Search results for: estimation of properties of the model

Authors: Akram Khaleghei, Ghosheh Balagh, Viliam Makis

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In this paper, we investigate the residual life prediction problem for a partially observable system subject to two failure modes, namely a catastrophic failure and a failure due to the system degradation. The system is subject to condition monitoring and the degradation process is described by a hidden Markov model with unknown parameters. The parameter estimation procedure based on an EM algorithm is developed and the formulas for the conditional reliability function and the mean residual life are derived, illustrated by a numerical example.

Keywords: partially observable system, hidden Markov model, competing risks, residual life prediction

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Authors: Manal Bouasria, Mohammed-Hichem Benzaama, Valérie Pralong, Yassine El Mendili

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Reducing the quantity of cement in cementitious composites can help to reduce the environmental effect of construction materials. By-products such as ferronickel slags (FNS), fly ash (FA), and Crepidula fornicata (CR) are promising options for cement replacement. In this work, we investigated the relevance of substituting cement with FNS-CR and FA-CR on the mechanical properties of mortar and on the thermal properties of concrete. Foraging intervals ranging from 2 to 28 days, the mechanical properties are obtained by 3-point bending and compression tests. The chosen mix is used to construct a prototype in order to study the material’s hygrothermal performance. The data collected by the sensors placed on the prototype was utilized to build an artificial neural network.

Keywords: artificial neural network, cement, circular economy, concrete, by products

Procedia PDF Downloads 114

Authors: Mesbaholdin Salami, Farzad Movahedi Sobhani, Mohammad Sadegh Ghazizadeh

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Evaluation of organizational performance is among the most important measures that help organizations and entities continuously improve their efficiency. Organizations can use the existing data and results from the comparison of units under investigation to obtain an estimation of their performance. The Malmquist Productivity Index (MPI) is an important index in the evaluation of overall productivity, which considers technological developments and technical efficiency at the same time. This article proposed a model based on the multistage MPI, considering limited data (Grey’s theory). This model can evaluate the performance of units using limited and uncertain data in a multistage process. It was applied by the electricity market manager to Iran’s electric power supply chain (EPSC), which contains uncertain data, to evaluate the performance of its actors. Results from solving the model showed an improvement in the accuracy of future performance of the units under investigation, using the Grey’s system theory. This model can be used in all case studies, in which MPI is used and there are limited or uncertain data.

Keywords: Malmquist Index, Grey's Theory, CCR Model, network data envelopment analysis, Iran electricity power chain

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Authors: Amira Mabrouk, Chokri Abdennadher

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The reduction of road congestion which is inherent to the use of vehicles is an obvious priority to public authority. Therefore, assessing the willingness to pay of an individual in order to save trip-time is akin to estimating the change in price which was the result of setting up a new transport policy to increase the networks fluidity and improving the level of social welfare. This study holds an innovative perspective. In fact, it initiates an economic calculation that has the objective of giving an estimation of the monetized time value during the trips made in Sfax. This research is founded on a double-objective approach. The aim of this study is to i) give an estimation of the monetized value of time; an hour dedicated to trips, ii) determine whether or not the consumer considers the environmental variables to be significant, iii) analyze the impact of applying a public management of the congestion via imposing taxation of city tolls on urban dwellers. This article is built upon a rich field survey led in the city of Sfax. With the use of the contingent valuation method, we analyze the “declared time preferences” of 450 drivers during rush hours. Based on the fond consideration of attributed bias of the applied method, we bring to light the delicacy of this approach with regards to the revelation mode and the interrogative techniques by following the NOAA panel recommendations bearing the exception of the valorization point and other similar studies about the estimation of transportation externality.

Keywords: willingness to pay, contingent valuation, time value, city toll

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Authors: Khaled M. EL-Naggar

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Synchronizing and damping torque coefficients of a synchronous machine can give a quite clear picture for machine behavior during transients. These coefficients are used as a power system transient stability measurement. In this paper, a crow search optimization algorithm is presented and implemented to study the power system stability during transients. The algorithm makes use of the machine responses to perform the stability study in time domain. The problem is formulated as a dynamic estimation problem. An objective function that minimizes the error square in the estimated coefficients is designed. The method is tested using practical system with different study cases. Results are reported and a thorough discussion is presented. The study illustrates that the proposed method can estimate the stability coefficients for the critical stable cases where other methods may fail. The tests proved that the proposed tool is an accurate and reliable tool for estimating the machine coefficients for assessment of power system stability.

