261 results about "Time loss" patented technology

The present principles provide systems and methods for detecting robot-access of a web-based interface by utilizing a minimum expected human response time (MEHRT) to complete a pre-determined task. After a user is prompted to complete the pre-determined task, a user-response time is calculated. The user-response time is compared to the MEHRT and if the user-response time is less than the MEHRT, then the system determines that the user is a robot. Additionally and/or alternatively, the MEHRT may be employed to impose a time penalty on robots and thereby deter robot access of the interface. The time penalty may be imposed by preventing a user from completing the pre-determined task until the MEHRT has passed.

Systems and methods are disclosed, especially designed for very compact hardware implementations, to generate random number strings with a high level of entropy at maximum speed. For immediate deployment of software implementations, certain permutations have been introduced to maintain the same level of unpredictability which is more amenable to hi-level software programming, with a small time loss on hardware execution; typically when hardware devices communicate with software implementations. Particular attention has been paid to maintain maximum correlation immunity, and to maximize non-linearity of the output sequence. Good stream ciphers are based on random generators which have a large number of secured internal binary variables, which lead to the page synchronized stream ciphering. The method for parsed page synchronization which is presented is especially valuable for Internet applications, where occasionally frame sequences are often mixed. The large number of internal variables with fast diffusion of individual bits wherein the masked message is fed back into the machine variables is potentially ideal for message authentication procedures.

The invention discloses a human behavior recognition method based on an attention mechanism and a 3D convolutional neural network. According to the human behavior recognition method, a 3D convolutional neural network is constructed; and the input layer of the 3D convolutional neural network includes two channels: an original grayscale image and an attention matrix. A 3D CNN model for recognizing ahuman behavior in a video is constructed; an attention mechanism is introduced; a distance between two frames is calculated to form an attention matrix; the attention matrix and an original human behavior video sequence form double channels inputted into the constructed 3D CNN and convolution operation is carried out to carry out vital feature extraction on a visual focus area. Meanwhile, the 3DCNN structure is optimized; a Dropout layer is randomly added to the network to freeze some connection weights of the network; the ReLU activation function is employed, so that the network sparsity isimproved; problems that computing load leap and gradient disappearing due to the dimension increasing and the layer number increasing are solved; overfitting under a small data set is prevented; and the network recognition accuracy is improved and the time losses are reduced.

The invention discloses a Sina microblog-based user grade sequencing algorithm. The Sina microblog-based user grade sequencing algorithm comprises the following steps: a) capturing real-time data in Sina microblogs; b) determining restraining factors which affect user grade sequencing in the Sina microblogs through data analysis; c) establishing a user influence power reference model in the user grade sequencing; d) establishing a user liveness reference model in the user grade sequencing; and e) getting a user weight calculation model by weighting the user influence power and the user liveness models, and realizing the user grade sequencing of the Sina microblogs by utilizing the model. The Sina microblog-based user grade sequencing algorithm can be used in the field of research of social networks. The Sina microblog-based user grade sequencing algorithm disclosed by the invention has higher rationality and smaller time loss, and is suitable for real-time network environments.

An arithmetic unit, for example a multiply and accumulate (MAC) unit 42, for a processing engine includes a partial product reduction tree 480. The partial product reduction tree will generate carry results and provides a final output to a final adder 470 connected to the partial production reduction tree. Unbiased rounding logic 476 is provided. A carry propagation tree is responsive to the carry results for anticipating a zero on each of N least significant bits of the final adder. When zero is anticipated on each of N least significant bits of the final adder, the carry propagation tree is operable to generate an output signal 477 which is used by the unbiased rounding stage to force the (N+1)th least significant bit of the final adder to zero. Through the use of a carry propagation tree to predict, or anticipate zeros on the N least significant bits, unbiased rounding can be effected without a time penalty in that a carry propagation tree can be configured to be at least a rapid as the carry propagation of the final adder. Where a zero anticipation function is provided, this can also be mapped onto the carry propagation tree, thus providing an efficient hardware implementation through sharing of that hardware between functions.

A packaging condition for packaging a product using a film roll is stored in a recording medium, and the packaging condition is read by a recording medium reading device in a rotator of a support shaft. In this case, an operator can set an optimum packaging condition at the time of exchange of packaging rolls regardless of his/her skill. Therefore, even an unskilled operator would not set an erroneous packaging condition which may result in additional time loss and film loss.

