Search results for: emission modeling

Authors: D. M. Mongelli, M. De Carli, L. Carnieletto, F. Busato

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This research aims to provide a contribution to the reduction of fossil fuels and the consequent reduction of CO2eq emissions for each European region. Simulations have been carried out to replace fossil fuel fired heating boilers with air-to-water heat pumps, when allowed by favorable environmental conditions (outdoor temperature, water temperature in emission systems, etc.). To estimate the potential coverage of high-temperature heat pumps in European regions, the energy profiles of buildings were considered together with the potential coefficient of performance (COP) of heat pumps operating with flow temperature with variable climatic regulation. The electrification potential for heating buildings was estimated by dividing the 38 European countries examined into 179 territorial units. The yields have been calculated in terms of energy savings and CO2eq reduction.

Keywords: Decarbonization, Space heating, Heat pumps, Energy policies.

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Authors: Muhammad Aqil, Ichiro Kita, Moses Macalinao

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Reliable water level forecasts are particularly important for warning against dangerous flood and inundation. The current study aims at investigating the suitability of the adaptive network based fuzzy inference system for continuous water level modeling. A hybrid learning algorithm, which combines the least square method and the back propagation algorithm, is used to identify the parameters of the network. For this study, water levels data are available for a hydrological year of 2002 with a sampling interval of 1-hour. The number of antecedent water level that should be included in the input variables is determined by two statistical methods, i.e. autocorrelation function and partial autocorrelation function between the variables. Forecasting was done for 1-hour until 12-hour ahead in order to compare the models generalization at higher horizons. The results demonstrate that the adaptive networkbased fuzzy inference system model can be applied successfully and provide high accuracy and reliability for river water level estimation. In general, the adaptive network-based fuzzy inference system provides accurate and reliable water level prediction for 1-hour ahead where the MAPE=1.15% and correlation=0.98 was achieved. Up to 12-hour ahead prediction, the model still shows relatively good performance where the error of prediction resulted was less than 9.65%. The information gathered from the preliminary results provide a useful guidance or reference for flood early warning system design in which the magnitude and the timing of a potential extreme flood are indicated.

Keywords: Neural Network, Fuzzy, River, Forecasting

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Authors: G. Martino, F. Silva, E. Marchal

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The control over delivered iron ore blend characteristics is one of the most important aspects of the mining business. The iron ore price is a function of its composition, which is the outcome of the beneficiation process. So, end-to-end integrated planning of mine operations can reduce risks of penalties on the iron ore price. In a standard iron mining company, the production chain is composed of mining, ore beneficiation, and client supply. When mine planning and client supply decisions are made uncoordinated, the beneficiation plant struggles to deliver the best blend possible. Technological improvements in several fields allowed bridging the gap between departments and boosting integrated decision-making processes. Clusterization and classification algorithms over historical production data generate reasonable previsions for quality and volume of iron ore produced for each pile of run-of-mine (ROM) processed. Mathematical modeling can use those deterministic relations to propose iron ore blends that better-fit specifications within a delivery schedule. Additionally, a model capable of representing the whole production chain can clearly compare the overall impact of different decisions in the process. This study shows how flexibilization combined with a planning optimization model between the mine and the ore beneficiation processes can reduce risks of out of specification deliveries. The model capabilities are illustrated on a hypothetical iron ore mine with magnetic separation process. Finally, this study shows ways of cost reduction or profit increase by optimizing process indicators across the production chain and integrating the different plannings with the sales decisions.

Keywords: Clusterization and classification algorithms, integrated planning, optimization, mathematical modeling, penalty minimization.

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Authors: Sukir Maryanto, Iyan Mulyana

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Fractal analyses of successive event of explosion earthquake and harmonic tremor recorded at Semeru volcano were carried out to investigate the dynamical system regarding to their generating mechanism. The explosive eruptions accompanied by explosion earthquakes and following volcanic tremor which are generated by continuous emission of volcanic ash. The fractal dimension of successive event of explosion and harmonic tremor was estimated by Critical Exponent Method (CEM). It was found that the method yield a higher fractal dimension of explosion earthquakes and gradually decrease during the occurrence of harmonic tremor, and can be considerably as correlated complexity of the source mechanism from the variance of fractal dimension.

