Search results for: integration model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 18580

Search results for: integration model

17860 Topographic Mapping of Farmland by Integration of Multiple Sensors on Board Low-Altitude Unmanned Aerial System

Authors: Mengmeng Du, Noboru Noguchi, Hiroshi Okamoto, Noriko Kobayashi

Abstract:

This paper introduced a topographic mapping system with time-saving and simplicity advantages based on integration of Light Detection and Ranging (LiDAR) data and Post Processing Kinematic Global Positioning System (PPK GPS) data. This topographic mapping system used a low-altitude Unmanned Aerial Vehicle (UAV) as a platform to conduct land survey in a low-cost, efficient, and totally autonomous manner. An experiment in a small-scale sugarcane farmland was conducted in Queensland, Australia. Subsequently, we synchronized LiDAR distance measurements that were corrected by using attitude information from gyroscope with PPK GPS coordinates for generation of precision topographic maps, which could be further utilized for such applications like precise land leveling and drainage management. The results indicated that LiDAR distance measurements and PPK GPS altitude reached good accuracy of less than 0.015 m.

Keywords: land survey, light detection and ranging, post processing kinematic global positioning system, precision agriculture, topographic map, unmanned aerial vehicle

Procedia PDF Downloads 229
17859 Model-Based Software Regression Test Suite Reduction

Authors: Shiwei Deng, Yang Bao

Abstract:

In this paper, we present a model-based regression test suite reducing approach that uses EFSM model dependence analysis and probability-driven greedy algorithm to reduce software regression test suites. The approach automatically identifies the difference between the original model and the modified model as a set of elementary model modifications. The EFSM dependence analysis is performed for each elementary modification to reduce the regression test suite, and then the probability-driven greedy algorithm is adopted to select the minimum set of test cases from the reduced regression test suite that cover all interaction patterns. Our initial experience shows that the approach may significantly reduce the size of regression test suites.

Keywords: dependence analysis, EFSM model, greedy algorithm, regression test

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17858 A Comparison Between Different Discretization Techniques for the Doyle-Fuller-Newman Li+ Battery Model

Authors: Davide Gotti, Milan Prodanovic, Sergio Pinilla, David Muñoz-Torrero

Abstract:

Since its proposal, the Doyle-Fuller-Newman (DFN) lithium-ion battery model has gained popularity in the electrochemical field. In fact, this model provides the user with theoretical support for designing the lithium-ion battery parameters, such as the material particle or the diffusion coefficient adjustment direction. However, the model is mathematically complex as it is composed of several partial differential equations (PDEs) such as Fick’s law of diffusion, the MacInnes and Ohm’s equations, among other phenomena. Thus, to efficiently use the model in a time-domain simulation environment, the selection of the discretization technique is of a pivotal importance. There are several numerical methods available in the literature that can be used to carry out this task. In this study, a comparison between the explicit Euler, Crank-Nicolson, and Chebyshev discretization methods is proposed. These three methods are compared in terms of accuracy, stability, and computational times. Firstly, the explicit Euler discretization technique is analyzed. This method is straightforward to implement and is computationally fast. In this work, the accuracy of the method and its stability properties are shown for the electrolyte diffusion partial differential equation. Subsequently, the Crank-Nicolson method is considered. It represents a combination of the implicit and explicit Euler methods that has the advantage of being of the second order in time and is intrinsically stable, thus overcoming the disadvantages of the simpler Euler explicit method. As shown in the full paper, the Crank-Nicolson method provides accurate results when applied to the DFN model. Its stability does not depend on the integration time step, thus it is feasible for both short- and long-term tests. This last remark is particularly important as this discretization technique would allow the user to implement parameter estimation and optimization techniques such as system or genetic parameter identification methods using this model. Finally, the Chebyshev discretization technique is implemented in the DFN model. This discretization method features swift convergence properties and, as other spectral methods used to solve differential equations, achieves the same accuracy with a smaller number of discretization nodes. However, as shown in the literature, these methods are not suitable for handling sharp gradients, which are common during the first instants of the charge and discharge phases of the battery. The numerical results obtained and presented in this study aim to provide the guidelines on how to select the adequate discretization technique for the DFN model according to the type of application to be performed, highlighting the pros and cons of the three methods. Specifically, the non-eligibility of the simple Euler method for longterm tests will be presented. Afterwards, the Crank-Nicolson and the Chebyshev discretization methods will be compared in terms of accuracy and computational times under a wide range of battery operating scenarios. These include both long-term simulations for aging tests, and short- and mid-term battery charge/discharge cycles, typically relevant in battery applications like grid primary frequency and inertia control and electrical vehicle breaking and acceleration.

