Abstract: Existing researches fail to involve formalized methods in evaluation and analysis of domain software and lack analysis on formal degree, this paper comes up with a formal degree evaluation approach for domain software based on evidence. Various levels of transformation models are mapped by formal analysis of evidence in life cycle of domain software so as to quantitatively measure degree of evidence. Evaluation model based on evidence is established by analyzing detailed evaluation requirement. A level model including mapping condition is established to describe formal degree at hierarchical level. This paper explains detailed evaluation process through an evaluation example. The approach stated in this paper can describe formal degree of domain software, evaluation data can support subsequent bottleneck analysis and trustworthy evolution, thus provide formal support for creditable construction and analysis.
Abstract: Control flow monitoring, information flow tracking and memory monitoring are the three main solutions to enhance the security of embedded system at the hardware architecture level. However, most of the current studies about the security of embedded system consider the above solutions in separate dimensions rather than a combined effort. We start from the operation model at the instruction level, and propose a security multi-strategy which combines information flow tracking and memory monitoring by studying the security operating mechanism of embedded system. As a hardware approach this strategy extends the embedded processor architecture with additional security defense control. The experimental results show this multi-strategy is more effective and can detect more malicious attacks than a single solution. The effectiveness of our proposed security multi-strategy has been verified in a Field programmable gate array (FPGA) prototype platform based on a customized Leon3 microprocessor.
Abstract: Expression theory is the mathematical foundation of evolutionary computation. In order to investigate the problems in Gene expression programming (GEP) expression theory, we clarified the difference between genotypic expression space and phenotypic expression space. We also presented phenotypic expression space definition and theory. Then we analyzed the reason of good and bad performance of different GEP algorithms based on expression space theory. We also proposed a new Adaptive multi-phenotype gene expression programming (AMGEP), in which the potential of genes is fully activated with gene combination. Experiments on benchmark problems showed that genotypic expression space and phenotypic expression space theory can explain the different performance of different algorithms and showed that AMGEP outperform other GEP algorithms in terms of search ability.
Abstract: After studying the routing and forwarding process of network stream and the implementation of SDN, we propose a retractable management model for flow table. A structure with parallel tables and synthesis processing is proposed according to the feature of SDN and traditional network. The parallel tables share the same storage resources. Thanks to the separation of data plane and control plane, control plane owns more computing resources than traditional device. It evaluates the role of nodes and the action of network flows, makes adjustment according to the historical and current information and streamlines flow tables by consolidating and simplifying old flow entries. Through simulation, it is proved that the realized method can defend offensive traffic while ensuring the safety of accessing and forwarding, especially existing blocking attack.
Abstract: MTL is a Monoidal t-norm based logic introduced by Esteva and Godo by omitting divisibility axiom from Hájek's Basic logic (BL). Many logics can be obtained by adding axioms to MTL logic. Logic system WBL is obtained by adding weak divisibility axiom to logic system MTL. Logic system WMV is obtained by adding involution axiom to logic system WBL. WBL-algebra corresponding to logic system WBL and WMV-algebra to logic systemWMV are defined respectively. It is proved that the both of logic system Luk and logic system Nilpotent minimum (NM) are the schematic extensions of logic system WMV. Weak Wajsberg algebra and the simplified form of logic system WMV are obtained.
Abstract: We propose an alternative Redundant array of independent disks (RAID) data layout, Asymmetrical grouping data organization (AGDO), for object-based data de-duplication backup system. Object-based data deduplication is an effective solution for detecting duplicate data for compound files. We designed an asymmetrical grouping strategy, the disk in the array are partitioned into different groups, and in each group parallelism data access scheme is adopted, different types of objects are stored in different groups with maybe different group size, it can set and manage dynamic group size by using dynamic disk group adjustment algorithms. The performance of AGDO is evaluated and proved to be sufficient for the continuous storage application. The result is that disk accesses are concentrated in a part of the disks over a long time period and reduces the power consumption to 25% in a 10-disk configuration. Moreover, object-based de-duplication combined with AGDO has great potential in increasing data restoration speed for compound files. We have shown that this combination makes average restoration speed improved 11%.
Abstract: This paper introduces a concept of User latent intentions (ULI) consisting of user preference intentions and user herd intentions for the expression of a user's personalized requirements of services. Theory of TCP-net and herd psychology is employed for the establishment of user preference decision model and user herd decision model, followed with a user-centric service discovery algorithm based on ULI. Simulation and experimental results demonstrate that the proposed ULI-based service discovery approach can increase the effectiveness of service discovery.
Abstract: This paper presents an extension of π-calculus, named p-π, with interval action prefixes. The syntax and operational semantics of p-π are formalized, and the algebraic and time-dependent properties are defined. Based on them, how time-dependent behaviors of systems can be modeled with p-π is demonstrated. Finally, a case study is given to illustrate how p-π is used in practise.
