Kenichi J Tomita

US Patent:

7108111, Sep 19, 2006

Filed:

Oct 25, 2004

Appl. No.:

10/972709

Inventors:

Kenichi Tomita - Williamsville NY, US

Assignee:

Enidine Incorporated - Orchard Park NY

International Classification:

F16F 9/18

US Classification:

188378

Abstract:

A shock and vibration isolator that includes a double acting mechanical spring assembly that is mounted to act in parallel with a fluid or liquid spring assembly. The mechanical spring is arranged to provide a first spring rate over a first displacement range and a second spring rate over a further second displacement range. The liquid spring is connected to an accumulator by control circuitry that is under the control of a microprocessor to release stored energy which combines with that of the mechanical spring to rapidly dissipate the input G forces to a level sufficient to protect a substructure.

US Patent:

20060201759, Sep 14, 2006

Filed:

Mar 11, 2005

Appl. No.:

11/078104

Inventors:

Gerald Spyche - South Wales NY, US
Kenichi Tomita - Williamsville NY, US

Assignee:

Enidine, Inc. - Orchard Park NY

International Classification:

F16D 51/60

US Classification:

188136000

Abstract:

A cabinet for reducing the G-loading upon a delicate instrument produced by shock and vibratory forces. The cabinet includes an inner frame and an outer frame that are co-joined by a series of horizontal isolators and double acting isolator or shock absorber assemblies.

US Patent:

60497939, Apr 11, 2000

Filed:

Nov 13, 1997

Appl. No.:

8/970050

Inventors:

Kenichi Tomita - Williamsville NY

International Classification:

G06N 302
G06N 500

US Classification:

706 17

Abstract:

A system for building an artificial neural network is provided which precisely defines the network's structure of artificial neurons, and non-iteratively determines the synapse-weights and hard limiter threshold of each artificial neuron of the network. The system includes a computer for analyzing input data, which represents patterns of different classes of signals, to generate one or more data points in two or three dimensions representative of the signals in each of the different classes. A distribution of the data points is visualized on a map on an output device coupled to the computer. The data points are clustered on the map into clusters in accordance with the classes associated with the data points, and the map is then partitioned into regions by defining linear boundaries between clusters. The artificial neural network is configured in accordance with the data points, clusters, boundaries, and regions, such that each boundary represents a different artificial neuron of the artificial neural network, and the geometric relationship of the regions on the map to the classes defines the logic connectivity of the artificial neurons. The synaptic weights and threshold of each artificial neuron in the network are graphically determined based on the data points of the map.

US Patent:

63247941, Dec 4, 2001

Filed:

Nov 12, 1999

Appl. No.:

9/439882

Inventors:

R. Leon Clinard - Paris IL
Scott Taylor - Amherst NY
Kenichi Tomita - Williamsville NY
Benjamin T. Houghton - Buffalo NY

Assignee:

Enidine, Inc.

International Classification:

E04B 198

US Classification:

521671

Abstract:

Apparatus is disclosed for protecting a structural object from the potentially harmful effects of a cyclic event such as an earthquake or high wind loads. A fluid spring is employed to stiffen the structural object and absorb kinetic energy stored by the spring. Fluid from the spring is exchanged with an accumulator where kinetic energy is dissipated as heat. A flow circuit regulates the exchange of fluid between the spring chamber and the accumulator chamber under controlled conditions to absorb the harmful effects of high external loads and to release the structural object when a high shock load is experienced.