Search results for: Dynamic Thermal Model
1083 A General Segmentation Scheme for Contouring Kidney Region in Ultrasound Kidney Images using Improved Higher Order Spline Interpolation
Authors: K. Bommanna Raja, M.Madheswaran, K.Thyagarajah
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A higher order spline interpolated contour obtained with up-sampling of homogenously distributed coordinates for segmentation of kidney region in different classes of ultrasound kidney images has been developed and presented in this paper. The performance of the proposed method is measured and compared with modified snake model contour, Markov random field contour and expert outlined contour. The validation of the method is made in correspondence with expert outlined contour using maximum coordinate distance, Hausdorff distance and mean radial distance metrics. The results obtained reveal that proposed scheme provides optimum contour that agrees well with expert outlined contour. Moreover this technique helps to preserve the pixels-of-interest which in specific defines the functional characteristic of kidney. This explores various possibilities in implementing computer-aided diagnosis system exclusively for US kidney images. Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17351082 Implementation of an Innovative Simplified Sliding Mode Observer-Based Robust Fault Detection in a Drum Boiler System
Authors: L. Khoshnevisan, H. R. Momeni, A. Ashraf-Modarres
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One of the robust fault detection filter (RFDF) designing method is based on sliding-mode theory. The main purpose of our study is to introduce an innovative simplified reference residual model generator to formulate the RFDF as a sliding-mode observer without any manipulation package or transformation matrix, through which the generated residual signals can be evaluated. So the proposed design is more explicit and requires less design parameters in comparison with approaches requiring changing coordinates. To the best author's knowledge, this is the first time that the sliding mode technique is applied to detect actuator and sensor faults in a real boiler. The designing procedure is proposed in a drum boiler in Synvendska Kraft AB Plant in Malmo, Sweden as a multivariable and strongly coupled system. It is demonstrated that both sensor and actuator faults can robustly be detected. Also sensor faults can be diagnosed and isolated through this method.Keywords: Boiler, fault detection, robustness, simplified sliding-mode observer.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19281081 Modeling and Simulation of Acoustic Link Using Mackenize Propagation Speed Equation
Authors: Christhu Raj M. R., Rajeev Sukumaran
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Underwater acoustic networks have attracted great attention in the last few years because of its numerous applications. High data rate can be achieved by efficiently modeling the physical layer in the network protocol stack. In Acoustic medium, propagation speed of the acoustic waves is dependent on many parameters such as temperature, salinity, density, and depth. Acoustic propagation speed cannot be modeled using standard empirical formulas such as Urick and Thorp descriptions. In this paper, we have modeled the acoustic channel using real time data of temperature, salinity, and speed of Bay of Bengal (Indian Coastal Region). We have modeled the acoustic channel by using Mackenzie speed equation and real time data obtained from National Institute of Oceanography and Technology. It is found that acoustic propagation speed varies between 1503 m/s to 1544 m/s as temperature and depth differs. The simulation results show that temperature, salinity, depth plays major role in acoustic propagation and data rate increases with appropriate data sets substituted in the simulated model.Keywords: Underwater Acoustics, Mackenzie Speed Equation, Temperature, Salinity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21801080 Finite Element Simulation of Multi-Stage Deep Drawing Processes and Comparison with Experimental Results
Authors: A. Pourkamali Anaraki, M. Shahabizadeh, B. Babaee
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The plastic forming process of sheet plate takes an important place in forming metals. The traditional techniques of tool design for sheet forming operations used in industry are experimental and expensive methods. Prediction of the forming results, determination of the punching force, blank holder forces and the thickness distribution of the sheet metal will decrease the production cost and time of the material to be formed. In this paper, multi-stage deep drawing simulation of an Industrial Part has been presented with finite element method. The entire production steps with additional operations such as intermediate annealing and springback has been simulated by ABAQUS software under axisymmetric conditions. The simulation results such as sheet thickness distribution, Punch force and residual stresses have been extracted in any stages and sheet thickness distribution was compared with experimental results. It was found through comparison of results, the FE model have proven to be in close agreement with those of experiment.Keywords: Deep drawing, Finite element method, Simulation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 50601079 Protection of Cultural Heritage against the Effects of Climate Change Using Autonomous Aerial Systems Combined with Automated Decision Support
Authors: Artur Krukowski, Emmanouela Vogiatzaki
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The article presents an ongoing work in research projects such as SCAN4RECO or ARCH, both funded by the European Commission under Horizon 2020 program. The former one concerns multimodal and multispectral scanning of Cultural Heritage assets for their digitization and conservation via spatiotemporal reconstruction and 3D printing, while the latter one aims to better preserve areas of cultural heritage from hazards and risks. It co-creates tools that would help pilot cities to save cultural heritage from the effects of climate change. It develops a disaster risk management framework for assessing and improving the resilience of historic areas to climate change and natural hazards. Tools and methodologies are designed for local authorities and practitioners, urban population, as well as national and international expert communities, aiding authorities in knowledge-aware decision making. In this article we focus on 3D modelling of object geometry using primarily photogrammetric methods to achieve very high model accuracy using consumer types of devices, attractive both to professions and hobbyists alike.
