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Background It remains unclear whether well-maintained subjects, with periodontitis in the past, effectively treated, and maintained for a long time, have the same subgingival microbiome as healthy subjects. Therefore, the objective of this study was to investigate the characteristics of the subgingival microbiome in well-maintained patients with a history of periodontitis compared with healthy subjects. Methods We recruited in 17 well-maintained individuals (no evidence of clinical inflammation and progress of periodontitis) and 21 healthy individuals. Periodontal clinical parameters, consisting of missing teeth, plaque index (PLI), periodontal depth (PD), and bleeding index (BI), were recorded and analyzed. The pooled subgingival samples from mesiobuccal sites of two maxillary first molars were collected. The V3-V4 region of 16S rRNA gene from 38 subgingival samples was sequenced and analyzed. Alpha diversity, microbial composition, types of bacteria, functional pathways between well-maintained group and health group were compared using Mann-Whitney U test. Spearman correlation was used in analyzing the symbiotic relationship among taxa. A classification model was constructed to distinguish two ecological types. Results The maintained individuals demonstrated a different microbiome from healthy subjects, with higher diversity, more disordered structure, more pathogenic microbiota, and more host-destructive metabolism pathways. The genera Actinomyces, Streptococcus, Leptotrichia, Capnocytophaga, Lautropia, and Fusobacterium were predominant components with relative abundance >5% in the subgingival microbiome of well-maintained patients. The classification model by microbiota got a remarkable accuracy of 83.33%. Conclusions Individuals with well-maintained periodontitis showed a more dysbiotic microbial community than healthy individuals. Therefore, close monitoring and scheduled maintenance treatment are necessary for them to maintain a healthy periodontal condition.

With the continuous improvement of substation automation, the number of communication equipment has risen sharply, the network topology is more complicated, and the problem of unable to locate the fault of process-level communication networks quickly and accurately has become more and more prominent. Under this background, to improve the maintenance efficiency of process-level communication networks in the smart substation, this article proposes a method for fault location of process-level communication networks based on deep neural networks. Based on the redundant monitoring of the fault state, the fault feature information of different monitoring nodes in the message transmission process is analyzed, and the characterization method of the fault feature information is proposed accordingly. Based on the emergence principle, it realizes the automatic generation of fault samples according to the physical connection, logical connection, and message subscription relationship of process-level communication networks. Combined with the training rules in deep learning theory, a fault location model of process-level communication networks based on deep neural networks is established, and the real-time location steps are given. Taking the process-level communication network of a typical 110kV smart substation as an example, simulations verify the effectiveness and accuracy of the proposed fault location method in single fault environments and multiple fault environments. Besides, accurate results can be obtained even when the fault feature information is wrong or missing, and the anti-interference ability is excellent.

Unmanned Ground Vehicles (UGVs) have been widely used in Internet of Things, military applications and outer space exploration. Reliable intelligent obstacle recognition is the key requirement and significant challenge for UGVs. To perform robust obstacle recognition under all conditions, data processing and fusing will be necessary based on multiple sensors. This paper carries out obstacle sensing and recognizing research by extracting obstacle feature evidence from camera and laser scanner. The feature evidence extracted from camera includes S/V in HSV color space. The laser feature evidences are related to penetrability value feature and λ 3 ∕ λ 2 feature based on covariance matrix. Then, the key step is to calculate the basic probability assignment based on these feature evidences. By applying Dempster’s combination rules the current obstacle is recognized based on D–S evidence theory. The test results show the validity of this new method and its application in cross-country environment perception, also give references to Internet of Vehicles including vehicle safety control and assistance driving technology, also the related algorithm can be potentially used in the Internet of Things or big data processing.

