Search results for: multifractal time series analysis
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 40915

Search results for: multifractal time series analysis

40345 Methaheuristic Bat Algorithm in Training of Feed-Forward Neural Network for Stock Price Prediction

Authors: Marjan Golmaryami, Marzieh Behzadi

Abstract:

Recent developments in stock exchange highlight the need for an efficient and accurate method that helps stockholders make better decision. Since stock markets have lots of fluctuations during the time and different effective parameters, it is difficult to make good decisions. The purpose of this study is to employ artificial neural network (ANN) which can deal with time series data and nonlinear relation among variables to forecast next day stock price. Unlike other evolutionary algorithms which were utilized in stock exchange prediction, we trained our proposed neural network with metaheuristic bat algorithm, with fast and powerful convergence and applied it in stock price prediction for the first time. In order to prove the performance of the proposed method, this research selected a 7 year dataset from Parsian Bank stocks and after imposing data preprocessing, used 3 types of ANN (back propagation-ANN, particle swarm optimization-ANN and bat-ANN) to predict the closed price of stocks. Afterwards, this study engaged MATLAB to simulate 3 types of ANN, with the scoring target of mean absolute percentage error (MAPE). The results may be adapted to other companies stocks too.

Keywords: artificial neural network (ANN), bat algorithm, particle swarm optimization algorithm (PSO), stock exchange

Procedia PDF Downloads 543
40344 Tga Analysis on the Decomposition of Active Material of Aquilaria Malaccencis

Authors: Nurshafika Adira Bt Audi Ashraf, Habsah Alwi

Abstract:

This study describes the series of analysis conducted after the use of Vacuum far Infra Red. Parameter including the constant drying temperature at 40°C with pressure difference (-400 bar, -500 bar and -600 bar) and constant drying pressure at -400 bar with difference temperature (40°C, 50°C and 60°C). The dried leaves with constant temperature and constant pressure is compared with the fresh leaves via several analysis including TGA, FTIR and Chromameter. Results indicated that the fresh leaves shows three degradation stages while temperature constant shows four stages of degradation and at constant pressure of -400 bar, five stages of degradation is shown. However, at the temperature constant with pressure -500 bar, five degradation stages are identified and at constant pressure with temperature 40°C, three stage of degradation is presence. It is assumed that it is due to the difference size of the sample as the particle size is decrease, the peak temperature shown in TG curves is also decrease which lead to the rapid ignition. Based on the FTIR analysis, fresh leaves gives the high presence of O-H and C=O group where both of the constant parameters give the absence of those due to the drying effects. In color analysis, the constant drying parameters (pressure and temperature) both shows that as the temperature increases, the average total of color change is also increases.

Keywords: chromameter, FTIR, TGA, Vaccum far infrared dying

Procedia PDF Downloads 362
40343 Impact of Harmonic Resonance and V-THD in Sohar Industrial Port–C Substation

Authors: R. S. Al Abri, M. H. Albadi, M. H. Al Abri, U. K. Al Rasbi, M. H. Al Hasni, S. M. Al Shidi

Abstract:

This paper presents an analysis study on the impacts of the changes of the capacitor banks, the loss of a transformer, and the installation of distributed generation on the voltage total harmonic distortion and harmonic resonance. The study is applied in a real system in Oman, Sohar Industrial Port–C Substation Network. Frequency scan method and Fourier series analysis method are used with the help of EDSA software. Moreover, the results are compared with limits specified by national Oman distribution code.

Keywords: power quality, capacitor bank, voltage total harmonics distortion, harmonic resonance, frequency scan

Procedia PDF Downloads 614
40342 Changes in Foreign Direct Investment Policy of India and Its Impact on Economic Development

Authors: Kishor P. Kadam

Abstract:

Foreign direct investment policy (FDI) is defined as an investment involving a long term relationship and reflecting a long duration interest and control of a resident entity in the home country (foreign direct investor or parent firm) in the host country. India has been one of the most translucent and open-minded FDI regimes among the emerging and developing economies. There is clear cut mentioned about the sectoral caps for foreign investment. The policy problems that have been identified by time to time surveys as acting as additional hurdles for FDI are laws, regulatory systems and government monopolies that do not have contemporary relevance. Foreign investment policies in the post-reforms period have emphasized greater encouragement and mobilization of non-debt creating private inflows for plunging reliance on debt flows. This paper will focus on how foreign direct investment policy changed from 1990-91 up to now. A time series data of 25 years is used for analysing the policy changes. It is observed that India has more liberal policy. The growth in number of Greenfield investments in India has been more impressive than the number of M&A deals whereas equity capital for incorporated bodies FDI inflows has been increased continuously 2014-15. India has made major changes in FDI Policy, and it has positive impact on economic development.

Keywords: FDI, India, economic development, government

Procedia PDF Downloads 358
40341 Analysis of EEG Signals Using Wavelet Entropy and Approximate Entropy: A Case Study on Depression Patients

Authors: Subha D. Puthankattil, Paul K. Joseph

Abstract:

Analyzing brain signals of the patients suffering from the state of depression may lead to interesting observations in the signal parameters that is quite different from a normal control. The present study adopts two different methods: Time frequency domain and nonlinear method for the analysis of EEG signals acquired from depression patients and age and sex matched normal controls. The time frequency domain analysis is realized using wavelet entropy and approximate entropy is employed for the nonlinear method of analysis. The ability of the signal processing technique and the nonlinear method in differentiating the physiological aspects of the brain state are revealed using Wavelet entropy and Approximate entropy.

