Delivery of medical multimedia contents through the TCP/IP network using RealSystem

We developed a low cost, user-friendly multimedia delivery system, to provide medical lectures saved as multimedia contents to persons engaged in medicine. This system was created using the RealSystem package with the TCP/IP network. Users can review lectures and medical meeting presentations with video and audio through the Internet, whenever convenient. Each medical source of video and slide has been clearly displayed on a screen. Members of medical associations or medical students can easily review the most interesting parts of these files. This system is being used efficiently in distance learning and aids the diffusion of the latest information and technology to busy physicians and medical students.     

A fast and compact elimination method of empty elements from a double‐array structure

A double‐array is a well‐known data structure to implement the trie. However, the space efficiency of the double‐array degrades with the number of key deletions because the double‐array keeps empty elements produced by the key deletion. This paper presents a fast and compact elimination method of empty elements using properties of the trie nodes that have no siblings. The present elimination method is implemented by C language. From simulation results for large sets of keys, the present elimination method is about 30–330 times faster than the conventional elimination method and maintains high space efficiency. Copyright © 2003 John Wiley & Sons, Ltd.     

RUNA: a multimodal command language for home robot users

This article describes a multimodal command language for home robot users, and a robot system which interprets users’ messages in the language through microphones, visual and tactile sensors, and control buttons. The command language comprises a set of grammar rules, a lexicon, and nonverbal events detected in hand gestures, readings of tactile sensors attached to the robots, and buttons on the controllers in the users’ hands. Prototype humanoid systems which immediately execute commands in the language are also presented, along with preliminary experiments of faceto-face interactions and teleoperations. Subjects unfamiliar with the language were able to command humanoids and complete their tasks with brief documents at hand, given a short demonstration beforehand. The command understanding system operating on PCs responded to multimodal commands without significant delay. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Construction of a robot control system which understands a voice and pointing actions

This research was aimed at making a robot that can go and get an object designated by the user. We produced a robot control system that uses pointing and voice control. This control system is composed of two systems. One system is the object instruction system that uses pointing, and the other is the object instruction system that uses voice. The approximate position of a designated object is recognized by the object instruction system that uses pointing, and information about the object and instructions about the operation are conveyed by the object instruction system that uses voice. This time, the object instruction system that uses pointing has been designed and verified as the first step. A calculation resource to calculate the approximate position of the designated object is obtained when the user points directly at the object. A robot can be moved around a designated object by using this system. The object instruction system that uses voice will be constructed in future work.     

Success rates in a multimodal command language for home robot users

This article considers the success rates in a multimodal command language for home robot users. In the command language, the user specifies action types and action parameter values to direct robots in multiple modes such as speech, touch, and gesture. The success rates of commands in the language can be estimated by user evaluations in several ways. This article presents some user evaluation methods, as well as results from recent studies on command success rates. The results show that the language enables users without much training to command home robots at success rates as high as 88%–100%. It is also shown that multimodal commands combining speech and button-press actions included fewer words and were significantly more successful than single-modal spoken commands.     

The effects of ce additions on the high temperature corrosion behavior of Fe-30Cr-5Al alloy in 80 Pet Na2SO4-20 Pct NaCI molten salt

High temperature corrosion tests in 80 pct Na₂SO₄-20 pct NaCI were made on five Fe-30 wt pct Cr-5 wt pct Al alloys containing various amounts of cerium up to 0.68 pct. After the corrosion tests, samples were examined metallographically and by X-ray diffraction and X-ray microanalysis. It was found that the surface scale formed on each sample decreased in thickness as the Ce content increased. Electron probe microanalyses suggest that this retarding behavior is related to the early formation of a Ce-induced protective scale of α-Al₂O₃. The role of Ce in promoting the formation of the α-Al₂O₃ scale is discussed.     

