Search results for: electrolyte-supported model

Authors: Pinzhe Zhao

Abstract:

This study focuses on predicting university students' cheating tendencies using psychological traits and machine learning techniques. Academic dishonesty is a significant issue that compromises the integrity and fairness of educational institutions. While much research has been dedicated to detecting cheating behaviors after they have occurred, there is limited work on predicting such tendencies before they manifest. The aim of this research is to develop a model that can identify students who are at higher risk of engaging in academic misconduct, allowing for earlier interventions to prevent such behavior. Psychological factors are known to influence students' likelihood of cheating. Research shows that traits such as test anxiety, moral reasoning, self-efficacy, and achievement motivation are strongly linked to academic dishonesty. High levels of anxiety may lead students to cheat as a way to cope with pressure. Those with lower self-efficacy are less confident in their academic abilities, which can push them toward dishonest behaviors to secure better outcomes. Students with weaker moral judgment may also justify cheating more easily, believing it to be less wrong under certain conditions. Achievement motivation also plays a role, as students driven primarily by external rewards, such as grades, are more likely to cheat compared to those motivated by intrinsic learning goals. In this study, data on students’ psychological traits is collected through validated assessments, including scales for anxiety, moral reasoning, self-efficacy, and motivation. Additional data on academic performance, attendance, and engagement in class are also gathered to create a more comprehensive profile. Using machine learning algorithms such as Random Forest, Support Vector Machines (SVM), and Long Short-Term Memory (LSTM) networks, the research builds models that can predict students’ cheating tendencies. These models are trained and evaluated using metrics like accuracy, precision, recall, and F1 scores to ensure they provide reliable predictions. The findings demonstrate that combining psychological traits with machine learning provides a powerful method for identifying students at risk of cheating. This approach allows for early detection and intervention, enabling educational institutions to take proactive steps in promoting academic integrity. The predictive model can be used to inform targeted interventions, such as counseling for students with high test anxiety or workshops aimed at strengthening moral reasoning. By addressing the underlying factors that contribute to cheating behavior, educational institutions can reduce the occurrence of academic dishonesty and foster a culture of integrity. In conclusion, this research contributes to the growing body of literature on predictive analytics in education. It offers a approach by integrating psychological assessments with machine learning to predict cheating tendencies. This method has the potential to significantly improve how academic institutions address academic dishonesty, shifting the focus from punishment after the fact to prevention before it occurs. By identifying high-risk students and providing them with the necessary support, educators can help maintain the fairness and integrity of the academic environment.

Keywords: academic dishonesty, cheating prediction, intervention strategies, machine learning, psychological traits, academic integrity

Procedia PDF Downloads 20

Authors: F. Chigondo, G. Chitabati

Abstract:

Hexavalent chromium is toxic and is widely used in many industries hence efficient and economical methods must be explored to remove the chromium(VI) from the environment. The removal of Cr (VI) from aqueous solutions onto polyaniline coated maize tassel was studied in batch mode at varying initial metal concentrations, adsorbent doses, pH and contact times. The residual Cr (VI) concentrations before and after adsorption were analyzed by Ultraviolet–visible spectroscopy. FTIR analysis of the polyaniline coated maize tassel showed the presence of C=C, C=N, C-H, C-N and N-H groups. Adsorption conditions were deduced to be pH of 2, adsorbent dosage 1g/L, Cr(VI) initial concentration of 40mg/L contact time of 150 minutes and agitation speed of 140rpm. Data obtained fitted best to the Langmuir isotherm (R2 = 0.972) compared to the Freundlich isotherm (R2 0.671. The maximum adsorption capacity was found to be 125mg/L. Correlation coefficients for pseudo first order and pseudo second order were 0.952 and 0.971 respectively. The adsorption process followed the pseudo-second order kinetic model. The studied polyaniline coated maize tassel can therefore be used as a promising adsorbent for the removal of Cr (VI) ion from aqueous solution.

