Search results for: transmission error
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3768

Search results for: transmission error

1728 Application of Support Vector Machines in Forecasting Non-Residential

Authors: Wiwat Kittinaraporn, Napat Harnpornchai, Sutja Boonyachut

Abstract:

This paper deals with the application of a novel neural network technique, so-called Support Vector Machine (SVM). The objective of this study is to explore the variable and parameter of forecasting factors in the construction industry to build up forecasting model for construction quantity in Thailand. The scope of the research is to study the non-residential construction quantity in Thailand. There are 44 sets of yearly data available, ranging from 1965 to 2009. The correlation between economic indicators and construction demand with the lag of one year was developed by Apichat Buakla. The selected variables are used to develop SVM models to forecast the non-residential construction quantity in Thailand. The parameters are selected by using ten-fold cross-validation method. The results are indicated in term of Mean Absolute Percentage Error (MAPE). The MAPE value for the non-residential construction quantity predicted by Epsilon-SVR in corporation with Radial Basis Function (RBF) of kernel function type is 5.90. Analysis of the experimental results show that the support vector machine modelling technique can be applied to forecast construction quantity time series which is useful for decision planning and management purpose.

Keywords: forecasting, non-residential, construction, support vector machines

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1727 Sensitivity of the Estimated Output Energy of the Induction Motor to both the Asymmetry Supply Voltage and the Machine Parameters

Authors: Eyhab El-Kharashi, Maher El-Dessouki

Abstract:

The paper is dedicated to precise assessment of the induction motor output energy during the unbalanced operation. Since many years ago and until now the voltage complex unbalance factor (CVUF) is used only to assess the output energy of the induction motor while this output energy for asymmetry supply voltage does not depend on the value of unbalanced voltage only but also on the machine parameters. The paper illustrates the variation of the two unbalance factors, complex voltage unbalance factor (CVUF) and impedance unbalance factor (IUF), with positive sequence voltage component, reveals that degree and manner of unbalance in supply voltage. From this point of view the paper delineates the current unbalance factor (CUF) to exactly reflect the output energy during unbalanced operation. The paper proceeds to illustrate the importance of using this factor in the multi-machine system to precise prediction of the output energy during the unbalanced operation. The use of the proposed unbalance factor (CUF) avoids the accumulation of the error due to more than one machine in the system which is expected if only the complex voltage unbalance factor (CVUF) is used.

Keywords: induction motor, electromagnetic torque, voltage unbalance, energy conversion

Procedia PDF Downloads 557
1726 Comparison of Statistical Methods for Estimating Missing Precipitation Data in the River Subbasin Lenguazaque, Colombia

Authors: Miguel Cañon, Darwin Mena, Ivan Cabeza

Abstract:

In this work was compared and evaluated the applicability of statistical methods for the estimation of missing precipitations data in the basin of the river Lenguazaque located in the departments of Cundinamarca and Boyacá, Colombia. The methods used were the method of simple linear regression, distance rate, local averages, mean rates, correlation with nearly stations and multiple regression method. The analysis used to determine the effectiveness of the methods is performed by using three statistical tools, the correlation coefficient (r2), standard error of estimation and the test of agreement of Bland and Altmant. The analysis was performed using real rainfall values removed randomly in each of the seasons and then estimated using the methodologies mentioned to complete the missing data values. So it was determined that the methods with the highest performance and accuracy in the estimation of data according to conditions that were counted are the method of multiple regressions with three nearby stations and a random application scheme supported in the precipitation behavior of related data sets.

Keywords: statistical comparison, precipitation data, river subbasin, Bland and Altmant

Procedia PDF Downloads 467
1725 Towards an Effective Approach for Modelling near Surface Air Temperature Combining Weather and Satellite Data

Authors: Nicola Colaninno, Eugenio Morello

Abstract:

The urban environment affects local-to-global climate and, in turn, suffers global warming phenomena, with worrying impacts on human well-being, health, social and economic activities. Physic-morphological features of the built-up space affect urban air temperature, locally, causing the urban environment to be warmer compared to surrounding rural. This occurrence, typically known as the Urban Heat Island (UHI), is normally assessed by means of air temperature from fixed weather stations and/or traverse observations or based on remotely sensed Land Surface Temperatures (LST). The information provided by ground weather stations is key for assessing local air temperature. However, the spatial coverage is normally limited due to low density and uneven distribution of the stations. Although different interpolation techniques such as Inverse Distance Weighting (IDW), Ordinary Kriging (OK), or Multiple Linear Regression (MLR) are used to estimate air temperature from observed points, such an approach may not effectively reflect the real climatic conditions of an interpolated point. Quantifying local UHI for extensive areas based on weather stations’ observations only is not practicable. Alternatively, the use of thermal remote sensing has been widely investigated based on LST. Data from Landsat, ASTER, or MODIS have been extensively used. Indeed, LST has an indirect but significant influence on air temperatures. However, high-resolution near-surface air temperature (NSAT) is currently difficult to retrieve. Here we have experimented Geographically Weighted Regression (GWR) as an effective approach to enable NSAT estimation by accounting for spatial non-stationarity of the phenomenon. The model combines on-site measurements of air temperature, from fixed weather stations and satellite-derived LST. The approach is structured upon two main steps. First, a GWR model has been set to estimate NSAT at low resolution, by combining air temperature from discrete observations retrieved by weather stations (dependent variable) and the LST from satellite observations (predictor). At this step, MODIS data, from Terra satellite, at 1 kilometer of spatial resolution have been employed. Two time periods are considered according to satellite revisit period, i.e. 10:30 am and 9:30 pm. Afterward, the results have been downscaled at 30 meters of spatial resolution by setting a GWR model between the previously retrieved near-surface air temperature (dependent variable), the multispectral information as provided by the Landsat mission, in particular the albedo, and Digital Elevation Model (DEM) from the Shuttle Radar Topography Mission (SRTM), both at 30 meters. Albedo and DEM are now the predictors. The area under investigation is the Metropolitan City of Milan, which covers an area of approximately 1,575 km2 and encompasses a population of over 3 million inhabitants. Both models, low- (1 km) and high-resolution (30 meters), have been validated according to a cross-validation that relies on indicators such as R2, Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). All the employed indicators give evidence of highly efficient models. In addition, an alternative network of weather stations, available for the City of Milano only, has been employed for testing the accuracy of the predicted temperatures, giving and RMSE of 0.6 and 0.7 for daytime and night-time, respectively.

Keywords: urban climate, urban heat island, geographically weighted regression, remote sensing

Procedia PDF Downloads 194
1724 Public Wi-Fi Security Threat Evil Twin Attack Detection Based on Signal Variant and Hop Count

Authors: Said Abdul Ahad Ahadi, Elyas Baray, Nitin Rakesh, Sudeep Varshney

Abstract:

Wi-Fi is a widely used internet source that is used to provide internet access in many areas such as Stores, Cafes, University campuses, Restaurants and so on. This technology brought more facilities in communication and networking. On the other hand, due to the transmission of data over the air, which makes the network vulnerable, so it becomes prone to various threats such as Evil Twin and etc. The Evil Twin is a kind of adversary which impersonates a legitimate access point (LAP) as it can happen by spoofing the name (SSID) and MAC address (BSSID) of a legitimate access point (LAP). And this attack can cause many threats such as MITM, Service Interruption, Access point service blocking. Various Evil Twin Attack Detection Techniques are proposed, but they require additional hardware, or they require protocol modification. In this paper, we proposed a new technique based on Access Point’s two fingerprints, Received Signal Strength Indicator (RSSI) and Hop Count, that is hard to copy by an adversary. And we implemented the technique in a system called “ETDetector,” which can detect and prevent the attack.

Keywords: evil twin, LAP, SSID, Wi-Fi security, signal variation, ETAD, kali linux, scapy, python

Procedia PDF Downloads 143
1723 Macroeconomic Impact of Economic Growth on Unemployment: A Case of South Africa

Authors: Ashika Govender

Abstract:

This study seeks to determine whether Okun’s Law is valid for the South African economy, using time series data for the period 2004 to 2014. The data were accessed from the South African Reserve Bank and Stats SA. The stationarity of the variables was analysed by applying unit root tests via the Augmented Dickey-Fuller test (ADF), the Phillips-Perron (PP) test, and the Kwiatkowski–Phillips–Schmidt–Shin test (KPSS) test. The study used an ordinary least square (OLS) model in analysing the dynamic version of Okun’s law. The Error Correction Model (ECM) was used to analyse the short-run impact of GDP growth on unemployment, as well as the speed of adjustment. The results indicate a short run and long run relationship between unemployment rate and GDP growth rate in period 2004q1-2014q4, suggesting that Okun’s law is valid for the South African economy. With a 1 percent increase in GDP, unemployment can decrease by 0.13 percent, ceteris paribus. The research culminates in important policy recommendations, highlighting the relationship between unemployment and economic growth in the spirit of the National Development Plan.

Keywords: unemployment, economic growth, Okun's law, South Africa

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1722 Prediction of the Mechanical Power in Wind Turbine Powered Car Using Velocity Analysis

Authors: Abdelrahman Alghazali, Youssef Kassem, Hüseyin Çamur, Ozan Erenay

Abstract:

Savonius is a drag type vertical axis wind turbine. Savonius wind turbines have a low cut-in speed and can operate at low wind speed. This makes it suitable for electricity or mechanical generation in low-power applications such as individual domestic installations. Therefore, the primary purpose of this work was to investigate the relationship between the type of Savonius rotor and the torque and mechanical power generated. And it was to illustrate how the type of rotor might play an important role in the prediction of mechanical power of wind turbine powered car. The main purpose of this paper is to predict and investigate the aerodynamic effects by means of velocity analysis on the performance of a wind turbine powered car by converting the wind energy into mechanical energy to overcome load that rotates the main shaft. The predicted results based on theoretical analysis were compared with experimental results obtained from literature. The percentage of error between the two was approximately around 20%. Prediction of the torque was done at a wind speed of 4 m/s, and an angular velocity of 130 RPM according to meteorological statistics in Northern Cyprus.