Abstract: By grouping Web services that share similar functionalities, Web service clustering can greatly enhance Web service discovery and selection. Most existing clustering techniques are designed to handle long text documents. However, the descriptions of most publicly available Web services are in the form of short text, which impairs the quality of service clustering due to the sparseness of useful information. Towards this issue, we propose a new service clustering approach based on transfer learning from auxiliary long text data obtained from Wikipedia. To handle the inconsistencies in semantics and topics between service descriptions and auxiliary data, we introduce a novel topic model-Tag aided dual Author topical model (TD-ATM), which jointly learns two sets of topics on the two data sets and automatically couples the topic parameters to avoid the potential inconsistencies between these two data sets. Experimental results show the proposed approach outperforms several existing Web service clustering approaches.
Abstract: For the scheduling problem of Semiconductor wafer fabrication (SWF), a new Dispatching rule based on the load balance (DRLB) is proposed. Further, a new Harmony search (HS) algorithm based receipt priority interval (HS_rpi) is presented to minimize the mean cycle time. A kind of chaotic sequence is used as the harmony vector. Then, a conversion method is designed to convert the real number harmony vector to the mixed vector representing the priorities of all receipts and the algorithm parameters. In order to increase the algorithm robustness and decrease the scale of the scheduling problem, based on receipt priority interval and DRLB, we give a special conversion method used to convert the above mixed vector to the solution of the scheduling problem of SWF. Computational simulations based on the practical instances validate the proposed algorithm.
Abstract: Local patterns record the gray-level differences between a referenced pixel in an image and its surrounding pixels, which have been commonly used to describe the image features. However, traditional local patterns ignore the spatial distribution feature of texture information in images. We group the gray-level variations along three directions, i.e., horizontal, vertical, and diagonal directions. Each group is then merged into a Local spatial distribution pattern (LSDP) to represent the spatial distribution image feature.We also construct the LSDP patterns for gradient and filtered images, and finally form the Complete local spatial distribution pattern (CLSDP) descriptor to completely describe the texture image feature. Experiments on textural and natural image sets were conducted to compare our CLSDP-based image retrieval algorithm with four previous competitors. The results show that our method is superior to existing algorithms considering both average precision and recall.
Abstract: This paper proposes the Decision feedbackfeedforward per-survivor processing (DFF-PSP) iterative separation algorithm and the Monte Carlo integrationbased method to compute the theoretical bound for Paired carrier multiple access (PCMA) Single channel blind separation (SCBS) which is highly complex with long memory. The truncated PSP is employed while the pre- and post- cursors are disregarded to control the complexity. The delayed decisions feedforward and local decisions feedback filters are designed to process the pre- and postcursors. The Bit-interleaved code modulation iterative decoder (BICM-ID) is combined with the second soft decision of the truncated PSP to obtain a better performance. The mixture signal model is regarded as a Multiple-access channel (MAC) with memory, and the theoretical performance bound is obtained via entropy inequality, Monte Carlo integration and Fano inequality. Simulation results show that the DFF-PSP iterative separation provides the good tradeoff between complexity and performance.
Abstract: Facial cosmetology is usually operated by surgeons on the basis of clinical experiences and is full of risks because of the lack of objective criteria and auxiliary tools. The available plastic simulation systems are not easy to manipulate. This paper presents a realistic cosmetic plastic surgery simulation framework guided automatically by golden ratio data, which is suitable for personalized realistic facial models from 3D laser scan. A golden ratio facial mask is made based on the ideal golden ratio facial mask data, with reference to the facial ratio of goodlooking groups of eastern people. The plastic design for the region of interest will be driven automatically by Laplacian coordinates deformation, based on the matched characteristic points and lines of the golden ratio facial mask to set the boundary conditions. The evaluation from clinical surgeons shows that the new plastic simulation system is practical and will be widely used in clinical operations.
Abstract: We introduce both shape prior and edge information to Markov random field (MRF) to segment target of interest in images. Kernel Principal component analysis (PCA) is performed on a set of training shapes to obtain statistical shape representation. Edges are extracted directly from images. Both of them are added to the MRF energy function and the integrated energy function is minimized by graph cuts. An alignment procedure is presented to deal with variations between the target object and shape templates. Edge information makes the influence of inaccurate shape alignment not too severe, and brings result smoother. The experiments indicate that shape and edge play important roles for complete and robust foreground segmentation.
