Search results for: Ground Response Analysis

Authors: Heejung Lee

Abstract:

To offer a large variety of products while maintaining low costs, high speed, and high quality in a mass customization product development environment, platform based product development has much benefit and usefulness in many industry fields. This paper proposes a product configuration strategy by similarity measure, incorporating the knowledge engineering principles such as product information model, ontology engineering, and formal concept analysis.

Keywords: Platform, product family, ontology, formal concept analysis.

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Authors: M.S.Nourbakhsh, M.E.khosroshahi

Abstract:

Gold coated silica core nanoparticles have an optical response dictated by the plasmon resonance. The wavelength at which the resonance occurs depends on the core and shell sizes, allowing nanoshells to be tailored for particular applications. The purposes of this study was to synthesize and use different concentration of gold nanoshells as exogenous material for skin tissue soldering and also to examine the effect of laser soldering parameters on the properties of repaired skin. Two mixtures of albumin solder and different concentration of gold nanoshells were prepared. A full thickness incision of 2×20 mm2 was made on the surface and after addition of mixtures it was irradiated by an 810nm diode laser at different power densities. The changes of tensile strength σt due to temperature rise, number of scan (Ns), and scan velocity (Vs) were investigated. The results showed at constant laser power density (I), σt of repaired incisions increases by increasing the concentration of gold nanoshells, Ns and decreasing Vs. It is therefore important to consider the trade off between the scan velocity and the surface temperature for achieving an optimum operating condition. In our case this corresponds to σt =1610 gr/cm2 at I~ 60 Wcm-2, T ~ 65ºC, Ns =10 and Vs=0.2mms-1.

Keywords: Tissue soldering, Diode laser, Gold Nanoshells, Tensile strength

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Authors: Nahid Ardalani, Ahmadreza Khoogar, H. Roohi

Abstract:

In this paper we compare the response of linear and nonlinear neural network-based prediction schemes in prediction of received Signal-to-Interference Power Ratio (SIR) in Direct Sequence Code Division Multiple Access (DS/CDMA) systems. The nonlinear predictor is Multilayer Perceptron MLP and the linear predictor is an Adaptive Linear (Adaline) predictor. We solve the problem of complexity by using the Minimum Mean Squared Error (MMSE) principle to select the optimal predictors. The optimized Adaline predictor is compared to optimized MLP by employing noisy Rayleigh fading signals with 1.8 GHZ carrier frequency in an urban environment. The results show that the Adaline predictor can estimates SIR with the same error as MLP when the user has the velocity of 5 km/h and 60 km/h but by increasing the velocity up-to 120 km/h the mean squared error of MLP is two times more than Adaline predictor. This makes the Adaline predictor (with lower complexity) more suitable than MLP for closed-loop power control where efficient and accurate identification of the time-varying inverse dynamics of the multi path fading channel is required.

Keywords: Power control, neural networks, DS/CDMA mobilecommunication systems.

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Authors: Yingjie Zhang, Ming Li, Ying Zhang, Jing Zhang, Zuolei Hu

Abstract:

In the actual start-up process of DC motors, the DC drive system often faces a conflict between energy consumption and acceleration performance. To resolve the conflict, this paper proposes a comprehensive performance index that energy consumption index is added on the basis of classical control performance index in the DC motor starting process. Taking the comprehensive performance index as the cost function, particle swarm optimization algorithm is designed to optimize the comprehensive performance. Then it conducts simulations on the optimization of the comprehensive performance of the DC motor on condition that the weight coefficient of the energy consumption index should be properly designed. The simulation results show that as the weight of energy consumption increased, the energy efficiency was significantly improved at the expense of a slight sacrifice of fastness indicators with the comprehensive performance index method. The energy efficiency was increased from 63.18% to 68.48% and the response time reduced from 0.2875s to 0.1736s simultaneously compared with traditional proportion integrals differential controller in energy saving.

