Search results for: Gaussian Mixture Model

Authors: S. M. M. Syairah, M. H. Rajikin, A-R. Sharaniza

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Several embryonic cellular mechanism including cell cycle, growth and apoptosis are regulated by phosphatidylinositol-3- kinase (PI3K)/Akt signaling pathway. The goal of present study is to determine the effects of annatto (Bixa orellana)-derived δ-tocotrienol (δ-TCT) on the regulations of PI3K/Akt genes in murine morula. Twenty four 6-8 week old (23-25g) female balb/c mice were randomly divided into four groups (G1-G4; n=6). Those groups were subjected to the following treatments for 7 consecutive days: G1 (control) received tocopherol stripped corn oil, G2 was given 60 mg/kg/day of δ-TCT mixture (contains 90% delta & 10% gamma isomers), G3 was given 60 mg/kg/day of pure δ-TCT (>98% purity) and G4 received 60 mg/kg/day α-TOC. On Day 8, females were superovulated with 5 IU Pregnant Mare’s Serum Gonadotropin (PMSG) for 48 hours followed with 5 IU human Chorionic Gonadotropin (hCG) before mated with males at the ratio of 1:1. Females were sacrificed by cervical dislocation for embryo collection 48 hours post-coitum. About fifty morulas from each group were used in the gene expression analyses using Affymetrix QuantiGene Plex 2.0 Assay. Present data showed a significant increase (p<0.05) in the average number (mean + SEM) of morula produced in G2 (27.32 + 0.23), G3 (25.42 + 0.21) and G4 (27.21 + 0.34) compared to control group (G1 – 14.61 + 0.25). This is parallel with the high expression of PDK1 gene with increase of 2.75-fold (G2), 3.07-fold (G3) and 3.59-fold (G4) compared to G1. From the present data, it can be concluded that supplementation with δ-TCT(s) and α-TOC induced high expression of PDK1 in G2-G4 which enhanced the PI3K/Akt signaling activity, resulting in the increased number of morula.

Keywords: Embryonic development, morula, nicotine, vitamin E.

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Authors: Chong-Yang Qiao

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Mobile augmented reality (MAR) tracking targets from the surroundings and aids operators for interactive data and procedures visualization, potential equipment and system understandably. Operators remotely communicate and coordinate with each other for the continuous tasks, information and data exchange between control room and work-site. In the routine work, distributed control system (DCS) monitoring and work-site manipulation require operators interact in real-time manners. The critical question is the improvement of user experience in cooperative works through applying Augmented Reality in the traditional industrial field. The purpose of this exploratory study is to find the cognitive model for the multiple task performance by MAR. In particular, the focus will be on the comparison between different tasks and environment factors which influence information processing. Three experiments use interface and interaction design, the content of start-up, maintenance and stop embedded in the mobile application. With the evaluation criteria of time demands and human errors, and analysis of the mental process and the behavior action during the multiple tasks, heuristic evaluation was used to find the operators performance with different situation factors, and record the information processing in recognition, interpretation, judgment and reasoning. The research will find the functional properties of MAR and constrain the development of the cognitive model. Conclusions can be drawn that suggest MAR is easy to use and useful for operators in the remote collaborative works.

Keywords: Mobile augmented reality, remote collaboration, user experience, cognitive model.

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Authors: Deepak Kumar, Vivek Kumar, V. P. Singh

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This paper describes a steady state model of a multiple effect evaporator system for simulation and control purposes. The model includes overall as well as component mass balance equations, energy balance equations and heat transfer rate equations for area calculations for all the effects. Each effect in the process is represented by a number of variables which are related by the energy and material balance equations for the feed, product and vapor flow for backward, mixed and split feed. For simulation 'fsolve' solver in MATLAB source code is used. The optimality of three sequences i.e. backward, mixed and splitting feed is studied by varying the various input parameters.

Keywords: MATLAB "fsolve" solver, multiple effectevaporators, black liquor, feeding sequences.

