Search results for: reliability; performance assessment
1650 Cardiac Disorder Classification Based On Extreme Learning Machine
Authors: Chul Kwak, Oh-Wook Kwon
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In this paper, an extreme learning machine with an automatic segmentation algorithm is applied to heart disorder classification by heart sound signals. From continuous heart sound signals, the starting points of the first (S1) and the second heart pulses (S2) are extracted and corrected by utilizing an inter-pulse histogram. From the corrected pulse positions, a single period of heart sound signals is extracted and converted to a feature vector including the mel-scaled filter bank energy coefficients and the envelope coefficients of uniform-sized sub-segments. An extreme learning machine is used to classify the feature vector. In our cardiac disorder classification and detection experiments with 9 cardiac disorder categories, the proposed method shows significantly better performance than multi-layer perceptron, support vector machine, and hidden Markov model; it achieves the classification accuracy of 81.6% and the detection accuracy of 96.9%.
Keywords: Heart sound classification, extreme learning machine
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19341649 The Evaluation of Electricity Generation and Consumption from Solar Generator: A Case Study at Rajabhat Suan Sunandha’s Learning Center in Samutsongkram
Authors: Chonmapat Torasa
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This paper presents the performance of electricity generation and consumption from solar generator installed at Rajabhat Suan Sunandha’s learning center in Samutsongkram. The result from the experiment showed that solar cell began to work and distribute the current into the system when the solar energy intensity was 340 w/m2, starting from 8:00 am to 4:00 pm (duration of 8 hours). The highest intensity read during the experiment was 1,051.64w/m2. The solar power was 38.74kWh/day. The electromotive force from solar cell averagely was 93.6V. However, when connecting solar cell with the battery charge controller system, the voltage was dropped to 69.07V. After evaluating the power distribution ability and electricity load of tested solar cell, the result showed that it could generate power to 11 units of 36-watt fluorescent lamp bulbs, which was altogether 396W. In the meantime, the AC to DC power converter generated 3.55A to the load, and gave 781VA.
Keywords: Solar Cell, Solar-cell power generating system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20651648 Redundancy in Steel Frames with Masonry Infill Walls
Authors: Hosein Ghaffarzadeh, Robab Naseri Ghalghachi
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Structural redundancy is an interesting point in seismic design of structures. Initially, the structural redundancy is described as indeterminate degree of a system. Although many definitions are presented for redundancy in structures, recently the definition of structural redundancy has been related to the configuration of structural system and the number of lateral load transferring directions in the structure. The steel frames with infill walls are general systems in the constructing of usual residential buildings in some countries. It is obviously declared that the performance of structures will be affected by adding masonry infill walls. In order to investigate the effect of infill walls on the redundancy of the steel frame which constructed with masonry walls, the components of redundancy including redundancy variation index, redundancy strength index and redundancy response modification factor were extracted for the frames with masonry infills. Several steel frames with typical storey number and various numbers of bays were designed and considered. The redundancy of frames with and without infill walls was evaluated by proposed method. The results showed the presence of infill causes increase of redundancy.Keywords: Structural redundancy, Masonry infill walls frames.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23641647 Effect of Blade Number on a Straight-Bladed Vertical-Axis Darreius Wind Turbine
Authors: Marco Raciti Castelli, Stefano De Betta, Ernesto Benini
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This paper presents a mean for reducing the torque variation during the revolution of a vertical-axis wind turbine (VAWT) by increasing the blade number. For this purpose, twodimensional CDF analysis have been performed on a straight-bladed Darreius-type rotor. After describing the computational model, a complete campaign of simulations based on full RANS unsteady calculations is proposed for a three, four and five-bladed rotor architecture characterized by a NACA 0025 airfoil. For each proposed rotor configuration, flow field characteristics are investigated at several values of tip speed ratio, allowing a quantification of the influence of blade number on flow geometric features and dynamic quantities, such as rotor torque and power. Finally, torque and power curves are compared for the analyzed architectures, achieving a quantification of the effect of blade number on overall rotor performance.Keywords: CFD, VAWT, NACA 0021, blade number
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 53361646 Investigation of Roll off Factor in Pulse Shaping Filter on Maximal Ratio Combining for CDMA 2000 System
Authors: G. S. Walia, H. P. Singh, Padma D.
