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2013 | Buch

IAENG Transactions on Engineering Technologies

Special Volume of the World Congress on Engineering 2012

herausgegeben von: Gi-Chul Yang, Sio-long Ao, Len Gelman

Verlag: Springer Netherlands

Buchreihe : Lecture Notes in Electrical Engineering

insite
SUCHEN

Über dieses Buch

This book contains fifty-eight revised and extended research articles written by prominent researchers participating in the Advances in Engineering Technologies and Physical Science conference, held in London, U.K., 4-6 July, 2012.

Topics covered include Applied and Engineering Mathematics, Computational Statistics, Mechanical Engineering, Bioengineering, Internet Engineering, Wireless Networks, Knowledge Engineering, Computational Intelligence, High Performance Computing, Manufacturing Engineering, and industrial applications. The book offers the state of art of tremendous advances in engineering technologies and physical science and applications, and also serves as an excellent reference work for researchers and graduate students working on engineering technologies and physical science and applications.

Inhaltsverzeichnis

Frontmatter
Inventory Control Under Parametric Uncertainty of Underlying Models

A large number of problems in inventory control, production planning and scheduling, location, transportation, finance, and engineering design require that decisions be made in the presence of uncertainty of underlying models. In the present paper we consider the case, where it is known that the underlying distribution belongs to a parametric family of distributions. The problem of determining an optimal decision rule in the absence of complete information about the underlying distribution, i.e., when we specify only the functional form of the distribution and leave some or all of its parameters unspecified, is seen to be a standard problem of statistical estimation. Unfortunately, the classical theory of statistical estimation has little to offer in general type of situation of loss function. In the paper, for improvement or optimization of statistical decisions under parametric uncertainty, a new technique of invariant embedding of sample statistics in a performance index is proposed. This technique represents a simple and computationally attractive statistical method based on the constructive use of the invariance principle in mathematical statistics. Unlike the Bayesian approach, an invariant embedding technique is independent of the choice of priors. It allows one to eliminate unknown parameters from the problem and to find the best invariant decision rules, which have smaller risk than any of the well-known decision rules. A numerical example is given.

Nicholas A. Nechval, Konstantin N. Nechval, Maris Purgailis
Periodic Solution and Strange Attractor in Impulsive Hopfield Networks with Time-Varying Delays

By constructing suitable Lyapunov functions, we study the existence, uniqueness and global exponential stability of periodic solution for impulsive Hopfield neural networks with time-varying delays. Our condition extends and generalizes a known condition for the global exponential periodicity of continuous Hopfield neural networks with time-varying delays. Further the numerical simulation shows that our system can occur many forms of complexities including gui strange attractor and periodic solution.

Yanxia Cheng, Yan Yan, Zhanji Gui
Solving Stiff Ordinary Differential Equations Using Extended Block Backward Differentiation Formulae

A comprehensive research on the existing Block Backward Differentiation Formulae (BBDF) was done. Based on the suitability in solving stiff ordinary differential equations (ODEs), BBDF of order 3 up 5 is collected using simplified strategy in controlling the step size and order of the method. Thus, Extended Block Backward Differentiation Formulae (EBBDF) is derived with the intention of optimizing the performance in terms of precision and computation time. The accuracy of the method are investigated using linear and non linear stiff initial value problems and its performance is compared with MATLAB’s suite of ODEs solvers namely ode15s and ode23s.

Siti Ainor Mohd Yatim, Zarina Bibi Ibrahim, Khairil Iskandar Othman, Mohamed Suleiman
On Fast Algorithms for Triangular and Dense Matrix Inversion

We first propose in this paper a recursive algorithm for triangular matrix inversion (TMI) based on the ‘Divide and Conquer’ (D&C) paradigm. Different versions of an original sequential algorithm are presented. A theoretical performance study permits to establish an accurate comparison between the designed algorithms. Our implementation is designed to be used in place of dtrtri, the level 3 BLAS TMI. Afterwards, we generalize our approach for dense matrix inversion (DMI) based on LU factorization (LUF). This latter is used in Mathematical software libraries such as LAPACK xGETRI and MATLAB inv.

$$\mathrm{{A}}=\mathrm{{LU}}$$

being the input dense matrix, xGETRI consists, once the factors L and U are known, in inverting U then solving the triangular matrix system

$$\mathrm{{XL}}=\mathrm{{U}}^{-1}$$

(i.e.

$${\mathrm{{L}}}^{\mathrm{{T}}}{\mathrm{{X}}}^{\mathrm{{T}}}=({\mathrm{{U}}}^{-1})^\mathrm{{T}}$$

, thus

$$\mathrm{{X}}={\mathrm{{A}}}^{-1})$$

. Two other alternatives may be derived here (L and U being known) : (i) first invert L, then solve the matrix system

$$\mathrm{{UX}}=\mathrm{{L}}^{-1}$$

for X ; (ii) invert both L and U, then compute the product

$$\mathrm{{X}}={\mathrm{{U}}}^{-1}{\mathrm{{L}}}^{-1}$$

. Each of these three procedures involves at least one triangular matrix inversion (TMI). Our DMI implementation aims to be used in place of the level 3 BLAS TMI-DMI. Efficient results could be obtained through an experimental study achieved on a set of large sized randomly generated matrices.

Ryma Mahfoudhi, Zaher Mahjoub
Adding Relation Between Two Levels of a Linking Pin Organization Structure Maximizing Communication Efficiency of Information

This paper proposes a model of adding relation to a linking pin organization structure where every pair of siblings in a complete binary tree of height

$$H$$

H

is adjacent such that the communication of information in the organization becomes the most efficient. For a model of adding an edge between a node with a depth

$$M$$

M

and its descendant with a depth

$$N$$

N

, we formulated the total shortening distance which is the sum of shortening lengths of shortest paths between every pair of all nodes and obtained an optimal depth

$$N^{*}$$

N

which maximizes the total shortening distance for each value of

$$M$$

M

.

Kiyoshi Sawada
Bayesian Inference for the Parameters of Two-Parameter Exponential Lifetime Models Based on Type-I and Type-II Censoring

The parameters of the two-parameter exponential distribution are estimated in this chapter from the Bayesian viewpoint based on complete, Type-I and Type-II censored samples. Bayes point estimates and credible intervals of the unknown parameters are proposed under the assumption of suitable priors on the unknown parameters and under the assumption of the squared error loss function. Illustrative example is provided to motivate the proposed Bayes point estimates and the credible intervals. Various Monte Carlo simulations are also performed to compare the performances of the classical and Bayes estimates.

