Earticle

Recently, with the development of wireless communication technology and the wide usage of mobile devices such as PDAs, netbooks, and smart phones, interests on mobile P2P networks have been increased. Location based routing schemes considering the mobility of mobile devices in order to provide mobile P2P services were proposed. However, the existing schemes cause high communication costs since they broadcast the messages to a whole network to create routing paths. In this paper, we propose a new location based routing scheme to efficiently create routing paths along with the mobility of mobile devices. The proposed scheme maintains the information of peers within 2-hop in order to reduce the costs of routing path searches. The proposed scheme searches the routing path considering the directionality of the destination peer and maintains it using the connectivity of peers. It was shown through performance evaluation that the proposed scheme outperforms the existing schemes.

In this paper, I have revised and supplement the Greenhouse Control System (GCS) proposed by existing. In addition, we studied the detailed design of the Greenhouse Control Engine (GCE) which is one of the engine that make up the GCS. GCE was designed to place the purpose of minimizing the cost consumed by the control device in the operation for the optimal control of the crop growth environment. The GCE consist of Data Aggregator (DA) to collect information of the greenhouse, Greenhouse Information Storage (GIS) stores the collected information, and Greenhouse Control Agent (GCA) is based on analysis of stored data and considering energy-efficient select the appropriate control devices. Also, this engine provides the greenhouse environment information collection and analysis service and the control device select service. And tested the designed GCE through the test bed.

A computational algorithm is proposed to solve a class of nonlinear optimal control problems. The proposed algorithm is based on replacing the original nonlinear optimal control problem by a sequence of time-varying linear quadratic optimal control problems. This is accomplished by employing an iterative technique developed by Banks [1-5] which is based on replacing the original nonlinear system by a sequence of linear time-varying systems. Then each of the time-varying linear quadratic optimal control problems is transformed into a standard quadratic programming problem by parameterizing the state variables by a finite length Legendre polynomials with unknown parameters. The solution of a standard nonlinear optimal control problem is presented, to show the effectiveness of the proposed method.

In this study, a marine navigation is proposed in order to solve problems including deviation from the route while a marine leisure ship is sailing, which gives a prior guide about expected route deviation at a real time through searching or makes it returned to the main routes from deviated areas when it is deviated from the navigated route. The proposed system is set with main routes and auxiliary ones. The latter provides the former with a prior guide about positions tended to be deviated while a ship is being sailed. Therefore, it has both of the functions to prevent route deviation in advance and to guide and make a ship returned to main routes from deviated ones by measuring the position of the ship until auxiliary routes and main ones are the same when the ship is deviated from the route. Also, the proposed system can increase convenience and safety of a marine leisure ship by reducing the time for the route search server to search the routes from the deviated positions to the destinations and to transmit the information about them.

Comparing to the big volume, large weight and high power consumption of the conventional samplers which are fixed on the lunar rover, the paper firstly described a novel flexible mini lunar sampling robot. Then the nonlinear dynamics resonance broken system is built to model the contact between the sampling robot and the lunar regolith. It is found to be suitable for drilling when the sampling robot is in the resonance condition. For the nonlinear time-varying system of the dynamic modeling of the sampler in drilling, we presented the method of the frequency neural-fuzzy adaptive control based on the dynamic resonant frequency prediction of the flexible sampling robot using neural networks. Firstly the algorithm predicts the dynamic resonant frequency of the sampling robot by GRNN. Then a neural-fuzzy adaptive control system is established, in which the frequency prediction error, the amplitude and its variable are adopted as the input and the sweep frequency bandwidth as the output, to adjust the frequency bandwidth dynamically. What’s more, the simulation results verify the effectiveness of the control strategy. Finally, the experimental results show that the control algorithm can improve the drilling depth, drilling efficiency and the discarding efficiency by 66.7%, 65.2% and 67.4%, respectively, in stimulant lunar regolith.

Monitoring the aircraft engine fuel flow is critical to the flight safety and the aircraft maintenance economy. Aim at predicting the aircraft engine fuel flow accurately and quickly, an aircraft engine fuel flow prediction method based on the process neural network is proposed in this paper. The learning speed of the existing learning algorithms (e.g. BP learning algorithm) for process neural network is too slow for the practical application. A Levenberg-Marquardt learning algorithm based on the expansion of the orthogonal basis functions is developed to raise the adaptability of the process neural network to the real problems. Finally, the proposed prediction method with the corresponding learning algorithm is utilized to predict the fuel flow of some aircraft engine, the results indicate that the proposed prediction method seems to perform well and appears suitable for using as an aircraft engine health condition monitoring tool, and the comparative results also indicate that the Levenberg-Marquardt learning algorithm has a faster learning convergence speed and a higher prediction accuracy than the BP learning algorithm.

