Search results for: Markovian Decision Process based Adaptive Scheduling
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 15645

Search results for: Markovian Decision Process based Adaptive Scheduling

14655 Designing AI-Enabled Smart Maintenance Scheduler: Enhancing Object Reliability through Automated Management

Authors: Arun Prasad Jaganathan

Abstract:

In today's rapidly evolving technological landscape, the need for efficient and proactive maintenance management solutions has become increasingly evident across various industries. Traditional approaches often suffer from drawbacks such as reactive strategies, leading to potential downtime, increased costs, and decreased operational efficiency. In response to these challenges, this paper proposes an AI-enabled approach to object-based maintenance management aimed at enhancing reliability and efficiency. The paper contributes to the growing body of research on AI-driven maintenance management systems, highlighting the transformative impact of intelligent technologies on enhancing object reliability and operational efficiency.

Keywords: AI, machine learning, predictive maintenance, object-based maintenance, expert team scheduling.

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14654 Public Participation in Sustainable Urban Planning

Authors: M. P. Amado, C. V. Santos, E. B. Moura, V.G. Silva

Abstract:

Urban planning, in particular on protected landscape areas, demands an increasing role of public participation within the frame of the efficiency of sustainable planning process. The development of urban planning actions in Protected Landscape areas, as Sintra-Cascais Natural Park, should perform a methodological process that is structured over distinct sequential stages, providing the development of a continuous, interactive, integrated and participative planning. From the start of Malveira da Serra and Janes Plan process, several public participation actions were promoted, in order to involve the local agents, stakeholders and the population in the decision of specific local key issues and define the appropriate priorities within the goals and strategies previously settled. As a result, public participation encouraged an innovative process that guarantees the efficiency of sustainable urban planning and promotes a sustainable new way of living in community.

Keywords: Protected landscape areas, Public participation, Sustainable development, Sustainable planning, Urban planning.

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14653 Process-based Business Transformation through Services Computing

Authors: Sinnakkrishnan Perumal, Nitish Pandey

Abstract:

Business transformation initiatives are required by any organization to jump from its normal mode of operation to the one that is suitable for the change in the environment such as competitive pressures, regulatory requirements, changes in labor market, etc., or internal such as changes in strategy/vision, changes in the capability, change in the management, etc. Recent advances in information technology in automating the business processes have the potential to transform an organization to provide it with a sustained competitive advantage. Process constitutes the skeleton of a business. Thus, for a business to exist and compete well, it is essential for the skeleton to be robust and agile. This paper details “transformation" from a business perspective, methodologies to bring about an effective transformation, process-based transformation, and the role of services computing in this. Further, it details the benefits that could be achieved through services computing.

Keywords: Business Transformation, Services Oriented Architecture, Business Processes, Process-based Transformation.

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14652 The Multi-objective Optimization for the SLS Process Parameters Based on Analytic Hierarchy Process

Authors: Yang Laixia, Deng Jun, Li Dichen, Bai Yang

Abstract:

The forming process parameters of Selective Laser Sintering(SLS) directly affect the forming efficiency and forming quality. Therefore, to determine reasonable process parameters is particularly important. In this paper, the weight of each target of the forming quality and efficiency is firstly calculated with the Analytic Hierarchy Process. And then the size of each target is measured by orthogonal experiment. Finally, the sum of the product of each target with the weight is compared to the process parameters in each group and obtained the optimal molding process parameters.

Keywords: Analytic Hierarchy Process, Multi-objective optimization, Orthogonal test, Selective Laser Sintering

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14651 Multi-Agent Model for Automation of Business Process Management System Based on Service Oriented Architecture

Authors: Soe Winn, May Thwe Oo

Abstract:

Business process automation is an important task in an enterprise business environment software development. The requirements of processing acceleration and automation level of enterprises are inherently different from one organization to another. We present a methodology and system for automation of business process management system architecture by multi-agent collaboration based on SOA. Design layer processes are modeled in semantic markup language for web services application. At the core of our system is considering certain types of human tasks to their further automation across over multiple platform environments. An improved abnormality processing with model for automation of BPMS architecture by multi-agent collaboration based on SOA is introduced. Validating system for efficiency of process automation, an application for educational knowledge base instance would also be described.

