Search results for: Predicted models

Authors: Campbell Townsend, David Hamilton

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Previous research has demonstrated that negative attitudes towards people with physical disabilities and obesity are predicted by a component of perceived vulnerability to disease; germ aversion. These findings have been suggested as illustrations of an evolved but over-active mechanism which promotes the avoidance of pathogen-carrying individuals. To date, this interpretation of attitude formation has not been explored with regard to people with intellectual disability, and no attempts have been made to examine possible mediating factors. This study examined attitudes in 333 adults and demonstrated that the moderate positive relationship between germ aversion and negative attitudes toward people with intellectual disability is fully mediated by social dominance orientation, a general preference for hierarchies and inequalities among social groups. These findings have implications for the design of programs which attempt to promote community acceptance and inclusion of people with disabilities.

Keywords: avoidance, evolutionary psychology, intellectual disability, prejudice

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Authors: M. Zeydan, G. Toğa

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This study deals with a multi-criteria optimization problem which has been transformed into a single objective optimization problem using Response Surface Methodology (RSM), Artificial Neural Network (ANN) and Grey Relational Analyses (GRA) approach. Grey-RSM and Grey-ANN are hybrid techniques which can be used for solving multi-criteria optimization problem. There have been two main purposes of this research as follows. 1. To determine optimum and robust fiber dyeing process conditions by using RSM and ANN based on GRA, 2. To obtain the best suitable model by comparing models developed by different methodologies. The design variables for fiber dyeing process in textile are temperature, time, softener, anti-static, material quantity, pH, retarder, and dispergator. The quality characteristics to be evaluated are nominal color consistency of fiber, maximum strength of fiber, minimum color of dyeing solution. GRA-RSM with exact level value, GRA-RSM with interval level value and GRA-ANN models were compared based on GRA output value and MSE (Mean Square Error) performance measurement of outputs with each other. As a result, GRA-ANN with interval value model seems to be suitable reducing the variation of dyeing process for GRA output value of the model.

Keywords: Artificial Neural Network, Grey Relational Analysis, Optimization, Response Surface Methodology

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Authors: M. Mohagheghian, A. M. Ghaedi, A. Vafaei

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An artificial neural network (ANN) model is presented for the prediction of kinematic viscosity of binary mixtures of poly (ethylene glycol) (PEG) in water as a function of temperature, number-average molecular weight and mass fraction. Kinematic viscosities data of aqueous solutions for PEG (0.55419×10-6 – 9.875×10-6 m2/s) were obtained from the literature for a wide range of temperatures (277.15 - 338.15 K), number-average molecular weight (200 -10000), and mass fraction (0.0 – 1.0). A three layer feed-forward artificial neural network was employed. This model predicts the kinematic viscosity with a mean square error (MSE) of 0.281 and the coefficient of determination (R2) of 0.983. The results show that the kinematic viscosity of binary mixture of PEG in water could be successfully predicted using an artificial neural network model.

Keywords: Artificial neural network, kinematic viscosity, poly ethylene glycol (PEG)

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Authors: R. Afroundeh, T. Arimitsu, R. Yamanaka, C. S. Lian, T. Yunoki, T. Yano, K. Shirakawa

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We investigated this hypothesis that arterial CO2 pressure (PaCO2) drives ventilation (V.E) with a time delay duringrecovery from short impulse-like exercise (10 s) with work load of 200 watts. V.E and end tidal CO2 pressure (PETCO2) were measured continuously during rest, warming up, exercise and recovery periods. PaCO2 was predicted (PaCO2 pre) from PETCO2 and tidal volume (VT). PETCO2 and PaCO2 pre peaked at 20 s of recovery. V.E increased and peaked at the end of exercise and then decreased during recovery; however, it peaked again at 30 s of recovery, which was 10 s later than the peak of PaCO2 pre. The relationship between V. E and PaCO2pre was not significant by using data of them obtained at the same time but was significant by using data of V.E obtained 10 s later for data of PaCO2 pre. The results support our hypothesis that PaCO2 drives V.E with a time delay.

Keywords: Arterial CO2 pressure, impulse-like exercise, time delay, ventilation.

