Search results for: support vector machine
2243 A Neuron Model of Facial Recognition and Detection of an Authorized Entity Using Machine Learning System
Authors: J. K. Adedeji, M. O. Oyekanmi
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This paper has critically examined the use of Machine Learning procedures in curbing unauthorized access into valuable areas of an organization. The use of passwords, pin codes, user’s identification in recent times has been partially successful in curbing crimes involving identities, hence the need for the design of a system which incorporates biometric characteristics such as DNA and pattern recognition of variations in facial expressions. The facial model used is the OpenCV library which is based on the use of certain physiological features, the Raspberry Pi 3 module is used to compile the OpenCV library, which extracts and stores the detected faces into the datasets directory through the use of camera. The model is trained with 50 epoch run in the database and recognized by the Local Binary Pattern Histogram (LBPH) recognizer contained in the OpenCV. The training algorithm used by the neural network is back propagation coded using python algorithmic language with 200 epoch runs to identify specific resemblance in the exclusive OR (XOR) output neurons. The research however confirmed that physiological parameters are better effective measures to curb crimes relating to identities.
Keywords: Biometric characters, facial recognition, neural network, OpenCV.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6712242 Axisymmetric Nonlinear Analysis of Point Supported Shallow Spherical Shells
Authors: M. Altekin, R. F. Yükseler
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Geometrically nonlinear axisymmetric bending of a shallow spherical shell with a point support at the apex under linearly varying axisymmetric load was investigated numerically. The edge of the shell was assumed to be simply supported or clamped. The solution was obtained by the finite difference and the Newton-Raphson methods. The thickness of the shell was considered to be uniform and the material was assumed to be homogeneous and isotropic. Sensitivity analysis was made for two geometrical parameters. The accuracy of the algorithm was checked by comparing the deflection with the solution of point supported circular plates and good agreement was obtained.
Keywords: Bending, nonlinear, plate, point support, shell.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18532241 A Real-Time Specific Weed Recognition System Using Statistical Methods
Authors: Imran Ahmed, Muhammad Islam, Syed Inayat Ali Shah, Awais Adnan
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The identification and classification of weeds are of major technical and economical importance in the agricultural industry. To automate these activities, like in shape, color and texture, weed control system is feasible. The goal of this paper is to build a real-time, machine vision weed control system that can detect weed locations. In order to accomplish this objective, a real-time robotic system is developed to identify and locate outdoor plants using machine vision technology and pattern recognition. The algorithm is developed to classify images into broad and narrow class for real-time selective herbicide application. The developed algorithm has been tested on weeds at various locations, which have shown that the algorithm to be very effectiveness in weed identification. Further the results show a very reliable performance on weeds under varying field conditions. The analysis of the results shows over 90 percent classification accuracy over 140 sample images (broad and narrow) with 70 samples from each category of weeds.Keywords: Weed detection, Image Processing, real-timerecognition, Standard Deviation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22332240 Empirical Process Monitoring Via Chemometric Analysis of Partially Unbalanced Data
Authors: Hyun-Woo Cho
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Real-time or in-line process monitoring frameworks are designed to give early warnings for a fault along with meaningful identification of its assignable causes. In artificial intelligence and machine learning fields of pattern recognition various promising approaches have been proposed such as kernel-based nonlinear machine learning techniques. This work presents a kernel-based empirical monitoring scheme for batch type production processes with small sample size problem of partially unbalanced data. Measurement data of normal operations are easy to collect whilst special events or faults data are difficult to collect. In such situations, noise filtering techniques can be helpful in enhancing process monitoring performance. Furthermore, preprocessing of raw process data is used to get rid of unwanted variation of data. The performance of the monitoring scheme was demonstrated using three-dimensional batch data. The results showed that the monitoring performance was improved significantly in terms of detection success rate of process fault.
