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This is a retrospective case–control study to ascertain the factors influencing nosocomial infection (NI) in elderly patients with hip fractures. A total of 80,174 patients (≥ 60 years) who suffered hip fractures between 2006 and 2017 were identified through a national inquiry of 94 hospitals. The patients were divided into an NI group and control group according to the occurrence or lack of occurrence of NI within 48 hours after surgery, respectively. Age, gender, hip fracture pattern, whether to operate, surgical treatments, and comorbidities were recorded as variables. A total of 9806 elderly hip fracture patients (60 years) were included, 1977 of whom were patients diagnosed with NI. The control group consisted of randomly drawn cases from the 9806 patients from different hospitals with a rate of one NI patient: four patients without NI. Patient gender, age, and in particular the number of comorbidities were associated with occurrence of NI. Using regression models to predict infection outcomes based on the number of comorbidities had an area under the curve (AUC) of 0.714, while using the Charlson comorbidity index (CCI) yielded a smaller value of 0.694. The most common comorbidities of this elderly cohort were chronic respiratory disease, hypertension, diabetes mellitus, cerebrovascular disease, and coronary heart disease. Older age, male gender, and greater number of comorbidities were found to be associated with the occurrence of NI. In particular, the number of comorbidities was the most accurate predictor of NI occurrence, and when used to build a regression model, it had greater predictive capability than CCI to predict NI in elderly hip fracture patients. Additionally, the common diseases of the elderly should be primarily considered when investigating the relationship between comorbidities and NI in older patients.

Background Pulmonary fibrosis (PF) is a devastating disease characterized by remodeling of lung architecture and abnormal deposition of fibroblasts in parenchymal tissue and ultimately results in respiratory failure and death. Preclinical studies suggest that mesenchymal stem cell (MSC) administration may be a safe and promising option in treating PF. The objective of our meta-analysis is to assess the efficacy of MSC therapy in preclinical models of PF. Methods We performed a comprehensive literature search in PubMed, EMBASE, Web of Science, and Cochrane Library databases from inception to March 17, 2021. Studies that assessed the efficacy of MSC therapy to animals with PF were included. The SYRCLE bias risk tool was employed to evaluate the bias of included studies. The primary outcomes included survival rate and pulmonary fibrosis scores. Meta-analysis was conducted via Cochrane Collaboration Review Manager (version 5.4) and Stata 14.0 statistical software. Results A total of 1120 articles were reviewed, of which 24 articles met inclusion criteria. Of these, 12 studies evaluated the survival rate and 20 studies evaluated pulmonary fibrosis scores. Compared to the control group, MSC therapy was associated with an improvement in survival rate (odds ratios (OR) 3.10, 95% confidence interval (CI) 2.06 to 4.67, P < 0.001, I2 = 0%) and a significant reduction in pulmonary fibrosis scores (weighted mean difference (WMD) 2.05, 95% CI −2.58 to −1.51, P < 0.001, I2 = 90%). Conclusions MSC therapy is a safe and effective method that can significantly improve the survival and pulmonary fibrosis of PF animals. These results provide an important basis for future translational clinical studies.

This paper is dedicated to developing high-efficiency face detection and tracking method for big dynamic crowds or numerous pedestrians. Three modules constitute the proposed method, i.e., face candidate generation, face candidate verification, and face target tracking. In this work, face candidates are localized using the features of the face area, edge information, and skin color. Non-face parts in the face candidates are further verified by the C-SVM learning model and then removed, by which the face targets can be generated with lower computation-complexity and satisfactory accuracy than other approaches. Finally, the face targets are tracked by an efficient and reliable searching scheme for improving the effective face detection rate. Experimental results show that the average face detection rate (FDR) of 85%, average effective FDR of 95%, a frame rate of 28–66 frames per second (fps), and about 30 faces detected per frame are obtained from various test videos with big dynamic crowds or numerous pedestrians, indicating the feasibility of the proposed method to achieve unconstrained face detection with high-efficiency and cost-effectiveness. This result makes the proposed method more attractive for the video surveillance system as compared to other approaches, especially in the high computational complexity-based methods.

