人体平衡机能检测分析系统的设计与实现

对人体平衡机能的检测和分析是判断人体是否有平衡机能障碍疾病和其平衡障碍程度的重要依据。本文设计了功能齐全、性能优良的人体平衡机能分析检测系统 ,提出了系统软件和硬件的实现方案 ,研制了该系统的样机 ,并进行了初步的临床应用。应用结果表明 ,该系统可以对人体平衡机能进行准确检测和定量分析 ,并可以帮助患者进行康复训练 。

Windows下的人体平衡机能检测分析系统

本系统利用了VxD技术实现在Windows下对人体平衡数据的检测,利用PC机串口对数据检测进行控制。系统应用程序对人体的平衡机能作了时域和频域的分析,其构成采用了MFC的ActiveX和DLL技术。

Development status and prospect of cold chain logistics of fruits,vegetables,and agricultural products based on intelligent technology

The cold chain in the production area of fruits and vegetables is the primary link to reduce product loss and improve product quality,but it is also a weak link.With the application of big data technology in cold chain logistics,intelligent devices,and technologies have become important carriers for improving the efficiency of cold chain logistics in fruit and vegetable production areas,extending the shelf life of fruits and vegetables,and reducing fruit and vegetable losses.They have many advantages in fruit and vegetable pre-cooling,sorting and packaging,testing,warehousing,transportation,and other aspects.This article summarizes the rapidly developing and widely used intelligent technologies at home and abroad in recent years,including automated guided vehicle intelligent handling based on electromagnetic or optical technology,intelligent sorting based on sensors,electronic optics,and other technologies,intelligent detection based on computer vision technology,intelligent transportation based on perspective imaging technology,etc.It analyses and studies the innovative research and achievements of various scholars in applying intelligent technology in fruit and vegetable cold chain storage,sorting,detection,transportation,and other links,and improves the efficiency of fruit and vegetable cold chain logistics.However,applying intelligent technology in fruit and vegetable cold chain logistics also faces many problems.The challenges of high cost,difficulty in technological integration,and talent shortages have limited the development of intelligent technology in the field of fruit and vegetable cold chains.To solve the current problems,it is proposed that costs be controlled through independent research and development,technological innovation,and other means to lower the entry threshold for small enterprises.Strengthen integrating intelligent technology and cold chain logistics systems to improve data security and system compatibility.At the same time,the government should introduce relevant policies,provide necessary financial support,and establish talent training mechanisms.Accelerate the development and improvement of intelligent technology standards in the field of cold chain logistics.Through technological innovation,cost control,talent cultivation,and policy guidance,we aim to promote the upgrading of the agricultural industry and provide ideas for improving the quality and efficiency of fruit and vegetable cold chain logistics.

飞行人员FCG正常值的测定

频域心电图(Frequency-domain Correla-tive Cardiograhy简称FCG)是我国首创的一种无创性检查心脏的新方法。它采用了座标转换方法,把时域心电图中的心电信号转变成频域信号,以进行多相、多角度的相关动态分析。

ST型双向自动闸调器性能试验台简介及试验工艺

铁道车辆采用闸瓦制动时,随着闸瓦的磨耗,闸瓦与车轮踏面之间的间隙会发生变化,进而影响制动缸活塞杆的行程,减弱制动力.为保证闸瓦与车轮踏面之间的间隙不受闸瓦磨耗的影响,保证制动力充足,采用闸调器对闸瓦和踏面之间的间隙进行调整.闸调器的性能试验是新造或检修闸调器安装上车前的最后一步,其质量直接关系到列车的运行安全.文章以我国铁道车辆使用最广泛的ST1-600型和ST2-250型闸调器为例,介绍了闸调器性能试验设备的技术条件和机能检测方法,并以此为基础,介绍了ST型双向自动闸调器性能试验工艺流程.

Design of intelligent line-tracking chess robot based on STM32

An intelligent line-tracking chess robot based on STM32 is introduced in this paper. Its hardware consists of photo- electric detection circuit, main control circuit, motor driven circuit, steering engine driven circuit and dial switch. The hardware structure and software flow chart of the system are described in details in this paper. The robot is driven by rear wheel motors, and the real-time position of the robot is determined by the ground information collected by infrared sensors. The heading direction of robot is adjusted by steering engine installed in front wheel, and the open angle of manipulator is controlled by the other steering engine which can ensure the robot moving chessmen accurately and quickly during the moving process. The test shows that the kind of intelligent chess robot can complete the task in a fast and accurate way.