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Authors: A. Manivannan, R. T. Narendhirakannan

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The objective of this research was to investigate biodegradation of water hyacinth (Eichhornia crassipes) to produce bioethanol using dilute-acid pretreatment (1% sulfuric acid) results in high hemicellulose decomposition and using yeast (Pachysolen tannophilus) as bioethanol producing strain. A maximum ethanol yield of 1.14g/L with coefficient, 0.24g g^-1; productivity, 0.015g l^-1h^-1 was comparable to predicted value 32.05g/L obtained by Central Composite Design (CCD). Maximum ethanol yield coefficient was comparable to those obtained through enzymatic saccharification and fermentation of acid hydrolysate using fully equipped fermentor. Although maximum ethanol concentration was low in lab scale, the improvement of lignocellulosic ethanol yield is necessary for large scale production.

Keywords: Acid hydrolysis, Biodegradation, Hemicellulose, Pachysolen tannophilus, Water hyacinth.

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Authors: Ahmed S. Elamary

Abstract:

Ultimate shear resistance (USR) of slender plate girders can be predicted theoretically using Cardiff theory or Höglund theory. This paper will be concerned with predicting the USR using Höglund theory and EC3. Two main factors can affect the USR, the panel width “b” and the web depth “d”, consequently, the panel aspect ratio (b/d) has to be identified by limits. In most of the previous study, there is no limit for panel aspect ratio indicated. In this paper theoretical analysis has been conducted to study the effect of (b/d) on the USR. The analysis based on ninety six test results of steel plate girders subjected to shear executed and collected by others. New formula proposed to predict the percentage of the distance between the plastic hinges form in the flanges “c” to panel width “b”. Conservative limits of (c/b) have been suggested to get a consistent value of USR.

Keywords: Ultimate shear resistance, Plate Girder, Höglund’s theory, EC3.

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Authors: Razieh Jalalabadi, Norouz Mohammad Nouri

Abstract:

Cavitation, usually known as a destructive phenomenon, involves turbulent unsteady two-phase flow. Having such features, cavitating flows have been turned to a challenging topic in numerical studies and many researches are being done for better understanding of bubbly flows and proposing solutions to reduce its consequent destructive effects. Aeration may be regarded as an effective protection against cavitation erosion in many hydraulic structures, like gated tunnels. The paper concerns numerical simulation of flow in discharge gated tunnel of a dam using ing RNG k -ε model coupled with the volume of fluid (VOF) method and the zone which is susceptible of cavitation inception in the tunnel is predicted. In the second step, a vent is considered in the mentioned zone for aeration and the numerical simulation is done again to study the effects of aeration. The results show that aeration is an impressively useful method to exclude cavitation in mentioned tunnels.

Keywords: Aeration, Cavitation, Two-phase flow, TurbulentFlow, Volume of Fluid (VOF) method.

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Authors: Hany Alashwal, Safaai Deris, Razib M. Othman

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The protein domain structure has been widely used as the most informative sequence feature to computationally predict protein-protein interactions. However, in a recent study, a research group has reported a very high accuracy of 94% using hydrophobicity feature. Therefore, in this study we compare and verify the usefulness of protein domain structure and hydrophobicity properties as the sequence features. Using the Support Vector Machines (SVM) as the learning system, our results indicate that both features achieved accuracy of nearly 80%. Furthermore, domains structure had receiver operating characteristic (ROC) score of 0.8480 with running time of 34 seconds, while hydrophobicity had ROC score of 0.8159 with running time of 20,571 seconds (5.7 hours). These results indicate that protein-protein interaction can be predicted from domain structure with reliable accuracy and acceptable running time.

Keywords: Bioinformatics, protein-protein interactions, support vector machines, protein features.

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Authors: Carine Moussaed, Stephen Wornom, Bruno Koobus, Maria Vittoria Salvetti, Alain Dervieux,

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The effects of dynamic subgrid scale (SGS) models are investigated in variational multiscale (VMS) LES simulations of bluff body flows. The spatial discretization is based on a mixed finite element/finite volume formulation on unstructured grids. In the VMS approach used in this work, the separation between the largest and the smallest resolved scales is obtained through a variational projection operator and a finite volume cell agglomeration. The dynamic version of Smagorinsky and WALE SGS models are used to account for the effects of the unresolved scales. In the VMS approach, these effects are only modeled in the smallest resolved scales. The dynamic VMS-LES approach is applied to the simulation of the flow around a circular cylinder at Reynolds numbers 3900 and 20000 and to the flow around a square cylinder at Reynolds numbers 22000 and 175000. It is observed as in previous studies that the dynamic SGS procedure has a smaller impact on the results within the VMS approach than in LES. But improvements are demonstrated for important feature like recirculating part of the flow. The global prediction is improved for a small computational extra cost.

