Search results for: single machine total weighted tardiness

Authors: Hossein Ghadimi, Alireza Alizadeh, Oveis Abedinia, Noradin Ghadimi

Abstract:

This paper presents an enhanced Honey Bee Mating Optimization (HBMO) to solve the optimal design of multi machine power system stabilizer (PSSs) parameters, which is called the Interactive Honey Bee Mating Optimization (IHBMO). Power System Stabilizers (PSSs) are now routinely used in the industry to damp out power system oscillations. The design problem of the proposed controller is formulated as an optimization problem and IHBMO algorithm is employed to search for optimal controller parameters. The proposed method is applied to multi-machine power system (MPS). The method suggested in this paper can be used for designing robust power system stabilizers for guaranteeing the required closed loop performance over a prespecified range of operating and system conditions. The simplicity in design and implementation of the proposed stabilizers makes them better suited for practical applications in real plants. The non-linear simulation results are presented under wide range of operating conditions in comparison with the PSO and CPSS base tuned stabilizer one through FD and ITAE performance indices. The results evaluation shows that the proposed control strategy achieves good robust performance for a wide range of system parameters and load changes in the presence of system nonlinearities and is superior to the other controllers.

Keywords: power system stabilizer, IHBMO, multimachine, nonlinearities

Procedia PDF Downloads 491

Authors: Jonny, T. Yuri M. Zagloel

Abstract:

This paper is made to present an Indonesian Healthcare model. Currently, there are nine TQM (Total Quality Management) practices in healthcare industry. However, these practices are not integrated yet. Therefore, this paper aims to integrate these practices as a model by using Structural Equation Modeling (SEM). After administering about 210 questionnaires to various stakeholders of this industry, a LISREL program was used to evaluate the model's fitness. The result confirmed that the model is fit because the p-value was about 0.45 or above required 0.05. This has signified that previously mentioned of nine TQM practices are able to be integrated as an Indonesian healthcare model.

Keywords: healthcare, total quality management (TQM), structural equation modeling (SEM), linear structural relations (LISREL)

Procedia PDF Downloads 282

Authors: O. E. Eberechi, G. P. Stevens

Abstract:

Legal theory has been referred to as the explanation of why things do or do not happen. It also describes situations and why they ensue. It provides a normative framework by which things are regulated and a foundation for the establishment of legal mechanisms/institutions that can bring about a desired change in a society. Furthermore, it offers recommendations in resolving practical problems and describes what the law is, what the law ought to be and defines the legal landscape generally. Some legal theories provide a universal standard, e.g. human rights, while others are capable of organizing and streamlining the collective use, and, by extension, bring order to society. Legal theory is used to explain how the world works and how it does not work. This paper will argue for the application of the principles of legal theory in the achievement of access to justice for female victims of sexual violence in refugee camps in Africa through the analysis of legal theories underpinning the access to justice for these women. It is a known fact that female refugees in camps in Africa often experience some form of sexual violation. The perpetrators of these incidents may never be apprehended, prosecuted, convicted or sentenced. Where prosecution does occur, the perpetrators are either acquitted as a result of poor investigation, inept prosecution, a lack of evidence, or the case may be dismissed owing to tardiness on the part of the prosecutor, which accounts for the culture of impunity in refugee camps. In other words, victims do not have access to the justice that could ameliorate the plight of the victims. There is, thus, a need for a legal framework that will facilitate access to justice for these victims. This paper will start with an introduction, and be followed by the definition of legal theory, its functions and its application in law. Secondly, it will provide a brief explanation of the problems faced by female refugees who are victims of sexual violence in refugee camps in Africa. Thirdly, it will embark on an analysis of theories which will be a help to an understanding of the precarious situation of female refugees, why they are violated, the need for access to justice for these victims, and the principles of legal theory in its usefulness in resolving access to justice for these victims.

