Dragonfly Algorithm (DA) is a recent swarm-based optimization method that imitates the hunting and migration mechanisms of idealized dragonflies. Recently, a binary DA (BDA) has been proposed. During ...the algorithm iterative process, the BDA updates its five main coefficients using random values. This updating mechanism can be improved to utilize the survival-of-the-fittest principle by adopting different functions such as linear, quadratic, and sinusoidal. In this paper, a novel BDA is proposed. The algorithm uses different strategies to update the values of its five main coefficients to tackle Feature Selection (FS) problems. Three versions of BDA have been proposed and compared against the original DA. The proposed algorithms are Linear-BDA, Quadratic-BDA, and Sinusoidal-BDA. The algorithms are evaluated using 18 well-known datasets. Thereafter, they are compared in terms of classification accuracy, the number of selected features, and fitness value. The results show that Sinusoidal-BDA outperforms other proposed methods in almost all datasets. Furthermore, Sinusoidal-BDA exceeds three swarm-based methods in all the datasets in terms of classification accuracy and it excels in most datasets when compared in terms of the fitness function value. In a nutshell, the proposed Sinusoidal-BDA outperforms the comparable feature selection algorithms and the proposed updating mechanism has a high impact on the algorithm performance when tackling FS problems.
•This paper proposes an improved Binary Dragonfly Algorithm (BDA) for Feature Selection.•Three versions of BDA are proposed: LBDA, QBDA, and SBDA .•Eighteen datasets taken from UCI machine learning repository are used for evaluation process.•SBDA excels LBDA and QBDA in terms of accuracy, number of features, and fitness function.•SBDA excels the nine comparative methods in 12 out of 18 dataset in terms of accuracy.
Dielectric microcavities with quality factors (Q-factors) in the thousands to billions markedly enhance light-matter interactions, with applications spanning high-efficiency on-chip lasing, frequency ...comb generation and modulation and sensitive molecular detection. However, as the dimensions of dielectric cavities are reduced to subwavelength scales, their resonant modes begin to scatter light into many spatial channels. Such enhanced scattering is a powerful tool for light manipulation, but also leads to high radiative loss rates and commensurately low Q-factors, generally of order ten. Here, we describe and experimentally demonstrate a strategy for the generation of high Q-factor resonances in subwavelength-thick phase gradient metasurfaces. By including subtle structural perturbations in individual metasurface elements, resonances are created that weakly couple free-space light into otherwise bound and spatially localized modes. Our metasurface can achieve Q-factors >2,500 while beam steering light to particular directions. High-Q beam splitters are also demonstrated. With high-Q metasurfaces, the optical transfer function, near-field intensity and resonant line shape can all be rationally designed, providing a foundation for efficient, free-space-reconfigurable and nonlinear nanophotonics.
Optical computing holds significant promise of information processing with ultrahigh speed and low power consumption. Recent developments in nanophotonic structures have generated renewed interests ...due to the prospects of performing analog optical computing with compact devices. As one prominent example, spatial differentiation has been demonstrated with nanophotonic structures and directly applied for edge detection in image processing. However, broadband isotropic two-dimensional differentiation, which is required in most imaging processing applications, has not been experimentally demonstrated yet. Here, we establish a connection between two-dimensional optical spatial differentiation and a nontrivial topological charge in the optical transfer function. Based on this connection, we experimentally demonstrate an isotropic two-dimensional differentiation with a broad spectral bandwidth, by using the simplest photonic device, i.e. a single unpatterned interface. Our work indicates that exploiting concepts from topological photonics can lead to new opportunities in optical computing.
This article proposes a novel parametric modeling technique incorporating a joint polynomial-transfer function with neural networks (short for neuro-PTF) for electromagnetic (EM) behaviors of ...microwave filters. In the proposed technique, the polynomial function is introduced together with the pole-residue-based transfer function to represent the EM responses. The pole-residue-based transfer function is used to represent the whole EM response at the beginning and is subsequently divided into multiple subtransfer functions where each subtransfer function contains one pair of pole/residue. A novel smoothness-discriminating algorithm is proposed to judge the smoothness of each subtransfer function response and separate the pole/residue pairs whose subtransfer function response is determined to be smooth. The proposed method introduces low nonlinear polynomial functions to re-fit the smooth parts of subresponse and remains the nonsmooth parts of subresponse for the highly nonlinear transfer functions to represent. By this way, the proposed method avoids the discontinuity problems of nonunique parameter extraction caused by fitting smooth curves using the highly nonlinear transfer function. Neural networks are proposed to learn the relationship between the polynomial coefficients/poles/residues and the geometrical parameters. Utilizing both advantages of the polynomial functions and transfer functions, the proposed method can produce more accurate models than the existing neuro-TF methods, especially with large geometrical variations. The accuracy and robustness of the proposed technique are demonstrated using three EM application examples of microwave filters.
