Search results for: Single Machine Infinite Bus (SMIB)
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2832

Search results for: Single Machine Infinite Bus (SMIB)

2712 A Serializability Condition for Multi-step Transactions Accessing Ordered Data

Authors: Rafat Alshorman, Walter Hussak

Abstract:

In mobile environments, unspecified numbers of transactions arrive in continuous streams. To prove correctness of their concurrent execution a method of modelling an infinite number of transactions is needed. Standard database techniques model fixed finite schedules of transactions. Lately, techniques based on temporal logic have been proposed as suitable for modelling infinite schedules. The drawback of these techniques is that proving the basic serializability correctness condition is impractical, as encoding (the absence of) conflict cyclicity within large sets of transactions results in prohibitively large temporal logic formulae. In this paper, we show that, under certain common assumptions on the graph structure of data items accessed by the transactions, conflict cyclicity need only be checked within all possible pairs of transactions. This results in formulae of considerably reduced size in any temporal-logic-based approach to proving serializability, and scales to arbitrary numbers of transactions.

Keywords: multi-step transactions, serializability, directed graph.

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2711 Normal and Peaberry Coffee Beans Classification from Green Coffee Bean Images Using Convolutional Neural Networks and Support Vector Machine

Authors: Hira Lal Gope, Hidekazu Fukai

Abstract:

The aim of this study is to develop a system which can identify and sort peaberries automatically at low cost for coffee producers in developing countries. In this paper, the focus is on the classification of peaberries and normal coffee beans using image processing and machine learning techniques. The peaberry is not bad and not a normal bean. The peaberry is born in an only single seed, relatively round seed from a coffee cherry instead of the usual flat-sided pair of beans. It has another value and flavor. To make the taste of the coffee better, it is necessary to separate the peaberry and normal bean before green coffee beans roasting. Otherwise, the taste of total beans will be mixed, and it will be bad. In roaster procedure time, all the beans shape, size, and weight must be unique; otherwise, the larger bean will take more time for roasting inside. The peaberry has a different size and different shape even though they have the same weight as normal beans. The peaberry roasts slower than other normal beans. Therefore, neither technique provides a good option to select the peaberries. Defect beans, e.g., sour, broken, black, and fade bean, are easy to check and pick up manually by hand. On the other hand, the peaberry pick up is very difficult even for trained specialists because the shape and color of the peaberry are similar to normal beans. In this study, we use image processing and machine learning techniques to discriminate the normal and peaberry bean as a part of the sorting system. As the first step, we applied Deep Convolutional Neural Networks (CNN) and Support Vector Machine (SVM) as machine learning techniques to discriminate the peaberry and normal bean. As a result, better performance was obtained with CNN than with SVM for the discrimination of the peaberry. The trained artificial neural network with high performance CPU and GPU in this work will be simply installed into the inexpensive and low in calculation Raspberry Pi system. We assume that this system will be used in under developed countries. The study evaluates and compares the feasibility of the methods in terms of accuracy of classification and processing speed.

Keywords: Convolutional neural networks, coffee bean, peaberry, sorting, support vector machine.

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2710 Development of a Robot Assisted Centrifugal Casting Machine for Manufacturing Multi-Layer Journal Bearing and High-Tech Machine Components

Authors: Mohammad Syed Ali Molla, Mohammed Azim, Mohammad Esharuzzaman

Abstract:

Centrifugal-casting machine is used in manufacturing special machine components like multi-layer journal bearing used in all internal combustion engine, steam, gas turbine and air craft turboengine where isotropic properties and high precisions are desired. Moreover, this machine can be used in manufacturing thin wall hightech machine components like cylinder liners and piston rings of IC engine and other machine parts like sleeves, and bushes. Heavy-duty machine component like railway wheel can also be prepared by centrifugal casting. A lot of technological developments are required in casting process for production of good casted machine body and machine parts. Usually defects like blowholes, surface roughness, chilled surface etc. are found in sand casted machine parts. But these can be removed by centrifugal casting machine using rotating metallic die. Moreover, die rotation, its temperature control, and good pouring practice can contribute to the quality of casting because of the fact that the soundness of a casting in large part depends upon how the metal enters into the mold or dies and solidifies. Poor pouring practice leads to variety of casting defects such as temperature loss, low quality casting, excessive turbulence, over pouring etc. Besides these, handling of molten metal is very unsecured and dangerous for the workers. In order to get rid of all these problems, the need of an automatic pouring device arises. In this research work, a robot assisted pouring device and a centrifugal casting machine are designed, developed constructed and tested experimentally which are found to work satisfactorily. The robot assisted pouring device is further modified and developed for using it in actual metal casting process. Lot of settings and tests are required to control the system and ultimately it can be used in automation of centrifugal casting machine to produce high-tech machine parts with desired precision.

