65results about How to "Optimize runtime" patented technology

The invention discloses an LTE system orthogonal frequency-division multiplexing (OFDM) signal peak-to-average ratio suppression method combining constellation expansion with tone reservation. According to the suppression method, an active constellation expansion intelligent gradient mapping algorithm principle and a tone reservation least square estimation algorithm are combined, and control over the signal peak-to-average ratio performance, the bit error rate performance of a system and the out-of-band frequency spectrum extension performance of transmitting signals is effectively achieved by correcting the position of constellation points. A high convergence speed can be obtained, and the system operation time is effectively optimized, so that it is ensured that under the condition of little influence on the bit error rate performance of the system, the OFDM signal peak-to-average ratio is reduced substantially, and the overall comprehensive performance of the LTE system is improved.

The invention relates to a multi-constraint service selection method and device based on global QoS decomposition, which is realized by establishing a single object optimization model with a number of constraints. The method comprises the steps that a corresponding dependency set and collision set are established for each candidate service according to the service dependency transmission characteristic; the global QoS constraint is decomposed into local QoS constraints corresponding to each service class; candidate services which do not satisfy the local QoS constraints under the service class are filtered; all filtered candidate services are checked, and the dependency set and collision set of the remaining candidate services are updated; an adaptive replacement method is used to carry out quality scale combination replacement in an unresolved state; the local fitness of each candidate service is calculated; and the candidate service with the greatest local adaptability in each service class is selected to form the final combination service. According to the invention, the complexity and running time are greatly optimized; the real-time demand of a user is satisfied; the scale of a candidate service space is narrowed; and the quality and performance of the network combination service are effectively ensured.

The invention relates to a high-performance ordering method for a MapReduce calculation frame. The method comprises the steps that buffer chains are respectively constructed in the Map stage according to partitions, the requirement that the partitions are ordered is removed, data of each partition are organized according to blocks, and the cost of data in copy and file IO aspects in internal storage is lowered; the ordering operation is not executed in the Map stage, a large buffer pool is adopted as the basic unit of ordering of one time in the Reduce stage, and the total merging approach quantity in the ordering merging state is made to be a value capable of being adjusted and optimized by a user. Through a mixed internal storage ordering algorithm, the two ordering stages in the MapReduce calculation frame are optimized, the influence of ordering on the performance of the calculation frame is basically eliminated, and then the resource validity of the calculation frame is improved, and the overall resource consumption of a cluster is reduced.

The invention discloses a projector and a control method of the running state of a cooling fan of the projector and is characterized in that temperature of essential parts in heat dissipation areas inside a case is detected, the corresponding cooling fan starts to run or keeps running when the detected temperature is higher than or equal to the given temperature while the corresponding cooling fan stops running when the detected temperature is lower than the given temperature. By detecting the temperature of selected corresponding essential parts inside the case of the projector, the control method of the invention controls the running states of corresponding cooling fans, optimizes the running time of the fans, ensures the service life of the machine, saves the energy and reduces the consumption at the same time.

The invention provides an air compression station optimization method based on deep learning. The air compression station optimization method based on deep learning comprises the steps that (A1) a monitoring Internet of Things is utilized to obtain operating parameters of all air compressors in an air compression station; (A2) a deep learning algorithm is utilized to analyze the operating parameters, and an operating mode feature model of all the air compressors in the air compression station is extracted; and (A3) a genetic algorithm is utilized to optimize the operating mode feature model, and the number of started air compressors and starting time are acquired. The method has the advantage that power consumption is low.

The invention discloses a layer allocation method applied to a three-dimensional integrated circuit. Firstly, a layout space and a chip model of the three-dimensional integrated circuit are established. Based on the established layout space, the overall layout of three-dimensional space is carried out, and the uniform distribution of integrated circuit cells in the three-dimensional space is obtained. Spatially uniformly distributed integrated circuit cells are distributed on each chip layer of the established chip model; after layer assignment, two-dimensional optimization method is adopted to further optimize the line length, so as to reduce the line length and the overlap of each layer and complete the overall layout of three-dimensional integrated circuits. The above method can inheritthe three-dimensional optimization results as far as possible and protect the solution space, so as to obtain better line length results, the number of TSVs and running time, and meet the high-precision requirements of integrated circuits.

The invention provides a multi-target buffer region distribution method of a remanufacturing system. A remanufacturing system model is established; the system is decomposed and node expanding is carried out; a probability parameter of the expanded node is calculated and a node arrival rate and an output rate are calculated; a system maximized output rate and a minimized remanufactured product inventory value are calculated; and then calculation is carried out by using a multi-target algorithm TS-NSGA II algorithm, thereby obtaining a performance index of a buffer region. Therefore, a problem of a multi-target buffer region distribution can be solved effectively. The method has good effects in convergence, diversity, and operating time.

