Search results for: OSU tidal prediction software
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6717

Search results for: OSU tidal prediction software

6687 Study of the Morpho-Sedimentary Evolution of Tidal Mouths on the Southern Fringe of the Gulf of Gabes, Southeast of Tunisia: Hydrodynamic Circulation and Associated Sedimentary Movements

Authors: Chadlia Ounissi, Maher Gzam, Tahani Hallek, Salah Mahmoudi, Mabrouk Montacer

Abstract:

This work consists of a morphological study of the coastal domain at the central fringe of the Gulf of Gabes, Southeast of Tunisia, belonging to the structural domain of the maritime Jeffara. The diachronic study of tidal mouths in the study area and the observation of morphological markers revealed the existence of hydro-sedimentary processes leading to sedimentary accumulation and filling of the estuarine system. This filling process is materialized by the genesis of a sandy cord and the lateral migration of the tidal mouth. Moreover, we have been able to affirm, by the use of satellite images, that the dominant and responsible current at this particular coastal morphology is directed to the North, having constituted a controversy on the occurrence of what is previously mentioned in the literature. The speed of the lateral displacement of the channel varies as a function of the hydrodynamic forcing. Wave-dominated sites recorded the fastest speed (18 m/year) in the image of the mouth of Wadi el Melah. Tidal dominated sites in the Wadi Zerkine satellite image recorded a very low lateral migration (2 m / year). This variation in speed indicates that the intensity of the coastal current is uneven along the coast. This general pattern of hydrodynamic circulation, to the north, of the central fringe of the Gulf of Gabes, is disturbed by hydro-sedimentary cells.

Keywords: tidal mouth, direction of current, filling, sediment transport, Gulf of Gabes

Procedia PDF Downloads 254
6686 Virtual Reality Based 3D Video Games and Speech-Lip Synchronization Superseding Algebraic Code Excited Linear Prediction

Authors: P. S. Jagadeesh Kumar, S. Meenakshi Sundaram, Wenli Hu, Yang Yung

Abstract:

In 3D video games, the dominance of production is unceasingly growing with a protruding level of affordability in terms of budget. Afterward, the automation of speech-lip synchronization technique is customarily onerous and has advanced a critical research subject in virtual reality based 3D video games. This paper presents one of these automatic tools, precisely riveted on the synchronization of the speech and the lip movement of the game characters. A robust and precise speech recognition segment that systematized with Algebraic Code Excited Linear Prediction method is developed which unconventionally delivers lip sync results. The Algebraic Code Excited Linear Prediction algorithm is constructed on that used in code-excited linear prediction, but Algebraic Code Excited Linear Prediction codebooks have an explicit algebraic structure levied upon them. This affords a quicker substitute to the software enactments of lip sync algorithms and thus advances the superiority of service factors abridged production cost.

Keywords: algebraic code excited linear prediction, speech-lip synchronization, video games, virtual reality

Procedia PDF Downloads 440
6685 Automatic Flood Prediction Using Rainfall Runoff Model in Moravian-Silesian Region

Authors: B. Sir, M. Podhoranyi, S. Kuchar, T. Kocyan

Abstract:

Rainfall-runoff models play important role in hydrological predictions. However, the model is only one part of the process for creation of flood prediction. The aim of this paper is to show the process of successful prediction for flood event (May 15–May 18 2014). The prediction was performed by rainfall runoff model HEC–HMS, one of the models computed within Floreon+ system. The paper briefly evaluates the results of automatic hydrologic prediction on the river Olše catchment and its gages Český Těšín and Věřňovice.

Keywords: flood, HEC-HMS, prediction, rainfall, runoff

Procedia PDF Downloads 363
6684 Numerical Investigation of the Bio-fouling Roughness Effect on Tidal Turbine

Authors: O. Afshar

Abstract:

Unlike other renewable energy sources, tidal current energy is an extremely reliable, predictable and continuous energy source as the current pattern and speed can be predicted throughout the year. A key concern associated with tidal turbines is their long-term reliability when operating in the hostile marine environment. Bio-fouling changes the physical shape and roughness of turbine components, hence altering the overall turbine performance. This paper seeks to employ Computational Fluid Dynamics (CFD) method to quantify the effects of this problem based on the obtained flow field information. The simulation is carried out on a NACA 63-618 aerofoil. The Reynolds Averaged Navier-Stokes (RANS) equations with Shear Stress Transport (SST) turbulent model are used to simulate the flow around the model. Different levels of fouling are studied on 2D aerofoil surface with quantified fouling height and density. In terms of lift and drag coefficient results, numerical results show good agreement with the experiment which was carried out in wind tunnel. Numerical results of research indicate that an increase in fouling thickness causes an increase in drag coefficient and a reduction in lift coefficient. Moreover, pressure gradient gradually becomes adverse as height of fouling increases. In addition, result by turbulent kinetic energy contour reveals it increases with fouling height and it extends into wake due to flow separation.

Keywords: tidal energy, lift coefficient, drag coefficient, roughness

Procedia PDF Downloads 359
6683 Monthly River Flow Prediction Using a Nonlinear Prediction Method

Authors: N. H. Adenan, M. S. M. Noorani

Abstract:

River flow prediction is an essential to ensure proper management of water resources can be optimally distribute water to consumers. This study presents an analysis and prediction by using nonlinear prediction method involving monthly river flow data in Tanjung Tualang from 1976 to 2006. Nonlinear prediction method involves the reconstruction of phase space and local linear approximation approach. The phase space reconstruction involves the reconstruction of one-dimensional (the observed 287 months of data) in a multidimensional phase space to reveal the dynamics of the system. Revenue of phase space reconstruction is used to predict the next 72 months. A comparison of prediction performance based on correlation coefficient (CC) and root mean square error (RMSE) have been employed to compare prediction performance for nonlinear prediction method, ARIMA and SVM. Prediction performance comparisons show the prediction results using nonlinear prediction method is better than ARIMA and SVM. Therefore, the result of this study could be used to developed an efficient water management system to optimize the allocation water resources.

Keywords: river flow, nonlinear prediction method, phase space, local linear approximation

Procedia PDF Downloads 384
6682 Mooring Analysis of Duct-Type Tidal Current Power System in Shallow Water

Authors: Chul H. Jo, Do Y. Kim, Bong K. Cho, Myeong J. Kim

Abstract:

The exhaustion of oil and the environmental pollution from the use of fossil fuel are increasing. Tidal current power (TCP) has been proposed as an alternative energy source because of its predictability and reliability. By applying a duct and single point mooring (SPM) system, a TCP device can amplify the generating power and keep its position properly. Because the generating power is proportional to cube of the current stream velocity, amplifying the current speed by applying a duct to a TCP system is an effective way to improve the efficiency of the power device. An SPM system can be applied at any water depth and is highly cost effective. Simple installation and maintenance procedures are also merits of an SPM system. In this study, we designed an SPM system for a duct-type TCP device for use in shallow water. Motions of the duct are investigated to obtain the response amplitude operator (RAO) as the magnitude of the transfer function. Parameters affecting the stability of the SPM system such as the fairlead departure angle, current velocity, and the number of clamp weights are analyzed and/or optimized. Wadam and OrcaFlex commercial software is used to design the mooring line.

Keywords: mooring design, parametric analysis, RAO (Response Amplitude Operator), SPM (Single Point Mooring)

Procedia PDF Downloads 262
6681 Software Cloning and Agile Environment

Authors: Ravi Kumar, Dhrubajit Barman, Nomi Baruah

Abstract:

Software Cloning has grown an active area in software engineering research community yielding numerous techniques, various tools and other methods for clone detection and removal. The copying, modifying a block of code is identified as cloning as it is the most basic means of software reuse. Agile Software Development is an approach which is currently being used in various software projects, so that it helps to respond the unpredictability of building software through incremental, iterative, work cadences. Software Cloning has been introduced to Agile Environment and many Agile Software Development approaches are using the concept of Software Cloning. This paper discusses the various Agile Software Development approaches. It also discusses the degree to which the Software Cloning concept is being introduced in the Agile Software Development approaches.