Keywords: Business process management system, businessprocess automation, multi-agent collaboration, Service OrientedArchitecture, extensible service application

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14650 Multidimensional Compromise Programming Evaluation of Digital Commerce Websites

Authors: C. Ardil

Abstract:

Multidimensional compromise programming evaluation of digital commerce websites is essential not only to have recommendations for improvement, but also to make comparisons with global business competitors. This research provides a multidimensional decision making model that prioritizes the objective criteria weights of various commerce websites using multidimensional compromise solution. Evaluation of digital commerce website quality can be considered as a complex information system structure including qualitative and quantitative factors for a multicriteria decision making problem. The proposed multicriteria decision making approach mainly consists of three sequential steps for the selection problem. In the first step, three major different evaluation criteria are characterized for website ranking problem. In the second step, identified critical criteria are weighted using the standard deviation procedure. In the third step, the multidimensional compromise programming is applied to rank the digital commerce websites.

Keywords: Standard deviation, commerce website, website evaluation, multicriteria decision making, multicriteria compromise programming, website quality, multidimensional decision analysis.

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14649 Data Mining in Oral Medicine Using Decision Trees

Authors: Fahad Shahbaz Khan, Rao Muhammad Anwer, Olof Torgersson, Göran Falkman

Abstract:

Data mining has been used very frequently to extract hidden information from large databases. This paper suggests the use of decision trees for continuously extracting the clinical reasoning in the form of medical expert-s actions that is inherent in large number of EMRs (Electronic Medical records). In this way the extracted data could be used to teach students of oral medicine a number of orderly processes for dealing with patients who represent with different problems within the practice context over time.

Keywords: Data mining, Oral Medicine, Decision Trees, WEKA.

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14648 Design of Multiple Clouds Based Global Performance Evaluation Service Broker System

Authors: Dong-Jae Kang, Nam-Woo Kim, Duk-Joo Son, Sung-In Jung

Abstract:

According to dramatic growth of internet services, an easy and prompt service deployment has been important for internet service providers to successfully maintain time-to-market. Before global service deployment, they have to pay the big cost for service evaluation to make a decision of the proper system location, system scale, service delay and so on. But, intra-Lab evaluation tends to have big gaps in the measured data compared with the realistic situation, because it is very difficult to accurately expect the local service environment, network congestion, service delay, network bandwidth and other factors. Therefore, to resolve or ease the upper problems, we propose multiple cloud based GPES Broker system and use case that helps internet service providers to alleviate the above problems in beta release phase and to make a prompt decision for their service launching. By supporting more realistic and reliable evaluation information, the proposed GPES Broker system saves the service release cost and enables internet service provider to make a prompt decision about their service launching to various remote regions.

Keywords: GPES Broker system, Cloud Service Broker, Multiple Cloud, Global performance evaluation service (GPES), Service provisioning

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14647 Distributed Load Flow Analysis using Graph Theory

Authors: D. P. Sharma, A. Chaturvedi, G.Purohit , R.Shivarudraswamy

Abstract:

In today scenario, to meet enhanced demand imposed by domestic, commercial and industrial consumers, various operational & control activities of Radial Distribution Network (RDN) requires a focused attention. Irrespective of sub-domains research aspects of RDN like network reconfiguration, reactive power compensation and economic load scheduling etc, network performance parameters are usually estimated by an iterative process and is commonly known as load (power) flow algorithm. In this paper, a simple mechanism is presented to implement the load flow analysis (LFA) algorithm. The reported algorithm utilizes graph theory principles and is tested on a 69- bus RDN.

