Aiming at the problem of print defect detection, this paper presents a defect detection system based on image processing. The system collects print image pictures by CCD camera and sends those pictures to the computer. After receiving pictures, the image processing software called VS2010 which is based on OPENCV processes the received pictures and extracts defective pictures by background difference method. The experimental results show that the algorithm can accurately identify the defect print and meet the system design requirements.
The aim of this study is to investigate the relationship between new human resource management (NHRM) practices and innovation performance. Further, the moderating role of IT ambidexterity was examined between NHRM and innovation performance. This study selected Pakistan's largest IT based semi-government organization National Database & Registration Authority (NADRA) as a case study. Data was collected from three major cities (Lahore, Gujranwala and Jhelum) of Pakistan. 500 employees of NADRA participated in the survey based study. The empirical results found the positive relationship between NHRM practices and innovation performance. The moderating influence of IT ambidexterity was also found in this study. Employees with high IT ambidexterity are more involved in innovation performance. Continuous adaption of technology enhances long term competitive advantage. Therefore, utilizing new technologies and knowledge consistently, is significant for the enhancement of innovation performance.
The droplets constant culturing analyzer based on microfluidic chip control is a device that cut the bacterial fluid into 800 microns long columnar droplets in parallel to culture, in order to realize real-time monitor and control paraments like pH and specific chemical factors of each parallel segments. The instrument can perform micro-droplet segmentation, fresh medium droplet generation, electric fusion of new micro-drops function, realizing the cell culture and passage operation of micro-droplet, thus realizing the function of microbial amplification and mutation adaptation evolution of microorganisms.
In order to ensure that the UAV online route planning results meet the terminal constraints of the task, a rolling optimization algorithm based on C/FD-GMRES for UAV online route planning is designed. The C/FD-GMRES is a real-time nonlinear receding horizon control approach; combining the homotopy continuation method differential approximation generalized minimum residual method instead of solving complex Riccati differential equations. At each sampling time, the C/FD-GMRES calculate a residual vector linear equation once and the product of Jacobi matrix and vector product is approximated to the forward difference, the GMRES fast algorithm is used to solve large scale linear equations in the end. The C/FD-GMRES method has a good real-time performance, not sensitive to the selection of initial estimates, and can meet the need of UAV terminal state constraints. Simulation results show that the algorithm can effectively avoid barriers of space and the planned trajectory can converge to a stable terminal state, meeting the real-time requirements.
Time-varying formation control problems for unmanned aerial vehicle (UAV) systems based on position estimation are investigated. Firstly, a distributed formation controller based on the estimator is proposed using only relative state information of neighbors. The stability can be guaranteed by proper parameters and it can be proven that the control input is able to drive the UAVs to the predefined formation. Secondly, extra item for inner collision avoidance is added to the control strategy, and the stability can be proven by using common Lyapunov approach. Finally, numerical simulations are provided to illustrate the effectiveness of the theoretical results.
Map-matching is the process to match a sequence of real world coordinates into a digital map, so as to identify the correct segment on which a vehicle is traveling and to determine the vehicle location on the segment. Map matching is one of the key components to model and analyze floating car data, and provide ITS services such as traffic condition analysis and navigation. Complex environment, inadequate attribute information, low sampling frequency, and location deviation exert great influence on the matching performance. This paper presents an improved map-matching algorithm based on Hidden-Markov model. A distance based weighted-average method is applied to improve the quality of the instantaneous GPS data, and a preprocessing and caching method for the shortest paths is used to accelerate the calculation of state transition probability. Comparative analyses show that more than 90% of positions are matched, and computation time is significantly improved.
In order to solve the problem of noise error in the process of vehicle vibration displacement, a new method of multi-scale wavelet transform reconstruction acceleration is proposed. this method makes full use of characteristics of wavelet transform in multi-scales. According to frequency range of low-frequency noise to determine the number of decomposition, while to removal high-frequency noise using the correlation between wavelet scales, reconstruct acceleration which has removed the signal noise, then integrate to get the vibration displacement. The simulation analysis results show that the method can be used to measure the vehicle vibration displacement accurately.
dSPACE based hardware-in-the-loop (HIL) missile control system simulation platform with the key benefits of powerful operational capability and convenient hardware interface is provided. The system structure design and development steps were analyzed. In the platform, the compiled simulation model, established in the MATLAB/Simulink, runs on the real-time hardware platform, and the actuator as the real physical part. This platform realized the HIL design and simulation, and the simulation process is similar to the real environment. Experimental results showed that the dSPACE based real-time simulation system is an excellent platform for missile control system design which enhanced the efficiency and reliability.
