Earticle

In this paper, we propose a power effective bus encoding scheme which can minimize crosstalk problems as well as bus transitions effectively. In current submicron technology, minimizing propagation delay and power consumption on buses is one of the most important design objectives in the field of System-on-Chip (SoC) design. Crosstalk between adjacent wires on bus may create significant propagation delay. Elimination or minimization of such faults is crucial not only for the system performance, but also for the reliability of SoC designs. Experimental results show that our proposed encoding technique can save dynamic power by up to 23.3% for 4- bit buses, while completely removing crosstalk delay.

Electronic circuit optimization design is important research field in engineering applications. Circuit scale and the time of evaluate the circuit are the challenge problems for circuit optimization design algorithm and the traditional optimization algorithms cannot solve the two problems very well. Cultural Algorithms are a class of computational models derived from observing the cultural evolution process in nature. Aiming at the disadvantages of basic Cultural Algorithms like being trapped easily into a local optimum, this paper improves the basic Cultural Algorithms and proposes the improved cultural algorithm (ICA) to solve the overcomes of the basic Cultural Algorithms. The new algorithm keeps not only the fast convergence speed characteristic of basic Cultural Algorithms, but effectively improves the capability of global searching as well. For the case studies, the new algorithm means has proved to be efficient and the experiment results show that the new means have got the better results.

Recently automotive embedded system has developed highly since the advent of smart car, electric card and so on. They have various value-added system for example IPA (Intelligent Parking Assistance), BSW (Blind Spot Warning), LDWS (Lane Departure warning System), LKS(Lane Keeping System)-these are ADAS (Advanced Driver Assistance Systems). AUTOSAR (AUTomotive Open System Architecture) is the most notable industrial standard for developing automotive embedded software. AUTOSAR is a partnership of automotive manufacturers and suppliers working together to develop and establish an open industry standard for automotive E/E architectures. In this paper, we will introduce AUTOSAR briefly and demonstrate the result of automotive software - LDWS (Lane Detection & Warning System) - development.

In this Paper, we propose a Personal Area Distance Computing System (PADCS). The proposed PADCS is built on WUSB (Wireless USB) over WBAN (Wireless Body Area Networks) protocol. And the PADCS is based on synchronized sensor nodes consisting of a WBAN, and location measurement results can be transmitted to the context-aware server through WUSB over WBAN protocol. In the PADCS, a WUSB host calculates the position of a receiving sensor node by using the difference between the times at which the sensor node received different WBAN beacon frames sent from the WUSB host. Performance of the PADCS is evaluated through simulation results and is compared with the Active Bat system with regard to distance computing error and the computing rate. The results demonstrate that the proposed system is a promising and feasible system for personal area distance computing environment where all sensor nodes comprise peripherals of a wearable computer system.

This paper presents a method for optimum tuning of Fractional PID controllers using PSO algorithm which have fractional or integer order transfer functions. Particle swarm optimization (PSO) is a robust stochastic optimization technique based on the movement and intelligence of swarm, applies the concept of social interaction to problem solving. The best parameters of Fractional-Order PID controller consist of proportional gain integral gain , fractional-order of integrator λ, derivative gain and fractional-order of differentiator μ can be determinate by using this technique. The proposed approach with defined cost function has a very easy implementation and ability of fast tuning of optimum fractional-order PID controllers parameters. From the comparison this technique with the other methods, its influence and efficiency are illustrated.

The problem of delay-dependent stochastic stability for neutral Markovian jump systems with mixed delays is investigated in this paper. Combined the new constructed Lyapunov functional with the introduced free matrices, and using the analysis technique of matrix inequalities, the delay-dependent stability conditions are obtained. The obtained results are formulated in terms of LMIs, which can be easily checked in practice by Matlab LMI control toolbox. Finally, two numerical examples are given to show the validity and potential of the developed criteria.

This paper presents a flexible service framework for tour-and-charging schedulers based on web services, aiming at providing an energy-efficient tour schedule services to electric vehicles. For a rent-a-car system which is a promising business model capable of dealing with high cost of electric vehicles, this service decides the visiting order for renters who want to visit multiple tour spots and need to have their vehicles charged during their trips. Mobile applications, running on Android operating systems, take the user selection via Google Map interface and submit to the scheduler by means of well-known Simple Object Access Protocol (SOAP). The tour scheduler implements not only a genetic algorithm to decide the visiting order for the given spot set but also a point-to-point A* algorithm to find an appropriate route between two consecutive spots on a graph-style road network, which necessarily contains the locations of charging facilities. Every parameter and result is encapsulated by KSOAP to comply with .NET platform. This service can enriches the smart transportation service, especially in long-term and short term rental and sharing businesses.

