Search

Objectives To systematically evaluate the efficacy and safety of Arbidol and lopinavir/ritonavir (LPV/r) in the treatment of coronavirus disease 2019(COVID-19) using a meta-analysis method. Methods The China Knowledge Network, VIP database, WanFang database PubMed database, Embase database, and Cochrane Library were searched for a collection of comparative studies on Arbidol and lopinavir/ritonavir in the treatment of coronavirus disease 2019. Meta-analysis was used to evaluate the efficacy and safety of Arbidol and lopinavir/ritonavir in the treatment of COVID-19. Results The results of the systematic review indicated that Arbidol had a higher positive-to-negative conversion rate of SARS-CoV-2 nucleic acid on Day 7 [P=0.03], a higher positive-to-negative conversion rate of SARS-CoV-2 nucleic acid on Day 14 [P=0.006], a higher improvement rate of chest CT on Day 14 [P=0.02], a lower incidence of adverse reactions [P=0.002] and lower rate of mortality[P=0.007]. There was no difference in the rate of cough disappearance on Day 14 [P=0.24] or the rate of severe/critical illness [P=0.07] between the two groups. Conclusions Arbidol may be superior tolopinavir/ritonavir in the treatment of COVID-19. However, due to the small number of included studies and the number of patients, high-quality multi-centre large-sample randomized double-blind controlled trials are still needed for verification. This article is protected by copyright. All rights reserved.

Background The aim of this study was to conduct a meta-analysis comparing the safety and feasibility of laparoscopic versus open resection for gastric gastrointestinal stromal tumors (GISTs) larger than 5 cm. Method We searched the Cochrane Library, PubMed, and Embase for relevant articles. Randomized and nonrandomized clinical trials were identified and included in this study. Searching for related articles on large GIST (>5 cm) for laparoscopic resection (laparoscopic group [LAPG]) and open resection (open group [OG]), RevMan 5.3 was used for data analysis, comparing 2 groups of operation time, intraoperative blood loss, complications, length of hospital stay, recurrence rate, disease-free survival, and overall survival. Results Seven studies including 440 patients were identified for the meta-analysis. Meta-analysis revealed that LAPG had less bleeding, shorter postoperative hospital stay, and a better 5-year disease-free survival. There was no significant difference between LAPG and OG in operation time, postoperative complications, recurrence rate, and overall survival. Conclusion Laparoscopic resection of large (>5 cm) GIST is safe and feasible and has the advantages of less intraoperative blood loss and fast postoperative recovery, with a good outcome in the recent oncology.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has become a worldwide life-threatening pandemic. Lianhua Qingwen is believed to possess the ability to treat or significantly improve the symptoms of COVID-19. These claims make it important to systematically evaluate the effects of using Lianhua Qingwen with Western medicine to treat COVID-19. OBJECTIVE: To evaluate the safety and efficacy of combination therapy, employing Lianhua Qingwen with Western medicine, to treat COVID-19, using a meta-analysis approach. SEARCH STRATEGY: China National Knowledge Infrastructure, Wanfang Database, VIP Database, PubMed, Embase, and Cochrane Library databases were searched for studies evaluating the effect of Lianhua Qingwen-Western medicine combination therapy in the treatment of COVID-19. INCLUSION CRITERIA: (1) Research object: hospitalized patients meeting the diagnostic criteria of COVID-19 were included. (2) Intervention measures: patients in the treatment group received Lianhua Qingwen treatment combined with Western medicine, while the control group received either Western medicine or Chinese medicine treatment. (3) Research type: randomized controlled trials and retrospective study were included. DATA EXTRACTION AND ANALYSIS: Two researchers extracted the first author, the proportion of males and females, age, body temperature, course of treatment, rate of disappearance of main symptoms, duration of fever, adverse reactions, and total effectiveness from the literature. Odds ratio (OR) and 95% confidence interval (CI) were used as the effect value for count data, and mean difference (MD) and 95% CI were used as the effect value for measurement data. RESULTS: Six articles met the inclusion criteria, including a total of 856 COVID-19 patients. The meta-analysis showed that Lianhua Qingwen combination therapy achieved higher rates of fever reduction (OR = 3.43, 95% CI [1.78, 6.59], P = 0.0002), cough reduction (OR = 3.39, 95% CI [1.85, 6.23], P

