42results about How to "Short completion time" patented technology

The invention provides a task scheduling device in a multimode distributive system. The task scheduling device comprises a new task pool, a task filter, a task filtering pool and a task dispatcher, wherein the new task pool is used for storing new tasks, and the new tasks at least comprise new tasks in which task marks are added; the task filter is used for filtering out tasks with empty marks from the new tasks stored in the new task pool; the task filtering pool is used for storing the tasks with empty marks, filtered by the task filter; and the task dispatcher is used for predicting a model according to task completion time by aiming at each task stored in the task filtering pool so as to predict the completion time for executing the task on each processing node in the node processing set, and allocating the task to the processing node with shortest predicted completion time.

A generalized, rationally-scaled design is disclosed for a line laying system for use in stringing communications cable across inaccessible spaces. The system includes a tethered projectile which is accurately aimed and launched to a defined target zone by means of a energy-store coupled with a pivoting release lever. The geometric details of placement of the pivot axis of the release lever are disclosed in detail. Specific configurations of the projectile guides and spring support ribs are also disclosed. Implications of design and materials upon accuracy and range are considered and optimal component finishes and tolerances are indicated.

The invention provides an automatic network cable distributing device which comprises a casing, cables, a baseplate, a cable outlet pillar, inserting and pulling mechanisms, a driving part, a cable plug, a sensor and a controller. The controller starts the driving part according to pre-jumping information and information transmitted by the sensor, and the driving part drives the inserting and pulling mechanisms on two sides of an inserting port to move, so that the cables can start from an initial position and accurately reach the inserting port needing jumping and at the target position according to the positioning sensor. Specifically, the inserting and pulling mechanisms are clamped and pull the cable plug of the cables in pre-jumping out, the cables get away from the initial position, are sequentially wound according to the cable winding rules and move towards the target position, and after reaching the target position, the cables are inserted into a socket at the target position, and cable distribution is finished. The automatic network cable distributing device is compact in structure, simple in dimension, easy to install and maintain, fast to start, short in time for finishing the process, less in components and low in cost and simple in control principle compared with the existing like products.

The invention relates to a portable resistivity method advanced forecasting system applicable to a TBM. The system comprises a plurality of non-polarized electrodes, a terminal control box and an electrode cable series. The non-polarized electrodes are electrically connected with the terminal control box. The terminal control box is electrically connected with the electrode cable series. The non-polarized electrodes are arranged to be capable of stretching out of a TBM cutterhead hob hole and making contact with a tunnel face to detect front geological signals. The terminal control box receives the signals collected by the non-polarized electrodes and predicts a front geologic body. The potential difference between a surrounding rock mass, a shield and the terminal control box is reduced and / or eliminated through electrode cables. According to the system, detection of unfavorable geologic bodies such as a fault fracture zone, a soft and hard layered stratum, a water-bearing cave and an underground river is achieved according to geologic body resistivity difference.

The invention discloses a flexible workshop robustness scheduling method based on a decomposition multi-target evolution algorithm. The method comprises the following steps: 1, reading such input information as operation, machine attributes and the like of a flexible operation workshop, defining an optimization object, and setting constraint conditions; 2, initializing parameters of the algorithm; 3, determining an adjacent domain of each subproblem, generating an initial parent group, and determining all Pereto non-dominant solutions from the initial group so as to form an external memory; 4, generating a child group, carrying out mating selection, breeding child individuals by use of an adaptive variation operator and a restoration-based intersection operator, and updating the external memory; 5, by use of the generated child group, updating a current optimal individual of each subproblem, and forming a new parent group; and 6, when it is determined that the individual object evaluation frequency reaches the maximum, outputting the external memory, i.e., a group of Pareto non-dominant flexible operation workshop scheduling solutions, and if the frequency does not reach the maximum, skipping to the fourth step. According to the invention, scheduling tasks in a flexible operation workshop can be rapidly and efficiency realized.

