Search results for: 2D constitutive model

Authors: Jafar Akbari, Masoud Rismanchian, Samira Ramezani

Abstract:

Purpose: The photocatalytic degradation of pollutants is a novel technology with various advantages such as high efficiency and energy saving. In this research, the effects of operational variables on the photocatalytic efficiency of TiO₂ coated on nickel foam in the removal of toluene from the simulated indoor air have been investigated. Methods: TiO₂ film were prepared via the sol-gel method and coated on nickel foam. The characteristics and morphology were found using XRD, SEM, and BET technique. Then, the effects of relative humidity, UV-A intensity, the initial toluene concentration, TiO₂ loading, and the air circulation velocity on the photocatalytic degradation rate have been evaluated. Results: The optimal degradation of toluene has been achieved with loading 4.35 g TiO2 on the foam, 30% RH, 5.4 µW.cm−2 UV-A intensity, and 20 ppm initial concentration in the air circulation velocity of 0.15 fpm. Conclusion: The changes of toluene photocatalytic degradation rate have been studied at various times. Also, the kinetic behavior of toluene photocatalytic degradation has been investigated using Langmuir-Hinshelwood (L-H) model.

Keywords: photocatalytic degradation, operational variables, tio₂, nickel foam, gaseous toluene, nanotechnology

Procedia PDF Downloads 87

Authors: Farooq A. Al-Sheikh, Ali Elkamel, William A. Anderson

Abstract:

A fluidized catalytic cracking unit (FCCU) is one of the effective units in many refineries. Modeling and optimization of FCCU were done by many researchers in past decades, but in this research, comparison between post- and oxy-combustion was studied in the regenerator-FCCU. Therefore, a simplified mathematical model was derived by doing mass/heat balances around both reactor and regenerator. A state space analysis was employed to show effects of the flow rates variables such as air, feed, spent catalyst, regenerated catalyst and flue gas on the output variables. The main aim of studying dynamic responses is to figure out the most influencing variables that affect both reactor/regenerator temperatures; also, finding the upper/lower limits of the influencing variables to ensure that temperatures of the reactors and regenerator work within normal operating conditions. Therefore, those values will be used as side constraints in the optimization technique to find appropriate operating regimes. The objective functions were modeled to be maximizing the energy in the reactor while minimizing the energy consumption in the regenerator. In conclusion, an oxy-combustion process can be used instead of a post-combustion one.

Keywords: FCCU modeling, optimization, oxy-combustion, post-combustion

Procedia PDF Downloads 211

Authors: Xizhen Zhou, Yanjie Ji

Abstract:

The charging behavior of drivers provides a reference for the planning and management of charging facilities. Based on the real trajectory data of electric vehicles, this study explored the influence of the surrounding environments of the parking spot on charging decisions. The built environment, the condition of vehicles, and the nearest charging station were all considered. And the mixed binary logit model was used to capture the impact of unobserved heterogeneity. The results show that the number of fast chargers in the charging station, parking price, dwell time, and shopping services all significantly impact the charging decision, while the leisure services, scenic spots, and mileage since the last charging are opposite. Besides, factors related to unobserved heterogeneity include the number of fast chargers, parking and charging prices, residential areas, etc. The interaction effects of random parameters further illustrate the complexity of charging choice behavior. The results provide insights for planning and managing charging facilities.

Keywords: charging decision, trajectory, electric vehicle, infrastructure, mixed logit

Procedia PDF Downloads 71

Authors: Salah Alrabeei, Mohammad Yousuf

Abstract:

The goal of option pricing theory is to help the investors to manage their money, enhance returns and control their financial future by theoretically valuing their options. However, most of the option pricing models have no analytical solution. Furthermore, not all the numerical methods are efficient to solve these models because they have nonsmoothing payoffs or discontinuous derivatives at the exercise price. In this paper, we solve the American option under jump diffusion models by using efficient time-dependent numerical methods. several techniques are integrated to reduced the overcome the computational complexity. Fast Fourier Transform (FFT) algorithm is used as a matrix-vector multiplication solver, which reduces the complexity from O(M2) into O(M logM). Partial fraction decomposition technique is applied to rational approximation schemes to overcome the complexity of inverting polynomial of matrices. The proposed method is easy to implement on serial or parallel versions. Numerical results are presented to prove the accuracy and efficiency of the proposed method.

Keywords: integral differential equations, jump–diffusion model, American options, rational approximation

Procedia PDF Downloads 120

Authors: Nada Slimane, Foued Theljani, Faouzi Bouani

Abstract:

The paper addresses the problem of fault diagnosis for systems operating in several modes (normal or faulty) based on states assessment. We use, for this purpose, a methodology consisting of three main processes: 1) sequential data clustering, 2) linear model regression and 3) state filtering. Typically, Kalman Filter (KF) is an algorithm that provides estimation of unknown states using a sequence of I/O measurements. Inevitably, although it is an efficient technique for state estimation, it presents two main weaknesses. First, it merely predicts states without being able to isolate/classify them according to their different operating modes, whether normal or faulty modes. To deal with this dilemma, the KF is endowed with an extra clustering step based fully on sequential version of the k-means algorithm. Second, to provide state estimation, KF requires state space models, which can be unknown. A linear regularized regression is used to identify the required models. To prove its effectiveness, the proposed approach is assessed on a simulated benchmark.