Background: Coronavirus disease 2019 has become a major problem for the world. We reported a representative case with thrombocytopenia.Case report: A 44-year-old female patient sought medical attention for fatigue and cough of 1 day duration. Thirteen days before disease onset, the patient had returned from Hubei province. Her body temperature on admission was 38.6℃. Blood routine test showed a white blood cell count of 4.0×109/L, lymphocyte count of 1×109/L, platelet count of 118×109/L, and C-reactive protein of 6.0mg/L. Lung computed tomography (CT) scan showed: large patches of ground-glass opacities at the posterior segment of the right upper lung lobe and bilaterally at the basal segment of the lower lung lobes. Her throat swabs tested positive for novel coronavirus nucleic acid. After antiviral and symptomatic treatment were given, on day 5 of hospitalization, her symptoms of coughing and chest pain worsened after coughing, and she also developed hemoptysis. Repeated lung CT scans showed that the lesion area had increased. The lymphocyte count had decreased to 0.55×109/L and the platelet count had decreased to 9×109/L on day 6. After a series of multimodal therapies were carried out, the patient’s platelet and lymphocyte count gradually increased to normal.Conclusion: We reported a COVID-2019 case with significant thrombocytopenia, which was more significantly decreased than in normal viral infections. However, the mechanism of thrombocytopenia is unknown and requires further research.

Off-road intelligent vehicle is an important application about Internet of Vehicles technology used in the transportation field, and the front obstacle recognition method is the key technology for off-road intelligent vehicle. In this paper, based on smart data aggregation inspired paradigm of IoT applications, we mainly study perception technology in vehicle networking by using image data and one symmetrical speeded-up robust features detector (SURF). By considering symmetry and image data aggregation, we found that data aggregation had the ability of providing global information for Internet of Vehicles systems. After we have built the experiment platform, the experiment results showed that this method is faster than Scale-Invariant Feature Transform algorithm in this case, which can satisfy the water detection accuracy and the real-time requirement. So, this method is effective for the water images detection with great symmetry to off-road intelligent vehicle, and it also gives a useful reference about environment perception technology and smart data aggregation inspired paradigm used in future Internet of Vehicles, intelligent vehicle, and traffic safety applications.

This paper studies the effect of carbon emission trading schemes in China and identifies the factors that influence companies' willingness to pay for carbon emissions, as expressed by the increase in energy costs due to the national carbon market. A questionnaire with a multiple-bounded discrete choice format was designed and 555 valid samples were gathered in this analysis. On average, companies are willing to pay 8.3% more on energy costs, while those participating in pilot trading schemes are willing to pay 10.2% more. Pilot companies also have higher investment in energy-saving technology, better awareness of both carbon mitigation technology and carbon policy, and clearer expectations of the national carbon market. The regression analysis shows that the willingness to pay (WTP) is influenced by several factors. The perception of the high pressure of energy costs will significantly decrease the WTP of the non-pilot companies. If a pilot company presumes that it will participate in the national trading schemes sooner, its willingness to pay will be higher. Participation or not in pilot trading schemes exerts an effect on companies' WTP because of two factors: awareness of carbon mitigation technology and the reduction ratio expected by the companies. Among all manufacturing sectors, companies involved in the non-ferrous, chemical, paper-making and iron and steel sectors can be brought into the national carbon market as priority participants, because they have a higher WTP for carbon emissions, or they have a shorter time expectation for participating in the national carbon market.

Lanthanide metal–organic frameworks (Ln-MOFs) have received much attention owing to their structural tunability and widely photofunctional applications. However, successful examples of Ln-MOFs with well-defined photonic performances at micro-/nanometer size are still quite limited. Herein, self-assemblies of 1,3,5-benzenetricarboxylic acid (BTC) and lanthanide ions afford isostructural crystalline Ln-MOFs. Tb-BTC, Eu@Tb-BTC, and Eu-BTC have 1D microrod morphologies, high photoluminescence (PL) quantum yields, and different emission colors (green, orange, and red). Spatially PL resolved spectra confirm that Ln-MOF microrods exhibit an optical waveguide effect with low waveguide loss coefficient (0.012≈0.033 dB μm−1) during propagation. Furthermore, these microrods feature both linear and chiral polarized photoemission with high anisotropy.

