Abstract:The screen lock of touch screen devices is designed to prevent the users' misuse without taking security into account. To solve this problem, this study provides a design of a secure scheme to unlock the touch screen. Unlike the traditional modes that unlock the touch screen by sliding the sliders or identifying the graphics and images, the presented design is a method to create a rhythm key based on the tapping gestures. The rhythm recognition algorithm is able to identify the rhythm sequence tapped on the screen, extracting rhythm features and creating the keys. Through testing, the new scheme can better match the rhythm gestures and improve the information security greatly. Meanwhile, as a new unlock method and relating to the individual's sense of music experience, the rhythm recognition focus on users' experience such as convenience, entertainment and reliability, all of which are human-computer interaction-friendly features.

Abstract:Travelling in metropolis is becoming increasingly difficult for people due to the growing population and busier traffic. Since taxi is important public traffic tools in cities, knowing how long it will take to find a taxi can be helpful for customers to plan their schedule and choose the best place to wait. This paper presents a method to predict the waiting time for a customer at a given time and location from historical taxi trajectories. With a parametric and a non-parametric model for arriving flow of vacant taxis, it predicts the time a single passenger needs to wait for a taxi service. Emulation experiment with large-scale taxi dataset in Hangzhou was conducted to verify the new method. The evaluation results validate that the mean prediction errors for both the parametric and non-parametric model are about 4.5 minutes. Moreover, the probability of that the prediction error is below 5 minutes for parametric model is about 83 percent.

Abstract:With the spread of social needs and development of techniques, social interaction is more and more frequent among people. To promote and assist human social interaction, it's important to understand the social context the user situates. The paper mainly studies the understanding of social contexts based on background sounds, the goal of which is to recognize the social context in which users reside through analyzing the differences of background sounds. It uses the Mel frequency cepstral coefficients to analyze sound features and classify the sounds based on an improved Dynamic Time Warping (DTW) algorithm. Experimental results show that the proposed algorithm is more effective than traditional methods.

Abstract:Due to its nonlinear potential, hyper video offers improvement in users' browsing efficiency and visual information's representation ability compared with that of traditional video. Based on the advantages of sketch and sketch based interface, this paper provides an intuitive sketch based interface for supporting hyper video creation to describe users' intention and improve user experiences. Furthermore, a force-directed graph layout algorithm for representing video semantics is discussed. This algorithm constructs a model for video semantics. It brings attributions such as temporal or spatial information, video structure and constraints between video clips into mass of nodes and attractive forces or repulsive force of edges in the force-directed graph. Result shows that it is an intuitive method to represent the dynamitic process of creation and modification for hyper videos.

Abstract:By means of significant test and co-linearity analysis, this paper proposes principal component linear encoding which selects the K-nearest neighbor visual word with the strongest linear correlation. The multiple linear regression method based on principal component is used to solve weak and instable coding caused by the visual words' co-linearity problem, improving the accuracy of the visual object classification effectively. Recognizing that the scarcity of the image quantify plays an important roles in the classification accuracy, the study analyzes the scarcity of the quantitative results obtained by the principal component linear encoding and then processes it with energy regularization to improve the classification efficiency further. The experimental results demonstrate that this method increases the recognition rate average over 1% than existing algorithms.

Abstract:Vehicular ad-hoc networks (VANETs) are a new kind of mobile ad hoc network, and applications over VANETs are emerging with bright prospects. Considering that a long-distance data dissemination mechanism is indispensable for most VANET applications, this paper presents Ara, a RoadSide Unit (RSU)-aided unicast routing mechanism for VANETs, and evaluates its performance under different traffic scenarios. The experimental results show that Ara can keep high data delivery ratios, low delay and few message overheads even in the case of RSU failures. Moreover, the paper theoretically analyzes the data delivery delay of Ara by establishing an analytical model. Based on a vehicular microscopic flow mobility model, the analytical model can deduce the delay under the different RSU conditions. The model has been verified on its validation by simulation experiments and therefore it can be applied to predict the performance of data delivery through Ara.

Abstract:Taking user's emotion regulation as application background, this paper presents a collaborative filtering algorithm integrating trust and preference of user's emotion to meet user's emotional needs. Firstly, a user preference model based on ratings and trust is presented to address the scalability issue of user preference model in collaborative filtering. The proposed model uses the number of ratings to set two thresholds to extend the calculation strategy of user similarity weight to selectively assign the trust value and correlation to the rating value in the user preference model. Secondly, in the process of producing the candidate set of items, the emotional connotation of items is customized. The user preference for emotional connotation of item is introduced to make up for the neglect of user's emotions in collaborative recommendation. Experimental results show that the presented algorithm has good scalability and therefore improves user satisfaction.

