A Fuzzy Data Envelopment Analysis (FDEA) is a popular technique to measure the relative efficiency of a Decision Making Unit (DMU) with respect to other DMUs under uncertain/imprecise information represented in form o...
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ISBN:
(纸本)9781665444071
A Fuzzy Data Envelopment Analysis (FDEA) is a popular technique to measure the relative efficiency of a Decision Making Unit (DMU) with respect to other DMUs under uncertain/imprecise information represented in form of fuzzy input and fuzzy output. However, in a real life application, due to higher order of uncertainty, the fuzzy set may not be a suitable choice, as the membership value alone cannot represent the input/output information precisely. Therefore in the paper, we extend the FDEA model to Intuitionistic Fuzzy Data Envelopment Analysis (IFDEA) model, namely, Parabolic Intuitionistic Fuzzy based Data Envelopment Analysis, where the input and output are demonstrated by Parabolic Intuitionistic Fuzzy Numbers (PIENs). Further the alpha-cut and beta-cut approach are used to convert the parabolic intuitionistic fuzzy inputs and outputs into their corresponding intervals and to compute the parametric efficiencies of the given DMUs. Additionally, we have used the section formula to defuzzify the parabolic intuitionistic fuzzy numbers into their crisp form to execute the optimization problem. Finally, the cross-efficiency technique is used to rank the DMUs.
This study addresses the problem of synthesising functional observers for positive time-delay systems subjected to unknown inputs. A functional observer architecture for the problem is presented. The existence conditi...
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This study addresses the problem of synthesising functional observers for positive time-delay systems subjected to unknown inputs. A functional observer architecture for the problem is presented. The existence conditions of the observer and a linear programming problem characterising the existence conditions of such a functional observer are also established. An algorithm for designing the observer is presented. Finally, examples are given to showcase the effectiveness of the observer.
As the data traffic is increasing, the spectrum bands are getting congested. It causes low latency and unreliable communication. Additional spectrum can be utilized to solve this problem but moving towards higher freq...
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As the data traffic is increasing, the spectrum bands are getting congested. It causes low latency and unreliable communication. Additional spectrum can be utilized to solve this problem but moving towards higher frequency means higher power requirement and increased cost. Cognitive radio network is another solution to this problem. It helps the nodes of a network to use the channels of the nearby bands which are not being used at that time. However, it has several challenges. One of these challenges is the transmission collision with the primary users of the network. Researchers have been working on this problem. However, it is still a major concern for the researchers. This paper proposes an algorithm that selects the optimal cognitive channel for the data transmission by the secondary user in such a way so that the transmission collision with the PU is minimized. After comparison with the existing latest similar protocol, the proposed protocol has shown 5.6% improvement in the throughput, 5.3% improvement in PDR. The delay is decreased by 0.6% and the transmission collision with PUs is reduced by 2.5%. (c) 2022 Elsevier B.V. All rights reserved.
Mathematical metabolic modelling is a systematic endeavour to allow identifying the main causes of an observed metabolic change and to estimate the consequences of an imposed metabolic perturbation regarding a biosyst...
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Mathematical metabolic modelling is a systematic endeavour to allow identifying the main causes of an observed metabolic change and to estimate the consequences of an imposed metabolic perturbation regarding a biosystem. Dynamic Constraint-based modelling (DCBM) has delivered promising results in metabolic engineering and in bioprocess design by providing mechanistically relevant systems-level knowledge of a network of bioreactions. Here, we seek to establish a DCBM approach that leverages convex optimization and nonlinear regression mathematical toolkit to estimate dynamic intracellular metabolic flux distributions in stored Red Blood Cells (RBCs) for transfusion purposes. First, we developed an ad-hoc metabolic network including 77 reactions and 74 metabolites, second, we adapted Flux Variability Analysis (FVA) technique to quantify the connection between exometabolomic dynamics and the dynamics of feasible intracellular reaction flux ranges. We have obtained fine-grained flux range dynamics of the intracellular reactions for the benchmark data published in (Bordbar et al., 2016). Then, we defined four objective functions regarding the accumulation of oxidative stress in stored RBCs for performing a dynamic Flux Balance Analysis (DFBA). In all four cases, time-resolved flux predictions were obtained respecting the imposed equality and inequality constraints. Last, we adapted a quadratic programming (QP) approach to calculate the Euclidean distance between the dynamic optimum flux vectors. The DCBM approach we have developed herein along with the developed metabolic network showed being suitable for the computational analysis of RBCs metabolic behaviour, and it is thought to be useful for other biosystems.
The intelligence exhibited by machines in decision making using mathematical algorithms in contrast to the human intelligence is known as artificial intelligence (AI). It is an area of engineering science that focuses...
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Beacon-based indoor positioning is popular in recent years. In this work, the authors aim to enhance the positioning accuracy by proposing signal power ranking (SPR) and solving related optimisation-based deployment p...