Workstation of a two-for-one twisting or cabling machine for production of carpet yarn, including winding device having package cradle with two frame arms for rotatable mounting of an empty tube or twisting package, package drive roller for frictionally driving twisting package, yarn traversing device for traversing transfer of a yarn to the twisting package, advance roller for regulating a yarn tension, and cover in area of the advance roller with an opening for yarn guided through the yarn traversing device to the twisting package. Package cradle has at least one movable, partially rotatable frame arm and designed so an empty tube with length of at least 315 mm is insertable, that the package drive roller has length of at least 286 mm, that yarn traversing device has traversing stroke of at least 11 inches, and that opening in cover corresponds with the yarn path arising due to the traversing stroke.

The invention discloses a method for estimating parameters of expectation maximization in a Gaussian mixture model. The method improves the specific calculation process of the EM algorithm on the basis of sample clustering, and provides the estimation of three parameters of w, μ and ∑ method, making it suitable for sample reduction and the input parameters of GMM are fuzzy color features. Due to the reduction in the number of samples, the parameter estimation process will not introduce unnecessary noise, thereby improving the accuracy of parameter estimation; due to the reduction in the number of samples, the improved EM algorithm is also improved in terms of storage capacity, calculation capacity, and running time. , which is beneficial to improve the efficiency of parameter estimation.

The invention relates to a TopPPR method for calculating large graph node proximity. The method is characterized by including the following steps: 1) determining initial values of a Top-k node set anda candidate set; 2) performing forward search on the current candidate set and updating the current Top-k node set and the candidate set according to the forward search result; 3) on the basis of allnon-zero forward residual values obtained through forward search, executing nr times of random walk sampling and updating the current Top-k node set and the candidate set; 4) performing batch rearward search on the candidate set in step 3) and updating the current Top-k node set and the candidate set according to the rearward search result; 5) judging the number of nodes in the Top-k set, stopping iteration when a threshold condition is met, or repeating steps from step 2) to step 4) until the threshold condition is met, therefore, a final result is obtained. The method provided by the invention can be widely applied to a large graph node top-k inquiry field.

This invention relates to a vertically integratable circuit and a method for producing same.

Unlike known methods for producing vertical electric connections, the present method uses process steps in the production of the vertically integratable circuit itself to permit vertical integration. This simplifies the sequence of production for vertically integratable circuits and thus the three-dimensional integrated circuit as a whole, thereby optimizing plant running times since process steps are saved. Because finished substrates are no longer the starting point for producing the vertical electric connections, an improved yield is moreover obtained since no process steps which could in particular change the already produced active circuit elements, such as steps with high process temperatures, are necessary any longer after production of the circuit elements.

The invention relates to a multi-mode building air conditioner control system, which comprises a monitoring center and air conditioner apparatuses, and is characterized by also comprising a power distribution network communication module, an air conditioner start/stop control module, an air supply temperature and humidity monitoring module, a return air temperature and humidity monitoring module, a filter blocking state monitoring module, an air flue fire resisting damper state monitoring module, an air conditioner apparatus power consumption information acquisition module and a multi-mode control and regulation module. According to the multi-mode building air conditioner control system, air conditioners are automatically controlled, monitored and measured, the operation states, the accident states, the energy consumption, the load change and the like of the air conditioner apparatuses are mastered, and the operation state and time of the apparatuses are optimized, so that the service life of the apparatuses is prolonged, the utilization rates of the apparatuses are effectively improved, the energy consumption is reduced, the labor intensity and the labor-hour numbers of maintenance personnel are reduced, and the operation cost of the apparatuses is reduced; a multi-mode control and regulation function is realized, all modules are reasonably distributed, the utilization rates of the apparatuses are effectively improved, the energy consumption is reduced, and an optimum experience is provided for users.

The invention relates to a dual-mode orthogonal frequency division multiplexing index modulation detection method and device based on deep learning. The dual-mode orthogonal frequency division multiplexing index modulation detection method comprises the following steps: (1) data preprocessing: preprocessing an obtained DMOFDMIM signal and an obtained channel; (2) training a DMOFDMIM model: takingthe preprocessed data obtained in the step (1) as the input of the DMOFDMIM model, and carrying out the offline training of the DMOFDMIM model; and (3) on-line modulation: carrying out on-line modulation on the new DM-OFDM-IM signal under the Rayleigh channel condition through the trained DM-OFDM-IM model. According to the detection and demodulation scheme based on the deep neural network providedby the invention, the bit error rate close to the maximum likelihood detector can be achieved in a relatively short operation time.

One embodiment provides a method for runtime piggybacking of concurrent data-parallel jobs in task-parallel machine learning (ML) programs including intercepting, by a processor, executable jobs including executable map reduce (MR) jobs and looped jobs in a job stream. The processor queues the executable jobs, and applies runtime piggybacking of multiple jobs by processing workers of different types. Runtime piggybacking for a ParFOR (parallel for) ML program is optimized including configuring the runtime piggybacking based on processing worker type, degree of parallelism and minimum time thresholds.

