Search

Environmental perception is the premise of autonomous driving. Aiming at the environmental perception technology of racing car, this paper studies the LiDAR obstacle detection algorithm, aiming at providing necessary information for the path planning and vehicle control of racing car, and realizing the safe driving of the car. An algorithm of target pile bucket detection of driverless formula racing cars in the competition environment is studied. For the detection of target buckets, our approach is to limit the axial distance of the LiDAR raw data, retain the effective LiDAR data around the car, then use the plane segmentation model algorithm to separate target buckets from the ground and filter out the ground, and finally use Euclidean cluster to extract target buckets data. The result of actual vehicle experiment show that the algorithm of the thesis can quickly detect the target bucket of the them on the racing car, which lays a good foundation for the path planning and vehicle control of the car.

This paper introduces a novel patrol inspection and platform for special equipment based on Unmanned Aerial Vehicle (UAV). The design of the multi-rotor UAV system is mainly composed of a six-axis UAV platform, inspection sensor modules and a ground station, including functions of obstacle avoidance, high-definition cameras detection, remote control and automatic generation of test reports. These performances can definitely enhance the reliability and stability of the UAV system and benefit the inspection patrol for potential diseases of special equipment. Then mechanical structural check is demonstrated and the patrol application example results show this approach can reduce the danger of detection task and improve the working efficiency compared to manual inspection.

For a long time, due to the insufficient importance of distribution network and the large number of poles, the grounding resistance of poles in distribution lines is often difficult to meet the standard requirements. Because the line arrester releases the lightning current through the pole, the effect of the grounding resistance of pole on the effect of the line arrester is an important concern of lightning protection in the distribution network. In this paper, a lightning strike distribution line model is established through PSCAD, and the influence of grounding resistance on lightning resistance level of non-arrester lines is analyzed through simulation. The effect of different grounding resistance and disposition density of lightning arrester on lightning resistance level is analyzed, and the safety of natural grounding of pole under lightning is verified. This paper illustrates the effectiveness and feasibility of using concrete poles for natural grounding of lightning arrester for distribution network line, and provides a basis for the lightning arrester configuration scheme of distribution overhead line.

The inaccuracy of road intersection in digital road map easily brings serious effects on the mobile navigation and other applications. Massive traveling trajectories of thousands of vehicles enable frequent updating of road intersection topology. In this paper, we first expand the road intersection detection issue into a topology calibration problem for road intersection influence zone. Distinct from the existing road intersection update methods, we not only determine the location and coverage of road intersection, but figure out incorrect or missing turning paths within whole influence zone based on unmatched trajectories as compared to the existing map. The important challenges of calibration issue include that trajectories are mixing with exceptional data, and road intersections are of different sizes and shapes, etc. To address above challenges, we propose a three-phase calibration framework, called CITT. It is composed of trajectory quality improving, core zone detection, and topology calibration within road intersection influence zone. From such components it can automatically obtain high quality topology of road intersection influence zone. Extensive experiments compared with the state-of-the-art methods using trajectory data obtained from Didi Chuxing and Chicago campus shuttles demonstrate that CITT method has strong stability and robustness and significantly outperforms the existing methods.

The battery system in the DC system is an important link to ensure the safe and stable operation of power plants and substations. The LiFePO4 battery will replacement of lead-acid batteries in the DC system is a trend in the future, because of its high energy density, wide operating temperature, long cycle life. The battery system in the DC system is consisted of a large number of cells, and the capacity is high, due to individual differences, will cause the battery imbalanced, resulting in a reduction in the usable capacity of the battery pack. This may cause battery pack life to decrease or damage the battery. In this article, a switching matrix type active equalization topology and its equalization strategy are designed, which is easy to be modular, simple and efficient. The experimental results verify the feasibility of the design.

Along with the development of power system, power load forecasting plays a more and more important role. It is not only an important part of power system dispatching, operation and planning, but also the foundation of economic operation and safe operation of power system. However, power load data generally have the characteristics of complexity and nonlinearity. At present, most forecasting methods, which are based on the traditional linear statistical theory, can not consider the time series and the nonlinear characteristics of load data at the same time. In this paper, a short term load forecasting model, GRU (gated recurrent unit) network is proposed, which is the variant of LSTM(long short term memory) being based on long and short memory neural network, and the simulation prediction is carried out by using the power load data of a region in Heilongjiang province. Comparing the prediction results with the traditional ones, it is proved that the error of GRU model is lower and the prediction effect is better.

The 2-μm waveband has gained much attention due to its potential applications in data communications and optical sensing. This wavelength range is of particular interests for integrated platform as it is transparent for silicon and is free of two photon absorption. We experimentally demonstrate a 2-μm silicon focusing grating coupler with subwavelength structure. The theoretical coupling efficiency for TM polarization is simulated to be 48% with 10 degrees tilt angle at 1952 nm. The measured peak coupling efficiency is 24.3% with the coupling angle of 11°. The grating coupler at two micron spectral band provides an efficient interface between the light source and the 2-μm photonic integrated circuits.