Keywords: Casting, cylinder liners, journal bearing, robot.

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2709 Spanning Tree Transformation of Connected Graphs into Single-Row Networks

Authors: S.L. Loh, S. Salleh, N.H. Sarmin

Abstract:

A spanning tree of a connected graph is a tree which consists the set of vertices and some or perhaps all of the edges from the connected graph. In this paper, a model for spanning tree transformation of connected graphs into single-row networks, namely Spanning Tree of Connected Graph Modeling (STCGM) will be introduced. Path-Growing Tree-Forming algorithm applied with Vertex-Prioritized is contained in the model to produce the spanning tree from the connected graph. Paths are produced by Path-Growing and they are combined into a spanning tree by Tree-Forming. The spanning tree that is produced from the connected graph is then transformed into single-row network using Tree Sequence Modeling (TSM). Finally, the single-row routing problem is solved using a method called Enhanced Simulated Annealing for Single-Row Routing (ESSR).

Keywords: Graph theory, simulated annealing, single-rowrouting and spanning tree.

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2708 Estimation of Synchronous Machine Synchronizing and Damping Torque Coefficients

Authors: Khaled M. EL-Naggar

Abstract:

Synchronizing and damping torque coefficients of a synchronous machine can give a quite clear picture for machine behavior during transients. These coefficients are used as a power system transient stability measurement. In this paper, a crow search optimization algorithm is presented and implemented to study the power system stability during transients. The algorithm makes use of the machine responses to perform the stability study in time domain. The problem is formulated as a dynamic estimation problem. An objective function that minimizes the error square in the estimated coefficients is designed. The method is tested using practical system with different study cases. Results are reported and a thorough discussion is presented. The study illustrates that the proposed method can estimate the stability coefficients for the critical stable cases where other methods may fail. The tests proved that the proposed tool is an accurate and reliable tool for estimating the machine coefficients for assessment of power system stability.

Keywords: Optimization, estimation, synchronous, machine, crow search.

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2707 Low Cost Microcontroller Based ECG Machine

Authors: Muhibul H. Bhuyan, Md. T. Hasan, Hasan Iskander

Abstract:

Electrocardiographic (ECG) machine is an important equipment to diagnose heart problems. Besides, the ECG signals are used to detect many other features of human body and behavior. But it is not so cheap and simple in operation to be used in the countries like Bangladesh, where most of the people are very low income earners. Therefore, in this paper, we have tried to implement a simple and portable ECG machine. Since Arduino Uno microcontroller is very cheap, we have used it in our system to minimize the cost. Our designed system is powered by a 2-voltage level DC power supply. It provides wireless connectivity to have ECG data either in smartphone having android operating system or a PC/laptop having Windows operating system. To get the data, a graphic user interface has been designed. Android application has also been made using IDE for Android 2.3 and API 10. Since it requires no USB host API, almost 98% Android smartphones, available in the country, will be able to use it. We have calculated the heart rate from the measured ECG by our designed machine and by an ECG machine of a reputed diagnostic center in Dhaka city for the same people at the same time on same day. Then we calculated the percentage of errors between the readings of two machines and computed its average. From this computation, we have found out that the average percentage of error is within an acceptable limit.

Keywords: Low cost ECG machine, heart diseases, remote monitoring, Arduino microcontroller.

