Search results for: convection-diffusion controlled model
Commenced in January 2007
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Edition: International
Paper Count: 18529

Search results for: convection-diffusion controlled model

14209 Wound Healing and Antioxidant Properties of 80% Methanol Leaf Extract of Verbascum sinaiticum (Scrophulariaceae), an Ethiopian Medicinal Plant

Authors: Solomon Assefa Huluka

Abstract:

Wounds account for severe morbidity, socioeconomic distress, and mortality around the globe.For several years, various herbal products are used to expediteand augment the innate wound healing process. In Ethiopian folkloricmedicine, Verbascum sinaiticum L. (V. sinaiticum) is commonlyapplied as a wound-healing agent. The present study investigated the potential wound healing and antioxidant properties of hydroalcoholic leaf extract of V. sinaiticum. The 80% methanol extract, formulated as 5% (w/w) and 10% (w/w) ointments, was evaluated in excision and incision wound models using nitrofurazone and simple ointment as positive and negative controls, respectively. Parameters such as wound contraction, period of epithelialization, and tensile strength were determined. Moreover, its in vitro antioxidant property was evaluated using a DPPH assay. In the excision model, both doses (5% and 10% w/w) of the extract showed a significant (p<0.001) wound healing efficacy compared to the negative control, as evidenced by enhanced wound contraction rate and shorter epithelialization time records. In the incision model, the lower dose (5% w/w) ointment formulation of the extract exhibited the maximum increment in tensile strength (85.6%) that was significant (p<0.001)compared to negative and untreated controls. Animals treated with 5% w/wointment, furthermore, showed a significantly (p < 0.05) higher percentage of tensile strength than nitrofurazone treated ones. Moreover, the hydroalcoholic extract of the plant showed a noticeable free radical scavenging property. The result of the present study upholds the folkloric use of V. sinaiticum in the treatment of wounds.

Keywords: wound healing, antioxidant, excision wound model, incision wound model, verbascum sinaiticum

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14208 A Multilayer Perceptron Neural Network Model Optimized by Genetic Algorithm for Significant Wave Height Prediction

Authors: Luis C. Parra

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The significant wave height prediction is an issue of great interest in the field of coastal activities because of the non-linear behavior of the wave height and its complexity of prediction. This study aims to present a machine learning model to forecast the significant wave height of the oceanographic wave measuring buoys anchored at Mooloolaba of the Queensland Government Data. Modeling was performed by a multilayer perceptron neural network-genetic algorithm (GA-MLP), considering Relu(x) as the activation function of the MLPNN. The GA is in charge of optimized the MLPNN hyperparameters (learning rate, hidden layers, neurons, and activation functions) and wrapper feature selection for the window width size. Results are assessed using Mean Square Error (MSE), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE). The GAMLPNN algorithm was performed with a population size of thirty individuals for eight generations for the prediction optimization of 5 steps forward, obtaining a performance evaluation of 0.00104 MSE, 0.03222 RMSE, 0.02338 MAE, and 0.71163% of MAPE. The results of the analysis suggest that the MLPNNGA model is effective in predicting significant wave height in a one-step forecast with distant time windows, presenting 0.00014 MSE, 0.01180 RMSE, 0.00912 MAE, and 0.52500% of MAPE with 0.99940 of correlation factor. The GA-MLP algorithm was compared with the ARIMA forecasting model, presenting better performance criteria in all performance criteria, validating the potential of this algorithm.

Keywords: significant wave height, machine learning optimization, multilayer perceptron neural networks, evolutionary algorithms

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14207 Thermodynamic Behaviour of Binary Mixtures of 1, 2-Dichloroethane with Some Cyclic Ethers: Experimental Results and Modelling

Authors: Fouzia Amireche-Ziar, Ilham Mokbel, Jacques Jose

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The vapour pressures of the three binary mixtures: 1, 2- dichloroethane + 1,3-dioxolane, + 1,4-dioxane or + tetrahydropyrane, are carried out at ten temperatures ranging from 273 to 353.15 K. An accurate static device was employed for these measurements. The VLE data were reduced using the Redlich-Kister equation by taking into consideration the vapour pressure non-ideality in terms of the second molar virial coefficient. The experimental data were compared to the results predicted with the DISQUAC and Dortmund UNIFAC group contribution models for the total pressures P and the excess molar Gibbs energies GE.

Keywords: disquac model, dortmund UNIFAC model, excess molar Gibbs energies GE, VLE

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14206 Coupled Hydro-Geomechanical Modeling of Oil Reservoir Considering Non-Newtonian Fluid through a Fracture

Authors: Juan Huang, Hugo Ninanya

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Oil has been used as a source of energy and supply to make materials, such as asphalt or rubber for many years. This is the reason why new technologies have been implemented through time. However, research still needs to continue increasing due to new challenges engineers face every day, just like unconventional reservoirs. Various numerical methodologies have been applied in petroleum engineering as tools in order to optimize the production of reservoirs before drilling a wellbore, although not all of these have the same efficiency when talking about studying fracture propagation. Analytical methods like those based on linear elastic fractures mechanics fail to give a reasonable prediction when simulating fracture propagation in ductile materials whereas numerical methods based on the cohesive zone method (CZM) allow to represent the elastoplastic behavior in a reservoir based on a constitutive model; therefore, predictions in terms of displacements and pressure will be more reliable. In this work, a hydro-geomechanical coupled model of horizontal wells in fractured rock was developed using ABAQUS; both extended element method and cohesive elements were used to represent predefined fractures in a model (2-D). A power law for representing the rheological behavior of fluid (shear-thinning, power index <1) through fractures and leak-off rate permeating to the matrix was considered. Results have been showed in terms of aperture and length of the fracture, pressure within fracture and fluid loss. It was showed a high infiltration rate to the matrix as power index decreases. A sensitivity analysis is conclusively performed to identify the most influential factor of fluid loss.