Keywords: 3D modeling, UAS, cultural heritage, preservation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6871078 Fuzzy EOQ Models for Deteriorating Items with Stock Dependent Demand and Non-Linear Holding Costs
Authors: G. C. Mahata, A. Goswami
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This paper deals with infinite time horizon fuzzy Economic Order Quantity (EOQ) models for deteriorating items with stock dependent demand rate and nonlinear holding costs by taking deterioration rate θ0 as a triangular fuzzy number (θ0 −δ 1, θ0, θ0 +δ 2), where 1 2 0 0 <δ ,δ <θ are fixed real numbers. The traditional parameters such as unit cost and ordering cost have been kept constant but holding cost is considered to vary. Two possibilities of variations in the holding cost function namely, a non-linear function of the length of time for which the item is held in stock and a non-linear function of the amount of on-hand inventory have been used in the models. The approximate optimal solution for the fuzzy cost functions in both these cases have been obtained and the effect of non-linearity in holding costs is studied with the help of a numerical example.
Keywords: Inventory Model, Deterioration, Holding Cost, Fuzzy Total Cost, Extension Principle.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18061077 Jobs Scheduling and Worker Assignment Problem to Minimize Makespan using Ant Colony Optimization Metaheuristic
Authors: Mian Tahir Aftab, Muhammad Umer, Riaz Ahmad
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This article proposes an Ant Colony Optimization (ACO) metaheuristic to minimize total makespan for scheduling a set of jobs and assign workers for uniformly related parallel machines. An algorithm based on ACO has been developed and coded on a computer program Matlab®, to solve this problem. The paper explains various steps to apply Ant Colony approach to the problem of minimizing makespan for the worker assignment & jobs scheduling problem in a parallel machine model and is aimed at evaluating the strength of ACO as compared to other conventional approaches. One data set containing 100 problems (12 Jobs, 03 machines and 10 workers) which is available on internet, has been taken and solved through this ACO algorithm. The results of our ACO based algorithm has shown drastically improved results, especially, in terms of negligible computational effort of CPU, to reach the optimal solution. In our case, the time taken to solve all 100 problems is even lesser than the average time taken to solve one problem in the data set by other conventional approaches like GA algorithm and SPT-A/LMC heuristics.Keywords: Ant Colony Optimization (ACO), Genetic algorithms (GA), Makespan, SPT-A/LMC heuristic.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 34621076 Predicting Global Solar Radiation Using Recurrent Neural Networks and Climatological Parameters
Authors: Rami El-Hajj Mohamad, Mahmoud Skafi, Ali Massoud Haidar
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Several meteorological parameters were used for the prediction of monthly average daily global solar radiation on horizontal using recurrent neural networks (RNNs). Climatological data and measures, mainly air temperature, humidity, sunshine duration, and wind speed between 1995 and 2007 were used to design and validate a feed forward and recurrent neural network based prediction systems. In this paper we present our reference system based on a feed-forward multilayer perceptron (MLP) as well as the proposed approach based on an RNN model. The obtained results were promising and comparable to those obtained by other existing empirical and neural models. The experimental results showed the advantage of RNNs over simple MLPs when we deal with time series solar radiation predictions based on daily climatological data.
