Search results for: system accuracy
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 19993

Search results for: system accuracy

19123 A New Method Presentation for Locating Fault in Power Distribution Feeders Considering DG

Authors: Rahman Dashti, Ehsan Gord

Abstract:

In this paper, an improved impedance based fault location method is proposed. In this method, online fault locating is performed using voltage and current information at the beginning of the feeder. Determining precise fault location in a short time increases reliability and efficiency of the system. The proposed method utilizes information about main component of voltage and current at the beginning of the feeder and distributed generation unit (DGU) in order to precisely locate different faults in acceptable time. To evaluate precision and accuracy of the proposed method, a 13-node is simulated and tested using MATLAB.

Keywords: distribution network, fault section determination, distributed generation units, distribution protection equipment

Procedia PDF Downloads 396
19122 DC/DC Boost Converter Applied to Photovoltaic Pumping System Application

Authors: S. Abdourraziq, M. A. Abdourraziq

Abstract:

One of the most famous and important applications of solar energy systems is water pumping. It is often used for irrigation or to supply water in countryside or private firm. However, the cost and the efficiency are still a concern, especially with a continued variation of solar radiation and temperature throughout the day. Then, the improvement of the efficiency of the system components is one of the different solutions to reducing the cost. In this paper, we will present a detailed definition of each element of a PV pumping system, and we will present the different MPPT algorithm used in the literature. Our system consists of a PV panel, a boost converter, a motor-pump set, and a storage tank.

Keywords: PV cell, converter, MPPT, MPP, PV pumping system

Procedia PDF Downloads 152
19121 Accuracy of VCCT for Calculating Stress Intensity Factor in Metal Specimens Subjected to Bending Load

Authors: Sanjin Kršćanski, Josip Brnić

Abstract:

Virtual Crack Closure Technique (VCCT) is a method used for calculating stress intensity factor (SIF) of a cracked body that is easily implemented on top of basic finite element (FE) codes and as such can be applied on the various component geometries. It is a relatively simple method that does not require any special finite elements to be used and is usually used for calculating stress intensity factors at the crack tip for components made of brittle materials. This paper studies applicability and accuracy of VCCT applied on standard metal specimens containing trough thickness crack, subjected to an in-plane bending load. Finite element analyses were performed using regular 4-node, regular 8-node and a modified quarter-point 8-node 2D elements. Stress intensity factor was calculated from the FE model results for a given crack length, using data available from FE analysis and a custom programmed algorithm based on virtual crack closure technique. Influence of the finite element size on the accuracy of calculated SIF was also studied. The final part of this paper includes a comparison of calculated stress intensity factors with results obtained from analytical expressions found in available literature and in ASTM standard. Results calculated by this algorithm based on VCCT were found to be in good correlation with results obtained with mentioned analytical expressions.

Keywords: VCCT, stress intensity factor, finite element analysis, 2D finite elements, bending

Procedia PDF Downloads 299
19120 Development of Medical Intelligent Process Model Using Ontology Based Technique

Authors: Emmanuel Chibuogu Asogwa, Tochukwu Sunday Belonwu

Abstract:

An urgent demand for creative solutions has been created by the rapid expansion of medical knowledge, the complexity of patient care, and the requirement for more precise decision-making. As a solution to this problem, the creation of a Medical Intelligent Process Model (MIPM) utilizing ontology-based appears as a promising way to overcome this obstacle and unleash the full potential of healthcare systems. The development of a Medical Intelligent Process Model (MIPM) using ontology-based techniques is motivated by a lack of quick access to relevant medical information and advanced tools for treatment planning and clinical decision-making, which ontology-based techniques can provide. The aim of this work is to develop a structured and knowledge-driven framework that leverages ontology, a formal representation of domain knowledge, to enhance various aspects of healthcare. Object-Oriented Analysis and Design Methodology (OOADM) were adopted in the design of the system as we desired to build a usable and evolvable application. For effective implementation of this work, we used the following materials/methods/tools: the medical dataset for the test of our model in this work was obtained from Kaggle. The ontology-based technique was used with Confusion Matrix, MySQL, Python, Hypertext Markup Language (HTML), Hypertext Preprocessor (PHP), Cascaded Style Sheet (CSS), JavaScript, Dreamweaver, and Fireworks. According to test results on the new system using Confusion Matrix, both the accuracy and overall effectiveness of the medical intelligent process significantly improved by 20% compared to the previous system. Therefore, using the model is recommended for healthcare professionals.