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Beacon-based indoor positioning is popular in recent years. In this work, the authors aim to enhance the positioning accuracy by proposing signal power ranking (SPR) and solving related optimisation-based deployment problem of beacons using wireless communication and Bluetooth 4.0 Bluetooth low-energy network technologies. The authors first adopt grid-based field to be the proposed deployment field. Second, they convert the received signal strength indicator (RSSI) to several levels called SPR. Third, an optimisation-based model for deployment problem of beacons in indoor positioning is proposed on the basis of the above two considerations. The proposed model is to minimise the number of beacons required under some fundamental conditions including full coverage and full discrimination, respectively. Finally, the algorithm of simulated annealing is applied to solve the linear programming problem in this model. By the optimal results, the user can obtain a vector table of RSSI for each location efficiently in the test field. On the other hand, the user in the test field can receive the beacon RSSI value at the same time. In order to determine the user's location, the received beacon RSSI value is compared with the values in the vector table.
So far, the research of wireless powered communication networks (WPCNs) mainly considers the scenarios with a single radio-frequency (RF) energy transmitter (ET) and a single sink. However, in practice, there are many...
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So far, the research of wireless powered communication networks (WPCNs) mainly considers the scenarios with a single radio-frequency (RF) energy transmitter (ET) and a single sink. However, in practice, there are many applications where multiple ETs and sinks need to be deployed. This study focuses on large-scale WPCNs having multiple RF ETs and sinks. Specifically, the authors aim to minimise the total energy provision by optimising ETs' transmit powers with the node-throughput demand and sum-throughput demand, respectively. For the node-throughput demand case, they firstly formulate it to be a convex optimisation problem, then transform it to be a linearprogramming (LP) problem, and finally present a distributed algorithm to obtain the optimal solution. For the sum-throughput demand case, they firstly formulate it to be a non-linear optimisation problem, then prove its convexity and finally propose an efficient dual subgradient algorithm to obtain the optimal solution. Simulation results demonstrate that compared to the sum-throughput demand, imposing the node-throughput demand can effectively alleviate the throughput unfairness at the cost of increased energy provision;the proposed optimal algorithms can substantially decrease the total energy provision of ETs;the energy provision reduction percentage achieved by their schemes increases as the number of ETs increases.
In this study, the problem of joint relay selection and power allocation (J-RS-PA) for NOMA-based multicast cognitive radio networks is considered. In particular, the aim is to simultaneously maximise the end-to-end S...
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In this study, the problem of joint relay selection and power allocation (J-RS-PA) for NOMA-based multicast cognitive radio networks is considered. In particular, the aim is to simultaneously maximise the end-to-end SINR/SNR of the primary and secondary transmitter-receiver (TR) pairs, subject to quality-of-service (QoS) constraints. Communication between the primary and secondary TR pairs is performed over two-phases, namely, the broadcasting phase, and the cooperation phase. In the broadcasting phase, the primary and secondary transmitters broadcast their data symbols;while in the cooperation phase, the selected relay forwards the decoded symbols to their intended receivers. However, the formulated J-RS-PA problem happens to be non-convex, resulting in computationally-prohibitive complexity. Consequently, an optimal low-complexity two-stage relay selection and power allocation (TS-RS-PA) algorithm is devised, which is based on the solution of linear programming problem reformulations. Simulation results are presented to validate the proposed TS-RS-PA algorithm, which is shown to yield the optimal SINR/SNR values in comparison to the J-RS-PA scheme, but with lower computational complexity, while satisfying QoS constraints.
In this paper, a method is proposed to solve Fuzzy linear Fractional programming (FLFP) problem where cost of the objective function, the resources and the technological coefficients are triangular fuzzy numbers. Here...
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ISBN:
(纸本)9781479900206
In this paper, a method is proposed to solve Fuzzy linear Fractional programming (FLFP) problem where cost of the objective function, the resources and the technological coefficients are triangular fuzzy numbers. Here, the FLFP problem is transformed into an equivalent deterministic Multi-Objective linear Fractional programming (MOLFP) problem. By using Fuzzy Mathematical programming approach transformed MOLFP problem is reduced single objective linearprogramming (LP) problem. The proposed procedure illustrated through a numerical example.
This work exploits Timed Continuous Petri Nets (TCPN) to design and test a novel energy-efficient thermal-aware real-time global scheduler for a hard real-time (HRT) task set running on a multiprocessor system. The TC...
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This work exploits Timed Continuous Petri Nets (TCPN) to design and test a novel energy-efficient thermal-aware real-time global scheduler for a hard real-time (HRT) task set running on a multiprocessor system. The TCPN model encompasses both the system and task set, including thermal features. In previous work we calculated the share of each task that must be executed per time interval by solving off-line an Integer programmingproblemproblem (ILP). A subsequent on-line stage allocated jobs to processors. We now perform the allocation off-line too, including an allocation controller and an execution controller in the on-line stage. This adds robustness by ensuring that actual task allocation and execution honor the safe schedule provided off-line. Last, the on-line controllers allow the design of an improved soft RT aperiodic task manager. Also, we experimentally prove that our scheduler yields fewer context switches and migrations on the HRT task set than RUN, a reference algorithm. Copyright (C) 2020 The Authors.
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