Keywords: Fractal dimension, Semeru volcano, explosionearthquake, harmonic tremor, Critical Exponent Method

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Authors: Rabih Ghostine, Craig Kapfer, Viswanathan Kannan, Ibrahim Hoteit

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Urban flooding resulting from a sudden release of water due to dam-break or excessive rainfall is a serious threatening environment hazard, which causes loss of human life and large economic losses. Anticipating floods before they occur could minimize human and economic losses through the implementation of appropriate protection, provision, and rescue plans. This work reports on the numerical modelling of flash flood propagation in urban areas after an excessive rainfall event or dam-break. A two-dimensional (2D) depth-averaged shallow water model is used with a refined unstructured grid of triangles for representing the urban area topography. The 2D shallow water equations are solved using a second-order well-balanced discontinuous Galerkin scheme. Theoretical test case and three flood events are described to demonstrate the potential benefits of the scheme: (i) wetting and drying in a parabolic basin (ii) flash flood over a physical model of the urbanized Toce River valley in Italy; (iii) wave propagation on the Reyran river valley in consequence of the Malpasset dam-break in 1959 (France); and (iv) dam-break flood in October 1982 at the town of Sumacarcel (Spain). The capability of the scheme is also verified against alternative models. Computational results compare well with recorded data and show that the scheme is at least as efficient as comparable second-order finite volume schemes, with notable efficiency speedup due to parallelization.

Keywords: Flood modeling, dam-break, shallow water equations, Discontinuous Galerkin scheme, MUSCL scheme.

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Authors: E. Farsad, S. P. Abbasi, A. Goodarzi, M. S. Zabihi

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Nowadays, quasi-continuous wave diode lasers are used in a widespread variety of applications. Temperature effects in these lasers can strongly influence their performance. In this paper, the effects of temperature have been experimentally investigated on different features of a 60W-QCW diode laser. The obtained results indicate that the conversion efficiency and operation voltage of diode laser decrease with the augmentation of the working temperature associated with a redshift in the laser peak wavelength. Experimental results show the emission peak wavelength of laser shifts 0.26 nm and the conversion efficiency decreases 1.76 % with the increase of temperature from 40 to 50 ̊C. Present study also shows the slope efficiency decreases gradually at low temperatures and rapidly at higher temperatures. Regarding the close dependence of the mentioned parameters to the operating temperature, it is of great importance to carefully control the working temperature of diode laser, particularly for medical applications.

Keywords: diode laser, experimentally, temperature, wavelength

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Authors: L. V. Fui, A. Ulugbek, S. S. Dol

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The in-cylinder flow and mixture formations are significant in view of today’s increasing concern on environmental issues and stringent emission regulations. In this paper, the numerical simulations of a SI engine at different engine speeds (2000-5000 rpm) at fixed intake flow pressure of 1 bar are studied using the AVL FIRE software. The simulation results show that when the engine speed at fixed intake flow pressure is increased, the volumetric efficiency of the engine decreases. This is due to a richer fuel conditions near the engine cylinder wall when engine speed is increased. Significant effects of impingement are also noted on the upper and side walls of the engine cylinder. These variations in mixture formation before ignition could affect the thermodynamics efficiency and specific fuel consumption that would lead to a reduced engine performance.

Keywords: AVL FIRE, fuel mass, IC engine, LES, RANS, turbulent intensity.

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Authors: Theerawat Songyot, Tham Manjing, Bunyarit Uyyanonvara, Chanjira Sinthanayothin

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Corner detection and optical flow are common techniques for feature-based video stabilization. However, these algorithms are computationally expensive and should be performed at a reasonable rate. This paper presents an algorithm for discarding irrelevant feature points and maintaining them for future use so as to improve the computational cost. The algorithm starts by initializing a maintained set. The feature points in the maintained set are examined against its accuracy for modeling. Corner detection is required only when the feature points are insufficiently accurate for future modeling. Then, optical flows are computed from the maintained feature points toward the consecutive frame. After that, a motion model is estimated based on the simplified affine motion model and least square method, with outliers belonging to moving objects presented. Studentized residuals are used to eliminate such outliers. The model estimation and elimination processes repeat until no more outliers are identified. Finally, the entire algorithm repeats along the video sequence with the points remaining from the previous iteration used as the maintained set. As a practical application, an efficient video stabilization can be achieved by exploiting the computed motion models. Our study shows that the number of times corner detection needs to perform is greatly reduced, thus significantly improving the computational cost. Moreover, optical flow vectors are computed for only the maintained feature points, not for outliers, thus also reducing the computational cost. In addition, the feature points after reduction can sufficiently be used for background objects tracking as demonstrated in the simple video stabilizer based on our proposed algorithm.

