Search results for: robust process

Authors: M. Ouassaf, S. Belaidi

Abstract:

Aromatase is an estrogen biosynthetic enzyme belonging to the cytochrome P450 family, which catalyzes the limiting step in the conversion of androgens to estrogens. As it is relevant for the promotion of tumor cell growth. A set of thirty 1,2,3-triazole derivatives was used in the quantitative structure activity relationship (QSAR) study using regression multiple linear (MLR), We divided the data into two training and testing groups. The results showed a good predictive ability of the MLR model, the models were statistically robust internally (R² = 0.982) and the predictability of the model was tested by several parameters. including external criteria (R²pred = 0.851, CCC = 0.946). The knowledge gained in this study should provide relevant information that contributes to the origins of aromatase inhibitory activity and, therefore, facilitates our ongoing quest for aromatase inhibitors with robust properties.

Keywords: aromatase inhibitors, QSAR, MLR, 1, 2, 3-triazole

Procedia PDF Downloads 83

Authors: Vedat Senol, Gursoy Turan, Anders Helmersson, Vortechz Andersson

Abstract:

In developing a mathematical model of a real structure, the simulation results of the model may not match the real structural response. This is a general problem that arises during dynamic motion of the structure, which may be modeled by means of parameter variations in the stiffness, damping, and mass matrices. These changes in parameters need to be estimated, and the mathematical model is updated to obtain higher control performances and robustness. In this study, a linear fractional transformation (LFT) is utilized for uncertainty modeling. Further, a general approach to the design of an H∞ control of a magneto-rheological damper (MRD) for vibration reduction in a building with mass, damping, and stiffness uncertainties is presented.

Keywords: uncertainty modeling, structural control, MR Damper, H∞, robust control

Procedia PDF Downloads 113

Authors: Ibrahim Isa Ali (Pantami), Abdu Jaafaru Bambale, Abimbola Alale, Danjuma Ibrahim Ndihgihdah, Muhammad Alkali, Adamu Idris Umar, Samson Olufunmilayo Abodunrin, Muhammad Dokko Zubairu, Moshood Kareem

Abstract:

This paper discusses the consideration and trade-offs used for the implementation of robust systems for orbit stability; Telemetry, Command and Ranging (TC& R) for Nigcomsat-1R and applicability for planned NigComSat-2 satellites. NigComSat-1R satellite was built by China Academy of Space Technology (CAST). The Satellite designed with quad-band payload (L, C, Ku, and Ka) was launched on the 20th of December 2011. The functionality of all satellite is driven by robust systems including Attitude & Orbit Control System (AOCS) and TC&R. The planned Nigcomsat-2 is a high throughput Satellite expected to function with better AOCS and TC&R.

Keywords: AOCS, CAST, Nigcomsat-1R, TC&R

Procedia PDF Downloads 69

Authors: Peifei Zhu, Zisheng Li, Yasuki Kakishita, Mayumi Suzuki, Tomoaki Chono

Abstract:

Segmentation of left ventricle (LV) from cardiac ultrasound images provides a quantitative functional analysis of the heart to diagnose disease. Active Shape Model (ASM) is a widely used approach for LV segmentation but suffers from the drawback that initialization of the shape model is not sufficiently close to the target, especially when dealing with abnormal shapes in disease. In this work, a two-step framework is proposed to improve the accuracy and speed of the model-based segmentation. Firstly, a robust and efficient detector based on Hough forest is proposed to localize cardiac feature points, and such points are used to predict the initial fitting of the LV shape model. Secondly, to achieve more accurate and detailed segmentation, ASM is applied to further fit the LV shape model to the cardiac ultrasound image. The performance of the proposed method is evaluated on a dataset of 800 cardiac ultrasound images that are mostly of abnormal shapes. The proposed method is compared to several combinations of ASM and existing initialization methods. The experiment results demonstrate that the accuracy of feature point detection for initialization was improved by 40% compared to the existing methods. Moreover, the proposed method significantly reduces the number of necessary ASM fitting loops, thus speeding up the whole segmentation process. Therefore, the proposed method is able to achieve more accurate and efficient segmentation results and is applicable to unusual shapes of heart with cardiac diseases, such as left atrial enlargement.

