Search results for: artificial boundary condition
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6750

Search results for: artificial boundary condition

6450 Transient Free Laminar Convection in the Vicinity of a Thermal Conductive Vertical Plate

Authors: Anna Bykalyuk, Frédéric Kuznik, Kévyn Johannes

Abstract:

In this paper, the influence of a vertical plate’s thermal capacity is numerically investigated in order to evaluate the evolution of the thermal boundary layer structure, as well as the convective heat transfer coefficient and the velocity and temperature profiles. Whereas the heat flux of the heated vertical plate is evaluated under time depending boundary conditions. The main important feature of this problem is the unsteadiness of the physical phenomena. A 2D CFD model is developed with the Ansys Fluent 14.0 environment and is validated using unsteady data obtained for plasterboard studied under a dynamic temperature evolution. All the phenomena produced in the vicinity of the thermal conductive vertical plate (plasterboard) are analyzed and discussed. This work is the first stage of a holistic research on transient free convection that aims, in the future, to study the natural convection in the vicinity of a vertical plate containing Phase Change Materials (PCM).

Keywords: CFD modeling, natural convection, thermal conductive plate, time-depending boundary conditions

Procedia PDF Downloads 257
6449 Alexa (Machine Learning) in Artificial Intelligence

Authors: Loulwah Bokhari, Jori Nazer, Hala Sultan

Abstract:

Nowadays, artificial intelligence (AI) is used as a foundation for many activities in modern computing applications at home, in vehicles, and in businesses. Many modern machines are built to carry out a specific activity or purpose. This is where the Amazon Alexa application comes in, as it is used as a virtual assistant. The purpose of this paper is to explore the use of Amazon Alexa among people and how it has improved and made simple daily tasks easier for many people. We gave our participants several questions regarding Amazon Alexa and if they had recently used or heard of it, as well as the different tasks it provides and whether it successfully satisfied their needs. Overall, we found that participants who have recently used Alexa have found it to be helpful in their daily tasks.

Keywords: artificial intelligence, Echo system, machine learning, feature for feature match

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6448 Wind Turbine Wake Prediction and Validation under a Stably-Stratified Atmospheric Boundary Layer

Authors: Yilei Song, Linlin Tian, Ning Zhao

Abstract:

Turbulence energetics and structures in the wake of large-scale wind turbines under the stably-stratified atmospheric boundary layer (SABL) can be complicated due to the presence of low-level jets (LLJs), a region of higher wind speeds than the geostrophic wind speed. With a modified one-k-equation, eddy viscosity model specified for atmospheric flows as the sub-grid scale (SGS) model, a realistic atmospheric state of the stable ABL is well reproduced by large-eddy simulation (LES) techniques. Corresponding to the precursor stably stratification, the detailed wake properties of a standard 5-MW wind turbine represented as an actuator line model are provided. An engineering model is proposed for wake prediction based on the simulation statistics and gets validated. Results confirm that the proposed wake model can provide good predictions for wind turbines under the SABL.

Keywords: large-eddy simulation, stably-stratified atmospheric boundary layer, wake model, wind turbine wake

Procedia PDF Downloads 152
6447 Phytopathology Prediction in Dry Soil Using Artificial Neural Networks Modeling

Authors: F. Allag, S. Bouharati, M. Belmahdi, R. Zegadi

Abstract:

The rapid expansion of deserts in recent decades as a result of human actions combined with climatic changes has highlighted the necessity to understand biological processes in arid environments. Whereas physical processes and the biology of flora and fauna have been relatively well studied in marginally used arid areas, knowledge of desert soil micro-organisms remains fragmentary. The objective of this study is to conduct a diversity analysis of bacterial communities in unvegetated arid soils. Several biological phenomena in hot deserts related to microbial populations and the potential use of micro-organisms for restoring hot desert environments. Dry land ecosystems have a highly heterogeneous distribution of resources, with greater nutrient concentrations and microbial densities occurring in vegetated than in bare soils. In this work, we found it useful to use techniques of artificial intelligence in their treatment especially artificial neural networks (ANN). The use of the ANN model, demonstrate his capability for addressing the complex problems of uncertainty data.

Keywords: desert soil, climatic changes, bacteria, vegetation, artificial neural networks

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6446 Numerical Solutions of Boundary Layer Flow over an Exponentially Stretching/Shrinking Sheet with Generalized Slip Velocity

Authors: Roslinda Nazar, Ezad Hafidz Hafidzuddin, Norihan M. Arifin, Ioan Pop

Abstract:

In this paper, the problem of steady laminar boundary layer flow and heat transfer over a permeable exponentially stretching/shrinking sheet with generalized slip velocity is considered. The similarity transformations are used to transform the governing nonlinear partial differential equations to a system of nonlinear ordinary differential equations. The transformed equations are then solved numerically using the bvp4c function in MATLAB. Dual solutions are found for a certain range of the suction and stretching/shrinking parameters. The effects of the suction parameter, stretching/shrinking parameter, velocity slip parameter, critical shear rate, and Prandtl number on the skin friction and heat transfer coefficients as well as the velocity and temperature profiles are presented and discussed.

