Earticle

A cross-layer optimization video transmission scheme, which includes two mechanisms, is proposed in this paper. The first is the encoding adjustment mechanism to handle buffer insufficiency. Large frames are divided into several sub-frames and the maximum number of packets in these sub-frames depends on the minimum buffer size in forwarding path. In addition, sending time of adjacent frames or sub-frames should be separated. And time intervals between adjacent frames or sub-frames are determined by the numbers of packets those frames or sub-frames have. The second is the priority based transmission mechanism to handle bandwidth insufficiency. Different dropping probabilities or scheduling opportunities are assigned to different frame types. Less important frames always have a high dropping probability or a small scheduling opportunity. In performance evaluation, various video sequences, buffer sizes and bandwidth reservations are employed. Simulation results verify that: (1) Cross-layer optimization is adaptive to different video sequences, buffer sizes and bandwidth reservations. That is to say, it is a content and network adaptive scheme. (2) Proposed scheme outperforms existing schemes significantly, especially when buffer size is small or bandwidth reservation is large. (3) A further advantage is that priority based transmission mechanism enhances video decoding quality while receives less packets. Thus it is friendly to other streams.

Brain tumour is the largest problem in the world. Few researchers have worked in that area. In the paper brain tumour is detected by the three different parameter of the proposed antenna namely return-loss of the antenna, current density of the brain phantom model with tumour and without tumour and specific absorption rate (SAR) with and without tumour. None of the previous work detects a tumour by three different parameter simultaneously. Initially the proposed antenna is designed at 2.45GHz and then applies different technology to make it ultra wide band. Antenna frequency is shifted and it become the ultra wide band and gives a bandwidth of 2.89GHz.S11 parameter of antenna achieved maximum at 7.624GHz that is 45.76dB. Found current density of the antenna is 770.6A/m2, SAR of the antenna is 2.67*106Watt/m3.Brain is assumed as a single layer Brain Phantom model in which brain is considered as centre radius of sphere of 10mm radius and placed in contact with upper part of the antenna, dielectric constant of brain is assumed as 45.8.it gives a return loss with brain model is 31.89dB at 7.61GHz and current density is 801.24A/m2, SAR of the brain phantom model with antenna is 3.15*106 Watt/m3.Now triangular shape tumor is assumed with dielectric constant of the tumor is 52.06 and it gives a return loss with tumor 32.26 at 7.544GHz.current density with tumor is 960.3A/m2, SAR of the phantom model with tumor and antenna is 3.069*106A/m2.The paper detect tumors by three different parameter simultaneously that is very important aspect.

Researches for urban rainfall-runoff simulation are inseparable from the hydrological information. However, this information is always composed of large amount of multi-source and heterogeneous data, which will bring significant difficulties to the information organization and management systems. In this paper, Geographical Information System (GIS), a specialized information system for the spatial information is introduced into the studies of urban rainfall-runoff simulation (URRS), in which a series of applications are presented. In these applications, hydrological information in urban region is collected, stored and processed by the spatial data storage, analysis and visualization abilities of GIS. The applications show that the integration of GIS and hydrological information is feasible in URRS and has achieved remarkable results, which can provide a strong data support to the simulation and control of urban storm water disaster.

Weighted association rules are to research on association rule mining expansion. It is aimed at users of different project importance of different database mining, to help users find interesting association rules, but also does not produce too many useless rules. The most important process of weighted association rules mining is weighted to generate frequent item sets. Unidirectional FP- tree node entry's serial number marking and recording the support count. Item number by the support from big is to small order determination. The paper presents the research of a novel weighted association rules algorithm based on unidirectional FP tree. Implementation results show that the algorithm unidirectional FP running efficiency is relatively high.

Neurocomputing in complex domain has yielded second generation neural networks. The neural network, which is based on complex value, contains different layers. The attributes of these layers are biases, weights, inputs and outputs. These attributes are also complex numbers. The signal processing, speech processing, learning and prediction of motion on plane are few areas in which complex domain neurocomputing is applied., since in the above said areas, the inputs and outputs are represented by complex values. It has been observed that the neural network with complex value can easily perform the transformation of geometric figures. The examples of transformations are rotation, parallel displacement of straight lines and circles. The neural network can extend to complex domain by the application of transformation. A number in complex domain is composed of different entities i.e. two real numbers and phase information. The two real numbers and phase information of any point on plane is naturally embedded in this number.

