For solving ICI ( Inter-Carrier Interference) suppression problem of CＲ ( Cognitive Ｒadio) system，the intelligent algorithm is designed to obtain the optimal interference subcarriers of un-LU ( un-Licensed User) ．Masking the optimal interference subcarriers can suppress ICI of CＲ． But the computation complexity of intelligent algorithm is high and computing speed is slow． So，the ICI suppression parallel algorithm is proposed．The new parallel algorithm can realize parallel computing on the multi-core processor to improve the computing speed of the intelligent algorithm and meet the practical application requirements of the CＲ system． The simulation results show that under the condition of satisfying the BEＲ ( Bit Error Ｒate) of the un-LU，the ICI of LU ( Licensed User) is reduced obviously and the better BEＲ performance of LU is obtained by the new ICI suppression parallel algorithm．

In order to overcome the limitations of the traditional optical fiber sensing test system，such as large dispersivity and complex process，a full digital optical fiber sensing test system is designed by combining the infrared photoelectric sensor and the technology of Internet of things． The system uses the MCU( Micro Control Unit) as the main control unit，the infrared proximity sensor is used as the IＲ LED( Infrared Light Emitting Diode) driver and the photoelectric conversion output unit，the ＲTC ( Ｒeal-Time Clock) chip and the EEPＲOM( Electrically-Erasable Programmable Ｒead-Only Memory) are used to read the time and the real-time storage of the photoelectric data． The WiFi ( Wireless Fidelity ) module realizes the network transmission of the photoelectric data． The key and the LCD( Liquid Crystal Display) display unit complete the human-computer interaction and other functions． Experiment results show that the system can be applied to non-contact object detection under special circumstances，color recognition and other occasions． It provides a feasible scheme for further realizing miniaturization and intellectualization of optical fiber sensing test system．

In order to increase the information security in information transmission，A communication technique based on information entropy and chaotic coding is proposed for modulation encryption． Theoretically，this technique chooses modulation methods adaptively for the signal with low bit error rate in accordance with realtime SNＲ ( Signal-Noise-Ｒatio ) estimation． It also increases the information security performance of the modulated signal by switching one modulation method to another according to the chaotic cipher codes．Numerically，an experimental implementation using time-variant channel，7 modulation methods and the chaotic Logistic map，demonstrates the validity and effectiveness of this technique．

Aiming at the problem of traffic accident caused by the far and near light switching in the car at night，a switching system of automobile near and far light based on OpenMV machine Vision module is designed，which is programmed using Python language，and lab color model to make image cutting and color block recognition for collecting data． The real-time processing of the image is realized． The experimental results show that the system has good self-adaptive ability，can realize the intelligent regulation to the near and far light lamp，and improve the safety factor of driver's night driving．

In view of the influence of residential area openness on the capacity of surrounding roads，this paper constructs an index system to evaluate the influence of residential area openness on road access based on the “pressure-state-response”( PSＲ: Pressure-State-Ｒesponse) model，and uses AHP ( Analytic Hierarchy Process) to determine the index weight，the comprehensive index method was introduced to evaluate the impact of residential area opening on road traffic． We choose class A and class B residential areas as the research object，and use VISSIM simulation software to simulate the road traffic and traffic conditions around the intersection of the two types of residential area． Simulation results show that the opening of class A residential area reduces the capacity of surrounding roads and the opening of class B residential areas improves the capacity of surrounding roads． The results of this study can provide theoretical reference for the traffic management departments to whether the district is fully open．

Traditional cloud computing service chain consists of intelligent terminals， internet and cloud datacenter，is inefficient for latency sensitive applications． MEC ( Mobile Edge Computing) pushs compute power，storage power，and network resources to the edge of the Internet to improve service speed for users and terminals． However，MEC can only manage compute resources and storage resources． MEC is combined with SDN ( Software-Defined Networks) for the sake of collaborative management of compute，storage and network resources． The state-of-the-art MEC scenarios and MEC improvement researches are investigated． A MEC-SDN system architecture is proposed in terms of MEC，SDN and cloud datacenter． The latest researches on MEC system evaluation are concluded in terms of application task，communication overhead，compute overhead and resource allocation． Finally，several encouraging areas of MEC-SDN in the future are shown．

In order to improve the search speed and shorten the search time of robot path planning，the characteristics of various algorithms is summarized． First，the history of mobile robot development and outline the key technologies of path planning are reviewed． Secondly，the mobile robot path planning is classified and summarized． From the perspective of the mobile robot's grasp of the environment，the mobile robot path planning is divided into two categories: global planning and local planning． Then the related algorithms of global planning and local planning are reviewed，and the development status，advantages and disadvantages of related algorithms are summarized． Finally，the future development trend of robot path planning technology in further research，hybrid algorithm， multi-robot collaboration， complex environment and multi-dimensional environment is pointed out．