The applications in high-power fields of white light-emitting diodes (WLEDs) are restricted due to their poor thermal stability. Transparent Y3Al5O12:Ce3+ phosphor-in-glass (YAG-PiG) provides an efficient way to resolve this problem. In this work, novel transparent Te/Pb-free YAG-PiGs are successfully prepared via a facile screen-printing route. It is revealed that 5 mol% Eu2O3 optimizes the concentration in substrate glass. Slight erosion of YAG particles occurs in the as-prepared samples. With increasing YAG concentration and film thickness, the intensities of photoluminescence spectra of YAG-PiGs increase. The energy transfer from Eu3+ to Ce3+ is greatly suppressed. Superior thermal stability and high quantum efficiency are obtained. The optimal optical performance values in terms of a luminous efficiency of 117.2 lm/W, a correlated color temperature of 5859 K and a color rendering index of 77.2 are achieved in YAG-PiGs. All of the results reveal that the as-prepared YAG-PiGs are promising candidates for high-power WLEDs.

The complexity of enterprises’ annual reports has increased significantly under supervision. Although the interactive relations of enterprises attracted interest both among scholars and practitioners, however, the decision support information is scattered in heterogeneous and enormous data. Here introduces a new learnable deep network—which implements an inference for entity- and relation-centric representations of multilayer, dynamical but sparse system. The results show the approach supporting accurate predictions from real data extracted from financial reports. Indeed, the method shows robustness with incomplete data, thus representing a valuable tool for gaining insights on privacy-protected financial systems.

There is a lot of unstructured text information in the notes to financial reports, also, text mining and information extraction are the difficulties in automatic processing of enterprise financial reports. In order to solve the problem of information extraction and text analysis for cross-paragraph events, this paper use the method of graph theory to construct the whole text features, and form a semantic block perception and classification method that embodies the chapter-semantic block-sentence-vocabulary feature words and their interrelations. Thus, it provides a systematic solution for extracting text information from financial report in large quantities, and offers a practical application scenario.

This paper proposes a model to extract textual information from financial reports automatically. It takes event extraction as the core, maps narrative information of financial reports into the concepts of financial accounting field, and forms the integration of heterogeneous data of distributed financial information. This study shows that the model can identify text events in large-scale financial reporting corpus, automatically extract events and theirs attribute information, and convert them into structured data. Moreover, this paper presents and evaluates the effect of the model in extracting information from annual reports of listed companies. The experimental results turn out that the model provides semantic mapping between text events and domain knowledge concepts, which is reasonable and reliable to be applied in the field of financial statement analysis.

The number of companies using social media to interact with users has been increasing. By analyzing the content generated by users online and mining the information contained therein, companies have applied them to product management and innovation, improving the competitiveness of enterprises. In the face of growing user-generated content, how to achieve effective information mining and transform into product knowledge has posed a challenge to the enterprise. In the background of smart phone products, this paper puts forward the integrated method and key technology of innovation knowledge management based on user-generated content, which should be able to provide a systematic solution for the interactive innovation knowledge management.

This paper presents a driver assistance system for vehicle detection and inter-vehicle distance estimation using a single-lens video camera on urban/suburb roads. The task of vehicle detection on urban/suburb roads is more challenging due to their high scene complexity. In this work, the still area of frame inside the host vehicle is first removed using temporal differencing, followed by detecting vanishing point. Segmentation of road regions is then conducted using vanishing point and road’s edge lines. Shadow regions at the bottoms of vehicles verified using the HOG feature and an SVM classifier are utilized to detect vehicle positions. The distances between the host and its front vehicles are estimated based on the locations of detected vehicles and vanishing point. Experimental results show varied performance of vehicle detection with different scenes of urban/suburb roads and the detection rate can achieve up to 94.08%, indicating the feasibility of the proposed method.

Background The basic endoscopic instruments are not suitable for removing calcified or hard discs in patients with thoracic disc herniations (TDH). We describe a percutaneous endoscopic technique for the treatment of calcified TDH using an endoscopic drill system with a T rigid bendable burr. Methods Eleven patients (8 males, mean age 42.1 years) with single-segmental calcified TDH were treated with percutaneous endoscopic surgeries. Results Our technique using this endoscopic drill system with a T rigid bendable burr is safe and effective for the treatment of calcified TDH. Conclusions Percutaneous endoscopic decompression using the T rigid bendable burr is a safe and reproducible surgical procedure for the treatment of calcified TDH.