Keywords: access to justice, underpinning legal theory, refugee, sexual violence

Procedia PDF Downloads 420

Authors: Kar Lin Nyam, Phey Yee Lim

Abstract:

The aim of this study was to determine the antioxidant potential, nutritional composition, and functional properties of kenaf leaves powder. Besides, the effect of kenaf leaves powder in bread qualities, properties, and consumer acceptability were evaluated. Different formulations of bread fortified with 0%, 4% and 8% kenaf leaves powder, respectively were produced. Physical properties of bread, such as loaf volume, dough expansion, crumb colour, and bread texture, were determined. Nine points hedonic scale was utilized in sensory evaluation to determine the best formulation (the highest overall acceptability). Proximate composition, calcium content, and antioxidant properties were also determined for the best formulation. 4% leaves powder bread was the most preferred by the panelists followed by control bread, and the least preferred was being 8% leaves powder bread. 4% leaves powder bread had significantly higher value of DPPH radical scavenging capacity (8.05 mg TE/100g), total phenolic content (12.88 mg GAE/100g) and total flavonoid content (13.26 mg QE/100g) compared to control bread (1.38 mg TE/100g, 8.17 mg GAE/100g, and 8.77 mg QE/100g respectively). Besides, 4% leaves powder bread also showed higher in calcium content and total dietary fiber compared to control bread. Kenaf leaves powder is suitable to be used as a source of natural antioxidant for fortification and nutrient improver in bread.

Keywords: dietary fibre, calcium, total phenolic content, total flavonoid content

Procedia PDF Downloads 119

Authors: Saeed Poormoaied, Zumbul Atan

Abstract:

Emergency shipments provide a powerful mechanism to alleviate the risk of imminent stock-outs and can result in substantial benefits in an inventory system. Customer satisfaction and high service level are immediate consequences of utilizing emergency shipments. In this paper, we consider a single-echelon periodic review inventory system consisting of a single local warehouse, being replenished from a central warehouse with ample capacity in an infinite horizon setting. Since the structure of the optimal policy appears to be complicated, we analyze this problem under an order-up-to-S inventory control policy framework, the (S, T) policy, with the emergency shipment consideration. In each period of the periodic review policy, there is a single opportunity at any point of time for the emergency shipment so that in case of stock-outs, an emergency shipment is requested. The goal is to determine the timing and amount of the emergency shipment during a period (emergency shipment policy) as well as the base stock periodic review policy parameters (replenishment policy). We show that how taking advantage of having an emergency shipment during periods improves the performance of the classical (S, T) policy, especially when fixed and unit emergency shipment costs are small. Investigating the structure of the objective function, we develop an exact algorithm for finding the optimal solution. We also provide a heuristic and an approximation algorithm for the periodic review inventory system problem. The experimental analyses indicate that the heuristic algorithm is computationally more efficient than the approximation algorithm, but in terms of the solution efficiency, the approximation algorithm performs very well. We achieve up to 13% cost savings in the (S, T) policy if we apply the proposed emergency shipment policy. Moreover, our computational results reveal that the approximated solution is often within 0.21% of the globally optimal solution.

Keywords: emergency shipment, inventory, periodic review policy, approximation algorithm.

Procedia PDF Downloads 131

Authors: João Rato, Nuno Costa

Abstract:

The human verbal communication is a two-way process which requires a mutual understanding that will result in some considerations. This kind of communication, also called dialogue, besides the supposed human agents it can also be performed between human agents and machines. The interaction between Men and Machines, by means of a natural language, has an important role concerning the improvement of the communication between each other. Aiming at knowing the performance of some speech recognition systems, this document shows the results of the accomplished tests according to the Word Error Rate evaluation method. Besides that, it is also given a set of information linked to the systems of Man-Machine communication. After this work has been made, conclusions were drawn regarding the Speech Recognition Systems, among which it can be mentioned their poor performance concerning the voice interpretation in noisy environments.

Keywords: automatic speech recognition, man-machine conversation, speech recognition, spoken dialogue systems, word error rate

Procedia PDF Downloads 315

Authors: Chul-Hee Jo, Do-Youb Kim, Seok-Jin Cho, Yu-Ho Rho

Abstract:

The Catenary Anchor Leg Mooring (CALM) Single Point Mooring (SPM) buoy system is the most popular and widely used type of offshore loading terminals. SPM buoy mooring systems have been deployed worldwide for a variety of applications, water depths and vessel sizes ranging from small production carriers to Very Large Crude Carriers (VLCCs). Because of safe and easy berthing and un-berthing operations, the SPM buoy mooring system is also preferred for offshore terminals. The SPM buoy consists of a buoy that is permanently moored to the seabed by means of multiple mooring lines. The buoy contains a bearing system that allows a part of it to rotate around the moored geostatic part. When moored to the rotating part of the buoy, a vessel is able to freely weathervane around the buoy. This study was verified the effects of design variables in order to design an SPM buoy mooring system through parametric analysis. The design variables have independent and nonlinear characteristics. Using parametric analysis, this research was found that the fairlead departure angle, wave height and period, chain diameter and line length effect to the mooring top tension, buoy excursion and line layback.

