Search results for: gaussian mixture models

Authors: Osayande Pascal Omondiagbe, Sherlock a Licorish

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Stack Overflow is a popular community question and answer portal which is used by practitioners to solve technology-related challenges during software development. Previous studies have shown that this forum is becoming a substitute for official software programming languages documentation. While tools have looked to aid developers by presenting interfaces to explore Stack Overflow, developers often face challenges searching through many possible answers to their questions, and this extends the development time. To this end, researchers have provided ways of predicting acceptable Stack Overflow answers by using various modeling techniques. However, less interest is dedicated to examining the performance and quality of typically used modeling methods, and especially in relation to models’ and features’ complexity. Such insights could be of practical significance to the many practitioners that use Stack Overflow. This study examines the performance and quality of various modeling methods that are used for predicting acceptable answers on Stack Overflow, drawn from 2014, 2015 and 2016. Our findings reveal significant differences in models’ performance and quality given the type of features and complexity of models used. Researchers examining classifiers’ performance and quality and features’ complexity may leverage these findings in selecting suitable techniques when developing prediction models.

Keywords: feature selection, modeling and prediction, neural network, random forest, stack overflow

Procedia PDF Downloads 118

Authors: Nieto Bernal Wilson, Carmona Suarez Edgar

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The organizations have structured and unstructured information in different formats, sources, and systems. Part of these come from ERP under OLTP processing that support the information system, however these organizations in OLAP processing level, presented some deficiencies, part of this problematic lies in that does not exist interesting into extract knowledge from their data sources, as also the absence of operational capabilities to tackle with these kind of projects.  Data Warehouse and its applications are considered as non-proprietary tools, which are of great interest to business intelligence, since they are repositories basis for creating models or patterns (behavior of customers, suppliers, products, social networks and genomics) and facilitate corporate decision making and research. The following paper present a structured methodology, simple, inspired from the agile development models as Scrum, XP and AUP. Also the models object relational, spatial data models, and the base line of data modeling under UML and Big data, from this way sought to deliver an agile methodology for the developing of data warehouses, simple and of easy application. The methodology naturally take into account the application of process for the respectively information analysis, visualization and data mining, particularly for patterns generation and derived models from the objects facts structured.

Keywords: data warehouse, model data, big data, object fact, object relational fact, process developed data warehouse

Procedia PDF Downloads 390

Authors: Sudipta Ghorai, Ossama Salem

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Pavement maintenance, repair, and rehabilitation (MRR) processes may have considerable environmental impacts due to traffic disruptions associated with work zones. The simulation models in use to predict the emission of work zones were mostly static emission factor models (SEFD). SEFD calculates emissions based on average operation conditions e.g. average speed and type of vehicles. Although these models produce accurate results for large-scale planning studies, they are not suitable for analyzing driving conditions at the micro level such as acceleration, deceleration, idling, cruising, and queuing in a work zone. The purpose of this study is to prepare a comprehensive work zone environmental assessment (WEA) framework to calculate the emissions caused due to disrupted traffic; by integrating traffic microsimulation tools with emission models. This will help highway officials to assess the benefits of accelerated construction and opt for the most suitable TMP not only economically but also from an environmental point of view.

Keywords: accelerated construction, pavement MRR, traffic microsimulation, congestion, emissions

Procedia PDF Downloads 434

Authors: Min Kyung An

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In Wireless Sensor Networks which consist of tiny wireless sensor nodes with limited battery power, one of the most fundamental applications is data aggregation which collects nearby environmental conditions and aggregates the data to a designated destination, called a sink node. Important issues concerning the data aggregation are time efficiency and energy consumption due to its limited energy, and therefore, the related problem, named Minimum Latency Aggregation Scheduling (MLAS), has been the focus of many researchers. Its objective is to compute the minimum latency schedule, that is, to compute a schedule with the minimum number of timeslots, such that the sink node can receive the aggregated data from all the other nodes without any collision or interference. For the problem, the two interference models, the graph model and the more realistic physical interference model known as Signal-to-Interference-Noise-Ratio (SINR), have been adopted with different power models, uniform-power and non-uniform power (with power control or without power control), and different antenna models, omni-directional antenna and directional antenna models. In this survey article, as the problem has proven to be NP-hard, we present and compare several state-of-the-art approximation algorithms in various models on the basis of latency as its performance measure.