Keywords: Radial Distribution network, Graph, Load-flow, Array.

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14646 Sustainable Intensification of Agriculture in Victoria’s Food Bowl: Optimizing Productivity with the use of Decision-Support Tools

Authors: M. Johnson, R. Faggian, V. Sposito

Abstract:

A participatory and engaged approach is key in connecting agricultural managers to sustainable agricultural systems to support and optimize production in Victoria’s food bowl. A sustainable intensification (SI) approach is well documented globally, but participation rates amongst Victorian farmers is fragmentary, and key outcomes and implementation strategies are poorly understood. Improvement in decision-support management tools and a greater understanding of the productivity gains available upon implementation of SI is necessary. This paper reviews the current understanding and uptake of SI practices amongst farmers in one of Victoria’s premier food producing regions, the Goulburn Broken; and it spatially analyses the potential for this region to adapt to climate change and optimize food production. A Geographical Information Systems (GIS) approach is taken to develop an interactive decision-support tool that can be accessible to on-ground agricultural managers. The tool encompasses multiple criteria analysis (MCA) that identifies factors during the construction phase of the tool, using expert witnesses and regional knowledge, framed within an Analytical Hierarchy Process. Given the complexities of the interrelations between each of the key outcomes, this participatory approach, in which local realities and factors inform the key outcomes and help to strategies for a particular region, results in a robust strategy for sustainably intensifying production in key food producing regions. The creation of an interactive, locally embedded, decision-support management and education tool can help to close the gap between farmer knowledge and production, increase on-farm adoption of sustainable farming strategies and techniques, and optimize farm productivity.

Keywords: Agriculture, decision-support management tools, GIS, sustainable intensification.

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14645 Simulation of a Control System for an Adaptive Suspension System for Passenger Vehicles

Authors: S. Gokul Prassad, S. Aakash, K. Malar Mohan

Abstract:

In the process to cope with the challenges faced by the automobile industry in providing ride comfort, the electronics and control systems play a vital role. The control systems in an automobile monitor various parameters, controls the performances of the systems, thereby providing better handling characteristics. The automobile suspension system is one of the main systems that ensure the safety, stability and comfort of the passengers. The system is solely responsible for the isolation of the entire automobile from harmful road vibrations. Thus, integration of the control systems in the automobile suspension system would enhance its performance. The diverse road conditions of India demand the need of an efficient suspension system which can provide optimum ride comfort in all road conditions. For any passenger vehicle, the design of the suspension system plays a very important role in assuring the ride comfort and handling characteristics. In recent years, the air suspension system is preferred over the conventional suspension systems to ensure ride comfort. In this article, the ride comfort of the adaptive suspension system is compared with that of the passive suspension system. The schema is created in MATLAB/Simulink environment. The system is controlled by a proportional integral differential controller. Tuning of the controller was done with the Particle Swarm Optimization (PSO) algorithm, since it suited the problem best. Ziegler-Nichols and Modified Ziegler-Nichols tuning methods were also tried and compared. Both the static responses and dynamic responses of the systems were calculated. Various random road profiles as per ISO 8608 standard are modelled in the MATLAB environment and their responses plotted. Open-loop and closed loop responses of the random roads, various bumps and pot holes are also plotted. The simulation results of the proposed design are compared with the available passive suspension system. The obtained results show that the proposed adaptive suspension system is efficient in controlling the maximum over shoot and the settling time of the system is reduced enormously.

Keywords: Automobile suspension, MATLAB, control system, PID, PSO.

