电力营销稽查“智检”机器人系统架构设计

为规避电力营销风险,提升稽查管理水平,设计基于数据挖掘的电力营销稽查“智检”机器人系统。以B/S架构为基础,调用后台数据库管理模块存储的记录型和文件型数据,通过数据的选择、清洗以及变换等数据预处理过程,采用K-means算法聚类用电轨迹特征识别用户用电情况,通过信息管理及营销工作、运营状态检测等子模块,进行电力营销稽查“智检”。算例分析结果表明:该系统可满足电力公司营销稽查智检业务的作业需求,数据聚类效果好,系统数据管理最坏时间复杂度低,通信性能与存储性能较强。

地下管线数据采集实时“智检”技术研究

传统地下管线数据质检过程多侧重于外业采集后的检查复核,缺少现场的实时数据检测,很难在第一时间发现测量问题,易导致工程返工,资源浪费的现象。提供了一种基于重力自流管线数据采集的实时"智检"技术,通过所采集的数据实时计算管线坡度和管线方向夹角等指标,利用其合理区间来分析管线数据质量,并给出实时预警提示。同时结合移动GIS、LBS来实现地下管线数据采集时的现场实时检测,辅助外业测量技术人员及时发现数据质量问题,现场进行复测修正,避免非必要的工程返工。该模拟实验分析表明可显著提升外业数据采集质量和工作效率。

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.

基于“互联网+”理念的建筑安全管理研究与应用

随着"互联网+"时代的到来,施工现场安全管理模式也应进行革新。本文主要针对"互联网+智检APP"和传统安全检查不足进行研究,创新建筑安全管理模式,建立智检APP系统功能框架,并结合工程实际,落实施工现场安全隐患排查,对智能检查及创建智能化文明工地具有借鉴意义。

10000客服智慧化运营与系统技术实现

通信技术发展日新月异,通信产品设计丰富多样,这极大地增加了客户服务工作的难度与复杂度。电信10000号既要能适应通信技术与产品设计的飞速变化,又要能快速高效地满足客户的需求,那么从运营到平台都要不断地发展与更新。当前中国电信已经进入智慧化运营的时代,10000号客服的智慧化是智慧化运营的重要组成部分。本文围绕10000客服智慧化运营提出了多种实现场景,并将大数据技术和语音语义识别技术集成运用到10000系统中以实现这些功能。

中小型棉纺企业技改的选择

为了降低中小型棉纺企业用工水平、实现高质量发展,从中小型纺织企业存在的细纱、络筒工序用工多、效率低、能耗大及历史遗留的棉纺落后产能、细纱机型号与状态差异大、纱库式自动络筒机改造难度大等方面阐述其技术改造滞后的原因;认为细纱智能落纱小车、平移式集落、串联式集落改造和数控车头配套改造、自络投纱系统改造、筒纱智能自动化全数检测包装线的创新与突破是纺企技改趋势.指出:纺企应抓住技改机遇,通过"短、平、快"技改弥补现有纺纱机械短板,并以细纱短车和纱库式自络为技改重点;实现"四高"的自动化改造主要为将用工多的操作改为自动化和工艺、质量、管理的智能化;落纱与投纱设备的选择应结合企业实际,自络投纱系统改造应兼顾细纱集落改造具有的可靠性好、找头率和生产率高的特点;各工序应做好纺织器材管理和维护保养工作;纺机制造企业在注重纺织机械研发的基础上应重视纺织器材配置.

Traffic light detection and recognition in intersections based on intelligent vehicle

To ensure revulsive driving of intelligent vehicles at intersections, a method is presented to detect and recognize the traffic lights. First, the stabling siding at intersections is detected by applying Hough transformation. Then, the colors of traffic lights are detected with color space transformation. Finally, self-associative memory is used to recognize the countdown characters of the traffic lights. Test results at 20 real intersections show that the ratio of correct stabling siding recognition reaches up to 90%;and the ratios of recognition of traffic lights and divided characters are 85% and 97%, respectively. The research proves that the method is efficient for the detection of stabling siding and is robust enough to recognize the characters from images with noise and broken edges.