Keywords: ontology-based, model, database, OOADM, healthcare

Procedia PDF Downloads 72
19119 Convolution Neural Network Based on Hypnogram of Sleep Stages to Predict Dosages and Types of Hypnotic Drugs for Insomnia

Authors: Chi Wu, Dean Wu, Wen-Te Liu, Cheng-Yu Tsai, Shin-Mei Hsu, Yin-Tzu Lin, Ru-Yin Yang

Abstract:

Background: The results of previous studies compared the benefits and risks of receiving insomnia medication. However, the effects between hypnotic drugs used and enhancement of sleep quality were still unclear. Objective: The aim of this study is to establish a prediction model for hypnotic drugs' dosage used for insomnia subjects and associated the relationship between sleep stage ratio change and drug types. Methodologies: According to American Academy of Sleep Medicine (AASM) guideline, sleep stages were classified and transformed to hypnogram via the polysomnography (PSG) in a hospital in New Taipei City (Taiwan). The subjects with diagnosis for insomnia without receiving hypnotic drugs treatment were be set as the comparison group. Conversely, hypnotic drugs dosage within the past three months was obtained from the clinical registration for each subject. Furthermore, the collecting subjects were divided into two groups for training and testing. After training convolution neuron network (CNN) to predict types of hypnotics used and dosages are taken, the test group was used to evaluate the accuracy of classification. Results: We recruited 76 subjects in this study, who had been done PSG for transforming hypnogram from their sleep stages. The accuracy of dosages obtained from confusion matrix on the test group by CNN is 81.94%, and accuracy of hypnotic drug types used is 74.22%. Moreover, the subjects with high ratio of wake stage were correctly classified as requiring medical treatment. Conclusion: CNN with hypnogram was potentially used for adjusting the dosage of hypnotic drugs and providing subjects to pre-screening the types of hypnotic drugs taken.

Keywords: convolution neuron network, hypnotic drugs, insomnia, polysomnography

Procedia PDF Downloads 189
19118 Arabic Light Stemmer for Better Search Accuracy

Authors: Sahar Khedr, Dina Sayed, Ayman Hanafy

Abstract:

Arabic is one of the most ancient and critical languages in the world. It has over than 250 million Arabic native speakers and more than twenty countries having Arabic as one of its official languages. In the past decade, we have witnessed a rapid evolution in smart devices, social network and technology sector which led to the need to provide tools and libraries that properly tackle the Arabic language in different domains. Stemming is one of the most crucial linguistic fundamentals. It is used in many applications especially in information extraction and text mining fields. The motivation behind this work is to enhance the Arabic light stemmer to serve the data mining industry and leverage it in an open source community. The presented implementation works on enhancing the Arabic light stemmer by utilizing and enhancing an algorithm that provides an extension for a new set of rules and patterns accompanied by adjusted procedure. This study has proven a significant enhancement for better search accuracy with an average 10% improvement in comparison with previous works.

Keywords: Arabic data mining, Arabic Information extraction, Arabic Light stemmer, Arabic stemmer

Procedia PDF Downloads 302
19117 Double Layer Security Authentication Model for Automatic Dependent Surveillance-Broadcast

Authors: Buse T. Aydin, Enver Ozdemir

Abstract:

An automatic dependent surveillance-broadcast (ADS-B) system has serious security problems. In this study, a double layer authentication scheme between the aircraft and ground station, aircraft to aircraft, ground station to ATC tower is designed to prevent any unauthorized aircrafts from introducing themselves as friends. This method can be used as a solution to the problem of authentication. The method is a combination of classical cryptographic methods and new generation physical layers. The first layer has employed the embedded key of the aircraft. The embedded key is assumed to installed during the construction of the utility. The other layer is a physical attribute (flight path, distance, etc.) between the aircraft and the ATC tower. We create a mathematical model so that two layers’ information is employed and an aircraft is authenticated as a friend or unknown according to the accuracy of the results of the model. The results of the aircraft are compared with the results of the ATC tower and if the values found by the aircraft and ATC tower match within a certain error margin, we mark the aircraft as friend. As a result, the ADS-B messages coming from this authenticated friendly aircraft will be processed. In this method, even if the embedded key is captured by the unknown aircraft, without the information of the second layer, the unknown aircraft can easily be determined. Overall, in this work, we present a reliable system by adding physical layer in the authentication process.

