Motorola Corporation

Other

Marc Alan Newman

William Chunhung Yip

James Brian Piket

Gerald V Piosenka

Michael C Murdock

Provided is a key lock operable for locking and unlocking a latch control mechanism. The key lock includes a key collar with a front face, an outer cylindrical surface, and a longitudinally extending key slot. A center collar is concentrically disposed about the key collar such that an inner cylindrical surface of the center collar is fit to and rotatable on the outer cylindrical surface of the key collar. A series of cylindrical rotating pins are disposed in the center collar, each rotating pin having a notch with a key ID surface configured to engage one of a corresponding series of ID cut surfaces of a key when the key is inserted in the key slot and rotated to a key verification position, thereby rotationally orienting each pin at a respective ID position.

Rotating pin key lock

A method and system simplifies and accomplishes the programming of a PED (12), such as a cellular telephone (22), via the use of a personal computer (PC). The present invention includes software (52, 54) within the PC (14) for providing a graphical user interface (GUI) to the user for ease and simplicity of selecting various programming features and settings associated with the cellular telephone to be programmed. The software further includes a translator (56) for translating these user selected features/settings into specific key depresses to be sent to the cellular telephone, via software and hardware interfaces (58, 18, 20), for accomplishing the programming of such features/settings. Additionally, the software includes the capability to monitor the data being displayed on the cellular telephone because such data may be required to accomplish various programming features.

Method and system for programming a cellular phone

A method for processing patent text (99) in a computer (200) including identifying boundaries of parts of patent text (100), loading at least one of the parts of the patent text into a working memory (102), analyzing at least one of the parts of the patent text (104), and reporting results (106) to a user (202). Alphanumeric drawing data can also be compared to patent text (100). The method can be coupled to work with a word processor program (208). The method can recognize and report (106 and 708) on claim dependency (400, 402, 404), specific characteristics (704) of patent text (99), and patent errors based on legal standards, practice standards, and Patent and Trademark Office standards, or even user preferences (702, 704, 706).

Method for syntactic and semantic analysis of patent text and drawings

An adapter (10) for a cellular telephone includes a first coupling apparatus (21) disposed on a first surface (30) of the adapter (10). The first coupling apparatus (21) is for engaging coupling apparatus disposed on a rear surface of the cellular telephone. The adapter (10) also includes an earpiece (40) coupled to a side (33) of the adapter (10) and a second coupling apparatus (23, 24) disposed on a second surface (32) of the adapter (10). The second coupling apparatus (23, 24) engages coupling apparatus disposed on a power source. The earpiece (40) comprises a speaker electrically coupled to connections on a connector for tapping an external audio output of a cellular telephone. The speaker (40) is constrained to maintain a position within one-half centimeter of the side (33) of the adapter (10). An outer shell of the earpiece (40) is connected to the side (33) of the adapter (10) and protrudes therefrom by a distance of less than a centimeter.

Cellular telephone security adapter and method

A post-processing method for an optical character recognition (OCR) method for combining different OCR engines to identify and resolve characters and attributes of the characters that are erroneously recognized by multiple optical character recognition engines. The characters can originate from many different types of character environments. OCR engine outputs are synchronized in order to detect matches and mismatches between said OCR engine outputs by using synchronization heuristics. The mismatches are resolved using resolution heuristics and neural networks. The resolution heuristics and neural networks are based on observing many different conventional OCR engines in different character environments to find what specific OCR engine correctly identifies a certain character having particular attributes. The results are encoded into the resolution heuristics and neural networks to create an optimal OCR post-processing solution.

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Mesa, AZ, United States of America

Marc Alan Newman