Keywords: optimization, estimation, synchronous, machine, crow search

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Authors: Pramod K. Prabhakar, Prem P. Srivastav

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Rohu (Labeo rohita) is an Indian major carp and highly relished freshwater food for its unique flavor, texture, and culinary properties. It is highly perishable and, spoilage occurs as a result of series of complicated biochemical changes brought about by enzymes which are the function of time and storage temperature also. The influence of storage temperature (5, 0, and -5 °C) on colour and texture of fish were studied during 14 days storage period in order to analyze kinetics of colour and textural changes. The rate of total colour change was most noticeable at the highest storage temperature (5°C), and these changes were well described by the first order reaction. Texture is an important variable of quality of the fish and is increasing concern to aquaculture industries. Textural parameters such as hardness, toughness and stiffness were evaluated on a texture analyzer for the different day of stored fish. The significant reduction (P ≤ 0.05) in hardness was observed after 2nd, 4th and 8th day for the fish stored at 5, 0, and -5 °C respectively. The textural changes of fish during storage followed a first order kinetic model and fitted well with this model (R2 > 0.95). However, the textural data with respect to time was also fitted to modified Maxwell model and found to be good fit with R2 value ranges from 0.96 to 0.98. Temperature dependence of colour and texture change was adequately modelled with the Arrhenius type equation. This fitted model may be used for the determination of shelf life of Rohu Rohu (Labeo rohita) Fish.

Keywords: first order kinetics, biochemical changes, Maxwell model, colour, texture, Arrhenius type equation

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Authors: Indra Bahadur Bhandari, Narayan Panthi, Ishwar Koirala, Devendra Adhikari

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We have used a theoretical model based on the assumption of compound formation in binary alloys to study the thermodynamic, microscopic, and surface properties of Bi-Pb and In-Pb liquid alloys. A review of the phase diagrams for these alloys shows that one of the stable complexes for Bi-Pb liquid alloy is BiPb3; also, that InPb is a stable phase in liquid In-Pb alloys. Using the same interaction parameters that are fitted for the free energy of mixing, we have been able to compute the bulk and thermodynamic properties of the alloys. From our observations, we are able to show that the Bi-Pb liquid alloy exhibits compound formation over the whole concentration range and the In-Pb alloys undergo phase separation. With regards to surface properties, Pb segregates more to the surface in In-Pb alloys than in Bi-Pb alloys. The viscosity isotherms have a positive deviation from ideality for both Bi-Pb and In-Pb alloys.

Keywords: asymmetry, Bi-Pb, deviation, In-Pb, interaction parameters

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Authors: Mustafa Gok, Sair Kahraman, Mustafa Fener

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In rock engineering applications, determining uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), and basic index properties such as density, porosity, and water absorption is crucial for the design of both underground and surface structures. However, obtaining reliable samples for direct testing, especially from rocks that weather quickly and have low strength, is often challenging. In such cases, indirect methods provide a practical alternative to estimate the physical and mechanical properties of these rocks. In this study, tuff samples collected from the Cappadocia region (Nevşehir) in Turkey were subjected to indirect testing methods. Over 100 tests were conducted, using needle penetrometer index (NPI), point load strength index (PLI), and disc shear index (BPI) to estimate the uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), density, and water absorption index of the tuffs. The relationships between the results of these indirect tests and the target physical properties were evaluated using simple and multiple regression analyses. The findings of this research reveal strong correlations between the indirect methods and the mechanical properties of the tuffs. Both uniaxial compressive strength and Brazilian tensile strength could be accurately predicted using NPI, PLI, and BPI values. The regression models developed in this study allow for rapid, cost-effective assessments of tuff strength in cases where direct testing is impractical. These results are particularly valuable for geological engineering applications, where time and resource constraints exist. This study highlights the significance of using indirect methods as reliable predictors of the mechanical behavior of weak rocks like tuffs. Further research is recommended to explore the application of these methods to other rock types with similar characteristics. Further research is required to compare the results with those of established direct test methods.

Keywords: brazilian tensile strength, disc shear strength, indirect methods, tuffs, uniaxial compressive strength

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Authors: Atbin Mahabbati, Jason Beringer, Matthias Leopold

