Crossover Process Research Articles

Ultraviolet luminescence properties of Te4+-doped YCa4O(BO3)3 phosphors

Te4+-doped YCa4O(BO3)3 phosphors were successfully prepared by a high temperature solid-state reaction method. XRD, SEM and XPS were used to characterize the crystal structure, particle size, morphology and element valence state of the samples. The room temperature fluorescence properties of the phosphors were measured by a fluorescence spectrophotometer. The excitation and emission bands, peaked at 310 nm and 380 nm, correspond to the 1S0→3P1 and 3P0,1 → 1S0 transitions of Te4+ ions, respectively. The 3 mol% Te4+-doped YCa4O(BO3)3 phosphor has the strongest fluorescence with a lifetime of 2.28 and 22.66 μs. The thermal quenching occurs at higher temperature, indicating a non-radiation transition that is dominated by the crossover process. The emission intensity of Te4+-doped YCa4O(BO3)3 phosphors at 380 nm changes linearly with the increase of temperature, suggesting that these fluorescent materials may be applied for temperature sensing.

What a week! A moderated‐mediation crossover model for daily boundary violations at home and partner evening affect

Increasingly blurred boundaries allow work to breach home borders, disrupting personal tasks and goals which feel like violations to employees and thereby may trigger affective strain responses. Yet, the potential adverse effects of boundary violations at home on partner affective strain remains unexplored. Based on affective events and crossover theories, we considered the occurrence of violations at home as work-related stressors originating at home and thereafter evoking emotional strain in partners through employees' own affective strain response. Based on the differential reactivity model, we expected employee affective strain responses to boundary violations at home and subsequent emotional transmission to partners would be exacerbated during a period (i.e., one week) of high emotional strain when employees and partners are hyper-responsive to their home environments. Event data were collected for seven days from 69 employees and partners for 483 data points. Since the occurrence of homebound violations and associated effects on employees and partners likely fluctuates daily, a multilevel two-stage moderated-mediation model was tested. Results showed indirect effects of violations on partner affective strain through employee affective strain, with a backdrop of high emotional strain for the week moderating the affective event and crossover processes. Implications for scholars and organizations are discussed.

Photoinduced Copper-Catalyzed Asymmetric C-O Cross-Coupling.

The construction of carbon-heteroatom bonds is one of the most active areas of research in organic chemistry because the function of organic molecules is often derived from the presence of heteroatoms. Although considerable advances have recently been achieved in radical-involved catalytic asymmetric C-N bond formation, there has been little progress in the corresponding C-O bond-forming processes. Here, we describe a photoinduced copper-catalyzed cross-coupling of readily available oxime esters and 1,3-dienes to generate diversely substituted allylic esters with high regio- and enantioselectivity (>75 examples; up to 95% ee). The reaction proceeds at room temperature under excitation by purple light-emitting diodes (LEDs) and features the use of a single, earth-abundant copper-based chiral catalyst as both the photoredox catalyst for radical generation and the source of asymmetric induction in C-O coupling. Combined experimental and density functional theory (DFT) computational studies suggest the formation of π-allylcopper complexes from redox-active oxime esters as bifunctional reagents and 1,3-dienes through a radical-polar crossover process.

Parameter Analysis of Differential Evolution Based Oversampling Approach for Highly Imbalanced Datasets

Nowadays, almost all performed activities are saved into databases. Data mining methods such as classifiers utilize these datasets for discovering hidden patterns and rules. Proposed methods for classification problems are generally developed considering approximately balanced datasets. However, imbalanced datasets that have the unequal instance numbers in its classes emerges as a common problem in most real domains. Many approaches at the data level are proposed to enable better classification of imbalanced datasets. Differential Evolution Based Oversampling Approach For Highly Imbalanced Datasets (DEBOHID) is one of the proposed method in order to handle this issue on imbalanced datasets. DEBOHID approach utilizes the crossover and mutation processes of DE for generating new synthetic samples. The parameters used by the crossover and mutation processes affect the solution quality. Therefore, in this study, solution quality in highly imbalanced datasets for different crossover and mutation parameter values of DEBOHID approach is investigated. Experimental studies are carried out by using three classifiers and two evaluation metrics for different parameter values. The obtained results are compared with well-known approaches in the literature.