Keywords: polyaniline-coated, maize tassels, adsorption, hexavalent chromium

Procedia PDF Downloads 203

Authors: Saeed Yazdani, Shahrbanoo Bagheri, Sepideh Nikravesh

Abstract:

Considering the importance and scarcity of water resources, the efficient management of water resources is of great importance. Adoption of modern irrigation technology is considered to be a key of increasing the efficiency of water used in agriculture. Policy makers have implemented several ways to induce the adoption of new irrigation technology. The empirical studies show that farmers are reluctant to utilize the use of new irrigation methods. This study aims to assess factors affecting on farmer’s decision on the application of water saving technologies with emphasize on crop price variation and water sources. A Logit model was employed to examine the impact of different variables on use of water saving technology. The required data gathered from a sample of 204 farmers in the year 2012. The results indicate that different variables such as crop price variability, water supply source, high-value crops, farm size, income, education, membership in cooperatives have a positive effect and variables such as age and number of plots have a negative impact on the probability of adopting modern water saving technologies.

Keywords: irrigation, water, water saving technology, scarcity

Procedia PDF Downloads 225

Authors: Essa Abrahim Abdulgader Saleem, Thien-My Dao

Abstract:

The main objective of this paper is to optimize series-parallel system reliability using Genetic Algorithm (GA) and statistical analysis; considering system reliability constraints which involve the redundant numbers of selected components, total cost, and total weight. To perform this work, firstly the mathematical model which maximizes system reliability subject to maximum system cost and maximum system weight constraints is presented; secondly, a statistical analysis is used to optimize GA parameters, and thirdly GA is used to optimize series-parallel systems reliability. The objective is to determine the strategy choosing the redundancy level for each subsystem to maximize the overall system reliability subject to total cost and total weight constraints. Finally, the series-parallel system case study reliability optimization results are showed, and comparisons with the other previous results are presented to demonstrate the performance of our GA.

Keywords: reliability, optimization, meta-heuristic, genetic algorithm, redundancy

Procedia PDF Downloads 337

Authors: Apidet Booranawong, Wiklom Teerapabkajorndet

Abstract:

An enhanced ad-hoc on-demand distance vector routing (E-AODV) protocol for control system applications in wireless sensor and actuator networks (WSANs) is proposed. Our routing algorithm is designed by considering both wireless network communication and the control system aspects. Control system error and network delay are the main selection criteria in our routing protocol. The control and communication performance is evaluated on multi-hop IEEE 802.15.4 networks for building-temperature control systems. The Gilbert-Elliott error model is employed to simulate packet loss in wireless networks. The simulation results demonstrate that the E-AODV routing approach can significantly improve the communication performance better than an original AODV routing under various packet loss rates. However, the control performance result by our approach is not much improved compared with the AODV routing solution.

Keywords: WSANs, building temperature control, AODV routing protocol, control system error, settling time, delay, delivery ratio

Procedia PDF Downloads 339

Authors: Ekin Ozer

Abstract:

Assessment of structural reliability is essential for efficient use of civil infrastructure which is subjected hazardous events. Dynamic analysis of finite element models is a commonly used tool to simulate structural behavior and estimate its performance accordingly. However, theoretical models purely based on preliminary assumptions and design drawings may deviate from the actual behavior of the structure. This study proposes up-to-date reliability estimation procedures which engages actual bridge vibration data modifying finite element models for finite element model updating and performing reliability estimation, accordingly. The proposed method utilizes vibration response measurements of bridge structures to identify modal parameters, then uses these parameters to calibrate finite element models which are originally based on design drawings. The proposed method does not only show that reliability estimation based on updated models differs from the original models, but also infer that non-updated models may overestimate the structural capacity.

Keywords: earthquake engineering, engineering vibrations, reliability estimation, structural health monitoring

Procedia PDF Downloads 223

Authors: Iqra Noor, Ihtzaz Qamar

Abstract:

Pitot-tube Jet pump, single-stage pump with low flow rate and high head, consists of a radial impeller that feeds water to rotating cavity. Water then enters stationary pitot-tube collector (diffuser), which discharges to the outside. By means of ANSYS Fluent 15.0, the internal flow characteristics for Pitot-tube Jet pump with standard pitot and curved pitot are studied. Under design condition, realizable k-e turbulence model and SIMPLEC algorithm are used to calculate 3D flow field inside both pumps. The simulation results reveal that energy is imparted to the flow by impeller and inside the rotor, forced vortex type flow is observed. Total pressure decreases inside pitot-tube whereas static pressure increases. Changing pitot-tube from standard to curved shape results in minimum flow circulation inside pitot-tube and leads to a higher pump performance.

