Focusing on the first and second question in the 2022 CUMCM problem A "Design of Maximum Output Power of Wave Energy", based on force analysis, the heave model of the float and vibrator is established. To compute the second-order non-homogeneous linear differential equation, this study uses fourth-order Runge-Kutta method to discretize it. The value of the integral function of the output power is approximated by the trapezoidal area. The maximum output power and the corresponding optimal damping coefficient are obtained by the genetic algorithm. The model validation passes simultaneously.

冯·诺伊曼体系结构是现代计算机的基础,了解其基本设计原则对理解计算机的组织结构、运行方式具有重要的意义.以冯·诺依曼计算机基本组成和指令执行流程为核心,以人工智能技术应用为背景,设计构建高度现实的虚拟仿真实验教学环境,将抽象、复杂、周期长的实验过程更逼真、立体地呈现出来,用以展示冯·诺依曼体系结构中各部件的微观原型,让计算机指令可设计、可呈现、可理解,让学生以"沉浸"方式深入理解冯·诺依曼体系结构的基本设计原则、计算机的结构组织和运行方式,填补面向计算机系统的原理性实验教学空白,对计算机专业实验教学具有重要的意义.

Sorting permutations by block moves is a fundamental combinatorial problem in genome rearrangements. The classic block move operation is called transposition, which switches two adjacent blocks, or equivalently, moves a block to some other position. But large blocks movement rarely occurs during real evolutionary events. A natural restriction of transposition is to bound the length of the blocks to be switched. In this paper, we investigate the problem called sorting by bounded singleton moves, where one of the switched blocks is exactly a singleton while the other is of length at most c. This problem generalizes the sorting by short block moves problem proposed by Heath and Vergara [11], which requires the total length of blocks switched bounded by 3. When c=3, we devise a 95-approximation algorithm for an arbitrary permutation, and a 127-approximation algorithm for a woven double-strip permutation. Our algorithms can be slightly extended to solve the sorting by c-bounded singleton moves problem for any constant c≥3, guaranteeing an approximation factor of 3c5 and 4c7 for arbitrary permutations and woven double-strip permutations respectively, just by exploiting a new lower bound of sorting by c-bounded singleton moves.

Scaffold filling is an interesting combinatorial optimization problem from genome sequencing. The one-sided scaffold filling problem can be stated as: given an incomplete scaffold with some genes missing and a reference scaffold, the purpose is to insert the missing genes back into the incomplete scaffold( called ”filling the scaffold”), such that the number of common adjacencies between the filled scaffold and the reference scaffold is maximized. This problem is NP-hard for genome with duplicated genes, and can be approximated within 1.25 by a very complicated combinatorial method. In this paper, we firstly improve the approximation factor to 6/5 by not-oblivious local search; then we show that this problem is MAX-SNP-complete.

可计算性(Computability)即算法有解性,是数学和计算机科学领域中重要的概念之一.可计算性逻辑(Computability Logic,CoL)是关于可计算性的形式理论,是一种交互的资源逻辑.其中,CoL2系统采用博弈的语义,是对经典命题逻辑的扩展,在经典命题逻辑的基础上添加了选择运算和一般原子,比经典命题逻辑更富有表达力,具有更广阔的应用前景,并且有较高的证明效率.分析了CoL2系统的可判定性,即通过提出一个算法来判断任意一个CoL2公式是否是可证明的,并且证明了该算法是多项式空间内运行的.

We introduce a new, substantially simplified version of the toggling-branching recurrence operation of computability logic, prove its equivalence to Japaridze’s old, “canonical” version, and also prove that both versions preserve the static property of their arguments.

Computability logic (CoL) is a formal theory of interactive computation. It understands computational problems as games played by two players: a machine and its environment, uses logical formalism to describe valid principles of computability and formulas to represent computational problems. Logic CL1 is a deductive system for a fragment of CoL. The logical vocabulary contains all of the operators of classical logic and choice operators, the atoms represent elementary games i.e. predicates of classical logic. In this paper, we present a program that takes a CL1-proof of an arbitrary formula $F$, and extract a winning strategy for $F$ from that proof then play $F$ using that strategy. We hope this paper would provide a starting point for further work in program extraction of the CoL-based arithmetic and other CoL-based applied systems.

This paper mainly introduces the principle and method of the search engine, it also gives the design and implementation of the multi-thread concurrent spider based on the local network. This spider adopts the BloomFilter to solve the URL duplicate and thread pool to manage the concurrent threads; it uses the IoC technique in Spring to provide the support of the different file formats such as DOC, PDF, XLS etc which can demonstrate the scalability of the whole application; the spider speeds up the I/O performance by storing the data in the light database. At the end of the paper, we give the comparison and the analysis between the local search engine and general business search engine in the efficiency and performance.

The minimum enclosing ball problem means to construct a ball of the minimum radius enclosing a given set of balls in S. We propose the concept of the diameter of a set of balls and give an approximation algorithm solve the diameter. We develop the 1+e approximation algorithm using core-sets. The time complexity of this algorithm is O(nd/e+d2/e3/2(1/e+d)log(1/e)). We prove the existence of the core-sets of size O(1/e) are unrelated to n and d.

