Earticle

Mainly targeting at a small-city level road network, this paper builds an in-memory index for fast map matching, one of the most fundamental building blocks for vehicle information services. For the ESRI shape file sequentially storing road objects such as intersections and links, our indexing scheme obtains the offset of each link and creates the corresponding record consisting of link id, two end points, and the offset. Along with node entries, each of which includes all emanating links for a node, this index makes it possible to traverse the shape file just like Dijkstra’s shortest path algorithm, while all index traversal steps are done within memory. The previous location of a vehicle gives the start point of a map match process, significantly reducing the number of links to check if they include a specific point. This scheme particularly helps us to build an analyzer application for a series of spatio- temporal streams such as battery discharge dynamics.

The paper designs and develops a casing cutting robot for the platform decommission. This robot can achieve the sea-bottom casing reclamation duties required by the environment protection acts related to decommissioning of offshore oil plants. The objective of this research work was to investigate and explore the casing cutting robot model for the platform decommission. A 2-linear axis cutting robot is prototyped and a test bench is designed in the laboratory for the research. A surface control system provides remote control functionalities for the operator to command signals and automatic sequences. The robot control system based on Programmable Multi-Axis Controller (PMAC), which makes it easier to be operated. Moreover a Human Machine Interface (HMI) is developed to monitor and control the cutting process conveniently. The laboratory test results show that the robot system developed is very usable and it is working satisfactory for the casing cutting.

Edge detection has been a popular practice in image processing and computer vision applications. Many image processing applications require the discovery of edge details in the gray or color images as a beginning stage of an image processing, vision and understanding. Generally, edge detection on grayscale images is not affluent enough to explain intensity changes. Therefore, we can use color edge information as an important method. Because the result is different when input images are color images or not (grayscale images). The main purpose of the proposed edge detection is to discern significant parts from the normal features in a given image. We assume that intensity varies rapidly in a significant part. There are many color spaces such as RGB, YIQ, and HSV (Hue, Saturation, and Value). In this paper, we conducted edge detection on each color spaces and compared the results. Simulation results show that the HSV color space gives the best detection performance.

It is not enough to recognize the situations which currently occur simply. The current situations have the causes that they get to occur. The causes can just be generated and they can make the situations like the current states while the ones which occurred in the past have continued. Furthermore, if the causes which made the current situations don't disappear, they can continue to stay the same, get worse, or be changed to another situation. Therefore, limiting the range of context awareness to the situations which currently occur can be insufficient as the system which recognizes situations of the everyday world. Therefore, this study aims at problem-solving of two things. First, it recognizes situations without advance information. Second, it infers causes of situations and predicts how the situations will turn out in the future. To solve these problems, this study uses multiple sensor data fusion together using Dempster-Shafer Evidence Theory (DST) and Kalman Filter (KF). It recognizes situations under the conditions without any advance information through DST, infers causes of the current situations, and predicts how the current situations will turn out in the future. At this moment, BPA is important to recognize situations through DST and infer causes and state transition equation plays an important role in predicting arrangement through KF. The study carries out context inference and cause inference using DST. It describes the plan which infers causes of situations without advance information. It calculates required state transition equation to predict the progress of the research and infers how the causes revealed through DST by using it will arrange the current situations in the future by using KF.

We introduce one configuration of a multi rotor Micro Aerial Vehicle (MAV) composed of six rotors. Accurate modeling and robust flight control of the SixRotor MAV are discussed in this work. Rigorous dynamic model of the SixRotor MAV is obtained both in reference and body frame coordinate systems. The main characteristic of this configuration is the gyroscopic effects and aerodynamic torques tend to be cancelled in the trimmed flight due to the unique mechanical structure, and the attitude and translation dynamics are decoupled which is benefit for designing the control scheme. A disturbance compensator based controller using the derived dynamic models is proposed here for robust hovering control. The disturbance compensator based controller designed by regarding the inaccurate part of the model and sensor noises as disturbances. The validity of the proposed control method has been verified through real-time experiments. The experimental results show that the performance of disturbance compensator based controller performs very well under sensor noise and external disturbances, and have more superiority than traditional PID controller.

In this paper, we present a method to optimize packet filtering by genetic algorithm. Packet filtering in our work consists of packet capturing and firewall rules reordering. Genetic algorithm is used to automate rules reordering and the discovery of optimal combination of packet capture configuration, in the framework of PF_RING platform and rules ordering. Our method has been tested in different sizes of network traffic load. Genetic Algorithm evolves configuration based on the recorded throughput rates; the higher the throughput the better the solution. Results obtained indicate the effectiveness of the approach.

