Search results for: management model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9548

Search results for: management model

7628 Modified Techniques for Distribution System Reliability Improvement by Parallel Operation of Transformers

Authors: Ohn Zin Lin, Okka, Cho Cho Myint

Abstract:

It is important to consider the effects of transformers on distribution system because they have the highest impact on system reliability. It is generally said that parallel operation of transformers (POT) can improve the system reliability. However, the estimation approach can be also considered for accuracy. In this paper, we propose a three-state components model and equations to determine the reliability improvement by POT, and cooperation of POT and distributed generation (DG). Based on the proposed model and techniques, the effect of POT is analyzed in four different tests with the consideration of conventional distribution system, distribution automation system (DAS) and DG. According to the results, the reliability is greatly improved by cooperation of POT, DAS and DG. The proposed model and methods are applicable to not only developing countries which have conventional distribution system but also developed countries in which DAS has already installed.

Keywords: Distribution system, reliability, dispersed generator, energy not supply, transformer parallel operation.

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7627 Variability of Hydrological Modeling of the Blue Nile

Authors: Abeer Samy, Oliver C. Saavedra Valeriano, Abdelazim Negm

Abstract:

The Blue Nile Basin is the most important tributary of the Nile River. Egypt and Sudan are almost dependent on water originated from the Blue Nile. This multi-dependency creates conflicts among the three countries Egypt, Sudan, and Ethiopia making the management of these conflicts as an international issue. Good assessment of the water resources of the Blue Nile is an important to help in managing such conflicts. Hydrological models are good tool for such assessment. This paper presents a critical review of the nature and variability of the climate and hydrology of the Blue Nile Basin as a first step of using hydrological modeling to assess the water resources of the Blue Nile. Many several attempts are done to develop basin-scale hydrological modeling on the Blue Nile. Lumped and semi distributed models used averages of meteorological inputs and watershed characteristics in hydrological simulation, to analyze runoff for flood control and water resource management. Distributed models include the temporal and spatial variability of catchment conditions and meteorological inputs to allow better representation of the hydrological process. The main challenge of all used models was to assess the water resources of the basin is the shortage of the data needed for models calibration and validation. It is recommended to use distributed model for their higher accuracy to cope with the great variability and complexity of the Blue Nile basin and to collect sufficient data to have more sophisticated and accurate hydrological modeling.

Keywords: Blue Nile Basin, Climate Change, Hydrological Modeling, Watershed.

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7626 Evolved Bat Algorithm Based Adaptive Fuzzy Sliding Mode Control with LMI Criterion

Authors: P.-W. Tsai, C.-Y. Chen, C.-W. Chen

Abstract:

In this paper, the stability analysis of a GA-Based adaptive fuzzy sliding model controller for a nonlinear system is discussed. First, a nonlinear plant is well-approximated and described with a reference model and a fuzzy model, both involving FLC rules. Then, FLC rules and the consequent parameter are decided on via an Evolved Bat Algorithm (EBA). After this, we guarantee a new tracking performance inequality for the control system. The tracking problem is characterized to solve an eigenvalue problem (EVP). Next, an adaptive fuzzy sliding model controller (AFSMC) is proposed to stabilize the system so as to achieve good control performance. Lyapunov’s direct method can be used to ensure the stability of the nonlinear system. It is shown that the stability analysis can reduce nonlinear systems into a linear matrix inequality (LMI) problem. Finally, a numerical simulation is provided to demonstrate the control methodology.

Keywords: Adaptive fuzzy sliding mode control, Lyapunov direct method, swarm intelligence, evolved bat algorithm.

