6162466
AQ, Rough Sets, and Matroid Theory
In order to acquire knowledge from database, there have been proposed several methods of inductive learning, such as ID3 family and AQ family. These methods are applied to discover meaningful knowledge from large database, and their usefulness is ensured. However,since there has been no formal approach proposed to treat these methods, efficiency of each method is only compared empirically. In this paper, we introduce matroid theory and rough sets to construct a common framework for empirical machine learning methods which induce knowledge from databases whose patterns are described as the combination of attribute-value pairs. Combination of the concepts of rough sets and matroid theory gives us an excellent framework and enables us to understand the differences and the similarities of these methods clearly. Using this framework, we compare three methods, AQ, Pawlak’s Consistent Rules. The results shows that they generate bases of Matroid from attribute-value space and that their solutions are optimal to the classification of the training samples.
206639604
COBRA: Integration of Knowledge-Bases with Case-Databases in the Domain of Congenital Malformation
There have been developed many medical decision support systems, such as MYCIN since the end of 1970's [2]. One of the most important problems of these decision support systems is that their input interface is based on verbal information and that they cannot handle multi-data, which causes the following two problems. First, users have to know correctly the meaning of medical technical terms on the input screen. However, medical experts who majors in respiratory diseases do not know technical terms in neurology usually. Therefore it is hard even for medical experts to use a medical expert system, which makes them difficult to apply to real-world situations. Second, we often need non-verbal information, such as visual images in order to understand medical technical terms, since those technical terms are closely related to those kinds of data. For example, a neurological symptom "ptosis" can be explained in words as shown in [1]. However, even medical experts cannot easily understand several technical terms in the explanation. Thus, if we can use visual images then it may be easier to understand those terms. Interestingly, those problems are also closely related not only to practical use, but also medical education. Medical education also needs non-verbal information, and the way how to describe non-verbal information by using technical terms. For example, medical students do not exactly know about ptosis. In order to understand this symptom, we need a picture or a photograph which shows a typical case of ptosis. In other words, medical education can be viewed as a process which learns the relations between verbal information and non-verbal information. Therefore, these problems suggest that medical intelligent systems should deal with many different kinds of data for practical use. Actually, medical da ta
6820086
BioCichlid: central dogma-based 3D visualization system of time-course microarray data on a hierarchical biological network
SUMMARY
BioCichlid is a 3D visualization system of time-course microarray data on molecular networks, aiming at interpretation of gene expression data by transcriptional relationships based on the central dogma with physical and genetic interactions. BioCichlid visualizes both physical (protein) and genetic (regulatory) network layers, and provides animation of time-course gene expression data on the genetic network layer. Transcriptional regulations are represented to bridge the physical network (transcription factors) and genetic network (regulated genes) layers, thus integrating promoter analysis into the pathway mapping. BioCichlid enhances the interpretation of microarray data and allows for revealing the underlying mechanisms causing differential gene expressions.


AVAILABILITY
BioCichlid is freely available and can be accessed at http://newton.tmd.ac.jp/. Source codes for both biocichlid server and client are also available.
7846033
Economic Advantage of Pharmacogenomics - Clinical Trials with Genetic Information
The purpose of this study is to clarify the benefit and loss for the pharmaceutical companies when they adopt introducing pharmacogenomics in their clinical trials (in the following description, clinical trials by using pharmacogenomics is called "pgx clinical trial"), that is, when they use genetic information in their clinical trials. Particularly, the benefit for the pharmaceutical companies in terms of following two points is analyzed. 1. Development cost of new drug and period of clinical trial can be reduced because a clinical trial needs less subjects, 2. The new drug can be placed on the market earlier because the development period can be shortened. A survey conducted by Japan Pharmaceutical Manufacturers Association revealed that the pharmaceutical companies in Japan are interested in "pgx clinical trial". Specifically, 95% of the member companies (n=19) of the Association replied that the establishment of a guideline for pgx clinical trial by regulatory authorities are highly desirable. However, 65% of them (n=13) also replied that pgx clinical trial is difficult for the time being. It can be concluded that the pharmaceutical companies are positive about pgx clinical trial, but they cannot take a step towards it for several reasons: some of them may be worried their sales for non-responders will be reduced, poor understanding of pgx among the concerned parties, and not matured methodology of pgx clinical trial. This study shows that the advantage of pgx clinical trial outweighs its disadvantage. The sales may decrease because the drug is not used for non-responders, however, the number of subjects necessary for a clinical trial can be reduced, study period can be shortened and the drug can be marketed earlier. Furthermore, adverse events (AE) and adverse drug reactions (ADR) during the clinical trial and post-marketing phase can be markedly reduced. This represents a great benefit for the patients, pharmaceutical companies and the society as a whole.
42031107
Algebraic Specification of Empirical Inductive Learning Methods based on Rough Sets and Matroid Theory
In order to acquire knowledge from databases, there have been proposed several methods of inductive learning, such as ID3 family and AQ family. These methods are applied to discover meaningful knowledge from large databases, and their usefulness is ensured. However, since there has been no formal approach proposed to treat these methods, efficiency of each method is only compared empirically. In this paper, we introduce matroid theory and rough sets to construct a common framework for empirical machine learning methods which induce the combination of attribute-value pairs from databases. Combination of the concepts of rough sets and matroid theory gives us an excellent framework and enables us to understand the differences and the similarities between these methods clearly. In this paper, we compare three classical methods, AQ, Pawlak's Consistent Rules and ID3. The results show that there exists the differences in algebraic structure between the former two and the latter and that this causes the differences between AQ and ID3.
