Search results for: COSMO models
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6807

Search results for: COSMO models

3447 Simulation of Government Management Model to Increase Financial Productivity System Using Govpilot

Authors: Arezou Javadi

Abstract:

The use of algorithmic models dependent on software calculations and simulation of new government management assays with the help of specialized software had increased the productivity and efficiency of the government management system recently. This has caused the management approach to change from the old bitch & fix model, which has low efficiency and less usefulness, to the capable management model with higher efficiency called the partnership with resident model. By using Govpilot TM software, the relationship between people in a system and the government was examined. The method of two tailed interaction was the outsourcing of a goal in a system, which is formed in the order of goals, qualified executive people, optimal executive model, and finally, summarizing additional activities at the different statistical levels. The results showed that the participation of people in a financial implementation system with a statistical potential of P≥5% caused a significant increase in investment and initial capital in the government system with maximum implement project in a smart government.

Keywords: machine learning, financial income, statistical potential, govpilot

Procedia PDF Downloads 72
3446 Site Selection and Construction Mechanism of the Island Settlements in China Based on CFD-GIS Technology

Authors: Weng Jiantao, Wu Yiqun

Abstract:

The efficiency of natural ventilation, wind pressure distribution on building surface, wind comfort for pedestrians and buildings’ wind tolerance in traditional settlements are closely related to the pattern of terrain. On the basis of field research on the typical island terrain in China, the physical and mathematical models are established by using CFD software, and then the simulation results of the wind field are exported. We discuss the relationship between wind direction and wind field results. Furthermore simulation results are imported into ArcGIS platform. The evaluation model of island site selection is established with considering slope factor. We realize the visual model of site selection on complex island terrain. The multi-plans of certain residential are discussed based on wind simulation; at last the optimal project is selected. Results can provide the theory guidance for settlement planning and construction in China's traditional island.

Keywords: CFD, island terrain, site selection, construction mechanism

Procedia PDF Downloads 513
3445 Dynamic Measurement System Modeling with Machine Learning Algorithms

Authors: Changqiao Wu, Guoqing Ding, Xin Chen

Abstract:

In this paper, ways of modeling dynamic measurement systems are discussed. Specially, for linear system with single-input single-output, it could be modeled with shallow neural network. Then, gradient based optimization algorithms are used for searching the proper coefficients. Besides, method with normal equation and second order gradient descent are proposed to accelerate the modeling process, and ways of better gradient estimation are discussed. It shows that the mathematical essence of the learning objective is maximum likelihood with noises under Gaussian distribution. For conventional gradient descent, the mini-batch learning and gradient with momentum contribute to faster convergence and enhance model ability. Lastly, experimental results proved the effectiveness of second order gradient descent algorithm, and indicated that optimization with normal equation was the most suitable for linear dynamic models.

Keywords: dynamic system modeling, neural network, normal equation, second order gradient descent

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3444 Adsorption of Phenolic Compounds on Activated Carbon DSAC36-24

Authors: Khaoula Hidouri, Ali Benhmidene, Bechir Chouachi, Dhananjay R. Mishra, Ammar Houas

Abstract:

Activated carbon DSAC36-24 iy is adsorbent materials, characterized by a specific surface area of 548.13 m²g⁻¹. Their manufacture uses the natural raw materials like the nucleus of dates. In this study the treatment is done in two stages: A chemical treatment by H3PO4 followed by a physical treatment under nitrogen for 1 hour then under stream of CO2 for 24 hours. A characterization of the various parameters was determined such as the measurement of the specific surface area, determination of pHPZC, bulk density, iodine value. The study of the adsorption of organic molecules (hydroquinone, paranitrophenol, 2,4-dinitrophenol, 2,4,6-trinitrophenol) indicates that the adsorption phenomena are essentially due to the van der Waals interaction. In the case of organic molecules carrying the polar substituents, the existence of hydrogen bonds is also proved by the donor-acceptor forces. The study of the pH effect was done with modeling by different models (Langmuir, Freundlich, Langmuir-Freundlich, Redlich-Peterson), a kinetic treatment is also followed by the application of Lagergren, Weber, Macky.

Keywords: adsoprtion ishoterms, adsorption kinetics, DSAC36-24, organic molecule

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3443 Addressing the Exorbitant Cost of Labeling Medical Images with Active Learning

Authors: Saba Rahimi, Ozan Oktay, Javier Alvarez-Valle, Sujeeth Bharadwaj

Abstract:

Successful application of deep learning in medical image analysis necessitates unprecedented amounts of labeled training data. Unlike conventional 2D applications, radiological images can be three-dimensional (e.g., CT, MRI), consisting of many instances within each image. The problem is exacerbated when expert annotations are required for effective pixel-wise labeling, which incurs exorbitant labeling effort and cost. Active learning is an established research domain that aims to reduce labeling workload by prioritizing a subset of informative unlabeled examples to annotate. Our contribution is a cost-effective approach for U-Net 3D models that uses Monte Carlo sampling to analyze pixel-wise uncertainty. Experiments on the AAPM 2017 lung CT segmentation challenge dataset show that our proposed framework can achieve promising segmentation results by using only 42% of the training data.