Keywords: EEG, depression, wavelet entropy, approximate entropy, relative wavelet energy, multiresolution decomposition

Procedia PDF Downloads 329
40340 Thermal Fatigue Behavior of 400 Series Ferritic Stainless Steels

Authors: Seok Hong Min, Tae Kwon Ha

Abstract:

In this study, thermal fatigue properties of 400 series ferritic stainless steels have been evaluated in the temperature ranges of 200-800oC and 200-900oC. Systematic methods for control of temperatures within the predetermined range and measurement of load applied to specimens as a function of temperature during thermal cycles have been established. Thermal fatigue tests were conducted under fully constrained condition, where both ends of specimens were completely fixed. It has been revealed that load relaxation behavior at the temperatures of thermal cycle was closely related with the thermal fatigue property. Thermal fatigue resistance of 430J1L stainless steel is found to be superior to the other steels.

Keywords: ferritic stainless steel, automotive exhaust, thermal fatigue, microstructure, load relaxation

Procedia PDF Downloads 339
40339 Quantitative Comparisons of Different Approaches for Rotor Identification

Authors: Elizabeth M. Annoni, Elena G. Tolkacheva

Abstract:

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia that is a known prognostic marker for stroke, heart failure and death. Reentrant mechanisms of rotor formation, which are stable electrical sources of cardiac excitation, are believed to cause AF. No existing commercial mapping systems have been demonstrated to consistently and accurately predict rotor locations outside of the pulmonary veins in patients with persistent AF. There is a clear need for robust spatio-temporal techniques that can consistently identify rotors using unique characteristics of the electrical recordings at the pivot point that can be applied to clinical intracardiac mapping. Recently, we have developed four new signal analysis approaches – Shannon entropy (SE), Kurtosis (Kt), multi-scale frequency (MSF), and multi-scale entropy (MSE) – to identify the pivot points of rotors. These proposed techniques utilize different cardiac signal characteristics (other than local activation) to uncover the intrinsic complexity of the electrical activity in the rotors, which are not taken into account in current mapping methods. We validated these techniques using high-resolution optical mapping experiments in which direct visualization and identification of rotors in ex-vivo Langendorff-perfused hearts were possible. Episodes of ventricular tachycardia (VT) were induced using burst pacing, and two examples of rotors were used showing 3-sec episodes of a single stationary rotor and figure-8 reentry with one rotor being stationary and one meandering. Movies were captured at a rate of 600 frames per second for 3 sec. with 64x64 pixel resolution. These optical mapping movies were used to evaluate the performance and robustness of SE, Kt, MSF and MSE techniques with respect to the following clinical limitations: different time of recordings, different spatial resolution, and the presence of meandering rotors. To quantitatively compare the results, SE, Kt, MSF and MSE techniques were compared to the “true” rotor(s) identified using the phase map. Accuracy was calculated for each approach as the duration of the time series and spatial resolution were reduced. The time series duration was decreased from its original length of 3 sec, down to 2, 1, and 0.5 sec. The spatial resolution of the original VT episodes was decreased from 64x64 pixels to 32x32, 16x16, and 8x8 pixels by uniformly removing pixels from the optical mapping video.. Our results demonstrate that Kt, MSF and MSE were able to accurately identify the pivot point of the rotor under all three clinical limitations. The MSE approach demonstrated the best overall performance, but Kt was the best in identifying the pivot point of the meandering rotor. Artifacts mildly affect the performance of Kt, MSF and MSE techniques, but had a strong negative impact of the performance of SE. The results of our study motivate further validation of SE, Kt, MSF and MSE techniques using intra-atrial electrograms from paroxysmal and persistent AF patients to see if these approaches can identify pivot points in a clinical setting. More accurate rotor localization could significantly increase the efficacy of catheter ablation to treat AF, resulting in a higher success rate for single procedures.

Keywords: Atrial Fibrillation, Optical Mapping, Signal Processing, Rotors

Procedia PDF Downloads 321
40338 The Use of Ward Linkage in Cluster Integration with a Path Analysis Approach

Authors: Adji Achmad Rinaldo Fernandes

Abstract:

Path analysis is an analytical technique to study the causal relationship between independent and dependent variables. In this study, the integration of Clusters in the Ward Linkage method was used in a variety of clusters with path analysis. The variables used are character (x₁), capacity (x₂), capital (x₃), collateral (x₄), and condition of economy (x₄) to on time pay (y₂) through the variable willingness to pay (y₁). The purpose of this study was to compare the Ward Linkage method cluster integration in various clusters with path analysis to classify willingness to pay (y₁). The data used are primary data from questionnaires filled out by customers of Bank X, using purposive sampling. The measurement method used is the average score method. The results showed that the Ward linkage method cluster integration with path analysis on 2 clusters is the best method, by comparing the coefficient of determination. Variable character (x₁), capacity (x₂), capital (x₃), collateral (x₄), and condition of economy (x₅) to on time pay (y₂) through willingness to pay (y₁) can be explained by 58.3%, while the remaining 41.7% is explained by variables outside the model.