Keywords: data aggregation, convergecast, gathering, approximation, interference, omni-directional, directional

Procedia PDF Downloads 209

Authors: Hamed K. Esfahani, Bithin Datta

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Transport of reactive chemical contaminant species in groundwater aquifers is a complex and highly non-linear physical and geochemical process especially for real life scenarios. Simulating this transport process involves solving complex nonlinear equations and generally requires huge computational time for a given aquifer study area. Development of optimal remediation strategies in aquifers may require repeated solution of such complex numerical simulation models. To overcome this computational limitation and improve the computational feasibility of large number of repeated simulations, Genetic Programming based trained surrogate models are developed to approximately simulate such complex transport processes. Transport process of acid mine drainage, a hazardous pollutant is first simulated using a numerical simulated model: HYDROGEOCHEM 5.0 for a contaminated aquifer in a historic mine site. Simulation model solution results for an illustrative contaminated aquifer site is then approximated by training and testing a Genetic Programming (GP) based surrogate model. Performance evaluation of the ensemble GP models as surrogate models for the reactive species transport in groundwater demonstrates the feasibility of its use and the associated computational advantages. The results show the efficiency and feasibility of using ensemble GP surrogate models as approximate simulators of complex hydrogeologic and geochemical processes in a contaminated groundwater aquifer incorporating uncertainties in historic mine site.

Keywords: geochemical transport simulation, acid mine drainage, surrogate models, ensemble genetic programming, contaminated aquifers, mine sites

Procedia PDF Downloads 258

Authors: Michalis Linardakis, Vasilis Grammatikopoulos, Athanasios Gregoriadis, Kalliopi Trouli

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Discrete choice models belong to the family of Conjoint analysis that are applied on the preferences of the respondents towards a set of scenarios that describe alternative choices. The scenarios have been pre-designed to cover all the attributes of the alternatives that may affect the choices. In this study, we examine how preschool educators integrate physical activities into their everyday teaching practices through the use of discrete choice models. One of the advantages of discrete choice models compared to other more traditional data collection methods (e.g. questionnaires and interviews that use ratings) is that the respondent is called to select among competitive and realistic alternatives, rather than objectively rate each attribute that the alternatives may have. We present the effort to construct and choose representative attributes that would cover all possible choices of the respondents, and the scenarios that have arisen. For the purposes of the study, we used a sample of 50 preschool educators in Greece that responded to 4 scenarios (from the total of 16 scenarios that the orthogonal design resulted), with each scenario having three alternative teaching practices. Seven attributes of the alternatives were used in the scenarios. For the analysis of the data, we used multinomial logit model with random effects, multinomial probit model and generalized mixed logit model. The conclusions drawn from the estimated parameters of the models are discussed.

Keywords: conjoint analysis, discrete choice models, educational data, multivariate statistical analysis

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Authors: N. Sopipan

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In this paper, we study of rainfall time series of weather stations in Nakhon Ratchasima province in Thailand using various statistical methods enabled to analyse the behaviour of rainfall in the study areas. Time-series analysis is an important tool in modelling and forecasting rainfall. ARIMA and Holt-Winter models based on exponential smoothing were built. All the models proved to be adequate. Therefore, could give information that can help decision makers establish strategies for proper planning of agriculture, drainage system and other water resource applications in Nakhon Ratchasima province. We found the best perform for forecasting is ARIMA(1,0,1)(1,0,1)12.

Keywords: ARIMA Models, exponential smoothing, Holt-Winter model

Procedia PDF Downloads 283

Authors: Keneilwe Maremi, Marlien Herselman, Adele Botha

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The main purpose and focus of this paper are to determine the Interoperability Maturity Models to consider when using School Management Systems (SMS). The importance of this is to inform and help schools with knowing which Interoperability Maturity Model is best suited for their SMS. To address the purpose, this paper will apply a scoping review to ensure that all aspects are provided. The scoping review will include papers written from 2012-2019 and a comparison of the different types of Interoperability Maturity Models will be discussed in detail, which includes the background information, the levels of interoperability, and area for consideration in each Maturity Model. The literature was obtained from the following databases: IEEE Xplore and Scopus, the following search engines were used: Harzings, and Google Scholar. The topic of the paper was used as a search term for the literature and the term ‘Interoperability Maturity Models’ was used as a keyword. The data were analyzed in terms of the definition of Interoperability, Interoperability Maturity Models, and levels of interoperability. The results provide a table that shows the focus area of concern for each Maturity Model (based on the scoping review where only 24 papers were found to be best suited for the paper out of 740 publications initially identified in the field). This resulted in the most discussed Interoperability Maturity Model for consideration (Information Systems Interoperability Maturity Model (ISIMM) and Organizational Interoperability Maturity Model for C2 (OIM)).

