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Data security is the focus of information security. As a primary method, file encryption is adopted for ensuring data security. Encryption algorithms created to meet the Data Encryption Standard (DES) and the Advanced Encryption Standard (AES) are widely used in a variety of systems. These algorithms are computationally highly complex, thus, the efficiency of encrypting or decrypting large files can be drastically reduced. To this end, we propose an optimized algorithm that efficiently encrypts and decrypts large files by parallelizing processing tasks on a single heterogeneous many-core processor in the Sunway TaihuLight computer system. Firstly, we convert the serial DES and AES programs to our experimental platform. Then we implement a task assignment strategy to test the converted algorithms. Finally, in order to optimize parallelized algorithms and improve data transmission performance, we apply the master-slave communication optimization, the three-stage parallel pipeline, and vectorization. Extensive experiments demonstrate that our optimized algorithm is faster than the state-of-the-art open-source implementations of DES and AES. Compared with the serial processing algorithms, our parallelized DES and AES perform nearly 40 times and 72 times faster, respectively. The work described in this paper leverages existing methods and provides a sound basis for the direction of future research in data encryption.

Air traffic operational efficiency has critical influence on energy conservation and pollutants reduction. The lack of models and tools makes it difficult to numerically calculate and evaluate the effect of aviation new technologies on green operation. In this research, the methods for the estimation of fuel consumption and pollutant emission based on recorded track data are studied. Firstly, aircraft performance parameters matching models are constructed to calculate fuel flow, aircraft mass, engine thrust, Mach number and aerodynamic forces under given track data. Meanwhile, aircraft pollutant emission models are established for calculating fuel consumption and pollutant emission in different flight phases. Furthermore, we developed software within Visual Studio environment to compute fuel consumption and pollutants data based on recorded Radar track data and recorded track data from radar control simulators. The results show that controllers personal skills may have significant influence on fuel saving and emission reduction. The constructed models and developed software in this paper can not only be used for quantitatively analyzing the impact of air traffic new technologies on civil aviation’s fuel conservation and pollutants reduction, but also can be used for evaluating the efficiency of different air traffic controller groups and helping air traffic controllers to make a better decision, thus obtain improved flight safety and increased airspace capability.

Increasing aircraft payload capability can be achieved by modifying the departure procedure out of airports surrounded by challenging terrain and thus may have the potential to transform the operation economy from financially unsustainable to commercially viable. A typical aerodrome is used for analysis since it is surrounded by mountainous terrain and has published SIDs for compliance with obstacle clearance requirements. The basic process loops for designing an EOSID are demonstrated, including calculations of MTOW, departure flight path, critiques to determine if it is necessary to design EOSID, and methods for finding new routes. Further, the metho–ds for calculating flight path by Boeing software for a Boeing 737-700 are given, including a basic flow chart, definition of vertical and horizontal profiles, and output of result parameters. The applicability of using Insight Animation as a valid platform for EOSID flight path demonstration is assessed, since these simulators are much more economical than FullFlight simulators, and provide design flexibility by easily checking the convenience of flight legs, and finding good routes in mountainous areas.

The sparse autoencoder was used for the construction of the face recognition. Firstly, the face image database we used is the MIT face image database, In order to achieve the better results, image preprocessing is essential. It included the shear of the effective face area and Local Binary Pattern of the effective face area. Secondly, through training the hidden layer, initializing the network and training the forward network, a machine for Face recognition can be built. The experimental results showed that the sparse autoencoder improved the accuracy of face recognition and achieved good results in practical operation.

According to backward technology, tedious process, failure orders and goods queuing of traditional tobacco enterprise logistics center, the process optimization methods is proposed by application of RFID technology. Firstly, actual operating environment of Harbin Tobacco Company (Abbr. HTC) logistics center in China is used as background to analyze the problems existing in the process through investigation. Secondly, the logistics center simulation model is established by using Flexsim simulation technology in order to find out the cause of the problems of logistics center operation process. Finally, operation process of logistics center is optimized. The result shows that the operating efficiency of logistics center has increased by 22.4%. It proves that the effect of this kind of research method for the optimization of tobacco logistics center process is remarkable and it provides a new way of thinking to implement RFID technology in the logistics center of this industry.

