Search results for: velocity prediction program

Authors: I. L. Kim, J. Y. Lee, A. K. Tekile

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In consequence of the very high urbanization rate of Korea, the number of traffic noise damages in areas congested with population and facilities is steadily increasing. The current environmental noise levels data in major cities of the country show that the noise levels exceed the standards set for both day and night times. This research was about comparative analysis in search for optimal soundproof panel shape and design factor that can minimize sound reflection noise. In addition to the normal flat-type panel shape, the reflection noise reduction of swelling-type, combined swelling and curved-type, and screen-type were evaluated. The noise source model Nord 2000, which often provides abundant information compared to models for the similar purpose, was used in the study to determine the overall noise level. Based on vehicle categorization in Korea, the noise levels for varying frequency from different heights of the sound source (directivity heights of Harmonize model) have been calculated for simulation. Each simulation has been made using the ray-tracing method. The noise level has also been calculated using the noise prediction program called SoundPlan 7.2, for comparison. The noise level prediction was made at 15m (R1), 30 m (R2) and at middle of the road, 2m (R3) receiving the point. By designing the noise barriers by shape and running the prediction program by inserting the noise source on the 2nd lane to the noise barrier side, among the 6 lanes considered, the reflection noise slightly decreased or increased in all noise barriers. At R1, especially in the cases of the screen-type noise barriers, there was no reduction effect predicted in all conditions. However, the swelling-type showed a decrease of 0.7~1.2 dB at R1, performing the best reduction effect among the tested noise barriers. Compared to other forms of noise barriers, the swelling-type was thought to be the most suitable for reducing the reflection noise; however, since a slight increase was predicted at R2, further research based on a more sophisticated categorization of related design factors is necessary. Moreover, as swellings are difficult to produce and the size of the modules are smaller than other panels, it is challenging to install swelling-type noise barriers. If these problems are solved, its applicable region will not be limited to other types of noise barriers. Hence, when a swelling-type noise barrier is installed at a downtown region where the amount of traffic is increasing every day, it will both secure visibility through the transparent walls and diminish any noise pollution due to the reflection. Moreover, when decorated with shapes and design, noise barriers will achieve a visual attraction than a flat-type one and thus will alleviate any psychological hardships related to noise, other than the unique physical soundproofing functions of the soundproof panels.

Keywords: reflection noise, shaped noise barriers, sound proof panel, traffic noise

Procedia PDF Downloads 507

Authors: Yanmin Zhao, Siu Ming Yiu

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To claim the ownership for an executable program is a non-trivial task. An emerging direction is to add a watermark to the program such that the watermarked program preserves the original program’s functionality and removing the watermark would heavily destroy the functionality of the watermarked program. In this paper, the first watermarking signature scheme with the watermark and the constraint function hidden in the symmetric key setting is constructed. The scheme uses well-known techniques of lattice trapdoors and a lattice evaluation. The watermarking signature scheme is unforgeable under the Short Integer Solution (SIS) assumption and satisfies other security requirements such as the unremovability security property.

Keywords: short integer solution (SIS) problem, symmetric-key setting, watermarking schemes, watermarked signatures

Procedia PDF Downloads 132

Authors: Kwanmuang Kaeodumkoeng, Jumnian Junhasobhaga

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This action research on the happy workplace program (HWP) promoting health literate workplace (HLW) in Thai Garment Industry Companies aimed to categorize activities promoting HLW and results of HWP in the Thai garment industry. Thirteen program reports purposely selected from sampled companies. Data were analyzed using descriptive statistics, paired t-test and content analysis. The results showed that the end of the program, the significant higher levels of work skills, life skills, and factors promoting happy workplace were found compared to before the program in all 13 companies. The activities and results of the HWP could be categorized in five steps of implementing an HWP, compared with the attributes of HLW were composed of 1) Leadership promotion; 2) Preparing workforce; 3) Planning, evaluating, and improving; 4) Communicating effectively; and 5) Designing easy to use materials and ensuring easy access.

Keywords: happy workplace program, health literate workplace, garment industry, indicators

Procedia PDF Downloads 235

Authors: Ivonne Tshuma, Ralf Cord-Ruwisch, Wendell Ela

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Water crisis is a world-wide problem because of population growth and climate change. Hence, desalination is a solution to water scarcity, which threatens the world. Reverse osmosis (RO) is the most used technique for desalination; unfortunately, this process, usually requires high-pressure requirement hence requires a lot of energy about 3 – 5.5 KWhr/m³ of electrical energy. The pressure requirements of RO can be alleviated by the use of PRO (pressure retarded osmosis) to drive the RO process. This paper proposes a process of utilizing the energy directly from PRO to drive an RO process. The paper mostly analyses the PRO process parameters such as cross-flow velocity, density, and buoyancy and how these have an effect on PRO hence ultimately the RO process. The experimental study of the PRO with various feed solution concentrations and cross-flow velocities at fixed applied pressure with different orientations of the PRO cell was performed. The study revealed that without cross-flow velocity, buoyancy effects were observed but not with cross-flow velocity.

