A playmate robot system for playing the rock-paper-scissors game with humans

We have developed a playmate robot system for playing the rock-paper-scissors game with humans. The playmate robot recognizes the hand motions of a human using image processing without attaching any additional units to the human. The playmate robot system consists of three parts: a game management part, a hand motion recognition part, and a robot hand control part. The system functions as follows. (1) Before the game is played, the game management part decides on the motion of the robot hand from amongst rock, paper, and scissors. After the game is played, the robot develops a reaction using speech and facial expressions depending on the result of the game. (2) The hand motion recognition part recognizes the hand motion of the human. It does not use any additional units on the human’s body, only a camera on the robot. (3) The robot hand control part shows the motion of the robot hand. A robot hand has four fingers that are controlled independently. We have played the rock-paper-scissors game with this playmate robot.     

A tabu search with an oscillation strategy for the discriminant analysis problem

This article proposes a tabu search approach to solve a mathematical programming formulation of the linear classification problem, which consists of determining an hyperplane that separates two groups of points as well as possible in ?^m. The tabu search approach proposed is based on a non-standard formulation using linear system infeasibility. The search space is the set of bases defined on the matrix that describes the linear system. The moves are performed by pivoting on a specified row and column. On real machine learning databases, our approach compares favorably with implementations based on parametric programming and irreducible infeasible constraint sets. Additional computational results for randomly generated instances confirm that our method provides a suitable alternative to the mixed integer programming formulation that is solved by a commercial code when the number of attributes m increases.     

A tool for multiobjective evolutionary algorithms

This paper introduces a software tool based on illustrative applications for the development, analysis and application of multiobjective evolutionary algorithms. The multiobjective evolutionary algorithms tool (MOEAT) written in C# using a variety of multiobjective evolutionary algorithms (MOEAs) offers a powerful environment for various kinds of optimization tasks. It has many useful features such as visualizing of the progress and the results of optimization in a dynamic or static mode, and decision variable settings. The performance measurements of well-known multiobjective evolutionary algorithms in MOEAT are done using benchmark problems. In addition, two case studies from engineering domain are presented.     

The use of data-derived label hierarchies in multi-label classification

Instead of traditional (multi-class) learning approaches that assume label independency, multi-label learning approaches must deal with the existing label dependencies and relations. Many approaches try to model these dependencies in the process of learning and integrate them in the final predictive model, without making a clear difference between the learning process and the process of modeling the label dependencies. Also, the label relations incorporated in the learned model are not directly visible and can not be (re)used in conjunction with other learning approaches. In this paper, we investigate the use of label hierarchies in multi-label classification, constructed in a data-driven manner. We first consider flat label sets and construct label hierarchies from the label sets that appear in the annotations of the training data by using a hierarchical clustering approach. The obtained hierarchies are then used in conjunction with hierarchical multi-label classification (HMC) approaches (two local model approaches for HMC, based on SVMs and PCTs, and two global model approaches, based on PCTs for HMC and ensembles thereof). The experimental results reveal that the use of the data-derived label hierarchy can significantly improve the performance of single predictive models in multi-label classification as compared to the use of a flat label set, while this is not preserved for the ensemble models.     

A system for efficient motor learning using multimodal augmented feedback

Numerous studies have established that using various forms of augmented feedback improves human motor learning. In this paper, we present a system that enables real-time analysis of motion patterns and provides users with objective information on their performance of an executed set of motions. This information can be used to identify individual segments of improper motion early in the learning process, thus preventing improperly learned motion patterns that can be difficult to correct once fully learned. The primary purpose of the proposed system is to serve as a general tool in the research on impact of different feedback modalities on the process of motor learning, for example, in sports or rehabilitation. The key advantages of the system are high-speed and high-accuracy tracking, as well as its flexibility, as it supports various types of feedback (auditory and visual, concurrent or terminal). The practical application of the proposed system is demonstrated through the example of learning a golf swing.     

基于肿瘤细胞断层图像轮廓的三维极坐标插值方法

利用“细胞CT”——激光扫描共聚焦显微镜可以获得肿瘤细胞三维断层图像,实现肿瘤细胞三维可视化,具有重要临床及科研意义。本文提出了一种针对细胞断层图像轮廓的三维极坐标插值方法,以图形形态学中心为极坐标原点,将轮廓点转换为极坐标表示。按极角采样获得离散轮廓点数据,综合多层轮廓信息,依照表面轮廓变化趋势,进行均匀三次B样条拟合完成插值。并针对肿瘤细胞核常见的分支核结构,利用曲率角点检测和数学形态学相结合的方法实现轮廓分割,并采用基于阈值半径的轮廓匹配方法实现分支轮廓对应,继而实现细胞分支核插值。结果显示,本方法可实现细胞及细胞核的三维插值,插值后轮廓表面三维重建表现出良好的曲面光滑性和连续性。极坐标插值数据可为细胞三维形态结构测量提供便利。     

基于工程管理的南海地质数据库

从南海地质数据资源、工程实例出发,结合高级语言设计和开发了基于工程管理的南海地质信息数据库系统.该系统设计实现了南海地质信息数据共享、数据融合、数据分析,简单快捷的结合到工程实例中,并应用ADO、DAO、OLE等计算机技术实现的数据资源快速导入、导出便于工程应用的目的.对工程中土的性质做详细的介绍,包括随深度的下降有效重度、抗剪强度、单位表面摩阻力、单位桩端阻力的变化情况.可以按层号、深度、土体性质等不同的条件进行查找.汇总功能可以绘制曲线,比较同一工程土体参数和不同工程之间的参数等,对工程设计和施工进行指导.     

Algorithms for the Homogeneous Set Sandwich Problem

A homogeneous set is a non-trivial module of a graph, i.e. a non-empty, non-unitary, proper subset of a graph's vertices such that all its elements present exactly the same outer neighborhood. Given two graphs the Homogeneous Set Sandwich Problem (HSSP) asks whether there exists a sandwich graph which has a homogeneous set. In 2001 Tang et al. published an all-fast algorithm which was recently proven wrong, so that the HSSP's known upper bound would have been reset thereafter at the former determined by Cerioli et al. in 1998. We present, notwithstanding, new deterministic algorithms which have it established at We give as well two even faster randomized algorithms, whose simplicity might lend them didactic usefulness. We believe that, besides providing efficient easy-to-implement procedures to solve it, the study of these new approaches allows a fairly thorough understanding of the problem.     

基于计算机视觉的果树害虫的形态特征分析

为解决农作物病虫害的诊断问题,选择京郊常见果树的三种害虫:桃蛀螟成虫、华北大黑鳃金龟成虫、桃六点天蛾,使用计算机视觉技术清除背景,获取该害虫的形状参数、偏心率等形态特征。通过判别分析,建立三种害虫形态特征的判别评分函数,并测试了该判别评分函数的有效性。实验结果表明,形状参数、偏心率、似圆度特征能反映这三种害虫的形态特点,可有效区分这三种害虫。