Keywords: Comprehensive performance index, energy consumption, acceleration performance, particle swarm optimal control.

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Authors: Diego Ordonez, Carlos Dafonte, Minia Manteiga, Bernardino Arcayy

Abstract:

This work presents a neural network model for the clustering analysis of data based on Self Organizing Maps (SOM). The model evolves during the training stage towards a hierarchical structure according to the input requirements. The hierarchical structure symbolizes a specialization tool that provides refinements of the classification process. The structure behaves like a single map with different resolutions depending on the region to analyze. The benefits and performance of the algorithm are discussed in application to the Iris dataset, a classical example for pattern recognition.

Keywords: Neural networks, Self-organizing feature maps, Hierarchicalsystems, Pattern clustering methods.

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Authors: P. Srinivas, P. V. N. Prasad

Abstract:

Since torque ripple is the main cause of noise and vibrations, the performance of Switched Reluctance Motor (SRM) can be improved by minimizing its torque ripple using a novel control technique called Direct Torque Control (DTC). In DTC technique, torque is controlled directly through control of magnitude of the flux and change in speed of the stator flux vector. The flux and torque are maintained within set hysteresis bands.

The DTC of SRM is analyzed by two methods. In one method, the actual torque is computed by conducting Finite Element Analysis (FEA) on the design specifications of the motor. In the other method, the torque is computed by Simplified Torque Equation. The variation of peak current, average current, torque ripple and speed settling time with Simplified Torque Equation model is compared with FEA based model.

Keywords: Direct Toque Control, Simplified Torque Equation, Finite Element Analysis, Torque Ripple.

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Authors: Ji-Hye Kim, Sung-Gaun Kim

Abstract:

Electro-hydraulic power steering (EHPS) system for the fuel rate reduction and steering feel improvement is comprised of ECU including the logic which controls the steering system and BL DC motor and produces the best suited cornering force, BLDC motor, high pressure pump integrated module and basic oil-hydraulic circuit of the commercial HPS system. Electro-hydraulic system can be studied in two ways such as experimental and computer simulation. To get accurate results in experimental study of EHPS system, the real boundary management is necessary which is difficult task. And the accuracy of the experimental results depends on the preparation of the experimental setup and accuracy of the data collection. The computer simulation gives accurate and reliable results if the simulation is carried out considering proper boundary conditions. So, in this paper, each component of EHPS was modeled, and the model-based analysis and control logic was designed by using AMESim

Keywords: Power steering system, Electro-Hydraulic power steering (EHPS) system, Modeling of EHPS system, Analysis modeling.

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Authors: Vishwajit M. Ghatge, David Looper

Abstract:

Over the last few decades, oilfield service rolling equipment has significantly increased in weight, primarily because of emissions regulations, which require larger/heavier engines, larger cooling systems, and emissions after-treatment systems, in some cases, etc. Larger engines cause more vibration and shock loads, leading to failure of electronics and control systems. If the vibrating frequency of the engine matches the system frequency, high resonance is observed on structural parts and mounts. One such existing automated control equipment system comprising wire rope mounts used for mounting computers was designed approximately 12 years ago. This includes the use of an industrialgrade computer to control the system operation. The original computer had a smaller, lighter enclosure. After a few years, a newer computer version was introduced, which was 10 lbm heavier. Some failures of internal computer parts have been documented for cases in which the old mounts were used. Because of the added weight, there is a possibility of having the two brackets impact each other under off-road conditions, which causes a high shock input to the computer parts. This added failure mode requires validating the existing mount design to suit the new heavy-weight computer. This paper discusses the modal finite element method (FEM) analysis and experimental modal analysis conducted to study the effects of vibration on the wire rope mounts and the computer. The existing mount was modelled in ANSYS software, and resultant mode shapes and frequencies were obtained. The experimental modal analysis was conducted, and actual frequency responses were observed and recorded. Results clearly revealed that at resonance frequency, the brackets were colliding and potentially causing damage to computer parts. To solve this issue, spring mounts of different stiffness were modeled in ANSYS software, and the resonant frequency was determined. Increasing the stiffness of the system increased the resonant frequency zone away from the frequency window at which the engine showed heavy vibrations or resonance. After multiple iterations in ANSYS software, the stiffness of the spring mount was finalized, which was again experimentally validated.