Keywords: cross-flow velocity, pressure retarded osmosis, density, buoyancy

Procedia PDF Downloads 136

Authors: Asmir Gogic, Aljo Mujcic, Sandra Ibric, Nermin Suljanovic

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Ubiquity of natural disasters during last few decades have risen serious questions towards the prediction of such events and human safety. Every disaster regardless its proportion has a precursor which is manifested as a disruption of some environmental parameter such as temperature, humidity, pressure, vibrations and etc. In order to anticipate and monitor those changes, in this paper we propose an overall system for disaster prediction and monitoring, based on wireless sensor network (WSN). Furthermore, we introduce a modified and simplified WSN routing protocol built on the top of the trickle routing algorithm. Routing algorithm was deployed using the bluetooth low energy protocol in order to achieve low power consumption. Performance of the WSN network was analyzed using a real life system implementation. Estimates of the WSN parameters such as battery life time, network size and packet delay are determined. Based on the performance of the WSN network, proposed system can be utilized for disaster monitoring and prediction due to its low power profile and mesh routing feature.

Keywords: bluetooth low energy, disaster prediction, mesh routing protocols, wireless sensor networks

Procedia PDF Downloads 385

Authors: K. Jagannath, Akhilesh Kotian, S. S. Sharma, Achutha Kini U., P. R. Prabhu

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Boiling process is characterized by the rapid formation of vapour bubbles at the solid–liquid interface (nucleate boiling) with pre-existing vapour or gas pockets. Computational fluid dynamics (CFD) is an important tool to study bubble dynamics. In the present study, CFD simulation has been carried out to determine the bubble detachment diameter and its terminal velocity. Volume of fluid method is used to model the bubble and the surrounding by solving single set of momentum equations and tracking the volume fraction of each of the fluids throughout the domain. In the simulation, bubble is generated by allowing water-vapour to enter a cylinder filled with liquid water through an inlet at the bottom. After the bubble is fully formed, the bubble detaches from the surface and rises up during which the bubble accelerates due to the net balance between buoyancy force and viscous drag. Finally when these forces exactly balance each other, it attains a constant terminal velocity. The bubble detachment diameter and the terminal velocity of the bubble are captured by the monitor function provided in FLUENT. The detachment diameter and the terminal velocity obtained is compared with the established results based on the shape of the bubble. A good agreement is obtained between the results obtained from simulation and the equations in comparison with the established results.

Keywords: bubble growth, computational fluid dynamics, detachment diameter, terminal velocity

Procedia PDF Downloads 384

Authors: Emad Amar, Tawfik Khattab, Fatma Zada

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Predicting earthquakes is an important issue in the study of geography. Accurate prediction of earthquakes can help people to take effective measures to minimize the loss of personal and economic damage, such as large casualties, destruction of buildings and broken of traffic, occurred within a few seconds. United States Geological Survey (USGS) science organization provides reliable scientific information of Earthquake Existed throughout history & Preliminary database from the National Center Earthquake Information (NEIC) show some useful factors to predict an earthquake in a seismic area like Aleutian Arc in the U.S. state of Alaska. The main advantage of this prediction method that it does not require any assumption, it makes prediction according to the future evolution of object's time series. The article compares between simulation data result from trained BP and RBF neural network versus actual output result from the system calculations. Therefore, this article focuses on analysis of data relating to real earthquakes. Evaluation results show better accuracy and higher speed by using radial basis functions (RBF) neural network.

Keywords: BP neural network, prediction, RBF neural network, earthquake

Procedia PDF Downloads 495

Authors: R. Sri Karthi Krishna, A. Saravana Kumar, Kesava Brahmaji, V. S. Vinoj

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The lunar surface may contain rough and non-uniform terrain with dips and peaks. Soft-landing is a method of landing the lander on the lunar surface without any damage to the vehicle. This project focuses on finding a safe landing site for the vehicle by developing a method for the lateral velocity determination of the lunar lander. This is done by processing the real time images obtained by means of an on-board vision sensor. The hazard avoidance phase of the soft-landing starts when the vehicle is about 200 m above the lunar surface. Here, the lander has a very low velocity of about 10 cm/s:vertical and 5 m/s:horizontal. On the detection of a hazard the lander is navigated by controlling the vertical and lateral velocity. In order to find an appropriate landing site and to accordingly navigate, the lander image processing is performed continuously. The images are taken continuously until the landing site is determined, and the lander safely lands on the lunar surface. By integrating this vision-based navigation with the INS a better accuracy for the soft-landing of the lunar lander can be obtained.

