Search results for: real time kernel preemption

Authors: Ben-Caleb Egbide, Iyoha Francis, Egharevba Mathew, Oduntan Emmanuel

Abstract:

The prosperity of any nation is determined not just by the availability of resources, but also by the discipline exercised in the management of those resources. This paper examines the functional association between adherence to budgetary estimates or budget discipline (BDISC) and national prosperity proxied by Real Gross Domestic Product (RGDP) and Relative Poverty Index (RPI)/Human Development Index (HDI). Adopting a longitudinal retrospective research strategy, time series data relating to both the endogenous and exogenous variables were extracted from official government publications for 36 years’ (1980-2015 in the case of RGDP and RPI), and for 26 years (1990-2015 in the case of HDI). Ordinary Least Square (OLS), as well as cointegration regressions, were employed to gauge both the short term and long term impact of BDISC on RPI/HDI and RGDP. The results indicated that BDISC is directly related with RGDP but indirectly related with RPI. The implication is that while adherence to budgetary estimate can enhance economic growth, it has the capacity to slow down the rate of poverty in the long run. The paper, therefore, recommend stricter adherence to budgets as a way out of economic under performance in Nigeria and engender the process of promoting human development and national prosperity.

Keywords: budget discipline, human development index, national prosperity, Nigeria

Procedia PDF Downloads 220

Authors: Khalida Douibi, Rodrigo Balp, Solène Le Bars

Abstract:

In the medical field, applications related to human experiments are frequently linked to reduced samples size, which makes the training of machine learning models quite sensitive and therefore not very robust nor generalizable. This is notably the case in Brain-Computer Interface (BCI) studies, where the sample size rarely exceeds 20 subjects or a few number of trials. To address this problem, several resampling approaches are often used during the data preparation phase, which is an overly critical step in a data science analysis process. One of the naive approaches that is usually applied by data scientists consists in the transformation of the entire database before the resampling phase. However, this can cause model’ s performance to be incorrectly estimated when making predictions on unseen data. In this paper, we explored the effect of data leakage observed during our BCI experiments for device control through the real-time classification of SSVEPs (Steady State Visually Evoked Potentials). We also studied potential ways to ensure optimal validation of the classifiers during the calibration phase to avoid overfitting. The results show that the scaling step is crucial for some algorithms, and it should be applied after the resampling phase to avoid data leackage and improve results.

Keywords: data leackage, data science, machine learning, SSVEP, BCI, overfitting

Procedia PDF Downloads 139

Authors: Gabriel Wosiak, Dyovani Coelho, Evaldo B. Carneiro-Neto, Ernesto C. Pereira, Mauro C. Lopes

Abstract:

In this work, the theoretical and experimental effects of induced charging currents on fast-scan cyclic voltammetry (FSCV) are investigated. Induced charging currents arise from the effect of ohmic drop in electrochemical systems, which depends on the presence of an uncompensated resistance. They cause the capacitive contribution to the total current to be different from the capacitive current measured in the absence of electroactive species. The paper shows that the induced charging current is relevant when the capacitive current magnitude is close to the total current, even for systems with low time constant. In these situations, the conventional background subtraction method may be inaccurate. A method is developed that separates the faradaic and capacitive currents by using a combination of voltametric experimental data and finite element simulation, by the obtention of a potential-dependent capacitance. The method was tested in a standard electrochemical cell with Platinum ultramicroelectrodes, in different experimental conditions as well in previously reported data in literature. The proposed method allows the real capacitive current to be separated even in situations where the conventional background subtraction method is clearly inappropriate.

Keywords: capacitive current, fast-scan cyclic voltammetry, finite-element method, electroanalysis

Procedia PDF Downloads 58

Authors: Assem M. F. Sallam, Ah. El-S. Makled

Abstract:

This paper presents a study on the trajectory of a two stage launch vehicle. The study includes dynamic responses of motion parameters as well as the variation of angles affecting the orientation of the launch vehicle (LV). LV dynamic characteristics including state vector variation with corresponding altitude and velocity for the different LV stages separation, as well as the angle of attack and flight path angles are also discussed. A flight trajectory study for the drop zone of first stage and the jettisoning of fairing are introduced in the mathematical modeling to study their effect. To increase the accuracy of the LV model, atmospheric model is used taking into consideration geographical location and the values of solar flux related to the date and time of launch, accurate atmospheric model leads to enhancement of the calculation of Mach number, which affects the drag force over the LV. The mathematical model is implemented on MATLAB based software (Simulink). The real available experimental data are compared with results obtained from the theoretical computation model. The comparison shows good agreement, which proves the validity of the developed simulation model; the maximum error noticed was generally less than 10%, which is a result that can lead to future works and enhancement to decrease this level of error.

