Analytical and Finite Element Analysis of Hydroforming Deep Drawing Process

This paper gives an overview of a deep drawing process by pressurized liquid medium separated from the sheet by a rubber diaphragm. Hydroforming deep drawing processing of sheet metal parts provides a number of advantages over conventional techniques. It generally increases the depth to diameter ratio possible in cup drawing and minimizes the thickness variation of the drawn cup. To explore the deformation mechanism, analytical and numerical simulations are used for analyzing the drawing process of an AA6061-T4 blank. The effects of key process parameters such as coefficient of friction, initial thickness of the blank and radius between cup wall and flange are investigated analytically and numerically. The simulated results were in good agreement with the results of the analytical model. According to finite element simulations, the hydroforming deep drawing method provides a more uniform thickness distribution compared to conventional deep drawing and decreases the risk of tearing during the process.

Evaluation of Risk Attributes Driven by Periodically Changing System Functionality

Modeling of the distributed systems allows us to represent the whole its functionality. The working system instance rarely fulfils the whole functionality represented by model; usually some parts of this functionality should be accessible periodically. The reporting system based on the Data Warehouse concept seams to be an intuitive example of the system that some of its functionality is required only from time to time. Analyzing an enterprise risk associated with the periodical change of the system functionality, we should consider not only the inaccessibility of the components (object) but also their functions (methods), and the impact of such a situation on the system functionality from the business point of view. In the paper we suggest that the risk attributes should be estimated from risk attributes specified at the requirements level (Use Case in the UML model) on the base of the information about the structure of the model (presented at other levels of the UML model). We argue that it is desirable to consider the influence of periodical changes in requirements on the enterprise risk estimation. Finally, the proposition of such a solution basing on the UML system model is presented.

The Haar Wavelet Transform of the DNA Signal Representation

The Deoxyribonucleic Acid (DNA) which is a doublestranded helix of nucleotides consists of: Adenine (A), Cytosine (C), Guanine (G) and Thymine (T). In this work, we convert this genetic code into an equivalent digital signal representation. Applying a wavelet transform, such as Haar wavelet, we will be able to extract details that are not so clear in the original genetic code. We compare between different organisms using the results of the Haar wavelet Transform. This is achieved by using the trend part of the signal since the trend part bears the most energy of the digital signal representation. Consequently, we will be able to quantitatively reconstruct different biological families.

A Finite Volume Procedure on Unstructured Meshes for Fluid-Structure Interaction Problems

Flow through micro and mini channels requires relatively high driving pressure due to the large fluid pressure drop through these channels. Consequently the forces acting on the walls of the channel due to the fluid pressure are also large. Due to these forces there are displacement fields set up in the solid substrate containing the channels. If the movement of the substrate is constrained at some points, then stress fields are established in the substrate. On the other hand, if the deformation of the channel shape is sufficiently large then its effect on the fluid flow is important to be calculated. Such coupled fluid-solid systems form a class of problems known as fluidstructure interactions. In the present work a co-located finite volume discretization procedure on unstructured meshes is described for solving fluid-structure interaction type of problems. A linear elastic solid is assumed for which the effect of the channel deformation on the flow is neglected. Thus the governing equations for the fluid and the solid are decoupled and are solved separately. The procedure is validated by solving two benchmark problems, one from fluid mechanics and another from solid mechanics. A fluid-structure interaction problem of flow through a U-shaped channel embedded in a plate is solved.

A Study on Flammability of Bio Oil Combustible Vapour Mixtures

Study of fire and explosion is very important mainly in oil and gas industries due to several accidents which have been reported in the past and present. In this work, we have investigated the flammability of bio oil vapour mixtures. This mixture may contribute to fire during the storage and transportation process. Bio oil sample derived from Palm Kernell shell was analysed using Gas Chromatography Mass Spectrometry (GC-MS) to examine the composition of the sample. Mole fractions of 12 selected components in the liquid phase were obtained from the GC-FID data and used to calculate mole fractions of components in the gas phase via modified Raoult-s law. Lower Flammability Limits (LFLs) and Upper Flammability Limits (UFLs) for individual components were obtained from published literature. However, stoichiometric concentration method was used to calculate the flammability limits of some components which their flammability limit values are not available in the literature. The LFL and UFL values for the mixture were calculated using the Le Chatelier equation. The LFLmix and UFLmix values were used to construct a flammability diagram and subsequently used to determine the flammability of the mixture. The findings of this study can be used to propose suitable inherently safer method to prevent the flammable mixture from occurring and to minimizing the loss of properties, business, and life due to fire accidents in bio oil productions.