Keywords: Single Point Mooring (SPM), Catenary Anchor Leg Mooring(CALM), design variables, parametric analysis, mooring system optimization

Procedia PDF Downloads 375

Authors: Essa Abrahim Abdulgader Saleem, Thien-My Dao

Abstract:

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

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

Procedia PDF Downloads 330

Authors: N. Pitcheswara Rao

Abstract:

In the process of conveying the information there may be a chance of signal being corrupted which leads to the erroneous bits in the message. The message may consist of single, double and multiple bit errors. In high-reliability applications, memory can sustain multiple soft errors due to single or multiple event upsets caused by environmental factors. The traditional hamming code with SEC-DED capability cannot be address these types of errors. It is possible to use powerful non-binary BCH code such as Reed-Solomon code to address multiple errors. However, it could take at least a couple dozen cycles of latency to complete first correction and run at a relatively slow speed. In order to overcome this drawback i.e., to increase speed and latency we are using reed-Muller code.

Keywords: SEC-DED, BCH code, Reed-Solomon code, Reed-Muller code

Procedia PDF Downloads 420

Authors: Nabil Saad, David Morgan, Manish Gupta

Abstract:

Visibility has become a key component of air quality and is regulated in many areas by environmental laws such as the EPA Clean Air Act and Regional Haze Rule. Typically, visibility is calculated by estimating the optical absorption and scattering of both gases and aerosols. A major component of the aerosols’ climatic effect is due to their scattering and absorption of solar radiation, which are governed by their optical and physical properties. However, the accurate assessment of this effect on global warming, climate change, and air quality is made difficult due to uncertainties in the calculation of single scattering albedo (SSA). Experimental complications arise in the determination of the single scattering albedo of an aerosol particle since it requires the simultaneous measurement of both scattering and extinction. In fact, aerosol optical absorption, in particular, is a difficult measurement to perform, and it’s often associated with large uncertainties when using filter methods or difference methods. In this presentation, we demonstrate the use of a new open-path Optical Extinction Analyzer (OEA) in conjunction with a nephelometer and two particle sizers, emphasizing the benefits that co-employment of the OEA offers to derive the complex refractive index of aerosols and their single scattering albedo parameter. Various use cases, data reproducibility, and instrument calibration will also be presented to highlight the value proposition of this novel Open-Path OEA.

Keywords: aerosols, extinction, visibility, albedo

Procedia PDF Downloads 82

Authors: Brian Tung, Yam Wing Siu, Tsun Se Cheong

Abstract:

Purpose: This research aims to explore how personal and environmental factors, especially the socio-economic changes and behavioral changes fostered by the COVID-19 outbreak pandemic, affect the financial vulnerability of a specific segment of people in financial distress. Innovative research methodology of machine learning will be applied to data collected from over 300 local individuals in Hong Kong seeking counseling or similar services in recent years. Results: First, machine learning has found that too much exposure to digital services and information on digitized services may lead to adverse effects on respondents’ financial vulnerability. Second, the improvement in financial literacy level provides benefits to the financially vulnerable group, especially those respondents who have started with a lower level. Third, serious addiction to digital technology can lead to worsened debt servicing ability. Machine learning also has found a strong correlation between debt servicing situations and income-seeking behavior as well as spending behavior. In addition, if the vulnerable groups are able to make appropriate investments, they can reduce the probability of incurring financial distress. Finally, being too active in borrowing and repayment can result in a higher likelihood of over-indebtedness. Conclusion: Findings can be employed in formulating a better counseling strategy for professionals. Debt counseling services can be more preventive in nature. For example, according to the findings, with a low level of financial literacy, the respondents are prone to overspending and unable to react properly to the e-marketing promotion messages pop-up from digital services or even falling into financial/investment scams. In addition, people with low levels of financial knowledge will benefit from financial education. Therefore, financial education programs could include tech-savvy matters as special features.

Keywords: personal finance, digitization of the economy, COVID-19 pandemic, addiction to digital technology, financial vulnerability

Procedia PDF Downloads 46

Authors: Youn-Hwan Kim, Jae-Won Moon, Hae-Joong Kim

Abstract:

This paper introduces the results of the study on the development of accelerated life test methods for the motor used in machine tools. In recent years, as well as efficiency for motors, there is a growing need for research on life expectancy of motors. It is considered impossible to calculate the acceleration coefficient by increasing the rotational load or temperature load as the acceleration stress in the motor system because the temperature of the copper exceeds the wire thermal class rating. This paper describes the equipment development procedure for the highly accelerated life test (HALT) of the 12kW three-phase squirrel-cage induction motors (SCIMs). After the test, the lifetime analysis was carried out, and it is compared with the life expectancy by finite element method (FEM) and bearing theory.

