The spatial dependence degree of economic data among regions becomes increasingly higher due to the rapid development of economic integration and globalization. In consideration of the fact that both the inhibition mechanisms of capital, labor and other factors on economic growth and spatial interaction are still unclear. Based on 140 county economic data of Shandong province in china, a spatial econometric identification model simultaneously solving selection of spatial weight matrix (SWM) and parameter identification is established, in which 15 possible explanatory variables(including the intercept),20 SWMs and 327680 possible spatial econometric models are involved. A parallel trans-dimensional simulated annealing algorithm(PTD-SA) is constructed to find the optimum SWM and parameters, which allows for moves that not only change parameter values and SWMs but also moves between competing models. Numerical results show that the optimum spatial econometric model can describe the regional economic disparity reasonably.
This paper proposes the steganography algorithm based on 1 coefficients after discrete cosine transform (+/- 1 DCT) for H.264/AVC. The +/- 1 DCT algorithm embeds information bits differently on the number of +/- 1 coefficients after DCT and quantization process. When the number of +/- 1 coefficients is more than or equal to 3, this algorithm embeds information bits by matrix encoding. The simulation results show that the degradation of video quality is negligible and the same overall bit-stream length is maintained. And the comparison with other algorithms shows the superiority of the +/- 1 DCT algorithm.
Currently, Regular Android software, injected in malicious code, is one of the important factors of that Android virus run rampant. Protecting the Android software has become a focus of attention in academia and industry. Addressing the safety protection issues of the Android software, this paper will present some new schemes for Android software security technology. On the basis of existing research results, we will propose some recommendable solutions to prevent android applications being decompiled. Take advantage of these methods, we will build the Android software protection system, which will mostly eliminate the feasibility of the secondary packaging for Android software, and extend the Android software safety lifecycle.
The computational cost of large sparse unsymmetric linear equations has brought a challenge to engineering and scientific fields in recent years. In this paper, we present a parallel algorithm for solving large sparse unsymmetric linear equations. We multiply the unsymmetric linear coefficient matrix by its transpose to transform the large sparse unsymmetric matrix into a symmetric one, in this way one can use existing scalable hierarchical parallel algorithms designed for symmetric problems to solve it. In addition, we parallel this process, and the decomposition method designed in this paper insure the parallel performance of the algorithm. Numerical results demonstrate that this algorithm possesses excellent parallel efficiency and good expansibility.
The BoW model is a mainstream in image retrieval, and is employed in many state-of-the-art retrieval process. However, there are two main problems in this model: semantic gap caused by image quantification, and insufficient feature discriminative power. Aiming to handle the problems of semantic gap and feature fusion. This paper propose to choose multiple features to describe interest points and make evaluations for them so that the better judgement result is obtained. And then, we will generate dictionaries for each features and their cartesian product. As a result, a coupled index for all images will be built. Finally, we utilize variable-weight for the scores from those three dictionaries to obtain the total score for each image in datasets. By this means, we narrow semantic gap and implement feature fusion. At the same time, we also prove that previous fusion approaches are the special cases of our proposed approach by changing the weights. The experimental results on two public datasets show the benefit of our approach, specially at the aspect of recognition accuracy.
Evolvable hardware (EHW) has recently become a highly attractive topic for the Fault-tolerant System design because it offers a way of adapting hardware to different environments. However, it is time-consuming when circuits become complex. According to our research, the most time consuming period in genetic algorithm (GA) is the fitness evaluation. To reduce the time, a new method based on fitness evaluation expansion GA is proposed. The fitness evaluation is divided into two stages by a threshold. When the generation is lower than the threshold, a fitness estimate strategy is introduced to estimate the offspring's fitness. When really evolving the fitness, a self-adaptive random sampling model is applied to select the output node from the Cartesian Genetic Programming (CGP) array. During the evolution process, the random sampling probability can be adjusted dynamically with the concentration degree of individuals, which can short the evaluation time and accelerate the convergence. Experiments show that this method can obtain about 5 times speedup while getting an ideal circuit.
Life efficiency and habit development are important topics in schedule managing services, especially for College Students (CSs). Because CSs' daily management is different from that of others, their daily life is fixed in courses managing but flexible in self habit development. This paper presents the course-oriented Cloud-Based Interactional Managing Services (CBIMSs), which is a daily scheduling application based on Sina App Engine (SAE), where a self-adapting alarming algorithm is proposed based on the geographical location. The proposed WiDay has an aesthetical interface with humanized functions, which brings a brand new User Experience (UE). The interactional sharing platform is developed with cloud computing in SAE, which provides the sharing services among clients. The mobile client contains a self-adapting alarm clock which could offer humanized reminder, such as canceling the user's running plan automatically if it's rainy at that time, which takes the feelings of users into account. It also provides a course-oriented sharing platform for CSs to share courses information, such as the assignments, notes, or even notification of calling for roll. WiDay could broaden CSs' learning platform and help them make daily planning intelligently.