This paper introduces the shift schedule of saving energy to keep the torque converter working high-efficiency. The author carries on the further study of saving energy shift theory, and presents the control method of saving energy shift schedule. At the same time, this paper expounds how to use the shift theory and puts forward the control method of saving energy shift schedule. At last, the author expounds how to use the delayed shift to solve the problem of shift cycle, so as to ensure the accuracy of the automatic shift control.

The AUTOSAR (AUTomotive Open System Architecture) software platform as the international industry standards of automotive electronic software performs PDU Transmission Mode in AUTOSAR COM (Communication) which processes signals in I-PDU for transmission and reception between ECUs. In this paper, we look around operation principles of three methods such as DIRECT/N-Times, PERIODIC, MIXED which are used when I-PDU transmission in COM. Also, we analyze the signal processing function which is executed in AUTOSAR COM and I-PDU transmission method, and present efficient I-PDU transmission methods to guarantee reliability and stability.

Sliding Mode controller (SMC) is a highly significant nonlinear controller under condition of certain and partly uncertain dynamic parameters of system. This controller is used to control of highly nonlinear systems especially for continuum robot manipulators, because this controller is a robust and stable. In opposition, conventional sliding mode controller is used in many applications; it has two important drawbacks; chattering phenomenon and nonlinear equivalent dynamic formulation in uncertain dynamic parameter. To reduce or eliminate the chattering two methods is used; modified proportional-derivative boundary derivative sliding function and design a nonlinear sliding surface function based on fuzzy inference system and applied to sliding mode controller. The nonlinear equivalent dynamic formulation problem in uncertain system can be solved by applied artificial intelligence theorem (e.g., fuzzy inference system). Based on this research chattering eliminated based on applied modified sliding function and fuzzy inference engine and this controller is more robust than conventional sliding mode controller and simple fuzzy sliding mode controller.

In this paper, class-dependent acoustic features are investigated to discriminate consonant class in dysarthric speech. In dysarthric speech, imprecise articulation causes different distortion of consonants depending on each consonant class. For this reason, discrimination of consonant class can play an important role in dysarthric speech processing as a preprocessing step. Therefore, to discriminate each consonant into one of five different classes such as stop, fricative, affricate, nasal, and glide, the discrimination is performed based on a support vector machine (SVM) is employed, which is constructed by using the class-dependent acoustic features combined with mel-frequency cepstral coefficients (MFCCs). It is shown from the discrimination experiments that an SVM using the class-dependent acoustic features relatively reduces average discrimination error rate by 7.67%, compared to that using only MFCCs.

During the grinding, the principal axis drives the grinding wheel to rotate at a high speed, which generates disturbance to the air flows around the grinding wheel. Therefore, a layer of air boundary can be formed on the surface of the working grinding wheel, which is the airflow field. Airflow field not only affects the machining accuracy of the workpiece and the enhanced abrasion of grinding wheel, but also prevents the efficient injection of the grinding fluid into the grinding zone. These processing conditions and lead to the increasing grinding force and rising grinding temperature, deteriorating the processing quality and surface integrity of the workpiece. With higher rotation speed of grinding wheel, the “airbond” of the air flow will be greater. And the grinding fluid will be harder to break through the “airbond” and be supplied to the grinding zone. In this study, on the basis of theoretical analysis on the airflow field of grinding wheel, a mathematical model was established, including the internal and external pressure differences of the airflow field, the airbond thickness δ, fluid density ρ, radius R and radius ω. In addition, the changing rules of airflow field along the grinding wheel were studied based on simulation tests. Results demonstrate that the tested airflow field presented the same pressure in concentric circles of the grinding wheel. Along the surface outer normal direction, the pressure value gradually decreased from the outer to the inner space, presenting negative pressure gradient. The velocity of the airflow field around the grinding wheel reduced as the distance from the wheel increased. To a certain thickness, the velocity became zero, which verified the existence of the boundary layer.