Keywords: background object tracking, feature point reduction, low cost tracking, video stabilization.

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Authors: B. Salmasian, A. Rabiee, T. Yousefzadeh

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In this research, the risk assessment of radiation hazard for the Research Nuclear Reactor has been studied. In the current study, the MCNPx computational code has been used and coupled with a developed program using MATLAB software to evaluate Total Effective Dose Equivalent (TEDE) and cancer risk according to the BEIR equations for various human organs. In this study, the risk assessment of cancer has been calculated for ten years after exposure, in each of body organs of different ages and sexes. Also, the risk assessment of cancer has been calculated in each of body organs of different ages and sexes due to exposure after the retirement of the reactor staff. According to obtained results, a conservative whole-body dose rate, during a year, is 0.261 Sv and the probability the cancer risk for women is more than men and for children is more than adults. It has been shown that thyroid cancer was more possible than others.

Keywords: MCNPx code, BEIR equation, equivalent dose, risk analysis.

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Authors: M. Sari Yilmaz, N. Karamahmut Mermer

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Coal fly ash is formed as a solid waste product from the combustion of coal in coal fired power stations. Huge amounts of fly ash are produced globally every year and are predicted to increase. Nowadays, less than half of the fly ash is used as a raw material for cement manufacturing, construction and the rest of it is disposed as a waste causing yet another environmental concern. For this reason, the recycling of this kind of slurries into useful materials is quite important in terms of economical and environmental aspects. The purpose of this study is to evaluate the Orhaneli and Tuncbilek coal fly ashes for utilization in some industrial applications. Therefore the mineralogical and chemical compositions of these fly ashes were analyzed by X-ray fluorescence spectroscopy, ourier-transform infrared spectrometer, and X-ray diffraction. The silicon (Si) and aluminum (Al) in the fly ashes were activated by alkali fusion technique with sodium hydroxide. The obtained extracts were analyzed for Si and Al content by inductively coupled plasma optical emission spectrometry.

Keywords: Extraction, Fly ash, Fusion, XRD.

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Authors: N. Tugrul, E. Moroydor Derun, E. Cinar, A. S. Kipcak, N. Baran Acarali, S. Piskin

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Fly ash is an important waste, produced in thermal power plants which causes very important environmental pollutions. For this reason the usage and evaluation the fly ash in various areas are very important. Nearly, 15 million tons/year of fly ash is produced in Turkey. In this study, usage of fly ash with diatomite and molasses for heavy metal (Cd) adsorption from wastewater is investigated. The samples of Seyitomer region fly ash were analyzed by X-ray fluorescence (XRF) and Scanning Electron Microscope (SEM) then diatomite (0 and 1% in terms of fly ash, w/w) and molasses (0-0.75 mL) were pelletized under 30 MPa of pressure for the usage of cadmium (Cd) adsorption in wastewater. After the adsorption process, samples of Seyitomer were analyzed using Optical Emission Spectroscopy (ICP-OES). As a result, it is seen that the usage of Seyitomer fly ash is proper for cadmium (Cd) adsorption and an optimum adsorption yield with 52% is found at a compound with Seyitomer fly ash (10 g), diatomite (0.5 g) and molasses (0.75 mL) at 2.5 h of reaction time, pH:4, 20ºC of reaction temperature and 300 rpm of stirring rate.

Keywords: Heavy metal, fly ash, molasses, diatomite, adsorption, wastewater.

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Authors: Kiurski S. Jelena, Kecić S. Vesna, Oros B. Ivana, Ranogajec G. Jonjaua

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The paper represents the dependence of ammonia concentration on microclimate parameters and photocopying shop circulation. The concentration of ammonia was determined during 8-hours working time over five days including three sampling points of a photocopying shop in Novi Sad, Serbia. The obtained results pointed out that the room temperature possesses the highest impact on ammonia release. The obtained ammonia concentration was in the range of 1.53 to 0.42ppm and decreased with the temperature decreasing from 24.6 to 20.7^oC. As the detected concentrations were within the permissible levels of The Occupational Safety and Health Administration, The National Institute for Occupational Safety and The Health and Official Gazette of Republic of Serbia, in the range of 35 to 200ppm, there was no danger to the employee’s health in the photocopying shop.