Keywords: Recurrent Neural Networks, Global Solar Radiation, Multi-layer perceptron, gradient, Root Mean Square Error.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25481075 Study of EEGs from Somatosensory Cortex and Alzheimer's Disease Sources
Authors: Md R. Bashar, Yan Li, Peng Wen
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This study is to investigate the electroencephalogram (EEG) differences generated from a normal and Alzheimer-s disease (AD) sources. We also investigate the effects of brain tissue distortions due to AD on EEG. We develop a realistic head model from T1 weighted magnetic resonance imaging (MRI) using finite element method (FEM) for normal source (somatosensory cortex (SC) in parietal lobe) and AD sources (right amygdala (RA) and left amygdala (LA) in medial temporal lobe). Then, we compare the AD sourced EEGs to the SC sourced EEG for studying the nature of potential changes due to sources and 5% to 20% brain tissue distortions. We find an average of 0.15 magnification errors produced by AD sourced EEGs. Different brain tissue distortion models also generate the maximum 0.07 magnification. EEGs obtained from AD sources and different brain tissue distortion levels vary scalp potentials from normal source, and the electrodes residing in parietal and temporal lobes are more sensitive than other electrodes for AD sourced EEG.
Keywords: Alzheimer's disease (AD), brain tissue distortion, electroencephalogram, finite element method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19031074 Preoperative to Intraoperative Space Registration for Management of Head Injuries
Authors: M. Gooroochurn, M. Ovinis, D. Kerr, K. Bouazza-Marouf, M. Vloeberghs
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A registration framework for image-guided robotic surgery is proposed for three emergency neurosurgical procedures, namely Intracranial Pressure (ICP) Monitoring, External Ventricular Drainage (EVD) and evacuation of a Chronic Subdural Haematoma (CSDH). The registration paradigm uses CT and white light as modalities. This paper presents two simulation studies for a preliminary evaluation of the registration protocol: (1) The loci of the Target Registration Error (TRE) in the patient-s axial, coronal and sagittal views were simulated based on a Fiducial Localisation Error (FLE) of 5 mm and (2) Simulation of the actual framework using projected views from a surface rendered CT model to represent white light images of the patient. Craniofacial features were employed as the registration basis to map the CT space onto the simulated intraoperative space. Photogrammetry experiments on an artificial skull were also performed to benchmark the results obtained from the second simulation. The results of both simulations show that the proposed protocol can provide a 5mm accuracy for these neurosurgical procedures.Keywords: Image-guided Surgery, Multimodality Registration, Photogrammetry, Preoperative to Intraoperative Registration.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15221073 Robust Numerical Scheme for Pricing American Options under Jump Diffusion Models
Authors: Salah Alrabeei, Mohammad Yousuf
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The goal of option pricing theory is to help the investors to manage their money, enhance returns and control their financial future by theoretically valuing their options. However, most of the option pricing models have no analytical solution. Furthermore, not all the numerical methods are efficient to solve these models because they have nonsmoothing payoffs or discontinuous derivatives at the exercise price. In this paper, we solve the American option under jump diffusion models by using efficient time-dependent numerical methods. several techniques are integrated to reduced the overcome the computational complexity. Fast Fourier Transform (FFT) algorithm is used as a matrix-vector multiplication solver, which reduces the complexity from O(M2) into O(M logM). Partial fraction decomposition technique is applied to rational approximation schemes to overcome the complexity of inverting polynomial of matrices. The proposed method is easy to implement on serial or parallel versions. Numerical results are presented to prove the accuracy and efficiency of the proposed method.Keywords: Integral differential equations, American options, jump–diffusion model, rational approximation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5461072 Heritability and Repeatability Estimates of Some Measurable Traits in Meat Type Chickens Reared for Ten Weeks in Abeokuta, Nigeria
Authors: A. J. Sanda, O. Olowofeso, M. A. Adeleke, A. O Oso, S. O. Durosaro, M. O. Sanda
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A total of 150 meat type chickens comprising 50 each of Arbor Acre, Marshall and Ross were used for this study which lasted for 10 weeks at the Federal University of Agriculture, Abeokuta, Nigeria. Growth performance data were collected from the third week through week 10 and data obtained were analysed using the Generalized Linear Model Procedure. Heritability estimates (h2) for body dimensions carried out on the chicken strains ranged from low to high. Marshall broiler chicken strain had the highest h2 for body weight 0.46±0.04, followed by Arbor Acre and Ross with h2 being 0.38±0.12 and 0.26±0.06, respectively. The repeatability estimates for body weight in the three broiler strains were high, and it ranged from 0.70 at week 4 to 0.88 at week 10. Relationships between the body weight and linear body measurements in the broiler chicken strains were positive and highly significant (p > 0.05).