In this paper, we present a global contrast intensification approach. Contrast intensification is generally carried out as a contrast expansion and after that a tonal intensification is followed. In this paper, we present a new contrast intensification method. First of all, a color image in RGB color space is transformed into YIQ color space. Then, the Y channel of YIQ is contrast restricted. We apply proposed histogram equalization approach on Y channel, or separated each channel of Y, I, and Q channels. The experimental results prove that the processed images look good-natured.

In the networked control system, the control interference, measurement noise and time delay make traditional digital PID algorithm not reach stable state. On the basis of simple digital PID algorithm, Kalman filter is first introduced, the effect of the interference and noise is decreased, and stability is improved. Then RBF (Radial Basis Function) neural network is used, Jacobian array is computed, the three parameters of PID algorithm are adjusted. Furthermore, the resistance integral saturation is used to limit the size of control quantity. Finally the simulation research on a DC (Direct Current) motor is done, and the simulation results show the effectiveness of the proposed algorithm when time delay, noise and interference are all large.

In a wireless sensor network, measures to rationally evaluate the signal detected and reported by the sensor are needed. To infer the context based on the detected signal, determination of basic probability assignment for multi-sensor data fusion using Dempster-Shafer Theory is proposed. If there is insufficient advance information in a wireless sensor network using different type of sensors, it is helpful to use the difference of the sensed signal values. First is to compare the measurement with the previous measurements and second is to compare the measurement with the filtering reference which is the basis of sensor report. In evaluation through comparison, one can compare the averages in a selected time band, but it may be more rational to compare the variance in evaluation of measured values. We applied such evaluation to determination of basic probability assignment to utilize it for context inference using DST.

Critical infrastructure is the backbone of our nation's economy and security. Cyber security and Communication works to prevent or minimize disruptions to critical information infrastructure in order to protect the public, the economy, and government services. And Software vulnerabilities can make possibility of a critical threat. There is lots of research being a large scale of software vulnerability. Critical infrastructure's security requirements are to process the large amounts of data in a short time. Taint analysis is becoming major technique in security analysis. In particular, proposed system focuses on tracing a taint analysis. Therefore, we proposed taint analysis method to determine by a single set of instruction and operands for threats detection. We proposed classification of binary level taint analysis that can find two types of threats, are control flow hijack and arbitrary memory write. Our evaluation results show that we can reduce number of instruction check.

This paper addresses the outer synchronization problem of complex networks with multiple coupling time-varying delays. First of all, some novel synchronization criteria are obtained by employing the Lyapunov stability theory and linear matrix inequality (LMI), we design some synchronization controllers to keep the given complex network synchronizing to the object trajectory. Furthermore, an adaptive outer synchronization scheme is derived to achieve global synchronization, which is simpler than some traditional controllers. Moreover, the presented results here can also be applied to complex networks with single time delay case. Finally, numerical analysis and simulations for two coupled complex networks which are composed of unified chaotic systems are given to demonstrate the effectiveness and feasibility of the proposed complex network control and synchronization schemes.

A hotspot offers Internet access over Wi-Fi through the use of a router connected to a link to an internet service provider. If the link is wireless, e.g., WiMAX, the hotspot becomes mobile. Under such a heterogeneous network, it is challenging to provide QoS and/or to control data rate. In this paper, we design and implement a policy server for commercial WiMAX mobile hotspots based on Policy and Charging Control (PCC) architecture defined in WiMAX Forum. The paper investigates a suitable QoS configuration including scheduling type. The experimental results show the feasibility of VoIP service over the mobile hotspots. The paper also shows how the rate limiting feature of our policy server can be utilized for different levels of customer service.

It is obvious that in order to keep normal operation of a metro system, tremendous works are needed for its maintenance, nevertheless how to get optimum maintenance solution is still a critical problem to be solved. This paper presents a Fuzzy-Set based theoretical approach for verifying the reasonability of current methods in maintenance, determining whether a device or facility system should be removed from operation for repair while the “Failure Mode and Effects Analysis (FMEA)” is used. Under such case, fuzzy quantitative treatment is operated to the linguistic/semantic expression of the FMEA, which identifies the failure status of the sub-systems (or its components) with fuzzy quantitative information for evaluating its overall deterioration state. A case study of vehicles’ maintenance in a metro network system in Shanghai is presented to show the applicability of the fuzzy treatment strategy to FMEA in the optimization of metro maintenance management.