Keywords: acceleration coefficient, bearing, HALT, life expectancy, motor

Procedia PDF Downloads 271

Authors: Ehsan Mehryaar

Abstract:

The rate of penetration is (RoP) one of the vital factors in the cost and time of tunnel boring projects; therefore, predicting it can lead to a substantial increase in the efficiency of the project. RoP is heavily dependent geological properties of the project site and TBM properties. In this study, 151-point data from Queen’s water tunnel is collected, which includes unconfined compression strength, peak slope index, angle with weak planes, and distance between planes of weaknesses. Since the size of the data is small, it was observed that it is imbalanced. To solve that problem synthetic minority oversampling technique is utilized. The model based on the model tree is proposed, where each leaf consists of a support vector machine model. Proposed model performance is then compared to existing empirical equations in the literature.

Keywords: Model tree, SMOTE, rate of penetration, TBM(tunnel boring machine), SVM

Procedia PDF Downloads 171

Authors: Wilfred Fritz

Abstract:

Grid connected solar PV inverters need to be compliant to standard regulations regarding unwanted harmonic generation. This paper gives an introduction to harmonics, solar PV inverter voltage regulation and balancing through compensation and investigates the behaviour of harmonic generation at different power levels. Practical measurements of harmonics and power levels with a power quality data logger were made, on a test network at a university in Germany. The test setup and test results are discussed. The major finding was that between the morning and afternoon load peak windows when the PV inverters operate under low solar insolation and low power levels, more unwanted harmonics are generated. This has a huge impact on the power quality of the grid as well as capital and maintenance costs. The design of a single-tuned harmonic filter towards harmonic mitigation is presented.

Keywords: harmonics, power quality, pulse width modulation, total harmonic distortion

Procedia PDF Downloads 231

Authors: Techale B., Hongxu Dong, Mihrete Getinet, Aregash Gabizew, Andrew H. Paterson, Kassahun Bantte

Abstract:

The genetic architecture of drought tolerance is expected to involve multiple loci that are unlikely to all segregate for alternative alleles in a single bi-parental population. Therefore, the identification of quantitative trait loci (QTL) that are expressed in diverse genetic backgrounds of multiple bi-parental populations provides evidence about both background-specific and common genetic variants. The purpose of this study was to map QTL related to drought tolerance using three connected mapping populations of different genetic backgrounds to gain insight into the genomic landscape of this important trait in elite Ethiopian germplasm. The three bi-parental populations, each with 207 F₂:₃ lines, were evaluated using an alpha lattice design with two replications under two moisture stress environments. Drought tolerance related traits were analyzed separately for each population using composite interval mapping, finding a total of 105 QTLs. All the QTLs identified from individual populations were projected on a combined consensus map, comprising a total of 25 meta QTLs for seven traits. The consensus map allowed us to deduce locations of a larger number of markers than possible in any individual map, providing a reference for genetic studies in different genetic backgrounds. The mQTL identified in this study could be used for marker-assisted breeding programs in sorghum after validation. Only one trait, reduced leaf senescence, showed a striking bias of allele distribution, indicating substantial standing variation among present varieties that might be employed in improving drought tolerance of Ethiopian and other sorghums.

Keywords: Drought tolerance , Mapping populations, Meta QTL, QTL mapping, Sorghum

Procedia PDF Downloads 169

Authors: S. Kadiyala, M. Berzins, D. Juba, W. Keyrouz

Abstract:

This paper describes the Material Point Method (MPM) for simulating a single-track laser melting process on an IN718 solid plate. MPM, known for simulating challenging multiphysics problems, is used to model the intricate thermal, mechanical, and fluid interactions during the laser sintering process. This study analyzes the formation of single tracks, exploring the impact of varying laser parameters such as speed, power, and spot diameter on the melt pool and track formation. The focus is on MPM’s ability to accurately simulate and capture the transient thermo-mechanical and phase change phenomena, which are critical in predicting the cooling rates before and after solidification of the laser track and the final melt pool geometry. The simulation results are rigorously compared with experimental data (AMB2022 benchmarks), demonstrating the effectiveness of MPM in replicating the physical processes in laser sintering. This research highlights the potential of MPM in advancing the understanding and simulation of melt pool physics in metal additive manufacturing, paving the way for optimized process parameters and improved material performance.

