The proportion of cyanobacterial biomass (PCB) can indicate the dominance of cyanobacteria in water, and it provides important information regarding the phytoplankton composition. Variations in the PCB can clarify the cyanobacteria accumulation process. Therefore, using remote sensing to obtain the spatial-temporal distribution of the PCB in inland lakes is very important for understanding the cyanobacterial bloom process. A total of 357 water samples was collected from three Chinese eutrophic inland lakes: Taihu Lake, Dianchi Lake, and Chaohu Lake, over eight field campaigns from 2013 to 2018. A normalized index of the PCB (NIPCB) was proposed using the absorption of chlorophyll-a (Chl-a) at 665 nm (achl(665)) and the absorption of phycocyanin (PC) at 620 nm (apc(620)) to indicate the PCB. A classification method using the PC index (PCI) was developed to identify the water types using the different algae composition features, and the relationship between the NIPCB and PCB in two water types was extensively examined. Finally, a semianalytical algorithm was developed to estimate the PCB based on the NIPCB index and the OLCI bands. The result of the estimated accuracy assessment using the independent validating data set demonstrated that the algorithm performance is satisfactory with mean absolute percentage error (MAPE) of 31.01% and root mean square error (RMSE) of 0.20. The MUMM method was then applied to conduct an OLCI image atmospheric correction with a satisfactory performance with the MAPE calculated between the measured remote sensing reflectance and the retrieved remote sensing from a satellite image of less than 25%. Consequently, the developed algorithm was successfully applied to three OLCI images of Dianchi Lake on April 12, 2017, Taihu Lake on May 18, 2017, and Chaohu Lake on September 8, 2018. The spatial distribution of the PCB in these three inland lakes is reasonable, and it demonstrated that the developed algorithm could be used to effectively monitor PCB at a large scale and provide important assistance in predicting the cyanobacterial blooms in eutrophic inland lakes by using remote sensing.

In this paper, we present a filtered beam search method to solve deadlock-free scheduling problems in FMSs, which are proven to be NP-hard. Some methods in literatures have been proposed to solve those problems, however, they are very time-consuming and not applicable in large scale systems. The algorithm presented in this paper is based on a fast and approximate heuristic method in searching decision trees, so it is very competitive in computation expense. With two evaluation functions, the proposed algorithm provides a trade-off between the solution quality and search effort. Siphon technology is used to prevent deadlock and reduce the complexity of the scheduling problem by searching only the necessary portion of the search graph.

An efficient algorithm based on graph-theoretic approach and genetic algorithm for finding optimal deadlock-free schedules in the automated manufacturing systems with limited central buffers is presented. The scheduling problem introduced In this work involves sequencing the operations on resources to avoid the deadlock situation and to minimize the makespan. With the help of digraph models of automated manufacturing systems, deadlock avoidance policy is proposed to supervise the release and acquisition of resources. In order to satisfy the deadlock free constraint of chromosomes, the deadlock avoidance policy is embedded into the decoding procedure of genetic algorithm and after adaptation of gene sequences, the feasibility of solutions can always be guaranteed for the peculiarity of the scheduling problem. With this deadlock free scheduling method, the optimal deadlock free schedules can be got under the restriction of different buffer capacities. The efficiency of deadlock free scheduling algorithm is proved by simulation results.

A class of flexible manufacturing systems is modeled by timed Petri nets, and a new deadlock free scheduling method based on genetic algorithm and timed Petri net model is proposed. Under the framework of timed Petri nets model, the scheduling problem can be formulated as finding a feasible transition firing sequence to avoid the deadlock situation and to minimize the makespan. In the genetic algorithm, Petri net transition sequence is coded and a deadlock detection method based on siphon technology is addressed to reschedule the sequence of transitions, and thus the quality of solutions can be improved. In the fitness computation procedure, a penalty item for the infeasible solution is involved to prevent the search process from converging to the infeasible solutions. The method proposed In this work can get a feasible scheduling strategy as well as enable the system to achieve good performance, and this is shown by simulation results.

