Capturing an Unknown Moving Target in Unknown Territory using Vision and Coordination

In this paper we present an extension to Vision Based LRTA* (VLRTA*) known as Vision Based Moving Target Search (VMTS) for capturing unknown moving target in unknown territory with randomly generated obstacles. Target position is unknown to the agents and they cannot predict its position using any probability method. Agents have omni directional vision but can see in one direction at some point in time. Agent-s vision will be blocked by the obstacles in the search space so agent can not see through the obstacles. Proposed algorithm is evaluated on large number of scenarios. Scenarios include grids of sizes from 10x10 to 100x100. Grids had obstacles randomly placed, occupying 0% to 50%, in increments of 10%, of the search space. Experiments used 2 to 9 agents for each randomly generated maze with same obstacle ratio. Observed results suggests that VMTS is effective in locate target time, solution quality and virtual target. In addition, VMTS becomes more efficient if the number of agents is increased with proportion to obstacle ratio.

Beam Orientation Optimization Using Ant Colony Optimization in Intensity Modulated Radiation Therapy

In intensity modulated radiation therapy (IMRT) treatment planning, beam angles are usually preselected on the basis of experience and intuition. Therefore, getting an appropriate beam configuration needs a very long time. Based on the present situation, the paper puts forward beam orientation optimization using ant colony optimization (ACO). We use ant colony optimization to select the beam configurations, after getting the beam configuration using Conjugate Gradient (CG) algorithm to optimize the intensity profiles. Combining with the information of the effect of pencil beam, we can get the global optimal solution accelerating. In order to verify the feasibility of the presented method, a simulated and clinical case was tested, compared with dose-volume histogram and isodose line between target area and organ at risk. The results showed that the effect was improved after optimizing beam configurations. The optimization approach could make treatment planning meet clinical requirements more efficiently, so it had extensive application perspective.

An E-learning System Architecture based on Cloud Computing

The massive proliferation of affordable computers, Internet broadband connectivity and rich education content has created a global phenomenon in which information and communication technology (ICT) is being used to transform education. Therefore, there is a need to redesign the educational system to meet the needs better. The advent of computers with sophisticated software has made it possible to solve many complex problems very fast and at a lower cost. This paper introduces the characteristics of the current E-Learning and then analyses the concept of cloud computing and describes the architecture of cloud computing platform by combining the features of E-Learning. The authors have tried to introduce cloud computing to e-learning, build an e-learning cloud, and make an active research and exploration for it from the following aspects: architecture, construction method and external interface with the model.

Improving Worm Detection with Artificial Neural Networks through Feature Selection and Temporal Analysis Techniques

Computer worm detection is commonly performed by antivirus software tools that rely on prior explicit knowledge of the worm-s code (detection based on code signatures). We present an approach for detection of the presence of computer worms based on Artificial Neural Networks (ANN) using the computer's behavioral measures. Identification of significant features, which describe the activity of a worm within a host, is commonly acquired from security experts. We suggest acquiring these features by applying feature selection methods. We compare three different feature selection techniques for the dimensionality reduction and identification of the most prominent features to capture efficiently the computer behavior in the context of worm activity. Additionally, we explore three different temporal representation techniques for the most prominent features. In order to evaluate the different techniques, several computers were infected with five different worms and 323 different features of the infected computers were measured. We evaluated each technique by preprocessing the dataset according to each one and training the ANN model with the preprocessed data. We then evaluated the ability of the model to detect the presence of a new computer worm, in particular, during heavy user activity on the infected computers.

Coupled Electromagnetic and Thermal Field Modeling of a Laboratory Busbar System

The paper presents coupled electromagnetic and thermal field analysis of busbar system (of rectangular cross-section geometry) submitted to short circuit conditions. The laboratory model was validated against both analytical solution and experimental observations. The considered problem required the computation of the detailed distribution of the power losses and the heat transfer modes. In this electromagnetic and thermal analysis, different definitions of electric busbar heating were considered and compared. The busbar system is a three phase one and consists of aluminum, painted aluminum and copper busbar. The solution to the coupled field problem is obtained using the finite element method and the QuickField™ program. Experiments have been carried out using two different approaches and compared with computed results.

Influence of Adaptation Gain and Reference Model Parameters on System Performance for Model Reference Adaptive Control

This article presents a detailed analysis and comparative performance evaluation of model reference adaptive control systems. In contrast to classical control theory, adaptive control methods allow to deal with time-variant processes. Inspired by the works [1] and [2], two methods based on the MIT rule and Lyapunov rule are applied to a linear first order system. The system is simulated and it is investigated how changes to the adaptation gain affect the system performance. Furthermore, variations in the reference model parameters, that is changing the desired closed-loop behaviour are examinded.

