Search results for: conjugate Fourier series
3229 Simulation of Photovoltaic Array for Specified Ratings of Converter
Authors: Smita Pareek, Ratna Dahiya
Abstract:
The power generated by solar photovoltaic (PV) module depends on surrounding irradiance, temperature, shading conditions, and shading pattern. This paper presents a simulation of photovoltaic module using Matlab/Simulink. PV Array is also simulated by series and parallel connections of modules and their characteristics curves are given. Further PV module topology/configuration are proposed for 5.5kW inverter available in the literature. Shading of a PV array either complete or partial can have a significant impact on its power output and energy yield; therefore, the simulated model characteristics curves (I-V and P-V) are drawn for uniform shading conditions (USC) and then output power, voltage and current are calculated for variation in insolation for shading conditions. Additionally the characteristics curves are also given for a predetermined shadowing condition.Keywords: array, series, parallel, photovoltaic, partial shading
Procedia PDF Downloads 5563228 Research of Interaction between Layers of Compressed Composite Columns
Authors: Daumantas Zidanavicius
Abstract:
In order to investigate the bond between concrete and steel in the circular steel tube column filled with concrete, the 7 series of specimens were tested with the same geometrical parameters but different concrete properties. Two types of specimens were chosen. For the first type, the expansive additives to the concrete mixture were taken to increase internal forces. And for the second type, mechanical components were used. All 7 series of the short columns were modeled by FEM and tested experimentally. In the work, big attention was taken to the bond-slip models between steel and concrete. Results show that additives to concrete let increase the bond strength up to two times and the mechanical anchorage –up to 6 times compared to control specimens without additives and anchorage.Keywords: concrete filled steel tube, push-out test, bond slip relationship, bond stress distribution
Procedia PDF Downloads 1193227 A Long Short-Term Memory Based Deep Learning Model for Corporate Bond Price Predictions
Authors: Vikrant Gupta, Amrit Goswami
Abstract:
The fixed income market forms the basis of the modern financial market. All other assets in financial markets derive their value from the bond market. Owing to its over-the-counter nature, corporate bonds have relatively less data publicly available and thus is researched upon far less compared to Equities. Bond price prediction is a complex financial time series forecasting problem and is considered very crucial in the domain of finance. The bond prices are highly volatile and full of noise which makes it very difficult for traditional statistical time-series models to capture the complexity in series patterns which leads to inefficient forecasts. To overcome the inefficiencies of statistical models, various machine learning techniques were initially used in the literature for more accurate forecasting of time-series. However, simple machine learning methods such as linear regression, support vectors, random forests fail to provide efficient results when tested on highly complex sequences such as stock prices and bond prices. hence to capture these intricate sequence patterns, various deep learning-based methodologies have been discussed in the literature. In this study, a recurrent neural network-based deep learning model using long short term networks for prediction of corporate bond prices has been discussed. Long Short Term networks (LSTM) have been widely used in the literature for various sequence learning tasks in various domains such as machine translation, speech recognition, etc. In recent years, various studies have discussed the effectiveness of LSTMs in forecasting complex time-series sequences and have shown promising results when compared to other methodologies. LSTMs are a special kind of recurrent neural networks which are capable of learning long term dependencies due to its memory function which traditional neural networks fail to capture. In this study, a simple LSTM, Stacked LSTM and a Masked LSTM based model has been discussed with respect to varying input sequences (three days, seven days and 14 days). In order to facilitate faster learning and to gradually decompose the complexity of bond price sequence, an Empirical Mode Decomposition (EMD) has been used, which has resulted in accuracy improvement of the standalone LSTM model. With a variety of Technical Indicators and EMD decomposed time series, Masked LSTM outperformed the other two counterparts in terms of prediction accuracy. To benchmark the proposed model, the results have been compared with traditional time series models (ARIMA), shallow neural networks and above discussed three different LSTM models. In summary, our results show that the use of LSTM models provide more accurate results and should be explored more within the asset management industry.Keywords: bond prices, long short-term memory, time series forecasting, empirical mode decomposition
Procedia PDF Downloads 1283226 Realization of Hybrid Beams Inertial Amplifier
Authors: Somya Ranjan Patro, Abhigna Bhatt, Arnab Banerjee
Abstract:
Inertial amplifier has recently gained increasing attention as a new mechanism for vibration control of structures. Currently, theoretical investigations are undertaken by researchers to reveal its fundamentals and to understand its underline principles in altering the structural response of structures against dynamic loadings. This paper investigates experimental and analytical studies on the dynamic characteristics of hybrid beam inertial amplifier (HBIA). The analytical formulation of the HBIA has been derived by implementing the spectral element method and rigid body dynamics. This formulation gives the relation between dynamic force and the response of the structure in the frequency domain. Further, for validation of the proposed HBIA, the experiments have been performed. The experimental setup consists of a 3D printed HBIA of polylactic acid (PLA) material screwed at the base plate of the shaker system. Two numbers of accelerometers are used to study the response, one at the base plate of the shaker second one placed at the top of the inertial amplifier. A force transducer is also placed in between the base plate and the inertial amplifier to calculate the total amount of load transferred from the base plate to the inertial amplifier. The obtained time domain response from the accelerometers have been converted into the frequency domain using the Fast Fourier Transform (FFT) algorithm. The experimental transmittance values are successfully validated with the analytical results, providing us essential confidence in our proposed methodology.Keywords: inertial amplifier, fast fourier transform, natural frequencies, polylactic acid, transmittance, vibration absorbers