Keywords: Ammonia, emission, indoor environment, photocopying procedure.

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Authors: M. Daoudi, A. Belghachi, L. Varani

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In this paper, we analyze the problem of quasiballistic electron transport in ultra small of mercury -cadmiumtelluride (Hg0.8Cd0.2Te -MCT) n+-n- n+ devices from hydrodynamic point view. From our study, we note that, when the size of the active layer is low than 0.1μm and for low bias application( ( ≥ 9mV), the quasi-ballistic transport has an important effect.

Keywords: Hg0.8Cd0.2Te semiconductor, Hydrodynamicmode, Quasi-ballistic transport, Submicron diode

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Authors: T. Aboumahboub, R. Brecha, H. B. Shrestha, U. F. Hutfilter, A. Geiges, W. Hare, M. Schaeffer, L. Welder, M. Gidden

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The proposed stringent mitigation targets require an immediate start for a drastic transformation of the whole energy system. The current Australian energy system is mainly centralized and fossil fuel-based in most states with coal and gas-fired plants dominating the total produced electricity over the recent past. On the other hand, the country is characterized by a huge, untapped renewable potential, where wind and solar energy could play a key role in the decarbonization of the Australia’s future energy system. However, integrating high shares of such variable renewable energy sources (VRES) challenges the power system considerably due to their temporal fluctuations and geographical dispersion. This raises the concerns about flexibility gap in the system to ensure the security of supply with increasing shares of such intermittent sources. One main flexibility dimension to facilitate system integration of high shares of VRES is to increase the cross-sectoral integration through coupling of electricity to other energy sectors alongside the decarbonization of the power sector and reinforcement of the transmission grid. This paper applies a multi-sectoral energy system optimization model for Australia. We investigate the cost-optimal configuration of a renewable-based Australian energy system and its transformation pathway in line with the ambitious range of proposed climate change mitigation targets. We particularly analyse the implications of linking the electricity and transport sectors in a prospective, highly renewable Australian energy system.

Keywords: Decarbonization, energy system modeling, sector coupling, variable renewable energies.

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Authors: Mohammed El Raey, Moustafa Osman Mohammed

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The spatial-ecological modeling is relating sustainable dispersions with social development. Sustainability with spatial-ecological model gives attention to urban environments in the design review management to comply with Earth’s system. Naturally exchanged patterns of ecosystems have consistent and periodic cycles to preserve energy flows and materials in Earth’s system. The Probabilistic Risk Assessment (PRA) technique is utilized to assess the safety of an industrial complex. The other analytical approach is the Failure-Safe Mode and Effect Analysis (FMEA) for critical components. The plant safety parameters are identified for engineering topology as employed in assessment safety of industrial ecology. In particular, the most severe accidental release of hazardous gaseous is postulated, analyzed and assessment in industrial region. The IAEA-safety assessment procedure is used to account the duration and rate of discharge of liquid chlorine. The ecological model of plume dispersion width and concentration of chlorine gas in the downwind direction is determined using Gaussian Plume Model in urban and rural areas and presented with SURFER®. The prediction of accident consequences is traced in risk contour concentration lines. The local greenhouse effect is predicted with relevant conclusions. The spatial-ecological model is predicted for multiple factors distribution schemes of multi-criteria analysis. The input–output analysis is explored from the spillover effect, and we conducted Monte Carlo simulations for sensitivity analysis. Their unique structure is balanced within “equilibrium patterns”, such as the composite index for biosphere with collective structure of many distributed feedback flows. These dynamic structures are related to have their physical and chemical properties and enable a gradual and prolonged incremental pattern. While this spatial model structure argues from ecology, resource savings, static load design, financial and other pragmatic reasons, the outcomes are not decisive in an artistic/architectural perspective. The hypothesis is deployed to unify analytic and analogical spatial structure in development urban environments using optimization loads as an example of integrated industrial structure where the process is based on engineering topology of systems ecology.

Keywords: Spatial-ecological modeling, spatial structure orientation impact, composite structure, industrial ecology.