Husam Awni Bayoud
Analysing Metric Data Structures Thinking of an Efficient GPU Implementation

Similarity search is becoming a field of interest because it can be applied to different areas in science and engineering. In real applications, when large volumes of data are processing, query response time can be quite high. In this case, it is necessary to apply mechanisms to significantly reduce the average query response time. For that purpose, modern GPU/Multi-GPU systems offer a very impressive cost/performance ratio. In this paper, the authors make a comparative study of the most popular pivot selection methods in order to stablish a set of attractive features from the point of view of future GPU implementations.

Roberto Uribe-Paredes, Enrique Arias, Diego Cazorla, José Luis Sánchez
Exploratory Analysis of Ergonomics Importance at Workplace and Safety Culture Amongst Occupational Safety and Health Practitioners

This paper is a revised and extended version of a paper that was presented at WCE 2012. The article reports on a study to identify key components which can be used to relate ergonomics awareness and safety culture. These components can be used to facilitate the research which is aimed at determining the elements that influence the ergonomics awareness and the relationship with safety culture in an organization. A survey was done using a sample of 108 OSH practitioners in manufacturing companies in Malaysia. Exploratory Factor Analysis was used to determine the importance of ergonomics at their workplace and their beliefs on the importance of safety culture to be inculcated at their companies. 3 factors for ergonomics importance were identified: (i) Implication of & Need for improvement, (ii) Fitting the job to the workers and (iii) Basic ergonomics consideration. Safety culture questions were focused on the OSH practitioners perceptions on safety climate importance. Three constructs were designed: (i) commitment and leadership, (ii) motivation and (iii) safety management system practice. This finding is significant in order to study the influence of the perceptions of OSH practitioners on ergonomics importance at workplace to the safety culture.

Md Sirat Rozlina, Mohamed Shaharoun Awaluddin, Syed Hassan Syed Abdul Hamid, Zakuan Norhayati
Least Squares Data Fitting Subject to Decreasing Marginal Returns

Let data of a univariate process be given. If the data are related by a sigmoid curve, but the sigmoid property has been lost due to the errors of the measuring process, then the least sum of squares change to the data that provides nonnegative third divided differences is proposed. The method is highly suitable for estimating points on a sigmoid curve of unspecified parametric form subject to increasing marginal returns or subject to diminishing marginal returns. It is a structured quadratic programming calculation, which is solved very efficiently by a special least squares algorithm that takes into account the form of the constraints. Some numerical results illustrate the method on a variety of data sets. Moreover, two applications of the method on real economic data demonstrate its modeling capability. The first one concerns renewable energy consumption data, which exhibit a sigmoid pattern. The second one concerns technological substitutions among the PDP computers to the VAX computers.

Ioannis C. Demetriou
The Further Development of Stem Taper and Volume Models Defined by Stochastic Differential Equations

Stem taper process measured repeatedly among a series of individual trees is standardly analyzed by fixed and mixed regression models. This stem taper process can be adequately modeled by parametric stochastic differential equations (SDEs). We focus on the segmented stem taper model defined by the Gompertz, geometric Brownian motion and Ornstein-Uhlenbeck stochastic processes. This class of models enables the representation of randomness in the taper dynamics. The parameter estimators are evaluated by maximum likelihood procedure. The SDEs stem taper models were fitted to a data set of Scots pine trees collected across the entire Lithuanian territory. Comparison of the predicted stem taper and stem volume with those obtained using regression based models showed a predictive power to the SDEs models.

Petras Rupšys
Computing Compressible Two-Component Flow Systems Using Diffuse Interface Method

Numerical simulation of compressible two-component flows that consider different materials and physical properties is conducted. An explicit finite volume numerical framework based on an extended second order Godunov approach is developed and implemented to solve an Eulerian type mathematical model. This model consists of five partial differential equations in one space dimension and it is known as the transport reduced model. A fixed Eulerian mesh is considered and the hyperbolic problem is tackled using a robust and efficient HLL Riemann solver. The performance of the numerical solver is verified against a comprehensive suite of numerical and experimental case studies in multi-dimensional space. Computing the evolution of interfaces between two immiscible fluids is considered as a major challenge for the present model and the numerical technique. The achieved numerical results demonstrate a very good agreement with all reference data.

A. Ballil, S. A. Jolgam, A. F. Nowakowski, F. C. G. A. Nicolleau
Turbulent Boundary Layer Gas–Solid Flow Based on Two-Fluid Model

Motion of Particles in a dilute turbulent boundary layer on a flat wall was simulated numerically. Eulerian-Eulerian two-way coupled model was used. Thermophoretic force and Brownian diffusion effects were investigated on the depositions of fine particles in a turbulent boundary layer. Turbulence closure was achieved by Prandtl’s mixing length model. The set of equations was solved numerically by using finite difference method. Introduced particle diffusion term played a significant role in numerical convergence. The proposed two-fluid approach for evaluating the effect of different forces on small particle deposition from a turbulent flow over a flat plate produced similar finding compared to Lagrangian method and computationally less expensive.

Hassan Basirat Tabrizi
Molten Carbonate Fuel Cell as a Reducer of CO $$_2$$ 2 Emissions from Gas Turbine Power Plants

A Molten Carbonate Fuel Cell (MCFC) is shown to reduce CO

$$_2$$

2

emissions from a Gas Turbine Power Plant (GTPP). The MCFC is placed in the flue gas stream of the gas turbine. The main advantages of this solution are: higher total electricity generated by a hybrid system and reduced CO

$$_2$$

2

emissions with power generation efficiency remained the same. The model of the MCFC is given and described. The results obtained show that use of an MCFC could reduce CO

$$_2$$

2

emissions by 73.

Jaroslaw Milewski, Rafal Bernat, Janusz Lewandowski
Computational Contact Modelling of Hip Resurfacing Devices

A combination of computational models and theoretical methods have been used and developed to study the contact of hip resurfacing devices under normal and edge loading conditions. Techniques were developed and the solutions based on using the finite element method. It was found that the study of hip joint modelling, numerical methodologies of mechanical wear simulations and shakedown analysis can be developed to study the contact mechanics and biotribology of hip resurfacing devices under central and edge loading conditions. Each method developed in this study provides a unique platform to study these problems.

Murat Ali, Ken Mao
Transport Phenomena in Engineering Problems: CFD-Based Computational Modeling

Computational Fluid Dynamics is a popular modeling approach which utilizes numerical methods and computer simulations to solve and analyze problems that involve transport phenomena in fluid flows. CFD-based models demonstrate high versatility and capability of dealing with a wide range of engineering problems. This chapter presents two examples of CFD-based computational modeling successfully applied for different fields of engineering: particle engineering by drying processes and thermal management.