Keywords: cluster integration, linkage, path analysis, compliant paying behavior

Procedia PDF Downloads 184
40337 StockTwits Sentiment Analysis on Stock Price Prediction

Authors: Min Chen, Rubi Gupta

Abstract:

Understanding and predicting stock market movements is a challenging problem. It is believed stock markets are partially driven by public sentiments, which leads to numerous research efforts to predict stock market trend using public sentiments expressed on social media such as Twitter but with limited success. Recently a microblogging website StockTwits is becoming increasingly popular for users to share their discussions and sentiments about stocks and financial market. In this project, we analyze the text content of StockTwits tweets and extract financial sentiment using text featurization and machine learning algorithms. StockTwits tweets are first pre-processed using techniques including stopword removal, special character removal, and case normalization to remove noise. Features are extracted from these preprocessed tweets through text featurization process using bags of words, N-gram models, TF-IDF (term frequency-inverse document frequency), and latent semantic analysis. Machine learning models are then trained to classify the tweets' sentiment as positive (bullish) or negative (bearish). The correlation between the aggregated daily sentiment and daily stock price movement is then investigated using Pearson’s correlation coefficient. Finally, the sentiment information is applied together with time series stock data to predict stock price movement. The experiments on five companies (Apple, Amazon, General Electric, Microsoft, and Target) in a duration of nine months demonstrate the effectiveness of our study in improving the prediction accuracy.

Keywords: machine learning, sentiment analysis, stock price prediction, tweet processing

Procedia PDF Downloads 149
40336 Gender and Advertisements: A Content Analysis of Pakistani Prime Time Advertisements

Authors: Aaminah Hassan

Abstract:

Advertisements carry a great potential to influence our lives because they are crafted to meet particular ends. Stereotypical representation in advertisements is capable of forming unconscious attitudes among people towards any gender and their abilities. This study focuses on gender representation in Pakistani prime time advertisements. For this purpose, 13 advertisements were selected from three different categories of foods and beverages, cosmetics, cell phones and cellular networks from the prime time slots of one of the leading Pakistani entertainment channel, ‘Urdu 1’. Both quantitative and qualitative analyses are carried out for range of variables like gender, age, roles, activities, setting, appearance and voice overs. The results revealed that gender representation in advertisements is stereotypical. Moreover, in few instances, the portrayal of women is not only culturally inappropriate but is demeaning to the image of women as well. Their bodily charm is used to promote products. Comparing different entertainment channels for their prime time advertisements and broadening the scope of this research will yield greater implications for the researchers who want to carry out the similar research. It is hoped that the current study would help in the promotion of media literacy among the viewers and media authorities in Pakistan.

Keywords: Advertisements, Content Analysis, Gender, Prime time

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40335 Attention-based Adaptive Convolution with Progressive Learning in Speech Enhancement

Authors: Tian Lan, Yixiang Wang, Wenxin Tai, Yilan Lyu, Zufeng Wu

Abstract:

The monaural speech enhancement task in the time-frequencydomain has a myriad of approaches, with the stacked con-volutional neural network (CNN) demonstrating superiorability in feature extraction and selection. However, usingstacked single convolutions method limits feature represen-tation capability and generalization ability. In order to solvethe aforementioned problem, we propose an attention-basedadaptive convolutional network that integrates the multi-scale convolutional operations into a operation-specific blockvia input dependent attention to adapt to complex auditoryscenes. In addition, we introduce a two-stage progressivelearning method to enlarge the receptive field without a dra-matic increase in computation burden. We conduct a series ofexperiments based on the TIMIT corpus, and the experimen-tal results prove that our proposed model is better than thestate-of-art models on all metrics.

Keywords: speech enhancement, adaptive convolu-tion, progressive learning, time-frequency domain

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40334 Design of an Active Compression System for Treating Vascular Disease Using a Series of Silicone Based Inflatable Mini Bladders

Authors: Gayani K. Nandasiri, Tilak Dias, William Hurley

Abstract:

Venous disease of human lower limb could range from minor asymptomatic incompetence of venous valves to chronic venous ulceration. The sheer prevalence of varicose veins and its associated significant costs of treating late complications such as chronic ulcers contribute to a higher burden on health care resources. In most of western countries with developed health care systems, treatment costs associated with Venous disease accounts for a considerable portion of their total health care budget, and it has become a high-cost burden to National Health Service (NHS), UK. The established gold standard of treatment for the venous disease is the graduated compression, where the pressure at the ankle being highest and decreasing towards the knee and thigh. Currently, medical practitioners use two main methods to treat venous disease; i.e. compression bandaging and compression stockings. Both these systems have their own disadvantages which lead to the current programme of research. The aim of the present study is to revolutionize the compression therapy by using a novel active compression system to deliver a controllable and more accurate pressure profiles using a series of inflatable mini bladders. Two types of commercially available silicones were tested for the application. The mini bladders were designed with a special fabrication procedure to provide required pressure profiles, and a series of experiments were conducted to characterise the mini bladders. The inflation/deflation heights of these mini bladders were investigated experimentally and using a finite element model (FEM), and the experimental data were compared to the results obtained from FEM simulations, which showed 70-80% agreement. Finally, the mini bladders were tested for its pressure transmittance characteristics, and the results showed a 70-80% of inlet air pressure transmitted onto the treated surface.

