1102results about How to "Eliminate negative effects" patented technology

Methods and apparatus for compensating the effects of display signal propagation delay in a display panel are disclosed. The apparatus comprises circuitry in addition to conventional display driver circuitry for delaying display line timing signals by an amount approximating the delay found in corresponding display lines. By delaying display line timing signals, for example in a column driver, by an time approximately equal the delay experienced in a corresponding row enable signal line, capacitors associated with the display pixels charge more fully resulting in a more vivid display image. Methods for compensating the effects of display signal propagation delay involve generating a plurality of delayed display timing signals and activating display lines in response to those delayed timing signals.

The invention relates to relates to a method for preparing a composition containing 1,3-di-unsaturated fatty acyl-2-saturated fatty acyl glyceryl ester, particularly containing 1,3-di-oleoyl-2-palmitoyl glyceryl ester (OPO), which comprises the steps of: carrying out random ester exchange on an ester rich in saturated fatty acid residue and an ester rich in unsaturated fatty acid residue serving as reaction substrates, and carrying out enzymatic oriented ester exchange on the reaction mixture and unsaturated fatty acid or unsaturated fatty acid ester. The invention also provides application of the composition to preparing formula milk powder for infant and preparing synthetic food for infant, and the formula milk powder for infant and the synthetic food for infant containing the composition.

The present invention relates to a plug-type connection for releasably connecting two bodies wherein the first body includes a first connection zone having a plurality of coaxially aligned first connection segments and the second body includes a plurality of coaxially aligned second connection segments. The first connection segment includes at least one segment with a non-circular cross-section and at least one segment having an axially tapering cross-section. The second connection segment includes at least one segment with a non-circular cross section sized and configured for rotatively engaging the non-circular cross section of the first connection segment and at least one segment sized and configured to mate with the at least one tapering section, wherein the tapered section of the first connection segment and the mating section of the second connection segment form an axially non-positive engagement for guiding the first body into engagement with the second body. The axially tapering cross-section of the first connection segment is preferably made from a deformable material so that the axially tapering cross section deforms when it mates with the second connection segment.

The invention discloses a multi-layer anomaly detection method based on network traffic. The invention is capable of detecting the small traffic attack behavior well with high detection accuracy, andmay adapt to different data sets. The invention comprises: firstly adopting a binary representation of symbol attributes in the data preprocessing stage to eliminate the negative influence of the traditional numerical size on the classification, and raising the attribute set of the data set to a relatively high dimension, so that the subsequent data classification effect is more accurate; then using the dimension reduction method to extract features and reduce the amount of data, so that the running speed is faster and the memory consumption is lower during the subsequent steps; subsequently,using the KNN outlier detection method and genetic algorithm combination method for data selection, so that different types of data are more balanced, each type of data is separated as far as possible, and the classification result is fairer; finally, using the constructed multi-layer classifier, thereby enabling more accurate identification of large-flow attacks and small-flow attacks.

A method and an apparatus for detecting gas concentration with infrared absorption characteristics have the function of automatic calibration. The function of automatic calibration is accomplished in such a manner that a reference chamber filled with CO2 gas of a known concentration is added in the apparatus; by switching the reference chamber in real-time or periodically into the detecting light path, the measured value of the concentration of CO2 gas in the reference chamber can be obtained; then by comparing the measured value with the standard value of known concentration of CO2 gas, the calibration factor is obtained; once finishing the calibration process, a detecting chamber is switched into the detecting light path so that a concentration of a gas can be detected accurately. In the apparatus of the present invention, the same detecting light path (e.g. the infrared light source, and the light filter, etc.), the same infrared light signal processing unit (e.g. the infrared sensor, the amplification circuit and the single-chip microcomputer system, etc.) are used for both the calibration process and the detection process. Therefore, the negative effect caused by difference of the characteristics of temperature drift of circuit components between different light paths in prior art can be eliminated, and the errors in the detected results by using the apparatus in the present invention is greatly reduced. In addition, the structure of the apparatus in the present invention is relatively simple, resulting in the lower production cost and no necessity for the manual maintenance.

The invention discloses a multi-person pose estimation method based on mask perceptual depth reinforcement learning. Firstly, a multi-person pose estimation model is constructed. The multi-person poseestimation model is composed of a detection network for acquiring a detection frame and a mask, a depth reinforcement learning network for improving the positioning accuracy, and a single-person poseestimation network. Then the multi-character pose estimation model is trained by training samples. During the test, the images to be detected are input into the trained multi-person pose estimation model to obtain the pose of all the detection frames of the images to be detected. The method of the invention introduces the mask information into the depth reinforcement learning network and the single-person attitude estimation network, improves the effects of the two stages, and solves the problems of gradient disappearance and gradient explosion by using the residual structure. The method of the invention is more competitive than other advanced multi-character posture estimation methods.

The invention discloses a semantic approximate query method for an RDF knowledge map. The offline stage of the invention comprises the following steps: firstly, the RDF knowledge map is divided into RDF knowledge maps according to the semantic locality characteristics of entities and predicates of the RDF knowledge map, and the divided knowledge maps are generated into trainable text corpus; secondly, context-sensitive semantic learning is performed on the text corpus using the text embedding model, and the semantic vectors of entities and predicates are obtained. In the on-line phase: firstly, the syntax of SPARQL query submitted by users is analyzed, and the semantics of the predicates is extended; secondly, an approximate query based on predicate semantic similarity is carried out froma given entity, and the semantic approximate query results are obtained. The method utilizes semantic locality features to carry out context-sensitive semantic learning on the RDF knowledge map, thereby supporting fuzzy query application of the RDF knowledge map, and returning approximate query results satisfying user query intent in real time.

The invention discloses a composite coating of diamond / W-C gradient structure, and a preparation method thereof. The composite coating is characterized in that a composite coating which takes a W-C gradient structure as a transition layer and takes a diamond coating as a wearable coating is formed on a WC-Co hard alloy; the preparation method comprises the steps as follows: the hard alloy is used as a sample; a surface layer WC is dipped in Murakami reagent so as to form a Co-rich layer; subsequently, pure tungsten is taken as target material and argon and carbonaceous gas are used as reaction gases to prepare the W-C gradient structure of different structures as the transition layer by a reaction sputtering method by adjusting the concentration of carbonaceous active gas in the reaction gas, thus preparing the diamond wearable coating by a chemical vapor deposition technique. The composite coating solves the problem of the bonding strength of the film / substrate and ensures the surface smoothness of the diamond film.

The invention discloses a network intrusion detection method. The network intrusion detection method includes: searching network data to construct a test network data set; performing feature extraction on the test network data set by utilizing a kernel principal component analysis method; constructing a training data set, putting the training data set into a support vector machine classifier for training; obtaining feature datasets, obtaining an optimal feature subset from the feature data set by using a genetic algorithm; utilizing a firefly swarm optimization algorithm to obtain the overalllocal optimal feature subset and the optimal support vector machine parameters from the optimal feature subset, processing the training data set according to the overall local optimal feature subset,and inputting the training data set into a support vector machine classifier for classification modeling to obtain a network intrusion detection model. According to the method, the simplicity and convenience of the algorithm are improved, abnormal data can be more effectively found from samples, the detection accuracy of network intrusion is effectively improved, the missing report rate and the false report rate are reduced, and the overall performance of network intrusion detection is improved.