This paper proposes a robust method for detecting copy-move forgery in images under various JPEG compression and Gaussian noise and blurring attacks. The method comprises feature extraction, feature matching, and duplicate block identification. The fast Fourier transform (FFT), singular value decomposition (SVD), and principal component analysis (PCA) are utilized for feature extraction. Then, the cascading matchers of FFT, SVD, and PCA are adopted for feature matching. Matched blocks are identified using cascade filtering with city block, horizontal, vertical, and frequency filters. Finally, the pixels on upper left corners of detected duplicate blocks are output for visual inspection. The major contributions of this paper are: (1) the proposed method is fully threshold-free; (2) only one-dimensional features are generated using FFT and SVD for feature matching; and (3) a high accuracy rate (> 97 %) is obtained even if the JPEG quality factor Q is 20. In extensive experiments, a 98 % accuracy rate and a 6 % false negative rate were obtained for the worst case of Q?=?20 and a region size of 32?×?32 pixels compared to existing works, indicating the feasibility of the proposed method.

Background The understanding for the impact of petrochemical pollutants exposure on renal functions is limited. Objectives Our study examined the associations between renal functions and pollutants exposure in adult residents living in the vicinity of a petrochemical industry. Methods We recruited 2069 adult residents near a big petrochemical complex in Taiwan in 2009–2012, and they were categorized into high exposure (HE) and low exposure (LE) groups based on their address to source by 10 km radius. Study subjects were measured the urinary levels of arsenic, cadmium, mercury, thallium, and 1-hydroxypyrene (1-OHP). The estimated glomerular filtration rate (eGFR) was calculated using the Taiwanese Chronic Kidney Disease Epidemiology Collaboration equation, and the chronic kidney disease (CKD) prevalence and risks were defined according to KDIGO 2012 guidelines. Adjusted generalized linear and logistic regression models were applied to evaluate the associations between petrochemical exposure and renal functions. Results Subjects in the HE areas had significantly lower eGFR, higher CKD prevalence, and higher levels of urinary arsenic, cadmium, mercury, thallium and 1-OHP. The closer to complex and high exposure group of study subjects were significantly associated with the decrease in eGFR, higher ORs for CKD and high-intermediate risk of CKD. In addition, the study subjects who had two-fold urinary arsenic and 1-OHP levels were significantly with decreased 0.68 and 0.49 ml/min/1.73 m2 of eGFR, respectively. Conclusions Residing closer and higher arsenic and polycyclic aromatic hydrocarbon exposure were associated with the renal impairment and risks of CKD among the residential population near the petrochemical industry.

This paper presents a real-time face detection system using a moving camera. The proposed system consists of three modules, including (1) detection of face candidates: Face candidates are generated using the information of skin color, edges, and face area, (2) verification of face candidates: HOG (Histogram of Oriented Gradient) features are generated from face candidates and a two-class C-SVM (Support Vector Machine) classifier with pretrained face samples is employed to determine whether face candidates are real faces or not, (3) face tracking: Overlapping area of two face targets in current and previous frames is estimated to determine whether the tracking will be continuous or not. By use of estimation of face size, the proposed method can avoid a huge amount of computation time that is required by a point-by-point scanning way in conventional methods. Moreover, the accuracy of the face detection can be improved greatly. The proposed system can successfully detect most faces of the crowds in open space, which is beneficial for quickly searching the specified persons to prevent the occurrence of possible criminal events.

Proposed method has good performance for a moving camera without additional sensors.Proposed method works well for tracking overlapping objects with scale changes.Proposed method outperforms the-state-of-art methods. This paper presents an effective method for the detection and tracking of multiple moving objects from a video sequence captured by a moving camera without additional sensors. Moving object detection is relatively difficult for video captured by a moving camera, since camera motion and object motion are mixed. In the proposed method, the feature points in the frames are found and then classified as belonging to foreground or background features. Next, moving object regions are obtained using an integration scheme based on foreground feature points and foreground regions, which are obtained using an image difference scheme. Then, a compensation scheme based on the motion history of the continuous motion contours obtained from three consecutive frames is applied to increase the regions of moving objects. Moving objects are detected using a refinement scheme and a minimum bounding box. Finally, moving object tracking is achieved using a Kalman filter based on the center of gravity of a moving object region in the minimum bounding box. Experimental results show that the proposed method has good performance.