Purpose:
This paper reports on the design and initial imaging performance of a dedicated cone-beam CT (CBCT) system for musculoskeletal (MSK) extremities. The system complements conventional CT and ...MR and offers a variety of potential clinical and logistical advantages that are likely to be of benefit to diagnosis, treatment planning, and assessment of therapy response in MSK radiology, orthopaedic surgery, and rheumatology.
Methods:
The scanner design incorporated a host of clinical requirements (e.g., ability to scan the weight-bearing knee in a natural stance) and was guided by theoretical and experimental analysis of image quality and dose. Such criteria identified the following basic scanner components and system configuration: a flat-panel detector (FPD, Varian 3030+, 0.194 mm pixels); and a low-power, fixed anode x-ray source with 0.5 mm focal spot (SourceRay XRS-125-7K-P, 0.875 kW) mounted on a retractable C-arm allowing for two scanning orientations with the capability for side entry, viz. a standing configuration for imaging of weight-bearing lower extremities and a sitting configuration for imaging of tensioned upper extremity and unloaded lower extremity. Theoretical modeling employed cascaded systems analysis of modulation transfer function (MTF) and detective quantum efficiency (DQE) computed as a function of system geometry, kVp and filtration, dose, source power, etc. Physical experimentation utilized an imaging bench simulating the scanner geometry for verification of theoretical results and investigation of other factors, such as antiscatter grid selection and 3D image quality in phantom and cadaver, including qualitative comparison to conventional CT.
Results:
Theoretical modeling and benchtop experimentation confirmed the basic suitability of the FPD and x-ray source mentioned above. Clinical requirements combined with analysis of MTF and DQE yielded the following system geometry: a ∼55 cm source-to-detector distance; 1.3 magnification; a 20 cm diameter bore (20 × 20 × 20 cm3 field of view); total acquisition arc of ∼240°. The system MTF declines to 50% at ∼1.3 mm−1 and to 10% at ∼2.7 mm−1, consistent with sub-millimeter spatial resolution. Analysis of DQE suggested a nominal technique of 90 kVp (+0.3 mm Cu added filtration) to provide high imaging performance from ∼500 projections at less than ∼0.5 kW power, implying ∼6.4 mGy (0.064 mSv) for low-dose protocols and ∼15 mGy (0.15 mSv) for high-quality protocols. The experimental studies show improved image uniformity and contrast-to-noise ratio (without increase in dose) through incorporation of a custom 10:1 GR antiscatter grid. Cadaver images demonstrate exquisite bone detail, visualization of articular morphology, and soft-tissue visibility comparable to diagnostic CT (10–20 HU contrast resolution).
Conclusions:
The results indicate that the proposed system will deliver volumetric images of the extremities with soft-tissue contrast resolution comparable to diagnostic CT and improved spatial resolution at potentially reduced dose. Cascaded systems analysis provided a useful basis for system design and optimization without costly repeated experimentation. A combined process of design specification, image quality analysis, clinical feedback, and revision yielded a prototype that is now awaiting clinical pilot studies. Potential advantages of the proposed system include reduced space and cost, imaging of load-bearing extremities, and combined volumetric imaging with real-time fluoroscopy and digital radiography.
In this work, an enhanced moth flame optimization (MFO) algorithm is proposed as a search strategy within a wrapper feature selection (FS) framework. It aims mainly to improve the classification ...tasks in medical applications. FS is an NP-hard problem because the run time of its procedure grows exponentially. The persistent necessity for a powerful FS system and the promising results of swarming behavior in various optimization scenarios motivated our attempts to develop a new FS approach. This paper uses a recently developed methodology inspired by the moth movement style in searching for a near-optimal feature subset for reliable disease diagnosis. The proposed modification strategy is based on two stages of enhancement. In the first stage, eight binary variants are produced using eight transfer functions. In the second stage, the Levy flight operator is integrated into the structure of MFO in combination with transfer functions. The main target is to increase the diversity of the algorithm and support the exploration of the search space. Twenty-three medical data sets downloaded from UCI, Keel, Kaggle data repositories are used to validate the proposed approaches. It has been demonstrated that the proposed approach significantly outperforms other well-known wrapper approaches across 83% of data sets. Furthermore, the proposed approach outperforms other methods in the literature across 75% of the data sets. The comparisons with filter-based approach reveal superior performance across 70% of the data sets. This work also conducts an extensive investigation of the parameters and studies the effects of different settings on the performance of the FS process. The empirical results and various comparisons reveal a remarkable effect of the Levy flight operator and transfer functions on the performance of MFO. This can be achieved through improving the diversity, achieving a greater exploration/exploitation trade-off, and enhancing the convergence trends of the optimizer.
On the Prediction of Solar Cycles Courtillot, V.; Lopes, F.; Le Mouël, J. L.