Aim To assess the subgingival microbial shift of maintained periodontitis treated by ultrasonic scaling (US) or air polishing (AP) during a 3-month maintenance interval. Materials and methods We conducted a 12-week randomized split-mouth controlled trial with US and AP in 17 maintained subjects (bleeding on probing [BOP%] ≤25%, probing depth [PD] ≤5 mm). They were monitored at baseline, week 2, week 8 and week 12. The V3-V4 region of the 16S rDNA from 136 subgingival plaque samples was sequenced and analysed. Results Treatment by US or AP could effectively reduce the PD, microbial richness, diversity, periodontitis-associated microbiota and pathogenic metabolism in maintained periodontitis. Bacteria recolonized after treatment and returned to the pre-treatment level 12 weeks after treatment. Ultrasonic scaling group demonstrated slight advantage in reducing BOP (%), pathogenic bacteria and metabolism than AP group. Pathogenic microbiota and commensal microbiota kept a balance in subgingival community of maintained patients during the 3-month interval. Conclusions Treatment by US or AP effectively reduced the pathogenicity of subgingival microbiome by reducing microbial diversity, proportion of periodontitis-associated microbiota and pathogenic metabolism. It helped to keep a balanced subgingival community and stable periodontal condition over a single maintenance interval of 3 months.

Aiming at the severity and distribution of abnormal behaviour, attack behaviour, compliance, and vulnerability of equipment in the power information system, this article applies big data technology to analyse and evaluate abnormal behaviour in the network, and uses machine learning to improve the network, the ability to identify security risks and the accuracy of assessments provide strong guarantees and technical support for improving the security and reliability of power information systems.

We report that the ferromagnetic resonance (FMR) response of the CoFeB/HfO2 heterostructures is stabilized and reversibly manipulated by ionic gel. Ionic gel with excellent flexibility is used as a medium to form an electric field. When a 4 V gate voltage is applied, the resonance field H r and peak-to-peak linewidth ΔH pp at different angles are regulated. When θ = 20°, the H r is regulated up to 82 Oe. When θ = 70°, ΔH pp is tuned up to 75 Oe. When the gate voltage is repeatedly applied, the FMR spectra can be freely switched between the initial state and the gated state. Our study provides an effective method to manipulate the damping of the magnetic film stably and reversibly.

A novel pedestrian detection system based on vision in urban traffic situations is presented to help the driver perceive the pedestrian ahead of the vehicle. To enhance the accuracy and to decrease the time spent on pedestrian detection in such complicated situations, the pedestrian is detected by dividing their body into several parts according to their corresponding features in the image. The candidate pedestrian leg is segmented based on the gentle AdaBoost algorithm by training the optimized histogram of gradient features. The candidate pedestrian head is located by matching the pedestrian head and shoulder model above the region of the candidate leg. Then the candidate leg, head and shoulder are combined by parts constraint and threshold adjustment to verify the existence of the pedestrian. Finally, the experiments in real urban traffic circumstances were conducted. The results show that the proposed pedestrian detection method can achieve pedestrian detection rate of 92.1% with the average detection time of 0.2257 s.

To solve the intelligent vehicles’ problems of ‘where am I?’ and ‘what is around me?’, a dense 3D sematic Simultaneous Localization and Mapping (SLAM) system is proposed to evaluate the pose of the intelligent vehicles and build the dense 3D semantic map. We address these challenges by combining a state of art Stereo-ORB-SLAM system and Convolutional Neural Networks. Firstly, we build a dense 3D point cloud map by using a four thread Stereo-ORB-SLAM system. Subsequently, a fully convolutional neural network architecture which uses RGB-D image as input is used to obtain pixel-wise segmentation. Finally, we fuse the geometric information and semantic information to get the semantic map. We test our method on the KITTI dataset and our dataset made with the Fpgalena stereo camera. Results indicate the system was effective in the real-time building of a semantic map, the speed of the entire system is about 10Hz, and the loop closing function can eliminate most of the drifting errors.