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To address the global challenges of climate and environmental changes, there is a need for quantifying and reducing uncertainties in environmental data, including observations of carbon, water, and energy. Global eddy covariance flux tower networks (FLUXNET), and their regional counterparts (i.e., OzFlux, AmeriFlux, China Flux, etc.) were established in the late 1990s and early 2000s to address the demand. Despite the capability of eddy covariance in validating process modelling analyses, field surveys and remote sensing assessments, there are some serious concerns regarding the challenges associated with the technique, e.g. data gaps and uncertainties. To address these concerns, this research has developed an ensemble model to fill the data gaps of CO₂ flux to avoid the limitations of using a single algorithm, and therefore, provide less error and decline the uncertainties associated with the gap-filling process. In this study, the data of five towers in the OzFlux Network (Alice Springs Mulga, Calperum, Gingin, Howard Springs and Tumbarumba) during 2013 were used to develop an ensemble machine learning model, using five feedforward neural networks (FFNN) with different structures combined with an eXtreme Gradient Boosting (XGB) algorithm. The former methods, FFNN, provided the primary estimations in the first layer, while the later, XGB, used the outputs of the first layer as its input to provide the final estimations of CO₂ flux. The introduced model showed slight superiority over each single FFNN and the XGB, while each of these two methods was used individually, overall RMSE: 2.64, 2.91, and 3.54 g C m⁻² yr⁻¹ respectively (3.54 provided by the best FFNN). The most significant improvement happened to the estimation of the extreme diurnal values (during midday and sunrise), as well as nocturnal estimations, which is generally considered as one of the most challenging parts of CO₂ flux gap-filling. The towers, as well as seasonality, showed different levels of sensitivity to improvements provided by the ensemble model. For instance, Tumbarumba showed more sensitivity compared to Calperum, where the differences between the Ensemble model on the one hand and the FFNNs and XGB, on the other hand, were the least of all 5 sites. Besides, the performance difference between the ensemble model and its components individually were more significant during the warm season (Jan, Feb, Mar, Oct, Nov, and Dec) compared to the cold season (Apr, May, Jun, Jul, Aug, and Sep) due to the higher amount of photosynthesis of plants, which led to a larger range of CO₂ exchange. In conclusion, the introduced ensemble model slightly improved the accuracy of CO₂ flux gap-filling and robustness of the model. Therefore, using ensemble machine learning models is potentially capable of improving data estimation and regression outcome when it seems to be no more room for improvement while using a single algorithm.

Keywords: carbon flux, Eddy covariance, extreme gradient boosting, gap-filling comparison, hybrid model, OzFlux network

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Authors: M. Çevik, S. Sabancı, D. Tezcan, C. Çelebi, F. İçier

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Ultrasound technology is the one of the non-thermal food processing method in recent years which has been used widely in the food industry. Ultrasound application in the food industry is divided into two groups: low and high intensity ultrasound application. While low intensity ultrasound is used to obtain information about physicochemical properties of foods, high intensity ultrasound is used to extract bioactive components and to inactivate microorganisms and enzymes. In this study, the ultrasound pre-treatment at a constant power (1500 W) and fixed frequency (20 kHz) was applied to the red beetroot slices having the dimension of 25×25×50 mm at the constant temperature (25°C) for different application times (0, 5, 10, 15 and 20 min). The red beet root slices pretreated with ultrasonication was squeezed immediately. The changes on rheological properties of red beet root juice depending on ultrasonication duration applied to slices were investigated. Rheological measurements were conducted by using Brookfield viscometer (LVDV-II Pro, USA). Shear stress-shear rate data was obtained from experimental measurements for 0-200 rpm range by using spindle 18. Rheological properties of juice were determined by fitting this data to some rheological models (Newtonian, Bingham, Power Law, Herschel Bulkley). It was investigated that the best model was Power Law model for both untreated red beet root juice (R2=0.991, χ2=0.0007, RMSE=0.0247) and red beetroot juice produced from ultrasonicated slices (R2=0.993, χ2=0.0006, RMSE=0.0216 for 20 min pre-treatment). k (consistency coefficient) and n (flow behavior index) values of red beetroot juices were not affected from the duration of ultrasonication applied to the slices. Ultrasound treatment does not result in any changes on the rheological properties of red beetroot juice. This can be explained by lack of ability to homogenize of the intensity of applied ultrasound.

Keywords: ultrasonication, rheology, red beet root slice, juice

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Authors: Sefiu A. Bello, Nasirudeen K. Raji, Jeleel A. Adebisi, Sadiq A. Raji

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Pure metals are not used in most cases for structural applications because of their limited properties. Presently, high entropy alloys (HEAs) are emerging by mixing comparative proportions of metals with the aim of maximizing the entropy leading to enhancement in structural and mechanical properties. Aluminum Silicon Nickel Iron Vanadium (AlSiNiFeV) alloy was developed using stir cast technique and analysed. Results obtained show that the alloy grade G0 contains 44 percentage by weight (wt%) Al, 32 wt% Si, 9 wt% Ni, 4 wt% Fe, 3 wt% V and 8 wt% for minor elements with tensile strength and elongation of 106 Nmm^-2 and 2.68%, respectively. X-ray diffraction confirmed intermetallic compounds having hexagonal closed packed (HCP), orthorhombic and cubic structures in cubic dendritic matrix. This affirmed transformation from the cubic structures of elemental constituents of the HEAs to the precipitated structures of the intermetallic compounds. A maximum tensile strength of 188 Nmm^-2 with 4% elongation was noticed at 10wt% of silica addition to the G0. An increase in tensile strength with an increment in silica content could be attributed to different phases and crystal geometries characterizing each HEA.