Indoor location based service (ILBS) is one of the current hottest research issues. ILBS cannot be realized without indoor positioning solutions. Among the many existing indoor positioning methods, the Wireless Local Area Network (WLAN) based trilateration is one of the most economic and easiest methods to be installed. The WLAN-based trilateration estimates the distance between an access point (AP) and a mobile device with the signal strength of the signal from the AP. Then, the WLAN-based trilateration estimates the location of the mobile device with the estimated distances and the coordinates of the APs. The first contribution of this paper is to propose a floor map repository that allows users to upload floor map files (AutoCAD files) and register coordinates of APs so that any software developer can use them after getting authorization. One of the drawbacks of the trilateration is its inaccuracy. The RF (radio frequency) signals between APs and a mobile device are very sensitive to the noise and the estimated distances are very inaccurate. The second contribution of this paper is that after discussing the pros and cons of various modified versions of trilateration, we find our own solution for indoor positioning and implement and publish our solution as a web service so that any software developer can use it.

In PWM system, the reflected voltage in the cable transmission process generates overvoltage and damps high-frequency ringing at motor terminals and further stresses the motor insulation, even leads to insulation breakdown in premature period. Firstly, in this paper, the cable equivalent mathematical model was established based on three-phase cable. Then the propagation velocity, the oscillation frequency and the oscillation duration of the pulse in the cable was described by mathematical method, and the effects of cable parameters on over-voltage at motor terminals was analyzed under the conditions of high-frequency. Secondly depending on the simulation by PSpice software, we tested and verified the conclusion by building simulation models.

Lithium power battery as the power source of the electric vehicle in series and parallel way, due to the performances of each monomer battery are inconsistent, it will seriously influence on the performance of the battery charges and discharges, and the incomplete consistency of the battery internal resistance is one of the reasons that affect these differences. In order to obtain the internal resistance of electric vehicle lithium power battery accurately, this article uses the FreedomCAR equivalent circuit model, adopting multiple linear regression algorithm which based on LINEST function. And the model and algorithm are verified and tested, the experimental results show that if adjusting the polarization time parameter constantly, we may reduce the estimation error, and we can calculate the internal resistance of the battery accurately.

In order to study the on-line fault monitoring and diagnosing for the rolling bearing this paper proposes a resonant demodulation measurement with an adaptive frequency selection based on LabVIEW. The wavelet packet function is used to decompose and reconstruct the measured vibration signal to extract the fault information accurately under the noise background. The kurtosis value of the signal within the range of all frequency bands is calculated and compared automatically to select a resonance frequency band containing the fault frequency. The fault frequency can be extracted by using the resonance demodulation and then the fault element can be identified. The experimental results show that the fault diagnosis result is the same as the fault simulation of the rolling bearing inner ring on the test bench.

In this paper, we present the review of energy harvesting contained in electromagnetic waves. An overview of existing energy harvesting techniques is discussed, which will motivate researchers to design antenna in the field of electromagnetic energy harvesting. It also focuses on a characteristic of patch antenna for designing Rectenna.

Many new concepts have recently been developed for human–computer interfaces. Xbox, introduced by Microsoft, is a game console. Kinect is a low-cost device that supports multiple speakers, a microphone, a red-green-blue camera, and a depth sensor camera for motion recognition. In the beginning, Kinect was developed for Xbox, but then supported various functions for the Windows operating system (OS). Similar to a Smart TV interface, in this study, we propose an intelligent interface for the Windows OS using Microsoft Kinect. Instead of using a mouse or keyboard, the interface helps humans interact with the computer using voice and hand gesture recognition. To interact with our system, users first register their voice commands in our recognition system, and then utilize those registered commands control the Windows OS. Our proposed system also provides scalability and flexibility and was assessed with a high level of recognition rate and user’s satisfaction.

In order to get the vehicle' actual driving mode in a different road conditions, the driving data is divided into kinematic sequence for analysis of driving cycle. On the basis of kinematics fragments, the characteristic parameters of kinematic sequence are carried out with the principal component analysis. Then driving cycle are synthesized based on dynamic clustering algorithm analysis to get the vehicle' driving state in different road conditions.

