Search results for: adaptive thermal comfort model

Authors: V. Rashtchi, H. Bizhani, F. R. Tatari

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This paper presents a new online loss minimization for an induction motor drive. Among the many loss minimization algorithms (LMAs) for an induction motor, a particle swarm optimization (PSO) has the advantages of fast response and high accuracy. However, the performance of the PSO and other optimization algorithms depend on the accuracy of the modeling of the motor drive and losses. In the development of the loss model, there is always a trade off between accuracy and complexity. This paper presents a new online optimization to determine an optimum flux level for the efficiency optimization of the vector-controlled induction motor drive. An induction motor (IM) model in d-q coordinates is referenced to the rotor magnetizing current. This transformation results in no leakage inductance on the rotor side, thus the decomposition into d-q components in the steady-state motor model can be utilized in deriving the motor loss model. The suggested algorithm is simple for implementation.

Keywords: induction machine, loss minimization, magnetizing current, particle swarm optimization

Procedia PDF Downloads 629

Authors: Nader Khalafian, Mohsen Ghaderi

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Field observations have revealed many examples of structures which were damaged due to ground surface deformation caused by the faulting phenomena. In this paper some efforts were made in order to estimate the length and location of the ground surface where large displacements were created due to the reverse faulting. This research has conducted in two steps; (1) in the first step, a 2D explicit finite element model were developed using ABAQUS software. A subroutine for Mohr-Coulomb failure criterion with strain softening model was developed by the authors in order to properly model the stress strain behavior of the soil in the fault rapture zone. The results of the numerical analysis were verified with the results of available centrifuge experiments. Reasonable coincidence was found between the numerical and experimental data. (2) In the second step, the effects of the fault dip angle (δ), depth of soil layer (H), dilation and friction angle of sand (ψ and φ) and the amount of fault offset (d) on the soil surface displacement and fault rupture path were investigated. An artificial neural network-based model (ANN), as a powerful prediction tool, was developed to generate a general model for predicting faulting characteristics. A properly sized database was created to train and test network. It was found that the length and location of the zone of displaced ground surface can be accurately estimated using the proposed model.

Keywords: reverse faulting, surface deformation, numerical, neural network

Procedia PDF Downloads 420

Authors: Vidula Shevade, B. J. Nagare, Sajeev Chacko

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First principles simulation, meaning density functional theory (DFT) calculations with plane waves and pseudopotential, has become a prized technique in condensed matter theory. Nanoparticles (NP) have been known to possess good catalytic activities, especially for molecules such as CO, O₂, etc. Among the metal NPs, Aluminium based NPs are also widely known for their catalytic properties. Aluminium metal is a lightweight, excellent electrical, and thermal abundant chemical element in the earth’s crust. Aluminium NPs, when added to solid rocket fuel, help improve the combustion speed and considerably increase combustion heat and combustion stability. Adding aluminium NPs into normal Al/Al₂O₃ powder improves the sintering processes of the ceramics, with high heat transfer performance, increased density, and enhanced thermal conductivity of the sinter. We used VASP and Gaussian 0₃ package to compute the geometries, electronic structure, and bonding properties of Al₁₂Ni as well as its interaction with O₂ and CO molecules. Several MD simulations were carried out using VASP at various temperatures from which hundreds of structures were optimized, leading to 24 unique structures. These structures were then further optimized through a Gaussian package. The lowest energy structure of Al₁₂Ni has been reported to be a singlet. However, through our extensive search, we found a triplet state to be lower in energy. In our structure, the Ni atom is found to be on the surface, which gives the non-zero magnetic moment. Incidentally, O2 and CO molecules are also triplet in nature, due to which the Al₁₂-Ni cluster is likely to facilitate the oxidation process of the CO molecule. Our results show that the most favourable site for the CO molecule is the Ni atom and that for the O₂ molecule is the Al atom that is nearest to the Ni atom. Al₁₂Ni-O₂ and Al₁₂-Ni-CO structures we extracted using VMD. Al₁₂Ni nanocluster, due to in triplet electronic structure configuration, indicates it to be a potential candidate as a catalyst for oxidation of CO molecules.