Keywords: Broiler chicken strains, heritability, repeatability, traits.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 29731071 The Power of Indigenous Peoples in Decision-Making Processes of Mining Projects: The Pilbara Region
Authors: K. N. Penna, J. P. English
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The destruction of the Juukan Gorge rock shelters in 2020 has catalysed impetus within Australian society for a significant change in engagement with Indigenous Peoples, and the approach to Indigenous cultural heritage, both within the Pilbara region and more broadly across Australia. Culture-based and people-centred approaches are inherent to inclusive sustainable development and Free, Prior, Informed Consent, outcomes encouraged by international and local recommendations on the human rights and cultural heritage preservation of Indigenous peoples. In this paper, we present an interpretive model of an evolved process for mining project development, incorporating culture-based and people-centred approaches, based on the Theory U system change method. The evolved process advocates a change in organisational mindset and culture, and a comprehensive understanding of Indigenous Peoples’ culture and values, as the foundations for increasing their influence and achieving mutually beneficial developments.
Keywords: Indigenous Engagement, mining industry, culture-based approach, people-centred approach, Theory U.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4091070 DEMO Based Optimal Power Purchase Planning Under Electricity Price Uncertainty
Authors: Tulika Bhattacharjee, A. K.Chakraborty
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Due to the deregulation of the Electric Supply Industry and the resulting emergence of electricity market, the volumes of power purchases are on the rise all over the world. In a bid to meet the customer-s demand in a reliable and yet economic manner, utilities purchase power from the energy market over and above its own production. This paper aims at developing an optimal power purchase model with two objectives viz economy and environment ,taking various functional operating constraints such as branch flow limits, load bus voltage magnitudes limits, unit capacity constraints and security constraints into consideration.The price of purchased power being an uncertain variable is modeled using fuzzy logic. DEMO (Differential Evolution For Multi-objective Optimization) is used to obtain the pareto-optimal solution set of the multi-objective problem formulated. Fuzzy set theory has been employed to extract the best compromise non-dominated solution. The results obtained on IEEE 30 bus system are presented and compared with that of NSGAII.Keywords: Deregulation, Differential Evolution, Multi objective Optimization, Pareto Optimal Set, Optimal Power Flow
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14961069 Autonomous Flight Performance Improvement of Load-Carrying Unmanned Aerial Vehicles by Active Morphing
Authors: Tugrul Oktay, Mehmet Konar, Mohamed Abdallah Mohamed, Murat Aydin, Firat Sal, Murat Onay, Mustafa Soylak
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In this paper, it is aimed to improve autonomous flight performance of a load-carrying (payload: 3 kg and total: 6kg) unmanned aerial vehicle (UAV) through active wing and horizontal tail active morphing and also integrated autopilot system parameters (i.e. P, I, D gains) and UAV parameters (i.e. extension ratios of wing and horizontal tail during flight) design. For this purpose, a loadcarrying UAV (i.e. ZANKA-II) is manufactured in Erciyes University, College of Aviation, Model Aircraft Laboratory is benefited. Optimum values of UAV parameters and autopilot parameters are obtained using a stochastic optimization method. Using this approach autonomous flight performance of UAV is substantially improved and also in some adverse weather conditions an opportunity for safe flight is satisfied. Active morphing and integrated design approach gives confidence, high performance and easy-utility request of UAV users.Keywords: Unmanned aerial vehicles, morphing, autopilots, autonomous performance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22591068 Stochastic Estimation of Wireless Traffic Parameters
Authors: Somenath Mukherjee, Raj Kumar Samanta, Gautam Sanyal
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Different services based on different switching techniques in wireless networks leads to drastic changes in the properties of network traffic. Because of these diversities in services, network traffic is expected to undergo qualitative and quantitative variations. Hence, assumption of traffic characteristics and the prediction of network events become more complex for the wireless networks. In this paper, the traffic characteristics have been studied by collecting traces from the mobile switching centre (MSC). The traces include initiation and termination time, originating node, home station id, foreign station id. Traffic parameters namely, call interarrival and holding times were estimated statistically. The results show that call inter-arrival and distribution time in this wireless network is heavy-tailed and follow gamma distributions. They are asymptotically long-range dependent. It is also found that the call holding times are best fitted with lognormal distribution. Based on these observations, an analytical model for performance estimation is also proposed.
