秦牧致《晚会》的一封信

我在《美国人与易经》一文中,提到莱布尼兹受《易经》影响而发明“二进法”,并非我对这一点深信不疑或者我对这方面有什么深入的研究。只是西方学者既有人持此一说,“存录”一番而已。成基同志此文有助于开拓人们思路,是很有意思的。附带说一句,《三国演义》和《孙子兵法》在欧亚好些国家都有人在阅读和研究,这和揣摩“谋略”也是有密切关系的。谨复。

An all-optical scheme of signed digit binary addition based on optical non-linear material

We propose a new integrated method which covers addition of any two signed digit numbers in all-optical domain. To implement this scheme we have exploited some photo-refractive characters of optical non-linear materials,which may experience 0.1-0.2dB attenuation loss as silica is used as non-linear medium. Moreover,the attenuation loss may be reduced to 0.001 dB/m if we consider the use of slow light at 1.56μm.

Buffer Overflow Detection on Binary Code

Most solutions for detecting buffer overflow are based on source code. But the requirement tor source code is not always practical especially for business software. A new approach was presented to detect statically the potential buffer overflow vulnerabilities in the binary code of software. The binary code was translated into assembly code without the lose of the information of string operation functions. The feature code abstract graph was constructed to generate more accurate constraint statements, and analyze the assembly code using the method of integer range constraint. After getting the elementary report on suspicious code where buffer overflows possibly happen, the control flow sensitive analysis using program dependence graph was done to decrease the rate of false positive. A prototype was implemented which demonstrates the feasibility and efficiency of the new approach.

Fake Reviews Tell No Tales？ Dissecting Click Farming in Content-Generated Social Networks

Recently, there has been a radial shift from traditional online social networks to content-generated social networks(CGSNs). Contemporary CGSNs, such as Dianping and Trip Advisor, are often the targets of click farming in which fake reviews are posted in order to boost or diminish the ratings of listed products and services simply through clicking. Click farming often emanates from a collection of multiple fake or compromised accounts, which we call click farmers. In this paper, we conduct a three-phase methodology to detect click farming. We begin by clustering communities based on newly-defined collusion networks. We then apply the Louvain community detection method to detecting communities. We finally perform a binary classification on detected-communities. Our results of over a year-long study show that(1) the prevalence of click farming is different across CGSNs;(2) most click farmers are lowly-rated;(3) click-farming communities have relatively tight relations between users;(4) more highly-ranked stores have a greater portion of fake reviews.

Cultural Binary Particle Swarm Optimization Algorithm and Its Application in Fault Diagnosis

Binary particle swarm optimization algorithm(BPSOA) has the excellent characters such as easy to implement and few set parameters.But it is tendentious to stick in the local optimal solutions and has slow convergence rate when the problem is complex.Cultural algorithm(CA) can exploit knowledge extracted during the search to improve the performance of an evolutionary algorithm and show higher intelligence in treating complicated problems.So it is proposed that integrating binary particle swarm algorithm into cultural algorithm frame to develop a more efficient cultural binary particle swarm algorithm (CBPSOA) for fault feature selection.In CBPSOA,BPSOA is used as the population space of CA;the evolution of belief space adopts crossover,mutation and selection operations;the designs of acceptance function and influence function are improved according to the evolution character of BPSOA.The tests of optimizing functions show the proposed algorithm is valid and effective.Finally,CBPSOA is applied for fault feature selection.The simulations on Tennessee Eastman process (TEP) show the CBPSOA can perform better and more quickly converge than initial BPSOA.And with fault feature selection,more satisfied performance of fault diagnosis is obtained.