Procedia PDF Downloads 923225 Proactive Pure Handoff Model with SAW-TOPSIS Selection and Time Series Predict
Authors: Harold Vásquez, Cesar Hernández, Ingrid Páez
Abstract:
This paper approach cognitive radio technic and applied pure proactive handoff Model to decrease interference between PU and SU and comparing it with reactive handoff model. Through the study and analysis of multivariate models SAW and TOPSIS join to 3 dynamic prediction techniques AR, MA ,and ARMA. To evaluate the best model is taken four metrics: number failed handoff, number handoff, number predictions, and number interference. The result presented the advantages using this type of pure proactive models to predict changes in the PU according to the selected channel and reduce interference. The model showed better performance was TOPSIS-MA, although TOPSIS-AR had a higher predictive ability this was not reflected in the interference reduction.Keywords: cognitive radio, spectrum handoff, decision making, time series, wireless networks
Procedia PDF Downloads 4773224 Ion Beam Sputtering Deposition of Inorganic-Fluoropolymer Nano-Coatings for Real-Life Applications
Authors: M. Valentini, D. Melisi, M. A. Nitti, R A. Picca, M. C. Sportelli, E. Bonerba, G. Casamassima, N. Cioffi, L. Sabbatini, G. Tantillo, A. Valentini
Abstract:
In recent years antimicrobial coatings are receiving increasing attention due to their high demand in medical applications as well as in healthcare and hygiene. Research and technology are constantly involved to develop advanced finishing which can provide bacteriostatic growth without compromising the other typical properties of a textile as durability and non-toxicity, just to cite a few. Here we report on the antimicrobial coatings obtained, at room temperature and without the use of solvents, by means of the ion beam co-sputtering technique of an Ag target and a polytetrafluoroethylene one. In particular, such method allows to conjugate the well-known antimicrobial action of silver with the anti-stain and water-repellent properties of the fluoropolymer. Moreover, different Ag nanoparticle loadings (φ) were prepared by tuning the material deposition conditions achieving a fine control on film thickness and their antimicrobial/anti-stain properties.Keywords: antimicrobial, ion beam sputtering, nanocoatings, anti-stain
Procedia PDF Downloads 3833223 QSAR, Docking and E-pharmacophore Approach on Novel Series of HDAC Inhibitors with Thiophene Linker as Anticancer Agents
Authors: Harish Rajak, Preeti Patel
Abstract:
HDAC inhibitors can reactivate gene expression and inhibit the growth and survival of cancer cells. The 3D-QSAR and Pharmacophore modeling studies were performed to identify important pharmacophoric features and correlate 3D-chemical structure with biological activity. The pharmacophore hypotheses were developed using e-pharmacophore script and phase module. Pharmacophore hypothesis represents the 3D arrangement of molecular features necessary for activity. A series of 55 compounds with well-assigned HDAC inhibitory activity was used for 3D-QSAR model development. Best 3D-QSAR model, which is a five PLS factor model with good statistics and predictive ability, acquired Q2 (0.7293), R2 (0.9811) and standard deviation (0.0952). Molecular docking were performed using Histone Deacetylase protein (PDB ID: 1t69) and prepared series of hydroxamic acid based HDAC inhibitors. Docking study of compound 43 show significant binding interactions Ser 276 and oxygen atom of dioxine cap region, Gly 151 and amino group and Asp 267 with carboxyl group of CONHOH, which are essential for anticancer activity. On docking, most of the compounds exhibited better glide score values between -8 to -10.5. We have established structure activity correlation using docking, energetic based pharmacophore modelling, pharmacophore and atom based 3D QSAR model. The results of these studies were further used for the design and testing of new HDAC analogs.Keywords: Docking, e-pharmacophore, HDACIs, QSAR, Suberoylanilidehydroxamic acid.
Procedia PDF Downloads 2923222 Fault Analysis of Induction Machine Using Finite Element Method (FEM)
Authors: Wiem Zaabi, Yemna Bensalem, Hafedh Trabelsi
Abstract:
The paper presents a finite element (FE) based efficient analysis procedure for induction machine (IM). The FE formulation approaches are proposed to achieve this goal: the magnetostatic and the non-linear transient time stepped formulations. The study based on finite element models offers much more information on the phenomena characterizing the operation of electrical machines than the classical analytical models. This explains the increase of the interest for the finite element investigations in electrical machines. Based on finite element models, this paper studies the influence of the stator and the rotor faults on the behavior of the IM. In this work, a simple dynamic model for an IM with inter-turn winding fault and a broken bar fault is presented. This fault model is used to study the IM under various fault conditions and severity. The simulation results are conducted to validate the fault model for different levels of fault severity. The comparison of the results obtained by simulation tests allowed verifying the precision of the proposed FEM model. This paper presents a technical method based on Fast Fourier Transform (FFT) analysis of stator current and electromagnetic torque to detect the faults of broken rotor bar. The technique used and the obtained results show clearly the possibility of extracting signatures to detect and locate faults.Keywords: Finite element Method (FEM), Induction motor (IM), short-circuit fault, broken rotor bar, Fast Fourier Transform (FFT) analysis
Procedia PDF Downloads 2913221 Fuzzy Time Series- Markov Chain Method for Corn and Soybean Price Forecasting in North Carolina Markets
Authors: Selin Guney, Andres Riquelme
Abstract:
Among the main purposes of optimal and efficient forecasts of agricultural commodity prices is to guide the firms to advance the economic decision making process such as planning business operations and marketing decisions. Governments are also the beneficiaries and suppliers of agricultural price forecasts. They use this information to establish a proper agricultural policy, and hence, the forecasts affect social welfare and systematic errors in forecasts could lead to a misallocation of scarce resources. Various empirical approaches have been applied to forecast commodity prices that have used different methodologies. Most commonly-used approaches to forecast commodity sectors depend on classical time series models that assume values of the response variables are precise which is quite often not true in reality. Recently, this literature has mostly evolved to a consideration of fuzzy time series models that provide more flexibility in terms of the classical time series models assumptions such as stationarity, and large sample size requirement. Besides, fuzzy modeling approach allows decision making with estimated values under incomplete information or uncertainty. A number of fuzzy time series models have been developed and implemented over the last decades; however, most of them are not appropriate for forecasting repeated and nonconsecutive transitions in the data. The modeling scheme used in this paper eliminates this problem by introducing Markov modeling approach that takes into account both the repeated and nonconsecutive transitions. Also, the determination of length of interval is crucial in terms of the accuracy of forecasts. The problem of determining the length of interval arbitrarily is overcome and a methodology to determine the proper length of interval based on the distribution or mean of the first differences of series to improve forecast accuracy is proposed. The specific purpose of this paper is to propose and investigate the potential of a new forecasting model that integrates methodologies for determining the proper length of interval based on the distribution or mean of the first differences of series and Fuzzy Time Series- Markov Chain model. Moreover, the accuracy of the forecasting performance of proposed integrated model is compared to different univariate time series models and the superiority of proposed method over competing methods in respect of modelling and forecasting on the basis of forecast evaluation criteria is demonstrated. The application is to daily corn and soybean prices observed at three commercially important North Carolina markets; Candor, Cofield and Roaring River for corn and Fayetteville, Cofield and Greenville City for soybeans respectively. One main conclusion from this paper is that using fuzzy logic improves the forecast performance and accuracy; the effectiveness and potential benefits of the proposed model is confirmed with small selection criteria value such MAPE. The paper concludes with a discussion of the implications of integrating fuzzy logic and nonarbitrary determination of length of interval for the reliability and accuracy of price forecasts. The empirical results represent a significant contribution to our understanding of the applicability of fuzzy modeling in commodity price forecasts.Keywords: commodity, forecast, fuzzy, Markov
Procedia PDF Downloads 2113220 Impact of the Simplification of Licensing Procedures for Industrial Complexes on Supply of Industrial Complexes and Regional Policies
Authors: Seung-Seok Bak, Chang-Mu Jung
Abstract:
An enough amount supply of industrial complexes is an important national policy in South Korea, which is highly dependent on foreign trade. A development process of the industrial complex can distinguish between the planning stage and the construction stage. The planning stage consists of the process of consulting with many stakeholders on the contents of the development of industrial complex, feasibility study, compliance with the Regional policies, and so on. The industrial complex planning stage, including licensing procedure, usually takes about three years in South Korea. The government determined that the appropriate supply of industrial complexes have been delayed, due to the long licensing period and drafted a law to shorten the license period in 2008. The law was expected to shorten the period of licensing, which was about three years, to six months. This paper attempts to show that the shortening of the licensing period does not positively affect the appropriate supply of industrial complexes. To do this, we used Interrupted Time Series Designs. As a result, it was found that the supply of industrial complexes was influenced more by other factors such as actual industrial complex demand of private sector and macro-level economic variables. In addition, the specific provisions of the law conflict with local policy and cause some problems such as damage to nature and agricultural land, traffic congestion.Keywords: development of industrial complexes, industrial complexes, interrupted time series designs, simplification of licensing procedures for industrial complexes, time series regression
Procedia PDF Downloads 2863219 Dynamics and Advection in a Vortex Parquet on the Plane
Authors: Filimonova Alexanra
Abstract:
Inviscid incompressible fluid flows are considered. The object of the study is a vortex parquet – a structure consisting of distributed vortex spots of different directions, occupying the entire plane. The main attention is paid to the study of advection processes of passive particles in the corresponding velocity field. The dynamics of the vortex structures is considered in a rectangular region under the assumption that periodic boundary conditions are imposed on the stream function. Numerical algorithms are based on the solution of the initial-boundary value problem for nonstationary Euler equations in terms of vorticity and stream function. For this, the spectral-vortex meshless method is used. It is based on the approximation of the stream function by the Fourier series cut and the approximation of the vorticity field by the least-squares method from its values in marker particles. A vortex configuration, consisting of four vortex patches is investigated. Results of a numerical study of the dynamics and interaction of the structure are presented. The influence of the patch radius and the relative position of positively and negatively directed patches on the processes of interaction and mixing is studied. The obtained results correspond to the following possible scenarios: the initial configuration does not change over time; the initial configuration forms a new structure, which is maintained for longer times; the initial configuration returns to its initial state after a certain period of time. The processes of mass transfer of vorticity by liquid particles on a plane were calculated and analyzed. The results of a numerical analysis of the particles dynamics and trajectories on the entire plane and the field of local Lyapunov exponents are presented.Keywords: ideal fluid, meshless methods, vortex structures in liquids, vortex parquet.