Keywords: boundary layer, exponentially stretching/shrinking sheet, generalized slip, heat transfer, numerical solutions

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6445 Studying Relationship between Local Geometry of Decision Boundary with Network Complexity for Robustness Analysis with Adversarial Perturbations

Authors: Tushar K. Routh

Abstract:

If inputs are engineered in certain manners, they can influence deep neural networks’ (DNN) performances by facilitating misclassifications, a phenomenon well-known as adversarial attacks that question networks’ vulnerability. Recent studies have unfolded the relationship between vulnerability of such networks with their complexity. In this paper, the distinctive influence of additional convolutional layers at the decision boundaries of several DNN architectures was investigated. Here, to engineer inputs from widely known image datasets like MNIST, Fashion MNIST, and Cifar 10, we have exercised One Step Spectral Attack (OSSA) and Fast Gradient Method (FGM) techniques. The aftermaths of adding layers to the robustness of the architectures have been analyzed. For reasoning, separation width from linear class partitions and local geometry (curvature) near the decision boundary have been examined. The result reveals that model complexity has significant roles in adjusting relative distances from margins, as well as the local features of decision boundaries, which impact robustness.

Keywords: DNN robustness, decision boundary, local curvature, network complexity

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6444 Exploring Acceptance of Artificial Intelligence Software Solution Amongst Healthcare Personnel: A Case in a Private Medical Centre

Authors: Sandra So, Mohd Roslan Ismail, Safurah Jaafar

Abstract:

With the rapid proliferation of data in healthcare has provided an opportune platform creation of Artificial Intelligence (AI). AI has brought a paradigm shift for healthcare professionals, promising improvement in delivery and quality. This study aims to determine the perception of healthcare personnel on perceived ease of use, perceived usefulness, and subjective norm toward attitude for artificial intelligence acceptance. A cross-sectional single institutional study of employees’ perception of adopting AI in the hospital was conducted. The survey was conducted using a questionnaire adapted from Technology Acceptance Model and a four-point Likert scale was used. There were 96 or 75.5% of the total population responded. This study has shown the significant relationship and the importance of ease of use, perceived usefulness, and subjective norm to the acceptance of AI. In the study results, it concluded that the determining factor to the strong acceptance of AI in their practices is mostly those respondents with the most interaction with the patients and clinical management.

Keywords: artificial intelligence, machine learning, perceived ease of use, perceived usefulness, subjective norm

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6443 MHD Chemically Reacting Viscous Fluid Flow towards a Vertical Surface with Slip and Convective Boundary Conditions

Authors: Ibrahim Yakubu Seini, Oluwole Daniel Makinde

Abstract:

MHD chemically reacting viscous fluid flow towards a vertical surface with slip and convective boundary conditions has been conducted. The temperature and the chemical species concentration of the surface and the velocity of the external flow are assumed to vary linearly with the distance from the vertical surface. The governing differential equations are modeled and transformed into systems of ordinary differential equations, which are then solved numerically by a shooting method. The effects of various parameters on the heat and mass transfer characteristics are discussed. Graphical results are presented for the velocity, temperature, and concentration profiles whilst the skin-friction coefficient and the rate of heat and mass transfers near the surface are presented in tables and discussed. The results revealed that increasing the strength of the magnetic field increases the skin-friction coefficient and the rate of heat and mass transfers toward the surface. The velocity profiles are increased towards the surface due to the presence of the Lorenz force, which attracts the fluid particles near the surface. The rate of chemical reaction is seen to decrease the concentration boundary layer near the surface due to the destructive chemical reaction occurring near the surface.

Keywords: boundary layer, surface slip, MHD flow, chemical reaction, heat transfer, mass transfer

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6442 Coexistence of Two Different Types of Intermittency near the Boundary of Phase Synchronization in the Presence of Noise

Authors: Olga I. Moskalenko, Maksim O. Zhuravlev, Alexey A. Koronovskii, Alexander E. Hramov

Abstract:

Intermittent behavior near the boundary of phase synchronization in the presence of noise is studied. In certain range of the coupling parameter and noise intensity the intermittency of eyelet and ring intermittencies is shown to take place. Main results are illustrated using the example of two unidirectionally coupled Rössler systems. Similar behavior is shown to take place in two hydrodynamical models of Pierce diode coupled unidirectionally.

