Tyler's and Maronna's M-estimators, as well as their regularized variants, are popular robust methods to estimate the scatter or covariance matrix of a multivariate distribution. In this work, we study the non...
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This paper presents a meta-surface-inspired antenna with magneto-electric features to reduce the antenna height and achieve low cross-polarization. An advantage of the antenna is that the proposed antenna has a simple...
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ISBN:
(数字)9781665479622
ISBN:
(纸本)9781665479639
This paper presents a meta-surface-inspired antenna with magneto-electric features to reduce the antenna height and achieve low cross-polarization. An advantage of the antenna is that the proposed antenna has a simple design. I addition to this, the proposed antenna has stable gain characteristics of RHCP in the frequency band ranging from 8.2 GHz to 10.2 GHz with a good impedance matching and low-cross polarization in a wide azimuth range.
The flexible job shop scheduling problem (FJSP) is a complex problem with significant applications in modern manufacturing. While various metainspired algorithms are widely used in FJSP, they of-ten converge to local ...
The flexible job shop scheduling problem (FJSP) is a complex problem with significant applications in modern manufacturing. While various metainspired algorithms are widely used in FJSP, they of-ten converge to local optima, especially as the problem size increases. To overcome this, we propose an adaptive hybrid algorithm with three stages of “explore-exploit-escape” (E3HA). In the first stage, we design a Simplified Variable Neighborhood Search (Sim-VNS) algorithm and introduce a Simplified Nopt1 Neighborhood for extensive exploration of solution spaces. In the second stage, we introduce the crossover operation from genetic algorithms to better exploit the elite solutions obtained in the first stage, and we also use mutation operations to improve the quality of regular solutions. Finally, in the third stage, we design a hybrid mechanism of Reverse Learning with Path Relinking (RLPR) and introduce a critical path neighborhood structure to increase the effectiveness of solutions in avoiding local optima and premature convergence. We perform ablation experiments to confirm the effectiveness of each stage of E3HA and test the algorithm on all BRdata and Fdata instances, comparing its performance to relevant existing state-of-the-art algorithms. The results show the effectiveness and stability of our algorithm for FJSP.
Large pre-trained language models are successfully being used in a variety of tasks, across many languages. With this ever-increasing usage, the risk of harmful side effects also rises, for example by reproducing and ...
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Peak-to-average power ratio (PAPR) one of the most important issues in orthogonal frequency division multiplexing (OFDM). Iterative clipping and filtering (CF) is a high efficiency technique to reduce PAPR in OFDM sys...
Peak-to-average power ratio (PAPR) one of the most important issues in orthogonal frequency division multiplexing (OFDM). Iterative clipping and filtering (CF) is a high efficiency technique to reduce PAPR in OFDM systems, but it needs numerous iterations to minimize the peak regrowth problem. This paper presents a new CF method which requires one iteration. The previous method needs 2K+1 IFFT/FFT blocks where K is iterations number. By using this algorithm, the number of FFT and IFFT operations have been decreased to three. The simulated results show that the QPSK modulated OFDM signal with 528 sub-carriers achieves a P APR reduction of 6.1 dB by passing the OFDM signal from white Gaussian noise channel with a good bit error rate performance at the receiver.
Screen printing is a well-known technique for producing disposable and low-cost screen-printed carbon electrode (SPCE) sensor. SPCE sensors have been used in many applications such as disease detection, toxin detectio...
Screen printing is a well-known technique for producing disposable and low-cost screen-printed carbon electrode (SPCE) sensor. SPCE sensors have been used in many applications such as disease detection, toxin detection, disease monitoring for the environment, and food analysis. Despite its outstanding advantages, electrochemical-based SPCE sensors have relatively low sensitivity as compared to chromatography-based and fluorimetry-based conventional sensors. A modification by improving the electrode’s materials may be implemented to produce an effective and sensitive SPCE sensor. Thus, in this study, a comparison of material between laser-induced graphene screen-printed electrode (LIG-SPE) and currently existing and widely used screen-printed carbon electrode (SPCE) is presented. Cyclic Voltammetry (CV) was conducted to compare the performance of the fabricated sensors for electrochemical detection and the R 2 calibration curves were performed to determine the linearity. The results shows that LIG SPE has better linearity (R 2 is 0.9596) compared to SPCE.
Edge computing is a new architectural model that aims to offer computing, storage, and networking resources to support Internet of Things. Its primary strategy involves transferring computational tasks to the edge of ...
Edge computing is a new architectural model that aims to offer computing, storage, and networking resources to support Internet of Things. Its primary strategy involves transferring computational tasks to the edge of network, which is closer to end-users. This paradigm facilitates offloading of computation, resulting in reduced latency and improved system performance. However, nodes located at the network edge have restricted energy and resources. As a result, running tasks entirely at the edge leads to higher energy consumption. This work proposes a novel three-tier offloading framework comprising of multiple mobile vehicles (MVs), a base station (BS), and a cloud data center (CDC). It jointly optimizes offloading rates of tasks, CPU computation rates of MVs, BS, and CDC, and the allocation of wireless bandwidth resources at MVs during partial computation offloading of tasks. It also considers limits of maximum computational resources and maximum delay of task execution. To further reduce the total system energy consumption, this work actively caches execution codes of tasks in MEC servers to reduce data transmission energy of MVs, which minimizes the total system energy consumption. This work develops a mixed integer nonlinear program and designs a mixed meta-heuristic algorithm with a multi-strategy adaptive particle swarm optimizer. Simulation results demonstrate that it outperforms various state-of-the-art algorithms by achieving lower energy consumption in fewer iterations.
The paper deals with the harmonic content of the input current of the voltage mode controlled boost converter in quasiperiodicity. By decrease of the input voltage the converter exhibits quasiperiodicity caused by Hop...
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Sparsity-based tensor recovery methods have shown great potential in suppressing seismic data noise. These methods exploit tensor sparsity measures capturing the low-dimensional structures inherent in seismic data ten...
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This work models a distributed community-based market with diverse assets (photovoltaic generators and energy storage systems), accounting for network constraints and adopting the relaxed branch flow model. The market...
This work models a distributed community-based market with diverse assets (photovoltaic generators and energy storage systems), accounting for network constraints and adopting the relaxed branch flow model. The market is modeled in a single and fully distributed approach, employing the alternating direction method of multipliers (ADMM) to prevent voltage and line capacity problems in the community network and improve data privacy and reduce the communication burden. Different scenarios, based on the penalty term and the agents' number, are tested to study the efficiency of the algorithm and the convergence rate of the ADMM distributed model. The proposed method is tested on 10-bus, 22-bus, and 33-bus medium voltage radial distribution networks, where each node contains a large prosumer with one or several assets. One important conclusion is that the implemented residual balancing technique improves the efficiency of the ADMM distributed algorithm by increasing the convergence rate and reducing the computational time.
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