Keywords: HEAs, phases model, aluminium, silicon, tensile strength, model

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Authors: Van-Dycke Sarpong Asare, Vincent Adongo

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Field measurement of subsurface seismic p-wave velocities was undertaken through seismic refraction tomography. The aim of this work is to obtain a model of the shallow subsurface material elastic properties relevant for geotechnical site characterization. The survey area is at Pwalugu in Northern Ghana, where a multipurpose dam, for electricity generation, irrigation, and potable water delivery, is being planned. A 24-channel seismograph and 24, 10 Hz electromagnetic geophones, deployed 5 m apart constituted the acquisition hardware. Eleven (2-D) seismic refraction profiles, nine of which ran almost perpendicular and two parallel to the White Volta at Pwalugu, were acquired. The refraction tomograms of the thirteen profiles revealed a subsurface model consisting of one minor and one major acoustic impedance boundaries – the top dry/loose sand and the variably weathered sandstone contact, and the overburden-sandstones bedrock contact respectively. The p-wave velocities and by inference, with a priori values of poison ratios, the s-wave velocities, assisted in characterizing the geotechnical conditions of the proposed site and also in evaluating the dynamic properties such as the maximum shear modulus, the bulk modulus, and the Young modulus.

Keywords: tomography, characterization, consolidated, Pwalugu and seismograph

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Authors: Ehsan Mehryaar, Seyed Armin Motahari Tabari

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Without a doubt, soil shear strength is the most important property of the soil. The majority of fatal and catastrophic geological accidents are related to shear strength failure of the soil. Therefore, its prediction is a matter of high importance. However, acquiring the shear strength is usually a cumbersome task that might need complicated laboratory testing. Therefore, prediction of it based on common and easy to get soil properties can simplify the projects substantially. In this paper, A hybrid model based on the classification and regression tree algorithm and logistic regression is proposed where each leaf of the tree is an independent regression model. A database of 189 points for clay soil, including Moisture content, liquid limit, plastic limit, clay content, and shear strength, is collected. The performance of the developed model compared to the existing models and equations using root mean squared error and coefficient of correlation.

Keywords: model tree, CART, logistic regression, soil shear strength

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Authors: Tasir Khan, Ishfaq Ahmad, Yejuan Wang, Muhammad Salam

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Distribution models of the wind speed data are essential to assess the potential wind speed energy because it decreases the uncertainty to estimate wind energy output. Therefore, before performing a detailed potential energy analysis, the precise distribution model for data relating to wind speed must be found. In this research, material from numerous criteria goodness-of-fits, such as Kolmogorov Simonov, Anderson Darling statistics, Chi-Square, root mean square error (RMSE), AIC and BIC were combined finally to determine the wind speed of the best-fitted distribution. The suggested method collectively makes each criterion. This method was useful in a circumstance to fitting 14 distribution models statistically with the data of wind speed together at four sites in Pakistan. The consequences show that this method provides the best source for selecting the most suitable wind speed statistical distribution. Also, the graphical representation is consistent with the analytical results. This research presents three estimation methods that can be used to calculate the different distributions used to estimate the wind. In the suggested MLM, MOM, and MLE the third-order moment used in the wind energy formula is a key function because it makes an important contribution to the precise estimate of wind energy. In order to prove the presence of the suggested MOM, it was compared with well-known estimation methods, such as the method of linear moment, and maximum likelihood estimate. In the relative analysis, given to several goodness-of-fit, the presentation of the considered techniques is estimated on the actual wind speed evaluated in different time periods. The results obtained show that MOM certainly provides a more precise estimation than other familiar approaches in terms of estimating wind energy based on the fourteen distributions. Therefore, MOM can be used as a better technique for assessing wind energy.