This paper proposes a water quality monitoring system of underwater robot with self-test and diagnosis capability. The system consists of underwater robot, water quality data collection module, self-test and diagnosis module, wireless communication module, and shore-based facility. The measurement results from each sensor of water quality data collection module are transmitted to the built-in micro-processor of the underwater robot. And the self-test and diagnosis module based on DSP connects with the built-in microprocessor through RS232. The self-test and diagnosis module conducts wavelet transform for the sensor information, generating extreme points of the wavelet transform, which are used to detect the abnormal state of the current system. The threshold method is introduced to reduce the influence of the noise. The disturbance of the noise can be alleviated by setting threshold for high frequency parameters of the wavelet transform. The exceptional information was detected by the self-test module and the water quality data information was transmitted to the shore- based facility through the wireless communication module. The shore-based facility can process, analyze and determine the collected information, and then give feedback to the underwater robot. The feasibility of the system design and the rationality of the water quality parameter measurement results were verified by experiments and on-site tests.

Ce-ZSM-5 catalyst has been successfully synthesized and studied for NO oxidation to NO2. Ce-ZSM-5 at various Ce % such as 5, 10, 15% were synthesized and characterized using various physiochemical analytical techniques like Diffuse reflectance UV spectroscopy (UV- DRS), Brunauer Emmett Teller (BET) technique, Differential Scanning Calorimetri (DSC), Thermo gravimetric analysis (TGA), powder XRD and scanning electron microscopy (SEM). Form the results it was noted the successful inclusion of Cerium oxide over the ZSM-5 used. Among the synthesized Ce-ZSM-5, ZSM-5 with 15% Ce loading was shown better activity towords the conversion of NO-NO2. Around 50 % of NO was converted into NO2.

In this paper, we present a method of determining the parameters of a dynamic system using state estimate filter. State estimate filters such as Extended Kalman filter and the Unscented Kalman filter are widely used to estimate the status in robot and GPS navigation systems. However, in dynamic systems, determining parameters is difficult because many kinds of the dynamic systems have the properties like a non-linearity and complexity. The work we have done is that the status and parameters are simultaneously estimated to decide the parameter value based on the measurement data set of the system. The works were applied to a coupled tank. The mentioned system was modeled and then setup for computer simulations and experimental purposes to test the performance of the estimation process.

The artificial fish swarm algorithm (AFSA) is a heuristic global optimization technique based on population which is easy to understand, good robustness, and not insensitive to initial values. The behavior of fishes has a great impact on the performance of the algorithm, such as global search and convergence speed. At present, there has no general research theory to select behaviors of fishes. In order to deal with this problem, we proposed an improved artificial fish swarm algorithm based on hybrid behavior selection. There are two mainly works in this paper. Firstly, we propose an improved algorithm based on swallowed behavior, which can greatly speed up the convergence. Secondly, in order to deal with the problems of easy to fall into local optimum value, we added breeding behavior to improve global optimization capability. The experiments on high dimensional function optimization showed that the improved algorithm has more powerful global exploration ability and faster convergence speed.

Spectrum-based Fault Localization (SBFL) has been proven to be an effective technique to locate faulty statement in program code. SBFL metrics exploit the records of statement execution (spectra) by pass and fail test cases for each statement to rank its likeliness to be faulty. However, in some cases, these spectra contain duplicated and ambiguous information or noise which may deteriorate the performance of SBFL metrics. We propose six noise reduction schemes to eliminate test cases which provide duplicated and ambiguous information and evaluate the resulting performance improvements in SBFL metrics. Based on our findings, we further provide a guide for SBFL practitioners to select the best performing noise reduction scheme for the SBFL metrics that they use.

This paper proposes a framework to design an automatic control system of a plant factory based on artificial neural network (ANN) and presents the simulation results of the proposed system. The proposed system can collect information of crop cultivation environment and monitor it in real-time by using various environment sensors. Installed wire or wireless sensor nodes, based on the sensor network, collect the growing condition's information such as temperature, humidity, CO2, and the control system is to monitor the control devices by using ANN. The proposed automatic control system provides that users can control all equipments installed on the plant factory directly or remotely and the equipments can be controlled automatically. The simulation results show the application possibility of the proposed system in a plant factory.