Keywords: vision aided INS, image processing, lateral velocity estimation, materials engineering

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Authors: Azzedine Hamza, Chouaib Chakour, Messaoud Ramdani

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Energy demand prediction plays a crucial role in achieving next-generation power systems for agricultural greenhouses. As a result, high prediction quality is required for efficient smart grid management and therefore low-cost energy consumption. The aim of this paper is to investigate the effectiveness of a hybrid data-driven model in day-ahead energy demand prediction. The proposed model consists of Discrete Wavelet Transform (DWT), and Adaptive Neuro-Fuzzy Inference System (ANFIS). The DWT is employed to decompose the original signal in a set of subseries and then an ANFIS is used to generate the forecast for each subseries. The proposed hybrid method (DWT-ANFIS) was evaluated using a greenhouse energy demand data for a week and compared with ANFIS. The performances of the different models were evaluated by comparing the corresponding values of Mean Absolute Percentage Error (MAPE). It was demonstrated that discret wavelet transform can improve agricultural greenhouse energy demand modeling.

Keywords: wavelet transform, ANFIS, energy consumption prediction, greenhouse

Procedia PDF Downloads 87

Authors: Xuyang Song, Jun Yin

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The smart card has been an extremely universal tool in public transit. It collects a large amount of data on buses, urban railway transit, and ferries and provides possibilities for passenger profiling. This paper combines offline analysis of passenger profiling and real-time prediction to propose a method that can accurately predict the destination station in real-time when passengers tag on. Firstly, this article constructs a static database of user travel characteristics after identifying passenger travel patterns based on the Density-Based Spatial Clustering of Applications with Noise (DBSCAN). The dual travel passenger habits are identified: OD travel habits and D station travel habits. Then a rapid real-time prediction algorithm based on Transit Passenger Profiling is proposed, which can predict the destination of in-board passengers. This article combines offline learning with online prediction, providing a technical foundation for real-time passenger flow prediction, monitoring and simulation, and short-term passenger behavior and demand prediction. This technology facilitates the efficient and real-time acquisition of passengers' travel destinations and demand. The last, an actual case was simulated and demonstrated feasibility and efficiency.

Keywords: travel behavior, destination prediction, public transit, passenger profiling

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Authors: M. D. Haneef, R. B. Randall, Z. Peng

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Journal bearings used in IC engines are prone to premature failures and are likely to fail earlier than the rated life due to highly impulsive and unstable operating conditions and frequent starts/stops. Vibration signature extraction and wear debris analysis techniques are prevalent in the industry for condition monitoring of rotary machinery. However, both techniques involve a great deal of technical expertise, time and cost. Limited literature is available on the application of these techniques for fault detection in reciprocating machinery, due to the complex nature of impact forces that confounds the extraction of fault signals for vibration based analysis and wear prediction. This work is an extension of a previous study, in which an engine simulation model was developed using a MATLAB/SIMULINK program, whereby the engine parameters used in the simulation were obtained experimentally from a Toyota 3SFE 2.0 litre petrol engines. Simulated hydrodynamic bearing forces were used to estimate vibrations signals and envelope analysis was carried out to analyze the effect of speed, load and clearance on the vibration response. Three different loads 50/80/110 N-m, three different speeds 1500/2000/3000 rpm, and three different clearances, i.e., normal, 2 times and 4 times the normal clearance were simulated to examine the effect of wear on bearing forces. The magnitude of the squared envelope of the generated vibration signals though not affected by load, but was observed to rise significantly with increasing speed and clearance indicating the likelihood of augmented wear. In the present study, the simulation model was extended further to investigate the bearing wear behavior, resulting as a consequence of different operating conditions, to complement the vibration analysis. In the current simulation, the dynamics of the engine was established first, based on which the hydrodynamic journal bearing forces were evaluated by numerical solution of the Reynold’s equation. Also, the essential outputs of interest in this study, critical to determine wear rates are the tangential velocity and oil film thickness between the journal and bearing sleeve, which if not maintained appropriately, have a detrimental effect on the bearing performance. Archard’s wear prediction model was used in the simulation to calculate the wear rate of bearings with specific location information as all determinative parameters were obtained with reference to crank rotation. Oil film thickness obtained from the model was used as a criterion to determine if the lubrication is sufficient to prevent contact between the journal and bearing thus causing accelerated wear. A limiting value of 1 µm was used as the minimum oil film thickness needed to prevent contact. The increased wear rate with growing severity of operating conditions is analogous and comparable to the rise in amplitude of the squared envelope of the referenced vibration signals. Thus on one hand, the developed model demonstrated its capability to explain wear behavior and on the other hand it also helps to establish a correlation between wear based and vibration based analysis. Therefore, the model provides a cost-effective and quick approach to predict the impending wear in IC engine bearings under various operating conditions.