Keywords: Wireless networks, traffic analysis, long-range dependence, heavy-tailed distribution.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18861067 Handwriting Velocity Modeling by Artificial Neural Networks
Authors: Mohamed Aymen Slim, Afef Abdelkrim, Mohamed Benrejeb
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The handwriting is a physical demonstration of a complex cognitive process learnt by man since his childhood. People with disabilities or suffering from various neurological diseases are facing so many difficulties resulting from problems located at the muscle stimuli (EMG) or signals from the brain (EEG) and which arise at the stage of writing. The handwriting velocity of the same writer or different writers varies according to different criteria: age, attitude, mood, writing surface, etc. Therefore, it is interesting to reconstruct an experimental basis records taking, as primary reference, the writing speed for different writers which would allow studying the global system during handwriting process. This paper deals with a new approach of the handwriting system modeling based on the velocity criterion through the concepts of artificial neural networks, precisely the Radial Basis Functions (RBF) neural networks. The obtained simulation results show a satisfactory agreement between responses of the developed neural model and the experimental data for various letters and forms then the efficiency of the proposed approaches.
Keywords: ElectroMyoGraphic (EMG) signals, Experimental approach, Handwriting process, Radial Basis Functions (RBF) neural networks, Velocity Modeling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23051066 The Application of FSI Techniques in Modeling of Realist Pulmonary Systems
Authors: Abdurrahim Bolukbasi, Hassan Athari, Dogan Ciloglu
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The modeling lung respiratory system that has complex anatomy and biophysics presents several challenges including tissue-driven flow patterns and wall motion. Also, the pulmonary lung system because of that they stretch and recoil with each breath, has not static walls and structures. The direct relationship between air flow and tissue motion in the lung structures naturally prefers an FSI simulation technique. Therefore, in order to toward the realistic simulation of pulmonary breathing mechanics the development of a coupled FSI computational model is an important step. A simple but physiologically relevant three-dimensional deep long geometry is designed and fluid-structure interaction (FSI) coupling technique is utilized for simulating the deformation of the lung parenchyma tissue that produces airflow fields. The real understanding of respiratory tissue system as a complex phenomenon have been investigated with respect to respiratory patterns, fluid dynamics and tissue viscoelasticity and tidal breathing period.
Keywords: Lung deformation and mechanics, tissue mechanics, viscoelasticity, fluid-structure interactions, ANSYS.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23191065 Characterization of Electrohydrodynamic Force on Dielectric-Barrier-Discharge Plasma Actuator Using Fluid Simulation
Authors: Hiroyuki Nishida, Taku Nonomura, Takashi Abe
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Wall-surface jet induced by the dielectric barrier discharge (DBD) has been proposed as an actuator for active flow control in aerodynamic applications. Discharge plasma evolution of the DBD plasma actuator was simulated based on a simple fluid model, in which the electron, one type of positive ion and negative ion were taken into account. Two-dimensional simulation was conducted, and the results are in agreement with the insights obtained from experimental studies. The simulation results indicate that the discharge mode changes depending on applied voltage slope; when the applied voltage is positive-going with high applied voltage slope, the corona-type discharge mode turns into the streamer-type discharge mode and the threshold voltage slope is around 300 kV/ms in this simulation. The characteristics of the electrohydrodynamic (EHD) force, which is the source of the wall-surface jet, also change depending on the discharge mode; the tentative peak value of the EHD force during the positive-going voltage phase is saturated by the periodical formation of the streamer-type discharge.Keywords: Dielectric barrier discharge, Plasma actuator, Fluid simulation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24541064 Probability Distribution of Rainfall Depth at Hourly Time-Scale
Authors: S. Dan'azumi, S. Shamsudin, A. A. Rahman
