Search results for: circuit models

Authors: Nadarajah I. Ramesh

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Much of the research on stochastic point process models for rainfall has focused on Poisson cluster models constructed from either the Neyman-Scott or Bartlett-Lewis processes. The doubly stochastic Poisson process provides a rich class of point process models, especially for fine-scale rainfall modelling. This paper provides an account of recent development on this topic and presents the results based on some of the fine-scale rainfall models constructed from this class of stochastic point processes. Amongst the literature on stochastic models for rainfall, greater emphasis has been placed on modelling rainfall data recorded at hourly or daily aggregation levels. Stochastic models for sub-hourly rainfall are equally important, as there is a need to reproduce rainfall time series at fine temporal resolutions in some hydrological applications. For example, the study of climate change impacts on hydrology and water management initiatives requires the availability of data at fine temporal resolutions. One approach to generating such rainfall data relies on the combination of an hourly stochastic rainfall simulator, together with a disaggregator making use of downscaling techniques. Recent work on this topic adopted a different approach by developing specialist stochastic point process models for fine-scale rainfall aimed at generating synthetic precipitation time series directly from the proposed stochastic model. One strand of this approach focused on developing a class of doubly stochastic Poisson process (DSPP) models for fine-scale rainfall to analyse data collected in the form of rainfall bucket tip time series. In this context, the arrival pattern of rain gauge bucket tip times N(t) is viewed as a DSPP whose rate of occurrence varies according to an unobserved finite state irreducible Markov process X(t). Since the likelihood function of this process can be obtained, by conditioning on the underlying Markov process X(t), the models were fitted with maximum likelihood methods. The proposed models were applied directly to the raw data collected by tipping-bucket rain gauges, thus avoiding the need to convert tip-times to rainfall depths prior to fitting the models. One advantage of this approach was that the use of maximum likelihood methods enables a more straightforward estimation of parameter uncertainty and comparison of sub-models of interest. Another strand of this approach employed the DSPP model for the arrivals of rain cells and attached a pulse or a cluster of pulses to each rain cell. Different mechanisms for the pattern of the pulse process were used to construct variants of this model. We present the results of these models when they were fitted to hourly and sub-hourly rainfall data. The results of our analysis suggest that the proposed class of stochastic models is capable of reproducing the fine-scale structure of the rainfall process, and hence provides a useful tool in hydrological modelling.

Keywords: fine-scale rainfall, maximum likelihood, point process, stochastic model

Procedia PDF Downloads 257

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 116

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

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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

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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

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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

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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

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Authors: Juhi Faridi, Mohd. Ajmal Kafeel

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The advancements in the field of Artificial Intelligence (AI) and technology has led to an evolution of an intelligent era. Neural networks, having the computational power and learning ability similar to the brain is one of the key AI technologies. Neuromorphic computing system (NCS) consists of the synaptic device, neuronal circuit, and neuromorphic architecture. Memristor are a promising candidate for neuromorphic computing systems, but when it comes to neuromorphic computing, the conductance behavior of the synaptic memristor or neuronal memristor needs to be studied thoroughly in order to fathom the neuroscience or computer science. Furthermore, there is a need of more simulation work for utilizing the existing device properties and providing guidance to the development of future devices for different performance requirements. Hence, development of NCS needs more simulation work to make use of existing device properties. This work aims to provide an insight to build neuronal circuits using memristors to achieve a Memristor based NCS.  Here we throw a light on the research conducted in the field of memristors for building analog and digital circuits in order to motivate the research in the field of NCS by building memristor based neural circuits for advanced AI applications. This literature is a step in the direction where we describe the various Key findings about memristors and its analog and digital circuits implemented over the years which can be further utilized in implementing the neuronal circuits in the NCS. This work aims to help the electronic circuit designers to understand how the research progressed in memristors and how these findings can be used in implementing the neuronal circuits meant for the recent progress in the NCS.

Keywords: analog circuits, digital circuits, memristors, neuromorphic computing systems

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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

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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

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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: 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

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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 596

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

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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 248

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 171

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

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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

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Authors: Daniel José de Oliveira Ferreira, Juan Harold Sosa-Arnao, Bruno Cássio Moreira, Leonardo Paes Rangel, Song Won Park

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The comprehensive CFD models have been used to represent and study the heterogeneous combustion of biomass. In the present work, the operation of a global flue gas circuit in the sugar-cane bagasse combustion, from wind boxes below primary air grate supply, passing by bagasse insertion in swirl burners and boiler furnace, to boiler bank outlet is simulated. It uses five different meshes representing each part of this system located in sequence: wind boxes and grate, boiler furnace, swirl burners, super heaters and boiler bank. The model considers turbulence using standard k-ε, combustion using EDM, radiation heat transfer using DTM with 16 ray directions and bagasse particle tracking represented by Schiller-Naumann model. The results showed good agreement with expected behavior found in literature and equipment design. The more detailed results view in separated parts of flue gas system allows to observe some flow behaviors that cannot be represented by usual simplifications like bagasse supply under homogeneous axial and rotational vectors and others that can be represented using new considerations like the representation of 26 thousand grate orifices by 144 rectangular inlets.