Keywords: launch vehicle modeling, launch vehicle trajectory, mathematical modeling, Matlab- Simulink

Procedia PDF Downloads 265

Authors: Apostolos Kalatzis, Ashish Teotia, Vishnunarayan Girishan Prabhu, Laura Stanley

Abstract:

Emotions are functional behaviors influenced by thoughts, stimuli, and other factors that induce neurophysiological changes in the human body. Understanding and classifying emotions are challenging as individuals have varying perceptions of their environments. Therefore, it is crucial that there are publicly available databases and virtual reality (VR) based environments that have been scientifically validated for assessing emotional classification. This study utilized two commercially available VR applications (Guided Meditation VR™ and Richie’s Plank Experience™) to induce acute stress and calm state among participants. Subjective and objective measures were collected to create a validated multimodal dataset and classification scheme for affective state classification. Participants’ subjective measures included the use of the Self-Assessment Manikin, emotional cards and 9 point Visual Analogue Scale for perceived stress, collected using a Virtual Reality Assessment Tool developed by our team. Participants’ objective measures included Electrocardiogram and Respiration data that were collected from 25 participants (15 M, 10 F, Mean = 22.28  4.92). The features extracted from these data included heart rate variability components and respiration rate, both of which were used to train two machine learning models. Subjective responses validated the efficacy of the VR applications in eliciting the two desired affective states; for classifying the affective states, a logistic regression (LR) and a support vector machine (SVM) with a linear kernel algorithm were developed. The LR outperformed the SVM and achieved 93.8%, 96.2%, 93.8% leave one subject out cross-validation accuracy, precision and recall, respectively. The VR assessment tool and data collected in this study are publicly available for other researchers.

Keywords: affective computing, biosignals, machine learning, stress database

Procedia PDF Downloads 127

Authors: Azam Fazelpour, Saeed Reza Dehghani, Vlastimil Masek, Yuri S. Muzychka

Abstract:

The study uses a novel image analysis based on thermal imaging to detect temperature contours created on salt ice surface during transient phenomena. Thermal cameras detect objects by using their emissivities and IR radiance. The ice surface temperature is not uniform during transient processes. The temperature starts to increase from the boundary of ice towards the center of that. Thermal cameras are able to report temperature changes on the ice surface at every individual moment. Various contours, which show different temperature areas, appear on the ice surface picture captured by a thermal camera. Identifying the exact boundary of these contours is valuable to facilitate ice surface temperature analysis. Image processing techniques are used to extract each contour area precisely. In this study, several pictures are recorded while the temperature is increasing throughout the ice surface. Some pictures are selected to be processed by a specific time interval. An image segmentation method is applied to images to determine the contour areas. Color thermal images are used to exploit the main information. Red, green and blue elements of color images are investigated to find the best contour boundaries. The algorithms of image enhancement and noise removal are applied to images to obtain a high contrast and clear image. A novel edge detection algorithm based on differences in the color of the pixels is established to determine contour boundaries. In this method, the edges of the contours are obtained according to properties of red, blue and green image elements. The color image elements are assessed considering their information. Useful elements proceed to process and useless elements are removed from the process to reduce the consuming time. Neighbor pixels with close intensities are assigned in one contour and differences in intensities determine boundaries. The results are then verified by conducting experimental tests. An experimental setup is performed using ice samples and a thermal camera. To observe the created ice contour by the thermal camera, the samples, which are initially at -20° C, are contacted with a warmer surface. Pictures are captured for 20 seconds. The method is applied to five images ,which are captured at the time intervals of 5 seconds. The study shows the green image element carries no useful information; therefore, the boundary detection method is applied on red and blue image elements. In this case study, the results indicate that proposed algorithm shows the boundaries more effective than other edges detection methods such as Sobel and Canny. Comparison between the contour detection in this method and temperature analysis, which states real boundaries, shows a good agreement. This color image edge detection method is applicable to other similar cases according to their image properties.

Keywords: color image processing, edge detection, ice contour boundary, salt ice, thermal image

Procedia PDF Downloads 302

Authors: Derlis Gregor, Kevin Cikel, Mario Arzamendia, Raúl Gregor

Abstract:

This paper presents a self-sustaining mobile system for counting and classification of vehicles through processing video. It proposes a counting and classification algorithm divided in four steps that can be executed multiple times in parallel in a SBC (Single Board Computer), like the Raspberry Pi 2, in such a way that it can be implemented in real time. The first step of the proposed algorithm limits the zone of the image that it will be processed. The second step performs the detection of the mobile objects using a BGS (Background Subtraction) algorithm based on the GMM (Gaussian Mixture Model), as well as a shadow removal algorithm using physical-based features, followed by morphological operations. In the first step the vehicle detection will be performed by using edge detection algorithms and the vehicle following through Kalman filters. The last step of the proposed algorithm registers the vehicle passing and performs their classification according to their areas. An auto-sustainable system is proposed, powered by batteries and photovoltaic solar panels, and the data transmission is done through GPRS (General Packet Radio Service)eliminating the need of using external cable, which will facilitate it deployment and translation to any location where it could operate. The self-sustaining trailer will allow the counting and classification of vehicles in specific zones with difficult access.