Keywords: Doyle-Fuller-Newman battery model, partial differential equations, discretization, numerical methods

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17857 Dynamics of a Susceptible-Infected-Recovered Model along with Time Delay, Modulated Incidence, and Nonlinear Treatment

Authors: Abhishek Kumar, Nilam

Abstract:

As we know that, time delay exists almost in every biological phenomenon. Therefore, in the present study, we propose a susceptible–infected–recovered (SIR) epidemic model along with time delay, modulated incidence rate of infection, and Holling Type II nonlinear treatment rate. The present model aims to provide a strategy to control the spread of epidemics. In the mathematical study of the model, it has been shown that the model has two equilibriums which are named as disease-free equilibrium (DFE) and endemic equilibrium (EE). Further, stability analysis of the model is discussed. To prove the stability of the model at DFE, we derived basic reproduction number, denoted by (R₀). With the help of basic reproduction number (R₀), we showed that the model is locally asymptotically stable at DFE when the basic reproduction number (R₀) less than unity and unstable when the basic reproduction number (R₀) is greater than unity. Furthermore, stability analysis of the model at endemic equilibrium has also been discussed. Finally, numerical simulations have been done using MATLAB 2012b to exemplify the theoretical results.

Keywords: time delayed SIR epidemic model, modulated incidence rate, Holling type II nonlinear treatment rate, stability

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17856 Simulation of Flow through Dam Foundation by FEM and ANN Methods Case Study: Shahid Abbaspour Dam

Authors: Mehrdad Shahrbanozadeh, Gholam Abbas Barani, Saeed Shojaee

Abstract:

In this study, a finite element (Seep3D model) and an artificial neural network (ANN) model were developed to simulate flow through dam foundation. Seep3D model is capable of simulating three-dimensional flow through a heterogeneous and anisotropic, saturated and unsaturated porous media. Flow through the Shahid Abbaspour dam foundation has been used as a case study. The FEM with 24960 triangular elements and 28707 nodes applied to model flow through foundation of this dam. The FEM being made denser in the neighborhood of the curtain screen. The ANN model developed for Shahid Abbaspour dam is a feedforward four layer network employing the sigmoid function as an activator and the back-propagation algorithm for the network learning. The water level elevations of the upstream and downstream of the dam have been used as input variables and the piezometric heads as the target outputs in the ANN model. The two models are calibrated and verified using the Shahid Abbaspour’s dam piezometric data. Results of the models were compared with those measured by the piezometers which are in good agreement. The model results also revealed that the ANN model performed as good as and in some cases better than the FEM.

Keywords: seepage, dam foundation, finite element method, neural network, seep 3D model

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17855 A Mixed Integer Linear Programming Model for Flexible Job Shop Scheduling Problem

Authors: Mohsen Ziaee

Abstract:

In this paper, a mixed integer linear programming (MILP) model is presented to solve the flexible job shop scheduling problem (FJSP). This problem is one of the hardest combinatorial problems. The objective considered is the minimization of the makespan. The computational results of the proposed MILP model were compared with those of the best known mathematical model in the literature in terms of the computational time. The results show that our model has better performance with respect to all the considered performance measures including relative percentage deviation (RPD) value, number of constraints, and total number of variables. By this improved mathematical model, larger FJS problems can be optimally solved in reasonable time, and therefore, the model would be a better tool for the performance evaluation of the approximation algorithms developed for the problem.

Keywords: scheduling, flexible job shop, makespan, mixed integer linear programming

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17854 A New Prediction Model for Soil Compression Index

Authors: D. Mohammadzadeh S., J. Bolouri Bazaz

Abstract:

This paper presents a new prediction model for compression index of fine-grained soils using multi-gene genetic programming (MGGP) technique. The proposed model relates the soil compression index to its liquid limit, plastic limit and void ratio. Several laboratory test results for fine-grained were used to develop the models. Various criteria were considered to check the validity of the model. The parametric and sensitivity analyses were performed and discussed. The MGGP method was found to be very effective for predicting the soil compression index. A comparative study was further performed to prove the superiority of the MGGP model to the existing soft computing and traditional empirical equations.

Keywords: new prediction model, compression index soil, multi-gene genetic programming, MGGP

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17853 BTG-BIBA: A Flexibility-Enhanced Biba Model Using BTG Strategies for Operating System

Authors: Gang Liu, Can Wang, Runnan Zhang, Quan Wang, Huimin Song, Shaomin Ji

Abstract:

Biba model can protect information integrity but might deny various non-malicious access requests of the subjects, thereby decreasing the availability in the system. Therefore, a mechanism that allows exceptional access control is needed. Break the Glass (BTG) strategies refer an efficient means for extending the access rights of users in exceptional cases. These strategies help to prevent a system from stagnation. An approach is presented in this work for integrating Break the Glass strategies into the Biba model. This research proposes a model, BTG-Biba, which provides both an original Biba model used in normal situations and a mechanism used in emergency situations. The proposed model is context aware, can implement a fine-grained type of access control and primarily solves cross-domain access problems. Finally, the flexibility and availability improvement with the use of the proposed model is illustrated.

Keywords: Biba model, break the glass, context, cross-domain, fine-grained

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17852 Proposing a Strategic Management Maturity Model for Continues Innovation

Authors: Ferhat Demir

Abstract:

Even if strategic management is highly critical for all types of organizations, only a few maturity models have been proposed in business literature for the area of strategic management activities. This paper updates previous studies and presents a new conceptual model for assessing the maturity of strategic management in any organization. Strategic management maturity model (S-3M) is basically composed of 6 maturity levels with 7 dimensions. The biggest contribution of S-3M is to put innovation into agenda of strategic management. The main objective of this study is to propose a model to align innovation with business strategies. This paper suggests that innovation (breakthrough new products/services and business models) is the only way of creating sustainable growth and strategy studies cannot ignore this aspect. Maturity models should embrace innovation to respond dynamic business environment and rapidly changing customer behaviours.