Keywords: finite element analysis, graduated compression, inflatable bladders, venous disease

Procedia PDF Downloads 180
40333 The Effects of Placement and Cross-Section Shape of Shear Walls in Multi-Story RC Buildings with Plan Irregularity on Their Seismic Behavior by Using Nonlinear Time History Analyses

Authors: Mohammad Aminnia, Mahmood Hosseini

Abstract:

Environmental and functional conditions sometimes necessitate the architectural plan of the building to be asymmetric, and this result in an asymmetric structure. In such cases, finding an optimal pattern for locating the components of the lateral load bearing system, including shear walls, in the building’s plan is desired. In case of shear walls, in addition to the location, the shape of the wall cross-section is also an effective factor. Various types of shear wall and their proper layout might come effective in better stiffness distribution and more appropriate seismic response of the building. Several studies have been conducted in the context of analysis and design of shear walls; however, few studies have been performed on making decisions for the location and form of shear walls in multi-story buildings, especially those with irregular plan. In this study, an attempt has been made to obtain the most reliable seismic behavior of multi-story reinforced concrete vertically chamfered buildings by using more appropriate shear walls form and arrangement in 7-, 10-, 12-, and 15-story buildings. The considered forms and arrangements include common rectangular walls and L-, T-, U- and Z-shaped plan, located as the core or in the outer frames of the building structure. Comparison of seismic behaviors of the buildings, including maximum roof displacement, and particularly the formation of plastic hinges and their distribution in the buildings’ structures, have been done based on the results of a series of nonlinear time history analyses by using a set of selected earthquake records. Results show that shear walls with U-shaped cross-section, placed as the building central core, and also walls with Z-shaped cross-section, placed at the corners give the building more reliable seismic behavior.

Keywords: vertically chamfered buildings, non-linear time history analyses, l-, t-, u- and z-shaped plan walls

Procedia PDF Downloads 254
40332 Transport Related Air Pollution Modeling Using Artificial Neural Network

Authors: K. D. Sharma, M. Parida, S. S. Jain, Anju Saini, V. K. Katiyar

Abstract:

Air quality models form one of the most important components of an urban air quality management plan. Various statistical modeling techniques (regression, multiple regression and time series analysis) have been used to predict air pollution concentrations in the urban environment. These models calculate pollution concentrations due to observed traffic, meteorological and pollution data after an appropriate relationship has been obtained empirically between these parameters. Artificial neural network (ANN) is increasingly used as an alternative tool for modeling the pollutants from vehicular traffic particularly in urban areas. In the present paper, an attempt has been made to model traffic air pollution, specifically CO concentration using neural networks. In case of CO concentration, two scenarios were considered. First, with only classified traffic volume input and the second with both classified traffic volume and meteorological variables. The results showed that CO concentration can be predicted with good accuracy using artificial neural network (ANN).

Keywords: air quality management, artificial neural network, meteorological variables, statistical modeling

Procedia PDF Downloads 519
40331 Detection of Patient Roll-Over Using High-Sensitivity Pressure Sensors

Authors: Keita Nishio, Takashi Kaburagi, Yosuke Kurihara

Abstract:

Recent advances in medical technology have served to enhance average life expectancy. However, the total time for which the patients are prescribed complete bedrest has also increased. With patients being required to maintain a constant lying posture- also called bedsore- development of a system to detect patient roll-over becomes imperative. For this purpose, extant studies have proposed the use of cameras, and favorable results have been reported. Continuous on-camera monitoring, however, tends to violate patient privacy. We have proposed unconstrained bio-signal measurement system that could detect body-motion during sleep and does not violate patient’s privacy. Therefore, in this study, we propose a roll-over detection method by the date obtained from the bi-signal measurement system. Signals recorded by the sensor were assumed to comprise respiration, pulse, body motion, and noise components. Compared the body-motion and respiration, pulse component, the body-motion, during roll-over, generate large vibration. Thus, analysis of the body-motion component facilitates detection of the roll-over tendency. The large vibration associated with the roll-over motion has a great effect on the Root Mean Square (RMS) value of time series of the body motion component calculated during short 10 s segments. After calculation, the RMS value during each segment was compared to a threshold value set in advance. If RMS value in any segment exceeded the threshold, corresponding data were considered to indicate occurrence of a roll-over. In order to validate the proposed method, we conducted experiment. A bi-directional microphone was adopted as a high-sensitivity pressure sensor and was placed between the mattress and bedframe. Recorded signals passed through an analog Band-pass Filter (BPF) operating over the 0.16-16 Hz bandwidth. BPF allowed the respiration, pulse, and body-motion to pass whilst removing the noise component. Output from BPF was A/D converted with the sampling frequency 100Hz, and the measurement time was 480 seconds. The number of subjects and data corresponded to 5 and 10, respectively. Subjects laid on a mattress in the supine position. During data measurement, subjects—upon the investigator's instruction—were asked to roll over into four different positions—supine to left lateral, left lateral to prone, prone to right lateral, and right lateral to supine. Recorded data was divided into 48 segments with 10 s intervals, and the corresponding RMS value for each segment was calculated. The system was evaluated by the accuracy between the investigator’s instruction and the detected segment. As the result, an accuracy of 100% was achieved. While reviewing the time series of recorded data, segments indicating roll-over tendencies were observed to demonstrate a large amplitude. However, clear differences between decubitus and the roll-over motion could not be confirmed. Extant researches possessed a disadvantage in terms of patient privacy. The proposed study, however, demonstrates more precise detection of patient roll-over tendencies without violating their privacy. As a future prospect, decubitus estimation before and after roll-over could be attempted. Since in this paper, we could not confirm the clear differences between decubitus and the roll-over motion, future studies could be based on utilization of the respiration and pulse components.

