Search results for: likelihood estimation method

Authors: Xiaobo Liu, Rakesh Mishra, Yun Zhang

Abstract:

Continuous monitoring of forest canopy height with large coverage is essential for obtaining forest carbon stocks and emissions, quantifying biomass estimation, analyzing vegetation coverage, and determining biodiversity. LiDAR can be used to collect accurate woody vegetation structure such as canopy height. However, LiDAR’s coverage is usually limited because of its high cost and limited maneuverability, which constrains its use for dynamic and large area forest canopy monitoring. On the other hand, optical satellite images, like Sentinel-2, have the ability to cover large forest areas with a high repeat rate, but they do not have height information. Hence, exploring the solution of integrating LiDAR data and Sentinel-2 images to enlarge the coverage of forest canopy height prediction and increase the prediction repeat rate has been an active research topic in the environmental remote sensing community. In this study, we explore the potential of training a Random Forest Regression (RFR) model and a Convolutional Neural Network (CNN) model, respectively, to develop two predictive models for predicting and validating the forest canopy height of the Acadia Forest in New Brunswick, Canada, with a 10m ground sampling distance (GSD), for the year 2018 and 2021. Two 10m airborne LiDAR-derived canopy height models, one for 2018 and one for 2021, are used as ground truth to train and validate the RFR and CNN predictive models. To evaluate the prediction performance of the trained RFR and CNN models, two new predicted canopy height maps (CHMs), one for 2018 and one for 2021, are generated using the trained RFR and CNN models and 10m Sentinel-2 images of 2018 and 2021, respectively. The two 10m predicted CHMs from Sentinel-2 images are then compared with the two 10m airborne LiDAR-derived canopy height models for accuracy assessment. The validation results show that the mean absolute error (MAE) for year 2018 of the RFR model is 2.93m, CNN model is 1.71m; while the MAE for year 2021 of the RFR model is 3.35m, and the CNN model is 3.78m. These demonstrate the feasibility of using the RFR and CNN models developed in this research for predicting large-coverage forest canopy height at 10m spatial resolution and a high revisit rate.

Keywords: remote sensing, forest canopy height, LiDAR, Sentinel-2, artificial intelligence, random forest regression, convolutional neural network

Procedia PDF Downloads 98

Authors: Min-Kook Park, Deuck Hang Lee, Hyun Mo Yang, Jae Hyun Kim, Kang Su Kim

Abstract:

Prestressed hollow-core slabs (HCS) are structurally optimized precast units with light-weight hollowed-sections and very economical due to the mass production by a unique production method. They have been thus widely used in the precast concrete constructions in many countries all around the world. It is, however, difficult to provide shear reinforcement in HCS units produced by the extrusion method, and thus all the shear forces should be resisted solely by concrete webs in the HCS units. This means that, for the HCS units, it is very important to estimate the contribution of web concrete to the shear resistance accurately. In design codes, however, the shear strengths for HCS units are estimated by the same equations that are used for typical prestressed concrete members, which were determined from the calibrations to experimental results of conventional prestressed concrete members other than HCS units. In this study, therefore, shear test results of HCS members with a wide range of influential variables were collected, and the shear strength equations in design codes were thoroughly examined by comparing to the experimental results in the shear database of HCS members. Acknowledgement: This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Science, ICT & Future Planning(NRF-2016R1A2B2010277).

Keywords: hollow-core, web-shear, precast concrete, prestress, capacity

Procedia PDF Downloads 510

Authors: Ebru Turgal, Beyza Doganay Erdogan

Abstract:

Machine learning aims to model the relationship between the response and features. Medical decision-making researchers would like to make decisions about patients’ course and treatment, by examining the repeated measurements over time. Boosting approach is now being used in machine learning area for these aims as an influential tool. The aim of this study is to show the usage of multivariate tree boosting in this field. The main reason for utilizing this approach in the field of decision-making is the ease solutions of complex relationships. To show how multivariate tree boosting method can be used to identify important features and feature-time interaction, we used the data, which was collected retrospectively from Ankara University Chest Diseases Department records. Dataset includes repeated PF ratio measurements. The follow-up time is planned for 120 hours. A set of different models is tested. In conclusion, main idea of classification with weighed combination of classifiers is a reliable method which was shown with simulations several times. Furthermore, time varying variables will be taken into consideration within this concept and it could be possible to make accurate decisions about regression and survival problems.

Keywords: boosted multivariate trees, longitudinal data, multivariate regression tree, panel data

Procedia PDF Downloads 205

Authors: Farid Benkaci-Alia, Abdelhamid Neggada, Sophie Laurentb

Abstract:

A new extraction method of polyphenols from honey using a biodegradable resin was developed and compared with the common commercial resin amberlite XAD2. For this purpose, three honey samples of Algerian origin were selected for the different physico-chemical and biochemical parameters study. After extraction of the target compounds by both resins, the polyphenol content was determined, the antioxidant activity was tested, and LC-MS analyses were performed for identification and quantification. The results showed that physico-chemical and biochemical parameters meet the norms of the International Honey commission, and the H1 sample seemed to be of high quality. The optimal conditions of extraction by biodegradable resin were a pH of 3, an adsorption dose of 40 g/L, a contact time of 50 min, an extraction temperature of 60°C and no stirring. The regeneration and reuse number of both resins was three cycles. The polyphenol contents demonstrated a higher extraction efficiency of biosorbent than of XAD2, especially in H1. LC-MS analyses allowed for the identification and quantification of fifteen compounds in the different honey samples extracted using both resins and the most abundant compound was 3,4,5-trimethoxybenzoic acid. In addition, the biosorbent extracts showed stronger antioxidant activities than the XAD2 extracts.