Keywords: condition monitoring, IC engine, journal bearings, vibration analysis, wear prediction

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Authors: Yiannis G. Smirlis

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The classification and the prediction of efficiencies in Data Envelopment Analysis (DEA) is an important issue, especially in large scale problems or when new units frequently enter the under-assessment set. In this paper, we contribute to the subject by proposing a grid structure based on interval segmentations of the range of values for the inputs and outputs. Such intervals combined, define hyper-rectangles that partition the space of the problem. This structure, exploited by Interval DEA models and a dominance relation, acts as a DEA pre-processor, enabling the classification and prediction of efficiency scores, without applying any DEA models.

Keywords: data envelopment analysis, interval DEA, efficiency classification, efficiency prediction

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Authors: Ali Ateş, Ansar B. Mwimbo, Ali H. Abdulkarim

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General transport equation has a wide range of application in Fluid Mechanics and Heat Transfer problems. In this equation, generally when φ variable which represents a flow property is used to represent fluid velocity component, general transport equation turns into momentum equations or with its well known name Navier-Stokes equations. In these non-linear differential equations instead of seeking for analytic solutions, preferring numerical solutions is a more frequently used procedure. Finite difference method is a commonly used numerical solution method. In these equations using velocity and pressure gradients instead of stress tensors decreases the number of unknowns. Also, continuity equation, by integrating the system, number of equations is obtained as number of unknowns. In this situation, velocity and pressure components emerge as two important parameters. In the solution of differential equation system, velocities and pressures must be solved together. However, in the considered grid system, when pressure and velocity values are jointly solved for the same nodal points some problems confront us. To overcome this problem, using staggered grid system is a referred solution method. For the computerized solutions of the staggered grid system various algorithms were developed. From these, two most commonly used are SIMPLE and SIMPLER algorithms. In this study Navier-Stokes equations were numerically solved for Newtonian flow, whose mass or gravitational forces were neglected, for incompressible and laminar fluid, as a hydro dynamically fully developed region and in two dimensional cartesian coordinate system. Finite difference method was chosen as the solution method. This is a parametric study in which varying values of velocity components, pressure and Reynolds numbers were used. Differential equations were discritized using central difference and hybrid scheme. The discritized equation system was solved by Gauss-Siedel iteration method. SIMPLE and SIMPLER were used as solution algorithms. The obtained results, were compared for central difference and hybrid as discritization methods. Also, as solution algorithm, SIMPLE algorithm and SIMPLER algorithm were compared to each other. As a result, it was observed that hybrid discritization method gave better results over a larger area. Furthermore, as computer solution algorithm, besides some disadvantages, it can be said that SIMPLER algorithm is more practical and gave result in short time. For this study, a code was developed in DELPHI programming language. The values obtained in a computer program were converted into graphs and discussed. During sketching, the quality of the graph was increased by adding intermediate values to the obtained result values using Lagrange interpolation formula. For the solution of the system, number of grid and node was found as an estimated. At the same time, to indicate that the obtained results are satisfactory enough, by doing independent analysis from the grid (GCI analysis) for coarse, medium and fine grid system solution domain was obtained. It was observed that when graphs and program outputs were compared with similar studies highly satisfactory results were achieved.

Keywords: finite difference method, GCI analysis, numerical solution of the Navier-Stokes equations, SIMPLE and SIMPLER algoritms

Procedia PDF Downloads 388

Authors: Dhouibi Mohamed, Stirbu Bogdan, Chabotier André, Pirlot Marc

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Effects of erosion and wear on the performance of small caliber guns have been analyzed throughout numerical and experimental studies. Mainly, qualitative observations were performed. Correlations between the volume change of the chamber and the maximum pressure are limited. This paper focuses on the development of a numerical model to predict the maximum pressure evolution when the interior shape of the chamber changes in the different weapon’s life phases. To fulfill this goal, an experimental campaign, followed by a numerical simulation study, is carried out. Two test barrels, « 5.56x45mm NATO » and « 7.62x51mm NATO,» are considered. First, a Coordinate Measuring Machine (CMM) with a contact scanning probe is used to measure the interior profile of the barrels after each 300-shots cycle until their worn out. Simultaneously, the EPVAT (Electronic Pressure Velocity and Action Time) method with a special WEIBEL radar are used to measure: (i) the chamber pressure, (ii) the action time, (iii) and the bullet velocity in each barrel. Second, a numerical simulation study is carried out. Thus, a coupled interior ballistic model is developed using the dynamic finite element program LS-DYNA. In this work, two different models are elaborated: (i) coupled Eularien Lagrangian method using fluid-structure interaction (FSI) techniques and a coupled thermo-mechanical finite element using a lumped parameter model (LPM) as a subroutine. Those numerical models are validated and checked through three experimental results, such as (i) the muzzle velocity, (ii) the chamber pressure, and (iii) the surface morphology of fired projectiles. Results show a good agreement between experiments and numerical simulations. Next, a comparison between the two models is conducted. The projectile motions, the dynamic engraving resistances and the maximum pressures are compared and analyzed. Finally, using this obtained database, a statistical correlation between the muzzle velocity, the maximum pressure and the chamber volume is established.