Radiation portal monitors (RPMs) are globally employed in ports to decrease the illicit trafficking of nuclear materials. Most RPMs are generally considered as threshold devices because they utilize large plastic scintillators, which have limited energy resolution and no position sensitivity, to count the gamma-rays and neutrons emitted by nuclear materials. Hence, we designed an RPM detector system with NaI(Tl) detectors inserted into the plastic scintillators to realize gamma-ray source identification and positioning. In this work, a 2D gamma-ray source positioning algorithm based on the attenuation law and solidangle variation was studied with the simulation results, and the variation of the positioning deviations with the real positions was spline interpolated to calibrate the calculated position. The testing experiment showed a small root mean square error (RMSE) for both x (0.86 cm) and y (1.52 cm) after calibration.

The purpose of this paper is to use machine learning technology to build more user profiles in the process of customer segmentation to assist marketing decision-making. Specifically, by introducing cross features into the construction of Feature Engineering, the accuracy of target group prediction can be further improved and the user subgroup after feature crossing can be mined. In addition, this paper also proposes an improved decision tree model, which can build more comprehensive user profiles, and then assist in intelligent marketing. Firstly, both methods need to preprocess the data. In addition, for the subsequent feature crossing, it is necessary to discretize the continuous features and implement one-hot encoding for all data. In the process of discretization, the paper realizes the automatic selection of better discrete granularity value. A specific example is given and a comparative experiment is carried out to verify the effectiveness of the method.

The present study systematically evaluated the clinical effects of mesh-plug and Lichtenstein herniorrhaphy in the treatment of primary inguinal hernia. PubMed, Embase, and the Cochrane Library (cut-off: May 25, 2020) databases were searched to select randomized controlled trials (RCTs) on mesh-plug and Lichtenstein herniorrhaphy for the treatment of primary inguinal hernia. Articles that met the inclusion criteria were screened and evaluated for quality. RevMan 5.3 software was used to perform a meta-analysis of operation time, discomfort in the inguinal region, haematoma, seroma, infection, time to return to normal activities, incidence of postoperative chronic pain, and recurrence rate. Eleven RCTs with 1457 patients in the mesh-plug group and 1472 in the Lichtenstein group were included. Meta-analysis showed that the mesh-plug herniorrhaphy group had a shorter operation time than the Lichtenstein herniorrhaphy group [P

Analysis of built-up areas—the most significant artificial urban areas—reveals physical development processes. Unlike previous research involving medium-resolution remote sensing (RS) images, this study used built-up area maps generated from multiple high-resolution RS images with abundant built-up area edge information to analyze development in Zhengzhou. A transferable built-up area extraction (TBUAE) algorithm was developed to map the built-up area maps. The algorithm allows the developed deep learning model used on a certain satellite image to be eligible for other types of satellite images by altering the data distribution with adaptive Wallis filtering (DT-AWF). The proposed method alleviates the pressure of deep learning on the demand for new satellite image samples that are time-consuming and laborious. Additionally, the accuracy of built-up area mapping using this method exceeds 90%. Quantitative and qualitative analyses were conducted on the map results to observe the urban development of Zhengzhou from 2016 to 2020. We found that Zhengzhou has expanded rapidly since it was defined as a central city in central China in 2016. Additionally, the suburban built-up area has expanded rapidly and developed together with the central city. Further, affected by the policy, the built-up areas in different regions of Zhengzhou has changed differently, the urban edge is more simplified, and the urban internal structure is more compact.