Keywords: intelligent transportation system, object detection, vehicle couting, vehicle classification, video processing

Procedia PDF Downloads 308

Authors: Huang Bai-Cheng

Abstract:

When deploying the Oriented Fast and Rotated Binary Robust Independent Elementary Feature (BRIEF) (ORB) extraction algorithm on field-programmable gate arrays (FPGA), the access of global storage for 31×31 pixel patches of the features has become the bottleneck of the system efficiency. Therefore, a feature zone strategy has been proposed. Zones are searched as features are detected. Pixels around the feature zones are extracted from global memory and distributed into patches corresponding to feature coordinates. The proposed FPGA structure is targeted on a Xilinx FPGA development board of Zynq UltraScale+ series, and multiple datasets are tested. Compared with the streaming pixel patch extraction method, the proposed architecture obtains at least two times acceleration consuming extra 3.82% Flip-Flops (FFs) and 7.78% Look-Up Tables (LUTs). Compared with the non-streaming one, the proposed architecture saves 22.3% LUT and 1.82% FF, causing a latency of only 0.2ms and a drop in frame rate for 1. Compared with the related works, the proposed strategy and hardware architecture have the superiority of keeping a balance between FPGA resources and performance.

Keywords: feature extraction, real-time, ORB, FPGA implementation

Procedia PDF Downloads 104

Authors: Zhao Kuo, Chen Liang, Zhang Zhongbing, Ruan Jinlu. He Shiyi, Xu Mengxuan

Abstract:

Stilbene, C₁₄H₁₂, is well known as one of the most useful organic scintillators for pulse shape discrimination (PSD) technique for its good scintillation properties. An on-line acquisition system and an off-line acquisition system were developed with several CAMAC standard plug-ins, NIM plug-ins, neutron/γ discriminating plug-in named 2160A and a digital oscilloscope with high sampling rate respectively for which stilbene crystals and photomultiplier tube detectors (PMT) as detector for accelerator neutron sources measurement carried out in China Institute of Atomic Energy. Pulse amplitude spectrums and charge amplitude spectrums were real-time recorded after good neutron/γ discrimination whose best PSD figure-of-merits (FoMs) are 1.756 for D-D accelerator neutron source and 1.393 for D-T accelerator neutron source. The probability of neutron events in total events was 80%, and neutron detection efficiency was 5.21% for D-D accelerator neutron sources, which were 50% and 1.44% for D-T accelerator neutron sources after subtracting the background of scattering observed by the on-line acquisition system. Pulse waveform signals were acquired by the off-line acquisition system randomly while the on-line acquisition system working. The PSD FoMs obtained by the off-line acquisition system were 2.158 for D-D accelerator neutron sources and 1.802 for D-T accelerator neutron sources after waveform digitization off-line processing named charge integration method for just 1000 pulses. In addition, the probabilities of neutron events in total events obtained by the off-line acquisition system matched very well with the probabilities of the on-line acquisition system. The pulse information recorded by the off-line acquisition system could be repetitively used to adjust the parameters or methods of PSD research and obtain neutron charge amplitude spectrums or pulse amplitude spectrums after digital analysis with a limited number of pulses. The off-line acquisition system showed equivalent or better measurement effects compared with the online system with a limited number of pulses which indicated a feasible method based on stilbene crystals detectors for the measurement of prompt neutrons neutron sources like prompt accelerator neutron sources emit a number of neutrons in a short time.

Keywords: stilbene crystal, accelerator neutron source, neutron / γ discrimination, figure-of-merits, CAMAC, waveform digitization

Procedia PDF Downloads 173

Authors: Zabeehullah, Fahim Arif, Yawar Abbas

Abstract:

Software Defined Network (SDN) is a next genera-tion networking model which simplifies the traditional network complexities and improve the utilization of constrained resources. Currently, most of the SDN based Internet of Things(IoT) environments use traditional network routing strategies which work on the basis of max or min metric value. However, IoT network heterogeneity, dynamic traffic flow and complexity demands intelligent and self-adaptive routing algorithms because traditional routing algorithms lack the self-adaptions, intelligence and efficient utilization of resources. To some extent, SDN, due its flexibility, and centralized control has managed the IoT complexity and heterogeneity but still Software Defined IoT (SDIoT) lacks intelligence. To address this challenge, we proposed a model called Deep Routing Strategy (DRS) which uses Deep Learning algorithm to perform routing in SDIoT intelligently and efficiently. Our model uses real-time traffic for training and learning. Results demonstrate that proposed model has achieved high accuracy and low packet loss rate during path selection. Proposed model has also outperformed benchmark routing algorithm (OSPF). Moreover, proposed model provided encouraging results during high dynamic traffic flow.

Keywords: SDN, IoT, DL, ML, DRS

Procedia PDF Downloads 95

Authors: N. Ammouchi

Abstract:

We have studied the effect of milling time on the structural and hyperfine properties of Ni45Al45Fe10 compound elaborated by mechanical alloying. The elaboration was performed by using the planetary ball mill at different milling times. The as milled powders were characterized by X-ray diffraction (XRD) and Mӧssbauer spectroscopy. From XRD diffraction spectra, we show that the β NiAl(Fe) was completely formed after 24 h of milling time. When the milling time increases, the lattice parameter increases, whereas the grain size decreases to a few nanometres and the mean level of microstrains increases. The analysis of Mӧssbauer spectra indicates that, in addition to a ferromagnetic phase, α-Fe, a paramagnetic disordered phase Ni Al (Fe) solid solution is observed after 2h and only this phase is present after 12h.