Keywords: variational multiscale LES, dynamic SGS model, unstructured grids, circular cylinder, square cylinder.

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Authors: Yue Hu, Xilu Zhao, Takao Yamaguchi, Manabu Sasajima, Yoshio Koike, Akira Hara

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This study optimized the design parameters of a cone loudspeaker as an example of high flexibility of the product design. We developed an acoustic analysis software program that considers the impact of damping caused by air viscosity. In sound reproduction, it is difficult to optimize each parameter of the loudspeaker design. To overcome the limitation of the design problem in practice, this study presents an acoustic analysis algorithm to optimize the design parameters of the loudspeaker. The material character of cone paper and the loudspeaker edge were the design parameters, and the vibration displacement of the cone paper was the objective function. The results of the analysis showed that the design had high accuracy as compared to the predicted value. These results suggested that although the parameter design is difficult, with experience and intuition, the design can be performed easily using the optimized design found with the acoustic analysis software.

Keywords: Air viscosity, design parameters, loudspeaker, optimization.

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

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

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

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Authors: K. Petcharaporn, S. Kumchoo

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The acidity (citric acid) is the one of chemical content that can be refer to the internal quality and it’s a maturity index of tomato, The titratable acidity (%TA) can be predicted by a non-destructive method prediction by using the transmittance short wavelength (SW-NIR) spectroscopy in the wavelength range between 665-955 nm. The set of 167 tomato samples divided into groups of 117 tomatoes sample for training set and 50 tomatoes sample for test set were used to establish the calibration model to predict and measure %TA by partial least squares regression (PLSR) technique. The spectra were pretreated with MSC pretreatment and it gave the optimal result for calibration model as (R = 0.92, RMSEC = 0.03%) and this model obtained high accuracy result to use for %TA prediction in test set as (R = 0.81, RMSEP = 0.05%). From the result of prediction in test set shown that the transmittance SW-NIR spectroscopy technique can be used for a non-destructive method for %TA prediction of tomato.

Keywords: Tomato, quality, prediction, transmittance, titratable acidity, citric acid.

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Authors: František Šebek, Petr Kubík, Jindřich Petruška, Jiří Hůlka

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Present study is aimed on the cutting process of circular cross-section rods where the fracture is used to separate one rod into two pieces. Incorporating the phenomenological ductile fracture model into the explicit formulation of finite element method, the process can be analyzed without the necessity of realizing too many real experiments which could be expensive in case of repetitive testing in different conditions. In the present paper, the steel AISI 1045 was examined and the tensile tests of smooth and notched cylindrical bars were conducted together with biaxial testing of the notched tube specimens to calibrate material constants of selected phenomenological ductile fracture models. These were implemented into the Abaqus/Explicit through user subroutine VUMAT and used for cutting process simulation. As the calibration process is based on variables which cannot be obtained directly from experiments, numerical simulations of fracture tests are inevitable part of the calibration. Finally, experiments regarding the cutting process were carried out and predictive capability of selected fracture models is discussed. Concluding remarks then make the summary of gained experience both with the calibration and application of particular ductile fracture criteria.

Keywords: Ductile fracture, phenomenological criteria, cutting process, explicit formulation, AISI 1045 steel.

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Authors: L.A.Kumaraswamidhas, P.Velmurugan, K.Sankaranarayanasamy

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This work has been conducted to study on comfort level of drivers of suspended cabin tractor semitrailer. Some drivers suffer from low back pain caused by vibration. The practical significance of applying suspended cabin type of tractor semi trailer was tested at different road conditions, different speed as well as different load conditions for comfortable driver seat interface (x, y, z ) and the process parameters have been prioritized using Taguchi-s L27 orthogonal array. Genetic Algorithm (GA) is used to optimize the human comfort vibration of suspended cabin tractor semitrailer drivers. The practical significance of applying GA to human comfort to reaction of suspended cabin tractor semitrailer has been validated by means of computing the deviation between predicted and experimentally obtained human comfort to vibration. The optimized acceleration data indicate a little uncomfortable ride for suspended cabin tractor semitrailer.