When performing railroad maintenance work on the railroad, the train watchmen give information of train access to railroad maintenance workers by radio through hand-signals and/or a radio. These existing methods have the possibility of making errors of information delivery due to weather situation, work structures or obstacles, and because railroad maintenance workers usually concentrate on their work, many chances are that they would not recognize the access of trains. In order to reduce the risk of railway traffic accidents of death and injury for track workers, this paper has developed a system that notifies track workers of train approaching information by combining the GPS location providing function of the smart phone and a notification system. The developed system does not need the construction of an independent wireless communication system, and is designed to notify track workers of train approaching information by using a simple Bluetooth module and safety jackets. Also, the system establishes a simple communication possible by using the bluetooth equipped in the smart phone between the alarm system and smart phones. If the proposed system is in use, it is expected that it can contribute to the prevention and reduction of railroad accidents of railroad maintenance workers by preventing accidents of railroad maintenance workers and securing their safety.

In electric vehicles EV, can be implemented a controller has highest extend of battery’s lifetime meet a superior dynamic speed behavior? This research offer multi-objective approaching planned by a Particle Swarm Optimization (PSO) complementary with Genetic Algorithm (GA). This hybrid evolutionary learning is utilized as an automated method to generate the optimal parameters of fuzzy logic controller (FLC) type Mamdani. The Pareto front characterizes the speed controller of an Induction Motor (IM). where the first function is the error between the actual speed and desired speed, and the other function is the energy dissipated from the electrical supply during (10 sec), in present work the multi-objective optimization of PSO and GA have been implemented separately using two M-file/MATLAB, and compacted the results to sketch the global Pareto, while the evaluation of “fitness functions” of the two computational algorithms have been determined using SIMULINK- MATLAB, the simulation has a completely mathematical model of induction motor IM, voltage source inverter VSI and FLC. The FLC have been implemented using RSLogix 5000. The empirical results demonstrate that the proposed method realized a limited disbursed energy as possible as better dynamic behavior of the IM speed along the Pareto front.

According to the dynamic characteristics of doubly-fed induction generator (DFIG) which is changing with the wind speed, the dynamic mathematical models of DFIG wind turbines major subsystems’ have been established, which includes the aerodynamic subsystem, drive train subsystem and generator subsystem. The whole nonlinear time-varying parameters dynamic mathematical model would be obtained to integrate the major subsystems’ dynamic mathematical models, and the whole linear time-varying parameters dynamic mathematical model can be obtained to linearize the whole linear time-varying parameters dynamic mathematical model. To take the 2MW DFIG wind turbine as example, the proposed model is validated by the study on the dynamic characteristics of DFIG with wind speed variation, and the results show that the proposed model could provide a theoretical support for optimal control of the DFIG wind turbines.

This paper considers the shortest path problem on directed acyclic graphs, where the uncertainty of input data (lengths of arcs) is modeled in the form of intervals. In order to handle the interval data the minmax criterion to the regret values is applied, where the original objective function with interval coefficients is transformed into that of finding the least maximum worst-case regret, which is called the minmax regret criterion. A heuristic algorithm exploiting properties to reduce the computational times and to improve the solution quality is developed and its performance is shown with computational experiments.

In this work, ZSM-5, a size selective heterogeneous catalyst was employed for the synthesis of p-xylen from durene by cracking. The reaction was carried out in gas phase using a fix bed reactor. During the reaction, benzene was used as solvent together with durene. To optimize the reaction conditions, temperature, feed ratio, feed flow rate, reaction time and catalyst load weight were investigated. The products were analyzed by gas chromatography (GC). The selectivity of p-xylene and the conversion of durene was 20.04% and 40.09% respectively when the reaction was carried out at 450 ˚C for 1 h using 1.0 g catalyst with feed ratio 1: 8 and flow rate 2.0 ml/h.

The goal of any temperature controller design is to keep the temperature of the target device on the desired value defined by the user as accurately as possible and using as little energy as possible. . The very control of temperature can be achieved by causing heater power to be simply switched on and off according to an under or over temperature condition respectively. Ultimately, the heater power will be regulated to achieve a desired system temperature but refinement can be employed to enhance the control accuracy. The temperature process is highly nonlinear and design of robust controllers for such nonlinear systems is a challenge. This paper proposes a novel method for the control of temperature process. The traditional PI controllers which are in practice produce high overshoot and the design procedure seems complex. The proposed intelligent controller offers better performance in terms of overshoot and settling time and thus increases the robustness of the system. This paper describes the modeling of the temperature process in detail and discusses how the process responds to conventional and intelligent controllers.