Keywords: hough forest, active shape model, segmentation, cardiac left ventricle

Procedia PDF Downloads 312

Authors: Di Han, Lingfeng Li

Abstract:

Selection of low-temperature separation dehydration and dehydrochlorination process applicable to skid design, using Hysys software to simulate the low-temperature separation dehydration and dehydrochlorination process under different refrigeration modes, focusing on comparing the refrigeration effect of different refrigeration modes, the condensation amount of hydrocarbon liquids and alcoholic wastewater, as well as the adaptability of the process, and determining the low-temperature separation process applicable to the natural gas dehydration and dehydrochlorination skid into the design of skid; and finally, to carry out the CNG recycling process calculations of the processed qualified natural gas and to determine the dehydration scheme and the key parameters of the compression process.

Keywords: skidding, dehydration and dehydrochlorination, cryogenic separation process, CNG recovery process calculations

Procedia PDF Downloads 107

Authors: Faisal Zaman, Ya Ping Wong, Boon Yian Ng

Abstract:

Point cloud source data for surface reconstruction is usually contaminated with noise and outliers. To overcome this, we present a novel approach using modified kernel density estimation (KDE) technique with bilateral filtering to remove noisy points and outliers. First we present a method for estimating optimal bandwidth of multivariate KDE using particle swarm optimization technique which ensures the robust performance of density estimation. Then we use mean-shift algorithm to find the local maxima of the density estimation which gives the centroid of the clusters. Then we compute the distance of a certain point from the centroid. Points belong to outliers then removed by automatic thresholding scheme which yields an accurate and economical point surface. The experimental results show that our approach comparably robust and efficient.

Keywords: point preprocessing, outlier removal, surface reconstruction, kernel density estimation

Procedia PDF Downloads 303

Authors: Troels Bo Jørgensen, Preben Hagh Strunge Holm, Henrik Gordon Petersen, Norbert Kruger

Abstract:

This paper presents a simulation framework for using machine learning techniques to determine robust robotic motions for handling deformable objects. The main focus is on applications in the meat sector, which mainly handle three-dimensional objects. In order to optimize the robotic handling, the robot motions have been parameterized in terms of grasp points, robot trajectory and robot speed. The motions are evaluated based on a dynamic simulation environment for robotic control of deformable objects. The evaluation indicates certain parameter setups, which produce robust motions in the simulated environment, and based on a visual analysis indicate satisfactory solutions for a real world system.

Keywords: deformable objects, robotic manipulation, simulation, real world system

Procedia PDF Downloads 254

Authors: Martin Bugeja, Helen Spiropolos

Abstract:

Using a sample of U.S. firms during the period 1993-2015, this study examines whether mergers and acquisitions (M&A) impact the compensation of the Chief Financial Officer (CFO) in the bidding and integration phases of M&As. The study finds that after controlling for CEO power, CFOs’ total compensation is higher during M&A years and is driven by higher equity incentives. These results are robust to controlling for self-selection. Furthermore, CFOs receive a greater bonus during the year of acquisition and the year prior. The study also investigates if CFO compensation during M&A years is driven by M&A characteristics and finds that deal size and diversification are positively related to total compensation while completion time is negatively related. The results are robust to a number of sensitivity tests and additional analyses.

Keywords: chief financial officer, compensation, mergers, acquisitions

Procedia PDF Downloads 23

Authors: M. S. Annie Christi

Abstract:

Transportation Problem (TP) is based on supply and demand of commodities transported from one source to the different destinations. Usual methods for finding solution of TPs are North-West Corner Rule, Least Cost Method Vogel’s Approximation Method etc. The transportation costs tend to vary at each time. We can use fuzzy numbers which would give solution according to this situation. In this study the Best Candidate Method (BCM) is applied. For ranking Centroid Ranking Technique (CRT) and Robust Ranking Technique have been adopted to transform the fuzzy TP and the above methods are applied to EDWARDS Vacuum Company, Crawley, in West Sussex in the United Kingdom. A Comparative study is also given. We see that the transportation cost can be minimized by the application of CRT under BCM.