The invention relates to a hydraulic four-point leveling method with accuracy less than 1 minute. The hydraulic four-point leveling method with the accuracy less than 1 minute is characterized in that according to different conditions of insufficient car body rigidity and sufficient car body rigidity, firstly, four legs are laid on the ground and absolute values of a transverse shaft and a vertical shaft of a precise sensor are adjusted to 900 seconds based on the foundation. A precise leveling is conducted after a rough leveling is finished. The leveling adopts a method of a low point being aligned to a high point so that a lift leveling is achieved. Proportion integration differentiation (PID) operation is conducted towards a tilt error of the transverse shaft and the vertical shaft of the precise sensor, control is conducted after a controlled quantity of lifting legs is calculated. In the process of PID, an integration element overcomes a proportional valve dead zone and a differentiation element restrains continuous increase of a leveling speed. Compared with the prior art, the hydraulic four-point leveling method with the accuracy less than 1 minute is high in leveling accuracy, reasonable in arrangement of the transverse shaft and the vertical shaft leveling order, capable of overcoming direction deflection caused by the insufficient car body rigidity, various in leveling methods and capable of choosing different modes according to different car body structures.

The invention discloses a method for solving separable task multi-time scheduling model in a distributed-type system. By establishing a new separable task multi-time scheduling model and utilizing genetic algorithm to solve the model, the shortest completion time of a task is acquired. A function expression of a task allocation scheme in regard to scheduling sequence of processors, scheduling times and number of the processors that participates in calculation is derived and further a separable task multi-time scheduling model with the shortest completion time the task as a goal is established. According to the invention, the genetic algorithm for solving the model provided by the invention can solve the best scheduling sequence of the processors, the scheduling times and the number of the processor that participates in the calculation, thus the best task allocation scheme and the shortest completion time of the task can be acquired.

The invention is suitable for the technical field of computers, and provides a cloud computing task allocation method and device, equipment and a storage medium. The method includes building a cloud task allocation model according to a to-be-distributed cloud computing task in a cloud task allocation request when the cloud task allocation request is received; performing first preset number of optimizations on the allocation of cloud computing tasks through the cloud task allocation model and an ant colony algorithm to generate first preset number of intermediate allocation paths; performing second preset number of optimizations on the intermediate allocation paths through a genetic algorithm to generate the optimal allocation path of the cloud computing task; and allocating the cloud computing task to a virtual machine in the cloud environment according to the optimal allocation path. Thus, the performance of cloud computing task allocation can be effectively enhanced through a combined hybrid swarm intelligence algorithm of the ant colony and genetic algorithms, short response time and completion time of the cloud computing task can be guaranteed, and the service quality and userexperience of a cloud computing platform can be enhanced.

The invention relates to a test system (1) for checking transmission processes in a mobile radio network (2). Said mobile radio network comprises a central switching computer (8), a local mobile telephone (13) for SIM communication, and a transmission unit (3) comprising a local transmission unit (5). Other components of the test system (1) include a local SIM simulation computer (10) which is connected to the local transmission unit (5) and to the mobile telephone (13), a control computer (23) which is used to control the testing operation and is connected to the mobile radio network (2), and an authentication computer (14) which is connected to the SIM simulation computer (10) and is used to authenticate the mobile telephone (13). A method used for the authentication uses only two communication steps carried out via the remote signal connection.

The invention relates to the technical field of Raman fiber amplifiers, and provides a gain dynamic control method, device and system of a Raman fiber amplifier. The method includes: determining whether the target gain is within the range of GAIN MASK; if the target gain is within the GAIN MASK range, directing locking the same to the target gain; if the target gain is within or outside the GAIN MASK range, locking the gain to the maximum value of the corresponding GAIN MASK gain, and then increasing the locked gain progressively according to a preset first step length until the target gain isreached or at least one pumped laser is present to reach the maximum output power. The invention achieves the effect that the amplifier in the optical fiber line can quickly respond to the change ofthe input optical signal, maintains the gain stability, prevents the optical channel without switching in the line from generating excessive power overshoot or undershoot, and on the other hand, whenthe gain switching occurs, the completion time of the switching is as short as possible.