Semisolid Structure and Parameters for A360 Aluminum Alloy Prepared by Mechanical Stirring

Semisolid metal processing uses solid–liquid slurries containing fine and globular solid particles uniformly distributed in a liquid matrix, which can be handled as a solid and flow like a liquid. In the recent years, many methods have been introduced for the production of semisolid slurries since it is scientifically sound and industrially viable with such preferred microstructures called thixotropic microstructures as feedstock materials. One such process that needs very low equipment investment and running costs is the cooling slope. In this research by using a mechanical stirrer slurry maker constructed by the authors, the effects of mechanical stirring parameters such as: stirring time, stirring temperature and stirring Speed on micro-structure and mechanical properties of A360 aluminum alloy in semi-solid forming, are investigated. It is determined that mold temperature and holding time of part in temperature of 580ºC have a great effect on micro-structure and mechanical properties(stirring temperature of 585ºC, stirring time of 20 minutes and stirring speed of 425 RPM). By optimizing the forming parameters, dendrite microstructure changes to globular and mechanical properties improves. This is because of breaking and globularzing dendrites of primary α-AL.

An Amalgam Approach for DICOM Image Classification and Recognition

This paper describes about the process of recognition and classification of brain images such as normal and abnormal based on PSO-SVM. Image Classification is becoming more important for medical diagnosis process. In medical area especially for diagnosis the abnormality of the patient is classified, which plays a great role for the doctors to diagnosis the patient according to the severeness of the diseases. In case of DICOM images it is very tough for optimal recognition and early detection of diseases. Our work focuses on recognition and classification of DICOM image based on collective approach of digital image processing. For optimal recognition and classification Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Support Vector Machine (SVM) are used. The collective approach by using PSO-SVM gives high approximation capability and much faster convergence.

Double Reduction of Ada-ECATNet Representation using Rewriting Logic

One major difficulty that faces developers of concurrent and distributed software is analysis for concurrency based faults like deadlocks. Petri nets are used extensively in the verification of correctness of concurrent programs. ECATNets [2] are a category of algebraic Petri nets based on a sound combination of algebraic abstract types and high-level Petri nets. ECATNets have 'sound' and 'complete' semantics because of their integration in rewriting logic [12] and its programming language Maude [13]. Rewriting logic is considered as one of very powerful logics in terms of description, verification and programming of concurrent systems. We proposed in [4] a method for translating Ada-95 tasking programs to ECATNets formalism (Ada-ECATNet). In this paper, we show that ECATNets formalism provides a more compact translation for Ada programs compared to the other approaches based on simple Petri nets or Colored Petri nets (CPNs). Such translation doesn-t reduce only the size of program, but reduces also the number of program states. We show also, how this compact Ada-ECATNet may be reduced again by applying reduction rules on it. This double reduction of Ada-ECATNet permits a considerable minimization of the memory space and run time of corresponding Maude program.

Effect of CW Laser Annealing on Silicon Surface for Application of Power Device

As application of re-activation of backside on power device Insulated Gate Bipolar Transistor (IGBT), laser annealing was employed to irradiate amorphous silicon substrate, and resistivities were measured using four point probe measurement. For annealing the amorphous silicon two lasers were used at wavelength of visible green (532 nm) together with Infrared (793 nm). While the green laser efficiently increased temperature at top surface the Infrared laser reached more deep inside and was effective for melting the top surface. A finite element method was employed to evaluate time dependent thermal distribution in silicon substrate.

Segmenting Ultrasound B-Mode Images Using RiIG Distributions and Stochastic Optimization

In this paper, we propose a novel algorithm for delineating the endocardial wall from a human heart ultrasound scan. We assume that the gray levels in the ultrasound images are independent and identically distributed random variables with different Rician Inverse Gaussian (RiIG) distributions. Both synthetic and real clinical data will be used for testing the algorithm. Algorithm performance will be evaluated using the expert radiologist evaluation of a soft copy of an ultrasound scan during the scanning process and secondly, doctor’s conclusion after going through a printed copy of the same scan. Successful implementation of this algorithm should make it possible to differentiate normal from abnormal soft tissue and help disease identification, what stage the disease is in and how best to treat the patient. We hope that an automated system that uses this algorithm will be useful in public hospitals especially in Third World countries where problems such as shortage of skilled radiologists and shortage of ultrasound machines are common. These public hospitals are usually the first and last stop for most patients in these countries.