Abstract:Speed and accuracy of information access are essential in modern logistics operations. In this paper, the RFID technology is applied to logistics containers for keeping information dynamically, and the concept of information containers as opposed to logistics containersis put forward. In order to improve the efficiency of data access on tag, a set of RFID middleware named tag operation system (TOS) is proposed. Firstly, the tag memory is paged according to the length of the electronic product code (EPC). Secondly, a bitmap is built up in the tag memory to index the free memory space. Thirdly, the data storage format identifier (DSFID) is designed to make memory paging more flexible. Finally, real-time memory database is set up in the host computer to improve efficiency of tag data query. The experimental results show that TOS can greatly enhance the efficiency of the reader operations on tag. TOS can be widely applied to the applications of lifecycle management of articles.

Abstract:In order to assesses accurately the characteristics of the land surface from different angles, and provides guidance to improve the simulation performance of land surface models, the framework of LSMS (Land Surface Modeling System) is constructed on the basis of scripting languages and Model-Data Fusion methods to provide researchers a land surface modeling environment from data processing to simulation analysis. The modeling system is an integration of observing data, land surface simulation, high-performance computing, data processing and analysis, and visualization techniques. Different land surface models were used in the framework to prove the utilization potentials of modeling system based on scripting language in high-performance computing environment and the role of various visualization schemes in the modeling system.

Abstract:The three layers supercomputing environment of Chinese Academy of Sciences is built to integrate the computing resources of the head center in Beijing, eight regional centers and several campus-level centers. To enhance the reliability of the supercomputing environment and provide stable and reliable computing services, the fault-tolerant mechanism research has become a research priority of the supercomputing environment. In this paper, the fault-tolerant basic concepts and computer fault-tolerant technologies are introduced at first. Next, a fault-tolerant framework of the supercomputing environment is proposed. Then the fault-tolerant solutions of different levels based on the framework and the performance test results in Deepcomp 7000 are presented. Finally, the fault-tolerant overheads of different levels are compared and analyzed to verify the impact on the application.

Abstract:Since processing large-scale spatial join aggregate (SJA) is usually difficult to be implemented on a single machine, parallel computing on cluster has been the key to process large-scale SJA operation efficiently. Map-Reduce has been the mainstream parallel computing technique for massive data on cluster. However, Map-Reduce does not directly support processing parallel SJA with both high efficiency and straightforward way, for it needs to perform a second reduce operation. This paper proposes a novel parallel computing model, Map-Reduce-Combine (MRC), which is able to process large-scale SJA efficiently with a simple way on cluster. MRC adds to Map-Reduce a Combine phase that can efficiently combine partial aggregate results distributed among different Reducers, which is caused by the multiple assignment of spatial object. For the spatial object assigned only once, a filter optimization method has been proposed to pick up the result of single assignment object obtained in Reduce phase and further enhance the performance of processing SJA. Extensive experiments in large real spatial data have demonstrated the efficiency, effectiveness, scalability and simplicity of the proposed parallel computing model for processing SJA on massive spatial data.

Abstract:This paper presents a parallel finite element algorithm based on the toolbox PHG for solving the nonlinear Poisson-Boltzmann equations for biomolecular systems. Previously TMSmesh, TransforMesh and ISO2Mesh were used to generate high resolution meshes. In this work a new method which combines mesh generation and adaptive mesh refinement is introduced to avoid complicated mesh generation steps. The new approach makes use of the capabilities of PHG in local mesh refinement and dynamic load balancing. The efficiency of the new method is demonstrated with a sphere model and the AChE system through both the decay of the a posteriori error estimates and the convergence of solvation-energy. In the meantime the method is also successfully applied to the Gramicidin Aion channel system.

Abstract:MAGMA is an open source high performance linear algebra package first developed for next-generation of heterogeneous/ hybrid architectures (CPUs+GPUs) with a dense linear algebra library similar to LAPACK in functionality, data storage, and interface. This paper presents performance testing and analysis of MAGMA. It first studies the matrix decomposition algorithm in MAGMA, then provides some useful suggestions of MAGMA usage and optimization through massive testing and source code analysis, and finally proposes a method for auto-tuning matrix decomposition block algorithms. In this test, the speedup is 1.09 for SGEQRF of square matrix and 1.8 for CGEQRF in terms of tall and skin matrix.