Timely sensing the abnormal condition of the bearings plays a crucial role in ensuring the normal and safe operation of the rotating machine. Most traditional bearing fault diagnosis methods are developed from machine learning, which might rely on the manual design features and prior knowledge of the faults. In this paper, based on the advantages of CNN model, a two-step fault diagnosis method developed from wavelet packet transform (WPT) and convolutional neural network (CNN) is proposed for fault diagnosis of bearings without any manual work. In the first step, the WPT is designed to obtain the wavelet packet coefficients from raw signals, which then are converted into the gray scale images by a designed data-to-image conversion method. In the second step, a CNN model is built to automatically extract the representative features from gray images and implement the fault classification. The performance of the proposed method is evaluated by a real rolling-bearing dataset. From the experimental study, it can be seen the proposed method presents a more superior fault diagnosis capability than other machine-learning-based methods.

This paper discusses four different ultrasonic guided wave standards. Three of them are China’s national standards or industry standards: GB/T 31211-2014 “Nondestructive Testing Ultrasound Guided Wave Detection”, GB/T 28704-2012“Non-destructive testing—Test method for ultrasonic guided wave testing based on magnetostrictive effects”, and DL/T 1452-2015 “Thermal Power Pipeline Ultrasound Guided Wave Detection”. The another one is ASTM E2929:“Standard Practice for Guided Wave Testing of Above Ground Steel Piping with Magnetostrictive Transfusion”. Through six aspects in this article, including testing application scope, preliminary requirements, standard specimen and comparative specimen, distant amplitude curve and time gain curve, the existing difference between China and America is obvious and diversity. It is necessary to explore the underlying reasons for the connection of Chinese code and international code in the field of Non-destructive testing. During the standardization, anyone of the standard should be actually compared on the presentation of chart, and the verification and comparison of results, and lists the similarities and differences of each part based on GB31211. This paper provides reference for China to integrate with foreign standards in the field of ultrasonic guided wave detection of pressure vessel and pipelines.

Background: Although nonpharmacological therapies are recommended as first-line treatments for insomnia, they do not widely implement in practice owing to costly or time-consuming. As a result, pharmacotherapy remains to be commonly prescribed for patients with the sleep disorder. Pharmacotherapy for insomnia consists of different types of drugs. Few studies focused on comprehensively evaluating all available drugs for insomnia. Our review aims to compare efficacy and safety of pharmacological and nonpharmacological treatments by synthesizing direct evidence and indirect evidence to help clinicians and patients make informed decisions for insomnia. Methods: We will search the MEDLINE, EMBASE, and Cochrane Register of Controlled Trials between January 2000 and June 12, 2021. Randomized controlled trials of pharmacological and nonpharmacological interventions for insomnia will be included. Study quality will be assessed on the basis of the methodology and categories described in the Cochrane Collaboration Handbook. Eight network meta-analyses were conducted. A Bayesian network meta-analysis would be performed, and relative ranking of agents would be assessed. A node splitting method will be used to examine the inconsistency between direct and indirect comparisons when a loop connecting 3 arms exists. Results: The results of this paper will be submitted to a peer-reviewed journal for publication. Conclusion: The conclusion of our study will provide updated evidence to rank the effectiveness and safety of pharmacological and nonpharmacological interventions for insomnia. Ethics and dissemination: Ethical approval is not applicable, as this study is a network meta-analysis based on published trials. INPLASY registration number: INPLASY202160031

Periodontal tissue damage, accompanied by the degradation and destruction of periodontal tissue collagen, is one of the most clinically common complications and difficulty self-repair in patients with diabetes. Human periodontal ligament stem cells (PDLSC) are the undifferentiated mesenchymal cells that persist in the periodontal ligament after development of periodontal tissue and the ability of PDLSC osteogenic differentiation is responsible for repairing periodontal tissue defects. However, the reasons of high glucose environment in diabetic patients inhibiting PDLSC to repair periodontal tissues are unclear. To address these issues, we propose exposing PDLSC to high-sugar mimics the diabetic environment and investigating the activity of osteogenic differentiation and adipogenic differentiation of PDLSC. At the cellular level, high glucose can promote the adipogenic differentiation and inhibit osteogenic differentiation to decrease the self-repair ability of PDLSC in periodontal tissues. Mechanistically at the molecular level, these effects are elicited via regulating the mRNA and protein expression of C/EBPβ, PPAR-γ.