GitHub has accumulated a great number of developers and open source projects. In this research, we utilize property graph model to explore complex relationships and entities of GitHub. We attempt to answer three questions associated with GitHub using the dataset from MSR2014 data challenge. Firstly, we propose a graph based method to find out the cross technology background developers on GitHub. Secondly we define interesting metrics based on discrete entropy to analyze the project imbalance induced by commit action within a software family. The results show that the imbalance of development size induced by root projects is greater than that of development speed. Finally, we sort out the relatively important root projects with two link analysis methods and the experiment result demonstrates that our method is effective.
K-means in the field of clustering analysis algorithms is a kind of more traditional algorithm. It exists many shortcomings. For example, K value is easily affected by man-made subjective factors, and the algorithm is easy to fall into a local optimal solution, and the clustering result is not stable, etc, And K-means++ algorithm as the classic improved algorithm of K-means algorithm, but there is still a phenomenon of unstable cluster center. This paper is a kind of improvement aimed at the shortcoming of K-means++ algorithm, which introduces the concept of the variance in probability and mathematical statistics. Variance reflects the degree of density between samples and other samples. In the K-means++ algorithm when you select the first initial clustering center, you need to select minimum variance of sample points, which is in the position of the largest sample density, then you select the next cluster centers based on the weight method of D 2 which is described in the K-means++ algorithm. Experimental results show the accuracy is higher and stability is better.
The Distributed Denial of Service (DDoS) attack has seriously harmed network availability over decades and there is still no effective defense mechanism. The emerging software-defined networking (SDN) gives a new way to rethink the defense of DDoS attacks. In this paper, we first modeled DDoS attacks from the perspective of network architecture. Then a software-defined security networking mechanism (SDSNM) was proposed to remove or restrict these necessary conditions which were summarized from the model. The SDSNM is mainly implemented at the edge SDN networks as well as inherits the infrastructure of IP core network. The Cloud computing and Chord technologies were applied to solve the expansibility and consistency problems. Experiments based on the prototype proved that the brand new mechanism was feasible and incrementally deployable. DDoS attacks were unable to be launched if strict access control policies were used. The attacker along with hosts in botnet can be located quickly and accurately when loose access control policies were used.
With the development of spatial information application technology of the digital waterway, there is an explosion in the amount of digital waterway spatial information. The purpose of this study is to propose a solution for data organization and service publishing of the digital waterway spatial information. First, the concept of multi-dimensional digital waterway model is introduced. This model fuses the digital waterway spatial information together in a unified framework. Second, the data organization method of multi-dimensional digital waterway model based on the geodatabase of ArcGIS is proposed. This method will provide a unified and efficient data management mode. Third, the service publishing method of multi-dimensional digital waterway model based on ArcGIS Server is presented. This method will provide the secure and uniform data service for the client sides. Based on the above methods, we provide a complete server-side solution for the multi-dimensional digital waterway system.
In this paper, a new method of extracting wrinkle baselines is achieved. First, obtains the deformation vector field in accordance with the deformation analysis on initial mesh and deformed mesh and stretch the cloth mesh to two-dimensional plane. Then, track and extract the sideline in two-dimensional triangular mesh as initial baselines and smooth it to forms the wrinkle curves. Finally, obtain the three-dimensional coordinate of vertex in the wrinkle curves and integrate the wrinkle curves into the wrinkle area. The experimental results show that the technique achieves a good effect of extracting wrinkle baselines and can be applied to cloth mesh models.
With the development of mobile communication technology, the species of mobile communication network system including CDMA, LTE, 5G is growing. As a result, network elements play a more and more important role. However, network elements face serious security threats and security risks to fight against increasing cyber attacks. In order to improve the security of network elements, this paper propose a security layered architecture based on components. Security layered architecture based on components divides security module into individual components. It can achieve the effect of high cohesion and low coupling.
Since communication devices are carried by people in a great number of delay tolerant networks, delay tolerant networks are one kind of social networks to some extent. Analyzing social properties has become an important issue in designing efficient routing protocols. In this paper, a more accurate and comprehensive metric for detecting the quality of the relationships between nodes is proposed considering contact time, contact frequency and contact regularity. Then an overlapping hierarchical community detection method is designed based on this new metric and a tree structure is built. Furthermore, we exploit the overlapping community structure and the tree structure to provide message forwarding path from source node to destination node. Simulation results show that our routing method based on overlapping hierarchical community detection (ROCD)achieves better delivery rate than the classic routing protocols SimBet and Bubble Rap without affecting the average delay.