Keywords: NiAlFe, nanostructured powders, X-ray diffraction, Mӧssbauer spectroscopy

Procedia PDF Downloads 362

Authors: Taweechai Nuntawisuttiwong, Natasha Dejdumrong

Abstract:

Newton-Lagrange Interpolations are widely used in numerical analysis. However, it requires a quadratic computational time for their constructions. In computer aided geometric design (CAGD), there are some polynomial curves: Wang-Ball, DP and Dejdumrong curves, which have linear time complexity algorithms. Thus, the computational time for Newton-Lagrange Interpolations can be reduced by applying the algorithms of Wang-Ball, DP and Dejdumrong curves. In order to use Wang-Ball, DP and Dejdumrong algorithms, first, it is necessary to convert Newton-Lagrange polynomials into Wang-Ball, DP or Dejdumrong polynomials. In this work, the algorithms for converting from both uniform and non-uniform Newton-Lagrange polynomials into Wang-Ball, DP and Dejdumrong polynomials are investigated. Thus, the computational time for representing Newton-Lagrange polynomials can be reduced into linear complexity. In addition, the other utilizations of using CAGD curves to modify the Newton-Lagrange curves can be taken.

Keywords: Lagrange interpolation, linear complexity, monomial matrix, Newton interpolation

Procedia PDF Downloads 217

Authors: Aicha Bensouici, Assia Mili, Naouel Rdjem, Nacera Baali

Abstract:

Copper oxide decorated reduced graphene oxide (GO) was obtained successfully using two steps route synthesis was used. Firstly, graphene oxide was obtained using a modified Hummers method by excluding sodium nitrate from starting materials. After washing-centrifugation routine pristine GO was decorated by copper oxide using a refluxation technique at 120°C during 2h, and an equal amount of GO and copper acetate was used. Three CuO-rGO nanocomposite samples types were obtained at 30min, 24h, and 7 day stirring time. TAC results show dose dependent behavior of CuO-rGO and confirm no influence of stirring time on antioxidant properties, 30min is considered as an optimal stirring condition.

Keywords: copper oxide, reduced graphene oxide, TAC, GO

Procedia PDF Downloads 92

Authors: Yanxue Shang, Jingbin Zeng

Abstract:

Chlorobenzene homologues (CBHs) are a category of environmental pollutants that can not be ignored. They can stay in the environment for a long period and are potentially carcinogenic. The traditional degradation method of CBHs is dechlorination followed by sample preparation and analysis. This is not only time-consuming and laborious, but the detection and analysis processes are used in conjunction with large-scale instruments. Therefore, this can not achieve rapid and low-cost detection. Compared with traditional sensing methods, colorimetric sensing is simpler and more convenient. In recent years, chromaticity sensors based on fluorescence have attracted more and more attention. Compared with sensing methods based on changes in fluorescence intensity, changes in color gradients are easier to recognize by the naked eye. Accordingly, this work proposes to use single drop microextraction (SDME) technology to solve the above problems. After the dechlorination reaction was completed, the organic droplet extracts Cl⁻ and realizes fluorescence colorimetric sensing at the same time. This method was integrated sample processing and visual in-situ detection, simplifying the detection process. As a fluorescence colorimetric sensor material, CsPbBr₃ was encapsulated in MOF-5 to construct CsPbBr₃@MOF-5 fluorescence colorimetric composite. Then the fluorescence colorimetric sensor was constructed by dispersing the composite in SDME organic droplets. When the Br⁻ in CsPbBr₃ exchanges with Cl⁻ produced by the dechlorination reactions, it is converted into CsPbCl₃. The fluorescence color of the single droplet of SDME will change from green to blue emission, thereby realizing visual observation. Therein, SDME can enhance the concentration and enrichment of Cl⁻ and instead of sample pretreatment. The fluorescence color change of CsPbBr₃@MOF-5 can replace the detection process of large-scale instruments to achieve real-time rapid detection. Due to the absorption ability of MOF-5, it can not only improve the stability of CsPbBr₃, but induce the adsorption of Cl⁻. Simultaneously, accelerate the exchange of Br- and Cl⁻ in CsPbBr₃ and the detection process of Cl⁻. The absorption process was verified by density functional theory (DFT) calculations. This method exhibits exceptional linearity for Cl⁻ in the range of 10⁻² - 10⁻⁶ M (10000 μM - 1 μM) with a limit of detection of 10⁻⁷ M. Whereafter, the dechlorination reactions of different kinds of CBHs were also carried out with this method, and all had satisfactory detection ability. Also verified the accuracy by gas chromatography (GC), and it was found that the SDME we developed in this work had high credibility. In summary, the in-situ visualization method of dechlorination reaction detection was a combination of sample processing and fluorescence colorimetric sensing. Thus, the strategy researched herein represents a promising method for the visual detection of dechlorination reactions and can be extended for applications in environments, chemical industries, and foods.

Keywords: chlorobenzene homologues, colorimetric sensor, metal halide perovskite, metal-organic frameworks, single drop microextraction

Procedia PDF Downloads 131

Authors: W. M. Ng, O. B. Iskender, L. Simonini, J. M. Gonzalez

Abstract:

A multitude of factors, including mechanical imperfections of the deployment system and separation instance of satellites from launchers, oftentimes results in highly uncontrolled initial tumbling motion immediately after deployment. In particular, small satellites which are characteristically launched as a piggyback to a large rocket, are generally allocated a large time window to complete detumbling within the early orbit phase. Because of the saturation risk of the actuators, current algorithms are conservative to avoid draining excessive power in the detumbling phase. This work aims to enable time-optimal switching of control modes during the early phase, reducing the time required to transit from launch to sun-pointing mode for power budget conscious satellites. This assumes the usage of B-dot controller for detumbling and PD controller for pointing. Nonlinear Euler's rotation equations are used to represent the attitude dynamics of satellites and Commercial-off-the-shelf (COTS) reaction wheels and magnetorquers are used to perform the manoeuver. Simulation results will be based on a spacecraft attitude simulator and the use case will be for multiple orbits of launch deployment general to Low Earth Orbit (LEO) satellites.