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The integration of wide variety of communication services is made possible with invention of 3G technology. Code Division Multiple Access 2000 operates on various RF channel bandwidths 1.2288 or 3.6864 Mcps (1x or 3x systems). It is a 3G system which offers high bandwidth and wireless broadband services but its efficiency is lowered due to various factors like fading, interference, scattering, absorption etc. This paper investigates the effect of diversity (MRC), roll off factor in Root Raised Cosine (RRC) filter for the BPSK and QPSK modulation schemes. It is possible to transmit data with minimum Inter symbol Interference and within limited bandwidth with proper pulse shaping technique. Bit error rate (BER) performance is analyzed by applying diversity technique by varying the roll off factor for BPSK and QPSK. Roll off factor reduces the ISI and diversity reduces the Fading.
Keywords: CDMA2000, Diversity, Root Raised Cosine, Roll off factor.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 31111645 Autonomous Underwater Vehicle (AUV) Dynamics Modeling and Performance Evaluation
Authors: K. M. Tan, A. Anvar, T.F. Lu
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A sophisticated simulator provides a cost-effective measure to carry out preliminary mission testing and diagnostic while reducing potential failures for real life at sea trials. The presented simulation framework covers three key areas: AUV modeling, sensor modeling, and environment modeling. AUV modeling mainly covers the area of AUV dynamics. Sensor modeling deals with physics and mathematical models that govern each sensor installed onto the AUV. Environment model incorporates the hydrostatic, hydrodynamics, and ocean currents that will affect the AUV in a real-time mission. Based on this designed simulation framework, custom scenarios provided by the user can be modeled and its corresponding behaviors can be observed. This paper focuses on the accuracy of the simulated data from AUV model and environmental model derived from a developed AUV test-bed which was jointly upgraded by DSTO and the University of Adelaide. The main contribution of this paper is to experimentally verify the accuracy of the proposed simulation framework.
Keywords: Autonomous Underwater Vehicle (AUV), simulator, framework, robotics, maritime robot, modeling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 47321644 Face Recognition Based On Vector Quantization Using Fuzzy Neuro Clustering
Authors: Elizabeth B. Varghese, M. Wilscy
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A face recognition system is a computer application for automatically identifying or verifying a person from a digital image or a video frame. A lot of algorithms have been proposed for face recognition. Vector Quantization (VQ) based face recognition is a novel approach for face recognition. Here a new codebook generation for VQ based face recognition using Integrated Adaptive Fuzzy Clustering (IAFC) is proposed. IAFC is a fuzzy neural network which incorporates a fuzzy learning rule into a competitive neural network. The performance of proposed algorithm is demonstrated by using publicly available AT&T database, Yale database, Indian Face database and a small face database, DCSKU database created in our lab. In all the databases the proposed approach got a higher recognition rate than most of the existing methods. In terms of Equal Error Rate (ERR) also the proposed codebook is better than the existing methods.
