Search results for: state machine diagrams
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3281

Search results for: state machine diagrams

2591 A Comparative Study of the Modeling and Quality Control of the Propylene-Propane Classical Distillation and Distillation Column with Heat Pump

Authors: C. Patrascioiu, Cao Minh Ahn

Abstract:

The paper presents the research evolution in the propylene – propane distillation process, especially for the distillation columns equipped with heat pump. The paper is structured in three parts: separation of the propylene-propane mixture, steady state process modeling, and quality control systems. The first part is dedicated to state of art of the two distillation processes. The second part continues the author’s researches of the steady state process modeling. There has been elaborated a software simulation instrument that may be used to dynamic simulation of the process and to design the quality control systems. The last part presents the research of the control systems, especially for quality control systems.

Keywords: Distillation, absorption, heat pump, Unisim Design.

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2590 Simulation and Validation of Spur Gear Heated by Induction using 3d Model

Authors: A. Chebak, N. Barka, A. Menou, J. Brousseau, D. S. Ramdenee

Abstract:

This paper presents the study of hardness profile of spur gear heated by induction heating process in function of the machine parameters, such as the power (kW), the heating time (s) and the generator frequency (kHz). The global work is realized by 3D finite-element simulation applied to the process by coupling and resolving the electromagnetic field and the heat transfer problems, and it was performed in three distinguished steps. First, a Comsol 3D model was built using an adequate formulation and taking into account the material properties and the machine parameters. Second, the convergence study was conducted to optimize the mesh. Then, the surface temperatures and the case depths were deeply analyzed in function of the initial current density and the heating time in medium frequency (MF) and high frequency (HF) heating modes and the edge effect were studied. Finally, the simulations results are validated using experimental tests.

Keywords: Induction heating, simulation, experimental validation, 3D model, hardness profile.

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2589 Stochastic Model Predictive Control for Linear Discrete-Time Systems with Random Dither Quantization

Authors: Tomoaki Hashimoto

Abstract:

Recently, feedback control systems using random dither quantizers have been proposed for linear discrete-time systems. However, the constraints imposed on state and control variables have not yet been taken into account for the design of feedback control systems with random dither quantization. Model predictive control is a kind of optimal feedback control in which control performance over a finite future is optimized with a performance index that has a moving initial and terminal time. An important advantage of model predictive control is its ability to handle constraints imposed on state and control variables. Based on the model predictive control approach, the objective of this paper is to present a control method that satisfies probabilistic state constraints for linear discrete-time feedback control systems with random dither quantization. In other words, this paper provides a method for solving the optimal control problems subject to probabilistic state constraints for linear discrete-time feedback control systems with random dither quantization.

Keywords: Optimal control, stochastic systems, discrete-time systems, probabilistic constraints, random dither quantization.

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2588 Use of Bayesian Network in Information Extraction from Unstructured Data Sources

Authors: Quratulain N. Rajput, Sajjad Haider

Abstract:

This paper applies Bayesian Networks to support information extraction from unstructured, ungrammatical, and incoherent data sources for semantic annotation. A tool has been developed that combines ontologies, machine learning, and information extraction and probabilistic reasoning techniques to support the extraction process. Data acquisition is performed with the aid of knowledge specified in the form of ontology. Due to the variable size of information available on different data sources, it is often the case that the extracted data contains missing values for certain variables of interest. It is desirable in such situations to predict the missing values. The methodology, presented in this paper, first learns a Bayesian network from the training data and then uses it to predict missing data and to resolve conflicts. Experiments have been conducted to analyze the performance of the presented methodology. The results look promising as the methodology achieves high degree of precision and recall for information extraction and reasonably good accuracy for predicting missing values.