This paper proposes an effective image forgery detection scheme that identifies a tampered foreground or background image using image watermarking and alpha mattes. In the proposed method, component-hue-difference-based spectral matting is used to obtain the foreground and background images based on the obtained alpha matte. Next, image watermarking based on the discrete wavelet transform, discrete cosine transform, and singular value decomposition is used to embed two different watermarks into the foreground and background images, respectively. Finally, the difference between the obtained singular values is used to detect tampering of foreground or background image. Experimental results show that the proposed method performs well in terms of image forgery detection.

Camera tampering and abnormalities are examined for video surveillance system.Brightness, edge details, and histogram information are computationally efficient.The system runs at 20-30frames/s, meeting the requirement of real-time operation.An average of 4.4% of missed events indicates the feasibility of proposed method. Camera tampering may indicate that a criminal act is occurring. Common examples of camera tampering are turning the camera lens to point to a different direction (i.e., camera motion) and covering the lens by opaque objects or with paint (i.e., camera occlusion). Moreover, various abnormalities such as screen shaking, fogging, defocus, color cast, and screen flickering can strongly deteriorate the performance of a video surveillance system. This study proposes an automated method for rapidly detecting camera tampering and various abnormalities for a video surveillance system. The proposed method is based on the analyses of brightness, edge details, histogram distribution, and high-frequency information, making it computationally efficient. The proposed system runs at a frame rate of 20-30frames/s, meeting the requirement of real-time operation. Experimental results show the superiority of the proposed method with an average of 4.4% of missed events compared to existing works.

The infrared image of solar cell's electroluminescence (EL) is one of the important means of hidden defects detection. In order to improve the automatic recognition rate of defect images, this paper adopts improved invariant moments for feature extraction. The scale factor of the improved invariant moments is eliminated by transformation. Therefore they have the properties of translation, rotation and scale invariance simultaneously in discrete state. At the same time, Support Vector Machine (SVM) is used to distinguish the defect image. The system which combined invariant moments with SVM is applied to classify the debris, crack, off-grid, open weld and black pieces. The recognition rate of 5 kinds of defects has reached more than 90%.

In order to seek a better way of control in sewage treatment, a control system which consisted of water unit, sand unit, the oxidation ditch unit, precipitation unit and sludge dewatering unit was designed. The paper investigates various controllable parameters in sewage treatment system and the way of present common automation control. We designed manual control variable aeration program and two automatic control subroutine which included thickness grille and pumping station by using WIN 32 software. The program is designed in Siemens STEP 7 V5.5 software development platform and chose the 10 input contacts which are I0.0~I0.7, I1.0~I1.1 and 10 output contact which are Q1.0~Q1.1, Q0.0~Q0.7.This design achieves automatic control and improves the purifying efficiency on the premise of ensuring water quality.

In order to improve the efficiency of electrostatic precipitators, a control system of constant current source based on Single Chip Microcomputer (SCM) is designed. In the control process, we use the pulse signal from microcontroller P1 port as digital signals of the switch. By changing the number of contact closure control, we achieve steady flow output of different magnitude. By using closed-loop feedback control, we achieve constant monitoring of dust concentration and ensure it compliance with outlet concentration of national requirements. The results show that microcontroller control system has a strong anti-interference, high accuracy, ease of programming, etc. Used in the electrostatic precipitator, collection efficiency can be further improved.

Automatic identification of defects on solar cell modules is the key of improving components efficiency of power generation and achieving the maximum utilization of energy[1]. This paper took the debris defects as an example. Considered the fact that scale factor would have an impact on moment invariants in discrete state, this paper adopted an improved moment invariant for the image feature extraction of debris defects. The scale factor of the new moment invariants is eliminated by transformation. Therefore they have the properties of translation, rotation and scaling simultaneously. Meanwhile, SVM (Support Vector Machine) classifier was used to identify the debris defects. The experimental results show that, compared with the traditional moment invariants, the identification rate of using the improved moment invariants for feature extraction is 96%.

Based on Abaqus/explicit dynamics finite element program, an ax symmetrical numerical model, the infinite fringe condition and friction contact condition were built, and then the surface contact stress condition of the dynamic consolidation was studied. The time-load properties of dynamic consolidation, the spread law of contact pressure for rammer bottom and the friction influence to contact stress between the hammer and foundation were gained. The results indicate that the dynamic consolidation load can be simplified to triangular load with the weight of the hammer itself; the contact stress distribution between the hammer and the foundation is not uniform; and frictionless contact hypothesis can led errors to the simulated result.

