Representing Shared Join Points with State Charts: A High Level Design Approach

Aspect Oriented Programming promises many advantages at programming level by incorporating the cross cutting concerns into separate units, called aspects. Join Points are distinguishing features of Aspect Oriented Programming as they define the points where core requirements and crosscutting concerns are (inter)connected. Currently, there is a problem of multiple aspects- composition at the same join point, which introduces the issues like ordering and controlling of these superimposed aspects. Dynamic strategies are required to handle these issues as early as possible. State chart is an effective modeling tool to capture dynamic behavior at high level design. This paper provides methodology to formulate the strategies for multiple aspect composition at high level, which helps to better implement these strategies at coding level. It also highlights the need of designing shared join point at high level, by providing the solutions of these issues using state chart diagrams in UML 2.0. High level design representation of shared join points also helps to implement the designed strategy in systematic way.

A Robust Frequency Offset Estimation Scheme for OFDM System with Cyclic Delay Diversity

Cyclic delay diversity (CDD) is a simple technique to intentionally increase frequency selectivity of channels for orthogonal frequency division multiplexing (OFDM).This paper proposes a residual carrier frequency offset (RFO) estimation scheme for OFDMbased broadcasting system using CDD. In order to improve the RFO estimation, this paper addresses a decision scheme of the amount of cyclic delay and pilot pattern used to estimate the RFO. By computer simulation, the proposed estimator is shown to benefit form propoerly chosen delay parameter and perform robustly.

Development of Heterogeneous Parallel Genetic Simulated Annealing Using Multi-Niche Crowding

In this paper, a new hybrid of genetic algorithm (GA) and simulated annealing (SA), referred to as GSA, is presented. In this algorithm, SA is incorporated into GA to escape from local optima. The concept of hierarchical parallel GA is employed to parallelize GSA for the optimization of multimodal functions. In addition, multi-niche crowding is used to maintain the diversity in the population of the parallel GSA (PGSA). The performance of the proposed algorithms is evaluated against a standard set of multimodal benchmark functions. The multi-niche crowding PGSA and normal PGSA show some remarkable improvement in comparison with the conventional parallel genetic algorithm and the breeder genetic algorithm (BGA).

Effectiveness and Usability Evaluation of 'Li2D' Courseware

Multimedia courseware has been accepted as a tool that can support teaching and learning process. 'Li2D' courseware was developed to assist student-s visualization on the topic of Loci in Two Dimension. This paper describes an evaluation on the effectiveness and usability of a 'Li2D' courseware. The quasi experiment was used for the effectiveness evaluation. Usability evaluation was accomplished based on four constructs of usability, namely: efficiency, learnability, screen design and satisfaction. An evaluation on the multimedia elements was also conducted. A total of 63 students of Form Two are involved in the study. The students are divided into two groups: control and experimental. The experimental group had to interact with 'Li2D' courseware as part of the learning activities while the control group used the conventional learning methods. The results indicate that the experimental group performed better than the control group in understanding the Loci in Two Dimensions topic. In terms of usability, the results showed that the students agreed on the usability in multimedia elements in the 'Li2D' courseware.

OXADM Asymmetrical Optical Device: Extending the Application to FTTH System

With the drastically growth in optical communication technology, a lossless, low-crosstalk and multifunction optical switch is most desirable for large-scale photonic network. To realize such a switch, we have introduced the new architecture of optical switch that embedded many functions on single device. The asymmetrical architecture of OXADM consists of 3 parts; selective port, add/drop operation, and path routing. Selective port permits only the interest wavelength pass through and acts as a filter. While add and drop function can be implemented in second part of OXADM architecture. The signals can then be re-routed to any output port or/and perform an accumulation function which multiplex all signals onto single path and then exit to any interest output port. This will be done by path routing operation. The unique features offered by OXADM has extended its application to Fiber to-the Home Technology (FTTH), here the OXADM is used as a wavelength management element in Optical Line Terminal (OLT). Each port is assigned specifically with the operating wavelengths and with the dynamic routing management to ensure no traffic combustion occurs in OLT.