Keywords: interoperability, interoperability maturity model, school management system, scoping review

Procedia PDF Downloads 183

Authors: Ivan Župan

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Critical infrastructure is essential for the functioning of a country and is designated for special protection by governments worldwide. Due to the increase in smart technology usage in every facet of the industry, including critical infrastructure, the exposure to malicious cyber-physical attacks has grown in the last few years. Proper security measures must be undertaken in order to defend against cyber-physical threats that can disrupt the normal functioning of critical infrastructure and, consequently the functioning of the country. This paper provides a review of the scientific literature of models, methods and technologies used to protect from cyber-physical threats in industries. The focus of the literature was observed from three aspects. The first aspect, resilience, concerns itself with the robustness of the system’s defense against threats, as well as preparation and education about potential future threats. The second aspect concerns security risk management for systems with cyber-physical aspects, and the third aspect investigates available testbed environments for testing developed models on scaled models of vulnerable infrastructure.

Keywords: critical infrastructure, cyber-physical security, smart industry, security methodology, security technology

Procedia PDF Downloads 57

Authors: Yasser Gaber, Mohamed Ismail, Serena Bisagni, Mohamad Takwa, Rajni Hatti-Kaul

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Enzymes are safe and selective catalysts. They skillfully catalyze chemical reactions; however, the native form is not usually suitable for industrial applications. Enzymes are therefore engineered by several techniques to meet the required catalytic task. Clopidogrel is recorded among the five best selling pharmaceutical in 2010 under the brand name Plavix. The commonly used route for production of the drug on an industrial scale is the synthesis of the racemic mixture followed by diastereomeric resolution to obtain the pure S isomer. The process consumes a lot of solvents and chemicals. We have evaluated a biocatalytic cleaner approach for asymmetric hydrolysis of racemic clopidogrel. Initial screening of a selected number of hydrolases showed only one enzyme EST to exhibit activity and selectivity towards the desired stereoisomer. As the crude EST is a mixture of several isoenzymes, a homology model of EST-1 was used in molecular dynamic simulations to study the interaction of the enzyme with R and S isomers of clopidogrel. Analysis of the geometric hindrances of the tetrahedral intermediates revealed a potential site for mutagenesis in order to improve the activity and the selectivity. Single point mutation showed dramatic increase in activity and inversion of the enantioselectivity (400 fold change in E value).

Keywords: biocatalysis, biotechnology, enzyme, protein engineering, molecular modeling

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Authors: Ali Hesari, Arezoo Esmaeeli

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Regarding to dramatic changes of fertility and higher order births during recent decades in Iran, access to knowledge about affecting factors on different birth orders has crucial importance. In this study, According to hierarchical structure of many of social sciences data and the effect of variables of different levels of social phenomena that determine different birth orders in 365 days ending to 1390 census have been explored by multilevel approach. In this paper, 2% individual row data for 1390 census is analyzed by HLM software. Three different hierarchical linear regression models are estimated for data analysis of the first and second, third, fourth and more birth order. Research results displays different outcomes for three models. Individual level variables entered in equation are; region of residence (rural/urban), age, educational level and labor participation status and province level variable is GDP per capita. Results show that individual level variables have different effects in these three models and in second level we have different random and fixed effects in these models.