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Authors: T. C. Manjunath, B. Bandyopadhyay

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Active vibration control is an important problem in structures. The objective of active vibration control is to reduce the vibrations of a system by automatic modification of the system-s structural response. In this paper, the modeling and design of a fast output sampling feedback controller for a smart flexible beam system embedded with shear sensors and actuators for SISO system using Timoshenko beam theory is proposed. FEM theory, Timoshenko beam theory and the state space techniques are used to model the aluminum cantilever beam. For the SISO case, the beam is divided into 5 finite elements and the control actuator is placed at finite element position 1, whereas the sensor is varied from position 2 to 5, i.e., from the nearby fixed end to the free end. Controllers are designed using FOS method and the performance of the designed FOS controller is evaluated for vibration control for 4 SISO models of the same plant. The effect of placing the sensor at different locations on the beam is observed and the performance of the controller is evaluated for vibration control. Some of the limitations of the Euler-Bernoulli theory such as the neglection of shear and axial displacement are being considered here, thus giving rise to an accurate beam model. Embedded shear sensors and actuators have been considered in this paper instead of the surface mounted sensors and actuators for vibration suppression because of lot of advantages. In controlling the vibration modes, the first three dominant modes of vibration of the system are considered.

Keywords: Smart structure, Timoshenko beam theory, Fast output sampling feedback control, Finite Element Method, State space model, SISO, Vibration control, LMI

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Authors: Vijaya Ilango, Avika Gupta

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Hydrogen fuel is a zero-emission fuel which uses electrochemical cells or combustion in internal engines, to power vehicles and electric devices. Methods of   hydrogen storage for subsequent use span many approaches, including high pressures, cryogenics and chemical compounds that reversibly release H₂ upon heating. Most research into hydrogen storage is focused on storing hydrogen as a lightweight, compact energy carrier for mobile applications. With the accelerating demand for cleaner and more efficient energy sources, hydrogen research has attracted more attention in the scientific community. Until now, full implementation of a hydrogen-based energy system has been hindered in part by the challenge of storing hydrogen gas, especially onboard an automobile. New techniques being researched may soon make hydrogen storage more compact, safe and efficient. In   this overview, few hydrogen storage methods and mechanism of hydrogen uptake in carbon nanotubes are summarized.

Keywords: Carbon nanotubes, Chemisorption, Hydrogen storage, Physisorption.

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Authors: Moustafa Osman Mohamed

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This paper will explore the influence of energy sector in Arab Republic of Egypt which has shared its responsibilities of many environmental challenges as the second largest economy in the Middle East (after Iran). Air and water pollution, desertification, inadequate disposal of solid waste and damage to coral reefs are serious problems that influence environmental management in Egypt. The intensive reliance of high population density and strong industrial growth are wearing Egypt's resources, and the rapidly-growing population has forced Egypt to breakdown agricultural land to residential and relevant use of commercial ingestion. The depletion effects of natural resources impose the government to apply innovation techniques in emission control and focus on sustainability. The cogeneration will be presented to control thermal losses and increase efficiency of energy power system.

Keywords: Cogeneration, energy indicators, power plant, electricity, environmental loads, environmental impact assessment.

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Authors: A. Pashayev, R. Sadiqov, C. Ardil, F. Ildiz , H. Karabork

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The new technology of fuzzy neural networks for identification of parameters for mathematical models of geofields is proposed and checked. The effectiveness of that soft computing technology is demonstrated, especially in the early stage of modeling, when the information is uncertain and limited.

Keywords: Identification, interpolation methods, neuro-fuzzy networks, geofield.

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Authors: Daehwan Kim, Jaemin Kim, Seongwon Cho, Yongsuk Jang, Sun-Tae Chung, Boo-Gyoun Kim

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AAM has been successfully applied to face alignment, but its performance is very sensitive to initial values. In case the initial values are a little far distant from the global optimum values, there exists a pretty good possibility that AAM-based face alignment may converge to a local minimum. In this paper, we propose a progressive AAM-based face alignment algorithm which first finds the feature parameter vector fitting the inner facial feature points of the face and later localize the feature points of the whole face using the first information. The proposed progressive AAM-based face alignment algorithm utilizes the fact that the feature points of the inner part of the face are less variant and less affected by the background surrounding the face than those of the outer part (like the chin contour). The proposed algorithm consists of two stages: modeling and relation derivation stage and fitting stage. Modeling and relation derivation stage first needs to construct two AAM models: the inner face AAM model and the whole face AAM model and then derive relation matrix between the inner face AAM parameter vector and the whole face AAM model parameter vector. In the fitting stage, the proposed algorithm aligns face progressively through two phases. In the first phase, the proposed algorithm will find the feature parameter vector fitting the inner facial AAM model into a new input face image, and then in the second phase it localizes the whole facial feature points of the new input face image based on the whole face AAM model using the initial parameter vector estimated from using the inner feature parameter vector obtained in the first phase and the relation matrix obtained in the first stage. Through experiments, it is verified that the proposed progressive AAM-based face alignment algorithm is more robust with respect to pose, illumination, and face background than the conventional basic AAM-based face alignment algorithm.