Dynamic Routing to Multiple Destinations in IP Networks using Hybrid Genetic Algorithm (DRHGA)

In this paper we have proposed a novel dynamic least cost multicast routing protocol using hybrid genetic algorithm for IP networks. Our protocol finds the multicast tree with minimum cost subject to delay, degree, and bandwidth constraints. The proposed protocol has the following features: i. Heuristic local search function has been devised and embedded with normal genetic operation to increase the speed and to get the optimized tree, ii. It is efficient to handle the dynamic situation arises due to either change in the multicast group membership or node / link failure, iii. Two different crossover and mutation probabilities have been used for maintaining the diversity of solution and quick convergence. The simulation results have shown that our proposed protocol generates dynamic multicast tree with lower cost. Results have also shown that the proposed algorithm has better convergence rate, better dynamic request success rate and less execution time than other existing algorithms. Effects of degree and delay constraints have also been analyzed for the multicast tree interns of search success rate.

Properties of MWCNTs/PAN Nanofiber Sheet Prepared from Chemically Modified MWCNTs

The nanofiber sheet of Multiwall Cabon Nanotube (MWCNTs)/Polyacylonitile (PAN) composites was fabricated from electrospun nanofiber. Firstly the surface of MWCNTs was chemically modified, comparing two different techniques consisting of admicellar polymerization and functionalization to improve the dispersion and prevent the aggregation in the PAN matrix. The modified MWCNTs were characterized by the dispersion in dimethylformamide (DMF) solvent, Laser particle size, and FTRaman. Lastly, DSC, SEM and mechanical properties of the nanofiber sheet were examined. The results show that the mechanical properties of the nanofiber sheet prepared from admicellar polymerization-modified MWCNTs were higher than those of the others.

Discrete-time Phase and Delay Locked Loops Analyses in Tracking Mode

Phase locked loops (PLL) and delay locked loops (DLL) play an important role in establishing coherent references (phase of carrier and symbol timing) in digital communication systems. Fully digital receiver including digital carrier synchronizer and symbol timing synchronizer fulfils the conditions for universal multi-mode communication receiver with option of symbol rate setting over several digit places and long-term stability of requirement parameters. Afterwards it is necessary to realize PLL and DLL in synchronizer in digital form and to approach to these subsystems as a discrete representation of analog template. Analysis of discrete phase locked loop (DPLL) or discrete delay locked loop (DDLL) and technique to determine their characteristics based on analog (continuous-time) template is performed in this posed paper. There are derived transmission response and error function for 1st order discrete locked loop and resulting equations and graphical representations for 2nd order one. It is shown that the spectrum translation due to sampling takes effect at frequency characteristics computing for specific values of loop parameters.

Region-Based Segmentation of Generic Video Scenes Indexing

In this work we develop an object extraction method and propose efficient algorithms for object motion characterization. The set of proposed tools serves as a basis for development of objectbased functionalities for manipulation of video content. The estimators by different algorithms are compared in terms of quality and performance and tested on real video sequences. The proposed method will be useful for the latest standards of encoding and description of multimedia content – MPEG4 and MPEG7.

RFU Based Computational Unit Design For Reconfigurable Processors

Fully customized hardware based technology provides high performance and low power consumption by specializing the tasks in hardware but lacks design flexibility since any kind of changes require re-design and re-fabrication. Software based solutions operate with software instructions due to which a great flexibility is achieved from the easy development and maintenance of the software code. But this execution of instructions introduces a high overhead in performance and area consumption. In past few decades the reconfigurable computing domain has been introduced which overcomes the traditional trades-off between flexibility and performance and is able to achieve high performance while maintaining a good flexibility. The dramatic gains in terms of chip performance and design flexibility achieved through the reconfigurable computing systems are greatly dependent on the design of their computational units being integrated with reconfigurable logic resources. The computational unit of any reconfigurable system plays vital role in defining its strength. In this research paper an RFU based computational unit design has been presented using the tightly coupled, multi-threaded reconfigurable cores. The proposed design has been simulated for VLIW based architectures and a high gain in performance has been observed as compared to the conventional computing systems.

