263 results about "Sequence optimization" patented technology

Methods of improving the kinetics of bimolecular interactions where reactants are present in low concentrations are provided. Methods of pre-amplifying one or more oligonucleotides using high concentration universal primers are provided. Methods of improving the error rate in oligonucleotide and / or polynucleotide syntheses are also provided. Methods for sequence optimization and oligonucleotides design are further provided.

An improved gene sequence optimization method, the systematic optimization method, is described for boosting the recombinant expression of genes in bacteria, yeast, insect and mammalian cells. This general method takes into account of multiple, preferably most or all, of the parameters and factors affecting protein expression including codon usage, tRNA usage, GC-content, ribosome binding sequences, promoter, 5′-UTR, ORF and 3′-UTR sequences of the genes to improve and optimize the gene sequences to boost the protein expression of the genes in bacteria, yeast, insect and mammalian cells. In particular, the invention relates to a system and a method for sequence optimization for improved recombinant protein expression using a particle swarm optimization algorithm. The improved systematic optimization method can be incorporated into a software for more efficient optimization.

An implantable medical device is connected to a multipolar LV lead and an implantable sensor. The sensor signal from the sensor is used to identify a time point of mitral valve closure for a cardiac cycle when a ventricular pulse generator generates pacing pulses that are applied to the electrodes of the multipolar LV lead according to a pacing sequence. A time interval processor determines the time interval from onset of LV activation to the time point of mitral valve closure. This procedure is repeated for multiple different pacing sequences of a sequence set. The pacing sequence that resulted in shortest time interval is then selected by a selector as the currently optimal pacing sequence for the patient.

Method, apparatus, and computer program products are provided for optimizing a stacking sequence for a composite laminate having multiple zones to reduce the number or length of internal ply edges in the composite laminate with the most design rule compliant sequences. Once the number and location of the zones and the number of plies having different properties required for each zone have been determined for the composite laminate, a master zone is generated. Advantageously, the property of the plies may be fiber orientation, though alternative properties such as material may be considered when determining the number of required plies. The master zone notionally includes the maximum number of plies having a respective property required by any one zone, and the plies of the master zone are sequenced using a predefined series of design rules. The plies of each zone are then arranged based upon the stacking sequence of the master zone. A transformation matrix, a second predefined series of design rules, and a weighted solid / void differential may be used when arranging the plies of each zone based upon the stacking sequence of the master zone.

The present invention provides an order sequencing optimization method for logistics. The process of the method includes the following steps that: since the same type of commodities may be stored in a plurality of different containers, containers from which corresponding commodities in orders should be taken out are determined according to the expiration dates of the commodities in the orders, the number of remaining commodities in the containers where the commodities are located or the distances of the containers before order sequencing optimization is performed; and the orders of the commodities of which the containers are determined are optimally sequenced. According to the order sequencing optimization method for logistics of the invention, an evolutionary computation optimization method is adopted to optimally sequence the orders, so that the orders of the same commodities can be arranged at adjacent positions as much as possible, and therefore, commodities which have taken out can be repeatedly utilized, and the problem of low efficiency caused by frequent transport of the commodities can be avoided; and a constructed learning group concept is utilized to expand the search range of the algorithm, so that optimization calculation can be prevented from being trapped in local optimum, and convergence precision is greatly increased. With the order sequencing optimization method for logistics of the invention adopted, the optimal commodity picking efficiency of the commodities in the orders in a logistics process can be realized.

The invention discloses an intersection traffic organization and signal timing dial method for tailgating opposite exit lane left-hand turning. According to the method, the problem that the number of left-turn vehicle entrance lanes and the number of left-turn vehicle exit lanes in a signal intersection are not matched is solved, phase position and sequence optimization in signal control is matched, an intersection releasing mode is reorganized, left-turn motor vehicles are made to turn leftwards by occupying the exit lanes, and therefore the left-turn traffic capacity of the intersection is improved. Emptying signal lamps are arranged to empty the queue of a left-turn tailgating motorcade, and the traffic flow conflict of the next conflict phase position is avoided. The left-turn traffic flow traffic efficiency can be effectively improved, the vehicle mean delay of the intersection is overall reduced, and the service level of the intersection is improved.