Keywords: mechanical power, torque, Savonius rotor, wind car

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1721 Analysis of Production Forecasting in Unconventional Gas Resources Development Using Machine Learning and Data-Driven Approach

Authors: Dongkwon Han, Sangho Kim, Sunil Kwon

Abstract:

Unconventional gas resources have dramatically changed the future energy landscape. Unlike conventional gas resources, the key challenges in unconventional gas have been the requirement that applies to advanced approaches for production forecasting due to uncertainty and complexity of fluid flow. In this study, artificial neural network (ANN) model which integrates machine learning and data-driven approach was developed to predict productivity in shale gas. The database of 129 wells of Eagle Ford shale basin used for testing and training of the ANN model. The Input data related to hydraulic fracturing, well completion and productivity of shale gas were selected and the output data is a cumulative production. The performance of the ANN using all data sets, clustering and variables importance (VI) models were compared in the mean absolute percentage error (MAPE). ANN model using all data sets, clustering, and VI were obtained as 44.22%, 10.08% (cluster 1), 5.26% (cluster 2), 6.35%(cluster 3), and 32.23% (ANN VI), 23.19% (SVM VI), respectively. The results showed that the pre-trained ANN model provides more accurate results than the ANN model using all data sets.

Keywords: unconventional gas, artificial neural network, machine learning, clustering, variables importance

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1720 Evaluation of Three Digital Graphical Methods of Baseflow Separation Techniques in the Tekeze Water Basin in Ethiopia

Authors: Alebachew Halefom, Navsal Kumar, Arunava Poddar

Abstract:

The purpose of this work is to specify the parameter values, the base flow index (BFI), and to rank the methods that should be used for base flow separation. Three different digital graphical approaches are chosen and used in this study for the purpose of comparison. The daily time series discharge data were collected from the site for a period of 30 years (1986 up to 2015) and were used to evaluate the algorithms. In order to separate the base flow and the surface runoff, daily recorded streamflow (m³/s) data were used to calibrate procedures and get parameter values for the basin. Additionally, the performance of the model was assessed by the use of the standard error (SE), the coefficient of determination (R²), and the flow duration curve (FDC) and baseflow indexes. The findings indicate that, in general, each strategy can be used worldwide to differentiate base flow; however, the Sliding Interval Method (SIM) performs significantly better than the other two techniques in this basin. The average base flow index was calculated to be 0.72 using the local minimum method, 0.76 using the fixed interval method, and 0.78 using the sliding interval method, respectively.

Keywords: baseflow index, digital graphical methods, streamflow, Emba Madre Watershed

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1719 Chitosan Magnetic Nanoparticles and Its Analytical Applications

Authors: Eman Alzahrani

Abstract:

Efficient extraction of proteins by removing interfering materials is necessary in proteomics, since most instruments cannot handle such contaminated sample matrices directly. In this study, chitosan-coated magnetic nanoparticles (CS-MNPs) for purification of myoglobin were successfully fabricated. First, chitosan (CS) was prepared by a deacetylation reaction during its extraction from shrimp-shell waste. Second, magnetic nanoparticles (MNPs) were synthesised, using the coprecipitation method, from aqueous Fe2+ and Fe3+ salt solutions by the addition of a base under an inert atmosphere, followed by modification of the surface of MNPs with chitosan. The morphology of the formed nanoparticles, which were about 23 nm in average diameter, was observed by transmission electron microscopy (TEM). In addition, nanoparticles were characterised using X-ray diffraction patterns (XRD), which showed the naked magnetic nanoparticles have a spinel structure and the surface modification did not result in phase change of the Fe3O4. The coating of MNPs was also demonstrated by scanning electron microscopy (SEM) analysis, energy dispersive analysis of X-ray spectroscopy (EDAX), and Fourier transform infrared (FT-IR) spectroscopy. The adsorption behaviour of MNPs and CS-MNPs towards myoglobin was investigated. It was found that the difference in adsorption capacity between MNPs and CS-MNPs was larger for CS-MNPs. This result makes CS-MNPs good adsorbents and attractive for using in protein extraction from biological samples.