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Authors: E. Elgendy, J. Schmidt

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Drop-in of R-22 alternatives in refrigeration and air conditioning systems requires a redesign of system components to improve system performance and reliability with the alternative refrigerants. The present paper aims at design adiabatic capillary tubes for R-22 alternatives such as R-417A, R-422D and R-438A. A theoretical model has been developed and validated with the available experimental data from literature for R-22 over a wide range of both operating and geometrical parameters. Predicted lengths of adiabatic capillary tube are compared with the lengths of the capillary tube needed under similar experimental conditions and majority of predictions are found to be within 4.4% of the experimental data. Hence, the model has been applied for R-417A, R- 422D and R-438A and capillary tube selection charts and correlations have been computed. Finally a comparison between the selected refrigerants and R-22 has been introduced and the results showed that R-438A is the closest one to R-22.

Keywords: Adiabatic flow, Capillary tube, R-22 alternatives, Rating charts, Modelling.

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Authors: A. Puras Trueba, J. R. Llata García

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A nonlinear optimal controller with a fuzzy gain scheduler has been designed and applied to a Line-Of-Sight (LOS) stabilization system. Use of Linear Quadratic Regulator (LQR) theory is an optimal and simple manner of solving many control engineering problems. However, this method cannot be utilized directly for multigimbal LOS systems since they are nonlinear in nature. To adapt LQ controllers to nonlinear systems at least a linearization of the model plant is required. When the linearized model is only valid within the vicinity of an operating point a gain scheduler is required. Therefore, a Takagi-Sugeno Fuzzy Inference System gain scheduler has been implemented, which keeps the asymptotic stability performance provided by the optimal feedback gain approach. The simulation results illustrate that the proposed controller is capable of overcoming disturbances and maintaining a satisfactory tracking performance.

Keywords: Fuzzy Gain-Scheduling, Gimbal, Line-Of-SightStabilization, LQR, Optimal Control

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Authors: Chieh-Yuan Tsai, Chuang-Cheng Chiu

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Biclustering aims at identifying several biclusters that reveal potential local patterns from a microarray matrix. A bicluster is a sub-matrix of the microarray consisting of only a subset of genes co-regulates in a subset of conditions. In this study, we extend the motif of subspace clustering to present a K-biclusters clustering (KBC) algorithm for the microarray biclustering issue. Besides minimizing the dissimilarities between genes and bicluster centers within all biclusters, the objective function of the KBC algorithm additionally takes into account how to minimize the residues within all biclusters based on the mean square residue model. In addition, the objective function also maximizes the entropy of conditions to stimulate more conditions to contribute the identification of biclusters. The KBC algorithm adopts the K-means type clustering process to efficiently make the partition of K biclusters be optimized. A set of experiments on a practical microarray dataset are demonstrated to show the performance of the proposed KBC algorithm.

Keywords: Microarray, Biclustering, Subspace clustering, Meansquare residue model.

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Authors: Sajeena Beevi. B, Jose P. P., G. Madhu

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The aim of this study was to obtain the optimal conditions for biogas production from anaerobic digestion of organic fraction of municipal solid waste (OFMSW) using response surface methodology (RSM). The parameters studied were initial pH, substrate concentration and total organic carbon (TOC). The experimental results showed that the linear model terms of initial pH and substrate concentration and the quadratic model terms of the substrate concentration and TOC had significant individual effect (p < 0.05) on biogas yield. However, there was no interactive effect between these variables (p > 0.05). The highest level of biogas produced was 53.4 L/Kg VS at optimum pH, substrate concentration and total organic carbon of 6.5, 99gTS/L and 20.32 g/L respectively.

Keywords: Anaerobic Digestion, Biogas, Optimization, Response Surface Methodology.

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Authors: Jung-Eun Park, Kyung-Whan Oh

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Intelligent systems are required in order to quickly and accurately analyze enormous quantities of data in the Internet environment. In intelligent systems, information extracting processes can be divided into supervised learning and unsupervised learning. This paper investigates intelligent clustering by unsupervised learning. Intelligent clustering is the clustering system which determines the clustering model for data analysis and evaluates results by itself. This system can make a clustering model more rapidly, objectively and accurately than an analyzer. The methodology for the automatic clustering intelligent system is a multi-agent system that comprises a clustering agent and a cluster performance evaluation agent. An agent exchanges information about clusters with another agent and the system determines the optimal cluster number through this information. Experiments using data sets in the UCI Machine Repository are performed in order to prove the validity of the system.

