A morphable model for the synthesis of 3D faces

Proximity based systems and methods that are implemented on an electronic device are disclosed. The method includes sensing an object spaced away and in close proximity to the electronic device. The method also includes performing an action in the electronic device when an object is sensed.

Proximity detector in handheld device

A location reporting paging communication system comprising space satellites, ground stations and a remote receiving unit adapted to resolve a global position from signals transmitted from a communication transmitter. The subscriber in possession of the remote receiving unit updates the paging network with global positioning information. A caller paging a subscriber in possession of the remote receiving unit may request the global location of the remote receiving unit. The paging network could divulge or block such information from a caller depending on the requirements of the subscriber.

Location reporting satellite paging system with optional blocking of location reporting

The various methods and devices described herein relate to devices which, in at least certain embodiments, may include one or more sensors for providing data relating to user activity and at least one processor for causing the device to respond based on the user activity which was determined, at least in part, through the sensors. The response by the device may include a change of state of the device, and the response may be automatically performed after the user activity is determined.

Automated Response to and Sensing of User Activity in Portable Devices

Enhancements of and to cell phone operations are based in whole or in part on determining the location of the cell phone. Systems and methods select and determine locations or areas of importance or relevance, and based on that information and other programmed factors affect or alter the operations of the cell phone. While the systems and methods are illustrated by use of cell phone embodiments and applications, they are equally applicable to virtually any portable or mobile communication device, including for example, wireless laptop computers and PDAs.

Realtime, location-based cell phone enhancements, uses, and applications

A system and method of automatically transferring a call between telephones based on the distance between the two telephones is provided. First the proximity of a first telephone to a second telephone is determined. If the proximity is within a predetermined limit or threshold, calls directed to the first telephone are transferred to the second telephone. Security of the transfer may be ensured to prevent fraudulent use of the subscription of either telephone. Procedures are provided which permit any the above-mentioned steps to be performed either at the level of the individual telephones involved in the transfer, or by an element of the network, such as an MSC or HLR.

System and method for automatically transferring a call from a first telephone to a designated telephone in close proximity

Smart city is an important application of the recent technology — Internet of Things (IoT). IoT enables wide range of physical objects and environments to be monitored in fine detail by using low cost, low power sensing and communication technologies. While there has been growing interest in the IoT for smart cities, there have been few systematic studies that can demonstrate weather practical insights can be extracted from the real time IoT data using advanced data analytics techniques such as anomaly detection. We carried out a case study of smart environment based on real time data collected by the city of Aarhus, Denmark. We analyzed and find the levels of different air pollution elements to detect the unhealthy or anomalous locations based on Air Quality Index (AQI). Machine learning framework namely neural network, Neuro-fuzzy method and Support Vector Machines for both binary and multi class problems has been used for anomalous location detection form pollution database. Simulation results using MATLAB show that Machine learning techniques are reliable in terms of accuracy and calculation time for smart environment.

An anomaly detection in smart cities modeled as wireless sensor network

Model-Free Predictive Control of Nonlinear Processes Based on Reinforcement Learning

The use of wearable recorders for long-term monitoring of physiological parameters has increased in the last few years. The ambulatory electrocardiogram (A-ECG) signals of five healthy subjects with four body movements or physical activities (PA)—left arm up down, right arm up down, waist twisting and walking—have been recorded using a wearable ECG recorder. The classification of these four PAs has been performed using neuro-fuzzy classifier (NFC) and support vector machines (SVM). The PA classification is based on the distinct, time-frequency features of the extracted motion artifacts contained in recorded A-ECG signals. The motion artifacts in A-ECG signals have been separated first by the discrete wavelet transform (DWT) and the time–frequency features of these motion artifacts have then been extracted using the Gabor transform. The Gabor energy feature vectors have been fed to the NFC and SVM classifiers. Both the classifiers have achieved a PA classification accuracy of over 95% for all subjects.

Physical activities recognition from ambulatory ECG signals using neuro-fuzzy classifiers and support vector machines

Edge detection is forefront of image processing algorithms. There are problems associated with different edge detectors. Thresholding is critical problem in edge detection. The paper represents three different methods of fuzzy based thresholding and resulted adaptive threshold is used in edge detection algorithm. Simulation results shows fuzzy thresholding based edge detection gives better results than conventional methods.

Hitesh Shah

Papers

System and method for automatically transferring a call from a first telephone to a designated telephone in close proximity

An anomaly detection in smart cities modeled as wireless sensor network

Model-Free Predictive Control of Nonlinear Processes Based on Reinforcement Learning

Physical activities recognition from ambulatory ECG signals using neuro-fuzzy classifiers and support vector machines

Edge detection techniques using fuzzy thresholding