Keywords: Experimental Modal Analysis, FEM Modal Analysis, Frequency, Modal Analysis, Resonance, Vibration.

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Authors: Ahmad Sharieh, R Bremananth

Abstract:

Artificial Intelligence based gaming is an interesting topic in the state-of-art technology. This paper presents an automation of a tradition Omani game, called Al-Hawalees. Its related issues are resolved and implemented using artificial intelligence approach. An AI approach called mini-max procedure is incorporated to make a diverse budges of the on-line gaming. If number of moves increase, time complexity will be increased in terms of propositionally. In order to tackle the time and space complexities, we have employed a back propagation neural network (BPNN) to train in off-line to make a decision for resources required to fulfill the automation of the game. We have utilized Leverberg- Marquardt training in order to get the rapid response during the gaming. A set of optimal moves is determined by the on-line back propagation training fashioned with alpha-beta pruning. The results and analyses reveal that the proposed scheme will be easily incorporated in the on-line scenario with one player against the system.

Keywords: Artificial neural network, back propagation gaming, Leverberg-Marquardt, minimax procedure.

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Authors: C. I. Omohimi, O. P. Sobukola, K. O. Sarafadeen, L.O. Sanni

Abstract:

Flour from Mucuna beans (Mucuna pruriens) were used in producing texturized meat analogue using a single screw extruder to monitor modifications on the proximate composition and the functional properties at high moisture level. Response surface methodology based on Box Behnken design at three levels of barrel temperature (110, 120, 130°C), screw speed (100,120,140rpm) and feed moisture (44, 47, 50%) were used in 17 runs. Regression models describing the effect of variables on the product responses were obtained. Descriptive profile analyses and consumer acceptability test were carried out on optimized flavoured extruded meat analogue. Responses were mostly affected by barrel temperature and moisture level and to a lesser extent by screw speed. Optimization results based on desirability concept indicated that a barrel temperature of 120.15°C, feed moisture of 47% and screw speed of 119.19 rpm would produce meat analogue of preferable proximate composition, functional and sensory properties which reveals consumers` likeness for the product.

Keywords: Functional properties, mucuna bean flour, optimization, proximate composition, texturized meat analogue.

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Authors: S. Qaedi, S. Seyedtabaii

Abstract:

Non-Destructive evaluation of in-service power transformer condition is necessary for avoiding catastrophic failures. Dissolved Gas Analysis (DGA) is one of the important methods. Traditional, statistical and intelligent DGA approaches have been adopted for accurate classification of incipient fault sources. Unfortunately, there are not often enough faulty patterns required for sufficient training of intelligent systems. By bootstrapping the shortcoming is expected to be alleviated and algorithms with better classification success rates to be obtained. In this paper the performance of an artificial neural network, K-Nearest Neighbour and support vector machine methods using bootstrapped data are detailed and shown that while the success rate of the ANN algorithms improves remarkably, the outcome of the others do not benefit so much from the provided enlarged data space. For assessment, two databases are employed: IEC TC10 and a dataset collected from reported data in papers. High average test success rate well exhibits the remarkable outcome.

