现代汉语结构助词“的”的分合问题研究

"的"是现代汉语结构助词中的一个典型成员。"的"的分合问题,既涉及语法研究,也关联语用实践,同时还与书面语的规范问题紧密相连。为此,文章以"的"的分合史和分合观为经纬,对"的"的分合问题进行了全面讨论和必要思考。"的"的分合史分"由分趋合"、"总体趋分"、"分合相持"三个时期。期间,存有"分用"和"合用"两种观念,有过"分用"和"合用"两次争议。同时,"合用"观的理由问题,分合史各期的划分问题,"分化说"的提法问题,实践检验的权威性问题,也都与"的"的分合问题密切相关。

Some studies on finding the nearest volume-preserving matrix

Finding the nearest volume-preserving matrix for a given matrix is studied. Amatrix equation is first obtained, which is a necessary condition for the solution to the problem.Then the equation is solved by the singular value decomposition method. Some additional results arealso provided to further characterize the solution. Using these results, a numerical algorithm isintroduced and a numerical test is given to illustrate the effectiveness of the algorithm.

Feature combination via importance-inhibition analysis

A new method for combining features via importance-inhibition analysis （IIA） is described to obtain more effective feature combination in learning question classification. Features are combined based on the inhibition among features as well as the importance of individual features. Experimental results on the Chinese questions set show that, the IIA method shows a gradual increase in average and maximum accuracies at all feature combinations, and achieves great improvement over the importance analysis（IA） method on the whole. Moreover, the IIA method achieves the same highest accuracy as the one by the exhaustive method, and further improves the performance of question classification.

Hybrid particle swarm optimization with differential evolution and chaotic local search to solve reliability-redundancy allocation problems

In order to solve reliability-redundancy allocation problems more effectively, a new hybrid algorithm named CDEPSO is proposed in this work, which combines particle swarm optimization （PSO） with differential evolution （DE） and a new chaotic local search. In the CDEPSO algorithm, DE provides its best solution to PSO if the best solution obtained by DE is better than that by PSO, while the best solution in the PSO is performed by chaotic local search. To investigate the performance of CDEPSO, four typical reliability-redundancy allocation problems were solved and the results indicate that the convergence speed and robustness of CDEPSO is better than those of PSO and CPSO （a hybrid algorithm which only combines PSO with chaotic local search）. And, compared with the other six improved meta-heuristics, CDEPSO also exhibits more robust performance. In addition, a new performance was proposed to more fairly compare CDEPSO with the same six improved recta-heuristics, and CDEPSO algorithm is the best in solving these problems.

Depth Classification of Underwater Targets Based on Complex Acoustic Intensity of Normal Modes

In order to solve the problem of depth classification of the underwater target in a very low frequency acoustic field, the active component of cross spectra of particle pressure and horizontal velocity （ACCSPPHV） is adopted to distinguish the surface vessel and the underwater target. According to the effective depth of a Pekeris waveguide, the placing depth forecasting equations of passive vertical double vector hydrophones are proposed. Numerical examples show that when the sum of depths of two hydro- phones is the effective depth, the sign distribution of ACCSPPHV has nothing to do with horizontal distance; in addition, the sum of the first critical surface and the second critical surface is equal to the effective depth. By setting the first critical surface less than the difference between the effective water depth and the actual water depth, that is, the second critical surface is greater than the actual depth, the three positive and negative regions of the whole ocean volume are equivalent to two positive and negative regions and therefore the depth classification of the underwater target is obtained. Besides, when the 20 m water depth is taken as the first critical surface in the simulation of underwater targets （40 Hz, 50 Hz, and 60 Hz respectively）, the effectiveness of the algorithm and the cor- reemess of relevant conclusions are verified, and the analysis of the corresponding forecasting performance is conducted.