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14644 Developing Structured Sizing Systems for Manufacturing Ready-Made Garments of Indian Females Using Decision Tree-Based Data Mining

Authors: Hina Kausher, Sangita Srivastava

Abstract:

In India, there is a lack of standard, systematic sizing approach for producing readymade garments. Garments manufacturing companies use their own created size tables by modifying international sizing charts of ready-made garments. The purpose of this study is to tabulate the anthropometric data which cover the variety of figure proportions in both height and girth. 3,000 data have been collected by an anthropometric survey undertaken over females between the ages of 16 to 80 years from the some states of India to produce the sizing system suitable for clothing manufacture and retailing. The data are used for the statistical analysis of body measurements, the formulation of sizing systems and body measurements tables. Factor analysis technique is used to filter the control body dimensions from the large number of variables. Decision tree-based data mining is used to cluster the data. The standard and structured sizing system can facilitate pattern grading and garment production. Moreover, it can exceed buying ratios and upgrade size allocations to retail segments.

Keywords: Anthropometric data, data mining, decision tree, garments manufacturing, ready-made garments, sizing systems.

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14643 Comparison between Associative Classification and Decision Tree for HCV Treatment Response Prediction

Authors: Enas M. F. El Houby, Marwa S. Hassan

Abstract:

Combined therapy using Interferon and Ribavirin is the standard treatment in patients with chronic hepatitis C. However, the number of responders to this treatment is low, whereas its cost and side effects are high. Therefore, there is a clear need to predict patient’s response to the treatment based on clinical information to protect the patients from the bad drawbacks, Intolerable side effects and waste of money. Different machine learning techniques have been developed to fulfill this purpose. From these techniques are Associative Classification (AC) and Decision Tree (DT). The aim of this research is to compare the performance of these two techniques in the prediction of virological response to the standard treatment of HCV from clinical information. 200 patients treated with Interferon and Ribavirin; were analyzed using AC and DT. 150 cases had been used to train the classifiers and 50 cases had been used to test the classifiers. The experiment results showed that the two techniques had given acceptable results however the best accuracy for the AC reached 92% whereas for DT reached 80%.

Keywords: Associative Classification, Data mining, Decision tree, HCV, interferon.

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14642 Performance Analysis of Artificial Neural Network with Decision Tree in Prediction of Diabetes Mellitus

Authors: J. K. Alhassan, B. Attah, S. Misra

Abstract:

Human beings have the ability to make logical decisions. Although human decision - making is often optimal, it is insufficient when huge amount of data is to be classified. Medical dataset is a vital ingredient used in predicting patient’s health condition. In other to have the best prediction, there calls for most suitable machine learning algorithms. This work compared the performance of Artificial Neural Network (ANN) and Decision Tree Algorithms (DTA) as regards to some performance metrics using diabetes data. WEKA software was used for the implementation of the algorithms. Multilayer Perceptron (MLP) and Radial Basis Function (RBF) were the two algorithms used for ANN, while RegTree and LADTree algorithms were the DTA models used. From the results obtained, DTA performed better than ANN. The Root Mean Squared Error (RMSE) of MLP is 0.3913 that of RBF is 0.3625, that of RepTree is 0.3174 and that of LADTree is 0.3206 respectively.

Keywords: Artificial neural network, classification, decision tree, diabetes mellitus.

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14641 Power Generation Scheduling of Thermal Units Considering Gas Pipelines Constraints

Authors: Sara Mohtashami, Habib Rajabi Mashhadi

Abstract:

With the growth of electricity generation from gas energy gas pipeline reliability can substantially impact the electric generation. A physical disruption to pipeline or to a compressor station can interrupt the flow of gas or reduce the pressure and lead to loss of multiple gas-fired electric generators, which could dramatically reduce the supplied power and threaten the power system security. Gas pressure drops during peak loading time on pipeline system, is a common problem in network with no enough transportation capacity which limits gas transportation and causes many problem for thermal domain power systems in supplying their demand. For a feasible generation scheduling planning in networks with no sufficient gas transportation capacity, it is required to consider gas pipeline constraints in solving the optimization problem and evaluate the impacts of gas consumption in power plants on gas pipelines operating condition. This paper studies about operating of gas fired power plants in critical conditions when the demand of gas and electricity peak together. An integrated model of gas and electric model is used to consider the gas pipeline constraints in the economic dispatch problem of gas-fueled thermal generator units.