14789474
Automated Selection of Rule Induction Methods Based on Recursive Iteration of Resampling Methods and Multiple Statistical Testing
One of the most important problems in rule induction methods is how to estimate which method is the best to use in an applied domain. While some methods are useful in some domains, they are not useful in other domains. Therefore it is very difficult to choose one of these methods. For this purpose, we introduce multiple testing based on recursive iteration of resampling methods for rule-induction (MULT-RECITE-R). This method consists of four procedures, which includes the inner loop and the outer loop procedures. First, original training samples(S0) are randomly split into new training samples(S1) and test samples(T1) using a resampling scheme. Second, S1 are again split into training sample(S2) and training samples(T2) using the same resampling scheme. Rule induction methods are applied and predefined metrics are calculated. This second procedure, as the inner loop, is repeated for 10000 times. Then, third, rule induction methods are applied to S1, and the metrics calculated by T1 are compared with those by T2. If the metrics derived by T2 predicts those by T1, then we count it as a success. The second and third procedures, as the outer loop, are iterated for 10000 times. Finally, fourth, the overall results are interpreted, and the best method is selected if the resampling scheme performs well. In order to evaluate this system, we apply this MULT-RECITE-R method to three UCI databases. The results show that this method gives the best selection of estimation methods statistically.
19316869
Avoidance Ability of Redundant Mobile Manipulators During Hand Trajectory Tracking
A vapor generator in which a plurality of tubes are connected together and arranged to form at least a portion of the boundary walls of a gas-tight enclosure. Portions of the tubes are bent to form a plurality of openings extending through at least one of the boundary walls. Some of the bent tube portions extend around the openings in the plane of the wall, and others of the bent tube portions extend out of the plane of the wall. The tubes, including the bent portions, extend at an angle with respect to a horizontal plane for their entire lengths to enable the tubes to drain. A burner is associated with each opening to apply heat to the enclosure, and fluid is passed through the tubes to apply heat to the fluid.
31262490
Equipment Operation by Motion Recognition with Wearable Wireless Acceleration Sensor
This paper proposes new system architecture for equipment operation based on the motion recognition using a 3-axis acceleration sensor. The small sensor is attached to the wrist with a band and is worn as a wearable device so as not to disturb body motion. The motion of the arm is detected by the acceleration sensor, and data are transmitted to the PC by Bluetooth signals. It has a wide detection range compared to video methods because the Bluetooth radio system has omni-directional characteristics. The data are analyzed using a DP matching method in the PC and the templates stored in advance are compared. Each template data correspond to the equipment operation. The IR signal is transmitted based on the results of matching and this signal operates the equipment. A television and a room light are selected for the system demonstration, and it is confirmed that turn on/off of each piece of equipment, changing channels and volume alternation can be performed through body motion.
5444349
Threshold Correction of Document Image Binarization for Ruled-line Extraction
In this paper, a new threshold correction method for document image binarization that is forcused on ruled-line extraction is presented. This method enhances the binary image of a ruled line, which is often adversely influenced by adjacent text pixels or background noise.The threshold correction method consists of two submethods. One is a noise reduction method that is based on background determination, and the other is a threshold surface conversion method. Both these methods use the aspect of local straightness feature to distinguish ruled-line pixels from background pixels.
27278741
An e-mail environment with handwriting using the HandsDraw digital ink format
This paper proposes a handwriting-based e-mail environment system, including the HandsDraw format, whose facilities include the reading and writing of handwritten massages, their transmission and reception, annotations or comments by recipients, confirmation of the author and time of writing, and reproduction of handwriting. The system has a user interface which is friendly even to a beginner, and can handle more expressive massages on the Internet. The system is regarded as an advanced mobile communication terminal of the kind which has been fashionable recently. Considering the advantages and disadvantages of pen input, encircling (lasso) selection and a button interface are used for dialogue. Users' opinions (collected by questionnaires, on the Internet, and from laboratory use of the system for 2 1/2 years) confirm all of the functions of the system. Some respondents have suggested the conversion of handwritten characters to a type font (rather than sending them directly) by using the character-recognition facility in this system. © 2002 Wiley Periodicals, Inc. Syst Comp Jpn, 33(14): 101–109, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/scj.1180
46587618
Architecture of TMN-based integrated management system for SDH/PDH mixed large-scale transport network
For efficient and integrated network management of SDH/PDH mixed large-scale transport networks, KDD has developed a TMN-based integrated management system. This paper describes an architecture of the system and its implementation. The features of the architecture are: (1) to employ a distributed system configuration based on TMN multi-layered functional architecture, (2) to newly define an integrated management information model which unifies different management information models for many kinds of NEs (Network Elements) and which enables us to manage a network with mixed SDH and PDH hierarchies of, and (3) to introduce a new alarm correlation mechanism for high system performance.