Keywords: comprehensive CFD model, sugar-cane bagasse combustion, sugar-cane bagasse grate boiler, axial

Procedia PDF Downloads 448

Authors: Eko Adhi Setiawan, Duli Asih Siregar, Aiman Setiawan

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Solar energy is abundant in nature, particularly in the tropics which have peak sun hour that can reach 8 hours per day. In the fabrication process, Photovoltaic’s (PV) performance are tested in standard test conditions (STC). It specifies a module temperature of 25°C, an irradiance of 1000 W/ m² with an air mass 1.5 (AM1.5) spectrum and zero wind speed. Thus, the results of the performance testing of PV at STC conditions cannot fully represent the performance of PV in the tropics. For example Indonesia, which has a temperature of 20-40°C. In this paper, the effect of temperature on the choice of the 5 kW AC inverter topology on the PV system such as the Central Inverter, String Inverter and AC-Module specifically for the tropics will be discussed. The proper inverter topology can be determined by analysis of the effect of temperature and irradiation on the PV panel. The effect of temperature and irradiation will be represented in the characteristics of I-V and P-V curves. PV’s characteristics on high temperature would be analyzed using Solar panel modeling through MATLAB Simulink based on mathematical equations that form Solar panel’s characteristic curve. Based on PV simulation, it is known then that temperature coefficients of short circuit current (ISC), open circuit voltage (VOC), and maximum output power (PMAX) consecutively as high as 0.56%/oC, -0.31%/oC and -0.4%/oC. Those coefficients can be used to calculate PV’s electrical parameters such as ISC, VOC, and PMAX in certain earth’s surface’s certain point. Then, from the parameters, the utility of the 5 kW AC inverter system can be determined. As the result, for tropical area, string inverter topology has the highest utility rates with 98, 80 %. On the other hand, central inverter and AC-Module Topology has utility rates of 92.69 % and 87.7 % eventually.

Keywords: Photovoltaic, PV-Inverter Configuration, PV Modeling, Solar Panel Characteristics.

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Authors: Pavel E. Mikriukov

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The demand for natural gas (NG) is increasing every year around the world, so it is necessary to produce and transport NG in large quantities. To solve this problem, liquefied natural gas (LNG) plants are used, using different equipment and different technologies to achieve the required LNG quality. To determine the best efficiency of the LNG liquefaction plant, it is necessary to analyze the equipment used in this process and identify other technological solutions for LNG production using more productive and energy-efficient equipment. Based on this, mathematical models of the technological process of the LNG plant were created, which are based on a two-circuit system of heat exchange equipment and a nitrogen isolated cycle for NG cooling. The final liquefaction of natural gas is performed on the construction of the basic principle of the Joule-Thompson effect. The pressure and temperature drop are considered on different types of equipment such as throttle valve, which was used in the basic scheme; turbo expander and supersonic separator, which act as new equipment, to be compared with the efficiency of the basic scheme of the unit. New configurations of LNG plants are suggested, which can be used in almost all LNG facilities. As a result of the analysis, it turned out that the turbo expander and the supersonic separator have comparatively equal potential in comparison with the baseline scheme execution on the throttle valve. A more rational method of selecting the technology and the equipment used for natural gas liquefaction can improve the efficiency of low-tonnage plants and reduce the cost of gas for own needs.

Keywords: gas liquefaction, gas, Joule-Thompson effect, LNG, low-tonnage LNG, supersonic separator, Throttle valve, turbo expander

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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: Misuk Kim, Seokho Kang, Jehyuk Lee, Hyunchang Cho, Sungzoon Cho

Abstract:

In semiconductor manufacturing, virtual metrology (VM) refers to methods to predict properties of a wafer based on machine parameters and sensor data of the production equipment, without performing the (costly) physical measurement of the wafer properties (Wikipedia). Additional benefits include avoidance of human bias and identification of important factors affecting the quality of the process which allow improving the process quality in the future. It is however rare to find VM applied to other areas of manufacturing. In this work, we propose to use VM to copper clad laminate (CCL) manufacturing. CCL is a core element of a printed circuit board (PCB) which is used in smartphones, tablets, digital cameras, and laptop computers. The manufacturing of CCL consists of three processes: Treating, lay-up, and pressing. Treating, the most important process among the three, puts resin on glass cloth, heat up in a drying oven, then produces prepreg for lay-up process. In this process, three important quality factors are inspected: Treated weight (T/W), Minimum Viscosity (M/V), and Gel Time (G/T). They are manually inspected, incurring heavy cost in terms of time and money, which makes it a good candidate for VM application. We developed prediction models of the three quality factors T/W, M/V, and G/T, respectively, with process variables, raw material, and environment variables. The actual process data was obtained from a CCL manufacturer. A variety of variable selection methods and learning algorithms were employed to find the best prediction model. We obtained prediction models of M/V and G/T with a high enough accuracy. They also provided us with information on “important” predictor variables, some of which the process engineers had been already aware and the rest of which they had not. They were quite excited to find new insights that the model revealed and set out to do further analysis on them to gain process control implications. T/W did not turn out to be possible to predict with a reasonable accuracy with given factors. The very fact indicates that the factors currently monitored may not affect T/W, thus an effort has to be made to find other factors which are not currently monitored in order to understand the process better and improve the quality of it. In conclusion, VM application to CCL’s treating process was quite successful. The newly built quality prediction model allowed one to reduce the cost associated with actual metrology as well as reveal some insights on the factors affecting the important quality factors and on the level of our less than perfect understanding of the treating process.