Keywords: Information Extraction, Bayesian Network, ontology, Machine Learning

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2587 Geospatial Assessment of State Lands in the Cape Coast Urban Area

Authors: E. B. Quarcoo, I. Yakubu, K. J. Appau

Abstract:

Current land use and land cover (LULC) dynamics in Ghana have revealed considerable changes in settlement spaces. As a result, this study is intended to merge the cellular automata and Markov chain models using remotely sensed data and Geographical Information System (GIS) approaches to monitor, map, and detect the spatio-temporal LULC change in state lands within Cape Coast Metropolis. Multi-temporal satellite images from 1986-2020 were pre-processed, geo-referenced, and then mapped using supervised maximum likelihood classification to investigate the state’s land cover history (1986-2020) with an overall mapping accuracy of approximately 85%. The study further observed the rate of change for the area to have favored the built-up area 9.8 (12.58 km2) to the detriment of vegetation 5.14 (12.68 km2), but on average, 0.37 km2 (91.43 acres, or 37.00 ha.) of the landscape was transformed yearly. Subsequently, the CA-Markov model was used to anticipate the potential LULC for the study area for 2030. According to the anticipated 2030 LULC map, the patterns of vegetation transitioning into built-up regions will continue over the following ten years as a result of urban growth.

Keywords: LULC, cellular automata, Markov Chain, state lands, urbanisation, public lands, cape coast metropolis.

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2586 Nonlinear Effects in Bubbly Liquid with Shock Waves

Authors: Raisa Kh. Bolotnova, Marat N. Galimzianov, Andrey S. Topolnikov, Uliana O. Agisheva, Valeria A. Buzina

Abstract:

The paper presents the results of theoretical and numerical modeling of propagation of shock waves in bubbly liquids related to nonlinear effects (realistic equation of state, chemical reactions, two-dimensional effects). On the basis on the Rankine- Hugoniot equations the problem of determination of parameters of passing and reflected shock waves in gas-liquid medium for isothermal, adiabatic and shock compression of the gas component is solved by using the wide-range equation of state of water in the analitic form. The phenomenon of shock wave intensification is investigated in the channel of variable cross section for the propagation of a shock wave in the liquid filled with bubbles containing chemically active gases. The results of modeling of the wave impulse impact on the solid wall covered with bubble layer are presented.

Keywords: bubbly liquid, cavitation, equation of state, shock wave

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2585 Adaptation of State/Transition-Based Methods for Embedded System Testing

Authors: Abdelaziz Guerrouat, Harald Richter

Abstract:

In this paper test generation methods and appropriate fault models for testing and analysis of embedded systems described as (extended) finite state machines ((E)FSMs) are presented. Compared to simple FSMs, EFSMs specify not only the control flow but also the data flow. Thus, we define a two-level fault model to cover both aspects. The goal of this paper is to reuse well-known FSM-based test generation methods for automation of embedded system testing. These methods have been widely used in testing and validation of protocols and communicating systems. In particular, (E)FSMs-based specification and testing is more advantageous because (E)FSMs support the formal semantic of already standardised formal description techniques (FDTs) despite of their popularity in the design of hardware and software systems.

Keywords: Formal methods, testing and validation, finite state machines, formal description techniques.

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2584 Adaptive Kalman Filter for Noise Estimation and Identification with Bayesian Approach

Authors: Farhad Asadi, S. Hossein Sadati

Abstract:

Bayesian approach can be used for parameter identification and extraction in state space models and its ability for analyzing sequence of data in dynamical system is proved in different literatures. In this paper, adaptive Kalman filter with Bayesian approach for identification of variances in measurement parameter noise is developed. Next, it is applied for estimation of the dynamical state and measurement data in discrete linear dynamical system. This algorithm at each step time estimates noise variance in measurement noise and state of system with Kalman filter. Next, approximation is designed at each step separately and consequently sufficient statistics of the state and noise variances are computed with a fixed-point iteration of an adaptive Kalman filter. Different simulations are applied for showing the influence of noise variance in measurement data on algorithm. Firstly, the effect of noise variance and its distribution on detection and identification performance is simulated in Kalman filter without Bayesian formulation. Then, simulation is applied to adaptive Kalman filter with the ability of noise variance tracking in measurement data. In these simulations, the influence of noise distribution of measurement data in each step is estimated, and true variance of data is obtained by algorithm and is compared in different scenarios. Afterwards, one typical modeling of nonlinear state space model with inducing noise measurement is simulated by this approach. Finally, the performance and the important limitations of this algorithm in these simulations are explained. 

