Jun Hyung Jo

Space layout planning using an evolutionary approach

Abstract This paper describes a design method based on constructing a genetic/evolutionary-design model whose idea is borrowed from natural genetics. Here, two major issues from the modelling involve how to represent design knowledge for the evolutionary design model and the usefulness of the model for design problems. For the representation of design knowledge in the model, a schema concept is introduced. The utility of the model is based on its computational efficiency and its capability of producing satisfactory solutions for the given set of problem requirements. The design problem used to demonstrate the approach is a large office layout planning problem with its associated topological and geometrical arrangements of space elements. An example drawn from the literature is used.

Ubiquitous Robot: A New Paradigm for Integrated Services

This paper presents the components and overall architecture of the ubiquitous robot (Ubibot) system developed to demonstrate ubiquitous robotics, a new paradigm for integrated services. The system has been developed on the basis of the definition of the ubiquitous robot as that of encompassing the software robot Sobot, embedded robot Embot and the mobile robot Mobot. This tripartite partition, which independently manifests intelligence, perception and action, enables the abstraction of intelligence through the standardization of sensory data and motor or action commands. The Ubibot system itself is introduced along with its component subsystems of Embots, the position Embot, vision Embot and sound Embot, the Mobots of Mybot and HSR, the Sobot, Rity, a virtual pet modeled as an artificial creature, and finally the middleware which seamlessly enables interconnection between other components. Three kinds of experiments are devised to demonstrate the fundamental features, of calm sensing, context awareness and seamless service transcending the spatial limitations in the abilities of earlier generation personal robots. The experiments demonstrate the proof of concept of this powerful new paradigm which shows great promise.

Academic directions of multimedia education

COMMUNICATIONS OF THE ACM January 2000/Vol. 43, No. 1 89 O ne significant characteristic of multimedia is that it is a vehicle for the convergence of the traditionally separate technologies of computing, entertainment, and telecommunications. To this is added a rich diversity of application areas wanting to exploit this new technological medium including education, commerce, advertising, and medicine, to name a few. This conjunction of technologies and applications creates a very fertile ground for innovation and creation of new multimedia forms. Vocationally, there is high mobility of practitioners in the field and there are very few well-defined career paths. In this rapidly evolving environment, it is imperative that practitioners are highly adaptable and multiskilled. In this context a number of universities have recently introduced undergraduate multimedia degrees. This has presented some interesting challenges to those involved in designing these courses. Under the garb of multimedia there is certainly industry demand for graduates, but defining “multimedia” has proved to be a difficult task. This burdens academics with the problem of achieving consensus on a curriculum for multimedia. This is not so much due to the wide scope of multidisciplinary applications of multimedia (much like word processing) but because the term “multimedia” has metamorphized into something akin to the mythological, multiheaded Hydra where its meaning is often determined by some immediate context in isolation from its source. Implicit in this debate about the definition of multimedia is the question of which discipline can claim ownership, with all that entails. Is it possible that multimedia is not part of an existing discipline but a new one? Some have argued that multimedia is like the emergence of computer science 30 years ago. CS, however, evolved from a conjunction of the fundamentally related disciplines of electrical engineering, mathematics, and other sciences. The similar academic and research cultures associated with these disciplines provided a strong sense of cohesion and direction to their progeny. Unfortunately, this is not the case with multimedia as a number of the disciplines that lay claim to it have traditionally antagonistic cultures. Attempts to synthesize a definition of multimedia and, hence, an undergraduate course as simply a conglomeration of the multitudinous diverse views Ruben Gonzalez, Greg Cranitch, and Jun Jo

A genetic search approach to space layout planning

Space layout planning is one of the most interesting, difficult and controversial area of computer-aided architectural design. Two major issues from the area are the topological assignment of space elements and the dimensioning of those space elements to meet certain criteria and constraints. Critical difficulties include the complexity of design information involved and the combinatorial explosion of alternatives. This paper introduces a design method which uses the evolutionary concept as a mechanism for controlling search over the huge design space. Schemas are introduced to formulate and interpret design information. The Pareto optimization concept is used in the solution of space layout planning as a multi-criteria optimization problem. An example is presented.

Heart Rate Prediction Model Based on Physical Activities Using Evolutionary Neural Network

Physical activity (PA) can influence heart rate(HR). But the relationship between HR and PA is hard to describe. In our previous works, HR prediction models based on PA were designed. However, the prediction time length and accuracy are usually hard to compromise. In this study, a new HR prediction method is proposed. The predicted HR is used as the input in the next prediction step. Only HR at the initial time step and PA signals are needed in a long prediction time length. Evolutionary neural network is used as the mathematic basic of the predictor to ensure the prediction accuracy. The results show the predicted HR can trace the actual HR well.

