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Pulsed power supply (PPS) is one of the electromagnetic forming (EMF) system components. Advances in power electronics converters led to more efficient and controllable pulsed power supplies. Development of solid-state based topologies in pulsed power applications have been considered in recent years. Using these topologies gives compactness and easiness to EMF systems unlike conventional structures...
In service function chaining (SFC), end-to-end traffic flows are classified and processed by an ordered set of service functions (SFs). When SF in the chain fails, the corresponding traffic flows cannot be processed further to reach the destination until the failed SF recovers. To cope with the SF failure, failover mechanisms to instantly recover such failed SFs are mandatory. In this paper, we propose...
Sparse code multiple access (SCMA) has been presented as a promising solution for uplink transmission since it enables random access so that the pre-establishment of link can be omitted. However, this randomness could cause codebook collision when different users pick the same codebook. Though the message passing algorithm (MPA) is employed to decode nonorthogonal codewords to lower the complexity,...
In this paper the adaptive mesh model is studied. First we introduce the 3 subdivision method which is already exist. Second, in order to make the simulation result more realistic and reasonable, we extend the traditional scheme and apply two different subdivision schemes on the triangular mesh. At last, a new mesh coarsening method is proposed, with the help of this method, we build a extended adaptive...
Resilience evaluation and enhancement has become a vital issue concerning the effectiveness of a current supply chain. This research paper proposes a multi-tier supplier selection policy for resilience enhancement as well as a customer-service-level oriented resilience measurement approach using on-time delivery rate as the indicator. A simple case study involving main supplier failure disturbance...
Recovery of sparse signals with unknown clustering pattern in the case of having partial erroneous prior knowledge on the supports of the signal is considered. In this case, we provide a modified sparse Bayesian learning model to incorporate prior knowledge and simultaneously learn the unknown clustering pattern. For this purpose, we add one more layer to support-aided sparse Bayesian learning algorithm...
In this paper, a new data-driven ILC method is proposed for I/O constrained nonlinear systems. An iterative dynamic linearization is introduced for the controlled nonlinear systems. All of the constraints on the system inputs and outputs are reformulated with a linear matrix inequality. The learning control law is then developed by minimizing a predesigned cost function subjected to the linear matrix...
In this paper, we aim to implement an urban network-level traffic routing scheme for autonomous vehicles to mitigate congestion in urban areas. We first present an implementation of a region-based dynamic traffic model. Subsequently, we present an innovative predictive routing approach for autonomous vehicles, dynamic forecast routing, and apply it on a set of homogeneous regions, making use of Urban-scale...
Recommenders play a significant role in a trust management framework of a mobile ad hoc network, as a node may not have complete knowledge of all its neighbors since it might not have had any interaction with some of its neighbors. Some of the inherent characteristics of mobile ad hoc network like limited radio range, mobility and noise in the channel, contribute to the incomplete knowledge of a node...
In this paper, a sequential channel sensing algorithm for multichannel heterogeneous Cognitive Radio Networks (CRNs) is studied. More specifically, a new transmission algorithm is introduced and its performance is evaluated via simulations. In the proposed algorithm, referred to as “Distributed algorithm”, we assume that the secondary users select their transmission channels without coordination by...
There arises the need in many wireless network applications to infer and track different models of interest. Some nodes in the network are informed, where they observe the different models and send information to the uninformed ones. Each uninformed node responds to one informed node and joins its group. In this work, we suggest an adaptive and distributed clustering and partitioning approach that...
A Job-shop scheduling problem (JSP) can be formulated as a combinatorial optimization problem. Up to now, the problem has been solved by various metaheuristic methods such as Genetic Algorithm (GA) and Tabu Search (TS). Recently, practical methods for JSP considering various practical constraints have been developed. However, although one of the challenges for practical production environment is considering...
Linearized Bregman iterations are low complexity and high precision approaches for solving the combined l1/l2 minimization problem. In this work we give a derivation of the linearized Bregman iteration and show the links to Kaczmarz's algorithm as well as to sparse least mean squares (LMS) filters. We present a novel extension allowing to perform combined l1/l2 minimization either in an LMS based...
This thesis puts forward a bus signal priority assessment index system, which including bus traffic efficiency, intersection traffic efficiency, implementation difficulty factors of methods and so on. Because there are some missing, uncertain or fuzzy indices, and relevance between indices. And decision-makers would have their subjective preferences. The thesis then puts forward a bus signal priority...
The finite-difference method (FDM) algorithm with staggered grid greatly improved the computational efficiency of solving differential equations in two dimensional simulation of GPR, but the strict Courant-Friedrich-Levy (CFL) condition must be satisfied. In three dimensional simulation of GPR, a maximum time-step size will lead to a serious numerical dispersion, while a minimum time-step size will...
The inefficiency in the use of expensive resource such as Magnetic Resonance Imaging (MRI) will lead to long delays in patient examination which has potential influence on patients care. The main purpose of this study is to improve MRI utilization and to reduce the waiting time of patients including outpatients, inpatients and emergency patients. Scheduling rules are designed on the basis of different...
In this paper, we propose a novel greedy iteration algorithm, called block matching pursuit (BMP), for arbitrary block sparse signal recovery. BMP can recover the target signal without prior information of block structure or block length and can estimate the true sparsity level. In each iteration, BMP processes a correlation test to estimate nonzero entries of signal with a fixed step size, and then...
Carbon Nanotubes (CNT) and graphene as a whole have been of interest since their discovery due to their unique properties. These include, but are not limited to: high electron mobility in room temperatures, relatively high thermal conductivity and possibly the highest resistance to mechanical stress. Hence, it is important to properly model structures and systems that might use graphene in future...
In this paper, we propose a probability based slot allocation scheme named p-persistent for vehicular networks. One vehicular node makes its decision on slot occupation according to the ratio of the slot number it has owned to the average slot number. In other words, more time slots a tagged vehicular node has owned, lower probability it will contend for a new slot with. Through this scheme the slot...
This paper investigates the coordinated multipoint transmission (CoMP) in heterogeneous cellular networks (HCNs) by analyzing a cooperative scheme based on the maximum long-term average received power (MLRP). Using stochastic geometry, the outage probability (OP) and energy efficiency (EE) of a two-tier HCN operating under this scheme are derived, based on which the trade-off between OP and EE is...
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