Keywords: extraction, polyphénols, biosorbent, resin amberlite, HPLC-MS

Procedia PDF Downloads 113

Authors: Sanam Pudasaini, A. T. K. Perera, Ahmed Syed Shaheer Uddin, Sum Huan Ng, Chun Yang

Abstract:

Development of high-efficiency and environment friendly bacterial inactivation methods is of great importance for preventing waterborne diseases which are one of the leading causes of death in the world. Traditional bacterial inactivation methods (e.g., ultraviolet radiation and chlorination) have several limitations such as longer treatment time, formation of toxic byproducts, bacterial regrowth, etc. Recently, an electroporation-based inactivation method was introduced as a substitute. Here, an electroporation-based continuous flow microfluidic device equipped with an array of micropillars is developed, and the device achieved high bacterial inactivation performance ( > 99.9%) within a short exposure time ( < 1 s). More than 99.9% reduction of Escherichia coli bacteria was obtained for the flow rate of 1 mL/hr, and no regrowth of bacteria was observed. Images from scanning electron microscope confirmed the formation of electroporation-induced nano-pore within the cell membrane. Through numerical simulation, it has been shown that sufficiently large electric field strength (3 kV/cm), required for bacterial electroporation, were generated using PDMS micropillars for an applied voltage of 300 V. Further, in this method of inactivation, there is no involvement of chemicals and the formation of harmful by-products is also minimum.

Keywords: electroporation, high-efficiency, inactivation, microfluidics, micropillar

Procedia PDF Downloads 186

Authors: Woldegerima G. Medhin, Tadele Araya

Abstract:

Background: Rabies is acute viral encephalitis affecting mainly carnivores and insectivorous but can affect any mammal. Case fatality rate is 100% once clinical signs appear. Rabies has a worldwide distribution in continental regions of Asia and Africa. Globally, rabies is responsible for more than 61000 human deaths annually. An estimation of human mortality rabies in Asia and Africa annually exceed 35172 and 21476 respectively. Ethiopia approximately 2900 people were estimated to die of rabies annually, Tigary region approximately 98 people were estimated to die annually. The aim of this study is to analyze trends, describe, and evaluate the ten years rabies data in Tigray, Ethiopia. Methods: We conducted descriptive epidemiological study from 15-30 February, 2023 of rabies exposure and death in humans by reviewing the health management information system report from Tigray Regional Health Bureau and vaccination coverage of dog population from 2013 to 2022. We used case definition, suspected cases are those bitten by the dogs displaying clinical signs consistent with rabies and confirmed cases were deaths from rabies at time of the exposure. Results: A total 21031 dog bites and 375 deaths report of rabies and 18222 post exposure treatments for humans in Tigray region were used. A suspected rabies patients had shown an increasing trend from 2013 to 2015 and 2018 to 2019. Overall mortality rate was 19/1000 in Tigray. Majority of suspected patients (45%) were age <15 years old. An estimated by Agriculture Bureau of Tigray Region about 12000 owned and 2500 stray dogs are available in the region, but yearly dog vaccination remains low (50%). Conclusion: Rabies is a public health problem in Tigray region. It is highly recommended to vaccinate individually owned dogs and concerned sectors should eliminate stray dogs. Surveillance system should strengthen for estimating the real magnitude, launch preventive and control measures.

Keywords: rabies, Virus, transmision, prevalence

Procedia PDF Downloads 77

Authors: Nasrin Bakhshizadeh, Ashkan Forootan

Abstract:

A major problem that affects the quality control of polymer in the industrial polymerization is the lack of suitable on-line measurement tools to evaluate the properties of the polymer such as melt and density indices. Controlling the polymerization in ordinary method is performed manually by taking samples, measuring the quality of polymer in the lab and registry of results. This method is highly time consuming and leads to producing large number of incompatible products. An online application for estimating melt index and density proposed in this study is a neural network based on the input-output data of the polyethylene production plant. Temperature, the level of reactors' bed, the intensity of ethylene mass flow, hydrogen and butene-1, the molar concentration of ethylene, hydrogen and butene-1 are used for the process to establish the neural model. The neural network is taught based on the actual operational data and back-propagation and Levenberg-Marquart techniques. The simulated results indicate that the neural network process model established with three layers (one hidden layer) for forecasting the density and the four layers for the melt index is able to successfully predict those quality properties.

Keywords: polyethylene, polymerization, density, melt index, neural network

Procedia PDF Downloads 147

Authors: Halison da Silva Pereira, Ciro Sobrinho Campolina Martins, Vitor Mainenti Leal Lopes

Abstract:

Long range performance is a goal for aircraft configuration optimization. Blended Wing Body (BWB) is presented in many works of literature as the most aerodynamically efficient design for a fixed-wing aircraft. Because of its high weight to thrust ratio, BWB is the ideal configuration for many Unmanned Aerial Vehicle (UAV) missions on geomatics applications. In this work, a BWB aerodynamic design for typical light geomatics payload is presented. Aerodynamic non-dimensional coefficients are predicted using low Reynolds number computational techniques (3D Panel Method) and wing parameters like aspect ratio, taper ratio, wing twist and sweep are optimized for high cruise performance and flight quality. The methodology of this work is a summary of tailless aircraft wing design and its application, with appropriate computational schemes, to light UAV subjected to low Reynolds number flows leads to conclusions like the higher performance and flight quality of thicker airfoils in the airframe body and the benefits of using aerodynamic twist rather than just geometric.

Keywords: blended wing body, low Reynolds number, panel method, UAV

Procedia PDF Downloads 590

Authors: Emna Benmohamed, Hela Ltifi, Mounir Ben Ayed

Abstract:

Bayesian Network (BN) is one of the most efficient classification methods. It is widely used in several fields (i.e., medical diagnostics, risk analysis, bioinformatics research). The BN is defined as a probabilistic graphical model that represents a formalism for reasoning under uncertainty. This classification method has a high-performance rate in the extraction of new knowledge from data. The construction of this model consists of two phases for structure learning and parameter learning. For solving this problem, the K2 algorithm is one of the representative data-driven algorithms, which is based on score and search approach. In addition, the integration of the expert's knowledge in the structure learning process allows the obtainment of the highest accuracy. In this paper, we propose a hybrid approach combining the improvement of the K2 algorithm called K2 algorithm for Parents and Children search (K2PC) and the expert-driven method for learning the structure of BN. The evaluation of the experimental results, using the well-known benchmarks, proves that our K2PC algorithm has better performance in terms of correct structure detection. The real application of our model shows its efficiency in the analysis of the phosphate laundry effluents' impact on the watershed in the Gafsa area (southwestern Tunisia).