Based on the propagation mode of electromagnetic wave and characteristics of channel fading for wireless communication systems, analysis on different wireless channel models which are applicable for different communication areas aiming at ground-air wireless communication system is made. However, these models only adapt for one communication scenario. To adapt for different communication scenarios in a same system, a comprehensive method which integrates different models is proposed in this paper. Comparisons are carried out between the simulated and field test link remaining powers. Results demonstrate the effectiveness of the proposed method. Link remaining powers under different communication scenarios can be obtained through this method, which will support the system design to a great extent.

The remote ECG communicates over the public Internet, and the public Internet security is not sufficient to ensure the information security of the remote ECG system. User data disclosure poses a security threat to the system. The ECG information security solution proposed in this paper adopts the method of preset multi-key-per-machine at the factory to avoid leakage caused by personnel factors, and uses the hash function to generate a secondary password for communication encryption during network transmission. Experiments show that this program can effectively resist the existing various attack methods and fully protect patient data security.

Moving object detection is one of the challenging problems in video monitoring systems, especially when the illumination changes and shadow exists. A method for real-time moving object detection is described. A new background model is proposed to handle the illumination varition problem. With optical flow technology and background subtraction, a moving object is extracted quickly and accurately. An effective shadow elimination algorithm based on color features is used to refine the moving objects. Experimental results demonstrate that the proposed method can update the background exactly and quickly along with the varition of illumination, and the shadow can be eliminated effectively. The proposed algorithm is a real-time one which the foundation for further object recognition and understanding of video monitoring systems.

A detailed design scheme of SCA-based communication system is introduced. The system architecture, software platform, hardware platform and design guides are then de scribed. After analyzing the characteristics of ad-hoc network, a design process of application waveforms and components of SCA-based ad-hoc network is proposed. The ad-hoc network radio is based on GPP+DSP+FPGA hardware architecture, and MHAL technique is utilized to realize the portability of waveforms on dedicated hardware processors. Different ad-hoc network protocols are implemented, making the radio applicable to different circumstances.

Based on the background of WiFi-based Ad-hoc network, four route protocols are simulated using OPNET plat form. Experimental result shows that AODV protocol has a better performance than other algorithms under the circumstance of high throughout and heavy burden. To meet the communication requirement of vehicle-borne Ad-hoc network under battlefield circumstance, a ne w cluster route protocol (CRP) is proposed based on AODV protocol. Its cluster architecture design reduces the influence of topology change on route search process and the flooding cost during route discovery process. It is proved that the performance of CRP is better than AODV protocol and ZRP protocol, and the end-to-end delay is reduced dramatically.

With the development of the Internet and technology, the trend of the intelligentization to the both ends of net is becoming more and more obvious. Cloud computing obtains rapidly develop and increasingly mature because of the powerful computing and storage capacity. While, the intelligent terminal equipment has a fast development, which outstanding express in stronger processing, popularization and diversify. Both of them promote the application in smart home. However, because of the diversify of the terminal, it causes some problems such as the relatively limited computing power, different data storage ability, various screen size. This paper proposes a cloud-terminal collaborative technology, using semantics and metadata structure to establish a unified and standard data model in the cloud. Then establish a unified and standard data model based on characteristics of the terminal and user requirements in the terminal. Finally, through the model matching, we can use the cloud resources efficiently and pertinently, and then provide personalized service for the user.

Because it requires less change frequency of heading angle, path planning is a special and crucial issue to autonomous underwater vehicles in contrast to robot in land. The solution described in this paper firstly employs global path planning based on geometric method, then carries out local path planning based on one new artificial field potential function, which uses sector as the parameter. In order to ensure real-time, the information of sonar is combined to the static global map. The performance of simulation shows that the algorithm can avoid inherent limitations of artificial potential field method before the problem happening, the frequency of heading angle change is fewer, new detected obstacles can be real-time avoided.

Based on the standard FA easily traps in a local optimum, this paper presents a method that the current particle choose the one in its visual field which has the best fitness as the global best particle. The experiment shows the advantaged algorithm has a better global search ability. The paper uses the advantaged FA into the group animation, the particle has good artificial intelligence performance, and can simulate group behavior in an actual way.