A method for optimizing a test sequence to diagnose a failure mode of a device, such as a vehicle, is provided. At least one symptom of a fault of the device is received, and a plurality of taxonomies is generated. The taxonomies include a device component taxonomy, a fault taxonomy, and a diagnostic taxonomy, and each taxonomy has a plurality of nodes. At least one diagnostic test sequence, based on the symptom and the taxonomies, is generated, costs associated with the diagnostic test sequence are determined, and a cost optimal test sequence, based on the costs and the diagnostic test sequence, is generated.

A flexible job shop order insertion dynamic scheduling optimization method is a solution method aiming at the delay problems caused by the order insertion in the job shop batch dynamic scheduling, andcomprises the steps of on the basis of establishing a mathematical model of the task sequence optimization and the order batch distribution, researching a batch selection strategy, adopting an example simulation mode to obtain the reasonable sub-batch number, at the same time, according to the simulation and calculation of the typical examples, giving a recommending value of the batch number; secondly, based on the three-layer gene chromosomes of the processes, the machines and the order distribution number, taking the minimum maximum time of completion and the delay period as the optimization targets; and finally, adopting a mixed algorithm of a particle swarm optimization algorithm and a genetic algorithm to improve the speed of evolution of the sub-batch number towards an optimal direction, thereby effectively reducing the tardiness quantity. The method is good at reducing the delay period in the job shop dynamic scheduling, and for the conventional genetic algorithm, enables the convergence speed and the stability to be improved substantially, at the same time, fully combines the actual production statuses of the intelligent job shops, greatly promotes the dynamic scheduling solution, and has the great application value in the engineering.

The invention discloses a method for restoring sequence and path of a unit and simultaneously performing optimization. The method includes: 1) obtaining data required by optimization calculation; 2) confirming a black-start power source which is safe and reliable to operate, selecting a unit with proper capacity and around an important load to serve as a set of units to be restored; 3) building a multi-objective optimization mathematical model for optimizing unit restoring sequence and unit restoring path simultaneously by considering mutual influence of unit restoring sequence optimization and unit restoring path optimization, leading in DE-EDA for solving, and giving a plurality of Pareto optimized unit restoring sequences and unit restoring paths and putting sequence of lines in the path; 4) performing various safety verifications on obtained Pareto optimized restoring schemes by adopting a numerical simulation technology; 5) enabling decision makers to choose one scheme as a main restoring scheme from the verified Pareto optimized schemes, and using other schemes as backup restoring schemes.

The invention discloses a retention time sequence optimization method based on multiplexing of a buffer unit. The method comprises the steps: finding the buffer unit on a function data path, wherein the function data path has the same starting point with a scanning path violating the retention time sequence; determining the maximum output load capacitance of the buffer unit according to the current time sequence; determining the maximum length of an interconnection line according to the maximum output load capacitance of the buffer unit and the current wiring condition; analyzing whether a new unit is allowed to be inserted to reduce the output load capacitance of the buffer unit or not according to the local unit density of an area where the buffer unit is located if the multiplexing of the buffer unit will additionally build a time sequence violation path, and if yes, reducing the output load capacitance of the buffer unit by inserting the new unit; finally, determining the connection relationship of the scanning input end of a scanning register according to the time sequence and the physical information. The method optimizes the retention time sequence of the scanning path in design, decreases the insertion number of buffer units, and reduces the design density and power consumption.

The invention discloses an induced draught fan and boost fan combined control method for a large thermal generator set. The thermal generator set comprises at least two induced draught fans and at least two boost fans. The control method includes the following portions, namely, stripping protection logic optimization of the induced draught fans and the boost fans, sequential control start step sequence optimization of the induced draught fans and the boost fans, the steps of the induced draught fan and boost fan combined control method in the normal running process, and the steps of the induced draught fan and boost fan combined control method under the abnormal working condition. By means of the method, the influences on pressure at the inlet of the FGD can be reduced when the boost fans are started; working condition changes can be responded to in time in the running process of the set; running of the set can be ensured by conducting adjustment in time through the RB method and other methods under the accident working condition; when device safety is influenced, interlocked stripping of the induced draught fans and the boost fans can be achieved, and the method has great significance in safe, stable and optimized running of the set.