Design of OTA with Common Drain and Folded Cascade Used in ADC

In this report, an OTA which is used in fully differential pipelined ADC was described. Using gain-boost architecture with difference-ended amplifier, this OTA achieve high-gain and high-speed. Besides, the CMFB circuit is also used, and some methods are concerned to improve the performance. Then, by optimization the layout design, OTA-s mismatch was reduced. This design was using TSMC 0.18um CMOS process and simulation both schematic and layout in Cadence. The result of the simulation shows that the OTA has a gain up to 80dB,a unity gain bandwidth of about 1.437GHz for a 2pF load, a slew rate is about 428V/μs, a output swing is 0.2V~1.35V, with the power supply of 1.8V, the power consumption is 88mW. This amplifier was used in a 10bit 150MHz pipelined ADC.

When Construction Material Traders Goes Electronic: Analysis of SMEs in Malaysian Construction Industry

This paper analyzed the perception of e-commerce application services by construction material traders in Malaysia. Five attributes were tested: usability, reputation, trust, privacy and familiarity. Study methodology consists of survey questionnaire and statistical analysis that includes reliability analysis, factor analysis, ANOVA and regression analysis. The respondents were construction material traders, including hardware stores in Klang Valley, Kuala Lumpur. Findings support that usability and familiarity with e-commerce services in Malaysia have insignificant influence on the acceptance of e-commerce application. However, reputation, trust and privacy attributes have significant influence on the choice of e-commerce acceptance by construction material traders. E-commerce applications studied included customer database, e-selling, emarketing, e-payment, e-buying and online advertising. Assumptions are made that traders have basic knowledge and exposure to ICT services. i.e. internet service and computers. Study concludes that reputation, privacy and trust are the three website attributes that influence the acceptance of e-commerce by construction material traders.

A K-Means Based Clustering Approach for Finding Faulty Modules in Open Source Software Systems

Prediction of fault-prone modules provides one way to support software quality engineering. Clustering is used to determine the intrinsic grouping in a set of unlabeled data. Among various clustering techniques available in literature K-Means clustering approach is most widely being used. This paper introduces K-Means based Clustering approach for software finding the fault proneness of the Object-Oriented systems. The contribution of this paper is that it has used Metric values of JEdit open source software for generation of the rules for the categorization of software modules in the categories of Faulty and non faulty modules and thereafter empirically validation is performed. The results are measured in terms of accuracy of prediction, probability of Detection and Probability of False Alarms.

Technology Integrated Education – Shaping the Personality and Social Development of the Young

There has been a strong link between computermediated education and constructivism learning and teaching theory.. Acknowledging how well the constructivism doctrine would work online, it has been established that constructivist views of learning would agreeably correlate with the philosophy of open and distance learning. Asynchronous and synchronous communications have placed online learning on the right track of a constructive learning path. This paper is written based on the social constructivist framework, where knowledge is constructed from social communication and interaction. The study explores the possibility of practicing this theory through incorporating online discussion in the syllabus and the ways it can be implemented to contribute to young people-s personality and social development by addressing some aspects that may contribute to the social problem such as prejudice, ignorance and intolerance.

A New Approach for Effect Evaluation of Sediment Management

Safety, river environment, and sediment utilization are the elements of the target of sediment management. As a change in an element by sediment management, may affect the other two elements, and the priority among three elements depends on stakeholders. It is necessary to develop a method to evaluate the effect of sediment management on each element and an integrated evaluation method for socio-economic effect. In this study, taking Mount Merapi basin as an investigation field, the method for an active volcanic basin was developed. An integrated evaluation method for sediment management was discussed from a socio-economic point on safety, environment, and sediment utilization and a case study of sediment management was evaluated by means of this method. To evaluate the effect of sediment management, some parameters on safety, utilization, and environment have been introduced. From a utilization point of view, job opportunity, additional income of local people, and tax income to local government were used to evaluate the effectiveness of sediment management. The risk degree of river infrastructure was used to describe the effect of sediment management on a safety aspect. To evaluate the effects of sediment management on environment, the mean diameter of grain size distribution of riverbed surface was used. On the coordinate system designating these elements, the direction of change in basin condition by sediment management can be predicted, so that the most preferable sediment management can be decided. The results indicate that the cases of sediment management tend to give the negative impacts on sediment utilization. However, these sediment managements will give positive impacts on safety and environment condition. Evaluation result from a social-economic point of view shows that the case study of sediment management reduces job opportunity and additional income for inhabitants as well as tax income for government. Therefore, it is necessary to make another policy for creating job opportunity for inhabitants to support these sediment managements.