Keywords: agile environment, refactoring, reuse, software cloning

Procedia PDF Downloads 499
6680 Using Combination of Different Sets of Features of Molecules for Improved Prediction of Solubility

Authors: Muhammet Baldan, Emel Timuçin

Abstract:

Generally, absorption and bioavailability increase if solubility increases; therefore, it is crucial to predict them in drug discovery applications. Molecular descriptors and Molecular properties are traditionally used for the prediction of water solubility. There are various key descriptors that are used for this purpose, namely Drogan Descriptors, Morgan Descriptors, Maccs keys, etc., and each has different prediction capabilities with differentiating successes between different data sets. Another source for the prediction of solubility is structural features; they are commonly used for the prediction of solubility. However, there are little to no studies that combine three or more properties or descriptors for prediction to produce a more powerful prediction model. Unlike available models, we used a combination of those features in a random forest machine learning model for improved solubility prediction to better predict and, therefore, contribute to drug discovery systems.

Keywords: solubility, molecular descriptors, machine learning, random forest

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6679 GraphNPP: A Graphormer-Based Architecture for Network Performance Prediction in Software-Defined Networking

Authors: Hanlin Liu, Hua Li, Yintan AI

Abstract:

Network performance prediction (NPP) is essential for the management and optimization of software-defined networking (SDN) and contributes to improving the quality of service (QoS) in SDN to meet the requirements of users. Although current deep learning-based methods can achieve high effectiveness, they still suffer from some problems, such as difficulty in capturing global information of the network, inefficiency in modeling end-to-end network performance, and inadequate graph feature extraction. To cope with these issues, our proposed Graphormer-based architecture for NPP leverages the powerful graph representation ability of Graphormer to effectively model the graph structure data, and a node-edge transformation algorithm is designed to transfer the feature extraction object from nodes to edges, thereby effectively extracting the end-to-end performance characteristics of the network. Moreover, routing oriented centrality measure coefficient for nodes and edges is proposed respectively to assess their importance and influence within the graph. Based on this coefficient, an enhanced feature extraction method and an advanced centrality encoding strategy are derived to fully extract the structural information of the graph. Experimental results on three public datasets demonstrate that the proposed GraphNPP architecture can achieve state-of-the-art results compared to current NPP methods.

Keywords: software-defined networking, network performance prediction, Graphormer, graph neural network

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6678 Jurrasic Deposit Ichnofossil Study of Cores from Bintuni Basin, Eastern Indonesia

Authors: Aswan Aswan

Abstract:

Ichnofossils were examined based on two wells cores of Jurassic sediment from Bintuni Basin, West Papua, Indonesia. The cores are the Jurassic interval and known as the potential reservoir interval in this area. Representative of 18 ichnogenera was recorded including forms assigned to Arenicolites, Asterosoma, Bergaueria, Chondrites, cryptic bioturbation, Glossifungites, Lockeia, Ophiomorpha, Palaeophycus, Phycosiphon, Planolites, Rhizocorallium, Rosselia, root structure, Skolithos, Teichicnus, Thalassinoides, and Zoophycos. The two cores represent a depositional system that is dominated by tidal flat, shallow marine shelf continuum possibly crossed by estuaries or tidal shoals channels. From the first core identified two deepening cycles. The shallow one is a shallow marine with tidal influence while the deeper one attached to the shelf. Shallow interval usually indicates by appearances of Ophiomorpha and Glossifungites while the deeper shallow marine interval signs by the abundance of Phycosiphon. The second core reveals eight deepening cycles.

Keywords: ichnofossil, Jurassic, sediment, reservoir, Bintuni, Indonesia, West Papua

Procedia PDF Downloads 341
6677 On Improving Breast Cancer Prediction Using GRNN-CP

Authors: Kefaya Qaddoum

Abstract:

The aim of this study is to predict breast cancer and to construct a supportive model that will stimulate a more reliable prediction as a factor that is fundamental for public health. In this study, we utilize general regression neural networks (GRNN) to replace the normal predictions with prediction periods to achieve a reasonable percentage of confidence. The mechanism employed here utilises a machine learning system called conformal prediction (CP), in order to assign consistent confidence measures to predictions, which are combined with GRNN. We apply the resulting algorithm to the problem of breast cancer diagnosis. The results show that the prediction constructed by this method is reasonable and could be useful in practice.