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2706 Introductory Design Optimisation of a Machine Tool using a Virtual Machine Concept

Authors: Johan Wall, Johan Fredin, Anders Jönsson, Göran Broman

Abstract:

Designing modern machine tools is a complex task. A simulation tool to aid the design work, a virtual machine, has therefore been developed in earlier work. The virtual machine considers the interaction between the mechanics of the machine (including structural flexibility) and the control system. This paper exemplifies the usefulness of the virtual machine as a tool for product development. An optimisation study is conducted aiming at improving the existing design of a machine tool regarding weight and manufacturing accuracy at maintained manufacturing speed. The problem can be categorised as constrained multidisciplinary multiobjective multivariable optimisation. Parameters of the control and geometric quantities of the machine are used as design variables. This results in a mix of continuous and discrete variables and an optimisation approach using a genetic algorithm is therefore deployed. The accuracy objective is evaluated according to international standards. The complete systems model shows nondeterministic behaviour. A strategy to handle this based on statistical analysis is suggested. The weight of the main moving parts is reduced by more than 30 per cent and the manufacturing accuracy is improvement by more than 60 per cent compared to the original design, with no reduction in manufacturing speed. It is also shown that interaction effects exist between the mechanics and the control, i.e. this improvement would most likely not been possible with a conventional sequential design approach within the same time, cost and general resource frame. This indicates the potential of the virtual machine concept for contributing to improved efficiency of both complex products and the development process for such products. Companies incorporating such advanced simulation tools in their product development could thus improve its own competitiveness as well as contribute to improved resource efficiency of society at large.

Keywords: Machine tools, Mechatronics, Non-deterministic, Optimisation, Product development, Virtual machine

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2705 Adjustment and Compensation Techniques for the Rotary Axes of Five-axis CNC Machine Tools

Authors: Tung-Hui Hsu, Wen-Yuh Jywe

Abstract:

Five-axis computer numerical control (CNC) machine tools (three linear and two rotary axes) are ideally suited to the fabrication of complex work pieces, such as dies, turbo blades, and cams. The locations of the axis average line and centerline of the rotary axes strongly influence the performance of these machines; however, techniques to compensate for eccentric error in the rotary axes remain weak. This paper proposes optical (Non-Bar) techniques capable of calibrating five-axis CNC machine tools and compensating for eccentric error in the rotary axes. This approach employs the measurement path in ISO/CD 10791-6 to determine the eccentric error in two rotary axes, for which compensatory measures can be implemented. Experimental results demonstrate that the proposed techniques can improve the performance of various five-axis CNC machine tools by more than 90%. Finally, a result of the cutting test using a B-type five-axis CNC machine tool confirmed to the usefulness of this proposed compensation technique.

Keywords: Calibration, compensation, rotary axis, five-axis computer numerical control (CNC) machine tools, eccentric error, optical calibration system, ISO/CD 10791-6

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2704 Estimating the Absorption of Volatile Organic Compounds in Four Biodiesels Using the UNIFAC Procedure

Authors: Corina M Mateescu, Edison Muzenda, Mohamed Belaid, Saka Abdulkareem, Ayo S Afolabi

Abstract:

This work considered the thermodynamic feasibility of scrubbing volatile organic compounds into biodiesel in view of designing a gas treatment process with this absorbent. A detailed vapour – liquid equilibrium investigation was performed using the original UNIFAC group contribution method. The four biodiesels studied in this work are methyl oleate, methyl palmitate, methyl linolenate and ethyl stearate. The original UNIFAC procedure was used to estimate the infinite dilution activity coefficients of 13 selected volatile organic compounds in the biodiesels. The calculations were done at the VOC mole fraction of 9.213x10-8. Ethyl stearate gave the most favourable phase equilibrium. A close agreement was found between the infinite dilution activity coefficient of toluene found in this work and those reported in literature. Thermodynamic models can efficiently be used to calculate vast amount of phase equilibrium behaviour using limited number of experimental data.

Keywords: Biodiesel, Equilibrium, Gas treatment, Infinitedilution, Thermodynamic

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2703 Boosting Method for Automated Feature Space Discovery in Supervised Quantum Machine Learning Models

Authors: Vladimir Rastunkov, Jae-Eun Park, Abhijit Mitra, Brian Quanz, Steve Wood, Christopher Codella, Heather Higgins, Joseph Broz

Abstract:

Quantum Support Vector Machines (QSVM) have become an important tool in research and applications of quantum kernel methods. In this work we propose a boosting approach for building ensembles of QSVM models and assess performance improvement across multiple datasets. This approach is derived from the best ensemble building practices that worked well in traditional machine learning and thus should push the limits of quantum model performance even further. We find that in some cases, a single QSVM model with tuned hyperparameters is sufficient to simulate the data, while in others - an ensemble of QSVMs that are forced to do exploration of the feature space via proposed method is beneficial.

Keywords: QSVM, Quantum Support Vector Machines, quantum kernel, boosting, ensemble.