Keywords: Face Recognition, Vector Quantization, Integrated Adaptive Fuzzy Clustering, Self Organization Map.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22411643 Analysis on the Feasibility of Landsat 8 Imagery for Water Quality Parameters Assessment in an Oligotrophic Mediterranean Lake
Authors: V. Markogianni, D. Kalivas, G. Petropoulos, E. Dimitriou
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Lake water quality monitoring in combination with the use of earth observation products constitutes a major component in many water quality monitoring programs. Landsat 8 images of Trichonis Lake (Greece) acquired on 30/10/2013 and 30/08/2014 were used in order to explore the possibility of Landsat 8 to estimate water quality parameters and particularly CDOM absorption at specific wavelengths, chlorophyll-a and nutrient concentrations in this oligotrophic freshwater body, characterized by inexistent quantitative, temporal and spatial variability. Water samples have been collected at 22 different stations, on late August of 2014 and the satellite image of the same date was used to statistically correlate the in-situ measurements with various combinations of Landsat 8 bands in order to develop algorithms that best describe those relationships and calculate accurately the aforementioned water quality components. Optimal models were applied to the image of late October of 2013 and the validation of the results was conducted through their comparison with the respective available in-situ data of 2013. Initial results indicated the limited ability of the Landsat 8 sensor to accurately estimate water quality components in an oligotrophic waterbody. As resulted by the validation process, ammonium concentrations were proved to be the most accurately estimated component (R = 0.7), followed by chl-a concentration (R = 0.5) and the CDOM absorption at 420 nm (R = 0.3). In-situ nitrate, nitrite, phosphate and total nitrogen concentrations of 2014 were measured as lower than the detection limit of the instrument used, hence no statistical elaboration was conducted. On the other hand, multiple linear regression among reflectance measures and total phosphorus concentrations resulted in low and statistical insignificant correlations. Our results were concurrent with other studies in international literature, indicating that estimations for eutrophic and mesotrophic lakes are more accurate than oligotrophic, owing to the lack of suspended particles that are detectable by satellite sensors. Nevertheless, although those predictive models, developed and applied to Trichonis oligotrophic lake are less accurate, may still be useful indicators of its water quality deterioration.Keywords: Landsat 8, oligotrophic lake, remote sensing, water quality.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15561642 A Review on Applications of Nanotechnology in Automotive Industry
Authors: Akshata S. Malani, Anagha D. Chaudhari, Rajeshkumar U. Sambhe
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Nanotechnology in pristine sense refers to building of structures at atomic and molecular scale. Meticulously nanotechnology encompasses the nanomaterials with at least one dimension size ranging from 1 to 100 nanometres. Unlike the literal meaning of its name, nanotechnology is a massive concept beyond imagination. This paper predominantly deals with relevance of nanotechnology in automotive industries. New generation of automotives looks at nanotechnology as an emerging trend of manufacturing revolution. Intricate shapes can be made out of fairly inexpensive raw materials instead of conventional fabrication process. Though the current era have enough technology to face competition, nanotechnology can give futuristic implications to pick up the modern pace. Nanotechnology intends to bridge the gap between automotives with superior technical performance and their cost fluctuation. Preliminarily, it is an area of great scientific interest and a major shaper of many new technologies. Nanotechnology can be an ideal building block for automotive industries, under constant evolution offering a very wide scope of activity. It possesses huge potential and is still in the embryonic form of research and development.
Keywords: Nanotechnology, nanomaterials, manufacturing, automotive industry.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 53581641 Face Texture Reconstruction for Illumination Variant Face Recognition
Authors: Pengfei Xiong, Lei Huang, Changping Liu
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In illumination variant face recognition, existing methods extracting face albedo as light normalized image may lead to loss of extensive facial details, with light template discarded. To improve that, a novel approach for realistic facial texture reconstruction by combining original image and albedo image is proposed. First, light subspaces of different identities are established from the given reference face images; then by projecting the original and albedo image into each light subspace respectively, texture reference images with corresponding lighting are reconstructed and two texture subspaces are formed. According to the projections in texture subspaces, facial texture with normal light can be synthesized. Due to the combination of original image, facial details can be preserved with face albedo. In addition, image partition is applied to improve the synthesization performance. Experiments on Yale B and CMUPIE databases demonstrate that this algorithm outperforms the others both in image representation and in face recognition.Keywords: texture reconstruction, illumination, face recognition, subspaces
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14821640 A Model for Business Network Governance: Case Study in the Pharmaceutical Industry
Authors: Emil Crişan, Matthias Klumpp
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This paper discusses the theory behind the existence of an idealistic model for business network governance and uses a clarifying case-study, containing governance structures and processes within a business network framework. The case study from a German pharmaceutical industry company complements existing literature by providing a comprehensive explanation of the relations between supply chains and business networks, and also between supply chain management and business network governance. Supply chains and supply chain management are only one side of the interorganizational relationships and ensure short-term performance, while real-world governance structures are needed for ensuring the long-term existence of a supply chain. Within this context, a comprehensive model for business governance is presented. An interesting finding from the case study is that multiple business network governance systems co-exist within the evaluated supply chain.