The invention discloses a maintenance personnel allocation method based on an equipment maintenance process. The maintenance personnel allocation method comprises the following steps: step 1, determining equipment maintenance process limiting conditions and maintenance personnel allocation situation judgment standards; Step 2, determining an antibody coding mode; Step 3, generating an immune algorithm feasible antibody through a matrix addressing mode; 4, judging whether the antibody is feasible or not; And 5, carrying out immune iteration on the initial antibody group to search the optimal antibody. The method has the advantages that the priority constraint and the work type of the maintenance process, Professional maintenance personnel, number and technology level conditions are comprehensively considered;, The matrix addressing mode is adopted, the speed of generating the feasible maintenance personnel allocation situation under the condition that the number of processes is large isincreased, the maintenance personnel allocation situation with the shortest maintenance process completion time and the balanced maintenance personnel workload can be searched through immune iteration based on balance degree judgment, and efficient maintenance of the equipment can be easily achieved. The method is high in universality, can be realized through a computer, and is suitable for various repairing mechanisms.

The invention discloses an AGV task scheduling method based on a simulated annealing algorithm, and belongs to the field of automatic warehousing system task scheduling. The method comprises the stepsof 1, determining position coordinates and endurance mileage of an AGV and position coordinates of a to-be-carried goods shelf and a sorting workstation; 2, setting parameters of a simulated annealing algorithm; 3, generating an initial task allocation scheme; 4, starting iterative search to generate candidate solutions; 5, the feasibility of the candidate solutions is checked, and if not, the step 4 is executed to regenerate the candidate solutions; 6, judging whether to accept the candidate solution or not, and if so, replacing the current solution with the candidate solution; 7, if the preset number of iterations is not reached, skipping to the step 4 to carry out the next iterative search; and 8, if the algorithm termination condition is met, outputting the current solution, otherwise, reducing the annealing temperature and skipping to the step 4 to start a new round of iterative search. An AGV task scheduling problem in an intelligent warehousing system environment can be rapidlysolved, and a task allocation scheme with the shortest or approximately shortest completion time is obtained.

The invention discloses a satellite task planning method with the minimum completion time under the condition of sufficient resources, and the method comprises the steps: 1, carrying out the discretization representation of a to-be-observed region through a grid, and enabling an original coverage problem of a larger region to be converted into a coverage problem of the grid; 2, obtaining a feasible solution on the coarse-grained grid and then cutting down the feasible solution, and finding a better feasible solution on the fine-grained grid; 3, repeatedly refining the grid in a nesting manner,and proposing a method for constructing a near coverage mode on the new grid to prevent all coverage modes from being regenerated each time; and 4, combining grid refinement, construction of a near coverage mode and a dynamic greedy-based heuristic algorithm, and performing multiple iterations to obtain a better feasible solution. According to the method, the satellite task arrangement result taking the minimum completion time as the purpose can be quickly obtained, so that the satellite can finish the observation task as early as possible under sufficient observation resources, the time required for executing the task is shortened, and the working efficiency of the satellite is improved.

The invention provides a scheduling method for a flexible job shop, and belongs to the technical field of dynamic scheduling. The method comprises the following steps: S1, establishing a corresponding mathematical model according to preset processing information in flexible job shop scheduling; S2, establishing a time discrete Markov decision model by taking a time point when the processing of each process is completed as a scheduled decision time point; S3, establishing a corresponding flexible workshop scheduling environment according to the mathematical model and a Markov decision model; and S4, constructing a neural network model according to the number of machines and the number of workpieces, and training the neural network model. According to the method, the flexible workshop scheduling problem is converted into the Markov decision model, and the neural network model is constructed to perform scheduling decision on the flexible workshop, so that the method has high adaptability and real-time performance, a reasonable scheduling scheme can be generated within a second level according to environmental changes, the influence of uncertain disturbance in a workshop environment on the production process is reduced, and the production efficiency of a production line is greatly improved.