In vehicular ad-hoc networks (VANETs), vehicles move highly and non-randomly along roads while exchanging information with other vehicles. Rapid movement of vehicles and frequent topology changes cause repeated link breakages, increasing the packet loss rate. Because of these characteristics, routing protocols based on greedy forwarding such as greedy perimeter stateless routing (GPSR) are known to be very suitable for VANETs. Greedy forwarding based routing protocols select the vehicle nearest to the destination as a relay vehicle within the transmission range of the sender vehicle. Therefore, it is challenging for selecting the next relay vehicle in a low density of vehicles. To this end, we propose a route -aware delay tolerant routing (RADTR) protocol by combing greedy forwarding and store- carry-forwarding for spare VANETs such as the early morning hours. RADTR uses map data to generate a scheduled route and to predict the moving position during the relay node selection process. And each vehicle is assumed to be aware of its route to its destination and a route is specified by a sequence of its scheduled roads. Simulation results using ns-2 revealed that RADTR performs much better than the existing routing protocols in sparse VANETs.

New mesoporous silica nanoparticle (MSNs) with high surface area and pore volume has been synthesized successfully using TritonX-100 as main and Tween 60 as co-template (at various concentrations). Ibuprofen a water insoluble model drug was loaded into the synthesized silica nanoparticle and studied for sustained release capability. All the as synthesized and drug loaded nanoparticle were characterized using physicochemical techniques such as FTIR, Difuse reflectance UV spectroscopy(UV-DRS), Brunauer Emmett Teller (BET) technique, Differential Scanning Calorimetri ( DSC ),Thermo gravimetric analysis (TGA), powder XRD and scanning electron microscopy( SEM) for the morphology and drug loading. From the results it was noted that all the silica nanoparticle synthesized by sol-gel method were mesoporous with high surface area and pore volume (1024.3, 1056.2 and 1083.6 m2 g-1 and 0.9229, 0.9904 and 0.8468 for TW6-1rt, TW6-2rt and TW6-3rt respectively) and have the capability of up taking 32 % ibuprofen model drug further they shows initial burst release for 50h followed by sustained maintenance of dose even after 150h.

Recently, IoT(Internet of Things) applications based on actuator networks not only need an appropriate way for representing information about actuator’s characteristics but also a common information for managing the involved elements. This paper presents the profiling architecture based on Web services for supporting configuration management in actuator networks. We design and implement a profile management tool based on XML (Extensible Markup Language) for representing actuator descriptions as well as the flow chart for generating and editing the actuator configuration profile in actuator networks.

To aim at some large-size complex equipments widely used in industrial enterprises, this paper analyzed the operation maintenance and management feature, and established the full life cycle model with four states, and then performed the reliability and security analysis on it. During modeling we not only considered all the possibly emerging states of the equipment such as working, storage, preventive maintenance, and corrective maintenance, but also still conducted the detailed analysis on the transfer relations among these states. Based on it, we constructed the non-Markov process model of the equipment, where the checking and repairing time were considered to follow the arbitrary distribution during preventive maintenance and corrective maintenance, and the failure time distribution was thought to be exponential. Hence, by the use of supplementary variables, we converted the non-Markov model into the Markov process model, and calculated the relative reliability and security indexes. Compared with classical two-state and three-state models, the results show the established model is accurate and effective, and possesses a broad adaptability.

According to embedded IP core structure and various DFT strategies, it is difficult to test NoC-based SoC especially for reuse situation. The paper proposes the design of a compatible IEEE 1500 standard core test wrapper, which makes different IP cores homogeneous from the point of test integration. A test response comparator is added to the test wrapper, which is capable of verifying directly whether there is failure in this IP. The comparator not only improves testing efficiency and also supports various test modes. The function and timing simulation of proposed wrapper are accomplished on ISCAS '89 circuits. A 2D Mesh NoC was constructed based on these wrappered IP cores and implemented unicast and multicast testing. The experimental results show that the wrapper can effectively realize embedded IP test access and isolation, and has the good adaptability to support various NoC test strategies.