Transgenic Bt-cotton now dominates the cotton-growing belt in northwestern China where there are few natural plant refuges to act as sources of moths susceptible to Bt toxin. As an initial step towards developing an insect resistance management (IRM) plan for the pest moth, Helicoverpa armigera, on Bt-cotton in this part of China, we assessed the potential of six crops grown in two configurations to act as refuge hosts for susceptible moth production in both broad-acre and small-holder farms. Egg and larval abundance indicated that H. armigera had a preference for chickpea, pigeon pea, and corn, over cotton, sorghum, and benne (sesame). There were no significant differences in egg or larval abundance between plot and strip configurations of these crop hosts. We found that sorghum was not attractive to H. armigera, contrary to the findings in other cotton production areas. Moreover, chickpea, pigeon pea, and corn were determined to be potential refuge hosts based on egg and larval abundance over the growing season. From the adult moth population dynamics in broad-acre and small-holder farms, the efficiency of alternative refuge crops, and local agricultural practices, we recommend that spring corn be grown as a strip crop as part of an IRM strategy to improve the probability of Bt-susceptible moth production and mating with resistant moths in broad-acre farms. In small-holder farms where current agricultural practices are entrenched, wheat and summer corn should be evaluated as refuge crops in the future.

Topology and operation principle of a novel doublysalient permanent magnet motor (DSPM) named switchfluxing permanent magnet motor (SFPM) are analyzed. Atfirst, based on the design principle of DSPM, originaldimensions are determined. Secondly, after the physical modelof motor is built, based on finite element analysis, the magneticfield distributions, flux densities in air-gap with no-load, magnetize and demagnetize, open-circuit flux-linkage, back-EMF, winding inductance at different conditions areinvestigated. At last, the motor exhibits higher torque density, most appropriates for brushless AC operation and so on. Theresults provide a foundation for analysis, design andparameter optimization.

In recent years, with the increasing development andapplication of wind power technology, the proportion of thewind power in power system is greater and greater. So, theconnection of wind power impacts on power system a lot. Inthe paper, based on the variable speed constant frequencydoubly-fed wind power generator, the IEEE-14 system isinjected to the wind farm. It adopts the method of combinationof steady and transient to analyze and get the maximumcapacity of stability for the wind power system. Simulationresults verify the accuracy of the method and determine themaximum capacity of wind farm.

In recent years, with the great success of sparse representation on face recognition, sparse representation based classification (SRC) and collaborative representation based classification (CRC) are two most popular methods, among which SRC with L1-norm minimization has a relatively better recognition rate but it is time consuming while CRC with L2-norm minimization has a relatively better time efficiency but recognition performance is lower than that of SRC, especially when face images are impaired or undesirable outliers are involved. To achieve both time efficiency as CRC and better recognition performance as SRC, a novel method called adaptable dense representation with CRC (ADR+CRC) is presented, which utilizes ADR for dictionary decomposition using the technique of low-rank matrices recovery to improve the deficiency of CRC that has poor recognition performance when face images are corrupted due to disguise and occlusion. Experimental results show the superiority of the proposed method when compared with the state-of-the-art methods.

Based on investigation and survey, the conformation and the distribution for underground goaf are gotten. The goaf can be completely filled by drilling holes and grouting with the mixture of sand and water, using masonry border to isolate and filtrate the filled space and unfilled space. The shaft fills with cement stabilized soil without settlement. The result shows that latent threats remove during expressway opening for 10 years and achieve expected technical feasibility, economy, and rationality.

As one of important technologies of IOT (Internet of Things), WSN (Wireless Sensor Networks) has been used in tunnel environmental monitoring. Tunnel environment monitoring has its particularity that WSN nodes show linear topologies. Traditional routing algorithms in WSN do not consider the linear topology of sensor nodes in tunnel and are difficult to realize long-time data transmission in limited battery power. In this paper, we propose Power Control Dynamic Source Routing algorithm (PC-DSR) by the thought of cross-layer design. Routing table is established according to the distance between nodes and the residual energy of nodes and optimum transmission power is calculated in order to save nodes’ power and prolong the life-time of the whole networks. Simulation results show that the novel algorithm can save node's transmission power, which increase the WSN lifetime of 12.3%.