Keywords: strategic management, innovation, business model, maturity model

Procedia PDF Downloads 188
17851 Integrated Mass Rapid Transit System for Smart City Project in Western India

Authors: Debasis Sarkar, Jatan Talati

Abstract:

This paper is an attempt to develop an Integrated Mass Rapid Transit System (MRTS) for a smart city project in Western India. Integrated transportation is one of the enablers of smart transportation for providing a seamless intercity as well as regional level transportation experience. The success of a smart city project at the city level for transportation is providing proper integration to different mass rapid transit modes by way of integrating information, physical, network of routes fares, etc. The methodology adopted for this study was primary data research through questionnaire survey. The respondents of the questionnaire survey have responded on the issues about their perceptions on the ways and means to improve public transport services in urban cities. The respondents were also required to identify the factors and attributes which might motivate more people to shift towards the public mode. Also, the respondents were questioned about the factors which they feel might restrain the integration of various modes of MRTS. Furthermore, this study also focuses on developing a utility equation for respondents with the help of multiple linear regression analysis and its probability to shift to public transport for certain factors listed in the questionnaire. It has been observed that for shifting to public transport, the most important factors that need to be considered were travel time saving and comfort rating. Also, an Integrated MRTS can be obtained by combining metro rail with BRTS, metro rail with monorail, monorail with BRTS and metro rail with Indian railways. Providing a common smart card to transport users for accessing all the different available modes would be a pragmatic solution towards integration of the available modes of MRTS.

Keywords: mass rapid transit systems, smart city, metro rail, bus rapid transit system, multiple linear regression, smart card, automated fare collection system

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17850 Comparison of Applicability of Time Series Forecasting Models VAR, ARCH and ARMA in Management Science: Study Based on Empirical Analysis of Time Series Techniques

Authors: Muhammad Tariq, Hammad Tahir, Fawwad Mahmood Butt

Abstract:

Purpose: This study attempts to examine the best forecasting methodologies in the time series. The time series forecasting models such as VAR, ARCH and the ARMA are considered for the analysis. Methodology: The Bench Marks or the parameters such as Adjusted R square, F-stats, Durban Watson, and Direction of the roots have been critically and empirically analyzed. The empirical analysis consists of time series data of Consumer Price Index and Closing Stock Price. Findings: The results show that the VAR model performed better in comparison to other models. Both the reliability and significance of VAR model is highly appreciable. In contrary to it, the ARCH model showed very poor results for forecasting. However, the results of ARMA model appeared double standards i.e. the AR roots showed that model is stationary and that of MA roots showed that the model is invertible. Therefore, the forecasting would remain doubtful if it made on the bases of ARMA model. It has been concluded that VAR model provides best forecasting results. Practical Implications: This paper provides empirical evidences for the application of time series forecasting model. This paper therefore provides the base for the application of best time series forecasting model.

Keywords: forecasting, time series, auto regression, ARCH, ARMA

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17849 Unlocking New Room of Production in Brown Field; ‎Integration of Geological Data Conditioned 3D Reservoir ‎Modelling of Lower Senonian Matulla Formation, RAS ‎Budran Field, East Central Gulf of Suez, Egypt

Authors: Nader Mohamed

Abstract:

The Late Cretaceous deposits are well developed through-out Egypt. This is due to a ‎transgression phase associated with the subsidence caused by the neo-Tethyan rift event that ‎took place across the northern margin of Africa, resulting in a period of dominantly marine ‎deposits in the Gulf of Suez. The Late Cretaceous Nezzazat Group represents the Cenomanian, ‎Turonian and clastic sediments of the Lower Senonian. The Nezzazat Group has been divided ‎into four formations namely, from base to top, the Raha Formation, the Abu Qada Formation, ‎the Wata Formation and the Matulla Formation. The Cenomanian Raha and the Lower Senonian ‎Matulla formations are the most important clastic sequence in the Nezzazat Group because they ‎provide the highest net reservoir thickness and the highest net/gross ratio. This study emphasis ‎on Matulla formation located in the eastern part of the Gulf of Suez. The three stratigraphic ‎surface sections (Wadi Sudr, Wadi Matulla and Gabal Nezzazat) which represent the exposed ‎Coniacian-Santonian sediments in Sinai are used for correlating Matulla sediments of Ras ‎Budran field. Cutting description, petrographic examination, log behaviors, biostratigraphy with ‎outcrops are used to identify the reservoir characteristics, lithology, facies environment logs and ‎subdivide the Matulla formation into three units. The lower unit is believed to be the main ‎reservoir where it consists mainly of sands with shale and sandy carbonates, while the other ‎units are mainly carbonate with some streaks of shale and sand. Reservoir modeling is an ‎effective technique that assists in reservoir management as decisions concerning development ‎and depletion of hydrocarbon reserves, So It was essential to model the Matulla reservoir as ‎accurately as possible in order to better evaluate, calculate the reserves and to determine the ‎most effective way of recovering as much of the petroleum economically as possible. All ‎available data on Matulla formation are used to build the reservoir structure model, lithofacies, ‎porosity, permeability and water saturation models which are the main parameters that describe ‎the reservoirs and provide information on effective evaluation of the need to develop the oil ‎potentiality of the reservoir. This study has shown the effectiveness of; 1) the integration of ‎geological data to evaluate and subdivide Matulla formation into three units. 2) Lithology and ‎facies environment interpretation which helped in defining the nature of deposition of Matulla ‎formation. 3) The 3D reservoir modeling technology as a tool for adequate understanding of the ‎spatial distribution of property and in addition evaluating the unlocked new reservoir areas of ‎Matulla formation which have to be drilled to investigate and exploit the un-drained oil. 4) This ‎study led to adding a new room of production and additional reserves to Ras Budran field. ‎