Today's fixed-cycle traffic signaling is highly suboptimal and aggregates traffic congestion and waste of energy in urban areas. In addition, it offers no quality-of-service guarantee and makes travel time prediction extremely hard. While existing traffic light control research primarily focuses on improving the average wait time of cars, we study in this paper how traffic light scheduling affects the worst-case wait time. In particular, we derive the time a car spends at an intersection in the best-case and the worst-case, respectively. Using the theoretical results, we propose a simple but effective controller and run simulation to verify its performance. The result shows that it works much better than fixed-cycle controllers in both light and heavy traffic scenarios.
Distributed drive electric vehicle steering system affect the vehicle handling stability, active safety and ride comfort and other performance. Electric power steering (EPS) is a new vehicle power steering technology, in line with the automotive energy conservation, environmental development theme, consistent with the theme of the development of automotive electronics, intelligent vehicles, and become the focus of attention for domestic and foreign auto industry experts and scholars. The dynamic model of EPS is established, and the influence of the perturbation of parameters such as parameter perturbation, sensor measurement noise and external disturbance in the dynamic model of electric power steering control system is analyzed by using H∞ control theory. In the process of solving controller, the weight function modeling and linear fractional transformation theory deals with these uncertainties and designs the H∞ controller of the steering assist process. The performance of the controller is simulated by Matlab. The simulation results show that the controller has good robust stability and robust performance.
Although the vehicle navigation system based on GNSS/MIMU can effectively improve the reliability and precision of the single navigation system, its application is still restricted by many problems such as expensive equipment, unstable satellite signals and other issues. In order to solve these problems, a vehicle navigation system based on low-cost sensors is designed in this paper. Firstly, the hardware platform of vehicle navigation system based on microcontroller, low-precision MIMU and low-cost GNSS receiver is designed. Then, the model of sensor's error, navigation system's error and vehicle velocity constraint is analyzed, and a vehicle navigation algorithm with dual modes is proposed. When satellite signal is valid, the navigation system works at GNSS/SINS integrated navigation mode based on Kalman filter. While the GNSS is unable to provide navigation information the system switches to SINS mode with the constraint of vehicle velocity. Finally, the feasibility and practicability of vehicle navigation system designed in the paper is verified by vehicle test. The results show that the dynamic accuracy of horizontal position is better than 1.5 meters, the dynamic accuracy of horizontal attitude is better than 0.2 degrees, the dynamic accuracy of azimuth attitude is better than 1.5 degrees and the dynamic accuracy of velocity is better than 0.15 meters per second. In addition, this system can work on the situation of satellite short-term failure, so as to meet the requirements of vehicle navigation in changeable driving environment.
In the fault period of high-speed train lateral damper, the vibration signal is non-linear and nonstationary, and features extracting is relatively difficult. In order to save this problem, a method of features extracting based on variational mode decomposition and multiscale entropy was proposed. The original signal was decomposed into several intrinsic mode function components after being processed by the variational mode decomposition mothed. Then, the best component was selected by the mutual information index. The feature matrix was constructed through the multiscale entropy of the best component, and removed redundant features using feature evaluation algorithm. The fault type of lateral damper was judged by transforming in the best subset of feature matrix in support vector machine. Experimental results show that the proposed method can extract the feature and judge the fault type of lateral damper effectively, which proves the feasibility of this mechanical fault diagnosis method.
Due to the Extensible Business Reporting Language (XBRL) have high compatibility and other features, it is widely used in finance field, as an information disclosure and retrieval tool in the Shanghai and Shenzhen Stock Exchange at present. This article mainly uses normative research and empirical research to discuss the influence of XBRL on quoted accounting information quality. Firstly, this article theoretically discusses the positive effect on the relevance and reliability of quoted company's accounting information, which based on XBRL standard. This article brings into the concept of earnings response coefficient in the process of empirical research, and uses event study method to research the reaction degree of market excess return on unexpected factors of company's financial report. This article uses stratified sampling to select annual report disclosure information of 501 quoted companies in the Shanghai stock market from 2012 to 2015 and uses these samples to do empirical research. The results are as follows, unexpected accounting surplus has positive correlation with earnings response coefficient; the persistence of company surplus has positive correlation with earnings response coefficient; the growth rate of company has positive correlation with earnings response coefficient; the risk variation of company has positive correlation with earnings response coefficient. From the western accounting theory perspective, the earnings response coefficient is larger and the higher of accounting information quality. From the empirical research, to some extent, the implementation of XBRL made a positive effect on our country's quoted company's accounting information quality.
