Nippon Telegraph and Telephone Corporation

Tadasu Uchiyama

Noboru Sonehara

Akira Hiraiwa

Masaru Miyamoto

Masaaki Fukumoto

Shigeru Oikawa

Kazuhiko Shinozawa

Yukio Tokunaga

A method of extracting information from a structured document includes the steps of assigning a partial tree identifier inclusive of a tag identifier to a selected partial tree wherein the tag identifier includes a name of a tag corresponding to a root of the selected partial tree, a name of at least one format attribute of the tag, and a value of the at least one format attribute, arranging names of format attributes in a predetermined order in the tag identifier if the at least one format attribute of the tag includes two or more format attributes, and identifying a partial tree having a partial tree identifier identical to the partial tree identifier of the selected partial tree from a list of partial tree identifiers of partial trees that exist in the structured document after updating thereof.

Extraction of information from structured documents

A full-time wearable input device, method for the same is provided, wherein the immediate accessibility is improved without sacrificing the operational integrity, and information can be inputted anytime, anywhere, and immediately. The full-time wearable input device comprises a detector for detecting the shock generated at the time of striking the fingertips against a physical surface, and an analyzer for analyzing the timing at which the fingertips strike the aforementioned physical surface and determining the input information based on the detection signal detected by the aforementioned detector. As the above-mentioned detector, a shock sensor, acceleration sensor, sound sensor and myoelectric sensor can be used. The input information is then determined based on the change in the shock, acceleration, sound and/or myoelectric potential as detected by the sensors which are worn on each finger, wrist, or arm.

Full-time wearable information managing device and method for the same

The purpose of the present invention is to provide a handwriting information detecting method and apparatus for the same, in which a user can choose any handwriting tool such as a pen or a pencil, and when the user writes with the tool, the handwriting information can be detected. The handwriting information detecting method of the present invention comprises steps of detecting a motion of a writing tool, held by a writing tool holder comprising at least one acceleration sensor, based on at least one acceleration signal output from the at least one acceleration sensor when the writing tool is grasped by fingers; and recognizing handwriting information of a character or a figure written by the writing tool according to the detected motion thereof, and outputting the information. Preferably, the step of detecting a motion of a writing tool further comprises steps of detecting pressure acting on the tip of a finger which grasps the writing tool; and judging the motion of the writing tool according to the detected pressure. The handwriting information detecting apparatus of the present invention comprises a writing tool holder for detachably holding a writing tool; at least one acceleration sensor, provided at the writing tool holder, for detecting acceleration of the writing tool which is grasped by fingers; and a handwriting information recognition circuit for recognizing information of handwriting performed by the writing tool based on the output of the at least one acceleration sensor.

Handwritting information detecting method and apparatus detachably

The present invention provides a handwritten character recognition method in which neighboring points are connected by straight lines and the segments in-between points are then interpolated using broken lines. Each broken line is equally divided into k segments, and a number is assigned to each division point therein according to the time sequence of the respective point. A (k+1)N.times.N (N is the number of strokes) matrix P consisting of the elements of row (k+1)(n-1)+1 and column k(m-1)+j comprising angle .OMEGA. formed by the straight line connecting division point i of stroke n and division point j of stroke m and the straight line connecting division point i of stroke n and division point j+1 of stroke m, is then calculated. The distance di between handwritten character Cx and matrix Qi (i=1-M) formed in the same manner from M templates corresponding to characters possessing the same number of strokes as character Cx, is calculated as the sum of the squares of each element of matrix P-Qi. The character Cz corresponding to the template Qz with the smallest distance dz is then selected as the recognition result.

Character recognition method

An apparatus is presented for providing a short time range forecast with relative high accuracy from weather radar images of cloud reflection data by incorporating physical properties of cloud in the forecasting method. The method consists of defining a plurality of lattice points on a radar image, and multiplying the reflection data from a group of neighboring lattice points obtained at a specific past point in time with selected coefficients. The products of multiplication are summed, and transformed into image data by specific function based on the properties relating to cloud. Squared errors of the difference between the computational reflection data and the observed reflection data are iterated to a value below a predetermined threshold value to select the coefficients, and these coefficients are used to provide forecasting of reflection data at a specific future point in time.

Rainfall, snowfall forecast apparatus and method

A neural network system for identifying forecasting, and controlling a non-linear flow on a physical system network, in which each branch between nodes in the physical system network is divided by a plurality of division points; a flow at each of the division points and a terminal point of each branch is calculated according to neural network model parameters specifying connections among the division points and the terminal point in a neural network model; an actual flow is measured at the terminal point of said each branch; an error of the calculated flow at the terminal point with respect to the measured actual flow at the terminal point is calculated; the neural network model parameters are adjusted to minimize the calculated error; and system dynamics parameters specifying dynamics of the physical system are determined according to the adjusted neural network model parameters. In addition, a target function to be optimized is calculated in terms of flows at terminal points of branches as a function of a control parameter specifying connecting and disconnecting of connections among branches at each node; and connections among branches at each node are connected/disconnected to optimize the calculated target function.

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Yokosuka, Japan

Tadasu Uchiyama