Keywords: Process Monitoring, kernel methods, multivariate filtering, data-driven techniques, quality improvement.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17202239 PhilSHORE: Development of a WebGIS-Based Marine Spatial Planning Tool for Tidal Current Energy Resource Assessment and Site Suitability Analysis
Authors: Ma. Rosario Concepcion O. Ang, Luis Caezar Ian K. Panganiban, Charmyne B. Mamador, Oliver Dan G. De Luna, Michael D. Bausas, Joselito P. Cruz
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PhilSHORE is a multi-site, multi-device and multicriteria decision support tool designed to support the development of tidal current energy in the Philippines. Its platform is based on Geographic Information Systems (GIS) which allows for the collection, storage, processing, analyses and display of geospatial data. Combining GIS tools with open source web development applications, PhilSHORE becomes a webGIS-based marine spatial planning tool. To date, PhilSHORE displays output maps and graphs of power and energy density, site suitability and site-device analysis. It enables stakeholders and the public easy access to the results of tidal current energy resource assessments and site suitability analyses. Results of the initial development show that PhilSHORE is a promising decision support tool for ORE project developments.Keywords: GIS, Site Suitability Analysis, Tidal Current Energy Resource Assessment, WebGIS.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26642238 Advance in Monitoring and Process Control of Surface Roughness
Authors: Somkiat Tangjitsitcharoen, Siripong Damrongthaveesak
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This paper presents an advance in monitoring and process control of surface roughness in CNC machine for the turning and milling processes. An integration of the in-process monitoring and process control of the surface roughness is proposed and developed during the machining process by using the cutting force ratio. The previously developed surface roughness models for turning and milling processes of the author are adopted to predict the inprocess surface roughness, which consist of the cutting speed, the feed rate, the tool nose radius, the depth of cut, the rake angle, and the cutting force ratio. The cutting force ratios obtained from the turning and the milling are utilized to estimate the in-process surface roughness. The dynamometers are installed on the tool turret of CNC turning machine and the table of 5-axis machining center to monitor the cutting forces. The in-process control of the surface roughness has been developed and proposed to control the predicted surface roughness. It has been proved by the cutting tests that the proposed integration system of the in-process monitoring and the process control can be used to check the surface roughness during the cutting by utilizing the cutting force ratio.
Keywords: Turning, milling, monitoring, surface roughness, cutting force ratio.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20992237 Measures and Influence of a Baw Filter on Digital Radio-Communications Signals
Authors: A. Diet, M. Villegas, G. Baudoin
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This work concerns the measurements of a Bulk Acoustic Waves (BAW) emission filter S parameters and compare with prototypes simulated types. Thanks to HP-ADS, a co-simulation of filters- characteristics in a digital radio-communication chain is performed. Four cases of modulation schemes are studied in order to illustrate the impact of the spectral occupation of the modulated signal. Results of simulations and co-simulation are given in terms of Error Vector Measurements to be useful for a general sensibility analysis of 4th/3rd Generation (G.) emitters (wideband QAM and OFDM signals)Keywords: RF architectures, BAW filters.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27482236 Employing Operations Research at Universities to Build Management Systems
Authors: Abdallah A. Hlayel
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Operations research science (OR) deals with good success in developing and applying scientific methods for problem solving and decision-making. However, by using OR techniques, we can enhance the use of computer decision support systems to achieve optimal management for institutions. OR applies comprehensive analysis including all factors that effect on it and builds mathematical modeling to solve business or organizational problems. In addition, it improves decision-making and uses available resources efficiently. The adoption of OR by universities would definitely contributes to the development and enhancement of the performance of OR techniques. This paper provides an understanding of the structures, approaches and models of OR in problem solving and decisionmaking.
Keywords: Best candidates' method, decision making, decision support system, operations research.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18712235 Scheduling Maintenance Actions for Gas Turbines Aircraft Engines
Authors: Anis Gharbi
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This paper considers the problem of scheduling maintenance actions for identical aircraft gas turbine engines. Each one of the turbines consists of parts which frequently require replacement. A finite inventory of spare parts is available and all parts are ready for replacement at any time. The inventory consists of both new and refurbished parts. Hence, these parts have different field lives. The goal is to find a replacement part sequencing that maximizes the time that the aircraft will keep functioning before the inventory is replenished. The problem is formulated as an identical parallel machine scheduling problem where the minimum completion time has to be maximized. Two models have been developed. The first one is an optimization model which is based on a 0-1 linear programming formulation, while the second one is an approximate procedure which consists in decomposing the problem into several two-machine subproblems. Each subproblem is optimally solved using the first model. Both models have been implemented using Lingo and have been tested on two sets of randomly generated data with up to 150 parts and 10 turbines. Experimental results show that the optimization model is able to solve only instances with no more than 4 turbines, while the decomposition procedure often provides near-optimal solutions within a maximum CPU time of 3 seconds.