Keywords: CFD, flow circulation, high pressure pump, impeller, internal flow, pickup tube pump, rectangle channels, rotating casing, turbulence

Procedia PDF Downloads 160

Authors: Najmeh Malekpour Bahabadi

Abstract:

Small fast-developing Iranian cities with a historical background have no defined criteria for their social sustainability. However, their traditional architecture is well-known as a socially and environmentally sustainable role model. In today's cities, citizens' participation has been considered an effective strategy to achieve social sustainability. By scrutinizing the extent and manner of public participation in traditional Iranian cities, taking Yazd's historical context as a case study, this study examines how these criteria can be applied to developing parts of the city. The paper first reviews the concepts, levels, and approaches of public participation to analyze different modes of citizen participation. Then, exploring social behavior and activities in Yazd, using the qualitative-analytical methodology, the paper compares diverse elements influencing participation with contemporary approaches. The findings of this study would lead to suggestions for the developing parts of the city to enhance their socially sustainable development.

Keywords: citizen participation, social behaviors, traditional city, built environment, social sustainability

Procedia PDF Downloads 127

Authors: Mark Schudeleit, Christian Sieg, Ferit Küçükay

Abstract:

This paper describes how to dimension the electric components of a 48V hybrid system considering real customer use. Furthermore, it provides information about savings in energy and CO2 emissions by a customer-tailored 48V hybrid. Based on measured customer profiles, the electric units such as the electric motor and the energy storage are dimensioned. Furthermore, the CO2 reduction potential in real customer use is determined compared to conventional vehicles. Finally, investigations are carried out to specify the topology design and preliminary considerations in order to hybridize a conventional vehicle with a 48V hybrid system. The emission model results from an empiric approach also taking into account the effects of engine dynamics on emissions. We analyzed transient engine emissions during representative customer driving profiles and created emission meta models. The investigation showed a significant difference in emissions when simulating realistic customer driving profiles using the created verified meta models compared to static approaches which are commonly used for vehicle simulation.

Keywords: customer use, dimensioning, hybrid electric vehicles, vehicle simulation, 48V hybrid system

Procedia PDF Downloads 508

Authors: Shanxiong Chen, Xu Han, Xiaolong Wang, Hui Ma

Abstract:

Yi is an ethnic group mainly living in mainland China, with its own spoken and written language systems, after development of thousands of years. Ancient Yi is one of the six ancient languages in the world, which keeps a record of the history of the Yi people and offers documents valuable for research into human civilization. Recognition of the characters in ancient Yi helps to transform the documents into an electronic form, making their storage and spreading convenient. Due to historical and regional limitations, research on recognition of ancient characters is still inadequate. Thus, deep learning technology was applied to the recognition of such characters. Five models were developed on the basis of the four-layer convolutional neural network (CNN). Alpha-Beta divergence was taken as a penalty term to re-encode output neurons of the five models. Two fully connected layers fulfilled the compression of the features. Finally, at the softmax layer, the orthographic features of ancient Yi characters were re-evaluated, their probability distributions were obtained, and characters with features of the highest probability were recognized. Tests conducted show that the method has achieved higher precision compared with the traditional CNN model for handwriting recognition of the ancient Yi.

Keywords: recognition, CNN, Yi character, divergence

Procedia PDF Downloads 165

Authors: Gurubasavaraju T. M.

Abstract:

The magnetorheological (MR) damper could provide variable damping force with respect to the different input magnetic field. The damping force could be estimated through computational analysis using finite element and computational fluid dynamics analysis. The double-ended damper operates without changing the total volume of fluid. In this paper, damping force of double ended damper under different magnetic field is computed. Initially, the magneto-statics analysis carried out to evaluate the magnetic flux density across the fluid flow gap. The respective change in the rheology of the MR fluid is computed by using the experimentally fitted polynomial equation of shear stress versus magnetic field plot of MR fluid. The obtained values are substituted in the Herschel Buckley model to express the non-Newtonian behavior of MR fluid. Later, using computational fluid dynamic (CFD) analysis damping characteristics in terms of force versus velocity and force versus displacement for the respective magnetic field is estimated. The purpose of the present approach is to characterize the preliminary designed MR damper before fabricating.