Keywords: attitude control, detumbling, small satellites, spacecraft autonomy, time optimal control

Procedia PDF Downloads 106

Authors: Fatemeh Yousefi, Narges Fallah, Mohsen Kian, Mehrzad Pakzadeh

Abstract:

The petrochemical complex releases wastewater, which is rich in organic pollutants and could not be treated easily. Treatment of the wastewater from a petrochemical industry has been investigated using a submerged membrane bioreactor (MBR). For this purpose, a pilot-scale submerged MBR with a flat-sheet ultrafiltration membrane was used for treatment of petrochemical wastewater according to Bandar Imam Petrochemical complex (BIPC) Aromatic plant. The testing system ran continuously (24-h) over 6 months. Trials on different membrane fluxes and hydraulic retention time (HRT) were conducted and the performance evaluation of the system was done. During the 167 days operation of the MBR at hydraulic retention time (HRT) of 18, 12, 6, and 3 and at an infinite sludge retention time (SRT), the MBR effluent quality consistently met the requirement for discharge to the environment. A fluxes of 6.51 and 13.02 L m-2 h-1 (LMH) was sustainable and HRT of 6 and 12 h corresponding to these fluxes were applicable. Membrane permeability could be fully recovered after cleaning. In addition, there was no foaming issue in the process. It was concluded that it was feasible to treat the wastewater using submersed MBR technology.

Keywords: membrane bioreactor (MBR), petrochemical wastewater, COD removal, biological treatment

Procedia PDF Downloads 503

Authors: Soudabeh Shemehsavar

Abstract:

In this paper, we consider the situation under a life test, in which the failure time of the test units are not related deterministically to an observable stochastic time varying covariate. In such a case, the joint distribution of failure time and a marker value would be useful for modeling the step stress life test. The problem of accelerating such an experiment is considered as the main aim of this paper. We present a step stress accelerated model based on a bivariate Wiener process with one component as the latent (unobservable) degradation process, which determines the failure times and the other as a marker process, the degradation values of which are recorded at times of failure. Parametric inference based on the proposed model is discussed and the optimization procedure for obtaining the optimal time for changing the stress level is presented. The optimization criterion is to minimize the approximate variance of the maximum likelihood estimator of a percentile of the products’ lifetime distribution.

Keywords: bivariate normal, Fisher information matrix, inverse Gaussian distribution, Wiener process

Procedia PDF Downloads 308

Authors: Anass Rahouti, Guillaume Salze, Ruggiero Lovreglio, Sélim Datoussaïd

Abstract:

In healthcare facilities, training the staff for firefighting and evacuation in real buildings is very challenging due to the presence of a vulnerable population in such an environment. In a standard environment, traditional approaches, such as fire drills, are often used to train the occupants and provide them with information about fire safety procedures. However, those traditional approaches may be inappropriate for a vulnerable population and can be inefficient from an educational viewpoint as it is impossible to expose the occupants to scenarios similar to a real emergency. Immersive serious games could be used as an alternative to traditional approaches to overcome their limitations. Serious games are already being used in different safety domains such as fires, earthquakes and terror attacks for several building types (e.g., office buildings, train stations, tunnels, etc.). In this study, we developed an immersive serious game to improve the fire safety skills of staff in healthcare facilities. An accurate representation of the healthcare environment was built in Unity3D by including visual and audio stimuli inspired from those employed in commercial action games. The serious game is organised in three levels. In each of them, the trainee is presented with a specific fire emergency and s/he can perform protective actions (e.g., firefighting, helping non-ambulant occupants, etc.) or s/he can ignore the opportunity for action and continue the evacuation. In this paper, we describe all the steps required to develop such a prototype, as well as the key questions that need to be answered, to develop a serious game for firefighting and evacuation in healthcare facilities.

Keywords: fire safety, healthcare, serious game, training

Procedia PDF Downloads 438

Authors: Dhurgham Al-Karawi, Nisreen Polus, Shakir Al-Zaidi, Sabah Jassim

Abstract:

The management of COVID-19 patients based on chest imaging is emerging as an essential tool for evaluating the spread of the pandemic which has gripped the global community. It has already been used to monitor the situation of COVID-19 patients who have issues in respiratory status. There has been increase to use chest imaging for medical triage of patients who are showing moderate-severe clinical COVID-19 features, this is due to the fast dispersal of the pandemic to all continents and communities. This article demonstrates the development of machine learning techniques for the test of COVID-19 patients using Chest X-Ray (CXR) images in nearly real-time, to distinguish the COVID-19 infection with a significantly high level of accuracy. The testing performance has covered a combination of different datasets of CXR images of positive COVID-19 patients, patients with viral and bacterial infections, also, people with a clear chest. The proposed AI scheme successfully distinguishes CXR scans of COVID-19 infected patients from CXR scans of viral and bacterial based pneumonia as well as normal cases with an average accuracy of 94.43%, sensitivity 95%, and specificity 93.86%. Predicted decisions would be supported by visual evidence to help clinicians speed up the initial assessment process of new suspected cases, especially in a resource-constrained environment.

