Search results for: novel simulation techniques

Authors: Mikel Alonso López

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In the first decade of the twenty-first century, advanced imaging techniques began to be applied for neuroscience research. The Functional Magnetic Resonance Imaging (fMRI) is one of the most important and most used research techniques for the investigation of emotions, because of its ease to observe the brain areas that oxygenate when performing certain tasks. In this research, we make a review about the main research carried out on the influence of the emotions in the decision-making process that is exposed by using the fMRI.

Keywords: decision making, emotions, fMRI, consumer behaviour

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Authors: Fathi Alwafie

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In this paper we present the simulation of the propagation characteristics of the picocellular propagation channel environment. The first aim has been to find a correct description of the environment for received wave. The result of the first investigations is that the environment of the indoor wave significantly changes as we change the electric parameters of material constructions. A modified 3D ray tracing image method tool has been utilized for the coverage prediction. A detailed analysis of the dependence of the indoor wave on the wide-band characteristics of the channel: Root Mean Square (RMS) delay spread characteristics and mean excess delay, is also investigated.

Keywords: propagation, ray tracing, network, mobile computing

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Authors: Lukasz Grabowski, Konrad Pietrykowski, Michal Bialy

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This paper presents the results of the research to verify the combustion in aircraft piston engine Asz62-IR. This engine was modernized and a type of ignition system was developed. Due to the high costs of experiments of a nine-cylinder 1,000 hp aircraft engine, a simulation technique should be applied. Therefore, computational fluid dynamics to simulate the combustion process is a reasonable solution. Accordingly, the tests for varied ignition advance angles were carried out and the optimal value to be tested on a real engine was specified. The CFD model was created with the AVL Fire software. The engine in the research had two spark plugs for each cylinder and ignition advance angles had to be set up separately for each spark. The results of the simulation were verified by comparing the pressure in the cylinder. The courses of the indicated pressure of the engine mounted on a test stand were compared. The real course of pressure was measured with an optical sensor, mounted in a specially drilled hole between the valves. It was the OPTRAND pressure sensor, which was designed especially to engine combustion process research. The indicated pressure was measured in cylinder no 3. The engine was running at take-off power. The engine was loaded by a propeller at a special test bench. The verification of the CFD simulation results was based on the results of the test bench studies. The course of the simulated pressure obtained is within the measurement error of the optical sensor. This error is 1% and reflects the hysteresis and nonlinearity of the sensor. The real indicated pressure measured in the cylinder and the pressure taken from the simulation were compared. It can be claimed that the verification of CFD simulations based on the pressure is a success. The next step was to research on the impact of changing the ignition advance timing of spark plugs 1 and 2 on a combustion process. Moving ignition timing between 1 and 2 spark plug results in a longer and uneven firing of a mixture. The most optimal point in terms of indicated power occurs when ignition is simultaneous for both spark plugs, but so severely separated ignitions are assured that ignition will occur at all speeds and loads of engine. It should be confirmed by a bench experiment of the engine. However, this simulation research enabled us to determine the optimal ignition advance angle to be implemented into the ignition control system. This knowledge allows us to set up the ignition point with two spark plugs to achieve as large power as possible.

Keywords: CFD model, combustion, engine, simulation

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Authors: O. Hinrichs, H. Franz, G. Reiter

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Electron guns have a key function in a series of thermal processes, like EB (electron beam) melting, evaporation or welding. These techniques need a high-intensity continuous electron beam that defocuses itself due to high space charge forces. A proper beam transport throughout the magnetic focusing system can be ensured by a space charge compensation via residual gas ions. The different pressure stages in the EB gun cause various degrees of compensation. A numerical model was installed to simulate realistic charge distributions within the beam by using CST-Particle Studio code. We will present current status of beam dynamic simulations. This contribution will focus on the creation of space charge ions and their influence on beam and gun components. Furthermore, the beam transport in the gun will be shown for different beam parameters. The electron source allows to produce beams with currents of 3 A to 15 A and energies of 40 keV to 45 keV.