Keywords: adaptive filtering, Bayesian approach Kalman filtering approach, variance tracking

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2583 An E-Government Implementation Model for Peruvian State Companies Based on COBIT 5.0: Definition and Goals of the Model

Authors: M. Bruzza, M. Tupia, F. Rodríguez

Abstract:

As part of the regulatory compliance process and the streamlining of public administration, the Peruvian government has implemented the National E-Government Plan in all state institutions with the aim of providing citizens with solid services based on the use of Information and Communications Technologies (ICT). As part of the regulations, the requisites to be met by public institutions have been submitted. However, the lack of an implementation model was detected, one that can serve as a guide to such institutions in order to materialize the organizational and technological structures needed, which allow them to provide the required digital services. This paper develops an implementation model of electronic government (e-government) for Peru’s state institutions, in compliance with current regulations based on a COBIT 5.0 framework. Furthermore, the paper introduces phase 1 of this model: business and IT goals, the goals cascade and the future model of processes.

Keywords: E-government, implementation, model, COBIT 5.0, digital services, u-government, m-government.

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2582 Production of Biodiesel Using Tannery Fleshing as a Feedstock via Solid-State Fermentation

Authors: C. Santhana Krishnan, A. M. Mimi Sakinah, Lakhveer Singh, Zularisam A. Wahid

Abstract:

This study was initiated to evaluate and optimize the conversion of animal fat from tannery wastes into methyl ester. In the pre-treatment stage, animal fats feedstock was hydrolysed and esterified through solid state fermentation (SSF) using Microbacterium species immobilized onto sand silica matrix. After 72 hours of fermentation, predominant esters in the animal fats were found to be with 83.9% conversion rate. Later, esterified animal fats were transesterified at 3 hour reaction time with 1% NaOH (w/v %), 6% methanol to oil ratio (w/v %) to produce 89% conversion rate. C13 NMR revealed long carbon chain in fatty acid methyl esters at 22.2817-31.9727 ppm. Methyl esters of palmitic, stearic, oleic represented the major components in biodiesel.

Keywords: Tannery wastes, fatty animal fleshing, trans-esterification, immobilization, solid state fermentation.

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2581 A Real-time 4M Collecting Method for Production Information System

Authors: Seung Woo Lee, So Jeong Nam, Jai-Kyung Lee

Abstract:

It can be said that the business sector is faced with a range of challenges–a rapidly changing business environment, an increase and diversification of customers- demands and the consequent need for quick response–for having in place flexible management and production info systems. As a matter of fact, many manufacturers have adopted production info management systems such as MES and ERP. Nevertheless, managers are having difficulties obtaining ever-changing production process information in real time, or responding quickly to any change in production related needs on the basis of such information. This is because they rely on poor production info systems which are not capable of providing real-time factory settings. If the manufacturer doesn-t have a capacity for collecting or digitalizing the 4 Ms (Man, Machine, Material, Method), which are resources for production, on a real time basis, it might to difficult to effectively maintain the information on production process. In this regard, this paper will introduce some new alternatives to the existing methods of collecting the 4 Ms in real time, which are currently comprise the production field.

Keywords: 4M, Acquisition of Data on shop-floor, Real-time machine interface

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2580 Three Dimensional Analysis of Sequential Quasi Isotropic Composite Disc for Rotating Machine Application

Authors: Amin Almasi

Abstract:

Composite laminates are relatively weak in out of plane loading, inter-laminar stress, stress concentration near the edge and stress singularities. This paper develops a new analytical formulation for laminated composite rotating disc fabricated from symmetric sequential quasi isotropic layers to predict three dimensional stress and deformation. This analysis is necessary to evaluate mechanical integrity of fiber reinforced multi-layer laminates used for high speed rotating applications such as high speed impellers. Three dimensional governing equations are written for rotating composite disc. Explicit solution is obtained with "Frobenius" expansion series. Based on analytical results, there are two separate zones of three dimensional stress fields in centre and edge of rotating disc. For thin discs, out of plane deformations and stresses are small in comparison with plane ones. For relatively thick discs deformation and stress fields are three dimensional.