Keywords: chaotic oscillators, phase synchronization, noise, intermittency of intermittencies

Procedia PDF Downloads 617
6441 Artificial Intelligence in Enterprise Information Systems: A Review

Authors: Danah S. Alabdulmohsin

Abstract:

Due to the fast growth of organizational data as well as the emergence of new technologies such as artificial intelligence (AI), organizations tend to utilize these new technologies in their enterprise information systems (EIS) either to overcome the issues they struggle with or to enhance their functions. The aim of this paper is to review the potential role of AI technologies in EIS, namely: enterprise resource planning systems (ERP), customer relation management systems (CRM), supply chain management systems (SCM), knowledge systems (KM), and human resources management systems (HRM). The paper provided the definitions of these systems as well as the definitions of AI technologies that have been used in EIS. In addition, the paper discussed the challenges that organizations might face while integrating AI with their information systems and explained why some organizations fail in achieving successful implementations of the integration.

Keywords: artificial intelligence, AI, enterprise information system, EIS, integration

Procedia PDF Downloads 70
6440 Comparative Study of Bending Angle in Laser Forming Process Using Artificial Neural Network and Fuzzy Logic System

Authors: M. Hassani, Y. Hassani, N. Ajudanioskooei, N. N. Benvid

Abstract:

Laser Forming process as a non-contact thermal forming process is widely used to forming and bending of metallic and non-metallic sheets. In this process, according to laser irradiation along a specific path, sheet is bent. One of the most important output parameters in laser forming is bending angle that depends on process parameters such as physical and mechanical properties of materials, laser power, laser travel speed and the number of scan passes. In this paper, Artificial Neural Network and Fuzzy Logic System were used to predict of bending angle in laser forming process. Inputs to these models were laser travel speed and laser power. The comparison between artificial neural network and fuzzy logic models with experimental results has been shown both of these models have high ability to prediction of bending angles with minimum errors.

Keywords: artificial neural network, bending angle, fuzzy logic, laser forming

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6439 Type A Quadricuspid Aortic Valve; Rarer than a Four-Leaf Clover, an Example of Availability Heuristic

Authors: Frazer Kirk, Rohen Skiba, Pankaj Saxena

Abstract:

The natural history of the QAV is poorly understood due to the exceeding rarity of the condition. Incidence rates vary between 0.00028-1%. Classically patients present with Aortic Regurgitation (AR) between 40-60 years of age experiencing palpitations, chest pain, or heart failure. (1, 2) Echocardiography is the mainstay of diagnosis for this condition; however, given the rarity of this condition, it can easily be overlooked, as demonstrated here. The case report that follows serves as a reminder of the condition to reduce the innate cognitive bias to overlook the diagnosis due to the availability heuristic. Intraoperative photography, echocardiographic and magnetic resonance imaging from this case for reference to demonstrate that while the diagnosis of Aortic regurgitation was recognized early, the valve morphology was underappreciated.

Keywords: quadricuspid aortic valve, cardiac surgery, echocardiography, congenital

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6438 Cell Biomass and Lipid Productivities of Meyerella planktonica under Autotrophic and Heterotrophic Growth Conditions

Authors: Rory Anthony Hutagalung, Leonardus Widjaja

Abstract:

Microalgae Meyerella planktonica is a potential biofuel source because it can grow in bulk in either autotrophic or heterotrophic condition. However, the quantitative growth of this algal type is still low as it tends to precipitates on the bottom. Beside, the lipid concentration is still low when grown in autotrophic condition. In contrast, heterotrophic condition can enhance the lipid concentration. The combination of autotrophic condition and agitation treatment was conducted to increase the density of the culture. On the other hand, a heterotrophic condition was set up to raise the lipid production. A two-stage experiment was applied to increase the density at the first step and to increase the lipid concentration in the next step. The autotrophic condition resulted higher density but lower lipid concentration compared to heterotrophic one. The agitation treatment produced higher density in both autotrophic and heterotrophic conditions. The two-stage experiment managed to enhance the density during the autotrophic stage and the lipid concentration during the heterotrophic stage. The highest yield was performed by using 0.4% v/v glycerol as a carbon source (2.9±0.016 x 106 cells w/w) attained 7 days after the heterotrophic stage began. The lipid concentration was stable starting from day 7.

Keywords: agitation, glycerol, heterotrophic, lipid productivity, Meyerella planktonica

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6437 Condition Assessment of State-Owned Immovable Assets in South Africa

Authors: Collen Maseloane, Chris Cloete

Abstract:

The study investigated the status of building condition assessments of state-owned immovable assets in South Africa. A stratified random sample of 200 (out of 372) personnel was drawn from the eight rele-vant business units of the Department of Public Works (DPW). A questionnaire comprising open-ended questions was distributed to the sampled participants and a total of 139 completed questionnaires were received. A significant number of state asset properties were found to be in poor condition owing to the asset managers’ inability to access automated information on the conditions of assets. It is recommended that the immovable asset register of the Department requires constant enhancement to update information on the condition of each state-owned immovable asset under its custodianship. Implementation of the proposals should contribute to the maintenance of the value of state assets in South Africa.