Keywords: best candidate method, centroid ranking technique, fuzzy transportation problem, robust ranking technique, transportation problem

Procedia PDF Downloads 256

Authors: Seyed Hamed Hashemi Sohi, Gerald Jo Denoga

Abstract:

Machining or metal cutting is one of the most widely used production processes in industry. The quality of the process and the resulting machined product depends on parameters like tool geometry, material, and cutting conditions. However, the relationships of these parameters to the cutting process are often based mostly on empirical knowledge. In this study, computer modeling and simulation using LS-DYNA software and a Smoothed Particle Hydrodynamic (SPH) methodology, was performed on the orthogonal metal cutting process to analyze three-dimensional deformation of AISI 1045 medium carbon steel during machining. The simulation was performed using the following constitutive models: the Power Law model, the Johnson-Cook model, and the Zerilli-Armstrong models (Z-A). The outcomes were compared against the simulated results obtained by Cenk Kiliçaslan using the Finite Element Method (FEM) and the empirical results of Jaspers and Filice. The analysis shows that the SPH method combined with the Zerilli-Armstrong constitutive model is a viable alternative to simulating the metal cutting process. The tangential force was overestimated by 7%, and the normal force was underestimated by 16% when compared with empirical values. The simulation values for flow stress versus strain at various temperatures were also validated against empirical values. The SPH method using the Z-A model has also proven to be robust against issues of time-scaling. Experimental work was also done to investigate the effects of friction, rake angle and tool tip radius on the simulation.

Keywords: metal cutting, smoothed particle hydrodynamics, constitutive models, experimental, cutting forces analyses

Procedia PDF Downloads 234

Authors: K. Shoylekova, K. Grigorova

Abstract:

The Petri nets are the first standard for business process modeling. Most probably, it is one of the core reasons why all new standards created afterwards have to be so reformed as to reach the stage of mapping the new standard onto Petri nets. The paper presents a Business process repository based on a universal database. The repository provides the possibility the data about a given process to be stored in three different ways. Business process repository is developed with regard to the reformation of a given model to a Petri net in order to be easily simulated two different techniques for business process simulation based on Petri nets - Yasper and Woflan are discussed. Their advantages and drawbacks are outlined. The way of simulating business process models, stored in the Business process repository is shown.

Keywords: business process repository, petri nets, simulation, Woflan, Yasper

Procedia PDF Downloads 335

Authors: S. Bangphan, P. Bangphan, T.Boonkang

Abstract:

Quality control helps industries in improvements of its product quality and productivity. Statistical Process Control (SPC) is one of the tools to control the quality of products that turning practice in bringing a department of industrial engineering process under control. In this research, the process control of a turning manufactured at workshops machines. The varying measurements have been recorded for a number of samples of a rice polished cylinder obtained from a number of trials with the turning practice. SPC technique has been adopted by the process is finally brought under control and process capability is improved.

Keywords: rice polished cylinder, statistical process control, control charts, process capability

Procedia PDF Downloads 463

Authors: J. Ritonja, R. Brezovnik, M. Petrun, B. Polajžer

Abstract:

Many modern synchronous generators in power systems are extremely weakly damped. The reasons are cost optimization of the machine building and introduction of the additional control equipment into power systems. Oscillations of the synchronous generators and related stability problems of the power systems are harmful and can lead to failures in operation and to damages. The only useful solution to increase damping of the unwanted oscillations represents the implementation of the power system stabilizers. Power system stabilizers generate the additional control signal which changes synchronous generator field excitation voltage. Modern power system stabilizers are integrated into static excitation systems of the synchronous generators. Available commercial power system stabilizers are based on linear control theory. Due to the nonlinear dynamics of the synchronous generator, current stabilizers do not assure optimal damping of the synchronous generator’s oscillations in the entire operating range. For that reason the use of the robust power system stabilizers which are convenient for the entire operating range is reasonable. There are numerous robust techniques applicable for the power system stabilizers. In this paper the use of sliding mode control for synchronous generator stability improvement is studied. On the basis of the sliding mode theory, the robust power system stabilizer was developed. The main advantages of the sliding mode controller are simple realization of the control algorithm, robustness to parameter variations and elimination of disturbances. The advantage of the proposed sliding mode controller against conventional linear controller was tested for damping of the synchronous generator oscillations in the entire operating range. Obtained results show the improved damping in the entire operating range of the synchronous generator and the increase of the power system stability. The proposed study contributes to the progress in the development of the advanced stabilizer, which will replace conventional linear stabilizers and improve damping of the synchronous generators.

Keywords: control theory, power system stabilizer, robust control, sliding mode control, stability, synchronous generator

Procedia PDF Downloads 197

Authors: Ali Akbar Attari, Ali Asghar Beheshti Shirazi

Abstract:

In this paper, we propose a blind and robust audio watermarking scheme based on spread spectrum in Discrete Wavelet Transform (DWT) domain. Watermarks are embedded in the low-frequency coefficients, which is less audible. The key idea is dividing the audio signal into small frames, and magnitude of the 6^th level of DWT approximation coefficients is modifying based upon the Direct Sequence Spread Spectrum (DSSS) technique. Also, the psychoacoustic model for enhancing in imperceptibility, as well as Savitsky-Golay filter for increasing accuracy in extraction, is used. The experimental results illustrate high robustness against most common attacks, i.e. Gaussian noise addition, Low pass filter, Resampling, Requantizing, MP3 compression, without significant perceptual distortion (ODG is higher than -1). The proposed scheme has about 83 bps data payload.

Keywords: audio watermarking, spread spectrum, discrete wavelet transform, psychoacoustic, Savitsky-Golay filter

Procedia PDF Downloads 170

Authors: Ljubica Milanović Glavan

Abstract:

Because of the increasing business pressures, companies must be adaptable and flexible in order to withstand them. Inadequate business processes and low level of business process orientation, that in its core accentuates business processes as opposed to business functions and focuses on process performance and customer satisfaction, hider the ability to adapt to changing environment. It has been shown in previous studies that the companies which have reached higher business process maturity level consistently outperform those that have not reached them. The aim of this paper is to provide a basic understanding of business process orientation concept and business process maturity model. Besides that the paper presents the state of business process orientation in Croatia that has been captured with a study conducted in 2013. Based on the results some practical implications and guidelines for managers are given.

Keywords: business process orientation, business process maturity, Croatia, maturity score

Procedia PDF Downloads 502

Authors: Arum Kingsley Chinedu, Ugwuowo Fidelis Ifeanyi, Oranye Henrietta Ebele

Abstract:

The Poisson regression model (PRM) is a nonlinear model that belongs to the exponential family of distribution. PRM is suitable for studying count variables using appropriate covariates and sometimes experiences the problem of multicollinearity in the explanatory variables and outliers on the response variable. This study aims to address the problem of multicollinearity and outliers jointly in a Poisson regression model. We developed an estimator called the robust modified jackknife PCKL parameter estimator by combining the principal component estimator, modified jackknife KL and transformed M-estimator estimator to address both problems in a PRM. The superiority conditions for this estimator were established, and the properties of the estimator were also derived. The estimator inherits the characteristics of the combined estimators, thereby making it efficient in addressing both problems. And will also be of immediate interest to the research community and advance this study in terms of novelty compared to other studies undertaken in this area. The performance of the estimator (robust modified jackknife PCKL) with other existing estimators was compared using mean squared error (MSE) as a performance evaluation criterion through a Monte Carlo simulation study and the use of real-life data. The results of the analytical study show that the estimator outperformed other existing estimators compared with by having the smallest MSE across all sample sizes, different levels of correlation, percentages of outliers and different numbers of explanatory variables.