Keywords: MR fluid, double ended MR damper, CFD, FEA

Procedia PDF Downloads 180

Authors: H. Loumi-Fergane, A. Belaidi

Abstract:

The problem of symmetries in field theory has been analyzed using geometric frameworks, such as the multisymplectic models by using in particular the multivector field formalism. In this paper, we expand the vector fields associated to infinitesimal symmetries which give rise to invariant quantities as Noether currents for classical field theories and relativistic mechanic using the multisymplectic geometry where the Poincaré-Cartan form has thus been greatly simplified using the Second Order Partial Differential Equation (SOPDE) for multi-vector fields verifying Euler equations. These symmetries have been classified naturally according to the construction of the fiber bundle used.  In this work, unlike other works using the analytical method, our geometric model has allowed us firstly to distinguish the angular moments of the gauge field obtained during different transformations while these moments are gathered in a single expression and are obtained during a rotation in the Minkowsky space. Secondly, no conditions are imposed on the Lagrangian of the mechanics with respect to its dependence in time and in qⁱ, the currents obtained naturally from the transformations are respectively the energy and the momentum of the system.

Keywords: conservation laws, field theories, multisymplectic geometry, relativistic mechanics

Procedia PDF Downloads 207

Authors: Bonchan Koo, Junhee Han, Dohyung Lee

Abstract:

The research attempts to evaluate the accuracy and efficiency of a design optimization procedure which combines wavelets-based solution algorithm and proper orthogonal decomposition (POD) database management technique. Aerodynamic design procedure calls for high fidelity computational fluid dynamic (CFD) simulations and the consideration of large number of flow conditions and design constraints. Even with significant computing power advancement, current level of integrated design process requires substantial computing time and resources. POD reduces the degree of freedom of full system through conducting singular value decomposition for various field simulations. For additional efficiency improvement of the procedure, adaptive wavelet technique is also being employed during POD training period. The proposed design procedure was applied to the optimization of wing aerodynamic performance. Throughout the research, it was confirmed that the POD/wavelets design procedure could significantly reduce the total design turnaround time and is also able to capture all detailed complex flow features as in full order analysis.

Keywords: POD (Proper Orthogonal Decomposition), wavelets, CFD, design optimization, ROM (Reduced Order Model)

Procedia PDF Downloads 467

Authors: Noha El-Gohary, Thanaa El-Shater, A. A. Mahfouz, M. M. Sakr

Abstract:

Searching for high power conversion efficiency and long lifetime are important goals when designing a power supply subsystem for satellite applications. To fulfill these goals, this paper presents a power supply subsystem for small satellites in which flywheel energy storage system is used as a secondary power source instead of chemical battery. In this paper, the model of flywheel energy storage system is introduced; a DC bus regulation control algorithm for charging and discharging of flywheel based on space vector pulse width modulation technique and motor current control is also introduced. Simulation results showed the operation of the flywheel for charging and discharging mode during illumination and shadowed period. The advantages of the proposed system are confirmed by the simulation results of the power supply system.

Keywords: small-satellites, flywheel energy storage system, space vector pulse width modulation, power conversion

Procedia PDF Downloads 400

Authors: Leila Jafari, Viliam Makis, G. B. Akram Khaleghei

Abstract:

In this paper, we present a maintenance model of a two-unit series system with economic dependence. Unit#1, which is considered to be more expensive and more important, is subject to condition monitoring (CM) at equidistant, discrete time epochs and unit#2, which is not subject to CM, has a general lifetime distribution. The multivariate observation vectors obtained through condition monitoring carry partial information about the hidden state of unit#1, which can be in a healthy or a warning state while operating. Only the failure state is assumed to be observable for both units. The objective is to find an optimal opportunistic maintenance policy minimizing the long-run expected average cost per unit time. The problem is formulated and solved in the partially observable semi-Markov decision process framework. An effective computational algorithm for finding the optimal policy and the minimum average cost is developed and illustrated by a numerical example.

