Abstract: This paper studies the error linear complexity of binary sequences with period 2n. One new representation of binary sequences with period 2n and new interpretation of Games-Chan algorithm are given. New properties about the first critical error linear complexity and one algorithm to compute the first critical error linear complexity are given. One formula of the minimum value k for which the k-error linear complexity is strictly less than the first critical error linear complexity is provided.
Abstract: In recent years, Peer-to-peer (P2P) file sharing networks such as BitTorrent and eMule become more and more popular. BitTorrent and eMule deploy their distributed networks based on Kademlia, a robust Distributed hash table (DHT) protocol to facilitate the delivery of contents. The Kademlia-based networks and its measurement tools (i.e., P2P crawlers) have intrigued many researchers in the P2P community. However, to our best knowledge, few versatile P2P crawlers are developed for intensive measurement on Kademlia-based networks. In this paper we develop such a crawler, namely Rainbow. For the first time, we theoretically analyze the convergence of Rainbow, and obtain its convergence order which determines the time complexity of crawling. We then experimentally verify the convergence of Rainbow. Finally, we demonstrate that Rainbow can be applied as a versatile measurement tool to identify various detailed characteristics for Kademlia-based networks.
Abstract: The difference between real-time CSCW systems and traditional distributed systems is that the former one is supposed to provide a natural, free and fast interface for multi-user interaction. However, the typical multi-user interaction method applied in 3D CAD systems is strict consistency maintenance, such as locking mechanism and floor control, which may generate a stagnant and unnatural interface. This paper proposes a 3D semanticbased Operational transformation (OT) to support less constrained multi-user interaction and to achieve consistency in collaborative CAD editing (co-CAD) systems, and it can be used in many collaborative CAD/CAM industries.
Abstract: This paper presents a case study for verifying a carry look-ahead adder using the axiom system of Propositional projection temporal logic (PPTL). To this end, the syntax, semantics and axiom system of PPTL are briefly introduced. Further, functions and architectures of the carry look-ahead adder are presented. In addition, four lemmas are proved with the axiom system of PPTL. Finally, the correctness of the adder is verified based on the lemmas and the axiom system of PPTL. The case study shows that the axiom system for PPTL is workable.
Abstract: In this paper, an optimized mechanism for Semiconductor wafer fabrication (SWF) by integrating the Adaptive neuro-fuzzy inference system (ANFIS) with Simulated annealing (SA) algorithm is proposed. In this approach, aiming to solve the rush order problem which significantly affect the cycle time and impact the Work in process (WIP) of lots due to the high priority, we build an ANFIS based prediction model which will be embedded into releasing to forecast product codes and quantities of the contingent rush orders. Then a scheduler based on SA algorithm is constructed, the coding of which represents a combination of scheduling policies, including lot releasing policies, dispatching rules, batching rules and settingup rules. When the SA finished its optimization process, an optimal scheduling policy is produced. By using the proposed approach??we will find that the system can be optimized to a large extent and give a better performance.
Abstract: Aiming at the problem of blind identification of underdetermined mixtures, we propose a method of blind identification based on second-order cyclostationary statistics. Estimate non zero cycle frequencies of original signals by cycle auto-correlation function of mixtures first and then stack the cycle correlation matrices corresponding to different cycle frequencies and time lags in a three order tensor, final achieve the estimation of mixing matrix by canonical decomposition. Simulation results indicate that the proposed algorithm estimates the mixing matrix with higher accuracy compared to the conventional algorithms.
Abstract: The performance of gate oxide is a critical factor which influences yield and reliability. Gate oxide short (GOS) has become a dominant failure of CMOS integrated circuits. Thus defect density of GOS is a key parameter for yield prediction of nanometer process. In this paper, a new approach for the defect density extraction of GOS incorporating defect clustering, as well as pseudo transistor arrays as test vehicles to collect mass of testing data are proposed. Experimental results show that it is in a good agreement with inline e-test data when the extracted defect density of GOS is used to predict yield.