Keywords: chitosan, magnetic nanoparticles, coprecipitation, adsorption

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1718 Impact of Different Modulation Techniques on the Performance of Free-Space Optics

Authors: Naman Singla, Ajay Pal Singh Chauhan

Abstract:

As the demand for providing high bit rate and high bandwidth is increasing at a rapid rate so there is a need to see in this problem and finds a technology that provides high bit rate and also high bandwidth. One possible solution is by use of optical fiber. Optical fiber technology provides high bandwidth in THz. But the disadvantage of optical fiber is of high cost and not used everywhere because it is not possible to reach all the locations on the earth. Also high maintenance required for usage of optical fiber. It puts a lot of cost. Another technology which is almost similar to optical fiber is Free Space Optics (FSO) technology. FSO is the line of sight technology where modulated optical beam whether infrared or visible is used to transfer information from one point to another through the atmosphere which works as a channel. This paper concentrates on analyzing the performance of FSO in terms of bit error rate (BER) and quality factor (Q) using different modulation techniques like non return to zero on off keying (NRZ-OOK), differential phase shift keying (DPSK) and differential quadrature phase shift keying (DQPSK) using OptiSystem software. The findings of this paper show that FSO system based on DQPSK modulation technique performs better.

Keywords: attenuation, bit rate, free space optics, link length

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1717 Preparation of 1D Nano-Polyaniline/Dendritic Silver Composites

Authors: Wen-Bin Liau, Wan-Ting Wang, Chiang-Jen Hsiao, Sheng-Mao Tseng

Abstract:

In this paper, an interesting and easy method to prepare one-dimensional nanostructured polyaniline/dendritic silver composites is reported. It is well known that the morphology of metal particle is a very important factor to influence the properties of polymer-metal composites. Usually, the dendritic silver is prepared by kinetic control in reduction reaction. It is not a thermodynamically stable structure. It is the goal to reduce silver ion to dendritic silver by polyaniline polymer via kinetic control and form one-dimensional nanostructured polyaniline/dendritic silver composites. The preparation is a two steps sequential reaction. First step, the polyaniline networks composed of nano fibrillar polyaniline are synthesized from aniline monomers aqueous with ammonium persulfate as the initiator at room temperature. In second step, the silver nitrate is added into polyaniline networks dispersed in deionized water. The dendritic silver is formed via reduction by polyaniline networks under the kinetic control. The formation of polyaniline is discussed via transmission electron microscopy (TEM). Nanosheets, nanotubes, nanospheres, nanosticks, and networks are observed via TEM. Then, the mechanism of formation of one-dimensional nanostructured polyaniline/dendritic silver composites is discussed. The formation of dendritic silver is observed by TEM and X-ray diffraction.

Keywords: 1D nanostructured polyaniline, dendritic silver, synthesis

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1716 Target Drug Delivery of Pamidronate Nanoparticles for Enhancing Osteoblastic Activity in Osteoporosis

Authors: Purnima Rawat, Divya Vohora, Sarika Gupta, Farhan J. Ahmad, Sushama Talegaonkar

Abstract:

Nanoparticles (NPs) that target bone tissue were developed using PLGA–mPEG (poly(lactic-co-glycolic-acid)–polyethylene glycol) diblock copolymers by using pamidronate as a bone-targeting moieties. These NPs are expected to enable the transport of hydrophilic drugs. The NP was prepared by in situ polymerization method, and their in- vitro characteristics were evaluated using dynamic light scattering, transmission electron microscopy (TEM) and in phosphate-buffered solution. The bone targeting potential of the NP was also evaluated on in-vitro pre-osteoblast MCT3E1 cell line using ALP activity, degree of mineralization and RT-PCR assay. The average particle size of the NP was 101.6 ± 3.7nm, zeta potential values were negative (-25±0.34mV) of the formulations and the entrapment efficiency was 93± 3.1 % obtained. The moiety of the PLGA–mPEG–pamidronate NPs exhibited the best apatite mineral binding ability in-vitro MCT3E1 pre-osteoblast cell line. Our results suggested that the developed nanoparticles may use as a delivery system for Pamidronate in bone repair and regeneration, warranting further evaluation of the treatment of bone disease.

Keywords: nanoparticle, pamidronate, in-situ polymerization, osteoblast

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1715 Flexible Capacitive Sensors Based on Paper Sheets

Authors: Mojtaba Farzaneh, Majid Baghaei Nejad

Abstract:

This article proposes a new Flexible Capacitive Tactile Sensors based on paper sheets. This method combines the parameters of sensor's material and dielectric, and forms a new model of flexible capacitive sensors. The present article tries to present a practical explanation of this method's application and advantages. With the use of this new method, it is possible to make a more flexibility and accurate sensor in comparison with the current models. To assess the performance of this model, the common capacitive sensor is simulated and the proposed model of this article and one of the existing models are assessed. The results of this article indicate that the proposed model of this article can enhance the speed and accuracy of tactile sensor and has less error in comparison with the current models. Based on the results of this study, it can be claimed that in comparison with the current models, the proposed model of this article is capable of representing more flexibility and more accurate output parameters for touching the sensor, especially in abnormal situations and uneven surfaces, and increases accuracy and practicality.