Keywords: building condition assessment, immovable asset register, life cycle asset management, public works, South Africa

Procedia PDF Downloads 103
6436 Modelling Vehicle Fuel Consumption Utilising Artificial Neural Networks

Authors: Aydin Azizi, Aburrahman Tanira

Abstract:

The main source of energy used in this modern age is fossil fuels. There is a myriad of problems that come with the use of fossil fuels, out of which the issues with the greatest impact are its scarcity and the cost it imposes on the planet. Fossil fuels are the only plausible option for many vital functions and processes; the most important of these is transportation. Thus, using this source of energy wisely and as efficiently as possible is a must. The aim of this work was to explore utilising mathematical modelling and artificial intelligence techniques to enhance fuel consumption in passenger cars by focusing on the speed at which cars are driven. An artificial neural network with an error less than 0.05 was developed to be applied practically as to predict the rate of fuel consumption in vehicles.

Keywords: mathematical modeling, neural networks, fuel consumption, fossil fuel

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6435 Boundary Layer Flow of a Casson Nanofluid Past a Vertical Exponentially Stretching Cylinder in the Presence of a Transverse Magnetic Field with Internal Heat Generation/Absorption

Authors: G. Sarojamma, K. Vendabai

Abstract:

An analysis is carried out to investigate the effect of magnetic field and heat source on the steady boundary layer flow and heat transfer of a Casson nanofluid over a vertical cylinder stretching exponentially along its radial direction. Using a similarity transformation, the governing mathematical equations, with the boundary conditions are reduced to a system of coupled, non –linear ordinary differential equations. The resulting system is solved numerically by the fourth order Runge – Kutta scheme with shooting technique. The influence of various physical parameters such as Reynolds number, Prandtl number, magnetic field, Brownian motion parameter, thermophoresis parameter, Lewis number and the natural convection parameter are presented graphically and discussed for non – dimensional velocity, temperature and nanoparticle volume fraction. Numerical data for the skin – friction coefficient, local Nusselt number and the local Sherwood number have been tabulated for various parametric conditions. It is found that the local Nusselt number is a decreasing function of Brownian motion parameter Nb and the thermophoresis parameter Nt.

Keywords: casson nanofluid, boundary layer flow, internal heat generation/absorption, exponentially stretching cylinder, heat transfer, brownian motion, thermophoresis

Procedia PDF Downloads 365
6434 Smart Water Main Inspection and Condition Assessment Using a Systematic Approach for Pipes Selection

Authors: Reza Moslemi, Sebastien Perrier

Abstract:

Water infrastructure deterioration can result in increased operational costs owing to increased repair needs and non-revenue water and consequently cause a reduced level of service and customer service satisfaction. Various water main condition assessment technologies have been introduced to the market in order to evaluate the level of pipe deterioration and to develop appropriate asset management and pipe renewal plans. One of the challenges for any condition assessment and inspection program is to determine the percentage of the water network and the combination of pipe segments to be inspected in order to obtain a meaningful representation of the status of the entire water network with a desirable level of accuracy. Traditionally, condition assessment has been conducted by selecting pipes based on age or location. However, this may not necessarily offer the best approach, and it is believed that by using a smart sampling methodology, a better and more reliable estimate of the condition of a water network can be achieved. This research investigates three different sampling methodologies, including random, stratified, and systematic. It is demonstrated that selecting pipes based on the proposed clustering and sampling scheme can considerably improve the ability of the inspected subset to represent the condition of a wider network. With a smart sampling methodology, a smaller data sample can provide the same insight as a larger sample. This methodology offers increased efficiency and cost savings for condition assessment processes and projects.

Keywords: condition assessment, pipe degradation, sampling, water main

Procedia PDF Downloads 133
6433 Indirect Intergranular Slip Transfer Modeling Through Continuum Dislocation Dynamics

Authors: A. Kalaei, A. H. W. Ngan

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In this study, a mesoscopic continuum dislocation dynamics (CDD) approach is applied to simulate the intergranular slip transfer. The CDD scheme applies an efficient kinematics equation to model the evolution of the “all-dislocation density,” which is the line-length of dislocations of each character per unit volume. As the consideration of every dislocation line can be a limiter for the simulation of slip transfer in large scales with a large quantity of participating dislocations, a coarse-grained, extensive description of dislocations in terms of their density is utilized to resolve the effect of collective motion of dislocation lines. For dynamics closure, namely, to obtain the dislocation velocity from a velocity law involving the effective glide stress, mutual elastic interaction of dislocations is calculated using Mura’s equation after singularity removal at the core of dislocation lines. The developed scheme for slip transfer can therefore resolve the effects of the elastic interaction and pile-up of dislocations, which are important physics omitted in coarser models like crystal plasticity finite element methods (CPFEMs). Also, the length and timescales of the simulationareconsiderably larger than those in molecular dynamics (MD) and discrete dislocation dynamics (DDD) models. The present work successfully simulates that, as dislocation density piles up in front of a grain boundary, the elastic stress on the other side increases, leading to dislocation nucleation and stress relaxation when the local glide stress exceeds the operation stress of dislocation sources seeded on the other side of the grain boundary. More importantly, the simulation verifiesa phenomenological misorientation factor often used by experimentalists, namely, the ease of slip transfer increases with the product of the cosines of misorientation angles of slip-plane normals and slip directions on either side of the grain boundary. Furthermore, to investigate the effects of the critical stress-intensity factor of the grain boundary, dislocation density sources are seeded at different distances from the grain boundary, and the critical applied stress to make slip transfer happen is studied.