The invention discloses an SVM efficient spectrum sensing method based on a Cholesky decomposition sampling covariance matrix. The method is implemented by adopting the following steps: S1, a covariance matrix of a Cholesky decomposition sensing signal is used to construct a statistical quantity; S2, the statistical quantity is marked with a label; S3, the statistical quantity and the corresponding label are used as a training sample set, and samples are trained by adopting an SVM algorithm to obtain a convex quadratic programming problem; S4, the convex quadratic programming problem is solvedby adopting a sequence optimization algorithm to obtain an SVM classifier; and S5, states of main users are classified by adopting the SVM classifier. According to the method, through the preprocessing of the Cholesky decomposition sensing signal sampling covariance matrix, the correlation between a PU signal and a noise can be reduced, and the number of sample sets is reduced, so that the distance between the PU signals and the noise is increased, the detection probability is improved, and the spectrum sensing complexity is reduced.

The invention relates to an arterial traffic four-intersection control sub-area bidirectional green wave coordination control method based on phase sequence optimization. A new cycle calculating formula is provided, the problem that a signal cycle value obtained with an original cycle formula is small is solved, and a more reasonable signal cycle is generated. A four-intersection phase sequence simultaneous-optimization method is designed, the phase sequence of intersections of four-intersection control sub-areas is optimized through a speed prediction control reward function, guide vehicle speeds corresponding to different road sections are given according to the optimized phase sequence, smooth bidirectional green waves are formed by the control sub-areas, and phase segmentation and upper-lower-line phase conflicting are avoided. The arterial traffic four-intersection control sub-area bidirectional green wave coordination control method has the advantages that the more reasonable signal cycle is generated, the vehicle speed on an artery can be highest within an allowed range under the manual control condition, the traveling time is saved, phase changes of the intersections are stable and smooth, the integrity of the phase sequence green time is guaranteed, conflicting of an original artery coordination control mode to control over road physical conditions and phase segmentation are overcome, and the arterial traffic four-intersection control sub-area bidirectional green wave coordination control method is an efficient and simple artery coordination control method.

The invention relates to the field of information retrieval, in particular to a method for querying a keyword based on a topic cluster unit in a relational database, and aims to solve the problem of huge time overhead caused by frequent table connections in a query process for an existing keyword online query method as well as the problem of low query efficiency of an existing keyword offline query method for query on a large-scale database with a complicated internal structure and huge data volume. The method for querying the keyword based on the topic cluster unit in the relational database is implemented by the following steps of 1, constructing a topic cluster unit: (1), performing vertical grouping based on data table characteristics and query logs; (2), proposing a table connection sequence optimization scheme in a topic cluster; and (3), performing horizontal grouping based on a topic cluster tuple association graph; 2, establishing an association rule-based index optimization mechanism; and 3, returning a query result to a user. The method is applied to the field of the information retrieval.

The invention discloses a double-angle sequencing optimization based pedestrian re-identification method, and belongs to the technical field of surveillance video retrieval. The double-angle sequencing optimization based pedestrian re-identification method comprises the steps of: firstly obtaining initial sequencing results through ways based on global characteristics and local characteristics; then taking an intersection set GKc(p) of front k results of the two sequencing results as initial values for inquiring a more reliable nearest neighbor; then regarding each goal gKc(j) in GKc(p) as a new inquiring factor for crossed opposite inquiry, weighting and fusing a sequence list of the opposite inquiry to obtain a whole optimized sequence list; finally, establishing a double-layer map for each gKc(j) in the GKc(p), and calculating neighbor similarity of the map to perform further rearrangement on the GKc(p) so as to further obtain a better re-identification effect.

A diagnostic test sequence optimizer includes a diagnostic test selector that determines a group of diagnostic test procedures related to a specific symptom and vehicle type from a pool of diagnostic procedures. A failure mode analyzer then selects one or more factors that can affect resolution of a vehicle operational problem and performs a failure mode analysis to quantify a comparative utility of the individual tests, and a factor weighter assigns a weight to each of the factors. A vehicle receiver receives information regarding the history of the test subject vehicle, and a sequence optimizer places the diagnostic test procedures in an optimized sequence in accordance with the comparative utilities of the individual diagnostic procedures, user preferences and a Failure Mode and Effects Analysis compiled by the manufacturer of the vehicle.