Keywords: Aircraft turbines, Scheduling, Identical parallel machines, 0-1 linear programming, Heuristic.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19752234 Enabling Integration across Heterogeneous Care Networks
Authors: Federico Cabitza, Marco P. Locatelli, Marcello Sarini, Carla Simone
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The paper shows how the CASMAS modeling language, and its associated pervasive computing architecture, can be used to facilitate continuity of care by providing members of patientcentered communities of care with a support to cooperation and knowledge sharing through the usage of electronic documents and digital devices. We consider a scenario of clearly fragmented care to show how proper mechanisms can be defined to facilitate a better integration of practices and information across heterogeneous care networks. The scenario is declined in terms of architectural components and cooperation-oriented mechanisms that make the support reactive to the evolution of the context where these communities operate.Keywords: Pervasive Computing, Communities of Care, HeterogeneousCare Networks, Multi-Agent System.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13322233 Assessing and Managing Intellectual Capital to Support Open Innovation Paradigm
Authors: Michele Grimaldi, Livio Cricelli, Francesco Rogo, Alessia Iannarelli
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The objective of this paper is to support the application of Open Innovation practices in firms and organizations by the assessment and management of Intellectual Capital. Intellectual Capital constituents are analyzed in order to verify their capability of acting as key drivers of Open Innovation processes and, therefore, of creating value. A methodology is defined to settle a procedure which helps to select the most relevant Intellectual Capital value drivers and to provide Communities of Innovation with strategic and managerial guidelines in sustaining Open Innovation paradigm. An application of the methodology is developed within a specifically addressed project and its results are hereafter examined.
Keywords: Assessment, Community of Innovation, Intellectual Capital, Management, Open Innovation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17592232 Computing Center Conditions for Non-analytic Vector Fields with Constant Angular Speed
Authors: Li Feng
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We investigate the planar quasi-septic non-analytic systems which have a center-focus equilibrium at the origin and whose angular speed is constant. The system could be changed into an analytic system by two transformations, with the help of computer algebra system MATHEMATICA, the conditions of uniform isochronous center are obtained.
Keywords: Non-analytic, center–focus problem, Lyapunov constant, uniform isochronous center.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12792231 Exploiting Machine Learning Techniques for the Enhancement of Acceptance Sampling
Authors: Aikaterini Fountoulaki, Nikos Karacapilidis, Manolis Manatakis
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This paper proposes an innovative methodology for Acceptance Sampling by Variables, which is a particular category of Statistical Quality Control dealing with the assurance of products quality. Our contribution lies in the exploitation of machine learning techniques to address the complexity and remedy the drawbacks of existing approaches. More specifically, the proposed methodology exploits Artificial Neural Networks (ANNs) to aid decision making about the acceptance or rejection of an inspected sample. For any type of inspection, ANNs are trained by data from corresponding tables of a standard-s sampling plan schemes. Once trained, ANNs can give closed-form solutions for any acceptance quality level and sample size, thus leading to an automation of the reading of the sampling plan tables, without any need of compromise with the values of the specific standard chosen each time. The proposed methodology provides enough flexibility to quality control engineers during the inspection of their samples, allowing the consideration of specific needs, while it also reduces the time and the cost required for these inspections. Its applicability and advantages are demonstrated through two numerical examples.Keywords: Acceptance Sampling, Neural Networks, Statistical Quality Control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16632230 Performance Evaluation of Minimum Quantity Lubrication on EN3 Mild Steel Turning
Authors: Swapnil Rajan Jadhav, Ajay Vasantrao Kashikar
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Lubrication, cooling and chip removal are the desired functions of any cutting fluid. Conventional or flood lubrication requires high volume flow rate and cost associated with this is higher. In addition, flood lubrication possesses health risks to machine operator. To avoid these consequences, dry machining and minimum quantity are two alternatives. Dry machining cannot be a suited alternative as it can generate greater heat and poor surface finish. Here, turning work is carried out on a Lathe machine using EN3 Mild steel. Variable cutting speeds and depth of cuts are provided and corresponding temperatures and surface roughness values were recorded. Experimental results are analyzed by Minitab software. Regression analysis, main effect plot, and interaction plot conclusion are drawn by using ANOVA. There is a 95.83% reduction in the use of cutting fluid. MQL gives a 9.88% reduction in tool temperature, this will improve tool life. MQL produced a 17.64% improved surface finish. MQL appears to be an economical and environmentally compatible lubrication technique for sustainable manufacturing.