Malware Detection in Smartphones Using Static Detection and Evaluation Model Based on Analytic Hierarchy Process

Mobile malware is rapidly increasing and its detection has become a critical issue. In this study, we summarize the common characteristics of this inalicious software on Android platform. We design a detection engine consisting of six parts： decompile, grammar parsing, control flow and data flow analysis, safety analysis, and comprehensive evaluation. In the comprehensive evaluation, we obtain a weight vector of 29 evaluation indexes using the analytic hierarchy process. During this process, the detection engine exports a list of suspicious API. On the basis of this list, the evaluation part of the engine performs a compre- hensive evaluation of the hazard assessment of software sample. Finally, hazard classification is given for the software. The false positive rate of our approach for detecting rnalware samples is 4. 7% and normal samples is 7.6%. The experimental results show that the accuracy rate of our approach is almost similar to the method based on virus signatures. Compared with the method based on virus signatures, our approach performs well in detecting unknown malware. This approach is promising for the application of malware detection.

Smartphone Malware Detection Model Based on Artificial Immune System

In order to solve the problem that me traditional signature-based detection technology cannot effectively detect unknown malware, we propose in this study a smartphone malware detection model （SP-MDM） based on artificial immune system, in which static malware analysis and dynamic malware analysis techniques are combined, and antigens are generated by encoding the characteristics extracted from the malware. Based on negative selection algorithm, the mature detectors are generated. By introducing clonal selection algorithm, the detectors with higher affinity are selected to undergo a proliferation and somatic hyper-mutation process, so that more excellent detector offspring can be generated. Experimental result shows that the detection model has a higher detection rate for unknown smartphone malware, and better detection performance can be achieved by increasing the clone generation.

Super-service-oriented Architecture in Large-scale Pervasive Computing Environments

This paper proposes an architecture model to support enhanced system performance in large-scale pervasive computing environments. The muitiformity of device （or peer ） services and network types in such environment is apt to result in notable service isomorphs. And moreover, as the environment cannot assure the stability of network communication and device services, the situation gets worse. Therefore, it becomes urgent to simplify user operations and let them take full and highly efficient advantage of the environments. Super-Service-Odented Architecture （SSOA） is an Serrice-Otiented Architecture （SOA）-based architecture for service management and organization in peryasive environments. With combining one kind of isomorphic services into a super service, SSOA provides better scalability and quick, convenient service invocations. Also, the complexity and instability of services, and network types are transparent, and system performance is highly promoted under the architecture.

Intelligent Camera for Surface Defect Inspection

An intelligent camera for surface defect inspection is presented which can pre-process the surface image of a rolled strip and pick defective areas out at a spead of 1 600 meters per minute. The camera is made up of a high speed line CCD, a 60 Mb/s CCD digitizer with correlated double sampling function, and a field programmable gate array(FPGA), which can quickly distinguish defective areas using a perceptron embedded in FPGA thus the data to be further processed would dramatically be reduced. Some experiments show that the camera can meet high producing speed, and reduce cost and complexity of automation surface inspection systems.

ON THE PERFORMANCE OF ANALOG MULTIUSER DETECTION IN ULTRA-WIDEBAND TRANSMITTED-REFERENCE SYSTEM

The detection performance is evaluated for our proposed analog multiuser receiver in Ultra-WideBand (UWB) transmitted-reference system. In the presence of dense multipath and multi-access signals,the performance analysis is difficult due to the complicated waveform of received impulse. We develop an approach to analyze the steady-state Signal-to-Interference-plus-Noise (SINR) of the detector output. The multipath-spread impulse is fitted to an exponentially decaying profile in the analysis. A closed-form expression of steady-state SINR is further deduced for the proposed Least Minimum Square (LMS) detector. The analysis is validated by simulations in Line-Of-Sight (LOS) and Non-Line-Of-Sight (NLOS) channel respectively. Based on the theoretical results,the multipath delay spread is employed to determine the optimal width of the integration window of the detector.

SVM multiuser detection based on heuristic kernel

A support vector machine （SVM） based multiuser detection （MUD） scheme in code-division multi- ple-access （CDMA） system is proposed. In this scheme, the equivalent support vector （SV） is obtained through a kernel sparsity approximation algorithm, which avoids the conventional costly quadratic pro-gramming （QP） procedure in SVM. Besides, the coefficient of the SV is attained through the solution to a generalized eigenproblem. Simulation results show that the proposed scheme has almost the same bit er-ror rate （BER） as the standard SVM and is better than minimum mean square error （MMSE） scheme. Meanwhile, it has a low comoutation complexity.