The Effectiveness of Ultrasound Treatment on the Germination Stimulation of Barley Seed and its Alpha-Amylase Activity

In the present study, the effects of ultrasound as emerging technology were investigated on germination stimulation, amount of alpha-amylase activity on dry barley seeds before steeping stage of malting process. All experiments were carried out at 20 KHz on the ultrasonic generator in 3 different ultrasonic intensities (20, 60 and 100% setting from total power of device) and time (5, 10 and 15 min) at constant temperature (30C). For determining the effects of these parameters on enzyme the Fuwa method assay based on the decreased staining value of blue starch–iodine complexes employed for measurement an activity. The results of these assays were analyzed by Qualitek4 software using the Taguchi statistical method to evaluate the factor-s effects on enzyme activity. It has been found that when malting barley is irradiated with an ultrasonic power, a stimulating effect occurs as to the enzyme activity.

Evaluation of Linear and Geometrically Nonlinear Static and Dynamic Analysis of Thin Shells by Flat Shell Finite Elements

The choice of finite element to use in order to predict nonlinear static or dynamic response of complex structures becomes an important factor. Then, the main goal of this research work is to focus a study on the effect of the in-plane rotational degrees of freedom in linear and geometrically non linear static and dynamic analysis of thin shell structures by flat shell finite elements. In this purpose: First, simple triangular and quadrilateral flat shell finite elements are implemented in an incremental formulation based on the updated lagrangian corotational description for geometrically nonlinear analysis. The triangular element is a combination of DKT and CST elements, while the quadrilateral is a combination of DKQ and the bilinear quadrilateral membrane element. In both elements, the sixth degree of freedom is handled via introducing fictitious stiffness. Secondly, in the same code, the sixth degrees of freedom in these elements is handled differently where the in-plane rotational d.o.f is considered as an effective d.o.f in the in-plane filed interpolation. Our goal is to compare resulting shell elements. Third, the analysis is enlarged to dynamic linear analysis by direct integration using Newmark-s implicit method. Finally, the linear dynamic analysis is extended to geometrically nonlinear dynamic analysis where Newmark-s method is used to integrate equations of motion and the Newton-Raphson method is employed for iterating within each time step increment until equilibrium is achieved. The obtained results demonstrate the effectiveness and robustness of the interpolation of the in-plane rotational d.o.f. and present deficiencies of using fictitious stiffness in dynamic linear and nonlinear analysis.

Second-order Time Evolution Scheme for Time-dependent Neutron Transport Equation

In this paper, the typical exponential method, diamond difference and modified time discrete scheme is researched for self adaptive time step. The second-order time evolution scheme is applied to time-dependent spherical neutron transport equation by discrete ordinates method. The numerical results show that second-order time evolution scheme associated exponential method has some good properties. The time differential curve about neutron current is more smooth than that of exponential method and diamond difference and modified time discrete scheme.

Sonochemically Prepared SnO2 Quantum Dots as a Selective and Low Temperature CO Sensor

In this study, a low temperature sensor highly selective to CO in presence of methane is fabricated by using 4 nm SnO2 quantum dots (QDs) prepared by sonication assisted precipitation. SnCl4 aqueous solution was precipitated by ammonia under sonication, which continued for 2 h. A part of the sample was then dried and calcined at 400°C for 1.5 h and characterized by XRD and BET. The average particle size and the specific surface area of the SnO2 QDs as well as their sensing properties were compared with the SnO2 nano-particles which were prepared by conventional sol-gel method. The BET surface area of sonochemically as-prepared product and the one calcined at 400°C after 1.5 hr are 257 m2/gr and 212 m2/gr respectively while the specific surface area for SnO2 nanoparticles prepared by conventional sol-gel method is about 80m2/gr. XRD spectra revealed pure crystalline phase of SnO2 is formed for both as-prepared and calcined samples of SnO2 QDs. However, for the sample prepared by sol-gel method and calcined at 400°C SnO crystals are detected along with those of SnO2. Quantum dots of SnO2 show exceedingly high sensitivity to CO with different concentrations of 100, 300 and 1000 ppm in whole range of temperature (25- 350°C). At 50°C a sensitivity of 27 was obtained for 1000 ppm CO, which increases to a maximum of 147 when the temperature rises to 225°C and then drops off while the maximum sensitivity for the SnO2 sample prepared by the sol-gel method was obtained at 300°C with the amount of 47.2. At the same time no sensitivity to methane is observed in whole range of temperatures for SnO2 QDs. The response and recovery times of the sensor sharply decreases with temperature, while the high selectivity to CO does not deteriorate.