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7625 Passenger Seat Vibration Control of Quarter Car System with MR Shock Absorber

Authors: Devdutt, M. L. Aggarwal

Abstract:

Semi-active Fuzzy control of quarter car system having three degrees of freedom and assembled with magneto-rheological (MR) shock absorber is studied in present paper. First, experimental work was performed on an MR shock absorber under different excitation conditions to obtain force-displacement and force-velocity curves. Then, for the application of experimental data in semi-active quarter car system, a polynomial model was selected. Finally, Fuzzy logic controller was designed having the combination of Forward fuzzy controller and Inverse fuzzy controller for integration in secondary suspension system of concerned model. The proposed controlled quarter car model was compared with uncontrolled system using simulation work under bump type of road excitation. Results obtained by simulation work shows the effectiveness of fuzzy controlled suspension system in improving the ride comfort and safety of travelling passengers compared to uncontrolled suspension system.

Keywords: MR shock absorber, three degrees of freedom, quarter car model, fuzzy controller.

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7624 The Alliance for Grassland Renewal: A Model for Teaching Endophyte Technology

Authors: C. A. Roberts, J. G. Andrae, S. R. Smith, M. H. Poore, C. A. Young, D. W. Hancock, G. J. Pent

Abstract:

To the author’s best knowledge, there are no published reports of effective methods for teaching fescue toxicosis and grass endophyte technology in the USA. To address this need, a group of university scientists, industry representatives, government agents, and livestock producers formed an organization called the Alliance for Grassland Renewal. One goal of the Alliance was to develop a teaching method that could be employed across all regions in the USA and all sectors of the agricultural community. The first step in developing this method was identification of experts who were familiar with the science and management of fescue toxicosis. The second step was curriculum development. Experts wrote a curriculum that addressed all aspects of toxicosis and management, including toxicology, animal nutrition, pasture management, economics, and mycology. The curriculum was created for presentation in lectures, laboratories, and in the field. The curriculum was in that it could be delivered across state lines, regardless of peculiar, in-state recommendations. The curriculum was also unique as it was unanimously supported by private companies otherwise in competition with each other. The final step in developing this teaching method was formulating a delivery plan. All experts, including university, industry, government, and production, volunteered to travel from any state in the USA, converge in one location, teach a 1-day workshop, then travel to the next location. The results of this teaching method indicate widespread success. Since 2012, experts across the entire USA have converged to teach Alliance workshops in Kansas, Oklahoma, Missouri, Kentucky, Georgia, South Carolina, North Carolina, and Virginia, with ongoing workshops in Arkansas and Tennessee. Data from post-workshop surveys indicate that instruction has been effective, as at least 50% of the participants stated their intention to adopt the endophyte technology presented in these workshops. The teaching method developed by the Alliance for Grassland Renewal has proved to be effective, and the Alliance continues to expand across the USA.

Keywords: Endophyte, Epichloë coenophiala, ergot alkaloids, fescue toxicosis, tall fescue.

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7623 Digital Paradoxes in Learning Theories

Authors: Marcello Bettoni

Abstract:

As a learning theory tries to borrow from science a framework to found its method, it shows paradoxes and paralysing contraddictions. This results, on one hand, from adopting a learning/teaching model as it were a mere “transfer of data" (mechanical learning approach), and on the other hand from borrowing the complexity theory (an indeterministic and non-linear model), that risks to vanish every educational effort. This work is aimed at describing existing criticism, unveiling the antinomic nature of such paradoxes, focussing on a view where neither the mechanical learning perspective nor the chaotic and nonlinear model can threaten and jeopardize the educational work. Author intends to go back over the steps that led to these paradoxes and to unveil their antinomic nature. Actually this could serve the purpose to explain some current misunderstandings about the real usefulness of Ict within the youth-s learning process and growth.

Keywords: Antinomy, complexity, Leibniz, paradox

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7622 A Novel Hybrid Mobile Agent Based Distributed Intrusion Detection System

Authors: Amir Vahid Dastjerdi, Kamalrulnizam Abu Bakar

Abstract:

The first generation of Mobile Agents based Intrusion Detection System just had two components namely data collection and single centralized analyzer. The disadvantage of this type of intrusion detection is if connection to the analyzer fails, the entire system will become useless. In this work, we propose novel hybrid model for Mobile Agent based Distributed Intrusion Detection System to overcome the current problem. The proposed model has new features such as robustness, capability of detecting intrusion against the IDS itself and capability of updating itself to detect new pattern of intrusions. In addition, our proposed model is also capable of tackling some of the weaknesses of centralized Intrusion Detection System models.