Keywords: image segmentation, active learning, convolutional neural network, 3D U-Net

Procedia PDF Downloads 158
3442 Developing an Integrated Seismic Risk Model for Existing Buildings in Northern Algeria

Authors: R. Monteiro, A. Abarca

Abstract:

Large scale seismic risk assessment has become increasingly popular to evaluate the physical vulnerability of a given region to seismic events, by putting together hazard, exposure and vulnerability components. This study, developed within the scope of the EU-funded project ITERATE (Improved Tools for Disaster Risk Mitigation in Algeria), explains the steps and expected results for the development of an integrated seismic risk model for assessment of the vulnerability of residential buildings in Northern Algeria. For this purpose, the model foresees the consideration of an updated seismic hazard model, as well as ad-hoc exposure and physical vulnerability models for local residential buildings. The first results of this endeavor, such as the hazard model and a specific taxonomy to be used for the exposure and fragility components of the model are presented, using as starting point the province of Blida, in Algeria. Specific remarks and conclusions regarding the characteristics of the Northern Algerian in-built are then made based on these results.

Keywords: Northern Algeria, risk, seismic hazard, vulnerability

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3441 Modelling of Atomic Force Microscopic Nano Robot's Friction Force on Rough Surfaces

Authors: M. Kharazmi, M. Zakeri, M. Packirisamy, J. Faraji

Abstract:

Micro/Nanorobotics or manipulation of nanoparticles by Atomic Force Microscopic (AFM) is one of the most important solutions for controlling the movement of atoms, particles and micro/nano metrics components and assembling of them to design micro/nano-meter tools. Accurate modelling of manipulation requires identification of forces and mechanical knowledge in the Nanoscale which are different from macro world. Due to the importance of the adhesion forces and the interaction of surfaces at the nanoscale several friction models were presented. In this research, friction and normal forces that are applied on the AFM by using of the dynamic bending-torsion model of AFM are obtained based on Hurtado-Kim friction model (HK), Johnson-Kendall-Robert contact model (JKR) and Greenwood-Williamson roughness model (GW). Finally, the effect of standard deviation of asperities height on the normal load, friction force and friction coefficient are studied.

Keywords: atomic force microscopy, contact model, friction coefficient, Greenwood-Williamson model

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3440 Studying Roughness Effects on Flow Regimes in Offshore Pipelines

Authors: Mohammad Sadegh Narges, Zahra Ghadampour

Abstract:

Due to the specific condition, offshore pipelines are given careful consideration and care in both design and operation. Most of the offshore pipeline flows are multi-phase. Multi-phase flows construct different pattern or flow regimes (in simultaneous gas-liquid flow, flow regimes like slug flow, wave and …) under different circumstances. One of the influencing factors on the flow regime is the pipeline roughness value. So far, roughness value influences and the sensitivity of the present models to this parameter have not been taken into consideration. Therefore, roughness value influences on the flow regimes in offshore pipelines are discussed in this paper. Results showed that geometry, absolute pipeline roughness value (materials that the pipeline is made of) and flow phases prevailing the system are of the influential parameters on the flow regimes prevailing multi-phase pipelines in a way that a change in any of these parameters results in a change in flow regimes in all or part of the pipeline system.

Keywords: absolute roughness, flow regime, multi-phase flow, offshore pipelines

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3439 BIM Application Research Based on the Main Entrance and Garden Area Project of Shanghai Disneyland

Authors: Ying Yuken, Pengfei Wang, Zhang Qilin, Xiao Ben

Abstract:

Based on the main entrance and garden area (ME&G) project of Shanghai Disneyland, this paper introduces the application of BIM technology in this kind of low-rise comprehensive building with complex facade system, electromechanical system and decoration system. BIM technology is applied to the whole process of design, construction and completion of the whole project. With the construction of BIM application framework of the whole project, the key points of BIM modeling methods of different systems and the integration and coordination of BIM models are elaborated in detail. The specific application methods of BIM technology in similar complex low-rise building projects are sorted out. Finally, the paper summarizes the benefits of BIM technology application, and puts forward some suggestions for BIM management mode and practical application of similar projects in the future.