Keywords: neural network, conformal prediction, cancer classification, regression

Procedia PDF Downloads 255
6676 Software Engineering Revolution Driven by Complexity Science

Authors: Jay Xiong, Li Lin

Abstract:

This paper introduces a new software engineering paradigm based on complexity science, called NSE (Nonlinear Software Engineering paradigm). The purpose of establishing NSE is to help software development organizations double their productivity, half their cost, and increase the quality of their products in several orders of magnitude simultaneously. NSE complies with the essential principles of complexity science. NSE brings revolutionary changes to almost all aspects in software engineering. NSE has been fully implemented with its support platform Panorama++.

Keywords: complexity science, software development, software engineering, software maintenance

Procedia PDF Downloads 240
6675 Software Architectural Design Ontology

Authors: Muhammad Irfan Marwat, Sadaqat Jan, Syed Zafar Ali Shah

Abstract:

Software architecture plays a key role in software development but absence of formal description of software architecture causes different impede in software development. To cope with these difficulties, ontology has been used as artifact. This paper proposes ontology for software architectural design based on IEEE model for architecture description and Kruchten 4+1 model for viewpoints classification. For categorization of style and views, ISO/IEC 42010 has been used. Corpus method has been used to evaluate ontology. The main aim of the proposed ontology is to classify and locate software architectural design information.

Keywords: semantic-based software architecture, software architecture, ontology, software engineering

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6674 The Cardiac Diagnostic Prediction Applied to a Designed Holter

Authors: Leonardo Juan Ramírez López, Javier Oswaldo Rodriguez Velasquez

Abstract:

We have designed a Holter that measures the heart´s activity for over 24 hours, implemented a prediction methodology, and generate alarms as well as indicators to patients and treating physicians. Various diagnostic advances have been developed in clinical cardiology thanks to Holter implementation; however, their interpretation has largely been conditioned to clinical analysis and measurements adjusted to diverse population characteristics, thus turning it into a subjective examination. This, however, requires vast population studies to be validated that, in turn, have not achieved the ultimate goal: mortality prediction. Given this context, our Insight Research Group developed a mathematical methodology that assesses cardiac dynamics through entropy and probability, creating a numerical and geometrical attractor which allows quantifying the normalcy of chronic and acute disease as well as the evolution between such states, and our Tigum Research Group developed a holter device with 12 channels and advanced computer software. This has been shown in different contexts with 100% sensitivity and specificity results.

Keywords: attractor , cardiac, entropy, holter, mathematical , prediction

Procedia PDF Downloads 136
6673 Audit of Intraoperative Ventilation Strategy in Prolonged Abdominal Surgery

Authors: Prabir Patel, Eugene Ming Han Lim

Abstract:

Introduction: Current literature shows that postoperative pulmonary complications following abdominal surgery may be reduced by using lower than conventional tidal volumes intraoperatively together with moderate levels of positive end expiratory pressure (PEEP). The recent studies demonstrated significant reduction demonstrated significant reduction in major complications in elective abdominal surgery through the use of lower tidal volumes (6-8 ml/kg predicted body weight), PEEP of 5 cmH20 and recruitment manoeuvres compared to higher ‘conventional’ volumes (10-12 mls/kg PBW) without lung recruitment. Our objective was to retrospectively audit current practice for patients undergoing major abdominal surgery in Sir Charles Gairdner Hospital. Methods: Patients over 18 undergoing elective general surgery lasting more than 3 hours and intubated during the duration of procedure were included in this audit. Data was collected over a 6 month period. Patients who had hepatic surgery, procedures necessitating one-lung ventilation, transplant surgery, documented history of pulmonary or intracranial hypertension were excluded. Results: 58 suitable patients were identified and notes were available for 54 patients. Key findings: Average peak airway pressure was 21cmH20 (+4), average peak airway pressure was less than 30 cmH20 in all patients, and less than 25 cmH20 in 80% of the cases. PEEP was used in 81% of the cases. Where PEEP was used, 75% used PEEP more than or equal to 5 cmH20. Average tidal volume per actual body weight was 7.1 ml/kg (+1.6). Average tidal volume per predicted body weight (PBW) was 8.8 ml/kg (+1.5). Average tidal volume was less than 10 ml/kg PBW in 90% of cases; 6-8 ml/kg PBW in 40% of the cases. There was no recorded use of recruitment manoeuvres in any cases. Conclusions: In the vast majority of patients undergoing prolonged abdominal surgery, a lung protective strategy using moderate levels of PEEP, peak airway pressures of less than 30 cmH20 and tidal volumes of less than 10 cmH20/kg PBW was utilised. A recent randomised control trial demonstrated benefit from utilising even lower volumes (6-8 mls/kg) based on findings in critical care patients, but this was compared to volumes of 10-12 ml/kg. Volumes of 6-8 ml/kg PBW were utilised in 40% of cases in this audit. Although theoretically beneficial, clinical benefit of lower volumes than what is currently practiced in this institution remains to be seen. The incidence of pulmonary complications was much lower than in the other cited studies and a larger data set would be required to investigate any benefit from lower tidal volume ventilation. The volumes used are comparable to results from published local and international data but PEEP utilisation was higher in this audit. Strategies that may potentially be implemented to ensure and maintain best practice include pre-operative recording of predicted body weight, adjustment of default ventilator settings and education/updates of current evidence.