To meet the requirements of a large-scale soil moisture monitoring system, this dissertation developed a new type of capacitive soil moisture sensor based on the detection and amplification of the singal peak-to-peak value named PA-1 sensor. PA-1 sensor was calibrated and evaluated under static laboratory conditions. A new type of soil moisture sensor named PA-1 is developed, which is based on the relationship between soil moisture and soil relative permittivity. Circuit design, operating features and exterior design of the sensor are introduced. PA-1 is calibrated in solution samples using the standard calibration method. Calibration experiment results show that PA-1 has a very linear measurement curve. The performance of PA-1 is studied and compared to the widely used Decagon Company’s EC-5 capacitive soil moisture sensor. Experiment results show that PA-1 has advantages of high sensitivity, low temperature drift, strong tolerance to electromagnetic interference and low power consumption. Keywords: sensor, Precision Agriculture, low temperature drift, low power consumption.

Data visualization is an emerging technology in location-based service. In this paper, the principle of moving target tracking and the transformation of coordinates were introduced. Latitude-longitude pairs of moving object were obtained by globe satellite data receiver and the map matching were adopted to realize the real-time target tracking correspondingly. Finally, the measurement data in location-based services were analyzed and presented by data visualization technology. The experiment results show the validity of the method.

Neutrons produced by cosmic rays comprise the main factor in radiation hazards for astronauts and spacecraft during space exploration. A silicon-photomultiplier- (SiPM-) array-coupled Cs2LiYCl6: Ce 3 + (CLYC) detector was proposed to measure neutrons onboard spacecraft. Since both light-collection efficiency and thermal noise rate are proportional to a SiPM’s size, it is necessary to compare CLYC’s characterization when coupled with SiPM arrays of different sizes. In this paper, a 4 × 4 array and an 8 × 8 array, both of which are composed of 3 × 3-mm2 SiPM elements, were coupled to a Φ 38 mm × 38 mm cylindrical CLYC detector. The energy resolution, pulse-shape-discrimination (PSD) performance, and temperature dependence were tested with two gamma-ray sources and a neutron source. Results indicate that both energy resolution and PSD performance mainly benefit from the higher light-collection efficiency of the large array. The peak centroids of 137Cs varied by ∼ 20% in the testing temperature region from -35 °C to +55 °C.

Aim to produce metal strips in millimeter scale, the Top Side-pouring Single Roll Casting process and the Top Side-pouring Twin Roll Casting process were investigated in this paper, using commercially pure lead and commercial-purity aluminum as the experimental materials. Numerical simulation was conducted before the experiment. The results show that, the Top Side-pouring Single Roll Casting process and the Top Side-pouring Twin Roll Casting process can both realize the uniform flow distribution and rapid solidification, but the surface of the strips cast by the former are irregularity because of free solidification, while that from the latter present a state of rolling. And one can change the gauge of nozzle and the speed of cooling roll, to regulate the thickness of thin strips, and by changing the shape of the nozzle, the thickness distribution can be handled.

Medical waste high temperature steam sterilization is a non-incineration sterilization technology. Basing on discussion the principle of medical waste steam sterilization technology, the device composition and treatment process of medical waste steam sterilization were analyzed; the advantages and disadvantages of medical waste steam sterilization technology were compared. At last, the prospects of medical waste high temperature steam sterilization were proposed.

The pollution of livestock sewage is one of important pollution sources that can cause non-point pollution in Chinese country. On the basis of analyzing the characters of the livestock sewage, the treatment principles of livestock sewage are discussed. At last, the comprehensive treatment processes of livestock sewage are put forward and analyzed.