Support Vector Machines Approach for Detecting the Mean Shifts in Hotelling-s T2 Control Chart with Sensitizing Rules

In many industries, control charts is one of the most frequently used tools for quality management. Hotelling-s T2 is used widely in multivariate control chart. However, it has little defect when detecting small or medium process shifts. The use of supplementary sensitizing rules can improve the performance of detection. This study applied sensitizing rules for Hotelling-s T2 control chart to improve the performance of detection. Support vector machines (SVM) classifier to identify the characteristic or group of characteristics that are responsible for the signal and to classify the magnitude of the mean shifts. The experimental results demonstrate that the support vector machines (SVM) classifier can effectively identify the characteristic or group of characteristics that caused the process mean shifts and the magnitude of the shifts.

A Novel SVM-Based OOK Detector in Low SNR Infrared Channels

Support Vector Machine (SVM) is a recent class of statistical classification and regression techniques playing an increasing role in applications to detection problems in various engineering problems, notably in statistical signal processing, pattern recognition, image analysis, and communication systems. In this paper, SVM is applied to an infrared (IR) binary communication system with different types of channel models including Ricean multipath fading and partially developed scattering channel with additive white Gaussian noise (AWGN) at the receiver. The structure and performance of SVM in terms of the bit error rate (BER) metric is derived and simulated for these channel stochastic models and the computational complexity of the implementation, in terms of average computational time per bit, is also presented. The performance of SVM is then compared to classical binary signal maximum likelihood detection using a matched filter driven by On-Off keying (OOK) modulation. We found that the performance of SVM is superior to that of the traditional optimal detection schemes used in statistical communication, especially for very low signal-to-noise ratio (SNR) ranges. For large SNR, the performance of the SVM is similar to that of the classical detectors. The implication of these results is that SVM can prove very beneficial to IR communication systems that notoriously suffer from low SNR at the cost of increased computational complexity.

SEM and AFM Investigations of Surface Defects and Tool Wear of Multilayers Coated Carbide Inserts

Coated tool inserts can be considered as the backbone of machining processes due to their wear and heat resistance. However, defects of coating can degrade the integrity of these inserts and the number of these defects should be minimized or eliminated if possible. Recently, the advancement of coating processes and analytical tools open a new era for optimizing the coating tools. First, an overview is given regarding coating technology for cutting tool inserts. Testing techniques for coating layers properties, as well as the various coating defects and their assessment are also surveyed. Second, it is introduced an experimental approach to examine the possible coating defects and flaws of worn multicoated carbide inserts using two important techniques namely scanning electron microscopy and atomic force microscopy. Finally, it is recommended a simple procedure for investigating manufacturing defects and flaws of worn inserts.

Formant Tracking Linear Prediction Model using HMMs for Noisy Speech Processing

This paper presents a formant-tracking linear prediction (FTLP) model for speech processing in noise. The main focus of this work is the detection of formant trajectory based on Hidden Markov Models (HMM), for improved formant estimation in noise. The approach proposed in this paper provides a systematic framework for modelling and utilization of a time- sequence of peaks which satisfies continuity constraints on parameter; the within peaks are modelled by the LP parameters. The formant tracking LP model estimation is composed of three stages: (1) a pre-cleaning multi-band spectral subtraction stage to reduce the effect of residue noise on formants (2) estimation stage where an initial estimate of the LP model of speech for each frame is obtained (3) a formant classification using probability models of formants and Viterbi-decoders. The evaluation results for the estimation of the formant tracking LP model tested in Gaussian white noise background, demonstrate that the proposed combination of the initial noise reduction stage with formant tracking and LPC variable order analysis, results in a significant reduction in errors and distortions. The performance was evaluated with noisy natual vowels extracted from international french and English vocabulary speech signals at SNR value of 10dB. In each case, the estimated formants are compared to reference formants.