Background Glycine air polishing has been proved to be safe, comfortable and time-saving. Whether it could substitute ultrasonic scaling to remove dental plaque biofilm during periodontal maintenance remains unclear. The purposes of this study were to evaluate the effect of supragingival glycine air polishing (SGAP) on the subgingival periodontal pathogens during maintenance therapy and to check the association of periodontal pathogens and clinical parameters. Methods Twenty-three chronic periodontitis patients during their maintenance therapy were enrolled in the 12-week study. According to randomized split-mouth design, the test side was treated with SGAP (65 μm), while the control side was treated with supragingival ultrasonic scaling and polishing (SUSP) with rubber cup. Clinical examination including plaque index (PLI), probing depth (PD), bleeding index (BI) were performed at baseline and 12 weeks post-treatment. Sampling of the subgingival plaque at each investigational site (mesiobuccal site of the mandibular first molar) was performed at baseline and 2, 4, 8, 12 weeks after maintenance treatment. Four periodontal pathogens including Porphyromonas gingivalis, Tannerella forsythia, Treponema denticola and Fusobacterium nucleatum were detected by 16S rDNA polymerase chain reaction. Results Clinical status generally improved after treatment in both groups. PLI in both groups, PD in SGAP group and bleeding on probing (%) in SUSP group significantly decreased after treatment (p < 0.05). There was no significant difference of clinical parameters between two groups before and after treatment. The detection rates of P. gingivalis, T. denticola in both groups, T. forsythia in SUSP group and F. nucleatum in SGAP group decreased after maintenance treatment in both groups, although no significant difference was found, and it rebound to baseline level at 12 weeks after maintenance treatment. There was no significant difference between SGAP group and SUSP group at any time point. T. denticola-positive sites had significantly greater BI than T. denticola-negative sites (p < 0.05). Discussion Supragingival glycine air polishing had a reliable effect in removing subgingival dental plaque biofilm during maintenance period, and three months may be a proper maintenance interval for pockets not more than 5 mm.

The traffic accidents, traffic jams and parking problems come to appear, and have caused more and more concerns of people. The automatic parking system can help us a lot to solve these problems. The automatic parking system in this paper includes two sections, environment perception and automatic controller. The median filter and least square method are used to process the laser sensor data. Then, feasible parking space can be displayed by using K-means clustering method. The Matlab fuzzy GUI is used to establish the fuzzy controller. The kinematics equation of car is utilized to simulate the automatic vertical parking in the Matlab/simulation with the different initial path angles. Experiment results show that the environmental perception method has perfect performance and the controlling algorithm of the automatic parking system has good feasibility.

The building density of Central Business District (CBD) is usually high. Land for a bus terminal is insufficient. In this situation, passengers in CBD have to walk far to take a bus, or take a long time to wait for a taxi. To solve this problem, this paper proposes an indirect approach: the design of a circle line of shuttle bus as a dynamic bus terminal in CBD. The shuttle bus can deliver people to the bus station through a circle line. This approach not only reduces the traffic pressure in CBD, but also saves travel time of the passenger. A bi-objective model is proposed to design a circle line of a shuttle bus for CBD. The problem is solved by non-dominated sorting genetic algorithm (NSGA-II). Furthermore, the Dalian city in China has been chosen as the case study to test the proposed method. The results indicate that the method is effective for circle line optimization of shuttle bus in central business district without a bus terminal.

One new structure of Semi-step Walking Wheel Modeled on Impeller is constructed based on Vehicle-Terramechanics. Based on Passive earth pressure of soil mechanics put forward by C.A.Coulomb, the front force formula of the vane of Semi-step Walking Wheel modeled on Impeller is reduced and the wheel traction force when a set of vanes insert the earth is derived. Some Kinematics Simulations are conducted for installing Lunar rover model with ADAMS software. The simulation results show that the wheel can travel smoothly on straight road, climb over bump obstacles. Also, the ability of the lunar rover one-side surmounting obstacle is better than the ability of two-sides. The walking wheel inherits high ride comfort of traditional wheel and excellent cross obstacle ability of walking wheel.

Although significant progress has been made in precision machining of free-form surfaces recently, inspection of such surfaces remains a difficult problem. In order to solve the problem that no specific standards for the verification of free-form surface profile are available, the profile parameters of free-form surface are proposed by referring to ISO standards regarding form tolerances and considering its complexity and non-rotational symmetry. Non-uniform rational basis spline(NURBS) for describing free-form surface is formulated. Crucial issues in surface inspection and profile error verification are localization between the design coordinate system(DCS) and measurement coordinate system(MCS) for searching the closest points on the design model corresponding to measured points. A quasi particle swarm optimization(QPSO) is proposed to search the transformation parameters to implement localization between DCS and MCS. Surface subdivide method which does the searching in a recursively reduced range of the parameters u and v of the NURBS design model is developed to find the closest points. In order to verify the effectiveness of the proposed methods, the design model is generated by NURBS and the measurement data of simulation example are generated by transforming the design model to arbitrary position and orientation, and the parts are machined based on the design model and are measured on CMM. The profile errors of simulation example and actual parts are calculated by the proposed method. The results verify that the evaluation precision of freeform surface profile error by the proposed method is higher 10%–22% than that by CMM software. The proposed method deals with the hard problem that it has a lower precision in profile error evaluation of free-form surface.