Keywords: fracture, hydro-geomechanical model, non-Newtonian fluid, numerical analysis, sensitivity analysis

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14205 Modelling Structural Breaks in Stock Price Time Series Using Stochastic Differential Equations

Authors: Daniil Karzanov

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This paper studies the effect of quarterly earnings reports on the stock price. The profitability of the stock is modeled by geometric Brownian diffusion and the Constant Elasticity of Variance model. We fit several variations of stochastic differential equations to the pre-and after-report period using the Maximum Likelihood Estimation and Grid Search of parameters method. By examining the change in the model parameters after reports’ publication, the study reveals that the reports have enough evidence to be a structural breakpoint, meaning that all the forecast models exploited are not applicable for forecasting and should be refitted shortly.

Keywords: stock market, earnings reports, financial time series, structural breaks, stochastic differential equations

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14204 Intelligent Production Machine

Authors: A. Şahinoğlu, R. Gürbüz, A. Güllü, M. Karhan

Abstract:

This study in production machines, it is aimed that machine will automatically perceive cutting data and alter cutting parameters. The two most important parameters have to be checked in machine control unit are progress feed rate and speeds. These parameters are aimed to be controlled by sounds of machine. Optimum sound’s features introduced to computer. During process, real time data is received and converted by Matlab software. Data is converted into numerical values. According to them progress and speeds decreases/increases at a certain rate and thus optimum sound is acquired. Cutting process is made in respect of optimum cutting parameters. During chip remove progress, features of cutting tools, kind of cut material, cutting parameters and used machine; affects on various parameters. Instead of required parameters need to be measured such as temperature, vibration, and tool wear that emerged during cutting process; detailed analysis of the sound emerged during cutting process will provide detection of various data that included in the cutting process by the much more easy and economic way. The relation between cutting parameters and sound is being identified.

Keywords: cutting process, sound processing, intelligent late, sound analysis

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14203 Research on the Online Learning Activities Design and Students’ Experience Based on APT Model

Authors: Wang Yanli, Cheng Yun, Yang Jiarui

Abstract:

Due to the separation of teachers and students, online teaching during the COVID-19 epidemic was faced with many problems, such as low enthusiasm of students, distraction, low learning atmosphere, and insufficient interaction between teachers and students. The essay designed the elaborate online learning activities of the course 'Research Methods of Educational Science' based on the APT model from three aspects of multiple assessment methods, a variety of teaching methods, and online learning environment and technology. Student's online learning experience was examined from the perception of online course, the perception of the online learning environment, and satisfaction after the course’s implementation. The research results showed that students have a positive overall evaluation of online courses, a high degree of engagement in learning, positive acceptance of online learning, and high satisfaction with it, but students hold a relatively neutral attitude toward online learning. And some dimensions in online learning experience were found to have positive influence on students' satisfaction with online learning. We suggest making the good design of online courses, selecting proper learning platforms, and conducting blended learning to improve students’ learning experience. This study has both theoretical and practical significance for the design, implementation, effect feedback, and sustainable development of online teaching in the post-epidemic era.

Keywords: APT model, online learning, online learning activities, learning experience

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14202 Optimization in Locating Firefighting Stations Using GIS Data and AHP Model; A Case Study on Arak City

Authors: Hasan Heydari

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In recent decades, locating urban services is one of the significant discussions in urban planning. Among these considerations, cities require more accurate planning in order to supply citizen needs, especially part of urban safety. In order to gain this goal, one of the main tasks of urban planners and managers is specifying suitable sites to locate firefighting stations. This study has been done to reach this purpose. Therefore effective criteria consist of coverage radius, population density, proximity to pathway network, land use (compatible and incompatible neighborhood) have been specified. After that, descriptive and local information of the criteria was provided and their layers were created in ArcGIS 9.3. Using Analytic Hierarchy Process (AHP) these criteria and their sub-criteria got the weights. These layers were classified regarding their weights and finally were overlaid by Index Overlay Model and provided the final site selection map for firefighting stations of Arak city. The results gained by analyzing in GIS environment indicate the existing fire station don’t cover the whole city sufficiently and some of the stations have established on the unsuitable sites. The output map indicates the best sites to locate firefighting stations of Arak.