In view of the fact that the constant steam injection rate of steam flooding is poor，an oscillatory steam injection rate optimization method of steam flooding based on improved PSO ( Particle Swarm Optimization) algorithm is proposed． Firstly，a mathematical model of steam injection rate of steam flooding is established． Then，the IPSO algorithm is used to solve the model and optimize of the oscillatory steam injection rate． Finally，the oscillatory steam injection rate optimization scheme of steam flooding is obtained．In the IPSO algorithm，we introduce chaos optimization operator to generate initial solutions and apply the self-adaptive mutation of particles according to the distance of the fitness of each particle． We adopt extreme disturbance on the individual history optimal values and global optimal value． It can speed up the convergence speed and increase the evolving ability of the population． The experimental results show that the established model is accurate and the optimization algorithm is effective． The proposed methodology can make steam flooding injection-production scheme more reasonable，ultimately contributing to its efficient operation．

The known current intelligent vehicle detection algorithms have problems such as large errors and inaccurate measurement results in practical applications． The algorithm used in this paper is based on the vehicle detection mechanism of the car hull line in the moving vehicle，and uses the feature of the bottom shadow to exist．And the binocular stereo matching distance measurement method based on machine vision is selected to realize the nearest vehicle distance measurement． Provide reliable information for intelligent vehicles and driver assistance．The final result of the system confirms the availability of more accurate vehicle and distance information in front of the road． The effective detection distance is 10 m ～50 m，and the overall recognition rate can reach 85% or more．

Anembedded wireless video capturing system is designed based on AＲM S3C2440，to achieve video monitoring． According to the functional requirements，both hardware structure and software architecture are designed． With embedded microcontroller S3C2440 as the core，the peripheral video capturing hardware modules are expanded． And the operating system adopts embedded Linux． The V4L programming interface is used to process the digital image information captured by the extended USB camera，and meanwhile to compress the captured video so as to achieve the fast transmission and storage．

It revealed the core institutions，research hotspots and forward disciplines in Liaoning province．Aiming to detect the research focus and disciplinary trend of Liaoning province by scientific knowledge map in recent 5 years． This study was based on the original data of 10 725 articles published by Liaoning province in web of science database during 2012 ～ 2016，It analyzed from published paper amount of year and highly cited documents． Using citespace software analyzed from co-institutional，keyword co-word analysis and disciplinary cooccurrence． Core institutions of Liaoning is China Medical university，In the field of engineering，chemistry and medical has achieved fruitful research results．

With the development of society，more and more“Sensational Headline”which does not match the text for the purpose of attracting the audiences attention phenomena has appeared． In order to identify the “Sensational Headline”news，methods of text similarity calculation based on an Improved VSM Combined with Cosine Similarity Method，the HowNet Method and an Improved VSM-HowNet Fusion Similarity Algorithm are introduced． These methods have higher total accuracy，total recall rate and total F1 value for the“Sensational Headline”news recognition than other text similarity calculation methods． For identifying an unknown type of news，the improved VSM-HowNet fusion similarity algorithm is more advantageous than other text similarity calculation methods．

To solve the structural lightweight and maximum stress minimization problems being a worldwide concern in the optimization design of the coupling，this paper makes structural topology optimization plate design on the SSWZ330 type cross-shaft universal coupling by making use of the finite element analysis software of Hyperworks and adopting the evolutionary structural optimization method． After the optimization of structural topology optimization plate design，the weight of materials can be saved by 9． 17%，the maximum static strain can be reduced by 2． 3%，and the maximum stress can be reduced by 52． 1%，improving the structural performance，reducing structural weight，and expanding the practical engineering application of Hyperworks software in the field of topology optimization design of mechanical parts．

In order to construct the high-quality graph which can reflect the intrinsic structure of highdimensional data，we propose a novel dimensionality reduction algorithm named DＲAG ( Dimensionality Ｒeduction based on Adaptive Graphs) ． Compared with other graph-based dimensionality reduction algorithms，the proposed DＲAG algorithm avoids the problem of parameter selection in the traditional k nearest neighbors or ε-ball neighborhood criterions and constructs sparse and superior adaptive graphs，taking the local information and noises of input data． The LPP ( Locality Preserving Projection) is applied to acquire a projection matrix，which describes the intrinsic structure of high-dimensional data accurately． Finally，we achieve the purpose of dimensionality reduction． In order to evaluate the performance of the proposed algorithm， we perform classification and clustering experiments on four image databases ( CMU PIE，Extended YaleB，OＲL and COIL 20) ，the experimental results show that the proposed algorithm outperforms some other methods in term of classification and clustering accuracy．

Many risk factors often interfere with the implementation of information construction projects in Colleges and universities，resulting in great risks of information projects． By studying the risk assessment of informatization construction projects in Colleges and universities，we can deepen our understanding of the risks of informatization construction and reduce or disperse the risks of the projects． Based on the 4E standard，the multilevel fuzzy evaluation model of the University Information Engineering is constructed． Through the statistical analysis，the risk factors and the weight of risk factors that affect the university information engineering are obtained so that the universities can better understand the overall risk situation，control the risk object． The fuzzy evaluation model is used to evaluate the Information Engineering Index System of M colleges and universities，and the comprehensive risk degree is determined． The results show that in the two first grade indexes of M University Information Engineering，the risk of e-mail has a great influence on the risk of Information Engineering in Colleges and universities，and the proportion is 54． 4%． The risk of teaching information is 51． 7% is a high risk grade． Therefore，it is necessary to strengthen the construction of organization guarantee，management standard，safety guarantee and information performance evaluation．