Keywords: Dissolved gas analysis, Transformer incipient fault, Artificial Neural Network, Support Vector Machine (SVM), KNearest Neighbor (KNN)

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Authors: A. Kurşun, M. Tunay Çetin, E. Çetin, H. Aykul

Abstract:

In this investigation an elastic stress analysis is carried out a woven steel fiber reinforced thermoplastic cantilever beam loaded uniformly at the upper surface. The composite beam material consists of low density polyethylene as a thermoplastic (LDFE, f.2.12) and woven steel fibers. Granules of the polyethylene are put into the moulds and they are heated up to 160°C by using electrical resistance. Subsequently, the material is held for 5min under 2.5 MPa at this temperature. The temperature is decreased to 30°C under 15 MPa pressure in 3min. Closed form solution is found satisfying both the governing differential equation and boundary conditions. We investigated orientation angle effect on stress distribution of composite cantilever beams. The results show that orientation angle play an important role in determining the responses of a woven steel fiber reinforced thermoplastic cantilever beams and an optimal design of these structures.

Keywords: Cantilever beam, elastic stress analysis, orientation angle, thermoplastic.

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Authors: S. Sendhilkumar, N. Mohanasundaram, M. Senthilkumar, S. N. Sivanandam

Abstract:

The operational life of rotating machines has to be extended using a predictive condition maintenance tool. Among various condition monitoring techniques, vibration analysis is most widely used technique in industry. Signals are extracted for evaluating the condition of machine; further diagnostics is carried out with detected signals to extend the life of machine. With help of detected signals, further interpretations are done to predict the occurrence of defects. To study the problem of defects, a test rig with various possibilities of defects is constructed and experiments are performed considering the unbalanced condition. Further, this paper presents an approach for fault diagnosis of unbalance condition using Elman neural network and frequency-domain vibration analysis. Amplitudes with variation in acceleration are fed to Elman neural network to classify fault or no-fault condition. The Elman network is trained, validated and tested with experimental readings. Results illustrate the effectiveness of Elman network in rotor-bearing system.

Keywords: Elman neural network, fault detection, rotating machines, unbalance, vibration analysis.

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Authors: R. Hanuma Naik, D. V. Ashok Kumar, K. S. R. Anjaneyulu

Abstract:

Several of the practical industrial control processes are multivariable processes. Due to the relation amid the variables (interaction), delay in the loops, it is very intricate to design a controller directly for these processes. So first, the interaction of the variables is analyzed using Relative Normalized Gain Array (RNGA), which considers the time constant, static gain and delay time of the processes. Based on the effect of RNGA, relative gain array (RGA) and NI, the pair (control configuration) of variables to be controlled by decentralized control is selected. The equivalent transfer function (ETF) of the process model is estimated as first order process with delay using the corresponding elements in the Relative gain array and Relative average residence time array (RARTA) of the processes. Secondly, a decentralized Proportional- Integral (PI) controller is designed for each ETF simply using frequency response specifications. Finally, the performance and robustness of the algorithm is comparing with existing related approaches to validate the effectiveness of the projected algorithm.

Keywords: Decentralized control, interaction, Multivariable processes, relative normalized gain array, relative average residence time array, steady state gain.

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Authors: Youngpo Lee, Sanghun Kim, Youngyoon Lee, Seokho Yoon

Abstract:

Due to its capability to resist jamming signals, chirp spread spectrum (CSS) technique has attracted much attention in the area of wireless communications. However, there has been little rigorous analysis for the performance of the CSS communication system in jamming environments. In this paper, we present analytic results on the performance of a CSS system by deriving symbol error rate (SER) expressions for a CSS M-ary phase shift keying (MPSK) system in the presence of broadband and tone jamming signals, respectively. The numerical results show that the empirical SER closely agrees with the analytic result.

Keywords: CSS, DM, jamming, broadband jamming, tone jamming.

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Authors: Othman Belgassim, Krzysztof Jemielniak

Abstract:

The analysis of Acoustic Emission (AE) signal generated from metal cutting processes has often approached statistically. This is due to the stochastic nature of the emission signal as a result of factors effecting the signal from its generation through transmission and sensing. Different techniques are applied in this manner, each of which is suitable for certain processes. In metal cutting where the emission generated by the deformation process is rather continuous, an appropriate method for analysing the AE signal based on the root mean square (RMS) of the signal is often used and is suitable for use with the conventional signal processing systems. The aim of this paper is to set a strategy in tool failure detection in turning processes via the statistic analysis of the AE generated from the cutting zone. The strategy is based on the investigation of the distribution moments of the AE signal at predetermined sampling. The skews and kurtosis of these distributions are the key elements in the detection. A normal (Gaussian) distribution has first been suggested then this was eliminated due to insufficiency. The so called Beta distribution was then considered, this has been used with an assumed β density function and has given promising results with regard to chipping and tool breakage detection.