Keywords: fertility, birth order, hierarchical approach, fixe effects, random effects

Procedia PDF Downloads 323

Authors: Ehsan Eshtehardian, Saeed Khodaverdi

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This paper surveys the studies on construction change and reveals some of the potential future works. A full-scale investigation of change literature, including change definitions, types, causes and effects, and change management systems, is accomplished to explore some of the coming change trends. It is tried to pick up the critical works in each section to deduct a true timeline of construction changes. The findings show that leaping from best practice guides in late 1990s and generic process models in the early 2000s to very advanced modeling environments in the mid-2000s and the early 2010s have made gaps along with opportunities for change researchers in order to develop some more easy and applicable models. Another finding is that there is a compelling similarity between the change and risk prediction models. Therefore, integrating these two concepts, specifically from proactive management point of view, may lead to a synergy and help project teams avoid rework. Also, the findings show that exploitation of cause-effect relationship models, in order to facilitate the dispute resolutions, seems to be an interesting field for future works.

Keywords: construction change, change management systems, dispute resolutions, change literature

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Authors: Yang Gon Seo, Chang-Joon Kim, Dae Hyeok Kim

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It is estimated that 1.5 billion tires are produced worldwide each year which will eventually end up as waste tires representing a major potential waste and environmental problem. Pyrolysis has been great interest in alternative treatment processes for waste tires to produce valuable oil, gas and solid products. The oil and gas products may be used directly as a fuel or a chemical feedstock. The solid produced from the pyrolysis of tires ranges typically from 30 to 45 wt% and have high carbon contents of up to 90 wt%. However, most notably the solid have high sulfur contents from 2 to 3 wt% and ash contents from 8 to 15 wt% related to the additive metals. Upgrading tire pyrolysis products to high-value products has concentrated on solid upgrading to higher quality carbon black and to activated carbon. Hydrogen sulfide and ammonia are one of the common malodorous compounds that can be found in emissions from many sewages treatment plants and industrial plants. Therefore, removing these harmful gasses from emissions is of significance in both life and industry because they can cause health problems to human and detrimental effects on the catalysts. In this work, pyrolytic carbon black from waste tires was used to develop adsorbent with good adsorption capacity for removal of hydrogen and ammonia. Pyrolytic carbon blacks were prepared by pyrolysis of waste tire chips ranged from 5 to 20 mm under the nitrogen atmosphere at 600℃ for 1 hour. Pellet-type adsorbents were prepared by a mixture of carbon black, metal oxide and sodium hydroxide or hydrochloric acid, and their adsorption capacities were estimated by using the breakthrough curve of a continuous fixed bed adsorption column at ambient condition. The adsorbent was manufactured with a mixture of carbon black, iron oxide(III), and sodium hydroxide showed the maximum working capacity of hydrogen sulfide. For ammonia, maximum working capacity was obtained by the adsorbent manufactured with a mixture of carbon black, copper oxide(II), and hydrochloric acid.

Keywords: adsorbent, ammonia, pyrolytic carbon black, hydrogen sulfide, metal oxide

Procedia PDF Downloads 242

Authors: Suren Chilingaryan

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We study two models describing a single two-level system coupled to two boson field modes in either a parallel or orthogonal setup. Both models may be feasible for experimental realization through Raman adiabatic driving in cavity QED. We study their ground state configurations; that is, we find the quantum precursors of the corresponding semi-classical phase transitions. We found that the ground state configurations of both models present the same critical coupling as the quantum Rabi model. Around this critical coupling, the ground state goes from the so-called normal configuration with no excitation, the qubit in the ground state and the fields in the quantum vacuum state, to a ground state with excitations, the qubit in a superposition of ground and excited state, while the fields are not in the vacuum anymore, for the first model. The second model shows a more complex ground state configuration landscape where we find the normal configuration mentioned above, two single-mode configurations, where just one of the fields and the qubit are excited, and a dual-mode configuration, where both fields and the qubit are excited.

Keywords: quantum optics, quantum phase transition, cavity QED, circuit QED

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Authors: Salah Alrabeei, Mohammad Yousuf

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The goal of option pricing theory is to help the investors to manage their money, enhance returns and control their financial future by theoretically valuing their options. However, most of the option pricing models have no analytical solution. Furthermore, not all the numerical methods are efficient to solve these models because they have nonsmoothing payoffs or discontinuous derivatives at the exercise price. In this paper, we solve the American option under jump diffusion models by using efficient time-dependent numerical methods. several techniques are integrated to reduced the overcome the computational complexity. Fast Fourier Transform (FFT) algorithm is used as a matrix-vector multiplication solver, which reduces the complexity from O(M2) into O(M logM). Partial fraction decomposition technique is applied to rational approximation schemes to overcome the complexity of inverting polynomial of matrices. The proposed method is easy to implement on serial or parallel versions. Numerical results are presented to prove the accuracy and efficiency of the proposed method.