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2702 Prediction of the Dynamic Characteristics of a Milling Machine Using the Integrated Model of Machine Frame and Spindle Unit

Authors: Jui P. Hung, Yuan L. Lai, Tzuo L. Luo, Hsi H. Hsiao

Abstract:

The machining performance is determined by the frequency characteristics of the machine-tool structure and the dynamics of the cutting process. Therefore, the prediction of dynamic vibration behavior of spindle tool system is of great importance for the design of a machine tool capable of high-precision and high-speed machining. The aim of this study is to develop a finite element model to predict the dynamic characteristics of milling machine tool and hence evaluate the influence of the preload of the spindle bearings. To this purpose, a three dimensional spindle bearing model of a high speed engraving spindle tool was created. In this model, the rolling interfaces with contact stiffness defined by Harris model were used to simulate the spindle bearing components. Then a full finite element model of a vertical milling machine was established by coupling the spindle tool unit with the machine frame structure. Using this model, the vibration mode that had a dominant influence on the dynamic stiffness was determined. The results of the finite element simulations reveal that spindle bearing with different preloads greatly affect the dynamic behavior of the spindle tool unit and hence the dynamic responses of the vertical column milling system. These results were validated by performing vibration on the individual spindle tool unit and the milling machine prototype, respectively. We conclude that preload of the spindle bearings is an important component affecting the dynamic characteristics and machining performance of the entire vertical column structure of the milling machine.

Keywords: Dynamic compliance, Milling machine, Spindle unit, Bearing preload.

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2701 Using Single Decision Tree to Assess the Impact of Cutting Conditions on Vibration

Authors: S. Ghorbani, N. I. Polushin

Abstract:

Vibration during machining process is crucial since it affects cutting tool, machine, and workpiece leading to a tool wear, tool breakage, and an unacceptable surface roughness. This paper applies a nonparametric statistical method, single decision tree (SDT), to identify factors affecting on vibration in machining process. Workpiece material (AISI 1045 Steel, AA2024 Aluminum alloy, A48-class30 Gray Cast Iron), cutting tool (conventional, cutting tool with holes in toolholder, cutting tool filled up with epoxy-granite), tool overhang (41-65 mm), spindle speed (630-1000 rpm), feed rate (0.05-0.075 mm/rev) and depth of cut (0.05-0.15 mm) were used as input variables, while vibration was the output parameter. It is concluded that workpiece material is the most important parameters for natural frequency followed by cutting tool and overhang.

Keywords: Cutting condition, vibration, natural frequency, decision tree, CART algorithm.

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2700 Design and Construction of the Semi-Automatic Sliced Ginger Machine

Authors: J. Chatthong, W. Boonchouytan, R. Burapa

Abstract:

The purpose of study was to design and construction the semi-automatic sliced ginger machine for reduce production times in sheet and slice ginger procedure furthermore, reduced amount of labor of slides and cutting method. Take consider into clean and safety of workers and consumers. The principle of machines, used 1 horsepower motor, rotation speed of sliced blade 967 rpm, the diameter of sliced dish 310 mm, consists of 2 blades for sheet cutting ginger and the power from motor which transfer to rotate the sliced blade roller, rotation speed 440 rpm. The slice cutter roller was sliced ginger from sheet ginger to line ginger. The conveyer could adjustment level of motors, used to the beginning area that sheet ginger was transference to the roller for sheet and sliced cutting in next process. The cover of sliced cutting had channel for 1 tuber of ginger. The semi-automatic sliced ginger machine could produced sheet ginger 81.8 kg/h (6.2 times of labor) and line ginger 17.9 kg/h (2.5 times of labor) compare with, labor work could produced sheet ginger 13.2 kg/h and line ginger 7.1 kg/h, and when timekeeper, the total times of semi auto machine 30.86 kg/h and labor 4.6 kg/h, there for the semi auto machine was 6.7 times of labor. The semiautomatic sliced ginger machine convenient, easy for use and maintain, in addition to reduce fatigue of body and seriousness from works; must be used high skill, and protection accident in slicing procedure. Beside, machine could used with other vegetables for example potato, carrot .etc

Keywords: Sliced Machine, Sliced Ginger, Line Ginger

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2699 Effect of the Machine Frame Structures on the Frequency Responses of Spindle Tool

Authors: Yuan L. Lai, Yong R. Chen, Jui P. Hung, Tzuo L. Luo, Hsi H. Hsiao

Abstract:

Chatter vibration has been a troublesome problem for a machine tool toward the high precision and high speed machining. Essentially, the machining performance is determined by the dynamic characteristics of the machine tool structure and dynamics of cutting process. Therefore the dynamic vibration behavior of spindle tool system greatly determines the performance of machine tool. The purpose of this study is to investigate the influences of the machine frame structure on the dynamic frequency of spindle tool unit through finite element modeling approach. To this end, a realistic finite element model of the vertical milling system was created by incorporated the spindle-bearing model into the spindle head stock of the machine frame. Using this model, the dynamic characteristics of the milling machines with different structural designs of spindle head stock and identical spindle tool unit were demonstrated. The results of the finite element modeling reveal that the spindle tool unit behaves more compliant when the excited frequency approaches the natural mode of the spindle tool; while the spindle tool show a higher dynamic stiffness at lower frequency that may be initiated by the structural mode of milling head. Under this condition, it is concluded that the structural configuration of spindle head stock associated with the vertical column of milling machine plays an important role in determining the machining dynamics of the spindle unit.

Keywords: Machine tools, Compliance, Frequency response function, Machine frame structure, Spindle unit

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2698 CompleX-Machine: An Automated Testing Tool Using X-Machine Theory

Authors: E. K. A. Ogunshile

Abstract:

This paper is aimed at creating an Automatic Java X-Machine testing tool for software development. The nature of software development is changing; thus, the type of software testing tools required is also changing. Software is growing increasingly complex and, in part due to commercial impetus for faster software releases with new features and value, increasingly in danger of containing faults. These faults can incur huge cost for software development organisations and users; Cambridge Judge Business School’s research estimated the cost of software bugs to the global economy is $312 billion. Beyond the cost, faster software development methodologies and increasing expectations on developers to become testers is driving demand for faster, automated, and effective tools to prevent potential faults as early as possible in the software development lifecycle. Using X-Machine theory, this paper will explore a new tool to address software complexity, changing expectations on developers, faster development pressures and methodologies, with a view to reducing the huge cost of fixing software bugs.

Keywords: Conformance testing, finite state machine, software testing, X-Machine.

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2697 Influence of an External Magnetic Field on the Acoustomagnetoelectric Field in a Rectangular Quantum Wire with an Infinite Potential by Using a Quantum Kinetic Equation

Authors: N. Q. Bau, N. V. Nghia

Abstract:

The acoustomagnetoelectric (AME) field in a rectangular quantum wire with an infinite potential (RQWIP) is calculated in the presence of an external magnetic field (EMF) by using the quantum kinetic equation for the distribution function of electrons system interacting with external phonons and electrons scattering with internal acoustic phonon in a RQWIP. We obtained ananalytic expression for the AME field in the RQWIP in the presence of the EMF. The dependence of AME field on the frequency of external acoustic wave, the temperature T of system, the cyclotron frequency of the EMF and the intensity of the EMF is obtained. Theoretical results for the AME field are numerically evaluated, plotted and discussed for a specific RQWIP GaAs/GaAsAl. This result has shown that the dependence of the AME field on intensity of the EMF is nonlinearly and it is many distinct maxima in the quantized magnetic region. We also compared received fields with those for normal bulk semiconductors, quantum well and quantum wire to show the difference. The influence of an EMF on AME field in a RQWIP is newly developed.

Keywords: Rectangular quantum wire, acoustomagnetoelectric field, electron-phonon interaction, kinetic equation method.

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2696 A Software of Intrusion Detection Mechanism for Virtual Platforms

Authors: Ying-Chuan Chen, Shuen-Tai Wang

Abstract:

Security is an interesting and significance issue for popular virtual platforms, such as virtualization cluster and cloud platforms. Virtualization is the powerful technology for cloud computing services, there are a lot of benefits by using virtual machine tools which be called hypervisors, such as it can quickly deploy all kinds of virtual Operating Systems in single platform, able to control all virtual system resources effectively, cost down for system platform deployment, ability of customization, high elasticity and high reliability. However, some important security problems need to take care and resolved in virtual platforms that include terrible viruses, evil programs, illegal operations and intrusion behavior. In this paper, we present useful Intrusion Detection Mechanism (IDM) software that not only can auto to analyze all system-s operations with the accounting journal database, but also is able to monitor the system-s state for virtual platforms.