The present invention provides a wind power fluctuation probability density modeling method based on nonparametric kernel density estimation. The method comprises the following steps: 1, extracting a fluctuation amount of wind power sample data by wavelet decomposition; 2, establishing a corresponding nonparametric kernel density estimation model based on a fluctuation amount sample, and then aiming at the model bandwidth selection problem, constructing a constrained bandwidth optimization model which uses a goodness-of-fit test as a constraint condition; and 3, solving the optimization model by using a constrained sequence optimization algorithm. According to the present invention, due to adoption of the wavelet decomposition method, a wind power fluctuation component can be more precisely extracted; moreover, a probability characteristic modeling method of the extracted fluctuation component is entirely driven by the sample data without performing prior subjective assumption on the probability density model, so that the method has higher modeling accuracy and applicability; and an improvement strategy aiming at the nonparametric kernel density estimation method also enables modeling accuracy and computing efficiency of the method to be effectively improved.

The invention discloses a task sequencing optimization method based on an overlayer shuttle car system, and a system thereof. The method comprises the steps of establishing a hybrid integer planning model in which shortest order sorting total time is used as an objective function for all order tasks in a single time window, adding a plurality of constrained conditions through analyzing correlationbetween orders and equipment, solving a hybrid integer planning model by means of a Gurobi linear planning solver, and obtaining an optimal warehouse outing sequence of the order tasks in the time window and the shortest order task finishing time. The task sequencing optimization method and the system thereof have advantages of supplying a new idea for task sequencing optimization research of theoverlayer shuttle car system, and supplying decision support for improving system efficiency.

The invention discloses a multi-dimension searching sequencing optimization algorithm and tool based on microblog data. The algorithm optimizes original searching sequencing results of the Lucene on the aspects of three dimensions of data characteristics, user characteristics and application characteristics, and the optimized sequencing result is improved on the aspects of representing the data characteristics, according with the inquiry intention of a user, according with the application theme and the like. The multi-dimension searching sequencing optimization tool is achieved based on financial microblog data and is divided into three modules, and each module finishes the optimization in one dimension. A sequencing optimization module for the data characteristics achieves data characteristic optimization at the dimension I, a sequencing optimization module for the user characteristics achieves user characteristic optimization at the dimension II and comprises two sub-modules which are a searching label optimization sub-module and a searching log optimization sub-module, and a sequencing optimization module for the application characteristics achieves application characteristic optimization at the dimension III. The tool is suitable for optimizing all basic searching results of the Lucene, can achieve optimization sequencing of the original searching results of the Lucene in a system searching module, and provides better searching experience for the user.

The invention discloses a method for combining image scaling and color space switching, which aims at solving the technical problems that the image scaling and the color space switching occupy system resources seriously and the calculation expense is high in an embedded image video processing system in the prior art. In the provided method for combining the image scaling and the color space switching, luma and chroma (YUV) color space scaling is performed and switching from a YUV 420 color space to a red-green-blue (RGB) 565 color space is finished by using a color space switching algorithm at the same time. By the method, the system resource occupation and the system expense are reduced; meanwhile, the system performance of embedded equipment is enhanced greatly through measures, such asscaling sequence optimization, sheet combination, algorithm preference and the like.

Methods and apparatus are provided for implementing a programmable chip using a high-level language. Code sequences such as high-level language software critical loops are converted into read / transform / write (RXW) processes with buffer based flow control between the processes. Having separate read and write processes allows an arbitrary number of sequential reads / writes to occur in any order, subject to buffer size, allowing bursting / sequential transactions that are more efficient than random accesses.

The invention discloses a node transmission sequence optimization competitive channel underwater acoustic network parallel communication method. According to the invention, each source node uses the same non-random algorithm to calculate the sequence and time of data transmission of the node in the transmission cycle; data are transmitted to a corresponding destination node after timing is up to the time; after the data of all source nodes are transmitted, each destination node uses the same non-random algorithm to calculate the sequence and time of ACK or NACK signaling transmission of the node in this transmission cycle; and after timing is up to the time, the destination node with correct received data transmits ACK signaling to the corresponding source node, and the destination node with wrong received data transmits NACK signaling to the corresponding source node. According to the method, the time required for one transmission cycle is effectively reduced and the channel utilization efficiency is improved under the premise of conflict-free parallel node data transmission. The method can be widely used in various underwater acoustic communication networks based on competition agreement, an underwater acoustic sensor network and other occasions.

