Patents by Inventor Aveek N. Chatterjee

Aveek N. Chatterjee has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 10418505
    Abstract: A method including installing solar pods at varying heights on a tower, where a size of each of the solar pods is inversely related its installation height on the tower, each of the solar pods including a transparent ovoid enclosure symmetrical about an axis, and a reflector and a solar cell both contained within the transparent ovoid enclosure, the solar cell positioned at a common focal point of the reflector such that substantially all light reflected by the reflector is directed at the solar cell.
    Type: Grant
    Filed: May 18, 2017
    Date of Patent: September 17, 2019
    Assignee: International Business Machines Corporation
    Inventors: Aveek N. Chatterjee, Kota V. R. M. Murali, Ninad D. Sathaye, Rajesh Sathiyanarayanan
  • Patent number: 10102477
    Abstract: A method, computer program product, and system for generating flavor profile models are provided. An alpha flavor model is determined. An electrode signal is transmitted to a taste simulator based on the alpha flavor model. User feedback is received. A variance between the alpha flavor model and the user feedback is determined. The variance is compared to a predetermined threshold. In response to determining that the variance is greater than the predetermined threshold, a beta flavor model is generated.
    Type: Grant
    Filed: May 26, 2016
    Date of Patent: October 16, 2018
    Assignee: International Business Machines Corporation
    Inventors: Siddique M. Adoni, Aveek N. Chatterjee, Dhandapani Shanmugam
  • Patent number: 10095979
    Abstract: A method, computer program product, and system for generating flavor profile models are provided. An alpha flavor model is determined. An electrode signal is transmitted to a taste simulator based on the alpha flavor model. User feedback is received. A variance between the alpha flavor model and the user feedback is determined. The variance is compared to a predetermined threshold. In response to determining that the variance is greater than the predetermined threshold, a beta flavor model is generated.
    Type: Grant
    Filed: July 6, 2015
    Date of Patent: October 9, 2018
    Assignee: International Business Machines Corporation
    Inventors: Siddique M. Adoni, Aveek N. Chatterjee, Dhandapani Shanmugam
  • Publication number: 20170256664
    Abstract: A method including installing solar pods at varying heights on a tower, where a size of each of the solar pods is inversely related its installation height on the tower, each of the solar pods including a transparent ovoid enclosure symmetrical about an axis, and a reflector and a solar cell both contained within the transparent ovoid enclosure, the solar cell positioned at a common focal point of the reflector such that substantially all light reflected by the reflector is directed at the solar cell.
    Type: Application
    Filed: May 18, 2017
    Publication date: September 7, 2017
    Inventors: Aveek N. Chatterjee, Kota V.R.M. Murali, Ninad D. Sathaye, Rajesh Sathiyanarayanan
  • Patent number: 9705021
    Abstract: A solar pod system, comprising of an oval transparent enclosure. The oval transparent enclosure encapsulates a circular paraboloidal reflector mounted on solar cell. The solar cell extends over the circular parabolic reflector to place the focus of the paraboloidal reflector on the solar cell, whereby the solar cell receives light reflected by the circular parabolic reflector.
    Type: Grant
    Filed: October 30, 2014
    Date of Patent: July 11, 2017
    Assignee: International Business Machines Corporation
    Inventors: Aveek N. Chatterjee, Kota V. R. M. Murali, Ninad D. Sathaye, Rajesh Sathiyanarayanan
  • Patent number: 9654414
    Abstract: A method for scheduling cost efficient data center load distribution is described. The method includes receiving a task to be performed by computing resources within a set of data centers. The method further includes determining, all available data centers to perform the task. The method further includes determining lowest computing cost task schedule from available data centers. The method further includes scheduling the task to be completed at an available data center with the lowest cost computing.