Steganography Algorithm to Hide Secret Message inside an Image

In this paper, the authors propose a new algorithm to hide data inside image using steganography technique. The proposed algorithm uses binary codes and pixels inside an image. The zipped file is used before it is converted to binary codes to maximize the storage of data inside the image. By applying the proposed algorithm, a system called Steganography Imaging System （gig） is developed. The system is then tested to see the viability of the proposed algorithm. Various sizes of data are stored inside the images and the Peak signal-to-noise ratio （PSNR） is also captured for each of the images tested. Based on the PSNR value of each images, the stego image has a higher PSNR value. Hence this new steganography algorithm is very efficient to hide the data inside the image.

Binary Bell Polynomials,Bilinear Approach to Exact Periodic Wave Solutions of(2+l)-Dimensional Nonlinear Evolution Equations

In the present letter, we get the appropriate bilinear forms of （2 ＋ 1）-dimensional KdV equation, extended （2 ＋ 1）-dimensional shallow water wave equation and （2 ＋ 1）-dimensional Sawada -Kotera equation in a quick and natural manner, namely by appling the binary Bell polynomials. Then the Hirota direct method and Riemann theta function are combined to construct the periodic wave solutions of the three types nonlinear evolution equations. And the corresponding figures of the periodic wave solutions are given. Furthermore, the asymptotic properties of the periodic wave solutions indicate that the soliton solutions can be derived from the periodic wave solutions.

Carbon-supported ultrafine Pt nanoparticles modified with trace amounts of cobalt as enhanced oxygen reduction reaction catalysts for proton exchange membrane fuel cells

To accelerate the kinetics of the oxygen reduction reaction(ORR)in proton exchange membrane fuel cells,ultrafine Pt nanoparticles modified with trace amounts of cobalt were fabricated and decorated on carbon black through a strategy involving modified glycol reduction and chemical etching.The obtained Pt36Co/C catalyst exhibits a much larger electrochemical surface area(ECSA)and an improved ORR electrocatalytic activity compared to commercial Pt/C.Moreover,an electrode prepared with Pt36Co/C was further evaluated under H2-air single cell test conditions,and exhibited a maximum specific power density of 10.27 W mgPt^-1,which is 1.61 times higher than that of a conventional Pt/C electrode and also competitive with most state-of-the-art Pt-based architectures.In addition,the changes in ECSA,power density,and reacting resistance during the accelerated degradation process further demonstrate the enhanced durability of the Pt36Co/C electrode.The superior performance observed in this work can be attributed to the synergy between the ultrasmall size and homogeneous distribution of catalyst nanoparticles,bimetallic ligand and electronic effects,and the dissolution of unstable Co with the rearrangement of surface structure brought about by acid etching.Furthermore,the accessible raw materials and simplified operating procedures involved in the fabrication process would result in great cost-effectiveness for practical applications of PEMFCs.

SECURE STEGANOGRAPHY BASED ON BINARY PARTICLE SWARM OPTIMIZATION

The objective of steganography is to hide message securely in cover objects for secret communication.How to design a secure steganographic algorithm is still major challenge in this re-search field.In this letter,developing secure steganography is formulated as solving a constrained IP(Integer Programming) problem,which takes the relative entropy of cover and stego distributions as the objective function.Furthermore,a novel method is introduced based on BPSO(Binary Particle Swarm Optimization) for achieving the optimal solution of this programming problem.Experimental results show that the proposed method can achieve excellent performance on preserving neighboring co-occurrence features for JPEG steganography.

A Ternary 4-Point Approximating Subdivision Scheme

In this paper, the author presents a class of stationary ternary 4-point approximating symmetrical subdivision algorithm that reproduces cubic polynomials. By these subdivision algorithms at each refinement step, new insertion control points on a finer grid are computed by weighted sums of already existing control points. In the limit of the recursive process, data is defined on a dense set of point, The objective is to find an improved subdivision approximating algorithm which has a smaller support and a higher approximating order. The author chooses a ternary scheme because the best way to get a smaller support is to pass from the binary to ternary or complex algorithm and uses polynomial reproducing propriety to get higher approximation order. Using the cardinal Lagrange polynomials the author has proposed a 4-point approximating ternary subdivision algorithm and found that a higher regularity of limit function does not guarantee a higher approximating order. The proposed 4-point ternary approximation subdivision family algorithms with the mask a have the limit function in C2 and have approximation order 4. Also the author has demonstrated that in this class there is no algorithm whose limit function is in C3. It can be seen that this stationary ternary 4-point approximating symmetrical subdivision algorithm has a lower computational cost than the 6-point binary approximation subdivision algorithm for a greater range of points.