Abstract:MIPS architecture is an important member of RISC processor family, and it is mainly applied in embedded systems. With its performance improvement, the MIPS processor is gradually used in the field of high-performance servers. The Loongson-3 processor is a typical representative of the MIPS architecture. As a main feature of high-performance server, the multi-core architecture is indispensible. Meanwhile, virtualization technology is another important application for the server, however in recent years the technology rarely has success on the Loongson-3 processor. Combining virtualization technology and multi-core technology on the Loongson-3 processor has much more difficulties as the method to simulate the multi-core architecture is hard and collaborative mechanism among different cores is complex. This paper analyzes the multi-core architecture and communication mechanisms of the multi-core architecture Loongson-3 processor and introduces a virtualization method for the multi-core architecture Loongson-3 processor. It mainly discusses the overall design of virtualization method of the multi-core Loongson-3 processor, the simulation of Loongson-3 multi-core architecture and the virtual inter-processor interrupt communication in the virtual machine. Experimental results show that the presented method provides useful and efficient multi-core virtualization support for the Loongson-3 processor.

Abstract:De Bruijn graph is a vastly used technique for developing genome assembly software nowadays. The scale of this kind of graph can reach billions of vertices and edges, posing great challenges to the genome assembly task. It is of great importance to study scalable genome assembly algorithms in order to cope with this situation. Despite some recent works and therefore begin to address the scalability problem with parallel assembly algorithms, massive De Bruijn graph processing is still very time consuming which needs optimized operations. This paper aims to significantly improve the efficiency of massive De Bruijn graph processing. Specifically, focus is placed on the time consuming and memory intensive processing in the construction phase and the simplification phase of De Bruijn graph. The study observes observe that the existing list ranking approach repeatedly performs parallel global sorting over all De Bruijin graph vertices, which results in a huge amount of communications between computing nodes. It therefore proposes to use depth-first traversal over the underlying De Bruijn graph once to achieve the same objective as the existing list ranking approach. The new method is fast, effective and can be executed in parallel. It has a computing complexity of O(g/p) and communication complexity of O(g), where g is the length of genome reference, p is the number of processors, which is smaller than the existing list ranking approach, Experimental results using error-free data show that, when the number of CPUs scales from 8 to 512, our algorithm has a speedup of 13 and 10 times on processing the data sets of E.coli and Yeast respectively; and when the number of CPUs scales from 32 to 512, the algorithm has a speedup of 7 and 10 times on processing the data sets of C.elegans and chr1 respectively.

Abstract:Currently, most of searching methods for microblog use vector space model to calculate the relevance between the query and document. The statistical method of Term Frequency-Inverse Document Frequency (TF-IDF) is widely used to determine the weight of words. However, only using word as the unit of microblog searching is not enough to detect the whole information content of a microblog, which is usually the intent of the search users. To solve this problem, a learning to rank algorithm for microblogs based on analysis features and dynamic stepsize is proposed. Firstly, some analysis features for microblogs are defined, The features can be obtained through statistical analysis method, and used to predict user's behaviors. Secondly, a method to calculate the relevance of microblogs based on part of speech is proposed. It uses the strategy of information entropy to calculate POS information content of microblog and it can be used to predict the information content of the microblog. Finally, based on the existing ListNet algorithm, the concept of dynamic stepsize is introduced to optimize the calculation of stepsize, eventually a learning to rank algorithm for microblogs based on dynamic stepsize named Ranking based on Dynamic Learning Stepsize (RDLS) algorithm is formulated. The experimental results show that RDLS algorithm can get a more optimal training model by using either direct features or both direct and analysis features with the same iterations, and can attain better effect in microblog ranking compared with the ListNet algorithm.

Abstract:Because of the diversity of users' interests and behavior, it is a great challenge to provide appropriate search results for different users. The social tags in Web 2.0 result from users' annotation behavior for pages that they are interested in. The user uses tags frequently to describe these topics, therefore the tags not only represent the user's query intention, but also reveal the Web information best. This paper presents a research for user-oriented query intention. It aims at adding the tags which can reflect the user's real query intention to the query. Tags as a supplement to the query keywords, not only can make up the defects of short queries, but also accord to the correlation between the query tags and Web content in sorting the related results. If the user just uses the keywords, the query log needs to be used to recommend high-quality tag as a supplement to the query keywords, and return more relevant results. Experimental results show that the proposed method is better in meeting the needs of users than other methods, making the search results more close to user requirements. This means that the social tags can make an important contribution to catching the query intention.