During the past decades,several polynomial algorithms have been developed for the problem of by reciprocal (abbreviated as SRT),which is to find the shortest sequence of reciprocal that transforms one genome into another. However,there are many shortest sequences of reciprocal for most problem instances. In consequence,the problem of finding all the shortest sequences of reciprocal is a natural generalization of SRT. This problem reduces easily to the problem of finding all the sorting reciprocal translocations of one genome with respect to another—that is,all ρ which can reduce the translocation distance of the resulting genome from another after applying ρ on one genome. In this paper,we give an efficient algorithm for finding all the reciprocal translocations. While the new algorithm improves little in asymptotic time complexity,the experimental results show that it performs better in practice than the brute force method.

多染色体基因组进化问题中常见的重组事件就是移位（translocation）,对此已有很多研究成果.但事实上更为普遍的情况是2个基因组包含不同基因,这需要考虑插入和删除事件.对于"通过移位-插入-删除进行基因组排序（简称SG-TID）"这个问题,此前已有一个求解移位-删除（或者移位-插入）序列的近似算法,以及求解SG-TID问题的启发式算法.在给出了移位-插入-删除距离的表达公式后,给出了在增加O（n）存储空间的条件下,O（n2）时间内求解该问题的精确算法.该算法比此前给出的算法要快.

Given a tree T = (V, E) with costs defined on edges, a positive integer k, and I terminal sets {S1, S2, . . ., Sl} with every Si sube V, the generalized k-multicut in trees problem (k-GMC(T)) asks to find an edge subset in E at the minimum cost such that its removal cuts at least k terminal sets. The k-GMC(T) problem is a natural generalization of the classical multicut in trees problem and the multiway cut in trees problem. This problem is hard to be approximated within O(n1/6-isin) for some small constant isin > 0 (Zhang, CiE'07). Based on a greedy approach and a rounding technique in linear programming, we give a bicriteria approximation algorithm for k-GMC(T). Our algorithm outputs in polynomial time a solution which cuts at least (1 - isin)k terminal sets and whose cost is within radic2/isinldrl times of the optimum for any small constant isin > 0, and hence gives sublinear approximation ratio for k-GMC(T).

Voting systems are common tools in a variety of areas. This paper studies parameterized computational complexity of control of Plurality, Condorcet and Approval voting systems, respectively. The types of controls considered include adding or deleting candidates or voters, under constructive or destructive setting. We obtain the following results: (1) constructive control by adding candidates in Plurality voting is W[2]-hard with respect to the parameter “number of added candidates”, (2) destructive control by adding candidates in Plurality voting is W[2]-hard with respect to the parameter “number of added candidates”, (3) constructive control by adding voters in Condorcet voting is W[1]-hard with respect to the parameter “number of added voters”, (4) constructive control by deleting voters in Condorcet voting is W[1]-hard with respect to the parameter “number of deleted voters”, (5) constructive control by adding voters in Approval voting is W[1]-hard with respect to the parameter “number of added voters”, and (6) constructive control by deleting voters in Approval voting is W[2]-hard with respect to the parameter “number of deleted voters”.

Given two signed multi-chromosomal genomes Π and Γ, where gene set of Γ is the proper subset of that of Π, the problem of sorting by translocation-deletions, which is abbrebiated as STD, is to find the shortest sequence transforming Π to Γ via the two operations mentioned above only. A lower bound of the distance from Π to Γ and an asymptotically optimal algorithm has been given [1]. In this paper we present a formula to calculate the translocation-deletions distance for the first time. Moreover, we improved the existing algorithms to a new one, which is the first algorithm presenting the precise distance and the optimal translocation and deletion sequence in polynomial-time. After giving the algorithm analysis, we illustrate the performence with an example.

Sorting genomes by translocation, insertion and deletions has already been researched for years such as in [1, 2]. However, the authors in [1] did not consider the case that a gene in the target genome does not appear in the source genome. Translocation is a reciprocal operation in sorting genomes, and deletion and insertion are reciprocal to each other. In this paper, we first correct an error in the algorithm in [2], and then propose an algorithm to sort the genomes with different genes using translocation, insertion and deletion in polynomial time O(n(3)). We also analyze the distance between the original genome and sorted genome.

The paper proposes the k-center clustering problem of high-dimensional space balls.The problem means as for the set B built by the multiple balls in a high-dimensional space,k balls are built to cover all the known balls in B and make the biggest radius of the k balls the smallest.We selectively select some balls from B to build sets,which is called the core set of B,and for a given e,we use the core set to propose the polynomial time 1+e approximation algorithm with ball number n and dimension d based on the k-center clustering problem of high-dimensional space balls.And the number of balls in S is O(1/e2),which is not related to the number of balls in B and the dimension of the space.

The hybrid flow-shop scheduling problem with multiprocessors and release dates may find its applications in real-time machine-vision systems among others.This problem is well known as NP-hard.Motivated by the above rcasoils, a genetic algorithm has been proposed in this work.The algorithm by trying different crossover operators and mutation operators along with different settings of the involved parameters have been implemented. The experiment results and concluded the best settings have been analyzed and discussed at last.