Keywords: Distributed Intrusion Detection System, Mobile Agents, Network Security.

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7621 Defining a Semantic Web-based Framework for Enabling Automatic Reasoning on CIM-based Management Platforms

Authors: Fernando Alonso, Rafael Fernandez, Sonia Frutos, Javier Soriano

Abstract:

CIM is the standard formalism for modeling management information developed by the Distributed Management Task Force (DMTF) in the context of its WBEM proposal, designed to provide a conceptual view of the managed environment. In this paper, we propose the inclusion of formal knowledge representation techniques, based on Description Logics (DLs) and the Web Ontology Language (OWL), in CIM-based conceptual modeling, and then we examine the benefits of such a decision. The proposal is specified as a CIM metamodel level mapping to a highly expressive subset of DLs capable of capturing all the semantics of the models. The paper shows how the proposed mapping provides CIM diagrams with precise semantics and can be used for automatic reasoning about the management information models, as a design aid, by means of newgeneration CASE tools, thanks to the use of state-of-the-art automatic reasoning systems that support the proposed logic and use algorithms that are sound and complete with respect to the semantics. Such a CASE tool framework has been developed by the authors and its architecture is also introduced. The proposed formalization is not only useful at design time, but also at run time through the use of rational autonomous agents, in response to a need recently recognized by the DMTF.

Keywords: CIM, Knowledge-based Information Models, OntologyLanguages, OWL, Description Logics, Integrated Network Management, Intelligent Agents, Automatic Reasoning Techniques.

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7620 A Dynamic Programming Model for Maintenance of Electric Distribution System

Authors: Juha Korpijärvi, Jari Kortelainen

Abstract:

The paper presents dynamic programming based model as a planning tool for the maintenance of electric power systems. Every distribution component has an exponential age depending reliability function to model the fault risk. In the moment of time when the fault costs exceed the investment costs of the new component the reinvestment of the component should be made. However, in some cases the overhauling of the old component may be more economical than the reinvestment. The comparison between overhauling and reinvestment is made by optimisation process. The goal of the optimisation process is to find the cost minimising maintenance program for electric power distribution system.

Keywords: Dynamic programming, Electric distribution system, Maintenance

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7619 Transient Heat Transfer Model for Car Body Primer Curing

Authors: D. Zabala, N. Sánchez, J. Pinto

Abstract:

A transient heat transfer mathematical model for the prediction of temperature distribution in the car body during primer baking has been developed by considering the thermal radiation and convection in the furnace chamber and transient heat conduction governing equations in the car framework. The car cockpit is considered like a structure with six flat plates, four vertical plates representing the car doors and the rear and front panels. The other two flat plates are the car roof and floor. The transient heat conduction in each flat plate is modeled by the lumped capacitance method. Comparison with the experimental data shows that the heat transfer model works well for the prediction of thermal behavior of the car body in the curing furnace, with deviations below 5%.

Keywords: Transient heat transfer, car body, lumpedcapacitance, primer baking.

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7618 Framework for Spare Inventory Management

Authors: Eman M. Wahba, Noha M. Galal, Khaled S. El-Kilany

Abstract:

Spare parts inventory management is one of the major areas of inventory research. Analysis of recent literature showed that an approach integrating spare parts classification, demand forecasting, and stock control policies is essential; however, adapting this integrated approach is limited. This work presents an integrated framework for spare part inventory management and an Excel based application developed for the implementation of the proposed framework. A multi-criteria analysis has been used for spare classification. Forecasting of spare parts- intermittent demand has been incorporated into the application using three different forecasting models; namely, normal distribution, exponential smoothing, and Croston method. The application is also capable of running with different inventory control policies. To illustrate the performance of the proposed framework and the developed application; the framework is applied to different items at a service organization. The results achieved are presented and possible areas for future work are highlighted.