Keywords: Face Alignment, AAM, facial feature detection, model matching.

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Authors: M. N. Zelenin, V. S. Mikhailov, R. P. Zhivotovsky

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It is known that residual welding deformations give negative effect to processability and operational quality of welded structures, complicating their assembly and reducing strength. Therefore, selection of optimal technology, ensuring minimum welding deformations, is one of the main goals in developing a technology for manufacturing of welded structures. Through years, JSC SSTC has been developing a theory for estimation of welding deformations and practical activities for reducing and compensating such deformations during welding process. During long time a methodology was used, based on analytic dependence. This methodology allowed defining volumetric changes of metal due to welding heating and subsequent cooling. However, dependences for definition of structures deformations, arising as a result of volumetric changes of metal in the weld area, allowed performing calculations only for simple structures, such as units, flat sections and sections with small curvature. In case of complex 3D structures, estimations on the base of analytic dependences gave significant errors. To eliminate this shortage, it was suggested to use finite elements method for resolving of deformation problem. Here, one shall first calculate volumes of longitudinal and transversal shortenings of welding joints using method of analytic dependences and further, with obtained shortenings, calculate forces, which action is equivalent to the action of active welding stresses. Further, a finiteelements model of the structure is developed and equivalent forces are added to this model. Having results of calculations, an optimal sequence of assembly and welding is selected and special measures to reduce and compensate welding deformations are developed and taken.

Keywords: Finite elements method, modeling, expected welding deformations, welding, assembling.

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Authors: T.C. Manjunath, B. Bandyopadhyay

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This paper features the modeling and design of a Robust Decentralized Fast Output Sampling (RDFOS) Feedback control technique for the active vibration control of a smart flexible multimodel Euler-Bernoulli cantilever beams for a multivariable (MIMO) case by retaining the first 6 vibratory modes. The beam structure is modeled in state space form using the concept of piezoelectric theory, the Euler-Bernoulli beam theory and the Finite Element Method (FEM) technique by dividing the beam into 4 finite elements and placing the piezoelectric sensor / actuator at two finite element locations (positions 2 and 4) as collocated pairs, i.e., as surface mounted sensor / actuator, thus giving rise to a multivariable model of the smart structure plant with two inputs and two outputs. Five such multivariable models are obtained by varying the dimensions (aspect ratios) of the aluminium beam. Using model order reduction technique, the reduced order model of the higher order system is obtained based on dominant Eigen value retention and the Davison technique. RDFOS feedback controllers are designed for the above 5 multivariable-multimodel plant. The closed loop responses with the RDFOS feedback gain and the magnitudes of the control input are obtained and the performance of the proposed multimodel smart structure system is evaluated for vibration control.

Keywords: Smart structure, Euler-Bernoulli beam theory, Fastoutput sampling feedback control, Finite Element Method, Statespace model, Vibration control, LMI, Model order Reduction.

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Authors: Zainul Huda

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This presentation reviews recent advances in superalloys and thermal barrier coating (TBC) for application in hot sections of energy-efficient gas-turbine engines. It has been reviewed that in the modern combined-cycle gas turbines (CCGT) applying single-crystal energy materials (SC superalloys) and thermal barrier coatings (TBC), and – in one design – closed-loop steam cooling, thermal efficiency can reach more than 60%. These technological advancements contribute to profitable and clean power generation with reduced emission. Alternatively, the use of advanced superalloys (e.g. GTD-111 superalloy, Allvac 718Plus superalloy) and advanced thermal barrier coatings (TBC) in modern gas-turbines has been shown to yield higher energy-efficiency in power generation.