Keywords: AE signal, skew, kurtosis, tool failure

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Authors: L. Hamsaveni, Navya Prakash, Suresha

Abstract:

Document Image Analysis recognizes text and graphics in documents acquired as images. An approach without Optical Character Recognition (OCR) for degraded document image analysis has been adopted in this paper. The technique involves document imaging methods such as Image Fusing and Speeded Up Robust Features (SURF) Detection to identify and extract the degraded regions from a set of document images to obtain an original document with complete information. In case, degraded document image captured is skewed, it has to be straightened (deskew) to perform further process. A special format of image storing known as YCbCr is used as a tool to convert the Grayscale image to RGB image format. The presented algorithm is tested on various types of degraded documents such as printed documents, handwritten documents, old script documents and handwritten image sketches in documents. The purpose of this research is to obtain an original document for a given set of degraded documents of the same source.

Keywords: Grayscale image format, image fusing, SURF detection, YCbCr image format.

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Authors: M.E.Karbaschi, R.Goudarzizadeh, N.Hedayat

Abstract:

Cylindrical concrete reservoirs are appropriate choice for storing liquids as water, oil and etc. By using of the pre-cast concrete reservoirs instead of the in-situ constructed reservoirs, the speed and precision of the construction would considerably increase. In this construction method, wall and roof panels would make in factory with high quality materials and precise controlling. Then, pre-cast wall and roof panels would carry out to the construction site for assembling. This method has a few faults such as: the existing weeks in connection of wall panels together and wall panels to foundation. Therefore, these have to be resisted under applied loads such as seismic load. One of the innovative methods which was successfully applied for seismic retrofitting of numerous pre-cast cylindrical water reservoirs in New Zealand, using of the high tensile cables around the reservoirs and post-tensioning them. In this paper, analytical modeling of wall and roof panels and post-tensioned cables are carried out with finite element method and the effect of height to diameter ratio, post-tensioning force value, liquid level in reservoir, installing position of tendons on seismic response of reservoirs are investigated.

Keywords: Seismic Retrofit, Pre-Cast, Concrete Reservoir, Post-Tensioning.

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Authors: Dong-Young Yoo, Jong-Whoi Shin, Gang Shin Lee, Jae-Il Lee

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As the disfunctions of the information society and social development progress, intrusion problems such as malicious replies, spam mail, private information leakage, phishing, and pharming, and side effects such as the spread of unwholesome information and privacy invasion are becoming serious social problems. Illegal access to information is also becoming a problem as the exchange and sharing of information increases on the basis of the extension of the communication network. On the other hand, as the communication network has been constructed as an international, global system, the legal response against invasion and cyber-attack from abroad is facing its limit. In addition, in an environment where the important infrastructures are managed and controlled on the basis of the information communication network, such problems pose a threat to national security. Countermeasures to such threats are developed and implemented on a yearly basis to protect the major infrastructures of information communication. As a part of such measures, we have developed a methodology for assessing the information protection level which can be used to establish the quantitative object setting method required for the improvement of the information protection level.

Keywords: Information Security Evaluation Methodology, Critical Information Infrastructure Protection.