Energy Efficient Resource Allocation in Timesharing Multiuser Systems with Hybrid Energy Harvesting Transmitter

An energy effi cient resource allocation scheme in timesharing multiuser system with a hybrid energy harvesting transmitter is studied in this paper. Specially, the operation energy of system is supplied by constant energy and energy harvesting, which harvests energy from external environment. Our goal is to maximize the energy effi ciency of timesharing multiuser systems by considering jointly allocation of transmission time and power control in an off-line manner. The original nonconvex objective function is transformed into convex optimization problem via the fractional programming approach. Then, we solve the convex problem by Lagrange dual decomposition method. Simulation results show that the proposed energy efficient resource allocation scheme has a better performance than the scheme which decomposes optimization problem into two parts(power allocation, time allocation) to solve iteratively.

Joint subcarrier and power allocation with threshold in cooperative multiuser networks

In this paper, we investigate a resource allocation issue in OFDMA-based decode-and-forward cooperative multiuser networks and propose joint subcarrier and power allocation schemes. The optimal solution of this combinable allocation shows high computational complexity, so we allocate subcarriers and power separately. At firstly, we distribute subcarriers to relays and users under the assumption of equal power distribution. Here, we propose an equal capacity increment （ECI） allocation strategy to achieve tradeoff between total throughput and fairness. To further improve the system performance, we introduce threshold into ECI strategy, named ECI strategy with threshold （ECI-T）, where subcarriers with bad performance are prevented from transmitting. Subsequently, a water-filling method is adopted to distribute the power to cooperative links in order to fully utilize the limited power. Simulation results show that system performance of the proposed schemes is significantly enhanced compared with an existing resource allocation scheme. Besides, the resource allocation schemes with the water- filling method notably outperform schemes with equal power allocation.

ANALYSIS OF AFFECTIVE ECG SIGNALS TOWARD EMOTION RECOGNITION

Recently,as recognizing emotion has been one of the hallmarks of affective computing,more attention has been paid to physiological signals for emotion recognition.This paper presented an approach to emotion recognition using ElectroCardioGraphy(ECG) signals from multiple subjects.To collect reliable affective ECG data,we applied an arousal method by movie clips to make subjects experience specific emotions without external interference.Through precise location of P-QRS-T wave by continuous wavelet transform,an amount of ECG features was extracted sufficiently.Since feature selection is a combination optimization problem,Improved Binary Particle Swarm Optimization(IBPSO) based on neighborhood search was applied to search out effective features to improve classification results of emotion states with the help of fisher or K-Nearest Neighbor(KNN) classifier.In the experiment,it is shown that the approach is successful and the effective features got from ECG signals can express emotion states excellently.

Optimization of sensing time and cooperative user allocation for OR-rule cooperative spectrum sensing in cognitive radio network

In order to improve the throughput of cognitive radio(CR), optimization of sensing time and cooperative user allocation for OR-rule cooperative spectrum sensing was investigated in a CR network that includes multiple users and one fusion center. The frame structure of cooperative spectrum sensing was divided into multiple transmission time slots and one sensing time slot consisting of local energy detection and cooperative overhead. An optimization problem was formulated to maximize the throughput of CR network, subject to the constraints of both false alarm probability and detection probability. A joint optimization algorithm of sensing time and number of users was proposed to solve this optimization problem with low time complexity. An allocation algorithm of cooperative users was proposed to preferentially allocate the users to the channels with high utilization probability. The simulation results show that the significant improvement on the throughput can be achieved through the proposed joint optimization and allocation algorithms.

A new hybrid algorithm for global optimization and slope stability evaluation

A new hybrid optimization algorithm was presented by integrating the gravitational search algorithm （GSA） with the sequential quadratic programming （SQP）, namely GSA-SQP, for solving global optimization problems and minimization of factor of safety in slope stability analysis. The new algorithm combines the global exploration ability of the GSA to converge rapidly to a near optimum solution. In addition, it uses the accurate local exploitation ability of the SQP to accelerate the search process and find an accurate solution. A set of five well-known benchmark optimization problems was used to validate the performance of the GSA-SQP as a global optimization algorithm and facilitate comparison with the classical GSA. In addition, the effectiveness of the proposed method for slope stability analysis was investigated using three ease studies of slope stability problems from the literature. The factor of safety of earth slopes was evaluated using the Morgenstern-Price method. The numerical experiments demonstrate that the hybrid algorithm converges faster to a significantly more accurate final solution for a variety of benchmark test functions and slope stability problems.