Maksim Mezhericher
Investigating the Effects on the Low Speed Response of a Pressure Charged IC Engine Through the Application of a Twin-Entry Turbine Housing

In this study, one-dimensional analysis using AVL Boost software has been carried out on a series of compression and spark ignition engines utilizing a manufacturer fitted single-entry turbocharger and a modified twin-entry unit, the latter adopting two symmetrical turbine housing inlet ports. The model reconstruction using AVL Boost considers parameters that accurately represent the physical engine conditions including manifold geometry, turbocharger flow maps and combustion chamber characteristics. Model validations have been made for a standard single-entry turbocharger configuration to predict the maximum engine power and torque, in comparison with available manufacturer data and analytical calculations. Further studies concentrate on engine performance comparisons between single- and twin-entry turbochargers at low engine speed conditions, typically in a range of 1000–3000 RPM. Improvements in turbine shaft speed, engine power and torque have been achieved, thus implying improved low speed engine response. This study reveals the potential commercial benefits of adopting a twin-entry turbocharger and contribution to the academic community through this additional research.

Alex Kusztelan, Denis Marchant, Yufeng Yao, Yawei Wang
A Data Mining Approach to Recognize Objects in Satellite Images to Predict Natural Resources

This paper presents an approach for the classification of satellite images by recognizing various objects in them. Satellite images are rich in geographical information that can be used in a number of useful ways. The proposed system classifies satellites images by extracting different objects from the images. Our object recognition mechanism extracts attributes from satellite images under two domains namely: color pixels’ organization and pixel intensity. The extracted attributes aid in the identification of objects lying inside the satellite images. Once we are able to identify objects, we proceeded further to classify satellite images with the help of decision trees. The system has been tested for a number satellite images acquired from around the globe. The objects in the images have been further subdivided into different sub categories to improve the classification and prediction process. This is a novel approach which is not using any image processing techniques but is utilizing the extracted features to identify objects and then using these objects to classify the satellite images.

Muhammad Shahbaz, Aziz Guergachi, Aneela Noreen, Muhammad Shaheen
Handling the Data Growth with Privacy Preservation in Collaborative Filtering

The emergence of electric business facilitates people in purchasing merchandises over the Internet. To sell the products better, online service providers use recommender systems to provide recommendations to customers. Most recommender systems are based on collaborative filtering (CF) technique. This technique provides recommendations based on users’ transaction history. Due to the technical limitations, many online merchants ask a third party to help develop and maintain recommender systems instead of doing that themselves. Therefore, they need to share their data with these third parties and users’ private information is prone to leaking. Furthermore, the fast data growth should be handled by the data owner efficiently without sacrificing privacy. In this chapter, we propose a privacy preserving data updating scheme for collaborative filtering purpose and study its performance on two different datasets. The experimental results show that the proposed scheme does not degrade recommendation accuracy and can preserve a satisfactory level of privacy while updating the data efficiently.

Xiwei Wang, Jun Zhang
Machine Learning-Based Missing Value Imputation Method for Clinical Datasets

Missing value imputation is one of the biggest tasks of data pre-processing when performing data mining. Most medical datasets are usually incomplete. Simply removing the incomplete cases from the original datasets can bring more problems than solutions. A suitable method for missing value imputation can help to produce good quality datasets for better analysing clinical trials. In this paper we explore the use of a machine learning technique as a missing value imputation method for incomplete cardiovascular data. Mean/mode imputation, fuzzy unordered rule induction algorithm imputation, decision tree imputation and other machine learning algorithms are used as missing value imputation and the final datasets are classified using decision tree, fuzzy unordered rule induction, KNN and K-Mean clustering. The experiment shows that final classifier performance is improved when the fuzzy unordered rule induction algorithm is used to predict missing attribute values for K-Mean clustering and in most cases, the machine learning techniques were found to perform better than the standard mean imputation technique.

M. Mostafizur Rahman, D. N. Davis
Opto-Electronic Hybrid Integrated Platform for High-Speed Telecom/Datacom Applications: Microwave Design and Optimization

An opto-electronic hybrid integrated platform was developed to enable the fabrication of broadband, low-cost, and compact transceivers for telecommunications. On this platform, an opto-electronic device such as a high-speed laser or a photodetector chip is integrated with a RF driver or an amplifier IC. A Kovar heatsink with multistep structure is designed for ease of optical coupling using a laser welding process. In order to control the high frequency resonances and improve the signal integrity, AlN based subcircuits are designed to feed the RF and DC signals separately. The interconnection networks between the IC and the opto-electronic device and also between the chips and high-speed transmission lines are carefully investigated to optimize the microwave performances. The influence of the packaging for this opto-electronic integration platform on the microwave performance is also analyzed in detail. The simulation results obtained and successful fabrication of a transmitter module demonstrate that the proposed platform can meet the requirements for high-speed WDM or TDM systems.

Wei Han, Marc Rensing, Xin Wang, Peter O’Brien, Frank H. Peters
Direct Torque Control of In-Wheel BLDC Motor Used in Electric Vehicle

Zero running emission, sustainability and efficiency of Electric Vehicle (EV) make it appropriate option for future transportation. In-wheel propulsion system of electric vehicles has been one of the main research concentrations in past decades. Brushless DC (BLDC) motor is the most suitable in-wheel motor because of its high efficiency, torque/speed characteristics, high power to size ratio, high operating life and noiseless operation. In this chapter direct torque control (DTC) switching technique with digital pulse width modulation (PWM) speed controller of BLDC motor for drive train system of EV has been reported. Effectiveness of the proposed BLDC motor drive is investigated through simulation and experiment. Obtained results show effective control of torque and remarkable reduction of torque ripple amplitude compare to conventional reported switching techniques. Improvements of in-wheel motor’s torque controllability result to more efficient and safer electric vehicles.

Alireza Tashakori Abkenar, Mehran Motamed Ektesabi
Different Detection Schemes Using Enhanced Double Weight Code for OCDMA Systems

This chapter investigates the performance of enhanced double weight (EDW) code for spectral-amplitude-coding optical code division multiple access (SAC-OCDMA) system using different detection techniques. EDW code possess ideal cross-correlation properties such as the maximum cross correlation of one that are important characteristics in the optical CDMA systems since these can eliminate multiple access interference and reduce noise. The EDW code has numerous advantages including the efficient and easy code construction, simple encoder/decoder design, existence for every natural number

$$n$$

n

, and weight, which can be any odd number greater than one. The experimental simulation results as well as the transmission performances are presented in this chapter.