Keywords: beam dynamic simulation, space charge compensation, thermionic electron source, EB melting, EB thermal processing

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Authors: Yanyan Zhang, Ziyu Diao, Zhentao Liu, Ruidong Yan

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The wear character of the main bearing is one of the critical indicators for the overhaul of an internal combustion engine, and the aim of this paper is to reveal the dynamic wear mechanism of the main bearings. A numerical simulation model combined multi-body dynamic equations of the engine, the average Reynolds equations of the bearing lubricant, asperity contact and wear model of the joint surfaces were established under typical operating conditions. The wear results were verified by experimental data, and then the influence of operating conditions, bearing clearance and cylinder pressure on the wear character of selected main bearings were analyzed. The results show that the contribution degree of different working conditions on the wear profile and depth of each bearing is obviously different, and the increase of joint clearance or cylinder pressure will accelerate the wear. The numerical model presented can be used to wear prognosis for joints and provide guidance for optimization design of sliding bearings.

Keywords: dynamic simulation, multi-body dynamics, sliding bearing, surface wear

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Authors: Bhekisipho Twala, Mantepu Masetshaba, Ramapulana Nkoana

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Multiple classifier systems combine several individual classifiers to deliver a final classification decision. However, an increasingly controversial question is whether such systems can outperform the single best classifier, and if so, what form of multiple classifiers system yields the most significant benefit. Also, multi-target tracking detection using multiple sensors is an important research field in mobile techniques and military applications. In this paper, several multiple classifiers systems are evaluated in terms of their ability to predict a system’s failure or success for multi-sensor target tracking tasks. The Bristol Eden project dataset is utilised for this task. Experimental and simulation results show that the human activity identification system can fulfill requirements of target tracking due to improved sensors classification performances with multiple classifier systems constructed using boosting achieving higher accuracy rates.

Keywords: single classifier, ensemble learning, multi-target tracking, multiple classifiers

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Authors: Korbinian Schmidtner, Rudolf Sailer, Perry Bartelt, Wolfgang Fellin, Jan-Thomas Fischer, Matthias Granig

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This study focuses on the evaluation of snow avalanche simulations, based on a survey that has been carried out among avalanche experts. In the last decades, the application of avalanche simulation tools has gained recognition within the realm of hazard management. Traditionally, avalanche runout models were used to predict extreme avalanche runout and prepare avalanche maps. This has changed rather dramatically with the application of numerical models. For safety regulations such as road safety simulation tools are now being coupled with real-time meteorological measurements to predict frequent avalanche hazard. That places new demands on model accuracy and requires the simulation of physical processes that previously could be ignored. These simulation tools are based on a deterministic description of the avalanche movement allowing to predict certain quantities (e.g. pressure, velocities, flow heights, runout lengths etc.) of the avalanche flow. Because of the highly variable regimes of the flowing snow, no uniform rheological law describing the motion of an avalanche is known. Therefore, analogies to fluid dynamical laws of other materials are stated. To transfer these constitutional laws to snow flows, certain assumptions and adjustments have to be imposed. Besides these limitations, there exist high uncertainties regarding the initial and boundary conditions. Further challenges arise when implementing the underlying flow model equations into an algorithm executable by a computer. This implementation is constrained by the choice of adequate numerical methods and their computational feasibility. Hence, the model development is compelled to introduce further simplifications and the related uncertainties. In the light of these issues many questions arise on avalanche simulations, on their assets and drawbacks, on potentials for improvements as well as their application in practice. To address these questions a survey among experts in the field of avalanche science (e.g. researchers, practitioners, engineers) from various countries has been conducted. In the questionnaire, special attention is drawn on the expert’s opinion regarding the influence of certain variables on the simulation result, their uncertainty and the reliability of the results. Furthermore, it was tested to which degree a simulation result influences the decision making for a hazard assessment. A discrepancy could be found between a large uncertainty of the simulation input parameters as compared to a relatively high reliability of the results. This contradiction can be explained taking into account how the experts employ the simulations. The credibility of the simulations is the result of a rather thoroughly simulation study, where different assumptions are tested, comparing the results of different flow models along with the use of supplemental data such as chronicles, field observation, silent witnesses i.a. which are regarded as essential for the hazard assessment and for sanctioning simulation results. As the importance of avalanche simulations grows within the hazard management along with their further development studies focusing on the modeling fashion could contribute to a better understanding how knowledge of the avalanche process can be gained by running simulations.