Indexing and Searching of Image Data in Multimedia Databases Using Axial Projection

This paper introduces and studies new indexing techniques for content-based queries in images databases. Indexing is the key to providing sophisticated, accurate and fast searches for queries in image data. This research describes a new indexing approach, which depends on linear modeling of signals, using bases for modeling. A basis is a set of chosen images, and modeling an image is a least-squares approximation of the image as a linear combination of the basis images. The coefficients of the basis images are taken together to serve as index for that image. The paper describes the implementation of the indexing scheme, and presents the findings of our extensive evaluation that was conducted to optimize (1) the choice of the basis matrix (B), and (2) the size of the index A (N). Furthermore, we compare the performance of our indexing scheme with other schemes. Our results show that our scheme has significantly higher performance.

A Goal Programming Approach for Plastic Recycling System in Thailand

Plastic waste is a big issue in Thailand, but the amount of recycled plastic in Thailand is still low due to the high investment and operating cost. Hence, the rest of plastic waste are burnt to destroy or sent to the landfills. In order to be financial viable, an effective reverse logistics infrastructure is required to support the product recovery activities. However, there is a conflict between reducing the cost and raising environmental protection level. The purpose of this study is to build a goal programming (GP) so that it can be used to help analyze the proper planning of the Thailand-s plastic recycling system that involves multiple objectives. This study considers three objectives; reducing total cost, increasing the amount of plastic recovery, and raising the desired plastic materials in recycling process. The results from two priority structures show that it is necessary to raise the total cost budget in order to achieve targets on amount of recycled plastic and desired plastic materials.

Identification of Cardiac Arrhythmias using Natural Resonance Complex Frequencies

An electrocardiogram (ECG) feature extraction system based on the calculation of the complex resonance frequency employing Prony-s method is developed. Prony-s method is applied on five different classes of ECG signals- arrhythmia as a finite sum of exponentials depending on the signal-s poles and the resonant complex frequencies. Those poles and resonance frequencies of the ECG signals- arrhythmia are evaluated for a large number of each arrhythmia. The ECG signals of lead II (ML II) were taken from MIT-BIH database for five different types. These are the ventricular couplet (VC), ventricular tachycardia (VT), ventricular bigeminy (VB), and ventricular fibrillation (VF) and the normal (NR). This novel method can be extended to any number of arrhythmias. Different classification techniques were tried using neural networks (NN), K nearest neighbor (KNN), linear discriminant analysis (LDA) and multi-class support vector machine (MC-SVM).

Simulation Modeling for Analysis and Evaluation of the Internal Handling Fleet System at Shahid Rajaee Container Port

The dramatic increasing of sea-freight container transportations and the developing trends for using containers in the multimodal handling systems through the sea, rail, road and land in nowadays market cause general managers of container terminals to face challenges such as increasing demand, competitive situation, new investments and expansion of new activities and need to use new methods to fulfil effective operations both along quayside and within the yard. Among these issues, minimizing the turnaround time of vessels is considered to be the first aim of every container port system. Regarding the complex structure of container ports, this paper presents a simulation model that calculates the number of trucks needed in the Iranian Shahid Rajaee Container Port for handling containers between the berth and the yard. In this research, some important criteria such as vessel turnaround time, gantry crane utilization and truck utilization have been considered. By analyzing the results of the model, it has been shown that increasing the number of trucks to 66 units has a significant effect on the performance indices of the port and can increase the capacity of loading and unloading up to 10.8%.

The Multi-Layered Perceptrons Neural Networks for the Prediction of Daily Solar Radiation

The Multi-Layered Perceptron (MLP) Neural networks have been very successful in a number of signal processing applications. In this work we have studied the possibilities and the met difficulties in the application of the MLP neural networks for the prediction of daily solar radiation data. We have used the Polack-Ribière algorithm for training the neural networks. A comparison, in term of the statistical indicators, with a linear model most used in literature, is also performed, and the obtained results show that the neural networks are more efficient and gave the best results.

Model of Controled Six Phase Induction Motor

In this paper, the authors take a look at advantages of multiphase induction motors comparing them with three phase ones and present the applications where six-phase induction motors are used. They elaborate the mathematical model of six-phase induction motor with two similar stator three phase winding, shifted by 30 degrees in space and three phase winding in rotor, in synchronous reference frame for soft starting and scalar control. The authors simulate and discuss results of speed and torque starting transients.