Keywords: catalyst, gaussian, nanoparticles, oxidation

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Authors: A. M. John-Otumu, M. M. Rahman, M. C. Onuoha, E. P. Ojonugwa

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A Convolutional Neural Network (CNN) model for predicting Lassa fever was built using Python 3.8.0 programming language, alongside Keras 2.2.4 and TensorFlow 2.6.1 libraries as the development environment in order to reduce the current high risk of Lassa fever in West Africa, particularly in Nigeria. The study was prompted by some major flaws in existing conventional laboratory equipment for diagnosing Lassa fever (RT-PCR), as well as flaws in AI-based techniques that have been used for probing and prognosis of Lassa fever based on literature. There were 15,679 blood smear microscopic image datasets collected in total. The proposed model was trained on 70% of the dataset and tested on 30% of the microscopic images in avoid overfitting. A 3x3x3 convolution filter was also used in the proposed system to extract features from microscopic images. The proposed CNN-based model had a recall value of 96%, a precision value of 93%, an F1 score of 95%, and an accuracy of 94% in predicting and accurately classifying the images into clean or infected samples. Based on empirical evidence from the results of the literature consulted, the proposed model outperformed other existing AI-based techniques evaluated. If properly deployed, the model will assist physicians, medical laboratory scientists, and patients in making accurate diagnoses for Lassa fever cases, allowing the mortality rate due to the Lassa fever virus to be reduced through sound decision-making.

Keywords: artificial intelligence, ANN, blood smear, CNN, deep learning, Lassa fever

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Authors: Amgad A. Farghal, Dina I. El Desouki

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Energy consumption and users’ satisfaction were compared in three LEED certified office buildings in turkey and an office building in Egypt. The field studies were conducted in summer 2012. The measured environmental parameters in the four buildings were indoor air temperature, relative humidity, CO2 percentage and light intensity. The traditional building is located in Smart Village in Abu Rawash, Cairo, Egypt. The building was studied for 7 days resulting in 84 responds. The three rated buildings are in Istanbul; Turkey. A Platinum LEED certified office building is owned by BASF and gained a platinum certificate for new construction and major renovation. The building was studied for 3 days resulting in 13 responds. A Gold LEED certified office building is owned by BASF and gained a gold certificate for new construction and major renovation. The building was studied for 2 days resulting in 10 responds. A silver LEED certified office building is owned by Unilever and gained a silver certificate for commercial interiors. The building was studied for 7 days resulting in 84 responds. The results showed that all buildings had no significant difference regarding occupants’ satisfaction with the amount of lighting, noise level, odor and access to the outdoor view. There was significant difference between occupants’ satisfaction in LEED certified buildings and the traditional building regarding the thermal environment and the perception of the general environment (colors, carpet and decoration. The findings suggest that careful design could lead to a certified building that enhances the thermal environment and the perception of the indoor environment leading to energy consumption without scarifying occupants’ satisfaction.

Keywords: energy consumption, occupants’ satisfaction, rating systems, office buildings

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Authors: Malihe Motiei, Nor Hidayati Zakaria, Davide Aloini

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This study aims to present a method to develop the failure measurement model for ERP post-implementation. To achieve this outcome, the study firstly evaluates the suitability of Technology-Organization-Environment framework for the proposed conceptual model. This study explains how to discover the constructs and subsequently to design and evaluate the constructs as formative or reflective. Constructs are used including reflective and purely formative. Then, the risk dimensions are investigated to determine the instruments to examine the impact of risk on ERP failure after implementation. Two construct as formative constructs consist inadequate implementation and poor organizational decision making. Subsequently six construct as reflective construct include technical risks, operational risks, managerial risks, top management risks, lack of external risks, and user’s inefficiency risks. A survey was conducted among Iranian industries to collect data. 69 data were collected from manufacturing sectors and the data were analyzed by Smart PLS software. The results indicated that all measurements included 39 critical risk factors were acceptable for the ERP post-implementation failure model.