In order to improve the network lifetime and energy efficiency, an uneven clustering routing protocol based on energy load balancing (ELBUC) is proposed. In the cluster head selection phase, sensor nodes are selected as candidate cluster heads by turns in ELBUC; in the data transmission phase, it proposes a least energy consumption routing strategy, which comprehensively considers the candidate routing node’s energy and the number of its members, so that the cluster head which has fewer nodes in the cluster become the rely node. Simulation results show that ELBUC protocol not only significantly prolongs the lifetime of the network, but also effectively balance the energy consumption between nodes, and improve the network energy efficiency.

This paper constructed a wireless sensor network model which includes multi hop mechanism based on the theory of complex network. In the non uniform clustering algorithm, the selection of the competitive radius affects the lifetime of the whole network. The optimal hop mechanism is added into the growth phase of the scale free network model, which makes the probability of the link between the nodes relate to the actual distance between nodes. This paper also discusses how parameters C and parameters Rmax affect the degree distribution, network coverage, and the number of cluster heads in the entire network model. We use the theory to analyze the degree distribution of the network along with the growth of network. And we also use the software to simulate the network performance parameters. We find that with the increase of parameters C, the network of competitive radius is more heterogeneous, the number of cluster heads are lager, and the proportion of the value between (2,10) of nodes degree in the network are large, but the coverage rate of the network are low. We also found that with the increasing of the parameters Rmax, the number of cluster heads in the network are smaller, and the proportion of the value between (2, 10) of nodes degree in the network, and the coverage rate of the network would increase.

The internal high temperature of tire not only reduces the service life of the tire, but also increases fuel consumption. An on-line monitoring system of temperature field in tire is designed. The temperature measurement module of lower computer is made up of temperature measurement network of thermocouple, single chip microcomputer and other modules. The upper computer software is designed under the environment of VC ++, making use of the serial port to realize communication. The functions such as temperature collection, analysis, display and storage capabilities were realized. The system has the advantages of convenient use, reliable operation, solving the difficult problem of obtaining tire actual temperature.

In order to improve the accuracy of lateral and vertical target recognition in a car-following situation, the box plot is used to analyze and filter discrete points to overcome the LIDAR point data error; application of the modified adaptive K-means clustering algorithm which is based on the clustering evaluation index is applied to process the LIDAR point from LUX4; the candidate targets are output by clustering results. The test results show that the obstacle detection algorithm is more robust and reliable in the car-following situation.

Based on the comparison of battery energy storage system, super capacitor energy storage system, superconducting storage system, flywheel energy storage system, hybrid energy storage system composed by battery and super capacitor is proposed. By Analysis the performance of the system, it can be know that the system has characteristics of high specific power and high specific energy, and the battery and super capacitor device can be flexibly configured, which make energy storage system performance greatly improved. This template explains and demonstrates how to prepare your camera-ready paper for Trans Tech Publications. The best is to read these instructions and follow the outline of this text.

Large-scale livestock pollution has become the third largest source of pollution following industrial pollution and domestic pollution. The possible dangers of livestock sewage pollution on rivers, lakes, underground water, soil, human health are pointed out. Pretreatment is necessary for processing of livestock sewage treatment. The principle, advantages and disadvantages, applicability of three modes of livestock sewage treatment including land spreading, natural treatment and industrialized treatment are summarized. It is very necessary to study and develop efficient, low-cost, resource utilization of livestock sewage treatment technology according to local conditions.

Subgrade compaction is an important task in modern traffic fields, where GPS ranging technology is one of the key technologies in intelligent compaction. In the paper, NMEA communication protocol was illustrated, the statement of GPGGA was analyzed, and the extraction of the single point geographical coordinate was realized correspondingly. Aimed at the phenomenon of data loss in signal drift and data acquisition, the missing data estimation algorithm for longitude and latitude was adopted to obtain the complete data sets as well. Finally, the deficiencies of the traditional longitude and latitude distance measuring formula were analyzed and a new model of measuring distance of longitude and latitude was discussed. The experimental results show that the method has the better stability of measurement, the higher test accuracy, which has a good application prospects in intelligent compaction. However, the real-time property of data processing still needs further research.