A two-bar plane truss is builtin MATLAB based on mathematical model. Then the authors use genetic algorithm toolbox to solve this problem. The parametric truss model is set up in the finite element analysis software ANSYS. It is analyzed by first-order algorithm. The comparison of two kinds results show the pure genetic algorithm doesn’t always have an advantage over other algorithms. In the end, a joint optimization method is put forward on the basis of genetic algorithm. It combines genetic algorithm based on MATLAB toolbox and numerical algorithm based on quasi-Newton method. This method is illustrated by the numerical example of the two-bar plane truss. The results show this joint optimization method can get the global optimal solution of this problem every time.

Switching Converters commonly known as DC/DC Converters have gained tremendous popularity due to their use in variety of applications such as hybrid energy systems, hybrid vehicles, satellite applications and portable electronic devices to name a few. The main positives of using high step up converters include improving voltage gain, reduction of voltage stress and current ripple. But these converters seem to have some disadvantages like very high EMI due to reverse recovery of the boost diode and considerable amount of losses which occur due to hard switching of the boost switch. Many variations of the original boost schematic have been suggested to overcome these problems. The Zero Voltage Transition (ZVT) Boost converter and Zero Current Transition (ZCT) Boost converter are such solutions. These soft switching topologies employ an auxiliary resonant circuit which allows the boost switch to turn on and off under zero voltage and zero current conditions respectively thus reducing the switching losses. In addition, these boost converter circuits have major drawback of low power efficiency particularly at light loads due to the negative value of inductor current at light loads. In this research, a novel technique for designing a boost converter is proposed. The proposed converter employs an auxiliary circuit which allows switching of the main switch as well as the auxiliary switch under zero voltage/zero current conditions. In addition, the boost converter automatically senses the zero current across the resonant inductor, thus forcing the convertor to step automatically from Continuous Conduction Mode (CCM) to Discontinuous conduction mode (DCM) when the inductor current tries to go negative. This prevents the inductor current to go negative and hence improve convertor’s power efficiency. A novel boost convertor which steps up 200V input voltage to 400V output is designed in PSIM software with a switching frequency of 100KHz. The simulation results show that the proposed convertor has an efficiency of about 99.3% at nominal output power.

This paper proposes an analysis method of user behavior to provide personalized program recommendation based on program tags in the field of broadcasting and television. Multidimensional Scaling Analysis is used to produce a quantitative description of viewing preferences. Hierarchical clustering is performed to determine the number of clusters, followed by K-means clustering to group the data according to audience interest in TV program tags. This divides the audience into groups with similar viewing preferences.

Linear algebraic equations based methods in the time difference of arrival (TDOA) localization are akind of excellent algorithms. In consideration of the constraints on parameters to be estimated, the first-order error in matrix and the second-order noise in vector, a sequential-quadratic-programming-based localization algorithm isproposed in this paper. An optimal solution of the linear equation model was obtained in the algorithm. Meanwhile, with the rank 1 constraint ignored, the problem was rewritten to a series of convex functions and then a semi-definite relaxation (SDR) solution was yielded additionally. However, the solution can only be used as an initial value for other TDOA localization algorithms due to the insufficient accuracy of the SDR solution. Final localization experiments demonstrate that the proposed algorithm has a higher positioning accuracy compared with other TDOA localization algorithms based on linear model. At the same time the result can be closer to the Cramer-Rao Lower Bound, especially at the low signal to noise ratio regime.

A sustainable business continuity management plan (BCM) is developed to adapt and respond to the current complex and dynamic business environment, while simultaneously accommodating the key system transformations. As an integral part of BCM, business preparedness reduces the impact of a disruption to employees, productivity and profitability. Additionally, BCM and disaster recovery helps service providers and owners of critical infrastructure, such as telecommunication networks and digitized energy utilities to resume operation within the shortest time in the event that a disaster strikes. The central drive of this extensive research is developing a maturity model for BCM/DR for measuring the capability of BCM and disaster recovery for the Kingdom of Saudi Arabia (KSA) companies. A qualitative research scheme, marked by an open-structured interview was adopted to explore the core aspect of the research topic. A customized maturity model for the KSA ICT sector was developed by analyzing the existing model and then validating the developed maturity model against the predefined objectives. The research demonstrated that the establishment of a standardized maturity model for BCM/DR as capability instrument for the ICT segment is valuable to address the gap in KSA organizations as they assess the competences of their BCM/DR programs or processes.