VisEvol: Visual Analytics to Support Hyperparameter Search through Evolutionary Optimization

AbstractDuring the training phase of machine learning (ML) models, it is usually necessary to configure several hyperparameters. This process is computationally intensive and requires an extensive search to infer the best hyperparameter set for the given problem. The challenge is exacerbated by the fact that most ML models are complex internally, and training involves trial‐and‐error processes that could remarkably affect the predictive result. Moreover, each hyperparameter of an ML algorithm is potentially intertwined with the others, and changing it might result in unforeseeable impacts on the remaining hyperparameters. Evolutionary optimization is a promising method to try and address those issues. According to this method, performant models are stored, while the remainder are improved through crossover and mutation processes inspired by genetic algorithms. We present VisEvol, a visual analytics tool that supports interactive exploration of hyperparameters and intervention in this evolutionary procedure. In summary, our proposed tool helps the user to generate new models through evolution and eventually explore powerful hyperparameter combinations in diverse regions of the extensive hyperparameter space. The outcome is a voting ensemble (with equal rights) that boosts the final predictive performance. The utility and applicability of VisEvol are demonstrated with two use cases and interviews with ML experts who evaluated the effectiveness of the tool.

A novel high-sensitive optical thermometer based on the multi-color emission in Pr3+ doped LiLaMgWO6 phosphors

Nowadays, optical thermometric materials with high sensing sensitivity in a wide temperature interval are urgently required due to the appealing prospect in the field of sensing technology. Herein, the double perovskite Pr3+: LiLaMgWO6 phosphors are successfully prepared via a high-temperature solid-state reaction method, and their concentration/temperature-dependent luminescence properties are discussed systematically. Upon UV excitation, the samples emit blue (3P0→3H4), green (3P0,1 → 3H5) and red emissions (1D2→3H4, 3P0→3F2) from Pr3+ ions. The different changing tendencies in relation to temperature are observed for the emissions from 3P0 and 1D2 multiplets, which are attributed to the effects of cross-over process to Pr3+-W6+ intervalence charge transfer (IVCT) state, cross relaxation process and multiphonon relaxation process. When the fluorescence intensity ratio (FIR) between 3P0→3F2 (654 nm) and 1D2→3H4 (616 nm) transitions is applied for temperature sensing, 0.5%Pr3+: LiLaMgWO6 displays a maximum absolute sensing sensitivity of 2421 × 10−4 K−1 at 573 K. Moreover, it can keep a comparatively high relative sensitivity (1%~3.25% K−1) and low temperature uncertainty (0.15–0.5 K) over a wide temperature range (~280 K), which are superior to those of many luminescence materials reported previously. The present study may provide useful design information to develop high-sensitive luminescent thermometers with a wide applicable temperature range.

Photoluminescence, optical transition properties and temperature-induced shift of charge transfer band and temperature sensing property of GdNbTiO6: Sm3+ phosphors

GdNbTiO6: Sm3+ phosphors with various Sm3+ concentrations were prepared via a high temperature solid-state reaction method. The crystal structure of the samples was characterized by means of X-ray diffraction (XRD) and the as-prepared samples were confirmed to be orthorhombic phase GdNbTiO6. Photoluminescence properties were investigated by measuring the concentration- and temperature-dependent photoluminescence spectra. Concentration-dependent luminescence quenching and luminescent thermal quenching behaviors were observed and they were respectively ascribed to the electric dipole-dipole interaction between Sm3+ ions and the cooperation of energy transfer and crossover process. The chromatic characteristics were found to be dependent on the excitation wavelength and Sm3+ concentration. In addition, temperature-induced redshift of charge transfer band of GdNbTiO6 host was found in temperature-dependent excitation spectra and the opposite variations of different excitation peaks were utilized for optical thermometry. Finally, the optical transition property was studied on the basis of the diffuse reflectance spectra and Judd-Ofelt (J-O) theory, meanwhile, its accuracy was evaluated by the result of emission spectra.