The invention provides a super-resolution method based on a convolutional neural network, and is aimed at searching a single-image super-resolution method which is fast in speed and high in restoration quality through a deep convolutional neural network. The invention provides a method of super-resolution reconstruction algorithm fusion more suitable for a single image to solve the problems that the time loss is great, hardware demands needed for realization of algorithms are high and the like. For features of different super-resolution algorithms, conventional super-resolution algorithms are analyzed and selected, so the selected super-resolution algorithms achieve advantage complementation after being fused, and the disadvantages for realization of the conventional super-resolution algorithms are overcome.

The invention discloses a method for compressed sensing synthetic aperture radar imaging based on dual sparse constraints. The method mainly solves the problems that a complete SAR image cannot be obtained in imaging through a traditional synthetic aperture radar imaging method and time loss is large. The method comprises a first step of utilizing radar to irradiate a ground sparse scene D and obtain echo signals r of the scene; a second step of constructing an orientation direction base matrix A of the scene and a distance direction base matrix B of the scene; a third step of obtaining an orientation direction measurement matrix theta, a distance direction measurement matrix omega and an echo measurement matrix S according to the orientation direction base matrix and the distance direction base matrix; a fourth step of constructing a Lagrangian function f(Y,U) according to the orientation direction measurement matrix, the distance direction measurement matrix and the echo measurement matrix; and a fifth step of using an alternate iteration multiplier method to solve the Lagrangian function f(Y,U) in the fourth step and obtaining an image of the scene D. The method can achieve high-resolution imaging of synthetic aperture radar in downsampling, is quick in imaging speed and can be used for large-area topographic mapping and cartography.

The invention relates to a training method and device of a neural network model for image processing. The method comprises that video frames adjacent in time are obtained; the neural network model output intermediate images corresponding to the video frames respectively; change of the video frames in relatively earlier time and optical flow information of the video frames in relatively later timeare obtained; and image formed by changing the intermediate image, corresponding to the video frame in relatively earlier time, according to the optical flow information is obtained; time loss betweenthe intermediate image corresponding to the video frame in relatively later time and an image after change is obtained; characteristic loss between the intermediate image and a target characteristicimage is obtained; and the neural network model is adjusted according to the time loss and the characteristic loss, the step of obtaining the video frames adjacent in time is returned to, and trainingis not stopped until the neural network model satisfies a training ending condition. Thus, the neural network model obtained by training has a better video characteristic conversion effect.

The invention provides a hybrid clustering method aiming at a complicated network, and belongs to the field of data mining of a community network. The method comprises the following steps of: partitioning the complicated network by a heuristic clustering method, and setting an optimization terminating function and an iterative terminating threshold value to obtain a relatively good network community division result; combining the networks by an optimization-based clustering method, and storing an optimal network community division result by calculating a final optimization terminating function; and finally outputting a community structure. By the method, a large-scale complicated network can be subjected to community division or clustering, so that a community division result is good; furthermore, the Girvan-Newman (GN) algorithm precision based on connection clustering coefficients is improved, and the time loss is avoided; and high user experience can be guaranteed.

The invention relates to a crop transpiration prediction method based on an improved extreme learning machine. First, soil environment data and meteorological data of a farmland are collected and normalized to obtain a training set; then, the training set is adopted to train an extreme learning machine network and improve an extreme learning machine; last, normalized data collected again is input into the improved extreme learning machine, and the improved extreme learning machine outputs crop transpiration obtained through prediction. Extreme learning machine improvement mainly comprises the steps that 1, a function based on waveform superposition is adopted to serve as an activation function for a hidden layer of the extreme learning machine; 2, a particle swarm optimization algorithm is adopted to optimize an input weight value and a threshold value between a network input layer and the hidden layer of the extreme learning machine. Through the prediction method, the prediction precision of crop transpiration is improved, prediction time loss is reduced, and meanwhile generalization performance and prediction stability of the traditional extreme learning machine network are improved.

The invention provides a seal image retrieval method of the round signet and belongs to the signet image automatic retrieval technical field, wherein, the method includes the following steps: the main character area of a signet is picked up and the main characters of the signet is divided; single character feature of the main characters is picked up; a reference signet database is created by means of the information of the main characters; moreover, a signet image is input to be matched with the reference signet in the reference signet database, thereby realizing automatic retrieval of the reference signet corresponding to the input signet image. The invention solves the bottleneck problem of the prior signet authentication system, i.e. labor and time loss caused by the unavoidable manual ID input phase; meanwhile, the Chinese character recognition method which is provided by the invention is not influenced by blurry and incomplete Chinese character and can obtain results of high correct rate.