Keywords: capacitive sensor, paper sheets, flexible, tactile, uneven

Procedia PDF Downloads 353
1714 Controlling Dimensions and Shape of Carbon Nanotubes Using Nanoporous Anodic Alumina under Different Conditions

Authors: Amine Mezni, Merfat Algethami, Ali Aldalbahi, Arwa Alrooqi, Abel Santos, Dusan Losic, Sarah Alharthi, Tariq Altalhi

Abstract:

In situ synthesis of carbon nanotubes featuring different diameters (10-200 nm), lengths (1 to 100 µm) and periodically nanostructured shape was performed in a custom designed chemical vapor deposition (CVD) system using nanoporous anodic alumina (NAA) under different conditions. The morphology of the resulting CNTs/NAA composites and free-standing CNTs were analyzed by transmission electron microscopy (TEM) and scanning electron microscopy (SEM). The results confirm that highly ordered arrays of CNTs with precise control of nanotube dimensions in the range 20-200 nm with tube length in the range < 1 µm to > 100 μm and with periodically shaped morphology can be fabricated using nanostructured NAA templates prepared by anodization. This technique allows us to obtain tubes open at one / both ends with a uniform diameter along the pore length without using any metal catalyst. Our finding suggests that this fabrication strategy for designing new CNTs membranes and structures can be significant for emerging applications as molecular separation/transport, optical biosensing, and drug delivery.

Keywords: carbon nanotubes, CVD approach, composites membrane, nanoporous anodic alumina

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1713 Performance Evaluation and Dear Based Optimization on Machining Leather Specimens to Reduce Carbonization

Authors: Khaja Moiduddin, Tamer Khalaf, Muthuramalingam Thangaraj

Abstract:

Due to the variety of benefits over traditional cutting techniques, the usage of laser cutting technology has risen substantially in recent years. Hot wire machining can cut the leather in the required shape by controlling the wire by generating thermal energy. In the present study, an attempt has been made to investigate the effects of performance measures in the hot wire machining process on cutting leather specimens. Carbonization and material removal rates were considered as quality indicators. Burning leather during machining might cause carbon particles, reducing product quality. Minimizing the effect of carbon particles is crucial for assuring operator and environmental safety, health, and product quality. Hot wire machining can efficiently cut the specimens by controlling the current through it. Taguchi- DEAR-based optimization was also performed in the process, which resulted in a required Carbonization and material removal rate. Using the DEAR approach, the optimal parameters of the present study were found with 3.7% prediction error accuracy.

Keywords: cabronization, leather, MRR, current

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1712 Using Artificial Intelligence Method to Explore the Important Factors in the Reuse of Telecare by the Elderly

Authors: Jui-Chen Huang

Abstract:

This research used artificial intelligence method to explore elderly’s opinions on the reuse of telecare, its effect on their service quality, satisfaction and the relationship between customer perceived value and intention to reuse. This study conducted a questionnaire survey on the elderly. A total of 124 valid copies of a questionnaire were obtained. It adopted Backpropagation Network (BPN) to propose an effective and feasible analysis method, which is different from the traditional method. Two third of the total samples (82 samples) were taken as the training data, and the one third of the samples (42 samples) were taken as the testing data. The training and testing data RMSE (root mean square error) are 0.022 and 0.009 in the BPN, respectively. As shown, the errors are acceptable. On the other hand, the training and testing data RMSE are 0.100 and 0.099 in the regression model, respectively. In addition, the results showed the service quality has the greatest effects on the intention to reuse, followed by the satisfaction, and perceived value. This result of the Backpropagation Network method is better than the regression analysis. This result can be used as a reference for future research.

Keywords: artificial intelligence, backpropagation network (BPN), elderly, reuse, telecare

Procedia PDF Downloads 212
1711 On the Effectiveness of Electricity Market Development Strategies: A Target Model for a Developing Country

Authors: Ezgi Avci-Surucu, Doganbey Akgul

Abstract:

Turkey’s energy reforms has achieved energy security through a variety of interlinked measures including electricity, gas, renewable energy and energy efficiency legislation; the establishment of an energy sector regulatory authority; energy price reform; the creation of a functional electricity market; restructuring of state-owned energy enterprises; and private sector participation through privatization and new investment. However, current strategies, namely; “Electricity Sector Reform and Privatization Strategy” and “Electricity Market and Supply Security Strategy” has been criticized for various aspects. The present paper analyzes the implementation of the aforementioned strategies in the framework of generation scheduling, transmission constraints, bidding structure and general aspects; and argues the deficiencies of current strategies which decelerates power investments and creates uncertainties. We conclude by policy suggestions to eliminate these deficiencies in terms of price and risk management, infrastructure, customer focused regulations and systematic market development.

Keywords: electricity markets, risk management, regulations, balancing and settlement, bilateral trading, generation scheduling, bidding structure

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1710 Experimental Study of the Electrical Conductivity and Thermal Conductivity Property of Micro-based Al-Cu-Nb-Mo Alloy

Authors: Uwa C. A., Jamiru T.