Keywords: Demand forecasting, intermittent demand, inventory management, integrated approach, spare parts, spare part classification

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7617 Assessment of Path Loss Prediction Models for Wireless Propagation Channels at L-Band Frequency over Different Micro-Cellular Environments of Ekiti State, Southwestern Nigeria

Authors: C. I. Abiodun, S. O. Azi, J. S. Ojo, P. Akinyemi

Abstract:

The design of accurate and reliable mobile communication systems depends majorly on the suitability of path loss prediction methods and the adaptability of the methods to various environments of interest. In this research, the results of the adaptability of radio channel behavior are presented based on practical measurements carried out in the 1800 MHz frequency band. The measurements are carried out in typical urban, suburban and rural environments in Ekiti State, Southwestern part of Nigeria. A total number of seven base stations of MTN GSM service located in the studied environments were monitored. Path loss and break point distances were deduced from the measured received signal strength (RSS) and a practical path loss model is proposed based on the deduced break point distances. The proposed two slope model, regression line and four existing path loss models were compared with the measured path loss values. The standard deviations of each model with respect to the measured path loss were estimated for each base station. The proposed model and regression line exhibited lowest standard deviations followed by the Cost231-Hata model when compared with the Erceg Ericsson and SUI models. Generally, the proposed two-slope model shows closest agreement with the measured values with a mean error values of 2 to 6 dB. These results show that, either the proposed two slope model or Cost 231-Hata model may be used to predict path loss values in mobile micro cell coverage in the well-considered environments. Information from this work will be useful for link design of microwave band wireless access systems in the region.

Keywords: Break-point distances, path loss models, path loss exponent, received signal strength.

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7616 Modeling and Stability Analysis of Viral Propagation in Wireless Mesh Networking

Authors: Haowei Chen, Kaiqi Xiong

Abstract:

We have developed a better model for understanding the dynamics of malware spread in WMNs in this paper. The suggested model provides an insight into how viral propagation with energy exhaustion and various dispersed node densities might function. Based on a theoretical examination of the suggested model, we conclude that the threshold parameter could be used to identify the dynamics of viral spread globally. When the threshold is less than 1, the virus may be contained, but if it is greater than 1, a pandemic may result. Lastly, we discuss the various viral propagation strategies in relation to the distributed node densities and communication radii in WMNs. The aforementioned numerical simulation findings could serve as a guarantee of the theoretical analyses’ correctness.

Keywords: Bluetooth Security, Malware Propagation, Wireless Mesh Networks, Stability Analysis.

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7615 Control Technology for a Daily Load-following Operation in a Nuclear Power Plant

Authors: Keuk Jong Yu, Sang Hee Kang, Sung Chang You

Abstract:

In Korea, the technology of a load fo nuclear power plant has been being developed. automatic controller which is able to control temperature and axial power distribution was developed. identification algorithm and a model predictive contact former transforms the nuclear reactor status into numerically. And the latter uses them and ge manipulated values such as two kinds of control ro this automatic controller, the performance of a coperation was evaluated. As a result, the automatic generated model parameters of a nuclear react to nuclear reactor average temperature and axial power the desired targets during a daily load follow.

Keywords: axial power distribution, model reactor temperature, system identification

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7614 Fractional Order Feedback Control of a Ball and Beam System

Authors: Santosh Kr. Choudhary

Abstract:

In this paper, fractional order feedback control of a ball beam model is investigated. The ball beam model is a particular example of the double Integrator system having strongly nonlinear characteristics and unstable dynamics which make the control of such system a challenging task. Most of the work in fractional order control systems are in theoretical nature and controller design and its implementation in practice is very small. In this work, a successful attempt has been made to design a fractional order PIλDμcontroller for a benchmark laboratory ball and beam model. Better performance can be achieved using a fractional order PID controller and it is demonstrated through simulations results with a comparison to the classic PID controller.