Constructed wetlands are new sewage treatment technology, which have advantages of good decontamination effect, low operating costs and easy maintenance. Base on analysis of constructed wetlands composition and purification mechanism, the constructed wetlands purification influence factors are summarized, and the problems and solutions of constructed wetlands are pointed out. Carrying out in-depth study on constructed wetlands design, operational control and maintenance management to improve comprehensive benefits of wetland sewage purification technology, have great practical significance and far-reaching social significance.

Medical waste is characteristic with high pollution and high risk. On the basis of analyzing typical transport process and disposal process of rural medical waste, the problems of rural medical waste management and disposal are pointed out. Countermeasures to strengthen rural medical waste management and disposal are proposed.

Optical components with complex surfaces are more and more widely applied, but it is very difficult to manufacture these components by using traditional mechanical fabricating methods. Fast tool servo system can manufacture these complex surfaces or microstructures efficiently and accurately. The relative position between the tool and workpiece surface will vary continuously in the fast tool servo machining process, owing to the height change of workpiece profile in the same circle, and this will worsen the cutting conditions and debase the machining accuracy. In this paper, the cutting characteristics are studied in the fast tool servo machining process of complex workpiece, including the varying rule of cutting angle, and its influences on the rake angle and back angle, and the choice of machining parameters. Furthermore, the conditions for identifying tool interference are given. On the basis of the above work, two kinds of typical complex workpieces are manufactured by using fast tool servo system, in...

This paper puts forward a type of device which can automatically measure the operation status of the module exchange in 112-system according to the measuring problems in the terminations of both the small-capacitance telephones and the burglar alarms. In this device, the measuring method of three-terminal phase is adopted, which can effectively measure the electric resistance and capacitance between the different layers of the lines. Therefore, it can complete the measurement of the subscriber lines. In addition, it is able to measure different types of switches and a variety of lines, and especially adds the measurements on the noise and the degree of balance. After its system goes through rigorous tests, the errors are measured to fulfill users’ demands, and thereby the purposes of saving manpower and improving the efficiency of measurement and feedback can be achieved.

Multiferroic NiFe2O4 (NFO)-BaTiO3 (BTO) bilayered thin films are epitaxially grown on (001) Nb-doped SrTiO3 (STO) substrates by pulsed-laser deposition (PLD). Different growth sequences of NFO and BTO on the substrate yield two kinds of epitaxial heterostructures with (001)-orientation, i.e. (001)-NFO/(001)-BTO/substrate and (001)-BTO/(001)-NFO/substrate. Microstructure studies from x-ray diffraction (XRD) and electron microscopies show differences between these two heterostructures, which result in different multiferroic behaviours. The heterostructured composite films exhibit good coexistence of both ferroelectric and ferromagnetic properties, in particular, obvious mag-netoelectric (ME) effect on coupling response.

Steam Assisted Gravity Drainage (SAGD) or non-SAGD heavy oil recovery process uses a considerable amount high-pressure steam and produces significant amount of oily wastewater. Conventional water treatment and steam generation process is very complex, producing poor quality water for reuse and low energy efficiency. Using evaporation process to replace those conventional treatment processes first emerged in Albert, North America. This eventually resulted in introducing conventional drum boiler to replace once-through steam generator to produce steam. The paper introduces evaporation technology to treat heavy oil wastewater and produce high-quality boiler feed water. It also provides comparison data between evaporation and conventional process (warm lime softening and weak acid cation ion exchange) from technical and operational aspects. Conclusion is that evaporation provides an alternate approach to produced water treatment, which is simpler, more cost effective and more reliable, and reduces complexity of the steam generation system. Additional steps can be taken to recover all liquid waste streams for reuse in the plant, resulting in zero liquid discharge. Key words: heavy oil wastewater, evaporation, boiler feed water, zero liquid discharge

