Feature Selection with a Local Search Strategy Based on the Forest Optimization Algorithm

Feature selection has been widely used in data mining and machine learning.Its objective is to select a minimal subset of features according to some reasonable criteria so as to solve the original task more quickly.In this article,a feature selection algorithm with local search strategy based on the forest optimization algorithm,namely FSLSFOA,is proposed.The novel local search strategy in local seeding process guarantees the quality of the feature subset in the forest.Next,the fitness function is improved,which not only considers the classification accuracy,but also considers the size of the feature subset.To avoid falling into local optimum,a novel global seeding method is attempted,which selects trees on the bottom of candidate set and gives the algorithm more diversities.Finally,FSLSFOA is compared with four feature selection methods to verify its effectiveness.Most of the results are superior to these comparative methods.

A Non-Monotone Trust Region Method with Non-Monotone Wolfe-Type Line Search Strategy for Unconstrained Optimization

In this paper, we propose and analyze a non-monotone trust region method with non-monotone line search strategy for unconstrained optimization problems. Unlike the traditional non-monotone trust region method, our algorithm utilizes non-monotone Wolfe line search to get the next point if a trial step is not adopted. Thus, it can reduce the number of solving sub-problems. Theoretical analysis shows that the new proposed method has a global convergence under some mild conditions.

Semantic model and optimization of creative processes at mathematical knowledge formation

The aim of this work is mathematical education through the knowledge system and mathematical modeling. A net model of formation of mathematical knowledge as a deductive theory is suggested here. Within this model the formation of deductive theory is represented as the development of a certain informational space, the elements of which are structured in the form of the orientated semantic net. This net is properly metrized and characterized by a certain system of coverings. It allows injecting net optimization parameters, regulating qualitative aspects of knowledge system under consideration. To regulate the creative processes of the formation and realization of mathematical know- edge, stochastic model of formation deductive theory is suggested here in the form of branching Markovian process, which is realized in the corresponding informational space as a semantic net. According to this stochastic model we can get correct foundation of criterion of optimization creative processes that leads to “great main points” strategy (GMP-strategy) in the process of realization of the effective control in the research work in the sphere of mathematics and its applications.

Cooperative UAV search strategy based on DMPC-AACO algorithm in restricted communication scenarios

Improvement of integrated battlefield situational awareness in complex environments involving dynamic factors such as restricted communications and electromagnetic interference(EMI)has become a contentious research problem.In certain mission environments,due to the impact of many interference sources on real-time communication or mission requirements such as the need to implement communication regulations,the mission stages are represented as a dynamic combination of several communication-available and communication-unavailable stages.Furthermore,the data interaction between unmanned aerial vehicles(UAVs)can only be performed in specific communication-available stages.Traditional cooperative search algorithms cannot handle such situations well.To solve this problem,this study constructed a distributed model predictive control(DMPC)architecture for a collaborative control of UAVs and used the Voronoi diagram generation method to re-plan the search areas of all UAVs in real time to avoid repetition of search areas and UAV collisions while improving the search efficiency and safety factor.An attention mechanism ant-colony optimization(AACO)algorithm is proposed for UAV search-control decision planning.The search strategy is adaptively updated by introducing an attention mechanism for regular instruction information,a priori information,and emergent information of the mission to satisfy different search expectations to the maximum extent.Simulation results show that the proposed algorithm achieves better search performance than traditional algorithms in restricted communication constraint scenarios.

Privacy-Preserving Multi-Keyword Fuzzy Adjacency Search Strategy for Encrypted Graph in Cloud Environment

In a cloud environment,outsourced graph data is widely used in companies,enterprises,medical institutions,and so on.Data owners and users can save costs and improve efficiency by storing large amounts of graph data on cloud servers.Servers on cloud platforms usually have some subjective or objective attacks,which make the outsourced graph data in an insecure state.The issue of privacy data protection has become an important obstacle to data sharing and usage.How to query outsourcing graph data safely and effectively has become the focus of research.Adjacency query is a basic and frequently used operation in graph,and it will effectively promote the query range and query ability if multi-keyword fuzzy search can be supported at the same time.This work proposes to protect the privacy information of outsourcing graph data by encryption,mainly studies the problem of multi-keyword fuzzy adjacency query,and puts forward a solution.In our scheme,we use the Bloom filter and encryption mechanism to build a secure index and query token,and adjacency queries are implemented through indexes and query tokens on the cloud server.Our proposed scheme is proved by formal analysis,and the performance and effectiveness of the scheme are illustrated by experimental analysis.The research results of this work will provide solid theoretical and technical support for the further popularization and application of encrypted graph data processing technology.