Abstract: This paper presents an ensemble kernelbased active learning method for PPI (Protein-protein interaction) extraction. This ensemble kernel is composed of feature-based kernel and structure-based kernel. Experimental results show that the F-scores of PPI extraction using ensemble kernel model on AIMED (Abstracts in medline), IEPA (the Interaction extraction performance assessment corpus) and BCPPI (Biocreative PPI dataset) corpora are 64.50%, 69.74% and 60.38% respectively. As the passive learning methods need large labeled data sets and it is expensive to label data manually, we integrate active learning strategy into the ensemble kernel model. The uncertainty-based sampling strategy is used in the active learning method. Two experiments for active learning are conducted on AIMED, IEPA, BCPPI corpus. The experimental results integrating the active learning strategy show that the F-scores on AIMED, IEPA and BCPPI corpora are better than those using the passive learning, and meantime reduce the labeling data.
Abstract: Narrow-Band power detector was applied to indicate the lock status in tracking loops of GPS receiver. Previous researches did not discover the statistical characteristics and mean time to lose lock of detector, thus the threshold selection did not have theoretical support. In this paper, the probability distribution of detector is derived theoretically by stochastic method, and the relationship between the lock probability and carrier to noise (C/N0) of the signal is discovered. Furthermore, the paper analyzes the Mean time to lose lock (MTLL) related to threshold setting and C/N0 of signal, providing a theoretical basis for threshold setting method of GPS tracking loops. At last, the simulations and real data test have been made to prove the results.
Abstract: A self-adaptive Cauchy evolutionary programming (ACEP) is proposed to solve vessel loading problem. The self-adaptive parameter r of Cauchy mutation is used to change the search step in time and the character of local period parameters k. The analysis on the search step, Markov chain, the operations of selection and competition and the empirical experiments of ACEP in solving the vessel loading problem are carried out. The results show that ACEP can outperform the fast evolutionary programming.
Abstract: UOF is the office document standard of China, and ISO29500 is the office document standard of Microsoft. These two standards occupy a very important position in the domestic office document. In order to achieve translation between these two standards, project team has conducted four periods of development and manual test work which is not only inefficient, but also brings difficulty because current office software cannot support the UOF standard well. So it is necessary to research automatic test tool to improve test efficiency and accuracy. Analyze the underlying XML code of the two standard documents, extract the test function attributes, conduct the information pre-treatment, and verify whether the translation is correct or not. Result shows that automatic test of translator can break away the constraints of office software, achieve automatic execution of test cases, reduce manual errors and improve test efficiency.
Abstract: In a Idendity-based proxy re-encryption (IBPRE) scheme, a proxy, converts a ciphertext for one identity into a ciphertext for another identity without knowing the underlying plaintext. IBPRE can be used for applications requiring delegation, such as delegated email processing. However, some scenarios require handle a fine-grained delegation. For example, the delegator wants to limit the proxy to only re-encrypt the encrypted emails associated with specific conditions. To overcome the limitation of existing IBPRE, we introduce the notion of Identity-based conditional proxy re-encryption (IBCPRE), whereby only ciphertext satisfying one condition set by delegator can be transformed by the proxy and then can be decrypted by delegatee. We further proposed a concrete IBCPRE scheme, and prove its security in the standard model.
Abstract: In this paper, a novel hybrid fuzzification method combining conventionally used triangle Membership functions (MFs) with two new membership functions - a peaky-triangle MF and a round-triangle MF - is proposed to improve the control effect of trajectory tracking control problems. Then its analog integrated circuit is designed and fabricated using a 0.6μm CMOS technology for hardware implementation. The experimental results show that this circuit provides an accurate output compared to the theoretical one with a fuzzification speed of 6.67MHz, which is fast enough for real-time applications. This special hybrid fuzzification can help improving the performance of fuzzy logic controller without increasing complexity.