Keywords: expert interview, hazard management, modeling, simulation, snow avalanche

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Authors: Melissa Langevin, Natalie Ward, Colleen Fitzgibbons, Christa Ramsey, Melanie Hogue, Anna Theresa Lobos

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Description: Root Cause Analysis (RCA) is used by health care teams to examine adverse events (AEs) to identify causes which then leads to recommendations for prevention Despite widespread use, RCA has limitations. Best practices have not been established for implementing recommendations or tracking the impact of interventions after AEs. During phase 1 of this study, we used simulation to analyze two fictionalized AEs that occurred in hospitalized paediatric patients to identify and understand how the errors occurred and generated recommendations to mitigate and prevent recurrences. Scenario A involved an error of commission (inpatient drug error), and Scenario B involved detecting an error that already occurred (critical care drug infusion error). Recommendations generated were: improved drug labeling, specialized drug kids, alert signs and clinical checklists. Aim: Use simulation to optimize interventions recommended post critical event analysis prior to implementation in the clinical environment. Methods: Suggested interventions from Phase 1 were designed and tested through scenario simulation in the clinical environment (medicine ward or pediatric intensive care unit). Each scenario was simulated 8 times. Recommendations were tested using different, voluntary teams and each scenario was debriefed to understand why the error was repeated despite interventions and how interventions could be improved. Interventions were modified with subsequent simulations until recommendations were felt to have an optimal effect and data saturation was achieved. Along with concrete suggestions for design and process change, qualitative data pertaining to employee communication and hospital standard work was collected and analyzed. Results: Each scenario had a total of three interventions to test. In, scenario 1, the error was reproduced in the initial two iterations and mitigated following key intervention changes. In scenario 2, the error was identified immediately in all cases where the intervention checklist was utilized properly. Independently of intervention changes and improvements, the simulation was beneficial to identify which of these should be prioritized for implementation and highlighted that even the potential solutions most frequently suggested by participants did not always translate into error prevention in the clinical environment. Conclusion: We conclude that interventions that help to change process (epinephrine kit or mandatory checklist) were more successful at preventing errors than passive interventions (signage, change in memory aids). Given that even the most successful interventions needed modifications and subsequent re-testing, simulation is key to optimizing suggested changes. Simulation is a safe, practice changing modality for institutions to use prior to implementing recommendations from RCA following AE reviews.

Keywords: adverse events, patient safety, pediatrics, root cause analysis, simulation

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Authors: Edward Schwalb, Matthias Dehmer, Michael Schlenkrich, Farzaneh Taslimi, Ketron Mitchell-Wynne, Horen Kuecuekyan

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We present a generalized feature extraction approach for supporting Machine Learning (ML) algorithms which perform tasks similar to Finite-Element Analysis (FEA). We report results for estimating the Head Injury Categorization (HIC) of vehicle engine compartments across various impact scenarios. Our experiments demonstrate that models learned using features derived with a simple discretization approach provide a reasonable approximation of a full simulation. We observe that Decision Trees could be as effective as Neural Networks for the HIC task. The simplicity and performance of the learned Decision Trees could offer a trade-off of a multiple order of magnitude increase in speed and cost improvement over full simulation for a reasonable approximation. When used as a complement to full simulation, the approach enables rapid approximate feedback to engineering teams before submission for full analysis. The approach produces mesh independent features and is further agnostic of the assembly structure.

Keywords: mechanical design validation, FEA, supervised decision tree, convolutional neural network.

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Authors: P. Javid, A. Aeenmehr, J. Taghavifar

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In this paper, supply air pressure of HVAC system has been modeled with second-order transfer function plus dead-time. In HVAC system, the desired input has step changes, and the output of proposed control system should be able to follow the input reference, so the idea of using model based predictive control is proceeded and designed in this paper. The closed loop control system is implemented in MATLAB software and the simulation results are provided. The simulation results show that the model based predictive control is able to control the plant properly.

Keywords: air conditioning system, GPC, dead time, air supply control

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Authors: T. J. Jamaleddine

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Purge columns or degasser vessels are widely used in the polyolefin process for removing trapped hydrocarbons and in-excess catalyst residues from the polymer particles. A uniform distribution of purged gases coupled with a plug-flow characteristic inside the column system is desirable to obtain optimum desorption characteristics of trapped hydrocarbon and catalyst residues. Computational Fluid Dynamics (CFD) approach is a promising tool for design optimization of these vessels. The success of this approach is profoundly dependent on the solution strategy and the choice of geometrical layout at the vessel outlet. Filling the column with solids and initially solving for the solids flow minimized numerical diffusion substantially. Adopting a cylindrical configuration at the vessel outlet resulted in less numerical instability and resembled the hydrodynamics flow of solids in the hopper segment reasonably well.