Procedia PDF Downloads 593218 Embedded System of Signal Processing on FPGA: Underwater Application Architecture
Authors: Abdelkader Elhanaoui, Mhamed Hadji, Rachid Skouri, Said Agounad
Abstract:
The purpose of this paper is to study the phenomenon of acoustic scattering by using a new method. The signal processing (Fast Fourier Transform FFT Inverse Fast Fourier Transform iFFT and BESSEL functions) is widely applied to obtain information with high precision accuracy. Signal processing has a wider implementation in general-purpose pro-cessors. Our interest was focused on the use of FPGAs (Field-Programmable Gate Ar-rays) in order to minimize the computational complexity in single processor architecture, then be accelerated on FPGA and meet real-time and energy efficiency requirements. Gen-eral-purpose processors are not efficient for signal processing. We implemented the acous-tic backscattered signal processing model on the Altera DE-SOC board and compared it to Odroid xu4. By comparison, the computing latency of Odroid xu4 and FPGA is 60 sec-onds and 3 seconds, respectively. The detailed SoC FPGA-based system has shown that acoustic spectra are performed up to 20 times faster than the Odroid xu4 implementation. FPGA-based system of processing algorithms is realized with an absolute error of about 10⁻³. This study underlines the increasing importance of embedded systems in underwater acoustics, especially in non-destructive testing. It is possible to obtain information related to the detection and characterization of submerged cells. So we have achieved good exper-imental results in real-time and energy efficiency.Keywords: DE1 FPGA, acoustic scattering, form function, signal processing, non-destructive testing
Procedia PDF Downloads 713217 Allylation of Active Methylene Compounds with Cyclic Baylis-Hillman Alcohols: Why Is It Direct and Not Conjugate?
Authors: Karim Hrratha, Khaled Essalahb, Christophe Morellc, Henry Chermettec, Salima Boughdiria
Abstract:
Among the carbon-carbon bond formation types, allylation of active methylene compounds with cyclic Baylis-Hillman (BH) alcohols is a reliable and widely used method. This reaction is a very attractive tool in organic synthesis of biological and biodiesel compounds. Thus, in view of an insistent and peremptory request for an efficient and straightly method for synthesizing the desired product, a thorough analysis of various aspects of the reaction processes is an important task. The product afforded by the reaction of active methylene with BH alcohols depends largely on the experimental conditions, notably on the catalyst properties. All experiments reported that catalysis is needed for this reaction type because of the poor ability of alcohol hydroxyl group to be as a suitable leaving group. Within the catalysts, several transition- metal based have been used such as palladium in the presence of acid or base and have been considered as reliable methods. Furthemore, acid catalysts such as BF3.OEt2, BiX3 (X= Cl, Br, I, (OTf)3), InCl3, Yb(OTf)3, FeCl3, p-TsOH and H-montmorillonite have been employed to activate the C-C bond formation through the alkylation of active methylene compounds. Interestingly a report of a smoothly process for the ability of 4-imethyaminopyridine(DMAP) to catalyze the allylation reaction of active methylene compounds with cyclic Baylis-Hillman (BH) alcohol appeared recently. However, the reaction mechanism remains ambiguous, since the C- allylation process leads to an unexpected product (noted P1), corresponding to a direct allylation instead of conjugate allylation, which involves the most electrophilic center according to the electron withdrawing group CO effect. The main objective of the present theoretical study is to better understand the role of the DMAP catalytic activity as well as the process leading to the end- product (P1) for the catalytic reaction of a cyclic BH alcohol with active methylene compounds. For that purpose, we have carried out computations of a set of active methylene compounds varying by R1 and R2 toward the same alcohol, and we have attempted to rationalize the mechanisms thanks to the acid–base approach, and conceptual DFT tools such as chemical potential, hardness, Fukui functions, electrophilicity index and dual descriptor, as these approaches have shown a good prediction of reactions products.The present work is then organized as follows: In a first part some computational details will be given, introducing the reactivity indexes used in the present work, then Section 3 is dedicated to the discussion of the prediction of the selectivity and regioselectivity. The paper ends with some concluding remarks. In this work, we have shown, through DFT method at the B3LYP/6-311++G(d,p) level of theory that: The allylation of active methylene compounds with cyclic BH alcohol is governed by orbital control character. Hence the end- product denoted P1 is generated by direct allylation.Keywords: DFT calculation, gas phase pKa, theoretical mechanism, orbital control, charge control, Fukui function, transition state
Procedia PDF Downloads 2923216 Effect of Damper Combinations in Series or Parallel on Structural Response
Authors: Ajay Kumar Sinha, Sharad Singh, Anukriti Sinha
Abstract:
Passive energy dissipation method for earthquake protection of structures is undergoing developments for improved performance. Combined use of different types of damping mechanisms has shown positive results in the near past. Different supplemental damping methods like viscous damping, frictional damping and metallic damping are being combined together for optimum performance. The conventional method of connecting passive dampers to structures is a parallel connection between the damper unit and structural member. Researchers are investigating coupling effect of different types of dampers. The most popular choice among the research community is coupling of viscous dampers and frictional dampers. The series and parallel coupling of these damping units are being studied for relative performance of the coupled system on response control of structures against earthquake. In this paper an attempt has been made to couple Fluid Viscous Dampers and Frictional Dampers in series and parallel to form a single unit of damping system. The relative performance of the coupled units has been studied on three dimensional reinforced concrete framed structure. The current theories of structural dynamics in practice for viscous damping and frictional damping have been incorporated in this study. The time history analysis of the structural system with coupled damper units, uncoupled damper units as well as of structural system without any supplemental damping has been performed in this study. The investigations reported in this study show significant improved performance of coupled system. A higher natural frequency of the system outside the forcing frequency has been obtained for structural systems with coupled damper units as against the other cases. The structural response of the structure in terms of storey displacement and storey drift show significant improvement for the case with coupled damper units as against the cases with uncoupled units or without any supplemental damping. The results are promising in terms of improved response of the structure with coupled damper units. Further investigations in this regard for a comparative performance of the series and parallel coupled systems will be carried out to study the optimum behavior of these coupled systems for enhanced response control of structural systems.Keywords: frictional damping, parallel coupling, response control, series coupling, supplemental damping, viscous damping