To reveal stress distribution rules of grain separating process in assembled axial flow threshing and separating device, regarding assembled axial flow threshing and separating device as object, High speed imaging technology is adopted in the shooting technique, stress model was set based on the stress principle, and stress distribution rules was obtained by simulation technology. Grain, broken ear movement and the movement as a whole and free movement of the grain threshing process is through the analysis of the EXCEL drawing, The test results show that distribution rules is irregular in grain separating process, is that, stress fluctuates at axial direction, and two peak values appear at early and middle threshing stage respectively; threshing and separating process finishes about 2.35 meters from the feeding mouth at axial direction. Off the spike in threshing and separating space motion unstable trajectory is a parabola, the speed decreased with the passage of time. No outside interference in the most free grain for approximate straight movement, in the medium of motion state, and axis direction and a certain angle.Therefore, grain rotors distribute at axial direction and rest results are consistent with theory analysis.

With the exponential increase of the cloud business volume, Data center occurs load imbalance caused by some physical machine inefficiency due to the diversity of users requirements. Therefore the cloud datacenter need an appropriate algorithm to balance the PMs load and ensure the resource utilization in the cloud datacenter. The paper defines and formulates the problem parameters and proposes a Multi-objective Discrete Particle Swarm Optimization (MDPSO) to schedule the resources to the VMs requests according to the requirements. The simulation shows that the MDPSO algorithm not only guarantees the resource utilization, but also insures the PMs Load balance.

In this paper we focused on mathematical formulation for capacitive pressure sensor. The most important parameter of every sensor are deflection on the application of applied pressure, variation of capacitance on deflection and sensitivity. Here we mathematically drive equation for every parameter. This article help researcher to develop MEMS based capacitive pressure sensor for particular application. For that purpose we also vary the thickness of sensing diaphragm. Our study in this article is mainly consider only case of pressure sensor in normal mode. Mostly researcher use FEM method for design and simulation of capacitive pressure sensor but using these equation they can easily design any sensor by changing the parameter of equation. The material for diaphragm is Si and for insulation layer is SiO₂ is taken in this article.

The response surface methodology optimizes in the study. The ultrasonic extraction process of polysaccharide from Lycopus lucidus Turcz. was optimized by using response surface methodology. The vitro antibacterial activity of roughly purified L. lucidus polysaccharide on Escherichia coli, Bacillus subtilis, Bacillus licheniformis and Staphylococcus aureus. The optimal extraction conditions were determined as followed: liquid-solid ratio: 40.73 mL/g; ultrasonic power: 542.70 W; under the optimized extraction conditions, the extraction yield of L. lucidus polysaccharide was 8.59% (close to the theoretical value of 8.55%). In addition, L. lucidus polysaccharide showed very strong antibacterial activities E. coli, S. aureus and quite significant antibacterial activities on B. licheniformis.

Ant colony algorithm (ACA) is a new heuristic algorithm which has been proven a successful technique and applied to a number of combinatorial optimization problems. An Granular ACA algorithm based on scout characteristic is proposed for solving the stagnation behavior and premature convergence problem of the basic ACA algorithm on TSP. Proposesing a Granular computing adaptive ant pheromones mechanism base on researching on ant colony algorithm model, pheromones update and pheromones selection had been improved. Make up the traditional ant colony algorithm for the calculation of distribution network planning that is slow and easy to fall into local optimal solution. And improved the convergence of the optimal solution. The validity of the GACA has been verified using a testing function. In addition, a satisfactory optimum solution for a Power Distribution Network Planning that has 73 users has been obtained.

One of the most serious complications of diabetes is Diabetic foot. The incidence of diabetic foot increases equally on a rise of diabetic's increases and it is often ignored by people leading to a rise in major amputations. Diabetic foot disease diagnosis is done by using fuzzy logic and beneficial as it incorporates the knowledge and experience of physician into fuzzy sets and rules. In this paper, we propose a fuzzy expert system framework for diabetic foot which constructs large scale knowledge based diabetic foot system. The knowledge is constructed by using the fuzzification. Fuzzy verdict mechanism uses triangular membership function with mamdanis inference. Defuzzification method is adopted to convert the fuzzy values into crisp values.