Keywords:

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14640 Multiple Criteria Decision Making for Turkish Air Force Stealth Fighter Aircraft Selection

Authors: C. Ardil

Abstract:

Neutrosophic logic decision analysis is proposed as a method of stealth fighter aircraft selection for Turkish Air Force. The opinion of experts is employed to rank the alternatives across a set of criteria. The analyst uses neutrosophic logic numbers to describe the experts' preferences. This approach can handle the situation in the case of unavailability of precise data, which is most commonly the case in stealth fighter aircraft selection. Neutrosophic logic numbers can consider the imprecision of the factors affecting decision making such as stealth analysis, survivability analysis, and performance analysis. Neutrosophic logic ranking is achieved using weighted arithmetic operator and weighted geometric operator and the alternatives are ranked from best to worst. An example is also presented to illustrate the applicability and effectiveness of the proposed method. 

Keywords: Neutrosophic set theory, stealth fighter aircraft selection, multiple criteria decision-making, neutrosophic logic decision making, Turkish Air Force, MCDM

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14639 Computer-aided Lenke Classification of Scoliotic Spines

Authors: Neila Mezghani, Philippe Phan, Hubert Labelle, Carl Eric Aubin, Jacques de Guise

Abstract:

The identification and classification of the spine deformity play an important role when considering surgical planning for adolescent patients with idiopathic scoliosis. The subject of this article is the Lenke classification of scoliotic spines using Cobb angle measurements. The purpose is two-fold: (1) design a rulebased diagram to assist clinicians in the classification process and (2) investigate a computer classifier which improves the classification time and accuracy. The rule-based diagram efficiency was evaluated in a series of scoliotic classifications by 10 clinicians. The computer classifier was tested on a radiographic measurement database of 603 patients. Classification accuracy was 93% using the rule-based diagram and 99% for the computer classifier. Both the computer classifier and the rule based diagram can efficiently assist clinicians in their Lenke classification of spine scoliosis.

Keywords: Scoliosis, Lenke model, decision-rules, computer aided classifier.

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14638 Integrating Life Cycle Uncertainties for Evaluating a Building Overall Cost

Authors: M. Arja, G. Sauce, B. Souyri

Abstract:

Overall cost is a significant consideration in any decision-making process. Although many studies were carried out on overall cost in construction, little has treated the uncertainties of real life cycle development. On the basis of several case studies, a feedback process was performed on the historical data of studied buildings. This process enabled to identify some factors causing uncertainty during the operational period. As a result, the research proposes a new method for assessing the overall cost during a part of the building-s life cycle taking account of the building actual value, its end-of-life value and the influence of the identified life cycle uncertainty factors. The findings are a step towards a higher level of reliability in overall cost evaluation taking account of some usually unexpected uncertainty factors.

Keywords: Asset management, building life cycle uncertainty, building value, overall cost.

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14637 Physical Activity and Cognitive Functioning Relationship in Children

Authors: Comfort Mokgothu

Abstract:

This study investigated the relation between processing information and fitness level of active (fit) and sedentary (unfit) children drawn from rural and urban areas in Botswana. It was hypothesized that fit children would display faster simple reaction time (SRT), choice reaction times (CRT) and movement times (SMT). 60, third grade children (7.0 – 9.0 years) were initially selected and based upon fitness testing, 45 participated in the study (15 each of fit urban, unfit urban, fit rural). All children completed anthropometric measures, skinfold testing and submaximal cycle ergometer testing. The cognitive testing included SRT, CRT, SMT and Choice Movement Time (CMT) and memory sequence length. Results indicated that the rural fit group exhibited faster SMT than the urban fit and unfit groups. For CRT, both fit groups were faster than the unfit group. Collectively, the study shows that the relationship that exists between physical fitness and cognitive function amongst the elderly can tentatively be extended to the pediatric population. Physical fitness could be a factor in the speed at which we process information, including decision making, even in children.