Keywords: Composite Disc, Rotating Machine.

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2579 Hair Mechanical Properties Depending on Age and Origin

Authors: Meriem Benzarti, Mohamed Ben Tkaya, Cyril Pailler Mattei, Hassan Zahouani

Abstract:

Hair is a non homogenous complex material which can be associated with a polymer. It is made up 95% of Keratin. Hair has a great social significance for human beings. In the High Middle Ages, for example, long hairs have been reserved for kings and nobles. Most common interest in hair is focused on hair growth, hair types and hair care, but hair is also an important biomaterial which can vary depending on ethnic origin or on age, hair colour for example can be a sign of ethnic ancestry or age (dark hair for Asiatic, blond hair for Caucasian and white hair for old people in general). In this context, different approaches have been conducted to determine the differences in mechanical properties and characterize the fracture topography at the surface of hair depending on its type and its age. A tensile testing machine was especially designed to achieve tensile tests on hair. This device is composed of a microdisplacement system and a force sensor whose peak load is limited to 3N. The curves and the values extracted from each experiment, allow us to compare the evolution of the mechanical properties from one hair to another. Observations with a Scanning Electron Microscope (SEM) and with an interferometer were made on different hairs. Thus, it is possible to access the cuticle state and the fracture topography for each category.

Keywords: Hair, relaxation test, SEM, interferometer, mechanical properties.

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2578 Genetic Algorithms for Feature Generation in the Context of Audio Classification

Authors: José A. Menezes, Giordano Cabral, Bruno T. Gomes

Abstract:

Choosing good features is an essential part of machine learning. Recent techniques aim to automate this process. For instance, feature learning intends to learn the transformation of raw data into a useful representation to machine learning tasks. In automatic audio classification tasks, this is interesting since the audio, usually complex information, needs to be transformed into a computationally convenient input to process. Another technique tries to generate features by searching a feature space. Genetic algorithms, for instance, have being used to generate audio features by combining or modifying them. We find this approach particularly interesting and, despite the undeniable advances of feature learning approaches, we wanted to take a step forward in the use of genetic algorithms to find audio features, combining them with more conventional methods, like PCA, and inserting search control mechanisms, such as constraints over a confusion matrix. This work presents the results obtained on particular audio classification problems.

Keywords: Feature generation, feature learning, genetic algorithm, music information retrieval.

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2577 Reducing the Imbalance Penalty through Artificial Intelligence Methods Geothermal Production Forecasting: A Case Study for Turkey

Authors: H. Anıl, G. Kar

Abstract:

In addition to being rich in renewable energy resources, Turkey is one of the countries that promise potential in geothermal energy production with its high installed power, cheapness, and sustainability. Increasing imbalance penalties become an economic burden for organizations, since the geothermal generation plants cannot maintain the balance of supply and demand due to the inadequacy of the production forecasts given in the day-ahead market. A better production forecast reduces the imbalance penalties of market participants and provides a better imbalance in the day ahead market. In this study, using machine learning, deep learning and time series methods, the total generation of the power plants belonging to Zorlu Doğal Electricity Generation, which has a high installed capacity in terms of geothermal, was predicted for the first one-week and first two-weeks of March, then the imbalance penalties were calculated with these estimates and compared with the real values. These modeling operations were carried out on two datasets, the basic dataset and the dataset created by extracting new features from this dataset with the feature engineering method. According to the results, Support Vector Regression from traditional machine learning models outperformed other models and exhibited the best performance. In addition, the estimation results in the feature engineering dataset showed lower error rates than the basic dataset. It has been concluded that the estimated imbalance penalty calculated for the selected organization is lower than the actual imbalance penalty, optimum and profitable accounts.