Keywords: CFD, degasser vessel, gas-solids flow, gas purging, purge column, species transport

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Authors: Ahlam Elkilani, Bayan Elsheikh Ali, Rasha Abu Romman, Amjed Al-mousa, Belal Sababha

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The amount of energy the world uses doubles every 20 years. Green homes play an important role in reducing the residential energy demand. This paper presents a platform that is intended to learn the behavior of home residents and build a profile about their habits and actions. The proposed resident aware home controller intervenes in the operation of home appliances in order to save energy without compromising the convenience of the residents. The presented platform can be used to simulate the actions and movements happening inside a home. The paper includes several optimization techniques that are meant to save energy in the home. In addition, several test scenarios are presented that show how the controller works. Moreover, this paper shows the computed actual savings when each of the presented techniques is implemented in a typical home. The test scenarios have validated that the techniques developed are capable of effectively saving energy at homes.

Keywords: green home, resident aware, resident profile, activity learning, machine learning

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Authors: Karoliina Nisula, Samuli Pekkola

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Business education has been criticized for being too theoretical and distant from business life. Different types of experiential learning environments ranging from manual role-play to computer simulations and enterprise resource planning (ERP) systems have been used to introduce the realistic and practical experience into business learning. Each of these learning environments approaches business learning from a different perspective. The implementations tend to be individual exercises supplementing the traditional courses. We suggest combining them into a business skills laboratory resembling an actual workplace. In this paper, we present a concrete implementation of an ERP-supported business learning environment that is used throughout the first year undergraduate business curriculum. We validate the implementation by evaluating the learning outcomes through the different domains of Bloom’s taxonomy. We use the role-play oriented practice enterprise model as a comparison group. Our findings indicate that using the ERP simulation improves the poor and average students’ lower-level cognitive learning. On the affective domain, the ERP-simulation appears to enhance motivation to learn as well as perceived acquisition of practical hands-on skills.

Keywords: business simulations, experiential learning, ERP systems, learning environments

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Authors: Thamir K. Ibrahim, M. M. Rahman, Marwah Noori Mohammed

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This study deals with modeling and performance enhancements of a gas-turbine combined cycle power plant. A clean and safe energy is the greatest challenges to meet the requirements of the green environment. These requirements have given way the long-time governing authority of steam turbine (ST) in the world power generation, and the gas turbine (GT) will replace it. Therefore, it is necessary to predict the characteristics of the GT system and optimize its operating strategy by developing a simulation system. The integrated model and simulation code for exploiting the performance of gas turbine power plant are developed utilizing MATLAB code. The performance code for heavy-duty GT and CCGT power plants are validated with the real power plant of Baiji GT and MARAFIQ CCGT plants the results have been satisfactory. A new technology of correlation was considered for all types of simulation data; whose coefficient of determination (R2) was calculated as 0.9825. Some of the latest launched correlations were checked on the Baiji GT plant and apply error analysis. The GT performance was judged by particular parameters opted from the simulation model and also utilized Adaptive Neuro-Fuzzy System (ANFIS) an advanced new optimization technology. The best thermal efficiency and power output attained were about 56% and 345MW respectively. Thus, the operation conditions and ambient temperature are strongly influenced on the overall performance of the GT. The optimum efficiency and power are found at higher turbine inlet temperatures. It can be comprehended that the developed models are powerful tools for estimating the overall performance of the GT plants.

Keywords: gas turbine, optimization, ANFIS, performance, operating conditions

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Authors: Jiri Barta

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At the present time, awareness, education, computer simulation and information systems protection are very serious and relevant topics. The article deals with perspectives and possibilities of implementation of emergence or natural hazard threats into the system which is developed for communication among members of crisis management staffs. The Czech Hydro-Meteorological Institute with its System of Integrated Warning Service resents the largest usable base of information. National information systems are connected to foreign systems, especially to flooding emergency systems of neighboring countries, systems of European Union and international organizations where the Czech Republic is a member. Use of outputs of particular information systems and computer simulations on a single communication interface of information system for communication among members of crisis management staff and setting the site interoperability in the net will lead to time savings in decision-making processes in solving extraordinary events and crisis situations. Faster managing of an extraordinary event or a crisis situation will bring positive effects and minimize the impact of negative effects on the environment.