Keywords: bedsore, high-sensitivity pressure sensor, roll-over, unconstrained bio-signal measurement

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40330 Minimization of Switching Losses in Cascaded Multilevel Inverters Using Efficient Sequential Switching Hybrid-Modulation Techniques

Authors: P. Satish Kumar, K. Ramakrishna, Ch. Lokeshwar Reddy, G. Sridhar

Abstract:

This paper presents two different sequential switching hybrid-modulation strategies and implemented for cascaded multilevel inverters. Hybrid modulation strategies represent the combinations of Fundamental-Frequency Pulse Width Modulation (FFPWM) and Multilevel Sinusoidal-Modulation (MSPWM) strategies, and are designed for performance of the well-known Alternative Phase Opposition Disposition (APOD), Phase Shifted Carrier (PSC). The main characteristics of these modulations are the reduction of switching losses with good harmonic performance, balanced power loss dissipation among the devices with in a cell, and among the series-connected cells. The feasibility of these modulations is verified through spectral analysis, power loss analysis and simulation.

Keywords: cascaded multilevel inverters, hybrid modulation, power loss analysis, pulse width modulation

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40329 Interdialytic Acupuncture Is an Add-on Option for Preserving Residual Renal Function: A Case Series Report

Authors: Lai Tzu-Hsuan, Lai Jung-Nien, Lin Jaung-Geng, Kao Shung-Te, Hsuan-Kuang Jung

Abstract:

Background: Whether acupuncture therapy contributes to preserving residual renal function (RRF) remains largely unknown. This case series evidenced the potential beneficial effects of acupuncture for preserving RRF in five patients with the end-stage renal disease under hemodialysis (HD) treatment. Participants: Five patients on HD receiving eight sessions of weekly 30-min interdialytic acupuncture (Inter-A) with residual urine volume (rUV) and residual glomerular filtration rate (rGFR) recorded once every two weeks were included for analysis. Outcomes: Changes in rUV and rGFR calculated using 24-hour urine collection data were analyzed to assess RRF. Variations in hemoglobin, urea Kt/V and serum albumin levels measured monthly were analyzed to evaluate HD adequacy. Results: After eight Inter-A sessions, mean (standard deviation (SD)) rUV and rGFR increased from 612 (184) ml/day and 1.48 (.94) ml/min/1.73 m2 at baseline to 803(289) ml/day and 2.04(1.17) ml/min/1.73m2 at 2- and 4-week follow-up, respectively. The mean percentage difference increased by 31% in rUV and 38% in rGFR. Routine measurements on HD adequacy also showed improvement. Conclusions: Acupuncture might be an optional add-on treatment for HD population with poor control of water; however, further well-designed controlled trials are warranted.

Keywords: end-stage renal disease, hemodialysis, acupuncture, residual renal function, residual urine volume

Procedia PDF Downloads 127
40328 The Impact of CO2 on Learning and Memory Duration of Bombus terrestris

Authors: Gholizadeh F. F., Goldansaz S. H., Bandani A. R., A. Ashouri

Abstract:

This study aimed to investigate the direct effects of increasing carbon dioxide (CO₂) concentration on the behavior of Bombus terrestris bumblebees in laboratory conditions to understand the outcomes of the augmentation of this gas in the Earth's atmosphere on the decline of populations of these pollinators. Learning and memory duration of bumblebees were evaluated as two main behavioral factors in social insects at different concentrations of CO₂. In both series of experiments, the behavior of bees under the influence of CO₂ changes compared to the control. Insects kept at high CO₂ concentrations learn less than control bees and spend more time identifying and navigating to discover their food source and access time (nectar consumption). These results showed that bees maybe lose some of their food resources due to poorer identification and act weaker on searching due to less memory and avoiding the enemy in higher CO₂ concentration. Therefore, CO₂ increasing concentration can be one of the reasons for the decline of these pollinating insects' populations by negatively affecting their fitness.

Keywords: Bombus terrestris, CO₂, learning, memory duration

Procedia PDF Downloads 174
40327 Spatiotemporal Analysis of Visual Evoked Responses Using Dense EEG

Authors: Rima Hleiss, Elie Bitar, Mahmoud Hassan, Mohamad Khalil

Abstract:

A comprehensive study of object recognition in the human brain requires combining both spatial and temporal analysis of brain activity. Here, we are mainly interested in three issues: the time perception of visual objects, the ability of discrimination between two particular categories (objects vs. animals), and the possibility to identify a particular spatial representation of visual objects. Our experiment consisted of acquiring dense electroencephalographic (EEG) signals during a picture-naming task comprising a set of objects and animals’ images. These EEG responses were recorded from nine participants. In order to determine the time perception of the presented visual stimulus, we analyzed the Event Related Potentials (ERPs) derived from the recorded EEG signals. The analysis of these signals showed that the brain perceives animals and objects with different time instants. Concerning the discrimination of the two categories, the support vector machine (SVM) was applied on the instantaneous EEG (excellent temporal resolution: on the order of millisecond) to categorize the visual stimuli into two different classes. The spatial differences between the evoked responses of the two categories were also investigated. The results showed a variation of the neural activity with the properties of the visual input. Results showed also the existence of a spatial pattern of electrodes over particular regions of the scalp in correspondence to their responses to the visual inputs.