    Type: Grant
    Filed: September 18, 2014
    Date of Patent: May 16, 2017
    Assignee: International Business Machines Corporation
    Inventors: Aveek N. Chatterjee, Hendrik F. Hamann, Shankar Km, Siyuan Lu, Kota V. R. M. Murali
  • Publication number: 20170011145
    Abstract: A method, computer program product, and system for generating flavor profile models are provided. An alpha flavor model is determined. An electrode signal is transmitted to a taste simulator based on the alpha flavor model. User feedback is received. A variance between the alpha flavor model and the user feedback is determined. The variance is compared to a predetermined threshold. In response to determining that the variance is greater than the predetermined threshold, a beta flavor model is generated.
    Type: Application
    Filed: May 26, 2016
    Publication date: January 12, 2017
    Inventors: Siddique M. Adoni, Aveek N. Chatterjee, Dhandapani Shanmugam
  • Publication number: 20170011164
    Abstract: A method, computer program product, and system for generating flavor profile models are provided. An alpha flavor model is determined. An electrode signal is transmitted to a taste simulator based on the alpha flavor model. User feedback is received. A variance between the alpha flavor model and the user feedback is determined. The variance is compared to a predetermined threshold. In response to determining that the variance is greater than the predetermined threshold, a beta flavor model is generated.
    Type: Application
    Filed: July 6, 2015
    Publication date: January 12, 2017
    Inventors: Siddique M. Adoni, Aveek N. Chatterjee, Dhandapani Shanmugam
  • Patent number: 9530092
    Abstract: In a method for training an artificial neural network based algorithm designed to monitor a first device, a processor receives a first data. A processor determines a first service action recommendation for a first device using the received first data and an artificial neural network (ANN) algorithm. A processor causes a second device to provide haptic feedback using the received first data. A processor receives a second service action recommendation for the first device based on the haptic feedback. A processor adjusts at least one parameter of the ANN algorithm such that the ANN algorithm determines a third service action recommendation for the first device using the received first data, wherein the third service action recommendation is equivalent to the second service action recommendation.
    Type: Grant
    Filed: November 10, 2015
    Date of Patent: December 27, 2016
    Assignee: International Business Machines Corporation
    Inventors: Aveek N. Chatterjee, Siddique M. Adoni, Dhandapani Shanmugam
  • Patent number: 9385087
    Abstract: Various embodiments include resistor structures. Particular embodiments include a resistor structure having multiple oxide layers, at least one of which includes a modified oxide. The modified oxide can aid in controlling the thermal capacitance and the thermal time constant of the resistor structure, or the thermal dissipation within the resistor structure.
    Type: Grant
    Filed: October 18, 2013
    Date of Patent: July 5, 2016
    Assignee: GLOBALFOUNDRIES INC.
    Inventors: Debarsi Chakraborty, Aveek N. Chatterjee
  • Publication number: 20160126393
    Abstract: A solar pod system, comprising of an oval transparent enclosure. The oval transparent enclosure encapsulates a circular paraboloidal reflector mounted on solar cell. The solar cell extends over the circular parabolic reflector to place the focus of the paraboloidal reflector on the solar cell, whereby the solar cell receives light reflected by the circular parabolic reflector.
    Type: Application
    Filed: October 30, 2014
    Publication date: May 5, 2016
    Inventors: Aveek N. Chatterjee, Kota V. R. M. Murali, Ninad D. Sathaye, Rajesh Sathiyanarayanan
  • Publication number: 20160087909
    Abstract: A method for scheduling cost efficient data center load distribution is described. The method includes receiving a task to be performed by computing resources within a set of data centers. The method further includes determining, all available data centers to perform the task. The method further includes determining lowest computing cost task schedule from available data centers. The method further includes scheduling the task to be completed at an available data center with the lowest cost computing.
    Type: Application
    Filed: September 18, 2014
    Publication date: March 24, 2016
    Inventors: Aveek N. Chatterjee, Hendrik F. Hamann, Shankar Km, Siyuan Lu, Kota V. R. M. Murali
  • Publication number: 20160063373
    Abstract: In a method for training an artificial neural network based algorithm designed to monitor a first device, a processor receives a first data. A processor determines a first service action recommendation for a first device using the received first data and an artificial neural network (ANN) algorithm. A processor causes a second device to provide haptic feedback using the received first data. A processor receives a second service action recommendation for the first device based on the haptic feedback. A processor adjusts at least one parameter of the ANN algorithm such that the ANN algorithm determines a third service action recommendation for the first device using the received first data, wherein the third service action recommendation is equivalent to the second service action recommendation.
