scholarly journals A Learning-Based Hybrid Framework for Dynamic Balancing of Exploration-Exploitation: Combining Regression Analysis and Metaheuristics

Mathematics ◽  
2021 ◽  
Vol 9 (16) ◽  
pp. 1976
Author(s):  
Emanuel Vega ◽  
Ricardo Soto ◽  
Broderick Crawford ◽  
Javier Peña ◽  
Carlos Castro
Keyword(s):  
Hybrid Approach ◽  
Main Idea ◽  
Spotted Hyena ◽  
Neural Network Approach ◽  
Hybrid Approaches ◽  
Fixed Dimension ◽  
Hybrid Framework ◽  
Tuning Methods ◽  
Exploration Exploitation ◽  
Optimisation Procedure

The idea of hybrid approaches have become a powerful strategy for tackling several complex optimisation problems. In this regard, the present work is concerned with contributing with a novel optimisation framework, named learning-based linear balancer (LB2). A regression model is designed, with the objective to predict better movements for the approach and improve the performance. The main idea is to balance the intensification and diversification performed by the hybrid model in an online-fashion. In this paper, we employ movement operators of a spotted hyena optimiser, a modern algorithm which has proved to yield good results in the literature. In order to test the performance of our hybrid approach, we solve 15 benchmark functions, composed of unimodal, multimodal, and mutimodal functions with fixed dimension. Additionally, regarding the competitiveness, we carry out a comparison against state-of-the-art algorithms, and the sequential parameter optimisation procedure, which is part of multiple successful tuning methods proposed in the literature. Finally, we compare against the traditional implementation of a spotted hyena optimiser and a neural network approach, the respective statistical analysis is carried out. We illustrate experimental results, where we obtain interesting performance and robustness, which allows us to conclude that our hybrid approach is a competitive alternative in the optimisation field.

scholarly journals Comparison of long-read sequencing technologies in interrogating bacteria and fly genomes

2021 ◽  
Author(s):  
Eric S Tvedte ◽  
Mark Gasser ◽  
Benjamin C Sparklin ◽  
Jane Michalski ◽  
Carl E Hjelmen ◽  
...  
Keyword(s):  
Bacterial Genome ◽  
Hybrid Approach ◽  
Cost Effective ◽  
Fruit Fly ◽  
Drosophila Ananassae ◽  
Whole Genome Sequencing Data ◽  
Sequencing Data ◽  
E Coli ◽  
Hybrid Approaches ◽  
Long Read

Abstract The newest generation of DNA sequencing technology is highlighted by the ability to generate sequence reads hundreds of kilobases in length. Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT) have pioneered competitive long read platforms, with more recent work focused on improving sequencing throughput and per-base accuracy. We used whole-genome sequencing data produced by three PacBio protocols (Sequel II CLR, Sequel II HiFi, RS II) and two ONT protocols (Rapid Sequencing and Ligation Sequencing) to compare assemblies of the bacteria Escherichia coli and the fruit fly Drosophila ananassae. In both organisms tested, Sequel II assemblies had the highest consensus accuracy, even after accounting for differences in sequencing throughput. ONT and PacBio CLR had the longest reads sequenced compared to PacBio RS II and HiFi, and genome contiguity was highest when assembling these datasets. ONT Rapid Sequencing libraries had the fewest chimeric reads in addition to superior quantification of E. coli plasmids versus ligation-based libraries. The quality of assemblies can be enhanced by adopting hybrid approaches using Illumina libraries for bacterial genome assembly or polishing eukaryotic genome assemblies, and an ONT-Illumina hybrid approach would be more cost-effective for many users. Genome-wide DNA methylation could be detected using both technologies, however ONT libraries enabled the identification of a broader range of known E. coli methyltransferase recognition motifs in addition to undocumented D. ananassae motifs. The ideal choice of long read technology may depend on several factors including the question or hypothesis under examination. No single technology outperformed others in all metrics examined.

scholarly journals Augmented Reality, Mixed Reality, and Hybrid Approach in Healthcare Simulation: A Systematic Review

2021 ◽  
Vol 11 (5) ◽  
pp. 2338
Author(s):  
Rosanna Maria Viglialoro ◽  
Sara Condino ◽  
Giuseppe Turini ◽  
Marina Carbone ◽  
Vincenzo Ferrari ◽  
...  
Keyword(s):  
Augmented Reality ◽  
Mixed Reality ◽  
Ethical Issues ◽  
Medical Training ◽  
Hybrid Approach ◽  
Dental Surgery ◽  
Feasibility Assessment ◽  
Hybrid Approaches ◽  
Custom Made ◽  
Improved Performance