Keywords: anaesthesia, intraoperative ventilation, PEEP, tidal volume

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6672 Influence of Security Attributes in Component-Based Software Development

Authors: Somayeh Zeinali

Abstract:

A component is generally defined as a piece of executable software with a published interface. Component-based software engineering (CBSE) has become recognized as a new sub-discipline of software engineering. In the component-based software development, components cannot be completely secure and thus easily become vulnerable. Some researchers have investigated this issue and proposed approaches to detect component intrusions or protect distributed components. Software security also refers to the process of creating software that is considered secure.The terms “dependability”, “trustworthiness”, and “survivability” are used interchangeably to describe the properties of software security.

Keywords: component-based software development, component-based software engineering , software security attributes, dependability, component

Procedia PDF Downloads 518
6671 Analysis on Prediction Models of TBM Performance and Selection of Optimal Input Parameters

Authors: Hang Lo Lee, Ki Il Song, Hee Hwan Ryu

Abstract:

An accurate prediction of TBM(Tunnel Boring Machine) performance is very difficult for reliable estimation of the construction period and cost in preconstruction stage. For this purpose, the aim of this study is to analyze the evaluation process of various prediction models published since 2000 for TBM performance, and to select the optimal input parameters for the prediction model. A classification system of TBM performance prediction model and applied methodology are proposed in this research. Input and output parameters applied for prediction models are also represented. Based on these results, a statistical analysis is performed using the collected data from shield TBM tunnel in South Korea. By performing a simple regression and residual analysis utilizinFg statistical program, R, the optimal input parameters are selected. These results are expected to be used for development of prediction model of TBM performance.

Keywords: TBM performance prediction model, classification system, simple regression analysis, residual analysis, optimal input parameters

Procedia PDF Downloads 278
6670 A 'Four Method Framework' for Fighting Software Architecture Erosion

Authors: Sundus Ayyaz, Saad Rehman, Usman Qamar

Abstract:

Software Architecture is the basic structure of software that states the development and advancement of a software system. Software architecture is also considered as a significant tool for the construction of high quality software systems. A clean design leads to the control, value and beauty of software resulting in its longer life while a bad design is the cause of architectural erosion where a software evolution completely fails. This paper discusses the occurrence of software architecture erosion and presents a set of methods for the detection, declaration and prevention of architecture erosion. The causes and symptoms of architecture erosion are observed with the examples of prescriptive and descriptive architectures and the practices used to stop this erosion are also discussed by considering different types of software erosion and their affects. Consequently finding and devising the most suitable approach for fighting software architecture erosion and in some way reducing its affect is evaluated and tested on different scenarios.

Keywords: software architecture, architecture erosion, prescriptive architecture, descriptive architecture

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6669 Diesel Fault Prediction Based on Optimized Gray Neural Network

Authors: Han Bing, Yin Zhenjie

Abstract:

In order to analyze the status of a diesel engine, as well as conduct fault prediction, a new prediction model based on a gray system is proposed in this paper, which takes advantage of the neural network and the genetic algorithm. The proposed GBPGA prediction model builds on the GM (1.5) model and uses a neural network, which is optimized by a genetic algorithm to construct the error compensator. We verify our proposed model on the diesel faulty simulation data and the experimental results show that GBPGA has the potential to employ fault prediction on diesel.