Keywords: Decision making, fitness, information processing, reaction time, cognition movement time.

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14636 Landslide Susceptibility Mapping: A Comparison between Logistic Regression and Multivariate Adaptive Regression Spline Models in the Municipality of Oudka, Northern of Morocco

Authors: S. Benchelha, H. C. Aoudjehane, M. Hakdaoui, R. El Hamdouni, H. Mansouri, T. Benchelha, M. Layelmam, M. Alaoui

Abstract:

The logistic regression (LR) and multivariate adaptive regression spline (MarSpline) are applied and verified for analysis of landslide susceptibility map in Oudka, Morocco, using geographical information system. From spatial database containing data such as landslide mapping, topography, soil, hydrology and lithology, the eight factors related to landslides such as elevation, slope, aspect, distance to streams, distance to road, distance to faults, lithology map and Normalized Difference Vegetation Index (NDVI) were calculated or extracted. Using these factors, landslide susceptibility indexes were calculated by the two mentioned methods. Before the calculation, this database was divided into two parts, the first for the formation of the model and the second for the validation. The results of the landslide susceptibility analysis were verified using success and prediction rates to evaluate the quality of these probabilistic models. The result of this verification was that the MarSpline model is the best model with a success rate (AUC = 0.963) and a prediction rate (AUC = 0.951) higher than the LR model (success rate AUC = 0.918, rate prediction AUC = 0.901).

Keywords: Landslide susceptibility mapping, regression logistic, multivariate adaptive regression spline, Oudka, Taounate, Morocco.

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14635 Software Engineering Interoperable Environment for University Process Workflow and Document Management

Authors: Bekim Fetaji, Majlinda Fetaji, Mirlinda Ebibi

Abstract:

The objective of the research was focused on the design, development and evaluation of a sustainable web based network system to be used as an interoperable environment for University process workflow and document management. In this manner the most of the process workflows in Universities can be entirely realized electronically and promote integrated University. Definition of the most used University process workflows enabled creating electronic workflows and their execution on standard workflow execution engines. Definition or reengineering of workflows provided increased work efficiency and helped in having standardized process through different faculties. The concept and the process definition as well as the solution applied as Case study are evaluated and findings are reported.

Keywords: design process workflows, workflow and documentmanagement, Business Process, software engineering

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14634 Biomechanics Analysis When Delivering Baby

Authors: Kristyanto B.

Abstract:

Plenty of analyses based on Biomechanics were carried out on many jobs in manufactures or services. Now Biomechanics analysis is being applied on mothers who are giving birth. The analysis conducted in terms of normal condition of the birth process without Gyn Bed (Obstetric Bed). The aim of analysis is to study whether it is risky or not when choosing the position of mother’s postures when delivering the baby. This investigation was applied on two positions that generally appear in common birth process. Results will show the analysis of both positions to support the birth process based on the Biomechanics analysis (Ergonomic approaches). 

Keywords: Biomechanics analysis, Birth process, Position of postures analysis, Ergonomic approaches.

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14633 "A Call for School Diversity": A Practical Response to the Supreme Court Decision on Race and American Schools

Authors: Nathaniel Bryan

Abstract:

American public schools should be the place that reflects America-s diverse society. The recent Supreme Court decision to discontinue the use of race as a factor in school admission policies has caused major setbacks in America-s effort to repair its racial divide, to improve public schools, and to provide opportunities for all people, regardless of race or creed. However, educators should not allow such legal decision to hinder their ability to teach children tolerance of others in schools and classrooms in America.

Keywords: Race, Supreme Court, injustice, racial quotas.