Feras N. Hasoon, Mohammed H. Al-Mansoori, Sahbudin Shaari
Multigate RADFET Dosimeter for Radioactive Environment Monitoring Applications

In this chapter, a new radiation sensitive FET (RADFET) dosimeter design (called the Dual-Dielectric Gate All Around DDGAA RADFET dosimeter) to improve the radiation sensitivity performance and its analytical analysis have been proposed, investigated and expected to improve the sensitivity behavior and fabrication process for RADFET dosimeter-based applications. Analytical models have been developed to predict and compare the performance of the proposed design and conventional (bulk) RADFET, where the comparison of device architectures shows that the proposed design exhibits a superior performance with respect to the conventional RADFET in term of fabrication process and sensitivity performances. The proposed design has linear radiation sensitivities of approximately

$$95.45\,\upmu \mathrm{{V/Gy}}$$

95.45

μ

V

/

Gy

for wide irradiation dose range (from

$$\mathrm{{Dose}}=50\,\mathrm{{Gy}}$$

Dose

=

50

Gy

to

$$\mathrm{{Dose}}=3000\,\mathrm{{Gy}}$$

Dose

=

3000

Gy

). Our results showed that the analytical analysis is in close agreement with the 2-D numerical simulation over a wide range of devices parameters. The proposed device and the Artificial Neural Networks (ANNs) have been used to study and show the impact of the proposed dosimeter on the environment monitoring and remote sensing applications. The obtained results make the DDGAA RADFET dosimeter a promising candidate for environment monitoring applications.

Fayçal Djeffal, Mohamed Meguellati
Multi-Objective-Based Approach to Optimize the Analog Electrical Behavior of GSDG MOSFET: Application to Nanoscale Circuit Design

In this chapter, the small signal parameters behavior of Gate Stack Double Gate (GSDG) MOSFET are studied and optimized using multi-objective genetic algorithms (MOGAs) for nanoscale CMOS analog circuits’ applications. The transconductance and the OFF-current are the small signal parameters which have been determined by the analytical explicit expressions in saturation and subthreshold regions. According to the analytical models, the objectives functions, which are the pre-requisite of genetic algorithms, are formulated to search the optimal small signal parameters in order to obtain the best electrical and dimensional transistor parameters to obtain and explore the better transistor performances for analog CMOS-based circuit applications. Thus, the encouraging obtained results may be of interest to practical applications. The optimized design is incorporated into circuit simulator to study and show the impact of our approach on the nanoscale CMOS-based circuits design. In this context, we proposed to study the electrical behavior of a ring oscillator circuit. In this study a great improvement of the oscillation frequency has been recorded in our case. The main advantages of the proposed approach are its simplicity of implementation and provide to designer optimal solutions that suites best analog application.

Toufik Bendib, Fayçal Djeffal
Performance Analysis of Series Hybrid Active Power Filter

In the area of active power filtering, the Series Hybrid Active Power Filter (SHAPF) has been taken into account increasingly. Existing methods used for controlling SHAPF are either based on detecting source current harmonics or load voltage harmonics. Generalised Instantaneous Power Theory (GIPT) gives simple and direct method of defining power quantities under sinusoidal and non-sinusoidal situations. In this paper the definition of GIPT is used to decompose voltage vector into different components, which represents different parts of the power quantity. The separated components of voltage vector are used to derive reference signal for the SHAPF. This paper presents a study on performance analysis of SHAPF where the method used for calculating reference is based on the GIPT. Steady state and transient performance of SHAPF used for compensating current type harmonic producing load and voltage type harmonics producing load are evaluated by the simulation study.

M. A. Mulla, R. Chudamani, A. Chowdhury
Protecting the End User Device in 4G Heterogeneous Networks

In recent years, there have been major developments in, and deployment of, diverse mobile technology. Security issues in mobile computing are now presenting significant challenges. Heterogeneous networks are the convergence of wired and wireless networks, other diverse end user devices and other communication technologies which provide very high speed connections. Major security challenges in 4G heterogeneous networks are inherent in current internet security threats and IP security vulnerabilities. In this paper, we propose a management system which is responsible for enforcing security policies and ensuring that security policies continued to be followed. The objective of this security management system is to prevent the mobile equipment from being abused or used as a malicious attack tool. The proposed security management system is consistent with the security specifications defined by ITU-T recommendation M.3400 TMN management functions. Finally, this paper will present a policy-based architecture for the security management system of 4G heterogeneous networks focusing on detection and prevention of malicious attacks.

Hani Alquhayz, Ali Al-Bayatti, Amelia Platt
Calibration Procedures for Indoor Location Using Fingerprinting

Fingerprinting is a location technique, based on the use of wireless networks, where data stored during the offline phase is compared with data collected by the mobile node during the online phase. When this location technique is used in a real-life scenario there is a high probability that the mobile node used throughout the offline phase is different from the mobile nodes that will be used during the online phase. This means that there might be very significant differences between the Received Signal Strength values acquired by the mobile node being located and the ones previously stored in the Fingerprinting Map. As a consequence, this difference between RSS values might contribute to increase the location estimation error. One possible solution to minimize these differences is to adapt the RSS values, acquired during the online phase, before sending them to the Location Estimation Algorithm. Also the internal parameters of the Location Estimation Algorithms, for example the weights of the Weighted k-Nearest Neighbour, might need to be tuned for every type of terminal. This paper focuses both approaches, using Direct Search optimization methods to adapt the Received Signal Strength and to tune the Location Estimation Algorithm parameters. As a result it was possible to decrease the location estimation error originally obtained without any calibration procedure.

Pedro Mestre, Luis Reigoto, Luis Coutinho, Aldina Correia, Joao Matias, Carlos Serodio
Handling the Congestion Control Problemof TCP/AQM Wireless Networks with PID Controllers

Internet users rely on the good capabilities of TCP/IP networks for dealing with congestion. The network delay and the number of users change constantly, which might lead to transmission problems. Usually, they are handled following approaches such as Drop Tail or Random Early Detection (RED) algorithms. During the last few years, automatic control techniques are providing practical solutions. Moreover, if there are wireless links, congestion control is more difficult to detect. This chapter presents a methodology to design a PID controller with a linear gain scheduling that allows a network with wireless links to deal with control congestion under a variety of configurations. The technique is compared with a standard PID and several tests are carried out using linear and non-linear environments.

Teresa Alvarez, Diego Martínez
On the Initial Network Topology Factor in Mobile Ad-Hoc Network

The impact of the initial network topology on performance of routing algorithms is explored. Typically researchers use a randomly chosen network topology for performance evaluation of their protocols and algorithms. Here we show that the initial network topology can have a significant impact on algorithm performance and can lead to biased results, in particular, an initial topology that includes a major connectivity obstacle such as low connectivity level (e.g., a tree topology) or bridges. Although users move according to commonly implemented random mobility models, the effect of the initial topology can persist over time. To avoid biased results we recommend using multiple initial topologies instead of one, and/or running the simulation in an initialization phase until the effect of the initial topology fades.