Keywords: Intelligent Clustering, Multi-Agent System, PCA, SOM, VC(Variance Criterion)

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Authors: Abimbola M. Enitan, Josiah Adeyemo

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Anaerobic modeling is a useful tool to describe and simulate the condition and behaviour of anaerobic treatment units for better effluent quality and biogas generation. The present investigation deals with the anaerobic treatment of brewery wastewater with varying organic loads. The chemical oxygen demand (COD) and total suspended solids (TSS) of the influent and effluent of the bioreactor were determined at various retention times to generate data for kinetic coefficients. The bio-kinetic coefficients in the modified Stover–Kincannon kinetic and methane generation models were determined to study the performance of anaerobic digestion process. At steady-state, the determination of the kinetic coefficient (K), the endogenous decay coefficient (Kd), the maximum growth rate of microorganisms (μmax), the growth yield coefficient (Y), ultimate methane yield (Bo), maximum utilization rate constant Umax and the saturation constant (KB) in the model were calculated to be 0.046 g/g COD, 0.083 (d¯¹), 0.117 (d-¹), 0.357 g/g, 0.516 (L CH4/gCODadded), 18.51 (g/L/day) and 13.64 (g/L/day) respectively. The outcome of this study will help in simulation of anaerobic model to predict usable methane and good effluent quality during the treatment of industrial wastewater. Thus, this will protect the environment, conserve natural resources, saves time and reduce cost incur by the industries for the discharge of untreated or partially treated wastewater. It will also contribute to a sustainable long-term clean development mechanism for the optimization of the methane produced from anaerobic degradation of waste in a close system.

Keywords: Brewery wastewater, methane generation model, environment, anaerobic modeling.

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Authors: Masoud Nasri, Ali Gholami, Ali Najafi

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In recent years, most of the regions in the world are exposed to degradation and erosion caused by increasing population and over use of land resources. The understanding of the most important factors on soil erosion and sediment yield are the main keys for decision making and planning. In this study, the sediment yield and soil erosion were estimated and the priority of different soil erosion factors used in the MPSIAC method of soil erosion estimation is evaluated in AliAbad watershed in southwest of Isfahan Province, Iran. Different information layers of the parameters were created using a GIS technique. Then, a multivariate procedure was applied to estimate sediment yield and to find the most important factors of soil erosion in the model. The results showed that land use, geology, land and soil cover are the most important factors describing the soil erosion estimated by MPSIAC model.

Keywords: land degradation, Soil erosion, Sediment yield, Aliabad, GIS technique, Land use.

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Authors: K. Yathish, K. G. Binu, B. S. Shenoy, D. S. Rao, R. Pai

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Load carrying capacity of an oil lubricated two-axial groove journal bearing is simulated by taking into account the viscosity variations in lubricant due to the addition of TiO2 nanoparticles as lubricant additive. Shear viscosities of TiO2 nanoparticle dispersions in oil are measured for various nanoparticle additive concentrations. The viscosity model derived from the experimental viscosities is employed in a modified Reynolds equation to obtain the pressure profiles and load carrying capacity of two-axial groove journal bearing. Results reveal an increase in load carrying capacity of bearings operating on nanoparticle dispersions as compared to plain oil.

Keywords: Journal bearing, TiO2 nanoparticles, viscosity model, Reynolds equation, load carrying capacity.

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Authors: Narasimhaiah Gorla, Annibal Scavarda

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Nowadays, where most of the leading economies are service oriented and e-business is being widely used for their management, supply chain management has become one of the most studied and practiced fields. Quality has an important role on today-s business processes, so it is important to understand the impact of IT service quality on the performance of supply chains. This paper will start by analyzing the Supply Chain Operations Reference (SCOR) model and each of its five activities: Plan, Source, Make, Delivery, and Return. This article proposes a framework for analyzing Effect of IT Service Quality on Supply Chain Performance. Using the proposed framework, hypotheses are framed for the direct effect of IT service quality on Supply Chain Performance and its indirect effect through effective Supply Chain Management. The framework will be validated empirically based on the surveys of executives of various organizations and statistical analyses of the data collected.