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14632 Strategic Investment in Infrastructure Development to Facilitate Economic Growth in the United States

Authors: Arkaprabha Bhattacharyya, Makarand Hastak

Abstract:

The COVID-19 pandemic is unprecedented in terms of its global reach and economic impacts. Historically, investment in infrastructure development projects has been touted to boost the economic growth of a nation. The State and Local governments responsible for delivering infrastructure assets work under tight budgets. Therefore, it is important to understand which infrastructure projects have the highest potential of boosting economic growth in the post-pandemic era. This paper presents relationships between infrastructure projects and economic growth. Statistical relationships between investment in different types of infrastructure projects (transit, water and wastewater, highways, power, manufacturing etc.) and indicators of economic growth are presented using historic data between 2002 and 2020 from the U.S. Census Bureau and U.S. Bureau of Economic Analysis (BEA). The outcome of the paper is the comparison of statistical correlations between investment in different types of infrastructure projects and indicators of economic growth. The comparison of the statistical correlations is useful in ranking the types of infrastructure projects based on their ability to influence economic prosperity. Therefore, investment in the infrastructures with the higher rank will have a better chance of boosting the economic growth. Once, the ranks are derived, they can be used by the decision-makers in infrastructure investment related decision-making process.

Keywords: Economic growth, infrastructure development, infrastructure projects, strategic investment.

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14631 A Normalization-based Robust Image Watermarking Scheme Using SVD and DCT

Authors: Say Wei Foo, Qi Dong

Abstract:

Digital watermarking is one of the techniques for copyright protection. In this paper, a normalization-based robust image watermarking scheme which encompasses singular value decomposition (SVD) and discrete cosine transform (DCT) techniques is proposed. For the proposed scheme, the host image is first normalized to a standard form and divided into non-overlapping image blocks. SVD is applied to each block. By concatenating the first singular values (SV) of adjacent blocks of the normalized image, a SV block is obtained. DCT is then carried out on the SV blocks to produce SVD-DCT blocks. A watermark bit is embedded in the highfrequency band of a SVD-DCT block by imposing a particular relationship between two pseudo-randomly selected DCT coefficients. An adaptive frequency mask is used to adjust local watermark embedding strength. Watermark extraction involves mainly the inverse process. The watermark extracting method is blind and efficient. Experimental results show that the quality degradation of watermarked image caused by the embedded watermark is visually transparent. Results also show that the proposed scheme is robust against various image processing operations and geometric attacks.

Keywords: Image watermarking, Image normalization, Singularvalue decomposition, Discrete cosine transform, Robustness.

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14630 An Adaptive Virtual Desktop Service in Cloud Computing Platform

Authors: Shuen-Tai Wang, Hsi-Ya Chang

Abstract:

Cloud computing is becoming more and more matured over the last few years and consequently the demands for better cloud services is increasing rapidly. One of the research topics to improve cloud services is the desktop computing in virtualized environment. This paper aims at the development of an adaptive virtual desktop service in cloud computing platform based on our previous research on the virtualization technology. We implement cloud virtual desktop and application software streaming technology that make it possible for providing Virtual Desktop as a Service (VDaaS). Given the development of remote desktop virtualization, it allows shifting the user’s desktop from the traditional PC environment to the cloud-enabled environment, which is stored on a remote virtual machine rather than locally. This proposed effort has the potential to positively provide an efficient, resilience and elastic environment for online cloud service. Users no longer need to burden the platform maintenances and drastically reduces the overall cost of hardware and software licenses. Moreover, this flexible remote desktop service represents the next significant step to the mobile workplace, and it lets users access their desktop environments from virtually anywhere.

Keywords: Cloud Computing, Virtualization, Virtual Desktop, VDaaS.