Ronit Nossenson, Adi Schwartz
Internet Key Exchange Protocol Using ECC-Based Public Key Certificate

Internet Key Exchange (IKE) protocol helps to exchange cryptographic techniques and keying materials as prior security association (SA) between two IP hosts. Similar to the several enhancements, the present paper proposes an efficient implementation of IKE using ECC-based public-key certificate that provides required security properties with much reduction in computation complexity and communication cost. The proposed method addresses both the Phase I and Phase II of IKE, where the main mode of the former instead of six, requires four rounds of message exchange. The formats specified in ISAKMP have been used for message exchanges in our implementation, thus the cookies of initiator-responder have been used to protect attacks like DoS, parallel session etc. The security analysis of the proposed method and comparison with other techniques are given and satisfactory performance is found.

Sangram Ray, G. P. Biswas
Intrusion Alert Correlation Framework: An Innovative Approach

Alert correlation analyzes the alerts from one or more collaborative intrusion detection systems (IDSs) to produce a concise overview of security-related activity on a network. The process consists of multiple components, each responsible for a different aspect of the overall correlation goal. The sequence order of the correlation components affects the process performance. The total time needed for the whole process depends on the number of processed alerts in each component. An innovative alert correlation framework is introduced based on a model that reduces the number of processed alerts as early as possible by discarding the irrelevant and false alerts in the first phases. A new component,

shushing the alerts

, is added to deal with the unrelated alerts. A modified algorithm for fusing the alerts is presented. The intruders’ intention is grouped into attack scenarios and thus used to detect future attacks. DARPA 2000 ID scenario specific datasets is used to evaluate the alert correlator model. The experimental results show that the correlation model is effective in achieving alert reduction and abstraction. The performance is improved after the attention is focused on correlating higher severity alerts.

Huwaida Tagelsir Elshoush, Izzeldin Mohamed Osman
An Interactive Shadow Removing Tool: A Granular Computing Approach

This work proposes a tool to remove shadow from colour images with the help of user interaction. Shadow detection and removal is an interesting and a difficult image enhancement problem. In this work, a novel granule based approach for colour image enhancement is proposed. The proposed method constructs a shadow classifier using a Granular Reflex Fuzzy Min-Max Neural Network (GrRFMN). Classification and clustering techniques based on granular data are up-coming and finding importance in various fields including computer vision. GrRFMN capability to process granules of data is exploited here to tackle the problem of shadows. In this work, granule of data represents a group of pixels in the form of a hyperbox. During the training phase, GrRFMN learns shadow and non-shadow regions through an interaction with the user. A trained GrRFMN is then used to compute fuzzy memberships of image granules in the region of interest to shadow and non-shadow regions. A post processing of image based on the fuzzy memberships is then carried out to remove the shadow. As GrRFMN is trainable on-line in a single pass through data, the proposed method is fast enough to interact with the user.

Abhijeet Vijay Nandedkar
Resolution Enhancement for Digital Off-Axis Hologram Reconstruction

A new method of digital off-axis hologram reconstruction based on the Fresnel transform is proposed. A combination of composite filtering, Abbe’s limitation, and digital lens formulae has been used with an appropriate handling of Fresnel impulse response propagator. A clear image of microscopic object is efficiently reconstructed from hologram using a plane wave with involvement of electric field along bi-cubic interpolation in the final reconstruction step. In particular, the proposed method automatically suppresses the zero order term and virtual image. The image can be reconstructed with large size using interpolation scheme with the Haar wavelet. The proposed method facilitates the transverse high resolution of microscopic image, which has better applicability than other approaches. Moreover, the advantages of this method are its simplicity and convenience in data processing.

Nazeer Muhammad, Dai-Gyoung Kim
A Novel Two-Scan Connected-Component Labeling Algorithm

This chapter proposes a novel two-scan labeling algorithm. In the first scan, all conventional two-scan labeling algorithms process image lines one by one, assigning each foreground pixel a provisional label, finding and resolving label equivalences between provisional labels. In comparison, our proposed method first scans image lines every four lines, assigns provisional labels to foreground pixels among each three lines, and finds and resolves label equivalences among those provisional labels. Then, it processes the leaving lines from top to bottom one by one, and for each line, assigns provisional labels to foreground pixels on the line, and finds and resolves label equivalences among the provisional labels and those assigned to the foreground pixels on the lines immediately above and below the current line. With our method, the average number of times for checking pixels for processing a foreground pixel will decrease; thus, the efficiency of labeling can be improved. Experimental results demonstrated that our method was more efficient than conventional label-equivalence-based labeling algorithms.

Lifeng He, Yuyan Chao, Yun Yang, Sihui Li, Xiao Zhao, Kenji Suzuki
Approaches to Bayesian Network Model Construction

Bayesian Network (BN) has sound mathematical basis, enables reasoning under uncertainty, and facilitates the update of beliefs, given new evidence. It also enables the visual representation of a model. These make BN suitable for solving uncertainty problems. This chapter details BN model construction approaches and presents our experiences with selecting the optimal construction approach.

Ifeyinwa E. Achumba, Djamel Azzi, Ifeanyi Ezebili, Sebastian Bersch
Fertilization Operator for Multi-Modal Dynamic Optimization

Solving Multi-modal Dynamic Optimization problems (MDO) has been a challenge for genetic algorithms (GAs). In this kind of optimization, an algorithm requires not only to find the multiple optimal solutions but also to locate a changing optimum dynamically. To enhance the performance of GAs in MDO, this paper proposes a New Genetic Operator NGO. The NGO is built on three components. First, a novel Genetic Algorithm with Dynamic Niche Sharing (GADNS) which permits to encourage the speciation. Second, an unsupervised fuzzy clustering that tracks multiple optima and enhances GADNS. Third, Spacial Separation (SS) which induces the stable sub-populations and allows local competition. In addition, NGO maintains diversity by a new genetic operators. To control the selection pressure, a new tournament selection is presented. Moving Peaks benchmark is applied to test the performance of NGO. The ability of the NGO to track multiple optima is demonstrated by a new diversity measure.