Keywords: ADS-B, authentication, communication with physical layer security, cryptography, identification friend or foe

Procedia PDF Downloads 172
19116 System Identification and Quantitative Feedback Theory Design of a Lathe Spindle

Authors: M. Khairudin

Abstract:

This paper investigates the system identification and design quantitative feedback theory (QFT) for the robust control of a lathe spindle. The dynamic of the lathe spindle is uncertain and time variation due to the deepness variation on cutting process. System identification was used to obtain the dynamics model of the lathe spindle. In this work, real time system identification is used to construct a linear model of the system from the nonlinear system. These linear models and its uncertainty bound can then be used for controller synthesis. The real time nonlinear system identification process to obtain a set of linear models of the lathe spindle that represents the operating ranges of the dynamic system. With a selected input signal, the data of output and response is acquired and nonlinear system identification is performed using Matlab to obtain a linear model of the system. Practical design steps are presented in which the QFT-based conditions are formulated to obtain a compensator and pre-filter to control the lathe spindle. The performances of the proposed controller are evaluated in terms of velocity responses of the the lathe machine spindle in corporating deepness on cutting process.

Keywords: lathe spindle, QFT, robust control, system identification

Procedia PDF Downloads 538
19115 Usability and Biometric Authentication of Electronic Voting System

Authors: Nighat Ayub, Masood Ahmad

Abstract:

In this paper, a new voting system is developed and its usability is evaluated. The main feature of this system is the biometric verification of the voter and then a few easy steps to cast a vote. As compared to existing systems available, e.g dual vote, the new system requires no training in advance. The security is achieved via multiple key concept (another part of this project). More than 100 student voters were participated in the election from University of Malakanad, Chakdara, PK. To achieve the reliability, the voters cast their votes in two ways, i.e. paper based and electronic based voting using our new system. The results of paper based and electronic voting system are compared and it is concluded that the voters cast their votes for the intended candidates on the electronic voting system. The voters were requested to fill a questionnaire and the results of the questionnaire are carefully analyzed. The results show that the new system proposed in this paper is more secure and usable than other systems.

Keywords: e-voting, security, usability, authentication

Procedia PDF Downloads 388
19114 Study of Structural Health Monitoring System for Vam Cong Cable-Stayed Bridge

Authors: L. M. Chinh

Abstract:

Vam Cong Bridge beside Can Tho Bridge is the next cable-stayed bridge spanning the Hau River, connecting Lap Vo district with Thot Not district. After construction by the end of 2018, the Vam Cong Bridge with Cao Lanh Bridge will help to improve the road network in this region of Mekong Delta. For this bridge, the SHM system also had designed for two stages – construction stage and exploitation stage. At the moment over 65% of the bridge construction had completed, and the bridge will be completed at the end of 2018. During the construction stage, the SHM system had been install to monitor behaviors of the bridge. Based on the study of the design documentation of the SHM system of the Vam Cong Bridge and site visit during construction work, many designs and installation errors have been detected. In this paper author thoroughly analyzed the pros and cons of this SHM system, simultaneously make conclusions and recommendations for this system. Specially concentrated on the possibility of implementing the acoustic emission method (AE) into this SHM system, which is an alternative to the further development of the system, enabling a full and cost-effective solution for the bridge management, which is of utmost importance for the service life and safe operation of the bridge.

Keywords: SHM system, design and installation, Vam Cong bridge, construction stage, acoustic emission method (AE)

Procedia PDF Downloads 232
19113 Monitoring System for Electronic Procurement Systems

Authors: Abdulah Fajar

Abstract:

Electronic Procurement System has been implemented at government institution in Indonesia. This system has been developed centrally at Institution of National Procurement Policy (LKPP) and implemented autonomously at either local or national government institution. The lack of competency at many institution on Information Technology Management arise several major problems. The main concern of LKPP to local administrator is assured that the system is running normally and always be able to serve the needs of its users. Monitoring system has been identified as the one of solution to prevent the problems appeared. Monitoring system is developed using Simple Network Management Protocol (SNMP) and implemented at LKPP. There are two modules; Main Dashboard and Local Agent. Main Dashboard is intended for LKPP and Local Agent is intended to implement at local autonomous e-procurement system (LPSE). There are several resources that must be monitored such as computation, memory and network traffic. Agile paradigm is applied to this project to assure user and system requirement is met. The length of project is the one of reason why agile paradigm has been chosen. The system has been successfully delivered to LKPP.