Keywords: site-selection, firefighting stations, analytic hierarchy process (AHP), GIS, index overlay model

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14201 Influence of Iron Ore Mineralogy on Cluster Formation inside the Shaft Furnace

Authors: M. Bahgat, H. A. Hanafy, S. Lakdawala

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Clustering phenomenon of pellets was observed frequently in shaft processes operating at higher temperatures. Clustering is a result of the growth of fibrous iron precipitates (iron whiskers) that become hooked to each other and finally become crystallized during the initial stages of metallization. If the pellet clustering is pronounced, sometimes leads to blocking inside the furnace and forced shutdown takes place. This work clarifies further the relation between metallic iron whisker growth and iron ore mineralogy. Various pellet sizes (6 – 12.0 & +12.0 mm) from three different ores (A, B & C) were (completely and partially) reduced at 985 oC with H2/CO gas mixture using thermos-gravimetric technique. It was found that reducibility increases by decreasing the iron ore pellet’s size. Ore (A) has the highest reducibility than ore (B) and ore (C). Increasing the iron ore pellet’s size leads to increase the probability of metallic iron whisker formation. Ore (A) has the highest tendency for metallic iron whisker formation than ore (B) and ore (C). The reduction reactions for all iron ores A, B and C are mainly controlled by diffusion reaction mechanism.

Keywords: shaft furnace, cluster, metallic iron whisker, mineralogy, ferrous metallurgy

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14200 Supervisor Controller-Based Colored Petri Nets for Deadlock Control and Machine Failures in Automated Manufacturing Systems

Authors: Husam Kaid, Abdulrahman Al-Ahmari, Zhiwu Li

Abstract:

This paper develops a robust deadlock control technique for shared and unreliable resources in automated manufacturing systems (AMSs) based on structural analysis and colored Petri nets, which consists of three steps. The first step involves using strict minimal siphon control to create a live (deadlock-free) system that does not consider resource failure. The second step uses an approach based on colored Petri net, in which all monitors designed in the first step are merged into a single monitor. The third step addresses the deadlock control problems caused by resource failures. For all resource failures in the Petri net model a common recovery subnet based on colored petri net is proposed. The common recovery subnet is added to the obtained system at the second step to make the system reliable. The proposed approach is evaluated using an AMS from the literature. The results show that the proposed approach can be applied to an unreliable complex Petri net model, has a simpler structure and less computational complexity, and can obtain one common recovery subnet to model all resource failures.

Keywords: automated manufacturing system, colored Petri net, deadlocks, siphon

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14199 Heat Transfer and Trajectory Models for a Cloud of Spray over a Marine Vessel

Authors: S. R. Dehghani, G. F. Naterer, Y. S. Muzychka

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Wave-impact sea spray creates many droplets which form a spray cloud traveling over marine objects same as marine vessels and offshore structures. In cold climates such as Arctic reigns, sea spray icing, which is ice accretion on cold substrates, is strongly dependent on the wave-impact sea spray. The rate of cooling of droplets affects the process of icing that can yield to dry or wet ice accretion. Trajectories of droplets determine the potential places for ice accretion. Combining two models of trajectories and heat transfer for droplets can predict the risk of ice accretion reasonably. The majority of the cooling of droplets is because of droplet evaporations. In this study, a combined model using trajectory and heat transfer evaluate the situation of a cloud of spray from the generation to impingement. The model uses some known geometry and initial information from the previous case studies. The 3D model is solved numerically using a standard numerical scheme. Droplets are generated in various size ranges from 7 mm to 0.07 mm which is a suggested range for sea spray icing. The initial temperature of droplets is considered to be the sea water temperature. Wind velocities are assumed same as that of the field observations. Evaluations are conducted using some important heading angles and wind velocities. The characteristic of size-velocity dependence is used to establish a relation between initial sizes and velocities of droplets. Time intervals are chosen properly to maintain a stable and fast numerical solution. A statistical process is conducted to evaluate the probability of expected occurrences. The medium size droplets can reach the highest heights. Very small and very large droplets are limited to lower heights. Results show that higher initial velocities create the most expanded cloud of spray. Wind velocities affect the extent of the spray cloud. The rate of droplet cooling at the start of spray formation is higher than the rest of the process. This is because of higher relative velocities and also higher temperature differences. The amount of water delivery and overall temperature for some sample surfaces over a marine vessel are calculated. Comparing results and some field observations show that the model works accurately. This model is suggested as a primary model for ice accretion on marine vessels.

Keywords: evaporation, sea spray, marine icing, numerical solution, trajectory

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14198 Modeling of Hydraulic Networking of Water Supply Subsystem Case of Addis Ababa

Authors: Solomon Weldegebriel Gebrelibanos

Abstract:

Water is one of the most important substances in human life that can give a human liberality with its cost and availability. Water comes from rainfall and runoff and reaches the ground as runoff that is stored in a river, ponds, and big water bodies, including sea and ocean and the remaining water portion is infiltrated into the ground to store in the aquifer. Water can serve human beings in various ways, including irrigation, water supply, hydropower and soon. Water supply is the main pillar of the water service to the human being. Water supply distribution in Addis Ababa arises from Legedadi, Akakai, and Gefersa. The objective of the study is to measure the performance of the water supply distribution in Addis Ababa city. The water supply distribution model is developed by computer-aided design software. The model can analyze the operational change, loss of water, and performance of the network. The two design criteria that have been employed to analyze the network system are velocity and pressure. The result shows that the customers are using the water at high pressure with low demand. The water distribution system is older than the expected service life with more leakage. Hence the study recommended that fixing Pressure valves and new distribution facilities can resolve the performance of the water supply system