The obstacle crossing ability analysis and improvement of the cable inspection robot

In this paper, the climbing obstacle capability of the previous special cable inspection robot （ Model Number： XS1T-1） is analyzed. Static equations are established to analyze the relationships between the external forces and the maximum height of an obstacle. Parameters affecting the obstacle crossing ability are obtained. According to the analysis results, an innovated small volume, simple structure and light weight climbing mechanism is proposed （Model Number： XS1T-2）. A simplified kinematics model of the mechanism is established. With two powered wheels, the obstacle crossing ability of the XSIT-2 is improved apparently. For the robot moving without deflection, the relationships of two powered input torques are deduced. The comparison of the simulation results clearly shows that the climbing ability of XS1T-2 is obviously improved, and it can meet the demands of inspection.

Face Detection from Four Captured Images Related to Intelligent Room for the Deaf

The intelligent environment needs Human-Computer Interactive technology （HCI） and a projector projects screen on wall in the intelligent environments. We propose the front-face detection from four captured images related to the intelligent room for the deaf. Our proposal purpose is that a deaf user faces wall displaying everywhere. system gets the images from four cameras, and detects the user region from a silhouette image using a different method, detects and cuts a motion body region from a different image, and cuts the vertexchest region from the cut body region image. The system attempts to find front-face using Haar-like feature, and selects a detected front-face image from the vertex-chest region. We estimate the front-face detection of recognition rate, which shows somewhat successfully.

On Observability and Detectability of Continuous-Time Stochastic Markov Jump Systems

This paper mainly studies observability and detectability for continuous-time stochastic Markov jump systems.Two concepts called W-observability and W-detectability for such systems are introduced,which are shown to coincide with various notions of observability and detectability reported recently in literature,such as exact observability,exact detectability and detectability.Besides,by introducing an accumulated energy function,some efficient criteria and interesting properties for both W-observability and W-detectability are obtained.

Outlier Mining Based Abnormal Machine Detection in Intelligent Maintenance

Assessing machine's performance through comparing the same or similar machines is important to implement intelligent maintenance for swarm machine.In this paper,an outlier mining based abnormal machine detection algorithm is proposed for this purpose.Firstly,the outlier mining based on clustering is introduced and the definition of cluster-based global outlier factor(CBGOF) is presented.Then the modified swarm intelligence clustering(MSIC) algorithm is suggested and the outlier mining algorithm based on MSIC is proposed.The algorithm can not only cluster machines according to their performance but also detect possible abnormal machines.Finally,a comparison of mobile soccer robots' performance proves the algorithm is feasible and effective.

A fast face detection architecture for auto-focus in smart-phones and digital cameras

Auto-focus is very important for capturing sharp human face centered images in digital and smart phone cameras. With the development of image sensor technology, these cameras support more and more highresolution images to be processed. Currently it is difficult to support fast auto-focus at low power consumption on high-resolution images. This work proposes an efficient architecture for an Ada Boost-based face-priority auto-focus. The architecture supports block-based integral image computation to improve the processing speed on high-resolution images; meanwhile, it is reconfigurable so that it enables the sub-window adaptive cascade classification, which greatly improves the processing speed and reduces power consumption. Experimental results show that 96% detection rate in average and 58 fps(frame per second) detection speed are achieved for the1080p(1920×1080) images. Compared with the state-of-the-art work, the detection speed is greatly improved and power consumption is largely reduced.

Reliability of weak signals detection in neurons with noise

Previous experimental and theoretical studies have demonstrated that a weak signal can be amplified and optimized by the assistance of noise. The response of the system undergoes stochastic resonance(SR) like behavior. The underlying mechanisms are fairly simple and robust. This phenomenon has been observed in a large variety of systems, including physical and biological systems. In the nervous system, the majority of synaptic input is too weak to make neurons fire a spike. This weak(or subthreshold) signals detection is very important for animal survival, and pulse detection is a simple but basic task of neuronal information transmission and processing. Some studies have found that subthreshold signals can be transmitted by the application of external noise. However, neurons are subjected to various kinds of inherent noise. Recently, theoretical work has revealed that this inherent noise improves signals detection ability. The detection ability of a single neuron is limited, and the neuronal circuit can perform this task very well by detecting the synchronization of presynaptic potentials. Here, we review recent studies of subthreshold detection by both single neurons and neuronal circuits.

Improved Scheme of Internet Congestion Control under Moving Average Filter

An important task of Internet congestion control is inhibiting sporadic data flow to maintain a suitable window size or route queue length. Such a requirement is just consistent with the basic idea and function of a moving average filter. In this paper one prior Internet congestion control model, named transmission control protocol (TCP)/random early detection (RED) stroboscopic model, is studied, and then one new scheme is proposed to enlarge its stable domain, where a simple moving average filter is introduced to inhibit sporadic data flow as possible. In the novel scheme the bifurcation phenomenon is postponed without any extra controller. The effectiveness of the new scheme is verified by theoretical analyses and numerical simulations.