The invention discloses a recognition method for a subassembly in assembly sequence planning. The recognition method comprises the steps of building a weighted non-vector connection diagram through a relationship between assemblies, and then determining basic parts; judging the subassembly according to the definition and the association degree of parts; finally, realizing a subassembly recognition algorithm through designing and compiling under a Matlab (matrix laboratory) environment. According to the recognition method disclosed by the invention, an algorithm instance verifies that a great significance in realizing assembly sequence optimization and shortening assembly sequence planning time is obtained by applying the subassembly recognition to the assembly sequence planning, an assembly sequence is simplified, and the assembly difficulty and the assembly cost are reduced.

The invention discloses a resource sequencing method and device. The resource sequencing method comprises the following steps: acquiring candidate resources; calculating first click through rate (CTR) scores of the candidate resources based on a logistic regression (LR) model; calculating second CTR scores and uncertainty scores of the candidate resources based on a linear confidence upper limit LinearUCB model; inputting the first CTR scores, the second CTR scores and the uncertainty scores serving as input features into a gradient boosting decision tree (GBDT) model, and calculating pre-estimated scores of the candidate resources based on the GBDT model; and sequencing the candidate resources according to the pre-estimated scores. Through adoption of the resource sequencing method, the accuracy of CTR pre-estimation can be increased effectively, so that sequencing optimization of the candidate resources is realized; candidate resources more preferred by a user are presented preferentially; and the user experience is improved.

The invention discloses a multi-fidelity design optimization method for a shell structure of an autonomous underwater vehicle. A multi-fidelity method of an addition bridging function based on a Kriging model is adopted, a multi-start optimization method and a unique self-adaptive model updating strategy are combined, and accordingly design optimization of the shell structure is conducted. The multi-fidelity method is adopted to construct an agent model of which the maximum stress of the shell structure avoids the instability of the critical load, when the agent model is constructed, a large amount of low-fidelity calculation and analysis are used, the precision of the model is improved, and meanwhile the total calculation cost of the optimization process of the structure design is reduced. During sequence optimization, a new agent model is adopted to update the strategy; meanwhile, an optimum point of the current model and an MSE maximum point of the current model are added into high and low fidelity sampling points; through the MSE maximum point of the added model, the global space can be sufficiently explored, and accordingly the total precision of the agent model is improved; accordingly, an optimum design scheme is obtained, and the precision and efficiency of design optimization are improved.

A method for monitoring and measuring an insulation resistance in ungrounded and grounded power supply systems includes the method steps of generating a periodic measuring signal, coupling in the measuring signal between active conductors of the power supply system to be monitored and ground, and detecting and evaluating measured values of the measuring signal. In one embodiment of the invention, the generated measuring signal is formed as a multi-frequency signal by the superposition of a finite number of harmonic oscillations with at least three harmonics. Alternatively, the multi-frequency signal can also be realized by means of a targeted, portioned construction of the signal shape in the time domain on the basis of a binary sequence optimization or by generating the measuring signal by means of the time-division multiplexing method.

The invention discloses a multi-operating-condition failure load based composite structure uncertainty optimization method. The method includes steps: (1) subjecting an established finite element model to model correction and confirmation under an uncertainty condition; (2) subjecting a composite to safety coefficient based two-stage optimization, wherein first-stage optimization refers to composite super layer optimization aiming at structural weight, and second-stage optimization refers to stacking sequence optimization aiming at structural bearing capacity; (3) on the basis of an uncertainty parameter range quantified in the step (1), performing bearing capacity reliability analysis on a scheme optimized in the step (2) to obtain reliability of structure bearing capacity under differentoperating conditions; (4) subjecting the composite to reliability based optimization, taking bearing reliability of the scheme optimized in the step (3) as a constraint pair, performing super layer optimization aiming at weight reduction, and performing second-stage stacking sequence optimization aiming at structure bearing capacity lower bound maximization.