A Crossover Algebra for Solving Minimum Spanning Tree in Network Design with Diameter Constraints

The minimum spanning tree problem with diameter constraint is an important problem for many applications such as network design and reliability. The diameter constraint makes it be different from the common minimum spanning tree problem, it is difficult to get the optimal solution, even the feasible solution can not be obtained by the traditional method. To address this problem, in this paper, a new crossover algebra is designed to ensure that the crossover tree still satisfies the diameter constraint. During the crossover process, structure of the subtree will be retained, thus avoiding the problem that the new generated tree is not a feasible solution. Experimental results show the effectiveness of the improved algorithm.

Genetic fuzzy optimized approximate multiplier design based non-linear anisotropic diffusion image denoising in VLSI

Multiplier is a building block used in processor, embedded, Very Large-Scale Integration (VLSI) applications and integrated circuits. There are three main parameters of VLSI design lies in speed, area and power. Approximate computing is a developing one in digital design used to increase the performance. Many conventional methods are introduced for efficient approximate multiplier design. A new approximation multiplier design approach was presented with partial products of multiplier. A new approximate compressor was designed with higher power or speed for target precision. However, the designed approach failed to minimize the design complexity. In order to reduce power consumption and design complexity during the noise removal process, Genetic Fuzzy Optimized Approximate Multiplier based Non-Linear Anisotropic Diffusion Image Denoising (GFOAM-NLADID) Method is introduced. The key objective of the GFOAM-NLADID Method is to perform efficient approximate design using genetic fuzzy concepts for reducing the noise artifacts from input images. GFOAM-NLADID method used genetic fuzzy optimization algorithm to find optimal component (i.e., full adder type, compressor, and tree) for constructing the approximate multiplier design. The optimal component is selected after calculating the fuzzy fitness function. When the fitness function satisfies the fuzzy rule, the component is chosen for efficient design. When the criteria are not satisfied by the particular component, selection, crossover and mutation process is performed to choose the global optimal solution. By choosing the optimal component in GFOAM-NLADID Method, power consumption and design complexity level gets reduced. After designing the approximate multiplier, Non-Linear Anisotropic Diffusion Image Denoising process is carried out in GFOAM-NLADID Method to remove the noisy artifacts and to improve the image quality performance. This in turn helps to improve the peak signal-to-noise ratio performance by GFOAM-NLADID method. Experimental evaluation of GFOAM-NLADID Method is carried out with performance metrics such as power consumption, filtering time and peak signal-to-noise ratio compared to the state-of-the-art works.

Modified Krill Herd Algorithm for constrained economic load dispatch problem

ABSTRACT Meta-heuristic techniques are gaining attractiveness to solve constrained economic load dispatch problems due to higher global solution capacity, flexibility and derivative-free structure. In this paper, Modified Krill Herd Algorithm (MKHA) is used to solve economic load dispatch problem having non-linear characteristics of generators and considering transmission losses. The proposed MKHA is a nature-inspired technique that incorporates crossover and mutation process designed in differential evolution which causes the krill to execute local search within definite section. Constraints manipulation trial is also made functional in the direction of approaching equality constraints to change total power generation depending upon the requirement of power by consumers. The proposed algorithm is testified on three systems and assessment is prepared on the basis of minimisation of fuel cost and arithmetic procedures. Relative examination of obtained outcome illustrates the efficacy of the proposed algorithm, with regard to the quality of solutions and higher efficiency.