Keywords: grain boundary, dislocation dynamics, slip transfer, elastic stress

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6432 Length Weight Relationship and Relative Condition Factor of Atropus atropos (Bloch and Schneider, 1801) from Mangalore Coast, India

Authors: D. P. Rajesh, H. N. Anjanayappa, P. Nayana, S. Benakappa

Abstract:

The present study deals with length-weight relationship of Atropus atropos for which no information is available on this aspect from Mangalore coast. Therefore the present investigation was undertaken. Fish samples were collected from fish landing center (Mangalore) and fish market. The regression co-efficient of male was found to be lower than female. From this observation it may be opined that female gained more weight with increase in length compared to male. Data on seasonal variation in condition factor (Kn) showed that Kn values were more or less similar in both the sexes, indicating almost identical metabolic activity. Gonadal development and high feeding intensity are the factors which influenced the condition factor. The seasonal fluctuations in the relative condition factor of both the sexes could be attributed to the sexual cycle, food intake and environmental factors. From the present study, it can be inferred that the variation in the condition of Atropus atropos was due to feeding activity and gonadal maturity.

Keywords: Atropus atropos, length-weight relationship, Mangalore coast, relative condition factor, Kn

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6431 Series Solutions to Boundary Value Differential Equations

Authors: Armin Ardekani, Mohammad Akbari

Abstract:

We present a method of generating series solutions to large classes of nonlinear differential equations. The method is well suited to be adapted in mathematical software and unlike the available commercial solvers, we are capable of generating solutions to boundary value ODEs and PDEs. Many of the generated solutions converge to closed form solutions. Our method can also be applied to systems of ODEs or PDEs, providing all the solutions efficiently. As examples, we present results to many difficult differential equations in engineering fields.

Keywords: computational mathematics, differential equations, engineering, series

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6430 Artificial Neural Networks Face to Sudden Load Change for Shunt Active Power Filter

Authors: Dehini Rachid, Ferdi Brahim

Abstract:

The shunt active power filter (SAPF) is not destined only to improve the power factor, but also to compensate the unwanted harmonic currents produced by nonlinear loads. This paper presents a SAPF with identification and control method based on artificial neural network (ANN). To identify harmonics, many techniques are used, among them the conventional p-q theory and the relatively recent one the artificial neural network method. It is difficult to get satisfied identification and control characteristics by using a normal (ANN) due to the nonlinearity of the system (SAPF + fast nonlinear load variations). This work is an attempt to undertake a systematic study of the problem to equip the (SAPF) with the harmonics identification and DC link voltage control method based on (ANN). The latter has been applied to the (SAPF) with fast nonlinear load variations. The results of computer simulations and experiments are given, which can confirm the feasibility of the proposed active power filter.

Keywords: artificial neural networks (ANN), p-q theory, harmonics, total harmonic distortion

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6429 Study on Impact of Existence of an Open Boundary Foreign Enclave and a 24-Hours Open Corridor for Foreigners inside Indian Territory

Authors: Debarshi Bhattacharya

Abstract:

In 2015, historic Land Boundary Agreement (LBA) executed between India and Bangladesh finally settled almost seven decades long overdue critical enclave problems of the two neighbouring countries. Enclaves within India and Bangladesh were the awful outcome of the partition of India in 1947. As a dire consequence, the populace within these enclaves enormously suffered from getting basic rights and opportunities and governmental support services till long 67 years after India’s independence and partition. As per LBA, 2015, 51 Bangladeshi (BD) enclaves inside Indian territory and 111 Indian enclaves inside Bangladesh territory were actually transferred to each other. But, by virtue of LBA, 1974 executed earlier between the two countries, one BD enclave situated inside India, namely Dohogram-Angarpota (D-A) twin enclave, had not yet been exchanged by means of LBA, 2015 and it still remains as an integral part, may not be contiguous, of Bangladesh completely surrounded by Indian territory. A study was undertaken through an extensive field survey to assess the impact of the existence of D-A BD enclave inside Indian territory from India’s perspective. Field survey was conducted for the purpose in the form of an interview, group discussion, questionnaire survey, personal interaction etc. to gather information from the Indian people residing adjacent to D-A enclave and Tin Bigha Corridor (TBC), people of D-A enclave, officials of Border Security Forces of India and Bangladesh, public representatives, representatives of political organizations etc. The issue of the existence of D-A BD enclave inside Indian territory seriously brought apprehension of future problems to the people of Kuchlibari Region of Mekhligunj Block, India, on its contiguity with Indian mainland due to 24-hour open access for the BD people through TBC. The anxiety of the local Indian people regarding threats to the national security of India as well as to the law and order issues of the locality due to the open border of D-A BD enclave in the region. On the other hand, it was observed that 24 hours opening of TBC brought significant positive changes to the people of D-A BD enclave in terms of their socio-economic condition and security status.