Deadlock must be avoided in a manufacturing system. In this paper, an efficient algorithm for finding a good deadlock-free schedule in a manufacturing system with enough (sufficient) or limited buffer is presented. This algorithm is based on the effective genetic algorithm (GA) search method. A formal Petri net structure is introduced, and the token player is used to assure deadlock freeness. In order to make the scheduling strategy generated by GA meet the required deadlock-free constraint, a Petri net is involved in checking the implementation of a manufacturing system during the job-scheduling process. The effectiveness and efficiency of the proposed approach is illustrated by several examples.

Flexible Manufacturing System (FMS) is a complex asynchronous concurrent system. The model of FMS should have the abilities to express the concurrency in the system and to analyze the behavior of the system. It is difficult to use any one method to model such a complex system as FMS. A modeling and verifying method using object-oriented modeling language "Unified Modeling Language (UML)" and SPIN (PROMELA model) is presented in this paper. Class diagram in UML is used to represent the static relations among the objects in FMS, and state diagram is used to describe the dynamic behaviour of the system. Then the UML model is translated into PROMELA model automatically, and property checking is followed with SPIN which is a model checking tools. The method can describe and check the properties of the system (from modeling, simulation, to model checking), and can be used to design reliable FMS control software naturally.

A modeling method for controller in FMS is presented. This method is based upon the timed automata. Model checker tool UPPAAL is used to model, simulate and verify the FMS model. In the previous work about FMS modeling, the behavior of FMS is more emphasized than the performance, or vice versa. Because the time is included into the modeling method in this paper, the scheduling and controlling problems in FMS can be integrated into this model. The performance of the system can be guaranteed while the system behavior is controlled. Upon this model, the optimal scheduling and optimal controlling can also be checked and verified.

A deadlock-free unsafe (DFU) state of Resource Allocation System (RAS) is deadlock-free but inevitable to enter a deadlock state. Previous research revealed that in many special systems, DFU states do not exist and polynomial deadlock avoidance policy (DAP) using one-step look ahead algorithms can avoid deadlock states. This paper first establishes the NP-completeness on determining the existence of DFU states. Then, giving necessary conditions of DFU states based on digraph analysis, it provides polynomial avoidance policies that inhibit loading new jobs to avoid DFU states. Furthermore, this method is generalized to mixed capacity systems and systems with flexible routings. Examples and simulation results are also presented.

This paper presents a method for deadlock avoidance algorithm used in Flexible Manufacturing System(FMS). This method is an improvement of the Banker algorithm. The Banker algorithm is commonly used in the operating system (OS), but some improvement will have to be made on the algorithm if this algorithm is used in FMS. The difference between the process in operating system and the job in the FMS is fully discussed. Based on this difference, the improvement is made. In order to improve the algorithm, formal methods are adopted to the manufacturing systems. The simulation model is translated into a format suitable for model checking. That is, the model is written into PROMELA, the input language of the popular model checker SPIN. After that, SPIN is used to verify that the model does not have deadlock.

A modeling method for controller in FMS is presented. This method is based upon the timed automata. Model checker tool UPPAAL is used to model, simulate and verify the FMS model. In the previous work about FMS modeling, the behavior of FMS is more emphasized than the performance, or vice versa. Because the time is included into the modeling method in this paper, the scheduling and controlling problems in FMS can be integrated into this model. The performance of the system can be guaranteed while the system behavior is controlled. Upon this model, the optimal scheduling and optimal controlling can also be checked and verified.

Cloth draping is of particular interest in the field of garment engineering. Most cloth draping simulation stresses the visual effects of garment design. However, the accuracy of the draping effect should not be overlooked, particularly for garment manufacturing. The accuracy of the draping behaviour is largely affected by the fabric properties. This paper discusses the issue of incorporating the fabric properties into the cloth model, so that its draping behaviour can be realistically simulated. These fabric properties are expressed in terms of a set of measurable mechanical properties. The draping behaviour of the cloth is derived based on elastic theory. Dynamic draping simulation is presented with illustrative examples.