Frequent item sets mining from high-dimensional dataset based on a novel binary particle swarm optimization

A novel binary particle swarm optimization for frequent item sets mining from high-dimensional dataset(BPSO-HD) was proposed, where two improvements were joined. Firstly, the dimensionality reduction of initial particles was designed to ensure the reasonable initial fitness, and then, the dynamically dimensionality cutting of dataset was built to decrease the search space. Based on four high-dimensional datasets, BPSO-HD was compared with Apriori to test its reliability, and was compared with the ordinary BPSO and quantum swarm evolutionary(QSE) to prove its advantages. The experiments show that the results given by BPSO-HD is reliable and better than the results generated by BPSO and QSE.

Evolutionary Computation for Realizing Distillation Separation Sequence Optimization Synthesis

Evolutionary algorithm is applied for distillation separation sequence optimization synthesis problems with combination explosion. The binary tree data structure is used to describe the distillation separation sequence, and it is directly applied as the coding method. Genetic operators, which ensure to prohibit illegal filial generations completely, are designed by using the method of graph theory. The crossover operator based on a single parent or two parents is designed successfully. The example shows that the average ratio of search space from evolutionary algorithm with two-parent genetic operation is lower, whereas the rate of successful minimizations from evolutionary algorithm with single parent genetic operation is higher.

Binary Bell Polynomials Approach to Generalized Nizhnik-Novikov-Veselov Equation

The elementary and systematic binary Bell polynomials method is applied to the generalized NizhnikNovikov-Veselov (GNNV) equation.The bilinear representation,bilinear B&cklund transformation,Lax pair and infiniteconservation laws of the GNNV equation are obtained directly,without too much trick like Hirota’s bilinear method.

Despreader for Direct Sequence Spread Spectrum System and Its Performance Analysis

A new type of despreader for direct sequence spread spectrum signal is proposed. Compared with traditional despreaders, the new despreader does not contain hard decision ware or handle binary sequence any more, and the locally stored spread spectrum signals are pre-modulated baseband signals (such as Gaussian minimum shift keying (GMSK) signals), which are much more similar to the received spread spectrum signals. Moreover, the missed detection probability of the despreader is about one order of magnitude lower than that of traditional ones. Based on the maximum likelihood criterion and phase probability density function of demodulated signal, a new method of ana- lyzing the despreaders’ performance is put forward, which is proved to be more accurate than traditional methods according to the numerical results. Finally, an adaptive despreader under different signal-to-noise ratios is given.

Network coding resources optimization with transmission delay constraint in multicast networks

Minimizing network coding resources of multicast networks,such as the number of coding nodes or links,has been proved to be NP-hard,and taking propagation delay into account makes the problem more complicated. To resolve this optimal problem,an integer encoding routing-based genetic algorithm( REGA) is presented to map the optimization problem into a genetic algorithm( GA)framework. Moreover,to speed up the search process of the algorithm,an efficient local search procedure which can reduce the searching space size is designed for searching the feasible solution.Compared with the binary link state encoding representation genetic algorithm( BLSGA),the chromosome length of REGA is shorter and just depends on the number of sinks. Simulation results show the advantages of the algorithm in terms of getting the optimal solution and algorithmic convergence speed.