Evaluation of the Displacement-Based and the Force-Based Adaptive Pushover Methods in Seismic Response Estimation of Irregular Buildings Considering Torsional Effects

Recent years, adaptive pushover methods have been developed for seismic analysis of structures. Herein, the accuracy of the displacement-based adaptive pushover (DAP) method, which is introduced by Antoniou and Pinho [2004], is evaluated for Irregular buildings. The results are compared to the force-based procedure. Both concrete and steel frame structures, asymmetric in plan and elevation are analyzed and also torsional effects are taking into the account. These analyses are performed using both near fault and far fault records. In order to verify the results, the Incremental Dynamic Analysis (IDA) is performed.

Study of MHD Oblique Stagnation Point Assisting Flow on Vertical Plate with Uniform Surface Heat Flux

The aim of this paper is to study the oblique stagnation point flow on vertical plate with uniform surface heat flux in presence of magnetic field. Using Stream function, partial differential equations corresponding to the momentum and energy equations are converted into non-linear ordinary differential equations. Numerical solutions of these equations are obtained using Runge-Kutta Fehlberg method with the help of shooting technique. In the present work the effects of striking angle, magnetic field parameter, Grashoff number, the Prandtl number on velocity and heat transfer characteristics have been discussed. Effect of above mentioned parameter on the position of stagnation point are also studied.

A Development of Home Service Robot using Omni-Wheeled Mobility and Task-Based Manipulation

In this paper, a Smart Home Service Robot, McBot II, which performs mess-cleanup function etc. in house, is designed much more optimally than other service robots. It is newly developed in much more practical system than McBot I which we had developed two years ago. One characteristic attribute of mobile platforms equipped with a set of dependent wheels is their omni- directionality and the ability to realize complex translational and rotational trajectories for agile navigation in door. An accurate coordination of steering angle and spinning rate of each wheel is necessary for a consistent motion. This paper develops trajectory controller of 3-wheels omni-directional mobile robot using fuzzy azimuth estimator. A specialized anthropomorphic robot manipulator which can be attached to the housemaid robot McBot II, is developed in this paper. This built-in type manipulator consists of both arms with 3 DOF (Degree of Freedom) each and both hands with 3 DOF each. The robotic arm is optimally designed to satisfy both the minimum mechanical size and the maximum workspace. Minimum mass and length are required for the built-in cooperated-arms system. But that makes the workspace so small. This paper proposes optimal design method to overcome the problem by using neck joint to move the arms horizontally forward/backward and waist joint to move them vertically up/down. The robotic hand, which has two fingers and a thumb, is also optimally designed in task-based concept. Finally, the good performance of the developed McBot II is confirmed through live tests of the mess-cleanup task.

DCGA Based-Transmission Network Expansion Planning Considering Network Adequacy

Transmission network expansion planning (TNEP) is an important component of power system planning that its task is to minimize the network construction and operational cost while satisfying the demand increasing, imposed technical and economic conditions. Up till now, various methods have been presented to solve the static transmission network expansion planning (STNEP) problem. But in all of these methods, the lines adequacy rate has not been studied after the planning horizon, i.e. when the expanded network misses its adequacy and needs to be expanded again. In this paper, in order to take transmission lines condition after expansion in to account from the line loading view point, the adequacy of transmission network is considered for solution of STNEP problem. To obtain optimal network arrangement, a decimal codification genetic algorithm (DCGA) is being used for minimizing the network construction and operational cost. The effectiveness of the proposed idea is tested on the Garver's six-bus network. The results evaluation reveals that the annual worth of network adequacy has a considerable effect on the network arrangement. In addition, the obtained network, based on the DCGA, has lower investment cost and higher adequacy rate. Thus, the network satisfies the requirements of delivering electric power more safely and reliably to load centers.

Modeling of Normal and Atherosclerotic Blood Vessels using Finite Element Methods and Artificial Neural Networks

Analysis of blood vessel mechanics in normal and diseased conditions is essential for disease research, medical device design and treatment planning. In this work, 3D finite element models of normal vessel and atherosclerotic vessel with 50% plaque deposition were developed. The developed models were meshed using finite number of tetrahedral elements. The developed models were simulated using actual blood pressure signals. Based on the transient analysis performed on the developed models, the parameters such as total displacement, strain energy density and entropy per unit volume were obtained. Further, the obtained parameters were used to develop artificial neural network models for analyzing normal and atherosclerotic blood vessels. In this paper, the objectives of the study, methodology and significant observations are presented.