Keywords: critical risk factors (CRFs), ERP projects, ERP post-implementation, measurement instruments, ERP system failure measurement model

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Authors: Lakhoua Najeh

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Aims of the work: After a presentation of the functionality of an example of a mechatronic system which is a paint mixer system, we present the concepts of modeling and safe operation. This paper briefly discusses how to model and protect the functioning of a mechatronic system relying mainly on functional analysis and safe operation techniques. Methods: For the study of an example of a mechatronic system, we use methods for external functional analysis that illustrate the relationships between a mechatronic system and its external environment. Thus, we present the Safe-Structured Analysis Design Technique method (Safe-SADT) which allows the representation of a mechatronic system. A model of operating safety and automation is proposed. This model enables us to use a functional analysis technique of the mechatronic system based on the GRAFCET (Graphe Fonctionnel de Commande des Etapes et Transitions: Step Transition Function Chart) method; study of the safe operation of the mechatronic system based on the Safe-SADT method; automation of the mechatronic system based on a software tool. Results: The expected results are to propose a model and safe operation of a mechatronic system. This methodology enables us to analyze the relevance of the different models based on Safe-SADT and GRAFCET in relation to the control and monitoring functions and to study the means allowing exploiting their synergy. Conclusion: In order to propose a general model of a mechatronic system, a model of analysis, safety operation and automation of a mechatronic system has been developed. This is how we propose to validate this methodology through a case study of a paint mixer system.

Keywords: mechatronic systems, system modeling, safe operation, Safe-SADT

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Authors: Makram Ben Jeddou

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The ABC classification is widely used by managers for inventory control. The classical ABC classification is based on the Pareto principle and according to the criterion of the annual use value only. Single criterion classification is often insufficient for a closely inventory control. Multi-criteria inventory classification models have been proposed by researchers in order to take into account other important criteria. From these models, we will consider the ZF model in order to make a sensitive analysis on the composite score calculated for each item. In fact, this score based on a normalized average between a good and a bad optimized index can affect the ABC items classification. We will then focus on the weights assigned to each index and propose a classification compromise.

Keywords: ABC classification, multi criteria inventory classification models, ZF-model

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Authors: Ozlem Uguz, Ali Demirci, Hanzade Haykiri-Acma, Serdar Yaman

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Lignitic coal holds its position as Turkey’s most important indigenous energy source to generate energy in thermal power plants. Hence, efficient and environmental-friendly use of lignite in electricity generation is of great importance. Thus, clean coal technologies have been planned to mitigate emissions and provide more efficient burning in power plants. In this context, oxygen enriched combustion (oxy-combustion) is regarded as one of the clean coal technologies, which based on burning with oxygen concentrations higher than that in air. As it is known that the most of the Turkish coals are low rank with high mineral matter content, unburnt carbon trapped in ash is, unfortunately, high, and it leads significant losses in the overall efficiencies of the thermal plants. Besides, the necessity of burning huge amounts of these low calorific value lignites to get the desired amount of energy also results in the formation of large amounts of ash that is rich in unburnt carbon. Oxygen enriched combustion technology enables to increase the burning efficiency through the complete burning of almost all of the carbon content of the fuel. This also contributes to the protection of air quality and emission levels drop reasonably. The aim of this study is to investigate the unburnt carbon content and the burning reactivities of several different lignite samples under oxygen enriched conditions. For this reason, the combined effects of temperature and oxygen/nitrogen ratios in the burning atmosphere were investigated and interpreted. To do this, Turkish lignite samples from Adıyaman-Gölbaşı and Kütahya-Tunçbilek regions were characterized first by proximate and ultimate analyses and the burning profiles were derived using DTA (Differential Thermal Analysis) curves. Then, these lignites were subjected to slow burning process in a horizontal tube furnace at different temperatures (200ºC, 400ºC, 600ºC for Adıyaman-Gölbaşı lignite and 200ºC, 450ºC, 800ºC for Kütahya-Tunçbilek lignite) under atmospheres having O₂+N₂ proportions of 21%O₂+79%N₂, 30%O₂+70%N₂, 40%O₂+60%N₂, and 50%O₂+50%N₂. These burning temperatures were specified based on the burning profiles derived from the DTA curves. The residues obtained from these burning tests were also analyzed by proximate and ultimate analyses to detect the unburnt carbon content along with the unused energy potential. Reactivity of these lignites was calculated using several methodologies. Burning yield under air condition (21%O₂+79%N₂) was used a benchmark value to compare the effectiveness of oxygen enriched conditions. It was concluded that oxygen enriched combustion method enhanced the combustion efficiency and lowered the unburnt carbon content of ash. Combustion of low-rank coals under oxygen enriched conditions was found to be a promising way to improve the efficiency of the lignite-firing energy systems. However, cost-benefit analysis should be considered for a better justification of this method since the use of more oxygen brings an unignorable additional cost.