Keywords: enclave, exchange of enclaves, land boundary agreement, Dohogram-Angarpota (D-A) Bangladeshi (BD) enclave, Tin Bigha Corridor

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6428 The Phonology and Phonetics of Second Language Intonation in Case of “Downstep”

Authors: Tayebeh Norouzi

Abstract:

This study aims to investigate the acquisition process of intonation. It examines the intonation structure of Tokyo Japanese and its realization by Iranian learners of Japanese. Seven Iranian learners of Japanese, differing in fluency, and two Japanese speakers participated in the experiment. Two sentences were used to test the phonological and phonetic characteristics of lexical pitch-accent as well as the intonation patterns produced by the speakers. Both sentences consisted of similar words with the same number of syllables and lexical pitch-accents but different syntactic structure. Speakers were asked to read each sentence three times at normal speed, and the data were analyzed by Praat. The results show that lexical pitch-accent, Accentual Phrase (AP) and AP boundary tone realization vary depending on sentence type. For sentences of type XdeYwo, the lexical pitch-accent is realized properly. However, there is a rise in AP boundary tone regardless of speakers’ level of fluency. In contrast, in sentences of type XnoYwo, the lexical pitch-accent and AP boundary tone vary depending on the speakers’ fluency level. Advanced speakers are better at grouping words into phrases and produce more native-like intonation patterns, though they are not able to realize downstep properly. The non-native speakers tried to realize proper intonation patterns by making changes in lexical accent and boundary tone.

Keywords: intonation, Iranian learners, Japanese prosody, lexical accent, second language acquisition.

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6427 Artificial Neural Network Approach for Vessel Detection Using Visible Infrared Imaging Radiometer Suite Day/Night Band

Authors: Takashi Yamaguchi, Ichio Asanuma, Jong G. Park, Kenneth J. Mackin, John Mittleman

Abstract:

In this paper, vessel detection using the artificial neural network is proposed in order to automatically construct the vessel detection model from the satellite imagery of day/night band (DNB) in visible infrared in the products of Imaging Radiometer Suite (VIIRS) on Suomi National Polar-orbiting Partnership (Suomi-NPP).The goal of our research is the establishment of vessel detection method using the satellite imagery of DNB in order to monitor the change of vessel activity over the wide region. The temporal vessel monitoring is very important to detect the events and understand the circumstances within the maritime environment. For the vessel locating and detection techniques, Automatic Identification System (AIS) and remote sensing using Synthetic aperture radar (SAR) imagery have been researched. However, each data has some lack of information due to uncertain operation or limitation of continuous observation. Therefore, the fusion of effective data and methods is important to monitor the maritime environment for the future. DNB is one of the effective data to detect the small vessels such as fishery ships that is difficult to observe in AIS. DNB is the satellite sensor data of VIIRS on Suomi-NPP. In contrast to SAR images, DNB images are moderate resolution and gave influence to the cloud but can observe the same regions in each day. DNB sensor can observe the lights produced from various artifact such as vehicles and buildings in the night and can detect the small vessels from the fishing light on the open water. However, the modeling of vessel detection using DNB is very difficult since complex atmosphere and lunar condition should be considered due to the strong influence of lunar reflection from cloud on DNB. Therefore, artificial neural network was applied to learn the vessel detection model. For the feature of vessel detection, Brightness Temperature at the 3.7 μm (BT3.7) was additionally used because BT3.7 can be used for the parameter of atmospheric conditions.