Keywords: distribution, model, pressure, velocity

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14197 Forecasting Residential Water Consumption in Hamilton, New Zealand

Authors: Farnaz Farhangi

Abstract:

Many people in New Zealand believe that the access to water is inexhaustible, and it comes from a history of virtually unrestricted access to it. For the region like Hamilton which is one of New Zealand’s fastest growing cities, it is crucial for policy makers to know about the future water consumption and implementation of rules and regulation such as universal water metering. Hamilton residents use water freely and they do not have any idea about how much water they use. Hence, one of proposed objectives of this research is focusing on forecasting water consumption using different methods. Residential water consumption time series exhibits seasonal and trend variations. Seasonality is the pattern caused by repeating events such as weather conditions in summer and winter, public holidays, etc. The problem with this seasonal fluctuation is that, it dominates other time series components and makes difficulties in determining other variations (such as educational campaign’s effect, regulation, etc.) in time series. Apart from seasonality, a stochastic trend is also combined with seasonality and makes different effects on results of forecasting. According to the forecasting literature, preprocessing (de-trending and de-seasonalization) is essential to have more performed forecasting results, while some other researchers mention that seasonally non-adjusted data should be used. Hence, I answer the question that is pre-processing essential? A wide range of forecasting methods exists with different pros and cons. In this research, I apply double seasonal ARIMA and Artificial Neural Network (ANN), considering diverse elements such as seasonality and calendar effects (public and school holidays) and combine their results to find the best predicted values. My hypothesis is the examination the results of combined method (hybrid model) and individual methods and comparing the accuracy and robustness. In order to use ARIMA, the data should be stationary. Also, ANN has successful forecasting applications in terms of forecasting seasonal and trend time series. Using a hybrid model is a way to improve the accuracy of the methods. Due to the fact that water demand is dominated by different seasonality, in order to find their sensitivity to weather conditions or calendar effects or other seasonal patterns, I combine different methods. The advantage of this combination is reduction of errors by averaging of each individual model. It is also useful when we are not sure about the accuracy of each forecasting model and it can ease the problem of model selection. Using daily residential water consumption data from January 2000 to July 2015 in Hamilton, I indicate how prediction by different methods varies. ANN has more accurate forecasting results than other method and preprocessing is essential when we use seasonal time series. Using hybrid model reduces forecasting average errors and increases the performance.

Keywords: artificial neural network (ANN), double seasonal ARIMA, forecasting, hybrid model

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14196 Two Dimensional Finite Element Model to Study Calcium Dynamics in Fibroblast Cell with Excess Buffer Approximation Involving ER Flux and SERCA Pump

Authors: Mansha Kotwani

Abstract:

The specific spatio-temporal calcium concentration patterns are required by the fibroblasts to maintain its structure and functions. Thus, calcium concentration is regulated in cell at different levels in various activities of the cell. The variations in cytosolic calcium concentration largely depend on the buffers present in cytosol and influx of calcium into cytosol from ER through IP3Rs or Raynodine receptors followed by reuptake of calcium into ER through sarcoplasmic/endoplasmic reticulum ATPs (SERCA) pump. In order to understand the mechanisms of wound repair, tissue remodeling and growth performed by fibroblasts, it is of crucial importance to understand the mechanisms of calcium concentration regulation in fibroblasts. In this paper, a model has been developed to study calcium distribution in NRK fibroblast in the presence of buffers and ER flux with SERCA pump. The model has been developed for two dimensional unsteady state case. Appropriate initial and boundary conditions have been framed along with physiology of the cell. Finite element technique has been employed to obtain the solution. The numerical results have been used to study the effect of buffers, ER flux and source amplitude on calcium distribution in fibroblast cell.

Keywords: buffers, IP3R, ER flux, SERCA pump, source amplitude

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14195 Synthesis and Characterization of Novel Hollow Silica Particle through DODAB Vesicle Templating

Authors: Eun Ju Park, Wendy Rusli, He Tao, Alexander M. Van Herk, Sanggu Kim

Abstract:

Hollow micro-/nano- structured materials have proven to be promising in wide range of applications, such as catalysis, drug delivery and controlled release, biotechnology, and personal and consumer care. Hollow sphere structures can be obtained through various templating approaches; colloid templates, emulsion templates, multi-surfactant templates, and single crystal templates. Vesicles are generally the self-directed assemblies of amphiphilic molecules including cationic, anionic, and cationic surfactants in aqueous solutions. The directed silica capsule formations were performed at the surface of dioctadecyldimethylammoniumbromide(DODAB) bilayer vesicles as soft template. The size of DODAB bilayer vesicles could be tuned by extrusion of a preheated dispersion of DODAB. The synthesized hollow silica particles were characterized by conventional TEM, cryo-TEM and SEM to determine the morphology and structure of particles and dynamic light scattering (DLS) method to measure the particle size and particle size distribution.