Keywords: Fractional order calculus, fractional order controller, fractional order system, ball and beam system, PIλDμ controller, modelling, simulation.

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7613 Malaria Parasite Detection Using Deep Learning Methods

Authors: Kaustubh Chakradeo, Michael Delves, Sofya Titarenko

Abstract:

Malaria is a serious disease which affects hundreds of millions of people around the world, each year. If not treated in time, it can be fatal. Despite recent developments in malaria diagnostics, the microscopy method to detect malaria remains the most common. Unfortunately, the accuracy of microscopic diagnostics is dependent on the skill of the microscopist and limits the throughput of malaria diagnosis. With the development of Artificial Intelligence tools and Deep Learning techniques in particular, it is possible to lower the cost, while achieving an overall higher accuracy. In this paper, we present a VGG-based model and compare it with previously developed models for identifying infected cells. Our model surpasses most previously developed models in a range of the accuracy metrics. The model has an advantage of being constructed from a relatively small number of layers. This reduces the computer resources and computational time. Moreover, we test our model on two types of datasets and argue that the currently developed deep-learning-based methods cannot efficiently distinguish between infected and contaminated cells. A more precise study of suspicious regions is required.

Keywords: Malaria, deep learning, DL, convolution neural network, CNN, thin blood smears.

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7612 An Analysis of Blackouts for Electric Power Transmission Systems

Authors: Karamitsos Ioannis, Orfanidis Konstantinos

Abstract:

In this paper an analysis of blackouts in electric power transmission systems is implemented using a model and studied in simple networks with a regular topology. The proposed model describes load demand and network improvements evolving on a slow timescale as well as the fast dynamics of cascading overloads and outages.

Keywords: Blackout, Generator, Load, Power Load.

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7611 Design and Application of NFC-Based Identity and Access Management in Cloud Services

Authors: Shin-Jer Yang, Kai-Tai Yang

Abstract:

In response to a changing world and the fast growth of the Internet, more and more enterprises are replacing web-based services with cloud-based ones. Multi-tenancy technology is becoming more important especially with Software as a Service (SaaS). This in turn leads to a greater focus on the application of Identity and Access Management (IAM). Conventional Near-Field Communication (NFC) based verification relies on a computer browser and a card reader to access an NFC tag. This type of verification does not support mobile device login and user-based access management functions. This study designs an NFC-based third-party cloud identity and access management scheme (NFC-IAM) addressing this shortcoming. Data from simulation tests analyzed with Key Performance Indicators (KPIs) suggest that the NFC-IAM not only takes less time in identity identification but also cuts time by 80% in terms of two-factor authentication and improves verification accuracy to 99.9% or better. In functional performance analyses, NFC-IAM performed better in salability and portability. The NFC-IAM App (Application Software) and back-end system to be developed and deployed in mobile device are to support IAM features and also offers users a more user-friendly experience and stronger security protection. In the future, our NFC-IAM can be employed to different environments including identification for mobile payment systems, permission management for remote equipment monitoring, among other applications.

Keywords: Cloud service, multi-tenancy, NFC, IAM, mobile device.

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7610 The Optimization of an Intelligent Traffic Congestion Level Classification from Motorists- Judgments on Vehicle's Moving Patterns

Authors: Thammasak Thianniwet, Satidchoke Phosaard, Wasan Pattara-Atikom

Abstract:

We proposed a technique to identify road traffic congestion levels from velocity of mobile sensors with high accuracy and consistent with motorists- judgments. The data collection utilized a GPS device, a webcam, and an opinion survey. Human perceptions were used to rate the traffic congestion levels into three levels: light, heavy, and jam. Then the ratings and velocity were fed into a decision tree learning model (J48). We successfully extracted vehicle movement patterns to feed into the learning model using a sliding windows technique. The parameters capturing the vehicle moving patterns and the windows size were heuristically optimized. The model achieved accuracy as high as 99.68%. By implementing the model on the existing traffic report systems, the reports will cover comprehensive areas. The proposed method can be applied to any parts of the world.