The invention provides a composite anti-mud agent based on a polycarboxylate-type pumping agent, an anti-mud pumping agent and a preparation method of the anti-mud pumping agent. The anti-mud pumping agent comprises a water reducing component which is namely a liquid polycarboxylate superplasticizer with solid content of 40%, a retarder component which is namely a conventional retarder, an entraining component which is namely an anionic surfactant synthesizing entraining agent and a composite anti-mud agent which is namely a mixture of calcium nitrate, polyvinyl alcohol, beta dextrin and diallyl dimethyl ammonium chloride. The preparation method of the anti-mud pumping agent comprises the following steps: firstly adding raw materials of the composite anti-mud agent into water, and preparing a composite anti-mud agent solution; adding the composite anti-mud agent solution into a mixture of the polycarboxylate superplasticizer, the entraining agent, the retarder and water, and uniformly stirring. The anti-mud pumping agent has the advantages that influence of content of mud in sand and stones on flowability of concrete can be obviously reduced without increasing the cost, the time loss in collapsed slump is reduced, and other properties such as strength of the concrete are not influenced.

In a system for content management, a dynamic lexicon allows dictionary and lexical data at NLP (natural-language processing) engines at remote sites to stay current with table data at a central location without suffering the time loss involved in computing new tables at the remote sites, or computing new tables at the central site and distributing them. As new terms are added to the dictionary, each term is assigned a unique token identifier. A first step involves downloading extensions to the table data in real time whenever a new word or expression is encountered. A second step involves periodically updating the table data in real time with recomputed data transmitted in compact data files from the central location. Content items in the local archive are re-indexed based on the updated table data. Maintaining tokens across generations of tables allows documents in different languages to be associated without requiring translation.

The invention discloses a road section pedestrian traffic signal control system based on pedestrian crossing clearance time. The road section pedestrian traffic signal control system based on the pedestrian crossing clearance time comprises a pedestrian data acquisition and recording unit, a pedestrian crossing clearance time computing unit and a signal implementation and feedback unit, and is applicable to pedestrian signal timing designs of thick crowd crossing districts and intersections with exclusive pedestrian phases. The road section pedestrian traffic signal control system based on the pedestrian crossing clearance time comprehensively takes time loss and pedestrian crossing traffic capacity decline due to mutual disturbance of stream of people of opposite directions during thick crowd crossing into consideration, overcomes the defects that the pedestrian speed is used as a constant and the pedestrian crossing capacity is unchanged in a traditional pedestrian traffic signal control, so that the timing result is more accurate and practical. Only the pedestrian flow and the pedestrian speed of the pedestrian crossing are needed to be measured and computed, so that the computation is concise.

The invention discloses a water reducing agent special for high-speed railway ballastless track self-compacting concrete. The water reducing agent is compounded from an ordinary polycarboxylic acid water reducing agent, slow-released type polycarboxylic acid water reducing agent mother solutions with different releasing speeds and releasing peak value time, a retarder, a degasifier and an air entraining agent. The invention provides a water reducing agent which is special for filling self-compacting concrete into a sealed space, solves the problems of economic and time loss in landslide extension degree of the self-compacting concrete, ensures the stable working state of the self-compacting concrete after being taken out from a machine till being cast, and meets the construction requirements of the self-compacting concrete.

The invention relates to a method for organising and managing a vehicle train by using a management unit, comprising: A) the management unit receiving vehicle train information which relates to at least two vehicles and comprises, for each of them, starting and destination points for a journey, times for the journey, e.g. departure time and/or arrival time, vehicle-specific information, e.g. engine power, vehicle weight, frontal cross-sectional area, fuel consumption; B) matching the times of the vehicles with one another and determining on the basis thereof a time for the vehicle train; C) matching starting and destination points of the vehicles with one another and determining on the basis thereof an itinerary for the vehicle train. D) calculating for each vehicle an individual value parameter which represents the consequences of taking part in the vehicle train, based on at least the vehicle-specific information and the specified itinerary, which value parameter represents one or more from among fuel saving, time gain or time loss.