Keywords: characterization, DODAB, hollow silica particle, synthesis, vesicle

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14194 Predictions of Values in a Causticizing Process

Authors: R. Andreola, O. A. A. Santos, L. M. M. Jorge

Abstract:

An industrial system for the production of white liquor of a paper industry, Klabin Paraná Papé is, formed by ten reactors was modeled, simulated, and analyzed. The developed model considered possible water losses by evaporation and reaction, in addition to variations in volumetric flow of lime mud across the reactors due to composition variations. The model predictions agreed well with the process measurements at the plant and the results showed that the slaking reaction is nearly complete at the third causticizing reactor, while causticizing ends by the seventh reactor. Water loss due to slaking reaction and evaporation occurs more pronouncedly in the slaking reaction than in the final causticizing reactors; nevertheless, the lime mud flow remains nearly constant across the reactors.

Keywords: causticizing, lime, prediction, process

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14193 Enhancement of Capacity in a MC-CDMA based Cognitive Radio Network Using Non-Cooperative Game Model

Authors: Kalyani Kulkarni, Bharat Chaudhari

Abstract:

This paper addresses the issue of resource allocation in the emerging cognitive technology. Focusing the quality of service (QoS) of primary users (PU), a novel method is proposed for the resource allocation of secondary users (SU). In this paper, we propose the unique utility function in the game theoretic model of Cognitive Radio which can be maximized to increase the capacity of the cognitive radio network (CRN) and to minimize the interference scenario. The utility function is formulated to cater the need of PUs by observing Signal to Noise ratio. The existence of Nash equilibrium is for the postulated game is established.

Keywords: cognitive networks, game theory, Nash equilibrium, resource allocation

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14192 Secure Cryptographic Operations on SIM Card for Mobile Financial Services

Authors: Kerem Ok, Serafettin Senturk, Serdar Aktas, Cem Cevikbas

Abstract:

Mobile technology is very popular nowadays and it provides a digital world where users can experience many value-added services. Service Providers are also eager to offer diverse value-added services to users such as digital identity, mobile financial services and so on. In this context, the security of data storage in smartphones and the security of communication between the smartphone and service provider are critical for the success of these services. In order to provide the required security functions, the SIM card is one acceptable alternative. Since SIM cards include a Secure Element, they are able to store sensitive data, create cryptographically secure keys, encrypt and decrypt data. In this paper, we design and implement a SIM and a smartphone framework that uses a SIM card for secure key generation, key storage, data encryption, data decryption and digital signing for mobile financial services. Our frameworks show that the SIM card can be used as a controlled Secure Element to provide required security functions for popular e-services such as mobile financial services.

Keywords: SIM card, mobile financial services, cryptography, secure data storage

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14191 Hybrid Seismic Energy Dissipation Devices Made of Viscoelastic Pad and Steel Plate

Authors: Jinkoo Kim, Minsung Kim

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This study develops a hybrid seismic energy dissipation device composed of a viscoelastic damper and a steel slit damper connected in parallel. A cyclic loading test is conducted on a test specimen to validate the seismic performance of the hybrid damper. Then a moment-framed model structure is designed without seismic load so that it is retrofitted with the hybrid dampers. The model structure is transformed into an equivalent simplified system to find out optimum story-wise damper distribution pattern using genetic algorithm. The effectiveness of the hybrid damper is investigated by fragility analysis and the life cycle cost evaluation of the structure with and without the dampers. The analysis results show that the model structure has reduced probability of reaching damage states, especially the complete damage state, after seismic retrofit. The expected damage cost and consequently the life cycle cost of the retrofitted structure turn out to be significantly small compared with those of the original structure. Acknowledgement: This research was supported by the Ministry of Trade, Industry and Energy (MOTIE) and Korea Institute for Advancement of Technology (KIAT) through the International Cooperative R & D program (N043100016).

Keywords: seismic retrofit, slit dampers, friction dampers, hybrid dampers

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14190 Bacteriophage Is a Novel Solution of Therapy Against S. aureus Having Multiple Drug Resistance

Authors: Sanjay Shukla, A. Nayak, R. K. Sharma, A. P. Singh, S. P. Tiwari

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Excessive use of antibiotics is a major problem in the treatment of wounds and other chronic infections, and antibiotic treatment is frequently non-curative, thus alternative treatment is necessary. Phage therapy is considered one of the most promising approaches to treat multi-drug resistant bacterial pathogens. Infections caused by Staphylococcus aureus are very efficiently controlled with phage cocktails, containing a different individual phages lysate infecting a majority of known pathogenic S. aureus strains. The aim of the present study was to evaluate the efficacy of a purified phage cocktail for prophylactic as well as therapeutic application in mouse model and in large animals with chronic septic infection of wounds. A total of 150 sewage samples were collected from various livestock farms. These samples were subjected for the isolation of bacteriophage by the double agar layer method. A total of 27 sewage samples showed plaque formation by producing lytic activity against S. aureus in the double agar overlay method out of 150 sewage samples. In TEM, recovered isolates of bacteriophages showed hexagonal structure with tail fiber. In the bacteriophage (ØVS) had an icosahedral symmetry with the head size 52.20 nm in diameter and long tail of 109 nm. Head and tail were held together by connector and can be classified as a member of the Myoviridae family under the order of Caudovirale. Recovered bacteriophage had shown the antibacterial activity against the S. aureus in vitro. Cocktail (ØVS1, ØVS5, ØVS9, and ØVS 27) of phage lysate were tested to know in vivo antibacterial activity as well as the safety profile. Result of mice experiment indicated that the bacteriophage lysate were very safe, did not show any appearance of abscess formation, which indicates its safety in living system. The mice were also prophylactically protected against S. aureus when administered with cocktail of bacteriophage lysate just before the administration of S. aureuswhich indicates that they are good prophylactic agent. The S. aureusinoculated mice were completely recovered by bacteriophage administration with 100% recovery, which was very good as compere to conventional therapy. In the present study, ten chronic cases of the wound were treated with phage lysate, and follow up of these cases was done regularly up to ten days (at 0, 5, and 10 d). The result indicated that the six cases out of ten showed complete recovery of wounds within 10 d. The efficacy of bacteriophage therapy was found to be 60% which was very good as compared to the conventional antibiotic therapy in chronic septic wounds infections. Thus, the application of lytic phage in single dose proved to be innovative and effective therapy for the treatment of septic chronic wounds.