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14629 Multi-Modal Film Boiling Simulations on Adaptive Octree Grids

Authors: M. Wasy Akhtar

Abstract:

Multi-modal film boiling simulations are carried out on adaptive octree grids. The liquid-vapor interface is captured using the volume-of-fluid framework adjusted to account for exchanges of mass, momentum, and energy across the interface. Surface tension effects are included using a volumetric source term in the momentum equations. The phase change calculations are conducted based on the exact location and orientation of the interface; however, the source terms are calculated using the mixture variables to be consistent with the one field formulation used to represent the entire fluid domain. The numerical model on octree representation of the computational grid is first verified using test cases including advection tests in severely deforming velocity fields, gravity-based instabilities and bubble growth in uniformly superheated liquid under zero gravity. The model is then used to simulate both single and multi-modal film boiling simulations. The octree grid is dynamically adapted in order to maintain the highest grid resolution on the instability fronts using markers of interface location, volume fraction, and thermal gradients. The method thus provides an efficient platform to simulate fluid instabilities with or without phase change in the presence of body forces like gravity or shear layer instabilities.

Keywords: Boiling flows, dynamic octree grids, heat transfer, interface capturing, phase change.

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14628 Fuzzy Processing of Uncertain Data

Authors: Petr Morávek, Miloš Šeda

Abstract:

In practice, we often come across situations where it is necessary to make decisions based on incomplete or uncertain data. In control systems it may be due to the unknown exact mathematical model, or its excessive complexity (e.g. nonlinearity) when it is necessary to simplify it, respectively, to solve it using a rule base. In the case of databases, searching data we compare a similarity measure with of the requirements of the selection with stored data, where both the select query and the data itself may contain vague terms, for example in the form of linguistic qualifiers. In this paper, we focus on the processing of uncertain data in databases and demonstrate it on the example multi-criteria decision making in the selection of variants, specified by higher number of technical parameters.

Keywords: fuzzy logic, linguistic variable, multicriteria decision

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14627 Optimizing Dialogue Strategy Learning Using Learning Automata

Authors: G. Kumaravelan, R. Sivakumar

Abstract:

Modeling the behavior of the dialogue management in the design of a spoken dialogue system using statistical methodologies is currently a growing research area. This paper presents a work on developing an adaptive learning approach to optimize dialogue strategy. At the core of our system is a method formalizing dialogue management as a sequential decision making under uncertainty whose underlying probabilistic structure has a Markov Chain. Researchers have mostly focused on model-free algorithms for automating the design of dialogue management using machine learning techniques such as reinforcement learning. But in model-free algorithms there exist a dilemma in engaging the type of exploration versus exploitation. Hence we present a model-based online policy learning algorithm using interconnected learning automata for optimizing dialogue strategy. The proposed algorithm is capable of deriving an optimal policy that prescribes what action should be taken in various states of conversation so as to maximize the expected total reward to attain the goal and incorporates good exploration and exploitation in its updates to improve the naturalness of humancomputer interaction. We test the proposed approach using the most sophisticated evaluation framework PARADISE for accessing to the railway information system.

Keywords: Dialogue management, Learning automata, Reinforcement learning, Spoken dialogue system

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14626 Soft-Sensor for Estimation of Gasoline Octane Number in Platforming Processes with Adaptive Neuro-Fuzzy Inference Systems (ANFIS)

Authors: Hamed.Vezvaei, Sepideh.Ordibeheshti, Mehdi.Ardjmand

Abstract:

Gasoline Octane Number is the standard measure of the anti-knock properties of a motor in platforming processes, that is one of the important unit operations for oil refineries and can be determined with online measurement or use CFR (Cooperative Fuel Research) engines. Online measurements of the Octane number can be done using direct octane number analyzers, that it is too expensive, so we have to find feasible analyzer, like ANFIS estimators. ANFIS is the systems that neural network incorporated in fuzzy systems, using data automatically by learning algorithms of NNs. ANFIS constructs an input-output mapping based both on human knowledge and on generated input-output data pairs. In this research, 31 industrial data sets are used (21 data for training and the rest of the data used for generalization). Results show that, according to this simulation, hybrid method training algorithm in ANFIS has good agreements between industrial data and simulated results.

Keywords: Adaptive Neuro-Fuzzy Inference Systems, GasolineOctane Number, Soft-sensor, Catalytic Naphtha Reforming

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