Keywords: Energy materials, gas turbine engines, superalloy, thermal barrier coating

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Authors: M. M. Fercan, A. S. Kipcak, O. Dere Ozdemir, M. B. Piskin, E. Moroydor Derun

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Coffee is a widely consumed beverage with many components such as caffeine, flavonoids, phenolic compounds, and minerals. Coffee consumption continues to increase due to its physiological effects, its pleasant taste, and aroma. Robusta and Arabica are two basic types of coffee beans. The coffee bean used for Turkish coffee is Arabica. There are many elements in the structure of coffee and have various effect on human health such as Sodium (Na), Boron (B), Magnesium (Mg) and Iron (Fe). In this study, the amounts of Mg, Na, Fe, and B contents in Turkish coffee are determined and effect of sugar addition is investigated for conscious consumption. The analysis of the contents of coffees was determined by using inductively coupled plasma optical emission spectrometry (ICP-OES). From the results of the experiments the Mg, Na, Fe and B contents of Turkish coffee after sugar addition were found as 19.83, 1.04, 0.02, 0.21 ppm, while without using sugar these concentrations were found 21.46, 0.81, 0.008 and 0.16 ppm. In addition, element contents were calculated for 1, 3 and 5 cups of coffee in order to investigate the health effects.

Keywords: Health effect, ICP-OES, sugar, Turkish coffee.

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Authors: Gulten Yilmaz, A. Beril Tugrul, Mustafa Demir, Dogan Yasar, Bayram Demir, Bulent Buyuk

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A Positron Emission Tomography (PET) is a radioisotope imaging technique that illustrates the organs and the metabolisms of the human body. This technique is based on the simultaneous detection of 511 keV annihilation photons, annihilated as a result of electrons annihilating positrons that radiate from positron-emitting radioisotopes that enter biological active molecules in the body. This study was conducted on ten patients in an effort to conduct patient-related experimental studies. Dosage monitoring for the bladder, which was the organ that received the highest dose during PET applications, was conducted for 24 hours. Assessment based on measuring urination activities after injecting patients was also a part of this study. The MIRD method was used to conduct dosage calculations for results obtained from experimental studies. Results obtained experimentally and theoretically were assessed comparatively.

Keywords: PET/CT, TLD, MIRD, Dose measurement, Patient doses.

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Authors: Yasin Tadayonrad, Alassane Ballé Ndiaye

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Most of the supply chain networks have many nodes starting from the suppliers’ side up to the customers’ side that each node sends/receives the raw materials/products from/to the other nodes. One of the major concerns in this kind of supply chain network is finding the best schedule for loading/unloading the shipments through the whole network by which all the constraints in the source and destination nodes are met and all the shipments are delivered on time. One of the main constraints in this problem is the loading/unloading capacity in each source/destination node at each time slot (e.g., per week/day/hour). Because of the different characteristics of different products/groups of products, the capacity of each node might differ based on each group of products. In most supply chain networks (especially in the Fast-moving consumer goods (FMCG) industry), there are different planners/planning teams working separately in different nodes to determine the loading/unloading timeslots in source/destination nodes to send/receive the shipments. In this paper, a mathematical problem has been proposed to find the best timeslots for loading/unloading the shipments minimizing the overall delays subject to respecting the capacity of loading/unloading of each node, the required delivery date of each shipment (considering the lead-times), and working-days of each node. This model was implemented on Python and solved using Python-MIP on a sample data set. Finally, the idea of a heuristic algorithm has been proposed as a way of improving the solution method that helps to implement the model on larger data sets in real business cases, including more nodes and shipments.

Keywords: Supply chain management, transportation, multiple-multiple network, timeslots management, mathematical modeling, mixed integer programming.

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Authors: H. Shayeghi, H. Hosseini, A. Shabani, M. Mahdavi

Abstract:

In this paper, optimal generation expansion planning (GEP) is investigated considering purchase prices, profits of independent power producers (IPPs) and reliability criteria using a new method based on hybrid coded Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). In this approach, optimal purchase price of each IPP is obtained by HCGA and reliability criteria are calculated by PSO technique. It should be noted that reliability criteria and the rate of carbon dioxide (CO2) emission have been considered as constraints of the GEP problem. Finally, the proposed method has been tested on the case study system. The results evaluation show that the proposed method can simply obtain optimal purchase prices of IPPs and is a fast method for calculation of reliability criteria in expansion planning. Also, considering the optimal purchase prices and profits of IPPs in generation expansion planning are caused that the expansion costs are decreased and the problem is solved more exactly.