Through the analysis of flowers pattern, firstly this paper abstracts the needed patterns and uses the genetic algorithm to generate new pattern so as to found a colorful pattern. And then through the analysis of the flowers pattern, it selects and assembles the various patterns automatically to create lots of different styles of the art patterns which can also be manually changed according to the actual needs. The above method has been proved in the experiment that it can enhance the creativity of the flowers pattern designer.

The reproduction of flight path during the aircraft approach and landing phase is an important part of flight unsafe incidents investigation. This article gives a method of extracting and processing flight parameter aiming at the problem that flight record data has a poor integrality, high rate of change and is hard to generated by flight path directly in that phase. In this article the airport environment which around aircraft in the landing phase is modeled, the flight path is reproduced by latitude and longitude and flight performance data, the flight path is calibrated in two ways, which one using a specific location point and other using the average latitude and longitude position point. The flight path which calibrated in the approach and landing phase which meets the needs of the project is obtained.

Vehicle monitoring technology based on the video image due to its features of easy maintenance and easy implement is concerned in recent years. Vehicle tracking is one of the key technologies to achieve video vehicle monitoring. How to achieve real-time vehicle tracking is the key and difficult problem at home and abroad. A method of Kalman tracking based on virtual loop is proposed in the paper. Two parts about vehicle presence detection and vehicle forecast tracking are introduced in this paper. Experimental results show that this method in the fast-path scenarios can effectively achieve vehicles tracking, fully meet the system requirements and have high practicality.

In this paper, we present efficient schemes to utilize multiple frames that contain the same text to get every clear word from these frames. Firstly, we use multiple frame traction to reduce text detection false alarms. And then detect and joint every clear text block from those frames to form a clearer integration frame. Later we uses Otsu threshold method to generate a binary text image. Finally, the binarized frames are sent to OCR engine for recognition. The experimental results show our method can improve the performance of text recognition in video significantly.

A complex geological object is a 3D entities, owned many characteristics such as structural complexity, heterogeneity and anisotropy. Its geometric modeling expresses not only the external space form, but also internal property features. Through researching algorithms such as curved surfaces reconstruction, curved surfaces intersection, subdivision and suture, a triangulated irregular network (TIN) modeling of complex geological object face structure had been achieved. On the base of complex geological object face structure triangulation grid, using 3D limited Delaunay subdivision algorithm, a 3D solid modeling of complex geological object had been achieved to overcome the technology difficult of the complicated structure block modeling. It realizes the smooth interpolation of seismic imaging velocity depth block model using block body model and velocity control point.

Layer velocity modeling is not enough for high accuracy pre-stack imaging. But block velocity modeling may accurately describe complex subsurface geological structure. Through the research of seismic exploration block modeling method, this paper proposes a new practical workflow about block modeling, researches Delaunay triangulation algorithm, achieves surface structure geometrical modeling, and keeps the geometry and topology relationship, such as geologic horizon and fault. On the basis of surface structure triangulation meshes, this paper also researches the algorithms of curved surfaces intersection, subdivision, suture, united output and 3D Delaunay triangulation, realizes block geometric surface modeling and complicated geologic solid modeling, and overcomes the technology puzzle of the complicated structure block modeling.

A new color image watermarking algorithm with resistance to JPEG lossy compression based on Quantization Index Modulation (QIM) is proposed in this paper. As it is known, QIM method can achieve a good balance between the embedding bit rate, robustness and distortion between the original image and the composited image by modulating the source signal into different clusters. The corresponding DCT coefficients margins of any two color channels selected from the three as the source signal is substantiated could achieve a high level embedding robustness and a low level distortion in this paper. However, JPEG lossy compression could bring a destructive influence to the watermark since it discards pretty much image information. In this paper, a compensation function is designed to correct the errors caused by JPEG compression. Experiments show the algorithm proposed has a good performance to resist the high compression ratio JPEG lossy compression and other attacks.

In this paper, a comparative study with three support vector machines (SVM) classifiers was carried out. The input images were first preprocessed to form the candidate text string regions. Next, Based on different features sets extracted by different methods, three SVM classifiers are used to analyze the textural properties of text and classify the text and no text strings in video frames. Then, a comparative evaluation of their performance is presented. The goal of the paper is to identify good feature selection for SVM in video text detecting task.