Keywords: Business network, pharmaceutical industry, supply chain governance, supply chain management.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23631639 A Retrospective Study of Vaginal Stenosis Following Treatment of Cervical Cancers and the Effectiveness of Rehabilitation Interventions
Authors: Manjusha R. Vagal, Shyam K. Shrivastava, Umesh Mahantshetty, Sudeep Gupta, Supriya Chopra, Reena Engineer, Amita Maheshwari, Atul Buduk
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Vaginal stenosis is a common side effect associated with pelvic radiotherapy in cervical cancer patients which contributes negatively to woman’s health and prevents adequate vaginal/cervical examination. Vaginal dilation with a dilator is routine practice and is internationally advocated as a prophylactic measure to preserve vaginal patency. This retrospective study was carried out with the aim to know the usefulness of vaginal dilation following pelvic radiation therapy in cervical cancer patients in India. Data from medical records of 183 cervical cancer patients, which met the study criteria, were collected related to the stage of the disease, treatment received, commencement period of dilation post radiation therapy, sexual status and side effects associated to dilation practice. Data related to vaginal dimensions as per the length of insertion of a small, medium and large dilator were collected on regular follow-ups until 36 months and/or more. Vaginal dimensions as measured with the length of medium dilator insertion were used for analysis of dilation therapy results using paired t-test. Patients who underwent vaginal dilation with dilator maintained vaginal patency, also the mean vaginal length significantly increased, from 8.02 cm ± 2.69 to 9.96 ± 2.89 cm with a p value <0.001. There was no significant difference found on vaginal patency with different intervals of initiation of dilation therapy. At the third year and more following dilation therapy, significant increase in vaginal length observed with a p value of 0.0001 in both sexually active and inactive patients. Compilation of vaginal dosage during brachytherapy was inadequate, and hence, the secondary objective of the study to determine the effect of radiotherapy on the outcome of rehabilitation intervention was not studied in detail. This retrospective study has found that dilation therapy with vaginal dilators post pelvic radiotherapy is effective in preventing vaginal stenosis and improving vaginal patency and cannot be substituted with vaginal intercourse. Sexual quality of life assessment in the Indian population needs much attention.
Keywords: Dilator, sexually active, vaginal dilation, vaginal stenosis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14701638 Interaction of Building Stones with Inorganic Water-Soluble Salts
Authors: Z. Pavlík, J. Žumár, M. Pavlíková, R. Černý
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Interaction of inorganic water-soluble salts and building stones is studied in the paper. Two types of sandstone and one type of spongillite as representatives of materials used in historical masonry are subjected to experimental testing. Within the performed experiments, measurement of moisture and chloride concentration profiles is done in order to get input data for computational inverse analysis. Using the inverse analysis, moisture diffusivity and chloride diffusion coefficient of investigated materials are accessed. Additionally, the effect of salt presence on water vapor storage is investigated using dynamic vapor sorption device. The obtained data represents valuable information for restoration of historical masonry and give evidence on the performance of studied stones in contact with water soluble salts.