Keywords: intelligent transportation system (ITS), traffic congestion level, human judgment, decision tree (J48), geographic positioning system (GPS).

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7609 An Experimental Investigation on the Droplet Behavior Impacting a Hot Surface above the Leidenfrost Temperature

Authors: Khaleel Sami Hamdan, Dong-Eok Kim, Sang-Ki Moon

Abstract:

An appropriate model to predict the size of the droplets resulting from the break-up with the structures will help in a better understanding and modeling of the two-phase flow calculations in the simulation of a reactor core loss-of-coolant accident (LOCA). A droplet behavior impacting on a hot surface above the Leidenfrost temperature was investigated. Droplets of known size and velocity were impacted to an inclined plate of hot temperature, and the behavior of the droplets was observed by a high-speed camera. It was found that for droplets of Weber number higher than a certain value, the higher the Weber number of the droplet the smaller the secondary droplets. The COBRA-TF model over-predicted the measured secondary droplet sizes obtained by the present experiment. A simple model for the secondary droplet size was proposed using the mass conservation equation. The maximum spreading diameter of the droplets was also compared to previous correlations and a fairly good agreement was found. A better prediction of the heat transfer in the case of LOCA can be obtained with the presented model.

Keywords: Break-up, droplet, impact, inclined hot plate, Leidenfrost temperature, LOCA.

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7608 Analysis of Driving Conditions and Preferred Media on Diversion

Authors: Yoon-Hyuk Choi

Abstract:

Studies on the distribution of traffic demands have been proceeding by providing traffic information for reducing greenhouse gases and reinforcing the road's competitiveness in the transport section, however, since it is preferentially required the extensive studies on the driver's behavior changing routes and its influence factors, this study has been developed a discriminant model for changing routes considering driving conditions including traffic conditions of roads and driver's preferences for information media. It is divided into three groups depending on driving conditions in group classification with the CART analysis, which is statistically meaningful. And the extent that driving conditions and preferred media affect a route change is examined through a discriminant analysis, and it is developed a discriminant model equation to predict a route change. As a result of building the discriminant model equation, it is shown that driving conditions affect a route change much more, the entire discriminant hit ratio is derived as 64.2%, and this discriminant equation shows high discriminant ability more than a certain degree.

Keywords: CART analysis, Diversion, Discriminant model, Driving conditions, and preferred media

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7607 Knowledge Management Applied to Forensic Sciences

Authors: Norma Rodrigues Gomes

Abstract:

This paper presents initiatives of Knowledge Management (KM) applied to Forensic Sciences field, especially developed at the Forensic Science Institute of the Brazilian Federal Police. Successful projects, related to knowledge sharing, drugs analysis and environmental crimes, are reported in the KM perspective. The described results are related to: a) the importance of having an information repository, like a digital library, in such a multidisciplinary organization; b) the fight against drug dealing and environmental crimes, enabling the possibility to map the evolution of crimes, drug trafficking flows, and the advance of deforestation in Amazon rain forest. Perspectives of new KM projects under development and studies are also presented, tracing an evolution line of the KM view at the Forensic Science Institute.

