Search results for: Voting techniques.
876 Enhance the Modeling of BLDC Motor Based on Fuzzy Logic
Authors: Murugan Marimuthu, Jeyabharath Rajaih
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This paper describes a simple way to control the speed of PMBLDC motor using Fuzzy logic control method. In the conventional PI controller the performance of the motor system is simulated and the speed is regulated by using PI controller. These methods used to improve the performance of PMSM drives, but in some cases at different operating conditions when the dynamics of the system also vary over time and it can change the reference speed, parameter variations and the load disturbance. The simulation is powered with the MATLAB program to get a reliable and flexible simulation. In order to highlight the effectiveness of the speed control method the FLC method is used. The proposed method targeted in achieving the improved dynamic performance and avoids the variations of the motor drive. This drive has high accuracy, robust operation from near zero to high speed. The effectiveness and flexibility of the individual techniques of the speed control method will be thoroughly discussed for merits and demerits and finally verified through simulation and experimental results for comparative analysis.Keywords: Hall position sensors, permanent magnet brushless DC motor, PI controller, Fuzzy Controller.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1785875 What the Future Holds for Social Media Data Analysis
Authors: P. Wlodarczak, J. Soar, M. Ally
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The dramatic rise in the use of Social Media (SM) platforms such as Facebook and Twitter provide access to an unprecedented amount of user data. Users may post reviews on products and services they bought, write about their interests, share ideas or give their opinions and views on political issues. There is a growing interest in the analysis of SM data from organisations for detecting new trends, obtaining user opinions on their products and services or finding out about their online reputations. A recent research trend in SM analysis is making predictions based on sentiment analysis of SM. Often indicators of historic SM data are represented as time series and correlated with a variety of real world phenomena like the outcome of elections, the development of financial indicators, box office revenue and disease outbreaks. This paper examines the current state of research in the area of SM mining and predictive analysis and gives an overview of the analysis methods using opinion mining and machine learning techniques.
Keywords: Social Media, text mining, knowledge discovery, predictive analysis, machine learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3849874 High Efficiency Electrolyte Lithium Battery and RF Characterization
Authors: Wei Quan, Liu Chao, Mohammed N. Afsar
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The dielectric properties and ionic conductivity of novel "ceramic state" polymer electrolytes for high capacity lithium battery are characterized by Radio frequency and Microwave methods in two broad frequency ranges from 50 Hz to 20 KHz and 4 GHz to 40 GHz. This innovative solid polymer electrolyte which is highly ionic conductive (10-3 S/cm at room temperature) from -40oC to +150oC can be used in any battery application. Such polymer exhibits properties more like a ceramic rather than polymer. The various applied measurement methods produced accurate dielectric results for comprehensive analysis of electrochemical properties and ion transportation mechanism of this newly invented polymer electrolyte. Two techniques and instruments employing air gap measurement by Capacitance Bridge and in-waveguide measurement by vector network analyzer are applied to measure the complex dielectric spectra. The complex dielectric spectra are used to determine the complex alternating current electrical conductivity and thus the ionic conductivity.
Keywords: Polymer electrolyte, dielectric permittivity, lithium battery, ionic relaxation, microwave measurement.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2424873 Spatial Data Mining by Decision Trees
Authors: S. Oujdi, H. Belbachir
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Existing methods of data mining cannot be applied on spatial data because they require spatial specificity consideration, as spatial relationships. This paper focuses on the classification with decision trees, which are one of the data mining techniques. We propose an extension of the C4.5 algorithm for spatial data, based on two different approaches Join materialization and Querying on the fly the different tables. Similar works have been done on these two main approaches, the first - Join materialization - favors the processing time in spite of memory space, whereas the second - Querying on the fly different tables- promotes memory space despite of the processing time. The modified C4.5 algorithm requires three entries tables: a target table, a neighbor table, and a spatial index join that contains the possible spatial relationship among the objects in the target table and those in the neighbor table. Thus, the proposed algorithms are applied to a spatial data pattern in the accidentology domain. A comparative study of our approach with other works of classification by spatial decision trees will be detailed.