Keywords: engraving process, finite element analysis, gun barrel erosion, interior ballistics, statistical correlation

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Authors: Jamerson Felipe Pereira Lima, Jeane Cecília Bezerra de Melo

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The difficulty and cost related to obtaining of protein tertiary structure information through experimental methods, such as X-ray crystallography or NMR spectroscopy, helped raising the development of computational methods to do so. An approach used in these last is prediction of tridimensional structure based in the residue chain, however, this has been proved an NP-hard problem, due to the complexity of this process, explained by the Levinthal paradox. An alternative solution is the prediction of intermediary structures, such as the secondary structure of the protein. Artificial Intelligence methods, such as Bayesian statistics, artificial neural networks (ANN), support vector machines (SVM), among others, were used to predict protein secondary structure. Due to its good results, artificial neural networks have been used as a standard method to predict protein secondary structure. Recent published methods that use this technique, in general, achieved a Q3 accuracy between 75% and 83%, whereas the theoretical accuracy limit for protein prediction is 88%. Alternatively, to achieve better results, support vector machines prediction methods have been developed. The statistical evaluation of methods that use different AI techniques, such as ANNs and SVMs, for example, is not a trivial problem, since different training sets, validation techniques, as well as other variables can influence the behavior of a prediction method. In this study, we propose a prediction method based on artificial neural networks, which is then compared with a selected SVM method. The chosen SVM protein secondary structure prediction method is the one proposed by Huang in his work Extracting Physico chemical Features to Predict Protein Secondary Structure (2013). The developed ANN method has the same training and testing process that was used by Huang to validate his method, which comprises the use of the CB513 protein data set and three-fold cross-validation, so that the comparative analysis of the results can be made comparing directly the statistical results of each method.

Keywords: artificial neural networks, protein secondary structure, protein structure prediction, support vector machines

Procedia PDF Downloads 619

Authors: Marcio Freire Cruz, Naoaki Ono, Shigehiko Kanaya, Carlos Arthur Mattos Teixeira Cavalcante

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The systems that record patient care information, known as Electronic Medical Record (EMR) and those that monitor vital signs of patients, such as heart rate, body temperature, and blood pressure have been extremely valuable for the effectiveness of the patient’s treatment. Several kinds of research have been using data from EMRs and vital signs of patients to predict illnesses. Among them, we highlight those that intend to predict, classify, or, at least identify patterns, of sepsis illness in patients under vital signs monitoring. Sepsis is an organic dysfunction caused by a dysregulated patient's response to an infection that affects millions of people worldwide. Early detection of sepsis is expected to provide a significant improvement in its treatment. Preceding works usually combined medical, statistical, mathematical and computational models to develop detection methods for early prediction, getting higher accuracies, and using the smallest number of variables. Among other techniques, we could find researches using survival analysis, specialist systems, machine learning and deep learning that reached great results. In our research, patients are modeled as points moving each hour in an n-dimensional space where n is the number of vital signs (variables). These points can reach a sepsis target point after some time. For now, the sepsis target point was calculated using the median of all patients’ variables on the sepsis onset. From these points, we calculate for each hour the position vector, the first derivative (velocity vector) and the second derivative (acceleration vector) of the variables to evaluate their behavior. And we construct a prediction model based on a Long Short-Term Memory (LSTM) Network, including these derivatives as explanatory variables. The accuracy of the prediction 6 hours before the time of sepsis, considering only the vital signs reached 83.24% and by including the vectors position, speed, and acceleration, we obtained 94.96%. The data are being collected from Medical Information Mart for Intensive Care (MIMIC) Database, a public database that contains vital signs, laboratory test results, observations, notes, and so on, from more than 60.000 patients.

