International Business Machines Corporation

Industry Technology Research Institute (itri)

Industrial Technology Research Institute

Hung-Yang Chang

Jun-Jang Jeng

Yi-Chang Molly Wang

Liang-Jie Zhang

Hui Lei

Liangzhao Zeng

Li-Ju Chen

Xinxin Zhu

Kuo-shu Luo

Chia-Wen Ho

Pawan Raghunath Chowdhary

Shyh-Kwei Chen

Santhosh Babu Kumaran

Tian-Jy Chao

Pei-Yun S Hsueh

James V Codella

Lih-Guong Jang

John Youssef Sayah

Subhro Das

Sreeram Ramakrishnan

Nien-Chu Wu

Tian Hao

Haifei Li

Yu Long

Joe Lu

Ning Li

Jenny S Li

Fei Liu

Qiqing Christine Ouyang

Seshadri Subbanna

Christian Alexander Lang

Yajuan Wang

Fenno F Heath, Iii

Jen-Yao Chung

Yashodhara M Patnaik

David Wayne Harrison

Ching-Hua Chen

Kun Lin

Chang Shu

Michael Dikun

Xinyu Hu

Embodiments of the present invention are directed to physiological sensing in a wearable device. Aspects include generating a multi-faceted feedback for a user. Generating the multi-faceted feedback includes generating a baseline physiological sampling schedule for a user, generating a quality-aware feedback of the user, generating a user-state-aware feedback of the user, and generating a context-aware feedback of the user. Aspects also include generating an adjusted physiological sampling schedule for the user based at least in part upon the multi-faceted feedback.

Continuous physiological sensing in energy-constrained wearables

An aspect includes querying, by a processor, a plurality of model data from a distributed data source based at least in part on one or more user characteristics. A plurality of sensor data is gathered associated with a condition of a user. A policy is generated including an end goal and one or more sub-goals based at least in part on the model data and the sensor data. The policy is iteratively adapted based at least in part on one or more detected changes in the sensor data collected over a period of time to adjust at least one of the one or more sub-goals. The policy and the one or more sub-goals are provided to the user.

Adaptive adjustment using sensor data and distributed data

A model-driven and QoS-aware infrastructure facilitates the scalable composition of Web services in highly dynamic environments. An exception management framework supports two modes of exception management for business processes, providing a novel policy-driven approach to exception management implemented in the system infrastructure. Exception management is implemented in the system infrastructure, with exception handling policies supplied by individual business processes. Using the exception management framework, developers define exception policies in a declarative manner. Before a business process is executed, the service composition middleware integrates the exception policies with normal business logic to generate a complete process schema. This policy driven-approach can significantly reduce the development time of business processes through its separation of the development of the business logic and the exception handling policies.

Apparatus and method for policy-driven business process exception handling

Disclosed is a computer-implemented method for recommending booths-to-visit to a user, comprising the following steps: accessing a user record, wherein the user record includes data indicative of booths which a user corresponding to the user record has visited in an exhibition; determining similarity level between records in a history database and the user record, the records in the history database including data indicative of the booths visited by previous visitors in the exhibition; selecting several of the records according to the determined similarity level; identifying shared ones of the selected records; determining the booths in the shared ones of the selected records not yet visited by the user; adding the determined booths to a candidate list; and presenting at least one of the booths in the candidate list to the user.

Computer-implemented method for recommending booths-to-visit

Disclosed is a computer-implemented method for recommending booths-to-visit to a user, comprising the following steps: accessing a user record, wherein the user record includes data indicative of booths which a user corresponding to the user record has visited in an exhibition; determining similarity level between records in a history database and the user record, the records in the history database including data indicative of the booths visited by previous visitors in the exhibition; selecting several of the records according to the determined similarity level; determining the booths in the all of the selected records not yet visited by the user; adding the determined booths to a candidate list; and presenting at least one of the booths in the candidate list to the user.

Technical solutions are described that address correcting input time-series data provided for analysis and predictions. An example computer-implemented method includes receiving, by a processor, a time-series data input by a user. The computer-implemented method also includes computing, by the processor, a first plurality of predicted values based on the time-series data input by the user; computing, by the processor, a second plurality of predicted values by. The computer-implemented method also includes determining estimated time-series data based on the time-series data input by the user. The computer-implemented method also includes computing the second plurality of predicted values based on the estimated time-series data. The computer-implemented method also includes determining, by the processor, a defect in the time-series data input by the user based on a distribution of a plurality of differences between respective values from the first plurality of predicted values and the second plurality of predicted values.