Keywords: C4.5 Algorithm, Decision trees, S-CART, Spatial data mining.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2986872 Distance Transmission Line Protection Based on Radial Basis Function Neural Network
Authors: Anant Oonsivilai, Sanom Saichoomdee
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To determine the presence and location of faults in a transmission by the adaptation of protective distance relay based on the measurement of fixed settings as line impedance is achieved by several different techniques. Moreover, a fast, accurate and robust technique for real-time purposes is required for the modern power systems. The appliance of radial basis function neural network in transmission line protection is demonstrated in this paper. The method applies the power system via voltage and current signals to learn the hidden relationship presented in the input patterns. It is experiential that the proposed technique is competent to identify the particular fault direction more speedily. System simulations studied show that the proposed approach is able to distinguish the direction of a fault on a transmission line swiftly and correctly, therefore suitable for the real-time purposes.
Keywords: radial basis function neural network, transmission lines protection, relaying, power system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2364871 User Intention Generation with Large Language Models Using Chain-of-Thought Prompting
Authors: Gangmin Li, Fan Yang
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Personalized recommendation is crucial for any recommendation system. One of the techniques for personalized recommendation is to identify the intention. Traditional user intention identification uses the user’s selection when facing multiple items. This modeling relies primarily on historical behavior data resulting in challenges such as the cold start, unintended choice, and failure to capture intention when items are new. Motivated by recent advancements in Large Language Models (LLMs) like ChatGPT, we present an approach for user intention identification by embracing LLMs with Chain-of-Thought (CoT) prompting. We use the initial user profile as input to LLMs and design a collection of prompts to align the LLM's response through various recommendation tasks encompassing rating prediction, search and browse history, user clarification, etc. Our tests on real-world datasets demonstrate the improvements in recommendation by explicit user intention identification and, with that intention, merged into a user model.
Keywords: Personalized recommendation, generative user modeling, user intention identification, large language models, chain-of-thought prompting.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 87870 A Soft Switching PWM DC-DC Boost Converter with Increased Efficiency by Using ZVT-ZCT Techniques
Authors: Yakup Sahin, Naim Suleyman Ting, Ismail Aksoy
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In this paper, an improved active snubber cell is proposed on account of soft switching (SS) family of pulse width modulation (PWM) DC-DC converters. The improved snubber cell provides zero-voltage transition (ZVT) turn on and zero-current transition (ZCT) turn off for main switch. The snubber cell decreases EMI noise and operates with SS in a wide range of line and load voltages. Besides, all of the semiconductor devices in the converter operate with SS. There is no additional voltage and current stress on the main devices. Additionally, extra voltage stress does not occur on the auxiliary switch and its current stress is acceptable value. The improved converter has a low cost and simple structure. The theoretical analysis of converter is clarified and the operating states are given in detail. The experimental results of converter are obtained by prototype of 500 W and 100 kHz. It is observed that the experimental results and theoretical analysis of converter are suitable with each other perfectly.Keywords: Active snubber cells, DC-DC converters, zero-voltage transition, zero-current transition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1928869 Application of Transform Fourier for Dynamic Control of Structures with Global Positioning System
Authors: J. M. de Luis Ruiz, P. M. Sierra García, R. P. García, R. P. Álvarez, F. P. García, E. C. López
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Given the evolution of viaducts, structural health monitoring requires more complex techniques to define their state. two alternatives can be distinguished: experimental and operational modal analysis. Although accelerometers or Global Positioning System (GPS) have been applied for the monitoring of structures under exploitation, the dynamic monitoring during the stage of construction is not common. This research analyzes whether GPS data can be applied to certain dynamic geometric controls of evolving structures. The fundamentals of this work were applied to the New Bridge of Cádiz (Spain), a worldwide milestone in bridge building. GPS data were recorded with an interval of 1 second during the erection of segments and turned to the frequency domain with Fourier transform. The vibration period and amplitude were contrasted with those provided by the finite element model, with differences of less than 10%, which is admissible. This process provides a vibration record of the structure with GPS, avoiding specific equipment.