Unmanned Ground Vehicles (UGVs) that can drive autonomously in cross-country environment have received a good deal of attention in recent years. They must have the ability to determine whether the current terrain is traversable or not by using onboard sensors. This paper explores new methods related to environment perception based on computer image processing, pattern recognition, multisensors data fusion, and multidisciplinary theory. Kalman filter is used for low-level fusion of physical level, thus using the D-S evidence theory for high-level data fusion. Probability Test and Gaussian Mixture Model are proposed to obtain the traversable region in the forward-facing camera view for UGV. One feature set including color and texture information is extracted from areas of interest and combined with a classifier approach to resolve two types of terrain (traversable or not). Also, three-dimension data are employed; the feature set contains components such as distance contrast of three-dimension data, edge chain-code curvature of camera image, and covariance matrix based on the principal component method. This paper puts forward one new method that is suitable for distributing basic probability assignment (BPA), based on which D-S theory of evidence is employed to integrate sensors information and recognize the obstacle. The subordination obtained by using the fuzzy interpolation is applied to calculate the basic probability assignment. It is supposed that the subordination is equal to correlation coefficient in the formula. More accurate results of object identification are achieved by using the D-S theory of evidence. Control on motion behavior or autonomous navigation for UGV is based on the method, which is necessary for UGV high speed driving in cross-country environment. The experiment results have demonstrated the viability of the new method.

ObjectiveThe purpose of this study was to build a video endoscopic inguinal lymphadenectomy (VEIL) via the 3-incision superolateral inguinal approach and explore the feasibility and significance of this method for vulvar cancer.MethodsThirty-seven patients with vulvar cancer who underwent VEIL via the 3-incision superolateral inguinal approach were enrolled and followed up. The number of excised lymph nodes, intraoperative complications, inguinal wound healing, and the prognosis were retrospectively analyzed.ResultsThe average number of excised lymph nodes per side is 8.8 ± 3.7 (4–18) among the 37 patients and after the new method was more mature, is 9.6 ± 3.6 among the 34 patients treated. Primary healing was found in 36 cases, whereas delayed healing occurred in 1 case complicated with diabetes. The lymph node–positive patients (6 cases) were supplemented with postoperative radiochemotherapy (RCT). All patients survived during the follow-up. Of the 2 recurrent patients, one patient who received surgery again and RCT survived without tumor. The other patient undergoing RCT survived with tumor.ConclusionsCompared with open lymphadenectomy, VEIL via the 3-incision lateral approach provides a feasible, but more cosmetic, and promising minimally invasive modality in clinic for treating patients with vulvar cancer.

Pedestrian detection and tracking is the key to autonomous vehicle navigation systems avoiding potentially dangerous situations. Firstly, the probability distribution of colour information is established after a pedestrian is located in an image. Then the detected results are utilized to initialize a Kalman filter to predict the possible position of the pedestrian centroid in the future frame. A Camshift tracking algorithm is used to track the pedestrian in the specific search window of the next frame based on the prediction results. The actual position of the pedestrian centroid is output from the Camshift tracking algorithm to update the gain and error covariance matrix of the Kalman filter. Experimental results in real traffic situations show the proposed pedestrian tracking algorithm can achieve good performance even when they are partly occluded in inconsistent illumination circumstances.

International audience; In this paper, we present two large video multi-modal datasets for RGB and RGB-D gesture recognition: the ChaLearn LAP RGB-D Isolated Gesture Dataset (IsoGD) and the Continuous Gesture Dataset (ConGD). Both datasets are derived from the ChaLearn Gesture Dataset (CGD) that has a total of more than 50000 gestures for the "one-shot-learning" competition. To increase the potential of the old dataset, we designed new well curated datasets composed of 249 gesture labels, and including 47933 gestures manually labeled the begin and end frames in sequences. Using these datasets we will open two competitions on the CodaLab platform so that researchers can test and compare their methods for "user independent" gesture recognition. The first challenge is designed for gesture spotting and recognition in continuous sequences of gestures while the second one is designed for gesture classification from segmented data. The baseline method based on the bag of visual words (BoVW) model is also presented.