Keywords: geology, oil and gas, geoscience, sequence stratigraphy

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17848 Multiscale Simulation of Ink Seepage into Fibrous Structures through a Mesoscopic Variational Model

Authors: Athmane Bakhta, Sebastien Leclaire, David Vidal, Francois Bertrand, Mohamed Cheriet

Abstract:

This work presents a new three-dimensional variational model proposed for the simulation of ink seepage into paper sheets at the fiber level. The model, inspired by the Hising model, takes into account a finite volume of ink and describes the system state through gravity, cohesion, and adhesion force interactions. At the mesoscopic scale, the paper substrate is modeled using a discretized fiber structure generated using a numerical deposition procedure. A modified Monte Carlo method is introduced for the simulation of the ink dynamics. Besides, a multiphase lattice Boltzmann method is suggested to fine-tune the mesoscopic variational model parameters, and it is shown that the ink seepage behaviors predicted by the proposed model can resemble those predicted by a method relying on first principles.

Keywords: fibrous media, lattice Boltzmann, modelling and simulation, Monte Carlo, variational model

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17847 Segmentation of Piecewise Polynomial Regression Model by Using Reversible Jump MCMC Algorithm

Authors: Suparman

Abstract:

Piecewise polynomial regression model is very flexible model for modeling the data. If the piecewise polynomial regression model is matched against the data, its parameters are not generally known. This paper studies the parameter estimation problem of piecewise polynomial regression model. The method which is used to estimate the parameters of the piecewise polynomial regression model is Bayesian method. Unfortunately, the Bayes estimator cannot be found analytically. Reversible jump MCMC algorithm is proposed to solve this problem. Reversible jump MCMC algorithm generates the Markov chain that converges to the limit distribution of the posterior distribution of piecewise polynomial regression model parameter. The resulting Markov chain is used to calculate the Bayes estimator for the parameters of piecewise polynomial regression model.

Keywords: piecewise regression, bayesian, reversible jump MCMC, segmentation

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17846 Comparison of Sourcing Process in Supply Chain Operation References Model and Business Information Systems

Authors: Batuhan Kocaoglu

Abstract:

Although using powerful systems like ERP (Enterprise Resource Planning), companies still cannot benchmark their processes and measure their process performance easily based on predefined SCOR (Supply Chain Operation References) terms. The purpose of this research is to identify common and corresponding processes to present a conceptual model to model and measure the purchasing process of an organization. The main steps for the research study are: Literature review related to 'procure to pay' process in ERP system; Literature review related to 'sourcing' process in SCOR model; To develop a conceptual model integrating 'sourcing' of SCOR model and 'procure to pay' of ERP model. In this study, we examined the similarities and differences between these two models. The proposed framework is based on the assumptions that are drawn from (1) the body of literature, (2) the authors’ experience by working in the field of enterprise and logistics information systems. The modeling framework provides a structured and systematic way to model and decompose necessary information from conceptual representation to process element specification. This conceptual model will help the organizations to make quality purchasing system measurement instruments and tools. And offered adaptation issues for ERP systems and SCOR model will provide a more benchmarkable and worldwide standard business process.

Keywords: SCOR, ERP, procure to pay, sourcing, reference model

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17845 Improve Student Performance Prediction Using Majority Vote Ensemble Model for Higher Education

Authors: Wade Ghribi, Abdelmoty M. Ahmed, Ahmed Said Badawy, Belgacem Bouallegue

Abstract:

In higher education institutions, the most pressing priority is to improve student performance and retention. Large volumes of student data are used in Educational Data Mining techniques to find new hidden information from students' learning behavior, particularly to uncover the early symptom of at-risk pupils. On the other hand, data with noise, outliers, and irrelevant information may provide incorrect conclusions. By identifying features of students' data that have the potential to improve performance prediction results, comparing and identifying the most appropriate ensemble learning technique after preprocessing the data, and optimizing the hyperparameters, this paper aims to develop a reliable students' performance prediction model for Higher Education Institutions. Data was gathered from two different systems: a student information system and an e-learning system for undergraduate students in the College of Computer Science of a Saudi Arabian State University. The cases of 4413 students were used in this article. The process includes data collection, data integration, data preprocessing (such as cleaning, normalization, and transformation), feature selection, pattern extraction, and, finally, model optimization and assessment. Random Forest, Bagging, Stacking, Majority Vote, and two types of Boosting techniques, AdaBoost and XGBoost, are ensemble learning approaches, whereas Decision Tree, Support Vector Machine, and Artificial Neural Network are supervised learning techniques. Hyperparameters for ensemble learning systems will be fine-tuned to provide enhanced performance and optimal output. The findings imply that combining features of students' behavior from e-learning and students' information systems using Majority Vote produced better outcomes than the other ensemble techniques.