Keywords: wind-speed modeling, goodness of fit, maximum likelihood method, linear moment

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Authors: Redvan Ghasemlounia, Elham Ansari, Hikmet Kerem Cigizoglu

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Hydrological modeling in arid and semi-arid regions is very important. Iran has many regions with these climate conditions such as Chaharmahal and Bakhtiari province that needs lots of attention with an appropriate management. Forecasting of hydrological parameters and estimation of hydrological events of catchments, provide important information that used for design, management and operation of water resources such as river systems, and dams, widely. Discharge in rivers is one of these parameters. This study presents the application and comparison of some estimation methods such as Feed-Forward Back Propagation Neural Network (FFBPNN), Multi Linear Regression (MLR), Gene Expression Programming (GEP) and Bayesian Network (BN) to predict the daily flow discharge of the Soolegan River, located at Chaharmahal and Bakhtiari province, in Iran. In this study, Soolegan, station was considered. This Station is located in Soolegan River at 51° 14՜ Latitude 31° 38՜ longitude at North Karoon basin. The Soolegan station is 2086 meters higher than sea level. The data used in this study are daily discharge and daily precipitation of Soolegan station. Feed Forward Back Propagation Neural Network(FFBPNN), Multi Linear Regression (MLR), Gene Expression Programming (GEP) and Bayesian Network (BN) models were developed using the same input parameters for Soolegan's daily discharge estimation. The results of estimation models were compared with observed discharge values to evaluate performance of the developed models. Results of all methods were compared and shown in tables and charts.

Keywords: ANN, multi linear regression, Bayesian network, forecasting, discharge, gene expression programming

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Authors: Kai Chun Yang, Shao-Wen Chen, Jong-Rong Wang, Chunkuan Shih, Jung-Hua Yang, Hsiung-Chih Chen, Wen-Sheng Hsu

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In this study, we build RADionuclide Transport, Removal And Dose Estimation/Symbolic Nuclear Analysis Package (SNAP/RADTRAD) model of Kuosheng Nuclear Power Plant which is based on the Final Safety Evaluation Report (FSAR) and other data of Kuosheng Nuclear Power Plant. It is used to estimate the radiation dose of the Exclusion Area Boundary (EAB), the Low Population Zone (LPZ), and the control room following ‘release from the containment’ case in Loss Of Coolant Accident (LOCA). The RADTRAD analysis result shows that the evaluation dose at EAB, LPZ, and the control room are close to the FSAR data, and all of the doses are lower than the regulatory limits. At last, we do a sensitivity analysis and observe that the evaluation doses increase as the intake rate of the control room increases.

Keywords: RADTRAD, radionuclide transport, removal and dose estimation, snap, symbolic nuclear analysis package, boiling water reactor, NPP, kuosheng

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Authors: M. Al Azri, M. Elzain, K. Bouziane, S. M. Chérif

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The electronic and magnetic properties of 6H-SiC with Mn impurities have been calculated using ab-initio calculations. Various configurations of Mn sites and Si and C vacancies were considered. The magnetic coupling between the two Mn atoms at substitutional and interstitials sites with and without vacancies is studied as a function of Mn atoms interatomic distance. It was found that the magnetic interaction energy decreases with increasing distance between the magnetic atoms. The energy levels appearing in the band gap due to vacancies and due to Mn impurities are determined. The calculated DOS’s are used to analyze the nature of the exchange interaction between the impurities. The band coupling model based on the p-d and d-d level repulsions between Mn and SiC has been used to describe the magnetism observed in each configuration. Furthermore, the impacts of applying U to Mn-d orbital on the magnetic moment have also been investigated. The results are used to understand the experimental data obtained on Mn- 6H-SiC (as-implanted and as –annealed) for various Mn concentration (CMn = 0.7%, 1.6%, 7%).

Keywords: ab-initio calculations, diluted magnetic semiconductors, magnetic properties, silicon carbide

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Authors: Arcady Ponosov

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A novel mathematical approach is suggested, which facilitates a compressed representation and efficient validation of parameter-rich ordinary differential equation models describing the dynamics of complex, especially biology-related, systems and which is based on identification of the system's latent variables. In particular, an efficient parameter estimation method for the compressed non-linear dynamical systems is developed. The method is applied to the so-called 'power-law systems' being non-linear differential equations typically used in Biochemical System Theory.

Keywords: generalized law of mass action, metamodels, principal components, synergetic systems

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Authors: Denys Osipenko, Jonathan Crook

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Because of the variety of the card holders’ behaviour types and income sources each consumer account can be transferred to a variety of states. Each consumer account can be inactive, transactor, revolver, delinquent, defaulted and requires an individual model for the income prediction. The estimation of transition probabilities between statuses at the account level helps to avoid the memorylessness of the Markov Chains approach. This paper investigates the transition probabilities estimation approaches to credit cards income prediction at the account level. The key question of empirical research is which approach gives more accurate results: multinomial logistic regression or multistage conditional logistic regression with binary target. Both models have shown moderate predictive power. Prediction accuracy for conditional logistic regression depends on the order of stages for the conditional binary logistic regression. On the other hand, multinomial logistic regression is easier for usage and gives integrate estimations for all states without priorities. Thus further investigations can be concentrated on alternative modeling approaches such as discrete choice models.