Keywords: computer simulation, communication, continuity, critical infrastructure, information systems, safety

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Authors: C. Manjula, Lilly Florence

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Software technology is developing rapidly which leads to the growth of various industries. Now-a-days, software-based applications have been adopted widely for business purposes. For any software industry, development of reliable software is becoming a challenging task because a faulty software module may be harmful for the growth of industry and business. Hence there is a need to develop techniques which can be used for early prediction of software defects. Due to complexities in manual prediction, automated software defect prediction techniques have been introduced. These techniques are based on the pattern learning from the previous software versions and finding the defects in the current version. These techniques have attracted researchers due to their significant impact on industrial growth by identifying the bugs in software. Based on this, several researches have been carried out but achieving desirable defect prediction performance is still a challenging task. To address this issue, here we present a machine learning based hybrid technique for software defect prediction. First of all, Genetic Algorithm (GA) is presented where an improved fitness function is used for better optimization of features in data sets. Later, these features are processed through Decision Tree (DT) classification model. Finally, an experimental study is presented where results from the proposed GA-DT based hybrid approach is compared with those from the DT classification technique. The results show that the proposed hybrid approach achieves better classification accuracy.

Keywords: decision tree, genetic algorithm, machine learning, software defect prediction

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Authors: Panasbodee Thachaopas, Duangdorm Gamnerdsap, Waraporn Inthip, Arissara Pungpa

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LDD’s IM Farm or Land Development Department’s Integrated Management Farm is the agricultural simulation application developed by Land Development Department relies on actual data in simulation game to grow 12 cash crops which are rice, corn, cassava, sugarcane, soybean, rubber tree, oil palm, pineapple, longan, rambutan, durian, and mangosteen. Launching in simulation game, players could select preferable areas for cropping from base map or Orthophoto map scale 1:4,000. Farm management is simulated from field preparation to harvesting. The system uses soil group, and present land use database to facilitate player to know whether what kind of crop is suitable to grow in each soil groups and integrate LDD’s data with other agencies which are soil types, soil properties, soil problems, climate, cultivation cost, fertilizer use, fertilizer price, socio-economic data, plant diseases, weed, pest, interest rate for taking on loan from Bank for Agriculture and Agricultural Cooperatives (BAAC), labor cost, market prices. These mentioned data affect the cost and yield differently to each crop. After completing, the player will know the yield, income and expense, profit/loss. The player could change to other crops that are more suitable to soil groups for optimal yields and profits.

Keywords: agricultural simulation, smart farmer, web application, factors of agricultural production

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Authors: Robert Pellerin, Michel Gamache, Remi Trudeau, Nathalie Perrier

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The context of large engineering projects is particularly favorable to the appearance of engineering changes and contractual modifications. These elements are potential causes for claims. In this paper, we investigate one of the critical components of the claim management process: the calculation of the impacts of changes in terms of losses of productivity due to the need to accelerate some project activities. When project changes are initiated, delays can arise. Indeed, project activities are often executed in fast-tracking in an attempt to respect the completion date. But the acceleration of project execution and the resulting rework can entail important costs as well as induce productivity losses. In the past, numerous methods have been proposed to quantify the duration of delays, the gains achieved by project acceleration, and the loss of productivity. The calculation related to those changes can be divided into two categories: direct cost and indirect cost. The direct cost is easily quantifiable as opposed to indirect costs which are rarely taken into account during the calculation of the cost of an engineering change or contract modification despite several research projects have been made on this subject. However, proposed models have not been accepted by companies yet, nor they have been accepted in court. Those models require extensive data and are often seen as too specific to be used for all projects. These techniques are also ignoring the resource constraints and the interdependencies between the causes of delays and the delays themselves. To resolve this issue, this research proposes a simulation model that mimics how major engineering changes or contract modifications are handled in large construction projects. The model replicates the use of overtime in a reactive scheduling mode in order to simulate the loss of productivity present when a project change occurs. Multiple tests were conducted to compare the results of the proposed simulation model with statistical analysis conducted by other researchers. Different scenarios were also conducted in order to determine the impact the number of activities, the time of occurrence of the change, the availability of resources, and the type of project changes on productivity loss. Our results demonstrate that the number of activities in the project is a critical variable influencing the productivity of a project. When changes occur, the presence of a large number of activities leads to a much lower productivity loss than a small number of activities. The speed of reducing productivity for 30-job projects is about 25 percent faster than the reduction speed for 120-job projects. The moment of occurrence of a change also shows a significant impact on productivity. Indeed, the sooner the change occurs, the lower the productivity of the labor force. The availability of resources also impacts the productivity of a project when a change is implemented. There is a higher loss of productivity when the amount of resources is restricted.