Keywords: dditive manufacturing simulation, material point method, phase change, melt pool physics

Procedia PDF Downloads 56

Authors: Sara ElElimy, Samir Moustafa

Abstract:

Mobile network operators start to face many challenges in the digital era, especially with high demands from customers. Since mobile network operators are considered a source of big data, traditional techniques are not effective with new era of big data, Internet of things (IoT) and 5G; as a result, handling effectively different big datasets becomes a vital task for operators with the continuous growth of data and moving from long term evolution (LTE) to 5G. So, there is an urgent need for effective Big data analytics to predict future demands, traffic, and network performance to full fill the requirements of the fifth generation of mobile network technology. In this paper, we introduce data science techniques using machine learning and deep learning algorithms: the autoregressive integrated moving average (ARIMA), Bayesian-based curve fitting, and recurrent neural network (RNN) are employed for a data-driven application to mobile network operators. The main framework included in models are identification parameters of each model, estimation, prediction, and final data-driven application of this prediction from business and network performance applications. These models are applied to Telecom Italia Big Data challenge call detail records (CDRs) datasets. The performance of these models is found out using a specific well-known evaluation criteria shows that ARIMA (machine learning-based model) is more accurate as a predictive model in such a dataset than the RNN (deep learning model).

Keywords: big data analytics, machine learning, CDRs, 5G

Procedia PDF Downloads 132

Authors: Mikheil Kalmakhelidze

Abstract:

Record linkage (RL) problem has become more and more important in recent years due to the growing interest towards big data analysis. The problem can be formulated in a very simple way: Given two entries a and b of a database, decide whether they represent the same object or not. There are two classical deterministic and probabilistic ways of solving the RL problem. Using simple Bayes classifier in many cases produces useful results but sometimes they show to be poor. In recent years several successful approaches have been made towards solving specific RL problems by neural network algorithms including single layer perception, multilayer back propagation network etc. In our work, we model the RL problem for specific dataset of student applications in fuzzy description logic (FDL) where linkage of specific pair (a,b) depends on the truth value of corresponding formula A(a,b) in a canonical FDL model. As a main result, we build neural network for deciding truth value of FDL formulas in a canonical model and thus link RL problem to machine learning. We apply the approach to dataset with 10000 entries and also compare to classical RL solving approaches. The results show to be more accurate than standard probabilistic approach.

Keywords: description logic, fuzzy logic, neural networks, record linkage

Procedia PDF Downloads 267

Authors: Lorico D. S. Lapitan Jr., Yihan Xu, Yuan Guo, Dejian Zhou

Abstract:

The ability of ultrasensitive detection of specific genes and discrimination of single nucleotide polymorphisms is important for clinical diagnosis and biomedical research. Herein, we report the development of a new ultrasensitive approach for label-free DNA detection using magnetic nanoparticle (MNP) assisted rapid target capture/separation in combination with signal amplification using poly-enzyme tagged polymer nanobead. The sensor uses an MNP linked capture DNA and a biotin modified signal DNA to sandwich bind the target followed by ligation to provide high single-nucleotide polymorphism discrimination. Only the presence of a perfect match target DNA yields a covalent linkage between the capture and signal DNAs for subsequent conjugation of a neutravidin-modified horseradish peroxidase (HRP) enzyme through the strong biotin-nuetravidin interaction. This converts each captured DNA target into an HRP which can convert millions of copies of a non-fluorescent substrate (amplex red) to a highly fluorescent product (resorufin), for great signal amplification. The use of polymer nanobead each tagged with thousands of copies of HRPs as the signal amplifier greatly improves the signal amplification power, leading to greatly improved sensitivity. We show our biosensing approach can specifically detect an unlabeled DNA target down to 10 aM with a wide dynamic range of 5 orders of magnitude (from 0.001 fM to 100.0 fM). Furthermore, our approach has a high discrimination between a perfectly matched gene and its cancer-related single-base mismatch targets (SNPs): It can positively detect the perfect match DNA target even in the presence of 100 fold excess of co-existing SNPs. This sensing approach also works robustly in clinical relevant media (e.g. 10% human serum) and gives almost the same SNP discrimination ratio as that in clean buffers. Therefore, this ultrasensitive SNP biosensor appears to be well-suited for potential diagnostic applications of genetic diseases.