By relying only on the router IQSize (Instantaneous Queue Size), the IntelRate controller has shown better performances than the existing explicit congestion control protocols. It fundamentally overcomes the defects of the existing protocols that can potentially misestimate network parameters and consume too much router computation resources. However, researchers are also interested in the design of certain controller parameters and the choice of their values because they can affect the performance of the controller. In this paper, we will experimentally investigate in details the effects of two important parameters of the fuzzy logic controller: the width of membership functions and the number of linguistic variables. Using extensive OPNET simulations, we show the performance tradeoffs when choosing values for these two parameters.

Roadside Unit (RSU) in Vehicular Ad-hoc Network (VANET) is an essential unit usually placed at intersections to collect and analyze traffic data given from smart vehicles. Due to the costs of RSU setup, effective RSU allocation is one of important issues in VANET. In this paper, we provide an optimal RSU allocation algorithm with a concept of intersection-connectivity between intersections. We initially find optimal RSU candidate intersections which can cover the entire intersections, in the meantime minimizing the overlapped transmission coverage of RSUs. Then we repeatedly eliminate RSU candidates by the value of intersection-connectivity between RSU candidate intersections. The intersection-connectivity between two intersections is basically measured by the number of vehicles with the same moving pattern such that pass through both intersections. Thus, a high value of intersection-connectivity between two intersections stands for that the traffic information obtained at one intersection can be carried-and-forwarded to the other intersection with a high probability by those vehicles. With this feature, we repeatedly remove RSUs having high intersection-connectivity with its neighbors. Finally, we provide simulated analyses of our algorithms using real urban roadmaps of JungGu and Seochogu in Seoul. We analyze how our algorithms work in different types of roadways with real traffic data, and find the optimal number and positions of RSUs in these areas.

China Train Control System (CTCS-3) is a safety critical computer system that features large-scale, complex structure, and redundant configuration. CTCS-3 and as well as the equipment and technologies related to it can ensure the safety and reliability running of high-speed trains, and so the assessment on its reliability becomes very important. Generally, the two elements such as common cause factor (CCF) and failure mode polymorphism can not be ignored when assessing the reliability on a large complicated system. There are some limitations existing when applying the traditional fault tree analysis (FTA) is used to deal with the two factors mentioned above, and considering that Bayesian network (BN) possesses the abilities of bidirectional reasoning and the uncertain knowledge solving, and therefore BN is introduced to change the flaws. The method firstly establishes the FTA model of system from top to bottom, and then converts the FTA model into BN model from the lower to the upper, hierarchically. Eventually, the reliability indices are calculated using the BN with regard to the CCF and multi-state factors. Through integrating and evaluating sub-models using the approach with FTA combined with BN in the CTCS-3 system, some interesting results are acquired. The relative results show that the proposed approach is quite effective, and also provides a theoretical basis to improve the system reliability.

King Sejong Station in King George Island plays a great role in the expansion of the human activities due to its geographical characteristics as an advance post and gateway to the mainland of Antarctica. This study addressed the precise positioning of King Sejong Station’s GPS CORS (Continuously Operating Reference Station) and the estimation of the crustal movement of Barton Peninsula, King George Island. The GPS data for 32 months (January 2007 to August 2009) were used for the study, and the relative positioning method was used for precise positioning. The observation data of O’Higgins, which is closest to King Sejong Station, were used as the fixed points among the IGS (International GNSS Service) CORSs. Precise positioning with a maximum of ±0.0172 m RMSE was possible for the X, Y, and Z components. The precise point positioning (PPP) of the GPS data showed that Barton Peninsula is moving at a speed of 19 mm/year northeast (30° azimuth).

In order to create the model of differential equations of system using limited and poor datum in the simulation of system dynamic the inverse GM model is proposed in this paper. In the system with poor information the classic estimation of parameter is difficult to be used to create the model of differential equations for analysis and forecasting. For this the principle and process of inverse GM model are studied according the grey GM model. Then inverse GM model is used in the in simulation of system dynamic of water pollutions to create the differential equations and simulate and forecast the future behaviors. The application case verifies the method of inverse GM model.