Procedia PDF Downloads 4433215 Analyzing the Empirical Link between Islamic Finance and Growth of Real Output: A Time Series Application to Pakistan
Authors: Nazima Ellahi, Danish Ramzan
Abstract:
There is a growing trend among development economists regarding the importance of financial sector for economic development and growth activities. The development thus introduced, helps to promote welfare effects and poverty alleviation. This study is an attempt to find the nature of link between Islamic banking financing and development of output growth for Pakistan. Time series data set has been utilized for a time period ranging from 1990 to 2010. Following the Phillip Perron (PP) and Augmented Dicky Fuller (ADF) test of unit root this study applied Ordinary Least Squares (OLS) method of estimation and found encouraging results in favor of promoting the Islamic banking practices in Pakistan.Keywords: Islamic finance, poverty alleviation, economic growth, finance, commerce
Procedia PDF Downloads 3363214 Applying Arima Data Mining Techniques to ERP to Generate Sales Demand Forecasting: A Case Study
Authors: Ghaleb Y. Abbasi, Israa Abu Rumman
Abstract:
This paper modeled sales history archived from 2012 to 2015 bulked in monthly bins for five products for a medical supply company in Jordan. The sales forecasts and extracted consistent patterns in the sales demand history from the Enterprise Resource Planning (ERP) system were used to predict future forecasting and generate sales demand forecasting using time series analysis statistical technique called Auto Regressive Integrated Moving Average (ARIMA). This was used to model and estimate realistic sales demand patterns and predict future forecasting to decide the best models for five products. Analysis revealed that the current replenishment system indicated inventory overstocking.Keywords: ARIMA models, sales demand forecasting, time series, R code
Procedia PDF Downloads 3773213 Improving the Performance of Requisition Document Online System for Royal Thai Army by Using Time Series Model
Authors: D. Prangchumpol
Abstract:
This research presents a forecasting method of requisition document demands for Military units by using Exponential Smoothing methods to analyze data. The data used in the forecast is an actual data requisition document of The Adjutant General Department. The results of the forecasting model to forecast the requisition of the document found that Holt–Winters’ trend and seasonality method of α=0.1, β=0, γ=0 is appropriate and matches for requisition of documents. In addition, the researcher has developed a requisition online system to improve the performance of requisition documents of The Adjutant General Department, and also ensuring that the operation can be checked.Keywords: requisition, holt–winters, time series, royal thai army
Procedia PDF Downloads 2963212 Dorsal Root Ganglion Neuromodulation as an Alternative to Opioids in the Evolving Healthcare Crisis
Authors: Adam J. Carinci
Abstract:
Background: The opioid epidemic is the most pressing healthcare crisis of our time. There is increasing recognition that opioids have limited long-term efficacy and are associated with hyperalgesia, addiction, and increased morbidity and mortality. Therefore, alternative strategies to combat chronic pain are paramount. We initiated a multicenter retrospective case series to review the efficacy of DRG stimulation in facilitating opioid tapering, opioid discontinuation and as a viable alternative to chronic opioid therapy. Purpose: The dorsal root ganglion (DRG) plays a key role in the development and maintenance of pain. Recent innovations in neuromodulation, specifically, dorsal root ganglion stimulation, offers an effective alternative to opioids in the treatment of chronic pain. This retrospective case series demonstrates preliminary evidence that DRG stimulation facilitates opioid tapering, opioid discontinuation and presents a viable alternative to chronic opioid therapy. Procedure: This small multicenter retrospective case series provides preliminary evidence that DRG stimulation facilitates opioid weaning, opioid tapering and is a viable option to opioid therapy in the treatment of chronic pain. A retrospective analysis was completed. Visual analog scale pain scores and pain medication usage were collected at the baseline visit and after four weeks, 3 months and 6 months of treatment. Ten consecutive patients across two study centers were included. The pain was rated 7.38 at baseline and decreased to 1.50 at the 4-week follow-up, a reduction of 79.5%. All patients significantly decreased their opioid pain medication use with an average > 30% reduction in morphine equivalents and four were able to discontinue their medications entirely. Conclusion: This Retrospective case series demonstrates preliminary evidence that DRG stimulation facilitates opioid tapering, opioid discontinuation and presents a viable alternative to chronic opioid therapy.Keywords: dorsal root ganglion, neuromodulation, opioid sparing, stimulation
Procedia PDF Downloads 1043211 Dynamic Modeling of the Exchange Rate in Tunisia: Theoretical and Empirical Study
Authors: Chokri Slim
Abstract:
The relative failure of simultaneous equation models in the seventies has led researchers to turn to other approaches that take into account the dynamics of economic and financial systems. In this paper, we use an approach based on vector autoregressive model that is widely used in recent years. Their popularity is due to their flexible nature and ease of use to produce models with useful descriptive characteristics. It is also easy to use them to test economic hypotheses. The standard econometric techniques assume that the series studied are stable over time (stationary hypothesis). Most economic series do not verify this hypothesis, which assumes, when one wishes to study the relationships that bind them to implement specific techniques. This is cointegration which characterizes non-stationary series (integrated) with a linear combination is stationary, will also be presented in this paper. Since the work of Johansen, this approach is generally presented as part of a multivariate analysis and to specify long-term stable relationships while at the same time analyzing the short-term dynamics of the variables considered. In the empirical part, we have applied these concepts to study the dynamics of of the exchange rate in Tunisia, which is one of the most important economic policy of a country open to the outside. According to the results of the empirical study by the cointegration method, there is a cointegration relationship between the exchange rate and its determinants. This relationship shows that the variables have a significant influence in determining the exchange rate in Tunisia.Keywords: stationarity, cointegration, dynamic models, causality, VECM models
Procedia PDF Downloads 3463210 Forecasting Amman Stock Market Data Using a Hybrid Method
Authors: Ahmad Awajan, Sadam Al Wadi
Abstract:
In this study, a hybrid method based on Empirical Mode Decomposition and Holt-Winter (EMD-HW) is used to forecast Amman stock market data. First, the data are decomposed by EMD method into Intrinsic Mode Functions (IMFs) and residual components. Then, all components are forecasted by HW technique. Finally, forecasting values are aggregated together to get the forecasting value of stock market data. Empirical results showed that the EMD- HW outperform individual forecasting models. The strength of this EMD-HW lies in its ability to forecast non-stationary and non- linear time series without a need to use any transformation method. Moreover, EMD-HW has a relatively high accuracy comparing with eight existing forecasting methods based on the five forecast error measures.Keywords: Holt-Winter method, empirical mode decomposition, forecasting, time series
Procedia PDF Downloads 1213209 Impact Location From Instrumented Mouthguard Kinematic Data In Rugby
Authors: Jazim Sohail, Filipe Teixeira-Dias
Abstract:
Mild traumatic brain injury (mTBI) within non-helmeted contact sports is a growing concern due to the serious risk of potential injury. Extensive research is being conducted looking into head kinematics in non-helmeted contact sports utilizing instrumented mouthguards that allow researchers to record accelerations and velocities of the head during and after an impact. This does not, however, allow the location of the impact on the head, and its magnitude and orientation, to be determined. This research proposes and validates two methods to quantify impact locations from instrumented mouthguard kinematic data, one using rigid body dynamics, the other utilizing machine learning. The rigid body dynamics technique focuses on establishing and matching moments from Euler’s and torque equations in order to find the impact location on the head. The methodology is validated with impact data collected from a lab test with the dummy head fitted with an instrumented mouthguard. Additionally, a Hybrid III Dummy head finite element model was utilized to create synthetic kinematic data sets for impacts from varying locations to validate the impact location algorithm. The algorithm calculates accurate impact locations; however, it will require preprocessing of live data, which is currently being done by cross-referencing data timestamps to video footage. The machine learning technique focuses on eliminating the preprocessing aspect by establishing trends within time-series signals from instrumented mouthguards to determine the impact location on the head. An unsupervised learning technique is used to cluster together impacts within similar regions from an entire time-series signal. The kinematic signals established from mouthguards are converted to the frequency domain before using a clustering algorithm to cluster together similar signals within a time series that may span the length of a game. Impacts are clustered within predetermined location bins. The same Hybrid III Dummy finite element model is used to create impacts that closely replicate on-field impacts in order to create synthetic time-series datasets consisting of impacts in varying locations. These time-series data sets are used to validate the machine learning technique. The rigid body dynamics technique provides a good method to establish accurate impact location of impact signals that have already been labeled as true impacts and filtered out of the entire time series. However, the machine learning technique provides a method that can be implemented with long time series signal data but will provide impact location within predetermined regions on the head. Additionally, the machine learning technique can be used to eliminate false impacts captured by sensors saving additional time for data scientists using instrumented mouthguard kinematic data as validating true impacts with video footage would not be required.Keywords: head impacts, impact location, instrumented mouthguard, machine learning, mTBI
Procedia PDF Downloads 2053208 Characterization of Hyaluronic Acid-Based Injections Used on Rejuvenation Skin Treatments
Authors: Lucas Kurth de Azambuja, Loise Silveira da Silva, Gean Vitor Salmoria, Darlan Dallacosta, Carlos Rodrigo de Mello Roesler
Abstract:
This work provides a physicochemical and thermal characterization assessment of three different hyaluronic acid (HA)-based injections used for rejuvenation skin treatments. The three products analyzed are manufactured by the same manufacturer and commercialized for application on different skin levels. According to the manufacturer, all three HA-based injections are crosslinked and have a concentration of 23 mg/mL of HA, and 0.3% of lidocaine. Samples were characterized by Fourier-transformed infrared (FTIR), differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), and scanning electron microscope (SEM) techniques. FTIR analysis resulted in a similar spectrum when comparing the different products. DSC analysis demonstrated that the fusion points differ in each product, with a higher fusion temperature observed in specimen A, which is used for subcutaneous applications, when compared with B and C, which are used for the middle dermis and deep dermis, respectively. TGA data demonstrated a considerable mass loss at 100°C, which means that the product has more than 50% of water in its composition. TGA analysis also showed that Specimen A had a lower mass loss at 100°C when compared to Specimen C. A mass loss of around 220°C was observed on all samples, characterizing the presence of hyaluronic acid. SEM images displayed a similar structure on all samples analyzed, with a thicker layer for Specimen A when compared with B and C. This series of analyses demonstrated that, as expected, the physicochemical and thermal properties of the products differ according to their application. Furthermore, to better characterize the crosslinking degree of each product and their mechanical properties, a set of different techniques should be applied in parallel to correlate the results and, thereby, relate injection application with material properties.Keywords: hyaluronic acid, characterization, soft-tissue fillers, injectable gels