Keywords: phage therapy, S aureus, antimicrobial resistance, lytic phage, and bacteriophage

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14189 Socio-Sensorial Assessment of Nursing Homes in Singapore: Towards Integrated Enabling Design

Authors: Zdravko Trivic, John Chye Fung, Ruzica Bozovic-Stamenovic

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Within the context of rapidly ageing population in Singapore and the pressing demands on both caregivers and care providers, an integrated approach to ageing-friendly and ability-sensitive enabling environment becomes an imperative. This particularly applies to nursing home environments and their immediate surroundings, as they are becoming one of the main available options of long-term care for many senior adults who are unable to age at home. Yet, despite the considerable efforts to break the still predominant clinical approach to eldercare and to introduce more home-like design and person-centric care model, nursing homes keep being stigmatised and perceived as not so desirable environments to grow old in. The challenges are further emphasised by the associated physical, sensorial, psychological and cognitive declines that are the common consequences of ageing. Such declines have an immense impact on almost all aspects of older adults’ daily functioning, including problems with mobility and spatial orientation, difficulties in communication, withdrawal from social interaction, higher level of depression and decreased sense of independence and autonomy. However, typical nursing home designs tend to neglect the full capacities of balanced and carefully integrated multisensory stimuli as active component of care and ability building. This paper outlines part of a larger multi-disciplinary study of six nursing homes in Singapore, with overarching objectives to create new models of supportive nursing home environments that go beyond the clinical care model and encourage community integration with the nursing home settings. The paper focuses on the largely neglected aspects of sensorial comfort and multi-sensorial properties of nursing homes, including both indoor and immediate outdoor spaces (boundaries). The objective was to investigate the sensory rhythms and explore their role in nursing home users’ daily routine and therapeutic capacities. Socio-sensory rhythms were captured and analysed through a combination of on-site sensory recordings of “objective” quantitative sensory data (air temperature and humidity, sound level and luminance) using multi-function environment meter, perceived experienced data, spatial mapping, first-person observations of nursing home users’ activity patterns, and interviews. This was done in addition to employment of available assessment tools, such as Wisconsin Person Directed Care assessment tool, Dementia Quality of Life [DQoL] instrument, and Resident Environment Impact Scale [REIS], as these tools address the issues of sensorial experience insufficiently and selectively. Key findings indicate varied levels of sensory comfort, as well as diversity, intensity, and customisation of multi-sensory conditions within different nursing home spaces. Sensory stimulation is typically concentrated in communal living areas of the nursing homes or in the areas that often provide controlled or limited access, including specifically designed sensory rooms and outdoor green spaces (gardens and terraces). Opportunities for sensory stimulation are particularly limited for bed-bound senior residents and within more functional areas, such as corridors. This suggests that the capacities of nursing home designs to provide more diverse and better integrated pleasant sensory conditions as integrated “therapeutic devices” to build nursing home residents’ physical and mental abilities, encourage activity and improve wellbeing are far from exhausted.

Keywords: ageing-supportive environment, enabling design, multi-sensory assessment, nursing home environment

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14188 Consumer Behaviour Model for Apparel E-Tailers Using Structural Equation Modelling

Authors: Halima Akhtar, Abhijeet Chandra

Abstract:

The paper attempts to analyze the factors that influence the Consumer Behavior to purchase apparel through the internet. The intentions to buy apparels online were based on in terms of user style, orientation, size and reputation of the merchant, social influence, perceived information utility, perceived ease of use, perceived pleasure and attractiveness and perceived trust and risk. The basic framework used was Technology acceptance model to explain apparels acceptance. A survey was conducted to gather the data from 200 people. The measures and hypotheses were analyzed using Correlation testing and would be further validated by the Structural Equation Modelling. The implications of the findings for theory and practice could be used by marketers of online apparel websites. Based on the values obtained, we can conclude that the factors such as social influence, Perceived information utility, attractiveness and trust influence the decision for a user to buy apparels online. The major factors which are found to influence an online apparel buying decision are ease of use, attractiveness that a website can offer and the trust factor which a user shares with the website.