Keywords: artificial neural network, day/night band, remote sensing, Suomi National Polar-orbiting Partnership, vessel detection, Visible Infrared Imaging Radiometer Suite

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6426 Integrated Gas Turbine Performance Diagnostics and Condition Monitoring Using Adaptive GPA

Authors: Yi-Guang Li, Suresh Sampath

Abstract:

Gas turbine performance degrades over time, and the degradation is greatly affected by environmental, ambient, and operating conditions. The engines may degrade slowly under favorable conditions and result in a waste of engine life if a scheduled maintenance scheme is followed. They may also degrade fast and fail before a scheduled overhaul if the conditions are unfavorable, resulting in serious secondary damage, loss of engine availability, and increased maintenance costs. To overcome these problems, gas turbine owners are gradually moving from scheduled maintenance to condition-based maintenance, where condition monitoring is one of the key supporting technologies. This paper presents an integrated adaptive GPA diagnostics and performance monitoring system developed at Cranfield University for gas turbine gas path condition monitoring. It has the capability to predict the performance degradation of major gas path components of gas turbine engines, such as compressors, combustors, and turbines, using gas path measurement data. It is also able to predict engine key performance parameters for condition monitoring, such as turbine entry temperature that cannot be directly measured. The developed technology has been implemented into digital twin computer Software, Pythia, to support the condition monitoring of gas turbine engines. The capabilities of the integrated GPA condition monitoring system are demonstrated in three test cases using a model gas turbine engine similar to the GE aero-derivative LM2500 engine widely used in power generation and marine propulsion. It shows that when the compressor of the model engine degrades, the Adaptive GPA is able to predict the degradation and the changing engine performance accurately using gas path measurements. Such a presented technology and software are generic, can be applied to different types of gas turbine engines, and provide crucial engine health and performance parameters to support condition monitoring and condition-based maintenance.

Keywords: gas turbine, adaptive GPA, performance, diagnostics, condition monitoring

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6425 The Diversity in the Concept of Existence from Kierkegaard to Sartre

Authors: Mohammad Motiee

Abstract:

From Kierkegaard to Sartre, the concept of 'being' was debated over various angles in the philosophy of being. Then, the futility, nothingness and absurdity of human condition in the world were all justified and led to a kind of solution by different approaches like Christianity, loss of faith, authentic existence and responsibility. In an extreme concern, the human condition in the world was pondered in different ways and the philosophy of thought tried to render an awareness of such condition for human beings. The present study aims at illustration of some approaches presented by prominent existentialists to justify the controversies in the concept of existence in human life.

Keywords: existence, existentialism, alienation, being

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6424 Capacity of Cold-Formed Steel Warping-Restrained Members Subjected to Combined Axial Compressive Load and Bending

Authors: Maryam Hasanali, Syed Mohammad Mojtabaei, Iman Hajirasouliha, G. Charles Clifton, James B. P. Lim

Abstract:

Cold-formed steel (CFS) elements are increasingly being used as main load-bearing components in the modern construction industry, including low- to mid-rise buildings. In typical multi-storey buildings, CFS structural members act as beam-column elements since they are exposed to combined axial compression and bending actions, both in moment-resisting frames and stud wall systems. Current design specifications, including the American Iron and Steel Institute (AISI S100) and the Australian/New Zealand Standard (AS/NZS 4600), neglect the beneficial effects of warping-restrained boundary conditions in the design of beam-column elements. Furthermore, while a non-linear relationship governs the interaction of axial compression and bending, the combined effect of these actions is taken into account through a simplified linear expression combining pure axial and flexural strengths. This paper aims to evaluate the reliability of the well-known Direct Strength Method (DSM) as well as design proposals found in the literature to provide a better understanding of the efficiency of the code-prescribed linear interaction equation in the strength predictions of CFS beam columns and the effects of warping-restrained boundary conditions on their behavior. To this end, the experimentally validated finite element (FE) models of CFS elements under compression and bending were developed in ABAQUS software, which accounts for both non-linear material properties and geometric imperfections. The validated models were then used for a comprehensive parametric study containing 270 FE models, covering a wide range of key design parameters, such as length (i.e., 0.5, 1.5, and 3 m), thickness (i.e., 1, 2, and 4 mm) and cross-sectional dimensions under ten different load eccentricity levels. The results of this parametric study demonstrated that using the DSM led to the most conservative strength predictions for beam-column members by up to 55%, depending on the element’s length and thickness. This can be sourced by the errors associated with (i) the absence of warping-restrained boundary condition effects, (ii) equations for the calculations of buckling loads, and (iii) the linear interaction equation. While the influence of warping restraint is generally less than 6%, the code suggested interaction equation led to an average error of 4% to 22%, based on the element lengths. This paper highlights the need to provide more reliable design solutions for CFS beam-column elements for practical design purposes.

