Tomihisa Kamada

Bio: Tomihisa Kamada is an academic researcher from University of Tokyo. The author has contributed to research in topics: The Internet & Hot spot (computer programming). The author has an hindex of 20, co-authored 33 publications receiving 4037 citations. Previous affiliations of Tomihisa Kamada include Nippon Telegraph and Telephone & Sony Broadcast & Professional Research Laboratories.

Terminal having application update managing function, and application update managing program and system

Abstract: A basic information recording unit 122 stores version data in which the versions of a plurality of application programs stored in a portable information device is written. An update verifying unit 110 receives update status data indicating whether an update to the version of at least one of the plurality of application programs is available. An update identifying unit 112 refers to the update status data and identifies an application program assigned an older version number in comparison with the updated version. A display processor 114 displays a menu screen where a plurality of startup icons for the plurality of application programs are located, and changes the appearance of the startup icon for the application program identified by the update identifying unit 112 to indicate that an update to the version is available.

A simple method for computing general position in displaying three-dimensional objects

Abstract: In 3D graphics, the selection of the location of the center of projection (eye) is very important in order to obtain the pictures by which the original shapes of 3D objects can be comprehended easily. The eye position from which the picture of 3D objects with the maximum shape information is obtained is called the “general position”. In the current practice of making pictures, the most general eye position is determined in ad hoc ways, because it is very difficult to determine the view, foreseeing the resultant display image. In this paper, a simple method for computing the general position is presented. First the general position problem based on the line data is formulated as a maximin problem. Then the algorithms of computing the most general eye position by solving this maximin problem are presented. Some examples of performing these algorithms yielding satisfactory results are also presented.

Internet television device capable of selecting hot spots by the use operation buttons

Abstract: An Internet television device having a capability of connecting to the Internet. An HTML document received from a WEB server includes a definition of assigning operation buttons of a remote controller to hot spots, the definition containing button identifiers indicative of the operation buttons. An Internet television device interprets the received HTML document to develop an image on an image memory. During this interpretation, the button identifiers of operation buttons of the remote controller are recognized so as to create a button assignment table which correlates the recognized button identifiers with hot spots corresponding to anchor tags in the HTML document. The HTML document also includes display information as to which button is assigned to each hot spot. When a user presses an operation button corresponding to a desired hot spot on the display screen, the Internet television device recognizes which hot spot has been designated by referring to the button assignment table and then selects the hot spot. Thus, it is possible to select a desired hot spot on a WEB browser screen in such a manner as in the channel selection of the TV set.

Mobile information terminal device, storage server, and method for providing storage region

Abstract: In a storage server (9) on a network (6), there is retained a storage region (97) dedicated to the user of a mobile telephone (10). A software, requester to purchase through a sales server (12) by the user, is not transferred directly to the mobile telephone (10) of the user but is stored in the user-dedicated storage region (97). The user uses the software by downloading it from its dedicated storage region (97) to its mobile telephone (10).

The igraph software package for complex network research

Abstract: There is no other package around that satisfies all the following requirements: •Ability to handle large graphs efficiently •Embeddable into higher level environments (like R [6] or Python [7]) •Ability to be used for quick prototyping of new algorithms (impossible with “click & play” interfaces) •Platform-independent and open source igraph aims to satisfy all these requirements while possibly remaining easy to use in interactive mode as well.

Software survey: VOSviewer, a computer program for bibliometric mapping.

Abstract: We present VOSviewer, a freely available computer program that we have developed for constructing and viewing bibliometric maps. Unlike most computer programs that are used for bibliometric mapping, VOSviewer pays special attention to the graphical representation of bibliometric maps. The functionality of VOSviewer is especially useful for displaying large bibliometric maps in an easy-to-interpret way. The paper consists of three parts. In the first part, an overview of VOSviewer’s functionality for displaying bibliometric maps is provided. In the second part, the technical implementation of specific parts of the program is discussed. Finally, in the third part, VOSviewer’s ability to handle large maps is demonstrated by using the program to construct and display a co-citation map of 5,000 major scientific journals.

Graph drawing by force-directed placement

Abstract: SUMMARY We present a modification of the spring-embedder model of Eades [ Congresses Numerantium, 42, 149–160, (1984)] for drawing undirected graphs with straight edges. Our heuristic strives for uniform edge lengths, and we develop it in analogy to forces in natural systems, for a simple, elegant, conceptuallyintuitive, and efficient algorithm.

The Spread of Obesity in a Large Social Network over 32 Years

Abstract: Background The prevalence of obesity has increased substantially over the past 30 years. We performed a quantitative analysis of the nature and extent of the person-to-person spread of obesity as a possible factor contributing to the obesity epidemic. Methods We evaluated a densely interconnected social network of 12,067 people assessed repeatedly from 1971 to 2003 as part of the Framingham Heart Study. The bodymass index was available for all subjects. We used longitudinal statistical models to examine whether weight gain in one person was associated with weight gain in his or her friends, siblings, spouse, and neighbors. Results Discernible clusters of obese persons (body-mass index [the weight in kilograms divided by the square of the height in meters], ≥30) were present in the network at all time points, and the clusters extended to three degrees of separation. These clusters did not appear to be solely attributable to the selective formation of social ties among obese persons. A person’s chances of becoming obese increased by 57% (95% confidence interval [CI], 6 to 123) if he or she had a friend who became obese in a given interval. Among pairs of adult siblings, if one sibling became obese, the chance that the other would become obese increased by 40% (95% CI, 21 to 60). If one spouse became obese, the likelihood that the other spouse would become obese increased by 37% (95% CI, 7 to 73). These effects were not seen among neighbors in the immediate geographic location. Persons of the same sex had relatively greater influence on each other than those of the opposite sex. The spread of smoking cessation did not account for the spread of obesity in the network. Conclusions Network phenomena appear to be relevant to the biologic and behavioral trait of obesity, and obesity appears to spread through social ties. These findings have implications for clinical and public health interventions.

An automated method for finding molecular complexes in large protein interaction networks.

Abstract: Recent advances in proteomics technologies such as two-hybrid, phage display and mass spectrometry have enabled us to create a detailed map of biomolecular interaction networks. Initial mapping efforts have already produced a wealth of data. As the size of the interaction set increases, databases and computational methods will be required to store, visualize and analyze the information in order to effectively aid in knowledge discovery. This paper describes a novel graph theoretic clustering algorithm, "Molecular Complex Detection" (MCODE), that detects densely connected regions in large protein-protein interaction networks that may represent molecular complexes. The method is based on vertex weighting by local neighborhood density and outward traversal from a locally dense seed protein to isolate the dense regions according to given parameters. The algorithm has the advantage over other graph clustering methods of having a directed mode that allows fine-tuning of clusters of interest without considering the rest of the network and allows examination of cluster interconnectivity, which is relevant for protein networks. Protein interaction and complex information from the yeast Saccharomyces cerevisiae was used for evaluation. Dense regions of protein interaction networks can be found, based solely on connectivity data, many of which correspond to known protein complexes. The algorithm is not affected by a known high rate of false positives in data from high-throughput interaction techniques. The program is available from ftp://ftp.mshri.on.ca/pub/BIND/Tools/MCODE .