Abstract: In one embodiment, the present disclosure is directed to a bathroom mirror lighting system comprising a mirror, a light source, a sensor, and a control circuit operably coupled to the light source and the sensor. The control circuit receives a sensor signal from the sensor indicative of at least one of a user's distance from the sensor, a user's position, a user's posture, a motion of the user towards or away from the sensor, or a task being performed by the user. The control circuit then transmits a control signal to the light source causing the light source to alter its light output based on the sensor signal from the sensor.

Abstract: In one embodiment, the present disclosure is directed to a bathroom mirror lighting system comprising a mirror, a light source, a sensor, and a control circuit operably coupled to the light source and the sensor. The control circuit receives a sensor signal from the sensor indicative of at least one of a user's distance from the sensor, a user's position, a user's posture, a motion of the user towards or away from the sensor, or a task being performed by the user. The control circuit then transmits a control signal to the light source causing the light source to alter its light output based on the sensor signal from the sensor.

Abstract: A health care provider (HCP) engagement engine is disclosed. The HCP engagement engine facilitates effective communication between pharmaceutical sales representatives (medical reps) and HCPs by generating, using machine learning algorithms, messages for the medical reps to send to HCPs. The recommended messages may be sent over a network and may include email messages, text messages, or online chat messages. The recommended messages may be drafted entirely by the engagement engine or may be drafted as addenda to messages already used by the medical reps. The HCP engagement engine uses historical data on actions performed by the HCPs and medical reps, as well as data collected from historical message recommendation events, in order to produce message recommendations.

Abstract: A method for identifying a pattern of a load cycle includes: performing statistics on a daily load of a system based on smart meter data; generating a curve of the daily load of the system according to the statistics on the daily load of the system; acquiring a result of clustering curves of loads of typical days by applying shape-based time sequence clustering analysis using the curve of the daily load of the system; and identifying a pattern of a load cycle according to the result of clustering the curves of the loads of the typical days.

Abstract: A method for identifying a pattern of a load cycle includes: performing statistics on a daily load of a system based on smart meter data; generating a curve of the daily load of the system according to the statistics on the daily load of the system; acquiring a result of clustering curves of loads of typical days by applying shape-based time sequence clustering analysis using the curve of the daily load of the system; and identifying a pattern of a load cycle according to the result of clustering the curves of the loads of the typical days.

Abstract: According to a computer implemented method and system for matching user-generated text content, users “freely” specify content by means of fed-in texts which are matched automatically, according to rules in the embodiment. An embodiment of the invention allows customers to specify what items or services to request or offer by adding, to the “MyHaves” or “MyWants” selection criteria, using typed-in descriptions. Traditionally, for the purpose of matching supplies and demands, the specification of an individual's “wants” and “haves” is done by selecting options that are predefined by, or hard-coded into, the system's “drop-down menu”—rather than allowing customers to freely define what they want or have.

Abstract: According to a computer implemented approach for expeditious resource re-allocation in a network, customers specify what items or services to request or offer by adding to the “MyHaves” or “MyWants” selection criteria. According to the method, a customer requests an item or service by adding it to his/her “MyWants” in any of the following three ways: using a single click, searching and then adding, or feeding in user-defined-inputs. Similarly, a customer declares to offer an item or service by adding it to his/her “MyHaves” in any of the three aforementioned ways. The system algorithm of an embodiment “crawls” to find matches between the “MyHaves” of offerers and the “MyWants” of requesters, paying attention to and giving priority to the proximity and social network rules in the system. When a match is found, the system automatically triggers an email that is sent to the offerer, notifying him/her that a fellow customer wants what the offerer-customer has.