Keywords: Bayesian network, classification, expert knowledge, structure learning, surface water analysis

Procedia PDF Downloads 131

Authors: M. S. Nikitenko, S. A. Kizilov, D. Y. Khudonogov

Abstract:

The paper considers an approach to a machine vision operating system combined with using a grid of light markers. This approach is used to solve several scientific and technical problems, such as measuring the capability of an apron feeder delivering coal from a lining return port to a conveyor in the technology of mining high coal releasing to a conveyor and prototyping an autonomous vehicle obstacle detection system. Primary verification of a method of calculating bulk material volume using three-dimensional modeling and validation in laboratory conditions with relative errors calculation were carried out. A method of calculating the capability of an apron feeder based on a machine vision system and a simplifying technology of a three-dimensional modelled examined measuring area with machine vision was offered. The proposed method allows measuring the volume of rock mass moved by an apron feeder using machine vision. This approach solves the volume control issue of coal produced by a feeder while working off high coal by lava complexes with release to a conveyor with accuracy applied for practical application. The developed mathematical apparatus for measuring feeder productivity in kg/s uses only basic mathematical functions such as addition, subtraction, multiplication, and division. Thus, this fact simplifies software development, and this fact expands the variety of microcontrollers and microcomputers suitable for performing tasks of calculating feeder capability. A feature of an obstacle detection issue is to correct distortions of the laser grid, which simplifies their detection. The paper presents algorithms for video camera image processing and autonomous vehicle model control based on obstacle detection machine vision systems. A sample fragment of obstacle detection at the moment of distortion with the laser grid is demonstrated.

Keywords: machine vision, machine vision operating system, light markers, measuring capability, obstacle detection system, autonomous transport

Procedia PDF Downloads 118

Authors: G. Amariei, K. Boltes, R. Rosal, P. Leton

Abstract:

Wastewater treatment plants (WWTPs) are supposed to hold an important place in the reduction of emerging contaminants, but provide an environment that has potential for the development and/or spread of adaptation, as bacteria are continuously mixed with contaminants at sub-inhibitory concentrations. Reviewing the literature, there are little data available regarding the use of adapted bacteria forming activated sludge community for toxicity assessment, and only individual validations have been performed. Therefore, the aim of this work was to study the toxicity of Triclosan (TCS) and Ibuprofen (IBU), individually and in binary combination, on adapted activated sludge (AS). For this purpose a battery of biomarkers were assessed, involving oxidative stress and cytotoxicity responses: glutation-S-transferase (GST), catalase (CAT) and viable cells with FDA. In addition, we compared the toxic effects on adapted bacteria with unadapted bacteria, from a previous research. Adapted AS comes from three continuous-flow AS laboratory systems; two systems received IBU and TCS, individually; while the other received the binary combination, for 14 days. After adaptation, each bacterial culture condition was exposure to IBU, TCS and the combination, at 12 h. The concentration of IBU and TCS ranged 0.5-4mg/L and 0.012-0.1 mg/L, respectively. Batch toxicity experiments were performed using Oxygraph system (Hansatech), for determining the activity of CAT enzyme based on the quantification of oxygen production rate. Fluorimetric technique was applied as well, using a Fluoroskan Ascent Fl (Thermo) for determining the activity of GST enzyme, using monochlorobimane-GSH as substrate, and to the estimation of viable cell of the sludge, by fluorescence staining using Fluorescein Diacetate (FDA). For IBU adapted sludge, CAT activity it was increased at low concentration of IBU, TCS and mixture. However, increasing the concentration the behavior was different: while IBU tends to stabilize the CAT activity, TCS and the mixture decreased this one. GST activity was significantly increased by TCS and mixture. For IBU, no variations it was observed. For TCS adapted sludge, no significant variations on CAT activity it was observed. GST activity it was significant decreased for all contaminants. For mixture adapted sludge the behaviour of CAT activity it was similar to IBU adapted sludge. GST activity it was decreased at all concentration of IBU. While the presence of TCS and mixture, respectively, increased the GST activity. These findings were consistent with the viability cells evaluation, which clearly showed a variation of sludge viability. Our results suggest that, compared with unadapted bacteria, the adapted bacteria conditions plays a relevant role in the toxicity behaviour towards activated sludge communities.

Keywords: adapted sludge community, mixture, PPCPs, toxicity

Procedia PDF Downloads 402

Authors: Tuhina-khatun, Mohamed Hanafi Musa, Mohd Rafii Yosup, Wong Mui Yun, Aktar-uz-Zaman, Mahbod Sahebi

Abstract:

Suppression subtractive hybridization (SSH) method is valuable tool for identifying differentially regulated genes in disease specific or tissue specific genes important for cellular growth and differentiation. It is a widely used method for separating DNA molecules that distinguish two closely related DNA samples. SSH is one of the most powerful and popular methods for generating subtracted cDNA or genomic DNA libraries. It is based primarily on a suppression polymerase chain reaction (PCR) technique and combines normalization and subtraction in a solitary procedure. The normalization step equalizes the abundance of DNA fragments within the target population, and the subtraction step excludes sequences that are common to the populations being compared. This dramatically increases the probability of obtaining low-abundance differentially expressed cDNAs or genomic DNA fragments and simplifies analysis of the subtracted library. SSH technique is applicable to many comparative and functional genetic studies for the identification of disease, developmental, tissue specific, or other differentially expressed genes, as well as for the recovery of genomic DNA fragments distinguishing the samples under comparison.