Investigating Different Options for Reheating the First Converter Inlet Stream of Sulfur Recovery Units (SRUs)

The modified Claus process is the major technology for the recovery of elemental sulfur from hydrogen sulfide. The chemical reactions that can occur in the reaction furnace are numerous and many byproducts such as carbon disulfide and carbon carbonyl sulfide are produced. These compounds can often contribute from 20 to 50% of the pollutants and therefore, should be hydrolyzed in the catalytic converter. The inlet temperature of the first catalytic reactor should be maintained over than 250 °C, to hydrolyze COS and CS2. In this paper, the various configurations for the first converter reheating of sulfur recovery unit are investigated. As a result, the performance of each method is presented for a typical clause unit. The results show that the hot gas method seems to be better than the other methods.

Scatterer Density in Nonlinear Diffusion for Speckle Reduction in Ultrasound Imaging: The Isotropic Case

This paper proposes a method for speckle reduction in medical ultrasound imaging while preserving the edges with the added advantages of adaptive noise filtering and speed. A nonlinear image diffusion method that incorporates local image parameter, namely, scatterer density in addition to gradient, to weight the nonlinear diffusion process, is proposed. The method was tested for the isotropic case with a contrast detail phantom and varieties of clinical ultrasound images, and then compared to linear and some other diffusion enhancement methods. Different diffusion parameters were tested and tuned to best reduce speckle noise and preserve edges. The method showed superior performance measured both quantitatively and qualitatively when incorporating scatterer density into the diffusivity function. The proposed filter can be used as a preprocessing step for ultrasound image enhancement before applying automatic segmentation, automatic volumetric calculations, or 3D ultrasound volume rendering.

Adoption of Appropriate and Cost Effective Technologies in Housing: Indian Experience

Construction cost in India is increasing at around 50 per cent over the average inflation levels. It have registered increase of up to 15 per cent every year, primarily due to cost of basic building materials such as steel, cement, bricks, timber and other inputs as well as cost of labour. As a result, the cost of construction using conventional building materials and construction is becoming beyond the affordable limits particularly for low-income groups of population as well as a large cross section of the middle - income groups. Therefore, there is a need to adopt cost-effective construction methods either by up-gradation of traditional technologies using local resources or applying modern construction materials and techniques with efficient inputs leading to economic solutions. This has become the most relevant aspect in the context of the large volume of housing to be constructed in both rural and urban areas and the consideration of limitations in the availability of resources such as building materials and finance. This paper makes an overview of the housing status in India and adoption of appropriate and cost effective technologies in the country.

Semi-Automatic Analyzer to Detect Authorial Intentions in Scientific Documents

Information Retrieval has the objective of studying models and the realization of systems allowing a user to find the relevant documents adapted to his need of information. The information search is a problem which remains difficult because the difficulty in the representing and to treat the natural languages such as polysemia. Intentional Structures promise to be a new paradigm to extend the existing documents structures and to enhance the different phases of documents process such as creation, editing, search and retrieval. The intention recognition of the author-s of texts can reduce the largeness of this problem. In this article, we present intentions recognition system is based on a semi-automatic method of extraction the intentional information starting from a corpus of text. This system is also able to update the ontology of intentions for the enrichment of the knowledge base containing all possible intentions of a domain. This approach uses the construction of a semi-formal ontology which considered as the conceptualization of the intentional information contained in a text. An experiments on scientific publications in the field of computer science was considered to validate this approach.

A Novel EMG Feedback Control Method in Functional Electrical Stimulation Cycling System for Stroke Patients

With getting older in the whole population, the prevalence of stroke and its residual disability is getting higher and higher recently in Taiwan. The functional electrical stimulation cycling system (FESCS) is useful for hemiplegic patients. Because that the muscle of stroke patients is under hybrid activation. The raw electromyography (EMG) represents the residual muscle force of stroke subject whereas the peak-to-peak of stimulus EMG indicates the force enhancement benefiting from ES. It seems that EMG signals could be used for a parameter of feedback control mechanism. So, we design the feedback control protocol of FESCS, it includes physiological signal recorder, FPGA biomedical module, DAC and electrical stimulation circuit. Using the intensity of real-time EMG signal obtained from patients, as a feedback control method for the output voltage of FES-cycling system.