slip at the interfaces, amplitude, frequency of vibration, length and thickness of the specimen. Finite element model developed can be utilized effectively in the design of machine tools, automobiles, aerodynamic and space structures, frames and machine members for enhancing their damping capacity.

On the Characteristics of Liquid Explosive Dispersing Flow

In this paper, some experiments of liquid dispersion flow driven by explosion in vertical plane were carried out using a liquid explosive dispersion device with film cylindrical constraints. The separated time series describing the breakup shape and dispersion process of liquid were recorded with high speed CMOS camera. The experimental results were analyzed and some essential characteristics of liquid dispersing flow are presented.

Global Kinetics of Direct Dimethyl Ether Synthesis Process from Syngas in Slurry Reactor over a Novel Cu-Zn-Al-Zr Slurry Catalyst

The direct synthesis process of dimethyl ether (DME) from syngas in slurry reactors is considered to be promising because of its advantages in caloric transfer. In this paper, the influences of operating conditions (temperature, pressure and weight hourly space velocity) on the conversion of CO, selectivity of DME and methanol were studied in a stirred autoclave over Cu-Zn-Al-Zr slurry catalyst, which is far more suitable to liquid phase dimethyl ether synthesis process than bifunctional catalyst commercially. A Langmuir- Hinshelwood mechanism type global kinetics model for liquid phase DME direct synthesis based on methanol synthesis models and a methanol dehydration model has been investigated by fitting our experimental data. The model parameters were estimated with MATLAB program based on general Genetic Algorithms and Levenberg-Marquardt method, which is suitably fitting experimental data and its reliability was verified by statistical test and residual error analysis.

Slugging Frequency Correlation for Inclined Gas-liquid Flow

In this work, new experimental data for slugging frequency in inclined gas-liquid flow are reported, and a new correlation is proposed. Scale experiments were carried out using a mixture of air and water in a 6 m long pipe. Two different pipe diameters were used, namely, 38 and 67 mm. The data were taken with capacitance type sensors at a data acquisition frequency of 200 Hz over an interval of 60 seconds. For the range of flow conditions studied, the liquid superficial velocity is observed to influence the frequency strongly. A comparison of the present data with correlations available in the literature reveals a lack of agreement. A new correlation for slug frequency has been proposed for the inclined flow, which represents the main contribution of this work.

Effect of Utilization of Organic and Inorganic Nitrogen Source on the Potato Shoots Dry Matter, Leaf Area Index and Plant Height, During Middle Stage of Growth

Cattle manure and mineral fertilizers are two source of Nitrogen, which can affect the growth and quantity of potato. In this research the effects of the use of cattle manure (5, 10, 15 and 20 ton ha-1), Nitrogen fertilizer (50, 100 and 150 kg N ha-1) and their interaction on potato growth were evaluated during field experiments in 2008 with the help of Randomized Complete Block (RCB) with the factorial arrangement of three experimental replications in Iran. At the 75 th day after emergence, dry weight of Shoots, leaf area index (LAI) and plant height were recorded. Results showed that, dry weight of Shoots, LAI and plant height increased linearly and very significantly in response to the application of manure and Nitrogen fertilizer. While the interaction between manure and Nitrogen fertilizer just on the LAI and plant height was significant, somehow the maximum amount of plant height( 73 cm) was obtained by using 150 kg Nitrogen + 15 tons of manure per hectare, and maximum LAI ( 5.36) was obtained by using 150 kg Nitrogen + 20 tons of manure per hectare. Also in this experiment maximum tuber yield (36.8 tons ha-1) was obtained by the utilization of 150 kg Nitrogen per hectare + 20 tons manure.

Analysis and Classification of Hiv-1 Sub- Type Viruses by AR Model through Artificial Neural Networks

HIV-1 genome is highly heterogeneous. Due to this variation, features of HIV-I genome is in a wide range. For this reason, the ability to infection of the virus changes depending on different chemokine receptors. From this point of view, R5 HIV viruses use CCR5 coreceptor while X4 viruses use CXCR5 and R5X4 viruses can utilize both coreceptors. Recently, in Bioinformatics, R5X4 viruses have been studied to classify by using the experiments on HIV-1 genome. In this study, R5X4 type of HIV viruses were classified using Auto Regressive (AR) model through Artificial Neural Networks (ANNs). The statistical data of R5X4, R5 and X4 viruses was analyzed by using signal processing methods and ANNs. Accessible residues of these virus sequences were obtained and modeled by AR model since the dimension of residues is large and different from each other. Finally the pre-processed data was used to evolve various ANN structures for determining R5X4 viruses. Furthermore ROC analysis was applied to ANNs to show their real performances. The results indicate that R5X4 viruses successfully classified with high sensitivity and specificity values training and testing ROC analysis for RBF, which gives the best performance among ANN structures.

Low-Cost and Highly Accurate Motion Models for Three-Dimensional Local Landmark-based Autonomous Navigation

Recently, the Spherical Motion Models (SMM-s) have been introduced [1]. These new models have been developed for 3D local landmark-base Autonomous Navigation (AN). This paper is revealing new arguments and experimental results to support the SMM-s characteristics. The accuracy and the robustness in performing a specific task are the main concerns of the new investigations. To analyze their performances of the SMM-s, the most powerful tools of estimation theory, the extended Kalman filter (EKF) and unscented Kalman filter (UKF), which give the best estimations in noisy environments, have been employed. The Monte Carlo validation implementations used to test the stability and robustness of the models have been employed as well.