Keywords: suppression subtractive hybridization, differentially expressed genes, disease specific genes, tissue specific genes

Procedia PDF Downloads 436

Authors: Dávid Kovács, Bálint Csanády, Dániel Boros, Iván Ivkovic, Lóránt Nagy, Dalma Tóth-Lakits, László Márkus, András Lukács

Abstract:

The modeling practice of financial instruments has seen significant change over the last decade due to the recognition of time-dependent and stochastically changing correlations among the market prices or the prices and market characteristics. To represent this phenomenon, the Stochastic Correlation Process (SCP) has come to the fore in the joint modeling of prices, offering a more nuanced description of their interdependence. This approach has allowed for the attainment of realistic tail dependencies, highlighting that prices tend to synchronize more during intense or volatile trading periods, resulting in stronger correlations. Evidence in statistical literature suggests that, similarly to the volatility, the SCP of certain stock prices follows rough paths, which can be described using fractional differential equations. However, estimating parameters for these equations often involves complex and computation-intensive algorithms, creating a necessity for alternative solutions. In this regard, the Fractional Ornstein-Uhlenbeck (fOU) process from the family of fractional processes offers a promising path. We can effectively describe the rough SCP by utilizing certain transformations of the fOU. We employed neural networks to understand the behavior of these processes. We had to develop a fast algorithm to generate a valid and suitably large sample from the appropriate process to train the network. With an extensive training set, the neural network can estimate the process parameters accurately and efficiently. Although the initial focus was the fOU, the resulting model displayed broader applicability, thus paving the way for further investigation of other processes in the realm of financial mathematics. The utility of SCP extends beyond its immediate application. It also serves as a springboard for a deeper exploration of fractional processes and for extending existing models that use ordinary Wiener processes to fractional scenarios. In essence, deploying both SCP and fractional processes in financial models provides new, more accurate ways to depict market dynamics.

Keywords: fractional Ornstein-Uhlenbeck process, fractional stochastic processes, Heston model, neural networks, stochastic correlation, stochastic differential equations, stochastic volatility

Procedia PDF Downloads 124

Authors: Shivi Agarwal, Trilok Mathur

Abstract:

This paper proposes the method to measure the total factor productivity (TFP) change by credibility theory for fuzzy input and output variables. Total factor productivity change has been widely studied with crisp input and output variables, however, in some cases, input and output data of decision-making units (DMUs) can be measured with uncertainty. These data can be represented as linguistic variable characterized by fuzzy numbers. Malmquist productivity index (MPI) is widely used to estimate the TFP change by calculating the total factor productivity of a DMU for different time periods using data envelopment analysis (DEA). The fuzzy DEA (FDEA) model is solved using the credibility theory. The results of FDEA is used to measure the TFP change for fuzzy input and output variables. Finally, numerical examples are presented to illustrate the proposed method to measure the TFP change input and output variables. The suggested methodology can be utilized for performance evaluation of DMUs and help to assess the level of integration. The methodology can also apply to rank the DMUs and can find out the DMUs that are lagging behind and make recommendations as to how they can improve their performance to bring them at par with other DMUs.

Keywords: chance-constrained programming, credibility theory, data envelopment analysis, fuzzy data, Malmquist productivity index

Procedia PDF Downloads 371

Authors: Y. D. Lim, K. S. Yap, K. T. Ooi

Abstract:

In recent years, environmental issue has been a hot topic in the world, especially the global warming effect caused by conventional non-environmentally friendly refrigerants has increased. Several studies of a more energy-efficient and environmentally friendly refrigeration system have been conducted in order to tackle the issue. In search of a better refrigeration system, CO2 refrigeration system has been proposed as a better option. However, the high throttling loss involved during the expansion process of the refrigeration cycle leads to a relatively low efficiency and thus the system is impractical. In order to improve the efficiency of the refrigeration system, it is suggested by replacing the conventional expansion valve in the refrigeration system with an expander. Based on this issue, a new type of expander-compressor combined unit, named Cross Vane Expander-Compressor (CVEC) was introduced to replace the compressor and the expansion valve of a conventional refrigeration system. A mathematical model was developed to calculate the performance of CVEC, and it was found that the machine is capable of saving the energy consumption of a refrigeration system by as much as 18%. Apart from energy saving, CVEC is also geometrically simpler and more compact. To further improve its efficiency, optimization study of the device is carried out. In this report, several design parameters of CVEC were chosen to be the variables of optimization study. This optimization study was done in a simulation program by using complex optimization method, which is a direct search, multi-variables and constrained optimization method. It was found that the main design parameters, which was shaft radius was reduced around 8% while the inner cylinder radius was remained unchanged at its lower limit after optimization. Furthermore, the port sizes were increased to their upper limit after optimization. The changes of these design parameters have resulted in reduction of around 12% in the total frictional loss and reduction of 4% in power consumption. Eventually, the optimization study has resulted in an improvement in the mechanical efficiency CVEC by 4% and improvement in COP by 6%.