Keywords: integral differential equations, jump–diffusion model, American options, rational approximation

Procedia PDF Downloads 100

Authors: Reza Pourjafar, Morteza Sohrabi-Gilani, Mostafa Jamshidi Avanaki, Malek Mohammad Ranjbar

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Cementitious composites like concrete, are the most widely used materials in civil infrastructures. Numerous investigations on fiber’s effect on the properties of cement-based composites have been conducted in the last few decades. The use of fibers such as carbon nanofibers (CNFs) and carbon nanotubes (CNTs) in these materials is an ongoing field and needs further researches and studies. Excellent mechanical, thermal, and electrical properties of carbon nanotubes and nanofibers have motivated the development of advanced nanocomposites with outstanding and multifunctional properties. In this study, the electrical resistance of CNF reinforced cement mortar was examined. Three different dosages of CNF were used, and the resistances were compared to plain cement mortar. One of the biggest challenges in this study is dispersing CNF particles in the mortar mixture. Therefore, polycarboxylate superplasticizer and ultrasonication of the mixture have been selected for the purpose of dispersing CNFs in the cement matrix. The obtained results indicated that the electrical resistance of the CNF reinforced mortar samples decreases with increasing CNF content, which would be the first step towards examining strain and damage monitoring ability of cementitious composites containing CNF for structural health monitoring purposes.

Keywords: carbon nanofiber, cement and concrete, CNF reinforced mortar, smart mater, strain monitoring, structural health monitoring

Procedia PDF Downloads 126

Authors: Hany Mohamed Abdu, Mohamed Hassan Gadallah, El-Giushi Mokhtar, Yehia Mahmoud Ismail

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Laser beam cutting is one nontraditional machining process. This paper optimizes the parameters of Laser beam cutting machining parameters of Stainless steel (316L) by considering the effect of input parameters viz. power, oxygen pressure, frequency and cutting speed. Statistical design of experiments are carried in three different levels and process responses such as 'Average kerf taper (Ta)' and 'Surface Roughness (Ra)' are measured accordingly. A quadratic mathematical model (RSM) for each of the responses is developed as a function of the process parameters. Responses predicted by the models (as per Taguchi’s L27 OA) are employed to search for an optimal parametric combination to achieve desired yield of the process. RSM models are developed for mean responses, S/N ratio, and standard deviation of responses. Optimization models are formulated as single objective problem subject to process constraints. Models are formulated based on Analysis of Variance (ANOVA) using MATLAB environment. Optimum solutions are compared with Taguchi Methodology results.

Keywords: optimization, laser cutting, robust design, kerf width, Taguchi method, RSM and DOE

Procedia PDF Downloads 598

Authors: D. S. C. Soares, D. G. Costa, J. T. S., A. K. S. Abud, T. P. Nunes, A. M. Oliveira Júnior

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Mathematical models of drying are used for the purpose of understanding the drying process in order to determine important parameters for design and operation of the dryer. The jackfruit is a fruit with high consumption in the Northeast and perishability. It is necessary to apply techniques to improve their conservation for longer in order to diffuse it by regions with low consumption. This study aimed to analyse several mathematical models (Page, Lewis, and Midilli) to indicate one that best fits the conditions of convective drying process using performance indicators associated with each model: accuracy (Af) and noise factors (Bf), mean square error (RMSE) and standard error of prediction (% SEP). Jackfruit drying was carried out in convective type tray dryer at a temperature of 50°C for 9 hours. It is observed that the model Midili was more accurate with Af: 1.39, Bf: 1.33, RMSE: 0.01%, and SEP: 5.34. However, the use of the Model Midilli is not appropriate for purposes of control process due to need four tuning parameters. With the performance indicators used in this paper, the Page model showed similar results with only two parameters. It is concluded that the best correlation between the experimental and estimated data is given by the Page’s model.