Keywords: ANOVA, MQL, regression analysis, surface roughness
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4402229 Performance Evaluation of Minimum Quantity Lubrication on EN3 Mild Steel Turning
Authors: Swapnil Rajan Jadhav, Ajay Vasantrao Kashikar
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Lubrication, cooling and chip removal are the desired functions of any cutting fluid. Conventional or flood lubrication requires high volume flow rate and cost associated with this is higher. In addition, flood lubrication possesses health risks to machine operator. To avoid these consequences, dry machining and minimum quantity are two alternatives. Dry machining cannot be a suited alternative as it can generate greater heat and poor surface finish. Here, turning work is carried out on a Lathe machine using EN3 Mild steel. Variable cutting speeds and depth of cuts are provided and corresponding temperatures and surface roughness values were recorded. Experimental results are analyzed by Minitab software. Regression analysis, main effect plot, and interaction plot conclusion are drawn by using ANOVA. There is a 95.83% reduction in the use of cutting fluid. MQL gives a 9.88% reduction in tool temperature, this will improve tool life. MQL produced a 17.64% improved surface finish. MQL appears to be an economical and environmentally compatible lubrication technique for sustainable manufacturing.
Keywords: ANOVA, MQL, regression analysis, surface roughness
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3372228 Effect of Support Distance on Damage of Drilled Thin CFRP Laminates
Authors: Jean François Chatelain, Imed Zaghbani, Gilbert Lebrun, Kaml Hasni
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Severe damages may occur during the drilling of carbon fiber reinforced plastics (CFRP). In practice, this damage is limited by adding a backup support to the drilled parts. For some aeronautical parts with curvatures, backing up parts is a demanding process. In order to simplify the operation, this research studies the effect of using a configurable setup to support parts on the resulting quality of drilled holes. The test coupons referenced in this study are twenty four-plies unidirectional laminates made of carbon fibers and epoxy resin. Different signals were measured during the drilling process for these laminates, including the thrust force, the displacement and the acceleration. The processing of these signals demonstrated that the damage is due to the combination of two main factors: the spring-back of the thin part and the thrust force. The results found were confirmed for different feeds and speeds. When the distance between supports is increased, it is observed that the spring-back increases but the thrust force decreases. The study proves the feasibility of unsupported drilling of thin CFRP laminates without creating any observable damage.
Keywords: CFRP, Damage, Drilling, Flexible setup.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17662227 The Control Vector Scheme for Design of Planar Primitive PH curves
Authors: Ching-Shoei Chiang, Sheng-Hsin Tsai, James Chen
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The PH curve can be constructed by given parameters, but the shape of the curve is not so easy to image from the value of the parameters. On the contract, Bézier curve can be constructed by the control polygon, and from the control polygon, we can image the figure of the curve. In this paper, we want to use the hodograph of Bézier curve to construct PH curve by selecting part of the control vectors, and produce other control vectors, so the property of PH curve exists.Keywords: PH curve, hodograph, Bézier curve.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14672226 A Decision Support System for Predicting Hospitalization of Hemodialysis Patients
Authors: Jinn-Yi Yeh, Tai-Hsi Wu
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Hemodialysis patients might suffer from unhealthy care behaviors or long-term dialysis treatments. Ultimately they need to be hospitalized. If the hospitalization rate of a hemodialysis center is high, its quality of service would be low. Therefore, how to decrease hospitalization rate is a crucial problem for health care. In this study we combined temporal abstraction with data mining techniques for analyzing the dialysis patients' biochemical data to develop a decision support system. The mined temporal patterns are helpful for clinicians to predict hospitalization of hemodialysis patients and to suggest them some treatments immediately to avoid hospitalization.Keywords: Hemodialysis, Temporal abstract, Data mining, Healthcare quality.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17072225 Sensor Network Based Emergency Response and Navigation Support Architecture
Authors: Dilusha Weeraddana, Ashanie Gunathillake, Samiru Gayan
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In an emergency, combining Wireless Sensor Network's data with the knowledge gathered from various other information sources and navigation algorithms, could help safely guide people to a building exit while avoiding the risky areas. This paper presents an emergency response and navigation support architecture for data gathering, knowledge manipulation, and navigational support in an emergency situation. At normal state, the system monitors the environment. When an emergency event detects, the system sends messages to first responders and immediately identifies the risky areas from safe areas to establishing escape paths. The main functionalities of the system include, gathering data from a wireless sensor network which is deployed in a multi-story indoor environment, processing it with information available in a knowledge base, and sharing the decisions made, with first responders and people in the building. The proposed architecture will act to reduce risk of losing human lives by evacuating people much faster with least congestion in an emergency environment.