Keywords: procurement system, SNMP, LKPP, LPSE

Procedia PDF Downloads 421
19112 Evaluating the Total Costs of a Ransomware-Resilient Architecture for Healthcare Systems

Authors: Sreejith Gopinath, Aspen Olmsted

Abstract:

This paper is based on our previous work that proposed a risk-transference-based architecture for healthcare systems to store sensitive data outside the system boundary, rendering the system unattractive to would-be bad actors. This architecture also allows a compromised system to be abandoned and a new system instance spun up in place to ensure business continuity without paying a ransom or engaging with a bad actor. This paper delves into the details of various attacks we simulated against the prototype system. In the paper, we discuss at length the time and computational costs associated with storing and retrieving data in the prototype system, abandoning a compromised system, and setting up a new instance with existing data. Lastly, we simulate some analytical workloads over the data stored in our specialized data storage system and discuss the time and computational costs associated with running analytics over data in a specialized storage system outside the system boundary. In summary, this paper discusses the total costs of data storage, access, and analytics incurred with the proposed architecture.

Keywords: cybersecurity, healthcare, ransomware, resilience, risk transference

Procedia PDF Downloads 129
19111 Applicability of Fuzzy Logic for Intrusion Detection in Mobile Adhoc Networks

Authors: Ruchi Makani, B. V. R. Reddy

Abstract:

Mobile Adhoc Networks (MANETs) are gaining popularity due to their potential of providing low-cost mobile connectivity solutions to real-world communication problems. Integrating Intrusion Detection Systems (IDS) in MANETs is a tedious task by reason of its distinctive features such as dynamic topology, de-centralized authority and highly controlled/limited resource environment. IDS primarily use automated soft-computing techniques to monitor the inflow/outflow of traffic packets in a given network to detect intrusion. Use of machine learning techniques in IDS enables system to make decisions on intrusion while continuous keep learning about their dynamic environment. An appropriate IDS model is essential to be selected to expedite this application challenges. Thus, this paper focused on fuzzy-logic based machine learning IDS technique for MANETs and presented their applicability for achieving effectiveness in identifying the intrusions. Further, the selection of appropriate protocol attributes and fuzzy rules generation plays significant role for accuracy of the fuzzy-logic based IDS, have been discussed. This paper also presents the critical attributes of MANET’s routing protocol and its applicability in fuzzy logic based IDS.

Keywords: AODV, mobile adhoc networks, intrusion detection, anomaly detection, fuzzy logic, fuzzy membership function, fuzzy inference system

Procedia PDF Downloads 172
19110 Design and Development of a Computerized Medical Record System for Hospitals in Remote Areas

Authors: Grace Omowunmi Soyebi

Abstract:

A computerized medical record system is a collection of medical information about a person that is stored on a computer. One principal problem of most hospitals in rural areas is using the file management system for keeping records. A lot of time is wasted when a patient visits the hospital, probably in an emergency, and the nurse or attendant has to search through voluminous files before the patient's file can be retrieved, this may cause an unexpected to happen to the patient. This Data Mining application is to be designed using a Structured System Analysis and design method which will help in a well-articulated analysis of the existing file management system, feasibility study, and proper documentation of the Design and Implementation of a Computerized medical record system. This Computerized system will replace the file management system and help to quickly retrieve a patient's record with increased data security, access clinical records for decision-making, and reduce the time range at which a patient gets attended to.

Keywords: programming, computing, data, innovation

Procedia PDF Downloads 117
19109 An Exploration of the Technical and Economic Feasibility of a Stand Alone Solar PV Generated DC Distribution System over AC Distribution System for Use in the Modern as Well as Future Houses of Isolated Areas

Authors: Alpesh Desai, Indrajit Mukhopadhyay

Abstract:

Standalone Photovoltaic (PV) systems are designed and sized to supply certain AC and/or DC electrical loads. In computers, consumer electronics and many small appliances as well as LED lighting the actual power consumed is DC. The DC system, which requires only voltage control, has many advantages such as feasible connection of the distributed energy sources and reduction of the conversion losses for DC-based loads. Also by using the DC power directly the cost of the size of the Inverter and Solar panel reduced hence the overall cost of the system reduced. This paper explores the technical and economic feasibility of supplying electrical power to homes/houses using DC voltage mains within the house. Theoretical calculated results are presented to demonstrate the advantage of DC system over AC system with PV on sustainable rural/isolated development.