In the process of design of electric vehicle control system, the response of each control node in the charging process is analyzed, then the control strategy of the charging process of vehicle on-board charging system is studied and designed according to the electric vehicle on-board charging system structural characteristics, with reference to the national standard of the electric vehicle conduction charging system. Based on the simulation technology of Simulink/Stateflow, the logic simulation model of vehicle on-board charging system control process was established. By changing the input data of the model, the transformation of the running state of the main control system between different state objects and the output control signal to carry on the simulation verification via observations. The simulation results show that the control logic of charging system is correct and practically useful.

Water quality pollution events in urban distribution system always show the characteristics as abruptness and variety, and the ability of qualitative detection of water quality contamination events is limited in water quality early warning. Aiming to these, the application of Dempster-Shafer theory in water quality analysis is studied on, and the quantitative detection method of contaminant in drinking water based on water quality parameters is proposed. Combining with experiment and simulation, the analysis results show that the method could weaken the dependence of historical data effectively. Comparing with regular cluster algorithm, the method adjusts local non-linear variation between contaminant concentration and water quality parameters and has better performance.

This paper considers the problem of cooperative spectrum sensing (CSS) in the censoring-enabled Cognitive Radio Networks (CRNs) with a crowd of battery-powered Secondary Users (SUs), where only significant local observations are submitted to the Fusion Center (FC). However, in order to monopolize the spectrum usage or disrupt the networks operation, malicious SUs may try to send falsified sensing reports to the FC even they are uncertain about their observations, which make the existing robust CSS schemes ineffective. To tackle these challenges, we formulate an optimization problem to improve the performance of CSS in the censoring-enabled CRNs, and develop an expectation maximization based algorithm to solve it, where the presences of primary user and the reliabilities of each SU can be jointly estimated. Extensive simulation results show that the proposed robust CSS scheme outperforms the previous reputation-based approaches under various attack scenarios.

In this paper, a new method for blind recognition of BCH code from an intercepted sequence of noise affected codewords is proposed. The proposed method recovers the parameters of a BCH code by finding the roots of it's generator polynomial. Firstly, the Galois Field Fourier Transform (GFFT) operation is carried out for each sequence of an estimated length. Then, find the positions of common zero spectral components of all sequences' GFFT. If such positions exist, the corresponding estimated length is the code length and the roots of the underlying generator polynomial are found. Furthermore, the theoretical analysis of the proposed method is given in detail and an optimal threshold is derived to minimize the summation of the false alarm and miss detection probability for distinguishing the root and non-root of the generator polynomial. Simulation results show that the proposed method outperforms the previous ones.

The RESTful Web-Service API is widely used to support interoperable machine-to-machine interaction over a network. RESTful API allows the server to authenticate each client by cookies or session on HTTP protocol. However, it is easy for a hacker to steal the identification information, e.g., by tapping the broadcast packets or by providing a fake proxy to do so. With the stolen identify, the hacker can disguise himself as an authenticated client to interact with a server. In this research, we propose a new mechanism called disposable token, which is based on token authentication of RESTful API on HTTP protocol. This mechanism asks a client to store the public and private token-pair computed by the server. In each communication, the client uses the stored public token, private token and the current timestamp to produce a disposable token, which is subsequently received by the server for verification. With this mechanism, each communication will be valid only in a fixed period of time, thus reducing risks of stolen identity.

An optimized design of cage antenna Using FEKO and genetic algorithm (GA) is presented. The geometry of the antenna is optimized by GA to get best VSWR and gain performances over the entire 100-400MHz band. The height of the optimized geometry of the cage antenna is only 0.75m, while the diameter is only 0.15m. The antenna can work over entire 100-400MHz with the VSWR lower than 3 and the gain higher than 1.55dBi.

Cache sharing among multiple computing units on chip is common in today's multi-core processors, and a lot of research has focused on the effective management of shared cache. A software management method called page coloring is commonly used to divide the cache among different applications competing for the same cache entries. Both static and dynamic cache partition mechanism have been implemented in operating system or user-space level. However, few efforts have been made under virtualization environments. Our previous work has provided a static cache partition method based on page coloring in Xen, following that, a dynamic cache partition mechanism called Colored Page Migration (CoPaM) is presented in this paper.

This paper presents a model for synthetically evaluating user trust and user capability (UT-IOCEM) in cooperative learning. In this paper, trust measure strategies and individual-oriented capability evaluation model namely UT-IOCEM are discussed. The architecture of UT-IOCEM has been proposed and used for flexible cooperative action delegation.