Keywords: engineering changes, indirect costs overtime, productivity, scheduling, simulation

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Authors: Emin Gundogar, Burak Erkayman, Aysegul Yilmaz, Nusret Sazak

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When considering current competition conditions on the world, satisfying customer demands on time has become an important factor that enables the firms take a step further. Therefore, production process must be completed faster to take the competitive advantage. A balanced assembly line is the one of most important factors affecting the speed of production lines. The aim of this study is to build an assembly line to balance the assembly line and to simulate it for different scenarios through a refrigerator factory. The times of the operations is analyzed and grouped by the priorities. First, a Kilbridge & Wester heuristics is put to the model then a simulation approach is implemented to the model and the differences are observed.

Keywords: assembly line design, assembly line balancing, simulation modelling, refrigeration industry

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Authors: Syeda Mainaaz Unnisa, Deepa Suresh

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Due to the increase in usage of public domain channels, such as the internet, and communication technology, there is a concern about the protection of intellectual property and security threats. This interest has led to growth in researching and implementing techniques for information hiding. Steganography is the art and science of hiding information in a private manner such that its existence cannot be recognized. Communication using steganographic techniques makes not only the secret message but also the presence of hidden communication, invisible. Steganalysis is the art of detecting the presence of this hidden communication. Parallel to steganography, steganalysis is also gaining prominence, since the detection of hidden messages can prevent catastrophic security incidents from occurring. Steganalysis can also be incredibly helpful in identifying and revealing holes with the current steganographic techniques, which makes them vulnerable to attacks. Through the formulation of new effective steganalysis methods, further research to improve the resistance of tested steganography techniques can be developed. Feature-based steganalysis method for JPEG images calculates the features of an image using the L1 norm of the difference between a stego image and the calibrated version of the image. This calibration can help retrieve some of the parameters of the cover image, revealing the variations between the cover and stego image and enabling a more accurate detection. Applying this method to various steganographic schemes, experimental results were compared and evaluated to derive conclusions and principles for more protected JPEG steganography.

Keywords: cover image, feature-based steganalysis, information hiding, steganalysis, steganography

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Authors: Damou Mehdi, Nouri Keltouma, Fahem Mohammed

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In this paper, the concept of substrate integrated waveguide (SIW) technology is used to design filter for 30 GHz communication systems. SIW is created in the substrate of RT/Duroid 5880 having relative permittivity ε_r= 2.2 and loss tangent tanφ = 0.0009. Four Via are placed on the century filter the structures of SIW are modeled using and have been optimized in software HFSS (High Frequency Structure Simulator), à transition is designed for a Ka-band transceiver module with a 28.5GHz center frequency, . and then the results are verified using another simulation CST Microwave Studio (Computer Simulation Technology). The return loss are less than -18 dB, and -13 dB respectively. The insertion loss is divided equally -1.2 dB and -1.4 respectively.

Keywords: transition, microstrip, substrat integrated wave guide, filter, via

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Authors: M. J. Davidson, N. Selvaraj, L. Venugopal

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The elevated temperature forming studies on the expansion of thin walled tubes have been studied in the present work. The influence of process parameters namely the die angle, the die ratio and the operating temperatures on the expansion of tube ends at elevated temperatures is carried out. The range of operating parameters have been identified by perfoming extensive simulation studies. The hot forming parameters have been evaluated for AA2014 alloy for performing the simulation studies. Experimental matrix has been developed from the feasible range got from the simulation results. The design of experiments is used for the optimization of process parameters. Response Surface Method’s (RSM) and Box-Behenken design (BBD) is used for developing the mathematical model for expansion. Analysis of variance (ANOVA) is used to analyze the influence of process parameters on the expansion of tube ends. The effect of various process combinations of expansion are analyzed through graphical representations. The developed model is found to be appropriate as the coefficient of determination value is very high and is equal to 0.9726. The predicted values are found to coincide well with the experimental results, within acceptable error limits.