Abstract:

Aluminum based alloys with a certain compositional blend and manufacturing method have been reported to have excellent electrical conductors. In the current investigation, metal powders of Aluminum (Al), Copper (Cu), Niobium (Nb), and Molybdenum (Mo) were weighed in accordance with certain ratios and spread equally by combining the powder particles. The metal particles were mixed using a tube mixer for 12 hours. Before pouring into a 30mm-diameter graphite mold, pre-pressed, and placed into an SPS furnace, the thermal conductivity of the mixed metal powders was evaluated using a portable Thermtest device. Axial pressure of 50 MPa was used at a heating rate of 50 oC/min, and a multi-stage heating procedure with a holding period of 10 min. was used to sinter at temperatures between 300 oC and 480 oC. After being cooled to room temperature, the specimens were unmolded to produce the aluminum, copper, niobium, and molybdenum alloy material. The HPS 2662 Precision Four-point Probe Meter was used to determine the electrical resistivity and the values used to calculate the electrical conductivity of the sintered alloy samples. Finally, the alloy with the highest electrical conductivity and thermal conductivity qualities was the one with the following composition: Al 93.5Cu4Nb1.5Mo1. It also had a density of 3.23 g/cm3. It could be advisable for usage in automobile radiator and electric transmission line components.

Keywords: Al-Cu-Nb-Mo, electrical conductivity, alloy, sintering, thermal conductivity

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1709 The Use of Fractional Brownian Motion in the Generation of Bed Topography for Bodies of Water Coupled with the Lattice Boltzmann Method

Authors: Elysia Barker, Jian Guo Zhou, Ling Qian, Steve Decent

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A method of modelling topography used in the simulation of riverbeds is proposed in this paper, which removes the need for datapoints and measurements of physical terrain. While complex scans of the contours of a surface can be achieved with other methods, this requires specialised tools, which the proposed method overcomes by using fractional Brownian motion (FBM) as a basis to estimate the real surface within a 15% margin of error while attempting to optimise algorithmic efficiency. This removes the need for complex, expensive equipment and reduces resources spent modelling bed topography. This method also accounts for the change in topography over time due to erosion, sediment transport, and other external factors which could affect the topography of the ground by updating its parameters and generating a new bed. The lattice Boltzmann method (LBM) is used to simulate both stationary and steady flow cases in a side-by-side comparison over the generated bed topography using the proposed method and a test case taken from an external source. The method, if successful, will be incorporated into the current LBM program used in the testing phase, which will allow an automatic generation of topography for the given situation in future research, removing the need for bed data to be specified.

Keywords: bed topography, FBM, LBM, shallow water, simulations

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1708 Multiloop Fractional Order PID Controller Tuned Using Cuckoo Algorithm for Two Interacting Conical Tank Process

Authors: U. Sabura Banu, S. K. Lakshmanaprabu

Abstract:

The improvement of meta-heuristic algorithm encourages control engineer to design an optimal controller for industrial process. Most real-world industrial processes are non-linear multivariable process with high interaction. Even in sub-process unit, thousands of loops are available mostly interacting in nature. Optimal controller design for such process are still challenging task. Closed loop controller design by multiloop PID involves a tedious procedure by performing interaction study and then PID auto-tuning the loop with higher interaction. Finally, detuning the controller to accommodate the effects of the other process variables. Fractional order PID controllers are replacing integer order PID controllers recently. Design of Multiloop Fractional Order (MFO) PID controller is still more complicated. Cuckoo algorithm, a swarm intelligence technique is used to optimally tune the MFO PID controller with easiness minimizing Integral Time Absolute Error. The closed loop performance is tested under servo, regulatory and servo-regulatory conditions.

Keywords: Cuckoo algorithm, mutliloop fractional order PID controller, two Interacting conical tank process

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1707 Continuity and Changes on Traditional Puppetry in Java: The Existences of Wayang Hip Hop

Authors: Taufik Hidayah

Abstract:

Wayang is a traditional puppet show originated from Java. This traditional art is characterized by distinctive Hinduism influence. Wayang reflects the social life of the Javanese society. It contains Javanese philosophy, myths, magical stories, and religion, as well as educational media and transmission for noble values of Javanese society conveyed through the story. Nowadays, the performance of wayang has faced a new challenge to maintain its existence in the public life of Javanese society. Modernity has penetrated into every shape of culture. Many people consider traditional culture as old fashioned, particularly the young generation. That is one of the reasons why many people have left traditional culture. For maintaining the existence of wayang, a new art called ‘wayang hip hop’ has arisen. Wayang hip hop seeks to modify wayang show into a more modern form, but without removing any principles and main functions of wayang art. This article will discuss theoretically the changes and traditional continuity in wayang hip hop based on a literature review and qualitative approaches. Wayang hip hop uses hip-hop music as the background music in the show. It will discuss about the impact that comes with the existential strengthening of wayang hip hop especially among the Javanese society and discuss the opportunities that arise regarding the function of wayang hip-hop as a medium of education, social criticism, and cultural revitalization of the Javanese society.