Keywords: Machine learning, deep learning, time series models, feature engineering, geothermal energy production forecasting.

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2576 Performance Analysis of a Flexible Manufacturing Line Operated Under Surplus-based Production Control

Authors: K. K. Starkov, A. Y. Pogromsky, I. J. B. F. Adan, J. E. Rooda

Abstract:

In this paper we present our results on the performance analysis of a multi-product manufacturing line. We study the influence of external perturbations, intermediate buffer content and the number of manufacturing stages on the production tracking error of each machine in the multi-product line operated under a surplusbased production control policy. Starting by the analysis of a single machine with multiple production stages (one for each product type), we provide bounds on the production error of each stage. Then, we extend our analysis to a line of multi-stage machines, where similarly, bounds on each production tracking error for each product type, as well as buffer content are obtained. Details on performance of the closed-loop flow line model are illustrated in numerical simulations.

Keywords: Flexible manufacturing systems, tracking systems, discrete time systems, production control, boundary conditions.

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2575 On Speeding Up Support Vector Machines: Proximity Graphs Versus Random Sampling for Pre-Selection Condensation

Authors: Xiaohua Liu, Juan F. Beltran, Nishant Mohanchandra, Godfried T. Toussaint

Abstract:

Support vector machines (SVMs) are considered to be the best machine learning algorithms for minimizing the predictive probability of misclassification. However, their drawback is that for large data sets the computation of the optimal decision boundary is a time consuming function of the size of the training set. Hence several methods have been proposed to speed up the SVM algorithm. Here three methods used to speed up the computation of the SVM classifiers are compared experimentally using a musical genre classification problem. The simplest method pre-selects a random sample of the data before the application of the SVM algorithm. Two additional methods use proximity graphs to pre-select data that are near the decision boundary. One uses k-Nearest Neighbor graphs and the other Relative Neighborhood Graphs to accomplish the task.

Keywords: Machine learning, data mining, support vector machines, proximity graphs, relative-neighborhood graphs, k-nearestneighbor graphs, random sampling, training data condensation.

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2574 Tax Innovation, Administration and Revenue Generation in Nigeria: Case of Cross River State

Authors: Ifere, Eugene Okoi, Eko, Eko Omini

Abstract:

Taxation as a potent fiscal policy instrument through which infrastructures and social services that drive the development process of any society has been ineffective in Nigeria. The adoption of appropriate measures is, however, a requirement for the generation of adequate tax revenue. This study set out to investigates efficiency and effectiveness in the administration of tax in Nigeria, using Cross River State as a case-study. The methodology to achieve this objective is a qualitative technique using structured questionnaires to survey the three senatorial districts in the state; the central limit theory is adopted as our analytical technique. Result showed a significant degree of inefficiency in the administration of taxes. It is recommended that periodic review and update of tax policy will bring innovation and effectiveness in the administration of taxes. Also proper appropriation of tax revenue will drive development in needed infrastructural and social services.

Keywords: Administration, Efficiency, Effectiveness, Taxation

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2573 Climate Change in Albania and Its Effect on Cereal Yield

Authors: L. Basha, E. Gjika

Abstract:

This study is focused on analyzing climate change in Albania and its potential effects on cereal yields. Initially, monthly temperature and rainfalls in Albania were studied for the period 1960-2021. Climacteric variables are important variables when trying to model cereal yield behavior, especially when significant changes in weather conditions are observed. For this purpose, in the second part of the study, linear and nonlinear models explaining cereal yield are constructed for the same period, 1960-2021. The multiple linear regression analysis and lasso regression method are applied to the data between cereal yield and each independent variable: average temperature, average rainfall, fertilizer consumption, arable land, land under cereal production, and nitrous oxide emissions. In our regression model, heteroscedasticity is not observed, data follow a normal distribution, and there is a low correlation between factors, so we do not have the problem of multicollinearity. Machine learning methods, such as Random Forest (RF), are used to predict cereal yield responses to climacteric and other variables. RF showed high accuracy compared to the other statistical models in the prediction of cereal yield. We found that changes in average temperature negatively affect cereal yield. The coefficients of fertilizer consumption, arable land, and land under cereal production are positively affecting production. Our results show that the RF method is an effective and versatile machine-learning method for cereal yield prediction compared to the other two methods: multiple linear regression and lasso regression method.