Keywords: jackknife modified KL, outliers, multicollinearity, principal component, transformed M-estimator.

Procedia PDF Downloads 20

Authors: Mohammad Ehson Rangiha, Bill Karakostas

Abstract:

Social Business Process Management (SBPM) promises to overcome limitations of traditional BPM by allowing flexible process design and enactment through the involvement of users from a social community. This paper proposes a meta-model and architecture for socially driven business process management systems. It discusses the main facets of the architecture such as goal-based role assignment that combines social recommendations with user profile, and process recommendation, through a real example of a charity organization.

Keywords: business process management, goal-based modelling, process recommendation social collaboration, social BPM

Procedia PDF Downloads 463

Authors: Michael Zimba

Abstract:

A duplicated image region may be subjected to a number of attacks such as noise addition, compression, reflection, rotation, and scaling with the intention of either merely mating it to its targeted neighborhood or preventing its detection. In this paper, we present an effective and robust method of detecting duplicated regions inclusive of those affected by the various attacks. In order to reduce the dimension of the image, the proposed algorithm firstly performs discrete wavelet transform, DWT, of a suspicious image. However, unlike most existing copy move image forgery (CMIF) detection algorithms operating in the DWT domain which extract only the low frequency sub-band of the DWT of the suspicious image thereby leaving valuable information in the other three sub-bands, the proposed algorithm simultaneously extracts features from all the four sub-bands. The extracted features are not only more accurate representation of image regions but also robust to additive noise, JPEG compression, and affine transformation. Furthermore, principal component analysis-eigenvalue decomposition, PCA-EVD, is applied to reduce the dimension of the features. The extracted features are then sorted using the more computationally efficient Radix Sort algorithm. Finally, same affine transformation selection, SATS, a duplication verification method, is applied to detect duplicated regions. The proposed algorithm is not only fast but also more robust to attacks compared to the related CMIF detection algorithms. The experimental results show high detection rates.

Keywords: affine transformation, discrete wavelet transform, radix sort, SATS

Procedia PDF Downloads 198

Authors: Shalini Rankawat, Mansi Rankawat, Rahul Dubey, Mazad Zaveri

Abstract:

Physiological signals such as electrocardiogram (ECG) and arterial blood pressure (ABP) in the intensive care unit (ICU) are often seriously corrupted by noise, artifacts, and missing data, which lead to errors in the estimation of heart rate (HR) and incidences of false alarm from ICU monitors. Clinical support in ICU requires most reliable heart rate estimation. Cardiac activity, because of its relatively high electrical energy, may introduce artifacts in Electroencephalogram (EEG), Electrooculogram (EOG), and Electromyogram (EMG) recordings. This paper presents a robust heart rate estimation method by detection of R-peaks of ECG artifacts in EEG, EMG & EOG signals, using energy-based function and a novel Signal Quality Index (SQI) assessment technique. SQIs of physiological signals (EEG, EMG, & EOG) were obtained by correlation of nonlinear energy operator (teager energy) of these signals with either ECG or ABP signal. HR is estimated from ECG, ABP, EEG, EMG, and EOG signals from separate Kalman filter based upon individual SQIs. Data fusion of each HR estimate was then performed by weighing each estimate by the Kalman filters’ SQI modified innovations. The fused signal HR estimate is more accurate and robust than any of the individual HR estimate. This method was evaluated on MIMIC II data base of PhysioNet from bedside monitors of ICU patients. The method provides an accurate HR estimate even in the presence of noise and artifacts.