Keywords: dynamic analysis, long short-term memory, prediction, sepsis

Procedia PDF Downloads 124

Authors: M. Karimpour, L. Hitihamillage, N. Elkhoury, S. Moridpour, R. Hesami

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Rail transport authorities around the world have been facing a significant challenge when predicting rail infrastructure maintenance work for a long period of time. Generally, maintenance monitoring and prediction is conducted manually. With the restrictions in economy, the rail transport authorities are in pursuit of improved modern methods, which can provide precise prediction of rail maintenance time and location. The expectation from such a method is to develop models to minimize the human error that is strongly related to manual prediction. Such models will help them in understanding how the track degradation occurs overtime under the change in different conditions (e.g. rail load, rail type, rail profile). They need a well-structured technique to identify the precise time that rail tracks fail in order to minimize the maintenance cost/time and secure the vehicles. The rail track characteristics that have been collected over the years will be used in developing rail track degradation prediction models. Since these data have been collected in large volumes and the data collection is done both electronically and manually, it is possible to have some errors. Sometimes these errors make it impossible to use them in prediction model development. This is one of the major drawbacks in rail track degradation prediction. An accurate model can play a key role in the estimation of the long-term behavior of rail tracks. Accurate models increase the track safety and decrease the cost of maintenance in long term. In this research, a short review of rail track degradation prediction models has been discussed before estimating rail track degradation for the curve sections of Melbourne tram track system using Adaptive Network-based Fuzzy Inference System (ANFIS) model.

Keywords: ANFIS, MGT, prediction modeling, rail track degradation

Procedia PDF Downloads 334

Authors: Vijay Kr. Yadav, Nilam Rathi

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Accurate prediction of glucose level for diabetes mellitus is required to avoid affecting the functioning of major organs of human body. This study describes the fundamental assumptions and two different methodologies of the Blood glucose prediction. First is based on the back-propagation algorithm of Artificial Neural Network (ANN), and second is based on the Neuro-Fuzzy technique, called Fuzzy Inference System (FIS). Errors between proposed methods further discussed through various statistical methods such as mean square error (MSE), normalised mean absolute error (NMAE). The main objective of present study is to develop mathematical model for blood glucose prediction before 12 hours advanced using data set of three patients for 60 days. The comparative studies of the accuracy with other existing models are also made with same data set.

Keywords: back-propagation, diabetes mellitus, fuzzy inference system, neuro-fuzzy

Procedia PDF Downloads 256

Authors: Soner Guler, Demet Yavuz, Refik Burak Taymuş, Fuat Korkut

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Because of the easy applying and not costing too much, ultrasonic pulse velocity (UPV) is one of the most used non-destructive techniques to determine concrete characteristics along with impact-echo, Schmidt rebound hammer (SRH) and pulse-echo. This article investigates the relationship between UPV and compressive strength of hybrid fiber reinforced concretes. Water/cement ratio (w/c) was kept at 0.4 for all concrete mixes. Compressive strength of concrete was targeted at 35 MPa. UPV testing and compressive strength tests were carried out at the curing age of 28 days. The UPV of concrete containing steel fibers has been found to be higher than plain concrete for all the testing groups. It is decided that there is not a certain relationship between fiber addition and strength.

Keywords: ultrasonic pulse velocity, hybrid fiber, compressive strength, fiber

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Authors: Ravinder Bahl, Jamini Sharma

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The paper demonstrates analysis of the cervical cancer based on a probabilistic model. It involves technique for classification and prediction by recognizing typical and diagnostically most important test features relating to cervical cancer. The main contributions of the research include predicting the probability of recurrences in no recurrence (first time detection) cases. The combination of the conventional statistical and machine learning tools is applied for the analysis. Experimental study with real data demonstrates the feasibility and potential of the proposed approach for the said cause.

Keywords: cervical cancer, recurrence, no recurrence, probabilistic, classification, prediction, machine learning

Procedia PDF Downloads 359

Authors: Mohammad Mahdi Mousavi

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Bankruptcy prediction models have been implemented for continuous evaluation and monitoring of firms. With the huge number of bankruptcy models, an extensive number of studies have focused on answering the question that which of these models are superior in performance. In practice, one of the drawbacks of existing comparative studies is that the relative assessment of alternative bankruptcy models remains an exercise that is mono-criterion in nature. Further, a very restricted number of criteria and measure have been applied to compare the performance of competing bankruptcy prediction models. In this research, we overcome these methodological gaps through implementing an extensive range of criteria and measures for comparison between dynamic and static bankruptcy models, and through proposing a multi-criteria framework to compare the relative performance of bankruptcy models in forecasting firm distress for UK firms.