Keywords: BIM, complex low-rise building, BIM modeling, model integration and coordination, 3D scanning

Procedia PDF Downloads 175
3438 Analyzing the Perceptions of Emotions in Aesthetic Music

Authors: Abigail Wiafe, Charles Nutrokpor, Adelaide Oduro-Asante

Abstract:

The advancement of technology is rapidly making people more receptive to music as computer-generated music requires minimal human interventions. Though algorithms are applied to generate music, the human experience of emotions is still explored. Thus, this study investigates the emotions humans experience listening to computer-generated music that possesses aesthetic qualities. Forty-two subjects participated in the survey. The selection process was purely arbitrary since it was based on convenience. Subjects listened and evaluated the emotions experienced from the computer-generated music through an online questionnaire. The Likert scale was used to rate the emotional levels after the music listening experience. The findings suggest that computer-generated music possesses aesthetic qualities that do not affect subjects' emotions as long as they are pleased with the music. Furthermore, computer-generated music has unique creativity, and expressioneven though the music produced is meaningless, the computational models developed are unable to present emotional contents in music as humans do.

Keywords: aesthetic, algorithms, emotions, computer-generated music

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3437 [Keynote Talk]: Machining Parameters Optimization with Genetic Algorithm

Authors: Dejan Tanikić, Miodrag Manić, Jelena Đoković, Saša Kalinović

Abstract:

This paper deals with the determination of the optimum machining parameters, according to the measured and modelled data of the cutting temperature and surface roughness, during the turning of the AISI 4140 steel. The high cutting temperatures are unwanted occurences in the metal cutting process. They impact negatively on the quality of the machined part. The machining experiments were performed using different cutting regimes (cutting speed, feed rate and depth of cut), with different values of the workpiece hardness, which causes different values of the measured cutting temperature as well as the measured surface roughness. The temperature and surface roughness data were modelled after that using Response Surface Methodology (RSM). The obtained RSM models are used in the process of optimization of the cutting regimes using the Genetic Algorithms (GA) tool, which enables the metal cutting process in the optimum conditions.

Keywords: genetic algorithms, machining parameters, response surface methodology, turning process

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3436 Low-Cost, Portable Optical Sensor with Regression Algorithm Models for Accurate Monitoring of Nitrites in Environments

Authors: David X. Dong, Qingming Zhang, Meng Lu

Abstract:

Nitrites enter waterways as runoff from croplands and are discharged from many industrial sites. Excessive nitrite inputs to water bodies lead to eutrophication. On-site rapid detection of nitrite is of increasing interest for managing fertilizer application and monitoring water source quality. Existing methods for detecting nitrites use spectrophotometry, ion chromatography, electrochemical sensors, ion-selective electrodes, chemiluminescence, and colorimetric methods. However, these methods either suffer from high cost or provide low measurement accuracy due to their poor selectivity to nitrites. Therefore, it is desired to develop an accurate and economical method to monitor nitrites in environments. We report a low-cost optical sensor, in conjunction with a machine learning (ML) approach to enable high-accuracy detection of nitrites in water sources. The sensor works under the principle of measuring molecular absorptions of nitrites at three narrowband wavelengths (295 nm, 310 nm, and 357 nm) in the ultraviolet (UV) region. These wavelengths are chosen because they have relatively high sensitivity to nitrites; low-cost light-emitting devices (LEDs) and photodetectors are also available at these wavelengths. A regression model is built, trained, and utilized to minimize cross-sensitivities of these wavelengths to the same analyte, thus achieving precise and reliable measurements with various interference ions. The measured absorbance data is input to the trained model that can provide nitrite concentration prediction for the sample. The sensor is built with i) a miniature quartz cuvette as the test cell that contains a liquid sample under test, ii) three low-cost UV LEDs placed on one side of the cell as light sources, with each LED providing a narrowband light, and iii) a photodetector with a built-in amplifier and an analog-to-digital converter placed on the other side of the test cell to measure the power of transmitted light. This simple optical design allows measuring the absorbance data of the sample at the three wavelengths. To train the regression model, absorbances of nitrite ions and their combination with various interference ions are first obtained at the three UV wavelengths using a conventional spectrophotometer. Then, the spectrophotometric data are inputs to different regression algorithm models for training and evaluating high-accuracy nitrite concentration prediction. Our experimental results show that the proposed approach enables instantaneous nitrite detection within several seconds. The sensor hardware costs about one hundred dollars, which is much cheaper than a commercial spectrophotometer. The ML algorithm helps to reduce the average relative errors to below 3.5% over a concentration range from 0.1 ppm to 100 ppm of nitrites. The sensor has been validated to measure nitrites at three sites in Ames, Iowa, USA. This work demonstrates an economical and effective approach to the rapid, reagent-free determination of nitrites with high accuracy. The integration of the low-cost optical sensor and ML data processing can find a wide range of applications in environmental monitoring and management.

