There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

This chapter introduces the finite element method (FEM) as a tool for solution of classical electromagnetic problems. Although we discuss the main points in the application of the finite element method to electromagnetic design, including formulation and implementation, those who seek deeper understanding of the finite element method should consult some of the works listed in the bibliography section.

Introduction to the Finite Element Method

This chapter introduces the subject of statistical pattern recognition (SPR). It starts by considering how features are defined and emphasizes that the nearest neighbor algorithm achieves error rates comparable with those of an ideal Bayes’ classifier. The concepts of an optimal number of features, representativeness of the training data, and the need to avoid overfitting to the training data are stressed. The chapter shows that methods such as the support vector machine and artificial neural networks are subject to these same training limitations, although each has its advantages. For neural networks, the multilayer perceptron architecture and back-propagation algorithm are described. The chapter distinguishes between supervised and unsupervised learning, demonstrating the advantages of the latter and showing how methods such as clustering and principal components analysis fit into the SPR framework. The chapter also defines the receiver operating characteristic, which allows an optimum balance between false positives and false negatives to be achieved.

Statistical Pattern Recognition

This study provides a bibliographic review in the broad field of green composites seeking-out for materials with a potential to be applied in the near future on automotive body panels. Hereupon, materials deriving from renewable resources will be preferred as opposed to the exhaustible fossil products. With the technical information of bio-polymers and natural reinforcements a database was created with the mechanical performance of several possible components for the prospect green composite. Following the review, an assessment is performed where aspects of suitability for the candidate elements in terms of mechanical properties are analyzed. In that section, renewable materials for matrix and reinforcement are screened accordingly in order to identify which hold both adequate strength and stiffness performance along with affordable cost so as to be a promising proposal for a green composite.

Green composites: A review of adequate materials for automotive applications

http://jultika.oulu.fi/files/nbnfi-fe2017112150815.pdf

One-part alkali-activated materials : a review

A fundamental issue in manufacturing systems is moving a local manufacturer into a supply chain network including wholesalers and retailers. In this research, a 3-phase framework is proposed to determine the food consumption pattern in food supply chains. In the first stage of this research, the consumer, availability and society factors for product classification according to the features of populations in Malaysia are identified (phase 1). Then, using statistical analysis, the effective factors are recognised (phase 2). In the third phase, the product clusters are recognised using a hybrid PCA and agglomerative clustering method. For this purpose, different clusters for the training step are used. The outcomes indicated that Age (0.94), City (0.79), Health Benefit Awareness (0.76) and Education (0.75) are the most effective factors in product consumption patterns, respectively. Moreover, the efficiency of the outcomes is evaluated using the Silhouette Coefficient, indicating that the proposed algorithm could provide solutions with a 68% score. Moreover, using Calinski-Harabasz Index, it was found that the algorithm provided more logic scores while the number of product patterns was 3 for the studied region (707.54).

/pdf/a-comprehensive-3-phase-framework-for-determining-the-2qgrbwh9.pdf

A Comprehensive 3-Phase Framework for Determining the Customer’s Product Usage in a Food Supply Chain

Identification of modal parameters is crucial especially in aerospace applications whereby the interactions of airflow with aircraft structures can result in undesirable structural deformations. This structural deformation can be predicted with knowledge of the modal parameters. This can be achieved through conventional modal testing that requires a known excitation force in order to extract these dynamic properties. This technique can be experimentally complex because of the need for artificial excitation and it also does not represent actual operational condition. The current work presents part of research work that address the practical implementation of operational modal analysis (OMA) applied to a cantilevered hybrid composite plate exposed to low speed airflow in a wind tunnel. A single contactless sensing system via a laser vibrometer is employed to measure the response. OMA technique applied in a wind-on condition succeeded in extracting the modal parameters of the hybrid composite plate which correlate well with modal testing using impact hammer excitation.

/pdf/identification-of-modal-properties-of-composite-thin-plate-3c05pext11.pdf

Identification of Modal Properties of Composite Thin Plate Using OMA in Wind Tunnel Environment

Damage Identification Through a Vibration Based Data of a Quad-Rotor Unmanned Aerial Vehicle(Uav) Using Convolutional Neural Networks(Cnns)

The demand on wind energy application will continue to increase as fossil fuel prices keep increasing and the reservoir keeps decreasing. In wind energy, wind turbine application should be properly selected. The material selection for turbine blade fabrication is highlighted as well in recent research. For green material application, the usage of natural fiber reinforced composite, especially kenaf fiber, in the fabrication of wind turbines needs to be given due attention. Woven and unwoven kenaf fiber is employed to fabricate composite plates which replicate the simple turbine blade model. At the same time, Macro Fiber Composite (MFC) is attached to the kenaf plates for micro energy harvester purposes. There are two methods to attach the MFC used in this study which are surface bonded and embedding into the plate. In order to investigate the effects of bonding MFC technique, modal Testing analysis and Taguchi method is employed. It is found out that the damping percentage of both woven and unwoven kenaf plates increase at 100 % and 50 % respectively when bonded with MFC on their surfaces. Bonded technique is suggested as the most influenced factor in micro energy harvesting at the vibration range of 20 to 60 Hz. It summarized that, the kenaf woven type, the distance from structure neutral axis, the stiffness of structure, the excitation vibration and the neutral frequency of a structure are highlighted as the factors influencing the performance of micro energy harvester as well.

/pdf/the-bonded-macro-fiber-composite-mfc-and-woven-kenaf-effect-4ws1dd8noh.pdf

The bonded macro fiber composite (MFC) and woven kenaf effect analyses on the micro energy harvester performance of kenaf plate using modal testing and Taguchi method

Signal processing is an important element used for identifying damage in any SHM-related application The method here is used to extract features from the use of different types of sensors, of which there are many The responses from the sensors are also interpreted to classify the location and severity of the damage This paper describes the signal processing approaches used for detecting the impact locations and monitoring the responses of impact damage Further explanations are also given on the most widely-used software tools for damage detection and identification implemented throughout this research work A brief introduction to these signal processing tools, together with some previous work related to impact damage detection, are presented and discussed in this paper

Faizal Mustapha

Papers

A Comprehensive 3-Phase Framework for Determining the Customer’s Product Usage in a Food Supply Chain

Identification of Modal Properties of Composite Thin Plate Using OMA in Wind Tunnel Environment

Damage Identification Through a Vibration Based Data of a Quad-Rotor Unmanned Aerial Vehicle(Uav) Using Convolutional Neural Networks(Cnns)

The bonded macro fiber composite (MFC) and woven kenaf effect analyses on the micro energy harvester performance of kenaf plate using modal testing and Taguchi method

Damage Classification in CFRP Laminates Using Principal Component Analysis (PCA) Approach