Search results for: experimental and numerical modelling

Authors: Fally Titikpina, Abderafi Charki, Antoine Caucheteux, David Bigaud

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The building sector is one of the largest energy consumer with about 40% of the final energy consumption in the European Union. Ensuring building energy performance is of scientific, technological and sociological matter. To assess a building energy performance, the consumption being predicted or estimated during the design stage is compared with the measured consumption when the building is operational. When valuing this performance, many buildings show significant differences between the calculated and measured consumption. In order to assess the performance accurately and ensure the thermal efficiency of the building, it is necessary to evaluate the uncertainties involved not only in measurement but also those induced by the propagation of dynamic and static input data in the model being used. The evaluation of measurement uncertainty is based on both the knowledge about the measurement process and the input quantities which influence the result of measurement. Measurement uncertainty can be evaluated within the framework of conventional statistics presented in the \textit{Guide to the Expression of Measurement Uncertainty (GUM)} as well as by Bayesian Statistical Theory (BST). Another choice is the use of numerical methods like Monte Carlo Simulation (MCS). In this paper, we proposed to evaluate the uncertainty associated to the use of a simplified model for the estimation of the energy consumption of a given building. A detailed review and discussion of these three approaches (GUM, MCS and BST) is given. Therefore, an office building has been monitored and multiple sensors have been mounted on candidate locations to get required data. The monitored zone is composed of six offices and has an overall surface of 102 $m^2$. Temperature data, electrical and heating consumption, windows opening and occupancy rate are the features for our research work.

Keywords: building energy performance, uncertainty evaluation, GUM, bayesian approach, monte carlo method

Procedia PDF Downloads 442

Authors: Guang-Ho Cha

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This paper presents a context-sensitive media similarity search algorithm. One of the central problems regarding media search is the semantic gap between the low-level features computed automatically from media data and the human interpretation of them. This is because the notion of similarity is usually based on high-level abstraction but the low-level features do not sometimes reflect the human perception. Many media search algorithms have used the Minkowski metric to measure similarity between image pairs. However those functions cannot adequately capture the aspects of the characteristics of the human visual system as well as the nonlinear relationships in contextual information given by images in a collection. Our search algorithm tackles this problem by employing a similarity measure and a ranking strategy that reflect the nonlinearity of human perception and contextual information in a dataset. Similarity search in an image database based on this contextual information shows encouraging experimental results.

Keywords: context-sensitive search, image search, similarity ranking, similarity search

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Authors: Amine Hamdi, Sidi Mohammed Merghache, Brahim Fernini

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During abrasive machining of hard steels by belt grinding, the finished surface texture is influenced by the pressure between the abrasive belt and the workpiece; this pressure is the force applied by the contact roller on the workpiece. Therefore, the contact roller has an important role and has a direct impact on process efficiency. The objective of this article is to study and compare the influence of different contact rollers on the belt ground surface texture. The quality of the surface texture is characterized by eight roughness parameters (Ra, Rz, Rp, Rv, Rsk, Rku, Rsm, and Rdq) and five parameters of the bearing area curve (Rpk, Rk, Rvk, Mr1, and Mr2). The results of the experimental tests indicate a better surface texture obtained by the PA 6 polyamide roller (hardness 60 Shore D) compared to that obtained with other rollers of the same hardness or of different hardness. Simultaneously, optimum medium pressure between the belt and the workpiece allows chip removal without fracturing the abrasive grains. This generates a good surface texture.

Keywords: belt grinding, contact roller, pressure, abrasive belt, surface texture

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Authors: H. E. Ferrari, R. Farengo, C. F. Clauser

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Tungsten (W) will be used in ITER as one of the plasma facing components (PFCs). The W could migrate to the plasma center. This could have a potentially deleterious effect on plasma confinement. Electron cyclotron resonance heating (ECRH) can be used to prevent W accumulation. We simulated a series of H mode discharges in ASDEX U with PFC containing W, where central ECRH was used to prevent W accumulation in the plasma center. The experiments showed that the W density profiles were flat after a sawtooth crash, and become hollow in between sawtooth crashes when ECRH has been applied. It was also observed that a saturated kink mode was active in these conditions. We studied the effect of saturated kink like instabilities on the redistribution of W impurities. The kink was modeled as the sum of a simple analytical equilibrium (large aspect ratio, circular cross section) plus the perturbation produced by the kink. A numerical code that follows the exact trajectories of the impurity ions in the total fields and includes collisions was employed. The code is written in Cuda C and runs in Graphical Processing Units (GPUs), allowing simulations with a large number of particles with modest resources. Our simulations show that when the W ions have a thermal velocity distribution, the kink has no effect on the W density. When we consider the plasma rotation, the kink can affect the W density. When the average passing frequency of the W particles is similar to the frequency of the kink mode, the expulsion of W ions from the plasma core is maximum, and the W density shows a hollow structure. This could have implications for the mitigation of W accumulation.