Keywords: drying, models, jackfruit, biotechnology

Procedia PDF Downloads 364

Authors: T. Y. Liu, C. H. Lin, Y. M. Ferng

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Wind energy is one of the clean renewable energy. However, the low frequency (20-200HZ) noise generated from the wind turbine blades, which bothers the residents, becomes the major problem to be developed. It is useful for predicting the aerodynamic noise by flow field and pressure distribution analysis on the wind turbine blades. Therefore, the main objective of this study is to use different turbulence models to analyse the flow field and pressure distributions of the wing blades. Three-dimensional Computation Fluid Dynamics (CFD) simulation of the flow field was used to calculate the flow phenomena for the National Renewable Energy Laboratory (NREL) Phase VI horizontal axis wind turbine rotor. Two different flow cases with different wind speeds were investigated: 7m/s with 72rpm and 15m/s with 72rpm. Four kinds of RANS-based turbulence models, Standard k-ε, Realizable k-ε, SST k-ω, and v2f, were used to predict and analyse the results in the present work. The results show that the predictions on pressure distributions with SST k-ω and v2f turbulence models have good agreements with experimental data.

Keywords: horizontal axis wind turbine, turbulence model, noise, fluid dynamics

Procedia PDF Downloads 249

Authors: Abdellatif Chebboub

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Agricultural production is sensitive to weather and thus directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments in yields, area, consumption, and international trade. We apply biophysical shocks derived from the Intergovernmental Panel on Climate Change’s representative concentration pathway with end-of-century radiative forcing of 8.5 W/m2. The mean biophysical yield effect with no incremental CO2 fertilization is a 17% reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11%, increase area of major crops by 11%, and reduce consumption by 3%. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences include model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change.

Keywords: climate change, agriculture, weather change, danger of climate change

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Authors: Ferhat Demir

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Even if strategic management is highly critical for all types of organizations, only a few maturity models have been proposed in business literature for the area of strategic management activities. This paper updates previous studies and presents a new conceptual model for assessing the maturity of strategic management in any organization. Strategic management maturity model (S-3M) is basically composed of 6 maturity levels with 7 dimensions. The biggest contribution of S-3M is to put innovation into agenda of strategic management. The main objective of this study is to propose a model to align innovation with business strategies. This paper suggests that innovation (breakthrough new products/services and business models) is the only way of creating sustainable growth and strategy studies cannot ignore this aspect. Maturity models should embrace innovation to respond dynamic business environment and rapidly changing customer behaviours.

Keywords: strategic management, innovation, business model, maturity model

Procedia PDF Downloads 172

Authors: Leah Lee

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This paper examines the correlation between deep learning models and emotions with noises to see whether or not noises mask emotions. The deep learning models used are plain convolutional neural networks (CNN), auto-encoder, long short-term memory (LSTM), and Visual Geometry Group-16 (VGG-16). Emotion datasets used are Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS), Crowd-sourced Emotional Multimodal Actors Dataset (CREMA-D), Toronto Emotional Speech Set (TESS), and Surrey Audio-Visual Expressed Emotion (SAVEE). To make it four times bigger, audio set files, stretch, and pitch augmentations are utilized. From the augmented datasets, five different features are extracted for inputs of the models. There are eight different emotions to be classified. Noise variations are white noise, dog barking, and cough sounds. The variation in the signal-to-noise ratio (SNR) is 0, 20, and 40. In summation, per a deep learning model, nine different sets with noise and SNR variations and just augmented audio files without any noises will be used in the experiment. To compare the results of the deep learning models, the accuracy and receiver operating characteristic (ROC) are checked.

Keywords: auto-encoder, convolutional neural networks, long short-term memory, speech emotion recognition, visual geometry group-16

Procedia PDF Downloads 55

Authors: Dev Ras Pandey, Bharat Mishra, S. K. Tripathi

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Cloud computing is ready to transform the structure of businesses and learning through supplying the real-time applications and provide an immediate help for small to medium sized businesses. The ability to run a hypervisor inside a virtual machine is important feature of virtualization and it is called nested virtualization. In today’s growing field of information technology, many of the virtualization models are available, that provide a convenient approach to implement, but decision for a single model selection is difficult. This paper explains the applications of operating system based virtualization in cloud computing with an appropriate/suitable model with their different specifications and user’s requirements. In the present paper, most popular models are selected, and the selection was based on container and hypervisor based virtualization. Selected models were compared with a wide range of user’s requirements as number of CPUs, memory size, nested virtualization supports, live migration and commercial supports, etc. and we identified a most suitable model of virtualization.