The output current of grid-connected PV inverters should not excess harmonic contents. Also, because they are driven connected with grid, the reliability of electric power’s quality should be secured. But, the current controllers of the grid-connected PV inverter decrease the electric power’s quality due to not considering the harmonic contents of the output current. This paper proposed the current controllers of the grid-connected PV inverters to supplement the decrease of the electric power’s quality because of the harmonic contents of the electric power’s quality and the harmonic contents of the output current. The proposed current controllers controlled the harmonic contents of the output current by controlling gains of the current controllers in consideration of the harmonic contents of the output current. As a result, when total harmonic distributions of the grid voltage were 0.4% and 4.1%, the excellence of the proposed current controllers was shown through the experience, by obtaining excellent results of being controlled low as the total harmonic distributions of the output current were 0.756% and 0.78% respectively.

With the development of numerical reservoir simulation technology, numerical simulation has been widely applied to studies on the mechanics of all chemical flooding and injection approaches. In this study, a mathematical model for three-dimensional two-phase six-component deep profile control with weak gel is established based on the mechanics of deep profile control with weak gel. The established model takes diffusion, crosslinking reaction, adsorption, degradation and other physical or chemical phenomena into consideration. A numerical simulation software for deep profile control with gel was created with FOR99 programming language. Using this software, we performed optimization on the slug combination and slug size for the intra-flooding deep profile control with gel in ASP flooding for Xingbei development zone of Daqing oil field. The analysis on the mechanics of deep profile control with gel demonstrated that the addition of the profile control system could strengthen the profile adjustment effect. After the crosslinking system is injected into oil layer, less displacing fluid could enter the high-permeability layers, stimulating more displacing fluid to enter moderate or low-permeability layers, thereby the oil displacement effect is improved.

A coding and decoding scheme controlling run length is presented. The proposed scheme limits the run length of data 0 in digital communication systems. We present a transformation approach to reduce the implementation complexity. The new adaptive scheme is implemented by combining the tree structure model and the candidate space model.

In this paper, a mathematical model for non-Darcy flow in low permeability oil reservoirs is developed, considering the threshold pressure gradient. The model is then discretized into difference equations and solved. FORTAN99 language is used to program the 3D three-phase numerical model for non-Darcy flow in the simulation software. FORTAN99 is used, because it is fast when performing huge engineering calculations. The pre and post processing system for the simulation software is developed using DELPHI language, because it has good interface with WINDOWS and has ability to manage databases. Numerical simulation is done in the simulation software combined with actual data from Yushulin low permeability oilfield. The effects of threshold pressure gradient, well spacing, and water injection modes are investigated. Results show that as the permeability increases from 1×10-3μm2 to 12×10-3μm2, the sweep efficiency and the water displacement recovery also increases significantly. When the permeability of reservoir is fixed at 5×10-3μm2, the threshold pressure gradient increases as the well spacing decreases from 350m to 150m. Compared with the inverted nine spot water injection pattern, the sweep efficiencies for the line water injection pattern and the five-spot water injection pattern increase by 6.64% and 7.78%, respectively. The water displacement recoveries for them are increased by 2.94% and 3.57%, respectively.

In order to meet the recently enhanced emission standards at home and abroad, it is necessary to develop the CRDI ECU control algorithm that users can adjust fuel injection timing and amount in response to their needs. Therefore, this study developed the simulator for knocking analysis that enables knocking discrimination and engine balance correction applicable to the ECU exclusive to the industrial CRDI engine. The purpose of this study is to provide the driver-oriented diagnostic services that enable drivers to diagnose vehicles directly by developing diagnostic devices for vehicles with the use of the results of the developed simulator for knocking analysis according to the OBD II standards. For this purpose, this study aims to improve the fuel efficiency of vehicles by proposing the S/W design method of the OBD-II diagnosis device that can provide real-time communications with the use of wired system and bluetooth module as a wireless system to send and receive automobile fault diagnosis signal and sensor output signal, and to suggest an improvement for engine efficiency by minimizing the generation of harmful exhaust gas

This paper presents DTV transmitter design based on the SW/HW hybrid architecture. Parts of the DTV transmission algorithm with less computational complexity are processed by the SW module in PC whereas computationally intensive parts are processed by the HW module in FPGA. The two parts are interconnected by the high speed serial link. To provide the multi-channel DTV signal, we design an architecture where several DTV waveforms are generated simultaneously and combined in the digital domain. We propose a simulink based communication system design and verification methodology. This method reduces the design and verification time of the prototype system significantly and reduces the RTL coding and verification burden.