Keywords: distribution system, energy efficiency, off-grid, stand-alone PV system, sustainability, techno-socio-economic

Procedia PDF Downloads 257
19108 A Machine Learning Approach for Anomaly Detection in Environmental IoT-Driven Wastewater Purification Systems

Authors: Giovanni Cicceri, Roberta Maisano, Nathalie Morey, Salvatore Distefano

Abstract:

The main goal of this paper is to present a solution for a water purification system based on an Environmental Internet of Things (EIoT) platform to monitor and control water quality and machine learning (ML) models to support decision making and speed up the processes of purification of water. A real case study has been implemented by deploying an EIoT platform and a network of devices, called Gramb meters and belonging to the Gramb project, on wastewater purification systems located in Calabria, south of Italy. The data thus collected are used to control the wastewater quality, detect anomalies and predict the behaviour of the purification system. To this extent, three different statistical and machine learning models have been adopted and thus compared: Autoregressive Integrated Moving Average (ARIMA), Long Short Term Memory (LSTM) autoencoder, and Facebook Prophet (FP). The results demonstrated that the ML solution (LSTM) out-perform classical statistical approaches (ARIMA, FP), in terms of both accuracy, efficiency and effectiveness in monitoring and controlling the wastewater purification processes.

Keywords: environmental internet of things, EIoT, machine learning, anomaly detection, environment monitoring

Procedia PDF Downloads 145
19107 Adaptive E-Learning System Using Fuzzy Logic and Concept Map

Authors: Mesfer Al Duhayyim, Paul Newbury

Abstract:

This paper proposes an effective adaptive e-learning system that uses a coloured concept map to show the learner's knowledge level for each concept in the chosen subject area. A Fuzzy logic system is used to evaluate the learner's knowledge level for each concept in the domain, and produce a ranked concept list of learning materials to address weaknesses in the learner’s understanding. This system obtains information on the learner's understanding of concepts by an initial pre-test before the system is used for learning and a post-test after using the learning system. A Fuzzy logic system is used to produce a weighted concept map during the learning process. The aim of this research is to prove that such a proposed novel adapted e-learning system will enhance learner's performance and understanding. In addition, this research aims to increase participants' overall understanding of their learning level by providing a coloured concept map of understanding followed by a ranked concepts list of learning materials.

Keywords: adaptive e-learning system, coloured concept map, fuzzy logic, ranked concept list

Procedia PDF Downloads 285
19106 Recession Rate of Gangotri and Its Tributary Glacier, Garhwal Himalaya, India through Kinematic GPS Survey and Satellite Data

Authors: Harish Bisht, Bahadur Singh Kotlia, Kireet Kumar

Abstract:

In order to reconstruct past retreating rates, total area loss, volume change and shift in snout position were measured through multi-temporal satellite data from 1989 to 2016 and kinematic GPS survey from 2015 to 2016. The results obtained from satellite data indicate that in the last 27 years, Chaturangi glacier snout has retreated 1172.57 ± 38.3 m (average 45.07 ± 4.31 m/year) with a total area and volume loss of 0.626 ± 0.001 sq. Km and 0.139 Km³, respectively. The field measurements through differential global positioning system survey revealed that the annual retreating rate was 22.84 ± 0.05 m/year. The large variations in results derived from both the methods are probably because of higher difference in their accuracy. Snout monitoring of the Gangotri glacier during the ablation season (May to September) in the years 2005 and 2015 reveals that the retreating rate has been comparatively more declined than that shown by the earlier studies. The GPS dataset shows that the average recession rate is 10.26 ± 0.05 m/year. In order to determine the possible causes of decreased retreating rate, a relationship between debris thickness and melt rate was also established by using ablation stakes. The present study concludes that remote sensing method is suitable for large area and long term study, while kinematic GPS is more appropriate for the annual monitoring of retreating rate of glacier snout. The present study also emphasizes on mapping of all the tributary glaciers in order to assess the overall changes in the main glacier system and its health.