Keywords: Moisture and chloride transport, sandstone, spongillite, moisture diffusivity, chloride diffusion coefficient.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18311637 Automated Detection of Alzheimer Disease Using Region Growing technique and Artificial Neural Network
Authors: B. Al-Naami, N. Gharaibeh, A. AlRazzaq Kheshman
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Alzheimer is known as the loss of mental functions such as thinking, memory, and reasoning that is severe enough to interfere with a person's daily functioning. The appearance of Alzheimer Disease symptoms (AD) are resulted based on which part of the brain has a variety of infection or damage. In this case, the MRI is the best biomedical instrumentation can be ever used to discover the AD existence. Therefore, this paper proposed a fusion method to distinguish between the normal and (AD) MRIs. In this combined method around 27 MRIs collected from Jordanian Hospitals are analyzed based on the use of Low pass -morphological filters to get the extracted statistical outputs through intensity histogram to be employed by the descriptive box plot. Also, the artificial neural network (ANN) is applied to test the performance of this approach. Finally, the obtained result of t-test with confidence accuracy (95%) has compared with classification accuracy of ANN (100 %). The robust of the developed method can be considered effectively to diagnose and determine the type of AD image.Keywords: Alzheimer disease, Brain MRI analysis, Morphological filter, Box plot, Intensity histogram, ANN.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 31421636 Smart Grid Communication Architecture Modeling for Heterogeneous Network Based Advanced Metering Infrastructure
Authors: S. Prem Kumar, H. Thameemul Ansari, V. Saminadan
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A smart grid is an emerging technology in the power delivery system which provides an intelligent, self-recovery and homeostatic grid in delivering power to the users. Smart grid communication network provides transmission capacity for information transformation within the connected nodes in the network, in favor of functional and operational needs. In the electric grids communication network delay is based on choosing the appropriate technology and the types of devices enforced. In distinction, the combination of IEEE 802.16 based WiMAX and IEEE 802.11 based WiFi technologies provides improved coverage and gives low delay performances to meet the smart grid needs. By incorporating this method in Wide Area Monitoring System (WAMS) and Advanced Metering Infrastructure (AMI) the performance of the smart grid will be considerably improved. This work deals with the implementation of WiMAX-WLAN integrated network architecture for WAMS and AMI in the smart grid.Keywords: WiMAX, WLAN, WAMS, Smart Grid, HetNet, AMI.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10171635 Input Variable Selection for RBFN-based Electric Utility's CO2 Emissions Forecasting
Authors: I. Falconett, K. Nagasaka
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This study investigates the performance of radial basis function networks (RBFN) in forecasting the monthly CO2 emissions of an electric power utility. We also propose a method for input variable selection. This method is based on identifying the general relationships between groups of input candidates and the output. The effect that each input has on the forecasting error is examined by removing all inputs except the variable to be investigated from its group, calculating the networks parameter and performing the forecast. Finally, the new forecasting error is compared with the reference model. Eight input variables were identified as the most relevant, which is significantly less than our reference model with 30 input variables. The simulation results demonstrate that the model with the 8 inputs selected using the method introduced in this study performs as accurate as the reference model, while also being the most parsimonious.
Keywords: Correlation analysis, CO2 emissions forecasting, electric power utility, radial basis function networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15371634 Wind Fragility for Soundproof Wall with the Variation of Section Shape of Frame
Authors: Seong Do Kim, Woo Young Jung
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Recently, damages due to typhoons and strong wind are on the rise. Considering this issue, we evaluated the performance of soundproofing walls based on the strong wind fragility by means of numerical analysis. Among the components of the soundproof wall, aluminum frame was the most vulnerable member, thus we have considered different section of aluminum frame in the determination of wind fragility. Wind load was randomly generated using Monte Carlo Simulation method. Moreover, limit state was based on the test standard of road construction soundproofing wall. In this study, the strong wind fragility was determined by considering the influence factors of wind exposure category, soundproof wall’s installation position, and shape of aluminum frame section. Results of this study could be used to determine the section shape of the frame that has high resistance to the wind during construction of the soundproofing wall.
Keywords: Aluminum frame soundproofing wall, Monte Carlo Simulation, numerical simulation, wind fragility.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8891633 Improving the Performance of Back-Propagation Training Algorithm by Using ANN
Authors: Vishnu Pratap Singh Kirar
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Artificial Neural Network (ANN) can be trained using back propagation (BP). It is the most widely used algorithm for supervised learning with multi-layered feed-forward networks. Efficient learning by the BP algorithm is required for many practical applications. The BP algorithm calculates the weight changes of artificial neural networks, and a common approach is to use a twoterm algorithm consisting of a learning rate (LR) and a momentum factor (MF). The major drawbacks of the two-term BP learning algorithm are the problems of local minima and slow convergence speeds, which limit the scope for real-time applications. Recently the addition of an extra term, called a proportional factor (PF), to the two-term BP algorithm was proposed. The third increases the speed of the BP algorithm. However, the PF term also reduces the convergence of the BP algorithm, and criteria for evaluating convergence are required to facilitate the application of the three terms BP algorithm. Although these two seem to be closely related, as described later, we summarize various improvements to overcome the drawbacks. Here we compare the different methods of convergence of the new three-term BP algorithm.