Completeness of bounded model checking temporal logic of knowledge

In order to find the completeness threshold which offers a practical method of making bounded model checking complete, the over-approximation for the complete threshold is presented. First, a linear logic of knowledge is introduced into the past tense operator, and then a new temporal epistemic logic LTLKP is obtained, so that LTLKP can naturally and precisely describe the system＇s reliability. Secondly, a set of prior algorithms are designed to calculate the maximal reachable depth and the length of the longest of loop free paths in the structure based on the graph structure theory. Finally, some theorems are proposed to show how to approximate the complete threshold with the diameter and recurrence diameter. The proposed work resolves the completeness threshold problem so that the completeness of bounded model checking can be guaranteed.

Validation of Fujinon intelligent chromoendoscopy with high definition endoscopes in colonoscopy

AIM:To validate high definition endoscopes with Fujinon intelligent chromoendoscopy(FICE) in colonoscopy.METHODS:The image quality of normal white light endoscopy(WLE),that of the 10 available FICE filters and that of a gold standard(0.2% indigo carmine dye) were compared.RESULTS:FICE-filter 4 [red,green,and blue(RGB) wavelengths of 520,500,and 405 nm,respectively] provided the best images for evaluating the vascular pattern compared to white light.The mucosal surface was best assessed using filter 4.However,the views obtained were not rated significantly better than those observed with white light.The "gold standard",indigo carmine(IC) dye,was found to be superior to both white light and filter 4.Filter 6(RGB wavelengths of 580,520,and 460 nm,respectively) allowed for exploration of the IC-stained mucosa.When assessing mucosal polyps,both FICE with magnification,and magnification following dye spraying were superior to the same techniques without magnification and to white light imaging.In the presence of suboptimal bowel preparation,observation with the FICE mode was possible,and endoscopists considered it to be superior to observation with white light.CONCLUSION:FICE-filter 4 with magnification improves the image quality of the colonic vascular patterns obtained with WLE.

Hydrophilic characteristics of soft rock in deep mines

A series of water absorption tests on dried soft rock have been conducted by the intelligent testing system for water absorption tests in deep soft rock, including tests of water absorption with and without pres- sure. The results show that the water absorbing capacity of rock with a certain pressure is larger than that of rock without pressure： however, the relationship between the water absorbing percentage and the time can be expressed by w（t） = a（l - e^-bt）. In hi-logarithmic coordinates, the hydrophilic relationship with time in tests with pressure could be characterized by linearity, while they present concave or convex in tests without pressure. Based on the hypothesis that each influential factor is irrelevant and they have a linear correlation with the water absorbing capacity, we calculated the weight coefficient of each factor according to experimental results under different conditions. The calculations demonstrate that the effec- tive porosity, content of smectite and kaolinite are all positively correlated with the water absorption capacity of rock; meanwhile, the fractal dimension of the effective pores presents a negative correlation with the water absorption capacity of rock. The water absorption capacity with pressure increases with increasing illite, chlorite and chlorite/smectite formation and a decrease in illite/smectite formation and the fractal dimension of the effective pores, while it is opposite in tests without pressure. The weight coefficient of smectite is smallest among positive factors, and the fractal dimension of the effective pores is the smallest amongst the negative factors.

AN INTELLIGENT METHOD FOR REAL-TIME DETECTION OF DDOS ATTACK BASED ON FUZZY LOGIC

The paper puts forward a variance-time plots method based on slide-window mechanism tocalculate the Hurst parameter to detect Distribute Denial of Service(DDoS)attack in real time.Basedon fuzzy logic technology that can adjust itself dynamically under the fuzzy rules,an intelligent DDoSjudgment mechanism is designed.This new method calculates the Hurst parameter quickly and detectsDDoS attack in real time.Through comparing the detecting technologies based on statistics andfeature-packet respectively under different experiments,it is found that the new method can identifythe change of the Hurst parameter resulting from DDoS attack traffic with different intensities,andintelligently judge DDoS attack self-adaptively in real time.