Keywords: Chaturangi glacier, Gangotri glacier, glacier snout, kinematic global positioning system, retreat rate

Procedia PDF Downloads 135
19105 Insider Theft Detection in Organizations Using Keylogger and Machine Learning

Authors: Shamatha Shetty, Sakshi Dhabadi, Prerana M., Indushree B.

Abstract:

About 66% of firms claim that insider attacks are more likely to happen. The frequency of insider incidents has increased by 47% in the last two years. The goal of this work is to prevent dangerous employee behavior by using keyloggers and the Machine Learning (ML) model. Every keystroke that the user enters is recorded by the keylogging program, also known as keystroke logging. Keyloggers are used to stop improper use of the system. This enables us to collect all textual data, save it in a CSV file, and analyze it using an ML algorithm and the VirusTotal API. Many large companies use it to methodically monitor how their employees use computers, the internet, and email. We are utilizing the SVM algorithm and the VirusTotal API to improve overall efficiency and accuracy in identifying specific patterns and words to automate and offer the report for improved monitoring.

Keywords: cyber security, machine learning, cyclic process, email notification

Procedia PDF Downloads 50
19104 Set-point Performance Evaluation of Robust ‎Back-Stepping Control Design for a Nonlinear ‎Electro-‎Hydraulic Servo System

Authors: Maria Ahmadnezhad, Seyedgharani Ghoreishi ‎

Abstract:

Electrohydraulic servo system have been used in industry in a wide ‎number of applications. Its ‎dynamics are highly nonlinear and also ‎have large extent of model uncertainties and external ‎disturbances. ‎In this thesis, a robust back-stepping control (RBSC) scheme is ‎proposed to overcome ‎the problem of disturbances and system ‎uncertainties effectively and to improve the set-point ‎performance ‎of EHS systems. In order to implement the proposed control ‎scheme, the system ‎uncertainties in EHS systems are considered as ‎total leakage coefficient and effective oil volume. In ‎addition, in ‎order to obtain the virtual controls for stabilizing system, the ‎update rule for the ‎system uncertainty term is induced by the ‎Lyapunov control function (LCF). To verify the ‎performance and ‎robustness of the proposed control system, computer simulation of ‎the ‎proposed control system using Matlab/Simulink Software is ‎executed. From the computer ‎simulation, it was found that the ‎RBSC system produces the desired set-point performance and ‎has ‎robustness to the disturbances and system uncertainties of ‎EHS systems.‎

Keywords: electro hydraulic servo system, back-stepping control, robust back-‎stepping control, Lyapunov redesign‎

Procedia PDF Downloads 993
19103 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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19102 The Methodology of System Modeling of Mechatronic Systems

Authors: Lakhoua Najeh

Abstract:

Aims of the work: After a presentation of the functionality of an example of a mechatronic system which is a paint mixer system, we present the concepts of modeling and safe operation. This paper briefly discusses how to model and protect the functioning of a mechatronic system relying mainly on functional analysis and safe operation techniques. Methods: For the study of an example of a mechatronic system, we use methods for external functional analysis that illustrate the relationships between a mechatronic system and its external environment. Thus, we present the Safe-Structured Analysis Design Technique method (Safe-SADT) which allows the representation of a mechatronic system. A model of operating safety and automation is proposed. This model enables us to use a functional analysis technique of the mechatronic system based on the GRAFCET (Graphe Fonctionnel de Commande des Etapes et Transitions: Step Transition Function Chart) method; study of the safe operation of the mechatronic system based on the Safe-SADT method; automation of the mechatronic system based on a software tool. Results: The expected results are to propose a model and safe operation of a mechatronic system. This methodology enables us to analyze the relevance of the different models based on Safe-SADT and GRAFCET in relation to the control and monitoring functions and to study the means allowing exploiting their synergy. Conclusion: In order to propose a general model of a mechatronic system, a model of analysis, safety operation and automation of a mechatronic system has been developed. This is how we propose to validate this methodology through a case study of a paint mixer system.

