Adaptive three-dimensional cellular genetic algorithm for balancing exploration and exploitation processes

This paper presents a new adaptive algorithm that aims to control the exploration/exploitation trade-off dynamically. The algorithm is designed based on three-dimensional cellular genetic algorithms (3D-cGAs). In this study, our methodology is based on the change in the global selection pressure induced by dynamic tuning of the local selection rate. The parameter tuning of the local selection method is a way to define the global selection pressure. A diversity speed measure is used to guide the algorithm. Therefore, the integration of existing techniques helps in achieving our aims. A benchmark of well-known continuous test functions and real world problems was selected to investigate the effectiveness of the algorithm proposed. In addition, we provide a comparison between the proposed algorithm and other static and dynamic algorithms in order to study the different effects on the performance of the algorithms. Overall, the results show that the proposed algorithm provides the most desirable performance in terms of efficiency, efficacy, and speed for most problems considered. The results also confirm that problems of various characteristics require different selection pressures, which are difficult to be identified.     

Newcomer adjustment during organizational socialization: A meta-analytic review of antecedents, outcomes, and methods.

The authors tested a model of antecedents and outcomes of newcomer adjustment using 70 unique samples of newcomers with meta-analytic and path modeling techniques. Specifically, they proposed and tested a model in which adjustment (role clarity, self-efficacy, and social acceptance) mediated the effects of organizational socialization tactics and information seeking on socialization outcomes (job satisfaction, organizational commitment, job performance, intentions to remain, and turnover). The results generally supported this model. In addition, the authors examined the moderating effects of methodology on these relationships by coding for 3 methodological issues: data collection type (longitudinal vs. cross-sectional), sample characteristics (school-to-work vs. work-to-work transitions), and measurement of the antecedents (facet vs. composite measurement). Discussion focuses on the implications of the findings and suggestions for future research. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Dynamic Fault-Tolerant three-dimensional cellular genetic algorithms

This paper proposes a new dynamic and algorithm-based approach to achieve fault tolerance using 3D cellular genetic algorithms (Dynamic Fault-Tolerant 3D-cGA). The proposed algorithm is an improved version of our previous algorithm (Fault-Tolerant 3D-cGA) that introduces and utilizes a dynamic adaptation feature to achieve further improvement. In Dynamic Fault-Tolerant 3D-cGA, faulty individuals are isolated and the maximum number of fitness evaluations is recalculated to adapt to faults encountered. To improve the performance of the algorithm, a mitigation technique is integrated into our algorithm by introducing an explicit migration operator. A benchmark of well-known real-world and test problems is used to test the effectiveness of the algorithm in order to investigate the influence of adaptation schemes and migration on algorithm performance. Faulty critical system data is tackled in conjunction with various fault ratios. To illustrate the improvement achieved, Dynamic Fault-Tolerant 3D-cGA is compared with Fault-Tolerant 3D-cGA, the previously proposed algorithm. The overall results demonstrate the ability of Dynamic Fault-Tolerant 3D-cGA to maintain system’s functionality despite an increasing number of faults with up to 40% of processing elements (PEs), and clearly illustrate the importance of migration. Significant improvements in the performance of the algorithm, measured as efficiency, efficacy, and speed, are achieved, especially when migration is employed.     

Modelling the impact of land-cover change on potential soil loss in the Taita Hills,Kenya, between 1987 and 2003 using remote-sensing and geospatial data

In sub-Saharan Africa, natural vegetation is being transformed into agricultural lands at a fast rate, endangering ecosystem services and increasing soil-loss potential, which may trigger land degradation. For the Taita Hills study area in Kenya, multi-temporal land-cover models of 1987, 1999 and 2003, derived from Satellite Pour l'Observation de la Terre (SPOT) imagery using a multi-scale segmentation/object relationship modelling (MSS/ORM) methodology and a rainfall layer, a digital elevation model (DEM) and a digital soil map were applied to model potential soil loss. Population growth in the area has led to a shortage of agricultural land and movement of people to the lowlands, evidenced by a 39% (9.3 km²) increase in croplands from 30% to 41% of the study area during the research time frame. Expansion took place mostly in surrounding foothills and lowlands, at the expense of natural shrubland and grassland, but also occurred in the hills. Universal soil-loss equation (USLE) model results showed a 60% (4 km²) increase in the area of very high potential soil loss, from 7% of the study area in 1987 to 12% in 2003, due mainly to very high soil-loss potential in croplands. Whilst the area of croplands as a whole increased, the relative proportion of very high soil-loss potential in croplands remained 20%, both in 1987 and in 2003, indicating that newly cleared agricultural lands with vulnerable soils are the most at-risk areas.     

Combining functional near-infrared spectroscopy and EEG measurements for the diagnosis of attention-deficit hyperactivity disorder

Neural Computing and Applications - Recently multimodal neuroimaging which combines signals from different brain modalities has started to be considered as a potential to improve the accuracy of...     

Routing table updating by using intelligent agents

In a network, one of the important problems is making an efficient routing decision. Many studies have been carried out on making a decision and several routing algorithms have been developed. In a network environment, every node has a routing table and these routing tables are used for making routing decisions. Nowadays, intelligent agents are used to make routing decisions. Intelligent agents have been inspired by social insects such as ants. One of the intelligent agent types is self a cloning ant. In this study, a self cloning ant colony approach is used. Self cloning ants are a new synthetic ant type. This ant assesses the situation and multiplies through cloning or destroying itself. It is done by making a routing decision and finding the optimal path. This study explains routing table updating by using the self cloning ant colony approach. In a real net, this approach has been used and routing tables have been created and updated for every node.     