Abstract: Subspace face recognition methods have attracted considerable interests in recent years. However, the accuracy rates of previous methods are not high. The reason is that the manifold of face image data is not utilized sufficiently and some patitcular characters of the individual image are neglected in these methods. Thus a new method to form graph of data is proposed in this paper and is used to develop two face recognition algorithms. The maximum minimum value of manifold can be preserved based on the new graph. At the same time the pixels correlation in individual image is considered sufficient under the constrain of spatial smoothness in the two developed algorithms. Therefore, the right recognition rates are enhanced by the two proposed algorithms. This is further confirmed by experiments.
Abstract: Lip segmentation, a sub-step of facial analysis, becomes more and more important in the fields of pattern recognition and human-computer interaction. In this paper, a novel algorithm for lip contour extraction that combines the merits of the pixel-based model and the parametric model is presented. Lip corner detection is the first step of this algorithm, utilizing a three-curve lip model to describe lip contour. The improved “Jumping Snake” algorithm is used to extract feature points for lip model implementation, which makes the novel algorithm more accurate and flexible. It is also made more robust with the introduction of geometric constraints. Experiments show that this approach with geometric constraints provides satisfactory results. It can also serve as an initial attempt for further applications.
Abstract: Information Card (InfoCard) is a usercentric identity management metasystem. It has been accepted as a standard of OASIS Identity Metasystem Interoperability Technical Committee. However, there is currently a lack of security analysis to InfoCard protocol, especially, with formal methods. In this paper, we accommodate such a requirement by analyzing security properties of InfoCard protocol adopting a formal protocol analysis tool. Our analysis result discovers that current InfoCard protocol is vulnerable against the session replay attack. Furthermore, we reveal the importance of two optional elements in InfoCard metasystem, token scope and proof key, and found that InfoCard protocol will be susceptible to manin- the-middle attack and token replay attack if these two optional elements lack.
Abstract: Multi-recipient public-key encryption can be used to solve the security issue of One-To-Many communications such as secure broadcast. In a multi-recipient public-key encryption scheme, a ciphertext generated by the sender with its private key can be decrypted correctly by each recipient with its own private key. To solve the key negotiation problem between the sender and each recipient, the ID-based multi-recipient encryption has been proposed recently. Baek et al. proposed a general method to design an ID-based multi-recipient public-key encryption scheme with the IND-CCA2 security by using REACT, and at the same time, they proposed an excellent scheme. However, analyses show that there are still some flaws in their scheme, such as exposing recipient identity and unfair encryption. Motivated by these concerns, we propose a new ID-based multi-recipient public-key encryption scheme based on the same design method. Analyses show that our proposal can overcome all the flaws in Baek et al.’s scheme and is more practical in applications.
Abstract: Recent study shows that discriminative learning methods could provide a significant improvement of word alignment quality. One of the difficulties of these methods is how to perform efficient search of word alignment. Although Inversion transduction grammar (ITG) provides a polynomial time algorithm using synchronous parsing techniques, a very harsh pruning is still needed to make the algorithm computationally feasible. We notice that previous pruning techniques mostly focus on pruning the bi-lingual spans??after what low quality alignments still exist. To address this problem, we propose an approach that prunes low quality hypotheses on-the-fly during parsing. Compared with previous pruning methods which only use high precision alignment links as constraints, our method could make use of “high recall” alignment links as well. To demonstrate our approach, we also propose a constrained learning framework, which generates high precision and high recall constraints from some existing alignment results. Experiment shows significant improvements of both alignment and translation quality over standard IBM Model 4 alignments on the Chinese-English test data.