Pedestrians are the vulnerable participants in transportation system when crashes happen. It is important to detect pedestrian efficiently and accurately in many computer vision applications, such as intelligent transportation systems (ITSs) and safety driving assistant systems (SDASs). This paper proposes a two-stage pedestrian detection method based on machine vision. In the first stage, AdaBoost algorithm and cascading method are adopted to segment pedestrian candidates from image. To confirm whether each candidate is pedestrian or not, a second stage is needed to eliminate some false positives. In this stage, a pedestrian recognizing classifier is trained with support vector machine (SVM). The input features used for SVM training are extracted from both the sample gray images and edge images. Finally, the performance of the proposed pedestrian detection method is tested with real-world data. Results show that the performance is better than conventional single-stage classifier, such as AdaBoost based or SVM based classifier.

New generation geometrical product specification (GPS) links the whole course of a geometrical product from the research, development, design, manufacturing and verification to its release, utilization, and maintenance. Measurement process is one of the most important part of verification/inspection in the new generation GPS. With the knowledge-intensive and globalization trend of the economy, unifying the evaluation and verification of form errors will play a vital role in international trade and technical communication. Considering the plane feature is one of the most basic geometric primitives which contribute significantly to fundamental mechanical products such as guide way of machine tool to achieve intended functionalities, the mathematical model of flatness error minimum zone solution is formulated and an improved genetic algorithm (IGA) is proposed to implement flatness error minimum zone evaluation. Then, two evaluation methods of flatness error uncertainty are proposed, which are based on the Guide to the Expression of Uncertainty in Measurement (GUM) and a Monte Carlo Method (MCM). The calculating formula and the propagation coefficients of each element and correlation coefficients based on GUM and the procedures based on MCM are developed. Finally, two examples are listed to prove the effectiveness of the proposed method. An investigation into the source and effects of different uncertainty contributors for practical measurement on CMM is carried out and the uncertainty contributors significant are analyzed for flatness error verification. Compared with conventional methods, the proposed method not only has the advantages of simple algorithm, good flexibility, more efficiency and accuracy, but also guarantees the minimum zone solution specified in the ISO/1101 standard. Furthermore, it accords with the requirement of the new generation GPS standard which the measurement uncertainty characterizing the reliability of the results is given together. And it is also extended to other form errors evaluation and verification.

Driving fatigue is one of the main reasons of traffic accident. In this field, the method based on multi-source information fusion has been a leading technique. A driver fatigue recognition model based on the Bayesian network was introduced in this paper. The real-time system monitored the state of the driver's features such as eyes, mouth and head movement through computer vision technique, their results were fused with Bayesian network inference algorithm and the final fusion result could be inferred according to the probability values of different variables states. Test results showed that this method could be more reasonably robust, reliable, and accurate in fatigue detection.

The road traffic signs recognition in open environment is an important research in the field of safe auxiliary driving, vehicle autonomous navigation and so on. Based on the characteristic of road signs, one-dimensional entropy division was carried on to segment the AOI image obtained by lane detection, and then the road signs were recognized by SVM with improved Hu moment features. Experiments show that the proposed method for road traffic signs recognition in open environment has good reliability and robustness

Slip-sinkage is one of the main factors influencing the driving safety of planetary rover in soft terrain. In the environment of scarce features, based on the stereo visual sensors, the visual odometry algorithm is firstly developed to calculate the position changes of planetary rover with six degrees of freedom, which combine with the wheel speed sensor achieve the estimation of wheel slip ratios. Then, on the basis of mechanical analysis of soft terrain, choosing the slip ratio as the state variable, the coordinated driving control algorithm is designed. Simulation and experiment results demonstrate the effectiveness of the proposed control algorithm.

This paper investigates the traction coordinating control issue of the wheeled lunar rover with Rocker Bogie in rough terrain. Based on the improved exponential approach law, the algorithm of coordinating control is designed to optimize the traction force and minimize the slip ratio, including the velocity and normal force control and sliding mode control. Then the co-simulations between ADAMS and MATLAB/Simulink are carried out in order to validate the proposed algorithm. Simulation results for a wheeled rover traversing moon-like terrain slopes and ditches demonstrate the effectiveness of the proposed control algorithm and the mobility improvement.