Keywords: Genetic Algorithm, Ride Comfort, Taguchi Method, Tractor Semitrailer

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Authors: Niloofar Yousefi, Marie Alaghband, Ivan Garibay

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With the increase of credit card usage, the volume of credit card misuse also has significantly increased, which may cause appreciable financial losses for both credit card holders and financial organizations issuing credit cards. As a result, financial organizations are working hard on developing and deploying credit card fraud detection methods, in order to adapt to ever-evolving, increasingly sophisticated defrauding strategies and identifying illicit transactions as quickly as possible to protect themselves and their customers. Compounding on the complex nature of such adverse strategies, credit card fraudulent activities are rare events compared to the number of legitimate transactions. Hence, the challenge to develop fraud detection that are accurate and efficient is substantially intensified and, as a consequence, credit card fraud detection has lately become a very active area of research. In this work, we provide a survey of current techniques most relevant to the problem of credit card fraud detection. We carry out our survey in two main parts. In the first part, we focus on studies utilizing classical machine learning models, which mostly employ traditional transnational features to make fraud predictions. These models typically rely on some static physical characteristics, such as what the user knows (knowledge-based method), or what he/she has access to (object-based method). In the second part of our survey, we review more advanced techniques of user authentication, which use behavioral biometrics to identify an individual based on his/her unique behavior while he/she is interacting with his/her electronic devices. These approaches rely on how people behave (instead of what they do), which cannot be easily forged. By providing an overview of current approaches and the results reported in the literature, this survey aims to drive the future research agenda for the community in order to develop more accurate, reliable and scalable models of credit card fraud detection.

Keywords: credit card fraud detection, user authentication, behavioral biometrics, machine learning, literature survey

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Authors: G. Bhushan, S. Dhingra, K. K. Dubey

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This paper presents the evaluation of performance (BSFC and BTE), combustion (P_max) and emission (CO, NO_x, HC and smoke opacity) parameters of karanja biodiesel in a single cylinder, four stroke, direct injection diesel engine by considering significant engine input parameters (blending ratio, compression ratio and load torque). Multi-objective optimization of performance, combustion and emission parameters is also carried out in a karanja biodiesel engine using hybrid RSM-NSGA-II technique. The pareto optimum solutions are predicted by running the hybrid RSM-NSGA-II technique. Each pareto optimal solution is having its own importance. Confirmation tests are also conducted at randomly selected few pareto solutions to check the authenticity of the results.

Keywords: Karanja biodiesel, single cylinder direct injection diesel engine, response surface methodology, central composite rotatable design, genetic algorithm.

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Authors: Giovanni Cicceri, Roberta Maisano, Nathalie Morey, Salvatore Distefano

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The main goal of this paper is to present a solution for a water purification system based on an Environmental Internet of Things (EIoT) platform to monitor and control water quality and machine learning (ML) models to support decision making and speed up the processes of purification of water. A real case study has been implemented by deploying an EIoT platform and a network of devices, called Gramb meters and belonging to the Gramb project, on wastewater purification systems located in Calabria, south of Italy. The data thus collected are used to control the wastewater quality, detect anomalies and predict the behaviour of the purification system. To this extent, three different statistical and machine learning models have been adopted and thus compared: Autoregressive Integrated Moving Average (ARIMA), Long Short Term Memory (LSTM) autoencoder, and Facebook Prophet (FP). The results demonstrated that the ML solution (LSTM) out-perform classical statistical approaches (ARIMA, FP), in terms of both accuracy, efficiency and effectiveness in monitoring and controlling the wastewater purification processes.

Keywords: EIoT, machine learning, anomaly detection, environment monitoring.

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Authors: M. Ahmadi Marvast, M. Sohrabi, H. Ganji

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The rate of production of main products of the Fischer-Tropsch reactions over Fe/HZSM5 bifunctional catalyst in a fixed bed reactor is investigated at a broad range of temperature, pressure, space velocity, H2/CO feed molar ratio and CO2, CH4 and water flow rates. Model discrimination and parameter estimation were performed according to the integral method of kinetic analysis. Due to lack of mechanism development for Fisher – Tropsch Synthesis on bifunctional catalysts, 26 different models were tested and the best model is selected. Comprehensive one and two dimensional heterogeneous reactor models are developed to simulate the performance of fixed-bed Fischer – Tropsch reactors. To reduce computational time for optimization purposes, an Artificial Feed Forward Neural Network (AFFNN) has been used to describe intra particle mass and heat transfer diffusion in the catalyst pellet. It is seen that products' reaction rates have direct relation with H2 partial pressure and reverse relation with CO partial pressure. The results show that the hybrid model has good agreement with rigorous mechanistic model, favoring that the hybrid model is about 25-30 times faster.