Abstract: Key exposure is a severe threat in digital signature, the scheme will be compromised provided that the private key of the signature is revealed. To remove the destruction of key exposure, the private key must be kept updated in the process of the signature. As a new cryptographic primitive, Attribute-based signature (ABS) scheme has the limitation in practical applications because the private key may be leaked. So far, very little works have focused on the key leakage of ABS, especially in the setting of lattices. To deal with the problem, we present the construction of Key evolving attribute-based signature (ke-ABS) under Short integer solution (SIS) problem. As a new research field in the point, our scheme has considered a threshold access structure, which allows users with attributes satisfying the defined policy that can generate a valid signature without revealing more information. Compared with the known schemes, our scheme provides an assurance of unforgeability and attribute signer privacy.
Abstract: With the underlay approach, Secondary users (SUs) can utilize the same frequency bands simultaneously with Primary users (PUs) in Cognitive radio networks (CRNs). How to choose the appropriate transmission power of SUs under the influence caused by other cells is a problem. To solve this problem, spectrum sensing is introduced to identify the existence of interference which using pilot signal to perform coherent processing. Consider the probability of detection of SUs, there exists a trade-off between the sensing time and the achievable throughput of CRNs. When the prior probability of other cells' activity is unknown to SUs, throughput of the CRNs can be viewed as a concave function. According to solving the optimization problem, the optimal sensing time is obtained. Simulation results show the feasibility and correctness.
Abstract: With the development of Radio frequency identification (RFID) technologies, theoretical study on the protocol's design promotes the increasing reality applications of this product. The protocol designers attach significance to untraceability analysis on key-update RFID authentication protocols. This paper analyzes two RFID authentication protocols in terms of forward untraceability and backward untraceability, which are two necessary conditions for key-update RFID protocols and ownership transfer protocols. This paper introduces impersonation attacks as well as desynchronization attacks to two protocols. This paper presents two enhanced protocols, which can achieve forward untraceability and backward untraceability privacy. This paper shows the outstanding efficiency and security properties of two improved schemes through detailed analysis and comparisons.
Abstract: We propose a class of Rate-compatible (RC) Low-density parity-check (LDPC) codes with a very wide range of code rates. To widen the range of rates, we have developed an optimal transmission scheme to push the upper bound of code rates to 0.96. Characterized by a parity check matrix in a dual-diagonal form, the proposed RC LDPC code can be encoded in linear time. Constructed from shifted identity sub-matrices, the proposed codes are particularly well-suited for the high-speed implementation of parallel encoders. Furthermore, the encoder can be implemented efficiently with several left circular shifters and XOR gates. To maximize the encoding speed, we have proposed a q-parallel encoder architecture, where q is the size of each sub-matrix. The implementation results into Field programmable gate array (FPGA) devices indicate that a 72-parallel encoder for the proposed RC LDPC code with a code rate from 0.5 to 0.96 is capable of reaching a speed of 42 Gigabits per second (Gbps) using a clock frequency of 300MHz.
Abstract: The last decade has witnessed a rapid growth in wireless communications technology, and as a result the demand for spectrum resources increased rapidly. Unfortunately, many new wireless demanders cannot access the limited wireless licenses in time while large chunks of spectrum are idle. To solve this, we design a multiunit double auction mechanism for heterogeneous spectrum channels, which take the spatial and temporal reuse into consideration. The proposed scheme first introduces the multi-participantsmulti-heterogeneous-spectrum trading double auction to illustrate the system model. Some techniques such as spectrum categorize, virtual sellers and buyers' conflict graph construction, and reconstruction of buyer groups are adopted to achieve a high efficiency of the algorithm. Then, we also prove the truthfulness, individual rationality, and budget balance of the proposed scheme. Finally, the simulation results show that the practical performance of the proposed scheme can efficiently improve the spectrum transaction ratio, reuse ratio, and the buyer's satisfactory ratio.
Abstract: Due to uncertain network connectivity, efficiently data forwarding in Mobile social networks (MSNs) becomes challenging. To conquer the problem, an Efficient data forwarding scheme based on geography intimacy (GIDF) for MSNs to achieve higher delivery ratio is proposed. In GIDF, we firstly propose an Intimacy based dynamic community detection algorithm (IDCD), which divide the MSNs into several communities. We propose a novel metric geography intimacy which can quantify the node's geographical information and the friendships between nodes. Based on geography intimacy, we further propose a routing algorithm to forward data. Compared with the geography intimacy between nodes, the next hop is found, further find the route of data forwarding by doing the similar operations. Extensive simulations on real data with the ONE simulator show that GIDF is more efficient than the existing algorithms.
Abstract: User preferences elicitation is a key issue of location recommendation. This paper proposes an adaptive user preferences elicitation scheme based on Collaborative filtering (CF) algorithm for location recommendation. In this scheme, user preferences are divided into user static preferences and user dynamic preferences. The former is estimated based on location category information and historical ratings. Meanwhile, the latter is evaluated based on geographical information and two-dimensional cloud model. The advantage of this method is that it not only considers the diversity of user preferences, but also can alleviate the data sparsity problem. In order to predict user preferences of new locations more precisely, the scheme integrates the similarity of user static preferences, user dynamic preferences and social ties into CF algorithm. Furthermore, the scheme is parallelized on the Hadoop platform for significant improvement in efficiency. Experimental results on Yelp dataset demonstrate the performance gains of the scheme.