Keywords: IT service quality, SCOR model, Supply Chain Management, Supply Chain Performance

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Authors: Maliheh Raji, Hossein Abolghasemi, Jaber Safdari, Ali Kargari

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Dysprosium is a rare earth element which is essential for many growing high-technology applications. Dysprosium along with neodymium plays a significant role in different applications such as metal halide lamps, permanent magnets, and nuclear reactor control rods preparation. The purification and separation of rare earth elements are challenging because of their similar chemical and physical properties. Among the various methods, membrane processes provide many advantages over the conventional separation processes such as ion exchange and solvent extraction. In this work, selective extraction and separation of dysprosium from aqueous solutions containing an equimolar mixture of dysprosium and neodymium by emulsion liquid membrane (ELM) was investigated. The organic membrane phase of the ELM was a nanofluid consisting of multiwalled carbon nanotubes (MWCNT), Span80 as surfactant, Cyanex 272 as carrier, kerosene as base fluid, and nitric acid solution as internal aqueous phase. Factors affecting separation of dysprosium such as carrier concentration, MWCNT concentration, feed phase pH and stripping phase concentration were analyzed using Taguchi method. Optimal experimental condition was obtained using analysis of variance (ANOVA) after 10 min extraction. Based on the results, using MWCNT nanofluid in ELM process leads to increase the extraction due to higher stability of membrane and mass transfer enhancement and separation factor of 6 for dysprosium over neodymium can be achieved under the optimum conditions. Additionally, demulsification process was successfully performed and the membrane phase reused effectively in the optimum condition.

Keywords: Emulsion liquid membrane, MWCNT nanofluid, separation, Taguchi Method.

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Authors: Vladimir Rastunkov, Jae-Eun Park, Abhijit Mitra, Brian Quanz, Steve Wood, Christopher Codella, Heather Higgins, Joseph Broz

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Quantum Support Vector Machines (QSVM) have become an important tool in research and applications of quantum kernel methods. In this work we propose a boosting approach for building ensembles of QSVM models and assess performance improvement across multiple datasets. This approach is derived from the best ensemble building practices that worked well in traditional machine learning and thus should push the limits of quantum model performance even further. We find that in some cases, a single QSVM model with tuned hyperparameters is sufficient to simulate the data, while in others - an ensemble of QSVMs that are forced to do exploration of the feature space via proposed method is beneficial.

Keywords: QSVM, Quantum Support Vector Machines, quantum kernel, boosting, ensemble.

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Authors: Sara Sallam, Mohamed Taqi, Naoual Belouaggadia

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Solar thermal power plants using parabolic trough collectors (PTC) are currently a powerful technology for generating electricity. Most of these solar power plants use thermal oils as heat transfer fluid. The latter is heated in the solar field and transfers the heat absorbed in an oil-water heat exchanger for the production of steam driving the turbines of the power plant. Currently, we are seeking to develop PTCs with direct steam generation (DSG). This process consists of circulating water under pressure in the receiver tube to generate steam directly into the solar loop. This makes it possible to reduce the investment and maintenance costs of the PTCs (the oil-water exchangers are removed) and to avoid the environmental risks associated with the use of thermal oils. The pressure drops in these systems are an important parameter to ensure their proper operation. The determination of these losses is complex because of the presence of the two phases, and most often we limit ourselves to describing them by models using empirical correlations. A comparison of these models with experimental data was performed. Our calculations focused on the evolution of the pressure of the liquid-vapor mixture along the receiver tube of a PTC-DSG for pressure values and inlet flow rates ranging respectively from 3 to 10 MPa, and from 0.4 to 0.6 kg/s. The comparison of the numerical results with experience allows us to demonstrate the validity of some models according to the pressures and the flow rates of entry in the PTC-DSG receiver tube. The analysis of these two parameters’ effects on the evolution of the pressure along the receiving tub, shows that the increase of the inlet pressure and the decrease of the flow rate lead to minimal pressure losses.