Keywords: Fourier transform, global position system, operational modal analysis, structural health monitoring.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 933868 Can Physical Activity and Dietary Fat Intake Influence Body Mass Index in a Cross-sectional Correlational Design?
Authors: D.O. Omondi, L.O.A. Othuon, G.M. Mbagaya
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The purpose of this study was to determine the influence of physical activity and dietary fat intake on Body Mass Index (BMI) of lecturers within a higher learning institutionalized setting. The study adopted a Cross-sectional Correlational Design and included 120 lecturers selected proportionately by simple random sampling techniques from a population of 600 lecturers. Data was collected using questionnaires, which had sections including physical activity checklist adopted from the international physical activity questionnaire (IPAQ), 24-hour food recall, anthropometric measurements mainly weight and height. Analysis involved the use of bivariate correlations and linear regression. A significant inverse association was registered between BMI and duration (in minutes) spent doing moderate intense physical activity per day (r=-0.322, p<0.01). Physical activity also predicted BMI (r2=0.096, F=13.616, β=-3.22, t=-3.69, n=120, P<0.01). However, the association between Body Mass Index and dietary fat was not significant (r=0.038, p>0.05). Physical activity emerged as a more powerful determinant of BMI compared to dietary fat intake.Keywords: Physical activity, dietary fat intake, Body MassIndex, Kenya.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1711867 The Implicit Methods for the Study of Tolerance
Authors: M. Bambulyakа
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Tolerance is a tool for achieving a social cohesion, particularly, among individuals and groups with different values. The aim is to study the characteristics of the ethnic tolerance, the inhabitants of Latvia. The ethnic tolerance is taught as a set of conscious and unconscious orientations of the individual in social interaction and inter-ethnic communication. It uses the tools of empirical studies of the ethnic tolerance which allows to identify the explicitly and implicitly levels of the emotional component of Latvia's residents. Explicit measurements were made using the techniques of self-report which revealed the index of the ethnic tolerance and the ethnic identity of the participants. The implicit component was studied using methods based on the effect of the emotional priming. During the processing of the results, there were calculated indicators of the positive and negative implicit attitudes towards members of their own and other ethnicity as well as the explicit parameters of the ethnic tolerance and the ethnic identity of Latvia-s residents. The implicit measurements of the ratio of neighboring ethnic groups against each other showed a mutual negative attitude whereas the explicit measurements indicate a neutral attitude. The data obtained contribute to a further study of the ethnic tolerance of Latvia's residents.
Keywords: ethnic tolerance, implicit measure, priming, ethnic attitudes
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1591866 An Advanced Time-Frequency Domain Method for PD Extraction with Non-Intrusive Measurement
Authors: Guomin Luo, Daming Zhang, Yong Kwee Koh, Kim Teck Ng, Helmi Kurniawan, Weng Hoe Leong
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Partial discharge (PD) detection is an important method to evaluate the insulation condition of metal-clad apparatus. Non-intrusive sensors which are easy to install and have no interruptions on operation are preferred in onsite PD detection. However, it often lacks of accuracy due to the interferences in PD signals. In this paper a novel PD extraction method that uses frequency analysis and entropy based time-frequency (TF) analysis is introduced. The repetitive pulses from convertor are first removed via frequency analysis. Then, the relative entropy and relative peak-frequency of each pulse (i.e. time-indexed vector TF spectrum) are calculated and all pulses with similar parameters are grouped. According to the characteristics of non-intrusive sensor and the frequency distribution of PDs, the pulses of PD and interferences are separated. Finally the PD signal and interferences are recovered via inverse TF transform. The de-noised result of noisy PD data demonstrates that the combination of frequency and time-frequency techniques can discriminate PDs from interferences with various frequency distributions.Keywords: Entropy, Fourier analysis, non-intrusive measurement, time-frequency analysis, partial discharge
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1589865 On the Learning of Causal Relationships between Banks in Saudi Equities Market Using Ensemble Feature Selection Methods
Authors: Adel Aloraini
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Financial forecasting using machine learning techniques has received great efforts in the last decide . In this ongoing work, we show how machine learning of graphical models will be able to infer a visualized causal interactions between different banks in the Saudi equities market. One important discovery from such learned causal graphs is how companies influence each other and to what extend. In this work, a set of graphical models named Gaussian graphical models with developed ensemble penalized feature selection methods that combine ; filtering method, wrapper method and a regularizer will be shown. A comparison between these different developed ensemble combinations will also be shown. The best ensemble method will be used to infer the causal relationships between banks in Saudi equities market.