Keywords: COVID-19, chest x-ray scan, artificial intelligence, texture analysis, local binary pattern transform, Gabor filter

Procedia PDF Downloads 132

Authors: Jaegu Choi, Jae-Mean Koo, Chang-Sung Seok, Byungwoo Moon

Abstract:

Since massive earthquakes in the world have been reported recently, the safety of nuclear power plants for seismic loading has become a significant issue. Seismic loading is the reverse cyclic loading, consisting of repeated tensile and compression by longitudinal and transverse wave. Up to this time, the study on characteristics of fracture toughness under reverse cyclic loading has been unsatisfactory. Therefore, it is necessary to obtain the fracture toughness under reverse cyclic load for the integrity estimation of nuclear power plants under seismic load. Fracture resistance (J-R) curves, which are used for determination of fracture toughness or integrity estimation in terms of elastic-plastic fracture mechanics, can be derived by the fracture resistance test using single specimen technique. The objective of this paper is to study the effects of reverse cyclic loading on a fracture resistance curve of ESG specimen, having a similar stress gradient compared to the crack surface of the real pipe. For this, we carried out the fracture toughness test under the reverse cyclic loading, while changing incremental plastic displacement. Test results showed that the J-R curves were decreased with a decrease of the incremental plastic displacement.

Keywords: reverse cyclic loading, j-r curve, ESG specimen, incremental plastic displacement

Procedia PDF Downloads 370

Authors: Nattawipa Pakasri

Abstract:

58S (60SiO2-36CaO-4P2O5), three-dimensionally ordered macroporous bioactive glasses (3DOM-BGs) were synthesized by the sol-gel method using dual templating methods. non-ionic surfactant Brij56 used as templates component produced mesoporous and the spherical PMMA colloidal crystals as one template component yielded either three-dimensionally ordered microporous products or shaped bioactive glass nanoparticles. The bioactive glass with aging step for 12 h at room temperature, no structure transformation occurred and the 3DOM structure was produced (Figure a) due to no shrinkage process between the aging step. After 48 h time of o 3DOM structure remained and, nanocube with ∼120 nm edge lengths and nanosphere particle with ∼50 nm was obtained (Figure c, d). PMMA packing templates have octahedral and tetrahedral holes to make 2 final shapes of 3DOM-BGs which is rounded and cubic, respectively. The ageing time change from 12h, 24h and 48h affected to the thickness of interconnecting macropores network. The wall thickness was gradually decrease after increase aging time.

Keywords: three-dimensionally ordered macroporous bioactive glasses, sol-gel method, PMMA, bioactive glass

Procedia PDF Downloads 99

Authors: Baglan Bazylova

Abstract:

The purpose of our article is to consider the social and psychological conflicts in Lyudmila Petrushevskaya’s stories as an artistic presentation of gender structure of modern society; to reveal originality of the characters’ inner world, the models of their behavior expressing the gender specific nature of modern feminine prose. Gender conflicts have taken the leading place in the modern prose. L. Petrushevskaya represents different types of conflicts including those which are shown in the images of real contradictions in the stories "Narratrix", "Thanks to Life”, "Virgin's Case", "Father and Mother". In the prose of Petrushevskaya the gender conflicts come out in two dimensions: The first one is love relations between a man and a woman. Because of the financial indigence, neediness a woman can’t afford herself even to fall in love and arrange her family happiness. The second dimension is the family conflict because of the male adultery. Petrushevskaya fixed on the unmanifistated conflict in detail. In the real life such gender conflict can appear in different forms but for the writer is important to show it as a life basis, hidden behind the externally safe facade of “the family happiness”. In the stories of L. Petrushevskaya the conflicts reflect the common character of the social and historical situations in which her heroines find themselves, in situations where a woman feels her opposition to the customary mode of life. The types of gender conflicts of these stories differ in character of verbal images. They are presented by the verbal and event ranks creating the conflicts just in operation.

Keywords: gender behavior of heroes, gender conflict, gender picture of the world, gender structure

Procedia PDF Downloads 496

Authors: Umer Masood Chaudry, Hafiz Muhammad Rehan Tariq, Chung-soo Kim, Tea-sung Jun

Abstract:

This study explored the influence of pre-stretching temperature on the microstructural characteristics and deformation behavior of AZ61 magnesium alloy and its implications on grain growth during subsequent annealing. AZ61 alloy was stretched to 5% plastic strain along rolling (RD) and transverse direction (TD) at room (RT) and cryogenic temperature (-150 oC, CT) followed by annealing at 320 oC for 1 h to investigate the twinning and dislocation evolution and its consequent effect on the flow stress, plastic strain and strain hardening rate. Compared to RT-stretched samples, significant improvement in yield stress, strain hardening rate and moderate reduction in elongation to failure were witnessed for CT-stretched samples along RD and TD. The subsequent EBSD analysis revealed the increased fraction of fine {10-12} twins and nucleation of multiple {10-12} twin variants caused by higher local stress concentration at the grain boundaries in CT-stretched samples as manifested by the kernel average misorientation. This higher twin fraction and twin-twin interaction imposed the strengthening by restricting the mean free path of dislocations, leading to higher flow stress and strain hardening rate. During annealing of the RT/CT-stretched samples, the residual strain energy and twin boundaries were decreased due to static recovery, leading to a coarse-grained twin-free microstructure. Strain induced boundary migration (SBIM) was found to be the predominant mechanism governing the grain growth during annealing via movement of high angle grain boundaries.