The self-piercing riveted (SPR) joints mechanical properties of coating on the behavior and quality between aluminum alloy and steel sheets was researched. NG5754 aluminum and cold rolled ST12 steel were used for this test. The Zinc-plated and E-coated were applied to the ST12 sheets. The test results showed that a coating on the surface of the ST12 sheets would affect the interlock quality in terms of interlock distance, head height and piercing material thickness. Analysis of interlock sections indicated that the SPR process needed various setting parameters for uncoated and coated sheets in order to achieve satisfied joints results. The research has also demonstrated that both Zinc-plated and E-coated affected the interlock strength and failure mechanism.

Information extraction is the prerequisite of remote sensing image segmentation, which is the key procedure of image analysis. In this paper we establish MAP-MRF framework using Markov random field(MRF),adopt the sampler training, and get the factor of model, introducing the simulated annealing to segment the image and extract the road. On the other hand, Support Vector Machines (SVM) plus Fuzzy C-Mean（FCM） model was proposed and integrated together for remote sensing image segmentation. Firstly, we need use non-supervised clustering for remote sensing image by using FCM; then SVM is adopted for further classification, and extract the road. Finally the comparison with two proposed algorithm was carried out, and after experiment, SVM plus FCM model is much more accurate than Markov random fields.

Phytoremediation is an relatively low cost, energy efficient, pleasing method of remediating heavy metals contaminated soil compared to other traditional remedial methods. It has been the reseach focus of the environmental scientists. This article views about the phytoremediation effect of strengthening measures through adding the EDTA, Citric acid, tartaric acid into the soils etc. and some other additional measures, such as fertilization, irrigation, plant cultivation and so on. The results of the measures' mechanisms and application discussed here provided a technical reference for the reseach and application of improving the phytoremediation efficiency.

In terms of the feature of the Self-Piercing Riveting process program, the evaluating index system for the process is created. The weighting aggregate is created with the analytic hierarchy process. The correctness of the weighting aggregate is tested by test results, Selecting the right test program basede on the value of weighting aggregate and synthetical importance.

Treatment of methanolic wastewater was studied in an anaerobic sequencing batch reactor (ASBR) for a period of 193 days. The results showed that the system worked efficiently when the system volume loading was of 4–8g COD/l. d. Both Methanol concentration and bicarbonate play an important role in the anaerobic conversion of methanol. The route by which methanol was converted into methane had great effect on the COD removal of system. The acetic acid utilization rate increased with the volume loading. When the volume loading was 8g COD/l. d, the acetic acid utilization rate was 5% and the COD removal was over 95%. While the volume loading was 12g COD/l. d, the acetic acid utilization rate was 15.83% and the COD removal is less than 78%. The results of this study suggest that treating methanolic wastewater using anaerobic sequencing batch reactor is feasible.

This paper uses Bumblebee stereo vision system to reconstruct the 3D terrain for patrol robot. Firstly, with the selected points in the disparity image, the ground plane equation of the current frame is calculated by the RANSAC (Random Sample Consensus) algorithm, and then estimated and predicted by the Kalman filter. Secondly, the elevation image is obtained through the distance between the obstacle and the ground plane, which is calculated on basis of the formula from the point to the plane. Finally, the noise points in the elevation image are removed through erosion and dilation operations, and the location and size of obstacles are determined via the connected component analysis method. The actual test in substation environment verified the reliability of the system.

The stratospheric nacelle system flying in the stratosphere has a very wide application future especially in the fields of modern scientific observation experiments and wireless communication. An attitude control system is designed to adjust and control nacelle attitude, while the reacting inertial wheel system based on PID controller is designed to adjust attitude and restrain changes produced by atmosphere disturbance, in order to keeping instruments tracking and pointing ground targets steadily. This paper uses genetic algorithm to tune PID parameters offline to make some performance optimal. After obtaining the optimal PID parameters, the attitude control system using MATLAB/Simulink is simulated. Simulation results show that the new parameters can improve some performance obviously, make some performance optimal and shorten system development time.

Aims at the mines locations exist the windage between the expectation and the fact in the laying mines, this can result in that the mines spaces appear the stochastic distribution. Firstly, we adopt the coordinate transform method, use the distributing theory of the multi-dimension random variable in the probability theory, and construct the normal distribution model of the mines space. Secodly, the construction model validity are validate by the simulation application, and the rule, that we can find the upside of the distributed area turn low, oppositely the width increased, if mine position distribution enhanced. Lastly, the gained conclusions can ensure the mine space can be controlde effectively when laying mines, and provide the basis of tactical decision-making.