The invention discloses a cloud computing task allocation method and device, cloud computing task allocation equipment and a storage medium. The method comprises the steps of receiving a cloud computing task sent by a user and decomposing the cloud computing task into a certain number of sub-tasks; obtaining the type of the subtask and the size of a required arithmetic unit; calculating the numberof arithmetic units required by the same subtask; and allocating each subtask to a corresponding number of arithmetic units, wherein the arithmetic units are authenticated and authorized arithmetic units. According to the method provided by the invention, idle computing resources on the network are fully utilized, the dependence of cloud computing on a large server and a super computer is avoided, cloud computing task allocation is more flexible in time and space, the limitation on the computing scale is smaller, and the method can be widely applied to various application scenes; and the multiple operation units receive the same subtask at the same time, it is guaranteed that the cloud computing task is short in response time and completion time, and then the service quality and the userexperience of the cloud computing platform are improved.

The invention discloses an excavation construction method of a high ground stress and basalt underground factory building cavern, which comprises the following steps of: carrying out layered horizontal pushing construction on a middle part, and carrying out reserved excavation construction on protective layers at two sides; wherein, the middle part has a layer height of 4.0+ / -0.5m, the width of each protective layer is 5+ / -0.5m, a pre-cracking hole is arranged between the upper protective layer and the lower protective layer and the middle layered horizontal pushing, the pre-cracking hole adopts two layers of middle layered pre-cracking blasting, when the excavation construction of the protective layers on the two sides are finished, the system support construction is completed in time. According to the invention, a middle layered excavation mode is adopted, so that the blasting scale can be reduced, and the disturbance to the surrounding rock can be reduced; the pre-cracking hole is arranged between the protective layer and the middle layered horizontal pushing, so that the damage of blasting vibration to a side wall can be reduced, and the stress release is facilitated; the protective layers are reserved on both sides, so that the stress adjustment and relaxation deformation of the excavation surface occur in the protective layers, a permanent side wall cannot be influenced,the excavation work amount of the protective layers is small, the completion time is short, the support can be followed in time, and the influence of bad geology on the stability of the surrounding rock of a high side wall can be effectively controlled.

The present disclosure relates to the field of diagnostics, specifically, to a method of identifying progressing multiple sclerosis (MS) in a subject. At least one performance parameter is determined from a dataset of activity measurements obtained from the subject using a mobile device, and the performance parameter is compared to a reference, whereby a subject with progressing MS will be identified. Also disclosed is a method of recommending an anti-CD20 antibody therapy against MS that includes the steps just mentioned and the further step of recommending the anti-CD20 antibody therapy if the subject suffers from progressing MS. Also disclosed is a mobile device having a processor, at least one sensor and a database as well as software which is tangibly embedded to the device and, when running on said device, carries out the method of this disclosure as well as the use of such a device for identifying a subject suffering from progressing MS.

The invention belongs to the field of big data information processing, and provides a Hadoop optimal parameter evaluation method and device. The Hadoop optimal parameter evaluation method comprises the following steps: receiving jobs transmitted by a client, constructing a job sequence, and determining the number of jobs in the job sequence; according to the number of jobs in the job sequence, calling a matched tuning scheme from a scheme database to evaluate Hadoop parameters, obtaining Hadoop optimal configuration parameters with the shortest job completion time, and outputting the Hadoop optimal configuration parameters to a Hadoop cluster server, wherein a first tuning scheme for a single job and a second tuning scheme for a non-single job are pre-stored in the scheme database.