Keywords: impurity transport, kink instability, tungsten accumulation, tungsten dynamics

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Authors: Marlon Gallo, Eduardo Miguel, Laura Oca, Eneko Gonzalez, Unai Iraola

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The heat generation of an energy storage system is an essential topic when designing a battery pack and its cooling system. Heat generation estimation is used together with thermal models to predict battery temperature in operation and adapt the design of the battery pack and the cooling system to these thermal needs guaranteeing its safety and correct operation. In the present work, a comparison between the use of a heat flux sensor (HFS) for indirect measurement of heat losses in a cell and the widely used and simplified version of Bernardi’s equation for estimation is presented. First, a Li-ion cell is thermally characterized with an HFS to measure the thermal parameters that are used in a first-order lumped thermal model. These parameters are the equivalent thermal capacity and the thermal equivalent resistance of a single Li-ion cell. Static (when no current is flowing through the cell) and dynamic (making current flow through the cell) tests are conducted in which HFS is used to measure heat between the cell and the ambient, so thermal capacity and resistances respectively can be calculated. An experimental platform records current, voltage, ambient temperature, surface temperature, and HFS output voltage. Second, an equivalent circuit model is built in a Matlab-Simulink environment. This allows the comparison between the generated heat predicted by Bernardi’s equation and the HFS measurements. Data post-processing is required to extrapolate the heat generation from the HFS measurements, as the sensor records the heat released to the ambient and not the one generated within the cell. Finally, the cell temperature evolution is estimated with the lumped thermal model (using both HFS and Bernardi’s equation total heat generation) and compared towards experimental temperature data (measured with a T-type thermocouple). At the end of this work, a critical review of the results obtained and the possible mismatch reasons are reported. The results show that indirectly measuring the heat generation with HFS gives a more precise estimation than Bernardi’s simplified equation. On the one hand, when using Bernardi’s simplified equation, estimated heat generation differs from cell temperature measurements during charges at high current rates. Additionally, for low capacity cells where a small change in capacity has a great influence on the terminal voltage, the estimated heat generation shows high dependency on the State of Charge (SoC) estimation, and therefore open circuit voltage calculation (as it is SoC dependent). On the other hand, with indirect measuring the heat generation with HFS, the resulting error is a maximum of 0.28ºC in the temperature prediction, in contrast with 1.38ºC with Bernardi’s simplified equation. This illustrates the limitations of Bernardi’s simplified equation for applications where precise heat monitoring is required. For higher current rates, Bernardi’s equation estimates more heat generation and consequently, a higher predicted temperature. Bernardi´s equation accounts for no losses after cutting the charging or discharging current. However, HFS measurement shows that after cutting the current the cell continues generating heat for some time, increasing the error of Bernardi´s equation.

Keywords: lithium-ion battery, heat flux sensor, heat generation, thermal characterization

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Authors: M. A. Askari, M. A. Nazari, P. Perrier, Y. Payan

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Growth and remodeling of biological structures have gained lots of attention over the past decades. Determining the response of living tissues to mechanical loads is necessary for a wide range of developing fields such as prosthetics design or computerassisted surgical interventions. It is a well-known fact that biological structures are never stress-free, even when externally unloaded. The exact origin of these residual stresses is not clear, but theoretically, growth is one of the main sources. Extracting body organ’s shapes from medical imaging does not produce any information regarding the existing residual stresses in that organ. The simplest cause of such stresses is gravity since an organ grows under its influence from birth. Ignoring such residual stresses might cause erroneous results in numerical simulations. Accounting for residual stresses due to tissue growth can improve the accuracy of mechanical analysis results. This paper presents an original computational framework based on gradual growth to determine the residual stresses due to growth. To illustrate the method, we apply it to a finite element model of a healthy human face reconstructed from medical images. The distribution of residual stress in facial tissues is computed, which can overcome the effect of gravity and maintain tissues firmness. Our assumption is that tissue wrinkles caused by aging could be a consequence of decreasing residual stress and thus not counteracting gravity. Taking into account these stresses seems therefore extremely important in maxillofacial surgery. It would indeed help surgeons to estimate tissues changes after surgery.