Keywords: Emergency response, Firefighters, Navigation, Wireless sensor network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19792224 Current Issues on Enterprise Architecture Implementation Evaluation
Authors: Fatemeh Nikpay, Rodina Binti Ahmad, Babak Darvish Rouhani
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Enterprise Architecture (EA) is employed by enterprises for providing integrated Information Systems (ISs) in order to support alignment of their business and Information Technology (IT). Evaluation of EA implementation can support enterprise to reach intended goals. There are some problems in current evaluation methods of EA implementation that lead to ineffectiveness implementation of EA. This paper represents current issues on evaluation of EA implementation. In this regard, we set the framework in order to represent evaluation’s issues based on their functionality and structure. The results of this research not only increase the knowledge of evaluation, but also could be useful for both academics and practitioners in order to realize the current situation of evaluations.
Keywords: Current issues on EA, implementation evaluation, Evaluation, Enterprise Architecture, Evaluation of Enterprise Architecture Implementation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 39822223 On Frenet-Serret Invariants of Non-Null Curves in Lorentzian Space L5
Authors: Melih Turgut, José Luis López-Bonilla, Süha Yılmaz
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The aim of this paper is to determine Frenet-Serret invariants of non-null curves in Lorentzian 5-space. First, we define a vector product of four vectors, by this way, we present a method to calculate Frenet-Serret invariants of the non-null curves. Additionally, an algebraic example of presented method is illustrated.
Keywords: Lorentzian 5-space, Frenet-Serret Invariants, Nonnull Curves
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14942222 Harmonic Analysis and Performance Improvement of a Wind Energy Conversions System with Double Output Induction Generator
Authors: M. Sedighizadeh, A. Rezazadeh
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Wind turbines with double output induction generators can operate at variable speed permitting conversion efficiency maximization over a wide range of wind velocities. This paper presents the performance analysis of a wind driven double output induction generator (DOIG) operating at varying shafts speed. A periodic transient state analysis of DOIG equipped with two converters is carried out using a hybrid induction machine model. This paper simulates the harmonic content of waveforms in various points of drive at different speeds, based on the hybrid model (dqabc). Then the sinusoidal and trapezoidal pulse-width–modulation control techniques are used in order to improve the power factor of the machine and to weaken the injected low order harmonics to the supply. Based on the frequency spectrum, total harmonics distortion, distortion factor and power factor. Finally advantages of sinusoidal and trapezoidal pulse width modulation techniques are compared.Keywords: DOIG, Harmonic Analysis, Wind.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17702221 Development System for Emotion Detection Based on Brain Signals and Facial Images
Authors: Suprijanto, Linda Sari, Vebi Nadhira , IGN. Merthayasa. Farida I.M
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Detection of human emotions has many potential applications. One of application is to quantify attentiveness audience in order evaluate acoustic quality in concern hall. The subjective audio preference that based on from audience is used. To obtain fairness evaluation of acoustic quality, the research proposed system for multimodal emotion detection; one modality based on brain signals that measured using electroencephalogram (EEG) and the second modality is sequences of facial images. In the experiment, an audio signal was customized which consist of normal and disorder sounds. Furthermore, an audio signal was played in order to stimulate positive/negative emotion feedback of volunteers. EEG signal from temporal lobes, i.e. T3 and T4 was used to measured brain response and sequence of facial image was used to monitoring facial expression during volunteer hearing audio signal. On EEG signal, feature was extracted from change information in brain wave, particularly in alpha and beta wave. Feature of facial expression was extracted based on analysis of motion images. We implement an advance optical flow method to detect the most active facial muscle form normal to other emotion expression that represented in vector flow maps. The reduce problem on detection of emotion state, vector flow maps are transformed into compass mapping that represents major directions and velocities of facial movement. The results showed that the power of beta wave is increasing when disorder sound stimulation was given, however for each volunteer was giving different emotion feedback. Based on features derived from facial face images, an optical flow compass mapping was promising to use as additional information to make decision about emotion feedback.