Abaqus finite element method and experimental study are carried out to research the silt embankment reinforced by sleeve valve barrel fracturing grouting method. Numerical model is determined based on the construction methods and mechanism, the calculation parameters are determined by experimental research. The displacement, force, and plastic are analyzed through comparative analysis of safety factor of attenuated embankment before and after reinforcement. The results show that the Reinforcement effect of sleeve valve barrel fracturing grouting method to stability attenuated roadbed is remarkable.

An efficient method for detecting moving vehicles based on the filtering of swinging trees and raindrops is proposed. To extract moving objects from the background, an adaptive background subtraction scheme with a shadow elimination model is used. Swinging trees are removed from foreground objects to reduce the computational complexity of subsequent tracking. Raindrops are removed from foreground objects when necessary. Performance evaluations are carried out using seven real-world traffic image sequences. Experimental results show average recognition rates of 96.83% and 97.20% for swinging trees and raindrops, respectively, indicating the feasibility of the proposed method.

A scheme based on a difference scheme using object structures and color analysis is proposed for video object segmentation in rainy situations. Since shadows and color reflections on the wet ground pose problems for conventional video object segmentation, the proposed method combines the background construction-based video object segmentation and the foreground extraction-based video object segmentation where pixels in both the foreground and background from a video sequence are separated using histogram-based change detection from which the background can be constructed and detection of the initial moving object masks based on a frame difference mask and a background subtraction mask can be further used to obtain coarse object regions. Shadow regions and color-reflection regions on the wet ground are removed from the initial moving object masks via a diamond window mask and color analysis of the moving object. Finally, the boundary of the moving object is refined using connected component labeling and morphological operations. Experimental results show that the proposed method performs well for video object segmentation in rainy situations.

A novel heterodyne interferometric ellipsometer was investigated to measure the thicknesses of thin films in the nanometer-accuracy.The depolarization effect of a Nonpolarizing Beam Splitter(NPBS) was characterized by the transmission-induced-retardance(TIR) between p and s components of a polarizing beam,reflectance ratio,transmittance ratio and reflection-induced-retardance(RIR),then a corresponding error model was established.The influence of the depolarization effect and misorientation of a multi-layer dielectric NPBS on the errors of ellipsometric parameters was investigated.Experimental results indicate that the fluctuation of the depolarization effect caused by the environmental temperatures,incident angles and the change of polarizating state has a major impact on the measurement accuracy,and it can not be eliminated by calibration.In order to implement the nanometer-accuracy,the misorientation angle must be smaller than 0.1°.Furthermore,it shows that the NPBS orientation angle errors for recombination of the measurement light and the reference light have more important contribution than another ones to the measurement accuracy.The thickness measurement error of thin film induced by NPBS is about 1.8-2.5 nm,which means that the NPBS is an assignable error source in the Mach-Zehnder interferometric ellipsometer.

Kernel-level Rootkit injects malicious code in the system kernel and realizes vicious function by modifying kernel code and data. The emergence of virtualization technology makes Rootkit hide itself and accesses system resources effectively. This paper proposes a kind of Rootkit based on VMM (VMRootkit) which can hide system process and system cannot find it. For realizing it, we firstly puts forward formal model of VMRootkit about cooperative concealment combined with Trojans thought about cooperative concealment, then researches the process switch and data structure of operating system and realized prototype of it, which can monitor system process and realize process depth hiding by modifying data structure related process view. Experiment shows that VMRootkit prototype meets the idea of cooperative concealment, can realize process depth hiding and has better hidden property than kernel-level Rootkit.

This paper is dedicated to the front vehicle detection and its distance estimation using one single-lens car video camera on the urban & suburb road roads. The proposed method mainly consists of road area detection and the front vehicle detection & distance calculation. Firstly, Hough transform is used to detect lines in which the appropriate straight lines are selected and their intersection points are exploited for obtaining the vanishing point. Then, both strong right and left edges are extracted and connected to the vanishing point for segmenting the road area, and on such area the bottom shadow of the front vehicle is utilized to locate the vehicle's position. Finally, the distance between the host vehicle and the front vehicle is calculated based on the position of a vehicle and the vanishing point. Experimental results show that the proposed technique can moderately detect the front vehicles on the urban & suburb roads with detection rate of 78% at least.