The thermal cycle system is a key module for the amplification of deoxyribonucleic acid in real-time polymerase chain reaction (PCR) instrument. The accuracy of quantification is directly influenced by the performance of the system, such as heating and cooling rate, temperature uniformity and temperature-controlled precision. Therefore, a proper thermal analysis method is very important to the thermal cycle system design. In this paper, an equivalent circuit model of the system using thermoelectric coolers was proposed. The modeling results were in good agreement with the experimental results. The use of this model allowed the static and dynamic performance of the system to be analyzed by using electrical circuit analysis software such as Multisim10. Also, it is an effective and simple way to study how the factors such as thermal resistance of heat sink and thermal grease affect the performance of the system.

A novel nonlinear modelling approach has been developed and implemented on Alstom gasifier using Wiener model. The linear element of the Wiener model was identified by a combined subspace state space method, which integrated MOESP (Multivariable Output-Error State Space) and N4SID (Numerical algorithms for subspace state space system identification) method in the estimation of system matrices. Then a single layer neural network was chosen as the nonlinearity of the model. The proposed model identification method was used to model Alstom gasifier with strong nonlinearity and multivariable couples. The results compared to a combined linear subspace identification method demonstrate that the nonlinear method proposed in this paper behave better approximation.

While the roundness error of micro-drill margins is measured, the special structure's Hopfield neural network is designed according to normal equation obtained by pseudo-inverse. The network has 5 neurons, the weights of which are elements of normal equation's symmetry matrix, the inputs vector of which is composed of numeral value of normal equation's right. At the same time, via simulated annealing algorithm, iteration is carried out in the light of Metropolis criterion, and the probability of convergence to global optical solution is 1 while the present temperature approaching to desired lease value. Thus the global optimization solution is obtained, which can be taken as coefficient of fitted ellipse, and the roundness error of micro-drill margins can be solved.

At present there are still some problems in the automatic test paper-making-system: The first is about the test question including graphs; The second is about the test question including formula; The third is about the difficulty degree of the test question which is set in advance and fixed, and can't be adjusted to meet the new need when the ability of examinees has changed; The forth is repetition of the same topic and focus in one test paper; the fifth is how to design the typesetting. In view of the above problems, taking the subject of “Object-Oriented Programming” for an example, a kind of self-adapted making test paper system, which can settle those problems, has been provided by the means of law of large numbers, the idea of machine learning and man-made assistant adjustment. It is simpler and more reliable than what is used nowadays.

In virtual machine (VM) systems, with the increase in the number of VMs and the demands of applications, the main memory is becoming a bottleneck of application performance. To improve paging performance for memory-intensive or I/O-intensive workloads, we propose the hypervisor REMOte disk CAche (REMOCA), which allows a virtual machine to use the memory resources on other physical machines as its cache between its virtual memory and virtual disk devices. The goal of REMOCA is to reduce disk accesses, which is much slower than transferring memory pages over modern interconnect networks. As a result, the average disk I/O latency can be improved. REMOCA is implemented within the hypervisor, by intercepting guest events such as page evictions and disk accesses. This design is transparent to the applications, and is compatible with existing techniques like ballooning and ghost buffer. Moreover, a combination of them can provide a more flexible resource management policy. Our experimental results show that REMOCA can efficiently alleviate the impact of thrashing behavior, and also significantly improve the performance for real-world I/O intensive applications.

Virtualization is often used in systems for the purpose of offering isolation among applications running in separate virtual machines (VM). Current virtual machine monitors (VMMs) have done a decent job in resource isolation in memory, CPU and I/O devices. However, when looking further into the usage of lower-level shared cache, we notice that one virtual machine’s cache behavior may interfere with another’s due to the uncontrolled cache sharing. In this situation, performance isolation cannot be guaranteed. This paper presents a cache partitioning approach which can be implemented in the VMM. We have implemented this mechanism in Xen VMM using the page coloring technique traditionally applied to the OS. Our VMM-based implementation is fully transparent to the guest OSes. It thus shows the advantages of simplicity and flexibility. Our evaluation shows that our cache partitioning method can work efficiently and improve the performance of co-scheduled applications running within different VMs. In the concurrent workloads selected from the SPEC CPU 2006 benchmarks, our technique achieves a performance improvement by up to 19% for the most sensitive workloads

As embedded systems are getting increasingly complex, preemption overheads become a serious load problem for many microchip-based application specific systems, and sometimes may even jeopardize the system schedulability. This paper presents a dynamic preemption threshold scheduling (DPT) that integrates the preemption threshold scheduling into the earliest deadline first The DPT scheduling can effectively reduce context switching by threads assignment and changing the task dynamic preemption threshold at runtime. Meanwhile, because the algorithm is based on dynamic scheduling, it can achieve higher processor utilization with relatively low costs in preemption switching and memory requirements. The DPT scheduling can also perfectly schedule a mixed task set with preemptive and non-preemptive tasks, and subsumes both as special cases.