This paper studies stabilization of logical control systems (LCSs) using an event-triggered control strategy. First, an LCS is converted into its algebraic state-space representation. In this framework, a stabilizabil...
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This paper studies stabilization of logical control systems (LCSs) using an event-triggered control strategy. First, an LCS is converted into its algebraic state-space representation. In this framework, a stabilizability criterion for LCSs is established, and the optimal triggering control problem is formulated. The goal of the optimal triggering control is to drive the LCS to a desired state while minimizing the number of states that trigger the control action. Then, the equivalence between designing the optimal triggering controller for an LCS and finding the minimum-weight arborescence in the corresponding transition graph is proved. Subsequently, based on the depth-first search and utilizing a Fibonacciheap-typed data structure, algorithms are established to determine the stabilizability of LCSs and to design the optimal triggering controller. Finally, an example involving the lac operon in the bacterium Escherichia coli is presented to illustrate the obtained results. (c) 2025 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
To calculate probabilistic damage stability for ships, it is crucial to generate damage scenarios that account for the vast number of possibilities and the inherent complexity of structural configurations. This proces...
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This paper proposes a teaching construction strategy based on the OBE concept for the core course of computer science majors in our university, data structure. The strategy aims to focus on the graduation requirements...
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ISBN:
(纸本)9798400712692
This paper proposes a teaching construction strategy based on the OBE concept for the core course of computer science majors in our university, data structure. The strategy aims to focus on the graduation requirements of our university, clarify the course objectives, innovate the teaching mode, and set reasonable evaluation methods. After nearly two years of teaching practice and evaluation, this paper analyzes the effectiveness of teaching reform and puts forward suggestions for continuous improvement.
In this paper we discuss the data structure and algorithms for the direct application of generalized Leibnitz rules to the numerical computation of partial derivatives in forward mode. The proposed data structure prov...
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In this paper we discuss the data structure and algorithms for the direct application of generalized Leibnitz rules to the numerical computation of partial derivatives in forward mode. The proposed data structure provides constant time access to the partial derivatives, which accelerates the automatic differentiation computations. The interaction among elements of the data structure is explained by several numerical examples. The paper contains analysis of the developed data structure and algorithms. Copyright (C) 2003 John Wiley Sons, Ltd.
Power consumption has become a limiting factor in designing next generation network routers. Recent observation shows that IP lookup engines dominate the power consumption of core routers. Previous work on reducing po...
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Power consumption has become a limiting factor in designing next generation network routers. Recent observation shows that IP lookup engines dominate the power consumption of core routers. Previous work on reducing power consumption of routers mainly focused on network-and system-level optimizations. This paper represents the first thorough study on the data structure optimization for lowering the power consumption in static random access memory (SRAM)-based IP lookup engines. Three different SRAM-based IP lookup architectures are discussed: nonpipelined, simple pipelined, and memory-balanced pipelined architectures. For each architecture, we formulate the problem of power minimization by revisiting the time-space tradeoff in multibit tries. Two distinct multibit trie algorithms are investigated: the expanded trie and the tree bitmap trie, which are widely used in SRAM-based IP lookup solutions. A theoretical framework is proposed to determine the optimal strides for building a multibit trie so that the worst-case power consumption of the IP lookup architecture is minimized. Experiments using real-life routing tables including both IPv4 and IPv6 data sets demonstrate that careful selection of strides in building the multibit tries can reduce the power consumption dramatically. We believe our methodology can be applied to other variants of multibit tries and can help in designing more power-efficient SRAM-based IP lookup architectures.
Algorithm Visualisation (AV) tool is commonly used to learn data structures. However, since that tool does not address technical details, some students may not know how to implement the data structures. This paper int...
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Algorithm Visualisation (AV) tool is commonly used to learn data structures. However, since that tool does not address technical details, some students may not know how to implement the data structures. This paper integrates the AV tool with Program Visualisation (PV) tool to help the students understanding the data structures' implementation. The integration (which is implemented as a tool named DS-PITON) works similarly as a PV tool except that the data structures are visualised with the AV tool. Through quasi experiments, it can be stated that DS-PITON helps students to get better assessment score and to complete their assessment faster (even though the impact on completion time can work in reverse on slow-paced students). Further, according to a questionnaire survey, the students believe that DS-PITON helps them learning data structure materials. (C) 2019 Production and hosting by Elsevier B.V. on behalf of Faculty of Computers and Information, Cairo University.