Keywords: security, cluster, cloud, virtualization, virtual machine, virus, intrusion detection

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2695 Design of Reconfigurable Parasitic Antenna for Single RF Chain MIMO Systems

Authors: C. Arunachalaperumal, B. Chandru, J. M. Mathana

Abstract:

In recent years parasitic antenna play major role in MIMO systems because of their gain and spectral efficiency. In this paper, single RF chain MIMO transmitter is designed using reconfigurable parasitic antenna. The Spatial Modulation (SM) is a recently proposed scheme in MIMO scenario which activates only one antenna at a time. The SM entirely avoids ICI and IAS, and only requires a single RF chain at the transmitter. This would switch ON a single transmit-antenna for data transmission while all the other antennas are kept silent. The purpose of the parasitic elements is to change the radiation pattern of the radio waves which is emitted from the driven element and directing them in one direction and hence introduces transmit diversity. Diode is connect between the patch and ground by changing its state (ON and OFF) the parasitic element act as reflector and director and also capable of steering azimuth and elevation angle. This can be achieved by changing the input impedance of each parasitic element through single RF chain. The switching of diode would select the single parasitic antenna for spatial modulation. This antenna is expected to achieve maximum gain with desired efficiency.

Keywords: MIMO system, single RF chain, Parasitic Antenna.

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2694 Field Programmable Gate Array Based Infinite Impulse Response Filter Using Multipliers

Authors: Rajesh Mehra, Bharti Thakur

Abstract:

In this paper, an Infinite Impulse Response (IIR) filter has been designed and simulated on an Field Programmable Gate Arrays (FPGA). The implementation is based on Multiply Add and Accumulate (MAC) algorithm which uses multiply operations for design implementation. Parallel Pipelined structure is used to implement the proposed IIR Filter taking optimal advantage of the look up table of target device. The designed filter has been synthesized on Digital Signal Processor (DSP) slice based FPGA to perform multiplier function of MAC unit. The DSP slices are useful to enhance the speed performance. The proposed design is simulated with Matlab, synthesized with Xilinx Synthesis Tool, and implemented on FPGA devices. The Virtex 5 FPGA based design can operate at an estimated frequency of 81.5 MHz as compared to 40.5 MHz in case of Spartan 3 ADSP based design. The Virtex 5 based implementation also consumes less slices and slice flip flops of target FPGA in comparison to Spartan 3 ADSP based implementation to provide cost effective solution for signal processing applications.

Keywords: Butterworth, DSP, IIR, MAC, FPGA.

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2693 Temperature Control of Industrial Water Cooler using Hot-gas Bypass

Authors: Jung-in Yoon, Seung-taek Oh, Seung-moon Baek, Jun-hyuk Choi, Jong-yeong Byun, Seok-kwon Jeong, Choon-guen Moon

Abstract:

In this study, we experiment on precise control outlet temperature of water from the water cooler with hot-gas bypass method based on PI control logic for machine tool. Recently, technical trend for machine tools is focused on enhancement of speed and accuracy. High speedy processing causes thermal and structural deformation of objects from the machine tools. Water cooler has to be applied to machine tools to reduce the thermal negative influence with accurate temperature controlling system. The goal of this study is to minimize temperature error in steady state. In addition, control period of an electronic expansion valve were considered to increment of lifetime of the machine tools and quality of product with a water cooler.

Keywords: Hot-gas bypass, Water cooler, PI control, Electronic Expansion Valve, Gain tuning

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2692 Designing Ontology-Based Knowledge Integration for Preprocessing of Medical Data in Enhancing a Machine Learning System for Coding Assignment of a Multi-Label Medical Text

Authors: Phanu Waraporn

Abstract:

This paper discusses the designing of knowledge integration of clinical information extracted from distributed medical ontologies in order to ameliorate a machine learning-based multilabel coding assignment system. The proposed approach is implemented using a decision tree technique of the machine learning on the university hospital data for patients with Coronary Heart Disease (CHD). The preliminary results obtained show a satisfactory finding that the use of medical ontologies improves the overall system performance.

Keywords: Medical Ontology, Knowledge Integration, Machine Learning, Medical Coding, Text Assignment.