Keywords: finite element method, growth, residual stress, soft tissue

Procedia PDF Downloads 256

Authors: Gabriela R. Silveira, Claudia S. Rocha, Lais S. Vitti, Jeane L. Borges, Helen B. Durgante

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Emerging adulthood occurs after adolescence in a period that maybe be marked by experimentation, identity reconfigurations, labor life demands, and insertion in the work environment, which tends to generate stress and emotional instability. Health promotion programs for the development of strengths and virtues, based on Positive Psychology, for emerging adults are sparse in Brazil. The aim of this study was to evaluate the preliminary effects of an online multi-component Positive Psychology program for the health promotion of emerging adults based on Cognitive Behavioural Therapy and Positive Psychology. The program included six online (synchronous) weekly group sessions of approximately two hours each and homework (asynchronous) activities. The themes worked were Values and self-care/Prudence, Optimism, Empathy, Gratitude, Forgiveness, and Meaning of life and work. This study presents data from a longitudinal, pre-experimental design with pre (T1) and post-test (T2) evaluation in the intervention group. 47 individuals aged between 19-30 years old participated, mean age of 24.53 years (SD=3.13), 37 females (78.7%). 42 (89.4%) self-defined as heterosexual, four (8.5%) as homosexual, and one (2.5%) as bisexual. 33 (70.2%) had incomplete higher education, four (8.5%) completed higher education, and seven (14.9%) had a graduate level of education. 27 participants worked (57.4%), out of which 25 were health workers (53.2%). 14 (29.8%) were caregivers, 27 (57.4%) had a spiritual belief, 36 (76.6%) had access to leisure, and 38 (80.9%) had perceived social support. The instruments used were a sociodemographic questionnaire, the 10-item Perceived Stress Scale, and the 12-item General Health Questionnaire. The program was advertised on social networks and interested participants filled out the Consent Form and the evaluation protocol at T1 and T2 via Google Docs form. The main research was approved (CEP n.1,899,368; 4,143,219; CAAE: 61997516.5.0000.5334) and complied with sanitary and Ethics criteria in research with human beings. Wilcoxon statistics revealed significant improvements in indicators of perceived stress between T1 (X=22.21, SD=6.79) and T2 (X=15.10, SD=5.82); (Z=-4.353; p=0.001) as well as depression and anxiety symptoms (T1:X=26.72, SD=8.84; T2: X=19.23, SD=4.68); (Z=-3.945, p=0.001) of the emerging adults after their participation in the programme. The programme has an innovative character not only for presenting an online Positive Psychology approach but also for being based on an intervention developed, evaluated, and manualized in Brazil. By focusing on emerging adults, this study contributes to advancing research on a relatively new field in developmental studies. As a limitation, this is a pre-experimental and pilot study, requiring an increase in sample size for greater statistical robustness, also qualitative data analysis is crucial for methodological complementarity. The importance of investing efforts to accompany this age group and provide advances in longitudinal research in the area of health promotion and disease prevention is highlighted.

Keywords: emerging adults, disease prevention, health promotion, online program

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Authors: N. Jinesh, K. Shankar

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This article presents a method of using the one dimensional piezo-electric patch on beam model for structural identification. A hybrid element constituted of one dimensional beam element and a PZT sensor is used with reduced material properties. This model is convenient and simple for identification of beams. Accuracy of this element is first verified against a corresponding 3D finite element model (FEM). The structural identification is carried out as an inverse problem whereby parameters are identified by minimizing the deviation between the predicted and measured voltage response of the patch, when subjected to excitation. A non-classical optimization algorithm Particle Swarm Optimization is used to minimize this objective function. The signals are polluted with 5% Gaussian noise to simulate experimental noise. The proposed method is applied on beam structure and identified parameters are stiffness and damping. The model is also validated experimentally.

Keywords: inverse problem, particle swarm optimization, PZT patches, structural identification

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Authors: Hidir S. Nogay

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In this study, two systems were created to predict interior temperature in induction motor. One of them consisted of a simple ANN model which has two layers, ten input parameters and one output parameter. The other one consisted of eight ANN models connected each other as cascaded. Cascaded ANN system has 17 inputs. Main reason of cascaded system being used in this study is to accomplish more accurate estimation by increasing inputs in the ANN system. Cascaded ANN system is compared with simple conventional ANN model to prove mentioned advantages. Dataset was obtained from experimental applications. Small part of the dataset was used to obtain more understandable graphs. Number of data is 329. 30% of the data was used for testing and validation. Test data and validation data were determined for each ANN model separately and reliability of each model was tested. As a result of this study, it has been understood that the cascaded ANN system produced more accurate estimates than conventional ANN model.