Companies of the single and small batch production, which supply machines, tools, fixtures and devices, highly contribute to the performance of series production and the quality of products manufactured. To obtain the...
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Companies of the single and small batch production, which supply machines, tools, fixtures and devices, highly contribute to the performance of series production and the quality of products manufactured. To obtain the current market position and differentiate from international competitors, the potentials given by Industry 4.0 need to be tackled. One potential lays in the development of a knowledge management system to store sensitive knowledge and manage it efficiently. Prequisite is a substantial data base which is obtained by a digital shadow to track the company's performance close to realtime. This paper focuses on the development of a data structure for companies of the single and small batch production to implement the digital shadow to enable the efficient use of a knowledge management system. (C) 2019 The Authors. Published by Elsevier B.V.
The article considers the research of the process of modeling firefighting stations. We presented them as queuing systems, which widely used for similar tasks. For creation the model we use discrete events and Agent-b...
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ISBN:
(纸本)9781538643402
The article considers the research of the process of modeling firefighting stations. We presented them as queuing systems, which widely used for similar tasks. For creation the model we use discrete events and Agent-based technology, AnyLogic tools in combination with the GIS map. Hybrid model contains Java programming code and AnyLogic Process Modelling Library. We determined data structure and a set of parameters which allows research the functionality of fire cars management. As criteria of functionality we use the level of cars' utilization and the response time. The conducted experiments confirmed the correctness of our approach and the functionality of the created model.
A streaming graph is a graph formed by a sequence of incoming edges with time stamps. Unlike the static graphs, the streaming graph is highly dynamic and time-related. Streaming graphs in the real world, which are of ...
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A streaming graph is a graph formed by a sequence of incoming edges with time stamps. Unlike the static graphs, the streaming graph is highly dynamic and time-related. Streaming graphs in the real world, which are of the high volume and velocity, can be challenging to the classic graph data structures: data of internet traffic, social network communication, and financial transections, etc. The traditional graph storage models like the adjacency matrix and the adjacency list are no longer sufficient for the large amount data and high frequency updates. And most the streaming graph structures are only supports the specific graph algorithms. Here a new data structure is presented to meet the challenge: a double orthogonal list in hash table (Dolha) as a high speed and high memory efficiency graph structure. Dolha has constant time cost for single edge processing, and near-linear space cost. Moreover, time cost for neighborhood queries in Dolha is linear, which enables it to support most algorithms of graphs without extra cost. A persistent structure based on Dolha is also presented, to handle the sliding window update and time related queries.
Objective. Due to the variability of human movements, muscle activations vary among trials and subjects. However, few studies investigated how data organization methods for addressing variability impact the extracted ...
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Objective. Due to the variability of human movements, muscle activations vary among trials and subjects. However, few studies investigated how data organization methods for addressing variability impact the extracted muscle synergies. Approach. Fifteen healthy subjects performed a large set of upper limb multi-directional point-to-point reaching movements. Then, the study extracted muscle synergies under different data settings and investigated how data structure prior to synergy extraction, namely concatenation, averaging, and single trial, the number of considered trials, and the number of reaching directions affected the number and components of muscle synergies. Main results. The results showed that the number and components of synergies were significantly affected by the data structure. The concatenation method identified the highest number of synergies, and the averaging method usually found a smaller number of synergies. When the concatenated trials or reaching directions was lower than a minimum value, the number of synergies increased with the increase of the number of trials or reaching directions;however, when the number of trials or reaching directions reached a threshold, the number of synergies was usually constant or with less variation even when novel directions and trials were added. Similarity analysis also showed a slight increase when the number of trials or reaching directions was lower than a threshold. This study recommends that at least five trials and four reaching directions and the concatenation method are considered in muscle synergies analysis during upper limb tasks. Significance. This study makes the researchers focus on the variability analysis induced by the diseases rather than the techniques applied for synergies analysis and promotes applications of muscle synergies in clinical scenarios.
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