The competition in the processing market of the domestic machinery parts has been getting intensified along with the economic development. First, corporations are demanding aggressive activities of production cost reduction for the sake of survival rather than profit generation. Such issues as production process, production time reduction, multi-functional structural change of possessed machinery, eco- friendly process development, etc. are emerging as imminent tasks. To resolve such issues, a variety of research theses from various perspectives have been published. The problem is the diversification of the parts processing method. In other words, it is the multi-kinds & small-scale production method. In the past, there had been an attempt to increase competitiveness through the non-cutting issues such as tool preparation time, tool replacement time, etc.; however, the time spent on the cutting process has been prolonged in recent days. Thus, there has been a demand for a direct solution as to the processing process, and the processing method by hard turning is being presented as the solution. This study analyzed the correlation of cutting force, tool abrasion, surface profile in accordance with the processing conditions using SKD11 in order to determine the optimal conditions at hard turning.

This paper proposes a new relay selection scheme for wireless cooperative networks that effectively distributes the traffic of packets from the source nodes to the sink. By estimating the channel information of the two-hop neighbors, the source node can choose the most optimal relay node to forward its messages on the basis of the transmission rate of the channels from the source to the relay and from the relay to the destination. The simulation results indicate that our scheme is efficient in increasing the packet delivery ratio, decreasing the average energy consumption, and decreasing the end-to-end delay.

Optimal reactive power flow (OPRF) reduces power system losses and provides better system voltage control by adjusting the reactive power control variables. It has significant influence on economic and secure operation of power systems. In this article, an improved biogeography-based optimization algorithm based on local search strategy (ILSBBO) is presented for solving optimal reactive power flow. The proposed method integrates local search strategy and selection operation of differential evolution (DE) with migration operator in original BBO to improve the efficiency of migration and overcome the premature convergence in BBO algorithm. It has been applied to standard IEEE 30-bus and IEEE 118-bus test systems, and the comparison results show that the proposed approach is feasible and efficient.

Traditional distributed power control algorithms in cognitive radio networks are based on the assumption of perfect channel estimation which can lead to performance degradation in practical system. Cognitive radio sensor network (CRSN) has emerged as a promising solution to address the spectrum-related challenges of wireless sensor networks (WSN). Moreover, cognitive radio (CR) gives us a possibility to maximize the utilization efficiency of limited spectrum resources. However, because the wireless devices coexist in the same radio environment, there are harmful channel conflicts among users. First at all, this paper presents a practical model of cumulative interferences from the entire cognitive radio based industrial wireless sensor networks (CR-IWSN). Then, based on the interference model, we propose an intelligent power control scheme to address the communication requirements. The simulation results show that the proposed distributed power control scheme can efficiently increase the energy efficiencies as well as the throughput of the CR-IWSN compared with the existing protocols.

Development in technology introduces novel kind of issues like cost optimization, system safety and cyber-attack. In order to solve these issues, sufficient information is needed but generally there is lack of information. We introduce the Bayesian network that is one of the most popular probabilistic methodologies to overcome the limitation of the issues. This paper presents two Bayesian network models related to system optimization and cyber security for specific industry control system to prepare the mobile environment.

The rail running table imposes to the vehicle a forced vibration. It is not smooth but instead it comprises a lot of faults that give to the rail running table a random surface. Furthermore under the primary suspension there are the Unsprung Masses which act without any dumping directly on the track panel. On the contrary the Sprung (Suspended) Masses that are cited above the primary suspension of the vehicle, act through a combination of springs and dumpers on the track. A part of the track mass is also added to the Unsprung Masses, which participates in their motion. The defects with long wavelength, which play a key role, on the dynamic component of the acting loads on the railway track, are analyzed using the second order differential equation of motion. A parametric investigation is performed for the case of an isolated defect

In this paper, we propose an ORB hardware accelerator design. Feature-based SIFT and SURF hardware accelerators that detect features in real-time require high hardware costs. To overcome this disadvantage, an ORB algorithm consisting of simple calculations was designed as the hardware accelerator. A comparison between the proposed ORB hardware accelerator with SIFT and SURF accelerators revealed that the block RAM usage of the former decreased by approximately 25% and 83%, and its slice logic usage decreased by approximately 40% and 68%, respectively. As approximately 9 ms were required for processing, it was verified that the proposed hardware accelerator could perform real-time feature detection.

A 1.1 V 81.8 dB delta-sigma analog-to-digital converter (ADC) is presented. The split time integration technique for implementing multi-bit digital-to-analog converter (DAC) without using DEM has been developed and used. In order to reduce power consumption and area, a successive approximation register (SAR) ADC is employed to function as both multi-bit quantizer and summing adder without using an additional amplifier. The proposed delta-sigma modulator operates at a 640 kHz clock rate and dissipates 850 W with a 1.1 V supply. It achieves 81.8 dB dynamic range (DR), 76.8 dB signal-to-noise and distortion ratio (SNDR) over a 5 kHz signal bandwidth. The core area is 235 m2 in a 45-nm CMOS technology.