Keywords: ECG, ABP, EEG, EMG, EOG, ECG artifacts, Teager-Kaiser energy, heart rate, signal quality index, Kalman filter, data fusion

Procedia PDF Downloads 669

Authors: Sabri Arik

Abstract:

In this paper, we study the global asymptotic robust stability of delayed neural networks with norm-bounded uncertainties. By employing the Lyapunov stability theory and Homeomorphic mapping theorem, we derive some new types of sufficient conditions ensuring the existence, uniqueness and global asymptotic stability of the equilibrium point for the class of neural networks with discrete time delays under parameter uncertainties and with respect to continuous and slopebounded activation functions. An important aspect of our results is their low computational complexity as the reported results can be verified by checking some properties symmetric matrices associated with the uncertainty sets of network parameters. The obtained results are shown to be generalization of some of the previously published corresponding results. Some comparative numerical examples are also constructed to compare our results with some closely related existing literature results.

Keywords: neural networks, delayed systems, lyapunov functionals, stability analysis

Procedia PDF Downloads 498

Authors: Ahtesham Javaid, Costin S. Bildea

Abstract:

The design and plantwide control of an integrated plant where the endothermic 1,4-butanediol dehydrogenation and the exothermic furfural hydrogenation is simultaneously performed in a single reactor is studied. The reactions can be carried out in an adiabatic reactor using small hydrogen excess and with reduced parameter sensitivity. The plant is robust and flexible enough to allow different production rates of γ-butyrolactone and 2-methyl furan, keeping high product purities. Rigorous steady state and dynamic simulations performed in AspenPlus and AspenDynamics to support the conclusions.

Keywords: dehydrogenation and hydrogenation, reaction coupling, design and control, process integration

Procedia PDF Downloads 308

Authors: E. Lacasa, J. L. Santolaya, I. Millán

Abstract:

The progress toward sustainability implies maintaining and preferably improving both, human and ecosystem well-being, according to a triple bottom line that includes the environmental, economic and social dimensions. The life cycle assessment (LCA) is a method applicable to all production sectors that aims to quantify the environmental pressures and the benefits related to goods and services, as well as the trade-offs and the scope for improving areas of the production process. While using LCA to measure the environmental dimension of sustainability is widespread, similar approaches for the economic and the social dimensions still have limited application worldwide and there is a need for consistent and robust methods and indicators. This paper focuses on the milk production process and presents the analysis of the flows exchanged by an industrial installation through accounting all the energy and material inputs and the associated emissions and waste outputs at this stage of its life cycle. The functional unit is one litre of milk produced. Different metrics and indicators are used to assess the three dimensions of sustainability. Metrics considered useful to assess the production activities are the total water and energy consumptions and the milk production volume of each cow. The global warming, the value added and the working hours are indicators used to measure each sustainability dimension. The study is performed with two types of feeding of the cows, which includes a change in percentages of components as well. Nutritional composition of the milk obtained is almost kept. It is observed that environmental and social improvements involve high economic costs.

Keywords: milk production, sustainability, indicators, life cycle assessment

Procedia PDF Downloads 402

Authors: Wendy Ampadu, Ray Diezmos, Hassan Malik, Jeremy Hyslob

Abstract:

There are several technologies out there for use as high-level switches as part of a system for shutting down flow to a vessel. Given that the asphalt truck loading poses issues such as poor visibility, coating, condensation, and fumes, a solution that is robust enough to last in these conditions is often needed in industries. Furthermore, the design of the loading arm, rack, and process equipment should allow for the safety of workers. The objective of this report includes the redesign of structures for use at loading facilities and selecting an overflow technology protection from hot bitumen. The report is based on loading facilities at a Canadian bitumen production company. The engineering design approach was used to create multiple redesign concepts for the loading dock system. Research on overfill systems was also completed by surveying the existing market for technologies and securing quotes from over 20 Canadian and United States instrumentation companies. A final loading dock redesign and level transmitter for overfill protection solution were chosen.