Abstract: Emotion recognition at sentence level is one of the fundamental problems of textual emotion understanding. Based on the observation that sentence emotional focus can be expressed by some clauses in this sentence, this paper proposes to find the emotional focus for sentence emotion recognition. For the sake of breaking through the problems brought about by depending on emotion lexicons, we first recognize word emotions in a sentence based on Maximum entropy model. And then homogeneous Markov model is built for clause emotion recognition; After that, a strategy based on emotion selection is proposed for a sentence with multiple clauses, and genetic algorithm is used for clause selection by textual feature weighting. The experimental results show that, comparing with the baseline, there are 9.1% and 3.6% improvement respectively for two different evaluations. It is demonstrated that finding emotional focus by clause selection is able to improve the performance of sentence emotion recognition significantly.
Abstract: In order to enhance global convergence capability of particle swarm optimization, this paper proposes a novel hybrid algorithm, called SMMBBPSO, based on the Nelder-Mead Simplex method (SM) and a Modified bare-bones particle swarm optimization (MBBPSO). In this algorithm, a new strategy based on K-means clustering is proposed to combine the powerful global search capability of MBBPSO and the high accurate local search capability of SM. This makes the proposed algorithm achieve a nice balance between exploitation and exploration capability. Meanwhile, an adaptive reinitialization strategy on inactive particles is proposed to help the swarm get away from local optimal positions. Finally, simulation results on benchmark functions demonstrate the effectiveness of the proposed algorithm.
Abstract: Variational methods for image decomposition have gained considerable attention in recent years. In such approaches, an image usually can be decomposed into a geometrical (or structure) component and a textured (or noise) feature. In this paper we propose an edge-preserving variational model which can split an image into four components: a first one containing the structure of the image, a second one the texture of the image, a third one the noise and a forth one the edge. Our decomposition model relies on the use of three different terms: the edgepreserving regularization for the geometrical component and the edge, a negative Sobolev norm for the texture, and a negative Besov norm for the noise. We explicitly give numerical scheme that is the synthesis of a projection algorithm, a redundant wavelet (or curvelet) soft threshold and two coupled Partial differential equations (PDE’s). Finally we show image decomposition results on synthetic and real image.
Abstract: The observer-based H∞ control problem is investigated for a class of complex nonlinear systems with unavailable states and time delays, and under uncertainties. Takagi-Sugeno (T-S) models are used to approximate the nonlinear systems, and a fuzzy observer is designed to estimate the system states, with which a fuzzy controller is designed to guarantee the stability of the fuzzy system. A compensator based on fuzzy logic systems is introduced to eliminate the approximating error and the uncertainties. Thus, the output-feedback controller is designed to ensure that the closed-loop system is Uniformly ultimately bounded (UUB) and satisfies the desired H∞ performance. In this method, it is not necessary for the approximating error and uncertainties to satisfy the constraint conditions. A simulation example demonstrates the effectiveness of the proposed control scheme.
Abstract: Predicting function of unknown proteins in PPI (Protein-protein interaction) network is an important task of bioinformatics. The traditional clustering and functional flow algorithms performed not well in clustering PPI networks. Therefore this paper introduced the concepts of pheromone and state transition probability in the Ant colony optimization (ACO) algorithm to optimize the process of forming functional modules. The pheromone on the paths which the ants have passed by was updated via the accumulative strategy instead of constants in order to generate clusters as completely as possible. The experiments on MIPS dataset turned out that our approach was superior to the flow methods in terms of precision, recall and f-measure value, meantime reduced the time consumed.
Abstract: Laptops are easy to lose to leak sensitive data, storing data in encrypted file systems does not sufficiently solve this problem. To decrypt a file, such systems often need to require a user to manually provide keys each time, which is annoying and directly discourages users to protect sensitive data effectively. The paper first presents a Portable key (PK) scheme, which employs a mobile phone to manage keys/passwords of a laptop. The laptop automatically requests key material from the mobile phone through Bluetooth link if needed, which sets users free from manually providing keys/passwords frequently. A remote control protocol is also provided to guarantee the security in case the mobile phone is lost. Finally, the paper extends the BAN logic and gives the formal security analysis and implementation, formal analysis shows that the scheme is secure to some typical attacks; implementation shows that the scheme brings little additional load to both sides and the protocol is efficient and practical.