Keywords: educational data mining, student performance prediction, e-learning, classification, ensemble learning, higher education

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17844 Geographic Information System Cloud for Sustainable Digital Water Management: A Case Study

Authors: Mohamed H. Khalil

Abstract:

Water is one of the most crucial elements which influence human lives and development. Noteworthy, over the last few years, GIS plays a significant role in optimizing water management systems, especially after exponential developing in this sector. In this context, the Egyptian government initiated an advanced ‘GIS-Web Based System’. This system is efficiently designed to tangibly assist and optimize the complement and integration of data between departments of Call Center, Operation and Maintenance, and laboratory. The core of this system is a unified ‘Data Model’ for all the spatial and tabular data of the corresponding departments. The system is professionally built to provide advanced functionalities such as interactive data collection, dynamic monitoring, multi-user editing capabilities, enhancing data retrieval, integrated work-flow, different access levels, and correlative information record/track. Noteworthy, this cost-effective system contributes significantly not only in the completeness of the base-map (93%), the water network (87%) in high level of details GIS format, enhancement of the performance of the customer service, but also in reducing the operating costs/day-to-day operations (~ 5-10 %). In addition, the proposed system facilitates data exchange between different departments (Call Center, Operation and Maintenance, and laboratory), which allowed a better understanding/analyzing of complex situations. Furthermore, this system reflected tangibly on: (i) dynamic environmental monitor/water quality indicators (ammonia, turbidity, TDS, sulfate, iron, pH, etc.), (ii) improved effectiveness of the different water departments, (iii) efficient deep advanced analysis, (iv) advanced web-reporting tools (daily, weekly, monthly, quarterly, and annually), (v) tangible planning synthesizing spatial and tabular data; and finally, (vi) scalable decision support system. It is worth to highlight that the proposed future plan (second phase) of this system encompasses scalability will extend to include integration with departments of Billing and SCADA. This scalability will comprise advanced functionalities in association with the existing one to allow further sustainable contributions.

Keywords: GIS Web-Based, base-map, water network, decision support system

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17843 Integration of a Load Switch with DC/DC Buck Converter for Power Distribution in Low Cost Educational Nanosatellite

Authors: Bentoutou Houari, Boutte Aissa, Belaidi El Yazid, Limam Lakhdar

Abstract:

The integration of a load switch with a DC/DC buck converter using LM2596 for power distribution in low-cost educational nanosatellites is a technique that aims to efficiently manage the power distribution system in these small spacecraft. The converter is based on the LM2596 regulator and designed to step down the input voltage of +16.8V to +12V, +5V, and +3.3V output, which are suitable for the nanosatellite's various subsystems. The load switch is based on MOSFET and is used to turn on or off the power supply to a particular load and protect the nanosatellite from power surges. A prototype of a +12V DC/DC buck converter with a high side load switch has been realized and tested, which meets our requirements and shows a good efficiency of 89%. In addition, the prototype features a capacitor between the source and gate of the MOSFET, which has effectively reduced the inrush current, demonstrating the effectiveness of this approach in reducing surges of current when the load is connected. The output current and voltage were measured at 0.7A and 11.89V, respectively, making this design suitable for use in low-cost educational nanosatellites.

Keywords: DC/DC buck converter, load switch, LM2596, electrical power subsystems, nanosatellite, inrush current

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17842 Effect of Different Model Drugs on the Properties of Model Membranes from Fishes

Authors: M. Kumpugdee-Vollrath, T. G. D. Phu, M. Helmis

Abstract:

A suitable model membrane to study the pharmacological effect of pharmaceutical products is human stratum corneum because this layer of human skin is the outermost layer and it is an important barrier to be passed through. Other model membranes which were also used are for example skins from pig, mouse, reptile or fish. We are interested in fish skins in this project. The advantages of the fish skins are, that they can be obtained from the supermarket or fish shop. However, the fish skins should be freshly prepared and used directly without storage. In order to understand the effect of different model drugs e.g. lidocaine HCl, resveratrol, paracetamol, ibuprofen, acetyl salicylic acid on the properties of the model membrane from various types of fishes e.g. trout, salmon, cod, plaice permeation tests were performed and differential scanning calorimetry was applied.

Keywords: fish skin, model membrane, permeation, DSC, lidocaine HCl, resveratrol, paracetamol, ibuprofen, acetyl salicylic acid

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17841 Lyapunov Functions for Extended Ross Model

Authors: Rahele Mosleh

Abstract:

This paper gives a survey of results on global stability of extended Ross model for malaria by constructing some elegant Lyapunov functions for two cases of epidemic, including disease-free and endemic occasions. The model is a nonlinear seven-dimensional system of ordinary differential equations that simulates this phenomenon in a more realistic fashion. We discuss the existence of positive disease-free and endemic equilibrium points of the model. It is stated that extended Ross model possesses invariant solutions for human and mosquito in a specific domain of the system.