Balance control during gait initiation: State-of-the-art and research perspectives

It is well known that balance control is affected by aging, neurological and orthopedic conditions. Poor balance control during gait and postural maintenance are associated with disability, falls and increased mortality. Gait initiation-the transient period between the quiet standing posture and steady state walking-is a functional task that is classically used in the literature to investigate how the central nervous system(CNS) controls balance during a whole-body movement involving change in the base of support dimensions and center of mass progression. Understanding how the CNS in able-bodied subjects exerts this control during such a challenging task is a prerequisite to identifying motor disorders in populations with specific impairments of the postural system. It may also provide clinicians with objective measures to assess the efficiency of rehabilitation programs and better target interventions according to individual impairments. The present review thus proposes a state-of-the-art analysis on:(1) the balance control mechanisms in play during gait initiation in able bodied subjects and in the case of some frail populations; and(2) the biomechanical parameters used in the literature to quantify dynamic stability during gait initiation. Balance control mechanisms reviewed in this article included anticipatory postural adjustments, stance leg stiffness, foot placement, lateral ankle strategy, swing foot strike pattern and vertical center of mass braking. Based on this review, the following viewpoints were put forward:(1) dynamic stability during gait initiation may share a principle of homeostatic regulation similar to most physiological variables, where separate mechanisms need to be coordinated to ensure stabilization of vital variables, and consequently; and(2) rehabilitation interventions which focus on separate or isolated components of posture, balance, or gait may limit the effectiveness of current clinical practices.

A novel speech emotion recognition algorithm based on combination of emotion data field and ant colony search strategy

In order to effectively conduct emotion recognition from spontaneous, non-prototypical and unsegmented speech so as to create a more natural human-machine interaction; a novel speech emotion recognition algorithm based on the combination of the emotional data field （EDF） and the ant colony search （ACS） strategy, called the EDF-ACS algorithm, is proposed. More specifically, the inter- relationship among the turn-based acoustic feature vectors of different labels are established by using the potential function in the EDF. To perform the spontaneous speech emotion recognition, the artificial colony is used to mimic the turn- based acoustic feature vectors. Then, the canonical ACS strategy is used to investigate the movement direction of each artificial ant in the EDF, which is regarded as the emotional label of the corresponding turn-based acoustic feature vector. The proposed EDF-ACS algorithm is evaluated on the continueous audio）＇visual emotion challenge （AVEC） 2012 dataset, which contains the spontaneous, non-prototypical and unsegmented speech emotion data. The experimental results show that the proposed EDF-ACS algorithm outperforms the existing state-of-the-art algorithm in turn-based speech emotion recognition.

社会工作质性评估研究的回顾(1990-2003)对中国社会工作的启示

Objective: This paper reviewed and examined the quality of all the qualitative evaluation studies indexed by two key search terms of “qualitative” and “evaluation” in the Social Work Abstracts database from 1990 to 2003 against a number of criteria typically adopted in the field of qualitative research. The review led to a dissatisfactory finding of the low quality of many qualitative evaluation studies due to their insensitivity to the following issues: philosophical basis of the study, auditability (detailed documentation of the participants and data collecting procedure), biases (acknowledgement of biases and preoccupation, and steps to deal with them), credibility or trustworthiness (triangulation, peer checking and participant verification of the findings), consistency (reliability consciousness and audit trails), and critical interpretation of the data (alternative explanations, disconfirming evidence, and limitations of the study). It was recommended that researchers be cautious when utilizing findings from the published qualitative evaluation studies; that social workers be sensitive to the issue of quality when conducting qualitative evaluation studies; that researchers be critical when judging the qualitative evaluation studies in social work; that researchers develop a clear set of guidelines for qualitative studies; that social work training institutes design qualified qualitative research courses; that a database of social work in China be established; that researchers be engaged in more qualitative studies that demonstrate high quality; that myths in qualitative research be debunked; and that adequate training for social workers on qualitative evaluation studies be provided.

Novel cued search strategy based on information gain for phased array radar

A search strategy based on the maximal information gain principle is presented for the cued search of phased array radars. First, the method for the determination of the cued search region, arrangement of beam positions, and the calculation of the prior probability distribution of each beam position is discussed. And then, two search algorithms based on information gain are proposed using Shannon entropy and Kullback-Leibler entropy, respectively. With the proposed strategy, the information gain of each beam position is predicted before the radar detection, and the observation is made in the beam position with the maximal information gain. Compared with the conventional method of sequential search and confirm search, simulation results show that the proposed search strategy can distinctly improve the search performance and save radar time resources with the same given detection probability.

