Abstract: A device for recognizing wafer identification number with automatically turning on and off recognizing function comprises a base, a support frame, a light source, a plurality of image capturing units, an image recognition unit and a control unit. The base comprises a wafer boat placing portion and a first switch disposed on the wafer boat placing portion. The light source and the image capturing units are disposed on the support frame. The control unit is electrically connected to the first switch, the light source, the image capturing units and the image recognition unit. As such, the device for recognizing wafer identification number with automatically turning on and off recognizing function can automatically turn on and off the light source, the image capturing units, and the image recognition unit, therefore the operation is very easy and convenience.

Abstract: Provided is a wafer notch automated aligner, including a main body, a wafer rotation mechanism, and a wafer positioning mechanism. The main body has a wafer boat placement portion. The wafer rotation mechanism is disposed on the main body and includes a rotor, the rotor extends through the wafer boat placement portion, and an angle between an axis of the rotor and the main body is between 0° and 90°. The wafer positioning mechanism is disposed on the main body and includes a positioning member, the positioning member extends through the wafer boat placement portion, and an axis of the positioning member is parallel to the axis of the rotor. Hence, a plurality of wafers is disposed in a stepped arrangement by the inclined rotor and the inclined positioning member, and the wafer notch automated aligner can rotate wafers, align notches, and identify wafer identifications.

Abstract: A method for calculating a total transmission probability within a social network based on timing includes a path probability calculating step, a first binary-addition tree searching step, a second binary-addition tree searching step and a transmission probability calculating step. The path probability calculating step is performed to calculate a plurality of time-path probability matrices from the social network. The first binary-addition tree searching step is performed to enumerate a plurality of feasible spread vectors and a plurality of 1-lag temporal vectors. The second binary-addition tree searching step is performed to enumerate a plurality of time-slot vectors of each of the 1-lag temporal vectors. The transmission probability calculating step is performed to calculate the total transmission probability of the social network. The time-path probability matrices are corresponding to a plurality of time values, and the time values are in the specific time and different from each other.

Abstract: A method for calculating a total transmission probability within a social network based on timing includes a path probability calculating step, a first binary-addition tree searching step, a second binary-addition tree searching step and a transmission probability calculating step. The path probability calculating step is performed to calculate a plurality of time-path probability matrices from the social network. The first binary-addition tree searching step is performed to enumerate a plurality of feasible spread vectors and a plurality of 1-lag temporal vectors. The second binary-addition tree searching step is performed to enumerate a plurality of time-slot vectors of each of the 1-lag temporal vectors. The transmission probability calculating step is performed to calculate the total transmission probability of the social network. The time-path probability matrices are corresponding to a plurality of time values, and the time values are in the specific time and different from each other.

Abstract: A predicting method of a plurality of wildfire propagation areas includes a network constructing step, a normalized adjacency matrix constructing step, a node ranking value calculating step, a state ranking value calculating step, a source node determining step and an occurrence probability calculating step. The node ranking value calculating step is performed to calculate a ranking value and a plurality of states of each of the nodes. The normalized adjacency matrix constructing step is performed to construct a normalized matrix. The state ranking value calculating step is performed to calculate a state ranking value and a state probability of each of the nodes. The source node determining step is performed to determine a source node of the wildfire propagation areas and the states corresponding to the source node. The occurrence probability calculating step is performed to calculate the occurrence probability of the wildfire propagation areas.

Abstract: A binary-addition tree algorithm-based network assessment method includes performing a parameter setting step, an arc enumerating step and an evaluating step. The parameter setting step is performed to set a plurality of state values of a state vector of one of a plurality of paths to 0, wherein the state vector of the one of the paths is represented by a binary value, and the state values of the state vector of the one of the paths are corresponding to a plurality of arcs, respectively. The arc path enumerating step is performed to enumerate all of the state values of the state vectors of the paths by adding 1 to the binary value corresponding to the state values of the state vector of the one of the paths according to a binary-addition tree algorithm. The evaluating step is performed to evaluate the state of the paths.

Abstract: A method for selecting single target node within a social network is configured to select the single target node and deliver a message. A node providing step is performed to set one of nodes within the social network as a source node. A probability calculating step is performed to calculate a plurality of propagation-node numbers of the source node according to a Monte Carlo module and a layered-search module. An expected value generating step is performed to generate an expected value according to the propagation-node numbers and a plurality of propagating success probabilities. A target node selecting step is performed to reset another of the nodes as the source node and repeat the probability calculating step and the expected value generating step to generate another expected value, and compare the expected value with the another expected value to select the single target node having a maximum expected value.

Abstract: A method for selecting multiple target nodes within a social network includes a selecting step, a simulation passing node number calculating step and a target node updating step. The selecting step is performed to select a plurality of simulation nodes from a plurality of nodes in the social network according to a simplified swarm forming rule. The simulation passing node number calculating step is performed to calculate a simulation passing node number of the simulation nodes according to a Monte Carlo simulation method and a layer search method. The target node updating step is performed to update the simulation nodes and the simulation passing node number as the target nodes and the target passing node number according to a simplified swarm updating rule, respectively.