Keywords: Fischer-Tropsch, heterogeneous modeling, kinetic study.

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Authors: Luis Fonseca, Filipe Cabral Pinto, Susana Sargento

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The increase of the world population, especially in large urban centers, has resulted in new challenges particularly with the control and optimization of public safety. Thus, in the present work, a solution is proposed for the prediction of criminal occurrences in a city based on historical data of incidents and demographic information. The entire research and implementation will be presented start with the data collection from its original source, the treatment and transformations applied to them, choice and the evaluation and implementation of the Machine Learning model up to the application layer. Classification models will be implemented to predict criminal risk for a given time interval and location. Machine Learning algorithms such as Random Forest, Neural Networks, K-Nearest Neighbors and Logistic Regression will be used to predict occurrences, and their performance will be compared according to the data processing and transformation used. The results show that the use of Machine Learning techniques helps to anticipate criminal occurrences, which contributed to the reinforcement of public security. Finally, the models were implemented on a platform that will provide an API to enable other entities to make requests for predictions in real-time. An application will also be presented where it is possible to show criminal predictions visually.

Keywords: Crime prediction, machine learning, public safety, smart city.

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Authors: M. M. Ali, Ahmed Al-Ani, Derek Eamus, Daniel K. Y. Tan

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In this glasshouse study, we developed a new imagebased non-destructive technique for detecting leaf P status of different crops such as cotton, tomato and lettuce. The plants were grown on a nutrient solution containing different P concentrations, e.g. 0%, 50% and 100% of recommended P concentration (P0 = no P, L; P1 = 2.5 mL 10 L-1 of P and P2 = 5 mL 10 L-1 of P). After 7 weeks of treatment, the plants were harvested and data on leaf P contents were collected using the standard destructive laboratory method and at the same time leaf images were collected by a handheld crop image sensor. We calculated leaf area, leaf perimeter and RGB (red, green and blue) values of these images. These data were further used in linear discriminant analysis (LDA) to estimate leaf P contents, which successfully classified these plants on the basis of leaf P contents. The data indicated that P deficiency in crop plants can be predicted using leaf image and morphological data. Our proposed nondestructive imaging method is precise in estimating P requirements of different crop species.

Keywords: Image-based techniques, leaf area, leaf P contents, linear discriminant analysis.

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Authors: Ramlan Zailani, Halim Ghafar, Mohamad Sofian So'aib

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Air infiltration in mass scale industrial applications of bio char production is inevitable. The presence of oxygen during the carbonization process is detrimental to the production of biochar yield and properties. The experiment was carried out on several wood species in a fixed-bed pyrolyser under various fractions of oxygen ranging from 0% to 11% by varying nitrogen and oxygen composition in the pyrolysing gas mixtures at desired compositions. The bed temperature and holding time were also varied. Process optimization was carried out by Response Surface Methodology (RSM) by employing Central Composite Design (CCD) using Design Expert 6.0 Software. The effect of oxygen ratio and holding time on biochar yield within the range studied were statistically significant. From the analysis result, optimum condition of 15.2% biochar yield of mangrove wood was predicted at pyrolysis temperature of 403 oC, oxygen percentage of 2.3% and holding time of two hours. This prediction agreed well with the experiment finding of 15.1% biochar yield.

Keywords: Mangrove wood, slow pyrolysis, oxygen infiltration.

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Authors: S. Benchelha, H. C. Aoudjehane, M. Hakdaoui, R. El Hamdouni, H. Mansouri, T. Benchelha, M. Layelmam, M. Alaoui

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The logistic regression (LR) and multivariate adaptive regression spline (MarSpline) are applied and verified for analysis of landslide susceptibility map in Oudka, Morocco, using geographical information system. From spatial database containing data such as landslide mapping, topography, soil, hydrology and lithology, the eight factors related to landslides such as elevation, slope, aspect, distance to streams, distance to road, distance to faults, lithology map and Normalized Difference Vegetation Index (NDVI) were calculated or extracted. Using these factors, landslide susceptibility indexes were calculated by the two mentioned methods. Before the calculation, this database was divided into two parts, the first for the formation of the model and the second for the validation. The results of the landslide susceptibility analysis were verified using success and prediction rates to evaluate the quality of these probabilistic models. The result of this verification was that the MarSpline model is the best model with a success rate (AUC = 0.963) and a prediction rate (AUC = 0.951) higher than the LR model (success rate AUC = 0.918, rate prediction AUC = 0.901).

