Takashi Uozumi

Hybrid evolutionary algorithm-based real-world flexible job shop scheduling problem: application service provider approach

Abstract This paper presents an approach for scheduling of customers’ orders in factories of plastic injection machines (FPIM) as a case of real-world flexible job shop scheduling problem. The objective of discussed work is to provide FPIM with high business speed which implies (a) providing a customers with convenient way for remote online access to the factory’s database and (b) developing an efficient scheduling routine for planning the assignment of the submitted customers’ orders to FPIM machines. Remote online access to FPIM database, approached via delivering the software as a Web-service in accordance with the application service provider (ASP) paradigm is proposed. As an approach addressing the issue of efficient scheduling routine a hybrid evolutionary algorithm (HEA) combining priority-dispatching rules (PDRs) with GA is developed. An implementation of HEA as a database stored procedure is discussed. Performance evaluation results are presented. The results obtained for evolving a schedule of 400 customers’ orders on experimental model of FPIM indicate that the business delays in order of half-an-hour can be achieved.

Scalable architecture for parallel distributed implementation of genetic programming on network of workstations

Abstract We present an approach for developing a scalable architecture for parallel distributed implementation of genetic programming (PDIGP). The approach is based on exploitation of the inherent parallelism among semi-isolated subpopulations in genetic programming (GP). Proposed implementation runs on cost-efficient configurations of networks on workstations in LAN and Internet environment. Developed architecture features single global migration broker and centralized manager of the semi-isolated subpopulations, which contribute to achieving quick propagation of the globally fittest individuals among the subpopulations, reducing the performance demands to the communication network, and achieving flexibility in system configurations by introducing dynamically scaling up opportunities. PDIGP exploits distributed component object model (DCOM) as a communication paradigm, which as a true system model offers generic support for the issues of naming, locating and protecting the distributed entities in proposed architecture of PDIGP. Experimentally obtained results of computational effort of proposed PDIGP are discussed. The results show that computational effort of PDIGP marginally differs from the computational effort in canonical panmictic GP evolving single large population. For PDIGP running on systems configurations with 16 workstations the computational effort is less than panmictic GP, while for smaller configurations it is insignificantly more. Analytically obtained and empirically proved results of the speedup of computational performance indicate that PDIGP features linear, close to ideal characteristics. Experimentally obtained results of PDIGP running on configurations with eight workstations show close to 8-fold overall speedup. These results are consistent with the anticipated cumulative effect of the insignificant increase of computational effort for the considered configuration and the close to linear speedup of computational performance.

An overview of Kansei engineering: a proposal of Kansei informatics toward realising safety and pleasantness of individuals in information network society

Kansei engineering is the newly proposed engineering discipline having a novel and unique goal. While its aim has been considered, from the beginning, to construct methodology and technology capable of providing industrial products and services reflecting users personal preference/requirement and being evaluated by satisfaction of users, its role is now growing up to consider a new leaf of more fundamental technical issues on Kansei informatics or human-computer interactions toward realising safety and pleasantness of individuals, which will be considered to be a most important fundamental problem in the coming information network society. In this paper, we try to describe an overview of Kansei engineering referring to biometrics. The contents include the background, objectives, present status, and present technical topics of Kansei engineering, where we also introduce concrete examples of developing researches. Future developments are also discussed.

Statistical method for classifying cries of baby based on pattern recognition of power spectrum

We develop a novel method applicable to classify the causes of crying infant based on pattern recognition of power spectrum of the cry. In our frame relied on F-value, it is available in power spectrum to order a statistical significance of frequency points which will contribute to the classification of cries. We verify performance of the method by taking the painful cries of infant with the genetic disease (ADEL). The result of our method achieves an excellent prediction. We also give a discussion on the relation between the set of frequency points extracted and the formants of cries.

Parallel genetic programming: component object-based distributed collaborative approach

We discuss the feasibility of applying the distributed collaborative approach for improving the computational performance of genetic programming (GP), implemented on cost-efficient clusters or the Internet. The proposed approach exploits the coarse grained inherent parallelism in GP among relatively autonomous subpopulations. The developed architecture of a distributed collaborative parallel GP (DCPGP) features a single, global migration broker and centralized manager of the semi-isolated subpopulations, which contribute to quick propagation of the globally fittest individuals among the subpopulations; this reduces the performance demands on the underlying communication network, and achieves dynamic scaling-up features. DCPGP exploits the distributed component object model (DCOM) as a communication paradigm, which as a true system model offers generic support for the issues of naming, locating and security of communicating entities of the developed architecture. Experimentally obtained speedup results show that close to linear speedup characteristics of the prototype of DCPGP are achieved on a network of 8 workstations.