Keywords: mechatronic systems, system modeling, safe operation, Safe-SADT

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19101 E-Learning Recommender System Based on Collaborative Filtering and Ontology

Authors: John Tarus, Zhendong Niu, Bakhti Khadidja

Abstract:

In recent years, e-learning recommender systems has attracted great attention as a solution towards addressing the problem of information overload in e-learning environments and providing relevant recommendations to online learners. E-learning recommenders continue to play an increasing educational role in aiding learners to find appropriate learning materials to support the achievement of their learning goals. Although general recommender systems have recorded significant success in solving the problem of information overload in e-commerce domains and providing accurate recommendations, e-learning recommender systems on the other hand still face some issues arising from differences in learner characteristics such as learning style, skill level and study level. Conventional recommendation techniques such as collaborative filtering and content-based deal with only two types of entities namely users and items with their ratings. These conventional recommender systems do not take into account the learner characteristics in their recommendation process. Therefore, conventional recommendation techniques cannot make accurate and personalized recommendations in e-learning environment. In this paper, we propose a recommendation technique combining collaborative filtering and ontology to recommend personalized learning materials to online learners. Ontology is used to incorporate the learner characteristics into the recommendation process alongside the ratings while collaborate filtering predicts ratings and generate recommendations. Furthermore, ontological knowledge is used by the recommender system at the initial stages in the absence of ratings to alleviate the cold-start problem. Evaluation results show that our proposed recommendation technique outperforms collaborative filtering on its own in terms of personalization and recommendation accuracy.

Keywords: collaborative filtering, e-learning, ontology, recommender system

Procedia PDF Downloads 371
19100 A Comparative Evaluation of Finite Difference Methods for the Extended Boussinesq Equations and Application to Tsunamis Modelling

Authors: Aurore Cauquis, Philippe Heinrich, Mario Ricchiuto, Audrey Gailler

Abstract:

In this talk, we look for an accurate time scheme to model the propagation of waves. Several numerical schemes have been developed to solve the extended weakly nonlinear weakly dispersive Boussinesq Equations. The temporal schemes used are two Lax-Wendroff schemes, second or third order accurate, two Runge-Kutta schemes of second and third order and a simplified third order accurate Lax-Wendroff scheme. Spatial derivatives are evaluated with fourth order accuracy. The numerical model is applied to two monodimensional benchmarks on a flat bottom. It is also applied to the simulation of the Algerian tsunami generated by a Mw=6 seism on the 18th March 2021. The tsunami propagation was highly dispersive and propagated across the Mediterranean Sea. We study here the effects of the order of temporal discretization on the accuracy of the results and on the time of computation.

Keywords: numerical analysis, tsunami propagation, water wave, boussinesq equations

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19099 A U-Net Based Architecture for Fast and Accurate Diagram Extraction

Authors: Revoti Prasad Bora, Saurabh Yadav, Nikita Katyal

Abstract:

In the context of educational data mining, the use case of extracting information from images containing both text and diagrams is of high importance. Hence, document analysis requires the extraction of diagrams from such images and processes the text and diagrams separately. To the author’s best knowledge, none among plenty of approaches for extracting tables, figures, etc., suffice the need for real-time processing with high accuracy as needed in multiple applications. In the education domain, diagrams can be of varied characteristics viz. line-based i.e. geometric diagrams, chemical bonds, mathematical formulas, etc. There are two broad categories of approaches that try to solve similar problems viz. traditional computer vision based approaches and deep learning approaches. The traditional computer vision based approaches mainly leverage connected components and distance transform based processing and hence perform well in very limited scenarios. The existing deep learning approaches either leverage YOLO or faster-RCNN architectures. These approaches suffer from a performance-accuracy tradeoff. This paper proposes a U-Net based architecture that formulates the diagram extraction as a segmentation problem. The proposed method provides similar accuracy with a much faster extraction time as compared to the mentioned state-of-the-art approaches. Further, the segmentation mask in this approach allows the extraction of diagrams of irregular shapes.

Keywords: computer vision, deep-learning, educational data mining, faster-RCNN, figure extraction, image segmentation, real-time document analysis, text extraction, U-Net, YOLO

Procedia PDF Downloads 131
19098 Numerical Solution of Space Fractional Order Solute Transport System

Authors: Shubham Jaiswal

Abstract:

In the present article, a drive is taken to compute the solution of spatial fractional order advection-dispersion equation having source/sink term with given initial and boundary conditions. The equation is converted to a system of ordinary differential equations using second-kind shifted Chebyshev polynomials, which have finally been solved using finite difference method. The striking feature of the article is the fast transportation of solute concentration as and when the system approaches fractional order from standard order for specified values of the parameters of the system.