Keywords: virtualization, OS based virtualization, container based virtualization, hypervisor based virtualization

Procedia PDF Downloads 290

Authors: Juan M. Rodriguez-Diaz

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The precision of parameter estimators in the Gaussian linear model is traditionally accounted by the variance-covariance matrix of the asymptotic distribution. However, this measure can underestimate the true variance, specially for small samples. Traditionally, optimal design theory pays attention to this variance through its relationship with the model's information matrix. For this reason it seems convenient, at least in some cases, adapt the optimality criteria in order to get the best designs for the actual variance structure, otherwise the loss in efficiency of the designs obtained with the traditional approach may be very important.

Keywords: correlated observations, information matrix, optimality criteria, variance-covariance matrix

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Authors: S. Belhour, A. K. Ferouani, C. Azizi

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In recent years, a considerable effort (experience, numerical simulation, and theoretical prediction models) has characterised by high efficiency and low cost. Then an improved physics analytical model for simulating is proposed. The performance of GaAs MESFETs has been developed for use in device design for high frequency. This model is based on mathematical analysis, and a new approach for the standard model is proposed, this approach allowed to conceive applicable model for MESFET’s operating in the turn-one or pinch-off region and valid for the short-channel and the long channel MESFET’s in which the two dimensional potential distribution contributed by the depletion layer under the gate is obtained by conventional approximation. More ever, comparisons between the analytical models with different values of mobility are proposed, and a good agreement is obtained.

Keywords: analytical, gallium arsenide, MESFET, mobility, models

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Authors: Mst. Tuhin Akter, Sharun Akter Khushbu, S. M. Shaqib

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A real-time system architecture is highly effective for monitoring and detecting various damaged products or fruits that may deteriorate over time or become infected with diseases. Deep learning models have proven to be effective in building such architectures. However, building a deep learning model from scratch is a time-consuming and costly process. A more efficient solution is to utilize deep neural network (DNN) based transfer learning models in the real-time monitoring architecture. This study focuses on using a novel strawberry dataset to develop effective transfer learning models for the proposed real-time monitoring system architecture, specifically for evaluating and detecting strawberry freshness. Several state-of-the-art transfer learning models were employed, and the best performing model was found to be Xception, demonstrating higher performance across evaluation metrics such as accuracy, recall, precision, and F1-score.

Keywords: strawberry freshness evaluation, deep neural network, transfer learning, image augmentation

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Authors: Mohammad Ahmad, Sander Gersen, Erwin Wilbers

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Carbon capture, transport and underground storage have become a major solution to reduce CO2 emissions from power plants and other large CO2 sources. A big part of this captured CO2 stream is transported at high pressure dense phase conditions and stored in offshore underground depleted oil and gas fields. CO2 is also transported in offshore pipelines to be used for enhanced oil and gas recovery. The captured CO2 stream with impurities may contain water that causes severe corrosion problems, flow assurance failure and might damage valves and instrumentations. Thus, free water formation should be strictly prevented. The purpose of this work is to study the solubility of water in pure CO2 and in CO2 mixtures under real pipeline pressure (90-150 bar) and temperature operation conditions (5-35°C). A set up was constructed to generate experimental data. The results show the solubility of water in CO2 mixtures increasing with the increase of the temperature or/and with the increase in pressure. A drop in water solubility in CO2 is observed in the presence of impurities. The data generated were then used to assess the capabilities of two mixture models: the GERG-2008 model and the EOS-CG model. By generating the solubility data, this study contributes to determine the maximum allowable water content in CO2 pipelines.

Keywords: carbon capture and storage, water solubility, equation of states, fluids engineering

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Authors: J. Alvarez Muñoz, Dominguez Lepe J. A.

