A method is described in which a topic similarity score, a product similarity score and an operating system similarity score between an original post and each one of a plurality of previous posts are determined; an overall similarity score of the each one of the plurality of previous posts based on the topic similarity score, the product similarity score and the operating system similarity score is determined; and a recommendation of a top K number of the plurality of previous posts based on the overall similarity score of the each one of the plurality of previous posts is sent to a display device.

An information analysis apparatus includes: a weight assigning unit that assigns a weight to each of a plurality of items based on an action taken by a user who has viewed a sales content on which the plurality of items to be recommended are posted; a selection unit that selects a plurality of pairs in which two items are selected among the plurality of items placed in the sales content and associated with each other; and an evaluation unit that evaluates a characteristic based on characteristic information indicating a property of each of the two items selected as a pair by the selection unit and the weight assigned by the weight assigning unit to the two items.

A system and methods for designing single-stage hardware sorting blocks, and further using the single-stage hardware sorting blocks to reduce the number of stages in multistage sorting processes, or to define multiway merge sorting networks.

A method of selecting, in hardware logic, an i.sup.th largest or a p.sup.th smallest number from a set of n m-bit numbers is described. The method is performed iteratively and in the r.sup.th iteration, the method comprises: summing an (m−r).sup.th bit from each of the m-bit numbers to generate a summation result and comparing the summation result to a threshold value. Depending upon the outcome of the comparison, the r.sup.th bit of the selected number is determined and output and additionally the (m−r−1).sup.th bit of each of the m-bit numbers is selectively updated based on the outcome of the comparison and the value of the (m−r).sup.th bit in the m-bit number. In a first iteration, a most significant bit from each of the m-bit numbers is summed and each subsequent iteration sums bits occupying successive bit positions in their respective numbers.

The subject matter presently claimed relates to a data quality management system and method whereby a first data point comprising a first obtained data and a first assigned value from is received from a first data repository, a first quality score as well as a first storable data of the first data point is determined and/or stored. A second data point comprising a second obtained data, which is similar to the first obtained data according to a predefined similarity measure, and a second assigned value is received from the second data repository, a second quality score as well as a second storable data is determined from the second data point and/or stored and a second transmittable data, determined from the second data point and/or the second quality score is transmitted to the first data repository, causing the first data repository to re-evaluate the first assigned value.

A memory-centric neural network system and operating method thereof includes: a processing unit; semiconductor memory devices coupled to the processing unit, the semiconductor memory devices containing instructions executed by the processing unit; a weight matrix constructed with rows and columns of memory cells, inputs of the memory cells of a same row being connected to one of axons, outputs of the memory cells of a same column being connected to one of neurons; timestamp registers registering timestamps of the axons and the neurons; and a lookup table containing adjusting values indexed in accordance with the timestamps, wherein the processing unit updates the weight matrix in accordance with the adjusting values.

An electronic system includes a mapping circuit configured to receive input samples of a dataset within a defined range of values. The mapping circuit is configured to perform comparisons that compare each input sample to each of a plurality of comparison values selected from the defined range of values. For each comparison, the mapping circuit generates an indication value specifying whether the input sample used in the comparison is greater than or equal to the comparison value used in the comparison. The system includes an adder circuit configured to generate a sum of the indication values for each comparison value and a memory configured to maintain counts corresponding to the comparison values. The counts are updated by the respective sums. The system includes a threshold detection circuit configured to determine, for the dataset, a threshold value or threshold range based on the counts read from the memory.

An inclination of a weighing apparatus is automatically detected by the apparatus itself while preventing an increase in the number of components. In order to achieve the object described above, a weighing apparatus includes a weight sensor, a built-in weight to be loaded on the weight sensor, an adding/removing unit for adding/removing the built-in weight, a memory storing a theoretical value of the built-in weight, and an arithmetic processing unit, wherein the arithmetic processing unit includes an inclination angle computing unit configured to obtain an apparatus inclination angle from an arc-cosine of a weighing value of the built-in weight and the theoretical value of the built-in weight.

The example embodiments are directed toward improvements in predicting an ideal audience size. In an embodiment, a method is disclosed comprising receiving a set of users associated with an object attribute; selecting samples from the set of users; computing hit rates for the samples, a respective hit rate in the hit rates computed by calculating a total number of users in a respective sample associated with an interaction associated with the object attribute; and selecting a recommended sample from the samples, the recommended sample comprising a sample having an associated hit rate that meets a preconfigured hit rate threshold.

A system for dynamically mitigating resonance in a transport refrigeration unit (TRU) during a mission, having: a TRU controller configured for operating a TRU engine during the mission according to an operational baseline, and while operating the TRU engine, contemporaneously performing steps including: obtaining a first set of data that comprises real time measurements from one or more accelerometers installed in the TRU; converting the real measurements to a second set of data that comprises real time shock and vibration data; processing the second set of data in a control loop to determine an updated operational baseline that avoids resonance detected in the first set of data; and operating the TRU engine according to the updated operational baseline.