PETOOL: MATLAB-based one-way and two-way split-step parabolic equation tool for radiowave propagation over variable terrain

A MATLAB-based one-way and two-way split-step parabolic equation software tool (PETOOL) has been developed with a user-friendly graphical user interface (GUI) for the analysis and visualization of radio-wave propagation over variable terrain and through homogeneous and inhomogeneous atmosphere. The tool has a unique feature over existing one-way parabolic equation (PE)-based codes, because it utilizes the two-way split-step parabolic equation (SSPE) approach with wide-angle propagator, which is a recursive forward–backward algorithm to incorporate both forward and backward waves into the solution in the presence of variable terrain. First, the formulation of the classical one-way SSPE and the relatively-novel two-way SSPE is presented, with particular emphasis on their capabilities and the limitations. Next, the structure and the GUI capabilities of the PETOOL software tool are discussed in detail. The calibration of PETOOL is performed and demonstrated via analytical comparisons and/or representative canonical tests performed against the Geometric Optic (GO) + Uniform Theory of Diffraction (UTD). The tool can be used for research and/or educational purposes to investigate the effects of a variety of user-defined terrain and range-dependent refractivity profiles in electromagnetic wave propagation.

Program summary

Program title: PETOOL (Parabolic Equation Toolbox)Catalogue identifier: AEJS_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEJS_v1_0.htmlProgram obtainable from: CPC Program Library, Queen?s University, Belfast, N. IrelandLicensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.htmlNo. of lines in distributed program, including test data, etc.: 143 349No. of bytes in distributed program, including test data, etc.: 23 280 251Distribution format: tar.gzProgramming language: MATLAB (MathWorks Inc.) 2010a. Partial Differential Toolbox and Curve Fitting Toolbox requiredComputer: PCOperating system: Windows XP and VistaClassification: 10Nature of problem: Simulation of radio-wave propagation over variable terrain on the Earth?s surface, and through homogeneous and inhomogeneous atmosphere.Solution method: The program implements one-way and two-way Split-Step Parabolic Equation (SSPE) algorithm, with wide-angle propagator. The SSPE is, in general, an initial-value problem starting from a reference range (typically from an antenna), and marching out in range by obtaining the field along the vertical direction at each range step, through the use of step-by-step Fourier transformations. The two-way algorithm incorporates the backward-propagating waves into the standard one-way SSPE by utilizing an iterative forward–backward scheme for modeling multipath effects over a staircase-approximated terrain.Unusual features: This is the first software package implementing a recursive forward–backward SSPE algorithm to account for the multipath effects during radio-wave propagation, and enabling the user to easily analyze and visualize the results of the two-way propagation with GUI capabilities.Running time: Problem dependent. Typically, it is about 1.5 ms (for conducting ground) and 4 ms (for lossy ground) per range step for a vertical field profile of vector length 1500, on Intel Core 2 Duo 1.6 GHz with 2 GB RAM under Windows Vista.     

Fracture problems in composite materials

In this paper a series of fracture problems in composite materials are identified, their methods of solution are briefly discussed, and some sample results are presented. The main problem of interest is the determination of the stress state in the neighborhood of localized imperfections such as cracks and inclusions which may exist in the composite. Particular emphasis is placed on the evaluation of quantities such as the stress intensity factors, the power of the stress singularity, and the strain energy release rate, which may be used directly or indirectly in connection with an appropriate fracture criterion for the prediction of fracture initiation and propagation load levels. The topics discussed in the paper include a crack in layered composites, a crack terminating at and going through a bi-material interface, a penny-shaped crack in a filament-reinforced elastic matrix, and inclusion problems in bonded materials.     

Minimizing the surface effect of PDMS–glass microchip on polymerase chain reaction by dynamic polymer passivation

Polydimethyl siloxane (PDMS)–glass microchip has a very strong surface effect on polymerase chain reaction (PCR), leading to a very poor PCR yield. In the work reported here, practical dynamic passivation of surfaces of PDMS–glass microchip using polyethylene glycol (PEG) or polyvinylpyrrolidone (PVP) was achieved using a conventional thermocycler. The passivation procedure was cost‐effective and easy to conduct. The effects of polymer molecular weight and polymer concentration on tube PCR efficiency were investigated primarily to prescreen out suitable polymers and polymer concentrations in the PCR mixture. The result from tube PCR indicated that both PEG and PVP could affect the performance of Taq polymerase. A final concentration of 0.025% (w/v) or 0.4% (w/v) polymer in the PCR mixture can enhance the tube PCR, while 1% (w/v) polymer was found to inhibit the reaction. PEG was more effective in tube PCR, although PVP performed better in chip PCR. Instead of employing the polymer directly in the PCR mixture, i.e. the conventional in situ passivation approach, another approach of dynamic passivation by pre‐injecting polymers into the microchip achieved better performance. The efficiency of pre‐passivation was found to follow the order: PVP10000>PVP55000, PEG8000> PEG10000>PEG400. After pre‐passivation with PVP10000, PVP55000 and PEG8000, the PCR efficiency can recover to 93%, 86% and 83%, respectively, of that obtained from tube PCR. Copyright © 2006 Society of Chemical Industry