Keywords: cultural revitalization, social criticism, education, continuity and change

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1706 A Comparative Study of Generalized Autoregressive Conditional Heteroskedasticity (GARCH) and Extreme Value Theory (EVT) Model in Modeling Value-at-Risk (VaR)

Authors: Longqing Li

Abstract:

The paper addresses the inefficiency of the classical model in measuring the Value-at-Risk (VaR) using a normal distribution or a Student’s t distribution. Specifically, the paper focuses on the one day ahead Value-at-Risk (VaR) of major stock market’s daily returns in US, UK, China and Hong Kong in the most recent ten years under 95% confidence level. To improve the predictable power and search for the best performing model, the paper proposes using two leading alternatives, Extreme Value Theory (EVT) and a family of GARCH models, and compares the relative performance. The main contribution could be summarized in two aspects. First, the paper extends the GARCH family model by incorporating EGARCH and TGARCH to shed light on the difference between each in estimating one day ahead Value-at-Risk (VaR). Second, to account for the non-normality in the distribution of financial markets, the paper applies Generalized Error Distribution (GED), instead of the normal distribution, to govern the innovation term. A dynamic back-testing procedure is employed to assess the performance of each model, a family of GARCH and the conditional EVT. The conclusion is that Exponential GARCH yields the best estimate in out-of-sample one day ahead Value-at-Risk (VaR) forecasting. Moreover, the discrepancy of performance between the GARCH and the conditional EVT is indistinguishable.

Keywords: Value-at-Risk, Extreme Value Theory, conditional EVT, backtesting

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1705 The Use of Lane-Centering to Assure the Visible Light Communication Connectivity for a Platoon of Autonomous Vehicles

Authors: Mohammad Y. Abualhoul, Edgar Talavera Munoz, Fawzi Nashashibi

Abstract:

The new emerging Visible Light Communication (VLC) technology has been subjected to intensive investigation, evaluation, and lately, deployed in the context of convoy-based applications for Intelligent Transportations Systems (ITS). The technology limitations were defined and supported by different solutions proposals to enhance the crucial alignment and mobility limitations. In this paper, we propose the incorporation of VLC technology and Lane-Centering (LC) technique to assure the VLC-connectivity by keeping the autonomous vehicle aligned to the lane center using vision-based lane detection in a convoy-based formation. Such combination can ensure the optical communication connectivity with a lateral error less than 30 cm. As soon as the road lanes are detectable, the evaluated system showed stable behavior independently from the inter-vehicle distances and without the need for any exchanged information of the remote vehicles. The evaluation of the proposed system is verified using VLC prototype and an empirical result of LC running application over 60 km in Madrid M40 highway.

Keywords: visible light communication, lane-centerin, platooning, intelligent transportation systems, road safety applications

Procedia PDF Downloads 171
1704 Comparison Of Data Mining Models To Predict Future Bridge Conditions

Authors: Pablo Martinez, Emad Mohamed, Osama Mohsen, Yasser Mohamed

Abstract:

Highway and bridge agencies, such as the Ministry of Transportation in Ontario, use the Bridge Condition Index (BCI) which is defined as the weighted condition of all bridge elements to determine the rehabilitation priorities for its bridges. Therefore, accurate forecasting of BCI is essential for bridge rehabilitation budgeting planning. The large amount of data available in regard to bridge conditions for several years dictate utilizing traditional mathematical models as infeasible analysis methods. This research study focuses on investigating different classification models that are developed to predict the bridge condition index in the province of Ontario, Canada based on the publicly available data for 2800 bridges over a period of more than 10 years. The data preparation is a key factor to develop acceptable classification models even with the simplest one, the k-NN model. All the models were tested, compared and statistically validated via cross validation and t-test. A simple k-NN model showed reasonable results (within 0.5% relative error) when predicting the bridge condition in an incoming year.

Keywords: asset management, bridge condition index, data mining, forecasting, infrastructure, knowledge discovery in databases, maintenance, predictive models

Procedia PDF Downloads 191
1703 From Parents to Pioneers: Examining Parental Impact on Entrepreneurial Traits in Latin America

Authors: Bert Seither

Abstract:

Entrepreneurship is a critical driver of economic growth, especially in emerging regions such as Latin America. This study investigates how parental influences, particularly parental individual entrepreneurial orientation (IEO), shape the entrepreneurial traits of Latin American entrepreneurs. By examining key factors like parental IEO, work ethic, parenting style, and family support, this research assesses how much of an entrepreneur's own IEO can be attributed to parental influence. The study also explores how socio-economic status and cultural context moderate the relationship between parental traits and entrepreneurial orientation. Data will be collected from 600 Latin American entrepreneurs via an online survey. This research aims to provide a comprehensive understanding of the intergenerational transmission of entrepreneurial traits and the broader socio-cultural factors that contribute to entrepreneurial success in diverse contexts. Findings from this study will offer valuable insights for policymakers, educators, and business leaders on fostering entrepreneurship across Latin America, providing practical applications for shaping entrepreneurial behavior through family influences.