Simulation-based medical training is considered an effective tool to acquire/refine technical skills, mitigating the ethical issues of Halsted’s model. This review aims at evaluating the literature on medical simulation techniques based on augmented reality (AR), mixed reality (MR), and hybrid approaches. The research identified 23 articles that meet the inclusion criteria: 43% combine two approaches (MR and hybrid), 22% combine all three, 26% employ only the hybrid approach, and 9% apply only the MR approach. Among the studies reviewed, 22% use commercial simulators, whereas 78% describe custom-made simulators. Each simulator is classified according to its target clinical application: training of surgical tasks (e.g., specific tasks for training in neurosurgery, abdominal surgery, orthopedic surgery, dental surgery, otorhinolaryngological surgery, or also generic tasks such as palpation) and education in medicine (e.g., anatomy learning). Additionally, the review assesses the complexity, reusability, and realism of the physical replicas, as well as the portability of the simulators. Finally, we describe whether and how the simulators have been validated. The review highlights that most of the studies do not have a significant sample size and that they include only a feasibility assessment and preliminary validation; thus, further research is needed to validate existing simulators and to verify whether improvements in performance on a simulated scenario translate into improved performance on real patients.

scholarly journals Phenomenological Implications of Modified Loop Cosmologies: An Overview

2021 ◽  
Vol 8 ◽  
Author(s):  
Bao-Fei Li ◽  
Parampreet Singh ◽  
Anzhong Wang
Keyword(s):  
Initial Conditions ◽  
Scale Effects ◽  
Hybrid Approach ◽  
Planck Scale ◽  
Power Spectra ◽  
Big Bang ◽  
Hamiltonian Constraint ◽  
Hybrid Approaches ◽  
Effective Dynamics ◽  
The Big Bang

In this paper, we first provide a brief review of the effective dynamics of two recently well-studied models of modified loop quantum cosmologies (mLQCs), which arise from different regularizations of the Hamiltonian constraint and show the robustness of a generic resolution of the big bang singularity, replaced by a quantum bounce due to non-perturbative Planck scale effects. As in loop quantum cosmology (LQC), in these modified models the slow-roll inflation happens generically. We consider the cosmological perturbations following the dressed and hybrid approaches and clarify some subtle issues regarding the ambiguity of the extension of the effective potential of the scalar perturbations across the quantum bounce, and the choice of initial conditions. Both of the modified regularizations yield primordial power spectra that are consistent with current observations for the Starobinsky potential within the framework of either the dressed or the hybrid approach. But differences in primordial power spectra are identified among the mLQCs and LQC. In addition, for mLQC-I, striking differences arise between the dressed and hybrid approaches in the infrared and oscillatory regimes. While the differences between the two modified models can be attributed to differences in the Planck scale physics, the permissible choices of the initial conditions and the differences between the two perturbation approaches have been reported for the first time. All these differences, due to either the different regularizations or the different perturbation approaches in principle can be observed in terms of non-Gaussianities.

A Hybrid Approach for Person Identification Using Palmprint and Face Biometrics

2015 ◽  
Vol 29 (06) ◽  
pp. 1556009 ◽  
Author(s):  
Mina Farmanbar ◽  
Önsen Toygar
Keyword(s):  
Hybrid Approach ◽  
Principal Component ◽  
Local Binary Patterns ◽  
Recognition System ◽  
Extraction Methods ◽  
Score Level Fusion ◽  
Linear Discriminant ◽  
Hybrid Approaches ◽  
Fusion Methods ◽  
Level Fusion

This paper proposes hybrid approaches based on both feature level and score level fusion strategies to provide a robust recognition system against the distortions of individual modalities. In order to compare the proposed schemes, a virtual multimodal database is formed from FERET face and PolyU palmprint databases. The proposed hybrid systems concatenate features extracted by local and global feature extraction methods such as Local Binary Patterns, Log Gabor, Principal Component Analysis and Linear Discriminant Analysis. Match score level fusion is performed in order to show the effectiveness and accuracy of the proposed schemes. The experimental results based on these databases reported a significant improvement of the proposed schemes compared with unimodal systems and other multimodal face–palmprint fusion methods.