Keywords: Neural Network, Backpropagation, Local Minima, Fast Convergence Rate.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 35591632 Use of Bayesian Network in Information Extraction from Unstructured Data Sources
Authors: Quratulain N. Rajput, Sajjad Haider
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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
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22321631 Segmenting Ultrasound B-Mode Images Using RiIG Distributions and Stochastic Optimization
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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.
Keywords: Endorcardial Wall, Rician Inverse Distributions, Segmentation, Ultrasound Images.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15731630 Automatic Segmentation of Thigh Magnetic Resonance Images
Authors: Lorena Urricelqui, Armando Malanda, Arantxa Villanueva
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Purpose: To develop a method for automatic segmentation of adipose and muscular tissue in thighs from magnetic resonance images. Materials and methods: Thirty obese women were scanned on a Siemens Impact Expert 1T resonance machine. 1500 images were finally used in the tests. The developed segmentation method is a recursive and multilevel process that makes use of several concepts such as shaped histograms, adaptative thresholding and connectivity. The segmentation process was implemented in Matlab and operates without the need of any user interaction. The whole set of images were segmented with the developed method. An expert radiologist segmented the same set of images following a manual procedure with the aid of the SliceOmatic software (Tomovision). These constituted our 'goal standard'. Results: The number of coincidental pixels of the automatic and manual segmentation procedures was measured. The average results were above 90 % of success in most of the images. Conclusions: The proposed approach allows effective automatic segmentation of MRIs from thighs, comparable to expert manual performance.
Keywords: Segmentation, thigh, magnetic resonance image, fat, muscle.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19051629 A Robust Eyelashes and Eyelid Detection in Transformation Invariant Iris Recognition: In Application with LRC Security System
Authors: R. Bremananth
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Biometric authentication is an essential task for any kind of real-life applications. In this paper, we contribute two primary paradigms to Iris recognition such as Robust Eyelash Detection (RED) using pathway kernels and hair curve fitting synthesized model. Based on these two paradigms, rotation invariant iris recognition is enhanced. In addition, the presented framework is tested with real-life iris data to provide the authentication for LRC (Learning Resource Center) users. Recognition performance is significantly improved based on the contributed schemes by evaluating real-life irises. Furthermore, the framework has been implemented using Java programming language. Experiments are performed based on 1250 diverse subjects in different angles of variations on the authentication process. The results revealed that the methodology can deploy in the process on LRC management system and other security required applications.Keywords: Authentication, biometric, eye lashes detection, iris scanning, LRC security, secure access.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10351628 MOSFET Based ADC for Accurate Positioning of Control Valves in Industry
Authors: K. Diwakar, N. Vasudevan, C. Senthilpari
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This paper presents MOSFET based analog to digital converter which is simple in design, has high resolution, and conversion rate better than dual slope ADC. It has no DAC which will limit the performance, no error in conversion, can operate for wide range of inputs and never become unstable. One of the industrial applications, where the proposed high resolution MOSFET ADC can be used is, for the positioning of control valves in a multi channel data acquisition and control system (DACS), using stepper motors as actuators of control valves. It is observed that in a DACS having ten control valves, 0.02% of positional accuracy of control valves can be achieved with the data update period of 250ms and with stepper motors of maximum pulse rate 20 Kpulses per sec. and minimum pulse width of 2.5 μsec. The reported accuracy so far by other authors is 0.2%, with update period of 255 ms and with 8 bit DAC. The accuracy in the proposed configuration is limited by the available precision stepper motor and not by the MOSFET based ADC.