Keywords: magnesium, twinning, twinning variant selection, EBSD, cryogenic deformation

Procedia PDF Downloads 55

Authors: Mohammad Saber Rohi, Saghar Heidari

Abstract:

In this paper, we studied the pricing problem of American options under a regime-switching model with the possibility of a non-optimal exercise policy (early or late exercise time) which is called an irrational strategy. For this, we consider a Markovmodulated model for the dynamic of the underlying asset as an alternative model to the classical Balck-Scholes-Merton model (BSM) and an intensity-based model for the irrational strategy, to provide more realistic results for American option prices under the irrational behavior in real financial markets. Applying a partial differential equation (PDE) approach, the pricing problem of American options under regime-switching models can be formulated as coupled PDEs. To solve the resulting systems of PDEs in this model, we apply a finite element method as the numerical solving procedure to the resulting variational inequality. Under some appropriate assumptions, we establish the stability of the method and compare its accuracy to some recent works to illustrate the suitability of the proposed model and the accuracy of the applied numerical method for the pricing problem of American options under the regime-switching model with irrational behaviors.

Keywords: irrational exercise strategy, rationality parameter, regime-switching model, American option, finite element method, variational inequality

Procedia PDF Downloads 58

Authors: Geeta Partap, Nitika Chugh

Abstract:

The present paper deals with the flexural vibrations of homogeneous, isotropic, generalized micropolar microstretch thermoelastic thin Euler-Bernoulli beam resonators, due to Exponential time varying load. Both the axial ends of the beam are assumed to be at simply supported conditions. The governing equations have been solved analytically by using Laplace transforms technique twice with respect to time and space variables respectively. The inversion of Laplace transform in time domain has been performed by using the calculus of residues to obtain deflection.The analytical results have been numerically analyzed with the help of MATLAB software for magnesium like material. The graphical representations and interpretations have been discussed for Deflection of beam under Simply Supported boundary condition and for distinct considered values of time and space as well. The obtained results are easy to implement for engineering analysis and designs of resonators (sensors), modulators, actuators.

Keywords: microstretch, deflection, exponential load, Laplace transforms, residue theorem, simply supported

Procedia PDF Downloads 297

Authors: Bright Kwakye-Awuah, Elizabeth Von-Kiti, Isaac Nkrumah, Baah Sefa-Ntiri, Craig D. Williams

Abstract:

Bauxite and kaolin from Ghana Bauxite Company mine site were used to synthesize zeolites. Bauxite served as the alumina source and kaolin the silica source. Synthesis variations include variation of aging time at constant crystallization time and variation of crystallization times at constant aging time. Characterization techniques such as X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive x-ray analysis (EDX) and Fourier transform infrared spectroscopy (FTIR) were employed in the characterization of the raw samples as well as the synthesized samples. The results obtained showed that the transformations that occurred and the phase of the resulting products were coordinated by the aging time, crystallization time, alkaline concentration and Si/Al ratio of the system. Zeolites A, X, Y, analcime, Sodalite, and ZK-14 were some of the phases achieved. Zeolite LTA was achieved with short crystallization times of 3, 5, 18 and 24 hours and a maximum aging of 24 hours. Zeolite LSX was synthesized with 24 hr aging followed with 24 hr hydrothermal treatment whilst zeolite Y crystallized after 48 hr of aging and 24 hr crystallization. Prolonged crystallization time produced a mixed phased product. Prolonged aging times, on the other hand, did not yield any zeolite as the sample was amorphous. Increasing the alkaline content of the reaction mixture above 5M introduced sodalite phase in the final product. The properties of the final products were comparable to zeolites synthesized from pure chemical reagents.

Keywords: bauxite, kaolin, aging, crystallization, zeolites

Procedia PDF Downloads 205

Authors: Chen Bo, Wen Zengping

Abstract:

Based on the results of previous studies, we focus on the research of real ground motion selection and scaling method for structural performance-based seismic evaluation using nonlinear dynamic analysis. The input of earthquake ground motion should be determined appropriately to make them compatible with the site-specific hazard level considered. Thus, an optimized selection and scaling method are established including the use of not only Monte Carlo simulation method to create the stochastic simulation spectrum considering the multivariate lognormal distribution of target spectrum, but also a spectral shape parameter. Its applications in structural fragility analysis are demonstrated through case studies. Compared to the previous scheme with no consideration of the uncertainty of target spectrum, the method shown here can make sure that the selected records are in good agreement with the median value, standard deviation and spectral correction of the target spectrum, and greatly reveal the uncertainty feature of site-specific hazard level. Meanwhile, it can help improve computational efficiency and matching accuracy. Given the important infection of target spectrum’s uncertainty on structural seismic fragility analysis, this work can provide the reasonable and reliable basis for structural seismic evaluation under scenario earthquake environment.