Khalid Jebari, Abdelaziz Bouroumi, Aziz Ettouhami
A Hardware Design for Binary Image Recognition

Recently, nonlinear composite correlation filters have been proposed for distortion-invariant pattern recognition. The filter design is based on logical operations and the correlation is computed with a nonlinear operation called morphological correlation. In this paper a new implementation in parallel hardware of these kinds of filters for image recognition is proposed. The architecture is designed for a Field Programmable Gate Array (FPGA) device. The proposed design performs the most time consuming task of the recognition procedure. In consequence, it reduces the time required for the nonlinear operations in the spatial domain. Simulation results are provided and discussed.

Saul Martinez-Diaz
In-Situ Vibrational Spectroscopies, BTEM Analysis and DFT Calculations

Reactions of

$$\mathrm{{Rh}}_{2}(\mathrm{{CO}})_{4}\mathrm{{Cl}}_{2}$$

Rh

2

(

CO

)

4

Cl

2

with two conjugated dienes, namely, 2,3-dimethyl-1,3-butadiene (DMBD) and isoprene, were performed in anhydrous hexane under argon atmosphere with multiple perturbations of reagents. These reactions were monitored by in-situ FTIR (FIR and MIR) and/or Raman spectroscopies and the collected spectra were further analyzed with BTEM family of algorithms. The combined spectroscopic data seems to suggest that one organo-rhodium product

$$\mathrm{{Rh}}_{2}(\mathrm{{CO}})_{4}\mathrm{{Cl}}_{2}(\eta ^{4}$$

Rh

2

(

CO

)

4

Cl

2

(

η

4

-diene) (

$$\mathrm{{diene}} = \mathrm{{DMBD}}$$

diene

=

DMBD

, isoprene) was the main product during the reactions. DFT calculations further confirm that three carbonyls are bonded to one rhodium atom while the 4th carbonyl and a chelating diene ligand are bonded to the other rhodium atom. The possible coordination geometry was obtained with (1) the consideration of the coordination chemistry and (2) the consistence between the DFT predicted spectra in FTIR and Raman regions with the corresponding BTEM estimates. The present contribution shows that BTEM can be meaningfully applied to the reaction of

$$\mathrm{{Rh}}_{2}(\mathrm{{CO}})_{4}\mathrm{{Cl}}_{2}$$

Rh

2

(

CO

)

4

Cl

2

and DMBD/isoprene in order to provide enhanced spectroscopic analysis, especially in the FIR and Raman regions. Furthermore, the present results provide a better understanding of the coordination chemistry of

$$\mathrm{{Rh}}_{2}(\mathrm{{CO}})_{4}\mathrm{{Cl}}_{2}$$

Rh

2

(

CO

)

4

Cl

2

with conjugated dienes.

Feng Gao, Chuanzhao Li, Effendi Widjaja, Marc Garland
Convergence Speed of Generalized Longest-Edge-Based Refinement

In the refinement of meshes, one wishes to iteratively subdivide a domain following geometrical partition rules. The aim is to obtain a new discretized domain with adapted regions. We prove that the Longest Edge

$$n$$

n

-section of triangles for

$$n\geqslant 4$$

n

4

produces a finite sequence of triangle meshes with guaranteed convergence of diameters and review previous result when

$$n$$

n

equals 2 and 3. We give upper and lower bounds for the convergence speed in terms of diameter reduction. Then we fill the gap in the analysis of the diameters convergence for generalized Longest Edge based refinement. In addition, we give a numerical study for the case of

$$n=4$$

n

=

4

, the so-called LE quatersection, evidencing its utility in adaptive mesh refinement.

José P. Suárez, Tania Moreno, Pilar Abad, Ángel Plaza
Labeling the Nodes in the Intrinsic Order Graph with Their Weights

This chapter deals with the study of some new properties of the intrinsic order graph. The intrinsic order graph is the natural graphical representation of a complex stochastic Boolean system (CSBS). A CSBS is a system depending on an arbitrarily large number

$$n$$

n

of mutually independent random Boolean variables. The intrinsic order graph displays its

$$2^{n}$$

2

n

vertices (associated to the CSBS) from top to bottom, in decreasing order of their occurrence probabilities. New relations between the intrinsic ordering and the Hamming weight (i.e., the number of

$$1$$

1

-bits in a binary

$$n$$

n

-tuple) are derived. Further, the distribution of the weights of the

$$2^{n}$$

2

n

nodes in the intrinsic order graph is analyzed.

Luis González
Solving VoIP QoS and Scalability Issues in Backbone Networks

Providing quality of service should be one of the main objectives when deploying sensitive applications into the network. Since network performance parameters are subject to frequent change, in this chapter we propose a novel approach to routing sensitive VoIP traffic in large networks. Our approach takes measured delay and jitter into consideration and we establish an overlay of the original network to route primarily VoIP traffic. This is achieved by first modeling the probability distributions of network performance parameters and then by calculating the best paths by means of graph algorithm utilizing aspects. Our approach also identifies weak network areas not suitable for VoIP deployment which can be subject to future network improvements.

Martin Hruby, Michal Olsovsky, Margareta Kotocova
Determining the Importance of Design Features on Usable Educational Websites

This research investigated the relative importance of specific design criteria developed for the purpose of this research, in the evaluation of the usability of educational websites from the point view of students. The results showed that content and navigation were the first and second preferred design categories to be considered while evaluating the usability of educational websites, while the architecture/organisation was the leasts important category. Also, the results showed that there was a statistically significant difference between males and females regarding only one category: the content. Females considered this to be the most important category while males considered it as the second most important. By contrast, the results showed that there were no statistically significant differences between the students of the two selected faculties (the Faculty of Information Technology and Science, and the Faculty of Economics and Administrative Sciences) concerning the relative importance of the developed criteria based on their majors/specialisations.

Layla Hasan
A Flexible Dynamic Data Structure for Scientific Computing

We present an approach for a generic, multi-dimensional run-time data structure suitable for high-performance scientific computing in C++. Our concept for associating meta-information with the data structure as well as different underlying datatypes is depicted. High-performance, multi-dimensional data access is realized by utilizing a heterogenous compile-time container generation function. The generalized data structure implementation is discussed and performance results are given with respect to reference implementations. We show that our approach is not only highly flexible but also offers high-performance data access by simultaneously relying on a small code base.

Josef Weinbub, Karl Rupp, Siegfried Selberherr
Application of Curriculum Design Maturity Model at Private Institution of Higher Learning in Malaysia: A Case Study

Capability Maturity Model (CMM) is applied as a process improvement model not only in software industry but also in education sector. This study proposes a maturity model, which constructed based on CMM, in guiding curriculum designers in Institution of Higher Learning (IHL) in Malaysia to design quality curriculum. The proposed maturity model possesses process and product elements; and it contains a set of key process areas and best practices. A case study is carried out in a private IHL in Malaysia to perform a pilot test on the proposed maturity model. The results may also help the institution to be informed of current as well as future improvement process, finally aid in producing quality curriculum for IHL in Malaysia.