Keywords: Landslide susceptibility mapping, regression logistic, multivariate adaptive regression spline, Oudka, Taounate, Morocco.

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Authors: Young S. Bang, Dong H. Yoon, Seung H. Yoo

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Emergency Core Coolant Bypass (ECC Bypass) has been regarded as an important phenomenon to peak cladding temperature of large-break loss-of-coolant-accidents (LBLOCA) in nuclear power plants (NPP). A modeling scheme to address the ECC Bypass phenomena and the calculation of LBLOCA using that scheme are discussed in the present paper. A hydraulic form loss coefficient (HFLC) from the reactor vessel downcomer to the broken cold leg is predicted by the computational fluid dynamics (CFD) code with a variation of the void fraction incoming from the downcomer. The maximum, mean, and minimum values of FLC are derived from the CFD results and are incorporated into the LBLOCA calculation using a system thermal-hydraulic code, MARS-KS. As a relevant parameter addressing the ECC Bypass phenomena, the FLC to the break and its range are proposed.

Keywords: CFD analysis, ECC Bypass, hydraulic form loss coefficient, system thermal-hydraulic code.

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Authors: Y. Harold Robinson, M. Rajaram

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Designing cost-efficient, secure network protocols for Wireless Sensor Networks (WSNs) is a challenging problem because sensors are resource-limited wireless devices. Security services such as authentication and improved pairwise key establishment are critical to high efficient networks with sensor nodes. For sensor nodes to correspond securely with each other efficiently, usage of cryptographic techniques is necessary. In this paper, two key predistribution schemes that enable a mobile sink to establish a secure data-communication link, on the fly, with any sensor nodes. The intermediate nodes along the path to the sink are able to verify the authenticity and integrity of the incoming packets using a predicted value of the key generated by the sender’s essential power. The proposed schemes are based on the pairwise key with the mobile sink, our analytical results clearly show that our schemes perform better in terms of network resilience to node capture than existing schemes if used in wireless sensor networks with mobile sinks.

Keywords: Wireless Sensor Networks, predistribution scheme, cryptographic techniques.

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Authors: Chun-Chi Li, Da-Wei Huang, Yin-Chia Su, Liang-Chih Tasi

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In hypersonic environments, the aerothermal effect makes it difficult for the optical side windows of optical guided missiles to withstand high heat. This produces cracking or breaking, resulting in an inability to function. This study used computational fluid mechanics to investigate the external cooling jet conditions of optical side windows. The turbulent models k-ε and k-ω were simulated. To be in better accord with actual aerothermal environments, a thermal radiation model was added to examine suitable amounts of external coolants and the optical window problems of aero-thermodynamics. The simulation results indicate that when there are no external cooling jets, because airflow on the optical window and the tail groove produce vortices, the temperatures in these two locations reach a peak of approximately 1600 K. When the external cooling jets worked at 0.15 kg/s, the surface temperature of the optical windows dropped to approximately 280 K. When adding thermal radiation conditions, because heat flux dissipation was faster, the surface temperature of the optical windows fell from 280 K to approximately 260 K. The difference in influence of the different turbulence models k-ε and k-ω on optical window surface temperature was not significant.

Keywords: aero-optical side window, aerothermal effect, cooling, hypersonic flow

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Authors: B. R. S. Babu, E. Prasad, P. V. Laveen, A. M. Vinodkumar

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Searching the “Island of stability” is a topic of extreme interest in theoretical as well as experimental modern physics today. This “island of stability” is spanned by superheavy elements (SHE's) that are produced in the laboratory. SHE's are believed to exist primarily due to the “magic” stabilizing effects of nuclear shell structure. SHE synthesis is extremely difficult due to their very low production cross section, often of the order of pico barns or less. Stabilizing effects of shell closures at proton number Z=82 and neutron number N=126 are predicted theoretically. Though stabilizing effects of Z=82 have been experimentally verified, no concluding observations have been made with N=126, so far. We measured and analyzed the total evaporation residue (ER) cross sections for a number of systems with neutron number around 126 to explore possible shell closure effects in ER cross sections, in this work.

Keywords: Superheavy element, fusion evaporation, evaporation reside, compound nucleus.