Keywords: Direct steam generation, parabolic trough collectors, pressure drop.

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Authors: Mohamad Mahdavi

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Most of the real queuing systems include special properties and constraints, which can not be analyzed directly by using the results of solved classical queuing models. Lack of Markov chains features, unexponential patterns and service constraints, are the mentioned conditions. This paper represents an applied general algorithm for analysis and optimizing the queuing systems. The algorithm stages are described through a real case study. It is consisted of an almost completed non-Markov system with limited number of customers and capacities as well as lots of common exception of real queuing networks. Simulation is used for optimizing this system. So introduced stages over the following article include primary modeling, determining queuing system kinds, index defining, statistical analysis and goodness of fit test, validation of model and optimizing methods of system with simulation.

Keywords: Estimation, queuing system, simulation model, probability distribution, non-Markov chain.

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Authors: Zhenzhen Xu, Chunfu Shao, Shengyou Wang, Chunjiao Dong

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To improve the satisfaction of residents' travel, this paper analyzes the characteristics and influencing factors of urban residents' travel behavior. First, a Multinominal Logit Model (MNL) model is built to analyze the characteristics of residents' travel behavior, reveal the influence of individual attributes, family attributes and travel characteristics on the choice of travel mode, and identify the significant factors. Then put forward suggestions for policy improvement. Finally, Support Vector Machine (SVM) and Multi-Layer Perceptron (MLP) models are introduced to evaluate the policy effect. This paper selects Futian Street in Futian District, Shenzhen City for investigation and research. The results show that gender, age, education, income, number of cars owned, travel purpose, departure time, journey time, travel distance and times all have a significant influence on residents' choice of travel mode. Based on the above results, two policy improvement suggestions are put forward from reducing public transportation and non-motor vehicle travel time, and the policy effect is evaluated. Before the evaluation, the prediction effect of MNL, SVM and MLP models was evaluated. After parameter optimization, it was found that the prediction accuracy of the three models was 72.80%, 71.42%, and 76.42%, respectively. The MLP model with the highest prediction accuracy was selected to evaluate the effect of policy improvement. The results showed that after the implementation of the policy, the proportion of public transportation in plan 1 and plan 2 increased by 14.04% and 9.86%, respectively, while the proportion of private cars decreased by 3.47% and 2.54%, respectively. The proportion of car trips decreased obviously, while the proportion of public transport trips increased. It can be considered that the measures have a positive effect on promoting green trips and improving the satisfaction of urban residents, and can provide a reference for relevant departments to formulate transportation policies.

Keywords: Travel characteristics analysis, transportation choice, travel sharing rate, neural network model, traffic resource allocation.

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Authors: Sophia Fry, Mahir Irtiza, Alexa Hoffman, Yousef Sardahi

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This study presents an intelligent control algorithm for a flexible robotic arm. Fuzzy control is used to control the motion of the arm to maintain the arm tip at the desired position while reducing vibration and increasing the system speed of response. The Fuzzy controller (FC) is based on adding the tip angular position to the arm deflection angle and using their sum as a feedback signal to the control algorithm. This reduces the complexity of the FC in terms of the input variables, number of membership functions, fuzzy rules, and control structure. Also, the design of the fuzzy controller is model-free and uses only our knowledge about the system. To show the efficacy of the FC, the control algorithm is implemented on the flexible joint manipulator (FJM) developed by Quanser. The results show that the proposed control method is effective in terms of response time, overshoot, and vibration amplitude.

Keywords: Fuzzy logic control, model-free control, flexible joint manipulators, nonlinear control.