Keywords: Cereal yield, climate change, machine learning, multiple regression model, random forest.

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2572 Numerical Simulation for the Formability Prediction of the Laser Welded Blanks (TWB)

Authors: Hossein Mamusi, Abolfazl Masoumi, Ramezanali Mahdavinezhad

Abstract:

Tailor-welded Blanks (TWBs) are tailor made for different complex component designs by welding multiple metal sheets with different thicknesses, shapes, coatings or strengths prior to forming. In this study the Hemispherical Die Stretching (HDS) test (out-of-plane stretching) of TWBs were simulated via ABAQUS/Explicit to obtain the Forming Limit Diagrams (FLDs) of Stainless steel (AISI 304) laser welded blanks with different thicknesses. Two criteria were used to detect the start of necking to determine the FLD for TWBs and parent sheet metals. These two criteria are the second derivatives of the major and thickness strains that are given from the strain history of simulation. In the other word, in these criteria necking starts when the second derivative of thickness or major strain reaches its maximum. With having the time of onset necking, one can measure the major and minor strains at the critical area and determine the forming limit curve.

Keywords: TWB, Forming Limit Diagram, Necking criteria, ABAQUS/Explicit

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2571 Optimal Linear Quadratic Digital Tracker for the Discrete-Time Proper System with an Unknown Disturbance

Authors: Jason Sheng-Hong Tsai, Faezeh Ebrahimzadeh, Min-Ching Chung, Shu-Mei Guo, Leang-San Shieh, Tzong-Jiy Tsai, Li Wang

Abstract:

In this paper, we first construct a new state and disturbance estimator using discrete-time proportional plus integral observer to estimate the system state and the unknown external disturbance for the discrete-time system with an input-to-output direct-feedthrough term. Then, the generalized optimal linear quadratic digital tracker design is applied to construct a proportional plus integral observer-based tracker for the system with an unknown external disturbance to have a desired tracking performance. Finally, a numerical simulation is given to demonstrate the effectiveness of the new application of our proposed approach.

Keywords: Optimal linear quadratic tracker, proportional plus integral observer, state estimator, disturbance estimator.

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2570 Yield Prediction Using Support Vectors Based Under-Sampling in Semiconductor Process

Authors: Sae-Rom Pak, Seung Hwan Park, Jeong Ho Cho, Daewoong An, Cheong-Sool Park, Jun Seok Kim, Jun-Geol Baek

Abstract:

It is important to predict yield in semiconductor test process in order to increase yield. In this study, yield prediction means finding out defective die, wafer or lot effectively. Semiconductor test process consists of some test steps and each test includes various test items. In other world, test data has a big and complicated characteristic. It also is disproportionably distributed as the number of data belonging to FAIL class is extremely low. For yield prediction, general data mining techniques have a limitation without any data preprocessing due to eigen properties of test data. Therefore, this study proposes an under-sampling method using support vector machine (SVM) to eliminate an imbalanced characteristic. For evaluating a performance, randomly under-sampling method is compared with the proposed method using actual semiconductor test data. As a result, sampling method using SVM is effective in generating robust model for yield prediction.

Keywords: Yield Prediction, Semiconductor Test Process, Support Vector Machine, Under Sampling

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2569 Some Applications of Transition Matrices via Eigen Values

Authors: Adil AL-Rammahi

Abstract:

In this short paper, new properties of transition matrix were introduced. Eigen values for small order transition matrices are calculated in flexible method. For benefit of these properties applications of these properties were studied in the solution of Markov's chain via steady state vector, and information theory via channel entropy. The implemented test examples were promised for usages.