The paper is carried out based on the problem that is not solved by the current Knowledge Inventory systemically. It means science and technology output of Chinese researchers and their international influence of the academy output. To study the scientific issue feasibly, choose the data base from 2007 to 2016 of the most important scientific and technological literature retrieval system of scientific statistics and scientific evaluation with international recognition, SCI as data source and collect the paper data of Chinese researchers which is inspected by SCI. Made use of information to explore the general situation of the science and technology output of Chinese researchers from quantitative to qualitative scientific practice based on the data analysis. Some feasible suggestions are provided to the strategic allocation of scientific talents.
Vehicle detection and recognition is the research focus in Intelligent Transportation System (ITS) with many challenges. Based on the success of Convolutional neural networks (CNN) in object detection and image classification, we propose a ZLCC to locate vehicle and classify its maker & model & shape. Our framework focuses on two new perspectives: (i) how to generate a small number of high quality region proposals, (ii) how to improve vehicle classification accuracy rate by hierarchical learning policy. We use deep network's responses to generate aware-map in detection, and train network with multiple candidates softmax regression. We demonstrate the success of ZLCC on Stanford Cars for using the deep VGG16 architecture.
The health care industry is a vital part of any country and its economy. The health care industry seek increasingly to improve quality by improving clinical outcomes, patient experiences and a business case that support movement toward ‘patient-centered care’. The health care industry by becoming knowledge based community. This can be done by creating communication between many hospitals, clinics, pharmacies, and customers. The sharing of knowledge should be increased, the reduction of administrative costs and improvement in the quality of care. The health care will be able to do this by using knowledge management (KM) and information technology (IT). This research study seeks to come up with a framework that investigates the different dimensions of knowledge management and IT and how it will help in improving health care. In order to come up with a framework the three elements of KM which are knowledge acquisition, knowledge application and knowledge dissemination and use of IT to make it efficient. If properly used IT can accelerate knowledge-sharing capabilities in both time and space dimensions. Locality, timing, and relevancy factors determine the expediency and the strength of IT's role in KM initiatives.
Urban transportation is developing rapidly, which leads to that intelligent traffic is the direction of future traffic. License plate recognition (LPR) technology is one of the key techniques. But in bad weather, images taken by cameras degrade dreadfully, which results in the poorer LPR effect. This paper introduces the propagating deconvolution, dark channel prior and color attenuation prior dehaze algorithms as the pretreatment of LPR, and proposes a license plate location method based on both color and edge information. In addition, this paper compares the influence of various dehaze algorithms on the license plates location.
Ports are quickening the pace of “intelligent port” with informatization exhibiting a strong competitive edge in the area of port operation. One of the challenges in the development is how to analyze the performance of informatizational applications in order to determine the main factors that affect the quality of them. According to the complex port informatizational condition and incomplete data collection, the Grey Correlation Matching Model is proposed to assess the informatization status of ports. This paper constructed the evaluation index, evaluated the index's attributes combining the Analytic Hierarchy Process (AHP), and analyzed the performance of 11 ports to rank order by using the Grey Correlation Matching Model. Compared with the grey target model, the results show that the improved algorithm is more advantageous in dealing with the informatizational assessment. Furthermore, such results can be used in future resource planning stages, at the time of improve the intelligent ports.
In order to improve the safety of motorists and to realize driving automation and unmanned, a road traffic signal recognition system based on the integration of ZigBee network and FRID is designed. Firstly, the devices of Radio Frequency Identification (RFID) is installed on the original road signs, traffic lights and road markings. It can transmit traffic signals, which are consistent with the original encoded information. At the same time, the device is the terminal node of ZigBee network. Then, routers and coordinator nodes are installed in the necessary place. At last, the network of road condition information is formed in the way of ad-hoc network. When the cars equipped with traffic signal recognition system are driving in this network, they can receive encoded information of traffic signal and converts the received traffic signal encoded information into a voice signal, or converts it into a vehicle control signal to control the vehicle. The system has some good points, with a high recognition rate, long recognition distance, real-time, secure, reliable, easy to implement and so on.