Keywords: expansion, optimization, Response Surface Method (RSM), ANOVA, bbd, residuals, regression, tube

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Authors: Zaynab El Khattabi, Youness Tabii, Abdelhamid Benkaddour

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Nowadays, huge amount of multimedia repositories make the browsing, retrieval and delivery of video contents very slow and even difficult tasks. Video summarization has been proposed to improve faster browsing of large video collections and more efficient content indexing and access. In this paper, we focus on approaches to video summarization. The video summaries can be generated in many different forms. However, two fundamentals ways to generate summaries are static and dynamic. We present different techniques for each mode in the literature and describe some features used for generating video summaries. We conclude with perspective for further research.

Keywords: video summarization, static summarization, video skimming, semantic features

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Authors: Amandeep Kaur

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Digital Image processing is a fundamental tool to perform various operations on the digital images for pattern recognition, noise removal and feature extraction. In this paper noise removal technique has been described for various types of noises. This paper comprises discussion about various noises available in the image due to different environmental, accidental factors. In this paper, various de-noising approaches have been discussed that utilize different wavelets and filters for de-noising. By analyzing various papers on image de-noising we extract that wavelet based de-noise approaches are much effective as compared to others.

Keywords: de-noising techniques, edges, image, image processing

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Authors: Emilia K. H. Danielsson-Waters, Malaz Elsaddig, Kevin Jones

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Unfortunately, it is well known that neonatal deaths are a common and potentially preventable occurrence across the world. Neonatal resuscitation is a simple and inexpensive intervention that can effectively reduce this rate, and can be taught and implemented globally. This project is a follow-on from one in 2012, which found that neonatal resuscitation simulation was valuable for education, but would be better improved by being delivered by local staff. Methods: This study involved auditing the neonatal admission and death records within a rural Ugandan hospital, alongside implementing a Train-The-Trainer teaching scheme to teach Neonatal Resuscitation. One local doctor was trained for simulating neonatal resuscitation, whom subsequently taught an additional 14 staff members in one-afternoon session. Participants were asked to complete questionnaires to assess their knowledge and confidence pre- and post-simulation, and a survey to identify barriers and drivers to simulation. Results: The results found that the neonatal mortality rate in this hospital was 25% between July 2016- July 2017, with birth asphyxia, prematurity and sepsis being the most common causes. Barriers to simulation that were identified predominantly included a lack of time, facilities and opportunity, yet all members stated simulation was beneficial for improving skills and confidence. The simulation session received incredibly positive qualitative feedback, and also a 0.58-point increase in knowledge (p=0.197) and 0.73-point increase in confidence (0.079). Conclusion: This research shows that it is possible to create a teaching scheme in a rural hospital, however, many barriers are in place for its sustainability, and a larger sample size with a more sensitive scale is required to achieve statistical significance. This is undeniably important, because teaching neonatal resuscitation can have a direct impact on neonatal mortality. Subsequently, recommendations include that efforts should be put in place to create a sustainable training scheme, for example, by employing a resuscitation officer. Moreover, neonatal resuscitation teaching should be conducted more frequently in hospitals, and conducted in a wider geographical context, including within the community, in order to achieve its full effect.

Keywords: neonatal resuscitation, sustainable medical education, train-the-trainer, Uganda

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Authors: Rudy Djamaluddin, Arbain Tata, Rita Irmawaty

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The study conducted a simulation of the effect of sea water to the bonding capacity of GFRP sheet on the concrete beams using a simulation tank. As it well known that, fiber reinforced polymer (FRP) has been applied to many purposes for civil engineering structures not only for new structures but also for strengthening of the deteriorated structures. The FRP has advantages such as its corrosion resistance, as well as high tensile strength, to weight ratio. Glass composed FRP (GFRP) sheet is most commonly used due to its relatively lower cost compared to the other FRP materials. GFRP sheet is applied externally by bonding it on the concrete surface. Many studies have been done to investigate the bonding of GFRP sheet. However, it is still very rarely studies on the effect of sea water to the bonding capacity of GFRP sheet on the strengthened beams due to flexural loadings. This is important to be clarified for the wider application of GFRP sheet especially on the flexural structure that directly contact to the sea environment. To achieve the objective of the study, a series of concrete beams strengthened with GFRP sheet on extreme tension surface were prepared. The beams then were stored on the sea water tank for six months. Results indicated the bonding capacity decreased after six months exposed to the sea water.