Keywords: Eigen value problem, transition matrix, state vector, information theory.

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2568 Tuning Cubic Equations of State for Supercritical Water Applications

Authors: Shyh-Ming Chern

Abstract:

Cubic equations of state (EoS), popular due to their simple mathematical form, ease of use, semi-theoretical nature and reasonable accuracy, are normally fitted to vapor-liquid equilibrium P-v-T data. As a result, they often show poor accuracy in the region near and above the critical point. In this study, the performance of the renowned Peng-Robinson (PR) and Patel-Teja (PT) EoS’s around the critical area has been examined against the P-v-T data of water. Both of them display large deviations at critical point. For instance, PR-EoS exhibits discrepancies as high as 47% for the specific volume, 28% for the enthalpy departure and 43% for the entropy departure at critical point. It is shown that incorporating P-v-T data of the supercritical region into the retuning of a cubic EoS can improve its performance at and above the critical point dramatically. Adopting a retuned acentric factor of 0.5491 instead of its genuine value of 0.344 for water in PR-EoS and a new F of 0.8854 instead of its original value of 0.6898 for water in PT-EoS reduces the discrepancies to about one third or less.

Keywords: Equation of state, EoS, supercritical water, SCW.

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2567 Phase Transformation Temperatures for Shape Memory Alloy Wire

Authors: Tan Wee Choon, Abdul Saad Salleh, Saifulnizan Jamian, Mohd. Imran Ghazali

Abstract:

Phase transformation temperature is one of the most important parameters for the shape memory alloys (SMAs). The most popular method to determine these phase transformation temperatures is the Differential Scanning Calorimeter (DSC), but due to the limitation of the DSC testing itself, it made it difficult for the finished product which is not in the powder form. A novel method which uses the Universal Testing Machine has been conducted to determine the phase transformation temperatures. The Flexinol wire was applied with force and maintained throughout the experiment and at the same time it was heated up slowly until a temperature of approximately 1000C with direct current. The direct current was then slowly decreased to cool down the temperature of the Flexinol wire. All the phase transformation temperatures for Flexinol wire were obtained. The austenite start at 52.540C and austenite finish at 60.900C, while martensite start at 44.780C and martensite finish at 32.840C.

Keywords: Phase transformation temperature, Robotic, Shapememory alloy, Universal Testing Machine.

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2566 TTCN-3 Based Conformance Testing of a Node Monitoring Protocol for MANETs

Authors: Mallikarjun B. Channappagoudar, Pallapa Venkataram

Abstract:

As a node monitoring protocol, which is a part of network management, operates in distributed manner, conformance testing of such protocols is more tedious than testing a peer-to-peer protocol. Various works carried out to give the methodology to do conformance testing of distributed protocol. In this paper, we have presented a formal approach for conformance testing of a Node Monitoring Protocol, which uses both static and mobile agents, for MANETs. First, we use SDL to obtain MSCs, which represent the scenario descriptions by sequence diagrams, which in turn generate test sequences and test cases. Later, Testing and Test Control Notation Version-3 (TTCN-3) is used to execute test cases with respect to generated test sequences to know the conformance of protocol against the given specification. This approach shows, the effective conformance testing of the distributed protocols for the network with varying node density and complex behavior. Experimental results for the protocol scenario represent the effectiveness of the method used.

Keywords: Conformance Testing, FSM, Mobile agent, TTCN, Test sequence.