Keywords: clustering, diagnosis, Kalman Filtering, k-means, regularized regression

Procedia PDF Downloads 182

Authors: Payal Patel

Abstract:

Textile machinery is one of the fastest evolving areas which has an application of mechanical engineering. The modular approach towards the processing right from the stage of cotton to the fabric, allows us to observe the result of each process on its input. Cost and space being the major constraints. The flyer is a component of roving machine, which is used as a part of spinning process. In the present work using the application of Hyper Works, the flyer arm has been modified which saves the material used for manufacturing the flyer. The size optimization of the flyer is carried out with the objective of reduction in weight under the constraints of standard operating conditions. The new design of the flyer is proposed and validated using the module of HyperWorks which is equally strong, but light weighted compared to the existing design. Dynamic balancing of the optimized model is carried out to align a principal inertia axis with the geometric axis of rotation. For the balanced geometry of flyer, air resistance is obtained theoretically and with Gambit and Fluent. Static analysis of the balanced geometry has been done to verify the constraint of operating condition. Comparison of weight, deflection, and factor of safety has been made for different aluminum alloys.

Keywords: flyer, size optimization, textile, weight

Procedia PDF Downloads 216

Authors: Shahnaz Ashrafpour, Tahereh Tohidi Moghadam, Bijan Ranjbar

Abstract:

Identifying the nature of protein-nanoparticle interactions and favored binding sites is an important issue in functional characterization of biomolecules and their physiological responses. Herein, interaction of silver nanoparticles with lysozyme as a model protein has been monitored via fluorescence spectroscopy. Formation of complex between the biomolecule and silver nanoparticles (AgNPs) induced a steady state reduction in the fluorescence intensity of protein at different concentrations of nanoparticles. Tryptophan fluorescence quenching spectra suggested that silver nanoparticles act as a foreign quencher, approaching the protein via this residue. Analysis of the Stern-Volmer plot showed quenching constant of 3.73 µM−1. Moreover, a single binding site in lysozyme is suggested to play role during interaction with AgNPs, having low affinity of binding compared to gold nanoparticles. Unfolding studies of lysozyme showed that complex of lysozyme-AgNPs has not undergone structural perturbations compared to the bare protein. Results of this effort will pave the way for utilization of sensitive spectroscopic techniques for rational design of nanobiomaterials in biomedical applications.

Keywords: nanocarrier, nanoparticles, surface plasmon resonance, quenching fluorescence

Procedia PDF Downloads 330

Authors: Abolghasem Akbari

Abstract:

The Natural Resources Conservation Service Curve Number (NRCS-CN) method is widely used for predicting direct runoff from rainfall. It employs the hydrologic soil groups and land use information along with period soil moisture conditions to derive NRCS-CN. This method has been well documented and available in popular rainfall-runoff models such as HEC-HMS, SWAT, SWMM and much more. Despite all benefits and advantages of this well documented and easy-to-use method, it does not take into account the effect of terrain slope and drainage area. This study aimed to first investigate the effect of slope on CN and then slope-adjusted runoff potential map is generated for Kuantan River Basin, Malaysia. The Hanng method was used to adjust CN values provided in National Handbook of Engineering and The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM) version 2 is used to derive slope map with the spatial resolution of 30 m for Kuantan River Basin (KRB). The study significantly enhanced the application of GIS tools and recent advances in earth observation technology to analyze the hydrological process.

Keywords: Kuantan, ASTER-GDEM, SCS-CN, runoff

Procedia PDF Downloads 287

Authors: Hany Mohamed Abdu, Mohamed Hassan Gadallah, El-Giushi Mokhtar, Yehia Mahmoud Ismail

Abstract:

Laser beam cutting is one nontraditional machining process. This paper optimizes the parameters of Laser beam cutting machining parameters of Stainless steel (316L) by considering the effect of input parameters viz. power, oxygen pressure, frequency and cutting speed. Statistical design of experiments are carried in three different levels and process responses such as 'Average kerf taper (Ta)' and 'Surface Roughness (Ra)' are measured accordingly. A quadratic mathematical model (RSM) for each of the responses is developed as a function of the process parameters. Responses predicted by the models (as per Taguchi’s L27 OA) are employed to search for an optimal parametric combination to achieve desired yield of the process. RSM models are developed for mean responses, S/N ratio, and standard deviation of responses. Optimization models are formulated as single objective problem subject to process constraints. Models are formulated based on Analysis of Variance (ANOVA) using MATLAB environment. Optimum solutions are compared with Taguchi Methodology results.