Parameter identification and pressure control of dynamic system in shield tunneling using least squares method

An estimation approach using least squares method was presented for identificationof model parameters of pressure control in shield tunneling.The state equation ofthe pressure control system for shield tunneling was analytically derived based on themass equilibrium principle that the entry mass of the pressure chamber from cutting headwas equal to excluding mass from the screw conveyor.The randomly observed noise wasnumerically simulated and mixed to simulated observation values of system responses.The numerical simulation shows that the state equation of the pressure control system forshield tunneling is reasonable and the proposed estimation approach is effective even ifthe random observation noise exists.The robustness of the controlling procedure is validatedby numerical simulation results.

Research on Anti-collision Algorithm of Short Distance Data communication based on Binary-Tree Disassembly

This paper puts forward adaptive anti collision algorithm based on two fork tree decomposition. New search algorithm built on the basis of binary-tree algorithm, using the uniqueness of the label EPC, to estimate the distribution of label by slot allocation, the huge and complicated two fork tree is decomposed into several simple binary-tree by search the collision slots for binary-tree, so, it can simplifies the search process. The algorithm fully considers4 important performance parameters of the reader paging times, transmission delay, energy consumption and throughput label, the simulation results show that, the improved anti-collision algorithm is obviously improved performance than other two fork tree algorithm, it is more suitable for RFID anti-collision protocols.

Recursive and Nonrecursive Traversal Algorithms for Dynamically Created Binary Trees

The modeling of dynamical systems from a time series implemented by our DSA program introduces binary trees of height D with all leaves on the same level, and the related subtrees of height L 〈 D. These are called e-trees and e-subtrees. The recursive and nonrecursive versions of the traversal algorithms for the trees with dynamically created nodes are discussed. The original nonrecursive algorithms that return the pointer to the next node in preorder, inorder and postorder traversals are presented. The space-time complexity analysis shows and the execution time measurements confirm that for these O（2D） algorithms, the recursive versions have approximately 10-25% better time constants. Still, the use of nonrecursive algorithms may be more appropriate in several occasions.

Hybrid weighted symbol-flipping decoding for nonbinary LDPC codes

A hybrid decoding algorithm is proposed for nonbinary low-density parity-check （LDPC） codes, which combines the weighted symbol-flipping （WSF） algorithm with the fast Fourier trans- form q-ary sum-product algorithm （FFT-QSPA）. The flipped position and value are determined by the symbol flipping metric and the received bit values in the first stage WSF algorithm. If the low- eomplexity WSF algorithm is failed, the second stage FFT-QSPA is activated as a switching strategy. Simulation results show that the proposed hybrid algorithm greatly reduces the computational complexity with the performance close to that of FFT-QSPA.

Multi-objective optimization of p-xylene oxidation process using an improved self-adaptive differential evolution algorithm

The rise in the use of global polyester fiber contributed to strong demand of the Terephthalic acid （TPA）. The liquid-phase catalytic oxidation of p-xylene （PX） to TPA is regarded as a critical and efficient chemical process in industry [ 1 ]. PX oxidation reaction involves many complex side reactions, among which acetic acid combustion and PX combustion are the most important. As the target product of this oxidation process, the quality and yield of TPA are of great concern. However, the improvement of the qualified product yield can bring about the high energy consumption, which means that the economic objectives of this process cannot be achieved simulta- neously because the two objectives are in conflict with each other. In this paper, an improved self-adaptive multi-objective differential evolution algorithm was proposed to handle the multi-objective optimization prob- lems. The immune concept is introduced to the self-adaptive multi-objective differential evolution algorithm （SADE） to strengthen the local search ability and optimization accuracy. The proposed algorithm is successfully tested on several benchmark test problems, and the performance measures such as convergence and divergence metrics are calculated. Subsequently, the multi-objective optimization of an industrial PX oxidation process is carried out using the proposed immune self-adaptive multi-objective differential evolution algorithm （ISADE）. Optimization results indicate that application oflSADE can greatly improve the yield of TPA with low combustion loss without degenerating TA quality.