Keywords: bitumen, reliability engineering, safety system, process safety management, asphalt, loading docks, tanker trucks

Procedia PDF Downloads 109

Authors: Thewodros K. Geberemariam

Abstract:

The rapid physical expansion of urbanization coupled with aging infrastructure presents a unique decision and management challenges for many big city municipalities. Cities must therefore upgrade and maintain the existing aging urban drainage infrastructure systems to keep up with the demands. Given the overall contribution of assets to municipal revenue and the importance of infrastructure to the success of a livable city, many municipalities are currently looking for a robust and smart urban drainage infrastructure asset management solution that combines management, financial, engineering and technical practices. This robust decision-making shall rely on sound, complete, current and relevant data that enables asset valuation, impairment testing, lifecycle modeling, and forecasting across the multiple asset portfolios. On this paper, predictive computational intelligence (CI) and multi-class machine learning (ML) coupled with online, offline, and historical record data that are collected from an array of multi-parameter sensors are used for the extraction of different operational and non-conforming patterns hidden in structured and unstructured data to determine and produce actionable insight on the current and future states of the network. This paper aims to improve the strategic decision-making process by identifying all possible alternatives; evaluate the risk of each alternative, and choose the alternative most likely to attain the required goal in a cost-effective manner using historical and near real-time urban drainage infrastructure data for urban drainage infrastructures assets that have previously not benefited from computational intelligence and machine learning advancements.

Keywords: computational intelligence, machine learning, urban drainage infrastructure, machine learning, classification, prediction, asset management space

Procedia PDF Downloads 116

Authors: A. Rahaf, S. Liyakathunsia

Abstract:

In today’s world, unprecedented operational pressure is faced by banks that test the efficiency, effectiveness, and agility of their business processes. In a typical banking process, a person’s authorization is usually based on his signature on most all of the transactions. Signature verification is considered as one of the highly significant information needed for any bank document processing. Banks usually use Signature Verification to authenticate the identity of individuals. In this paper, a business process model has been proposed in order to increase the quality of the verification process and to reduce time and needed resources. In order to understand the current process, a survey has been conducted and distributed among bank employees. After analyzing the survey, a process model has been created using Bizagi modeler which helps in simulating the process after assigning time and cost of it. The outcomes show that the automation of signature verification process is highly recommended for a banking business process.

Keywords: business process management, process modeling, quality, Signature Verification

Procedia PDF Downloads 390

Authors: Kannapha Amaruchkul

Abstract:

We formulate a dynamic overbooking model for a tour operator, in which most reservations contain at least two people. The cancellation rate and the timing of the cancellation may depend on the group size. We propose two overbooking policies, namely economic- and service-based. In an economic-based policy, we want to minimize the expected oversold and underused cost, whereas, in a service-based policy, we ensure that the probability of an oversold situation does not exceed the pre-specified threshold. To illustrate the applicability of our approach, we use tour package data in 2016-2018 from a tour operator in Thailand to build a data-driven robust optimization model, and we tested the proposed overbooking policy in 2019. We also compare the data-driven approach to the conventional approach of fitting data into a probability distribution.

Keywords: applied stochastic model, data-driven robust optimization, overbooking, revenue management, tour operator

Procedia PDF Downloads 103

Authors: Amit Verma, Simranjeet Kaur, Sandeep Kaur

Abstract:

Test Case Prioritization (TCP) has gained wide spread acceptance as it often results in good quality software free from defects. Due to the increase in rate of faults in software traditional techniques for prioritization results in increased cost and time. Main challenge in TCP is difficulty in manually validate the priorities of different test cases due to large size of test suites and no more emphasis are made to make the TCP process automate. The objective of this paper is to detect the priorities of different test cases using an artificial neural network which helps to predict the correct priorities with the help of back propagation algorithm. In our proposed work one such method is implemented in which priorities are assigned to different test cases based on their frequency. After assigning the priorities ANN predicts whether correct priority is assigned to every test case or not otherwise it generates the interrupt when wrong priority is assigned. In order to classify the different priority test cases classifiers are used. Proposed algorithm is very effective as it reduces the complexity with robust efficiency and makes the process automated to prioritize the test cases.