A Multi-Objective Model for Supply Chain Network Design under Stochastic Demand

In this article, the design of a Supply Chain Network (SCN) consisting of several suppliers, production plants, distribution centers and retailers, is considered. Demands of retailers are considered stochastic parameters, so we generate amounts of data via simulation to extract a few demand scenarios. Then a mixed integer two-stage programming model is developed to optimize simultaneously two objectives: (1) minimization the fixed and variable cost, (2) maximization the service level. A weighting method is utilized to solve this two objective problem and a numerical example is made to show the performance of the model.

Noise Factors of RFID-Aided Positioning

In recent years, Radio Frequency Identification (RFID) is followed with interest by many researches, especially for the purpose of indoor positioning as the innate properties of RFID are profitable for achieving it. A lot of algorithms or schemes are proposed to be used in the RFID-based positioning system, but most of them are lack of environmental consideration and it induces inaccuracy of application. In this research, a lot of algorithms and schemes of RFID indoor positioning are discussed to see whether effective or not on application, and some rules are summarized for achieving accurate positioning. On the other hand, a new term “Noise Factor" is involved to describe the signal loss between the target and the obstacle. As a result, experimental data can be obtained but not only simulation; and the performance of the positioning system can be expressed substantially.

Communication and Quality in Distributed Agile Development: An Empirical Case Study

Through inward perceptions, we intuitively expect distributed software development to increase the risks associated with achieving cost, schedule, and quality goals. To compound this problem, agile software development (ASD) insists one of the main ingredients of its success is cohesive communication attributed to collocation of the development team. The following study identified the degree of communication richness needed to achieve comparable software quality (reduce pre-release defects) between distributed and collocated teams. This paper explores the relevancy of communication richness in various development phases and its impact on quality. Through examination of a large distributed agile development project, this investigation seeks to understand the levels of communication required within each ASD phase to produce comparable quality results achieved by collocated teams. Obviously, a multitude of factors affects the outcome of software projects. However, within distributed agile software development teams, the mode of communication is one of the critical components required to achieve team cohesiveness and effectiveness. As such, this study constructs a distributed agile communication model (DAC-M) for potential application to similar distributed agile development efforts using the measurement of the suitable level of communication. The results of the study show that less rich communication methods, in the appropriate phase, might be satisfactory to achieve equivalent quality in distributed ASD efforts.

Face Recognition using a Kernelization of Graph Embedding

Linearization of graph embedding has been emerged as an effective dimensionality reduction technique in pattern recognition. However, it may not be optimal for nonlinearly distributed real world data, such as face, due to its linear nature. So, a kernelization of graph embedding is proposed as a dimensionality reduction technique in face recognition. In order to further boost the recognition capability of the proposed technique, the Fisher-s criterion is opted in the objective function for better data discrimination. The proposed technique is able to characterize the underlying intra-class structure as well as the inter-class separability. Experimental results on FRGC database validate the effectiveness of the proposed technique as a feature descriptor.

Support Vector Machine based Intelligent Watermark Decoding for Anticipated Attack

In this paper, we present an innovative scheme of blindly extracting message bits from an image distorted by an attack. Support Vector Machine (SVM) is used to nonlinearly classify the bits of the embedded message. Traditionally, a hard decoder is used with the assumption that the underlying modeling of the Discrete Cosine Transform (DCT) coefficients does not appreciably change. In case of an attack, the distribution of the image coefficients is heavily altered. The distribution of the sufficient statistics at the receiving end corresponding to the antipodal signals overlap and a simple hard decoder fails to classify them properly. We are considering message retrieval of antipodal signal as a binary classification problem. Machine learning techniques like SVM is used to retrieve the message, when certain specific class of attacks is most probable. In order to validate SVM based decoding scheme, we have taken Gaussian noise as a test case. We generate a data set using 125 images and 25 different keys. Polynomial kernel of SVM has achieved 100 percent accuracy on test data.