Keywords: condition-based maintenance, semi-Markov decision process, multivariate Bayesian control chart, partially observable system, two-unit system

Procedia PDF Downloads 460

Authors: Jamid Ul Islam, Zillur Rahman

Abstract:

The impulse for customer engagement research in online brand communities (OBCs) is largely acknowledged in the literature. Applying congruity theory, this study proposes a model of customer engagement by examining how two congruities viz. self-brand image congruity and value congruity influence customers’ engagement in online brand communities. The consequent effect of customer engagement on brand loyalty is also studied. This study collected data through a questionnaire survey of 395 students of a higher educational institute in India, who were active on Facebook and followed a brand community (at least one). The data were analyzed using structure equation modelling. The results revealed that both the types of congruity i.e., self-brand image congruity and value congruity significantly affect customer engagement. A positive effect of customer engagement on brand loyalty was also affirmed by the results. This study integrates and broadens extant explanations of different congruity effects on consumer behavior-an area that has received little attention. This study is expected to add new trends to engage customers in online brand communities and offer realistic insights to the domain of social media marketing.

Keywords: congruity theory, customer engagement, Facebook, online brand communities

Procedia PDF Downloads 349

Authors: Evangelia Gaitanidou, Evangelos Bekiaris

Abstract:

Considering that resilience implies the ability of a system to adapt continuously in order to respond to its operational goals, a system is considered as more or less resilient depending on the level and time of recovering from disruptive events and/or shocks to its initial state. Regarding transport systems, enhancing resilience is considered imperative for two main reasons: Such systems provide critical support to every socio-economic activity, while being one of the most important economic sectors and, secondly, the paths that convey people, goods and information, are the same through which risks are propagated. RESOLUTE (RESilience management guidelines and Operationalization appLied to Urban Transport Environment) Horizon 2020 research project is answering those needs, by proposing and testing a set of guidelines for resilience management of the urban transport system. The methods and steps towards this goal, through a step-wise methodology, taking into account established models like FRAM (Functional Resonance Analysis Model), and upon gathering existing practices are described in this paper, together with an overview of the produced guidelines. The overall aim is to create a framework which public transport authorities could consult and apply, for rendering their infrastructure resilient against natural disaster and other threats.

Keywords: guidelines, infrastructure, resilience, transport

Procedia PDF Downloads 249

Authors: Yanhua Ma, Lu Zhai, Xinchen Wang, Hongyu Liang

Abstract:

In this paper, by understanding the development status of the human-machine interface in today's automobile cab, a subjective and objective evaluation system for evaluating the optimization of human-machine interface matching in automobile cab was established. The man-machine interface of the car cab was divided into a software interface and a hard interface. Objective evaluation method of software human factor analysis is used to evaluate the hard interface matching; The analytic hierarchy process is used to establish the evaluation index system for the software interface matching optimization, and the multi-level fuzzy comprehensive evaluation method is used to evaluate hard interface machine. This article takes Dongfeng Sokon (DFSK) C37 model automobile as an example. The evaluation method given in the paper is used to carry out relevant analysis and evaluation, and corresponding optimization suggestions are given, which have certain reference value for designers.

Keywords: analytic hierarchy process, fuzzy comprehension evaluation method, human-machine interface, matching optimization, software human factor analysis

Procedia PDF Downloads 156

Authors: M. Naeimi, H. Aghazadeh, E. Afjei, A. Siadatan

Abstract:

In this paper, a novel view of air gap magnetic field analysis of synchronous reluctance motor and permanent magnet assisted synchronous reluctance motor under static eccentricity to provide the precise fault diagnosis based on three-dimensional finite element method is presented. Analytical nature of this method makes it possible to simulate reliable and precise model by considering the end effects and axial fringing effects. The results of the three-dimensional finite element analysis of synchronous reluctance motor and permanent magnet synchronous reluctance motor such as flux linkage, flux density, and compression both of SynRM and PM-SynRM for various eccentric motor conditions are obtained and analyzed. These results present useful information regarding to the detection of static eccentricity.