Keywords: brain activity, categorization, dense EEG, evoked responses, spatio-temporal analysis, SVM, time perception

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40326 Morphology and Mineralogy of Acid Treated Soil

Authors: P. Hari Prasad Reddy, C. H. Rama Vara Prasad, G. Kalyan Kumar

Abstract:

This paper presents the morphological and mineralogical changes occurring in the soil due to immediate and prolonged interaction with different concentrations of phosphoric acid and sulphuric acid. In order to assess the effect of acid contamination, a series of sediment volume, scanning electron microscopy and X-ray diffraction analysis tests were carried out on soil samples were exposed to different concentrations (1N, 4N and 8N) of phosphoric and sulphuric acid. Experimental results show that both acids showed severe morphological and mineralogical changes with synthesis of neogenic formations mainly at higher concentrations (4N and 8N) and at prolonged duration of interaction (28 and 80 days).

Keywords: phosphoric acid, scanning electron microscopy, sulphuric acid, x-ray diffraction analysis

Procedia PDF Downloads 423
40325 Toward Green Islamic Finance: A Case Study from an Emirati Islamic Bank

Authors: Nada Hamed, Mariam Aldhaheri, Sonia Abdennadher

Abstract:

Islamic Finance is not a new term that emerging in the global market, but it is still under scope by many countries. Its characteristics and regulation are not widely clear and implemented. In 2015, The United Nation announced a plan about potential benefits of using Islamic Finance as a sustainable development approach. Enhancing its application in financial markets could protect from unexpected crisis that might be created from the traditional tools of finance. This paper focuses on this area to test if Islamic finance could be used for maintaining sustainable development and if the term of 'Green Islamic Finance' could be implemented to minimize the deficiencies and 'pollution’ generated from traditional techniques and tools of finance. This paper intends to measure the impact on financial performance and sustainability when financial institutions use Islamic finance or better practice it. The objective of this explanatory research is to measure the performance of Islamic Finance with using a case study of an Islamic bank. The paper would analyze and compare the behavior of financial institutions that used traditional financing tools and converted to Islamic banking system. The methodology used is based on a case study of an Islamic bank in Dubai with comparing its performance before implementing Islamic Finance and after. The selected case study represents the first national bank in Emirates Arab Unis who adopt the Islamic finance approach. Based on a time series analysis, a quantitative analysis would be also used through looking at various set of ratios that are routinely used to measure bank performance.

Keywords: Islamic finance, financial stability, green finance, Islamic finance practices, financial ratios

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40324 Continuous Land Cover Change Detection in Subtropical Thicket Ecosystems

Authors: Craig Mahlasi

Abstract:

The Subtropical Thicket Biome has been in peril of transformation. Estimates indicate that as much as 63% of the Subtropical Thicket Biome is severely degraded. Agricultural expansion is the main driver of transformation. While several studies have sought to document and map the long term transformations, there is a lack of information on disturbance events that allow for timely intervention by authorities. Furthermore, tools that seek to perform continuous land cover change detection are often developed for forests and thus tend to perform poorly in thicket ecosystems. This study investigates the utility of Earth Observation data for continuous land cover change detection in Subtropical Thicket ecosystems. Temporal Neural Networks are implemented on a time series of Sentinel-2 observations. The model obtained 0.93 accuracy, a recall score of 0.93, and a precision score of 0.91 in detecting Thicket disturbances. The study demonstrates the potential of continuous land cover change in Subtropical Thicket ecosystems.

Keywords: remote sensing, land cover change detection, subtropical thickets, near-real time

Procedia PDF Downloads 158
40323 Audience Perceptions and Attitudes Towards the Representation of Tribal South African Culture in Drama Series

Authors: Oluwayemisi Mary Onyenanakeya, Kevin Onyenankeya

Abstract:

Commercial media entertainment offerings especially mainstream soap operas, in South Africa, are progressively infusing dominant social values and ideas which are alien to South African tribal societies. In most of the commodified television drama series, people who hold tight to traditional beliefs and values are often characterised as traditionalists, while those who have imbibed the western defined dicta and ideology of modernity are seen as progressives. This study, therefore, sought to ascertain how South African tribal language, traditional institutions, values, social norms and ancestral beliefs are portrayed through the television drama, Generations: The Legacy, and what the viewers think about those constructions and the implication for cultural identity. The mixed methods approach was employed involving the administration of questionnaire to 350 participants selected through random sampling and a content analysis of 20 episodes of Generations: The Legacy. The findings further showed that the values and traditions represented in generation do not significantly reflect the South African tribal tradition and values (p-value > 0.05). In most instances where traditional values are represented they tend to be portrayed as old fashioned (p-value > 0.05), and inferior and backward (p-value > 0.05). In addition, the findings indicate that Generations: The legacy is a vehicle for promoting dominant culture.