Adaptive Regions of Interest Based on HSV Histograms for Lane Marks Detection

The lane detection is a vital component of autonomous vehicle systems. Although many different approaches have been proposed in the literature it is still a challenge to correctly identify road lane marks under abrupt light variations. In this work a vision-based ego-lane detection system is proposed with the capability of automatically adapting to abrupt lighting changes. The proposed method automatically adjusts the feature extraction and salient point tracking cues introduced by the GOLDIE (Geometric Overture for Lane Detection by Intersections Entirety) algorithm. The variance of the lighting conditions is measured using hue-saturation histogram and abrupt light changes on the road are detected based on the difference between histograms. Experimental comparison with previously proposed algorithms demonstrated that this method achieved efficient lane detection in the presence of shadows and headlights. In particular, the accuracy of the algorithm applied on the footage with highest light variation increased 12.5% on average. The overall detection rate increased 4%, which illustrated the applicability of the method.

The Future of Robot-Assisted Learning in the Home

Abstract Imagine a home system where children can have an educational assistant with them at all times – a helper to ensure that they understand and are understood. The concept of robots interacting with humans is not new and was predicted in many movies and novels and on television long before the technology was available. With the robot revolution upon us, small-scale household robots are becoming more accepted and widespread. The majority of current household robot applications take the role of service robots in the home, undertaking menial tasks. However, their use in education has great potential. With human–robot interface (HRI) technology, this educational scenario is not only possible but also probable. In the future, household robots will provide the physical interface and mobility for these home-based e-learning systems. It is also envisaged that ubiquitous robots, which consist of embedded, mobile and software robots, will became essential in home network systems. In this paper we anticipate that the software robot, a type of virtual robot, will become the core of many robot-based e-learning systems which will be integrated with household robots. These e-learning software robots can traverse time and space and assist the child at any time and any place and connect to any device through a network. In this paper, we discuss the use of home robots, HRI and software robot-assisted learning which constitutes an e-learning system for young children within the home environment.

Morphology-Controlled High-Efficiency Small Molecule Organic Solar Cells without Additive Solvent Treatment

This paper focuses on nano-morphology-controlled small-molecule organic solar cells without solvent treatment for high power-conversion efficiencies (PCEs). The maximum high PCE reaches up to 7.22% with a bulk-heterojunction (BHJ) thickness of 320 nm. This high efficiency was obtained by eliminating solvent additives such as 1,8-diiodooctane (DIO) to find an alternative way to control the domain sizes in the BHJ layer. Furthermore, the generalized transfer matrix method (GTMM) analysis has been applied to confirm the effects of applying a different thickness of BHJs for organic solar cells from 100 to 320 nm, respectively. Finally, the study showed an alternative way to achieve high PCE organic solar cells without additive solvent treatments to control the morphology of the bulk-heterojunction.

Automatic Bridge Crack Detection A Texture Analysis-Based Approach

To date, identifying cracks in bridges and determining bridge conditions primarily involve manual labour. Bridge inspection by human experts has some drawbacks such as the inability to physically examine all parts of the bridge, sole dependency on the expert knowledge of the bridge inspector. Moreover it requires proper training of the human resource and overall it is not cost effective. This article proposes an automatic bridge inspection approach exploiting wavelet-based image features along with Support Vector Machines for automatic detection of cracks in bridge images. A two-stage approach is followed, where in the first stage a decision is made as whether an image should undergo a pre-processing step (depending on image characteristics), and later in the second stage, wavelet features are extracted from the image using a sliding window-based technique. We obtained an overall accuracy of 92.11% while conducting experiments even on noisy and complex bridge images.

A Research of Physical Activity's Influence on Heart Rate Using Feedforward Neural Network

Heart rate (HR) signal analysis is widely used in the medicine and medical research area. Physical activities (PA) are commonly recognized to greatly affect the changes of heart rate. However, the direct relationship between heart rate and physical activities is hard to describe. In this paper, a model using feedforward neural network with the function of HR prediction is designed. This model reflects the effect how PA affect HR. Experiments was conducted based on the reallife signals from a healthy male. The mean absolute error of the predicted heart rate was relatively small. The result shows the potential of the proposed method.