Keywords: optical sensor, regression model, nitrites, water quality

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3435 FZP Design Considering Spherical Wave Incidence

Authors: Sergio Pérez-López, Daniel Tarrazó-Serrano, José M. Fuster, Pilar Candelas, Constanza Rubio

Abstract:

Fresnel Zone Plates (FZPs) are widely used in many areas, such as optics, microwaves or acoustics. On the design of FZPs, plane wave incidence is typically considered, but that is not usually the case in ultrasounds, especially in applications where a piston emitter is placed at a certain distance from the lens. In these cases, having control of the focal distance is very important, and with the usual Fresnel equation a focal displacement from the theoretical distance is observed due to the plane wave supposition. In this work, a comparison between FZP with plane wave incidence design and FZP with point source design in the case of piston emitter is presented. Influence of the main parameters of the piston in the final focalization profile has been studied. Numerical models and experimental results are shown, and they prove that when spherical wave incidence is considered for the piston case, it is possible to have a fine control of the focal distance in comparison with the classical design method.

Keywords: focusing, Fresnel zone plates, FZP, ultrasound

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3434 Natural Emergence of a Core Structure in Networks via Clique Percolation

Authors: A. Melka, N. Slater, A. Mualem, Y. Louzoun

Abstract:

Networks are often presented as containing a “core” and a “periphery.” The existence of a core suggests that some vertices are central and form the skeleton of the network, to which all other vertices are connected. An alternative view of graphs is through communities. Multiple measures have been proposed for dense communities in graphs, the most classical being k-cliques, k-cores, and k-plexes, all presenting groups of tightly connected vertices. We here show that the edge number thresholds for such communities to emerge and for their percolation into a single dense connectivity component are very close, in all networks studied. These percolating cliques produce a natural core and periphery structure. This result is generic and is tested in configuration models and in real-world networks. This is also true for k-cores and k-plexes. Thus, the emergence of this connectedness among communities leading to a core is not dependent on some specific mechanism but a direct result of the natural percolation of dense communities.

Keywords: cliques, core structure, percolation, phase transition

Procedia PDF Downloads 174
3433 Revolutionizing Interior Design with AI: A Comprehensive Analysis of Coohom’s Innovative Features

Authors: Raghad Alshabrawi, Raghad Alafif

Abstract:

Coohom is revolutionizing the world of interior design by seamlessly blending cutting-edge AI technology with an intuitive, user-friendly platform. Catering to both professionals and enthusiasts, Coohom empowers users to transform their creative visions into stunning 3D realities with unmatched speed and precision. This research explores Coohom’s groundbreaking AI capabilities, from personalized design suggestions to real-time layout optimization and photorealistic rendering. Compared to competitors like SketchUp and AutoCAD, Coohom stands out with its simplicity, accessibility, and AI-driven innovation. User feedback reveals overwhelming satisfaction, with Coohom’s AI praised for delivering diverse design options, unparalleled accuracy, and significant time savings. As AI continues to reshape the design landscape, Coohom leads the charge, making professional-grade design effortless and accessible to all. This paper highlights the transformative potential of Coohom, showcasing how it is setting a new benchmark for creativity, efficiency, and innovation in the digital design industry.

Keywords: interor design, coohom AI 3D, 3D Models, sketced

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3432 Theoretical Calculation of Wingtip Devices for Agricultural Aircraft

Authors: Hashim Bashir

Abstract:

The Vortex generated at the edges of the wing of an Aircraft are called the Wing Tip Vortex. The Wing Tip Vortices are associated with induced drag. The induced drag is responsible for nearly 50% of aircraft total drag and can be reduced through modifications to the wing tip. Some models displace wingtips vortices outwards diminishing the induced drag. Concerning agricultural aircrafts, wing tip vortex position is really important, while spreading products over a plantation. In this work, theoretical calculations were made in order to study the influence in aerodynamic characteristics and vortex position, over Sudanese agricultural aircraft, by the following types of wing tips: delta tip, winglet and down curved. The down curved tip was better for total drag reduction, but not good referring to vortex position. The delta tip gave moderate improvement on aerodynamic characteristic and on vortex position. The winglet had a better vortex position and lift increment, but caused an undesirable result referring to the wing root bending moment. However, winglet showed better development potential for agricultural aircraft.

Keywords: wing tip device, wing tip vortice, agricultural aircaft, winglet

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3431 Microwave-Assisted Inorganic Salt Pretreatment of Sugarcane Leaf Waste

Authors: Preshanthan Moodley, E. B. Gueguim-Kana

Abstract:

The objective of this study was to develop a method to pretreat sugarcane leaf waste using microwave-assisted (MA) inorganic salt. The effects of process parameters of salt concentration, microwave power intensity and pretreatment time on reducing sugar yield from enzymatically hydrolysed sugarcane leaf waste were investigated. Pretreatment models based on MA-NaCl, MA-ZnCl2 and MA-FeCl3 were developed. Maximum reducing sugar yield of 0.406 g/g was obtained with 2 M FeCl3 at 700W for 3.5 min. Scanning electron microscopy (SEM) and Fourier Transform Infrared analysis (FTIR) showed major changes in lignocellulosic structure after MA-FeCl3 pretreatment with 71.5 % hemicellulose solubilization. This pretreatment was further assessed on sorghum leaves and Napier grass under optimal MA-FeCl3 conditions. A 2 fold and 3.1-fold increase in sugar yield respectively were observed compared to previous reports. This pretreatment was highly effective for enhancing enzymatic saccharification of lignocellulosic biomass.