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Rainfall data at fine resolution and knowledge of its characteristics plays a major role in the efficient design and operation of agricultural, telecommunication, runoff and erosion control as well as water quality control systems. The paper is aimed to study the statistical distribution of hourly rainfall depth for 12 representative stations spread across Peninsular Malaysia. Hourly rainfall data of 10 to 22 years period were collected and its statistical characteristics were estimated. Three probability distributions namely, Generalized Pareto, Exponential and Gamma distributions were proposed to model the hourly rainfall depth, and three goodness-of-fit tests, namely, Kolmogorov-Sminov, Anderson-Darling and Chi-Squared tests were used to evaluate their fitness. Result indicates that the east cost of the Peninsular receives higher depth of rainfall as compared to west coast. However, the rainfall frequency is found to be irregular. Also result from the goodness-of-fit tests show that all the three models fit the rainfall data at 1% level of significance. However, Generalized Pareto fits better than Exponential and Gamma distributions and is therefore recommended as the best fit.Keywords: Goodness-of-fit test, Hourly rainfall, Malaysia, Probability distribution.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 29051063 Grid-Connected Inverter Experimental Simulation and Droop Control Implementation
Authors: Nur Aisyah Jalalludin, Arwindra Rizqiawan, Goro Fujita
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In this study, we aim to demonstrate a microgrid system experimental simulation for an easy understanding of a large-scale microgrid system. This model is required for industrial training and learning environments. However, in order to create an exact representation of a microgrid system, the laboratory-scale system must fulfill the requirements of a grid-connected inverter, in which power values are assigned to the system to cope with the intermittent output from renewable energy sources. Aside from that, during fluctuations in load capacity, the grid-connected system must be able to supply power from the utility grid side and microgrid side in a balanced manner. Therefore, droop control is installed in the inverter’s control board to maintain a balanced power sharing in both sides. This power control in a stand-alone condition and droop control in a grid-connected condition must be implemented in order to maintain a stabilized system. Based on the experimental results, power control and droop control can both be applied in the system by comparing the experimental and reference values.
Keywords: Droop control, droop characteristic, grid-connected inverter, microgrid, power control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 30651062 Operational Risk – Scenario Analysis
Authors: Milan Rippel, Petr Teply
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This paper focuses on operational risk measurement techniques and on economic capital estimation methods. A data sample of operational losses provided by an anonymous Central European bank is analyzed using several approaches. Loss Distribution Approach and scenario analysis method are considered. Custom plausible loss events defined in a particular scenario are merged with the original data sample and their impact on capital estimates and on the financial institution is evaluated. Two main questions are assessed – What is the most appropriate statistical method to measure and model operational loss data distribution? and What is the impact of hypothetical plausible events on the financial institution? The g&h distribution was evaluated to be the most suitable one for operational risk modeling. The method based on the combination of historical loss events modeling and scenario analysis provides reasonable capital estimates and allows for the measurement of the impact of extreme events on banking operations.Keywords: operational risk, scenario analysis, economic capital, loss distribution approach, extreme value theory, stress testing
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24171061 Performance Evaluation of Data Mining Techniques for Predicting Software Reliability
Authors: Pradeep Kumar, Abdul Wahid
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Accurate software reliability prediction not only enables developers to improve the quality of software but also provides useful information to help them for planning valuable resources. This paper examines the performance of three well-known data mining techniques (CART, TreeNet and Random Forest) for predicting software reliability. We evaluate and compare the performance of proposed models with Cascade Correlation Neural Network (CCNN) using sixteen empirical databases from the Data and Analysis Center for Software. The goal of our study is to help project managers to concentrate their testing efforts to minimize the software failures in order to improve the reliability of the software systems. Two performance measures, Normalized Root Mean Squared Error (NRMSE) and Mean Absolute Errors (MAE), illustrate that CART model is accurate than the models predicted using Random Forest, TreeNet and CCNN in all datasets used in our study. Finally, we conclude that such methods can help in reliability prediction using real-life failure datasets.