Keywords: MOSFET based ADC, Actuators, Positional accuracy, Stepper Motors.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26111627 Using Interpretive Structural Modeling to Determine the Relationships among Knowledge Management Criteria inside Malaysian Organizations
Authors: Reza Sigari Tabrizi, Yeap Peik Foong, Nazli Ebrahimi
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This paper is concerned with the establishment of relationships among knowledge management (KM) criteria that will ensure an essential foundation to evaluate KM outcomes. The major issue under investigation is to assess the popularity of criteria within organizations and to establish a structure of criteria for measuring KM results. An empirical survey was conducted among Malaysian organizations to investigate KM criteria for measuring success of KM initiatives. Therefore, knowledge workers as the respondents were targeted to establish a structure of criteria for evaluating KM outcomes. An established structure of criteria based on the Interpretive Structural Modeling (ISM) is used to map criteria relationships inside organizations. This structure is portrayed to identify that how these set of criteria are related. This network schema should be investigated and implemented to promote innovation and improve enterprise performance. To the researchers, this survey has significant insights into relationship between KM programs and business success.
Keywords: Knowledge Management, Knowledge ManagementOutcomes, KM Criteria, Innovation, Interpretive Structural Modeling
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 36371626 Adaption Model for Building Agile Pronunciation Dictionaries Using Phonemic Distance Measurements
Authors: Akella Amarendra Babu, Rama Devi Yellasiri, Natukula Sainath
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Where human beings can easily learn and adopt pronunciation variations, machines need training before put into use. Also humans keep minimum vocabulary and their pronunciation variations are stored in front-end of their memory for ready reference, while machines keep the entire pronunciation dictionary for ready reference. Supervised methods are used for preparation of pronunciation dictionaries which take large amounts of manual effort, cost, time and are not suitable for real time use. This paper presents an unsupervised adaptation model for building agile and dynamic pronunciation dictionaries online. These methods mimic human approach in learning the new pronunciations in real time. A new algorithm for measuring sound distances called Dynamic Phone Warping is presented and tested. Performance of the system is measured using an adaptation model and the precision metrics is found to be better than 86 percent.Keywords: Pronunciation variations, dynamic programming, machine learning, natural language processing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8001625 Extend of Self-Life of Potato Round Slices with Edible Coating, Green Tea and Ascorbic Acid
Authors: A. Spanou, P. Giannouli
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The effects of coatings based on sodium alginate (S.A) and carboxyl methyl cellulose (CMC) on the color and moisture characteristics of potato round slices were investigated. It is the first time that this combination of polysaccharides is used as edible coating which alone had the best performance as inhibitor of potato color discoloration during the storage of 15 days at 4oC. When ascorbic acid (AA) and green tea (GT) were added in the above edible coating its effects on potato round slices changed. The mixtures of sodium alginate and carboxyl methyl cellulose with ascorbic acid or with green tea behave as a potential moisture barrier, resulting to the extent of potato samples self–life. These data suggests that both GT and AA are potential inhibitors of dehydration in potatoes and not only natural antioxidants.
Keywords: Ascorbic acid, edible coating, green tea, moisture barrier.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 33991624 Cognitive Radio Spectrum Management
Authors: Swapnil Singhal, Santosh Kumar Singh
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The emerging Cognitive Radio is combo of both the technologies i.e. Radio dynamics and software technology. It involve wireless system with efficient coding, designing, and making them artificial intelligent to take the decision according to the surrounding environment and adopt themselves accordingly, so as to deliver the best QoS. This is the breakthrough from fixed hardware and fixed utilization of the spectrum. This software-defined approach of research is centralized at user-definition and application driven model, various software method are used for the optimization of the wireless communication. This paper focused on the Spectrum allocation technique using genetic algorithm GA to evolve radio, represented by chromosomes. The chromosomes gene represents the adjustable parameters in given radio and by using GA, evolving over the generations, the optimized set of parameters are evolved, as per the requirement of user and availability of the spectrum, in our prototype the gene consist of 6 different parameters, and the best set of parameters are evolved according to the application need and availability of the spectrum holes and thus maintaining best QoS for user, simultaneously maintaining licensed user rights. The analyzing tool Matlab is used for the performance of the prototype.
