Patents | Tuhin Sharma

Cognitively inducing sleep cycles by leveraging wearables

Tue, 28 Nov 2017 00:00:00 +0000

Description

The present disclosure relates to sleep cycles, and more specifically to optimizing sleep quality by inducing sleep stages.

Sleep cycles consist of two main types of sleep, rapid-eye-movement (REM) sleep and non-rapid-eye-movement (NREM) sleep. NREM sleep is composed of three distinct stages: N1, N2, and N3. The sleep cycle begins with NREM sleep, starting with N1, then transitioning to N2, then to N3, and then to a second N2, then to REM. A complete sleep cycle ends with REM. NREM sleep and REM sleep continue to cycle throughout the course of sleep.

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Mitigation of perishable product waste through promotion recommendation

Mon, 20 Nov 2017 00:00:00 +0000

Description

The present invention relates generally to the field of computer data modeling, and more particularly to model generation of the effects of external events on consumer-packaged goods.

Perishable items are often put on clearance sale when it nears expiry date in order to clear inventory, maximize profits, or minimize loss of product. Typically, products are discarded if not sold be the expiration date. Promotions, such as putting items on “sale” or “clearance,” are used to avoid having to discard the expired items. It may be advantageous to determine an optimal promotion time frame or window to maximize profits and minimize waste.

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Enabling wearables to cognitively alter notifications and improve sleep cycles

Thu, 19 Oct 2017 00:00:00 +0000

Description

According to one embodiment, a method, computer system, and computer program product for cognitively adjusting a notification alert delivery time are provided. The embodiment may include receiving a message notification from a sender. The embodiment may also include determining an importance of the received message notification based on a plurality of notification attributes and a plurality of person attributes that are each associated with the received message notification. The embodiment may further include, in response to determining to alert a user of the received message notification based on the determined importance, identifying a current user sleep stage. The embodiment may also include, in response to determining the current user sleep stage will minimally impact the user, transmitting the received message notification to a user device

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Use of Asset and Enterprise Data to Predict Asset Personality Attributes

Thu, 01 Sep 2016 00:00:00 +0000

Description

The present invention relates generally to the field of resource management, and more particularly to the use of operator (herein referred to as asset or operator interchangeably) data to predict an operator’s psychometric profile, such as the big five personality traits (i.e., those traits recognized by most psychologists as the five basic dimensions of personality) of openness, conscientiousness, extraversion, agreeableness, and neuroticism, and the use of the predicted profile in operator assignment and management.

One of the key roles of leaders, managers, supervisors, directors, etc. (herein collectively referred to as managers) is to ensure that the employees, contractors, operators, etc. (herein collectively referred to as assets or operators) that are placed on tasks and in groups match the needs of those tasks and groups as best as the manager can determine. A better match generally means better, more efficient productivity, and a positive outcome for the team and the company as a whole. Because of this, managers are very motivated to determine the correct operator be placed where the operator would do the most good, such as on a particular piece of machinery, equipment, apparatus, hardware, or inanimate asset ( herein collectively referred to as inanimate asset). However, often it is difficult to determine which operator would be a good fit until the position has already been filled and the task is underway. Any ability to decrease this uncertainty, and to increase the chances that the chosen operator is a good fit and a good choice for the position, would be considered a positive for most of those in leadership roles.

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User experience using social and financial information

Thu, 11 Feb 2016 00:00:00 +0000

Description

At least one financial information for a user is received. A machine learning model is determined. The machine learning model is determined based on the user. A personality of the user is determined based on the machine learning model and the at least one financial information for the user. A recommendation is provided based on the determined personality of the user.

Embodiments of the present invention include a method, computer program product, and system for providing a recommendation using social and financial information. In one embodiment, at least one financial information for a user is received. A machine learning model is determined. The machine learning model is determined based on the user. A personality of the user is determined based on the machine learning model and the at least one financial information for the user. A recommendation is provided based on the determined personality of the user.

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