Abstract: The goal of authentication scheme for Vehicular ad hoc networks (VANETs) is to ensure reliability and integrity of message. Due to the timeliness of traffic-related messages and the highly dynamic nature of VANETs, it still is a challenge to solve the three key issues simultaneously, i.e. security, efficiency and conditional privacy-preserving, on the design of authentication scheme for VANETs. To address this challenge, an efficient Conditional privacy-preserving authentication (CPPA) scheme is proposed in this paper. Compared with the most recent proposed CPPA schemes, our proposed scheme markedly decreases the computation costs of the message-signing phase and the message verification phase, while satisfies all security requirements of VANETs and provides conditional privacy-preserving.
Abstract: In opportunistic networks, a successful message transmission between node pairs depends on the message size, the transmission speed and the connection duration time. This paper proposes a new message forwarding algorithm to improve the message delivery ratio and reduce the energy consumption. Previous encounter characteristics between nodes are used to estimate future connection duration time using a three point estimation method. Furthermore, the buffer utilization of nodes is used as a weight for the likelihoods to meet destinations according to the hop count of messages stored in the buffer. The simulation results show that the proposed forwarding algorithm achieves higher delivery ratio and less overhead ratio than the other four popular routing protocols. In addition, the proposed algorithm gains a better average residual energy performance among all the compared protocols.
Abstract: Z-source Neutral point clamped (NPC) inverter inherits the advantages of Z-source inverter, which can buck-boost energy and allow the shoot-through states. At the same time, Z-source NPC inverter has high running efficiency and less harmonic content. Hence, it can be widely used in motor drives and fuel cell applications. When increasing the modulation index, one can only get smaller shoot through value in Z-source NPC inverter, therefore the output voltage of the inverter can not be boosted very high. In this paper, a novel cascaded Z-source neutral point clamped inverter is proposed by cascading two Z-source networks in series. An Alternative phase opposition disposition (APOD) carrier-based modulator is applied to control the proposed Z-source inverter. To confirm the operating principle of the new Z-source NPC inverter, a generic APOD carrier-based modulator for the cascaded Z-source NPC Inverter under Matlab/Sinmulink is built. The simulation results show that the boost factor has been increased from 1/(1-2D) for the traditional Z source NPC inverter to 1/(1-4D) for the proposed cascaded Z-source NPC inverter. A prototype of the cascaded Z-source NPC inverter has been set up. The experimental results verify that the new topology can increase the boost factor and expand the voltage regulation range of the inverter.
Abstract: Water region detection based on SAR images is a difficult problem for its computing complexity. This paper proposes a novel water region detection method in SAR image of complex scenery. The algorithm takes advantages of Bag of visual words (BOV) to precisely describe the homogeneous region in complex scenery. Local pattern histogram (LPH) and single-class Support vector machine (SVM) are adopted to determine the edge information of water region precisely. The feature extraction is calculated block by block, which reduces computing workload and interference from noise. The experiments based on SAR images of real complex scenery show that the proposed method achieves higher accuracy and robustness.
Abstract: The beam-wave interaction efficiency of a 170 GHz megawatt-level corrugated coaxial-gyrotron operating with TE31,12 mode was studied numerically. According to the self-consistent nonlinear theory, the efficiencies of two types of coaxial resonator were calculated and compared. Taking into account electronic velocity spread and cavity wall resistivity, the beam-wave interactions of improved cavity were investigated. The relationships between efficiency and magnetic field, voltage, current, beam radius, velocity ratio, and parameters of groove are presented. The results show that the voltage and magnetic field have great influence on efficiency, but the current and velocity spread do slightly. The optimized geometry parameters can improve efficiency, reduce the impact of velocity spread on efficiency, and achieve around 48.6% electronic efficiency and 1.7MW output power at 5% velocity spread and 6.896×10-8Ωm resistivity.
Abstract: A 320-356GHz fixed-tuned frequency doubler is realized with discrete Schottky diodes mounted on 50μm thick quartz substrate. Influence of circuit channel width and thermal dissipation of the diode junctions are discussed for high multiplying efficiency. The doubler circuit is flip-chip mounted on gold electroplated oxygenfree copper film for grounding of RF and DC signals, and better thermal transportation. The whole multiplying circuit is optimized and established in Computer simulation technology (CST) suite. The highest measured multiplying efficiency is 8.0% and its output power is 5.4mW at 328GHz. The measured typical output power is 4.0mW in 320-356GHz.