Keywords: Causal interactions , banks, feature selection, regularizere,
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1747864 Threshold Concepts in TESOL: A Thematic Analysis of Disciplinary Guiding Principles
Authors: Neil Morgan
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The notion of Threshold Concepts has offered a fertile new perspective on the transformative effects of mastery of particular concepts on student understanding of subject matter and their developing identities as inductees into disciplinary discourse communities. Only by successfully traversing essential knowledge thresholds can neophytes achieve the more sophisticated understandings of subject matter possessed by mature members of a discipline. This paper uses thematic analysis of disciplinary guiding principles to identify nine candidate Threshold Concepts that appear to underpin effective TESOL practice. The relationship between these candidate TESOL Threshold Concepts, TESOL principles, and TESOL instructional techniques appears to be amenable to a schematic representation based on superordinate categories of TESOL practitioner concern and, as such, offers an alternative to the view of Threshold Concepts as a privileged subset of disciplinary core concepts. The paper concludes by exploring the potential of a Threshold Concepts framework to productively inform TESOL initial teacher education (ITE) and in-service education and training (INSET).
Keywords: TESOL, threshold concepts, TESOL principles, TESOL ITE/INSET, community of practice.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 742863 Semantic Indexing Approach of a Corpora Based On Ontology
Authors: Mohammed Erritali
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The growth in the volume of text data such as books and articles in libraries for centuries has imposed to establish effective mechanisms to locate them. Early techniques such as abstraction, indexing and the use of classification categories have marked the birth of a new field of research called "Information Retrieval". Information Retrieval (IR) can be defined as the task of defining models and systems whose purpose is to facilitate access to a set of documents in electronic form (corpus) to allow a user to find the relevant ones for him, that is to say, the contents which matches with the information needs of the user. This paper presents a new semantic indexing approach of a documentary corpus. The indexing process starts first by a term weighting phase to determine the importance of these terms in the documents. Then the use of a thesaurus like Wordnet allows moving to the conceptual level. Each candidate concept is evaluated by determining its level of representation of the document, that is to say, the importance of the concept in relation to other concepts of the document. Finally, the semantic index is constructed by attaching to each concept of the ontology, the documents of the corpus in which these concepts are found.Keywords: Semantic, indexing, corpora, WordNet, ontology.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1368862 Comparative Analysis of SVPWM and the Standard PWM Technique for Three Level Diode Clamped Inverter fed Induction Motor
Authors: L. Lakhdari, B. Bouchiba, M. Bechar
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The multi-level inverters present an important novelty in the field of energy control with high voltage and power. The major advantage of all multi-level inverters is the improvement and spectral quality of its generated output signals. In recent years, various pulse width modulation techniques have been developed. From these technics we have: Sinusoidal Pulse Width Modulation (SPWM) and Space Vector Pulse Width Modulation (SVPWM). This work presents a detailed analysis of the comparative advantage of space vector pulse width modulation (SVPWM) and the standard SPWM technique for Three Level Diode Clamped Inverter fed Induction Motor. The comparison is based on the evaluation of harmonic distortion THD.