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.

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.

AN ADAPTIVE MOVING TARGET TRACKING ALGORITHM FOR SMART ANTENNA SYSTEMS

In wireless communication environment, the time-varying channel and angular spreads caused by multipath fading and the mobility of Mobile Stations (MS) degrade the performance of the conventional Direction-Of-Arrival (DOA) tracking algorithms. On the other hand, although the DOA estimation methods based on the Maximum Likelihood (ML) principle have higher resolution than the beamforming and the subspace based methods, prohibitively heavy computation limits their practical applications. This letter first proposes a new suboptimal DOA estimation algorithm that combines the advantages of the lower complexity of subspace algorithm and the high accuracy of ML based algo- rithms, and then proposes a Kalman filtering based tracking algorithm to model the dynamic property of directional changes for mobile terminals in such a way that the association between the estimates made at different time points is maintained. At each stage during tracking process, the current suboptimal estimates of DOA are treated as measurements, predicted and updated via a Kalman state equation, hence adaptive tracking of moving MS can be carried out without the need to perform unduly heavy computations. Computer simulation results show that this proposed algorithm has better per- formance of DOA estimation and tracking of MS than the conventional ML or subspace based algo- rithms in terms of accuracy and robustness.

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.

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.

Intelligent GPS-Less Speed Detection and Clustering in VANET

Vehicular Ad Hoc Network （VANET） has emerged as a new wireless network for vehicular communications. To provide a flexible and high reliable communication service in VANET, vehicles are clustered to construct many small networks （clusters） so that channel interferences and flooding messages can be limited. This research presents a novel Multi-Resolution Relative Speed Detection （MRSD） model to improve the clustering algorithm in VANET without using Global Positioning System （GPS）. MRSD uses the Moving Average Convergence Divergence （MACD）, the Momentum of Received Signal Strength （MRSS）, and Artificial Neural Networks （ANNs） to estimate the motion state and the relative speed of a vehicle based purely on Received Signal Strength. The proposed MRSD model is accurate with the assistance of the intelligent classification, and incurs less overhead in the cluster head election than that of other algorithms.

Intelligent outdoor video advertisement recommendation system based on analysis of audiences' characteristics

An integrated implementation framework of an intelligent recommendation system for outdoor video advertising is proposed, which is based on the analysis of audiences＇ characteristics. Firstly, the images of the scene and the people who view the video advertisements are captured by the net- work camera deployed on the video advertising terminal side. Then audiences＇ characteristics can be obtained by applying computer vision technologies ： face detection, face tracking, gender recogni- tion and age estimation. Finally, an intelligent recommendation algorithm is designed to decide the most fitting video ads for each terminal according to multi-dimensional statistical information of its reover, a novel face detection method and a new face tracking method have been proposed to meet the practical requirements of the system, of which the average Fl-score is O. 988 and 0. 951 respec- tively.

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.

Video-based construction vehicles detection and its application in intelligent monitoring system

While vehicle detection on highways has been reported before, to the best of our knowledge, intelligent monitoring system that aims at detecting hydraulic excavators and dump trucks on state-owned land has not been explored thoroughly yet. In this paper, we present an automatic, video-based algorithm for detecting hydraulic excavators and dump trucks. Derived from lessons learned from video processing, we proposed methods for foreground detection based on an improved frame difference algorithm, and then detected hydraulic excavators and dump trucks in the respective region of interest. From our analysis, we proposed methods based on inverse valley feature of mechanical arm and spatial-temporal reasoning for hydraulic excavator detection. In addition, we explored dump truck detection strategies that combine structured component projection with the spatial relationship. Experiments on real-monitoring sites demonstrated the promising performance of our system.