Abstract: A reliability evaluating method for a multi-state flow network and a system thereof are presented. The method includes following steps: finding candidate path sets included in the multi-state flow network; converting the candidate path sets into candidate path values according to a prime number function; removing the repeated candidate path values to keep the corresponded candidate path sets as the non-repeated minimal path; calculating the reliability of the multi-state flow network based on the data flow and data load of the minimal path sets.

Abstract: A land battle process evaluation method and system thereof are provided. The land battle result evaluation method includes a flow network for presenting the land battle process problem. The flow network includes a plurality of land nodes and a plurality of connection paths for connecting the plurality of land nodes. A source node and a sink node may be disposed in the plurality of land nodes. A plurality of attack paths are formed by a combination of the plurality of connection paths from the source node to the sink node. The actual process of the land battle is simulated by the flow network and the probability of the various attack plans are obtained, such that the practical command is provided by reference to the evaluation result.

Abstract: A product disassembling method and non-transitory computer readable media thereof are provided. According to the components of the product and the disassembling attributes of the components, the disassembling sequence that minimizes the total disassembling time can be planned. The method includes the following steps: an initial disassembling sequence solution is randomly generated. The disassembling sequence solution is updated by using an update mechanism. The disassembling time of the update disassembling sequence solution is calculated by using a fitness function. The best fitness value is obtained after the continuously updating, so as to determine whether to update or maintain the initial disassembling sequence solution. The corresponding disassembling sequence is considered as the best planning result.

Abstract: A management method for objects supply and a management system using the same are provided. The management method is adapted to an object-supply network model including a start point, an end point, multiple sub-points and multiple sub-routes, and includes following steps: obtaining a plurality of object states and corresponding probability distributions of each supply sub-route and connection relationships among the supply sub-routes; listing a plurality of object supply routes corresponding to each of the object states, and calculating supply route reliability values of the respective object supply routes by a network reliability algorithm; and, managing the input objects and output objects according to the object supply route with the maximum supply route reliability value.

Abstract: A method and a system of evaluating traffic network reliability adapted to a traffic route network with sub-routes are provided.

Abstract: A project management method and a system thereof are provided. The method adapted for a project network model with multiple edges includes following steps: obtaining multiple assignment values of each edge, multiple state distributions corresponding to the assignment values, a connecting configuration between the edges, and an assignment upper bound and a demand level of the project network model; enumerating at least one project path composed of the edges; enumerating at least one critical value assignment vector according to the assignment values of each edge and the assignment upper bound; calculating a project reliability for each critical value assignment vector according to the at least one project path; and, selecting a critical value assignment vector with a maximal project reliability of the at least one critical value assignment vector to perform a value assignment for the project network model.

Abstract: A method and a system of evaluating traffic network reliability adapted to a traffic route network with sub-routes are provided.

Abstract: Disclosed are a reliability evaluation system for multi-state flow network and a method thereof. The system includes an element-gaining module and a reliability calculation module. The method includes using a GCF calculating means to calculate an initial reliability according a first and second system-state vector, comparing values of all elements in a set being composed of elements of a second grade of a third system-state vector, excluding an element with a greater value and other related thereof in all grades in the third system-state vector when only one element in the set except the element with greater values so as to obtain remaining elements, using the GCF calculating means to perform the calculation of the remaining element to obtain a calculation results, and summing the initial reliability and the calculation results so as to obtain a reliability of the multi-state flow network.

Abstract: A network reliability evaluation method for an acyclic network and a system thereof are provided. The network reliability evaluation method searches all minimal paths from a source node to a sink source based on nodes according to the properties of the acyclic network. In conventional network reliability evaluation methods, searching all minimal paths is based on arcs. Therefore, the network reliability evaluation method and the system thereof can effectively reduce the complexity of calculation.

Abstract: A reliability evaluating method for multi-state flow network with learning effect and a non-transitory storage device are provided. The method includes following steps: finding a plurality of minimum paths of the multi-state flow network; each arc of the plurality of minimum paths generating greater a load requirement capacity by the learning effect; judging whether the load requirement capacity is matching the maximum capacity and finding the system state vector; and calculating the reliability of the multi-state flow network as a basis for decision-making.

Abstract: A reliability evaluating method for multi-state flow network with learning effect and a non-transitory storage device are provided. The method includes following steps: finding a plurality of minimum paths of the multi-state flow network; each arc of the plurality of minimum paths generating greater a load requirement capacity by the learning effect; judging whether the load requirement capacity is matching the maximum capacity and finding the system state vector; and calculating the reliability of the multi-state flow network as a basis for decision-making.

Abstract: A product disassembling method and non-transitory computer readable media thereof are provided. According to the components of the product and the disassembling attributes of the components, the disassembling sequence that minimizes the total disassembling time can be planned. The method includes the following steps: an initial disassembling sequence solution is randomly generated. The disassembling sequence solution is updated by using an update mechanism. The disassembling time of the update disassembling sequence solution is calculated by using a fitness function. The best fitness value is obtained after the continuously updating, so as to determine whether to update or maintain the initial disassembling sequence solution. The corresponding disassembling sequence is considered as the best planning result.