Keywords: identity, soap opera, South Africa, television

Procedia PDF Downloads 286
40322 A Method of Detecting the Difference in Two States of Brain Using Statistical Analysis of EEG Raw Data

Authors: Digvijaysingh S. Bana, Kiran R. Trivedi

Abstract:

This paper introduces various methods for the alpha wave to detect the difference between two states of brain. One healthy subject participated in the experiment. EEG was measured on the forehead above the eye (FP1 Position) with reference and ground electrode are on the ear clip. The data samples are obtained in the form of EEG raw data. The time duration of reading is of one minute. Various test are being performed on the alpha band EEG raw data.The readings are performed in different time duration of the entire day. The statistical analysis is being carried out on the EEG sample data in the form of various tests.

Keywords: electroencephalogram(EEG), biometrics, authentication, EEG raw data

Procedia PDF Downloads 458
40321 Condition Assessment of Reinforced Concrete Bridge Deck Using Ground Penetrating Radar

Authors: Azin Shakibabarough, Mojtaba Valinejadshoubi, Ashutosh Bagchi

Abstract:

Catastrophic bridge failure happens due to the lack of inspection, lack of design and extreme events like flooding, an earthquake. Bridge Management System (BMS) is utilized to diminish such an accident with proper design and frequent inspection. Visual inspection cannot detect any subsurface defects, so using Non-Destructive Evaluation (NDE) techniques remove these barriers as far as possible. Among all NDE techniques, Ground Penetrating Radar (GPR) has been proved as a highly effective device for detecting internal defects in a reinforced concrete bridge deck. GPR is used for detecting rebar location and rebar corrosion in the reinforced concrete deck. GPR profile is composed of hyperbola series in which sound hyperbola denotes sound rebar and blur hyperbola or signal attenuation shows corroded rebar. Interpretation of GPR images is implemented by numerical analysis or visualization. Researchers recently found that interpretation through visualization is more precise than interpretation through numerical analysis, but visualization is time-consuming and a highly subjective process. Automating the interpretation of GPR image through visualization can solve these problems. After interpretation of all scans of a bridge, condition assessment is conducted based on the generated corrosion map. However, this such a condition assessment is not objective and precise. Condition assessment based on structural integrity and strength parameters can make it more objective and precise. The main purpose of this study is to present an automated interpretation method of a reinforced concrete bridge deck through a visualization technique. In the end, the combined analysis of the structural condition in a bridge is implemented.

Keywords: bridge condition assessment, ground penetrating radar, GPR, NDE techniques, visualization

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40320 Applying Multivariate and Univariate Analysis of Variance on Socioeconomic, Health, and Security Variables in Jordan

Authors: Faisal G. Khamis, Ghaleb A. El-Refae

Abstract:

Many researchers have studied socioeconomic, health, and security variables in the developed countries; however, very few studies used multivariate analysis in developing countries. The current study contributes to the scarce literature about the determinants of the variance in socioeconomic, health, and security factors. Questions raised were whether the independent variables (IVs) of governorate and year impact the socioeconomic, health, and security dependent variables (DVs) in Jordan, whether the marginal mean of each DV in each governorate and in each year is significant, which governorates are similar in difference means of each DV, and whether these DVs vary. The main objectives were to determine the source of variances in DVs, collectively and separately, testing which governorates are similar and which diverge for each DV. The research design was time series and cross-sectional analysis. The main hypotheses are that IVs affect DVs collectively and separately. Multivariate and univariate analyses of variance were carried out to test these hypotheses. The population of 12 governorates in Jordan and the available data of 15 years (2000–2015) accrued from several Jordanian statistical yearbooks. We investigated the effect of two factors of governorate and year on the four DVs of divorce rate, mortality rate, unemployment percentage, and crime rate. All DVs were transformed to multivariate normal distribution. We calculated descriptive statistics for each DV. Based on the multivariate analysis of variance, we found a significant effect in IVs on DVs with p < .001. Based on the univariate analysis, we found a significant effect of IVs on each DV with p < .001, except the effect of the year factor on unemployment was not significant with p = .642. The grand and marginal means of each DV in each governorate and each year were significant based on a 95% confidence interval. Most governorates are not similar in DVs with p < .001. We concluded that the two factors produce significant effects on DVs, collectively and separately. Based on these findings, the government can distribute its financial and physical resources to governorates more efficiently. By identifying the sources of variance that contribute to the variation in DVs, insights can help inform focused variation prevention efforts.

Keywords: ANOVA, crime, divorce, governorate, hypothesis test, Jordan, MANOVA, means, mortality, unemployment, year

Procedia PDF Downloads 270
40319 Unified Power Quality Conditioner Presentation and Dimensioning

Authors: Abderrahmane Kechich, Othmane Abdelkhalek

Abstract:

Static converters behave as nonlinear loads that inject harmonic currents into the grid and increase the consumption of the inactive power. On the other hand, the increased use of sensitive equipment requires the application of sinusoidal voltages. As a result, the electrical power quality control has become a major concern in the field of power electronics. In this context, the active power conditioner (UPQC) was developed. It combines both serial and parallel structures; the series filter can protect sensitive loads and compensate for voltage disturbances such as voltage harmonics, voltage dips or flicker when the shunt filter compensates for current disturbances such as current harmonics, reactive currents and imbalance. This double feature is that it is one of the most appropriate devices. Calculating parameters is an important step and in the same time it’s not easy for that reason several researchers based on trial and error method for calculating parameters but this method is not easy for beginners researchers especially what about the controller’s parameters, for that reason this paper gives a mathematical way to calculate of almost all of UPQC parameters away from trial and error method. This paper gives also a new approach for calculating of PI regulators parameters for purpose to have a stable UPQC able to compensate for disturbances acting on the waveform of line voltage and load current in order to improve the electrical power quality.