Keywords: synchronous reluctance motor (SynRM), permanent magnet assisted synchronous reluctance motor (PMaSynRM), finite element method, static eccentricity, fault analysis

Procedia PDF Downloads 311

Authors: Salah A. Al-Garyani, Yousef Swesi

Abstract:

Gas hydrates can be hazardous to upstream operations. On the other hand, the high gas storage capacity of hydrate may be utilized for natural gas storage and transport. Research on the promotion of hydrate formation, as related to natural gas storage and transport, has received relatively little attention. The primary objective of this study is to gain a better understanding of the effects of ionic surfactants, particularly their molecular structures and concentration, on the formation of tetrahydrofuran (THF) hydrate, which is often used as a model hydrate former for screening hydrate promoters or inhibitors. The surfactants studied were sodium n-dodecyl sulfate (SDS), sodium n-hexadecyl sulfate (SHS). Our results show that, at concentrations below the solubility limit, the induction time decreases with increasing surfactant concentration. At concentrations near or above the solubility, however, the surfactant concentration no longer has any effect on the induction time. These observations suggest that the effect of surfactant on THF hydrate formation is associated with surfactant monomers, not the formation of micelle as previously reported. The lowest induction time (141.25 ± 21 s, n = 4) was observed in a solution containing 7.5 mM SDS. The induction time decreases by a factor of three at concentrations near or above the solubility, compared to that without surfactant.

Keywords: tetrahydrofuran, hydrate, surfactant, induction time, monomers, micelle

Procedia PDF Downloads 410

Authors: Abhilash Balan Paleri

Abstract:

Hand woven fabric embellishes an exceptional identity in the social milieu of Kerala; still, the artisans and handloom sector is undergoing crisis due to various reasons. The hand woven school uniform initiative of Govt. of Kerala launched in 2016 aims at enhancing the sector, ensuring sustainability at artisan and end-user levels. The Kerala Government already distributed 23 lakhs meters of cloth (for shirting, suiting, and skirting) woven by 4085 artisans in their traditional looms covering 4.5 lakhs of students in the public education sector which covers cover 3,701 schools in the state. The 2019-20 year production is expected to be 42 Lakhs meters of hand woven clothing catering 8.6 lakhs of students in the primary sector. This particular investigation unveils the upshots of the initiative, and the observations are derived through systematic enquiry with artisans, authorities, and end-users. The findings show a remarkable positive impact in the livelihood of artisans and the entire handloom sector.

Keywords: handloom school uniform initiative of Kerala, hand woven fabric, sustainability, handloom weavers

Procedia PDF Downloads 148

Authors: Arash Esmaeili, Zhibang Liu, Yang Xiang, Jimmy Yun, Lei Shao

Abstract:

A high pressure carbon dioxide (CO₂) absorption from a specific gas in a conventional column has been evaluated by the Aspen HYSYS simulator using a wide range of single absorbents and blended solutions to estimate the outlet CO₂ concentration, absorption efficiency and CO₂ loading to choose the most proper solution in terms of CO₂ capture for environmental concerns. The property package (Acid Gas-Chemical Solvent) which is compatible with all applied solutions for the simulation in this study, estimates the properties based on an electrolyte non-random two-liquid (E-NRTL) model for electrolyte thermodynamics and Peng-Robinson equation of state for the vapor and liquid hydrocarbon phases. Among all the investigated single amines as well as blended solutions, piperazine (PZ) and the mixture of piperazine and monoethanolamine (MEA) have been found as the most effective absorbents respectively for CO₂ absorption with high reactivity based on the simulated operational conditions.

Keywords: absorption, amine solutions, Aspen HYSYS, carbon dioxide, simulation

Procedia PDF Downloads 186

Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo ferraioli

Abstract:

In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring . SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, deep learning, convolutional neural network, deep neural network, SAR polarimetry

Procedia PDF Downloads 90

Authors: Vijaya Dixit Aasheesh Dixit

Abstract:

Shipbuilding industry operates in Engineer Procure Construct (EPC) context. Product mix of a shipyard comprises of various types of ships like bulk carriers, tankers, barges, coast guard vessels, sub-marines etc. Each order is unique based on the type of ship and customized requirements, which are engineered into the product right from design stage. Thus, to execute every new project, a shipyard needs to upgrade its production expertise. As a result, over the long run, holistic learning occurs across different types of projects which contributes to the knowledge base of the shipyard. Simultaneously, in the short term, during execution of a project comprising of multiple sister ships, repetition of similar tasks leads to learning at activity level. This research aims to capture above learnings of a shipyard and incorporate learning curve effect in project scheduling and materials procurement to improve project performance. Extant literature provides support for the existence of such learnings in an organization. In shipbuilding, there are sequences of similar activities which are expected to exhibit learning curve behavior. For example, the nearly identical structural sub-blocks which are successively fabricated, erected, and outfitted with piping and electrical systems. Learning curve representation can model not only a decrease in mean completion time of an activity, but also a decrease in uncertainty of activity duration. Sister ships have similar material requirements. The same supplier base supplies materials for all the sister ships within a project. On one hand, this provides an opportunity to reduce transportation cost by batching the order quantities of multiple ships. On the other hand, it increases the inventory holding cost at shipyard and the risk of obsolescence. Further, due to learning curve effect the production scheduled of each consequent ship gets compressed. Thus, the material requirement schedule of every next ship differs from its previous ship. As more and more ships get constructed, compressed production schedules increase the possibility of batching the orders of sister ships. This work aims at integrating materials management with project scheduling of long duration projects for manufacturing of multiple sister ships. It incorporates the learning curve effect on progressively compressing material requirement schedules and addresses the above trade-off of transportation cost and inventory holding and shortage costs while satisfying budget constraints of various stages of the project. The activity durations and lead time of items are not crisp and are available in the form of probabilistic distribution. A Stochastic Mixed Integer Programming (SMIP) model is formulated which is solved using evolutionary algorithm. Its output provides ordering dates of items and degree of order batching for all types of items. Sensitivity analysis determines the threshold number of sister ships required in a project to leverage the advantage of learning curve effect in materials management decisions. This analysis will help materials managers to gain insights about the scenarios: when and to what degree is it beneficial to treat a multiple ship project as an integrated one by batching the order quantities and when and to what degree to practice distinctive procurement for individual ship.

Keywords: learning curve, materials management, shipbuilding, sister ships

Procedia PDF Downloads 502

Authors: Aviv Yaniv, Ron Ben Arosh, Nadav Gasner, Michael Konviser, Arbel Yaniv

Abstract:

This paper introduces two methods for the evaluation of Question Decomposition Meaning Representation (QDMR) as predicted by sequence-to-sequence model and COPYNET parser for natural language questions processing, motivated by the fact that previous evaluation metrics used for this task do not take into account some characteristics of the representation, such as partial ordering structure. To this end, several heuristics to extract such partial dependencies are formulated, followed by the hereby proposed evaluation methods denoted as Proportional Graph Matcher (PGM) and Conversion to Normal String Representation (Nor-Str), designed to better capture the accuracy level of QDMR predictions. Experiments are conducted to demonstrate the efficacy of the proposed evaluation methods and show the added value suggested by one of them- the Nor-Str, for better distinguishing between high and low-quality QDMR when predicted by models such as COPYNET. This work represents an important step forward in the development of better evaluation methods for QDMR predictions, which will be critical for improving the accuracy and reliability of natural language question-answering systems.

Keywords: NLP, question answering, question decomposition meaning representation, QDMR evaluation metrics

Procedia PDF Downloads 78

Authors: Rejab Hajlaoui, Tarek Moulahi, Hervé Guyennet

Abstract:

In a highway scenario, the vehicle speed can exceed 120 kmph. Therefore, any vehicle can enter or leave the network within a very short time. This mobility adversely affects the network connectivity and decreases the life time of all established links. To ensure an effective stability in vehicular ad hoc networks with minimum broadcasting storm, we have developed a weighted algorithm based on the k-medoids clustering algorithm (WKCA). Indeed, the number of clusters and the initial cluster heads will not be selected randomly as usual, but considering the available transmission range and the environment size. Then, to ensure optimal assignment of nodes to clusters in both k-medoids phases, the combined weight of any node will be computed according to additional metrics including direction, relative speed and proximity. Empirical results prove that in addition to the convergence speed that characterizes the k-medoids algorithm, our proposed model performs well both AODV-Clustering and OLSR-Clustering protocols under different densities and velocities in term of end-to-end delay, packet delivery ratio, and throughput.