Abstract: Chaotic special properties make the chaotic encryption technology be an important research field of information science and technology. However, as digital chaos is affected by the limited precision of computer, chaotic system properties present degradation—short periodicity of output sequence. This paper proposes a double K-L (Karhunen-Loeve) transform method for Logistic 0/1 sequence, and then analyzes autocorrelation, period, complexity and frequency spectrum. Simulation results show that this method can effectively improve the complexity and the length selection of key sequence. Moreover, it can also increase the period of Logistic sequence in wider range, which makes up the short periodicity phenomenon of digital chaotic sequence and makes digital chaotic key sequence be applied safely in encryption system.
Abstract: Coverage enhancement is one of the hot research topics in wireless multimedia sensor networks. A novel Coverage-enhancing algorithm based on three-dimensional Directional perception and co-evolution (DPCCA) is proposed in multimedia sensor networks on the basis of the model whose pitch angle and deviation angle can be adjusted. Based on the proposed elliptical cone sensing model, we can derive the coverage area of the node and calculate the optimal pitch angle according the information of monitoring area and the nodes, and then the deviation angle is optimized based on co-evolution algorithm, which eliminate the overlapped and blind sensing area effectively. A set of simulations demonstrate the effectiveness of our algorithm in coverage ratio.
Abstract: This paper presents a Polarity comparing and uniqueness guarantee (PCUG) timing synchronization estimation approach for MB-OFDM based UWB systems. Difference of the two cross correlation functions is computed, between a received symbol, the successive received symbol and predefined preamble sequence. It makes sense to propose polarity comparison and identification ideas to the scenario, for the result of cross correlation difference exceeding threshold is not always unique. If the polarity of the first exceeding threshold sample is different with that of predefined sequence, the current received sample is estimated to be the right timing point; otherwise the algorithm is put forward to find out a peak of correlation summation to figure out timing point. The proposed algorithm could make the uniqueness of timing index for sure. MSEs of PCUG are evidently lower than the reference algorithm. The total and exact synchronization probability could get as much as 98.98% and 95.92%.
Abstract: With the development of E-commerce and mobile communication technology, Mobile E-commerce (M-commerce) has become one of the important means of trade. Identity authentication is the basic security issue in M-commerce. In this paper, an efficient Elliptic curve based One-time password (OTP) identity authentication scheme (MOTP) for M-commerce is proposed, also, International mobile equipment identity (IMEI) of mobile devices is introduced as an important authentication factors. At the end, this paper analyzes the novel scheme by BAN logic and does simulation in OPNET.
Abstract: Multiple virtual networks (VNs) sharing an underlying substrate network is considered a promising tool to diversify and reshape the future inter-networking paradigm. In this paper, based on the robust optimization theory, a robust dynamic approach is presented, which periodically identifies bandwidth allocation to VNs to work reasonable well for a range of traffic patterns over a period of time, rather than certain traffic pattern instance. This problem is formulated as a robust optimization problem using path-flow model aiming to compute the minimumcost bandwidth allocation, and a distributed algorithm is proposed by using the primal decomposition method. The numerical result obtained from simulation experiments demonstrates the strength and the effectiveness of the proposed algorithm.
Abstract: Prior secure routing protocols in ad hoc networks are vulnerable under many kinds of attacks, such as wormhole attack, vertex cut attack, etc. Direct anonymous ad hoc on demand vector (DAAODV) protocol uses Direct anonymous attestation (DAA) protocol and Property based attestation (PBA) protocol to solve this problem, but its efficiency is relatively low. We propose a routing protocol called FuzzyAODV, which uses Trusted Computing technology to ensure routing security, while simplifies the secure link establishment. We also take malicious nodes into consideration, and propose a method to identify possible DoS attacks, thus adopt different strategies accordingly to keep high performance. We evaluate the performance of our protocol using NS2 network simulator, and the result shows that our protocol is more efficient than DAAODV protocol. Security analysis demonstrates the correctness of our solution.