Keywords: Induction motor, multi-level inverters, NPC inverter, sinusoidal pulse width modulation, space vector pulse width modulation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 978861 Design of Cooperative Processes of Innovation
Authors: Suzanne Yaganeh, Janni Nielsen, Leif Bloch Rasmussen
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This paper invites to dialogue and reflections on innovation and entrepreneurship by presenting concepts of innovation leading to the introduction of a complex theoretical framework; Cooperative Innovation (CO-IN). CO-IN is a didactic model enhancing and scaffolding processes of cooperation creating innovation drawing on a Scandinavian tradition. CO-IN is based on a cross-sectorial and multidisciplinary approach. We introduce the concept of complementarity to help capture the validity of diversity and we suggest the concept of “the space in between" to understand the creation of identity as a collective mind. We see dialogue and the use of multi modal techniques as essential tools for conceptualizations giving possibility for clarification of the complexity and diversity leading to decision making based on knowledge as commons. We introduce the didactic design and present our empirical findings from an innovation workshop in Argentina. In a final paragraph we reflect on the design as a support of the development of common ground, collective mind and collective action and the creation of knowledge as commons to facilitate innovation and entrepreneurship.Keywords: CO-operative Innovation, didactic design, dialogue and ICT.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1718860 Automatic Method for Exudates and Hemorrhages Detection from Fundus Retinal Images
Authors: A. Biran, P. Sobhe Bidari, K. Raahemifar
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Diabetic Retinopathy (DR) is an eye disease that leads to blindness. The earliest signs of DR are the appearance of red and yellow lesions on the retina called hemorrhages and exudates. Early diagnosis of DR prevents from blindness; hence, many automated algorithms have been proposed to extract hemorrhages and exudates. In this paper, an automated algorithm is presented to extract hemorrhages and exudates separately from retinal fundus images using different image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLAHE), Gabor filter and thresholding. Since Optic Disc is the same color as the exudates, it is first localized and detected. The presented method has been tested on fundus images from Structured Analysis of the Retina (STARE) and Digital Retinal Images for Vessel Extraction (DRIVE) databases by using MATLAB codes. The results show that this method is perfectly capable of detecting hard exudates and the highly probable soft exudates. It is also capable of detecting the hemorrhages and distinguishing them from blood vessels.Keywords: Diabetic retinopathy, fundus, CHT, exudates, hemorrhages.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2642859 Phytopathology Prediction in Dry Soil Using Artificial Neural Networks Modeling
Authors: F. Allag, S. Bouharati, M. Belmahdi, R. Zegadi
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The rapid expansion of deserts in recent decades as a result of human actions combined with climatic changes has highlighted the necessity to understand biological processes in arid environments. Whereas physical processes and the biology of flora and fauna have been relatively well studied in marginally used arid areas, knowledge of desert soil micro-organisms remains fragmentary. The objective of this study is to conduct a diversity analysis of bacterial communities in unvegetated arid soils. Several biological phenomena in hot deserts related to microbial populations and the potential use of micro-organisms for restoring hot desert environments. Dry land ecosystems have a highly heterogeneous distribution of resources, with greater nutrient concentrations and microbial densities occurring in vegetated than in bare soils. In this work, we found it useful to use techniques of artificial intelligence in their treatment especially artificial neural networks (ANN). The use of the ANN model, demonstrate his capability for addressing the complex problems of uncertainty data.
Keywords: Desert soil, Climatic changes, Bacteria, Vegetation, Artificial neural networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1890858 Using Structural Equation Modeling in Causal Relationship Design for Balanced-Scorecards' Strategic Map
Authors: A. Saghaei, R. Ghasemi
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Through 1980s, management accounting researchers described the increasing irrelevance of traditional control and performance measurement systems. The Balanced Scorecard (BSC) is a critical business tool for a lot of organizations. It is a performance measurement system which translates mission and strategy into objectives. Strategy map approach is a development variant of BSC in which some necessary causal relations must be established. To recognize these relations, experts usually use experience. It is also possible to utilize regression for the same purpose. Structural Equation Modeling (SEM), which is one of the most powerful methods of multivariate data analysis, obtains more appropriate results than traditional methods such as regression. In the present paper, we propose SEM for the first time to identify the relations between objectives in the strategy map, and a test to measure the importance of relations. In SEM, factor analysis and test of hypotheses are done in the same analysis. SEM is known to be better than other techniques at supporting analysis and reporting. Our approach provides a framework which permits the experts to design the strategy map by applying a comprehensive and scientific method together with their experience. Therefore this scheme is a more reliable method in comparison with the previously established methods.Keywords: BSC, SEM, Strategy map.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2705857 Information Security in E-Learning through Identification of Humans