The invention discloses a preparation method and a use method of black hole liquid for the printed circuit board industry. The black hole liquid comprises the following components: a conductive agent, graphene oxide, a dispersing agent and a binding agent. The method comprises the following steps: by taking a graphite plate as an anode, a titanium plate or a graphite plate as a cathode and ultrapure water or an ammonia water solution as an electrolyte, carrying out electrolysis for a certain time, adding a conductive agent and a binder, and adjusting the pH value to 9-10, so as to obtain the black hole liquid. When the black hole liquid prepared by the method is used for treating the surface of a non-metal base material of a printed circuit board or a hole wall subjected to pretreatment, a conductive film layer with good binding force and conductivity can be obtained.

The invention provides an automatic network cable distributing device which comprises a casing, cables, a baseplate, a cable outlet pillar, inserting and pulling mechanisms, a driving part, a cable plug, a sensor and a controller. The controller starts the driving part according to pre-jumping information and information transmitted by the sensor, and the driving part drives the inserting and pulling mechanisms on two sides of an inserting port to move, so that the cables can start from an initial position and accurately reach the inserting port needing jumping and at the target position according to the positioning sensor. Specifically, the inserting and pulling mechanisms are clamped and pull the cable plug of the cables in pre-jumping out, the cables get away from the initial position, are sequentially wound according to the cable winding rules and move towards the target position, and after reaching the target position, the cables are inserted into a socket at the target position, and cable distribution is finished. The automatic network cable distributing device is compact in structure, simple in dimension, easy to install and maintain, fast to start, short in time for finishing the process, less in components and low in cost and simple in control principle compared with the existing like products.

The invention discloses a method for solving separable task multi-time scheduling model in a distributed-type system. By establishing a new separable task multi-time scheduling model and utilizing genetic algorithm to solve the model, the shortest completion time of a task is acquired. A function expression of a task allocation scheme in regard to scheduling sequence of processors, scheduling times and number of the processors that participates in calculation is derived and further a separable task multi-time scheduling model with the shortest completion time the task as a goal is established. According to the invention, the genetic algorithm for solving the model provided by the invention can solve the best scheduling sequence of the processors, the scheduling times and the number of the processor that participates in the calculation, thus the best task allocation scheme and the shortest completion time of the task can be acquired.

The present disclosure relates to improved light-based assays, especially ligand binding assays, in which light is emitted from moieties stimulated by stimulating moieties. There is provided a method of generating and detecting a light signal comprising (a) providing a fluid sample comprising an analyte of interest; (b) contacting said sample with a first reagent comprising a molecular recognition element that binds to said analyte; (c) contacting said sample with a second reagent that (i) binds to said analyte in the presence of said first reagent; or (ii) binds to said first reagent; wherein said second reagent contains a light-generating reporter or chemiexcitation emitter; (d) removing unbound first and second reagents; (e) introducing into said sample a source of singlet oxygen or a chemiexcitation stimulator; and (f) measuring the production of light from said reporter.

The invention discloses a preparation method of a connecting conductor material for an energy storage system, which comprises the following steps of: fusing and welding a prepared pure nickel foil and a pretreated aluminum material into a nickel-aluminum composite material through a polymer diffusion welding technology in the preparation process, and treating the nickel-aluminum composite material by adopting a linear cutting technology or a blanking technology, and finally, preparing the connecting conductor material for the energy storage system through local polishing and insulating material spraying processes. According to the method, the preparation cost of the material is effectively reduced, the pollution to the environment is reduced, the safety performance of the battery is effectively improved, the service life of the battery is effectively prolonged, and the problems that the sleeve is not attached, the process is complex, and the sleeve is easy to crack are solved. In addition, according to the method, single-face, double-face or local single-face and double-face compounding can be carried out according to needs, the cost is controlled to the minimum under the condition that the using performance is not affected, and the material effectiveness is maximized.