    Type: Application
    Filed: November 10, 2015
    Publication date: March 3, 2016
    Inventors: Aveek N. Chatterjee, Siddique M. Adoni, Dhandapani Shanmugam
  • Patent number: 9230208
    Abstract: In a method for training an artificial neural network based algorithm designed to monitor a first device, a processor receives a first data. A processor determines a first service action recommendation for a first device using the received first data and an artificial neural network (ANN) algorithm. A processor causes a second device to provide haptic feedback using the received first data. A processor receives a second service action recommendation for the first device based on the haptic feedback. A processor adjusts at least one parameter of the ANN algorithm such that the ANN algorithm determines a third service action recommendation for the first device using the received first data, wherein the third service action recommendation is equivalent to the second service action recommendation.
    Type: Grant
    Filed: December 18, 2013
    Date of Patent: January 5, 2016
    Assignee: International Business Machines Corporation
    Inventors: Aveek N. Chatterjee, Siddique M. Adoni, Dhandapani Shanmugam
  • Patent number: 9218565
    Abstract: In a method for training an artificial neural network based algorithm designed to monitor a first device, a processor receives a first data. A processor determines a first service action recommendation for a first device using the received first data and an artificial neural network (ANN) algorithm. A processor causes a second device to provide haptic feedback using the received first data. A processor receives a second service action recommendation for the first device based on the haptic feedback. A processor adjusts at least one parameter of the ANN algorithm such that the ANN algorithm determines a third service action recommendation for the first device using the received first data, wherein the third service action recommendation is equivalent to the second service action recommendation.
    Type: Grant
    Filed: June 19, 2014
    Date of Patent: December 22, 2015
    Assignee: International Business Machines Corporation
    Inventors: Aveek N. Chatterjee, Siddique M. Adoni, Dhandapani Shanmugam
  • Publication number: 20150170024
    Abstract: In a method for training an artificial neural network based algorithm designed to monitor a first device, a processor receives a first data. A processor determines a first service action recommendation for a first device using the received first data and an artificial neural network (ANN) algorithm. A processor causes a second device to provide haptic feedback using the received first data. A processor receives a second service action recommendation for the first device based on the haptic feedback. A processor adjusts at least one parameter of the ANN algorithm such that the ANN algorithm determines a third service action recommendation for the first device using the received first data, wherein the third service action recommendation is equivalent to the second service action recommendation.
    Type: Application
    Filed: June 19, 2014
    Publication date: June 18, 2015
    Inventors: Aveek N. Chatterjee, Siddique M. Adoni, Dhandapani Shanmugam
  • Publication number: 20150170023
    Abstract: In a method for training an artificial neural network based algorithm designed to monitor a first device, a processor receives a first data. A processor determines a first service action recommendation for a first device using the received first data and an artificial neural network (ANN) algorithm. A processor causes a second device to provide haptic feedback using the received first data. A processor receives a second service action recommendation for the first device based on the haptic feedback. A processor adjusts at least one parameter of the ANN algorithm such that the ANN algorithm determines a third service action recommendation for the first device using the received first data, wherein the third service action recommendation is equivalent to the second service action recommendation.
    Type: Application
    Filed: December 18, 2013
    Publication date: June 18, 2015
    Applicant: International Business Machines Corporation
    Inventors: Aveek N. Chatterjee, Siddique M. Adoni, Dhandapani Shanmugam
  • Publication number: 20150108608
    Abstract: Various embodiments include resistor structures. Particular embodiments include a resistor structure having multiple oxide layers, at least one of which includes a modified oxide. The modified oxide can aid in controlling the thermal capacitance and the thermal time constant of the resistor structure, or the thermal dissipation within the resistor structure.
    Type: Application
    Filed: October 18, 2013
    Publication date: April 23, 2015
    Applicant: International Business Machines Corporation
    Inventors: Debarsi Chakraborty, Aveek N. Chatterjee