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2691 A Comparison of Single of Decision Tree, Decision Tree Forest and Group Method of Data Handling to Evaluate the Surface Roughness in Machining Process

Authors: S. Ghorbani, N. I. Polushin

Abstract:

The machinability of workpieces (AISI 1045 Steel, AA2024 aluminum alloy, A48-class30 gray cast iron) in turning operation has been carried out using different types of cutting tool (conventional, cutting tool with holes in toolholder and cutting tool filled up with composite material) under dry conditions on a turning machine at different stages of spindle speed (630-1000 rpm), feed rate (0.05-0.075 mm/rev), depth of cut (0.05-0.15 mm) and tool overhang (41-65 mm). Experimentation was performed as per Taguchi’s orthogonal array. To evaluate the relative importance of factors affecting surface roughness the single decision tree (SDT), Decision tree forest (DTF) and Group method of data handling (GMDH) were applied.

Keywords: Decision Tree Forest, GMDH, surface roughness, taguchi method, turning process.

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2690 Accurate Fault Classification and Section Identification Scheme in TCSC Compensated Transmission Line using SVM

Authors: Pushkar Tripathi, Abhishek Sharma, G. N. Pillai, Indira Gupta

Abstract:

This paper presents a new approach for the protection of Thyristor-Controlled Series Compensator (TCSC) line using Support Vector Machine (SVM). One SVM is trained for fault classification and another for section identification. This method use three phase current measurement that results in better speed and accuracy than other SVM based methods which used single phase current measurement. This makes it suitable for real-time protection. The method was tested on 10,000 data instances with a very wide variation in system conditions such as compensation level, source impedance, location of fault, fault inception angle, load angle at source bus and fault resistance. The proposed method requires only local current measurement.

Keywords: Fault Classification, Section Identification, Feature Selection, Support Vector Machine (SVM), Thyristor-Controlled Series Compensator (TCSC)

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2689 Analysis of Advanced Modulation Format Using Gain and Loss Spectrum for Long Range Radio over Fiber System

Authors: Shaina Nagpal, Amit Gupta

Abstract:

In this work, all optical Stimulated Brillouin Scattering (SBS) generated single sideband with suppressed carrier is presented to provide better efficiency. The generation of single sideband and enhanced carrier power signal using the SBS technique is further used to strengthen the low shifted sideband and to suppress the upshifted sideband. These generated single sideband signals are able to work at high frequency ranges. Also, generated single sideband is validated over 90 km transmission using single mode fiber with acceptable bit error rate. The results for an equivalent are then compared so that the acceptable technique is chosen and also the required quality for the optimum performance of the system is reported.

Keywords: Stimulated Brillouin scattering, radio over fiber, upper side band, quality factor.

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2688 Design and Simulation of Low Speed Axial Flux Permanent Magnet (AFPM) Machine

Authors: Ahmad Darabi, Hassan Moradi, Hossein Azarinfar

Abstract:

In this paper presented initial design of Low Speed Axial Flux Permanent Magnet (AFPM) Machine with Non-Slotted TORUS topology type by use of certain algorithm (Appendix). Validation of design algorithm studied by means of selected data of an initial prototype machine. Analytically design calculation carried out by means of design algorithm and obtained results compared with results of Finite Element Method (FEM).

Keywords: Axial Flux Permanent Magnet (AFPM) Machine, Design Algorithm, Finite Element Method (FEM), TORUS

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2687 Atmospheric Plasma Innovative Roll-to-Roll Machine for Continuous Materials

Authors: I. Kulyk, M. Stefan

Abstract:

Atmospheric plasma is emerging as a promising technology for many industrial sectors, because of its ecological and economic advantages respect to the traditional production processes. For textile industry, atmospheric plasma is becoming a valid alternative to the conventional wet processes, but the plasma machines realized so far do not allow the treatment of fibrous mechanically weak material. Novel atmospheric plasma machine for industrial applications, developed by VenetoNanotech SCpA in collaboration with Italian producer of corona equipment ME.RO SpA is presented. The main feature of this pre-industrial scale machine is the possibility of the inline plasma treatment of delicate fibrous substrates such as fibre sleeves, for example wool tops, cotton fibres, polymeric tows, mineral fibers and so on, avoiding burnings and disruption of the faint materials.

Keywords: Atmospheric plasma, industrial machine, fibrous materials.