Aiming at the problem that path planning for automatic handling robot in an environment with obstacles, the working environment model of the handling robot is analyzed. And then a path optimization algorithm based on fusing ant colony and particle swarm optimization algorithm is proposed. First of all, this algorithm uses the global search ability of particle swarm to go on a rough search and quickly plans the starting point to the end of the initial path. Then, the pheromone distribution is performed on the initial path. Finally, the ant colony algorithm is used to search the path carefully to get the optimal path. Experimental verification shows that compared with a single ant colony or particle swarm optimization algorithm, fused algorithm about ant colony and particle swarm optimization has a significant improvement in the number of iterations and path planning.
For the problem of uneven distribution of passengers and poor flow of passenger in subway, a intelligent riding system based on dynamic hybrid people identification is established by the analysis tools of the dynamic hybrid algorithm. First of all, the collection of the car image is used to have pretreatment that includes gray and binarization, the degree of congestion within a single compartment is defined as four levels though the proportion of passengers in the image. And then, image recognition is done by the dynamic hybrid algorithm, the level of congestion of the compartment is determined. Ultimately, the level is displayed to the next station in the form of warning lights and text. Experiment and comparison results show that the background elimination method is proposed to improve the recognizable identity of the population in this paper, and the effective identification time is 6.28 s, it is much less than the running time of the subway station, this system can improve the capacity of the subway and the environment of the subway.
Hybrid vehicular power system is a complicated and nonlinear system, and its energy management strategy is one key factor for vehicle performance. The hybrid powertrain consisting of engine, Ni-MH battery and ultra-capacitor is designed, and the energy management strategy for a hybrid vehicular power system is proposed by Haar wavelet which makes vehicle power demand into high frequency and low frequency parts, then distributed among engine, Ni-MH battery and ultra-capacitor by genetic algorithm with the aim of reducing fuel consumption, therefore, improves the system performance and lengthens the service life of components. System modeling and simulation are conducted in Matlab, and the results show that this method of power distribution can meet the design requirements, and have better fuel economy compared to fuzzy control strategy.
To satisfy the weather service requirements of Chongqing traffic departments, this paper designed the traffic weather service system of Chongqing (TWSSC) based on WebGIS by using B/S technology and taking the advantage of the client technology. TWSSC integrates highway information, highway meteorological observing data and forecasting and early warning service information, and apply such technology as tile map, Skyline 3D map and road weather inversion technique. TWSSC has functions of querying Chongqing highway information, monitoring weather conditions in real time, issuing early warning information, and visualizing meteorological service data and products.
Due to the rapid evolution of modern image processing and pattern recognition techniques, there exists a variety of biometric techniques like fingerprints, iris (retina) scans, and speech recognition etc. nowadays. However, among them, face recognition is still the most common technique which is in use due to the fact that it is easy to install and has less complexity. It has been a prominent research field for security applications such as video surveillance, fraud detection, person tracking and crowd recognition. This research work discusses and implements the facial recognition by using MATLAB environment in real time. In this work, the face recognition system is implemented using Principal Component Analysis (PCA) and Eigenface approach by dealing with large dataset. A methodology is proposed to produce more accuracy and efficiency by removing the unrelated space from the image. Also, a graphical Interface System (GUI) is developed in order to make our system clearer and to measure the training time. Furthermore, large databases (ORL and private Database named face-100) are tested through PCA and Eigenfaces approach and then the person identification is carried out. The system successfully recognized the human faces and worked better in different conditions like illumination and blur conditions of the face. The rate of male and female accuracy is also calculated.
The 60 GHz band has gained great interest as an enabler for multi-Gb/s wireless links. Due to the high 60 GHz path loss (about 82 dB per 5 m), a high gain antenna is required to maintain budget requirements. Basically, phased-array antennas that provide higher gain and beam scanning capabilities are attractive for 60 GHz non-line-of-sight (NLOS) communication scenarios. This paper presents an array antenna consisted of 15 × 20 array elements for working in 60 GHz. The substrate of the antenna is FR4 epoxy with relative dielectric constant 4.4 and dielectric loss tangent 0.02. The size of the array antenna is 30 × 20. The interval of antenna elements is 13.14 mm. The HFSS's simulation results show that the peak gain, efficiency, and impedance bandwidth of the flat array antenna can achieve 28.76 dBi, 95.978%, and 20 GHz, respectively. At the same time, the array antenna also has a good directivity.