Keywords: complex optimization method, COP, cross vane expander-compressor, CVEC, design optimization, direct search, energy saving, improvement, mechanical efficiency, multi variables

Procedia PDF Downloads 375

Authors: Y. T. Chui, W. M. Au, L. Li

Abstract:

Recently, wearable electronic textiles have been emerging in today’s market and were developed rapidly since, beside the needs for the clothing uses for leisure, fashion wear and personal protection, there also exist a high demand for the clothing to be capable for function in this electronic age, such as interactive interfaces, sensual being and tangible touch, social fabric, material witness and so on. With the requirements of wearable electronic textiles to be more comfortable, adorable, and easy caring, conductive yarn becomes one of the most important fundamental elements within the wearable electronic textile for interconnection between different functional units or creating a functional unit. The properties of conductive yarns from different companies can vary to a large extent. There are vitally important criteria for selecting the conductive yarns, which may directly affect its optimization, prospect, applicability and performance of the final garment. However, according to the literature review, few researches on conductive yarns on shelf focus on the assessment methods of conductive yarns for the scientific selection of material by a systematic way under different conditions. Therefore, in this study, direction of selecting high-quality conductive yarns is given. It is to test the stability and reliability of the conductive yarns according the problems industrialists would experience with the yarns during the every manufacturing process, in which, this assessment system can be classified into four stage. That is 1) Yarn stage, 2) Fabric stage, 3) Apparel stage and 4) End user stage. Several tests with clear experiment procedures and parameters are suggested to be carried out in each stage. This assessment method suggested that the optimal conducting yarns should be stable in property and resistant to various corrosions at every production stage or during using them. It is expected that this demonstration of assessment method can serve as a pilot study that assesses the stability of Ag/nylon yarns systematically at various conditions, i.e. during mass production with textile industry procedures, and from the consumer perspective. It aims to assist industrialists to understand the qualities and properties of conductive yarns and suggesting a few important parameters that they should be reminded of for the case of higher level of suitability, precision and controllability.

Keywords: applicability, assessment method, conductive yarn, wearable electronics

Procedia PDF Downloads 538

Authors: Sultan Ahmad Azizi, Gaurang J. Joshi

Abstract:

Urban transportation has come to lime light in recent times due to deteriorating travel quality. The economic growth of India has boosted significant rise in private vehicle ownership in cities, whereas public transport systems have largely been ignored in metropolitan cities. Even though there is latent demand for public transport systems like organized bus services, most of the metropolitan cities have unsustainably low share of public transport. Unfortunately, Indian metropolitan cities have failed to maintain balance in mode share of various travel modes in absence of timely introduction of mass transit system of required capacity and quality. As a result, personalized travel modes like two wheelers have become principal modes of travel, which cause significant environmental, safety and health hazard to the citizens. Of late, the policy makers have realized the need to improve public transport system in metro cities for sustaining the development. However, the challenge to the transit planning authorities is to design a transit system for cities that may attract people to switch over from their existing and rather convenient mode of travel to the transit system under the influence of household socio-economic characteristics and the given travel pattern. In this context, the fast-growing industrial city of Surat is taken up as a case for the study of likely shift to bus transit. Deterioration of public transport system of bus after 1998, has led to tremendous growth in two-wheeler traffic on city roads. The inadequate and poor service quality of present bus transit has failed to attract the riders and correct the mode use balance in the city. The disaggregate travel behavior for trip generations and the travel mode choice has been studied for the West Adajan residential sector of city. Mode specific utility functions are calibrated under multi-nominal logit environment for two-wheeler, cars and auto rickshaws with respect to bus transit using SPSS. Estimation of shift to bus transit is carried indicate an average 30% of auto rickshaw users and nearly 5% of 2W users are likely to shift to bus transit if service quality is improved. However, car users are not expected to shift to bus transit system.

Keywords: bus transit, disaggregate travel nehavior, mode choice Behavior, public transport

Procedia PDF Downloads 266

Authors: Farhood Rismanchian, Seong Hyeon Park, Young Hoon Lee

Abstract:

During the recent years, demand for healthcare services has dramatically increased. As the demand for healthcare services increases, so does the necessity of constructing new healthcare buildings and redesigning and renovating existing ones. Increasing demands necessitate the use of optimization techniques to improve the overall service efficiency in healthcare settings. However, high complexity of care processes remains the major challenge to accomplish this goal. This study proposes a method based on process mining results to address the high complexity of care processes and to find the optimal layout of the various medical centers in an emergency department. ProM framework is used to discover clinical pathway patterns and relationship between activities. Sequence clustering plug-in is used to remove infrequent events and to derive the process model in the form of Markov chain. The process mining results served as an input for the next phase which consists of the development of the optimization model. Comparison of the current ED design with the one obtained from the proposed method indicated that a carefully designed layout can significantly decrease the distances that patients must travel.

Keywords: Mixed Integer programming, Facility layout problem, Process Mining, Healthcare Operation Management

Procedia PDF Downloads 345

Authors: Ali Abdul Kadhim, Fue Lien

Abstract:

Solid particle distribution on an impingement surface has been simulated utilizing a graphical processing unit (GPU). In-house computational fluid dynamics (CFD) code has been developed to investigate a 3D turbulent impinging jet using the lattice Boltzmann method (LBM) in conjunction with large eddy simulation (LES) and the multiple relaxation time (MRT) models. This paper proposed an improvement in the LBM-cellular automata (LBM-CA) probabilistic method. In the current model, the fluid flow utilizes the D3Q19 lattice, while the particle model employs the D3Q27 lattice. The particle numbers are defined at the same regular LBM nodes, and transport of particles from one node to its neighboring nodes are determined in accordance with the particle bulk density and velocity by considering all the external forces. The previous models distribute particles at each time step without considering the local velocity and the number of particles at each node. The present model overcomes the deficiencies of the previous LBM-CA models and, therefore, can better capture the dynamic interaction between particles and the surrounding turbulent flow field. Despite the increasing popularity of LBM-MRT-CA model in simulating complex multiphase fluid flows, this approach is still expensive in term of memory size and computational time required to perform 3D simulations. To improve the throughput of each simulation, a single GeForce GTX TITAN X GPU is used in the present work. The CUDA parallel programming platform and the CuRAND library are utilized to form an efficient LBM-CA algorithm. The methodology was first validated against a benchmark test case involving particle deposition on a square cylinder confined in a duct. The flow was unsteady and laminar at Re=200 (Re is the Reynolds number), and simulations were conducted for different Stokes numbers. The present LBM solutions agree well with other results available in the open literature. The GPU code was then used to simulate the particle transport and deposition in a turbulent impinging jet at Re=10,000. The simulations were conducted for L/D=2,4 and 6, where L is the nozzle-to-surface distance and D is the jet diameter. The effect of changing the Stokes number on the particle deposition profile was studied at different L/D ratios. For comparative studies, another in-house serial CPU code was also developed, coupling LBM with the classical Lagrangian particle dispersion model. Agreement between results obtained with LBM-CA and LBM-Lagrangian models and the experimental data is generally good. The present GPU approach achieves a speedup ratio of about 350 against the serial code running on a single CPU.