Keywords: fault prediction, neural network, GM(1, 5) genetic algorithm, GBPGA

Procedia PDF Downloads 273
6668 A Promising Thrombolytic and Anticoagulant Serine Protease Purified from Lug Worms Inhabiting Tidal Flats

Authors: Hye Jin Kim, Hwa Sung Shin

Abstract:

Ischemic stroke means the caused brain damage due to neurological defects, occurring occlusion of cerebral vascular resulting in thrombus or embolism. t-PA (tissue Plasminogen Activator) is the only thrombolytic agent passed the FDA (Food and Drug Administration). However, t-PA directly dissolves the thrombus (direct activity) through fibrinolysis, showing side effects such as re-occlusion. In this study, we evaluated the thrombolytic activities of the serine protease extracted from lugworms inhabiting tidal flats. The new serine protease identified as 38 kDa by SDS-PAGE was not toxic to brain endothelial cells line (hCMEC/D3). Also, the plasmin synthesis inhibition activity (indirect activity) of the new serine protease was confirmed through fibrin zymography assay and fibrin plate assay. It was higher than direct activity as compared to u-PA (urokinase Plasminogen Activator). The activities were found to be maintained at a wide range of temperature (4-70 ℃) and pH 7-10 compared to previous thrombolytic agents from the azocasein assay. In addition, the new serine protease has shown anticoagulant activity from fibrinogenolytic activity assay. In conclusion, the serine protease in lug worms inhabiting the tidal flats could be considered a promising thrombolytic candidate for the treatment of ischemic stroke.

Keywords: alkaline serine protease, bifunctional thrombolytic activity, fibrinolytic activity, ischemic stroke, lug worms

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6667 Resistance to Chloride Penetration of High Strength Self-Compacting Concretes: Pumice and Zeolite Effect

Authors: Kianoosh Samimi, Siham Kamali-Bernard, Ali Akbar Maghsoudi

Abstract:

This paper aims to contribute to the characterization and the understanding of fresh state, compressive strength and chloride penetration tendency of high strength self-compacting concretes (HSSCCs) where Portland cement type II is partially substituted by 10% and 15% of natural pumice and zeolite. First, five concrete mixtures with a control mixture without any pozzolan are prepared and tested in both fresh and hardened states. Then, resistance to chloride penetration for all formulation is investigated in non-steady state and steady state by measurement of chloride penetration and diffusion coefficient. In non-steady state, the correlation between initial current and chloride penetration with diffusion coefficient is studied. Moreover, the relationship between diffusion coefficient in non-steady state and electrical resistivity is determined. The concentration of free chloride ions is also measured in steady state. Finally, chloride penetration for all formulation is studied in immersion and tidal condition. The result shows that, the resistance to chloride penetration for HSSCC in immersion and tidal condition increases by incorporating pumice and zeolite. However, concrete with zeolite displays a better resistance. This paper shows that the HSSCC with 15% pumice and 10% zeolite is suitable in fresh, hardened, and durability characteristics.

Keywords: Chloride penetration, immersion, pumice, HSSCC, tidal, zeolite

Procedia PDF Downloads 216
6666 Dry Relaxation Shrinkage Prediction of Bordeaux Fiber Using a Feed Forward Neural

Authors: Baeza S. Roberto

Abstract:

The knitted fabric suffers a deformation in its dimensions due to stretching and tension factors, transverse and longitudinal respectively, during the process in rectilinear knitting machines so it performs a dry relaxation shrinkage procedure and thermal action of prefixed to obtain stable conditions in the knitting. This paper presents a dry relaxation shrinkage prediction of Bordeaux fiber using a feed forward neural network and linear regression models. Six operational alternatives of shrinkage were predicted. A comparison of the results was performed finding neural network models with higher levels of explanation of the variability and prediction. The presence of different reposes are included. The models were obtained through a neural toolbox of Matlab and Minitab software with real data in a knitting company of Southern Guanajuato. The results allow predicting dry relaxation shrinkage of each alternative operation.