For better or for worse family-related well-being: A meta-analysis of crossover effects in dyadic studies.

The present preregistered meta-analysis aimed to assess the evidence regarding the work-family interactions, as dyadic studies report them. The introduction differentiated between spillover (or intra-individual) effects and crossover (or inter-individual) effects by using dyadic studies. Following an online and reference list search, out of the initial 339 studies, 36 eligible articles reported correlations between one partner's variables and the other partner's variables. Analyses included 1504 effect sizes and used meta-analytical calculations and structural equation modeling. Both partners' well-being measures had small proportions of shared variance (i.e. shared variance up to 13.69%). The following analyses focused on the potential effects that could explain the shared variance of family-related well-being. There was little evidence of a crossover effect from one's work-related variables toward the partners' family-related well-being. Furthermore, analyses using structural equation modeling did not yield any results to support a crossover effect from one's work-family interaction toward their partner's well-being. These findings suggest that the literature needs new research studies regarding how family-related demands and resources are related to well-being and personal resources in the crossover processes.

Optimization in job shop scheduling problem using Genetic Algorithm (study case in furniture industry)

Job shop scheduling problem belongs to a class of NP-Hard problems. We solve a scheduling problem in a job shop based furniture company. The company produces several products such as chair, table, home decorations, and home accessories. Currently, the company schedules the order using Earliest Due Date (EDD) and First Come First Serve (FCFS) methods. The best schedule resulted from those methods is then chosen and used as the initial solution for Genetic Algorithm (GA) method. The proposed algorithm is implemented in MATLAB 2019a to minimize the makespan. Parameters used in the GA formation of new generations are done by crossover using the Precedence Preservative Crossover (PPX) method and mutations using job-pair exchange mutations. The selection of chromosomes for regeneration in the crossover process is chosen by two chromosomes that have the best fitness and for the mutation process, one chromosome that has the worst fitness is chosen. Solution from genetic algorithm is better than EDD for the case study. From the results, GA produces shorter makespan compared to EDD and FCFS methods. The EDD method gives a makespan of 104,280 minutes and the FCFS method gives a makespan of 118,440 minutes, while GA provides a makespan of 81,780 minutes.

Parameter tuning of a genetic algorithm for finding central vertices in graphs

This paper studies a genetic algorithm for finding the central vertices in graphs. The algorithm uses a different approach to the solution method presentation and describes a new insight in the crossover process. Studies are conducted to find the optimal parameters of the genetic algorithm such us crossover probability, mutation probability and population size. Based on the results, it can be claimed that with the right parameters, our algorithm shows good running time results with high accuracy of the correct answers.

Chaotic evolutionary algorithms for dynamic instability enhancement

The algorithm principle is presented based on a geometry optimization of aeroelastic energy harvester. Efficiency of this class of devices highly depends on oscillation amplitude caused by dynamic instability of the system, which is related to its geometry. Optimization was performed using a genetic algorithm (GA) that processes data from CFD calculations. This algorithm generated a random population of twenty-arm geometrical figures. Each geometry was subjected to a numerical experiment during which its movement in a fluid-filled channel were simulated and resultant force acting on body was calculated. The calculations were repeated for angular orientation of the object varying from 0 to 180 degrees, at 5 degrees step, in order to obtain a complete characteristic of aerodynamical forces acting on body related to its angular orientation. For each of the obtained functions, satisfaction of Den Hartog’s criterion is examined, which is the basis for geometry evaluation. In order to accelerate the calculations, classical GA has been modified by substituting random crossover process by operation determined by chaotic process — in this case, a logistic map. The numerical calculations was carried by Method of Fundamental Solutions.

With grit to innovative teams?