Procedia PDF Downloads 823207 A New Floating Point Implementation of Base 2 Logarithm
Authors: Ahmed M. Mansour, Ali M. El-Sawy, Ahmed T. Sayed
Abstract:
Logarithms reduce products to sums and powers to products; they play an important role in signal processing, communication and information theory. They are primarily used for hardware calculations, handling multiplications, divisions, powers, and roots effectively. There are three commonly used bases for logarithms; the logarithm with base-10 is called the common logarithm, the natural logarithm with base-e and the binary logarithm with base-2. This paper demonstrates different methods of calculation for log2 showing the complexity of each and finds out the most accurate and efficient besides giving in- sights to their hardware design. We present a new method called Floor Shift for fast calculation of log2, and then we combine this algorithm with Taylor series to improve the accuracy of the output, we illustrate that by using two examples. We finally compare the algorithms and conclude with our remarks.Keywords: logarithms, log2, floor, iterative, CORDIC, Taylor series
Procedia PDF Downloads 5173206 Kosodum Tribal Dance Series, Series 1 Dhemsa and Rela: An Example of an Exceptional Inter-Organizational Cooperation for the Preservation of Tribal Dance Form
Authors: Vidya Meshram, Shrinivas Surpam, Akshay Kokode, Laxman Shedmake, Ramesh Parchake
Abstract:
Tribal dance form is an integral part of the tribal culture as they represent the traditional culture of the tribal community. This article provide the reasons for the need to preserve the tribal dance form of Indian tribal people as a part of the cultural heritage. This article describe our experience of co-ordination of three organization to conduct a dance performance of Gond Tribe artists in the Mumbai City. This is the part of the promotion of tribal artist at big platform, although the preservation and awareness of tribal dance form in the metro cities. This is an example of an exceptional Inter-Organizational Cooperation between Kosodum Welfare Private Limited, GondwanaJangomDhemsaRelaNrutya Dal &GondwanaMitraMandal, Mumbai, for the preservation of tribal dance form.Keywords: tribal, art, culture, preservation
Procedia PDF Downloads 1513205 Geological Characteristics and Hydrocarbon Potential of M’Rar Formation Within NC-210, Atshan Saddle Ghadamis-Murzuq Basins, Libya
Authors: Sadeg M. Ghnia, Mahmud Alghattawi
Abstract:
The NC-210 study area is located in Atshan Saddle between both Ghadamis and Murzuq basins, west Libya. The preserved Palaeozoic successions are predominantly clastics reaching thickness of more than 20,000 ft in northern Ghadamis Basin depocenter. The Carboniferous series consist of interbedded sandstone, siltstone, shale, claystone and minor limestone deposited in a fluctuating shallow marine to brackish lacustrine/fluviatile environment which attain maximum thickness of over 5,000ft in the area of Atshan Saddle and recorded 3,500 ft. in outcrops of Murzuq Basin flanks. The Carboniferous strata was uplifted and eroded during Late Paleozoic and early Mesozoic time in northern Ghadamis Basin and Atshan Saddle. The M'rar Formation age is Tournaisian to Late Serpukhovian based on palynological markers and contains about 12 cycles of sandstone and shale deposited in shallow to outer neritic deltaic settings. The hydrocarbons in the M'rar reservoirs possibly sourced from the Lower Silurian and possibly Frasinian radioactive hot shales. The M'rar Formation lateral, vertical and thickness distribution is possibly influenced by the reactivation of Tumarline Strik-Slip fault and its conjugate faults. A pronounced structural paleohighs and paleolows, trending SE & NW through the Gargaf Saddle, is possibly indicative of the present of two sub-basins in the area of Atshan Saddle. A number of identified seismic reflectors from existing 2D seismic covering Atshan Saddle reflect M’rar deltaic 12 sandstone cycles. M’rar7, M’rar9, M’rar10 and M’rar12 are characterized by high amplitude reflectors, while M’rar2 and M’rar6 are characterized by medium amplitude reflectors. These horizons are productive reservoirs in the study area. Available seismic data in the study area contributed significantly to the identification of M’rar potential traps, which are prominently 3- way dip closure against fault zone. Also seismic data indicates the presence of a significant strikeslip component with the development of flower-structure. The M'rar Formation hydrocarbon discoveries are concentrated mainly in the Atshan Saddle located in southern Ghadamis Basin, Libya and Illizi Basin in southeast of Algeria. Significant additional hydrocarbons may be present in areas adjacent to the Gargaf Uplift, along structural highs and fringing the Hoggar Uplift, providing suitable migration pathways.Keywords: hydrocarbon potential, stratigraphy, Ghadamis basin, seismic, well data integration
Procedia PDF Downloads 613204 Electroencephalography (EEG) Analysis of Alcoholic and Control Subjects Using Multiscale Permutation Entropy
Authors: Lal Hussain, Wajid Aziz, Sajjad Ahmed Nadeem, Saeed Arif Shah, Abdul Majid
Abstract:
Brain electrical activity as reflected in Electroencephalography (EEG) have been analyzed and diagnosed using various techniques. Among them, complexity measure, nonlinearity, disorder, and unpredictability play vital role due to the nonlinear interconnection between functional and anatomical subsystem emerged in brain in healthy state and during various diseases. There are many social and economical issues of alcoholic abuse as memory weakness, decision making, impairments, and concentrations etc. Alcoholism not only defect the brains but also associated with emotional, behavior, and cognitive impairments damaging the white and gray brain matters. A recently developed signal analysis method i.e. Multiscale Permutation Entropy (MPE) is proposed to estimate the complexity of long-range temporal correlation time series EEG of Alcoholic and Control subjects acquired from University of California Machine Learning repository and results are compared with MSE. Using MPE, coarsed grained series is first generated and the PE is computed for each coarsed grained time series against the electrodes O1, O2, C3, C4, F2, F3, F4, F7, F8, Fp1, Fp2, P3, P4, T7, and T8. The results computed against each electrode using MPE gives higher significant values as compared to MSE as well as mean rank differences accordingly. Likewise, ROC and Area under the ROC also gives higher separation against each electrode using MPE in comparison to MSE.Keywords: electroencephalogram (EEG), multiscale permutation entropy (MPE), multiscale sample entropy (MSE), permutation entropy (PE), mann whitney test (MMT), receiver operator curve (ROC), complexity measure