Keywords: E-tailers, consumer behaviour, technology acceptance model, structural modelling

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14187 State Estimation of a Biotechnological Process Using Extended Kalman Filter and Particle Filter

Authors: R. Simutis, V. Galvanauskas, D. Levisauskas, J. Repsyte, V. Grincas

Abstract:

This paper deals with advanced state estimation algorithms for estimation of biomass concentration and specific growth rate in a typical fed-batch biotechnological process. This biotechnological process was represented by a nonlinear mass-balance based process model. Extended Kalman Filter (EKF) and Particle Filter (PF) was used to estimate the unmeasured state variables from oxygen uptake rate (OUR) and base consumption (BC) measurements. To obtain more general results, a simplified process model was involved in EKF and PF estimation algorithms. This model doesn’t require any special growth kinetic equations and could be applied for state estimation in various bioprocesses. The focus of this investigation was concentrated on the comparison of the estimation quality of the EKF and PF estimators by applying different measurement noises. The simulation results show that Particle Filter algorithm requires significantly more computation time for state estimation but gives lower estimation errors both for biomass concentration and specific growth rate. Also the tuning procedure for Particle Filter is simpler than for EKF. Consequently, Particle Filter should be preferred in real applications, especially for monitoring of industrial bioprocesses where the simplified implementation procedures are always desirable.

Keywords: biomass concentration, extended Kalman filter, particle filter, state estimation, specific growth rate

Procedia PDF Downloads 419
14186 Using Vulnerability to Reduce False Positive Rate in Intrusion Detection Systems

Authors: Nadjah Chergui, Narhimene Boustia

Abstract:

Intrusion Detection Systems are an essential tool for network security infrastructure. However, IDSs have a serious problem which is the generating of massive number of alerts, most of them are false positive ones which can hide true alerts and make the analyst confused to analyze the right alerts for report the true attacks. The purpose behind this paper is to present a formalism model to perform correlation engine by the reduction of false positive alerts basing on vulnerability contextual information. For that, we propose a formalism model based on non-monotonic JClassicδє description logic augmented with a default (δ) and an exception (є) operator that allows a dynamic inference according to contextual information.

Keywords: context, default, exception, vulnerability

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14185 Prediction of Deformations of Concrete Structures

Authors: A. Brahma

Abstract:

Drying is a phenomenon that accompanies the hardening of hydraulic materials. It can, if it is not prevented, lead to significant spontaneous dimensional variations, which the cracking is one of events. In this context, cracking promotes the transport of aggressive agents in the material, which can affect the durability of concrete structures. Drying shrinkage develops over a long period almost 30 years although most occurred during the first three years. Drying shrinkage stabilizes when the material is water balance with the external environment. The drying shrinkage of cementitious materials is due to the formation of capillary tensions in the pores of the material, which has the consequences of bringing the solid walls of each other. Knowledge of the shrinkage characteristics of concrete is a necessary starting point in the design of structures for crack control. Such knowledge will enable the designer to estimate the probable shrinkage movement in reinforced or prestressed concrete and the appropriate steps can be taken in design to accommodate this movement. This study is concerned the modelling of drying shrinkage of the hydraulic materials and the prediction of the rate of spontaneous deformations of hydraulic materials during hardening. The model developed takes in consideration the main factors affecting drying shrinkage. There was agreement between drying shrinkage predicted by the developed model and experimental results. In last we show that developed model describe the evolution of the drying shrinkage of high performances concretes correctly.

Keywords: drying, hydraulic concretes, shrinkage, modeling, prediction

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14184 The Impact of Artificial Intelligence on Spare Parts Technology

Authors: Amir Andria Gad Shehata

Abstract:

Minimizing the inventory cost, optimizing the inventory quantities, and increasing system operational availability are the main motivations to enhance forecasting demand of spare parts in a major power utility company in Medina. This paper reports in an effort made to optimize the orders quantities of spare parts by improving the method of forecasting the demand. The study focuses on equipment that has frequent spare parts purchase orders with uncertain demand. The pattern of the demand considers a lumpy pattern which makes conventional forecasting methods less effective. A comparison was made by benchmarking various methods of forecasting based on experts’ criteria to select the most suitable method for the case study. Three actual data sets were used to make the forecast in this case study. Two neural networks (NN) approaches were utilized and compared, namely long short-term memory (LSTM) and multilayer perceptron (MLP). The results as expected, showed that the NN models gave better results than traditional forecasting method (judgmental method). In addition, the LSTM model had a higher predictive accuracy than the MLP model.