Keywords: cascaded neural network, internal temperature, inverter, three-phase induction motor

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Authors: Hrishi Rakshit, Pooneh Bagheri Zadeh

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This paper investigates the performance of drone classification methods using conventional DCNN with different hyperparameters, when additional drone audio data is embedded in the dataset for training and further classification. In this paper, first a custom dataset is created using different images of drones from University of South California (USC) datasets and Leeds Beckett university datasets with embedded drone audio signal. The three well-known DCNN architectures namely, Resnet50, Darknet53 and Shufflenet are employed over the created dataset tuning their hyperparameters such as, learning rates, maximum epochs, Mini Batch size with different optimizers. Precision-Recall curves and F1 Scores-Threshold curves are used to evaluate the performance of the named classification algorithms. Experimental results show that Resnet50 has the highest efficiency compared to other DCNN methods.

Keywords: drone classifications, deep convolutional neural network, hyperparameters, drone audio signal

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Authors: Rabia Hunky, Hayat Kalifa, Bai

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The wettability of carbonate reservoirs has been widely recognized as an important parameter in oil recovery by flooding technology. Many surfactants have been studied for this application. However, the importance of wettability alteration in sandstone reservoirs by surfactant has been poorly studied. In this paper, our recent study of the relationship between rock surface wettability and cumulative oil recovery for sandstone cores is reported. In our research, it has been found there is a good agreement between the wettability and oil recovery. Nonionic surfactants, Tomadol® 25-12 and Tomadol® 45-13, are very effective in wettability alteration of sandstone core surface from highly oil-wet conditions to water-wet conditions. By spontaneous imbibition test, Interfacial tension, and contact angle measurement these two surfactants exhibit the highest recovery of the synthetic oil made with heavy oil. Based on these experimental results, we can further conclude that the contact angle measurement and imbibition test can be used as rapid screening tools to identify better EOR surfactants to increase heavy oil recovery from sandstone reservoirs.

Keywords: EOR, oil gas, IOR, WC, IF, oil and gas

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Authors: Cherief Houria, Fouka Mourad

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In this work, the simulation of the radiation attenuation is carried out in a photon detector consisting of different common shielding material using a Monte Carlo program called PTM. The aim of the study is to investigate the effect of atomic weight and the thickness of shielding materials on the gamma radiation attenuation ability. The linear attenuation coefficients of Aluminum (Al), Iron (Fe), and lead (Pb) elements were evaluated at photons energy of 661:7KeV that are considered to be emitted from a standard radioactive point source Cs 137. The experimental measurements have been performed for three materials to obtain these linear attenuation coefficients, using a Gamma NaI(Tl) scintillation detector. Our results have been compared with the simulation results of the linear attenuation coefficient using the XCOM database and Geant4 codes and reveal that they are well agreed with both simulation data.

Keywords: gamma photon, Monte Carlo program, radiation attenuation, shielding material, the linear attenuation coefficient

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Authors: Pisut Painmanakul, Thawatchai Chintateerachai, Supanid Lertlapwasin, Nusara Rojvilavan, Tanun Chalermsinsuwan, Nattawin Chawaloesphonsiya, Onanong Larpparisudthi

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Conventional coagulation, advance oxidation process (AOPs), and the combined process were evaluated and compared for its suitability to treat the stabilized cutting-oil wastewater. The 90% efficiency was obtained from the coagulation at Al2(SO4)3 dosage of 150 mg/L and pH 7. On the other hands, efficiencies of AOPs for 30 minutes oxidation time were 10% for acoustic oxidation, 12% for acoustic oxidation with hydrogen peroxide, 76% for Fenton, and 92% sono-Fenton processes. The highest efficiency for effective oil removal of AOPs required large amount of chemical. Therefore, AOPs were studied as a post-treatment after conventional separation process. The efficiency was considerable as the effluent COD can pass the standard required for industrial wastewater discharge with less chemical and energy consumption.

Keywords: cutting oily-wastewater, advance oxidation process, sono-fenton, combined process

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Authors: Jin-Wei Liang, Hung-Yi Chen, Lung Lin

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In this paper feedforward controller is designed to eliminate nonlinear hysteresis behaviors of a piezoelectric stack actuator (PSA) driven system. The control design is based on inverse Prandtl-Ishlinskii (P-I) hysteresis model identified using particle swarm optimization (PSO) technique. Based on the identified P-I model, both the inverse P-I hysteresis model and feedforward controller can be determined. Experimental results obtained using the inverse P-I feedforward control are compared with their counterparts using hysteresis estimates obtained from the identified Bouc-Wen model. Effectiveness of the proposed feedforward control scheme is demonstrated. To improve control performance feedback compensation using traditional PID scheme is adopted to integrate with the feedforward controller.