Keywords: copper clad laminate, predictive modeling, quality control, virtual metrology

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

Abstract:

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: Elif Aykin Dincer, Mustafa Erbas

Abstract:

The vacuum drying behavior of beef slices (10 x 4 x 0.2 cm3) was experimentally investigated at the temperature of 60, 70, and 80°C under 25 mbar ultimate vacuum pressure and the mathematical models (Lewis, Page, Midilli, Two-term, Wangh and Singh and Modified Henderson and Pabis) were used to fit the vacuum drying of beef slices. The increase in drying air temperature resulted in a decrease in drying time. It took approximately 206, 180 and 157 min to dry beef slices from an initial moisture content to a final moisture content of 0.05 kg water/kg dry matter at 60, 70 and 80 °C of vacuum drying, respectively. It is also observed that the drying rate increased with increasing drying temperature. The coefficients (R2), the reduced chi-square (x²) and root mean square error (RMSE) values were obtained by application of six models to the experimental drying data. The best model with the highest R2 and, the lowest x² and RMSE values was selected to describe the drying characteristics of beef slices. The Page model has shown a better fit to the experimental drying data as compared to other models. In addition, the effective moisture diffusivities of beef slices in the vacuum drying at 60 - 80 °C varied in the range of 1.05 – 1.09 x 10-10 m2/s. Consequently, this results can be used to simulate vacuum drying process of beef slices and improve efficiency of the drying process.

Keywords: beef slice, drying models, effective diffusivity, vacuum

Procedia PDF Downloads 273

Authors: Tohid Rahimi, Yahya Naderi, Babak Yousefi, Seyed Hossein Hoseini

Abstract:

Today’s modern interconnected power system is highly complex in nature. In this, one of the most important requirements during the operation of the electric power system is the reliability and security. Power and frequency oscillation damping mechanism improve the reliability. Because of power system stabilizer (PSS) low speed response against of major fault such as three phase short circuit, FACTs devise that can control the network condition in very fast time, are becoming popular. However, FACTs capability can be seen in a major fault present when nonlinear models of FACTs devise and power system equipment are applied. To realize this aim, the model of multi-machine power system with FACTs controller is developed in MATLAB/SIMULINK using Sim Power System (SPS) blockiest. Among the FACTs device, Static synchronous series compensator (SSSC) due to high speed changes its reactance characteristic inductive to capacitive, is effective power flow controller. Tuning process of controller parameter can be performed using different method. However, Genetic Algorithm (GA) ability tends to use it in controller parameter tuning process. In this paper, firstly POD controller is used to power oscillation damping. But in this station, frequency oscillation dos not has proper damping situation. Therefore, FOD controller that is tuned using GA is using that cause to damp out frequency oscillation properly and power oscillation damping has suitable situation.

Keywords: power oscillation damping (POD), frequency oscillation damping (FOD), Static synchronous series compensator (SSSC), Genetic Algorithm (GA)

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Authors: Alemaw Kefale, Aramde Fetene, Hayal Desta

Abstract:

This study analyzed the users' and experts' views on the green space quality and planning models in Debre Berhan (DB) and Debre Markos (DM) cities in Ethiopia. A questionnaire survey was conducted on 350 park users (148 from DB and 202 from DM) to rate the accessibility, size, shape, vegetation cover, social and cultural context, conservation and heritage, community participation, attractiveness, comfort, safety, inclusiveness, and maintenance of green spaces using a Likert scale. A key informant interview was held with 13 experts in DB and 12 in DM. Descriptive statistics and tests of independence of variables using the chi-square test were done. A statistically significant association existed between the perception of green space quality attributes and users' occupation (χ² (160, N = 350) = 224.463, p < 0.001), age (χ² (128, N = 350) = 212.812, p < 0.001), gender (χ² (32, N = 350) = 68.443, p < 0.001), and education level (χ² (192, N = 350) = 293.396, p < 0.001). 61.7 % of park users were unsatisfied with the quality of urban green spaces. The users perceived dense vegetation cover as "good," with a mean value of 3.41, while the remaining were perceived as "medium with a mean value of 2.62 – 3.32". Only quantitative space standards are practiced as a green space planning model, while other models are unfamiliar and never used in either city. Therefore, experts need to be aware of and practice urban green models during urban planning to ensure that new developments include green spaces to accommodate the community's and the environment's needs.

Keywords: urban green space, quality, users and experts, green space planning models, Ethiopia

Procedia PDF Downloads 36