Taking the advantages of groove pedestal and pier pedestal, a new type of pre-tensioned pedestal is constructed. The new pedestal makes full use of the deck (also the bottom formwork of the beam) to bear the tensile force so as to reduce the quantity of the pedestal construction. The new pedestal can adapt to variable geotechnical conditions by properly enlarge the arm of the turnover moment and the self-weight. The new pedestal is optimized through the bearing capacity analysis of the anti-overturning, the anti-slipping, the table anti-compressing, the force transfer plate, and the cross tie beams. The stress distribution of local bearing bracket is calculated by the finite element method so as to be reinforced accordingly. Based on practical application in some project, the new pedestal has the features of technical feasibility, security & reliability, affordability, and convenience in operation.

This paper presents a visual surveillance scheme for cage aquaculture that automatically detects and tracks ships (intruders). For ship detection and tracking, we propose a robust foreground detection and background updating to effectively reduce the influence of sea waves. Furthermore, we propose a fast 4-connected component labeling method to greatly reduce the computational cost associated with the conventional method. Wave ripples are removed from regions with ships. An improved full search algorithm based on adaptive template block matching with a wave ripple removal is presented to quickly, accurately, and reliably track overlapping ships whose scales change. Experimental results demonstrate that the proposed schemes have outstanding performance in ship detection and tracking. The proposed visual surveillance system for cage aquaculture triggers an alarm if intruders are detected. The security of cage aquaculture can be increased. The proposed visual surveillance can thus greatly help the popularization of cage aquaculture for ocean farming.

Bismuth telluride thin films with layered nanostructure have been fabricated by radio frequency (RF) mag- netron sputtering. Thin films were deposited at various substrate temperatures and durations with a single Bi2Te3 target. The microstructures and chemical compositions of these films were characterized by X-ray diffraction (XRD), scan- ning electron microscope (SEM) and energy dispersive spectroscope (EDS). Electrical transport property and Seebeck coefficient were measured on these thin films. The results show that substrate temperature is a key factor on the micro- structure and transport property of bismuth telluride thin films. High temperature is beneficial for the formation of lay- ered nanostructure and the enhancement of power factor. The highest power factor was obtained on the thin film de- posited at 400℃. However, Te deficiency was observed in these thin films. Thus thermoelectric property would be further enhanced by optimizing composition of these thin films.

Research highlights? We proposed a method for hand gesture recognition based on Gabor filters and support vector machines under varying illumination. ? The proposed method is robust against varying illumination and insensitive to hand-pose variations. ? The proposed method allows users to wear either a long- or short-sleeve shirt. ? The recognition rates are improved from 72.8% to 93.7% by using the proposed hand-pose correction module. In this paper, we present a novel approach for hand gesture recognition based on Gabor filters and support vector machine (SVM) classifiers for environments with varying illumination. The proposed method (1) is robust against varying illumination, which is achieved using an adaptive skin-color model switching method; (2) is insensitive to hand-pose variations, which is achieved using a Gabor filter-based gesture angle estimation and correction method; (3) allows users to wear either a long- or short-sleeve shirt, which is achieved using a method that segments the hand from the forearm. To evaluate the robustness of the proposed method, we created a database of hand gestures in realistic conditions. A recognition rate of 96.1% was achieved using the proposed method. A dynamic gesture recognition system is also presented for real-life conditions. In the proposed system, the recognition results improved from 72.8% to 93.7% when the hand-pose correction module was used, indicating that using the responses of Gabor filters to estimate the hand-pose angle is effective.

Objective The precise cause of congenital sensorineural hearing loss (CSNHL) is unclear in many cases. In a previous study we found that offspring from guinea pigs with autoimmune sensorineural hearing loss (ASNHL) exhibited signs of SNHL. Here we studied women with autoimmune inner ear diseases (AIED) and their offspring. Our aim was to determine if autoimmune damage may be one of the causes of CSNHL. Methods Thirty-eight pregnant women with AIED were recruited. Thirty-three had ASNHL; one with autoimmune delayed endolymphatic hydrops (ADEH) and four with autoimmune Meniere's disease (AIMD). The following were assessed in all women: audiogram, auditory brain stem response (ABR), otoacoustic emission (OAE), vestibular function test and presence of inner ear antigens. The following were assessed in offspring from these women: OAE, ABR and presence of inner ear antigens. Results Five of the 38 children born to women with AIED had SNHL (an incidence much higher than normal). OAEs were not inducible in these children shortly after birth or within 46–100 days after birth. Abnormal ABR findings were apparent in these five children and inner ear antigens were detected in three of the five children (the mother's of these children were also positive for inner ear antigens). Conclusions These preliminary findings suggest that the prevalence of congenital ASNHL may be increased in offspring born to women with AIED.