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Authors: Abdulkadir Abu Lawal

Abstract:

The study was carried out to establish the probability density function of some selected building construction projects of similar complexity delivered using Bill of Quantities (BQ) and Lump Sum (LS) forms of contract, and to draw a reliability scenario for each form of contract. 30 of such delivered projects are analyzed for each of the contract forms using Weibull Analysis, and their Weibull functions (α, and β) are determined based on their completion times. For the BQ form of contract delivered projects, α is calculated as 1.6737E20 and β as + 0.0115 and for the LS form, α is found to be 5.6556E03 and β is determined as + 0.4535. Using these values, respective probability density functions are calculated and plotted, as handy tool for risk analysis of future projects of similar characteristics. By input of variables from other projects, decision making processes can be made for a whole project or its components using EVM Analysis in project evaluation and review techniques. This framework, as a quantitative approach, depends on the assumption of normality in projects completion time, it can help greatly in determining the completion time probability for veritable projects using any of the contract forms under consideration. Projects aspects that are not amenable to measurement, on the other hand, can be analyzed using fuzzy sets and fuzzy logic. This scenario can be drawn for different types of building construction projects, and using different suitable forms of contract in projects delivery.

Keywords: Building construction, Projects, Forms of contract, Probability density function, Reliability scenario.

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Authors: Mert Bal, Hayri Sever, Oya Kalıpsız

Abstract:

Medical Decision Support Systems (MDSSs) are sophisticated, intelligent systems that can provide inference due to lack of information and uncertainty. In such systems, to model the uncertainty various soft computing methods such as Bayesian networks, rough sets, artificial neural networks, fuzzy logic, inductive logic programming and genetic algorithms and hybrid methods that formed from the combination of the few mentioned methods are used. In this study, symptom-disease relationships are presented by a framework which is modeled with a formal concept analysis and theory, as diseases, objects and attributes of symptoms. After a concept lattice is formed, Bayes theorem can be used to determine the relationships between attributes and objects. A discernibility relation that forms the base of the rough sets can be applied to attribute data sets in order to reduce attributes and decrease the complexity of computation.

Keywords: Formal Concept Analysis, Rough Set Theory, Granular Computing, Medical Decision Support System.

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Authors: Jianwei Zhang, Dazhi Jiang, Huaxin Peng, Chunqi Wang

Abstract:

Stress-strain curve of inter-tube connected carbon nanotube (CNT) reinforced polymer composite under axial loading generated from molecular dynamics simulation is presented. Comparison of the response to axial mechanical loading between this composite system with composite systems reinforced by long, continuous CNTs (replicated via periodic boundary conditions) and short, discontinuous CNTs has been made. Simulation results showed that the inter-tube connection improved the mechanical properties of short discontinuous CNTs dramatically. Though still weaker than long CNT/polymer composite, more remarkable increase in the stiffness relative to the polymer was observed in the inter-tube connected CNT/polymer composite than in the discontinuous CNT/polymer composite. The manually introduced bridge break process resulted in a stress-strain curve of ductile fracture mode, which is consistent with the experimental result.

Keywords: Carbon nanotube, inter-tube connection, molecular dynamics, stress-strain curve

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Authors: Raida El Mansouri, Elhillali Kerkouche, Allaoua Chaoui

Abstract:

The Petri net tool INA is a well known tool by the Petri net community. However, it lacks a graphical environment to cerate and analyse INA models. Building a modelling tool for the design and analysis from scratch (for INA tool for example) is generally a prohibitive task. Meta-Modelling approach is useful to deal with such problems since it allows the modelling of the formalisms themselves. In this paper, we propose an approach based on the combined use of Meta-modelling and Graph Grammars to automatically generate a visual modelling tool for INA for analysis purposes. In our approach, the UML Class diagram formalism is used to define a meta-model of INA models. The meta-modelling tool ATOM3 is used to generate a visual modelling tool according to the proposed INA meta-model. We have also proposed a graph grammar to automatically generate INA description of the graphically specified Petri net models. This allows the user to avoid the errors when this description is done manually. Then the INA tool is used to perform the simulation and the analysis of the resulted INA description. Our environment is illustrated through an example.

Keywords: INA, Meta-modelling, Graph Grammars, AToM3, Automatic Code Generation.