Prostate segmentation from MRI is a necessary first step and plays a key role in different stages of clinical decision making process. In this paper, we propose a MR T1 Image segmentation method of the prostate based on distance regularized level set evolution with a deformable shape prior. To smooth the prostate image to reduce the noise, we introduce a prostate image with Gaussian kernel and get an edge indicator. To avoid the leakage induced on account of prostate boundaries missing, or blending with surrounding tissues, we introduce priori shape information to construct an energy function with a distance regularization term and an external shape energy term containing the edge indicator and minimize it by solving the gradient flow which can be implemented with a finite difference scheme. To verify the MRI segmentation method of a prostate presented in this paper, we utilize the optimal value of parameters λ, μ, α and ε in the distance regularized level set evolution model and the deformable shape prior of prostate to segment a part of images from normal prostate, benign hyperplasia prostate and cancer prostate. The experiment results show that the MRI segmentation method of prostate presented in this paper is effective for different situation of different patients.

In order to monitor working conditions of the hydraulic excavator correctly, the data mining technology is applied in it. Firstly, the basic theory of hydraulic excavation is studied; Secondly, the basic theory of data mining is summarized; Thirdly, the application of rough set is analyzed; then design of status monitoring system for hydraulic excavator is carried out; finally, a case study of excavator monitoring system is carried out, and results show that the data mining technology is an effective method for monitoring the condition of hydraulic excavator.

This work proposes the application of a hybrid Particle Swarm Optimization (PSO) with Levenberg Marquardt Back-Propagation (LMBP) algorithm to train Artificial Neural Networks (ANNs) for classification of medium resolution multispectral satellite imageries. ANNs have been widely used in satellite image classification and have been shown to outperform traditional classifiers in many situations. However the Back Propagation (BP) algorithm traditionally used in training ANN suffer the problem of local minima entrapment, thus affecting the accuracy and performance of the ANN classifier. A hybrid combination of PSO and LMBP algorithm is applied to resolve the aforementioned problem and enhance the accuracy and performance of the ANN classifier. To investigate the performance of the proposed method, medium resolution multispectral satellite imagery was classified using the proposed classifier and its performance compared with that of conventional LMBP and Scaled Conjugate Back-Propagation (SCBP) trained ANN classifier. Results obtained shows that the hybrid PSO and LMBP trained ANN classifier out performs the conventional LMBP and SCBP trained ANN classifier and achieves ≈95% accuracy on the test medium resolution satellite imagery.

MOOC (Massive Open Online Courses), is a new mode of distance education courses based on the Internet technology. To solve problems in MOOC, such as lacks of management, supervision and comprehensive evaluation etc., this paper aims to study MOOC academic management and analysis method in contexts of colleges and universities. To supervise and trace students’ learning process, an academic management system of MOOC was constructed. To assess and predict students’ learning trends and achievements, an academic analysis model was established based on learning and interaction data analysis. Experimental results prove the above method insures expected learning effects when applying MOOC in colleges and universities.

High-performance conjugate gradient (HPCG) is the latest benchmark adopted by the TOP500 organization, and thus how to optimize the HPCG source code for different heterogeneous computing platforms to achieve a higher floating-point computation rate has already become a new hot issue in HPC field. In the paper, we used the CPU + MIC heterogeneous computing platforms, and successfully ported HPCG to the platform. Through the analysis of HPCG source code and optimization for CPU + MIC platforms, practical significance and the value of further research is put forward. Results of performing the benchmark indicate that the design of optimization methods is reasonable and has facilitated the speedup of HPCG benchmark.

The majority of image-processing techniques interact treating the impression as being a two dimensional signal and applying normal signal-processing techniques to it. Within this document we offer a new standard approach to have the hidden restrictions which aren't revealed by the Sobel together Canny filters together in face-recognition environment. We've also showed the effect of the contrast and threshold around the photos. In the same manner, we have shown our techniques about the video. Thus, many beautiful contrast and the hidden data are shared.

Taxi subsidy program established is reasonable or not is one important step to research the "taxi difficult" issue in today's society. In this paper, we analyze the correlation of the three indicators and 15 factors, get the correlation between the index and its influencing factors, then reuse roughset preliminary screening for data factors, combined factor analysis to obtain the final subsidy program evaluation model. Substituted into the value of the three indicators before and after subsidies respectively, obtained the evaluation value before andafter the subsidy. Q1, Q2, andQ1Q2, the subsidy program for "ease taxi difficult" has some help.

The unscented Kalman filter (UKF) has become a popular method for nonlinear state estimation during the last decade. However, the conventional UKF may not be suitable for real-world applications with state constrains that stem from physical definitions, physical laws or model restrictions. A UKF based method with optimized parameters was proposed in this paper to handle state constraints via the projection of sigma points. In the proposed method, the generated sigma points that violate the state constraints were projected onto the constraint boundary first. The three free parameters of the UKF, i.e., α ,β ,κ , were then optimized using a Gaussian process optimization (GPO) method. Simulations indicate that the proposed optimized UKF algorithm with the projection of sigma points can handle constrained state estimation problem effectively and efficiently.