Abstract:Clustering algorithm of medical image is a significant part of special field image clustering. Due to technical limit and many problems in specific area, the study in this direction has been very challenging. The exiting algorithms of clustering require shape and density of data object, which imply that there won't be a good outcome for the application of medical image clustering. To solve the problem above, this paper firstly detects texture from image, proposes T-LBP method, divides the preprocessed image into multiple spaces, calculates the value of LBP spaces, and then builds a spatial sequence LBP histogram. In the end, the clustering method of MCST is proposed based on the created LBP histogram. The outcome of this experiment indicates that the algorithm presented in this paper achieved good results in terms of time complexity and clustering function.

Abstract:Many new data applications, such as wireless sensor networks, and traditional data applications that process images produce massive probabilistic data. In probabilistic data management, the Top-k similarity join operation returns the most similar k pairs of probabilistic data and thus has important value. Histogram is one of the most frequently-used data models for representing probabilistic data. Earth Mover's Distance (EMD) is more robust in quantifying the similarities between histogram-represented probabilistic data. However, EMD computation has a cubic time complexity, which brings great challenges to the EMD-based Top-k similarity joins. Based on the MapReduce framework, this paper utilizes the good properties of EMD's dual problem and proposes two EMD-based Top-k similarity join algorithms on massive probabilistic dataset. A baseline solution named Top-k BNLJ algorithm is first developed on the idea of block-nested-loop join, and the novel Top-k DLPJ algorithm is then built on the improved idea of data locality preserving data partition strategy which significantly reduces the amount of data transferred during MapReduce jobs. Extensive experiments on large real-world datasets, with millions of probabilistic data, have verified the efficiency, effectiveness and scalability of Top-k DLPJ algorithm.

Abstract:Four dimensional Gallant-Lambert-Vanstone (GLV) method can be applied for faster scalar multiplication on some elliptic curves over F_p2 , such as the Longa-Sica GLS curves with special complex multiplication (CM), and the Guillevic-Ionica's curves via Weil restriction. This study generalizes Long-Sica four dimensional GLV decomposition methods, and gives explicit and efficient decompositions in quartic CM fields for such elliptic curves as well as the bound for the decomposed coefficients. The presented results well support the GLV method for faster implementations of scalar multiplications on desired curves.

Abstract:Lai and Massey designed IDEA in 1991 when Lai-Massey scheme was first used in the algorithm. Vaudenay in 1999 added a function σ which has the orthomorphic or α-almost orthomorphic property in Lai-Massey scheme, and proved that this construction could make Lai-Massey scheme satisfy the Luby-Rackoff theorem. In this paper, the provable security of Lai-Massey scheme against differential and linear cryptanalysis is investigated. Firstly, the infimum of the number of differentially active F-functions in Lai-Massey scheme is given no matter if F is an orthomorphism or not. Secondly, the results in this paper indicate that when F is an orthomorphism, the infimum of the number of differentially active F-functions is the same as that of Feistel scheme. Finally, a dual model is introduced to study the duality between the differential characteristic chains and linear approximation chains in Lai-Massey scheme, which can be used to obtain similar results of linear cryptanalysis for Lai-Massey scheme directly.

Abstract:The pollard kangaroo method is a very effective way to solve the discrete logarithm problem in an interval of size N, which needs approximately 2 √N group operations under heuristic average case. For those fast inversion groups, Galbraith and Ruprai use equivalence classes method to lower the times of group operations which are needed under heuristic average case to approximately 1.36 √N.Based on Galbraith and Ruprai, this paper optimizes the method and adjusts the active interval of the tame kangaroos and wild kangaroos, in a way of changing each of their intervals to approximately 0.8581 times the original one, so that the group operations under heuristic average case is lowered to approximately 1.338√N.

Abstract:Location-Proof in smart-phone based on WiFi wireless network is developed rapidly and has raised broad concern in the recent years. Two secure and reliable protocols of location-proof in smart-phone based on WiFi wireless network are proposed. Employing cryptograph and appropriate parameters, the protocols ensure integrity, reliability and anonymity of the location-proof. Anonymity denotes the protocols protect the information of identity when proving the location. Analysis and proof of the security of the location-proof protocols are provided. Compared with similar protocols, the presented schemes have more advantages in terms of efficiency and safety.

Abstract:Due to the defects caused by design principle and mechanism, Trusted Computing Platform can't effectively protect the system security from physical attacks. A novel design method based on signal integrity analysis was introduced to solve this problem. Based on the work stated above, this paper proposes a revised logical hierarchical design of TPM-APM (TPM-analog parameter measurement) sub-module. Furthermore, engineering implementation method of TPM-APM sub-module is provided by measuring the analog parameters of delay. Through comparing eye patterns, the practicability of implementing the TPM-APM sub-module is verified. Detailed analysis and experiment reveal that the revised TPM-APM sub-module can effectively enhance the ability of protecting Trusted Computing Platform against physical attacks.