Keywords: the Bouc-Wen hysteresis model, particle swarm optimization, Prandtl-Ishlinskii model, automation engineering

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Authors: Beatriz Botella-Gil, Patricio Martínez-Barco, Lea Canales

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The Internet and ICT are an integral element of and omnipresent in our daily lives. Technologies have changed the way we see the world and relate to it. The number of companies in the ICT sector is increasing every year, and there has also been an increase in the work that occurs online, from sending e-mails to the way companies promote themselves. In social life, ICT’s have gained momentum. Social networks are useful for keeping in contact with family or friends that live far away. This change in how we manage our relationships using electronic devices and social media has been experienced differently depending on the age of the person. According to currently available data, people are increasingly connected to social media and other forms of online communication. Therefore, it is no surprise that violent content has also made its way to digital media. One of the important reasons for this is the anonymity provided by social media, which causes a sense of impunity in the victim. Moreover, it is not uncommon to find derogatory comments, attacking a person’s physical appearance, hobbies, or beliefs. This is why it is necessary to develop artificial intelligence tools that allow us to keep track of violent comments that relate to violent events so that this type of violent online behavior can be deterred. The objective of our research is to create a guide for detecting and recording violent messages. Our annotation guide begins with a study on the problem of violent messages. First, we consider the characteristics that a message should contain for it to be categorized as violent. Second, the possibility of establishing different levels of aggressiveness. To download the corpus, we chose the social network Twitter for its ease of obtaining free messages. We chose two recent, highly visible violent cases that occurred in Spain. Both of them experienced a high degree of social media coverage and user comments. Our corpus has a total of 633 messages, manually tagged, according to the characteristics we considered important, such as, for example, the verbs used, the presence of exclamations or insults, and the presence of negations. We consider it necessary to create wordlists that are present in violent messages as indicators of violence, such as lists of negative verbs, insults, negative phrases. As a final step, we will use automatic learning systems to check the data obtained and the effectiveness of our guide.

Keywords: human language technologies, language modelling, offensive language detection, violent online content

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Authors: H. Nouri, I. E. Achouri, A. Grimes, H. Ait Said, M. Aissou, Y. Zebboudj

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This paper aims to analysis the behaviour of DC corona discharge in wire-to-plate electrostatic precipitators (ESP). Current-voltage curves are particularly analysed. Experimental results show that discharge current is strongly affected by the applied voltage. The proposed method of current identification is to use the method of least squares. Least squares problems that of into two categories: linear or ordinary least squares and non-linear least squares, depending on whether or not the residuals are linear in all unknowns. The linear least-squares problem occurs in statistical regression analysis; it has a closed-form solution. A closed-form solution (or closed form expression) is any formula that can be evaluated in a finite number of standard operations. The non-linear problem has no closed-form solution and is usually solved by iterative.

Keywords: electrostatic precipitator, current-voltage characteristics, least squares method, electric field, magnetic field

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Authors: Isra Elfatih Salih Edrees, Mehmet Serdar Ufuk Türeli

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In this paper, an energy-aware method is presented, integrating energy-efficient relay-augmented techniques for correlated data routing with the goal of optimizing bottleneck throughput in wireless sensor networks. The system tackles the dual challenge of throughput optimization while considering sensor network energy consumption. A unique routing metric has been developed to enable throughput maximization while minimizing energy consumption by utilizing data correlation patterns. The paper introduces a game theoretic framework to address the NP-complete optimization problem inherent in throughput-maximizing correlation-aware routing with energy limitations. By creating an algorithm that blends energy-aware route selection strategies with the best reaction dynamics, this framework provides a local solution. The suggested technique considerably raises the bottleneck throughput for each source in the network while reducing energy consumption by choosing the best routes that strike a compromise between throughput enhancement and energy efficiency. Extensive numerical analyses verify the efficiency of the method. The outcomes demonstrate the significant decrease in energy consumption attained by the energy-efficient relay-augmented bottleneck throughput maximization technique, in addition to confirming the anticipated throughput benefits.