Binary Gravitational Search based Algorithm for Optimum Siting and Sizing of DG and Shunt Capacitors in Radial Distribution Systems

This paper presents a binary gravitational search algorithm (BGSA) is applied to solve the problem of optimal allotment of DG sets and Shunt capacitors in radial distribution systems. The problem is formulated as a nonlinear constrained single-objective optimization problem where the total line loss (TLL) and the total voltage deviations (TVD) are to be minimized separately by incorporating optimal placement of DG units and shunt capacitors with constraints which include limits on voltage, sizes of installed capacitors and DG. This BGSA is applied on the balanced IEEE 10 Bus distribution network and the results are compared with conventional binary particle swarm optimization.

Research on the Teaching Strategy of Broadcasting and Hosting Specialty in Colleges and Universities from the Perspective of New Media

With the continuous development of science and technology and the comprehensive arrival of the information era, new media has gradually emerged and developed, which has had a serious impact on the original media form. Under the background of new media, higher requirements are put forward for the education and teaching activities of broadcasting and hosting specialty in colleges and universities, and the combination of new media technology and Chinese educational practice is the general trend in the current education field, which can effectively improve students’ learning quality and learning effects, and provide a broader space for the development of new media professions. This paper mainly explores the teaching strategies of broadcasting and hosting specialty in colleges and universities from the perspective of new media.

Parallel Minimax Searching Algorithm for Extremum of Unimodal Unbounded Function

In this paper we consider a parallel algorithm that detects the maximizer of unimodal function f(x) computable at every point on unbounded interval (0, ∞). The algorithm consists of two modes: scanning and detecting. Search diagrams are introduced as a way to describe parallel searching algorithms on unbounded intervals. Dynamic programming equations, combined with a series of liner programming problems, describe relations between results for every pair of successive evaluations of function f in parallel. Properties of optimal search strategies are derived from these equations. The worst-case complexity analysis shows that, if the maximizer is located on a priori unknown interval (n-1], then it can be detected after cp(n)=「2log「p/2」+1(n+1)」-1 parallel evaluations of f(x), where p is the number of processors.

Research Progress in Laser Active Debris Removal of CAST

Based on the introduction to theresearch status and trend of international space-based laser debris re-moval technology, the existing problems of space-based laser debris removal technology are systematically analyzed.In view of the existing problems, the work and research progress of the Beijing Institute of Spacecraft EnvironmentEngineering in this field are introduced from several aspects, such as dynamic behavior of laser-driven debris, orbittransfer model, ground simulation system, space-based removal system scheme and target selection strategy. The mainresearch methods include laser-driven micro-impulse measurement experiment, surface triangulation three-dimension-al reconstruction calculation method based on laser-material interaction theory, simulation calculation based on orbitaldynamics, etc. It also looks forward to the future research direction in the field of this technology.

From basic researches to new achievements in therapeutic strategies of KRAS-driven cancers

Among the numerous oncogenes involved in human cancers, KRAS represents the most studied and best characterized cancerrelated genes.Several therapeutic strategies targeting oncogenic KRAS(KRASonc) signaling pathways have been suggested,including the inhibition of synthetic lethal interactions, direct inhibition of KRASonc itself, blockade of downstream KRASonc effectors, prevention of post-translational KRASonc modifications, inhibition of the induced stem cell-like program, targeting of metabolic peculiarities, stimulation of the immune system, inhibition of inflammation, blockade of upstream signaling pathways,targeted RNA replacement, and oncogene-induced senescence.Despite intensive and continuous efforts, KRASonc remains an elusive target for cancer therapy.To highlight the progress to date, this review covers a collection of studies on therapeutic strategies for KRAS published from 1995 to date.An overview of the path of progress from earlier to more recent insights highlight novel opportunities for clinical development towards KRASonc-signaling targeted therapeutics.

Levy Constrained Search in Fock Space：An Alternative Approach to Noninteger Electron Number

By extending the Levy wavefunction constrained search to Fock Space,one can define a wavefunction constrained search for electron densities in systems having noninteger number of electrons.For pure-state v-representable densities,the results are equivalent to what one would obtain with the zero-temperature grand canonical ensemble.In other cases,the wavefunction constrained search in Fock space presents an upper bound to the grand canonical ensemble functional.One advantage of the Fock-space wavefunction constrained search functional over the zero-temperature grand-canonical ensemble constrained search functional is that certain specific excited states(i.e.,those that are not ground-statev-representable) are the stationary points of the Fock-space functional.However,a potential disadvantage of the Fock-space constrained search functional is that it is not convex.