This paper deals with the design and development of bipolar Ni/MH batteries. After optimizing the parameters of bipolar plates by adjusting electrode thickness and modifying the capacity ratio of two adjacent electrodes of a single cell, some bipolar Ni/MH stacks with a voltage of 6 V were assembled and examined. Electrochemical testing results showed that the bipolar battery has excellent high rate discharge and recharge characteristics, satisfying pulse discharge performance even in a low state of charge (SOC). Moreover, the battery showed good stability during pulse cycles as simulating hybrid electric vehicle working conditions. It would be a promising alternative for power storage system in hybrid electric vehicles.

A novel improved particle swarm algorithm named competition particle swarm optimization (CPSO) is proposed to calibrate the Underwater Transponder coordinates. To improve the performance of the algorithm, TVAC algorithm is introduced into CPSO to present anextension competition particle swarm optimization(ECPSO). The proposed method is tested with a set of 10 standard optimization benchmark problems and the results are compared with those obtained through existing PSO algorithms,basic particle swarm optimization(BPSO),linear decreasing inertia weight particle swarm optimization(LWPSO),exponential inertia weight particle swarm optimization(EPSO), andtime-varying acceleration coefficient(TVAC). The results demonstrate that CPSO and ECPSO manifest faster searching speed, accuracy, and stability. The searching performance for multimodulus function of ECPSO is superior to CPSO. At last, calibration of the underwater transponder coordinates is present using particle swarm algorithm, and novel improved particle swarm algorithm shows better performance than other algorithms.

The relationship between tension wheel equipment's transmission efficiency and angle changes is studied theoretically. Regarding the features of practical data, Solidworks 3D software is adopted to establish the tension wheel equipment model. Then such model is processed in ANSYS Workbench, and its Young's modulus, density and other physical parameters are set. The relationship between the coefficient of friction and tension is analyzed by static simulation. The dynamic simulation results show the movement of tension wheel equipment with different outside load is discussed, as well as the relationship between transmission efficiency and tension. The simulation verifies the correctness of the model and provides a new approach for the analysis of the reliability and working conditions of the catenary tension wheel equipment.

In this paper, an improved feature selection algorithm by conditional mutual information with Parzen window was proposed, which adopted conditional mutual information as an evaluation criterion of feature selection in order to overcome the deficiency of feature redundant and used Parzen window to estimate the probability density functions and calculate the conditional mutual information of continuous variables, in such a way as to achieve feature selection for continuous data.

Stock index series is Non-stationary, Nonlinear and factors with impact on stock index fluctuation are complex, a time series forecasting model combined ARIMA model and wavelet neural network is presented. The combined model uses BP neural network as the main framework, uses wavelet basis function instead of transfer function in the network, also add some inner factors of the time series mining by ARIMA model, as the part impute of Wavelet Neural Network. So it is more scientific and rational that using inner factors and external other factors. The last simulate experiment shows that the wavelet neural network forecasting model based on ARIMA has higher accuracy than ARIMA model or BP network.

Heavy machine is mainly used for large-scale, large parts of the processing, is the country's headed guard equipment. Heavy machine's non-normal shutdown will result in significant damage to the enterprise, how to effectively improve the maintenance of machine, maintain a normal and stable heavy machine urgently needed to study. In this paper, we choose some heavy machine manufacturer's heavy boring machine as object of study, then collect and process machine failure information, and apply the method of Failure Mode and Effects Analysis (FMEA) to analyze and calculate heavy boring's risk of failure modes, in accordance with results of the analysis to provide maintenance strategy to improve maintenance effectiveness. this study can be as reference for other studies' application FMEA on heavy machine.