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Authors: Jae-Neung Lee, Keun-Chang Kwak

Abstract:

This paper describes an analysis of domestic and international trends of image processing for data in UAV (unmanned aerial vehicle) and also explains about UAV and Quadcopter. Overseas examples of image processing using UAV include image processing for totaling the total numberof vehicles, edge/target detection, detection and evasion algorithm, image processing using SIFT(scale invariant features transform) matching, and application of median filter and thresholding. In Korea, many studies are underway including visualization of new urban buildings.

Keywords: Image Processing, UAV, Quadcopter, Target detection.

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Authors: Monika Garg, Lillie Dewan

Abstract:

Three novel and significant contributions are made in this paper Firstly, non-recursive formulation of Haar connection coefficients, pioneered by the present authors is presented, which can be computed very efficiently and avoid stack and memory overflows. Secondly, the generalized approach for state analysis of singular bilinear time-invariant (TI) and time-varying (TV) systems is presented; vis-˜a-vis diversified and complex works reported by different authors. Thirdly, a generalized approach for parameter estimation of bilinear TI and TV systems is also proposed. The unified framework of the proposed method is very significant in that the digital hardware once-designed can be used to perform the complex tasks of state analysis and parameter estimation of different types of bilinear systems single-handedly. The simplicity, effectiveness and generalized nature of the proposed method is established by applying it to different types of bilinear systems for the two tasks.

Keywords: Bilinear Systems, Haar Wavelet, Haar ConnectionCoefficients, Parameter Estimation, Singular Bilinear Systems, StateAnalysis.

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Authors: Elia Favarelli, Enrico Testi, Andrea Giorgetti

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Autonomous structural health monitoring (SHM) of many structures and bridges became a topic of paramount importance for maintenance purposes and safety reasons. This paper proposes a set of machine learning (ML) tools to perform automatic feature selection and detection of anomalies in a bridge from vibrational data and compare different feature extraction schemes to increase the accuracy and reduce the amount of data collected. As a case study, the Z-24 bridge is considered because of the extensive database of accelerometric data in both standard and damaged conditions. The proposed framework starts from the first four fundamental frequencies extracted through operational modal analysis (OMA) and clustering, followed by time-domain filtering (tracking). The fundamental frequencies extracted are then fed to a dimensionality reduction block implemented through two different approaches: feature selection (intelligent multiplexer) that tries to estimate the most reliable frequencies based on the evaluation of some statistical features (i.e., entropy, variance, kurtosis), and feature extraction (auto-associative neural network (ANN)) that combine the fundamental frequencies to extract new damage sensitive features in a low dimensional feature space. Finally, one-class classification (OCC) algorithms perform anomaly detection, trained with standard condition points, and tested with normal and anomaly ones. In particular, principal component analysis (PCA), kernel principal component analysis (KPCA), and autoassociative neural network (ANN) are presented and their performance are compared. It is also shown that, by evaluating the correct features, the anomaly can be detected with accuracy and an F1 score greater than 95%.

Keywords: Anomaly detection, dimensionality reduction, frequencies selection, modal analysis, neural network, structural health monitoring, vibration measurement.

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Authors: Clara Inés Pardo Martínez, William H. Alfonso Piña

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In emerging economies, recycling is an opportunity for the cities to increase the lifespan of sanitary landfills, reduce the costs of the solid waste management, decrease the environmental problems of the waste treatment through reincorporate waste in the productive cycle and protect and develop people’s livelihoods of informal waste pickers. However, few studies have analysed the possibilities and strategies to integrate formal and informal sectors in the solid waste management for the benefit of both. This study seek to make a strength, weakness, opportunity, and threat (SWOT) analysis in three recycling associations of Bogotá with the aim to understand and determine the situation of recycling from perspective of informal sector in its transition to enter as authorized waste providers. Data used in the analysis are derived from multiple strategies such as literature review, the Bogota’s recycling database, focus group meetings, governmental reports, national laws and regulations and specific interviews with key stakeholders. Results of this study show as the main stakeholders of formal and informal sector of waste management can identify the internal and internal conditions of recycling in Bogotá. Several strategies were designed based on the SWOTs determined, could be useful for Bogotá to advance and promote recycling as a key strategy for integrated sustainable waste management in the city.