Keywords: ASDR, Cognitive Radio, QoS, Spectrum.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20541623 Climate Related Financial Risk for Automobile Industry and Impact to Financial Institutions
Authors: S. Mahalakshmi, B. Senthil Arasu
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As per the recent changes happening in the global policies, climate related changes and the impact it causes across every sector are viewed as green swan events – in essence, climate related changes can happen often and lead to risk and lot of uncertainty, but need to be mitigated instead of considering them as black swan events. This brings about a question on how this risk can be computed, so that the financial institutions can plan to mitigate it. Climate related changes impact all risk types – credit risk, market risk, operational risk, liquidity risk, reputational risk and others. And the models required to compute this have to consider the different industrial needs of the counterparty, as well as the factors that are contributing to this – be it in the form of different risk drivers, or the different transmission channels or the different approaches and the granular form of data availability. This brings out to the suggestion that the climate related changes, though it affects Pillar I risks, will be a Pillar II risk. This has to be modeled specifically based on the financial institution’s actual exposure to different industries, instead of generalizing the risk charge. And this will have to be considered as the additional capital to be met by the financial institution in addition to their Pillar I risks, as well as the existing Pillar II risks. In this paper, we present a risk assessment framework to model and assess climate change risks - for both credit and market risks. This framework helps in assessing the different scenarios, and how the different transition risks affect the risk associated with the different parties. This research paper delves on the topic of increase in concentration of greenhouse gases, that in turn causing global warming. It then considers the various scenarios of having the different risk drivers impacting credit and market risk of an institution, by understanding the transmission channels, and also considering the transition risk. The paper then focuses on the industry that’s fast seeing a disruption: automobile industry. The paper uses the framework to show how the climate changes and the change to the relevant policies have impacted the entire financial institution. Appropriate statistical models for forecasting, anomaly detection and scenario modeling are built to demonstrate how the framework can be used by the relevant agencies to understand their financial risks. The paper also focuses on the climate risk calculation for the Pillar II capital calculations, and how it will make sense for the bank to maintain this in addition to their regular Pillar I and Pillar II capital.
Keywords: Capital calculation, climate risk, credit risk, pillar II risk, scenario modeling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4241622 Left Ventricular Model Using Second Order Electromechanical Coupling: Effects of Viscoelastic Damping
Authors: Elie H. Karam, Antoine B. Abche
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It is known that the heart interacts with and adapts to its venous and arterial loading conditions. Various experimental studies and modeling approaches have been developed to investigate the underlying mechanisms. This paper presents a model of the left ventricle derived based on nonlinear stress-length myocardial characteristics integrated over truncated ellipsoidal geometry, and second-order dynamic mechanism for the excitation-contraction coupling system. The results of the model presented here describe the effects of the viscoelastic damping element of the electromechanical coupling system on the hemodynamic response. Different heart rates are considered to study the pacing effects on the performance of the left-ventricle against constant preload and afterload conditions under various damping conditions. The results indicate that the pacing process of the left ventricle has to take into account, among other things, the viscoelastic damping conditions of the myofilament excitation-contraction process.Keywords: Myocardial sarcomere, cardiac pump, excitationcontraction coupling, viscoelasicity
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14261621 Real-Time Specific Weed Recognition System Using Histogram Analysis
Authors: Irshad Ahmad, Abdul Muhamin Naeem, Muhammad Islam
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Information on weed distribution within the field is necessary to implement spatially variable herbicide application. Since hand labor is costly, an automated weed control system could be feasible. This paper deals with the development of an algorithm for real time specific weed recognition system based on Histogram Analysis of an image that is used for the weed classification. This algorithm is specifically developed to classify images into broad and narrow class for real-time selective herbicide application. The developed system has been tested on weeds in the lab, which have shown that the system to be very effectiveness in weed identification. Further the results show a very reliable performance on images of weeds taken under varying field conditions. The analysis of the results shows over 95 percent classification accuracy over 140 sample images (broad and narrow) with 70 samples from each category of weeds.Keywords: Image Processing, real-time recognition, Weeddetection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1773