The invention provides a research on registration on a remote-sensing image based on an improved SIFT feature. According to the characteristics of large data volume and high overlapping rate of the remote-sensing image and defects of matching errors and the matching efficiency caused by complex factors including illumination and geometric difference etc., an improved method of SIFT feature descriptors is deeply researched: constructing the feature descriptors by employing a feature point circular area; performing division of a local area and calculation of a gradient histogram by employing an adaptive quantization strategy, re-determining the principal direction of each descriptor by employing an interpolation method, and improving the feature descriptors of an SIFT algorithm; and employing a novel SIFT feature matching algorithm based on block matching. According to the method, the time loss for feature extraction and matching is reduced through removal of non-overlapped areas, and the uniqueness and the robustness of the feature point descriptors can be guaranteed.

The invention provides a method for improving a digital channel waveform capture rate of a mixed oscilloscope. A data acquisition module, a sampling point and pixel point conversion module and a pixel point storage module are realized through FPGA, and data acquisition and screen pixel point generation are completed by employing a parallel processing mode. According to the method, acquisition, processing, storage and display of the data are realized completely through the FPGA, the parallel processing mode is employed, and a conversion speed is fast; when the mixed oscilloscope is in an operation mode, only a small amount of pixel point data is needed to transmit, transmission of original acquired data is not needed, and time loss of data transmission is greatly reduced.

The invention relates to a station pile-free rental device used in a bicycle rental system and a working method, which belongs to the transportation field. The rental device provided by the invention comprises a short distance device identification module and a bicycle lock control device control module. The working method comprises the steps that a short distance detection module detects whether a bicycle is within a designated area to generate a dynamic two-dimensional code and a temporary bicycle locking password; a user scans the two-dimensional code information, carries out communication through mobile phone GPRS, uploads corresponding data to a server, and the data are verified; a bicycle rent and return request is sent to a lock control device; the bicycle lock control device receives a text message through a text message transceiver unit to determine the bicycle rent and return request, and at the same time the lock state of the bicycle is acquired; GPRS communication is carried out after GPS positioning; and bicycle rent and return information is uploaded to the server, and then is pushed to the user. According to the invention, the device and the working method are safe and reliable and are easy to operate; the pile-free mode reduces personnel and time loss; low power consumption is realized through the text message transceiver unit; and the service life of a bicycle battery is prolonged.

To address a problem that efficiency of beverage-packaging lines in some domestic beverage enterprises is hard to quantify, the invention provides a practical and effective information system for production line efficiency assessment and equipment state monitoring. Via the system, information-based digital assessment of efficiency during production line operation can be realized. Via assessment of an equipment speed rate V- curve, shutdown records of key devices can be extracted; the shutdown records comprise shutdown starting time, the shutdown ending time, shutdown duration, shutdown types, shutdown devices, reasons behind shutdown and the like; all kinds of time loss caused by internal and external factors can be accurately quantified and assessed, and therefore a production line efficiency assessing and monitoring system based on four indexes used as measurement standards which include total asset utilization rates, line production rates, rates of comprehensive utilization of equipment and line efficiency. Digitalization of beverage packaging production line can be realized; comprehensive management capability, inter-department coordination and cooperation capability, equipment operation capability and fault handling capability of the enterprises can be overall reflected.

The invention discloses a concrete synergist. The concrete synergist is prepared from the following raw materials in percentage by mass: 7%-12% of acrylic emulsion, 2%-3% of sodium dodecyl sulfate, 5%-7% of polyalcohol, 5%-10% of triisopropanolamine, 10%-15% of nano calcium carbonate, 3%-5% of diethylenetriamine-5-tetraoxaoctadecanoicacid, 2%-4% of sodium lignosulfonate, 1%-3% of nanometer silicongranules, 10%-15% of octyl phenolic tackifying resins and the balance of water. According to the concrete synergist disclosed by the invention, gaps in concrete can be stuffed, the bending tensile strength and the permeability resistance of the concrete are improved, the concrete is endowed with high mechanical force resistant performance, the problem of large time loss in collapsed slump of theconcrete is solved, the frost melting resistant capacity and the durability of the concrete can be improved at the same time, and the service life of the concrete can be prolonged.

The invention provides a favorite data processing method and device and a server. The method comprises the steps that an object link is acquired from favorite configuration information; HTTP (Hyper Text Transport Protocol) request information is sent to a WEB server corresponding to the object link; HTTP response information returned by the WEB server is received, wherein the HTTP response information comprises HTTP response state codes corresponding to the object link; a link sign of the object link is acquired according to the HTTP response state codes; and the link sign is prompted to be displayed in the position of the object link in the favorite. A user can judge the effectiveness of the object link visually through the link sign, so that time loss and consumption of server resources caused by invalid link access are greatly reduced.