Input data correction

Disclosed is a computer-implemented method for recommending booths-to-visit to a user, comprising the following steps: accessing a user record, wherein the user record includes data indicative of booths which a user corresponding to the user record has visited in an exhibition; determining similarity level between records in a history database and the user record, the records in the history database including data indicative of the booths visited by previous visitors in the exhibition; selecting one of the records according to the determined similarity level; determining the booths in the selected record not yet visited by the user; obtaining the user's current location in the exhibition; determining a target booth, from the booths not yet visited by the user, by referring to the current location and a map database; and sending to the user a message indicative of the target booth.

Embodiments of the present invention are directed to a computer-implemented method for stress monitoring. Methods include receiving, by a processor, a plurality of user stress labels corresponding to a plurality of events. Methods also include determining an individualized stress profile based at least in part upon the user stress labels. Methods also include receiving heart rate sensor data from a wearable device. Methods also include extracting a cardiovascular feature from the heart rate sensor data. Methods also include determining a stress index based at least in part upon the individualized stress profile and the cardiovascular feature. Methods also include outputting the stress index.

Real-time continuous stress monitoring using wearable devices

A method and system for tracking eye recovery. The method includes: receiving eye data from an eyewear, wherein the eye data includes images acquired by an image capturing device in the eyewear; analyzing the eye data to determine an eye recovery status, wherein the analyzing is carried out by comparing the eye data to an initial set of eye conditions; and providing a notification of the eye recovery status.

Tracking eye recovery

Disclosed is a computer-implemented method for recommending booths-to-visit to a user. The method includes: accessing a map database of an exhibition; accessing a history database that stores a plurality of records indicative of booths visited by a previous visitor in the exhibition; accessing a user record that includes data indicative of the booths which the user has visited; determining similarity level between each record in the history database and the user record, selecting one of the records according to the determined similarity level so as for the selected record to function as a reference record, usable to determine the booths not yet visited by the user; obtaining the user's current location in the exhibition, and determining a target booth, from the booths not yet visited by the user, by referring to the current location and the map database; and sending to the user a message indicative of the target booth.

A microfluidic system-on-a-chip includes signal processing, light generation and detection, and fluid handling functions formed on a single substrate. The disclosed integrated system has a smaller footprint than device structures where individual components are manufactured separately and then assembled. Moreover, the integrated system obviates alignment challenges associated with conventionally packaged architecture.

Integrated microfluidics system

An architecture, system, and method are provided for a commitment loop solution for on demand business activity management. A Business Performance Management (BPM) loop includes nodes each relating to different tasks for processing performance management trigger data generated by a business entity in real time. The beginning or sensing element of the loop is triggered by a token (representing a business event from a business process). The ending or executing element provides a business action to be implemented by the business entity. The token is passed from node to node sequentially in a particular order around the loop. Processing of the data represented by the token is governed by policies, which can be changed dynamically and follow a life cycle.

Business performance management (BPM) system and method having a physical star architecture, data processing rings and BPM loops

An architecture, system, and method are provided for a commitment loop solution for on demand business activity management. A Business Performance Management (BPM) loop is defined as a set of nodes each relating to different tasks for processing performance management trigger data generated by a business entity in real time, where the beginning or sensing element of the loop is triggered by a token (representing a business event from a business process) and the ending or executing element provides a business action to be implemented by the business entity. The token is passed from node to node sequentially in a particular order around the loop. Processing of the data represented by the token is governed by policies, which can be changed dynamically and follow a life cycle. On demand business activity management of larger aggregates of business entities (i.e. enterprises and value chains) is achieved by extending this architecture by building upon the BPM loops of the component entities to form a BPM net, adding nodes as necessary. This architecture, system and method can be implemented at multiple levels of granularity from operational or tactical business activities to enterprise wide strategic activities.

Method and apparatus of on demand business activity management using business performance management loops

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Scarsdale, NY, United States of America

Hung-Yang Chang