Keywords: correlated data aggregation, energy efficiency, game theory, relay-augmented routing, throughput maximization, wireless sensor networks

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Authors: J. Yang, Y. Ma, X. Zhang, S. Li, Y. Zhang

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The traditional k-means algorithm has been widely used as a simple and efficient clustering method. However, the algorithm often converges to local minima for the reason that it is sensitive to the initial cluster centers. In this paper, an algorithm for selecting initial cluster centers on the basis of minimum spanning tree (MST) is presented. The set of vertices in MST with same degree are regarded as a whole which is used to find the skeleton data points. Furthermore, a distance measure between the skeleton data points with consideration of degree and Euclidean distance is presented. Finally, MST-based initialization method for the k-means algorithm is presented, and the corresponding time complexity is analyzed as well. The presented algorithm is tested on five data sets from the UCI Machine Learning Repository. The experimental results illustrate the effectiveness of the presented algorithm compared to three existing initialization methods.

Keywords: degree, initial cluster center, k-means, minimum spanning tree

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Authors: Mojtaba Valinataj

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Nowadays reversible logic has received many attentions as one of the new fields for reducing the power consumption. On the other hand, the processing systems have weaknesses against different external effects. In this paper, some error detecting reversible logic serial multipliers are proposed by incorporating the parity-preserving gates. This way, the new designs are presented for signed parity-preserving serial multipliers based on the Booth's algorithm by exploiting the new arrangements of existing gates. The experimental results show that the proposed 4×4 multipliers in this paper reach up to 20%, 35%, and 41% enhancements in the number of constant inputs, quantum cost, and gate count, respectively, as the reversible logic criteria, compared to previous designs. Furthermore, all the proposed designs have been generalized for n×n multipliers with general formulations to estimate the main reversible logic criteria as the functions of the multiplier size.

Keywords: Booth’s algorithm, error detection, multiplication, parity-preserving gates, quantum computers, reversible logic

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Authors: Toshanlal Meenpal, Ankita Meenpal

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A very important technique in reversible data hiding field is Difference expansion. Secret message as well as the cover image may be completely recovered without any distortion after data extraction process due to reversibility feature. In general, in any difference expansion scheme embedding is performed by integer transform in the difference image acquired by grouping two neighboring pixel values. This paper proposes an improved reversible difference expansion embedding scheme. We mainly consider edge direction for embedding by modifying the difference of two neighboring pixels values. In general, the larger difference tends to bring a degraded stego image quality than the smaller difference. Image quality in the range of 0.5 to 3.7 dB in average is achieved by the proposed scheme, which is shown through the experimental results. However payload wise it achieves almost similar capacity in comparisons with previous method.

Keywords: information hiding, wedge direction, difference expansion, integer transform

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Authors: Soroush Hooshyar, Mohamadali Masoudian, Natalie Germann

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Many soft materials such as polymer solutions can develop localized bands with different shear rates, which are known as shear bands. Using the generalized bracket approach of nonequilibrium thermodynamics, we recently developed a new two-fluid model to study shear banding for semi-dilute polymer solutions. The two-fluid approach is an appropriate means for describing diffusion processes such as Fickian diffusion and stress-induced migration. In this approach, it is assumed that the local gradients in concentration and, if accounted for, also stress generate a nontrivial velocity difference between the components. Since the differential velocity is treated as a state variable in our model, the implementation of the boundary conditions arising from the derivative diffusive terms is straightforward. Our model is a good candidate for benchmark simulations because of its simplicity. We analyzed its behavior in cylindrical Couette flow, a rectilinear channel flow, and a 4:1 planar contraction flow. The latter problem was solved using the OpenFOAM finite volume package and the impact of shear banding on the lip and salient vortices was investigated. For the other smooth geometries, we employed a standard Chebyshev pseudospectral collocation method. The results showed that the steady-state solution is unique with respect to initial conditions, deformation history, and the value of the diffusivity constant. However, smaller the value of the diffusivity constant is, the more time it takes to reach the steady state.

Keywords: nonequilibrium thermodynamics, planar contraction, polymer solutions, shear banding, two-fluid approach

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Authors: M. S. Khurram, S. A. Memon, S. Khan

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Bed voidage behavior among different flow regimes for Geldart A, B, and D particles (fluid catalytic cracking catalyst (FCC), particle A and glass beads) of diameter range 57-872 μm, apparent density 1470-3092 kg/m³, and bulk density range 890-1773 kg/m³ were investigated in a gas-solid circulating fluidized bed of 0.1 m-i.d. and 2.56 m-height of plexi-glass. Effects of variables (gas velocity, particle properties, and static bed height) were analyzed on bed voidage. The axial voidage profile showed a typical trend along the riser: a dense bed at the lower part followed by a transition in the splash zone and a lean phase in the freeboard. Bed expansion and dense bed voidage increased with an increase of gas velocity as usual. From experimental results, a generalized model relationship based on inverse fluidization number for dense bed voidage from bubbling to fast fluidization regimes was presented.