Chee Ling Thong, Yusmadi Yah Jusoh, Rusli Abdullah, Nor Hayati Alwi
Reducing Job Failure Due to Churn in Dynamics Grids

The utilization of desktop grid computing in large-scale computational applications is an important issue at present for solving compute-intensive problems. However, such large-scale distributed systems are subject to churn, i.e., continuous hosts arrival, leaving and failure. We address the problem of churn in dynamic grids, and evaluate the impact of reliability-aware resource allocation on the performance of the system.

K. Abdelkader, J. Broeckhove
Parallel Algorithm for Multiplying Integer Polynomials and Integers

This chapter aims to develop and analyze an effective parallel algorithm for multiplying integer polynomials and integers. Multiplying integer polynomials is of fundamental importance when generating parameters for public key cryptosystems, whereas their effective implementation translates directly into the speed of such algorithms in practical applications. The algorithm has been designed specifically to accelerate the process of generating modular polynomials, but due to its good numerical properties it may surely be used to multiply integers. The basic idea behind this new method was to adapt it to parallel computing. Nowadays, it is a very important property, as it allows us to fully exploit the computing power offered by modern processors. The combination of the Chinese Remainder Theorem and the Fast Fourier Transform made it possible to develop a highly effective multiplication method. Under certain conditions our integer polynomial multiplication method is asymptotically faster than the algorithm based on Fast Fourier Transform when applied to multiply both: polynomials and their coefficients. Undoubtedly, this result is the major theoretical conclusion of this chapter.

Andrzej Chmielowiec
A Model to Improve Reliability in Cloud Computing

The cloud computing offers dynamically scalable resources provided as a service over the Internet. It promises the drop in capital expenditure. But practically speaking if this is to become reality there are still some challenges which is to be still addressed. Amongst, the main issues are related to security and trust, since the user’s data has to be released to the Cloud and thus leaves the secured area of the data owner. The users must trust the providers. There must be a strong trust relationship exist between the service providers and the users. This paper provides a model based on reputation which allows only reliable providers to provide the computing power and the resources which in turn can provide a reliable infrastructure for cloud computing.

P. Srivaramangai, Rengaramanujam Srinivasan
Natural Gas Price Forecasting: A Novel Approach

Earlier discarded as an irritant by-product of crude oil exploration, Natural gas is considered as world’s most important fuel due to environmental considerations. It plays an important role in meeting global energy demand and has significant share in the international energy market. Natural Gas is emerging as an alternative to crude oil and coal as the main energy source and the global energy consumption pattern has transformed from preeminence of crude oil and gas to escalating share of gas. Accordingly, there is a spur in demand of natural gas and business entities across the world are interested to comprehend natural gas price forecast. The forecast is likely to meet different objectives of producers, suppliers, traders and bankers engaged in natural gas exploration, production, transportation and trading as well as end users. For the supplier the objective is to meet the demand with profit and for the trader it is for doing business. Of late researchers have exercised different approaches to forecast price by developing numerical models in terms of specific parameters which have relationship with Natural Gas price. This chapter examines application of contemporary forecasting techniques—Time Series Analysis as well as Nonparametric Regression invoking Alternating Conditional Expectations (ACE) to forecast Natural Gas price. Noticeable predictor variables that may explicate statistically important amount of inconsistencies in the response variable (i.e. Natural Gas price) have been recognized and the correlation between variables has been distinguished to model Natural Gas price.

Prerna Mishra
Structured Data Mining for Micro Loan Performance Prediction: The Case of Indonesian Rural Bank

The ability to predict small businesses’ future loan performance based on submitted loan applications is crucial for Indonesian rural banks. The small capacity of these particular banks requires an efficient approach to extract knowledge from structured (quantitative) and unstructured (qualitative) type of credit information. The eXtensible Markup Language (XML) is used to organize this complementary credit data from an Indonesian rural bank. The credit performance evaluation application presented utilizes a mapping approach to preserve structural aspects of data within a format on which wider selections of data mining techniques are applied. Results from decision tree and association rule mining algorithms demonstrate the potential of the approach to generate reliable and valid patterns useful for evaluation of existing lending policy.

Novita Ikasari, Fedja Hadzic
Financial Forecasting Using the Kolmogorov–Feller Equation

An approach to analysing a financial time series using the Kolmogorov-Feller Equation is considered, in particular, the Generalised Kolmogorov-Feller Equation (GKFE), subject to variations in the Stochastic Volatility. Using the Mittag-Leffler memory function, we derive an expression for the Impulse Response Function associated with a short time window of data which is then used to derive an algorithm for computing a new index using a standard moving window process. It is shown that application of this index to financial time series, subject to a low volatility condition, correlates with the start, direction and end of a trend depending on the sampling rate of the time series and the look-back window or ‘period’ that is used. An example of this is provided in the chapter using MetaTrader4.

Jonathan Blackledge, Marc Lamphiere, Kieran Murphy, Shaun Overton
Surface Quality Improvement in CNC End Milling of Aluminum Alloy Using Nanolubrication System

Aerospace applications and energy saving strategies in general raised the interest and study in the field of lightweight materials, especially on aluminum alloys. Aluminum Al2017-T4 and Al6061-T6 alloy which are used in this research work have low specific weight and high strength.The (CNC) milling machine facilities provides a wide variety of parameters setup, making the machining process of the aluminum alloy excellent in manufacturing complicated special products. However, the demand for high quality focuses attention especially on the roughness of the machined surface. The key solution for this issue is by introducing the nanolubrication system since it could produce much less friction in the tool-chip interface. In this research work, the Al2017-T4 and Al6061-T6 is machined by using the carbon onion nanoparticle and

$$\mathrm{{SiO}}_{2}$$

SiO

2

nanoparticles, respecticely when it mixed with ordinary mineral oil at various concentrations as a nanolubrication system. The reduction of surface roughness could be obtained when carbon onion and

$$\mathrm{{SiO}}_{2}$$

SiO

2

nanolubricant are used compared with the case of using ordinary lubricant due to the tribological properties of the carbon onion and

$$\mathrm{{SiO}}_{2}$$

SiO

2

nanolubricant to reduce the coefficient of friction in the tool-chip interface.