Keywords: bankruptcy prediction, data envelopment analysis, performance criteria, performance measures

Procedia PDF Downloads 247

Authors: Nishant Parashar, Sawan S. Sinha, Balaji Srinivasan

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We perform an investigation of the unclosed terms in the evolution equation of the velocity gradient tensor (VGT) in compressible decaying turbulent flow. Velocity gradients in a compressible turbulent flow field influence several important nonlinear turbulent processes like cascading and intermittency. In an attempt to understand the dynamics of the velocity gradients various researchers have tried to model the unclosed terms in the evolution equation of the VGT. The existing models proposed for these unclosed terms have limited applicability. This is mainly attributable to the complex structure of the higher order gradient terms appearing in the evolution equation of VGT. We investigate these higher order gradients using the data from direct numerical simulation (DNS) of compressible decaying isotropic turbulent flow. The gas kinetic method aided with weighted essentially non-oscillatory scheme (WENO) based flow- reconstruction is employed to generate DNS data. By applying neural-network to the DNS data, we map the structure of the unclosed higher order gradient terms in the evolution of the equation of the VGT with VGT itself. We validate our findings by performing alignment based study of the unclosed higher order gradient terms obtained using the neural network with the strain rate eigenvectors.

Keywords: compressible turbulence, neural network, velocity gradient tensor, direct numerical simulation

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Authors: Feng Guolin, Gong Zhiqiang

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In order to study the spatial structure and dynamical mechanism of extreme precipitation in East Asia, a corresponding climate network is constructed by employing the method of event synchronization. It is found that the area of East Asian summer extreme precipitation can be separated into two regions: one with high area weighted connectivity receiving heavy precipitation mostly during the active phase of the East Asian Summer Monsoon (EASM), and another one with low area weighted connectivity receiving heavy precipitation during both the active and the retreat phase of the EASM. Besides，a way for the prediction of extreme precipitation is also developed by constructing a directed climate networks. The simulation accuracy in East Asia is 58% with a 0-day lead, and the prediction accuracy is 21% and average 12% with a 1-day and an n-day (2≤n≤10) lead, respectively. Compare to the normal EASM year, the prediction accuracy is lower in a weak year and higher in a strong year, which is relevant to the differences in correlations and extreme precipitation rates in different EASM situations. Recognizing and identifying these effects is good for understanding and predicting extreme precipitation in East Asia.

Keywords: synchronization, climate network, prediction, rainfall

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Authors: Louaifi Hamaili Samira, Mataoui Amina, Cheraitia Tadjeddine

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This investigation proposes a numerical analysis of two turbulent parallel jets impinging a heated plate. The heat transfer enhancement is carried out according of the main parameters of the jet-wall interaction. The numerical solution of the stationary equations (RANS) is performed by the finite volume method using the k - ε model. A parametric study is performed to evaluate simultaneously the effect of nozzle-plate distance and velocity ratios in the range 0≤λ≤1. It is found that good local cooling is obtained for λ= 0.25 when the impinging distance is between 4w and 8w than for velocity ratios λ=1 and λ= 0.75. On the other hand, for impinging distances exceeding 8w, the velocity ratio λ =0.75 is more appropriate for good local cooling of the plate.

Keywords: two unequal jets, turbulence, mixing, heat transfer, CFD

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Authors: S. Teksin, S. Yayla

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The aim of the present study was to investigate details of flow structure in downstream of a circular cylinder base mounted on a flat surface in a rectangular duct with the dimensions of 8000 x 1000 x 750 mm in deep water flow for the Reynolds number 2500, 5000 and 7500. A flexible strip was attached to behind the cylinder and compared the bare body. Also, it was analyzed that how boundary layer affects the structure of flow around the cylinder. Diameter of the cylinder was 60 mm and the length of the flexible splitter plate which had a certain modulus of elasticity was 150 mm (L/D=2.5). Time-averaged velocity vectors, vortex contours, streamwise and transverse velocity components were investigated via Particle Image Velocimetry (PIV). Velocity vectors and vortex contours were displayed through the sections in which boundary layer effect was not present. On the other hand, streamwise and transverse velocity components were monitored for both cases, i.e. with and without boundary layer effect. Experiment results showed that the vortex formation occured in a larger area for L/D=2.5 and the point where the vortex was maximum from the base of the cylinder was shifted. Streamwise and transverse velocity component contours were symmetrical with reference to the center of the cylinder for all cases. All Froud numbers based on the Reynolds numbers were quite smaller than 1. The flow characteristics of velocity component values of attached circular cylinder arrangement decreased approximately twenty five percent comparing to bare cylinder case.

Keywords: partical image velocimetry, elastic plate, cylinder, flow structure

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Authors: Jeoungsu Na, Jaehawn Lee, Changil Hong, Suhee Kim

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A molecular dynamics simulation in a converging-diverging nozzle was performed to study molecular collisions and their influence to average flow velocity according to a variety of vacuum levels. The static pressures and the dynamic pressure exerted by the molecule collision on the selected walls were compared to figure out the intensity variances of the directional flows. With pressure differences constant between the entrance and the exit of the nozzle, the numerical experiment was performed for molecular velocities and directional flows. The result shows that the velocities increased at the nozzle exit as the vacuum level gets higher in that area because less molecular collisions.