Keywords: Business Intelligence, Digital Library, Forensic Science, Knowledge Management

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7606 Artificial Neural Network-Based Short-Term Load Forecasting for Mymensingh Area of Bangladesh

Authors: S. M. Anowarul Haque, Md. Asiful Islam

Abstract:

Electrical load forecasting is considered to be one of the most indispensable parts of a modern-day electrical power system. To ensure a reliable and efficient supply of electric energy, special emphasis should have been put on the predictive feature of electricity supply. Artificial Neural Network-based approaches have emerged to be a significant area of interest for electric load forecasting research. This paper proposed an Artificial Neural Network model based on the particle swarm optimization algorithm for improved electric load forecasting for Mymensingh, Bangladesh. The forecasting model is developed and simulated on the MATLAB environment with a large number of training datasets. The model is trained based on eight input parameters including historical load and weather data. The predicted load data are then compared with an available dataset for validation. The proposed neural network model is proved to be more reliable in terms of day-wise load forecasting for Mymensingh, Bangladesh.

Keywords: Load forecasting, artificial neural network, particle swarm optimization.

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7605 Agent/Group/Role Organizational Model to Simulate an Industrial Control System

Authors: Noureddine Seddari, Mohamed Belaoued, Salah Bougueroua

Abstract:

The modeling of complex systems is generally based on the decomposition of their components into sub-systems easier to handle. This division has to be made in a methodical way. In this paper, we introduce an industrial control system modeling and simulation based on the Multi-Agent System (MAS) methodology AALAADIN and more particularly the underlying conceptual model Agent/Group/Role (AGR). Indeed, in this division using AGR model, the overall system is decomposed into sub-systems in order to improve the understanding of regulation and control systems, and to simplify the implementation of the obtained agents and their groups, which are implemented using the Multi-Agents Development KIT (MAD-KIT) platform. This approach appears to us to be the most appropriate for modeling of this type of systems because, due to the use of MAS, it is possible to model real systems in which very complex behaviors emerge from relatively simple and local interactions between many different individuals, therefore a MAS is well adapted to describe a system from the standpoint of the activity of its components, that is to say when the behavior of the individuals is complex (difficult to describe with equations). The main aim of this approach is the take advantage of the performance, the scalability and the robustness that are intuitively provided by MAS.

Keywords: Complex systems, modeling and simulation, industrial control system, MAS, AALAADIN, AGR, MAD-KIT.

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7604 CSTR Control by Using Model Reference Adaptive Control and PSO

Authors: Neha Khanduja

Abstract:

This paper presents a comparative analysis of continuously stirred tank reactor (CSTR) control based on adaptive control and optimal tuning of PID control based on particle swarm optimization. In the design of adaptive control, Model reference adaptive control (MRAC) scheme is used, in which the adaptation law have been developed by MIT rule & Lyapunov’s rule. In PSO control parameters of PID controller is tuned by using the concept of particle swarm optimization to get optimized operating point for minimum integral square error (ISE) condition. The results show the adjustment of PID parameters converting into the optimal operating point and the good control response can be obtained by the PSO technique.

Keywords: Model reference adaptive control (MRAC), optimal control, particle swarm optimization (PSO).

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7603 Model-free Prediction based on Tracking Theory and Newton Form of Polynomial

Authors: Guoyuan Qi , Yskandar Hamam, Barend Jacobus van Wyk, Shengzhi Du

Abstract:

The majority of existing predictors for time series are model-dependent and therefore require some prior knowledge for the identification of complex systems, usually involving system identification, extensive training, or online adaptation in the case of time-varying systems. Additionally, since a time series is usually generated by complex processes such as the stock market or other chaotic systems, identification, modeling or the online updating of parameters can be problematic. In this paper a model-free predictor (MFP) for a time series produced by an unknown nonlinear system or process is derived using tracking theory. An identical derivation of the MFP using the property of the Newton form of the interpolating polynomial is also presented. The MFP is able to accurately predict future values of a time series, is stable, has few tuning parameters and is desirable for engineering applications due to its simplicity, fast prediction speed and extremely low computational load. The performance of the proposed MFP is demonstrated using the prediction of the Dow Jones Industrial Average stock index.