Keywords: Classification, Cascade Correlation Neural Network, Random Forest, Software reliability, TreeNet.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18271060 Numerical Simulation of Fluid-Structure Interaction on Wedge Slamming Impact Using Particle Method
Authors: Sung-Chul Hwang, Di Ren, Sang-Moon Yoon, Jong-Chun Park, Abbas Khayyer, Hitoshi Gotoh
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This paper presents a fully Lagrangian coupled Fluid-Structure Interaction (FSI) solver for simulations of fluid-structure interactions, which is based on the Moving Particle Semi-implicit (MPS) method to solve the governing equations corresponding to incompressible flows as well as elastic structures. The developed solver is verified by reproducing the high velocity impact loads of deformable thin wedges with three different materials such as mild steel, aluminium and tin during water entry. The present simulation results for aluminium are compared with analytical solution derived from the hydrodynamic Wagner model and linear Wan’s theory. And also, the impact pressure and strain on the water entry wedge with three different materials, such as mild steel, aluminium and tin, are simulated and the effects of hydro-elasticity are discussed.Keywords: Fluid-structure interaction (FSI), Moving Particle Semi-implicit (MPS) method, Elastic structure, Incompressible fluid Wedge slamming impact.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20841059 Estimation of Missing or Incomplete Data in Road Performance Measurement Systems
Authors: Kristjan Kuhi, Kati K. Kaare, Ott Koppel
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Modern management in most fields is performance based; both planning and implementation of maintenance and operational activities are driven by appropriately defined performance indicators. Continuous real-time data collection for management is becoming feasible due to technological advancements. Outdated and insufficient input data may result in incorrect decisions. When using deterministic models the uncertainty of the object state is not visible thus applying the deterministic models are more likely to give false diagnosis. Constructing structured probabilistic models of the performance indicators taking into consideration the surrounding indicator environment enables to estimate the trustworthiness of the indicator values. It also assists to fill gaps in data to improve the quality of the performance analysis and management decisions. In this paper authors discuss the application of probabilistic graphical models in the road performance measurement and propose a high-level conceptual model that enables analyzing and predicting more precisely future pavement deterioration based on road utilization.
Keywords: Probabilistic graphical models, performance indicators, road performance management, data collection
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18221058 Image Haze Removal Using Scene Depth Based Spatially Varying Atmospheric Light in Haar Lifting Wavelet Domain
Authors: Prabh Preet Singh, Harpreet Kaur
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This paper presents a method for single image dehazing based on dark channel prior (DCP). The property that the intensity of the dark channel gives an approximate thickness of the haze is used to estimate the transmission and atmospheric light. Instead of constant atmospheric light, the proposed method employs scene depth to estimate spatially varying atmospheric light as it truly occurs in nature. Haze imaging model together with the soft matting method has been used in this work to produce high quality haze free image. Experimental results demonstrate that the proposed approach produces better results than the classic DCP approach as color fidelity and contrast of haze free image are improved and no over-saturation in the sky region is observed. Further, lifting Haar wavelet transform is employed to reduce overall execution time by a factor of two to three as compared to the conventional approach.
Keywords: Depth based atmospheric light, dark channel prior, lifting wavelet.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5331057 Convergence Analysis of Training Two-Hidden-Layer Partially Over-Parameterized ReLU Networks via Gradient Descent
Authors: Zhifeng Kong
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Over-parameterized neural networks have attracted a great deal of attention in recent deep learning theory research, as they challenge the classic perspective of over-fitting when the model has excessive parameters and have gained empirical success in various settings. While a number of theoretical works have been presented to demystify properties of such models, the convergence properties of such models are still far from being thoroughly understood. In this work, we study the convergence properties of training two-hidden-layer partially over-parameterized fully connected networks with the Rectified Linear Unit activation via gradient descent. To our knowledge, this is the first theoretical work to understand convergence properties of deep over-parameterized networks without the equally-wide-hidden-layer assumption and other unrealistic assumptions. We provide a probabilistic lower bound of the widths of hidden layers and proved linear convergence rate of gradient descent. We also conducted experiments on synthetic and real-world datasets to validate our theory.Keywords: Over-parameterization, Rectified Linear Units (ReLU), convergence, gradient descent, neural networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8811056 Hippocampus Segmentation using a Local Prior Model on its Boundary
Authors: Dimitrios Zarpalas, Anastasios Zafeiropoulos, Petros Daras, Nicos Maglaveras