Keywords: optimization, laser cutting, robust design, kerf width, Taguchi method, RSM and DOE

Procedia PDF Downloads 620

Authors: Kumaresh Selvakumar, Man Young Kim

Abstract:

A wet scrubber is an air pollution control device that removes particulate matter and acid gases from waste gas streams found in marine engine exhaust. If the flue gases in the exhaust is employed for CFD simulation, it makes the problem complicate due to the involvement of emissions. Owing to the fact, the scrubber system in this paper is handled with appropriate approach by designing with the flow properties of hot air and water droplet injections to evaluate the flow behavior inside the system. Since the wet scrubber has the capability of operating over wide range of mixture compositions, the current scrubber model with the designing approach doesn’t deviate from the actual behavior of the system. The scrubber design is constructed with engine exhaust pipe with the purpose of measuring the flow properties inside the scrubber by the influence of exhaust pipe characteristics. The flow properties are computed by the thermodynamic variables such as temperature and pressure with the flow velocity. In this work, numerical analyses have been conducted for the flow of fluid in the scrubber system through CFD technique.

Keywords: wet scrubber, water droplet injections, thermodynamic variables, CFD technique

Procedia PDF Downloads 345

Authors: Kanlaya Ratanasuphakarn, Suttipong Boonphadung

Abstract:

The research on the development of ability in reading comprehension based on metacognitive strategies aimed to (1) improve the students’development of ability in reading comprehension based on metacognitive strategies, (2) evaluate the students’ satisfaction on using metacognitive strategies in learning as a tool developing the ability in reading comprehension. Forty-eight of Mattayom 3 students who have enrolled in the subject of research for learning development of semester 2 in 2013 were purposively selected as the research cohort. The research tools were lesson plans for reading comprehension, pre-posttest and satisfaction questionnaire that were approved as content validity and reliability (IOC=.66-1.00,0.967). The research found that the development of ability in reading comprehension of the research samples before using metacognitive strategies in learning activities was in the normal high level. Additionally, the research discovered that the students’ satisfaction of the research cohort after applying model in learning activities appeared to be high level of satisfaction on using metacognitive strategies in learning as a tool for the development of ability in reading comprehension.

Keywords: development of ability, metacognitive strategies, satisfaction, reading comprehension

Procedia PDF Downloads 309

Authors: Omolade Adeleke, Jonathan Olusegun Famoroti

Abstract:

This study empirically examined the monetary policy and economic growth in the classical cycles in 8 member countries of the West African Economic and Monetary Union (WAEMU), using the Markov switching model for the Two-phase Regime, covering the period 1980Q1 to 2020Q4. Our estimates suggest that these countries demonstrate to have similar business cycles, and the economies stay more in an expansion regime than a recession regime. The result further shows that the union has an average duration period of 3.1 and 15.9 quarters for contraction and expansion periods, respectively. The business cycle duration, on average, suggests 19 quarters, varying from country to country. Therefore, the formulation of policies that can enhance aggregate demand by member countries in the union is an antidote for recession and is necessary to drive the economy into equilibrium. Also, a low-interest rate and reduced inflation rate would ginger long-run economic growth.

Keywords: monetary policy, business cycle, economic growth, Markov switching

Procedia PDF Downloads 76

Authors: Adila Shafqat

Abstract:

Climate change and urbanization has changed the face of many cities in developing countries. Urbanization is linked with land use and land cover change, that is further intensify by the effects of changing climates. Green infrastructures provide numerous ecosystem services which effect the physical set up of the cities in the long run. Land surface temperatures is considered as defining parameter in the studies of the thermal impact on the land cover. Current study is conducted in the semi-arid urban areas of the Bahawalpur region. Accordingly, Land Surface Temperatures and land cover maps are derived from Landsat image through remote sensing techniques. The cooling impact of green infrastructure is determined by calculating land surface temperature of buffered zones around green infrastructures. A regression model is applied for results. It is seen that land surface temperature around green infrastructures in 1 to 3 degrees lower than the built up surroundings. The result indicates that the urban green infrastructures should be planned according to the local needs and characteristics of landuse so that they can effectively tackle land surface temperatures of urban areas.

Keywords: climate change, surface temperatures, green spaces, urban planning

Procedia PDF Downloads 120

Authors: Mingbao Chen

Abstract:

The blue economy is a new comprehensive marine economy integrated with resources, industries, and regions, and is an upgraded version of the marine economy. The blue economy attaches great importance to the coordinated development of the ecological environment and the economy, which is an emerging economic form advocated by all countries in the world. This paper constructs the model including four variables：natural capital, economic capital, intellectual capital, cultural capital. Theoretically, this paper deduces the function mechanism of variables on economic growth, and empirically calculates the driving force and influence of the blue economy on the national economy by using data of China's 2006-2015 year. The results show that natural capital and economic capital remain the main factors of blue growth in the blue economy. And with the development of economic society and technological progress, the role of intellectual capital and cultural capital is bigger and bigger. Therefore, promoting the development of marine science and technology and culture is the focus of the future blue economic development.