Mohd Sayuti Ab Karim, Ahmed Aly Diaa Mohammed Sarhan, Mohd Hamdi Abd Shukor
A Price-Based Decision Policy to Mitigate the Tragedy of the Commons and Anti-Commons

In developing countries subsidies play an important role and are used in one way or another to extend the information and communication services to the information “have nots” through subsidized communication services. However, subsidies may have an impact on network resource utilization, quality of service and the amount of revenue generated. For example, subsidies may lead to low Quality of Service (QoS) and high resource utilization while in some instances unsubsidized services may lead to high quality of services and low utilization of resources. This

see-saw effect

may eventually lead to market failure and it may, now and then, destroy market efficiency. This phenomenon calls for a combined study, in which the relationship between subsidy, price, QoS and resource utilization is investigated. In this chapter, the impact of subsidies on quality of service and resource utilization in multitier communities is investigated. We try to find a middle ground between implementation of subsidy policy and its effects on QoS and resource utilization in a network.

M. Sumbwanyambe, A. L. Nel
Modeling Emergency Department Using a Hybrid Simulation Approach

Within hospital, emergency department is one of the most important unit that involves complex patient movement flow and detailed operational activities. As an integrated system, the efficiency of emergency department depends on its interaction between inter-departmental units and intra-departmental elements. Over the years, with the rapid development of computer technology, there has been a rising trend of using simulation modeling to improve healthcare operations. Discrete-event simulation (DES) has become a popular and effective decision-making tool for modeling the stochastic operational activities in a system. However for a whole system approach, system dynamics (SD) has advantages over DES. SD does not require vast data and is able to capture the interdependency relations between different units in an integrated system. Both approaches have strengths and weaknesses that may support and complement each other. An integrated model of both approaches will provide a realistic view of a complex system. This chapter provides an overview of the hybrid simulation modeling applications to emergency department.

Norazura Ahmad, Noraida Abdul Ghani, Anton Abdulbasah Kamil, Razman Mat Tahar
The Challenge of Adopting Minimal Quantities of Lubrication for End Milling Aluminium

End milling is a very common metal cutting process used for the machining of most types of metal. The process is inherently intermittent causing the tool tip edge to constantly fluctuate between various levels of temperatures, specifically from cold to

$$300\,\,^\circ \mathrm{C}$$

300

C

when cutting Al alloy. During dry end milling cutting temperatures need to remain within the design specifications of the tool tip. Even working with Al alloy the tool tip is subjected to thermal cyclic stresses. Conventional wisdom states that it is essential to use flood cooling during end milling, as intermittent cooling increases the effect of thermal shock and build up edge. Al alloy—unlike other materials—needs cutting fluid to avoid smearing the insert edges and to improve the surface finish. Modern machining companies constantly face the challenges of environmental issues that affect the manufacturing costs of machined parts. New environmental manufacturing techniques need to be developed for companies to remain competitive in the future. The research presented in this paper represents the experimentation involved in determining a suitable environmental alternative to using copious amounts of cutting fluid during end milling of Al alloy. Previous experimental evaluation of Minimal Quantities of Lubrication (MQL) when applied to the machining of Al alloy has proved to be inconclusive.

Brian Boswell, Mohammad Nazrul Islam
Fine-Tuning Negotiation Time in Multi-Agent Manufacturing Systems

Global market competition has put intense pressure on the manufacturing industry to become more agile and responsive to market changes. Multi-agent systems (MAS) provide a decentralised control architecture that can reduce complexity, increase flexibility, and enhance fault tolerance for manufacturing systems. Shop floor control applications can be designed based on the paradigm of agent negotiation. This often involves the contract net protocol (CNP) and previous research has suggested that the timing parameters of CNP can affect significantly the performance of agent negotiation. This chapter discusses the combinatorial variations of these parameters using a discrete-event simulation case study.

W. L. Yeung
Adhesive Bonding of Attachments in Automotive Final Assembly

In modern societies there is an increasing concern regarding the environmental impact of automotives is driving automotive manufacturers to develop lighter and, thus, less fuel consuming vehicles. Customers’ protection during crash is a major demand which motivates automotive manufacturers to improve production processes which can satisfy the highly demanding market. Simultaneously, the introduction of new manufacturing techniques is strongly correlated with additional costs, which should be analyzed and quantified, in order to prove the sustainability of such processes for automotive production. This chapter considers adhesive bonding for joining attachments (i.e. roof components) on painted automotive shell surfaces as a potential technique in volume production. In order to introduce such type of adhesive joining process in current production lines, different process chain scenarios are proposed depending on the paint type in order to achieve the required strength of connection, especially during crash loads. Production costs are gathered and a proposed cost analysis is presented for evaluating the suggested scenarios aiming to identify cost intensive procedures.

Loucas Papadakis, Vassos Vassiliou, Michalis Menicou, Manuel Schiel, Klaus Dilger
Uncertainty Components in Performance Measures

Data quality is a multi-dimensional concept and this research will explore its impact in performance measurement systems (PMSs). Despite the large numbers of publications on the design of PMSs and the definition of critical success factors to develop Performance Measures (PMs), from the data user perspective there are possibilities of finding data quality problems, that may have a negative impact in decision making. This work identifies and classifies uncertainty components of PMSs, and proposes a qualitative method for PMs’ quality assessment. Fuzzy PMs are used to represent uncertainty that is present in any physical system. A method is also proposed to calculate an indicator of the compliance between a fuzzy PM and its target value, that can serve as a risk indicator for the decision-maker.

Sérgio Dinis Teixeira de Sousa, Eusébio Manuel Pinto Nunes, Isabel da Silva Lopes
Decision Making of Industrialized Building System: A Supply Chain Perspective on the Influence of Behavioral Economic Factors

Decision making skills with a wide range of decision scenario are relevant to the members of construction supply chain as decision making processes are essential to be understood in ensuring the success of a building project. Currently, there are likely that few decisional issues in the application of Industrialized Building Systems (IBS) require the invention of a completely new dimension and outlook. There is an increasing use of IBS to substitute conventional construction methods in Malaysia, however, the use of IBS technology is often resisted, apparently on grounds other than simply technological. The aim of this chapter is to present the influence of behavioral economic factors on IBS decision making as perceived by IBS supply chain members in Malaysia. Conclusions are drawn and recommendations are made with respect to the perception of behavioral aspects, socio-economic and IBS technology associated with building projects.

Sharifah Akmam Syed Zakaria, Graham Brewer, Thayaparan Gajendran
Metadaten
Titel
IAENG Transactions on Engineering Technologies
herausgegeben von
Gi-Chul Yang
Sio-long Ao
Len Gelman
Copyright-Jahr
2013
Verlag
Springer Netherlands
Electronic ISBN
978-94-007-6190-2
Print ISBN
978-94-007-6189-6
DOI
https://doi.org/10.1007/978-94-007-6190-2