Keywords: ground motion selection, scaling method, seismic fragility analysis, spectral shape

Procedia PDF Downloads 279

Authors: Rodrigo Arnaldo Scarpel

Abstract:

Trend following is a widely accepted investment strategy that adopts a rule-based trading mechanism that rather than striving to predict market direction or on information gathering to decide when to buy and when to sell a stock. Thus, in trend following one must respond to market’s movements that has recently happen and what is currently happening, rather than on what will happen. Optimally, in trend following strategy, is to catch a bull market at its early stage, ride the trend, and liquidate the position at the first evidence of the subsequent bear market. For applying the trend following strategy one needs to find the trend and identify trade signals. In order to avoid false signals, i.e., identify fluctuations of short, mid and long terms and to separate noise from real changes in the trend, most academic works rely on moving averages and other technical analysis indicators, such as the moving average convergence divergence (MACD) and the relative strength index (RSI) to uncover intelligible stock trading rules following trend following strategy philosophy. Recently, some works has applied machine learning techniques for trade rules discovery. In those works, the process of rule construction is based on evolutionary learning which aims to adapt the rules to the current environment and searches for the global optimum rules in the search space. In this work, instead of focusing on the usage of machine learning techniques for creating trading rules, a time series trend classification employing a semi-supervised approach was used to early identify both the beginning and the end of upward and downward trends. Such classification model can be employed to identify trade signals and the decision-making procedure is that if an up-trend (down-trend) is identified, a buy (sell) signal is generated. Semi-supervised learning is used for model training when only part of the data is labeled and Semi-supervised classification aims to train a classifier from both the labeled and unlabeled data, such that it is better than the supervised classifier trained only on the labeled data. For illustrating the proposed approach, it was employed daily trade information, including the open, high, low and closing values and volume from January 1, 2000 to December 31, 2022, of the São Paulo Exchange Composite index (IBOVESPA). Through this time period it was visually identified consistent changes in price, upwards or downwards, for assigning labels and leaving the rest of the days (when there is not a consistent change in price) unlabeled. For training the classification model, a pseudo-label semi-supervised learning strategy was used employing different technical analysis indicators. In this learning strategy, the core is to use unlabeled data to generate a pseudo-label for supervised training. For evaluating the achieved results, it was considered the annualized return and excess return, the Sortino and the Sharpe indicators. Through the evaluated time period, the obtained results were very consistent and can be considered promising for generating the intended trading signals.

Keywords: evolutionary learning, semi-supervised classification, time series data, trading signals generation

Procedia PDF Downloads 69

Authors: Catarina Maria Neto Da Cruz, Ana Maria Reis D’Azevedo Breda

Abstract:

The world is changing and, consequently, the young people need more sophisticated tools and skills to lead with the world’s complexity. The Organisation for Economic Co-operation and Development Learning Framework 2030 suggests an interdisciplinary knowledge as a principle for the future of education systems. In the curricular document Portuguese about the profile of students leaving compulsory education, the critical thinking and creative thinking are pointed out as skills to be developed, which imply the interconnection of different knowledge, applying it in different contexts and learning areas. Unlike primary school teachers, teachers specialized in a specific area lead to more difficulties in the implementation of interdisciplinary approaches in the classrooms and, despite the effort, the interdisciplinarity is not a common practice in schools. Statement like "Mathematics is everywhere" is unquestionable, however, many math teachers show difficulties in presenting such evidence in their classes. Mathematical modelling and problems in real contexts are promising in the development of interdisciplinary pedagogical practices and in Portugal there is a continuous training offer to contribute to the development of teachers in terms of their pedagogical approaches. But when teachers find themselves in the classroom, without a support, do they feel able to implement interdisciplinary practices? In this communication we will try to approach this issue through a case study involving a group of Mathematics teachers, who attended a training aimed at stimulating interdisciplinary practices in real contexts, namely related to the COVID-19 pandemic.

Keywords: education, mathematics, teacher training, interdisciplinarity

Procedia PDF Downloads 73

Authors: Wildan Maulana Wildan, Siti Annisa Rahmayani Icha

Abstract:

Nowadays advances in information technology are needed by all the inhabitants of the earth for the sake of ease all their work, but it is worth to introduced the technological advances in the world of children. Before the technology is growing rapidly, children busy with various of traditional games and have high socialization. Moreover, after it presence, almost all of children spend more their time for playing gadget, It can affect the education of children and will change the character and personality children. However, children also can not be separated with the technology. Because the technology insight knowledge of children will be more extensive. Because the world can not be separated with advances in technology as well as with children, there should be developed a smartphone operating system that is child-friendly. The operating system is able to filter contents that do not deserve children, even in this system there is a reminder of a time study, prayer time and play time for children and there are interactive contents that will help the development of education and children's character. Children need technology, and there are some ways to introduce it to children. We must look at the characteristics of children in different environments. Thus advances in technology can be beneficial to the world children and their parents, and educators do not have to worry about advances in technology. We should be able to take advantage of advances in technology best possible.

Keywords: information technology, smartphone operating system, education, character

Procedia PDF Downloads 492