Keywords: GEP Problem, IPPs, Reliability Criteria, GA, PSO.

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Authors: M. Seguini, D. Nedjar

Abstract:

An accuracy nonlinear analysis of a deep beam resting on elastic perfectly plastic soil is carried out in this study. In fact, a nonlinear finite element modeling for large deflection and moderate rotation of Euler-Bernoulli beam resting on linear and nonlinear random soil is investigated. The geometric nonlinear analysis of the beam is based on the theory of von Kàrmàn, where the Newton-Raphson incremental iteration method is implemented in a Matlab code to solve the nonlinear equation of the soil-beam interaction system. However, two analyses (deterministic and probabilistic) are proposed to verify the accuracy and the efficiency of the proposed model where the theory of the local average based on the Monte Carlo approach is used to analyze the effect of the spatial variability of the soil properties on the nonlinear beam response. The effect of six main parameters are investigated: the external load, the length of a beam, the coefficient of subgrade reaction of the soil, the Young’s modulus of the beam, the coefficient of variation and the correlation length of the soil’s coefficient of subgrade reaction. A comparison between the beam resting on linear and nonlinear soil models is presented for different beam’s length and external load. Numerical results have been obtained for the combination of the geometric nonlinearity of beam and material nonlinearity of random soil. This comparison highlighted the need of including the material nonlinearity and spatial variability of the soil in the geometric nonlinear analysis, when the beam undergoes large deflections.

Keywords: Finite element method, geometric nonlinearity, material nonlinearity, soil-structure interaction, spatial variability.

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Authors: Isaac K. E. Ampomah, Seong-Bae Park, Sang-Jo Lee

Abstract:

Over the past decade, there have been promising developments in Natural Language Processing (NLP) with several investigations of approaches focusing on Recognizing Textual Entailment (RTE). These models include models based on lexical similarities, models based on formal reasoning, and most recently deep neural models. In this paper, we present a sentence encoding model that exploits the sentence-to-sentence relation information for RTE. In terms of sentence modeling, Convolutional neural network (CNN) and recurrent neural networks (RNNs) adopt different approaches. RNNs are known to be well suited for sequence modeling, whilst CNN is suited for the extraction of n-gram features through the filters and can learn ranges of relations via the pooling mechanism. We combine the strength of RNN and CNN as stated above to present a unified model for the RTE task. Our model basically combines relation vectors computed from the phrasal representation of each sentence and final encoded sentence representations. Firstly, we pass each sentence through a convolutional layer to extract a sequence of higher-level phrase representation for each sentence from which the first relation vector is computed. Secondly, the phrasal representation of each sentence from the convolutional layer is fed into a Bidirectional Long Short Term Memory (Bi-LSTM) to obtain the final sentence representations from which a second relation vector is computed. The relations vectors are combined and then used in then used in the same fashion as attention mechanism over the Bi-LSTM outputs to yield the final sentence representations for the classification. Experiment on the Stanford Natural Language Inference (SNLI) corpus suggests that this is a promising technique for RTE.

Keywords: Deep neural models, natural language inference, recognizing textual entailment, sentence-to-sentence relation.

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Authors: E. Moroydor Derun, A. S. Kipcak, O. Dere Ozdemir, M. B. Piskin

Abstract:

Tea is consumed by a big part of the world-s population. It has an enormous importance for the Turkish culture. Nearly it is brewed every morning and evening at the all houses. Also it is consumed with lemon wedge. Habitual drinking of tea infusions may significantly contribute to daily dietary requirements of elements. Different instrumental techniques are used for determination of these elements. But atomic and mass spectroscopic methods are preferred most. In these study chromium, iron and selenium contents after the hot water brewing of black and green tea were determined by Optical Emission Spectroscopy (ICP-OES). Furthermore, effect of lemon addition on chromium, iron and selenium concentration tea infusions is investigated. Results of the investigation showed that concentration of chromium, iron and selenium increased in black tea with lemon addition. On the other hand only selenium is increased with lemon addition in green tea. And iron concentration is not detected in green tea but its concentration is determined as 1.420 ppm after lemon addition.

Keywords: Black tea, green tea, ICP-OES, lemon

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