Bin Lin Yu

6356213, Mar 12, 2002

May 31, 2000

09/583601

Dawei Huang - Brisbane, AU
Bin Yu - Summit NJ

Lucent Technologies Inc. - Murray Hill NJ

H03M 700

341 60, 37524014, 375245

A lossless encoding methodology is described based on residual coding techniques and using a modified Least Mean Squares methodology to develop a predictor for a signal to be encoded, and a residual as the difference between the signal and its predicted value. After the residual for an input signal segment is obtained according to the method of the invention, that method is again applied to the residual value process to develop a second predictor, from which a second residual value is obtained. The method is then applied for at least one further iteration to the most recently obtained residual value process to develop a third predictor for the signal to be encoded. A single prediction value is then selected as a statistical representative of those multiple predictor values. The residual value to be used for encoding the input signal increment is determined as the difference between the signal value and the selected predictor value.

6785240, Aug 31, 2004

Jun 2, 2000

09/585738

Jin Cao - Edison NJ
R. Drew Davis - Piscataway NJ
Scott Alan Vander Wiel - Fanwood NJ
Bin Yu - Berkeley CA

Lucent Technologies Inc. - Murray Hill NJ

H04J 116

370238, 370252

In many packetized communication networks, it is not feasible to obtain exact counts of traffic (OD counts) between specific origin-destination node pairs, because the link counts that are readily obtainable at router interfaces are aggregated indiscriminately over OD pairs. The best that can be done is to make a probabilistic inference concerning the OD counts from the observed link counts. Such an inference relies upon a known linear relationship between observed link counts and unknown OD counts, and a statistical model describing how the values of the OD and link counts are probabilistically distributed. Disclosed is an improved method for making such inferences. The disclosed method takes explicit account of past data when forming a current estimate of the OD counts. As a consequence, behavior that evolves in time is described with improved accuracy and smoothness.

6827840, Dec 7, 2004

Jun 13, 2002

10/170903

Kalle Levon - New York NY
Bin Yu - Brooklyn NY
Yanxiu Zhou - Brooklyn NY

Polytechnic University - Brooklyn NY

G01N 27327

205787, 205775

Enantiomeric resolution is realized by combining an electrochemical method with ligand exchange (LE) in a novel electrochemical method named chiral ligand exchange potentiometry. Chiral selector ligands preferentially recognize certain enantiomers and undergo ligand exchange with the enantiomeric labile coordination complexes to form diastereoisomeric complexes. These complexes can form in solution and be recognized by an unmodified electrode, or they can be immobilized on the surface of a modified electrode (chiral sensor) incorporated with the chiral selector ligand by polysiloxane monolayer immobilization (PMI). Considerable stereoselectivity occurs in the formation of these diastereoisomeric complexes, and their net charges (Nernst factors) are different, thus enabling enantiomers to be distinguished by potentiometric electrodes without any pre-separation processes.

20040058380, Mar 25, 2004

Sep 12, 2002

10/242590

Kalle Levon - New York NY, US
Yanxiu Zhou - Brooklyn NY, US
Bin Yu - Brooklyn NY, US

G01N033/53
C12P019/46
C12M001/34

435/007100, 435/287200, 205/777500

Surface-molecularly imprinted sensors were fabricated for detecting ionic molecules. Target molecules are recognized by the combination of a hydrophobic interaction with the imprinted polymer layer to provide specificity and an electrostatic interaction to provide sensitivity Coupling surface imprinting techniques with an electrochemical detection method, such as potentiometry, allows specific recognition of target molecules and translation of the recognition event into an output signal by the sensor.

20040161861, Aug 19, 2004

Nov 21, 2003

10/719688

Kalle Levon - New York NY, US
Olga Tarasenko - Brooklyn NY, US
Bin Yu - West Hartford CT, US

G01N033/543

436/518000

A glycoconjugate sensor specific to a target biological entity may be fabricated by coating a support surface with polymers appended with carbohydrates. The carbohydrates appended to the polymers may be chosen by (i) identifying the surface glycoconjugates of a target biological entity and (ii) selecting corresponding carbohydrates that may specifically bind with the identified TAMPs, such as glycoconjugates. An ELISA platform may be used as the glycoconjugate sensor for detecting specific carbohydrate binding of the sensor to spores.