Keywords: global stability, invariant solutions, Lyapunov function, stationary points

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17840 Prediction of Seismic Damage Using Scalar Intensity Measures Based on Integration of Spectral Values

Authors: Konstantinos G. Kostinakis, Asimina M. Athanatopoulou

Abstract:

A key issue in seismic risk analysis within the context of Performance-Based Earthquake Engineering is the evaluation of the expected seismic damage of structures under a specific earthquake ground motion. The assessment of the seismic performance strongly depends on the choice of the seismic Intensity Measure (IM), which quantifies the characteristics of a ground motion that are important to the nonlinear structural response. Several conventional IMs of ground motion have been used to estimate their damage potential to structures. Yet, none of them has been proved to be able to predict adequately the seismic damage. Therefore, alternative, scalar intensity measures, which take into account not only ground motion characteristics but also structural information have been proposed. Some of these IMs are based on integration of spectral values over a range of periods, in an attempt to account for the information that the shape of the acceleration, velocity or displacement spectrum provides. The adequacy of a number of these IMs in predicting the structural damage of 3D R/C buildings is investigated in the present paper. The investigated IMs, some of which are structure specific and some are nonstructure-specific, are defined via integration of spectral values. To achieve this purpose three symmetric in plan R/C buildings are studied. The buildings are subjected to 59 bidirectional earthquake ground motions. The two horizontal accelerograms of each ground motion are applied along the structural axes. The response is determined by nonlinear time history analysis. The structural damage is expressed in terms of the maximum interstory drift as well as the overall structural damage index. The values of the aforementioned seismic damage measures are correlated with seven scalar ground motion IMs. The comparative assessment of the results revealed that the structure-specific IMs present higher correlation with the seismic damage of the three buildings. However, the adequacy of the IMs for estimation of the structural damage depends on the response parameter adopted. Furthermore, it was confirmed that the widely used spectral acceleration at the fundamental period of the structure is a good indicator of the expected earthquake damage level.

Keywords: damage measures, bidirectional excitation, spectral based IMs, R/C buildings

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17839 Tracy: A Java Library to Render a 3D Graphical Human Model

Authors: Sina Saadati, Mohammadreza Razzazi

Abstract:

Since Java is an object-oriented language, It can be used to solve a wide range of problems. One of the considerable usages of this language can be found in Agent-based modeling and simulation. Despite the significant power of Java, There is not an easy method to render a 3-dimensional human model. In this article, we are about to develop a library which helps modelers present a 3D human model and control it with Java. The library runs two server programs. The first one is a web page server that can connect to any browser and present an HTML code. The second server connects to the browser and controls the movement of the model. So, the modeler will be able to develop a simulation and display a good-looking human model without any knowledge of any graphical tools.

Keywords: agent-based modeling and simulation, human model, graphics, Java, distributed systems

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17838 Big Brain: A Single Database System for a Federated Data Warehouse Architecture

Authors: X. Gumara Rigol, I. Martínez de Apellaniz Anzuola, A. Garcia Serrano, A. Franzi Cros, O. Vidal Calbet, A. Al Maruf

Abstract:

Traditional federated architectures for data warehousing work well when corporations have existing regional data warehouses and there is a need to aggregate data at a global level. Schibsted Media Group has been maturing from a decentralised organisation into a more globalised one and needed to build both some of the regional data warehouses for some brands at the same time as the global one. In this paper, we present the architectural alternatives studied and why a custom federated approach was the notable recommendation to go further with the implementation. Although the data warehouses are logically federated, the implementation uses a single database system which presented many advantages like: cost reduction and improved data access to global users allowing consumers of the data to have a common data model for detailed analysis across different geographies and a flexible layer for local specific needs in the same place.

Keywords: data integration, data warehousing, federated architecture, Online Analytical Processing (OLAP)

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17837 Empowering Middle School Math Coordinators as Agents of Transformation: The Impact of the Mitar Program on Mathematical Literacy and Social-Emotional Learning Integration

Authors: Saleit Ron

Abstract:

The Mitar program was established to drive a shift in middle school mathematics education, emphasizing the connection of math to real-life situations, exploring mathematical modeling and literacy, and integrating social and emotional learning (SEL) components for enhanced excellence. The program envisions math coordinators as catalysts for change, equipping them to create educational materials, strengthen leadership skills, and develop SEL competencies within coordinator communities. These skills are then employed to lead transformative efforts within their respective schools. The program engaged 90 participants across six math coordinator communities during 2022-2023, involving 30-60 hours of annual learning. The process includes formative and summative evaluations through questionnaires and interviews, revealing participants' high contentment and successful integration of acquired skills into their schools. Reflections from participants highlighted the need for enhanced change leadership processes, often seeking more personalized mentoring to navigate challenges effectively.