A CNN based Hybrid approach towards automatic image registration

2013 ◽  
Vol 62 (1) ◽  
pp. 33-49 ◽  
Author(s):  
Pattathal V. Arun ◽  
Sunil K. Katiyar
Keyword(s):  
Neural Network ◽  
Image Registration ◽  
Feature Matching ◽  
Spatial Information ◽  
Contextual Information ◽  
Hybrid Approach ◽  
Cellular Neural Network ◽  
Contextual Knowledge ◽  
Neural Network Approach ◽  
Statistical Measures

Abstract Image registration is a key component of various image processing operations which involve the analysis of different image data sets. Automatic image registration domains have witnessed the application of many intelligent methodologies over the past decade; however inability to properly model object shape as well as contextual information had limited the attainable accuracy. In this paper, we propose a framework for accurate feature shape modeling and adaptive resampling using advanced techniques such as Vector Machines, Cellular Neural Network (CNN), SIFT, coreset, and Cellular Automata. CNN has found to be effective in improving feature matching as well as resampling stages of registration and complexity of the approach has been considerably reduced using corset optimization The salient features of this work are cellular neural network approach based SIFT feature point optimisation, adaptive resampling and intelligent object modelling. Developed methodology has been compared with contemporary methods using different statistical measures. Investigations over various satellite images revealed that considerable success was achieved with the approach. System has dynamically used spectral and spatial information for representing contextual knowledge using CNN-prolog approach. Methodology also illustrated to be effective in providing intelligent interpretation and adaptive resampling.

scholarly journals How valuation approach choice affects financial analysts’ target price accuracy

2021 ◽  
Author(s):  
Gülcan Erkilet ◽  
Gerrit Janke ◽  
Rainer Kasperzak
Keyword(s):  
Hybrid Approach ◽  
Financial Analysts ◽  
Theory And Practice ◽  
Target Price ◽  
Hybrid Approaches ◽  
Valuation Technique ◽  
Valuation Methodology ◽  
Market Approach ◽  
Fundamental Value ◽  
A Company

AbstractThis paper examines which valuation approaches financial analysts use to value a company and whether the chosen valuation approach affects the target price accuracy. To address these questions, we conduct content analyses of 867 hand-collected analyst reports on German publicly listed companies published between January 2014 and June 2017. We find that sell-side analysts more frequently use the single-period market approach when formulating target prices, followed by the multi-period income approach, and a mixture of both by combining the results, the so-called hybrid valuation approach. Additionally, we show that 612 of the analyzed analyst reports are based on a holistic valuation methodology instead of a sum of the parts valuation technique. Both univariate and multivariate analyses emphasize that the choice of valuation approach is significantly associated with the accuracy of price targets. Specifically, the income and market approach lead to significantly more accurate target prices compared to the hybrid approach. We also find that the target price accuracy is higher when analysts apply the holistic rather than the sum of the parts valuation approach to determine the fundamental value of the company. Additional results emphasize that target price accuracy improves when analysts use the sum of the parts valuation that bases solely on market or income approaches rather than hybrid approaches. Hence, we contribute to theory and practice by providing evidence on the link between the choice of valuation approach and the analysts’ target price accuracy as well as on the performance of certain valuation techniques.

scholarly journals Urgent hybrid approach in treatment of the acute myocardial infarction complicated by the ventricular septal rupture

2014 ◽  
Vol 142 (3-4) ◽  
pp. 226-228
Author(s):  
Mina Radosavljevic-Radovanovic ◽  
Nebojsa Radovanovic ◽  
Aleksandra Arandjelovic ◽  
Predrag Mitrovic ◽  
Ana Uscumlic ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Acute Myocardial Infarction ◽  
Hybrid Approach ◽  
Stable Condition ◽  
Coronary Intervention ◽  
Operative Risk ◽  
Ventricular Septal Rupture ◽  
Surgical Closure ◽  
Hybrid Approaches ◽  
Hemodynamic State

Introduction. Ventricular septal rupture (VSR) in the acute myocardial infarction (AMI) is a rare but very serious complication, still associated with high mortality, despite significant improvements in pharmacological and surgical treatment. Therefore, hybrid approaches are introduced as new therapeutical options. Case Outline. We present an urgent hybrid approach, consisting of the initial percutaneous coronary intervention (PCI) of the infarct-related artery, followed by immediate surgical closure of the ventricular septal rupture, for treatment of high risk, hemodynamically unstable female patient with AMI caused by one-vessel disease and complicated by VSR and cardiogenic shock. Since the operative risk was also very high (EUROSCORE II 37%), this therapeutic decision was based on the assumption that preoperative PCI could promptly establish blood flow and thereby lessen the risks, duration and complexity of urgent cardiosurgical intervention, performed on the same day. This approach proved to be successful and the patient was discharged from the hospital on the fifteenth postoperative day in stable condition. Conclusion. In selected cases, with high operative risk and unstable hemodynamic state due to AMI complicated by VSR, urgent hybrid approach consisting of the initial PCI followed by surgical closure of VSR may represent an acceptable treatment option and contribute to the treatment of this complex group of patients.