Keywords: CUDA, GPU parallel programming, LES, lattice Boltzmann method, MRT, multi-phase flow, probabilistic model

Procedia PDF Downloads 210

Authors: Md. Shah Alam

Abstract:

Mushfiq Ahmad has defined a Mixed Number, which is the sum of a scalar and a Cartesian vector. He has also defined the elementary group operations of Mixed numbers i.e. the norm of Mixed numbers, the product of two Mixed numbers, the identity element and the inverse. It has been observed that Mixed Number is consistent with Pauli matrix algebra and a handy tool to work with Dirac electron theory. Its use as a mathematical method in Physics has been studied. (1) We have applied Mixed number in Quantum Mechanics: Mixed Number version of Displacement operator, Vector differential operator, and Angular momentum operator has been developed. Mixed Number method has also been applied to Klein-Gordon equation. (2) We have applied Mixed number in Electrodynamics: Mixed Number version of Maxwell’s equation, the Electric and Magnetic field quantities and Lorentz Force has been found. (3) An associative transformation of Mixed Number numbers fulfilling Lorentz invariance requirement is developed. (4) We have applied Mixed number algebra as an extension of Complex number. Mixed numbers and the Quaternions have isomorphic correspondence, but they are different in algebraic details. The multiplication of unit Mixed number and the multiplication of unit Quaternions are different. Since Mixed Number has properties similar to those of Pauli matrix algebra, Mixed Number algebra is a more convenient tool to deal with Dirac equation.

Keywords: mixed number, special relativity, quantum mechanics, electrodynamics, pauli matrix

Procedia PDF Downloads 370

Authors: Umit Candan, Kadir Dogan, Ozkan Akin

Abstract:

In this study, the use of a modified rotor 6/4 Switched Reluctance Motor (SRM) and a Brushless Direct Current Motor (BLDC) in pan-tilt systems is compared. Pan-tilt systems are critical mechanisms that enable the precise orientation of cameras and sensors, and their performance largely depends on the characteristics of the motors used. The aim of the study is to determine how the performance of the SRM can be improved through rotor modifications and how these improvements can compete with BLDC motors. Using Finite Element Method (FEM) analyses, the design characteristics and magnetic performance of the 6/4 Switched Reluctance Motor are examined in detail. The modified SRM is found to offer increased torque capacity and efficiency while standing out with its simple construction and robustness. FEM analysis results of SRM indicate that considering its cost-effectiveness and performance improvements achieved through modifications, the SRM is a strong alternative for certain pan-tilt applications. This study aims to provide engineers and researchers with a performance comparison of the modified rotor 6/4 SRM and BLDC motors in pan-tilt systems, helping them make more informed and effective motor selections.

Keywords: reluctance machines, switched reluctance machines, pan-tilt application, comparison, FEM analysis

Procedia PDF Downloads 64

Authors: Syed Khurram Mahmud, Athar Naveed, Shoaib Arif

Abstract:

Beamforming is a signal processing technique extensively utilized in wireless communications and radars for desired signal intensification and interference signal minimization through spatial selectivity. In this paper, we present a method for calculation of optimal weight vectors for smart antenna array, to achieve a directive pattern during transmission and selective reception in interference prone environment. In proposed scheme, Mutual Information (MI) extrema are evaluated through an energy constrained objective function, which is based on a-priori information of interference source and desired array factor. Signal to Interference plus Noise Ratio (SINR) performance is evaluated for both transmission and reception. In our scheme, MI is presented as an index to identify trade-off between information gain, SINR, illumination time and spatial selectivity in an energy constrained optimization problem. The employed method yields lesser computational complexity, which is presented through comparative analysis with conventional methods in vogue. MI based beamforming offers enhancement of signal integrity in degraded environment while reducing computational intricacy and correlating key performance indicators.

Keywords: beamforming, interference, mutual information, wireless communications

Procedia PDF Downloads 283

Authors: Davoud Maleki, Neda Zamani

Abstract:

The present study aims at exploring the effective accountability model of Islamic Azad University using a qualitative approach of grounded theory. The data of this study were obtained from semi-structured interviews with 25 professors and scholars in Islamic Azad University of Tehran who were selected by theoretical sampling method. In the data analysis, the stepwise method and Strauss and Corbin analytical methods (1992) were used. After identification of the main component (balanced response to stakeholders’ needs) and using it to bring the categories together, expressions and ideas representing the relationships between the main and subcomponents, and finally, the revealed components were categorized into six dimensions of the paradigm model, with the relationships among them, including causal conditions (7 components), main component (balanced response to stakeholders’ needs), strategies (5 components), environmental conditions (5 components), intervention features (4 components), and consequences (3 components). Research findings show an exploratory model for describing the relationships between causal conditions, main components, accountability strategies, environmental conditions, university environmental features, and that consequences.