Keywords: multinomial regression, conditional logistic regression, credit account state, transition probability

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Authors: Balaji Sankar, Sadanand Kulkarni

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Compliant foil gas lubricated bearings are used for the support of light loads in the order of few kilograms at high speeds, in the order of 50,000 RPM. The stiffness of the foil bearings depends both on the stiffness of the compliant foil and on the lubricating gas film. The stiffness of the bearings plays a crucial role in the stable operation of the supported rotor over a range of speeds. This paper describes a numerical approach to estimate the stiffness of the bearings using pseudo spectral scheme. Methodology to obtain the stiffness of the foil bearing as a function of weight of the shaft is given and the results are presented.

Keywords: foil bearing, simulation, numerical, stiffness estimation

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Authors: Jens Friedrich, Matthias A. Gebele, Armin Lechler, Alexander Verl

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Chatter vibrations and process instabilities are the most important factors limiting the productivity of the milling process. Chatter can leads to damage of the tool, the part or the machine tool. Therefore, the estimation and prediction of the process stability is very important. The process stability depends on the spindle speed, the depth of cut and the width of cut. In milling, the process conditions are defined in the NC-program. While the spindle speed is directly coded in the NC-program, the depth and width of cut are unknown. This paper presents a new simulation based approach for the prediction of the depth and width of cut of a milling process. The prediction is based on a material removal simulation with an analytically represented tool shape and a multi-dexel approach for the work piece. The new calculation method allows the direct estimation of the depth and width of cut, which are the influencing parameters of the process stability, instead of the removed volume as existing approaches do. The knowledge can be used to predict the stability of new, unknown parts. Moreover with an additional vibration sensor, the stability lobe diagram of a milling process can be estimated and improved based on the estimated depth and width of cut.

Keywords: dexel, process stability, material removal, milling

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Authors: Marcos Valdez Alexander Junior, Igor Aguilar-Alonso

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Malnutrition is the root of different diseases that universally affect everyone, diseases such as obesity and malnutrition. The objective of this research is to predict the calories of the food to be eaten, developing a smart mobile application to show the user if a meal is balanced. Due to the large percentage of obesity and malnutrition in Peru, the present work is carried out. The development of the intelligent application is proposed with a three-layer architecture, and for the prediction of the nutritional value of the food, the use of pre-trained models based on convolutional neural networks is proposed.

Keywords: volume estimation, calorie estimation, artificial vision, food nutrition

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Authors: F. Abbas Pour Khotbehsara, B. Salehpour, A. Kianvash

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Many industrial materials like magnets need to be tested for the radiation environment expected at linear colliders (LC) where the accelerator and detectors will be subjected to large influences of beta, neutron and gamma’s over their life Gamma irradiation of the permanent sample magnets using a 60Co source was investigated up to an absorbed dose of 700Mrad shows a negligible effect on some magnetic properties of Nd-Fe-B. In this work, it has been tried to investigate the change of some important properties of Barium hexa ferrite. Results showed little decreases of magnetic properties at doses rang of 0.5 to 2.5 Mrad. But at the gamma irradiation dose up to 10 Mrad it is showed a few increase of properties. Also study of gamma irradiation of Nd-Fe-B showed considerably increase of magnetic properties.

Keywords: gamma ray irradiation, hard ferrite, magnetic coefficient, magnetic material, radiation dose

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Authors: Chulsang Yoo, Gildo Kim

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Dual polarization radar provides comprehensive information about rainfall by measuring multiple parameters. In Korea, for the rainfall estimation, JPOLE and CSU-HIDRO algorithms are generally used. This study evaluated the local applicability of JPOLE and CSU-HIDRO algorithms in Korea by using the observed rainfall data collected on August, 2014 by the Biseulsan dual polarization radar data and KMA AWS. A total of 11,372 pairs of radar-ground rain rate data were classified according to thresholds of synthetic algorithms into suitable and unsuitable data. Then, evaluation criteria were derived by comparing radar rain rate and ground rain rate, respectively, for entire, suitable, unsuitable data. The results are as follows: (1) The radar rain rate equation including KDP, was found better in the rainfall estimation than the other equations for both JPOLE and CSU-HIDRO algorithms. The thresholds were found to be adequately applied for both algorithms including specific differential phase. (2) The radar rain rate equation including horizontal reflectivity and differential reflectivity were found poor compared to the others. The result was not improved even when only the suitable data were applied. Acknowledgments: This work was supported by the Basic Science Research Program through the National Research Foundation of Korea, funded by the Ministry of Education (NRF-2013R1A1A2011012).