Authors: Hassan Haleh, Zohreh Nasiri, Parisa Farahpour
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During recent years, the traditional learning approaches have undergone fundamental changes due to the emergence of new technologies such as multimedia, hypermedia and telecommunication. E-learning is a modern world phenomenon that has come into existence in the information age and in a knowledgebased society. E-learning has developed significantly within a short period of time. Thus it is of a great significant to secure information, allow a confident access and prevent unauthorized accesses. Making use of individuals- physiologic or behavioral (biometric) properties is a confident method to make the information secure. Among the biometrics, fingerprint is more acceptable and most countries use it as an efficient methods of identification. This article provides a new method to compare the fingerprint comparison by pattern recognition and image processing techniques. To verify fingerprint, the shortest distance method is used together with perceptronic multilayer neural network functioning based on minutiae. This method is highly accurate in the extraction of minutiae and it accelerates comparisons due to elimination of false minutiae and is more reliable compared with methods that merely use directional images.Keywords: Fingerprint, minutiae, extraction of properties, multilayer neural network
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1649856 Performance Comparison of AODV and Soft AODV Routing Protocol
Authors: Abhishek, Seema Devi, Jyoti Ohri
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A mobile ad hoc network (MANET) represents a system of wireless mobile nodes that can self-organize freely and dynamically into arbitrary and temporary network topology. Unlike a wired network, wireless network interface has limited transmission range. Routing is the task of forwarding data packets from source to a given destination. Ad-hoc On Demand Distance Vector (AODV) routing protocol creates a path for a destination only when it required. This paper describes the implementation of AODV routing protocol using MATLAB-based Truetime simulator. In MANET's node movements are not fixed while they are random in nature. Hence intelligent techniques i.e. fuzzy and ANFIS are used to optimize the transmission range. In this paper, we compared the transmission range of AODV, fuzzy AODV and ANFIS AODV. For soft computing AODV, we have taken transmitted power and received threshold as input and transmission range as output. ANFIS gives better results as compared to fuzzy AODV.Keywords: ANFIS, AODV, fuzzy, MANET, reactive routing protocol, routing protocol, Truetime.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1329855 Current Status of Industry 4.0 in Material Handling Automation and In-house Logistics
Authors: Orestis Κ. Efthymiou, Stavros T. Ponis
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In the last decade, a new industrial revolution seems to be emerging, supported -once again- by the rapid advancements of Information Technology in the areas of Machine-to-Machine (M2M) communication permitting large numbers of intelligent devices, e.g. sensors to communicate with each other and take decisions without any or minimum indirect human intervention. The advent of these technologies have triggered the emergence of a new category of hybrid (cyber-physical) manufacturing systems, combining advanced manufacturing techniques with innovative M2M applications based on the Internet of Things (IoT), under the umbrella term Industry 4.0. Even though the topic of Industry 4.0 has attracted much attention during the last few years, the attempts of providing a systematic literature review of the subject are scarce. In this paper, we present the authors’ initial study of the field with a special focus on the use and applications of Industry 4.0 principles in material handling automations and in-house logistics. Research shows that despite the vivid discussion and attractiveness of the subject, there are still many challenges and issues that have to be addressed before Industry 4.0 becomes standardized and widely applicable.Keywords: Industry 4.0, internet of things, manufacturing systems, material handling, logistics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1658854 A Novel Feedback-Based Integrated FiWi Networks Architecture by Centralized Interlink-ONU Communication
Authors: Noman Khan, B. S. Chowdhry, A.Q.K Rajput
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Integrated fiber-wireless (FiWi) access networks are a viable solution that can deliver the high profile quadruple play services. Passive optical networks (PON) networks integrated with wireless access networks provide ubiquitous characteristics for high bandwidth applications. Operation of PON improves by employing a variety of multiplexing techniques. One of it is time division/wavelength division multiplexed (TDM/WDM) architecture that improves the performance of optical-wireless access networks. This paper proposes a novel feedback-based TDM/WDM-PON architecture and introduces a model of integrated PON-FiWi networks. Feedback-based link architecture is an efficient solution to improves the performance of optical-line-terminal (OLT) and interlink optical-network-units (ONUs) communication. Furthermore, the feedback-based WDM/TDM-PON architecture is compared with existing architectures in terms of capacity of network throughput.
