Recently, multi-car elevator (MCE) system has captured attention as an effective mean for the improvement of transportation capability in a high-rise building. The MCE has two or more cars in one shaft. In this paper, we propose an algorithm for group controllers of MCE system, and show the effectiveness of our algorithm through computer simulation.

This paper investigates the usefulness of a new priority list for two-processor scheduling problem of program nets. Firstly, we discuss the weakness of a previously proposed priority list and then introduce a new priority list. Through simulation experiment we show that the new priority list is better than the previous one and can generate the same length of schedules as GA scheduling, which implies the new priority list can generate approximately optimal schedules.

Automatic detection of prohibited items is vital in helping security staff be more efficient while improving the public safety index. However, prohibited item detection within X-ray security inspection images is limited by various factors, including the imbalance distribution of categories, diversity of prohibited item scales, and overlap between items. In this paper, we propose to leverage the Poisson blending algorithm with the Canny edge operator to alleviate the imbalance distribution of categories maximally in the X-ray images dataset. Based on this, we improve the cascade network to deal with the other two difficulties. To address the prohibited scale diversity problem, we propose the Re-BiFPN feature fusion method, which includes a coordinate attention atrous spatial pyramid pooling (CA-ASPP) module and a recursive connection. The CA-ASPP module can implicitly extract direction-aware and position-aware information from the feature map. The recursive connection feeds the CA-ASPP module processed multi-scale feature map to the bottom-up backbone layer for further multi-scale feature extraction. In addition, a Rep-CIoU loss function is designed to address the overlapping problem in X-ray images. Extensive experimental results demonstrate that our method can successfully identify ten types of prohibited items, such as Knives, Scissors, Pressure, etc. and achieves 83.4% of mAP, which is 3.8% superior to the original cascade network. Moreover, our method outperforms other mainstream methods by a significant margin.

An automorphism of a graph G=(V, E) is such a one-to-one correspondence from vertex set V to itself that all the adjacencies of the vertices are maintained. Given a subset S of V whose one-to-one correspondence is decided, if the vertices of V-S possess unique correspondence in all the automorphisms that satisfy the decided correspondence for S, S is called determiner set of G. Further, S is called minimal determiner set if no proper subset of S is a determiner set and called kernel set if determiner set S with the smallest number of elements. Moreover, a problem to judge whether or not S is a determiner set is called determiner set decision problem. The purpose of this research is to deal with determiner set decision problem. In this paper, we firstly give the definitions and properties related to determiner sets and then propose an algorithm JDS that judges whether a given S is a determiner set of G in polynomial computation time. Finally, we evaluate the proposed algorithm JDS by applying it to possibly find minimal determiner sets for 100 randomly generated graphs. As the result, all the obtained determiner sets are minimal, which implies JDS is a reasonably effective algorithm for the judgement of determiner sets.

Software testing is an important problem to design a large software system and it is difficult to be solved due to its computational complexity. We try to use program nets to approach this problem. As the first step towards solving software testing problem, this paper provides a technique to generate subnets of a program net and applies this technique to software testing. Firstly, definitions and properties of program nets are introduced based on our previous works, and the explanation of software testing problem is given. Secondly, polynomial algorithms are proposed to generate subnets that can cover all the given program net. Finally, a case study is presented to show how to find subnets covering a given program net by using the proposed algorithms, as well as to show the input test data of the program net for software testing.

This paper provides a list-scheduling method for program nets executed with two processors. The program nets dealt with in this paper are acyclic and SWITCH-less, and the priority list proposed in this paper consists of both dynamic and static lists. First, we point out the weakness of a previously proposed priority list and propose a new priority list. Then we give properties of the new priority list and further prove this new priority list can generate optimal schedules for the program nets whose AND-nodes possess at most single input edge. Finally, we compare the new priority list with the previous one to show the new priority list can generate shorter schedules than the previous for the nets whose AND-nodes may have two input edges.