Keywords: communication, clustering algorithm, k-medoids, sensor, vehicular ad hoc network

Procedia PDF Downloads 239

Authors: Manisha Bal, B. C. Meikap

Abstract:

Highly toxic and corrosive gas H₂S is recognized as one of the hazardous air pollutants which has significant effect on the human health. Abatement of H₂S gas from the air is very necessary. H₂S gas is mainly released from the industries like paper and leather industry as well as during the production of crude oil, during wastewater treatment, etc. But the emission of H₂S gas in high concentration may cause immediate death while at lower concentrations can cause various respiratory problems. In the present study, self priming venturi scrubber is used to remove the H₂S gas from the air. Response surface methodology with central composite design has been chosen to observe the effect of process parameters on the removal efficiency of H₂S. Experiments were conducted by varying the throat gas velocity, liquid level in outer cylinder, and inlet H₂S concentration. ANOVA test confirmed the significant effect of parameters on the removal efficiency. A quadratic equation has been obtained which predicts the removal efficiency very well. The suitability of the developed model has been judged by the higher R² square value which obtained from the regression analysis. From the investigation, it was found that the throat gas velocity has most significant effect and inlet concentration of H₂S has less effect on H₂S removal efficiency.

Keywords: desulfurization, pollution control, response surface methodology, venturi scrubber

Procedia PDF Downloads 138

Authors: Nissa Phloimontri

Abstract:

This research explores the current physical conditions of motorcycle taxi stands located near the BTS stations in the central business district (CBD) and the comfort conditions of motorcycle taxi drivers. The criteria set up for physical stand survey and assessment are the integration of multimodal access design guidelines. After the survey, stands that share similar characteristics are classified into a series of typologies. Based on the environmental comfort model, questionnaires and in-depth interviews are conducted to evaluate the comfort levels of drivers including physical, functional, and psychological comfort. The results indicate that there are a number of motorcycle taxi stands that are not up to standard and are not conducive to the work-related activities of drivers. The study concludes by recommending public policy for integrated paratransit stops that support the multimodal transportation and seamless mobility concepts within the specific context of Bangkok as well as promote the quality of work life of motorcycle taxi drivers.

Keywords: motorcycle taxi, paratransit stops, environmental comfort, quality of work life

Procedia PDF Downloads 112

Authors: Juan Bojórquez, Henry E. Reyes, Edén Bojórquez, Alfredo Reyes-Salazar

Abstract:

This paper addressed the use of Artificial Intelligence to obtain the structural reliability of reinforced concrete buildings. For this purpose, artificial neuronal networks (ANN) are developed to predict seismic demand hazard curves. In order to have enough input-output data to train the ANN, a set of reinforced concrete buildings (low, mid, and high rise) are designed, then a probabilistic seismic hazard analysis is made to obtain the seismic demand hazard curves. The results are then used as input-output data to train the ANN in a feedforward backpropagation model. The predicted values of the seismic demand hazard curves found by the ANN are then compared. Finally, it is concluded that the computer time analysis is significantly lower and the predictions obtained from the ANN were accurate in comparison to the values obtained from the conventional methods.

Keywords: structural reliability, seismic design, machine learning, artificial neural network, probabilistic seismic hazard analysis, seismic demand hazard curves

Procedia PDF Downloads 196

Authors: Minseo Jo

Abstract:

The purpose of this paper is to examine the factors in the hedonic price models, that has significance impact in determining the price of apartments. There are many variables employed in the hedonic price models and their effectiveness vary differently according to the researchers and the regions they are analysing. In order to consider various conditions, the meta-regression analysis has been selected for the study. In this paper, four meta-independent variables, from the 65 hedonic price models to analysis. The factors that influence the prices of apartments, as well as including factors that influence the prices of apartments, regions, which are divided into two of the research performed, years of research performed, the coefficients of the functions employed. The covariance between the four meta-variables and p-value of the coefficients and the four meta-variables and number of data used in the 65 hedonic price models have been analyzed in this study. The six factors that are most important in deciding the prices of apartments are positioning of apartments, the noise of the apartments, points of the compass and views from the apartments, proximity to the public transportations, companies that have constructed the apartments, social environments (such as schools etc.).

Keywords: hedonic price model, housing price, meta-regression analysis, characteristics

Procedia PDF Downloads 402