PARTIALLY BLIND EXTRACTION OF CONTINUOUS CHAOTIC SIGNALS FROM A LINEAR MIXTURE

In this paper, we address the problem of blind extraction and separation of a continuous chaotic signal from a linear mixture consisting of some chaotic signal and/or random signals. The problem of blind extraction is firstly formulated as a problem of the synchronization-based parameter estimation. Then an efficient least square based parameter estimation method is introduced to determine the desired extracting vector. The proposed blind signal extraction scheme is applicable to blind separation of chaotic signals by formulating the separation problem as the extraction of each chaotic source. Numerical simulation shows that the proposed approach can blindly extract and separate the desired chaotic signals and it is also robust to measurement noise.

A novel hybrid estimation of distribution algorithm for solving hybrid flowshop scheduling problem with unrelated parallel machine

The hybrid flow shop scheduling problem with unrelated parallel machine is a typical NP-hard combinatorial optimization problem, and it exists widely in chemical, manufacturing and pharmaceutical industry. In this work, a novel mathematic model for the hybrid flow shop scheduling problem with unrelated parallel machine(HFSPUPM) was proposed. Additionally, an effective hybrid estimation of distribution algorithm was proposed to solve the HFSPUPM, taking advantage of the features in the mathematic model. In the optimization algorithm, a new individual representation method was adopted. The(EDA) structure was used for global search while the teaching learning based optimization(TLBO) strategy was used for local search. Based on the structure of the HFSPUPM, this work presents a series of discrete operations. Simulation results show the effectiveness of the proposed hybrid algorithm compared with other algorithms.

Volterra Integral Equations and Some Nonlinear Integral Equations with Variable Limit of Integration as Generalized Moment Problems

In this paper we will see that, under certain conditions, the techniques of generalized moment problem will apply to numerically solve an Volterra integral equation of first kind or second kind. Volterra integral equation is transformed into a one-dimensional generalized moment problem, and shall apply the moment problem techniques to find a numerical approximation of the solution. Specifically you will see that solving the Volterra integral equation of first kind f（t） = {a^t K（t, s）x（s）ds a ≤ t ≤ b or solve the Volterra integral equation of the second kind x（t） =f（t）＋{a^t K（t,s）x（s）ds a ≤ t ≤ b is equivalent to solving a generalized moment problem of the form un = {a^b gn（s）x（s）ds n = 0,1,2… This shall apply for to find the solution of an integrodifferential equation of the form x＇（t） = f（t） ＋ {a^t K（t,s）x（s）ds for a ≤ t ≤ b and x（a） = a0 Also considering the nonlinear integral equation： f（x）= {fa^x y（x-t）y（t）dt This integral equation is transformed a two-dimensional generalized moment problem. In all cases, we will find an approximated solution and bounds for the error of the estimated solution using the techniques ofgeneralized moment problem.

Expanding the US-China cooperation on service programs： New opportunities for both countries

For years, the US and China have cooperated closely on manufacturing programs, which helps China become the world manufacturing center. While they both have gained much from the cooperation, there are also increasing frictions, disputes, complains and dissatisfaction with each other because of the huge trade unbalance problem and other significant issues. The US is eager to expand export to China, but China seems hesitating to decide what to import from the US. This paper presents an analysis about the benefits of the US-China cooperation with a primary focus on the service sector, which remains a large and untapped opportunity for China. The goal of the paper is to explore a new route to relieve the trade balance issues as they separately impact both nations. While focusing on analyzing several immediate opportunities, the paper also investigates several new ideas that rest on technology as well as entrepreneurial development.