Keywords: accountability, effectiveness, Islamic Azad University, grounded theory

Procedia PDF Downloads 90

Authors: Mahamad Yousif, Eoin Cunningham, Beatrice Smyth

Abstract:

Every year ~6 million tonnes of feathers are produced globally. Due to feathers’ low density and possible contamination with pathogens, their disposal causes health and environmental problems. The extraction of keratin, which represents >90% of feathers’ dry weight, could offer a solution due to its wide range of applications in the food, medical, cosmetics, and biopolymer industries. One of these applications is the production of biofilms which can be used for packaging, edible films, drug delivery, wound healing etc. Several studies in the last two decades investigated keratin film production and its properties. However, the effects of many parameters on the properties of the films remain to be investigated including the extraction method, crosslinker type and concentration, and the film production method. These parameters were investigated in this study. Keratin was extracted from chicken feathers using two methods, alkaline extraction with 0.5 M NaOH at 80 °C or sulphitolysis extraction with 0.5 M sodium sulphite, 8 M urea, and 0.25-1 g sodium dodecyl sulphate (SDS) at 100 °C. The extracted keratin was mixed with different types and concentrations of plasticizers (glycerol and polyethylene glycol) and crosslinkers (formaldehyde (FA), glutaraldehyde, cinnamaldehyde, glyoxal, and 1,4-Butanediol diglycidyl ether (BDE)). The mixtures were either cast in a mould or compression moulded to produce films. For casting, keratin powder was initially dissolved in water to form a 5% keratin solution and the mixture was dried in an oven at 60 °C. For compression moulding, 10% water was added and the compression moulding temperature and pressure were in the range of 60-120 °C and 10-30 bar. Finally, the tensile properties, solubility, and transparency of the films were analysed. The films prepared using the sulphitolysis keratin had superior tensile properties to the alkaline keratin and formed successfully with lower plasticizer concentrations. Lowering the SDS concentration from 1 to 0.25 g/g feathers improved all the tensile properties. All the films prepared without crosslinkers were 100% water soluble but adding crosslinkers reduced solubility to as low as 21%. FA and BDE were found to be the best crosslinkers increasing the tensile strength and elongation at break of the films. Higher compression moulding temperature and pressure lowered the tensile properties of the films; therefore, 80 °C and 10 bar were considered to be the optimal compression moulding temperature and pressure. Nevertheless, the films prepared by casting had higher tensile properties than compression moulding but were less transparent. Two optimal films, prepared by film casting, were identified and their compositions were: (a) Sulphitolysis keratin, 20% glycerol, 10% FA, and 10% BDE. (b) Sulphitolysis keratin, 20% glycerol, and 10% BDE. Their tensile strength, elongation at break, Young’s modulus, solubility, and transparency were: (a) 4.275±0.467 MPa, 86.12±4.24%, 22.227±2.711 MPa, 21.34±1.11%, and 8.57±0.94* respectively. (b) 3.024±0.231 MPa, 113.65±14.61%, 10±1.948 MPa, 25.03±5.3%, and 4.8±0.15 respectively. A higher value indicates that the film is less transparent. The extraction method, film composition, and production method had significant influence on the properties of keratin films and should therefore be tailored to meet the desired properties and applications.

Keywords: compression moulding, crosslinker, film casting, keratin, plasticizer, solubility, tensile properties, transparency

Procedia PDF Downloads 41

Authors: Fazıl Gökgöz, Fahrettin Filiz

Abstract:

Load forecasting has become crucial in recent years and become popular in forecasting area. Many different power forecasting models have been tried out for this purpose. Electricity load forecasting is necessary for energy policies, healthy and reliable grid systems. Effective power forecasting of renewable energy load leads the decision makers to minimize the costs of electric utilities and power plants. Forecasting tools are required that can be used to predict how much renewable energy can be utilized. The purpose of this study is to explore the effectiveness of LSTM-based neural networks for estimating renewable energy loads. In this study, we present models for predicting renewable energy loads based on deep neural networks, especially the Long Term Memory (LSTM) algorithms. Deep learning allows multiple layers of models to learn representation of data. LSTM algorithms are able to store information for long periods of time. Deep learning models have recently been used to forecast the renewable energy sources such as predicting wind and solar energy power. Historical load and weather information represent the most important variables for the inputs within the power forecasting models. The dataset contained power consumption measurements are gathered between January 2016 and December 2017 with one-hour resolution. Models use publicly available data from the Turkish Renewable Energy Resources Support Mechanism. Forecasting studies have been carried out with these data via deep neural networks approach including LSTM technique for Turkish electricity markets. 432 different models are created by changing layers cell count and dropout. The adaptive moment estimation (ADAM) algorithm is used for training as a gradient-based optimizer instead of SGD (stochastic gradient). ADAM performed better than SGD in terms of faster convergence and lower error rates. Models performance is compared according to MAE (Mean Absolute Error) and MSE (Mean Squared Error). Best five MAE results out of 432 tested models are 0.66, 0.74, 0.85 and 1.09. The forecasting performance of the proposed LSTM models gives successful results compared to literature searches.

Keywords: deep learning, long short term memory, energy, renewable energy load forecasting

Procedia PDF Downloads 269

Authors: Chanchal Mewar, Shikha Gangil, Yashwant Parihar, Virendra Dhakar, Bharat Modhera

Abstract:

Biodiesel was prepared from Karanja oil by three step methods: saponification, acidification and esterification. In first step, saponification was done in presence of methanol and KOH or NaOH with Karanja oil. During second step acidification, various acids such as H3PO4, HCl, H2SO4 were used as acid catalyst. In third step, esterification followed by purification was done with various silica sources as Ludox (colloidal silicate) and fumed silica gel. It was found that there was no significant change in density, kinematic viscosity, iodine number, acid value, saponification number, flash point, cloud point, pour point and cetane number after purification by these adsorbents. The objective of this research is the comparison among different adsorbents which were used for the purification of biodiesel. Ludox (colloidal silicate) and fumed silica gel were used as adsorbents for the removal of glycerin from biodiesel and evaluate the effectiveness of biodiesel purity. Furthermore, this study compared the results of distilled water washing also. It was observed that Ludox, fumed silica gel and distilled water produced yield about 93%, 91% and 83% respectively. Highest yield was obtained with Ludox at 100 oC temperature using H3PO4 as acid catalyst and NaOH as base catalyst with methanol, (3:1) alcohol to oil molar ratio in 90 min.