Procedia PDF Downloads 4813203 Analysis of Spatial and Temporal Data Using Remote Sensing Technology
Authors: Kapil Pandey, Vishnu Goyal
Abstract:
Spatial and temporal data analysis is very well known in the field of satellite image processing. When spatial data are correlated with time, series analysis it gives the significant results in change detection studies. In this paper the GIS and Remote sensing techniques has been used to find the change detection using time series satellite imagery of Uttarakhand state during the years of 1990-2010. Natural vegetation, urban area, forest cover etc. were chosen as main landuse classes to study. Landuse/ landcover classes within several years were prepared using satellite images. Maximum likelihood supervised classification technique was adopted in this work and finally landuse change index has been generated and graphical models were used to present the changes.Keywords: GIS, landuse/landcover, spatial and temporal data, remote sensing
Procedia PDF Downloads 4233202 Integrated Intensity and Spatial Enhancement Technique for Color Images
Authors: Evan W. Krieger, Vijayan K. Asari, Saibabu Arigela
Abstract:
Video imagery captured for real-time security and surveillance applications is typically captured in complex lighting conditions. These less than ideal conditions can result in imagery that can have underexposed or overexposed regions. It is also typical that the video is too low in resolution for certain applications. The purpose of security and surveillance video is that we should be able to make accurate conclusions based on the images seen in the video. Therefore, if poor lighting and low resolution conditions occur in the captured video, the ability to make accurate conclusions based on the received information will be reduced. We propose a solution to this problem by using image preprocessing to improve these images before use in a particular application. The proposed algorithm will integrate an intensity enhancement algorithm with a super resolution technique. The intensity enhancement portion consists of a nonlinear inverse sign transformation and an adaptive contrast enhancement. The super resolution section is a single image super resolution technique is a Fourier phase feature based method that uses a machine learning approach with kernel regression. The proposed technique intelligently integrates these algorithms to be able to produce a high quality output while also being more efficient than the sequential use of these algorithms. This integration is accomplished by performing the proposed algorithm on the intensity image produced from the original color image. After enhancement and super resolution, a color restoration technique is employed to obtain an improved visibility color image.Keywords: dynamic range compression, multi-level Fourier features, nonlinear enhancement, super resolution
Procedia PDF Downloads 5433201 Comparing Forecasting Performances of the Bass Diffusion Model and Time Series Methods for Sales of Electric Vehicles
Authors: Andreas Gohs, Reinhold Kosfeld
Abstract:
This study should be of interest for practitioners who want to predict precisely the sales numbers of vehicles equipped with an innovative propulsion technology as well as for researchers interested in applied (regional) time series analysis. The study is based on the numbers of new registrations of pure electric and hybrid cars. Methods of time series analysis like ARIMA are compared with the Bass Diffusion-model concerning their forecasting performances for new registrations in Germany at the national and federal state levels. Especially it is investigated if the additional information content from regional data increases the forecasting accuracy for the national level by adding predictions for the federal states. Results of parameters of the Bass Diffusion Model estimated for Germany and its sixteen federal states are reported. While the focus of this research is on the German market, estimation results are also provided for selected European and other countries. Concerning Bass-parameters and forecasting performances, we get very different results for Germany's federal states and the member states of the European Union. This corresponds to differences across the EU-member states in the adoption process of this innovative technology. Concerning the German market, the adoption is rather proceeded in southern Germany and stays behind in Eastern Germany except for Berlin.Keywords: bass diffusion model, electric vehicles, forecasting performance, market diffusion
Procedia PDF Downloads 1553200 Risk Assessments of Longest Dry Spells Phenomenon in Northern Tunisia
Authors: Majid Mathlouthi, Fethi Lebdi
Abstract:
Throughout the world, the extent and magnitude of droughts have economic, social and environmental consequences. Today climate change has become more and more felt; most likely they increase the frequency and duration of droughts. An analysis by event of dry event, from series of observations of the daily rainfall is carried out. A daily precipitation threshold value has been set. A catchment localized in Northern Tunisia where the average rainfall is about 600 mm has been studied. Rainfall events are defined as an uninterrupted series of rainfall days understanding at least a day having received a precipitation superior or equal to a fixed threshold. The dry events are constituted of a series of dry days framed by two successive rainfall events. A rainfall event is a vector of coordinates the duration, the rainfall depth per event and the duration of the dry event. The depth and duration are found to be correlated. So we use conditional probabilities to analyse the depth per event. The negative binomial distribution fits well the dry event. The duration of the rainfall event follows a geometric distribution. The length of the climatically cycle adjusts to the Incomplete Gamma. Results of this analysis was used to study of the effects of climate change on water resources and crops and to calibrate precipitation models with little rainfall records. In response to long droughts in the basin, the drought management system is based on three phases during each of the three phases; different measurements are applied and executed. The first is before drought, preparedness and early warning; the second is drought management, mitigation in the event of drought; and the last subsequent drought, when the drought is over.Keywords: dry spell, precipitation threshold, climate vulnerability, adaptation measures
Procedia PDF Downloads 80