Illumination normalization with time-dependent intrinsic images for video surveillance

Variation in illumination conditions caused by weather, time of day, etc., makes the task difficult when building video surveillance systems of real world scenes. Especially, cast shadows produce troublesome effects, typically for object tracking from a fixed viewpoint, since it yields appearance variations of objects depending on whether they are inside or outside the shadow. In this paper, we handle such appearance variations by removing shadows in the image sequence. This can be considered as a preprocessing stage which leads to robust video surveillance. To achieve this, we propose a framework based on the idea of intrinsic images. Unlike previous methods of deriving intrinsic images, we derive time-varying reflectance images and corresponding illumination images from a sequence of images instead of assuming a single reflectance image. Using obtained illumination images, we normalize the input image sequence in terms of incident lighting distribution to eliminate shadowing effects. We also propose an illumination normalization scheme which can potentially run in real time, utilizing the illumination eigenspace, which captures the illumination variation due to weather, time of day, etc., and a shadow interpolation method based on shadow hulls. This paper describes the theory of the framework with simulation results and shows its effectiveness with object tracking results on real scene data sets.     

Hard X-Ray Microscope With Submicrometer Spatial Resolution

A high-resolution hard x-ray microscope is described. This system is capable of detecting line features as small as 0.6 µm in width, and resolving line pairs 1.2-µm wide and 1.2-µm apart. Three types of two-dimensional image detectors are discussed and compared for use with hard x rays in high resolution. Principles of x-ray image magnification are discussed based on x-ray optics and diffraction physics. Examples of applications are shown in microradiography with fiber reinforced composite materials (SiC in Ti₃Al Nb) and in diffraction imaging (topography) with device patterns on a silicon single crystal. High-resolution tomography has now become a reality.     

Studying re-opened bugs in open source software

Bug fixing accounts for a large amount of the software maintenance resources. Generally, bugs are reported, fixed, verified and closed. However, in some cases bugs have to be re-opened. Re-opened bugs increase maintenance costs, degrade the overall user-perceived quality of the software and lead to unnecessary rework by busy practitioners. In this paper, we study and predict re-opened bugs through a case study on three large open source projects—namely Eclipse, Apache and OpenOffice. We structure our study along four dimensions: (1) the work habits dimension (e.g., the weekday on which the bug was initially closed), (2) the bug report dimension (e.g., the component in which the bug was found) (3) the bug fix dimension (e.g., the amount of time it took to perform the initial fix) and (4) the team dimension (e.g., the experience of the bug fixer). We build decision trees using the aforementioned factors that aim to predict re-opened bugs. We perform top node analysis to determine which factors are the most important indicators of whether or not a bug will be re-opened. Our study shows that the comment text and last status of the bug when it is initially closed are the most important factors related to whether or not a bug will be re-opened. Using a combination of these dimensions, we can build explainable prediction models that can achieve a precision between 52.1–78.6 % and a recall in the range of 70.5–94.1 % when predicting whether a bug will be re-opened. We find that the factors that best indicate which bugs might be re-opened vary based on the project. The comment text is the most important factor for the Eclipse and OpenOffice projects, while the last status is the most important one for Apache. These factors should be closely examined in order to reduce maintenance cost due to re-opened bugs.     

Fuzzy Conditional Probability Relations and their Applications in Fuzzy Information Systems

In our real-world applications, data may be imprecise in which levels or degrees of preciseness of data are intuitively different. In this case, fuzzy set expressions are considered as an alternative to represent the imprecise data. In general, the degree of similarity relationship between two fuzzy (imprecise) data in real-world applications may not necessarily be symmetric or transitive. In order to provide such a degree of similarity between two fuzzy data, we introduced the fuzzy conditional probability relation. The concept of a fuzzy conditional probability relation may be considered as a concrete example of weak similarity relation which in turn is a special type of fuzzy binary relation generalizing similarity relation. Two important applications concerning the application of Knowledge Discovery and Data Mining (KDD) in the presence of a fuzzy data table (usually called fuzzy information system), namely removing redundant objects and recognizing partial or total dependency of (domain) attributes, are considered induced by the fuzzy conditional probability relation. Here, the fuzzy information system contains precise as well as imprecise data (fuzzy values) about objects of interest characterized by some attributes. Related to the dependency of attributes, we introduce the fuzzy functional dependency that satisfies Armstrongs Axioms. In addition, we also discuss some interesting applications such as approximate data reduction and projection, approximate data querying and approximate joining in order to extend the query system.