Keywords: acid, pretreatment, salt, sugarcane leaves

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3430 Fractal Analysis of Polyacrylamide-Graphene Oxide Composite Gels

Authors: Gülşen Akın Evingür, Önder Pekcan

Abstract:

The fractal analysis is a bridge between the microstructure and macroscopic properties of gels. Fractal structure is usually provided to define the complexity of crosslinked molecules. The complexity in gel systems is described by the fractal dimension (Df). In this study, polyacrylamide- graphene oxide (GO) composite gels were prepared by free radical crosslinking copolymerization. The fractal analysis of polyacrylamide- graphene oxide (GO) composite gels were analyzed in various GO contents during gelation and were investigated by using Fluorescence Technique. The analysis was applied to estimate Df s of the composite gels. Fractal dimension of the polymer composite gels were estimated based on the power law exponent values using scaling models. In addition, here we aimed to present the geometrical distribution of GO during gelation. And we observed that as gelation proceeded GO plates first organized themselves into 3D percolation cluster with Df=2.52, then goes to diffusion limited clusters with Df =1.4 and then lines up to Von Koch curve with random interval with Df=1.14. Here, our goal is to try to interpret the low conductivity and/or broad forbidden gap of GO doped PAAm gels, by the distribution of GO in the final form of the produced gel.

Keywords: composite gels, fluorescence, fractal, scaling

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3429 Thermodynamic Properties of Binary Mixtures of 1, 2-Dichloroethane with Some Polyethers: DISQUAC Calculations Compared with Dortmund UNIFAC Results

Authors: F. Amireche, I. Mokbel, J. Jose, B. F. Belaribi

Abstract:

The experimental vapour-liquid equilibria (VLE) at isothermal conditions and excess molar Gibbs energies GE are carried out for the three binary mixtures: 1, 2- dichloroethane + ethylene glycol dimethyl ether, + diethylene glycol dimethyl ether or + diethylene glycol diethyl ether, at ten temperatures ranging from 273 to 353.15 K. A good static device was employed for these measurements. The VLE data were reduced using the Redlich-Kister equation by taking into consideration the vapour pressure non-ideality in terms of the second molar virial coefficient. The experimental data were compared to the results predicted with the DISQUAC and Dortmund UNIFAC group contribution models for the total pressures P, the excess molar Gibbs energies GE and the excess molar enthalpies HE.

Keywords: Disquac model, Dortmund UNIFAC model, 1, 2- dichloroethane, excess molar Gibbs energies GE, polyethers, VLE

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3428 Influence of Major Axis on the Aerodynamic Characteristics of Elliptical Section

Authors: K. B. Rajasekarababu, J. Karthik, G. Vinayagamurthy

Abstract:

This paper is intended to explain the influence of major axis on aerodynamic characteristics of elliptical section. Many engineering applications such as off shore structures, bridge piers, civil structures and pipelines can be modelled as a circular cylinder but flow over complex bodies like, submarines, Elliptical wing, fuselage, missiles, and rotor blades, in which the parameters such as axis ratio can influence the flow characteristics of the wake and nature of separation. Influence of Major axis in Flow characteristics of elliptical sections are examined both experimentally and computationally in this study. For this research, four elliptical models with varying major axis [*AR=1, 4, 6, 10] are analysed. Experimental works have been conducted in a subsonic wind tunnel. Furthermore, flow characteristics on elliptical model are predicted from k-ε turbulence model using the commercial CFD packages by pressure based transient solver with Standard wall conditions.The analysis can be extended to estimation and comparison of Drag coefficient and Fatigue analysis of elliptical sections.

Keywords: elliptical section, major axis, aerodynamic characteristics, k-ε turbulence model

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3427 Prediction of Rolling Forces and Real Exit Thickness of Strips in the Cold Rolling by Using Artificial Neural Networks

Authors: M. Heydari Vini

Abstract:

There is a complicated relation between effective input parameters of cold rolling and output rolling force and exit thickness of strips.in many mathematical models, the effect of some rolling parameters have been ignored and the outputs have not a desirable accuracy. In the other hand, there is a special relation among input thickness of strips,the width of the strips,rolling speeds,mandrill tensions and the required exit thickness of strips with rolling force and the real exit thickness of the rolled strip. First of all, in this paper the effective parameters of cold rolling process modeled using an artificial neural network according to the optimum network achieved by using a written program in MATLAB,it has been shown that the prediction of rolling stand parameters with different properties and new dimensions attained from prior rolled strips by an artificial neural network is applicable.