Keywords: spatial fractional order advection-dispersion equation, second-kind shifted Chebyshev polynomial, collocation method, conservative system, non-conservative system

Procedia PDF Downloads 253
19097 Development of Intelligent Smart Multi Tracking Agent System to Support of Logistics Safety

Authors: Umarov Jamshid, Ju-Su Kim, Hak-Jun Lee, Man-Kyo Han, Ryum-Duck Oh

Abstract:

Recently, it becomes convenient to identify the location information of cargos by using GPS and wireless communication technologies. The development of IoT technologies and tracking system allows us to confirm site situation on an ad hoc basis in all the industries and social environments. Moreover, it allows us to apply IT technologies to a manageable extent. However, there have been many limitations for using the system due to the difficulty of identifying location information in real time and also due to the simple features. To globalize the logistics related tracking system, it is required to conduct a study to resolve the aforementioned problem. On that account, this paper designed and developed the IoT and RTLS based intelligent multi tracking agent system for more secure, accurate and reliable transportation in relation to logistics.

Keywords: GPS, tracking agent system, IoT, RTLS, Logistics

Procedia PDF Downloads 640
19096 Sparse Signal Restoration Algorithm Based on Piecewise Adaptive Backtracking Orthogonal Least Squares

Authors: Linyu Wang, Jiahui Ma, Jianhong Xiang, Hanyu Jiang

Abstract:

the traditional greedy compressed sensing algorithm needs to know the signal sparsity when recovering the signal, but the signal sparsity in the practical application can not be obtained as a priori information, and the recovery accuracy is low, which does not meet the needs of practical application. To solve this problem, this paper puts forward Piecewise adaptive backtracking orthogonal least squares algorithm. The algorithm is divided into two stages. In the first stage, the sparsity pre-estimation strategy is adopted, which can quickly approach the real sparsity and reduce time consumption. In the second stage iteration, the correction strategy and adaptive step size are used to accurately estimate the sparsity, and the backtracking idea is introduced to improve the accuracy of signal recovery. Through experimental simulation, the algorithm can accurately recover the estimated signal with fewer iterations when the sparsity is unknown.

Keywords: compressed sensing, greedy algorithm, least square method, adaptive reconstruction

Procedia PDF Downloads 139
19095 The Enlightenment of the Ventilation System in Chinese Traditional Residence to Architecture Design

Authors: Wu Xingchun, Chen Xi

Abstract:

Nowadays, China's building energy consumption constitutes 25% of the total energy consumption, half of which was caused by air conditioning in both summer and winter. The ventilation system in Chinese traditional residence, which is totally passive and environmentally friendly, works effectively to create comfortable indoor environment. The research on the ventilation system in Chinese traditional residence can provide advancements to architecture design and energy savings to the society. Through field investigation, case analysis, strategy proposing and other methods, it comes out that the location and layout, the structure system and the design of atrium are the most important elements for a good ventilation system. Taking every factor into consideration, techniques are deployed extensively such as the organization of draught, the design of the thermal pressure ventilation system and the application of modern materials. With the enlightenment of the ventilation system in Chinese traditional residence, we can take effective measures to achieve low energy consumption and sustainable architecture.

Keywords: ventilation system, chinese traditional residence, energy consumption, sustainable architecture

Procedia PDF Downloads 703
19094 Mobile Platform’s Attitude Determination Based on Smoothed GPS Code Data and Carrier-Phase Measurements

Authors: Mohamed Ramdani, Hassen Abdellaoui, Abdenour Boudrassen

Abstract:

Mobile platform’s attitude estimation approaches mainly based on combined positioning techniques and developed algorithms; which aim to reach a fast and accurate solution. In this work, we describe the design and the implementation of an attitude determination (AD) process, using only measurements from GPS sensors. The major issue is based on smoothed GPS code data using Hatch filter and raw carrier-phase measurements integrated into attitude algorithm based on vectors measurement using least squares (LSQ) estimation method. GPS dataset from a static experiment is used to investigate the effectiveness of the presented approach and consequently to check the accuracy of the attitude estimation algorithm. Attitude results from GPS multi-antenna over short baselines are introduced and analyzed. The 3D accuracy of estimated attitude parameters using smoothed measurements is over 0.27°.

Keywords: attitude determination, GPS code data smoothing, hatch filter, carrier-phase measurements, least-squares attitude estimation

Procedia PDF Downloads 150