48 results about "Preference index" patented technology

The invention provides a testing device and a testing method for testing environmental preference behaviors of fishes. The device is characterized in that water inlet pipes with a flow regulator and water outlet pipes with a flow regulator are respectively installed at the two ends of a water trough, one ends of the water inlet pipes are communicated with a pressure-bearing water tank, flow conditioning meshes are respectively installed at the communicating ports of the water inlet pipes which are communicated with the water channel, upper flow guide baffles are installed between the water inlet pipes and the water outlet pipes to form flow guide channels, isolating nets are installed at the front ends of the water inlet pipes and the water outlet pipes, and the pressure-bearing water tank is connected with a variable-frequency water pump and a variable-frequency regulator. The method comprises the steps of 1) preparation before testing; 2) testing and correction of the testing device; 3) testing of preference behaviors of fishes; 4) testing data acquisition and preference index calculation; 5) maintenance and cleaning of the device. The testing device and the testing method for testing the environmental preference behaviors of the fishes can realize researches on the preference behaviors under various environmental factors such as flowing speed, river bed materials and illumination according to different environmental factors which are distributed in an experimental area.

A management module registers a request to convert code from a first code set to a second code set, identifies a code set converter (CSC), determines whether a most recently used CSC is the identified CSC and, in response to determining that the most recently used CSC is not the identified CSC, locates a user-preferred CSC pool comprising a subset of locally stored CSCs each corresponding to a preference index. The management module, in response to determining that the identified CSC is located within the user-preferred CSC pool, searches the user-preferred CSC pool for the identified CSC, loads the identified CSC, initiates the identified CSC that converts the code from the first code set to the second code set, modifies usage data for the identified CSC, and orders the user-preferred CSC pool based on a preference index for each CSC stored in the CSC pool.

The invention provides a broadcasting and television program recommendation system and method. The method includes the steps: inputting an object to be recommended, an audience preference index and an audience time period; storing program playing information as a program data source; storing audience information as an audience data source; calling the program data source and the audience data source and calculating the audience preference index of each user to form an audience preference matrix; calculating a connection relation value between the users according to the audience preference matrix, taking each user as a node and building a path between two users to form a connection network when the connection relation value between the users is larger than a set threshold value; determining credibility between the users according to the node and the path; determining the recommendation level of different users for different programs according to credibility and audience preference; selecting a set number of users according to the sequence of credibility from high to low, selecting a set number of programs according to the sequence of the recommendation level of the set number of users from high to low, and generating a program list of each user.

The invention discloses a mobile user tag based personalized food recommendation method. The method comprises the following steps that a user-restaurant location preference index is got; a restaurant-tag preference index is got, and a restaurant-tag preference vector is obtained; a user-tag preference index is got, and a user-tag preference vector is obtained; according to the restaurant-tag preference vector and the user-tag preference vector, a user-restaurant preference index is got; according to the user-restaurant preference index, the similarity of users is got; according to the similarity of the users, a predicted preference index of a target user to a target restaurant is got; according to the user-restaurant location preference index and the predicted preference index of the target user to the target restaurant, a mean absolute deviation MAEua of the target user ua is got, and therefore recommending is carried out. The mobile user tag based personalized food recommendation method has the advantages that by combining the user, the target of a merchant and the position, the personalized food recommending is carried out, the recommending quality is improved, and the recommending speed is increased.

In an embodiment, the disclosure provides a light source comprising at least one solid state light emitter. The light source, in operation, emits substantially white light having a Lighting Preference Index (LPI) of at least about 105, and this emission from the light source comprises a UV-violet flux of at least about 1%. Use of the lamps, light sources, and methods of the present disclosure may afford the ability to display linens and clothing under energy-efficient LED-based illumination, and may impart an effect to (especially white) clothing, that makes them look cleaner than under illumination by prior art LED lamps.

According to some embodiments, a composite light source includes at least one blue light source having a peak wavelength in the range of about 400 nanometer (nm) to about 460 nm; at least one LAG phosphor; at least one narrow red down-converter; and wherein the composite light source has a Lighting Preference Index (LPI) of at least 120. Numerous other aspects are provided.

The invention provides a set-top box random switching construction method based on user preferences. The method comprises the following steps: 1, initially setting equal preference indexes of a user specific to each channel, and setting unit time T; 2, counting the number of channels watched by the user according to the set unit time T; 3, reading the watching statistical data of the each watched channel, and constructing a random standby channel set; 4, generating a random number from the constructed frequency set, wherein a channel number corresponding to the random number indicates a randomly-switched channel. Through adoption of the method, channels can be generated randomly according to the watching habits and preferences of a user, and favorite channels of the user can be selected easily at a high hit rate.