Keywords: axial voidage, circulating fluidized bed, splash zone, static bed

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Authors: Nishant Rodrigues, Nicole Spanedda, Chilukuri K. Mohan, Arindam Chakraborty

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A crucial objective in quantum chemistry is the computation of the energy levels of chemical systems. This task requires electron-repulsion integrals as inputs, and the steep computational cost of evaluating these integrals poses a major numerical challenge in efficient implementation of quantum chemical software. This work presents a moment-based machine-learning approach for the efficient evaluation of electron-repulsion integrals. These integrals were approximated using linear combinations of a small number of moments. Machine learning algorithms were applied to estimate the coefficients in the linear combination. A random forest approach was used to identify promising features using a recursive feature elimination approach, which performed best for learning the sign of each coefficient but not the magnitude. A neural network with two hidden layers were then used to learn the coefficient magnitudes along with an iterative feature masking approach to perform input vector compression, identifying a small subset of orbitals whose coefficients are sufficient for the quantum state energy computation. Finally, a small ensemble of neural networks (with a median rule for decision fusion) was shown to improve results when compared to a single network.

Keywords: quantum energy calculations, atomic orbitals, electron-repulsion integrals, ensemble machine learning, random forests, neural networks, feature extraction

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Authors: See-Yuan Cheng, Kwang-Yhee Chin, Shuhaimi Mansor

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Rear-roof spoiler is commonly used for improving the aerodynamic performance of road vehicles. This study aims to investigate the effect of yaw angle on the effectiveness of strip-type rear-roof spoiler in providing lower drag and lift coefficients of a hatchback model. A computational fluid dynamics (CFD) method was used. The numerically obtained results were compared to the experimental data for validation of the CFD method. At increasing yaw angle, both the drag and lift coefficients of the model were to increase. In addition, the effectiveness of spoiler was deteriorated. These unfavorable effects were due to the formation of longitudinal vortices around the side edges of the model that had caused the surface pressure of the model to drop. Furthermore, there were significant crossflow structures developed behind the model at larger yaw angle, which were associated with the drop in the surface pressure of the rear section of the model and cause the drag coefficient to rise.

Keywords: Ahmed model, aerodynamics, spoiler, yaw angle

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Authors: Arianne Van Der Wal, Femke Van Horen, Amir Grinstein

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Consumers in today’s world are confronted with the alarming consequences of unsustainable behavior such as pollution and resource degradation. In addition, they are facing an increase in uncertainty due to, for instance, economic instability and terror attacks. Although these two problems are central to consumers’ lives, occur on a global scale, and have significant impact on the world’s political, economic, environmental, and social landscapes, they have not been systematically studied in tandem before. Contributing to research on persuasion and pro-social behavior, this paper shows in five studies (three experimental studies and one field study) that the two problems are intertwined. We demonstrate that uncertainty leads to lower sustainable behavior in comparison to certainty (Studies 1 and 2) and that this is due to consumers displaying higher levels of temporal discounting (i.e., adopting a more immediate orientation; Study 2). Finally, providing valuable implications for policy makers and responsible marketers, we show that emphasizing the immediate benefits of sustainable behavior during uncertainty buffers the negative effect (Studies 3 and 4).

Keywords: sustainable behavior, uncertainty, temporal discounting, framing

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Authors: Rouzbeh Ramezani, Renzo Di Felice

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Nowadays, removal of CO₂ as one of the major contributors to global warming using alternative solvents with high CO₂ absorption efficiency, is an important industrial operation. In this study, three amines, including 2-methylpiperazine, potassium sarcosinate and potassium lysinate as potential additives, were added to the potassium carbonate solution as a base solvent for CO₂ capture. In order to study the absorption performance of CO₂ in terms of loading capacity of CO₂ and absorption rate, the absorption experiments in a blend of additives with potassium carbonate were carried out using the vapor-liquid equilibrium apparatus at a temperature of 313.15 K, CO₂ partial pressures ranging from 0 to 50 kPa and at mole fractions 0.2, 0.3, and 0.4. Furthermore, the performance of CO₂ absorption in these blend solutions was compared with pure monoethanolamine and with pure potassium carbonate. Finally, a correlation with good accuracy was developed using the nonlinear regression analysis in order to predict CO₂ loading capacity.