Keywords: test case prioritization, classification, artificial neural networks, TF-IDF

Procedia PDF Downloads 357

Authors: Nicolas Haber

Abstract:

The study addresses the design process of integrated product-service offerings as a measure of answering environmental sustainability concerns by replacing stand-alone physical artefacts with comprehensive solutions relying on functional results rather than conventional product sales. However, views regarding this transformation are dissimilar and differentiated: The study discusses the importance and requirements of product-service systems before analysing the theoretical studies accomplished in the extent of their design and development processes. Based on this, a framework, built on a design science approach, is proposed, where the distinct approaches from the literature are merged towards a unified structure serving as a generic methodology to designing product-service systems. Each stage of this model is then developed to present a holistic design proposal called the Functional Engineered Product-Service System (FEPSS) model. Product-service systems are portrayed as customisable solutions tailored to specific settings and defined circumstances. Moreover, the approaches adopted to guide the design process are diversified. A thorough analysis of the design strategies and development processes however, allowed the extraction of a design backbone, valid to varied situations and contexts whether they are product-oriented, use-oriented or result-oriented. The goal is to guide manufacturers towards an eased adoption of these integrated offerings, given their inherited environmental benefits, by proposing a robust all-purpose design process.

Keywords: functional product, integrated product-service offerings, product-service systems, sustainable design

Procedia PDF Downloads 264

Authors: Afrouz Yousefi, Mohtada Sadrzadeh

Abstract:

The widespread presence of poly- and perfluoroalkyl substances (PFAS) poses a significant concern due to their ability to accumulate in living organisms and their persistence in the environment, thanks to their robust carbon-fluorine (C-F) bonds, which require substantial energy to break (485 kJ/mol). The prevalence of toxic PFAS compounds can be highly detrimental to ecosystems, wildlife, and human health. Ongoing efforts are dedicated to investigating methods for fully breaking down and eliminating PFAS from the environment. Among the various techniques employed, advanced oxidation processes have shown promise in completely breaking down emerging contaminants in wastewater. However, the drawback lies in the relatively slow reaction rates of these processes and the substantial energy input required, which currently impedes their widespread commercial adoption. We developed a hybrid process, comprising electro-Fenton as an advanced oxidation process and membrane distillation, to simultaneously degrade organic PFAS pollutants and extract pure water from the mixture. In this study, environmentally persistent perfluorooctanoic acid (PFOA), as an emerging contaminant, was used to study the effectiveness of the electro-Fenton/membrane distillation hybrid system. The PFOA degradation studies were conducted in two modes: electro-Fenton and electro-Fenton coupled with membrane distillation. High-performance liquid chromatography with ultraviolet detection (HPLC-UV), ion-chromatography (measuring fluoride ion concentration), total organic carbon (TOC) decay, mineralization current efficiency (MCE), and specific energy consumption (SEC) were evaluated for a single EF and hybrid EF-MD processes. In contrast to a single EF reaction, TOC decay improved significantly in the EF-MD process. Overall, the MCE of hybrid processes surpassed 100% while it remained under 50% for a single EF reaction. Calculations of specific energy consumption (SEC) demonstrated a substantial decrease of nearly one-third in energy usage when integrating the EF reaction with the MD process.

Keywords: water treatment, PFAS, membrane distillation, electro-Fenton, advanced oxidation

Procedia PDF Downloads 27

Authors: Thang V. Kieu, Long P. Nguyen

Abstract:

Kernelized Correlation Filter (KCF) based trackers have gained a lot of attention recently because of their accuracy and fast calculation speed. However, this algorithm is not robust in cases where the object is lost by a sudden change of direction, being obscured or going out of view. In order to improve KCF performance in long-term tracking, this paper proposes an anomaly detection method for target loss warning by analyzing the response map of each frame, and a classification algorithm for reliable target re-locating mechanism by using Random fern. Being tested with Visual Tracker Benchmark and Visual Object Tracking datasets, the experimental results indicated that the precision and success rate of the proposed algorithm were 2.92 and 2.61 times higher than that of the original KCF algorithm, respectively. Moreover, the proposed tracker handles occlusion better than many state-of-the-art long-term tracking methods while running at 60 frames per second.

Keywords: correlation filter, long-term tracking, random fern, real-time tracking

Procedia PDF Downloads 111