Solar physics,
2021/1, Letnik:
296, Številka:
1
Journal Article
Recenzirano
Odprti dostop
This article deals with the prediction of the upcoming solar activity cycle, Solar Cycle 25. We propose that astronomical ephemeris, specifically taken from the catalogs of aphelia of the four Jovian ...planets, could be drivers of variations in solar activity, represented by the series of sunspot numbers (SSN) from 1749 to 2020. We use singular spectrum analysis (SSA) to associate components with similar periods in the ephemeris and SSN. We determine the transfer function between the two data sets. We improve the match in successive steps: first with Jupiter only, then with the four Jovian planets and finally including commensurable periods of pairs and pairs of pairs of the Jovian planets (following Mörth and Schlamminger in
Planetary Motion, Sunspots and Climate, Solar-Terrestrial Influences on Weather and Climate
, 193,
1979
). The transfer function can be applied to the ephemeris to predict future cycles. We test this with success using the “hindcast prediction” of Solar Cycles 21 to 24, using only data preceding these cycles, and by analyzing separately two 130 and 140 year-long halves of the original series. We conclude with a prediction of Solar Cycle 25 that can be compared to a dozen predictions by other authors: the maximum would occur in 2026.2 (± 1 yr) and reach an amplitude of 97.6 (± 7.8), similar to that of Solar Cycle 24, therefore sketching a new “Modern minimum”, following the Dalton and Gleissberg minima.
This paper proposes a novel technique to develop a low-cost electromagnetic (EM) centric multiphysics parametric model for microwave components. In the proposed method, we use space mapping ...techniques to combine the computational efficiency of EM single physics (EM only) simulation with the accuracy of the multiphysics simulation. The EM responses with respect to different values of geometrical parameters in nondeformed structures without considering other physics domains are regarded as coarse model. The coarse model is developed using the parametric modeling methods such as artificial neural networks or neuro-transfer function techniques. The EM responses with geometrical and nongeometrical design parameters as variables in the practical deformed structures due to thermal and structural mechanical stress factors are regarded as fine model. The fine model represents the behavior of EM centric multiphysics responses. The proposed model includes the EM domain coarse model and two mapping neural networks to map the EM domain (single physics) to the multiphysics domain. Our proposed technique can achieve good accuracy for multiphysics parametric modeling with fewer multiphysics training data and less computational cost. After the modeling process, the proposed model can be used to provide accurate and fast prediction of EM centric multiphysics responses of microwave components with respect to the changes of design parameters within the training ranges. The proposed technique is illustrated by a tunable four-pole waveguide filter example at 10.5-11.5 GHz and an iris coupled microwave cavity filter example at 690-720 MHz.
1. Large differences exist in the predictions of plant responses to climate change among models that consider population variation and those that do not. Models that treat species as homogeneous ...entities typically predict net positive impacts of climate change on temperate forest productivity, while most studies that consider adaptive genetic variation within species conclude that the impacts of climate change on forest productivity will be negative. 2. We present a modelling approach that predicts plant responses to climate change using both ecological and genetic variables. The model uses growth data from multi-site provenance trials together with climate data for provenance source locations and test sites to predict distribution and productivity of tree populations under climate change. We used an extensive lodgepole pine Pinus contorta provenance data set to illustrate the model. 3. Spatially explicit predictions of the impacts of climate change on production were developed and suggested that different populations of lodgepole pine will respond very differently to climate change. Large production losses will be seen in many areas, although modest production increases may occur in some areas by 2085. The model further projects a significant redistribution of the species' potential habitat northwards and upwards in altitude over the next several decades. 4. Synthesis and applications. This study points to the need to consider population differences when modelling biotic responses to climate change, and suggests that climate change will render populations maladapted in many areas. The model also provides a key tool potentially to mitigate climate change impacts by identifying populations expected to be best adapted throughout the next generation of forests. Finally, the study highlights the value of wide-ranging long-term provenance tests in addressing key issues in ecology and climate change.
There are several methods for estimating the SoC of lithium-ion batteries that use electrochemical battery models or artificial intelligence and intelligent algorithms. These methods have numerous ...advantages but are complex and computationally intensive. This paper presents a new method for estimating the SoC of lithium-ion batteries based on identifying the transfer function of the measured battery voltage response to the charging current pulse. It is assumed that the transfer function of the battery changes with the state of charge. In the learning phase, a reference table of known SoCs and associated transfer functions is created. The parameters of these transfer functions form the reference points in hyperspace. In the phase of determining the unknown SoC of the battery, the parameters of the measured transfer function form a point in hyperspace that is compared with the reference points of the transfer functions for known SoCs. The unknown SoC of the battery at the particular measurement time is obtained by finding the two reference points closest to the point of unknown SoC using the Euclidean distance and a linear interpolation based on this distance. The method is simple, computationally undemanding, insensitive to measurement noise, and has high accuracy in SoC estimation.
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