Keywords: Multimodal Emotion Detection, EEG, Facial Image, Optical Flow, compass mapping, Brain Wave
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22622220 Kalman Filter for Bilinear Systems with Application
Authors: Abdullah E. Al-Mazrooei
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In this paper, we present a new kind of the bilinear systems in the form of state space model. The evolution of this system depends on the product of state vector by its self. The well known Lotak Volterra and Lorenz models are special cases of this new model. We also present here a generalization of Kalman filter which is suitable to work with the new bilinear model. An application to real measurements is introduced to illustrate the efficiency of the proposed algorithm.
Keywords: Bilinear systems, state space model, Kalman filter.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19402219 Ontology-based Query System for UNITEN Postgraduate Students
Authors: Zaihisma C. Cob, Alicia Y.C. Tang, Sharifah J. Syed Aziz
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This paper proposes a new model to support user queries on postgraduate research information at Universiti Tenaga Nasional. The ontology to be developed will contribute towards shareable and reusable domain knowledge that makes knowledge assets intelligently accessible to both people and software. This work adapts a methodology for ontology development based on the framework proposed by Uschold and King. The concepts and relations in this domain are represented in a class diagram using the Protégé software. The ontology will be used to support a menudriven query system for assisting students in searching for information related to postgraduate research at the university.Keywords: Ontology, Protégé, postgraduate program, query system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16452218 Synthesis of Filtering in Stochastic Systems on Continuous-Time Memory Observations in the Presence of Anomalous Noises
Authors: S. Rozhkova, O. Rozhkova, A. Harlova, V. Lasukov
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We have conducted the optimal synthesis of rootmean- squared objective filter to estimate the state vector in the case if within the observation channel with memory the anomalous noises with unknown mathematical expectation are complement in the function of the regular noises. The synthesis has been carried out for linear stochastic systems of continuous - time.
Keywords: Mathematical expectation, filtration, anomalous noise, memory.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19372217 The Hybrid Knowledge Model for Product Development Management
Authors: Heejung Lee, Hyo-Won Suh
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Hybrid knowledge model is suggested as an underlying framework for product development management. It can support such hybrid features as ontologies and rules. Effective collaboration in product development environment depends on sharing and reasoning product information as well as engineering knowledge. Many studies have considered product information and engineering knowledge. However, most previous research has focused either on building the ontology of product information or rule-based systems of engineering knowledge. This paper shows that F-logic based knowledge model can support such desirable features in a hybrid way.Keywords: Ontology, rule, F-logic, product development.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14472216 Weighted-Distance Sliding Windows and Cooccurrence Graphs for Supporting Entity-Relationship Discovery in Unstructured Text
Authors: Paolo Fantozzi, Luigi Laura, Umberto Nanni
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The problem of Entity relation discovery in structured data, a well covered topic in literature, consists in searching within unstructured sources (typically, text) in order to find connections among entities. These can be a whole dictionary, or a specific collection of named items. In many cases machine learning and/or text mining techniques are used for this goal. These approaches might be unfeasible in computationally challenging problems, such as processing massive data streams. A faster approach consists in collecting the cooccurrences of any two words (entities) in order to create a graph of relations - a cooccurrence graph. Indeed each cooccurrence highlights some grade of semantic correlation between the words because it is more common to have related words close each other than having them in the opposite sides of the text. Some authors have used sliding windows for such problem: they count all the occurrences within a sliding windows running over the whole text. In this paper we generalise such technique, coming up to a Weighted-Distance Sliding Window, where each occurrence of two named items within the window is accounted with a weight depending on the distance between items: a closer distance implies a stronger evidence of a relationship. We develop an experiment in order to support this intuition, by applying this technique to a data set consisting in the text of the Bible, split into verses.Keywords: Cooccurrence graph, entity relation graph, unstructured text, weighted distance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6562215 Result Validation Analysis of Steel Testing Machines