Design a robust oscillation-free controller for multi input-multi output (MIMO) nonlinear uncertain dynamical system (sensitive dental joint) is the main objective in this research. In this paper, robust sliding mode controller will be selected as a main control technique and linear controller will be design to improve the stability and robustness to control of dental joint. The proposed approach effectively combines of design methods from switching sliding mode controller, and linear Proportional-Integral-Derivative (PID) control to improve the performance, stability and robustness of the sliding mode controller. Conventional sliding mode controller has two important subparts, switching and equivalent. Switching part (discontinuous part) is very important in uncertain condition but it causes chattering phenomenon. To solve the chattering, the most common method used is linear boundary layer saturation method, but this method lost the stability. To reduce the chattering with respect to stability and robustness; linear controller is added to the switching part of the sliding mode controller. The linear controller is to reduce the role of sliding surface slope and switching (sign) function. This controller improves the stability and robustness, reduces the chattering as well and reduces the level of energy due to the torque performance as well.

A new kind of adaptive sliding mode control method is proposed for simplified missile model of pitch channel with time varying and uncertain parameters. Sliding mode control is an effective method for coping with system uncertainties. Adaptive method is integrated with sliding mode method and a Lyapunov function is constructed to guarantee the whole system is stable. Through the theoretical analysis and numericala simulation, comparison between PID control and sliding mode control shows that the adaptive sliding mode control of the uncertain missile system has a better control effect. And with consideration of three kind of parameter uncertainties in simulation, sliding mode control has better robustness.

To address the problem that reactive navigation is prone to local optimality under uncertain and complex environments, a POMDP-based global path planning algorithm is proposed for mobile robots. A 6-tuple model is constructed for path planning under complex dynamic environments, and the global optimality is realizes by maximizing the accumulative reward function. State transition function and observation function are used to handle unknown obstacles and noisy perception by modeling the error probability. Belief state space is introduced, and a value iteration algorithm using point-based policy treepruning is developed to solve for real time planning policy, which effectively reduces the computational complexity. Simulation results show that using this algorithm the robot can automatically adapt to different probing granularities, avoid obstacles under complex uncertain environments, and achieve the optimal paths.

Micro pumps play important roles in microfluidic system. Biologically inspired actuation mechanisms have great advantages in the micro pump design. This work aims to develop a numerical model for bio-inspired micro pump based on the specific and genuine movement pattern of the sperm. The model also employs a modified immersed boundary-lattice Boltzmann method. In the model, an elastic film is used to mimic a sperm moving with its head fixed. The fluctuation vibration of the film could then drive the static fluid to move. The modified immersed boundary-lattice Boltzmann method directly introduces the velocity information of the film into the traditional lattice Boltzmann equation, which improve the computational efficiency. Pressure distribution, streamlines and the flow rate curves are used to analyze the flow field dynamic process of the model. The effects of the model parameters (e.g. frequency, kinematic viscosity, amplitude and wavelength) on the stable flow rate are also studied comprehensively.

Through the establishment of the capital flight model of asymmetric evolutionary game, this paper focuses on the study of game relationship among perpetrators, perpetrator assistants and government, and analyzes the evolutionary stable process under different conditions by three-dimensional figures. This paper also analyzes and compares features between the two parties’ model and the three parties’ model, connecting the two kinds of evolutionary games and providing a theoretic basis for a better understanding of the mechanism of capital flight and motivation of all groups. The result shows that by making use of expectation, government can control the ESS of capital flight groups by adjusting relative benefits and punishment in different regulation modes. It can also expand the strategy space that is in favor of capital control through the adjustment. In the end, this paper will propose policy suggestions for the control of capital flight according to the research findings above.

In this paper, impact of heat and mass transfer on peristaltic hemodynamic Jeffery fluid model through a tapered vertical channel under the influence of radiation is studied under long wavelength and low Reynolds number assumptions are investigated. Closed form expressions for the axial velocity pressure gradient, temperature, heat transfer coefficient and Concentration distribution (Mass transfer distribution) on the channel walls have been computed numerically. In addition, it has been illustrated graphically for significant various parameters such as, Radiation parameter, Prandtl number, heat source/sink parameter, Soret number, Schmidt number and Jeffery fluid parameter.