The invention relates to a constant-flow-rate water drainage control method and control system. The control method comprises the following steps: monitoring a liquid level height at an opening-closinggate, and obtaining liquid level height data; calculating a corresponding theoretical overflowing area according to a set water drainage flow rate and the liquid level height data; and adjusting theopening degree of the opening-closing gate and enabling the real-time overflowing area of the opening-closing gate to be equal to the theoretical overflowing area. The constant-flow-rate water drainage control method is capable of realizing accurate and stable control for the water drainage flow rate; and the constant-flow-rate water drainage control system is compact in structure, convenient to install, low in cost, high in response speed, and not liable to cause the problem of blocking and sealing failure.

The invention discloses a distributed machine learning task online scheduling method based on edge cloud cooperation. The method comprises the following steps: step 1, modeling an ML task scheduling problem of minimizing total completion time by using integer linear programming; 2, establishing a lower bound of a target function based on the irrelevant parallel machine model, replacing xjsw and njof the original problem with a new variable njsw, and customizing the original problem again; 3, decoupling the re-customized problem into two optimization problems; 4, for each arrived ML task, sequentially distributing Dj data blocks of the ML task to a worker; and step 5, recording a newly arrived ML task set as [Ja], and after all tasks in the [Ja] are allocated with works, sequentially judging whether each task is using the worker or not. The method has the advantages that cloud and edge server providers can be helped to maximize resource utilization of the cloud and edge server providers so as to obtain economic benefits as high as possible, and meanwhile, dynamic scheduling is performed according to the task load and the demand difference of each user so as to enable the overall training time to be shortest.

A semiconductor memory device includes a selection signal generation unit configured to generate a plurality of selection signals that are sequentially activated, a path selection unit configured to select a transmission path of sequentially input information data in response to the plurality of selection signals, a plurality of first storage units, each configured to have a first storage completion time and store an output signal of the path selection unit, and a plurality of second storage units, each configured to have a second storage completion time, which is longer than the first storage completion time, and store a respective output signal of the plurality of first storage units.

The invention discloses a value log-based checkpoint implementation method and system, a storage medium and equipment, and the method comprises the steps: S1, storing an insertion operation in a memory in a value log implementation process; S2, acquiring a log serial number corresponding to a current check point of a value log system; S3, freezing and storing the memory area of the insertion operation, and changing the attribute of the memory area into read-only; adding the frozen memory area into a to-be-written disk queue, and setting a new writable area for storing insertion operation in the memory; S4, writing to-be-written content into the disk queue into a disk; and S5, writing the log serial number corresponding to the current check point into a check point control file in the disk. According to the method, the check point operation time and the recovery time during downtime can be shortened.

The invention discloses an aerated concrete equipment turning platform for automatically removing waste bricks. The base fixes the feet, the base, and the separation moving device. The flipping table fixing frame is vertically fixed on the workbench. There are two flipping fixing frames that are symmetrical to each other. The base is equipped with a ball mill, bearing seat, bearing, end liner, bead, and oblique grid plate, which realizes that the turning table does not need to manually remove the waste bricks, and directly removes the waste bricks through the ball mill, so that the production efficiency of the turning table is higher. The product completion time is faster, and the turnover table is highly automated.

The present invention relates to a resource requisition scheduling method for data sharding, including: A. determining the maximum possible number of data shards that data can be divided into; B. generating a pre-scheduled resource set; C. determining that each data shard is allocated to a pre-scheduled resource node D. Calculate the final completion time of the task; E. Obtain the completion time and the data fragmentation scale factor; F. Obtain the scale coefficient with the largest value to obtain the actual fragmentation size of the data fragmentation; G. According to the remaining data volume Or the number of remaining shards can be iterated and data sharding is completed; H. According to the pre-segmentation coefficient and the actual and slicing granularity, the final data shard size and corresponding resource scheduling strategy are obtained. The present invention can make full use of the performance of available resource nodes in resource requisition scheduling, adopt a reasonable data fragmentation strategy, and requisition reasonable resource nodes for each data fragmentation to perform data processing, so that the overall task completion time is the shortest, and the task efficiency is effectively improved. execution efficiency.