Use of Spreadsheets as an Introductory Tool for Solving Fluid-Structure Interaction Problem

A simple and intuitive manner for solving fluid-structure interaction problem has been developed using Microsoft Excel spreadsheets. By eliminating the need of previous knowledge of any programming language, the method appears as an interesting introduction to numerical solutions of partial differential equations, due to the direct and didactic way that it is developed. Proposed procedure enables the analysis of tridimensional geometries using the finite difference method and can be extended to other differential equations or boundary conditions. The author＇s objective in this paper is to develop a simple and reliable preliminary method for solving acoustic fluid-structure interaction problems with application to dam-reservoir interaction phenomena and also contribute in the educational growth for undergraduate students that are beginning research in such matter.

Positive Solutions of Boundary Value Problem for a Coupled System of Nonlinear Third-order Differential Equations

By using cone expansion-compression theorem in this paper, we study boundary value problems for a coupled system of nonlinear third-order differential equation. Some sufficient conditions are obtained which guarantee the boundary value problems for a coupled system of nonlinear third-order differential equation has at least one positive solution. Some examples are given to verify our results.

两广华侨农场粤语中的近代汉语“知章庄”调查研究

近代汉语中知章庄三组声母的分合问题是汉语史研究的一桩公案。越南广宁省归侨粤语知章庄三组声母今读表现为声母相同,韵母有别的格局,可以为"近代汉语阶段知章庄已经完全合流,它们的不同在于韵母"的观点提供直接的证据。

IPSO-based hybrid approaches for reliability-redundancy allocation problems

The problem of maximizing system reliability through component reliability choices and component redundancy is called tell-ability-redundancy allocation problem （RAP）, and it is a difficult but realistic nonlinear mixed-integer optimization prob- lem. For the RAP. we pay attention to an improved particle swarm optimization （IPSO）, and introduce four hybrid approaches for combining the IPSO with other conventional search techniques, such as harmony search （HS） and LXPM （a real coded GA）. The basic structure of the hybrid approaches includes two phases. After devising an initial solution by the HS or LXPM technique in the first phase, the IPSO performs an optimal search in the next phase. In addition, a new procedure by using golden search, named GS, is developed for further improving the solutions obtained by IPSO. Consequently, four ISPO-based hybrid approaches are proposed including HS-IPSO, LXPM-IPSO, HS-IPSO-GS, and LXPM-IPSO-GS. In order to validate the per-formance of proposed approaches, five nonlinear mixed-integer RAPs are investigated where both the number of re- dundancy components and the corresponding component reliability in each subsystem are to be decided simultaneously. As shown, the proposed approaches are all superior in terms of both optimal solutions and robustness to those by IPSO. Especially the pro-posed LXPM-IPSO-GS has shown more excellent performance than other typical approaches in the literature.

An SDP randomized approximation algorithm for max hypergraph cut with limited unbalance

We consider the design of semidefinite programming （SDP） based approximation algorithm for the problem Max Hypergraph Cut with Limited Unbalance （MHC-LU）： Find a partition of the vertices of a weighted hypergraph H = （V, E） into two subsets V1, V2 with ｜｜V2｜ - ｜1/1 ｜｜ ≤ u for some given u and maximizing the total weight of the edges meeting both V1 and V2. The problem MHC-LU generalizes several other combinatorial optimization problems including Max Cut, Max Cut with Limited Unbalance （MC-LU）, Max Set Splitting, Max Ek-Set Splitting and Max Hypergraph Bisection. By generalizing several earlier ideas, we present an SDP randomized approximation algorithm for MHC-LU with guaranteed worst-case performance ratios for various unbalance parameters τ = u/｜V｜. We also give the worst-case performance ratio of the SDP-algorithm for approximating MHC-LU regardless of the value of τ. Our strengthened SDP relaxation and rounding method improve a result of Ageev and Sviridenko （2000） on Max Hypergraph Bisection （MHC-LU with u = 0）, and results of Andersson and Engebretsen （1999）, Gaur and Krishnamurti （2001） and Zhang et al. （2004） on Max Set Splitting （MHC-LU with u = ｜V｜）. Furthermore, our new formula for the performance ratio by a tighter analysis compared with that in Galbiati and Maffioli （2007） is responsible for the improvement of a result of Galbiati and Maffioli （2007） on MC-LU for some range of τ.