A Classification Framework using a Diverse Intensified Strawberry Optimized Neural Network (DISON) for Clinical Decision-making

A novel classification framework for clinical decision making that uses an Extremely Randomized Tree (ERT) based feature selection and a Diverse Intensified Strawberry Optimized Neural network (DISON) is proposed. DISON is a Feed Forward Artificial Neural Network where the optimization of weights and bias is done using a two phase training strategy. Two algorithms namely Strawberry Plant Optimization (SPO) algorithm and Gradient-descent Back-propagation algorithm are used sequentially to identify the optimum weights and bias. The novel two phase training method and the stochastic duplicate-elimination strategy of SPO helps in addressing the issue of local optima associated with conventional neural networks. The relevant attributes are selected based on the feature importance values computed using an ERT classifier.Vertebral Column, Pima Indian diabetes (PID), Cleveland Heart disease (CHD) and Statlog Heart disease (SHD) datasets from the University of California Irvine machine learning repository are used for experimentation. The framework has achieved an accuracy of 87.17% for Vertebral Column, 90.92% for PID, 93.67% for CHD and 94.5% for SHD. The classifier performance has been compared with existing works and is found to be competitive in terms of accuracy, sensitivity and specificity. Wilcoxon test confirms the statistical superiority of the proposed method.     

On the Determination of Minimal Facets and Edges of a Polyhedral Set

In this paper we investigate the image of a polyhedral set under a linear map. Moreover, we present an algorithm for the determination of so-called minimal facets and certain minimal irredundant proper edges of a convex polyhedral set in ℝ³. © 1997 John Wiley & Sons, Ltd.     

Pareto simulated annealing—a metaheuristic technique for multiple-objective combinatorial optimization

This paper presents a multiple-objective metaheuristic procedure—Pareto simulated annealing. The goal of the procedure is to find in a relatively short time a good approximation of the set of efficient solutions of a multiple-objective combinatorial optimization problem. The procedure uses a sample, of so-called generating solutions. Each solution explores its neighbourhood in a way similar to that of classical simulated annealing. Weights of the objectives, used for their local aggregation, are tuned in each iteration in order to assure a tendency for approaching the efficient solutions set while maintaining a uniform distribution of the generating solutions over this set. A computational experiment shows that the method is a better tool for approximating the efficient set than some previous proposals. © 1998 John Wiley & Sons, Ltd.     

基于认知特性的信息显示方式

大规模信息的不断涌现使目前的WIMP界面显示方式已无法满足信息显示的要求,同时也给人们处理和理解信息带来极大的困难.本文从认知工效学的角度,深入分析了目前WIMP界面中信息显示与交互方式所存在问题及其原因,并对近年来信息可视化领域中出现的焦点与场景(focus+context)显示技术作了简要的介绍,进一步分析了该技术所面临的挑战.     

A global optimization approach for generating efficient points for multiobjective concave fractional programs

In this article, we present a global optimization approach for generating efficient points for multiobjective concave fractional programming problems. The main work of the approach involves solving an instance of a concave multiplicative fractional program (W̄). Problem (W̄) is a global optimization problem for which no known algorithms are available. Therefore, to render the approach practical, we develop and validate a branch and bound algorithm for globally solving problem (W̄). To illustrate the performance of the global optimization approach, we use it to generate efficient points for a sample multiobjective concave fractional program. Copyright © 2006 John Wiley & Sons, Ltd.     

生命进化动力之哲学思考

对生命进化的本质问题作了新的哲学思考,提出进化的本质是物种在生存的驱动下生存效率的优化过程,是原始细胞自主性与环境选择的双向过程。同时提出推动物种进化的动力在于生存资源稀缺性与物种自私性之间的矛盾和多细胞物种效率优化过程中自身的局部利益与整体利益之间的矛盾。     

Model specification search using a genetic algorithm with factor reordering for a simple structure factor analysis model

Abstract:  Many techniques for automated model specification search based on numerical indices have been proposed, but no single decisive method has yet been determined. In the present article, the performance and features of the model specification search method using a genetic algorithm (GA) were verified. A GA is a robust and simple metaheuristic algorithm with great searching power. While there has already been some research applying metaheuristics to the model fitting task, we focus here on the search for a simple structure factor analysis model and propose a customized algorithm for dealing with certain problems specific to that situation. First, implementation of model specification search using a GA with factor reordering for a simple structure factor analysis is proposed. Then, through a simulation study using generated data with a known true structure and through example analysis using real data, the effectiveness and applicability of the proposed method were demonstrated.     

Defining and Measuring Mechanisms of Change in Psychological Therapies: The Path Not Taken

Metcalf and Dimidjian (this issue) have provided an important review of the current evidence base for mindfulness‐based cognitive therapy (MBCT) and presented a helpful summary of the proposed mechanisms of change. It is necessary to engage in a continuous dialogue regarding the evidence base for change mechanisms, and the article by Metcalf and Dimidjian highlights an important barrier of concern to the field of treatment outcome research. The present commentary aims to expand the discussion regarding the definition, measurement, and evaluation of “mechanisms of change.” Using MBCT as an example, this commentary addresses the ambiguity surrounding the definition and operationalisation of these mechanisms in research on psychological therapies and how the method of measurement may impact the results obtained in clinical trials. It is argued that a potentially fruitful avenue of future research would involve investigation of techniques, important client‐therapeutic processes, and mechanisms in a single study in order to comprehensively evaluate how change occurs.     

Being engaged when resources are low: A multi-source study of selective optimization with compensation at work

This study examined self-regulation in the form of selective optimization with compensation (SOC) at work as a moderator of the relationships of job control (as a job resource) and feeling recovered and energized in the morning (as a personal energy resource) with self- and coworker-rated work engagement. SOC was hypothesized to offset low levels of job control and low levels of personal energy. Based on a sample of 405 public-service employees in Germany, including a multi-source subsample of 141 employees and their respective coworkers, the results showed that SOC use moderated the relationship between the level of personal energy and self-ratings as well as coworker ratings of work engagement such that SOC mitigated low levels of personal energy. SOC at work did not offset low job control. The results suggest that using SOC is particularly important when employees lack energy. SOC strategies should, therefore, be fostered by managers and organizations.     

体温计知识及诊断技术在近代中国的传播与应用——

19世纪末,体温计作为西方医学发展出的新型医疗器具被广泛应用于临床。体温计知识及诊断技术也是西方医学在华传播的重要内容之一,梳理并探讨了其在近代中国的传播途径和应用过程。中医界对于体温计及诊断技术则表现出既接纳又排斥的复杂态度。受中西汇通思想的影响,中医医家将“衷中参西”观念贯彻于诊疗模式,以体温计可以精确测知体温变化之长协助中医临床的辨证。虽然对于“传统”中医四诊诊断模式而言,体温计的应用不免会破坏其传统性,但也在不断受到西医新的诊疗器具与诊断技术的挑战中寻求传承与发展。