Authors: Wasiu O. Ajagbe, Habeeb O. Hamzat, Waris A. Adebisi
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Structural failures occur due to a number of reasons. These may include under design, poor workmanship, substandard materials, misleading laboratory tests and lots more. Reinforcing steel bar is an important construction material, hence its properties must be accurately known before being utilized in construction. Understanding this property involves carrying out mechanical tests prior to design and during construction to ascertain correlation using steel testing machine which is usually not readily available due to the location of project. This study was conducted to determine the reliability of reinforcing steel testing machines. Reconnaissance survey was conducted to identify laboratories where yield and ultimate tensile strengths tests can be carried out. Six laboratories were identified within Ibadan and environs. However, only four were functional at the time of the study. Three steel samples were tested for yield and tensile strengths, using a steel testing machine, at each of the four laboratories (LM, LO, LP and LS). The yield and tensile strength results obtained from the laboratories were compared with the manufacturer’s specification using a reliability analysis programme. Structured questionnaire was administered to the operators in each laboratory to consider their impact on the test results. The average value of manufacturers’ tensile strength and yield strength are 673.7 N/mm2 and 559.7 N/mm2 respectively. The tensile strength obtained from the four laboratories LM, LO, LP and LS are given as 579.4, 652.7, 646.0 and 649.9 N/mm2 respectively while their yield strengths respectively are 453.3, 597.0, 550.7 and 564.7 N/mm2. Minimum tensile to yield strength ratio is 1.08 for BS 4449: 2005 and 1.15 for ASTM A615. Tensile to yield strength ratio from the four laboratories are 1.28, 1.09, 1.17 and 1.15 for LM, LO, LP and LS respectively. The tensile to yield strength ratio shows that the result obtained from all the laboratories meet the code requirements used for the test. The result of the reliability test shows varying level of reliability between the manufacturers’ specification and the result obtained from the laboratories. Three of the laboratories; LO, LS and LP have high value of reliability with the manufacturer i.e. 0.798, 0.866 and 0.712 respectively. The fourth laboratory, LM has a reliability value of 0.100. Steel test should be carried out in a laboratory using the same code in which the structural design was carried out. More emphasis should be laid on the importance of code provisions.
Keywords: Reinforcing steel bars, reliability analysis, tensile strength, universal testing machine, yield strength.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7202214 Comparison of Deep Convolutional Neural Networks Models for Plant Disease Identification
Authors: Megha Gupta, Nupur Prakash
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Identification of plant diseases has been performed using machine learning and deep learning models on the datasets containing images of healthy and diseased plant leaves. The current study carries out an evaluation of some of the deep learning models based on convolutional neural network architectures for identification of plant diseases. For this purpose, the publicly available New Plant Diseases Dataset, an augmented version of PlantVillage dataset, available on Kaggle platform, containing 87,900 images has been used. The dataset contained images of 26 diseases of 14 different plants and images of 12 healthy plants. The CNN models selected for the study presented in this paper are AlexNet, ZFNet, VGGNet (four models), GoogLeNet, and ResNet (three models). The selected models are trained using PyTorch, an open-source machine learning library, on Google Colaboratory. A comparative study has been carried out to analyze the high degree of accuracy achieved using these models. The highest test accuracy and F1-score of 99.59% and 0.996, respectively, were achieved by using GoogLeNet with Mini-batch momentum based gradient descent learning algorithm.
Keywords: comparative analysis, convolutional neural networks, deep learning, plant disease identification
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