Keywords: blue growth, natural capital, intellectual capital, cultural capital

Procedia PDF Downloads 156

Authors: Tugrul Oktay, Mehmet Konar, Mohamed Abdallah Mohamed, Murat Aydin, Firat Sal, Murat Onay, Mustafa Soylak

Abstract:

In this paper, it is aimed to improve autonomous flight performance of a load-carrying (payload: 3 kg and total: 6kg) unmanned aerial vehicle (UAV) through active wing and horizontal tail active morphing and also integrated autopilot system parameters (i.e. P, I, D gains) and UAV parameters (i.e. extension ratios of wing and horizontal tail during flight) design. For this purpose, a loadcarrying UAV (i.e. ZANKA-II) is manufactured in Erciyes University, College of Aviation, Model Aircraft Laboratory is benefited. Optimum values of UAV parameters and autopilot parameters are obtained using a stochastic optimization method. Using this approach autonomous flight performance of UAV is substantially improved and also in some adverse weather conditions an opportunity for safe flight is satisfied. Active morphing and integrated design approach gives confidence, high performance and easy-utility request of UAV users.

Keywords: unmanned aerial vehicles, morphing, autopilots, autonomous performance

Procedia PDF Downloads 673

Authors: Lei Ye, Min Liu, Yong-Li Gao, Jun Zhang

Abstract:

Purpose: The aims of the study are to investigate the status of health-promoting lifestyle and to compare the healthy lifestyle of emergency nurses in different levels of hospitals in Sichuan province, China. The investigation is mainly about the health-promoting lifestyle, including spiritual growth, health responsibility, physical activity, nutrition, interpersonal relations, stress management. Then the factors were analyzed influencing the health-promoting lifestyle of emergency nurses in hospitals of Sichuan province in order to find the relevant models to provide reference evidence for intervention. Study Design: A cross-sectional research method was adopted. Stratified cluster sampling, based on geographical location, was used to select the health facilities of 1389 emergency nurses in 54 hospitals from Sichuan province in China. Method: The 52-item, six-factor structure Health-Promoting Lifestyle Profile II (HPLP- II) instrument was used to explore participants’ self-reported health-promoting behaviors and measure the dimensions of health responsibility, physical activity, nutrition, interpersonal relations, spiritual growth, and stress management. Demographic characteristics, education, work duration, emergency nursing work duration and self-rated health status were documented. Analysis: Data were analyzed through SPSS software ver. 17.0. Frequency, percentage, mean ± standard deviation were used to describe the general information, while the Nonparametric Test was used to compare the constituent ratio of general data of different hospitals. One-way ANOVA was used to compare the scores of health-promoting lifestyle in different levels hospital. A multiple linear regression model was established. P values which were less than 0.05 determined statistical significance in all analyses. Result: The survey showed that the total score of health-promoting lifestyle of nurses at emergency departments in Sichuan Province was 120.49 ± 21.280. The relevant dimensions are ranked by scores in descending order: interpersonal relations, nutrition, health responsibility, physical activity, stress management, spiritual growth. The total scores of the three-A hospital were the highest (121.63 ± 0.724), followed by the senior class hospital (119.7 ± 1.362) and three-B hospital (117.80 ± 1.255). The difference was statistically significant (P=0.024). The general data of nurses was used as the independent variable which includes age, gender, marital status, living conditions, nursing income, hospital level, Length of Service in nursing, Length of Service in emergency, Professional Title, education background, and the average number of night shifts. The total score of health-promoting lifestyle was used as dependent variable; Multiple linear regression analysis method was adopted to establish the regression model. The regression equation F = 20.728, R2 = 0.061, P < 0.05, the age, gender, nursing income, turnover intention and status of coping stress affect the health-promoting lifestyle of nurses in emergency department, the result was statistically significant (P < 0.05 ). Conclusion: The results of the investigation indicate that it will help to develop health promoting interventions for emergency nurses in all levels of hospital in Sichuan Province through further research. Managers need to pay more attention to emergency nurses’ exercise, stress management, self-realization, and conduct intervention in nurse training programs.