Keywords: cold rolling, artificial neural networks, rolling force, real rolled thickness of strips

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3426 An ALM Matrix Completion Algorithm for Recovering Weather Monitoring Data

Authors: Yuqing Chen, Ying Xu, Renfa Li

Abstract:

The development of matrix completion theory provides new approaches for data gathering in Wireless Sensor Networks (WSN). The existing matrix completion algorithms for WSN mainly consider how to reduce the sampling number without considering the real-time performance when recovering the data matrix. In order to guarantee the recovery accuracy and reduce the recovery time consumed simultaneously, we propose a new ALM algorithm to recover the weather monitoring data. A lot of experiments have been carried out to investigate the performance of the proposed ALM algorithm by using different parameter settings, different sampling rates and sampling models. In addition, we compare the proposed ALM algorithm with some existing algorithms in the literature. Experimental results show that the ALM algorithm can obtain better overall recovery accuracy with less computing time, which demonstrate that the ALM algorithm is an effective and efficient approach for recovering the real world weather monitoring data in WSN.

Keywords: wireless sensor network, matrix completion, singular value thresholding, augmented Lagrange multiplier

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3425 Kinetic Studies of Bioethanol Production from Salt-Pretreated Sugarcane Leaves

Authors: Preshanthan Moodley, E. B. Gueguim Kana

Abstract:

This study examines the kinetics of S. cerevisiae BY4743 growth and bioethanol production from sugarcane leaf waste (SLW), utilizing two different optimized pretreatment regimes; under two fermentation modes: steam salt-alkali filtered enzymatic hydrolysate (SSA-F), steam salt-alkali unfiltered (SSA-U), microwave salt-alkali filtered (MSA-F) and microwave salt-alkali unfiltered (MSA-U). The kinetic coefficients were determined by fitting the Monod, modified Gompertz, and logistic models to the experimental data with high coefficients of determination R² > 0.97. A maximum specific growth rate (µₘₐₓ) of 0.153 h⁻¹ was obtained under SSA-F and SSA-U whereas, 0.150 h⁻¹ was observed with MSA-F and MSA-U. SSA-U gave a potential maximum bioethanol concentration (Pₘ) of 31.06 g/L compared to 30.49, 23.26 and 21.79g/L for SSA-F, MSA-F and MSA-U respectively. An insignificant difference was observed in the μmax and Pm for the filtered and unfiltered enzymatic hydrolysate for both SSA and MSA pretreatments, thus potentially reducing a unit operation. These findings provide significant insights for process scale up.

Keywords: lignocellulosic bioethanol, microwave pretreatment, sugarcane leaves, kinetics

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3424 Civil-Military Relations in Turkey, Europe, and Middle East

Authors: Dorsa Bakhshandehgeyazdi

Abstract:

This article tries to comprehend the change of Turkish common military relations in an analogical viewpoint. The investigation is taking into account two criteria: institutional / legitimate systems and political oversight of the military's self-sufficiency. Examination of European furthermore, Middle Eastern common military relations models to the Turkish ideal model discloses grave contrasts in the middle of Turkish and Middle Eastern common military relations. The Turkish model in change for not less than 10 years is closer to the European show in both lawful and political perspectives. However, the article underscores that Turkish common military relations are still in change and despite the fact that the EU increase procedure has continuously democratized the legitimate arrangement of the nation, law based combining obliges further advances in the political area. A the result, stabilization in Turkey depends not just on withdrawing of the military from the political domain, additionally on the best possible civilization of the administration in hypothesis and practice.

Keywords: Turkish common military, institutional, legitimate systems, political oversight, middle Eastern common military

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3423 Combining a Continuum of Hidden Regimes and a Heteroskedastic Three-Factor Model in Option Pricing

Authors: Rachid Belhachemi, Pierre Rostan, Alexandra Rostan

Abstract:

This paper develops a discrete-time option pricing model for index options. The model consists of two key ingredients. First, daily stock return innovations are driven by a continuous hidden threshold mixed skew-normal (HTSN) distribution which generates conditional non-normality that is needed to fit daily index return. The most important feature of the HTSN is the inclusion of a latent state variable with a continuum of states, unlike the traditional mixture distributions where the state variable is discrete with little number of states. The HTSN distribution belongs to the class of univariate probability distributions where parameters of the distribution capture the dependence between the variable of interest and the continuous latent state variable (the regime). The distribution has an interpretation in terms of a mixture distribution with time-varying mixing probabilities. It has been shown empirically that this distribution outperforms its main competitor, the mixed normal (MN) distribution, in terms of capturing the stylized facts known for stock returns, namely, volatility clustering, leverage effect, skewness, kurtosis and regime dependence. Second, heteroscedasticity in the model is captured by a threeexogenous-factor GARCH model (GARCHX), where the factors are taken from the principal components analysis of various world indices and presents an application to option pricing. The factors of the GARCHX model are extracted from a matrix of world indices applying principal component analysis (PCA). The empirically determined factors are uncorrelated and represent truly different common components driving the returns. Both factors and the eight parameters inherent to the HTSN distribution aim at capturing the impact of the state of the economy on price levels since distribution parameters have economic interpretations in terms of conditional volatilities and correlations of the returns with the hidden continuous state. The PCA identifies statistically independent factors affecting the random evolution of a given pool of assets -in our paper a pool of international stock indices- and sorting them by order of relative importance. The PCA computes a historical cross asset covariance matrix and identifies principal components representing independent factors. In our paper, factors are used to calibrate the HTSN-GARCHX model and are ultimately responsible for the nature of the distribution of random variables being generated. We benchmark our model to the MN-GARCHX model following the same PCA methodology and the standard Black-Scholes model. We show that our model outperforms the benchmark in terms of RMSE in dollar losses for put and call options, which in turn outperforms the analytical Black-Scholes by capturing the stylized facts known for index returns, namely, volatility clustering, leverage effect, skewness, kurtosis and regime dependence.