Keywords: Bogotá, recycling, solid waste management, SWOT analysis.

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Authors: Weishou Shen, Dong Liu, Di Ji, Haoyun Shen, Naifeng Lin

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Based on the field investigation and long term remote sensing data, the dynamics of the alpine wetland in the river basin and their response to climate change were studied. Results showed the alpine wetlands accounted for 3.73% of total basin in 2010. Lake and river appeared an increasing trend in the past 30 years, with an increase of 34.36 % and 24.57%. However, swamp exhibited a tendency of decreasing with 233.74 km2. Annual average temperature, maximum temperature, minimum temperature and precipitation in the river basin all exhibited an increasing trend, whereas relative humidity exhibited a decreasing trend. Ice and snow melting are main reasons of lake and river area enhancement and swamp area descend. There existed 91.78%-97.86% of reduced swamp converted into lakes on the basis of remote sensing image interpretation. China-s government policy of implementing development in the river basin is the major driving force of artificial wetland growth.

Keywords: alpine wetland dynamics, climate change, Yarlung Zangbo River basin

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Authors: H. Mehdi, Kh. S. Karimov, A. A. Kavokin

Abstract:

Methods of clustering which were developed in the data mining theory can be successfully applied to the investigation of different kinds of dependencies between the conditions of environment and human activities. It is known, that environmental parameters such as temperature, relative humidity, atmospheric pressure and illumination have significant effects on the human mental performance. To investigate these parameters effect, data mining technique of clustering using entropy and Information Gain Ratio (IGR) K(Y/X) = (H(X)–H(Y/X))/H(Y) is used, where H(Y)=-ΣPi ln(Pi). This technique allows adjusting the boundaries of clusters. It is shown that the information gain ratio (IGR) grows monotonically and simultaneously with degree of connectivity between two variables. This approach has some preferences if compared, for example, with correlation analysis due to relatively smaller sensitivity to shape of functional dependencies. Variant of an algorithm to implement the proposed method with some analysis of above problem of environmental effects is also presented. It was shown that proposed method converges with finite number of steps.

Keywords: Clustering, Correlation analysis, EnvironmentalParameters, Information Gain Ratio, Mental Performance.

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Authors: Ebunoluwa G. Gabriel, Victoria A. Jideani, Daniel I. O. Ikhu-Omoregbe

Abstract:

The current desire in food and industrial emulsification is the use of natural emulsifiers. Bambara groundnut flour (BGNF) and its starch (BGNS) will serve both emulsifying and nutritional purposes if found suitable. This current study was aimed at investigating the emulsifying properties of BGNF/BGNS. BGNS was extracted from the BGNF. Emulsions were prepared using a wide range of flour-oil-water and starch-oil-water composition as generated through the application of Response Surface (D-optimal) design. Prepared emulsions were investigated for stability to creaming/sedimentation (using the kinetic information from turbiscan) and flocculation/coalescence (by monitoring the droplet diameter growth using optical microscope) over 5 days. The most stable emulsions (one BGNF-stabilized and the other BGNS-stabilized) were determined. The optimal emulsifier/oil composition was 9g/39g for BGNF and 5g/30g for BGNS. The two emulsions had only 30% and 50% growth in oil droplet diameter respectively by day 5, compared to over 3000% in the unstable ones. The BGNF-stabilized emulsions were more stable than the BGNS-stabilized ones. Emulsions were successfully stabilized with BGNF and BGNS.

Keywords: Bambara groundnut, coalescence, creaming, emulsification, emulsion, emulsion stability.

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