It has been shown that the active disturbance rejection control (ADRC), first proposed by Han Jingqing, is very an effective approach to control the uncertain system, whether the plant is linear or nonlinear, time-varying or time-invariant. This paper has quantitatively presented the relation between the observer bandwidth of LESO and the controller’s sampling-period in theory. Moreover, it is proven that the shorter the sampling-period, the higher the control degree of accuracy is for the same plant, and the smaller the plant’s “time-scaling”, the larger the closed-loop control error is for the same sampling-period of controller by simulation. In general, this paper will contribute to improving specific ADRC based controller design and tuning for researchers and practice engineers.

In this paper, we proposed a new error diffusion filter construction method for digital halftoning with random space-filling curve. A random space-filling curve is introduced to incorporate some randomness for regular space-filling curve such as Peano curve and Hilbert curve. Since the round error is propagated to adjacent pixels whose output values have not been determined, the error diffusion filter is not fixed. So, error diffusion filter is determined dynamically according to those adjacent pixels and uniform distribution method about adjacent pixels or single pixel distribution along scanning curve path. We used interpolation technique to these two distribution method to get better quality haftoning results. We showed the experimental results of proposed method.

This paper is to realize an electric power generator utilizing wave force through hydraulic mechanism. The wave power generator using hydraulic mechanism is very useful since it produces energy in the ocean. This experiment used a check valve, oil pressure tube, and generator to embody the wave power generator through hydraulic mechanism. Check valve was used to make the fluid flow in one direction, and oil pressure tube for the movement of the fluid. The volume and pressure of the fluid in the structure were calculated. The factors which affected the volume and pressure of the fluid in the structure were analyzed. And the results from this study shall be applied to the actual marine construction, and utilized in the research for the reinforcement of the structure.

The increase of the phase number of asynchronous electric drive system of vehicles allows not only to improve a number of its technical-and-economic characteristics, but also to create the hybrid traction drives according to scheme “AC Diesel-generator – Commutator – AC induction motor(s)” which will differ fundamentally from the existing ones, and have more simple design and less energy losses (in comparison with analogous existing hybrid drives). These AC hybrid traction drives of novel type are based on the use of the multiphase Diesel generators and non-traditional controlled multiphase induction motors.

Computer games are steadily one of major way to enjoy leisure time. Main goal of game entertainment is to keep the player’s immersion. Thus, balance design taking game difficulty into account has an important role in game design. In recent years, a number of studies tried to adaptive difficulty by using various algorithms which detect player dependent difficulty. Most of these algorithms need customizing itself for each game. Measuring features which determine game difficulty is the major problem of these ways of game balancing. But, it can be easy by using the player’s immersion during playing games. And, player’s immersion is detected by analyzing electroencephalogram (EEG) signals. In this paper, we propose a dynamic game difficulty control system, by using this emotion recognition technique with PAD model by using players’ EEG signals during playing a rhythm game which has three different difficulty levels.

This project is a research of wind speed measurement system, with a high-precision, low-power, whose control core uses the Samsung S3C2410 32-bit microprocessor with high performance, low power consumption. The system adopts the LCD, and can display the current value of wind speed and wind direction which can be transmitted by ZigBee. The system can set up two limit of wind speed corresponding to two alarms, two relay outputs, and any configuration. The system has simple operation, eye-catching display, reliable performance, and can be widely used in meteorology, civil aviation, highway, construction, energy and other industries.

The pure electric vehicle with dual-energy storage system is driven under complex driving states. Owing to its nonlinear model, the fuzzy control is usually used in energy distribution. It is difficult for the conventional fuzzy controller without integral part to eliminate the static errors. Its control effect is not satisfactory. The required power minus actual power is the deviation. The self-adaptive fuzzy PI control adjusts the deviation values through tuning the parameters of PI controller in real time. Its control effect is satisfactory. The results of simulation experiment indicate that the self-adaptive fuzzy PI control is more economical than the fuzzy control under the same driving states.

This paper considers a condition-based maintenance (i.e. CBM) model for the hydro generating unit in the deregulated power system. As the downtime cost of the generating unit varies according to the time-varying electricity price, the economic dependence among the critical component of the generating unit is dynamic. In this paper, the proposed Dynamic-Economic-Dependence and proportional hazards model based CBM policy considers the dynamic economic dependence among components as well as the reliability and the monitoring information of different critical components. An example for the hydro generating unit is presented to verify the effectiveness of the proposed condition based maintenance policy.