Face recognition is quite challenging especially in a varying illumination scenario. In this paper, an effective method for face recognition based on dual-tree complex wavelet transform under low illumination environments is proposed. To alleviate the effect of lighting change on face image, logarithmic transform is performed, and a wavelet denoising model is then used to remove the low-frequency components in the details of LH, HL, and HH subbands. To enhance facial features, six difference images obtained from the four LL subbands are utilized and averaged to a so-called mean face. Results show that serious cast shadows on face images can be effectively removed such that face recognition rate can be greatly improved. To verify the feasibility of the proposed method, Yale face database B is used. Experimental results show that an overall recognition rate of 96% can be achieved.

In a fault-tolerant on-chip network, overhead due to the Automatic Repeat-reQuest (ARQ) operation may significantly impact the performance. In this work, an intelligent prefetching scheme that can effectively mitigate the performance hits from the ARQ overhead is proposed. Specifically, a packet-based retransmission scheme is incorporated to improve payload utilization while using Error-Detecting Code (EDC). A Virtual Cut-Through (VCT) switching is implemented to alleviate drastic performance degradation in dealing with the damaged data caused by noise upsets during packet transmissions. Potential performance advantages in terms of packet latency and transmission throughput were carefully analyzed to validate the practice of our proposed prefetching scheme in the designed network on-chip systems.

The detection of copy-move forgery image is important in the field of blind image forensics because it is of pure image processing technique without any support of embedded security information. The proposed method consists of a boosting scheme, feature extraction and similarity matching for the detection of duplicated regions. The boosting scheme comprises an estimation of dark channel, histogram equalization and grayscale layering, by which the number of image blocks on each subimage layer can be dramatically reduced so that the time efficiency of subsequent lexicographical sorting and similarity matching can be greatly improved. Experimental results show that the proposed boosting scheme can significantly enhance the computation efficiency and have a good detection rate. Moreover, the propose method is robust to any angles rotation attack.

A nighttime driver-assistance system is developed in this study. Through lane detection, neighboring vehicle detection, lane deviation detection, and front vehicle distance estimation of real-time road images retrieved using a charge-coupled device camera, the developed system can issue timely alarms to warn drivers and increase their driving safety at nighttime. In lane detection, the developed system employs clear edge information and lane orientation, and performs edge operations and lane marking using Hough Transform. Vehicle detection is performed by recognizing vehicle characteristics (e.g., tail lights and symmetry) and colors. The front vehicle distance is estimated by counting the number of lane segments. The experimental results of numerous highway image tests show that the developed system can effectively facilitate safe driving in a common environment. Keywords: Driver-assistance system, Lane detection, Neighboring vehicles detection, Lane deviation detection, and Vehicle distance estimation.

The mechanisms underlying insulin sensitivity and fat tissue distribution in chronic renal insufficiency remain unclear. Previous studies have shown the benefits of angiotensin II receptor blockers on moderately nourished to well-nourished patients with the metabolic syndrome. The current study explored the effect of losartan, the first selective angiotensin II receptor blocker, on insulin sensitivity and visceral fat tissue distribution in a 5/6 nephrectomized (N) rat model and investigated the expression of adipose tissue adipocytokines. Male Sprague-Dawley rats (200 g to 250 g) were subjected to 5/6 nephrectomy, and the adipocytes isolated from the visceral fat tissues were then studied. Results showed that desmin expression was significantly suppressed and systolic blood pressure was successfully normalized in the losartan-administered (NA) group. The weight of the visceral fat pad remarkably decreased in the N and NA groups (100 mg/500 ml drinking water) compared with the control group. The weight did not decrease further in the NA group compared with the N group. Insulin resistance was more remarkable in the N group compared with the control and NA groups. Moreover, the adipose tissue expression of adiponectin and leptin was downregulated whereas that of resistin was upregulated in the N group compared with the control group. However, the adiponectin, leptin, and resistin adipose tissue expression returned to their basal values in the NA group. These findings indicated that losartan administration ameliorated renal injury, systolic blood pressure, and adipocytokine imbalance of the adipose tissue in chronic renal insufficiency. Insulin sensitivity was not improved.