scholarly journals Coupling the Cell Method with the Boundary Element Method in Static and Quasi–Static Electromagnetic Problems

Mathematics ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 1426
Author(s):  
Federico Moro ◽  
Lorenzo Codecasa
Keyword(s):  
Boundary Element Method ◽  
Boundary Element ◽  
Hybrid Approach ◽  
Iterative Solution ◽  
Third Order ◽  
Electromagnetic Problems ◽  
Cell Method ◽  
Hybrid Approaches ◽  
Complex Topology ◽  
Element Method

A unified discretization framework, based on the concept of augmented dual grids, is proposed for devising hybrid formulations which combine the Cell Method and the Boundary Element Method for static and quasi-static electromagnetic field problems. It is shown that hybrid approaches, already proposed in literature, can be rigorously formulated within this framework. As a main outcome, a novel direct hybrid approach amenable to iterative solution is derived. Both direct and indirect hybrid approaches, applied to an axisymmetric model, are compared with a reference third-order 2D FEM solution. The effectiveness of the indirect approach, equivalent to the direct approach, is finally tested on a fully 3D benchmark with more complex topology.

Calibration of impact of attributes in the real estate mass appraisal

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Krzysztof Dmytrów ◽  
Wojciech Kuźmiński
Keyword(s):  
Real Estate ◽  
Design Methodology ◽  
Hybrid Approach ◽  
Calibration System ◽  
Content Type ◽  
The Real ◽  
The Real Estate ◽  
Hybrid Approaches ◽  
Residential Properties ◽  
Statistical Approaches

PurposeOur research aims in designation of a hybrid approach in the calibration of an attribute impact vector in order to guarantee its completeness in case when other approaches cannot ensure this.Design/methodology/approachReal estate mass appraisal aims at valuating a large number of properties by means of a specialised algorithm. We can apply various methods for this purpose. We present the Szczecin Algorithm of Real Estate Mass Appraisal (SAREMA) and the four methods of calibration of an attribute impact vector. Eventually, we present its application on the example of 318 residential properties in Szczecin, Poland.FindingsWe compare the results of appraisals obtained with the application of the hybrid approach with the appraisals obtained for the three remaining ones. If the database is complete and reliable, the econometric and statistical approaches could be recommended because they are based on quantitative measures of relationships between the values of attributes and properties' unit values. However, when the database is incomplete, the expert and, subsequently, hybrid approaches are used as supplementary ones.Originality/valueThe application of the hybrid approach ensures that the calibration system of an attribute impact vector is always complete. This is because it incorporates the expert approach that can be used even if the database excludes application of approaches that are based on quantitative measures of relationship between the unit real estate value and the value of attributes.

scholarly journals Prognostics for an actuator with the combination of support vector regression and particle filter

2019 ◽  
Vol 277 ◽  
pp. 02008
Author(s):  
Runxia Guo ◽  
Jianfei Sui ◽  
Jiusheng Chen
Keyword(s):  
Particle Filter ◽  
Support Vector Regression ◽  
Traditional Approach ◽  
Hybrid Approach ◽  
Support Vector ◽  
Hybrid Framework ◽  
Particle Filter Algorithm ◽  
Kendall Correlation ◽  
Maintenance Schedules ◽  
Traditional Approaches

The accurate prognostics for actuator malfunctions is a challenging task. Developing reliable prognostic methods is vital for providing reasonable preventive maintenance schedules and preventing unexpected failures. Particle filter has been proved to be a traditional approach to deal with actuator prognostic problems. However, the measurement function in the particle filter algorithm cannot be obtained in the prediction process, this paper presents a hybrid framework combining support vector regression (SVR) and particle filter (PF). The SVR output prediction results are employed as the “measurements” for the subsequent PF algorithm. To accomplish the accurate prognostics for actuator fault of civil aircraft, an improved PF based on Kendall correlation coefficient is put forward to solve the problem of particles’ degeneracy. The experimental results are presented, demonstrating that the SVR-PF hybrid approach has satisfactory performance with better prognostics accuracy and higher fault resolution than traditional approaches.

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