Keywords: CSU-HIDRO algorithm, dual polarization radar, JPOLE algorithm, radar rainfall estimation algorithm

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Authors: Angela U. Makolo

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Protein-coding and Non-coding regions determine the biology of a sequenced transcriptome. Research advances have shown that Non-coding regions are important in disease progression and clinical diagnosis. Existing bioinformatics tools have been targeted towards Protein-coding regions alone. Therefore, there are challenges associated with gaining biological insights from transcriptome sequence data. These tools are also limited to computationally intensive sequence alignment, which is inadequate and less accurate to identify both Protein-coding and Non-coding regions. Alignment-free techniques can overcome the limitation of identifying both regions. Therefore, this study was designed to develop an efficient sequence alignment-free model for identifying both Protein-coding and Non-coding regions in sequenced transcriptomes. Feature grouping and randomization procedures were applied to the input transcriptomes (37,503 data points). Successive iterations were carried out to compute the gradient vector that converged the developed Protein-coding and Non-coding Region Identifier (PNRI) model to the approximate coefficient vector. The logistic regression algorithm was used with a sigmoid activation function. A parameter vector was estimated for every sample in 37,503 data points in a bid to reduce the generalization error and cost. Maximum Likelihood Estimation (MLE) was used for parameter estimation by taking the log-likelihood of six features and combining them into a summation function. Dynamic thresholding was used to classify the Protein-coding and Non-coding regions, and the Receiver Operating Characteristic (ROC) curve was determined. The generalization performance of PNRI was determined in terms of F1 score, accuracy, sensitivity, and specificity. The average generalization performance of PNRI was determined using a benchmark of multi-species organisms. The generalization error for identifying Protein-coding and Non-coding regions decreased from 0.514 to 0.508 and to 0.378, respectively, after three iterations. The cost (difference between the predicted and the actual outcome) also decreased from 1.446 to 0.842 and to 0.718, respectively, for the first, second and third iterations. The iterations terminated at the 390th epoch, having an error of 0.036 and a cost of 0.316. The computed elements of the parameter vector that maximized the objective function were 0.043, 0.519, 0.715, 0.878, 1.157, and 2.575. The PNRI gave an ROC of 0.97, indicating an improved predictive ability. The PNRI identified both Protein-coding and Non-coding regions with an F1 score of 0.970, accuracy (0.969), sensitivity (0.966), and specificity of 0.973. Using 13 non-human multi-species model organisms, the average generalization performance of the traditional method was 74.4%, while that of the developed model was 85.2%, thereby making the developed model better in the identification of Protein-coding and Non-coding regions in transcriptomes. The developed Protein-coding and Non-coding region identifier model efficiently identified the Protein-coding and Non-coding transcriptomic regions. It could be used in genome annotation and in the analysis of transcriptomes.

Keywords: sequence alignment-free model, dynamic thresholding classification, input randomization, genome annotation

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Authors: Aurea C. L. Lacerda, Paulo R. H. Moreno, Bruna M. P. Vianna, Cristina H. R. Serra, Airton Martin, André R. Baby, Vladi O. Consiglieri, Telma M. Kaneko

Abstract:

The modified Franz cell is the most widely used model for in vitro permeation studies, however it still presents some disadvantages. Thus, some alternative methods have been developed such as Skin PAMPA, which is a bio- artificial membrane that has been applied for skin penetration estimation of xenobiotics based on HT permeability model consisting. Skin PAMPA greatest advantage is to carry out more tests, in a fast and inexpensive way. The membrane system mimics the stratum corneum characteristics, which is the primary skin barrier. The barrier properties are given by corneocytes embedded in a multilamellar lipid matrix. This layer is the main penetration route through the paracellular permeation pathway and it consists of a mixture of cholesterol, ceramides, and fatty acids as the dominant components. However, there is no consensus on the membrane composition. The objective of this work was to compare the performance among different bio-artificial membranes for studying the permeation in skin PAMPA system. Material and methods: In order to mimetize the lipid composition`s present in the human stratum corneum six membranes were developed. The membrane composition was equimolar mixture of cholesterol, ceramides 1-O-C18:1, C22, and C20, plus fatty acids C20 and C24. The membrane integrity assay was based on the transport of Brilliant Cresyl Blue, which has a low permeability; and Lucifer Yellow with very poor permeability and should effectively be completely rejected. The membrane characterization was performed using Confocal Laser Raman Spectroscopy, using stabilized laser at 785 nm with 10 second integration time and 2 accumulations. The membrane behaviour results on the PAMPA system were statistically evaluated and all of the compositions have shown integrity and permeability. The confocal Raman spectra were obtained in the region of 800-1200 cm-1 that is associated with the C-C stretches of the carbon scaffold from the stratum corneum lipids showed similar pattern for all the membranes. The ceramides, long chain fatty acids and cholesterol in equimolar ratio permitted to obtain lipid mixtures with self-organization capability, similar to that occurring into the stratum corneum. Conclusion: The artificial biological membranes studied for Skin PAMPA showed to be similar and with comparable properties to the stratum corneum.