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Authors: Jeongim Kang, Moon Hee Kim, Seong Baeg Kim

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This paper proposes a novel e-learning model that is  based on a dynamic formative evaluation. On evaluating the existing  format of e-learning, conditions regarding repetitive learning to  achieve mastery, causes issues for learners to lose tension and become  neglectful of learning. The dynamic formative evaluation proposed is  able to supplement limitation of the existing approaches. Since a  repetitive learning method does not provide a perfect feedback, this  paper puts an emphasis on the dynamic formative evaluation that is  able to maximize learning achievement. Through the dynamic  formative evaluation, the instructor is able to refer to the evaluation  result when making an estimation about the learner. To show the flow  chart of learning, based on the dynamic formative evaluation, the  model proves its effectiveness and validity.

 

Keywords: Online learning, dynamic formative evaluation, mastery learning, repetitive learning method, learning achievement.

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Authors: Hemalan Nambier a/l Vijiyan, Agileswari K. Ramasamy, Au Mau Teng, Syed Khaleel Ahmed

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Small signal stability causes small perturbations in the generator that can cause instability in the power network. It is generally known that small signal stability are directly related to the generator and load properties. This paper examines the effects of generator input variations on power system oscillations for a small signal stability study. Eigenvaules and eigenvectors are used to examine the stability of the power system. The dynamic power system's mathematical model is constructed and thus calculated using load flow and small signal stability toolbox on MATLAB. The power system model is based on a 3-machine 9-bus system that was modified to suit this study. In this paper, Participation Factors are a means to gauge the effects of variation in generation with other parameters on the network are also incorporated.

Keywords: Eigen-analysis, generation modeling, participationfactor, small signal stability.

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Authors: T. J. Jemi Jeya, V. Sriram

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Pile Supported Caisson breakwater is an ecofriendly breakwater very useful in coastal zone protection. The model is developed by considering the advantages of both caisson breakwater and pile supported breakwater, where the top portion is a vertical or quarter circle caisson and the bottom portion consists of a pile supported breakwater defined as Vertical Pile Supported Breakwater (VPSCB) and Quarter-circle Pile Supported Breakwater (QPSCB). The study mainly focuses on comparison of run up over VPSCB and QPSCB under oblique waves. The experiments are carried out in a shallow wave basin under different water depths (d = 0.5 m & 0.55 m) and under different oblique regular waves (0⁰, 15⁰, 30⁰). The run up over the surface is measured by placing two run up probes over the surface at 0.3 m on both sides from the centre of the model. The results show that the non-dimensional shoreward run up shows slight decrease with respect to increase in angle of wave attack.

Keywords: Caisson breakwater, pile supported breakwater, quarter circle breakwater, vertical breakwater.

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Authors: A. Bulatbayeva, A. Kusainov, P. Makhanova, A. Bashchikulov

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In the article there have been revealed the properties of designing the research teaching the military masters and in the context it has been offered the program of mastering by the masters military men the methodology of research work, in the course of practical teaching activity there has been considered the developed and approbated model of organization of the process of mastering by the masters the methodology of research work. As a whole, the research direction of master preparation leaves its sign to the content of education, forms of organization of educational process, scientific work of masters. In this connection the offered in the article properties of organization of research teaching and a model of organization of mastering by the masters military men the methodology of research work can be taken into account when designing the content of master preparation.

Keywords: Masters militaries, Methodology of research work, Military knowledge, Research teaching.

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Authors: Mehdi Salehi Barough, Saviz Sehat Kashani, A.A. Bidokhti, A.Ranjbar

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The presence of cold air with the convergent topography of the Lut valley over the valley-s sloping terrain can generate Low Level Jets (LLJ). Moreover, the valley-parallel pressure gradients and northerly LLJ are produced as a result of the large-scale processes. In the numerical study the regional MM5 model was run leading to achieve an appropriate dynamical analysis of flows in the region for summer and winter. The results of this study show the presence of summer synoptical systems cause the formation of north-south pressure gradients in the valley which could be led to the blowing of winds with the velocity more than 14 ms-1 and vulnerable dust and wind storms lasting more than 120 days. Whereas the presence of cold air masses in the region in winter, cause the average speed of LLJs decrease. In this time downslope flows are noticeable in creating the night LLJs.