Keywords: coal, energy, oxygen enriched combustion, reactivity

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Authors: Arjun Paul, Adrijit Goswami

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In our present work, an economic order quantity inventory model with shortages is developed where holding cost is expressed as linearly increasing function of time and demand rate is a ramp type function of time. The items considered in the model are deteriorating in nature so that a small fraction of the items is depleted with the passage of time. In order to consider a more realistic situation, the deterioration rate is assumed to follow a continuous uniform distribution with the parameters involved being triangular fuzzy numbers. The inventory manager offers his customer a discount in case he is willing to backorder his demand when there is a stock-out. The optimum ordering policy and the optimum discount offered for each backorder are determined by minimizing the total cost in a replenishment interval. For better illustration of our proposed model in both the crisp and fuzzy sense and for providing richer insights, a numerical example is cited to exemplify the policy and to analyze the sensitivity of the model parameters.

Keywords: fuzzy deterioration rate, price discount on backorder, ramp type demand, shortage, time varying holding cost

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Authors: Palanisamy Samyraj, Sriram Yogesh, Kishore Kumar, Vaishak Cibi

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The project is about design and analysis of crankshaft using Al-Al2O3 composite material. The project is mainly concentrated across two areas one is to design and analyze the composite material, and the other is to work on the practical model. Growing competition and the growing concern for the environment has forced the automobile manufactures to meet conflicting demands such as increased power and performance, lower fuel consumption, lower pollution emission and decrease noise and vibration. Metal matrix composites offer good properties for a number of automotive components. The work reports on studies on Al-Al2O3 as the possible alternative material for a crank shaft. These material have been considered for use in various components in engines due to the high amount of strength to weight ratio. These materials are significantly taken into account for their light weight, high strength, high specific modulus, low co-efficient of thermal expansion, good air resistance properties. In addition high specific stiffness, superior high temperature, mechanical properties and oxidation resistance of Al2O3 have developed some advanced materials that are Al-Al2O3 composites. Crankshafts are used in automobile industries. Crankshaft is connected to the connecting rod for the movement of the piston which is subjected to high stresses which cause the wear of the crankshaft. Hence using composite material in crankshaft gives good fuel efficiency, low manufacturing cost, less weight.

Keywords: metal matrix composites, Al-Al2O3, high specific modulus, strength to weight ratio

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Authors: Arash Gharibi

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Mankind has always used models to solve problems. Essentially, models are simplified versions of reality, whose need stems from having to deal with complexity; many processes or phenomena are too complex to be described completely. Thus a fundamental model requirement is that it contains the characteristic features that are essential in the context of the problem to be solved or described. Models are used in virtually every scientific domain to deal with various problems. During the recent decades, the number of models has increased exponentially. Publication of models as part of original research has traditionally been in in scientific periodicals, series, monographs, agency reports, national journals and laboratory reports. This makes it difficult for interested groups and communities to stay informed about the state-of-the-art. During the modeling process, many important decisions are made which impact the final form of the model. Without a record of these considerations, the final model remains ill-defined and open to varying interpretations. Unfortunately, the details of these considerations are often lost or in case there is any existing information about a model, it is likely to be written intuitively in different layouts and in different degrees of detail. In order to overcome these issues, different domains have attempted to implement their own approaches to preserve their models’ information in forms of model documentation. The most frequently cited model documentation approaches show that they are domain specific, not to applicable to the existing models and evolutionary flexibility and intrinsic corrections and improvements are not possible with the current approaches. These issues are all because of a lack of unified standards for model documentation. As a way forward, this research will propose a new standard for capturing and managing models’ information in a unified way so that interoperability and reusability of models become possible. This standard will also be evolutionary, meaning members of modeling realm could contribute to its ongoing developments and improvements. In this paper, the current 3 of the most common metamodels are reviewed and according to pros and cons of each, a new metamodel is proposed.

