Gaze direction based vehicle teleoperation method with omnidirectional image stabilization and automatic body rotation control

In robot teleoperation, a robot works as a physical agent at a remote site for a robot operator. There are mainly two tasks in robot teleoperation using camera images: environment recognition using visual information and robot control according to the recognition. In this paper, we propose a gaze direction based vehicle teleoperation method with an omnidirectional image stabilization and an automatic body rotation control. In the proposed method, we manage above two tasks in the same manner that are usually treated separately. This method is an intuitive vehicle teleoperation method where an operator do not need to have concern about vehicle body orientations and can absorb differences of vehicle driving mechanisms. That is, this method frees an operator from being bothered from controlling a vehicle and the operator can concentrate on where he/she intends to go. This method mainly consists of two technologies: an omnidirectional image stabilization technology and automatic body rotation control. The conducted experiments show effectiveness of the proposed method.     

Infra-chromatic bound for exact maximum clique search

Many efficient exact branch and bound maximum clique solvers use approximate coloring to compute an upper bound on the clique number for every subproblem. This technique reasonably promises tight bounds on average, but never tighter than the chromatic number of the graph.Li and Quan, 2010, AAAI Conference, p. 128–133 describe a way to compute even tighter bounds by reducing each colored subproblem to maximum satisfiability problem (MaxSAT). Moreover they show empirically that the new bounds obtained may be lower than the chromatic number.Based on this idea this paper shows an efficient way to compute related “infra-chromatic” upper bounds without an explicit MaxSAT encoding. The reported results show some of the best times for a stand-alone computer over a number of instances from standard benchmarks.     

Development of a contextual decision-making game for improving students' learning performance in a health education course

Heath education is an important component of the curriculum for fostering children's correct health knowledge and good daily life habits. However, educators have indicated that most children might fail to realize the importance and meaning of health education content owing to the lack of authentic scenarios and daily life experience. With the advancement of computer technologies, researchers have tried to develop multimedia learning content in order to improve students' learning performance. Among various technology-enhanced learning alternatives, digital game-based learning has been recognized as a highly potential approach to motivating students. However, several previous studies have indicated that, without properly incorporating learning content into game scenarios, the effectiveness of digital game-based learning might not be as good as expected in comparison with conventional technology-enhanced learning. In this study, a contextual digital game was developed for improving students' learning performance in an elementary school health education course. A quasi experiment was conducted to evaluate the effectiveness of the proposed approach by situating the experimental group in the game-based learning scenario and the control group to learn with conventional e-books. The experimental results showed that the proposed approach not only improved the students' learning motivation, but also their learning achievement and problem-solving competences. Moreover, the significant two-way interaction suggested that the contextual game-based learning approach benefited the higher motivation students more than the lower motivation ones in terms of the advanced knowledge, showing the importance and potential of applying contextual games to health education activities.     

GJK算法的一种特殊情形的形式化验证和应用

计算几何算法经常用于机器人避碰运动规划等安全攸关领域,对这些算法进行正确性证明非常重要.用形式化方法对算法进行验证是一种十分有效的手段,尤其是定理证明的方法用严格的数学公理和定理推理证明逻辑模型的性质,对所验证的性质而言是完备的.基于GJK算法设计了计算空间两条线段间距离的算法,用定理证明器HOL4对其相关的定义和定理进行形式化定义和证明,进而基于霍尔逻辑完成形式化表示和证明,对该算法的正确性实现了形式化验证.最后,给出了这一经过验证的算法在双臂机器人无碰撞运动规划中的应用.     

Style synthesis and analysis of car designs for style quantification based on product appearance similarities

Understanding how similar design appears is a key element to understanding companies’ design strategies. However, it is difficult to evaluate companies’ design strategies with conventional style measurement methods since they only taxonomically measure whether a specific characteristic is included in a specific style. This study numerically measured car design similarities to synthesize and analyze car brand styles, thereupon discovering the design trends among car brands for strategic design positioning. This paper aims to find methods for quantifying style differences and identifying unique design elements of car designs among 23 automobile manufacturers based on design similarities of a large quantity of car designs (N = 119). To achieve this goal, a hybrid style quantification methodology – a mixture of Fourier decomposition, eye tracker, and shape grammar – was created to evaluate similarities, visual significance, and combinations of 19 car design elements. Fourier decomposition was incorporated to find the quantifiable values of design similarities of car design elements. Visual significance analysis was also conducted for each car design element through eye tracker to measure the importance of certain design elements for weighting factors. Then, each combination of design elements was compared with car design elements of other cars for similarity calculations. Finally, car design alternatives were synthesized, and transitions of design positioning were analyzed based on the similarity values weighed by the visual significance results. Using the suggested methods, alternate designs can be synthesized while preserving brands’ design styles, and design trends can be analyzed for strategic evaluation.     

K-means clustering algorithm for multimedia applications with flexible HW/SW co-design

In this paper, we report a hardware/software (HW/SW) co-designed K-means clustering algorithm with high flexibility and high performance for machine learning, pattern recognition and multimedia applications. The contributions of this work can be attributed to two aspects. The first is the hardware architecture for nearest neighbor searching, which is used to overcome the main computational cost of a K-means clustering algorithm. The second aspect is the high flexibility for different applications which comes from not only the software but also the hardware. High flexibility with respect to the number of training data samples, the dimensionality of each sample vector, the number of clusters, and the target application, is one of the major shortcomings of dedicated hardware implementations for the K-means algorithm. In particular, the HW/SW K-means algorithm is extendable to embedded systems and mobile devices. We benchmark our multi-purpose K-means system against the application of handwritten digit recognition, face recognition and image segmentation to demonstrate its excellent performance, high flexibility, fast clustering speed, short recognition time, good recognition rate and versatile functionality.     

面向大型分布式软件项目的敏捷开发模型研究

面向分布运行的大规模信息化项目,支持基于广域网络的协同开发团队,规避软件过程风险,确立在需求演进状态下实现"业务驱动开发"的软件过程管理模型,是软件工程领域的重要课题。我们采用的方法是:基于一个支持分布式软件开发的支撑平台,并拓展XP的基本属性,改"结对编程"为"分布式编程"和"IRC资源分配",从而完善传统XP存在的先天性不足,保证软件开发元素的完整性和关联紧密性,提高了系统开发效率和软件制品质量。