Keywords: Fiber-wireless (FiWi), Passive Optical Network (PON), TDM/WDM architecture
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1729853 Interactive Methods of Design Education as the Principles of Social Implications of Modern Communities
Authors: Pelin Yildiz
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The term interactive education indicates the meaning related with multidisciplinary aspects of distance education following contemporary means around a common basis with different functional requirements. The aim of this paper is to reflect the new techniques in education with the new methods and inventions. These methods are better supplied by interactivity. The integration of interactive facilities in the discipline of education with distance learning is not a new concept but in addition the usage of these methods on design issue is newly being adapted to design education. In this paper the general approach of this method and after the analysis of different samples, the advantages and disadvantages of these approaches are being identified. The method of this paper is to evaluate the related samples and then analyzing the main hypothesis. The main focus is to mention the formation processes of this education. Technological developments in education should be filtered around the necessities of the design education and the structure of the system could then be formed or renewed. The conclusion indicates that interactive methods of education in design issue is a meaning capturing not only technical and computational intelligence aspects but also aesthetical and artistic approaches coming together around the same purpose.Keywords: Interactive education, distance learning, designeducation, computational intelligence.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1642852 Determining Cluster Boundaries Using Particle Swarm Optimization
Authors: Anurag Sharma, Christian W. Omlin
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Self-organizing map (SOM) is a well known data reduction technique used in data mining. Data visualization can reveal structure in data sets that is otherwise hard to detect from raw data alone. However, interpretation through visual inspection is prone to errors and can be very tedious. There are several techniques for the automatic detection of clusters of code vectors found by SOMs, but they generally do not take into account the distribution of code vectors; this may lead to unsatisfactory clustering and poor definition of cluster boundaries, particularly where the density of data points is low. In this paper, we propose the use of a generic particle swarm optimization (PSO) algorithm for finding cluster boundaries directly from the code vectors obtained from SOMs. The application of our method to unlabeled call data for a mobile phone operator demonstrates its feasibility. PSO algorithm utilizes U-matrix of SOMs to determine cluster boundaries; the results of this novel automatic method correspond well to boundary detection through visual inspection of code vectors and k-means algorithm.
Keywords: Particle swarm optimization, self-organizing maps, clustering, data mining.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1718851 Developing an Advanced Algorithm Capable of Classifying News, Articles and Other Textual Documents Using Text Mining Techniques
Authors: R. B. Knudsen, O. T. Rasmussen, R. A. Alphinas
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The reason for conducting this research is to develop an algorithm that is capable of classifying news articles from the automobile industry, according to the competitive actions that they entail, with the use of Text Mining (TM) methods. It is needed to test how to properly preprocess the data for this research by preparing pipelines which fits each algorithm the best. The pipelines are tested along with nine different classification algorithms in the realm of regression, support vector machines, and neural networks. Preliminary testing for identifying the optimal pipelines and algorithms resulted in the selection of two algorithms with two different pipelines. The two algorithms are Logistic Regression (LR) and Artificial Neural Network (ANN). These algorithms are optimized further, where several parameters of each algorithm are tested. The best result is achieved with the ANN. The final model yields an accuracy of 0.79, a precision of 0.80, a recall of 0.78, and an F1 score of 0.76. By removing three of the classes that created noise, the final algorithm is capable of reaching an accuracy of 94%.