Abstract: Exploiting Internet path diversity to enhance communication reliability and performance is an important research field. Although the Internet has enormous physical diversity in the underlaying infrastructure, inter-domain routing protocol and routing policies highly limit this path diversity in the Internet. In order to investigate the effects of routing policies on inter-domain paths, we develop a measurement study framework to characterize and classify inter-domain paths. In this framework, we define the concepts of the transit strategy and the valley and valley-free paths, and give a formal model of strategylabeled inter-domain paths. Then we develop three associated algorithms: Topology extraction (TE), Multi-path computation algorithm (MCA) and Classification of path pattern (CPP), which are used to compute and classify inter-domain paths. Experimental results show two useful and important observations that valley paths have averagely more than 73% in all inter-domain paths, and Class 1 paths account for 64.6% of all valley paths. The observations may guide the design of inter-domain routing protocol, especially the design of multi-path routing, to achieve higher performance and reliability.
Abstract: Efficient and reliable resource allocation algorithm is one of the key problems for the realization of cognitive radio networks. Due to the rapidly changing characteristics of cognitive environment, water-filling algorithm is difficult to meet this environment because of the interaction with primary users. In this paper, we propose a primary user Quality of service (QoS) and activity concerned resource allocation algorithm in OFDM based cognitive radio system with a risk-return model which reflects availability of subcarriers or primary user activity and date transmission outage probability constraint to guarantee primary users’ QoS. Taking maximization of the expected sum rate of cognitive system as the objective function, we solve this optimization problem by a Lagrangian dual method under the introduced primary user outage probability constraint. Finally, the performance comparison of water-filling algorithm and our algorithm is given. The simulation results show that the proposed algorithm can obtain more transmission capacity and effectively guarantee primary users’ QoS.
Abstract: This paper proposes a novel routing algorithm for opportunistic networks: Context-based adaptive routing (CBAR) that uses network context information and Dempster-Shafer (D-S) evidence theory to calculate a node’s basic reliability assignment function, which describes the reliability of the node’s credibility, incredibility and unknown credibility. As message distributes, the context will determine whether the node is credible or not, then CBAR selects the node with higher value of reliability regarding to its credibility to forward the message, otherwise, floods the message so that better robustness and delivery probability can be achieved. We used Opportunistic network environment simulator (ONE) to simulate and compare the performance of CBAR algorithm with existing routing algorithms which shows that CBAR has better performance in terms of delivery ratio, average latency, and overhead ratio.
Abstract: To maximize the utility of cognitive networks, the interference constraints to ensure primary users’ Quality of service (QoS) standards is considered in this paper. The interference temperature model was used to model network interference effects, so that the interference caused by cognitive user’s signal transmission cannot surpass the primary user’s interference temperature limitation. Multi-users’ power allocation was studied based on the analysis of multiple interference temperature limitation of the power model and multi-user access power control. The power allocation issue is converted into a multiconstrained nonlinear programming problem with the interference temperature limitation and then an improved simulated annealing genetic algorithm is proposed to solve this problem. Simulation results show that the improved simulated annealing genetic algorithm has better accuracy and convergence performance.
Abstract: In this paper, we define a new security property called “instance-non-malleability” for the Instance-dependent commitment (IDC). Our definition can be consistent with the definition of non-malleability for zero-knowledge proofs, which was not the case for previous definitions of non-malleability for commitments. Our definition of instance-non-malleable instance-dependent commitment requires the non-malleability of the instances as well as the committed messages. We also present a DDHbased IDC scheme, which satisfies previous definitions of non-malleability but not our definition of instance-nonmalleable IDC, to show that instance-non-malleability is a stronger notion. Finally, we modify our DDH-based construction to satisfy our definition of instance-non-malleable IDC. The security of our construction is proved in the random oracle model.