Keywords: Cold advection, Low Level Jet, MM5 Model, Pressure gradient

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Authors: Krasimir I. Ivanov, Elitsa N. Kolentsova, Dimitar Y. Dimitrov, Georgi V. Avdeev, Tatyana T. Tabakova

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In recent research copper and manganese systems were found to be the most active in CO and organic compounds oxidation among the base catalysts. The mixed copper manganese oxide has been widely studied in oxidation reactions because of their higher activity at low temperatures in comparison with single oxide catalysts. The results showed that the formation of spinel CuxMn3−xO4 in the oxidized catalyst is responsible for the activity even at room temperature. That is why the most of the investigations are focused on the hopcalite catalyst (CuMn2O4) as the best coppermanganese catalyst. Now it’s known that this is true only for CO oxidation, but not for mixture of CO and VOCs. The purpose of this study is to investigate the alumina supported copper-manganese catalysts with different Cu/Mn molar ratio in terms of oxidation of CO, methanol and dimethyl ether. The catalysts were prepared by impregnation of γ-Al2O3 with copper and manganese nitrates and the catalytic activity measurements were carried out in two stage continuous flow equipment with an adiabatic reactor for simultaneous oxidation of all compounds under the conditions closest possible to the industrial. Gas mixtures on the input and output of the reactor were analyzed with a gas chromatograph, equipped with FID and TCD detectors. The texture characteristics were determined by low-temperature (- 196oС) nitrogen adsorption in a Quantachrome Instruments NOVA 1200e (USA) specific surface area & pore analyzer. Thermal, XRD and TPR analyses were performed. It was established that the active component of the mixed Cu- Mn/γ–alumina catalysts strongly depends on the Cu/Mn molar ratio. Highly active alumina supported Cu-Mn catalysts for CO, methanol and DME oxidation were synthesized. While the hopcalite is the best catalyst for CO oxidation, the best compromise for simultaneous oxidation of all components is the catalyst with Cu/Mn molar ratio 1:5.

Keywords: Supported copper-manganese catalysts, CO and VOCs oxidation.

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Authors: Margarita Zavala, Julio Rolón, Gabriel Chavira, José González, Jorge Orozco, Roberto Pichardo

Abstract:

Adolescence is a neuralgic stage in the formation of every human being, generally at this stage is when the middle school level is studied. In 2006 in Mexico incorporated “mentoring" space to assist students in their integration and participation in life. In public middle schools, is sometimes difficult to be aware of situations that affect students because of the number of them and traditional records management. Whit this they lose the opportunity to provide timely support as a preventive way. In order to provide this support, it is required to know the students by detecting the relevant information that has greater impact on their learning process. This research is looking to check if it is possible to identify student’s relevant information to detect when it is at risk, and then to propose a model to manage in a proper way such information.

Keywords: Adolescence, mentoring, middle school students, mentoring system support.

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Authors: Lingzhi Li, Jiankun Zhang, Tiantian Gu

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Hazard management that can prevent fatal accidents and property losses is a fundamental process during the buildings’ construction stage. However, due to lack of safety supervision resources and operational pressures, the conduction of hazard management is poor and ineffective in China. In order to improve the quality of construction safety management, it is critical to explore the use of information technologies to ensure that the process of hazard management is efficient and effective. After exploring the existing problems of construction hazard management in China, this paper develops the griddization management model for construction hazard management. First, following the knowledge grid infrastructure, the griddization computing infrastructure for construction hazards management is designed which includes five layers: resource entity layer, information management layer, task management layer, knowledge transformation layer and application layer. This infrastructure will be as the technical support for realizing grid management. Second, this study divides the construction hazards into grids through city level, district level and construction site level according to grid principles. Last, a griddization management process including hazard identification, assessment and control is developed. Meanwhile, all stakeholders of construction safety management, such as owners, contractors, supervision organizations and government departments, should take the corresponding responsibilities in this process. Finally, a case study based on actual construction hazard identification, assessment and control is used to validate the effectiveness and efficiency of the proposed griddization management model. The advantage of this designed model is to realize information sharing and cooperative management between various safety management departments.

Keywords: Construction hazard, grid management, griddization computing, process.