Keywords: entrepreneurial orientation, parental influence, Latin American entrepreneurs, socio-economic status, cultural context

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1702 Low Dose In-Line Electron Holography for 3D Atomic Resolution Tomography of Soft Materials

Authors: F. R. Chen, C. Kisielowski, D. Van Dyck

Abstract:

In principle, the latest generation aberration-corrected transmission electron microscopes (TEMs) could achieve sub-Å resolution, but there is bottleneck that hinders the final step towards revealing 3D structure. Firstly, in order to achieve a resolution around 1 Å with single atom sensitivity, the electron dose rate needs to be sufficiently large (10⁴-10⁵eÅ⁻² s⁻¹). With such large dose rate, the electron beam can induce surfaces alterations or even bulk modifications, in particular, for electron beam sensitive (soft) materials such as nm size particles, organic materials, proteins or macro-molecules. We will demonstrate methodology of low dose electron holography for observing 3D structure for soft materials such as single Oleic acid molecules at atomic resolution. The main improvement of this new type of electron holography is based on two concepts. Firstly, the total electron dose is distributed over many images obtained at different defocus values from which the electron hologram is then reconstructed. Secondly, in contrast to the current tomographic methods that require projections from several directions, the 3D structural information of the nano-object is then extracted from this one hologram obtained from only one viewing direction.

Keywords: low dose electron microscopy, in-line electron holography, atomic resolution tomography, soft materials

Procedia PDF Downloads 192
1701 An Approach for Coagulant Dosage Optimization Using Soft Jar Test: A Case Study of Bangkhen Water Treatment Plant

Authors: Ninlawat Phuangchoke, Waraporn Viyanon, Setta Sasananan

Abstract:

The most important process of the water treatment plant process is the coagulation using alum and poly aluminum chloride (PACL), and the value of usage per day is a hundred thousand baht. Therefore, determining the dosage of alum and PACL are the most important factors to be prescribed. Water production is economical and valuable. This research applies an artificial neural network (ANN), which uses the Levenberg–Marquardt algorithm to create a mathematical model (Soft Jar Test) for prediction chemical dose used to coagulation such as alum and PACL, which input data consists of turbidity, pH, alkalinity, conductivity, and, oxygen consumption (OC) of Bangkhen water treatment plant (BKWTP) Metropolitan Waterworks Authority. The data collected from 1 January 2019 to 31 December 2019 cover changing seasons of Thailand. The input data of ANN is divided into three groups training set, test set, and validation set, which the best model performance with a coefficient of determination and mean absolute error of alum are 0.73, 3.18, and PACL is 0.59, 3.21 respectively.

Keywords: soft jar test, jar test, water treatment plant process, artificial neural network

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1700 Capability Prediction of Machining Processes Based on Uncertainty Analysis

Authors: Hamed Afrasiab, Saeed Khodaygan

Abstract:

Prediction of machining process capability in the design stage plays a key role to reach the precision design and manufacturing of mechanical products. Inaccuracies in machining process lead to errors in position and orientation of machined features on the part, and strongly affect the process capability in the final quality of the product. In this paper, an efficient systematic approach is given to investigate the machining errors to predict the manufacturing errors of the parts and capability prediction of corresponding machining processes. A mathematical formulation of fixture locators modeling is presented to establish the relationship between the part errors and the related sources. Based on this method, the final machining errors of the part can be accurately estimated by relating them to the combined dimensional and geometric tolerances of the workpiece – fixture system. This method is developed for uncertainty analysis based on the Worst Case and statistical approaches. The application of the presented method is illustrated through presenting an example and the computational results are compared with the Monte Carlo simulation results.

Keywords: process capability, machining error, dimensional and geometrical tolerances, uncertainty analysis

Procedia PDF Downloads 307
1699 Behavior of an Elevated Liquid Storage Tank under Near-Fault Earthquakes

Authors: Koushik Roy, Sourav Gur, Sudib K. Mishra

Abstract:

Evidence of pulse type features in near-fault ground motions has raised serious concern to the structural engineering community, in view of their possible implications on the behavior of structures located on the fault regions. Studies in the recent past explore the effects of pulse type ground motion on the special structures, such as transmission towers in view of their high flexibility. Identically, long period sloshing of liquid in the storage tanks under dynamic loading might increase their failure vulnerability under near-fault pulses. Therefore, the behavior of the elevated liquid storage tank is taken up in this study. Simple lumped mass model is considered, with the bilinear force-deformation hysteresis behavior. Set of near-fault seismic ground acceleration time histories are adopted for this purpose, along with the far-field records for comparison. It has been demonstrated that pulse type motions lead to significant increase of the responses; in particular, sloshing of the fluid mass could be as high as 5 times, then the far field counterpart. For identical storage capacity, slender tanks are found to be more vulnerable than the broad ones.

Keywords: far-field motion, hysteresis, liquid storage tank, near fault earthquake, sloshing

Procedia PDF Downloads 403