Effective arithmetic optimization algorithm with probabilistic search strategy for function optimization problems

This paper proposes an enhanced arithmetic optimization algorithm(AOA)called PSAOA that incorporates the proposed probabilistic search strategy to increase the searching quality of the original AOA.Furthermore,an adjustable parameter is also developed to balance the exploration and exploitation operations.In addition,a jump mechanism is included in the PSAOAto assist individuals in jumping out of local optima.Using 29 classical benchmark functions,the proposed PSAOA is extensively tested.Compared to the AOA and other well-known methods,the experiments demonstrated that the proposed PSAOA beats existing comparison algorithms on the majority of the test functions.

Research on the Development Strategy of Ningbo Transportation Port &Shipping Industry

Firstly, the development background of Ningbo Transportation Port & Shipping Industry is analyzed on a spatial scale. Based on that, the strategic goal of Ningbo transportation port Port & Shipping Industry is put forward, and strategic path analysis of strategic objectives is carried out. Finally, with the dynamic resource view, the strategic integration model of Ningbo Port & Shipping Industry is proposed.

Searching for a Target Traveling between a Hiding Area and an Operating Area over Multiple Routes

We consider the problem of searching for a target that moves between a hiding area and an operating area over multiple fixed routes. The search is carried out with one or more cookie-cutter sensors, which can detect the target instantly once the target comes within the detection radius of the sensor. In the hiding area, the target is shielded from being detected. The residence times of the target, respectively, in the hiding area and in the operating area, are exponentially distributed. These dwell times are mathematically described by Markov transition rates. The decision of which route the target will take on each travel to and back from the operating area is governed by a probability distribution. We study the mathematical formulation of this search problem and analytically solve for the mean time to detection. Based on the mean time to capture, we evaluate the performance of placing the searcher(s) to monitor various travel route(s) or to scan the operating area. The optimal search design is the one that minimizes the mean time to detection. We find that in many situations the optimal search design is not the one suggested by the straightforward intuition. Our analytical results can provide operational guidances to homeland security, military, and law enforcement applications.

小兴安岭红松阔叶混交林土壤动物群落研究

Soil animal communities of Pinus koraiensis broad_leaved mixed forest were studied.The purpose was to discuss the dynamic characteristic of soil animals and relationship with environmental factors.The ecosystem geography distribution law of soil animals, soil animals’role and function in ecological system were revealed.In June,August,October each year,three plots were selected. In each plot, four layers were sampled(litter layer,0～10 cm,10～20 cm & 20～30 cm),adding up to 72 soil sample.The area for large_sized soil animals was 50 cm×50 cm,and the area for middle_small_sized soil animals was 10 cm × 10 cm.Separated soil animals through adopting hand_picking method and Tullgren method respectively.Sampled the soil animals in two continuing years.Shannon_Wiener index was adopted to analyze the diversity of soil animals.Monad liner regression was used to search the relationship between soil animals and environmental factors.The dominant groups were Oribatida, Isotomidae.There were relatively great changes in groups and individual numbers of dominant groups and rare groups when the reason changed.The individual numbers of dominant groups and the groups of rare groups changed.The number of individual and group was the most in August.Obviously it correlated with climatic factors in middle temperate zone.The evenness was low and dominance was high. The diversity index was not most.Among the annual fluctuating there was a increasing trend. The evenness was low and dominance was high.The diversity index was low.It conformed with the law of reason change.The correlation between soil animals and atmospheric temperature,rainfall,ground temperature and sunlight showed the correlation with rainfall and soil temperature was the most significant.

基于多维尺度分析的个人金融产品差异性研究

本文通过问卷调查获得数据,运用多维尺度分析了国内12家主要商业银行的主打个人金融产品并对其差异性做了实证研究。文章得出如下结论:我国商业银行个人金融产品的层次差别并不十分明显,产品或服务从形式到功能上都存在着较大的同质性;个人金融产品主要是单一型产品,缺乏为客户提供多项业务相结合的交叉式或捆绑式服务,不能满足消费者的多元化需求;不同收入的消费人群对个人金融产品的需求不同。在此基础上,作者提出了我国商业银行应实行个人金融产品或服务的差异化战略;以核心产品为依托,实现业务向全方位拓展延伸;针对不同消费群体进行差异化的金融创新和产品推销等应对策略。