Keywords: biodiesel, three step method, purification, silica sources

Procedia PDF Downloads 506

Authors: Sijo S. Thomas, S. Hridya, Manoj Mohan, Bibin Jacob, Hysen Thomas

Abstract:

Ferrites are iron based oxides with technologically significant magnetic properties and have widespread applications in medicine, technology, and industry. There has been a growing interest in the study of magnetic, electrical and structural properties of mixed ferrites. In the present work, structural and magnetic properties of Nickel and Calcium substituted Fe₃O₄ nanoparticles were investigated. NiₓCa₁₋ₓFe₂O₄ nanoparticles (x = 0, 0.1, 0.3, 0.5, 0.7, 0.9) were synthesized by chemical co-precipitation method and the samples were subsequently sintered at 900°C. The magnetic and structural properties of NiₓCa₁₋ₓFe₂O₄ were investigated using Vibrating Sample Magnetometer and X-Ray diffraction. The XRD results revealed that the synthesized particles have nanometer size and it varies from 46-72 nm as the calcium concentration diminishes. The variation is explained based on the increase in the reaction rate with Ni concentration which favors the formation of ultrafine particles of mixed ferrites. VSM results show pure CaFe₂O₄ exhibit paramagnetic behavior with low saturation value. As the concentration of Ca decreases, a transition occurs from paramagnetic state to ferromagnetic state. When the concentration of Ni becomes dominant, magnetic saturation, coercivity, and retentivity become high, indicating near ferromagnetic behavior of the compound.

Keywords: co-precipitation, ferrites, magnetic behavior, structure

Procedia PDF Downloads 251

Authors: Shahin A. Abdel-Naby, James P. Colgan, Michael S. Pindzola

Abstract:

A time-dependent close-coupling method is developed to calculate a total, double and triple autoionization rates for hollow atomic ions of four-electron systems. This work was motivated by recent observations of the four-electron Auger process in near K-edge photoionization of C+ ions. The time-dependent close-coupled equations are solved using lattice techniques to obtain a discrete representation of radial wave functions and all operators on a four-dimensional grid with uniform spacing. Initial excited states are obtained by relaxation of the Schrodinger equation in imaginary time using a Schmidt orthogonalization method involving interior subshells. The radial wave function grids are partitioned over the cores on a massively parallel computer, which is essential due to the large memory requirements needed to store the coupled-wave functions and the long run times needed to reach the convergence of the ionization process. Total, double, and triple autoionization rates are obtained by the propagation of the time-dependent close-coupled equations in real-time using integration over bound and continuum single-particle states. These states are generated by matrix diagonalization of one-electron Hamiltonians. The total autoionization rates for each L excited state is found to be slightly above the single autoionization rate for the excited configuration using configuration-average distorted-wave theory. As expected, we find the double and triple autoionization rates to be much smaller than the total autoionization rates. Future work can be extended to study electron-impact triple ionization of atoms or ions. The work was supported in part by grants from the American University of Sharjah and the US Department of Energy. Computational work was carried out at the National Energy Research Scientific Computing Center (NERSC) in Berkeley, California, USA.

Keywords: hollow atoms, autoionization, auger rates, time-dependent close-coupling method

Procedia PDF Downloads 156

Authors: X. F. Sun, X. D. Wen, L. J. Liu, C. C. Wu, Y. H. Jia

Abstract:

The field reversed closed magnetic field configuration plasmoid has a potential for large thrust and high power propulsion missions such as deep space exploration due to its high plasma density and larger azimuthal current, which will be a most competitive program for the next generation electric propulsion technology. Moreover, without the electrodes, it also has a long lifetime. Thus, the research on this electric propulsion technology is quite necessary. The plasmoid will be formatted and accelerated by applying a rotation magnetic field (RMF) method. And, the essence of this technology lies on the generation of the azimuthal electron currents driven by RMF. Therefore, the effect of RMF current on the plasmoid acceleration efficiency is a concerned problem. In the paper, the influences of the penetration process of RMF in plasma, the relations of frequency and amplitude of input RF power with current strength and the RMF antenna configuration on the plasmoid acceleration efficiency will be given by a two-fluid numerical simulation method. The results show that the radio-frequency and input power have remarkable influence on the formation and acceleration of plasmoid. These results will provide useful advice for the development, and optimized designing of field reversed configuration plasmoid thruster.

Keywords: rotation magnetic field, current driven, plasma penetration, electric propulsion

Procedia PDF Downloads 118

Authors: Yeanchon H. Dulanlebit, Nikmans Hattu, Gloria Bora

Abstract:

Seaweed is a type of macro algae which are good source of iodine and have been widely used as food and nutrition supplement. One of iodine species that found in ocean plant is iodate. Analysis of iodate in seaweed (Eucheuma cottonii) from coastal area of Maluku has been done. The determination is done by using spectrophotometric method. Iodate in sample is reduced in excess of potassium iodide in the presence of acid solution, and then is reacted with starch to form blue complex. The study found out that the highest wavelength on determination of iodate species using spectrophotometer analysis method is 570 nm. Optimum value to yield maximum absorption is used in this research. Contents of iodate in seawater from coastal area of Ambon Island, Western Seram and Southeast Maluku are 0.2655, 0.2719 and 0.1760 mg/L, respectively. While in seaweeds from Ambon Island, Western Seram, Southeast Maluku-Taar, Ohoidertawun and Wab are 6.3122, 6.3293, 6.2333, 3.7406 and 4.4207 mg/kg in dry weight. Bioconcentration (enrichment) factor of iodate in seaweed (Eucheuma cottonii) from the three samples (cluster) is different; in Coastal area of Ambon Island, Western Seram and Southeast Maluku respectively are 23.78, 23.28 and 27.26.

Keywords: bioconcentration, eucheuma cottonii, iodate, iodine, seaweed

Procedia PDF Downloads 219