Abstract: In order to improve the dynamic performance of the Global navigation satellite system (GNSS) receiver, we propose a novel Doppler-parameter detection algorithm using short-term cyclic iteration. The algorithm is capable of calculating the initial Doppler shift, the shift velocity and acceleration from only four consecutive phase errors. Then we present a new carrier tracking loop based on the algorithm, and discuss the issues involving the noise suppression and the feedback control. Simulation results demonstrate that the proposed loop can effectively detect the high-order Doppler shift transition and stably track the signals in the dynamic environment.
Abstract: Bandpass filter with equal-ripple response in the passband and four transmission zeros in the stopband is synthesized in this letter. Equivalent circuit model is proposed. Based on even- and odd-mode theory, design formulas are derived to provide relationship between filtering characteristics (center frequency, bandwidth, and transmission zeros) and circuit parameters for the filter. To verify the design concept, a bandpass filter with a fractional bandwidth of 26.7% (ripple level 0.01dB) at the center frequency of 3.9 GHz is designed and fabricated. The measured insertion loss is less than 0.6 dB, and return loss is higher than 19.4 dB in the passband. The stopband extends to 10.4 GHz with the rejection level of 20 dB. Measured results show good agreement with simulations.
Abstract: Both scattering center and polarimetric information are of great significance for radar target recognition and classification. Firstly, a Coherent polarization attributed (CPA) scattering center model is established to provide a relatively complete description of the target physical structure. Then, an effective parameter estimation method is proposed, where the full-polarization echoes are used for imaging to enhance the target’s features, thereafter, the parameters of the CPA model are estimated via image segmentation and an Approximatemaximum likelihood (AML) method. Particularly, the Cramer-Rao bounds (CRBs) for parameter estimation of the CPA model are derived. Experiments with the measured data in anechoic chamber validate the performance of the proposed method.
Abstract: Path planning on the surfaces of a cuboidshaped object is a scientific value and practical significance of the research topic, because of its potential applications with many fields. On basis of analysis for calculation of the minimum distance of any two points on a cuboid, by incorporating Expanding neighborhood search (ENS) procedure into the algorithm, a new discrete jumping particle swarm algorithm, ENS-JPSO, is presented for solving the traveling salesman problems on the surfaces of a cuboid, in which the path-relinking strategy is used to update velocities and positions of particles in the swarm, in order to improve the exploitation capability of the algorithm. After visual implementation of the experimental system in Java with 3D APIs, The effectiveness of the proposed method are tested on several TSPLIB instances with satisfactory results. And further comparison with other methods for various sets of random points has demonstrated that the proposed algorithm is able to obtain the best route for large-scale instances of TSPs on a cuboid.
Abstract: We put forward a multi points updated and distance filtered Kriging surrogate model. When building Kriging models, two update approaches are used to select infilling points: optimal points and maximized expected improvement. We use Improved general pattern search (IGPS) algorithm to get these points. In IGPS, search step is substituted by GA and SQP and poll step is retained. To decrease simulation times, we adopt a distance filter to eliminate potentially replicated samples. A satellite orbit parameter optimization problem is formulated, which is solved by the proposed method and STK/Analyzer respectively. The results showed that Kriging models, which use multi update points and distance filter, yield global approximations that are more accurate than Analyzer.
Abstract: In order to reduce power consumption and additional chip area, an improved Current mode logic (CML) latch, which can work at a lower power supply without the level shifter, is presented. To compensate the speed loss caused by large voltage swing, a cross coupled pair is added to the load of the latch. A simplified model which divides operating situation into different phases is built to illustrate the operating principle of the structure and optimize the speed of the circuit. Further analysis also indicates that the latch can work at a much lower voltage supply. The proposed divider has been used in a frequency synthesizer. Measurements were made to support above features. It has been proved that the structure in this work has more advantages than the conventional ones.