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Authors: Wei-Lun Hsu, Mon-Jyh Lin, Jyh-Ping Hsu

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The dissolution of spherical particles in liquids is analyzed dynamically. Here, we consider the case the dissolution of solute yields a solute-free solid phase in the outer portion of a particle. As dissolution proceeds, the interface between the undissolved solid phase and the solute-free solid phase moves towards the center of the particle. We assume that there exist two resistances for the diffusion of solute molecules: the resistance due to the solute-free portion of the particle and that due to a surface layer near solid-liquid interface. In general, the equation governing the dynamic behavior of dissolution needs to be solved numerically. However, analytical expressions for the temporal variation of the size of the undissoved portion of a particle and the variation of dissolution time can be obtained in some special cases. The present analysis takes the effect of variable bulk solute concentration on dissolution into account.

Keywords: dissolution of particles, surface layer, shrinking core model, dissolution time.

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Authors: F. F. Howard, I. Yakubu, C. B. Boye, J. S. Y. Kuma

Abstract:

Natural and human activities, such as mining operations, expose the natural soil to adverse environmental conditions, leading to contamination of soil, groundwater, and surface water, which has negative effects on humans, flora, and fauna. Bare or partly exposed soil is most liable to fluvial erosion. This paper enumerates various methods used to identify, map, and model fluvial erosion in a mining environment. Classical, Artificial Intelligence (AI), and GIS methods have been reviewed. One of the many classical methods used to estimate river erosion is the Revised Universal Soil Loss Equation (RUSLE) model. The RUSLE model is easy to use. Its reliance on empirical relationships that may not always be applicable to specific circumstances or locations is a flaw. Other classical models for estimating fluvial erosion are the Soil and Water Assessment Tool (SWAT) and the Universal Soil Loss Equation (USLE). These models offer a more complete understanding of the underlying physical processes and encompass a wider range of situations. Although more difficult to utilise, they depend on the availability and dependability of input data for correctness. AI can help deal with multivariate and complex difficulties and predict soil loss with higher accuracy than traditional methods, and also be used to build unique models for identifying degraded areas. AI techniques have become popular as an alternative predictor for degraded environments. However, this research proposed a hybrid of classical, AI, and GIS methods for efficient and effective modelling of fluvial erosion.

Keywords: Fluvial erosion, classical methods, Artificial Intelligence, Geographic Information System.

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Authors: N. Tahouni, M. Gholami, M. H. Panjeshahi

Abstract:

Gas flaring is one of the most GHG emitting sources in the oil and gas industries. It is also a major way for wasting such an energy that could be better utilized and even generates revenue. Minimize flaring is an effective approach for reducing GHG emissions and also conserving energy in flaring systems. Integrating waste and flared gases into the fuel gas networks (FGN) of refineries is an efficient tool. A fuel gas network collects fuel gases from various source streams and mixes them in an optimal manner, and supplies them to different fuel sinks such as furnaces, boilers, turbines, etc. In this article we use fuel gas network model proposed by Hasan et al. as a base model and modify some of its features and add constraints on emission pollution by gas flaring to reduce GHG emissions as possible. Results for a refinery case study showed that integration of flare gas stream with waste and natural gas streams to construct an optimal FGN can significantly reduce total annualized cost and flaring emissions.

Keywords: Flaring, Fuel gas network, GHG emissions.

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Authors: X. Mamaqi, J.Miguel, P. Olave

Abstract:

The aim of this paper is to provide an empirical evidence about the effects that the management of continuous training have on employability (or employment stability) in the Spanish labour market. With this purpose a binary logit model with interaction effect is been used. The dependent variable includes two situations of the active workers: continuous and discontinuous employability. To distinguish between them an Employability Index Stability (ESI) was calculated taking into account two factors: time worked and job security. Various aspects of the continuous training and personal workers data are used as independent variables. The data obtained from a survey of a sample of 918 employed have revealed a relationship between the likelihood of continuous employability and continuous training received. The empirical results support the positive and significant relationship between various aspects of the training provided by firms and employability likelihood of the workers, postulate alike from a theoretical point of view.

Keywords: training management, employability/employmentstability, binary logit model, interaction effect, Spanish marketlabour.

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