Faced with the growing demand of highway message propagation, network security, as well as the great challenges of global energy crisis, mobile interconnection and energy conservation are considered to be the key factors to promote the development of automotive electronics innovation in Intelligent Transportation System (ITS). Existing network planning is mainly performance-oriented and often neglects the radiation concerns, which have direct impacts not only on the environment but also on the network operators' long-term profitability. In this paper, we investigate a novel optimization framework for multiple Roadside unit (RSU) deployment in eco-sustainable communication networks for intelligent transportation (IT). The term "eco-sustainable" refers to low carbon, low exposure to radiation, low energy consumption and energy cost. We propose a generic integer linear programming (ILP) model which optimally and simultaneously: (i) minimizes the total cost, (ii) identifies the locations of RSUs, (iii) takes radiation constraints into consideration, (iv) meets the minimum information rate, (v) satisfies the coverage requirements so as to allow the users' accesses through the heterogeneous RSUs. We solve the model using Gurobi, which is the newest ILP solver by now. In addition, a new algorithm is proposed. Computational results show that compared with Gurobi, although there is a gap between the results, a shorter running time stands out in the new algorithm. Besides, we use AIMMS to get an interface of the final result intuitively, which makes improvements in visualization. We can also find when low exposure to radiation is concerned under the "Eco-Sustainable" network planning strategy, more dispersed RSUs to be distributed along with greater changes in the resulting network configuration, and thus the corresponding RSUs energy reduction, carbon emissions reduction as well as operational cost savings can be achieved.
A Broadcast Encryption (BE) scheme allows a sender to safely transmit messages to a dynamically chosen set of system users via insecure channels. An identity-based encryption scheme is a public key encryption scheme that can take arbitrary strings as public keys. This paper presents an identity-based broadcast encryption scheme (IBBE) for open networks where senders, including the entities outside the system, have the ability to broadcast messages to any subset of the system users but only the target receivers can retrieve the messages. Compared with a recently introduced primitive referred to as contributory broadcast encryption (CBE), our scheme has comparable properties and is more practicable: the cost of our scheme is much lower and the total number of the system users can be efficiently changed.
In-vehicle electronics is the fastest growing area of auto technology. A large part of this growth is in the area of Advanced Driver Assistance Systems (ADAS), which have become a very important part of the modern automobile. These ADAS systems usually run multiple applications simultaneously (e.g., Lane Departure Warning, Traffic Sign Detection, Pedestrian Detection, etc.). Each of these applications consists of multiple tasks and has hard real-time constrains that need to be satisfied. Finding new ways to reduce the cost, size, weight, complexity, and power consumption of the hardware used in these systems, while being able to offer more and more configurable features has always been a challenging problem for automotive suppliers and OEMs. The solution can be found in heterogeneous multicore embedded System on Chip (SoC), but the transition toward multi-core architectures has created more challenges at the software side, where fast deployment, integration and verification of the software is required. In addition to that, the temporal behavior of such safety critical applications must be predicted, with minimal processor reservation and memory usage. In this paper we will present a workflow to easily deploy and schedule multiple vision based ADAS applications on heterogeneous multi-core platform. This will be accomplished by employing Single Rate Data Flow (SRDF) graph as a base model of computation combined with hierarchical scheduling strategy that provides functional isolation and predictable timing between these applications. The results of this work could be used towards the design and implementation of partitioned, real-time operating systems that execute on heterogeneous multicore system on chip environment and a tool-chain to auto-generate such a system.
Pulse-based charging method for battery cells has been recognized as a fast and efficient way to overcome the shortcoming of slow charging time in distributed battery cells. The pulse frequency for controlling the battery charge will change within a certain range. The optimal frequency is determined to achieve the minimized battery impedance. The adaptation of a duty cycle of the pulse by decreasing the concentrated polarization guarantees a safe charging operation of all the distributed cells within a temperature range of 5°C to 45°C. The proposed charging process can be completed to about 80% of its maximum capacity in less than 20 minutes without damaging the battery characteristics. The newly designed charging results show that about two times faster than the conventional constant-current constant-voltage (CC-CV) charging method and 52% more efficient than the constant current fast charging method. The implemented high fidelity electrical model provides an approach looking into the effect of the pulse on the internal electrochemical reaction process. In addition, cell terminal voltage and temperature are simultaneously monitored in real time so as to adjust the frequency and duty of the proposed charging pulse method preventing battery degradation.
Community Question Answering (CQA) sites are becoming an increasingly important source of information where users can share knowledge on various topics. Although these sites provide opportunities for users to seek for help or provide answers, they also bring new challenges. One of the challenges is most new questions posted everyday cannot be routed to the appropriate users who can answer them in CQA. That is to say, experts cannot receive questions that match their expertise. Therefore new questions cannot be answered in time. In this paper, we propose an approach which based on distributed representations of words to predict the best answerer for a new question on CQA sites. Our approach considers both user activity and user authority. The user activity and user authority are based on the previous questions answered by the user. We have applied our model on the dataset downloaded from StackOverflow, one of the biggest CQA sites. The results show that our approach performs better than the TF-IDF and Language Model based methods.
Traditional file storage application mode of urban construction data files has many drawbacks. It is unable to meet the needs of the rapid development of urbanization. Based on the Dalian urban construction information data, combining with GIS spatial analysis techniques, Urban Construction Integrated Geographic Information System is constructed by database storage and C/S architecture in this paper.