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A suitable mixing time of the concrete, allows form a homogeneous mass, quality that leads to greater compressive strength and durability. Although there are recommendations as ASTM C94 standard these mention the time and the number of minimum and maximum speed for a ready-mix concrete of good quality, the specific behavior that would have a concrete mixed on site to variability of the mixing time is unknown. In this study was evaluated the behavior a design of mixture structural of f´c=250 kg/cm2, elaborate on site with limestone aggregate in warm sub-humid climate, subjected to different mixing times. Based on the recommendation for ready-mixed concrete ASTM C94, different times were set at 70, 90, 100, 110, 120, 140 total revolutions. A field study in which 14 works were observed where structural concrete made on site was used, allowed to set at 24 the number of revolutions to the reference mixture. For the production of concrete was used a hand feed concrete mixer with drum speed 28 RPM, the ratio w/c was 0.36 corrected, with a slump of 5-6 cm, for all mixtures. The compressive strength tests were performed at 3, 7, 14, and 28 days. The most outstanding results show increases in resistance in the mixtures of 24 to 70 revolutions between 8 and 17 percent and 70 to 90 revolutions of 3 to 8 percent. Increasing the number of revolutions at 110, 120 and 140, there was a reduction of the compressive strength of 0.5 to 8 percent. Regarding mixtures consistencies, they had a slump of 5 cm to 24, 70 and 90 rpm and less than 5 cm from 100 revolutions. Clearly, those made with more than 100 revolutions mixtures not only decrease the compressive strength but also the workability.

Keywords: compressive strength, concrete, mixing time, workability

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Authors: Duduku Krishnaiah, S. M. Anisuzzaman, Kumaran Govindaraj, Chiam Chel Ken, Zykamilia Kamin

Abstract:

Pure essential oil is highly demanded in the market since most of the so-called pure essential oils in the market contains alcohol. This is because of the usage of alcohol in separating oil and water mixture. Removal of pure essential oil from water without using any chemical solvent has become a challenging issue. Adsorbents generally have the properties of separating hydrophobic oil from hydrophilic mixture. Polypropylen nanofiber is a thermoplastic polymer which is produced from propylene. It was used as an adsorbent in this study. Based on the research, it was found that the polypropylene nanofiber was able to adsorb peppermint oil from the aqueous solution over a wide range of concentration. Based on scanning electron microscope (SEM), nanofiber has very small nano diameter fiber size in average before the adsorption and larger scaled average diameter of fibers after adsorption which indicates that smaller diameter of nanofiber enhances the adsorption process. The adsorption capacity of peppermint oil increases as the initial concentration of peppermint oil and amount of polypropylene nanofiber used increases. The maximum adsorption capacity of polypropylene nanofiber was found to be 689.5 mg/g at (T= 30°C). Moreover, the adsorption capacity of peppermint oil decreases as the temperature of solution increases. The equilibrium data of polypropylene nanofiber is best represented by Freundlich isotherm with the maximum adsorption capacity of 689.5 mg/g. The adsorption kinetics of polypropylene nanofiber was best represented by pseudo-second order model.

Keywords: nanofiber, adsorption, peppermint essential oil, isotherms, adsorption kinetics

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Authors: Bahdja Guerfi, N. Hadhoum, I. Azouz, M. Bendoumia, S. Bouafia, F. Z. Hadjadj Aoul

Abstract:

Background: 'Penicillin V' is a narrow, bactericidal antibiotic of the beta-lactam family of the naturally occurring penicillin group. It is limited to infections due to the germs defined as sensitive. The objective of this work was to identify and to characterize Penicillin V acid and its related compounds by High-performance liquid chromatography (HPLC). Methods: Firstly phenoxymethylpenicillin was identified by an infrared absorption. The organoleptic characteristics, pH, and determination of water content were also studied. The dosage of Penicillin V acid active substance and the determination of its related compounds were carried on waters HPLC, equipped with a UV detector at 254 nm and Discovery HS C18 column (250 mm X 4.6 mm X 5 µm) which is maintained at room temperature. The flow rate was about 1 ml per min. A mixture of water, acetonitrile and acetic acid (65:35:01) was used as mobile phase for phenoxyacetic acid ‘impurity B' and a mixture of water, acetonitrile and acetic acid (650:150:5.75) for the assay and 4-hydroxypenicillin V 'impurity D'. Results: The identification of Penicillin V acid active substance and the evaluation of its chemical quality showed conformity with USP 35th edition. The Penicillin V acid content in the raw material is equal to 1692.22 UI/mg. The percentage content of phenoxyacetic acid and 4-hydroxypenicillin V was respectively: 0.035% and 0.323%. Conclusion: Through these results, we can conclude that the Penicillin V acid active substance tested is of good physicochemical quality.

Keywords: characterization, HPLC, Penicillin V acid, related substances

Procedia PDF Downloads 265