Experiences and problems with hygiene masks reported by Japanese hay fever sufferers

Purpose – In Japan, one of the countermeasures used to avoid the symptoms of hay fever (HF) is a hygiene mask; however, a mask can cause discomfort. The authors believe that co-occurrence analysis, which has been widely in the sciences, will be valuable to this issue. The purpose of this paper is to identify problems associated with the use of hygiene masks and recommend improvements in their function and comfort. The goal of this study was to obtain information for the development of effective hygiene masks for HF sufferers and therefore, improve their quality of life. Design/methodology/approach – The authors conducted a survey of university students with HF (n=1,519) to identify problems with hygiene masks. Students completed self-report questionnaires and co-occurrence analyses were used to examine the data from a holistic perspective. Moreover, technical data, relative to the problems of wearing a mask were acquired experimentally using thermal, hygroscopic, and airflow properties. Findings – Among J...

A Hierarchical Image Annotation Method Based on SVM and Semi-supervised EM

Abstract Automatic image annotation, which aims at automatically identifying and then assigning semantic keywords to the meaningful objects in a digital image, is not a very difficult task for human but has been regarded as a difficult and challenging problem to machines. In this paper, we present a hierarchical annotation scheme considering that generally human s visual identification to a scenery object is a rough-to-fine hierarchical process. First, the input image is segmented into multiple regions and each segmented region is roughly labeled with a general keyword using the multi-classification support vector machine. Since the results of rough annotation affect fine annotation directly, we construct the statistical contextual relationship to revise the improper labels and improve the accuracy of rough annotation. To obtain reasonable fine annotation for those roughly classified regions, we propose an active semi-supervised expectation-maximization algorithm, which can not only find the representative pattern of each fine class but also classify the roughly labeled regions into corresponded fine classes. Finally, the contextual relationship is applied again to revise the improper fine labels. To illustrate the effectiveness of the presented approaches, a prototype image annotation system is developed, the preliminary results of which showed that the hierarchical annotation scheme is effective.

Real-time P and R wave detection in exercise electrocardiogram

The analysis of electrocardiogram (ECG) is used in the diagnosis of the heart disease. Various algorithms have been proposed and used to detect ECG characteristics while it is difficult to detect P wave in real-time accurately. In the present study, we developed the real-time exercise ECG analyzer and the performance of this system was discussed. The method of defining P and R wave is based on a template-matching algorithm. In particular, the computerized algorithm analyzes a single channel ECG signal. The system extracts P-P, R-R and P-R interval from an incoming ECG signal sampled at 1KHz, and also performs spectral analysis of P-P and P-R intervals. The system was evaluated on recordings from 5 healthy subjects. The proposed algorithm had high correlation between P-P and R-R intervals (more than 0.97), for this reason we considered that algorithm was able to detect P wave accurately. Results were displayed on the screen immediately, and we obtained that a correlation diagram of P-P and P-R intervals. The developed system provides the good quality in real-time and the additional information on the fluctuation of P-R intervals.

Component Object Based Single System Image for Dependable Implementation of Genetic Programming on Clusters

We present a distributed component-object model (DCOM) based single system image (SSI) for dependable parallel implementation of genetic programming (DPIGP). DPIGP is aimed to significantly and reliably improve the computational performance of genetic programming (GP) exploiting the inherent parallelism in GP among the evaluation of individuals. It runs on cost-effective clusters of commodity, non-dedicated, heterogeneous workstations or PCs. Developed SSI represents the pool of heterogeneous workstations as a single, unified virtual resource – a metacomputer, and addresses the issues of locating and allocating the physical resources, communicating between the entities of DPIGP, scheduling and load balancing. In addition, addressing the issue of fault tolerance, SSI allows for building a highly available metacomputer in which the cases of workstation failure result only in a corresponding partial degradation of the overall performance characteristics of DPIGP. Adopting DCOM as a communicating paradigm offers the benefits of software platform- and network protocol neutrality of proposed approach; and the generic support for the issues of locating, allocating and security of the distributed entities of DPIGP.

Evaluation of autonomic nervous system with correlation diagram of R-R interval and P-R interval

We developed and examined a new method to evaluate the cooperation between sinoatrial node (SA node) and atrioventricular node (AV node) with a correlation diagram of R-R and P-R interval which we newly developed. Twenty healthy subjects were examined. Electrocardiograph was measured during supine rest, sitting rest, and submaximal exercise by an electrically braked cycle ergometer. One subject was selectively blocked autonomic nervous system (ANS) by pharmacological agents. The correlation diagram of R-R and P-R interval was plotted by beat-to-beat. We also evaluated both sympathetic nervous activity (SNS) and parasympathetic nervous activity (PNS) with spectral analysis of R-R interval variability during exercise. According to the correlation diagrams, both R-R interval and P-R interval decreased with progress of exercise intensity, and these showed nonlinearity. The correlation diagram for PNS blockade was overlapped on physiological response. PNS activities decreased to near zero at halfway of exercise by spectral analysis. SNS activities rapidly increased when PNS activities near zero. The correlation diagram was useful for evaluation of cooperation between SA and AV node because it reflected ANS activity. It is indicated that the cooperation between SA and AV node will be evaluated with the correlation diagram and spectral analysis together.