Keywords: absorption rate, carbon dioxide, CO2 capture, global warming, loading capacity

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Authors: Elkedrouci Lotfi, Diao Bo, Pang Sen, Li Yi

Abstract:

Deterioration of reinforced concrete structures is a serious concern in the construction engineering, largely due to chloride induced corrosion of reinforcement. Chloride penetration is markedly influenced by one or several major factors at the same time such as cuing in combination with different crack widths which have spectacular effect on reinforced concrete structures. This research presents the results of an experimental investigation involving reinforced concrete beams with three different crack widths ranging from 0 to 0.2mm, curing temperatures of 20°C or 40°C and water-to-cement of 0.5. Chloride content profiles were determined under non-steady state diffusion at 20°C. Based on the obtained results, higher chloride content was obtained under condition of high curing temperature in combination with large crack more than 0.1mm and there are no significant differences between narrow crack width (less than 0.1 mm) and beams without crack (0mm).

Keywords: crack width, high curing temperature, rapid chloride migration, reinforced concrete beam

Procedia PDF Downloads 190

Authors: Erez Yerushalmi, Sani Ziv

Abstract:

The rising demand for healthcare services, without a corresponding rise in public supply, led to a debate on whether to increase private healthcare provision - especially in hospital services and second-tier healthcare. Proponents for increasing private healthcare highlight gains in efficiency, while opponents its risk to social welfare. None, however, provide a measure of the social value and its impact on the economy in terms of a monetary value. In this paper, we impute a minimum social value of public healthcare that corresponds to indifference between gains in efficiency, with losses to social welfare. Our approach resembles contingent valuation methods that introduce a hypothetical market for non-commodities, but is different from them because we use numerical simulation techniques to exploit certain market failure conditions. In this paper, we develop a general equilibrium model that distinguishes between public-private healthcare services and public-private financing. Furthermore, the social value is modelled as a by product of healthcare services. The model is then calibrated to our unique health focused Social Accounting Matrix of Israel, and simulates the introduction of a hypothetical health-labour market - given that it is heavily regulated in the baseline (i.e., the true situation in Israel today). For baseline parameters, we estimate the minimum social value at around 18% public healthcare financing. The intuition is that the gain in economic welfare from improved efficiency, is offset by the loss in social welfare due to a reduction in available social value. We furthermore simulate a deregulated healthcare scenario that internalizes the imputed value of social value and searches for the optimal weight of public and private healthcare provision.

Keywords: contingent valuation method (CVM), general equilibrium model, hypothetical market, private-public healthcare, social value of public healthcare

Procedia PDF Downloads 129

Authors: H. Mat Kiah, Rafiziana M. Kasmani, Norazana Ibrahim, Roshafima R. Ali, Aziatul N.Sadikin

Abstract:

An experimental study has been done to investigate the flame acceleration in a closed pipe. A horizontal steel pipe, 2m long and 0.1 m in diameter (L/D of 20), was used in this work. For tests with 90 degree bends, the bend had a radius of 0.1 m and thus, the pipe was lengthened 1 m (based on the centreline length of the segment). Ignition was affected one end of the vessel while the other end was closed. Only stoichiometric concentration (Ф, = 1.0) of natural gas/air mixtures will be reported in this paper. It was demonstrated that bend pipe configuration gave three times higher in maximum over-pressure (5.5 bars) compared to straight pipe (2.0 bars). From the results, the highest flame speed of 63 m s-1 was observed in a gas explosion with bent pipe, greater by a factor of ~3 as compared with straight pipe (23 m s-1). This occurs because bending acts similar to an obstacle, in which this mechanism can induce more turbulence, initiating combustion in an unburned pocket at the corner region and causing a high mass burning rate which increases the flame speed.

Keywords: bending, gas explosion, bending, flame acceleration, over-pressure

Procedia PDF Downloads 395

Authors: Seok Hong Min, Tae Kwon Ha

Abstract:

With increasing demands for high performance materials, intensive interest on the Ti has been focused. Especially, low cost production process of Ti has been extremely necessitated from wide parts and various industries. Tetrachloride (TiCl₄) is produced by fluidized bed using high TiO₂ feedstock and used as an intermediate product for the production of metal titanium sponge. Reduction of TiCl₄ is usually conducted by Kroll process using magnesium as a reduction reagent, producing metallic Ti in the shape of sponge. The process is batch type and takes very long time including post processes treating sponge. As an alternative reduction reagent, hydrogen in the state of plasma has long been strongly recommended. Experimental confirmation has not been completely reported yet and more strict analysis is required. In the present study, hydrogen plasma reduction process has been thermodynamically analyzed focusing the effects of temperature, pressure and concentration. All thermodynamic calculations were performed using the FactSage® thermodynamical software.

Keywords: TiCl₄, titanium, hydrogen, plasma, reduction, thermodynamic calculation

Procedia PDF Downloads 309