Keywords: metamodel, modeling, interoperability, reuse

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Authors: Ahmed H. Amer, A. Amar, Sh. Hamada, I. I. Bondouk, F. A. El-Hussiny

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Elastic scattering of α-particles from 9Be and 11B nuclei at different alpha energies have been analyzed. Optical model parameters (OMPs) of α-particles elastic scattering by these nuclei at different energies have been obtained. In the present calculations, the real part of the optical potential are derived by folding of nucleon-nucleon (NN) interaction into nuclear matter density distribution of the projectile and target nuclei using computer code FRESCO. A density-dependent version of the M3Y interaction (CDM3Y6), which is based on the G-matrix elements of the Paris NN potential, has been used. Volumetric integrals of the real and imaginary potential depth (JR, JW) have been calculated and found to be energy dependent. Good agreement between the experimental data and the theoretical predictions in the whole angular range. In double folding (DF) calculations, the obtained normalization coefficient Nr is in the range 0.70–1.32.

Keywords: elastic scattering, optical model, double folding model, density distribution

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Authors: O. Behar, A. Khellaf, K. Mohammedi, S. Ait Kaci

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Up to now, most validation studies have been based on the MBE and RMSE, and therefore, focused only on long and short terms performance to test and classify solar radiation models. This traditional analysis does not take into account the quality of modeling and linearity. In our analysis we have tested 22 solar radiation models that are capable to provide instantaneous direct and global radiation at any given location Worldwide. We introduce a new indicator, which we named Global Accuracy Indicator (GAI) to examine the linear relationship between the measured and predicted values and the quality of modeling in addition to long and short terms performance. Note that the quality of model has been represented by the T-Statistical test, the model linearity has been given by the correlation coefficient and the long and short term performance have been respectively known by the MBE and RMSE. An important founding of this research is that the use GAI allows avoiding default validation when using traditional methodology that might results in erroneous prediction of solar power conversion systems performances.

Keywords: solar radiation model, parametric model, performance analysis, Global Accuracy Indicator (GAI)

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Authors: Dzhavidan Zeinalov, Bugra Sen, Firangiz Aslanova

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Most text-to-speech models cannot operate well in low-resource languages and require a great amount of high-quality training data to be considered good enough. Yet, with the improvements made in ASR systems, it is now much easier than ever to collect data for the design of custom text-to-speech models. In this work, our work on using the ASR model to collect data to build a viable text-to-speech system for one of the leading financial institutions of Azerbaijan will be outlined. NVIDIA’s implementation of the Tacotron 2 model was utilized along with the HiFiGAN vocoder. As for the training, the model was first trained with high-quality audio data collected from the Internet, then fine-tuned on the bank’s single speaker call center data. The results were then evaluated by 50 different listeners and got a mean opinion score of 4.17, displaying that our method is indeed viable. With this, we have successfully designed the first text-to-speech model in Azerbaijani and publicly shared 12 hours of audiobook data for everyone to use.

Keywords: Azerbaijani language, HiFiGAN, Tacotron 2, text-to-speech, transfer learning, whisper

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Authors: Angela Luft, Sebastian Bremen, Nicolae Balc

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Additive manufacturing processes have entered large parts of the industry and their range of application have progressed and grown significantly in the course of time. A major advantage of additive manufacturing is the innate flexibility of the machines. This corelates with the ongoing demand of creating highly flexible production environments. However, the potential of additive manufacturing technologies to enhance the flexibility of production systems has not yet been truly considered and quantified in a systematic way. In order to determine the potential of additive manufacturing technologies with regards to the strategic flexibility design in production systems, an integrated evaluation model has been developed, that allows for the simultaneous consideration of both conventional as well as additive production resources. With the described model, an operational scope of action can be identified and quantified in terms of mix and volume flexibility, process complexity, and machine capacity that goes beyond the current cost-oriented approaches and offers a much broader and more holistic view on the potential of additive manufacturing. A respective evaluation model is presented this paper.

