Applied Mechanics and Materials Vol. 421

Abstract: This paper presents a literature review on applications of Levy flight. Nowadays, Levy flight laws has been used for a broad class of processes such as in physical, chemical, biological, statistical and also in financial. From the review, Levy flight technique has been applied mostly in physics area where the researchers use Levy flight technique to solve and optimize the problem regarding diffusive, scaling and transmission. This paper also reviews the latest researches using modified Levy flight technique such as truncated, smoothly truncated and gradually truncated Levy Flight for optimization. Finally, future trends of Levy flight are discussed.

Abstract: Cuckoo Search (CS) is an optimization algorithm developed by Yang and Deb in 2009. This paper describes an overview of CS which is inspired by the life of a bird family, called Cuckoo as well as overview of CS applications in various categories for solving optimization problems. Special lifestyle of Cuckoo and their characteristics in egg laying and breeding has been the basic motivation for this optimization algorithm. The categories that reviewed are Engineering, Pattern Recognition, Software Testing & Data Generation, Networking, Job Scheduling and Data Fusion and Wireless Sensor Networks. From the reviewed CS mostly applied in engineering area for solving optimization problems. The objective of this paper is to provide overview and summarize the review of application of the CS.

Abstract: Glowworm Swarm Optimization (GSO) algorithm is a derivative-free, meta-heuristic algorithm and mimicking the glow behavior of glowworms which can efficiently capture all the maximum multimodal function. Nevertheless, there are several weaknesses to locate the global optimum solution for instance low calculation accuracy, simply falling into the local optimum, convergence rate of success and slow speed to converge. This paper reviews the exposition of a new method of swarm intelligence in solving optimization problems using GSO. Recently the GSO algorithm was used simultaneously to find solutions of multimodal function optimization problem in various fields in today industry such as science, engineering, network and robotic. From the paper review, we could conclude that the basic GSO algorithm, GSO with modification or improvement and GSO with hybridization are considered by previous researchers in order to solve the optimization problem. However, based on the literature review, many researchers applied basic GSO algorithm in their research rather than others.

Abstract: This paper reviews the applications of Firefly Algorithm (FA) in various domain of optimization problem. Optimization is a process of determining the best solution to make something as functional and effective as possible by minimizing or maximizing the parameters involved in the problems. Several categories of optimization problem such as discrete, chaotic, multi-objective and many more are addressed by inspiring the behavior of fireflies as mentioned in the literatures. Literatures found that FA was mostly applied by researchers to solve the optimization problems in Computer Science and Engineering domain. Some of them are enhanced or hybridized with other techniques to discover better performance. In addition, literatures found that most of the cases that used FA technique have outperformed compare to other metaheuristic algorithms.

Abstract: An improved localization algorithm was proposed to solve the problem of low location accuracy and large computational cost in nearest neighbor (KNN) algorithm for LANDMARC system. The novel algorithm combined RFID and wireless sensor networks. It divided location area into several sub areas, utilized the sensor network to locate the target node to corresponding sub area, removed the reference nodes far from the target node, narrowed down the selection scope of the k value, used KNN algorithm to calculate the coordinate of target node in the sub area and applied the Taylor series iteration to improve the accuracy. Experiment results shows that the proposed algorithm improves the location accuracy evidently.

Abstract: This paper gave an example for the design of automatic image segmentation system by using deep staining of blood cell image. The paper also described how to auto-locate the target position, and how to collect training samples with large entropy further. The spatial information of target object also contained valid information, so this paper put forward to use the relative distance between the inner points and the centre of a circle as a feature of a training sample to work together with the RGB features. And for the segmentation image can be applied to the later medical diagnosis conveniently, the Gauss process classifier had been used in medical image segmentation firstly because of its clear probabilistic interpretation. Compared with SVM, GP is better in this system.

Abstract: Prediction of resting-state electroencephalography (EEG) usinghigh-dimensional pattern is a challenge due to the uniqueness of each persons brainwave. This study uses the headache EEG recording as the example, and predicts the informative different states by using an intelligent feature selection method. Vomiting and nausea are usually appeared in headache attacks, andit is sensitive to light, sound, or movement. In this study, we use the EEG recording with four classes (inter-headache, pre-headache, headache and post-headache) as the medical database. This study focuses three merits: First, we establish two balanced datasets which contain 2-class (inter-headache and headache) and 4-class brainwave datasets from the original imbalanced headache database so that there is no bias of the prediction system. The 2-class dataset consists of 22 subjects and 176 trials, and the 4-class dataset consists of 40 subjects and 320 trials. Secondly, we propose an efficient SVM-based method for predicting the headache attacks from the EEGby using an inheritable bi-objective combinatorial genetic algorithm (IBCGA). IBCGA automatically selects important features from the brainwave, and the 2-class prediction accuracy of leave-one-trial-out independenttest is 81.25%. Third, from the analysis of the brain region and channel frequency, the brain region T4 is the most important brain regions and alpha and beta frequencies are the most informative frequencies.

Abstract: In this paper, a new inexact smoothing method is presented for solving the symmetric conic linear programming (SCLP) in materials. Based on a regularized version of Chen-Harker-Kanzow-Smale smoothing function, our algorithm reformulates the SCLP as an equivalent nonlinear system of equations. At each iteration, Newtons method is adopted to solve the system approximately. Under suitable assumptions, the algorithm is proved to possess global convergence and local superlinear convergence.

Abstract: Information and communication technology is one of the key issues of smart grid and the basis of its realization. To standardization of smart grid information architecture, this paper analyzes smart grid conceptual reference model, propose smart grid hierarchical information architecture, including grid equipment layer, communication gird layer, data storage layer and data application layer. For this information architecture, this paper finally discusses smart gird protection system.

Abstract: T-based work instruction systems help to transfer the diversity of information for workers in an effective manner. In this way, the worker is supported in the comprehension of the task, which leads to such systems receiving increased recognition from manufacturing companies. However, the currently available worker information systems make no statement about how to involve their information processing early in the development process. Because to this, the basic idea of simultaneous engineering could be feasible and a partially automated, timely and cost-effective processing of assembly relevant information could occur. The approach of the development process-oriented, computer integrated documentation and visualisation process for assembly processes (CIV process) consider this problem field and add an innovative contribution.