Keywords: DNA detection, polymer beads, signal amplification, single nucleotide polymorphisms

Procedia PDF Downloads 244

Authors: Arpita Saha, Apoorv Jain, Satish Chandra, Indrajit Ghosh

Abstract:

Level of service at a signal controlled intersection is directly measured from the delay. Similarly, saturation flow rate is a fundamental parameter to measure the intersection capacity. The present study calculates vehicle arrival rate, departure rate, and queue length for every five seconds interval in each cycle. Based on the queue lengths, the total delay of the cycle has been calculated using Simpson’s 1/3rd rule. Saturation flow has been estimated in terms of veh/hr of green/lane for every five seconds interval of the green period until at least three vehicles are left to cross the stop line. Vehicle composition shows an immense effect on total delay and saturation flow rate. The increase in two-wheeler proportion increases the saturation flow rate and reduces the total delay per vehicle significantly. Additionally, an increase in the heavy vehicle proportion reduces the saturation flow rate and increases the total delay for each vehicle.

Keywords: delay, saturation flow, signalised intersection, vehicle composition

Procedia PDF Downloads 451

Authors: Zhaoan Wang

Abstract:

Research in predictive maintenance modeling has improved in the recent years to predict failures and needed maintenance with high accuracy, saving cost and improving manufacturing efficiency. However, classic prediction models provide little valuable insight towards the most important features contributing to the failure. By analyzing and quantifying feature importance in predictive maintenance models, cost saving can be optimized based on business goals. First, multiple classifiers are evaluated with cross-validation to predict the multi-class of failures. Second, predictive performance with features provided by different feature selection algorithms are further analyzed. Third, features selected by different algorithms are ranked and combined based on their predictive power. Finally, linear explainer SHAP (SHapley Additive exPlanations) is applied to interpret classifier behavior and provide further insight towards the specific roles of features in both local predictions and global model behavior. The results of the experiments suggest that certain features play dominant roles in predictive models while others have significantly less impact on the overall performance. Moreover, for multi-class prediction of machine failures, the most important features vary with type of machine failures. The results may lead to improved productivity and cost saving by prioritizing sensor deployment, data collection, and data processing of more important features over less importance features.

Keywords: automated supply chain, intelligent manufacturing, predictive maintenance machine learning, feature engineering, model interpretation

Procedia PDF Downloads 120

Authors: Utkarsh A. Mishra, Ankit Bansal

Abstract:

At high temperature, radiative heat transfer is the dominant mode of heat transfer. It is governed by various phenomena such as photon emission, absorption, and scattering. The solution of the governing integrodifferential equation of radiative transfer is a complex process, more when the effect of participating medium and wavelength properties are taken into consideration. Although a generic formulation of such radiative transport problem can be modeled for a wide variety of problems with non-gray, non-diffusive surfaces, there is always a trade-off between simplicity and accuracy of the problem. Recently, solutions of complicated mathematical problems with statistical methods based on randomization of naturally occurring phenomena have gained significant importance. Photon bundles with discrete energy can be replicated with random numbers describing the emission, absorption, and scattering processes. Photon Monte Carlo (PMC) is a simple, yet powerful technique, to solve radiative transfer problems in complicated geometries with arbitrary participating medium. The method, on the one hand, increases the accuracy of estimation, and on the other hand, increases the computational cost. The participating media -generally a gas, such as CO₂, CO, and H₂O- present complex emission and absorption spectra. To model the emission/absorption accurately with random numbers requires a weighted sampling as different sections of the spectrum carries different importance. Importance sampling (IS) was implemented to sample random photon of arbitrary wavelength, and the sampled data provided unbiased training of MC estimators for better results. A better replacement to uniform random numbers is using deterministic, quasi-random sequences. Halton, Sobol, and Faure Low-Discrepancy Sequences are used in this study. They possess better space-filling performance than the uniform random number generator and gives rise to a low variance, stable Quasi-Monte Carlo (QMC) estimators with faster convergence. An optimal supervised learning scheme was further considered to reduce the computation costs of the PMC simulation. A one-dimensional plane-parallel slab problem with participating media was formulated. The history of some randomly sampled photon bundles is recorded to train an Artificial Neural Network (ANN), back-propagation model. The flux was calculated using the standard quasi PMC and was considered to be the training target. Results obtained with the proposed model for the one-dimensional problem are compared with the exact analytical and PMC model with the Line by Line (LBL) spectral model. The approximate variance obtained was around 3.14%. Results were analyzed with respect to time and the total flux in both cases. A significant reduction in variance as well a faster rate of convergence was observed in the case of the QMC method over the standard PMC method. However, the results obtained with the ANN method resulted in greater variance (around 25-28%) as compared to the other cases. There is a great scope of machine learning models to help in further reduction of computation cost once trained successfully. Multiple ways of selecting the input data as well as various architectures will be tried such that the concerned environment can be fully addressed to the ANN model. Better results can be achieved in this unexplored domain.