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2565 Adsorption of H2 and CO on Iron-based Catalysts for Fischer-Tropsch Synthesis

Authors: Weixin Qian, Haitao Zhang, Hongfang Ma, Yongdi Liu, Weiyong Ying, Dingye Fang

Abstract:

The adsorption properties of CO and H2 on iron-based catalyst with addition of Zr and Ni were investigated using temperature programmed desorption process. It was found that on the carburized iron-based catalysts, molecular state and dissociative state CO existed together. The addition of Zr was preferential for the molecular state adsorption of CO on iron-based catalyst and the presence of Ni was beneficial to the dissociative adsorption of CO. On H2 reduced catalysts, hydrogen mainly adsorbs on the surface iron sites and surface oxide sites. On CO reduced catalysts, hydrogen probably existed as the most stable CH and OH species. The addition of Zr was not benefit to the dissociative adsorption of hydrogen on iron-based catalyst and the presence of Ni was preferential for the dissociative adsorption of hydrogen.

Keywords: adsorption, Fischer-Tropsch synthesis, iron-based catalysts

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2564 Control of Thermal Flow in Machine Tools Using Shape Memory Alloys

Authors: Reimund Neugebauer, Welf-Guntram Drossel, Andre Bucht, Christoph Ohsenbrügge

Abstract:

In this paper the authors propose and verify an approach to control heat flow in machine tool components. Thermal deformations are a main aspect that affects the accuracy of machining. Due to goals of energy efficiency, thermal basic loads should be reduced. This leads to inhomogeneous and time variant temperature profiles. To counteract these negative consequences, material with high melting enthalpy is used as a method for thermal stabilization. The increased thermal capacity slows down the transient thermal behavior. To account for the delayed thermal equilibrium, a control mechanism for thermal flow is introduced. By varying a gap in a heat flow path the thermal resistance of an assembly can be controlled. This mechanism is evaluated in two experimental setups. First to validate the ability to control the thermal resistance and second to prove the possibility of a self-sufficient option based on the selfsensing abilities of thermal shape memory alloys.

Keywords: energy-efficiency, heat transfer path, MT thermal stability, thermal shape memory alloy

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2563 Synthetic Aperture Radar Remote Sensing Classification Using the Bag of Visual Words Model to Land Cover Studies

Authors: Reza Mohammadi, Mahmod R. Sahebi, Mehrnoosh Omati, Milad Vahidi

Abstract:

Classification of high resolution polarimetric Synthetic Aperture Radar (PolSAR) images plays an important role in land cover and land use management. Recently, classification algorithms based on Bag of Visual Words (BOVW) model have attracted significant interest among scholars and researchers in and out of the field of remote sensing. In this paper, BOVW model with pixel based low-level features has been implemented to classify a subset of San Francisco bay PolSAR image, acquired by RADARSAR 2 in C-band. We have used segment-based decision-making strategy and compared the result with the result of traditional Support Vector Machine (SVM) classifier. 90.95% overall accuracy of the classification with the proposed algorithm has shown that the proposed algorithm is comparable with the state-of-the-art methods. In addition to increase in the classification accuracy, the proposed method has decreased undesirable speckle effect of SAR images.

Keywords: Bag of Visual Words, classification, feature extraction, land cover management, Polarimetric Synthetic Aperture Radar.

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2562 Virtual Learning Process Environment: Cohort Analytics for Learning and Learning Processes

Authors: Ayodeji Adesina, Derek Molloy

Abstract:

Traditional higher-education classrooms allow lecturers to observe students- behaviours and responses to a particular pedagogy during learning in a way that can influence changes to the pedagogical approach. Within current e-learning systems it is difficult to perform continuous analysis of the cohort-s behavioural tendency, making real-time pedagogical decisions difficult. This paper presents a Virtual Learning Process Environment (VLPE) based on the Business Process Management (BPM) conceptual framework. Within the VLPE, course designers can model various education pedagogies in the form of learning process workflows using an intuitive flow diagram interface. These diagrams are used to visually track the learning progresses of a cohort of students. This helps assess the effectiveness of the chosen pedagogy, providing the information required to improve course design. A case scenario of a cohort of students is presented and quantitative statistical analysis of their learning process performance is gathered and displayed in realtime using dashboards.

Keywords: Business process management, cohort analytics, learning processes, virtual learning environment.

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