Keywords: neural network, dry relaxation, knitting, linear regression

Procedia PDF Downloads 550
6665 A Prediction Model of Adopting IPTV

Authors: Jeonghwan Jeon

Abstract:

With the advent of IPTV in the fierce competition with existing broadcasting system, it is emerged as an important issue to predict how much the adoption of IPTV service will be. This paper aims to suggest a prediction model for adopting IPTV using classification and Ranking Belief Simplex (CaRBS). A simplex plot method of representing data allows a clear visual representation to the degree of interaction of the support from the variables to the prediction of the objects. CaRBS is applied to the survey data on the IPTV adoption.

Keywords: prediction, adoption, IPTV, CaRBS

Procedia PDF Downloads 388
6664 Comparison of the Distillation Curve Obtained Experimentally with the Curve Extrapolated by a Commercial Simulator

Authors: Lívia B. Meirelles, Erika C. A. N. Chrisman, Flávia B. de Andrade, Lilian C. M. de Oliveira

Abstract:

True Boiling Point distillation (TBP) is one of the most common experimental techniques for the determination of petroleum properties. This curve provides information about the performance of petroleum in terms of its cuts. The experiment is performed in a few days. Techniques are used to determine the properties faster with a software that calculates the distillation curve when a little information about crude oil is known. In order to evaluate the accuracy of distillation curve prediction, eight points of the TBP curve and specific gravity curve (348 K and 523 K) were inserted into the HYSYS Oil Manager, and the extended curve was evaluated up to 748 K. The methods were able to predict the curve with the accuracy of 0.6%-9.2% error (Software X ASTM), 0.2%-5.1% error (Software X Spaltrohr).

Keywords: distillation curve, petroleum distillation, simulation, true boiling point curve

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6663 Enhanced Extra Trees Classifier for Epileptic Seizure Prediction

Authors: Maurice Ntahobari, Levin Kuhlmann, Mario Boley, Zhinoos Razavi Hesabi

Abstract:

For machine learning based epileptic seizure prediction, it is important for the model to be implemented in small implantable or wearable devices that can be used to monitor epilepsy patients; however, current state-of-the-art methods are complex and computationally intensive. We use Shapley Additive Explanation (SHAP) to find relevant intracranial electroencephalogram (iEEG) features and improve the computational efficiency of a state-of-the-art seizure prediction method based on the extra trees classifier while maintaining prediction performance. Results for a small contest dataset and a much larger dataset with continuous recordings of up to 3 years per patient from 15 patients yield better than chance prediction performance (p < 0.004). Moreover, while the performance of the SHAP-based model is comparable to that of the benchmark, the overall training and prediction time of the model has been reduced by a factor of 1.83. It can also be noted that the feature called zero crossing value is the best EEG feature for seizure prediction. These results suggest state-of-the-art seizure prediction performance can be achieved using efficient methods based on optimal feature selection.

Keywords: machine learning, seizure prediction, extra tree classifier, SHAP, epilepsy

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6662 Comparison of Tidalites in Siliciclastics and Mixed Siliciclastic Carbonate Systems: An Outstanding Example from Proterozoic Simla Basin, Western Lesser Himalaya, India

Authors: Tithi Banerjee, Ananya Mukhopadhyay

Abstract:

The comparison of ancient tidalites recorded in both siliciclastics and carbonates has not been well documented due to a lack of suitable outcropping examples. The Proterozoic Simla Basin, Lesser Himalaya serves a unique example in this regard. An attempt has been made in the present work to differentiate sedimentary facies and architectural elements of tidalites in both siliciclastics and carbonates recorded in the Simla Basin. Lithofacies and microfacies analysis led to identification of 11 lithofacies and 4 architectural elements from the siliciclastics, 6 lithofacies and 3 architectural elements from the carbonates. The most diagnostic features for comparison of the two tidalite systems are sedimentary structures, textures, and architectural elements. The physical features such as flaser-lnticular bedding, mud/silt couplets, tidal rhythmites, tidal bundles, cross stratified successions, tidal bars, tidal channels, microbial structures are common to both the environments. The architecture of these tidalites attests to sedimentation in shallow subtidal to intertidal flat facies, affected by intermittent reworking by open marine waves/storms. The seventeen facies attributes were categorized into two major facies belts (FA1 and FA2). FA1 delineated from the lower part of the Chhaosa Formation (middle part of the Simla Basin) represents a prograding muddy pro-delta deposit whereas FA2 delineated from the upper part of the Basantpur Formation (lower part of the Simla Basin) bears the signature of an inner-mid carbonate ramp deposit. Facies distribution indicates development of highstand systems tract (HST) during sea level still stand related to normal regression. The aggradational to progradational bedsets record the history of slow rise in sea level.