Keywords: radiative heat transfer, Monte Carlo Method, pseudo-random numbers, low discrepancy sequences, artificial neural networks

Procedia PDF Downloads 215

Authors: Cheng Fang, Lingwei Quan, Cunyue Lu

Abstract:

Human pose estimation and tracking are to accurately identify and locate the positions of human joints in the video. It is a computer vision task which is of great significance for human motion recognition, behavior understanding and scene analysis. There has been remarkable progress on human pose estimation in recent years. However, more researches are needed for human pose tracking especially for online tracking. In this paper, a framework, called PoseSRPN, is proposed for online single-person pose estimation and tracking. We use Siamese network attaching a pose estimation branch to incorporate Single-person Pose Tracking (SPT) and Visual Object Tracking (VOT) into one framework. The pose estimation branch has a simple network structure that replaces the complex upsampling and convolution network structure with deconvolution. By augmenting the loss of fully convolutional Siamese network with the pose estimation task, pose estimation and tracking can be trained in one stage. Once trained, PoseSRPN only relies on a single bounding box initialization and producing human joints location. The experimental results show that while maintaining the good accuracy of pose estimation on COCO and PoseTrack datasets, the proposed method achieves a speed of 59 frame/s, which is superior to other pose tracking frameworks.

Keywords: computer vision, pose estimation, pose tracking, Siamese network

Procedia PDF Downloads 144

Authors: R. K. Chaurasiya, N. D. Londhe, S. Ghosh

Abstract:

The study of the electrical signals produced by neural activities of human brain is called Electroencephalography. In this paper, we propose an automatic and efficient EEG signal classification approach. The proposed approach is used to classify the EEG signal into two classes: epileptic seizure or not. In the proposed approach, we start with extracting the features by applying Discrete Wavelet Transform (DWT) in order to decompose the EEG signals into sub-bands. These features, extracted from details and approximation coefficients of DWT sub-bands, are used as input to Principal Component Analysis (PCA). The classification is based on reducing the feature dimension using PCA and deriving the support-vectors using Support Vector Machine (SVM). The experimental are performed on real and standard dataset. A very high level of classification accuracy is obtained in the result of classification.

Keywords: discrete wavelet transform, electroencephalogram, pattern recognition, principal component analysis, support vector machine

Procedia PDF Downloads 624

Authors: Melkamu A. Zeru, Aweke A. Mitiku, Endashaw Amuka

Abstract:

Background: Under-five mortality is the likelihood that a baby will pass away before turning exactly 5 years old, represented as a percentage per 1,000 live births. Exploring the spatial distribution and identifying the temporal pattern is important to reducing under-five child mortality globally, including in Ethiopia. Thus, this study aimed to identify the risk factors of under-five mortality and the spatiotemporal variation in Ethiopian administrative zones. Method: This study used the 2000-2016 Ethiopian Demographic and Health Survey (EDHS) data, which were collected using a two-stage sampling method. A total of 43,029 (10,873 in 2000, 9,861 in 2005, 11,654 in 2011, and 10,641 in 2016) weighted sample under-five child mortality was used. The space-time dynamic model was employed to account for spatial and time effects in 65 administrative zones in Ethiopia. Results: From the result of a general nesting spatial-temporal dynamic model, there was a significant space-time interaction effect [γ = -0.1444, 95 % CI (-0.6680, -0.1355)] for under-five mortality. The increase in the percentages of mothers illiteracy [𝛽 = 0.4501, 95% CI (0.2442, 0.6559)], not vaccinated[𝛽= 0.7681, 95% CI (0.5683, 0.9678)], unimproved water[𝛽= 0.5801, CI (0.3793, 0.7808)] were increased death rates for under five children while increased percentage of contraceptive use [𝛽= -0.6609, 95% CI (-0.8636, -0.4582)] and ANC visit > 4 times [𝛽= -0.1585, 95% CI(-0.1812, -0.1357)] were contributed to the decreased under-five mortality rate at the zone in Ethiopia. Conclusions: Even though the mortality rate for children under five has decreased over time, still there is still higher in different zones of Ethiopia. There exists spatial and temporal variation in under-five mortality among zones. Therefore, it is very important to consider spatial neighbourhoods and temporal context when aiming to avoid under-five mortality.