Keywords: GFRP sheet, sea water, concrete beams, bonding

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Authors: Peña A. Roland R., Lozano P. Jean P.

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The waterflooding process is an enhanced oil recovery (EOR) method that appears tremendously successful. This paper shows the importance of the role of the numerical modelling of waterflooding and how to provide a better description of the fluid flow during this process. The mathematical model is based on the mass conservation equations for the oil and water phases. Rock compressibility and capillary pressure equations are coupled to the mathematical model. For discretizing and linearizing the partial differential equations, we used the Finite Volume technique and the Newton-Raphson method, respectively. The results of three scenarios for waterflooding in porous media are shown. The first scenario was estimating the water saturation in the media without rock compressibility and without capillary pressure. The second scenario was estimating the front of the water considering the rock compressibility and capillary pressure. The third case is to compare different fronts of water saturation for three fluids viscosity ratios without and with rock compressibility and without and with capillary pressure. Results of the simulation indicate that the rock compressibility and the capillary pressure produce changes in the pressure profile and saturation profile during the displacement of the oil for the water.

Keywords: capillary pressure, numerical simulation, rock compressibility, two-phase flow

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Authors: Yosra Mefteh Rekik, Younes Boujelbene

Abstract:

We introduce in this paper a new conceptual model representing the stock market dynamics. This model is essentially based on cognitive behavior of the intelligence investors. In order to validate our model, we build an artificial stock market simulation based on agent-oriented methodologies. The proposed simulator is composed of market supervisor agent essentially responsible for executing transactions via an order book and various kinds of investor agents depending to their profile. The purpose of this simulation is to understand the influence of psychological character of an investor and its neighborhood on its decision-making and their impact on the market in terms of price fluctuations. Therefore, the difficulty of the prediction is due to several features: the complexity, the non-linearity and the dynamism of the financial market system, as well as the investor psychology. The Artificial Neural Networks learning mechanism take on the role of traders, who from their futures return expectations and place orders based on their expectations. The results of intensive analysis indicate that the existence of agents having heterogeneous beliefs and preferences has provided a better understanding of price dynamics in the financial market.

Keywords: artificial intelligence methods, artificial stock market, behavioral modeling, multi-agent based simulation

Procedia PDF Downloads 428

Authors: Khaled Ayfi

Abstract:

In industrial oxygen systems at high temperature and high pressure, contamination by solid particles is one of the principal causes of ignition hazards. Indeed, gas can sweep away particles, generated by corrosion inside the pipes or during maintenance operations (welding residues, careless disassembly, etc.) and produce accumulations at places where the gas velocity decrease. Moreover, in such an environment rich in oxygen (oxidant), particles are highly reactive and can ignite system walls more actively and at higher temperatures. Oxidation based thermal effects are responsible for mechanical properties lost, leading to the destruction of the pressure equipment wall. To deal with this problem, a numerical analysis is done regarding a sample representative of a wall subjected to pressure and temperature. The validation and analysis are done comparing the numerical simulations results to experimental measurements. More precisely, in this work, we propose a numerical model that describes the thermomechanical behavior of thin metal disks under pressure and subjected to laser heating. This model takes into account the geometric and material nonlinearity and has been validated by the comparison of simulation results with experimental measurements.

Keywords: ignition, oxygen, numerical simulation, thermomechanical behavior

Procedia PDF Downloads 93

Authors: Thien X. Dinh, Peter Witt

Abstract:

A one-dimensional model for the simulation of condensation and solidification of a metallurgical vapor in the mixture of gas during supersonic expansion is presented. In the model, condensation is based on critical nucleation and drop-growth theory. When the temperature falls below the supercooling point, all the formed liquid droplets in the condensation phase are assumed to solidify at an infinite rate. The model was verified with a Computational Fluid Dynamics simulation of magnesium vapor condensation and solidification. The obtained results are in reasonable agreement with CFD data. Therefore, the model is a promising, efficient tool for use in the design process for supersonic nozzles applied in mineral processes since it is faster than the CFD counterpart by an order of magnitude.

Keywords: condensation, metallurgical flow, solidification, supersonic expansion

Procedia PDF Downloads 48