Keywords: math coordinators, mathematical literacy, mathematical modeling, SEL competencies

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17836 Is Electricity Consumption Stationary in Turkey?

Authors: Eyup Dogan

Abstract:

The number of research articles analyzing the integration properties of energy variables has rapidly increased in the energy literature for about a decade. The stochastic behaviors of energy variables are worth knowing due to several reasons. For instance, national policies to conserve or promote energy consumption, which should be taken as shocks to energy consumption, will have transitory effects in energy consumption if energy consumption is found to be stationary in one country. Furthermore, it is also important to know the order of integration to employ an appropriate econometric model. Despite being an important subject for applied energy (economics) and having a huge volume of studies, several known limitations still exist with the existing literature. For example, many of the studies use aggregate energy consumption and national level data. In addition, a huge part of the literature is either multi-country studies or solely focusing on the U.S. This is the first study in the literature that considers a form of energy consumption by sectors at sub-national level. This research study aims at investigating unit root properties of electricity consumption for 12 regions of Turkey by four sectors in addition to total electricity consumption for the purpose of filling the mentioned limits in the literature. In this regard, we analyze stationarity properties of 60 cases . Because the use of multiple unit root tests make the results robust and consistent, we apply Dickey-Fuller unit root test based on Generalized Least Squares regression (DFGLS), Phillips-Perron unit root test (PP) and Zivot-Andrews unit root test with one endogenous structural break (ZA). The main finding of this study is that electricity consumption is trend stationary in 7 cases according to DFGLS and PP, whereas it is stationary process in 12 cases when we take into account the structural change by applying ZA. Thus, shocks to electricity consumption have transitory effects in those cases; namely, agriculture in region 1, region 4 and region 7, industrial in region 5, region 8, region 9, region 10 and region 11, business in region 4, region 7 and region 9, total electricity consumption in region 11. Regarding policy implications, policies to decrease or stimulate the use of electricity have a long-run impact on electricity consumption in 80% of cases in Turkey given that 48 cases are non-stationary process. On the other hand, the past behavior of electricity consumption can be used to predict the future behavior of that in 12 cases only.

Keywords: unit root, electricity consumption, sectoral data, subnational data

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17835 The Impact of Artificial Intelligence on Digital Factory

Authors: Mona Awad Wanis Gad

Abstract:

The method of factory making plans has changed loads, in particular, whilst it's miles approximately making plans the factory building itself. Factory making plans have the venture of designing merchandise, plants, tactics, organization, regions, and the construction of a factory. Ordinary restructuring is turning into greater essential for you to preserve the competitiveness of a manufacturing unit. Regulations in new regions, shorter lifestyle cycles of product and manufacturing era, in addition to a VUCA global (Volatility, Uncertainty, Complexity and Ambiguity) cause extra common restructuring measures inside a factory. A digital factory model is the planning foundation for rebuilding measures and turns into a critical device. Furthermore, digital building fashions are increasingly being utilized in factories to help facility management and manufacturing processes. First, exclusive styles of digital manufacturing unit fashions are investigated, and their residences and usabilities to be used instances are analyzed. Within the scope of research are point cloud fashions, building statistics fashions, photogrammetry fashions, and those enriched with sensor information are tested. It investigated which digital fashions permit a simple integration of sensor facts and in which the variations are. In the end, viable application areas of virtual manufacturing unit models are determined by a survey, and the respective digital manufacturing facility fashions are assigned to the application areas. Ultimately, an application case from upkeep is selected and implemented with the assistance of the best virtual factory version. It is shown how a completely digitalized preservation process can be supported by a digital manufacturing facility version by offering facts. Among different functions, the virtual manufacturing facility version is used for indoor navigation, facts provision, and display of sensor statistics. In summary, the paper suggests a structuring of virtual factory fashions that concentrates on the geometric representation of a manufacturing facility building and its technical facilities. A practical application case is proven and implemented. For that reason, the systematic selection of virtual manufacturing facility models with the corresponding utility cases is evaluated.

Keywords: augmented reality, digital factory model, factory planning, restructuring digital factory model, photogrammetry, factory planning, restructuring building information modeling, digital factory model, factory planning, maintenance

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17834 Knowledge Management as Tool for Environmental Management System Implementation in Higher Education Institutions

Authors: Natalia Marulanda Grisales

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The most significant changes in the characteristics of consumers have contributed to the development and adoption of methodologies and tools that enable organizations to be more competitive in the marketplace. One of these methodologies is the integration of Knowledge Management (KM) phases and Environmental Management Systems (EMS). This integration allows companies to manage and share the required knowledge for EMS adoption, from the place where it is generated to the place where it is going to be exploited. The aim of this paper is to identify the relationship between KM phases as a tool for the adoption of EMS in HEI. The methodology has a descriptive scope and a qualitative approach. It is based on a case study and a review of the literature about KM and EMS. We conducted 266 surveys to students, professors and staff at Minuto de Dios University (Colombia). Data derived from the study indicate that if a HEI wants to achieve an adequate knowledge acquisition and knowledge transfer, it must have clear goals for implementing an EMS. Also, HEI should create empowerment and training spaces for students, professors and staff. In the case study, HEI must generate alternatives that enhance spaces of knowledge appropriation. It was found that 85% of respondents have not received any training from HEI about EMS. 88% of respondents believe that the actions taken by the university are not efficient to knowledge transfer in order to develop an EMS.