In order to detect the obstacle from the large amount of 3D LIDAR data in hybrid cross-country environment for unmanned ground vehicle, a new graph approach based on Markov random field was presented. Firstly, the preprocessing method based on the maximum blurred line is applied to segment the projection of every laser scan line inx-yplane. Then, based onK-means clustering algorithm, the same properties of the line are combined. Secondly, line segment nodes are precisely positioned by using corner detection method, and the next step is to take advantage of line segment nodes to build an undirected graph for Markov random field. Lastly, the energy function is calculated by means of analyzing line segment features and solved by graph cut. Two types of line mark are finally classified into two categories: ground and obstacle. Experiments prove the feasibility of the approach and show that it has better performance and runs in real time.

To enhance the active safety and realize the autonomy of intelligent vehicle on highway curved road, a lane changing trajectory is planned and tracked for lane changing maneuver on curved road. The kinematics model of the intelligent vehicle with nonholonomic constraint feature and the tracking error model are established firstly. The longitudinal and lateral coupling and the difference of curvature radius between the outside and inside lane are taken into account, which is helpful to enhance the authenticity of desired lane changing trajectory on curved road. Then the trajectory tracking controller of closed-loop control structure is derived using integral backstepping method to construct a new virtual variable. The Lyapunov theory is applied to analyze the stability of the proposed tracking controller. Simulation results demonstrate that this controller can guarantee the convergences of both the relative position tracking errors and the position tracking synchronization.

A new detection technique for molecular spectrum, based on direct determination of light intensity absorbed, was developed, which is generally applicable to the determination of light-absorbing substances with the sensitivity as high as that of fluorometry. The quantitative formula of the method was reduced. It was demonstrated that spectra obtained by this method were similar to the corresponding absorption spectra. The analytical characteristics, such as sensitivity, detection limit, etc., were studied using absorbent materials in different ranges of wavelength and compared with both spectrophotometry and fluorometry.

Environment perception is one of the important issues for unmanned ground vehicle (UGV). It is necessary to develop waters hole detection and tracking method in cross-country environment. This paper is related to the waters hole detection and tracking by using visual information. Image processing strategies based on support vector machine (SVM) and speeded up robust feature (SURF) methods are employed to detect and track waters hole. It focuses on how to extract the waters feature descriptor by exploring the machine learning algorithm. Based on the S/V color features and Gray Level Co-occurrence Matrix, the waters feature descriptor is extracted. The radial basis function (RBF) kernel function and the sampling-window size are determined by using the SVM classifier. The optimal parameters are obtained under the cross-validation conditions by the grid method. In terms of waters tracking, SURF feature matching method is applied to extract the remarkable feature points, then to observe the relation between feature point movement of adjacent frames and scale change ratio. Experiments show that SURF algorithm can still be effective to detect and match the remarkable feature points, against the negative effects of waters scale transformation and affine transform. The conclusion is that the computing speed of SURF algorithm is about three times faster than that of scale-invariant feature transform (SIFT) algorithm, and the comprehensive performance of SURF algorithm is better.

Electrostatic discharge (ESD) protection structures in the D-Mode GaAs HEMT technology are commonly constructed using either stacked Schottky diode or Single-Gate clamp. This paper develops an improved ESD protection clamp based on a novel multi-gate pHEMT in D-Mode technology. With similar layout area, the proposed ESD protection clamp can carry much higher current than the conventional single-gate pHEMT clamp under the human body model (HBM) stress.

In this paper, a new monolithically integrated, digitally-controlled variable gain amplifier (DVGA) is presented. The DVGA includes a gain block, a digital step attenuator (DSA), and a ¼ W driver amplifier, fabricated by using commercial GaAs BiFET process. This high performance, low cost DVGA operates from 100MHz to 4000MHz, with 0.5dB step and 31.5dB gain dynamic range. It shows the noise figure of 4dB, output IP3 of 41dBm, and 25dBm output power at 1dB gain compression (P1dB). The DVGA consumes total 175mA DC current with 5V power supply at room temperature.