Keywords: Artificial neural network, competitive dynamics, logistic regression, text classification, text mining.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 535850 Fault Diagnosis of Nonlinear Systems Using Dynamic Neural Networks
Authors: E. Sobhani-Tehrani, K. Khorasani, N. Meskin
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This paper presents a novel integrated hybrid approach for fault diagnosis (FD) of nonlinear systems. Unlike most FD techniques, the proposed solution simultaneously accomplishes fault detection, isolation, and identification (FDII) within a unified diagnostic module. At the core of this solution is a bank of adaptive neural parameter estimators (NPE) associated with a set of singleparameter fault models. The NPEs continuously estimate unknown fault parameters (FP) that are indicators of faults in the system. Two NPE structures including series-parallel and parallel are developed with their exclusive set of desirable attributes. The parallel scheme is extremely robust to measurement noise and possesses a simpler, yet more solid, fault isolation logic. On the contrary, the series-parallel scheme displays short FD delays and is robust to closed-loop system transients due to changes in control commands. Finally, a fault tolerant observer (FTO) is designed to extend the capability of the NPEs to systems with partial-state measurement.
Keywords: Hybrid fault diagnosis, Dynamic neural networks, Nonlinear systems.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2221849 Development of New Control Techniques for Vibration Isolation of Structures using Smart Materials
Authors: Shubha P Bhat, Krishnamurthy, T.C.Manjunath, C. Ardil
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In this paper, the effects of the restoring force device on the response of a space frame structure resting on sliding type of bearing with a restoring force device is studied. The NS component of the El - Centro earthquake and harmonic ground acceleration is considered for earthquake excitation. The structure is modeled by considering six-degrees of freedom (three translations and three rotations) at each node. The sliding support is modeled as a fictitious spring with two horizontal degrees of freedom. The response quantities considered for the study are the top floor acceleration, base shear, bending moment and base displacement. It is concluded from the study that the displacement of the structure reduces by the use of the restoring force device. Also, the peak values of acceleration, bending moment and base shear also decreases. The simulation results show the effectiveness of the developed and proposed method.Keywords: DOF, Space structures, Acceleration, Excitation, Smart structure, Vibration, Isolation, Earthquakes.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1840848 Investigating the Geopolymerization Process of Aluminosilicates and Its Impact on the Compressive Strength of the Produced Geopolymers
Authors: Heba Z. Fouad, Tarek M. Madkour, Safwan A. Khedr
Abstract:
This paper investigates multiple factors that impact the formation of geopolymers and their compressive strength to be utilized in construction as an environmentally-friendly material. Bentonite and Kaolinite were thermally calcinated at 750 °C to obtain Metabentonite and Metakaolinite with higher reactivity. Both source materials were activated using a solution of sodium hydroxide (NaOH). Thereafter, samples were cured at different temperatures. The samples were analyzed chemically using a host of spectroscopic techniques. The bulk density and compressive strength of the produced geopolymer pastes were studied. Findings indicate that the ratio of NaOH solution to source material affects the compressive strength, being optimal at 0.54. Moreover, controlled heat curing was proven effective to improve compressive strength. The existence of characteristic Fourier Transform Infrared Spectroscopy (FTIR) peaks at approximately 1020 cm-1 and 460 cm-1 which correspond to the asymmetric stretching vibration of Si-O-T and bending vibration of Si-O-Si, hence, confirming the formation of the target geopolymer.
Keywords: alcination of metakaolinite, compressive strength, FTIR analysis, geopolymer, green cement
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 384847 UDCA: An Energy Efficient Clustering Algorithm for Wireless Sensor Network
Authors: Boregowda S.B., Hemanth Kumar A.R. Babu N.V, Puttamadappa C., And H.S Mruthyunjaya
Abstract:
In the past few years, the use of wireless sensor networks (WSNs) potentially increased in applications such as intrusion detection, forest fire detection, disaster management and battle field. Sensor nodes are generally battery operated low cost devices. The key challenge in the design and operation of WSNs is to prolong the network life time by reducing the energy consumption among sensor nodes. Node clustering is one of the most promising techniques for energy conservation. This paper presents a novel clustering algorithm which maximizes the network lifetime by reducing the number of communication among sensor nodes. This approach also includes new distributed cluster formation technique that enables self-organization of large number of nodes, algorithm for maintaining constant number of clusters by prior selection of cluster head and rotating the role of cluster head to evenly distribute the energy load among all sensor nodes.
Keywords: Clustering algorithms, Cluster head, Energy consumption, Sensor nodes, and Wireless sensor networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2390