Keywords: continuous hidden threshold, factor models, GARCHX models, option pricing, risk-premium

Procedia PDF Downloads 298
3422 A 15 Minute-Based Approach for Berth Allocation and Quay Crane Assignment

Authors: Hoi-Lam Ma, Sai-Ho Chung

Abstract:

In traditional integrated berth allocation with quay crane assignment models, time dimension is usually assumed in hourly based. However, nowadays, transshipment becomes the main business to many container terminals, especially in Southeast Asia (e.g. Hong Kong and Singapore). In these terminals, vessel arrivals are usually very frequent with small handling volume and very short staying time. Therefore, the traditional hourly-based modeling approach may cause significant berth and quay crane idling, and consequently cannot meet their practical needs. In this connection, a 15-minute-based modeling approach is requested by industrial practitioners. Accordingly, a Three-level Genetic Algorithm (3LGA) with Quay Crane (QC) shifting heuristics is designed to fulfill the research gap. The objective function here is to minimize the total service time. Preliminary numerical results show that the proposed 15-minute-based approach can reduce the berth and QC idling significantly.

Keywords: transshipment, integrated berth allocation, variable-in-time quay crane assignment, quay crane assignment

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3421 Hominin Niche in the Times of Climate Change

Authors: Emilia Hunt, Sally C. Reynolds, Fiona Coward, Fabio Parracho Silva, Philip Hopley

Abstract:

Ecological niche modeling is widely used in conservation studies, but application to the extinct hominin species is a relatively new approach. Being able to understand what ecological niches were occupied by respective hominin species provides a new perspective into influences on evolutionary processes. Niche separation or overlap can tell us more about specific requirements of the species within the given timeframe. Many of the ancestral species lived through enormous climate changes: glacial and interglacial periods, changes in rainfall, leading to desertification or flooding of regions and displayed impressive levels of adaptation necessary for their survival. This paper reviews niche modeling methodologies and their application to hominin studies. Traditional conservation methods might not be directly applicable to extinct species and are not comparable to hominins. Hominin niche also includes aspects of technologies, use of fire and extended communication, which are not traditionally used in building conservation models. Future perspectives on how to improve niche modeling for extinct hominin species will be discussed.

Keywords: hominin niche, climate change, evolution, adaptation, ecological niche modelling

Procedia PDF Downloads 192
3420 Low Cost LiDAR-GNSS-UAV Technology Development for PT Garam’s Three Dimensional Stockpile Modeling Needs

Authors: Mohkammad Nur Cahyadi, Imam Wahyu Farid, Ronny Mardianto, Agung Budi Cahyono, Eko Yuli Handoko, Daud Wahyu Imani, Arizal Bawazir, Luki Adi Triawan

Abstract:

Unmanned aerial vehicle (UAV) technology has cost efficiency and data retrieval time advantages. Using technologies such as UAV, GNSS, and LiDAR will later be combined into one of the newest technologies to cover each other's deficiencies. This integration system aims to increase the accuracy of calculating the volume of the land stockpile of PT. Garam (Salt Company). The use of UAV applications to obtain geometric data and capture textures that characterize the structure of objects. This study uses the Taror 650 Iron Man drone with four propellers, which can fly for 15 minutes. LiDAR can classify based on the number of image acquisitions processed in the software, utilizing photogrammetry and structural science principles from Motion point cloud technology. LiDAR can perform data acquisition that enables the creation of point clouds, three-dimensional models, Digital Surface Models, Contours, and orthomosaics with high accuracy. LiDAR has a drawback in the form of coordinate data positions that have local references. Therefore, researchers use GNSS, LiDAR, and drone multi-sensor technology to map the stockpile of salt on open land and warehouses every year, carried out by PT. Garam twice, where the previous process used terrestrial methods and manual calculations with sacks. Research with LiDAR needs to be combined with UAV to overcome data acquisition limitations because it only passes through the right and left sides of the object, mainly when applied to a salt stockpile. The UAV is flown to assist data acquisition with a wide coverage with the help of integration of the 200-gram LiDAR system so that the flying angle taken can be optimal during the flight process. Using LiDAR for low-cost mapping surveys will make it easier for surveyors and academics to obtain pretty accurate data at a more economical price. As a survey tool, LiDAR is included in a tool with a low price, around 999 USD; this device can produce detailed data. Therefore, to minimize the operational costs of using LiDAR, surveyors can use Low-Cost LiDAR, GNSS, and UAV at a price of around 638 USD. The data generated by this sensor is in the form of a visualization of an object shape made in three dimensions. This study aims to combine Low-Cost GPS measurements with Low-Cost LiDAR, which are processed using free user software. GPS Low Cost generates data in the form of position-determining latitude and longitude coordinates. The data generates X, Y, and Z values to help georeferencing process the detected object. This research will also produce LiDAR, which can detect objects, including the height of the entire environment in that location. The results of the data obtained are calibrated with pitch, roll, and yaw to get the vertical height of the existing contours. This study conducted an experimental process on the roof of a building with a radius of approximately 30 meters.