This article in the Journal Gruppe. Interaktion. Organisation. (GIO) develops a theoretical model for the emergence of team grit, i.e. the competence to pursue long-term goals with passion and perseverance. We examine the role of team grit for today’s dynamic innovation processes, building on findings from research on individual grit. Our model shows how team inputs as well as the dynamic interaction of team processes and affective and cognitive emergent states lead to the emergence of team grit and thus promote team innovation. We explore contagion and crossover processes as mechanisms for team grit to emerge, and examine team processes that we assume to affect team grit. Our model not only provides a starting point for further research on team grit, but also provides practitioners with recommendations to foster team grit in order to improve their innovative performance in the team.

Multiobjective Optimization Configuration of a Prosumer’s Energy Storage System Based on an Improved Fast Nondominated Sorting Genetic Algorithm

With the deepening of the “source-load-storage” interaction and the development of demand response technology, the emergence of prosumers has led to new vitality and potential for the optimal operation of microgrids. By implementing a demand response mechanism for prosumers, peak shaving and valley filling are realized, and load fluctuations are balanced. However, the high costs of investing and operating energy storage system (ESS) restrict their ability to participate in the scheduling of microgrids. In this paper, for the objectives of obtaining the lowest comprehensive costs and the smallest load fluctuations, an INSGA-II (Improved Fast Nondominated Sorting Genetic Algorithm) algorithm is proposed for the multiobjective configuration optimization model of a prosumer’s ESS. To ensure the diversity of the population and improve the search ability of the algorithm in space, based on the original NSGA-II algorithm, the proportion factor set in the selection strategy is improved. The normal distribution crossover operator is introduced in the crossover process, and the local chaotic search strategy is added after the formation of the next generation of the population. An example of a science and technology park with five users is simulated and analyzed. Upon comparison with various typical intelligent algorithms, the results show that the performance of the improved NSGA-II algorithm is the best. At the same time, multiple calculation results show that the improved NSGA-II algorithm has strong algorithmic stability.

An Artificial Bee Colony algorithm for Efficient Optimized Data Aggregation to Agricultural IoT Devices Application

ABSTRACT The current world have structured and gained numerous advantages from state-of-the-art of digital and computerized technologies. Internet of Things (IoT) has recently started playing a key role in day-to-day lives, stretching perceptions, and having the capability to monitor our surrounding environment. The definition for agriculture is given as the practice, science, or art for soil cultivation, crop production utilizing diverse techniques of preparation and technologies, and marketing of farming’s end products. Farmer efficacy and effectively can be enhanced with Wireless Sensor Network (WSN) installation for agricultural practice optimization. Gathering of data from multiple sensors is done during data aggregation. To optimize the data aggregation, metaheuristic methods are applied. The processes of mutation, crossover, and natural selection, are replicated in the evolutionary algorithm known as Genetic Algorithm (GA). Artificial Bee Colony (ABC) algorithm’s primary benefit is that it does not get trapped in the calculation of their local minima, and that it also considers the global and local search. An Artificial Bee Colony (ABC) algorithm has been proposed.

Merging radical-polar crossover/cycloisomerization processes: access to polyfunctional furans enabled by metallaphotoredox catalysis

Metallaphotoredox catalysis for furan synthesis: The cyclisation of yne-enones proceeds smoothly via consecutive reductive radical-polar crossover and cycloisomerization processes enabled by cooperative photoredox-neutral and copper catalysis.

A New Approach Method of Crossover Process Based On Genetic Algorithm Using High Dimensional Benchmark Functions

A New Approach Method of Crossover Process Based On Genetic Algorithm Using High Dimensional Benchmark Functions

Modular access to 1,2-allenyl ketones based on a photoredox-catalysed radical-polar crossover process.

Herein, a new protocol dealing with the preparation of 1,2-allenyl ketones has been successfully developed via the reactions of enynes with radicals enabled by dual photoredox/copper catalysis. Based on the results of a deuteration experiment and the competition reaction between cyclopropanation and allenation, the mechanism based on a photoredox-neutral-catalysed radical-polar crossover process has been proposed. Synthetic applications of allenes have also been demonstrated.