Keywords: environmental management systems, higher education institutions, knowledge management, training

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17833 Gradient-Based Reliability Optimization of Integrated Energy Systems Under Extreme Weather Conditions: A Case Study in Ningbo, China

Authors: Da LI, Peng Xu

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Recent extreme weather events, such as the 2021 European floods and North American heatwaves, have exposed the vulnerability of energy systems to both extreme demand scenarios and potential physical damage. Current integrated energy system designs often overlook performance under these challenging conditions. This research, focusing on a regional integrated energy system in Ningbo, China, proposes a distinct design method to optimize system reliability during extreme events. A multi-scenario model was developed, encompassing various extreme load conditions and potential system damages caused by severe weather. Based on this model, a comprehensive reliability improvement scheme was designed, incorporating a gradient approach to address different levels of disaster severity through the integration of advanced technologies like distributed energy storage. The scheme's effectiveness was validated through Monte Carlo simulations. Results demonstrate significant enhancements in energy supply reliability and peak load reduction capability under extreme scenarios. The findings provide several insights for improving energy system adaptability in the face of climate-induced challenges, offering valuable references for building reliable energy infrastructure capable of withstanding both extreme demands and physical threats across a spectrum of disaster intensities.

Keywords: extreme weather events, integrated energy systems, reliability improvement, climate change adaptation

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17832 Implementing Building Information Modelling to Attain Lean and Green Benefits

Authors: Ritu Ahuja

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Globally the built environment sector is striving to be highly efficient, quality-centred and socially-responsible. Built environment sector is an integral part of the economy and plays an important role in urbanization, industrialization and improved quality of living. The inherent challenges such as excessive material and process waste, over reliance on resources, energy usage, and carbon footprint need to be addressed in order to meet the needs of the economy. It is envisioned that these challenges can be resolved by integration of Lean-Green-Building Information Modelling (BIM) paradigms. Ipso facto, with BIM as a catalyst, this research identifies the operational and tactical connections of lean and green philosophies by providing a conceptual integration framework and underpinning theories. The research has developed a framework for BIM-based organizational capabilities for enhanced adoption and effective use of BIM within architectural organizations. The study was conducted through a sequential mixed method approach focusing on collecting and analyzing both qualitative and quantitative data. The framework developed as part of this study will enable architectural organizations to successfully embrace BIM on projects and gain lean and green benefits.

Keywords: BIM, lean, green, AEC organizations

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17831 Integration of an Innovative Complementary Approach Inspired by Clinical Hypnosis into Oncology Care: Nurses’ Perception of Comfort Talk

Authors: Danny Hjeij, Karine Bilodeau, Caroline Arbour

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Background: Chemotherapy infusions often lead to a cluster of co-occurring and difficult-to-treat symptoms (nausea, tingling, etc.), which may negatively impact the treatment experience at the outpatient clinic. Although several complementary approaches have shown beneficial effects for chemotherapy-induced symptom management, they are not easily implementable during chemotherapy infusion. In response to this limitation, comfort talk (CT), a simple, fast conversational method inspired by the language principles of clinical hypnosis, is known to optimize the management of symptoms related to antineoplastic treatments. However, the perception of nurses who have had to integrate this practice into their care has never been documented. Study design: A qualitative descriptive study with iterative content analysis was conducted among oncology nurses working in a chemotherapy outpatient clinic who had previous experience with CT. Semi-structured interviews were conducted by phone, using a pre-tested interview guide and a sociodemographic survey to document their perception of CT. The conceptual framework. Results: A total of six nurses (4 women, 2 men) took part in the interviews (N=6). The average age of participants was 49 years (36-61 years). Participants had an average of 24 years of experience (10-38 years) as a nurse, including 14.5 years in oncology (5-32 years). Data saturation (i.e., redundancy of words) was observed around the fifth interview. A sixth interview was conducted as confirmation. Six themes emerged: two addressing contextual and organizational obstacles at the chemotherapy outpatient clinic, and three addressing the added value of CT for oncology nursing care. Specific themes included: 1) the outpatient oncology clinic, a saturated care setting, 2) the keystones that support the integration of CT into care, 3) added value for patients, 4) a positive and rewarding experience for nurses, 5) collateral benefits, and 6) CT an approach to consider during the COVID-19 pandemic. Conclusion: For the first time, this study describes nurses' perception of the integration of CT into the care surrounding the administration of chemotherapy at the outpatient oncology clinic. In summary, contextual and organizational difficulties, as well as the lack of training, are among the main obstacles that could hinder the integration of CT in oncology. Still, the experience was reported mostly as positive. Indeed, nurses saw HC as an added value to patient care and meeting their need for holistic care. HC also appears to be beneficial for patients on several levels (for pain management in particular). Results will be used to inform future knowledge transfer activities related to CT in oncology nursing.

Keywords: cancer, chemotherapy, comfort talk, oncology nursing role

Procedia PDF Downloads 78