In this study, the path planning problem in 3D automated optical inspection (AOI) machines is considered. In the problem, the primary objective is finding a path that minimizes the total working time among all possible paths for the camera. In 3D AOI machines, a very precise level of image processing has to be performed when inspecting the mounted components on printed circuit boards (PCBs). Therefore, both the routing time of the camera path and the image processing time have to be considered when calculating the total working time of the camera in the AOI machines. In this paper, we propose efficient heuristic algorithms that can find the paths that have the shortest total working times. The performances of the proposed methods primarily depend on the NEH-based procedure, which is one of our proposed improvement procedures. We introduce several construction and improvement procedures, and select the best combination as our proposed approach. The results of computational experiments conducted on real data to evaluate the performance of our proposed approach show that our proposed methods improve on the original path planning performances. In addition, tests done on randomly generated data indicate that our proposed approach is superior to other benchmark approaches, including metaheuristic algorithms, in terms of computing time and performance measures.

In this paper, a modified fuzzy logic control for integrated vehicle dynamics control is presented. This modification is derived from incorporating data exponential forgetting technique into the standard fuzzy controller. The proposed controller is capable of adjusting the robustness of the fuzzy logic controller based on operating conditions, considering uncertainties and nonlinear characteristics of vehicle dynamics. The controller uses yaw rate and side slip angle errors and their integrals as inputs in order to compute the total yaw moment and lateral force required for desired responses. The subsystems considered in the integrated control system are active steering and direct yaw moment controls. To show the efficiency of the proposed controller and also to investigate the benefits of the modified controller over the standard fuzzy logic control schemes simulation during a severe lane change maneuver are executed. Simulation results reveal that the proposed controller can effectively enhance the vehicle stability and handling performances, and also show the advantages of modified controller compared to the standard form.

This paper has tested a possibility of securing the braking force in constant power region and the constant torque which is expanded by braking test for small scaled test equipment. Consequently, as securing the braking power with just electric brake in high speed region with expanding the constant torque region and the constant power region, M car can use the pure electric braking because of electric brake of all speed regions. If it is possible to decrease the components which is concerned with air braking decreasing the opportunities to use, the effects of the diminished the weight of vehicle can be expected. The reduction effect of maintenance cost for brake parts can be brought, and the full electric braking in electric rail car can give a good riding comfortableness to passengers, energy efficiency and noise seduction.

The rolling bearing vibration is a complex, non-stationary and dynamic process. The vibration signal can not be described through a fixed time or frequency function. This increases the difficulty of fault diagnosis. Therefore, this paper proposed a rolling bearing fault diagnosis method based on local mean decomposition (LMD) and time-frequency analysis. Firstly, we need to draw time-domain waveform and power spectrum of vibration signal in this method. Secondly, we can gain the energy density distribution of signal using directly time-frequency analysis of signal, the time-frequency analysis of intrinsic mode function (IMF) and the time-frequency analysis of production function (PF). We gain the IMF by decomposing the original signal by the ensemble empirical mode decomposition (EEMD).and after the original signal is decomposed by the local mean decomposition,we gain the PF .Finally, according to the energy density distribution of signal, diagnose the fault of the rolling bearing. The simulation results show that we can gain the clearer the energy density distribution using the time-frequency of PF of signal to diagnose fault and improve the reliability of the fault diagnosis

This paper aims to enhance efficiency of management through physical, logical consumer channel clustering and reliability on metering reading data, and achieve expandability of wireless metering reading network through channel use that can be identified between proximate clusters, by suggesting channel set-up based on multichannel cluster mixed with network channel and group channel to resolve the problems and implement various services. Further, the article aims to reduce installment time and maintenance repair cost through hierarchical network structure composed with four differentiated devices in wireless AMR systems, and suggest wireless AMR network based on multichannel cluster substantializing various services by supporting various movement modes through quick error recovery and back up functions. The AMI Network is based on multichannel cluster mixed with network channels and group channels, which increases management efficiency through channel clustering of physical, logical consumer, and enhances reliability on meter reading data through channel use which can be identified between geographically proximate clusters.

In this paper, three speech codecs; G.729 (8 kbps), Speex (8kbps) and GSM (13kbps) were tested together with several predetermined SNR value ranging from 10dB to 45dB with a sample of 8 second speech. VoIP QoS such as packet jitter is analyzed in order to make a comparison of speech quality of those three speech codecs in wireless LAN 802.11g environment. Result shows that at lower SNR, GSM achieve higher packet jitter than that G.729 and Speex. At higher SNR, GSM achieves lower packet jitter as compared than that G.729 and Speex.