Keywords: Forecast, model-free predictor, prediction, time series

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7602 CFD Simulation of SO2 Removal from Gas Mixtures using Ceramic Membranes

Authors: Azam Marjani, Saeed Shirazian

Abstract:

This work deals with modeling and simulation of SO2 removal in a ceramic membrane by means of FEM. A mass transfer model was developed to predict the performance of SO2 absorption in a chemical solvent. The model was based on solving conservation equations for gas component in the membrane. Computational fluid dynamics (CFD) of mass and momentum were used to solve the model equations. The simulations aimed to obtain the distribution of gas concentration in the absorption process. The effect of the operating parameters on the efficiency of the ceramic membrane was evaluated. The modeling findings showed that the gas phase velocity has significant effect on the removal of gas whereas the liquid phase does not affect the SO2 removal significantly. It is also indicated that the main mass transfer resistance is placed in the membrane and gas phase because of high tortuosity of the ceramic membrane.

Keywords: Gas separation, finite element, ceramic, sulphur dioxide, simulation.

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7601 Dispenser Longitudinal Movement ControlDesign Based on Auto - Disturbances –Rejection - Controller

Authors: Qiaozhen Song

Abstract:

Based on the feature of model disturbances and uncertainty being compensated dynamically in auto – disturbances-rejection-controller (ADRC), a new method using ADRC is proposed for the decoupling control of dispenser longitudinal movement in big flight envelope. Developed from nonlinear model directly, ADRC is especially suitable for dynamic model that has big disturbances. Furthermore, without changing the structure and parameters of the controller in big flight envelope, this scheme can simplify the design of flight control system. The simulation results in big flight envelope show that the system achieves high dynamic performance, steady state performance and the controller has strong robustness.

Keywords: ADRC, ESO, nonlinear system

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7600 Complexity Leadership and Knowledge Management in Higher Education

Authors: Prabhakar Venugopal Gantasala

Abstract:

Complex environments triggered by globalization have necessitated new paradigms of leadership – Complexity Leadership that encompass multiple roles that leaders need to take upon. Success of Higher Education institutions depends on how well leaders can provide adaptive, administrative and enabling leadership. Complexity Leadership seems all the more relevant for institutions that are knowledge-driven and thrive on Knowledge creation, Knowledge storage and retrieval, Knowledge Sharing and Knowledge applications. Discussed in this paper are the elements of Globalization and the opportunities and challenges that are brought forth by globalization. The Complexity leadership paradigm in a knowledge-based economy and the need for such a paradigm shift for higher education institutions is presented. Further, the paper also discusses the support the leader requires in a knowledge-driven economy through knowledge management initiatives.

Keywords: Globalization, Complexity Leadership, Knowledge Management.

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7599 Statistical Analysis of the Impact of Maritime Transport Gross Domestic Product on Nigeria’s Economy

Authors: K. P. Oyeduntan, K. Oshinubi

Abstract:

Nigeria is referred as the ‘Giant of Africa’ due to high population, land mass and large economy. However, it still trails far behind many smaller economies in the continent in terms of maritime operations. As we have seen that the maritime industry is the sparkplug for national growth, because it houses the most crucial infrastructure that generates wealth for a nation, it is worrisome that a nation with six seaports lag in maritime activities. In this research, we have studied how the Gross Domestic Product (GDP) of the maritime transport influences the Nigerian economy. To do this, we applied Simple Linear Regression (SLR), Support Vector Machine (SVM), Polynomial Regression Model (PRM), Generalized Additive Model (GAM) and Generalized Linear Mixed Model (GLMM) to model the relationship between the nation’s Total GDP (TGDP) and the Maritime Transport GDP (MGDP) using a time series data of 20 years. The result showed that the MGDP is statistically significant to the Nigerian economy. Amongst the statistical tool applied, the PRM of order 4 describes the relationship better when compared to other methods. The recommendations presented in this study will guide policy makers and help improve the economy of Nigeria.

Keywords: Economy, GDP, maritime transport, port, regression.

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