Keywords: emergency nurse, health-promoting lifestyle profile II, health behaviors, lifestyle

Procedia PDF Downloads 282

Authors: Bok Yae Chung, Eun Hee Oh

Abstract:

Breast cancer patients require more nutritional interventions than others. However, a few studies have attempted to assess the overall nutritional status, to reduce body weight and BMI by improving diet, and to improve the prognosis of cancer for breast cancer patients. The purpose of this study was to evaluate the effect of diet intervention in the breast cancer patients through meta-analysis. For the study purpose, 16 studies were selected by using PubMed, ScienceDirect, ProQuest and CINAHL. Meta-analysis was performed using a random-effects model, and the effect size on outcome variables in breast cancer was calculated. The effect size for outcome variables of diet intervention was a large effect size. For heterogeneity, moderator analysis was performed using intervention type and intervention duration. All moderators did not significant difference. Diet intervention has significant positive effects on outcome variables in breast cancer. As a result, it is suggested that the timing of the intervention should be no more than six months, but a strategy for sustaining long-term intervention effects should be added if nutritional intervention is to be administered for breast cancer patients in the future.

Keywords: breast cancer, diet, mete-analysis, intervention

Procedia PDF Downloads 435

Authors: Nikita Koradia

Abstract:

Hyundai Motor Company, which started off as a small fish in a big sea, paved its way out successfully and established itself as an independent group from the conglomerate. Hyundai, with its officious power across the globe and particularly in South Korea in the automobile industry, has one the most complex yet fascinating governance structure. Being the second largest contributor to the Gross Domestic Product of South Korea after Samsung and having a market share of 51.3% domestically in automobile industry, Hyundai has faced its part of criticism owing to its anti-labor union approach and owing to its internalization of supply chain management. The censure has been coming from across jurisdictions like China, India, Canada, the EU, etc. The paper focuses on the growth of Hyundai and its inward and outward investment structure. The paper questions the ability of Hyundai to become a mini-state in itself by focusing on its governance structure. The paper further elaborates on its compliance and disclosure regime in the field of Corporate social responsibility and explores how far the business structure adopted by Hyundai works in its favor to become one of the leading automobile contenders in the market.

Keywords: compliance regime, disclosure regime, Hyundai motor company, supply-chain management

Procedia PDF Downloads 118

Authors: Mingxin Li, Liya Ni

Abstract:

Autonomous parking is a valuable feature applicable to many robotics applications such as tour guide robots, UV sanitizing robots, food delivery robots, and warehouse robots. With auto-parking, the robot will be able to park at the charging zone and charge itself without human intervention. As compared to self-driving vehicles, auto-parking is more challenging for a small-scale mobile robot only equipped with a front camera due to the camera view limited by the robot’s height and the narrow Field of View (FOV) of the inexpensive camera. In this research, auto-parking of a small-scale mobile robot with a front camera only was achieved in a four-step process: Firstly, transfer learning was performed on the AlexNet, a popular pre-trained convolutional neural network (CNN). It was trained with 150 pictures of empty parking slots and 150 pictures of occupied parking slots from the view angle of a small-scale robot. The dataset of images was divided into a group of 70% images for training and the remaining 30% images for validation. An average success rate of 95% was achieved. Secondly, the image of detected empty parking space was processed with edge detection followed by the computation of parametric representations of the boundary lines using the Hough Transform algorithm. Thirdly, the positions of the entrance point and center of available parking space were predicted based on the robot kinematic model as the robot was driving closer to the parking space because the boundary lines disappeared partially or completely from its camera view due to the height and FOV limitations. The robot used its wheel speeds to compute the positions of the parking space with respect to its changing local frame as it moved along, based on its kinematic model. Lastly, the predicted entrance point of the parking space was used as the reference for the motion control of the robot until it was replaced by the actual center when it became visible again by the robot. The linear and angular velocities of the robot chassis center were computed based on the error between the current chassis center and the reference point. Then the left and right wheel speeds were obtained using inverse kinematics and sent to the motor driver. The above-mentioned four subtasks were all successfully accomplished, with the transformed learning, image processing, and target prediction performed in MATLAB, while the motion control and image capture conducted on a self-built small scale differential drive mobile robot. The small-scale robot employs a Raspberry Pi board, a Pi camera, an L298N dual H-bridge motor driver, a USB power module, a power bank, four wheels, and a chassis. Future research includes three areas: the integration of all four subsystems into one hardware/software platform with the upgrade to an Nvidia Jetson Nano board that provides superior performance for deep learning and image processing; more testing and validation on the identification of available parking space and its boundary lines; improvement of performance after the hardware/software integration is completed.

Keywords: autonomous parking, convolutional neural network, image processing, kinematics-based prediction, transfer learning

Procedia PDF Downloads 132

Authors: Mohamed Noureldin, Jinkoo Kim

Abstract:

In this study, a genetic algorithm was used to find out the optimum locations of the slit dampers satisfying a target displacement. A seismic retrofit scheme for a building structure was presented using steel plate slit dampers. A cyclic loading test was used to verify the energy dissipation capacity of the slit damper. The seismic retrofit of the model structure using the slit dampers was compared with the retrofit with enlarging shear walls. The capacity spectrum method was used to propose a simple damper distribution scheme proportional to the inter-story drifts. The validity of the simple story-wise damper distribution procedure was verified by comparing the results of the genetic algorithm. It was observed that the proposed simple damper distribution pattern was in a good agreement with the optimum distribution obtained from the genetic algorithm. Acknowledgment: This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2017R1D1A1B03032809).