Keywords: bio-artificial membranes, comparison, confocal Raman, skin PAMPA

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Authors: Krisada Lekdee, Sunee Sammatat, Nittaya Boonsit

Abstract:

This paper proposes a GLMM with spatial and temporal effects for malaria data in Thailand. A Bayesian method is used for parameter estimation via Gibbs sampling MCMC. A conditional autoregressive (CAR) model is assumed to present the spatial effects. The temporal correlation is presented through the covariance matrix of the random effects. The malaria quarterly data have been extracted from the Bureau of Epidemiology, Ministry of Public Health of Thailand. The factors considered are rainfall and temperature. The result shows that rainfall and temperature are positively related to the malaria morbidity rate. The posterior means of the estimated morbidity rates are used to construct the malaria maps. The top 5 highest morbidity rates (per 100,000 population) are in Trat (Q3, 111.70), Chiang Mai (Q3, 104.70), Narathiwat (Q4, 97.69), Chiang Mai (Q2, 88.51), and Chanthaburi (Q3, 86.82). According to the DIC criterion, the proposed model has a better performance than the GLMM with spatial effects but without temporal terms.

Keywords: Bayesian method, generalized linear mixed model (GLMM), malaria, spatial effects, temporal correlation

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Authors: In-Sung Lee, Un-Hwan Park, Jun-Hyeok Heo, Tae-Hyeon Oh, Dae-Gyu Park

Abstract:

Statistical Energy Analysis is to be the most effective CAE Method for air-born noise analysis in the Automotive area. This study deals with a method to predict the noise level inside of the car under the steady-state condition using the SEA model of car for air-born noise analysis. We can identify weakened part due to the acoustic material properties using it. Therefore, it is useful for the material structural design.

Keywords: air-born noise, material structural design, acoustic material properties, absorbing

Procedia PDF Downloads 425

Authors: R. Niranchana, K. Meena Alias Jeyanthi

Abstract:

As a result of the present climate change dilemma, the energy balancing strategy is to construct a sustainable environment has become a top concern for researchers worldwide. The environment itself has always been a solution from the earliest days of human evolution. Carbon capture begins with its accurate estimation and monitoring credit inventories, and its efficient use. Sustainable urban planning with deliverables of re-use energy models might benefit from assessment methods like biomass carbon credit ranking. The term "biomass energy" refers to the various ways in which living organisms can potentially be converted into a source of energy. The approaches that can be applied to biomass and an algorithm for evaluating carbon credits are presented in this paper. The micro-climate evaluation using Computational Fluid dynamics was carried out across the location (1 km x1 km) at Dindigul, India (10°24'58.68" North, 77°54.1.80 East). Sustainable Urban design must be carried out considering environmental and physiological convection, conduction, radiation and evaporative heat exchange due to proceeding solar access and wind intensities.

Keywords: biomass, climate assessment, urban planning, multi-regression, carbon estimation algorithm

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Authors: K. B. Rajasekarababu, J. Karthik, G. Vinayagamurthy

Abstract:

This paper is intended to explain the influence of major axis on aerodynamic characteristics of elliptical section. Many engineering applications such as off shore structures, bridge piers, civil structures and pipelines can be modelled as a circular cylinder but flow over complex bodies like, submarines, Elliptical wing, fuselage, missiles, and rotor blades, in which the parameters such as axis ratio can influence the flow characteristics of the wake and nature of separation. Influence of Major axis in Flow characteristics of elliptical sections are examined both experimentally and computationally in this study. For this research, four elliptical models with varying major axis [*AR=1, 4, 6, 10] are analysed. Experimental works have been conducted in a subsonic wind tunnel. Furthermore, flow characteristics on elliptical model are predicted from k-ε turbulence model using the commercial CFD packages by pressure based transient solver with Standard wall conditions.The analysis can be extended to estimation and comparison of Drag coefficient and Fatigue analysis of elliptical sections.

Keywords: elliptical section, major axis, aerodynamic characteristics, k-ε turbulence model

Procedia PDF Downloads 437