Keywords: LiDAR, unmanned aerial vehicle, low-cost GNSS, contour

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3419 Three-Stage Least Squared Models of a Station-Level Subway Ridership: Incorporating an Analysis on Integrated Transit Network Topology Measures

Authors: Jungyeol Hong, Dongjoo Park

Abstract:

The urban transit system is a critical part of a solution to the economic, energy, and environmental challenges. Furthermore, it ultimately contributes the improvement of people’s quality of lives. For taking these kinds of advantages, the city of Seoul has tried to construct an integrated transit system including both subway and buses. The effort led to the fact that approximately 6.9 million citizens use the integrated transit system every day for their trips. Diagnosing the current transit network is a significant task to provide more convenient and pleasant transit environment. Therefore, the critical objective of this study is to establish a methodological framework for the analysis of an integrated bus-subway network and to examine the relationship between subway ridership and parameters such as network topology measures, bus demand, and a variety of commercial business facilities. Regarding a statistical approach to estimate subway ridership at a station level, many previous studies relied on Ordinary Least Square regression, but there was lack of studies considering the endogeneity issues which might show in the subway ridership prediction model. This study focused on both discovering the impacts of integrated transit network topology measures and endogenous effect of bus demand on subway ridership. It could ultimately contribute to developing more accurate subway ridership estimation accounting for its statistical bias. The spatial scope of the study covers Seoul city in South Korea, and it includes 243 subway stations and 10,120 bus stops with the temporal scope set during twenty-four hours with one-hour interval time panels each. The subway and bus ridership information in detail was collected from the Seoul Smart Card data in 2015 and 2016. First, integrated subway-bus network topology measures which have characteristics regarding connectivity, centrality, transitivity, and reciprocity were estimated based on the complex network theory. The results of integrated transit network topology analysis were compared to subway-only network topology. Also, the non-recursive approach which is Three-Stage Least Square was applied to develop the daily subway ridership model as capturing the endogeneity between bus and subway demands. Independent variables included roadway geometry, commercial business characteristics, social-economic characteristics, safety index, transit facility attributes, and dummies for seasons and time zone. Consequently, it was found that network topology measures were significant size effect. Especially, centrality measures showed that the elasticity was a change of 4.88% for closeness centrality, 24.48% for betweenness centrality while the elasticity of bus ridership was 8.85%. Moreover, it was proved that bus demand and subway ridership were endogenous in a non-recursive manner as showing that predicted bus ridership and predicted subway ridership is statistically significant in OLS regression models. Therefore, it shows that three-stage least square model appears to be a plausible model for efficient subway ridership estimation. It is expected that the proposed approach provides a reliable guideline that can be used as part of the spectrum of tools for evaluating a city-wide integrated transit network.

Keywords: integrated transit system, network topology measures, three-stage least squared, endogeneity, subway ridership

Procedia PDF Downloads 180
3418 Shock Formation for Double Ramp Surface

Authors: Abdul Wajid Ali

Abstract:

Supersonic flight promises speed, but the design of the air inlet faces an obstacle: shock waves. They prevent air flow in the mixed compression ports, which reduces engine performance. Our research investigates this using supersonic wind tunnels and schlieren imaging to reveal the complex dance between shock waves and airflow. The findings show clear patterns of shock wave formation influenced by internal/external pressure surfaces. We looked at the boundary layer, the slow-moving air near the inlet walls, and its interaction with shock waves. In addition, the study emphasizes the dependence of the shock wave behaviour on the Mach number, which highlights the need for adaptive models. This knowledge is key to optimizing the combined compression inputs, paving the way for more powerful and efficient supersonic vehicles. Future engineers can use this knowledge to improve existing designs and explore innovative configurations for next-generation ultrasonic applications.

Keywords: oblique shock formation, boundary layer interaction, schlieren images, double wedge surface

Procedia PDF Downloads 69