Keywords: slit dampers, seismic retrofit, genetic algorithm, optimum design

Procedia PDF Downloads 223

Authors: Prajamitra Bhuyan

Abstract:

Transport operators have a range of intervention options available to improve or enhance their networks. But often such interventions are made in the absence of sound evidence on what outcomes may result. Cycling superhighways were promoted as a sustainable and healthy travel mode which aims to cut traffic congestion. The estimation of the impacts of the cycle superhighways on congestion is complicated due to the non-random assignment of such intervention over the transport network. In this paper, we analyse the causal effect of cycle superhighways utilising pre-innervation and post-intervention information on traffic and road characteristics along with socio-economic factors. We propose a modeling framework based on the propensity score and outcome regression model. The method is also extended to doubly robust set-up. Simulation results show the superiority of the performance of the proposed method over existing competitors. The method is applied to analyse a real dataset on the London transport network, and the result would help effective decision making to improve network performance.

Keywords: average treatment effect, confounder, difference-in-difference, intelligent transportation system, potential outcome

Procedia PDF Downloads 240

Authors: Artur Krukowski, Emmanouela Vogiatzaki

Abstract:

The article presents an ongoing work in research projects such as SCAN4RECO or ARCH, both funded by the European Commission under Horizon 2020 program. The former one concerns multimodal and multispectral scanning of Cultural Heritage assets for their digitization and conservation via spatiotemporal reconstruction and 3D printing, while the latter one aims to better preserve areas of cultural heritage from hazards and risks. It co-creates tools that would help pilot cities to save cultural heritage from the effects of climate change. It develops a disaster risk management framework for assessing and improving the resilience of historic areas to climate change and natural hazards. Tools and methodologies are designed for local authorities and practitioners, urban population, as well as national and international expert communities, aiding authorities in knowledge-aware decision making. In this article we focus on 3D modelling of object geometry using primarily photogrammetric methods to achieve very high model accuracy using consumer types of devices, attractive both to professions and hobbyists alike.

Keywords: 3D modelling, UAS, cultural heritage, preservation

Procedia PDF Downloads 123

Authors: Nikolaos Mamalis

Abstract:

The work of the eminent architect and composer has undoubtedly been influenced both by his architecture and collaboration with Le Corbusier and by the conquests of the musical avant-garde of the 20th century (Schoenberg, Messian, Bartock, electroacoustic music). It is known that the golden mean and the Fibonacci sequence played a momentous role in the Architectural Avant-garde (Modulor) and expanded on musical pursuits. Especially in the 50s (serialism), it was a structural tool for composition. Xenakis' architectural and musical work (Sacrifice, Metastasis, Rebonds, etc.) received the influence of the Golden Section, as has been repeatedly demonstrated. However, the idea of this retrospective sequence and the reflection raised by the search for new proportions, both in the architectural and the musical work of Xenakis, was not limited to constituting a step, a workable formula that acted unifyingly with regard to the other parameters of the musical work, or as an aesthetic model that makes sense - philosophically and poetically - an anthropocentric dimension as in other composers (see Luigi Nono) ̇ triggered a qualitative leap, an opening of the composer to the assimilation of mathematical concepts and scientific types in music and the consolidation of new sound horizons of stochastic music.

Keywords: golden ratio, music, space, stochastic music

Procedia PDF Downloads 52

Authors: Srinidhi. A, Naveed Ahmed, Twinkle Hareendran, Vriksha Prakash

Abstract:

This work reviews some of the advanced image processing techniques for deep learning applications. Object detection by template matching, image denoising, edge detection, and super-resolution modelling are but a few of the tasks. The paper looks in into great detail, given that such tasks are crucial preprocessing steps that increase the quality and usability of image datasets in subsequent deep learning tasks. We review some of the methods for the assessment of image quality, more specifically sharpness, which is crucial to ensure a robust performance of models. Further, we will discuss the development of deep learning models specific to facial emotion detection, age classification, and gender classification, which essentially includes the preprocessing techniques interrelated with model performance. Conclusions from this study pinpoint the best practices in the preparation of image datasets, targeting the best trade-off between computational efficiency and retaining important image features critical for effective training of deep learning models.

Keywords: image processing, machine learning applications, template matching, emotion detection

Procedia PDF Downloads 16

Authors: Yagya Raj Pandeya, Joonwhoan Lee

Abstract:

The dynamic behavior of music and video makes it difficult to evaluate musical instrument playing in a video by computer system. Any television or film video clip with music information are rich sources for analyzing musical instruments using modern machine learning technologies. In this research, we integrate the audio and video information sources using convolutional neural network (CNN) and pass network learned features through recurrent neural network (RNN) to preserve the dynamic behaviors of audio and video. We use different pre-trained CNN for music and video feature extraction and then fine tune each model. The music network use 2D convolutional network and video network use 3D convolution (C3D). Finally, we concatenate each music and video feature by preserving the time varying features. The long short term memory (LSTM) network is used for long-term dynamic feature characterization and then use late fusion with generalized mean. The proposed network performs better performance to recognize the musical instrument using audio-video multimodal neural network.