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Authors: Kalyan Kumar Mandal, Damodar Maity

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The degradation of concrete due to various hygrochemo- mechanical actions is inevitable for the structures particularly built to store water. Therefore, it is essential to determine the material properties of dam-like structures due to ageing to predict the behavior of such structures after a certain age. The degraded material properties are calculated by introducing isotropic degradation index. The predicted material properties are used to study the behavior of aged dam at different ages. The dam is modeled by finite elements and displacement and is considered as an unknown variable. The parametric study reveals that the displacement is quite larger for comparatively lower design life of the structure because the degradation of elastic properties depends on the design life of the dam. The stresses in dam cam be unexpectedly large at any age with in the design life. The outcomes of the present study indicate the importance of the consideration ageing effect of concrete exposed to water for the safe design of dam throughout its life time.

Keywords: Hygro-chemo-mechanical, isotropic degradation, finite element method, Koyna earthquake.

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Authors: Mohammad Bakhshi, Firas Al Janabi

Abstract:

High resolution rain data are very important to fulfill the input of hydrological models. Among models of high-resolution rainfall data generation, the temporal disaggregation was chosen for this study. The paper attempts to generate three different rainfall resolutions (4-hourly, hourly and 10-minutes) from daily for around 20-year record period. The process was done by DiMoN tool which is based on random cascade model and method of fragment. Differences between observed and simulated rain dataset are evaluated with variety of statistical and empirical methods: Kolmogorov-Smirnov test (K-S), usual statistics, and Exceedance probability. The tool worked well at preserving the daily rainfall values in wet days, however, the generated data are cumulated in a shorter time period and made stronger storms. It is demonstrated that the difference between generated and observed cumulative distribution function curve of 4-hourly datasets is passed the K-S test criteria while in hourly and 10-minutes datasets the P-value should be employed to prove that their differences were reasonable. The results are encouraging considering the overestimation of generated high-resolution rainfall data.

Keywords: DiMoN tool, disaggregation, exceedance probability, Kolmogorov-Smirnov Test, rainfall.

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Authors: Elena Ezhova, Vadim Mottl, Olga Krasotkina

Abstract:

The problem of estimating time-varying regression is inevitably concerned with the necessity to choose the appropriate level of model volatility - ranging from the full stationarity of instant regression models to their absolute independence of each other. In the stationary case the number of regression coefficients to be estimated equals that of regressors, whereas the absence of any smoothness assumptions augments the dimension of the unknown vector by the factor of the time-series length. The Akaike Information Criterion is a commonly adopted means of adjusting a model to the given data set within a succession of nested parametric model classes, but its crucial restriction is that the classes are rigidly defined by the growing integer-valued dimension of the unknown vector. To make the Kullback information maximization principle underlying the classical AIC applicable to the problem of time-varying regression estimation, we extend it onto a wider class of data models in which the dimension of the parameter is fixed, but the freedom of its values is softly constrained by a family of continuously nested a priori probability distributions.

Keywords: Time varying regression, time-volatility of regression coefficients, Akaike Information Criterion (AIC), Kullback information maximization principle.

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Authors: M. H. Sedaghat, A. Zamani, S. Morshedi, R. Janamiri, M. Safdari, I. Mahdavi, A. Hosseini, A. Hatampour

Abstract:

Although lots of experiments have been done in enhanced oil recovery, the number of experiments which consider the effects of local and global heterogeneity on efficiency of enhanced oil recovery based on the polymer-surfactant flooding is low and rarely done. In this research, we have done numerous experiments of water flooding and polymer-surfactant flooding on a five spot glass micromodel in different conditions such as different positions of layers. In these experiments, five different micromodels with three different pore structures are designed. Three models with different layer orientation, one homogenous model and one heterogeneous model are designed. In order to import the effect of heterogeneity of porous media, three types of pore structures are distributed accidentally and with equal ratio throughout heterogeneous micromodel network according to random normal distribution. The results show that maximum EOR recovery factor will happen in a situation where the layers are orthogonal to the path of mainstream and the minimum EOR recovery factor will happen in a situation where the model is heterogeneous. This experiments show that in polymer-surfactant flooding, with increase of angles of layers the EOR recovery factor will increase and this recovery factor is strongly affected by local heterogeneity around the injection zone.

Keywords: Layered Reservoir, Micromodel, Local Heterogeneity, Polymer-Surfactant Flooding, Enhanced Oil Recovery.

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