Keywords: spare part, spare part inventory, inventory model, optimization, maintenanceneural network, LSTM, MLP, forecasting demand, inventory management

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14183 Computational Fluid Dynamics Simulation on Heat Transfer of Hot Air Bubble Injection into Water Column

Authors: Jae-Yeong Choi, Gyu-Mok Jeon, Jong-Chun Park, Yong-Jin Cho, Seok-Tae Yoon

Abstract:

When air flow is injected into water, bubbles are formed in various types inside the water pool along with the air flow rate. The bubbles are floated in equilibrium with forces such as buoyancy, surface tension and shear force. Single bubble generated at low flow rate maintains shape, but bubbles with high flow rate break up to make mixing and turbulence. In addition to this phenomenon, as the hot air bubbles are injected into the water, heat affects the interface of phases. Therefore, the main scope of the present work reveals how to proceed heat transfer between water and hot air bubbles injected into water. In the present study, a series of CFD simulation for the heat transfer of hot bubbles injected through a nozzle near the bottom in a cylindrical water column are performed using a commercial CFD software, STAR-CCM+. The governing equations for incompressible and viscous flow are the continuous and the RaNS (Reynolds- averaged Navier-Stokes) equations and discretized by the FVM (Finite Volume Method) manner. For solving multi-phase flow, the Eulerian multiphase model is employed and the interface is defined by VOF (Volume-of-Fluid) technique. As a turbulence model, the SST k-w model considering the buoyancy effects is introduced. For spatial differencing the 3th-order MUSCL scheme is adopted and the 2nd-order implicit scheme for time integration. As the results, the dynamic behavior of the rising hot bubbles with the flow rate injected and regarding heat transfer mechanism are discussed based on the simulation results.

Keywords: heat transfer, hot bubble injection, eulerian multiphase model, flow rate, CFD (Computational Fluid Dynamics)

Procedia PDF Downloads 147
14182 A Global Business Network Built on Hive: Two Use Cases: Buying and Selling of Products and Services and Carrying Out of Social Impact Projects

Authors: Gheyzer Villegas, Edgardo Cedeño, Veruska Mata, Edmundo Chauran

Abstract:

One of the most significant changes that occurred in global commerce was the emergence of cryptocurrencies and blockchain technology. There is still much debate about the adoption of the economic model based on crypto assets, and myriad international projects and initiatives are being carried out to try and explore the potential that this new field offers. The Hive blockchain is a prime example of this, featuring two use cases: of how trade based on its native currencies can give successful results in the exchange of goods and services and in the financing of social impact projects. Its decentralized management model and visionary administration of its development fund have become a key part of its success.

Keywords: Hive, business, network, blockchain

Procedia PDF Downloads 62
14181 Estimation of Snow and Ice Melt Contributions to Discharge from the Glacierized Hunza River Basin, Karakoram, Pakistan

Authors: Syed Hammad Ali, Rijan Bhakta Kayastha, Danial Hashmi, Richard Armstrong, Ahuti Shrestha, Iram Bano, Javed Hassan

Abstract:

This paper presents the results of a semi-distributed modified positive degree-day model (MPDDM) for estimating snow and ice melt contributions to discharge from the glacierized Hunza River basin, Pakistan. The model uses daily temperature data, daily precipitation data, and positive degree day factors for snow and ice melt. The model is calibrated for the period 1995-2001 and validated for 2002-2013, and demonstrates close agreements between observed and simulated discharge with Nash–Sutcliffe Efficiencies of 0.90 and 0.88, respectively. Furthermore, the Weather Research and Forecasting model projected temperature, and precipitation data from 2016-2050 are used for representative concentration pathways RCP4.5 and RCP8.5, and bias correction was done using a statistical approach for future discharge estimation. No drastic changes in future discharge are predicted for the emissions scenarios. The aggregate snow-ice melt contribution is 39% of total discharge in the period 1993-2013. Snow-ice melt contribution ranges from 35% to 63% during the high flow period (May to October), which constitutes 89% of annual discharge; in the low flow period (November to April) it ranges from 0.02% to 17%, which constitutes 11 % of the annual discharge. The snow-ice melt contribution to total discharge will increase gradually in the future and reach up to 45% in 2041-2050. From a sensitivity analysis, it is found that the combination of a 2°C temperature rise and 20% increase in precipitation shows a 10% increase in discharge. The study allows us to evaluate the impact of climate change in such basins and is also useful for the future prediction of discharge to define hydropower potential, inform other water resource management in the area, to understand future changes in snow-ice melt contribution to discharge, and offer a possible evaluation of future water quantity and availability.

Keywords: climate variability, future discharge projection, positive degree day, regional climate model, water resource management

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14180 Synthesis and Characterization of Ferromagnetic Ni-Cu Alloys for Thermal Rectification Applications

Authors: Josue Javier Martinez Flores, Jaime Alvarez Quintana

Abstract:

A thermal rectifier consists of a device which can load a different heat flow which depends on the direction of that flow. That device is a thermal diode. It is well known that heat transfer in solids basically depends on the electrical, magnetic and crystalline nature of materials via electrons, magnons and phonons as thermal energy carriers respectively. In the present research, we have synthesized polycrystalline Ni-Cu alloys and identified the Curie temperatures; and we have observed that by way of secondary phase transitions, it is possible manipulate the heat conduction in solid state thermal diodes via transition temperature. In this sense, we have succeeded in developing solid state thermal diodes with a control gate through the Curie temperature via the activation and deactivation of magnons in Ni-Cu ferromagnetic alloys at room temperature. Results show thermal diodes with thermal rectification factors up to 1.5. Besides, the performance of the electrical rectifiers can be controlled by way of alloy Cu content; hence, lower Cu content alloys present enhanced thermal rectifications factors than higher ones.

Keywords: thermal rectification, Curie temperature, ferromagnetic alloys, magnons

Procedia PDF Downloads 242