Keywords: multimodal, 3D convolution, music-video feature extraction, generalized mean

Procedia PDF Downloads 215

Authors: E. L. Albuquerque, U. L. Fulco, G. S. Ourique

Abstract:

The focus of this work is on the numerical investigation of the charge transport properties of the de novo-designed alpha3 polypeptide, as well as in its variants, all of them probed by gene engineering. The theoretical framework makes use of a tight-binding model Hamiltonian, together with ab-initio calculations within quantum chemistry simulation. The alpha3 polypeptide is a 21-residue with three repeats of the seven-residue amino acid sequence Leu-Glu-Thr-Leu-Ala-Lys-Ala, forming an alpha–helical bundle structure. Its variants are obtained by Ala→Gln substitution at the e (5th) and g (7th) position, respectively, of the alpha3 polypeptide amino acid sequence. Using transmission electron microscopy and atomic force microscopy, it was observed that the alpha3 polypeptide and one of its variant do have the ability to form fibrous assemblies, while the other does not. Our main aim is to investigate whether or not the biased alpha3 polypeptide and its variants can be also identified by quantum charge transport measurements through current-voltage (IxV) curves as a pattern to characterize their fibrous assemblies. It was observed that each peptide has a characteristic current pattern, which may be distinguished by charge transport measurements, suggesting that it might be a useful tool for the development of biosensors.

Keywords: charge transport properties, electronic transmittance, current-voltage characteristics, biological sensor

Procedia PDF Downloads 665

Authors: A. Newman-Tancredi, R. Depoortère, P. Gruca, E. Litwa, M. Lason, M. Papp

Abstract:

The N-methyl-D-aspartic acid (NMDA) receptor antagonist, ketamine, can elicit rapid-acting antidepressant (RAAD) effects in treatment-resistant patients, but it requires parenteral co-administration with a classical antidepressant under medical supervision. In addition, ketamine can also produce serious side effects that limit its long-term use, and there is much interest in identifying RAADs based on ketamine’s mechanism of action but with safer profiles. Ketamine elicits GABAergic interneuron inhibition, glutamatergic neuron stimulation, and, notably, activation of serotonin 5-HT1A receptors in the prefrontal cortex (PFC). Direct activation of the latter receptor subpopulation with selective ‘biased agonists’ may therefore be a promising strategy to identify novel RAADs and, consistent with this hypothesis, the prototypical cortical biased agonist, NLX-101, exhibited robust RAAD-like activity in the chronic mild stress model of depression (CMS). The present study compared the effects of a novel, selective 5-HT1A receptor-biased agonist, NLX-204, with those of ketamine and NLX-101. Materials and methods: CMS procedure was conducted on Wistar rats; drugs were administered either intraperitoneally (i.p.) or by bilateral intracortical microinjection. Ketamine: 10 mg/kg i.p. or 10 µg/side in PFC; NLX-204 and NLX-101: 0.08 and 0.16 mg/kg i.p. or 16 µg/side in PFC. In addition, interaction studies were carried out with systemic NLX-204 or NLX-101 (each at 0.16 mg/kg i.p.) in combination with intracortical WAY-100635 (selective 5-HT1A receptor antagonist; 2 µg/side) or muscimol (GABA-A receptor agonist, 12.5 ng/side). Anhedonia was assessed by CMS-induced decrease in sucrose solution consumption; anxiety-like behavior was assessed using the Elevated Plus Maze (EPM), and cognitive impairment was assessed by the Novel Object Recognition (NOR) test. Results: A single administration of NLX-204 was sufficient to reverse the CMS-induced deficit in sucrose consumption, similarly to ketamine and NLX-101. NLX-204 also reduced CMS-induced anxiety in the EPM and abolished CMS-induced NOR deficits. These effects were maintained (EPM and NOR) or enhanced (sucrose consumption) over a subsequent 2-week period of treatment. The anti-anhedonic response of the drugs was also maintained for several weeks Following treatment discontinuation, suggesting that they had sustained effects on neuronal networks. A single PFC administration of NLX-204 reversed deficient sucrose consumption, similarly to ketamine and NLX-101. Moreover, the anti-anhedonic activities of systemic NLX-204 and NLX 101 were abolished by coadministration with intracortical WAY-100635 or muscimol. Conclusions: (i) The antidepressant-like activity of NLX-204 in the rat CMS model was as rapid as that of ketamine or NLX-101, supporting targeting cortical 5-HT1A receptors with selective, biased agonists to achieve RAAD effects. (ii)The anti-anhedonic activity of systemic NLX-204 was mimicked by local administration of the compound in the PFC, confirming the involvement of cortical circuits in its RAAD-like effects. (iii) Notably, the effects of systemic NLX-204 and NLX-101 were abolished by PFC administration of muscimol, indicating that they act by (indirectly) eliciting a reduction in cortical GABAergic neurotransmission. This is consistent with ketamine’s mechanism of action and suggests that there are converging NMDA and 5-HT1A receptor signaling cascades in PFC underlying the RAAD-like activities of ketamine and NLX-204. Acknowledgements: The study was financially supported by NCN grant no. 2019/35/B/NZ7/00787.