Keywords: UPQC, Shunt active filer, series active filer, PI controller, PWM control, dual-loop control

Procedia PDF Downloads 398
40318 Approximation of Periodic Functions Belonging to Lipschitz Classes by Product Matrix Means of Fourier Series

Authors: Smita Sonker, Uaday Singh

Abstract:

Various investigators have determined the degree of approximation of functions belonging to the classes W(L r , ξ(t)), Lip(ξ(t), r), Lip(α, r), and Lipα using different summability methods with monotonocity conditions. Recently, Lal has determined the degree of approximation of the functions belonging to Lipα and W(L r , ξ(t)) classes by using Ces`aro-N¨orlund (C 1 .Np)- summability with non-increasing weights {pn}. In this paper, we shall determine the degree of approximation of 2π - periodic functions f belonging to the function classes Lipα and W(L r , ξ(t)) by C 1 .T - means of Fourier series of f. Our theorems generalize the results of Lal and we also improve these results in the light off. From our results, we also derive some corollaries.

Keywords: Lipschitz classes, product matrix operator, signals, trigonometric Fourier approximation

Procedia PDF Downloads 476
40317 Effects of Boiling Temperature and Time on Colour, Texture and Sensory Properties of Volutharpa ampullacea perryi Meat

Authors: Xianbao Sun, Jinlong Zhao, Shudong He, Jing Li

Abstract:

Volutharpa ampullacea perryi is a high-protein marine shellfish. However, few data are available on the effects of boiling temperatures and time on quality of the meat. In this study, colour, texture and sensory characteristics of Volutharpa ampullacea perryi meat during the boiling cooking processes (75-100 °C, 5-60 min) were investigated by colors analysis, texture profile analysis (TPA), scanning electron microscope (SEM) and sensory evaluation. The ratio of cooking loss gradually increased with the increase of temperature and time. The colour of meat became lighter and more yellower from 85 °C to 95 °C in a short time (5-20 min), but it became brown after a 30 min treatment. TPA results showed that the Volutharpa ampullacea perryi meat were more firm and less cohesive after a higher temperature (95-100 °C) treatment even in a short period (5-15 min). Based on the SEM analysis, it was easily found that the myofibrils structure was destroyed at a higher temperature (85-100 °C). Sensory data revealed that the meat cooked at 85-90 °C in 10-20 min showed higher scores in overall acceptance, as well as color, hardness and taste. Based on these results, it could be constructed that Volutharpa ampullacea perryi meat should be heated on a suitable condition (such as 85 °C 15 min or 90 °C 10 min) in the boiling cooking to be ensure a better acceptability.

Keywords: Volutharpa ampullacea perryi meat, boiling cooking, colour, sensory, texture

Procedia PDF Downloads 277
40316 A Decadal Flood Assessment Using Time-Series Satellite Data in Cambodia

Authors: Nguyen-Thanh Son

Abstract:

Flood is among the most frequent and costliest natural hazards. The flood disasters especially affect the poor people in rural areas, who are heavily dependent on agriculture and have lower incomes. Cambodia is identified as one of the most climate-vulnerable countries in the world, ranked 13th out of 181 countries most affected by the impacts of climate change. Flood monitoring is thus a strategic priority at national and regional levels because policymakers need reliable spatial and temporal information on flood-prone areas to form successful monitoring programs to reduce possible impacts on the country’s economy and people’s likelihood. This study aims to develop methods for flood mapping and assessment from MODIS data in Cambodia. We processed the data for the period from 2000 to 2017, following three main steps: (1) data pre-processing to construct smooth time-series vegetation and water surface indices, (2) delineation of flood-prone areas, and (3) accuracy assessment. The results of flood mapping were verified with the ground reference data, indicating the overall accuracy of 88.7% and a Kappa coefficient of 0.77, respectively. These results were reaffirmed by close agreement between the flood-mapping area and ground reference data, with the correlation coefficient of determination (R²) of 0.94. The seasonally flooded areas observed for 2010, 2015, and 2016 were remarkably smaller than other years, mainly attributed to the El Niño weather phenomenon exacerbated by impacts of climate change. Eventually, although several sources potentially lowered the mapping accuracy of flood-prone areas, including image cloud contamination, mixed-pixel issues, and low-resolution bias between the mapping results and ground reference data, our methods indicated the satisfactory results for delineating spatiotemporal evolutions of floods. The results in the form of quantitative information on spatiotemporal flood distributions could be beneficial to policymakers in evaluating their management strategies for mitigating the negative effects of floods on agriculture and people’s likelihood in the country.

Keywords: MODIS, flood, mapping, Cambodia

Procedia PDF Downloads 121