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2686 Optimal Current Control of Externally Excited Synchronous Machines in Automotive Traction Drive Applications

Authors: Oliver Haala, Bernhard Wagner, Maximilian Hofmann, Martin Marz

Abstract:

The excellent suitability of the externally excited synchronous machine (EESM) in automotive traction drive applications is justified by its high efficiency over the whole operation range and the high availability of materials. Usually, maximum efficiency is obtained by modelling each single loss and minimizing the sum of all losses. As a result, the quality of the optimization highly depends on the precision of the model. Moreover, it requires accurate knowledge of the saturation dependent machine inductances. Therefore, the present contribution proposes a method to minimize the overall losses of a salient pole EESM and its inverter in steady state operation based on measurement data only. Since this method does not require any manufacturer data, it is well suited for an automated measurement data evaluation and inverter parametrization. The field oriented control (FOC) of an EESM provides three current components resp. three degrees of freedom (DOF). An analytic minimization of the copper losses in the stator and the rotor (assuming constant inductances) is performed and serves as a first approximation of how to choose the optimal current reference values. After a numeric offline minimization of the overall losses based on measurement data the results are compared to a control strategy that satisfies cos (ϕ) = 1.

Keywords: Current control, efficiency, externally excited synchronous machine, optimization.

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2685 Romanian Single-parent Families: Quality of Life

Authors: Bertha Sânduleasa, Aniela Matei, Mihaela Ghenţa, Nicolina Racoceanu

Abstract:

The increasing divorce and fertility rates outside of marriage, the changing values in the last decades have led to a high prevalence of single parent families. Currently, worldwide, singleparent families represent about a quarter of all families. Recent changes occurring in the structure of single-parent families and also the multitude of factors that influence the quality of life of these families require the development of new research tools in order to provide foundations for social policies addressed to this type of family. The purpose of this paper is to present an analysis concerning the quality of life for single parent families in Romania, based on data collected through a research methodology developed by the authors within a scientific research project funded by a national grant called Partnerships in priority areas.

Keywords: Family policies, quality of life, single-parent families, work-life balance.

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2684 Using Machine Learning Techniques for Autism Spectrum Disorder Analysis and Detection in Children

Authors: Norah Alshahrani, Abdulaziz Almaleh

Abstract:

Autism Spectrum Disorder (ASD) is a condition related to issues with brain development that affects how a person recognises and communicates with others which results in difficulties with interaction and communication socially and it is constantly growing. Early recognition of ASD allows children to lead safe and healthy lives and helps doctors with accurate diagnoses and management of conditions. Therefore, it is crucial to develop a method that will achieve good results and with high accuracy for the measurement of ASD in children. In this paper, ASD datasets of toddlers and children have been analyzed. We employed the following machine learning techniques to attempt to explore ASD: Random Forest (RF), Decision Tree (DT), Na¨ıve Bayes (NB) and Support Vector Machine (SVM). Then feature selection was used to provide fewer attributes from ASD datasets while preserving model performance. As a result, we found that the best result has been provided by SVM, achieving 0.98% in the toddler dataset and 0.99% in the children dataset.

Keywords: Autism Spectrum Disorder, ASD, Machine Learning, ML, Feature Selection, Support Vector Machine, SVM.

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2683 Evaluating Machine Learning Techniques for Activity Classification in Smart Home Environments

Authors: Talal Alshammari, Nasser Alshammari, Mohamed Sedky, Chris Howard

Abstract:

With the widespread adoption of the Internet-connected devices, and with the prevalence of the Internet of Things (IoT) applications, there is an increased interest in machine learning techniques that can provide useful and interesting services in the smart home domain. The areas that machine learning techniques can help advance are varied and ever-evolving. Classifying smart home inhabitants’ Activities of Daily Living (ADLs), is one prominent example. The ability of machine learning technique to find meaningful spatio-temporal relations of high-dimensional data is an important requirement as well. This paper presents a comparative evaluation of state-of-the-art machine learning techniques to classify ADLs in the smart home domain. Forty-two synthetic datasets and two real-world datasets with multiple inhabitants are used to evaluate and compare the performance of the identified machine learning techniques. Our results show significant performance differences between the evaluated techniques. Such as AdaBoost, Cortical Learning Algorithm (CLA), Decision Trees, Hidden Markov Model (HMM), Multi-layer Perceptron (MLP), Structured Perceptron and Support Vector Machines (SVM). Overall, neural network based techniques have shown superiority over the other tested techniques.

Keywords: Activities of daily living, classification, internet of things, machine learning, smart home.

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