Keywords: depression, ketamine, serotonin, 5-HT1A receptor, chronic mild stress

Procedia PDF Downloads 113

Authors: Yuzuru Mitsui, Takashi Ikegami

Abstract:

The exponents of Taylor’s law in deterministic chaotic systems are computed, and their meanings are intensively discussed. Taylor’s law is the scaling relationship between the mean and variance (in both space and time) of population abundance, and this law is known to hold in a variety of ecological time series. The exponents found in the temporal Taylor’s law are different from those of the spatial Taylor’s law. The temporal Taylor’s law is calculated on the time series from the same locations (or the same initial states) of different temporal phases. However, with the spatial Taylor’s law, the mean and variance are calculated from the same temporal phase sampled from different places. Most previous studies were done with stochastic models, but we computed the temporal and spatial Taylor’s law in deterministic systems. The temporal Taylor’s law evaluated using the same initial state, and the spatial Taylor’s law was evaluated using the ensemble average and variance. There were two main discoveries from this work. First, it is often stated that deterministic systems tend to have the value two for Taylor’s exponent. However, most of the calculated exponents here were not two. Second, we investigated the relationships between chaotic features measured by the Lyapunov exponent, the correlation dimension, and other indexes with Taylor’s exponents. No strong correlations were found; however, there is some relationship in the same model, but with different parameter values, and we will discuss the meaning of those results at the end of this paper.

Keywords: chaos, density effect, population dynamics, Taylor’s law

Procedia PDF Downloads 174

Authors: Xiao-Li Liu, Ling-Yun Zhao, Xing-Jie Liang, Hai-Ming Fan

Abstract:

Owing to their unique properties, magnetic nanoparticles have been used as diagnostic and therapeutic agents for biomedical applications. Highly monodispersed magnetic nanoparticles with controlled particle size and surface coating have been successfully synthesized as a model system to investigate the effect of surface coating on the T2 relaxivity and specific absorption rate (SAR) under an alternating magnetic field, respectively. Amongst, by using mPEG-g-PEI to solubilize oleic-acid capped 6 nm magnetic nanoparticles, the T2 relaxivity could be significantly increased by up to 4-fold as compared to PEG coated nanoparticles. Moreover, it largely enhances the cell uptake with a T2 relaxivity of 92.6 mM-1s-1 for in vitro cell MRI. As for hyperthermia agent, SAR value increase with the decreased thickness of PEG surface coating. By elaborate optimization of surface coating and particle size, a significant increase of SAR (up to 74%) could be achieved with a minimal variation on the saturation magnetization (<5%). The 19 nm magnetic nanoparticles with 2000 Da PEG exhibited the highest SAR of 930 W•g-1 among the samples, which can be maintained in various simulated physiological conditions. This systematic work provides a general strategy for the optimization of surface coating of magnetic core for high performance MRI contrast agent and hyperthermia agent.

Keywords: magnetic nanoparticles, magnetic hyperthermia, magnetic resonance imaging, surface modification

Procedia PDF Downloads 510

Authors: T. Y. Liu, C. H. Lin, Y. M. Ferng

Abstract:

Wind energy is one of the clean renewable energy. However, the low frequency (20-200HZ) noise generated from the wind turbine blades, which bothers the residents, becomes the major problem to be developed. It is useful for predicting the aerodynamic noise by flow field and pressure distribution analysis on the wind turbine blades. Therefore, the main objective of this study is to use different turbulence models to analyse the flow field and pressure distributions of the wing blades. Three-dimensional Computation Fluid Dynamics (CFD) simulation of the flow field was used to calculate the flow phenomena for the National Renewable Energy Laboratory (NREL) Phase VI horizontal axis wind turbine rotor. Two different flow cases with different wind speeds were investigated: 7m/s with 72rpm and 15m/s with 72rpm. Four kinds of RANS-based turbulence models, Standard k-ε, Realizable k-ε, SST k-ω, and v2f, were used to predict and analyse the results in the present work. The results show that the predictions on pressure distributions with SST k-ω and v2f turbulence models have good agreements with experimental data.

Keywords: horizontal axis wind turbine, turbulence model, noise, fluid dynamics

Procedia PDF Downloads 265