Keywords: proterozoic, Simla Basin, tidalites, inner-mid carbonate ramp, prodelta, TST, HST

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6661 Revolutionary Solutions for Modeling and Visualization of Complex Software Systems

Authors: Jay Xiong, Li Lin

Abstract:

Existing software modeling and visualization approaches using UML are outdated, which are outcomes of reductionism and the superposition principle that the whole of a system is the sum of its parts, so that with them all tasks of software modeling and visualization are performed linearly, partially, and locally. This paper introduces revolutionary solutions for modeling and visualization of complex software systems, which make complex software systems much easy to understand, test, and maintain. The solutions are based on complexity science, offering holistic, automatic, dynamic, virtual, and executable approaches about thousand times more efficient than the traditional ones.

Keywords: complex systems, software maintenance, software modeling, software visualization

Procedia PDF Downloads 372
6660 Towards Development of a Framework for Saudi Education Software Ecosystem

Authors: Fazal-e-Amin, Abdullah S. Alghamdi, Iftikhar Ahmad

Abstract:

Software ecosystems’ concept is an inspiration from the natural ecosystem. Software ecosystems refer to large systems developed on top of a platform composed of different components developed by different entities of that ecosystem. Ecosystems improve information access, dissemination and coordination considerably. The ability to evolve and accommodate new subsystems gives a boost to the software ecosystems. In this paper, Saudi education software ecosystem is discussed and its need and potential benefits are highlighted. This work will provide a basis for further research in this area and foundation in development of Saudi education ecosystem.

Keywords: software ecosystem, education software, framework, software engineering

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6659 Analyzing the Effectiveness of Different Testing Techniques in Ensuring Software Quality

Authors: R. M. P. C. Bandara, M. L. L. Weerasinghe, K. T. C. R. Kumari, A. G. D. R. Hansika, D. I. De Silva, D. M. T. H. Dias

Abstract:

Software testing is an essential process in software development that aims to identify defects and ensure that software is functioning as intended. Various testing techniques are employed to achieve this goal, but the effectiveness of these techniques varies. This research paper analyzes the effectiveness of different testing techniques in ensuring software quality. The paper explores different testing techniques, including manual and automated testing, and evaluates their effectiveness in terms of identifying defects, reducing the number of defects in software, and ensuring that software meets its functional and non-functional requirements. Moreover, the paper will also investigate the impact of factors such as testing time, test coverage, and testing environment on the effectiveness of these techniques. This research aims to provide valuable insights into the effectiveness of different testing techniques, enabling software development teams to make informed decisions about the testing approach that is best suited to their needs. By improving testing techniques, the number of defects in software can be reduced, enhancing the quality of software and ultimately providing better software for users.

Keywords: software testing life cycle, software testing techniques, software testing strategies, effectiveness, software quality

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6658 An Improved Prediction Model of Ozone Concentration Time Series Based on Chaotic Approach

Authors: Nor Zila Abd Hamid, Mohd Salmi M. Noorani

Abstract:

This study is focused on the development of prediction models of the Ozone concentration time series. Prediction model is built based on chaotic approach. Firstly, the chaotic nature of the time series is detected by means of phase space plot and the Cao method. Then, the prediction model is built and the local linear approximation method is used for the forecasting purposes. Traditional prediction of autoregressive linear model is also built. Moreover, an improvement in local linear approximation method is also performed. Prediction models are applied to the hourly ozone time series observed at the benchmark station in Malaysia. Comparison of all models through the calculation of mean absolute error, root mean squared error and correlation coefficient shows that the one with improved prediction method is the best. Thus, chaotic approach is a good approach to be used to develop a prediction model for the Ozone concentration time series.

Keywords: chaotic approach, phase space, Cao method, local linear approximation method

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