Keywords: cavitation, molecular collision, nozzle, vacuum, velocity increase

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Authors: Nabilah Filzah Mohd Radzuan, Zalinda Othman, Azuraliza Abu Bakar, Abdul Razak Hamdan

Abstract:

Uncertain data is believed to be an important issue in building up a prediction model. The main objective in the time series uncertainty analysis is to formulate uncertain data in order to gain knowledge and fit low dimensional model prior to a prediction task. This paper discusses the performance of a number of techniques in dealing with uncertain data specifically those which solve uncertain data condition by minimizing the loss of compression properties.

Keywords: compression properties, uncertainty, uncertain time series, mining technique, weather prediction

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Authors: Kuei-Yu Chien, Hsiu-Yu Chiu, Chia-Nan Chen, Shu-Chen Chen

Abstract:

Background: Frailty is associated with decreased physical performances that affect mobility of the elderly. Time up and go test (TUG) was the common method to evaluate mobility in the community. The purpose of this study was to compare the parameters in different stages of Time up and go test (TUG) and physical performance between pre-frail elderly (PFE) and non-frail elderly (NFE). We also investigated the relationship between TUG parameters and physical performance. Methods: Ninety-two community-dwelling older adults were as participants in this study. Based on Canadian Study of Health and Aging Clinical Frailty Scale, 22 older adults were classified as PFE (71.77 ± 6.05 yrs.) and 70 were classified as NFE (71.2 ± 5.02 yrs.). We performed body composition and physical performance, including balance, muscular strength/endurance, mobility, cardiorespiratory endurance, and flexibility. Results: Pre-frail elderly took significantly longer time than NFE in TUG test (p=.004). Pre-frail elderly had lower turning average angular velocity (p = .017), turning peak angular velocity (p = .041) and turning-stand to sit peak angular velocity (p = .037) than NFE. The turning related parameters related to open-eye stand on right foot, 30-second chair stand test, back scratch, and 2-min step tests. Conclusions: Turning average angular velocity, turning peak angular velocity and turning-stand to sit peak angular velocity mainly affected the TUG performance. We suggested that static/dynamic balance, agility, flexibility, and muscle strengthening of lower limbs exercise were important to PFE.

Keywords: mobility, aglity, active ageing, functional fitness

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Authors: Ahmed Yousef A. Al Sultan

Abstract:

Introduction: The aim of this review is based on clinical research that studies the changes in middle cerebral artery velocity using Transcranial Doppler (TCD) and cerebral oxygen saturation using cerebral oximetry in patients undergoing carotid endarterectomy (CEA) surgery under local anesthesia (LA). Patients with or without neurological symptoms during the surgery are taking a role in this study using triplet method of cerebral oximetry, transcranial doppler and awake test in detecting any cerebral ischemic symptoms. Methods: about one hundred patients took part during their CEA surgeries under local anesthesia, using triple assessment mentioned method, Patients requiring general anesthesia be excluded from analysis. All data were recorded at eight surgery stages separately to serve this study. Results: In total regional cerebral oxygen saturation (rSO2), middle cerebral artery (MCA) velocity, and pulsatility index were significantly decreased during carotid artery clamping step in CEA procedures on the targeted carotid side. With most observed changes in MCA velocity during the study. Discussion: Cerebral oxygen saturation and middle cerebral artery velocity were significantly decreased during clamping step of the procedures on the targeted side. The team with neurological symptoms during the procedures showed higher changes of rSO2 and MCA velocity than the team without neurological symptoms. Cerebral rSO2 and MCA velocity significantly increased directly after de-clamping of the internal carotid artery on the affected side.

Keywords: awake testing, carotid endarterectomy, cerebral oximetry, Tanscranial Doppler

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Authors: Ulas Vural, M. Ergun Okay, E. Mesut Yildiz

Abstract:

Telecommunication service providers demand accurate and precise prediction of customer churn probabilities to increase the effectiveness of their customer relation services. The large amount of customer data owned by the service providers is suitable for analysis by machine learning methods. In this study, expenditure data of customers are analyzed by using an artificial neural network (ANN). The ANN model is applied to the data of customers with different billing duration. The proposed model successfully predicts the churn probabilities at 83% accuracy for only three months expenditure data and the prediction accuracy increases up to 89% when the nine month data is used. The experiments also show that the accuracy of ANN model increases on an extended feature set with information of the changes on the bill amounts.

Keywords: customer relationship management, churn prediction, telecom industry, deep learning, artificial neural networks

Procedia PDF Downloads 143