This paper introduces a new domain-oriented distributed vulnerability scanning mechanism based on the studies of other vulnerability scanning systems, which have difficulties on dealing with network crossing, interceptor crossing and bottleneck effect, etc. After giving some description about domain-oriented distributed architecture, this paper introduces a SOA-like service providing mode. Following introduction leads to a new hierarchical strategy scheduling model that solves the problems of distributed scheduling management. A comparing experiment on the new scanning prototype and a Centralized scanner called Nessus is given at the end of this paper. At last, it comes to the conclusion that this new domain-oriented distributed vulnerability scanning mechanism has great performance on timing and accuracy.

The basic principle of wavelet neural network is analyzed and the learning algorithm is improved as well. Correspondingly, fault pattern recognition model is constructed based on improved wavelet neural network. Simulation experiment shows that improved wavelet neural network has good fault-tolerant capacity and global convergence. However, how to establish an objective criterion of parameter settings and enhance the real time capability of fault pattern recognition still need further research.

Data missing in data pretreatment has a serious effect on the accuracy of subsequent analysis results in data mining. In this paper, the cause of data missing and the corresponding effect on data mining were discussed. Then the missing pattern and the application limitation of traditional missing value estimation were analyzed as well. Finally, the estimation algorithm of missing value in MAR (missing at random) pattern was mainly studied and applied in fault classification based on wavelet neural network. The experiment results show the efficiency of the algorithm.

The flexible job-shop scheduling problem (FJSP) is an extension of the classical job-shop scheduling problem (JSP). This paper presents a hybrid genetic algorithm which incorporates the principle of ldquothe survival of the fittestrdquo from genetic algorithm (GA) into tabu search (TS) to solve the FJSP. According to the characteristics of the FJSP, an extended operation-based representation which simultaneously describes the sequence of operations and the assignment of operations to machines are applied to represent solution for the genetic algorithm, and solutions are constructed using a procedure that generates active schedules. Two effective crossover and mutation operators are proposed to adapt to the chromosome structure. After individuals of GA are obtained, TS is applied to improve these solutions. The neighborhood structures of TS are designed by extending proposition proposed by Balas and Vazacopoulos to FJSP. The hybrid algorithm is tested on a set of standard instance taken from the literature and compared with other approaches. The computation results validate the effectiveness of the proposed algorithm.

In this paper, a texture image segmentation algorithm based on improved wavelet neural network is proposed.This algorithm can overcome shortcomings of traditional threshold segmentation techonologies. By using texture features of images, a series of fractal texture feature parameters which will be taken as input layer factors of wavelet network are created by this algorithm. Then, the wavelet neural network is trained with self-adaptive pheromone volatilization mechanism and dynamic heuristic search strategy of improved ant colony algorithm. Finally, the trained wavelet neural network is taken as the classifier of image pixel to realize segmentation of texture images. Simulation experiment shows that, improved algorithm could realize self-adaptive segmentation based on different texture features of images and it is robuster. However, further researches on methods of improving convergence speed of this algorithm and objective criteria for assessing whether texture images have been segmented successfully or not are needed.

Pulse Coupled Neural Network (PCNN) is widely used in image processing for its basic characteristics of coupling mechanism and achieved some results. PCNN model has been improved as follows: Firstly, correlation coefficient is used to control the bonding strength. Secondly, the threshold setting is adjusted by the least error. Thirdly, A Trous transform is combined with PCNN model to form the combination forecasting model. The improved combination model was implemented in annual rainfall forecasting to check its feasibility.

The resource of image noise is analysized in this paper. Considering the image fuzzy generated in the process of image denoising in spatial field, the image denoising method based on wavelet neural network with orthonormal bases is elaborated. The denoising principle and construction method of orthonormal wavelet network is described. In the simulation experiment, median filtering, adaptive median filtering and sym wavelet neural network with orthonormal bases were used separately in the denoising for contaminated images. The experiment shows that, compared with traditional denoising method, image denoising method based on orthonormal wavelet neural network improves greatly the image quality and decreases the image ambiguity.