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Segmentation techniques based on Active Contour Models have been strongly benefited from the use of prior information during their evolution. Shape prior information is captured from a training set and is introduced in the optimization procedure to restrict the evolution into allowable shapes. In this way, the evolution converges onto regions even with weak boundaries. Although significant effort has been devoted on different ways of capturing and analyzing prior information, very little thought has been devoted on the way of combining image information with prior information. This paper focuses on a more natural way of incorporating the prior information in the level set framework. For proof of concept the method is applied on hippocampus segmentation in T1-MR images. Hippocampus segmentation is a very challenging task, due to the multivariate surrounding region and the missing boundary with the neighboring amygdala, whose intensities are identical. The proposed method, mimics the human segmentation way and thus shows enhancements in the segmentation accuracy.Keywords: Medical imaging & processing, Brain MRI segmentation, hippocampus segmentation, hippocampus-amygdala missingboundary, weak boundary segmentation, region based segmentation, prior information, local weighting scheme in level sets, spatialdistribution of labels, gradient distribution on boundary.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17431055 Multi-Criteria Decision-Making Selection Model with Application to Chemical Engineering Management Decisions
Authors: Mohsen Pirdashti, Arezou Ghadi, Mehrdad Mohammadi, Gholamreza Shojatalab
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Chemical industry project management involves complex decision making situations that require discerning abilities and methods to make sound decisions. Project managers are faced with decision environments and problems in projects that are complex. In this work, case study is Research and Development (R&D) project selection. R&D is an ongoing process for forward thinking technology-based chemical industries. R&D project selection is an important task for organizations with R&D project management. It is a multi-criteria problem which includes both tangible and intangible factors. The ability to make sound decisions is very important to success of R&D projects. Multiple-criteria decision making (MCDM) approaches are major parts of decision theory and analysis. This paper presents all of MCDM approaches for use in R&D project selection. It is hoped that this work will provide a ready reference on MCDM and this will encourage the application of the MCDM by chemical engineering management.Keywords: Chemical Engineering, R&D Project, MCDM, Selection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 40601054 Environmental Impacts of Point and Non-Point Source Pollution in Krishnagiri Reservoir: A Case Study in South India
Authors: N. K. Ambujam, V. Sudha
Abstract:
Reservoirs are being contaminated all around the world with point source and Non-Point Source (NPS) pollution. The most common NPS pollutants are sediments and nutrients. Krishnagiri Reservoir (KR) has been chosen for the present case study, which is located in the tropical semi-arid climatic zone of Tamil Nadu, South India. It is the main source of surface water in Krishnagiri district to meet the freshwater demands. The reservoir has lost about 40% of its water holding capacity due to sedimentation over the period of 50 years. Hence, from the research and management perspective, there is a need for a sound knowledge on the spatial and seasonal variations of KR water quality. The present study encompasses the specific objectives as (i) to investigate the longitudinal heterogeneity and seasonal variations of physicochemical parameters, nutrients and biological characteristics of KR water and (ii) to examine the extent of degradation of water quality in KR. 15 sampling points were identified by uniform stratified method and a systematic monthly sampling strategy was selected due to high dynamic nature in its hydrological characteristics. The physicochemical parameters, major ions, nutrients and Chlorophyll a (Chl a) were analysed. Trophic status of KR was classified by using Carlson's Trophic State Index (TSI). All statistical analyses were performed by using Statistical Package for Social Sciences programme, version-16.0. Spatial maps were prepared for Chl a using Arc GIS. Observations in KR pointed out that electrical conductivity and major ions are highly variable factors as it receives inflow from the catchment with different land use activities. The study of major ions in KR exhibited different trends in their values and it could be concluded that as the monsoon progresses the major ions in the water decreases or water quality stabilizes. The inflow point of KR showed comparatively higher concentration of nutrients including nitrate, soluble reactive phosphorus (SRP), total phosphors (TP), total suspended phosphorus (TSP) and total dissolved phosphorus (TDP) during monsoon seasons. This evidently showed the input of significant amount of nutrients from the catchment side through agricultural runoff. High concentration of TDP and TSP at the lacustrine zone of the reservoir during summer season evidently revealed that there was a significant release of phosphorus from the bottom sediments. Carlson’s TSI of KR ranged between 81 and 92 during northeast monsoon and summer seasons. High and permanent Cyanobacterial bloom in KR could be mainly due to the internal loading of phosphorus from the bottom sediments. According to Carlson’s TSI classification Krishnagiri reservoir was ranked in the hyper-eutrophic category. This study provides necessary basic data on the spatio-temporal variations of water quality in KR and also proves the impact of point and NPS pollution from the catchment area. High TSI warrants a greater threat for the recovery of internal P loading and hyper-eutrophic condition of KR. Several expensive internal measures for the reduction of internal loading of P were introduced by many scientists. However, the outcome of the present research suggests for the innovative algae harvesting technique for the removal of sediment nutrients.
Keywords: Hyper-eutrophication, Krishnagiri reservoir, nutrients, NPS pollution.
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