Keywords: beam-columns, cold-formed steel, finite element model, interaction equation, warping-restrained boundary conditions

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6423 Three Issues for Integrating Artificial Intelligence into Legal Reasoning

Authors: Fausto Morais

Abstract:

Artificial intelligence has been widely used in law. Programs are able to classify suits, to identify decision-making patterns, to predict outcomes, and to formalize legal arguments as well. In Brazil, the artificial intelligence victor has been classifying cases to supreme court’s standards. When those programs act doing those tasks, they simulate some kind of legal decision and legal arguments, raising doubts about how artificial intelligence can be integrated into legal reasoning. Taking this into account, the following three issues are identified; the problem of hypernormatization, the argument of legal anthropocentrism, and the artificial legal principles. Hypernormatization can be seen in the Brazilian legal context in the Supreme Court’s usage of the Victor program. This program generated efficiency and consistency. On the other hand, there is a feasible risk of over standardizing factual and normative legal features. Then legal clerks and programmers should work together to develop an adequate way to model legal language into computational code. If this is possible, intelligent programs may enact legal decisions in easy cases automatically cases, and, in this picture, the legal anthropocentrism argument takes place. Such an argument argues that just humans beings should enact legal decisions. This is so because human beings have a conscience, free will, and self unity. In spite of that, it is possible to argue against the anthropocentrism argument and to show how intelligent programs may work overcoming human beings' problems like misleading cognition, emotions, and lack of memory. In this way, intelligent machines could be able to pass legal decisions automatically by classification, as Victor in Brazil does, because they are binding by legal patterns and should not deviate from them. Notwithstanding, artificial intelligent programs can be helpful beyond easy cases. In hard cases, they are able to identify legal standards and legal arguments by using machine learning. For that, a dataset of legal decisions regarding a particular matter must be available, which is a reality in Brazilian Judiciary. Doing such procedure, artificial intelligent programs can support a human decision in hard cases, providing legal standards and arguments based on empirical evidence. Those legal features claim an argumentative weight in legal reasoning and should serve as references for judges when they must decide to maintain or overcome a legal standard.

Keywords: artificial intelligence, artificial legal principles, hypernormatization, legal anthropocentrism argument, legal reasoning

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6422 Recent Developments in Artificial Intelligence and Information Communications Technology

Authors: Dolapo Adeyemo

Abstract:

Technology can be designed specifically for geriatrics and persons with disabilities or ICT accessibility solutions. Both solutions stand to benefit from advances in Artificial intelligence, which are computer systems that perform tasks that require human intelligence. Tasks such as decision making, visual perception, speech recognition, and even language translation are useful in both situation and will provide significant benefits to people with temporarily or permanent disabilities. This research’s goal is to review innovations focused on the use of artificial intelligence that bridges the accessibility gap in technology from a user-centered perspective. A mixed method approach that utilized a comprehensive review of academic literature on the subject combined with semi structure interviews of users, developers, and technology product owners. The internet of things and artificial intelligence technology is creating new opportunities in the assistive technology space and proving accessibility to existing technology. Device now more adaptable to the needs of the user by learning the behavior of users as they interact with the internet. Accessibility to devices have witnessed significant enhancements that continue to benefit people with disabilities. Examples of other advances identified are prosthetic limbs like robotic arms supported by artificial intelligence, route planning software for the visually impaired, and decision support tools for people with disabilities and even clinicians that provide care.

Keywords: ICT, IOT, accessibility solutions, universal design

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6421 Numerical Solution of Steady Magnetohydrodynamic Boundary Layer Flow Due to Gyrotactic Microorganism for Williamson Nanofluid over Stretched Surface in the Presence of Exponential Internal Heat Generation

Authors: M. A. Talha, M. Osman Gani, M. Ferdows

Abstract:

This paper focuses on the study of two dimensional magnetohydrodynamic (MHD) steady incompressible viscous Williamson nanofluid with exponential internal heat generation containing gyrotactic microorganism over a stretching sheet. The governing equations and auxiliary conditions are reduced to a set of non-linear coupled differential equations with the appropriate boundary conditions using similarity transformation. The transformed equations are solved numerically through spectral relaxation method. The influences of various parameters such as Williamson parameter γ, power constant λ, Prandtl number Pr, magnetic field parameter M, Peclet number Pe, Lewis number Le, Bioconvection Lewis number Lb, Brownian motion parameter Nb, thermophoresis parameter Nt, and bioconvection constant σ are studied to obtain the momentum, heat, mass and microorganism distributions. Moment, heat, mass and gyrotactic microorganism profiles are explored through graphs and tables. We computed the heat transfer rate, mass flux rate and the density number of the motile microorganism near the surface. Our numerical results are in better agreement in comparison with existing calculations. The Residual error of our obtained solutions is determined in order to see the convergence rate against iteration. Faster convergence is achieved when internal heat generation is absent. The effect of magnetic parameter M decreases the momentum boundary layer thickness but increases the thermal boundary layer thickness. It is apparent that bioconvection Lewis number and bioconvection parameter has a pronounced effect on microorganism boundary. Increasing brownian motion parameter and Lewis number decreases the thermal boundary layer. Furthermore, magnetic field parameter and thermophoresis parameter has an induced effect on concentration profiles.

Keywords: convection flow, similarity, numerical analysis, spectral method, Williamson nanofluid, internal heat generation

Procedia PDF Downloads 157