Variation elliptical piston skirt has better mechanical and thermodynamic properties and it is widely applied in internal combustion engine in recent years. Because of its complex form, its geometrical precision evaluation is a difficult problem. In this paper, quasi-particle swarm optimization (QPSO) is proposed to calculate the minimum zone error and ellipticity of cross-section linear profile, where initial positions and initial velocities of all particles are generated by using quasi-random Halton sequences which sample points have good distribution properties and the particles’ velocities are modified by constriction factor approach. Then, the design formula and mathematical model of the cross-section linear profile of variation elliptical piston skirt are set up and its objective function calculation approach using QPSO to solve the minimum zone cross-section linear profile error is developed which conforms to the ISO/1101 standard. Finally, the experimental results evaluated by QPSO, particle swarm optimization (PSO), improved genetic algorithm (IGA) and the least square method (LSM) confirm the effectiveness of the proposed QPSO and it improves the linear profile error evaluation accuracy and efficiency. This method can be extended to other complex curve form error evaluation such as cam curve profile.

Reliable detection of non-traversable hazards is a key requirement and significant challenge to unmanned ground vehicle (UGV) autonomous cross-country navigation. DLUT is developing a daytime obstacle detection capability using UGV mounted sensors and has performed three obstacle detection algorithms. In this paper, we currently focus on the cues for obstacle detection color camera sensor provides. Color or monochrome images were collected from a general dynamics autonomous system and processed off-line with run-time passive perception software that includes: a water obstacle detector, a non-traversable tree trunk detector, a bush or shrub detector. A detailed description of each obstacle detection algorithm and their performance is presented in this paper.

Pedestrian detection is a rapidly evolving topic in many computer vision applications such as intelligent vehicle, surveillance and advanced robotics. The pedestrian collision avoidance not only requires detection of pedestrian but also requires prediction by tracking to analyze its dynamics and behaviors. The objective of this paper is to provide a method realizing pedestrian detection and tracking based on monocular vision. The first part of the paper is to detect pedestrian from the image. Both the rectangle features and edge orientation features are calculated by integral image techniques and Adaboost is used to fulfill discriminative features selection and classifiers training. The second part contains a pedestrian tracking method based on Kalman filtering. Experiments are performed to test and verify the pedestrian detection and tracking method under normal urban environments. The experiment results show that the method can detect and track pedestrian ahead of vehicle with different sizes and postures.

With the rapid development of internal combustion engines (ICE) industry, the cross-section contour of variation elliptical piston skirt is widely used in order to achieve better mechanical and thermodynamics performances which the cross-section elliptic degree is diverse in the highness direction and the axis section contour is convex curve. Because of its complex form its geometrical precision evaluation is a difficult problem. Particle swarm optimization (PSO) that is based on two fundamental disciplines (social science and computer science) is proposed to implement the minimum zone evaluation of the cross-section contour error of variation elliptical piston skirt and the particle' velocity is modified by constriction factor approach. Then, the design formula of the cross-section contour of variation elliptical piston is given and its objective function calculation approach using PSO to solve the minimum zone error of cross-section contour is developed which conforms to the ISO/1101 standard. Finally, the experimental results evaluated by PSO, the least square method (LSM) and improved genetic algorithm (IGA) confirm the effectiveness of PSO and it improves the cross-section contour error evaluation accuracy of variation elliptical piston skirt.

Sealed storage and access control are the characteristics of USB KEY integrated with smart card, a kind of USB KEY-based approach for virtual assets protection is presented. Virtual assets of users are stored in the hidden partition of USB KEY which is not able to read out, it would be displayed on the screen of USB KEY after user’s PIN verified. If a PIN is blocked, it must be reloaded, it is designed that answering private questions and reloading key are adopted to generate a new PIN. In this scheme, line protection is used to protect the communication data from being tampered, and reloading PIN is effective to resist PIN guess, furthermore, it is convenient to use that the users are no longer to remember all kinds of usernames and passwords.

The driver's face orientation monitoring is an important component of driving assistant of vehicle safety, and it is one of the effective measures for preventing serious traffic accidents. In a large number of research methods, the method based on vision has been a leading technique due to its hardware's characteristics of small size, low cost and non-intrusiveness to drivers. This paper presents a real time system which can alert drivers when they feel drowsy or lose alertness based on the eyes, mouth detection and face orientation monitoring. Test results show that the system can monitor the face features effectively and give out the information of driver's face orientation according to corresponding regulations.