Keywords: under-five children mortality, space-time dynamic, spatiotemporal, Ethiopia

Procedia PDF Downloads 26

Authors: D. ChobfroushKhoei, S. K. Heidari , Sh. Dariadel

Abstract:

Carbon nanotubes were used in medical sciences especially in drug delivery system and cancer therapy. In this study, we functionalized carboxylated single-wall carbon nanotubes (SWNT-COOH) with 2-en 4-hydroxy cyclo 1-octanon. Synthesized sample was characterized by FT-IR, Raman spectroscopy, SEM, TGA and cellular investigations. The results showed well formation of SWNT-Ester. Cell viability assay results and microscopic observations demonstrated that cancerous cells were killed in the sample. The synthesized sample can be used as a toxic material for cancer therapy.

Keywords: MWNT-COOH, functionalization, phenylisocyanate, phenylisothiocyanate, 1, 4-phenylendiamine, toxicity investigation

Procedia PDF Downloads 439

Authors: Pitcheswara Rao Nelapati

Abstract:

In the process of conveying the information there may be a chance of signal being corrupted which leads to the erroneous bits in the message. The message may consist of single, double and multiple bit errors. In high-reliability applications, memory can sustain multiple soft errors due to single or multiple event upsets caused by environmental factors. The traditional hamming code with SEC-DED capability cannot be address these types of errors. It is possible to use powerful non-binary BCH code such as Reed-Solomon code to address multiple errors. However, it could take at least a couple dozen cycles of latency to complete first correction and run at a relatively slow speed. In order to overcome this drawback i.e., to increase speed and latency we are using reed-Muller code.

Keywords: SEC-DED, BCH code, Reed-Solomon code, Reed-Muller code

Procedia PDF Downloads 419

Authors: Stanle Madonsela

Abstract:

For learning to take place effectively, learners have to use language. Language becomes a critical tool by which to communicate, to express feelings, desires and thoughts, and most of all to learn. However, each individual’s capacity to use language is unique. In multilingual countries, classrooms usually comprise learners from different language backgrounds, and therefore the language used for teaching and learning requires rethinking. Interaction in the classroom, if done in a language that is understood by the learners, could maximise the outcomes of learning. This paper explores the extent to which the use of a single code becomes a source of anxiety to learners in multilingual classrooms in South African schools. It contends that a multilingual approach in the learning process should be explored in order to promote learner autonomy in the learning process.

Keywords: anxiety, classroom, foreign language teaching, multilingual

Procedia PDF Downloads 523

Authors: Rachid Ziteuni, Selt Omar

Abstract:

In this paper, we propose a new polynomial metaheuristic elaboration (tabu search) for solving scheduling problems. This method allows us to solve the scheduling problem of n tasks on m identical parallel machines with unavailability periods. This problem is NP-complete in the strong sens and finding an optimal solution appears unlikely. Note that all data in this problem are integer and deterministic. The performance criterion to optimize in this problem which we denote Pm/N-c/summs of (wjCj) is the weighted sum of the end dates of tasks.

Keywords: scheduling, parallel identical machines, unavailability periods, metaheuristic, tabu search

Procedia PDF Downloads 321

Authors: Azita Ramezani, Ghazal Mashhadiagha, Bahareh Sanabakhsh

Abstract:

This study researches the combination of Random. Forest classifiers with large language models (LLMs) and natural language processing (NLP) to improve diagnostic accuracy in chest X-ray analysis using the Indiana University dataset. Utilizing advanced NLP techniques, the research preprocesses textual data from radiological reports to extract key features, which are then merged with image-derived data. This improved dataset is analyzed with Random Forest classifiers to predict specific clinical results, focusing on the identification of health issues and the estimation of case urgency. The findings reveal that the combination of NLP, LLMs, and machine learning not only increases diagnostic precision but also reliability, especially in quickly identifying critical conditions. Achieving an accuracy of 99.35%, the model shows significant advancements over conventional diagnostic techniques. The results emphasize the large potential of machine learning in medical imaging, suggesting that these technologies could greatly enhance clinician judgment and patient outcomes by offering quicker and more precise diagnostic approximations.

Keywords: natural language processing (NLP), large language models (LLMs), random forest classifier, chest x-ray analysis, medical imaging, diagnostic accuracy, indiana university dataset, machine learning in healthcare, predictive modeling, clinical decision support systems

Procedia PDF Downloads 32