The invention belongs to the technical field of engine control and particularly relates to a control method and system of engine shutdown for a hybrid vehicle. The control method comprises the steps of detecting basic information of a vehicle which includes engine information, motor information, battery information, gearbox information and vehicle information; detecting SCR (selective catalytic reduction) system temperature; when an engine is under running and if the basic information of the vehicle meets engine shutdown conditions with the SCR system temperature higher than a set value for aperiod of time, shutting down the engine. The control method and system have the advantages that the method and system are used to reasonably control stop time of an engine, running time of the engineof a hybrid system is optimized, and urea crystallization in the SCR system due to frequent start and stop of the engine of the hybrid system is decreased.

The invention relates to an ultraviolet ray photocatalytic air-conditioning system. The ultraviolet ray photocatalytic air-conditioning system comprises a monitoring center and air-conditioning equipment and is characterized by also comprising a power distribution network communication module, an air conditioner start-stop control module, a supply air temperature and humidity monitoring module, a return air temperature and humidity monitoring module, a filter blockage state monitoring module, an air passage fire damper state monitoring module, an air-conditioning equipment electricity consumption information acquisition module, an ultraviolet ray photocatalytic purification device and an air quality detecting module. The ultraviolet ray photocatalytic air-conditioning system realizes the automatic control, monitoring and measurement of an air conditioner, masters an operating condition, an emergency condition, energy consumption, load change and the like of the air-conditioning equipment and optimizes the operating condition and time of the equipment, thus, the service life of the equipment can be prolonged, the utilization rate of the equipment is effectively increased, and the energy consumption, the labor intensity and working hours of maintainers and the operating cost of the equipment are reduced; and the ultraviolet ray photocatalytic purification device is used for purifying air to achieve a sterilization effect and effectively degrade odorous gases in air.

The data link breakdown survival technique involves the use of user interface (12) serviced by a main computer (10). The data is passed to a processor (14) by way of another interface thus giving access to an air to ground transmission transmitter-receiver link (15). There is a second spare computer (11) across the first one receiving the same information as the first computer.

The invention discloses a moving object trajectory simplification algorithm based on feature selection. The algorithm comprises the following steps of processing the trajectory data of a moving object by adopting a DBSCAN density clustering algorithm to obtain a velocity interval of a trajectory; dividing the trajectory of the moving object according to the speed interval to obtain a trajectory segment corresponding to the speed interval; performing feature analysis on each trajectory section, selecting a simplified algorithm, and performing simplified processing on the trajectory data of the trajectory section; and combining the simplification results of each trajectory segment to obtain a trajectory simplification result of the moving object. According to the moving object trajectory simplification algorithm based on feature selection provided by the invention, the trajectory segments are divided according to the speed features, and then the direction feature judgment or the distance feature judgment is performed in the trajectory segments, so that the simplification algorithm suitable for each trajectory segment is selected, the optimization of execution time and error measurement is realized, and the simplification effect is improved.

The invention relates to a building air conditioner intelligent system having an anti-freezing warning function. The system comprises a monitoring center and air conditioning equipment, and is characterized by further comprising a power distribution network connection module, an air conditioner starting/stopping control module, an air feeding temperature/humidity monitoring module, an air return temperature/humidity monitoring module, a filter blockage state monitoring module, an air way fireproof valve state monitoring module, an air conditioning equipment electricity utilization information acquiring module and an air way anti-freezing monitoring module. The system realizes automatic control, monitoring and measurement of an air conditioner, masters the operation state, the accident state, the energy consumption, the load change and the like of air conditioning equipment, and optimizes the operation state and time of the equipment, so that the service life of the equipment can be prolonged, the utilization rate of the equipment is effectively increased, the energy consumption is reduced, the labor intensity and the labor hour number of maintainers are reduced, and the operating cost of the equipment is reduced; and the air way anti-freezing monitoring module is arranged for preventing an air way from being frozen to guarantee stable equipment operation.

The invention relates to an intelligent system of a building air conditioner. The intelligent system is composed of a monitoring center, an air conditioner, a distribution network connection module, an air conditioner starting-shutdown control module, an air supply temperature and humidity monitoring module, an air return temperature and humidity monitoring module, a filter clogging state monitoring module, an air channel fireproof valve state monitoring module, and an air conditioner electricity usage information collection module. With the system, automatic control, monitoring, and measurement of an air conditioner can be realized, changes of the operation state, the accident state, energy consumption and the load of the air conditioner can be gotten, and the operation state and time of the air conditioner are optimized, so that the service life of the air conditioner can be prolonged, the equipment utilization rate is effectively improved, the energy consumption is reduced, the labor intensity and working time of the maintenance staff are also reduced, and the equipment operation cost is lowered. According to the power supply information of the power distribution network, the power supply strategy of the air conditioner is determined, so that the scheduling requirement of the air conditioner and the power supply network can be met to the greatest extent and thus the electricity usage efficiency and reliability of the power distribution network are improved.