Keywords: additive manufacturing, capacity planning, production systems, strategic production planning, flexibility enhancement

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Authors: Prateek Sharma, Venkata Ramachandrarao Maddali, Kapil Kukreja, B. N. Mohapatra

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Waste management is one of the pressing issues of India. Several initiatives by the Indian Government, including the recent one “Swachhata hi Seva” campaign launched by Prime Minister on 15th August 2018, can be one of the game changers to waste disposal. Under this initiative, the government, cement industry and other stakeholders are working hand in hand to dispose of single-use plastics in cement plants in rotary kilns. This is an exemplary effort and a move that establishes the Indian Cement industry as one of the key players in a circular economy. One of the cement plants in Southern India has been mandated by the state government to co-process shredded plastic and refuse-derived fuel (RDF) available in nearby regions as an alternative fuel in their cement plant. The plant has set a target of 25 % thermal substitution rate (TSR) by RDF in the next five years. Most of the cement plants in India and abroad have achieved high TSR through pre calciner firing. But the cement plant doesn’t have the precalciner and has to achieve this daunting task of 25 % TSR by firing through the main kiln burner. Since RDF is a heterogeneous waste with the change in fuel quality, it is difficult to achieve this task; hence plant has to resort to firing some portion of RDF/plastics at kiln inlet. But kiln inlet has reducing conditions as observed during measurements) under baseline condition. The combustion behavior of RDF of different sizes at different firing locations in riser was studied with the help of a computational fluid dynamics tool. It has been concluded that RDF above 50 mm size results in incomplete combustion leading to CO formation. Moreover, best firing location appears to be in the bottom portion of the kiln riser.

Keywords: kiln inlet, plastics, refuse derived fuel, thermal substitution rate

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Authors: Motalleb Byzedi, Seyedeh Chaman Naderi Korvandan

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Regarding annual statistics of groundwater level resources about current piezometers at Qorveh plains, both ARMA & PARMA modeling methods were applied in this study by the using of SAMS software. Upon performing required tests, a model was used with minimum amount of Akaike information criteria and suitable model was selected for piezometers. Then it was possible to make necessary estimations by using these models for future fluctuations in each piezometer. According to the results, ARMA model had more facilities for modeling of aquifer. Also it was cleared that eastern parts of aquifer had more failures than other parts. Therefore it is necessary to prohibit critical parts along with more supervision on taking rates of wells.

Keywords: qorveh plain, groundwater level, ARMA, PARMA

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Authors: Sami Mestiri, Abdeljelil Farhat

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The aim of this current paper is to predict the credit risk of banks in Tunisia, over the period (2000-2005). For this purpose, two methods for the estimation of the logistic regression model with random effects: Penalized Quasi Likelihood (PQL) method and Gibbs Sampler algorithm are applied. By using the information on a sample of 528 Tunisian firms and 26 financial ratios, we show that Bayesian approach improves the quality of model predictions in terms of good classification as well as by the ROC curve result.

Keywords: forecasting, credit risk, Penalized Quasi Likelihood, Gibbs Sampler, logistic regression with random effects, curve ROC

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Authors: Yi Wang, Xun Liang

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This paper introduces a model of internet public opinion waves, which describes the message propagation and measures the influence of a detected event. We collect data on public opinion propagation from different platforms on the internet, including micro-blogs and news. Then, we compare the spread of public opinion to the seismic waves and correspondently define the P-wave and S-wave and other essential attributes and characteristics in the process. Further, a model is established to evaluate the magnitude scale of the events. In the end, a practical example is used to analyze the influence of network public opinion and test the reasonability and effectiveness of the proposed model.

Keywords: internet public opinion waves (IPOW), magnitude scale, cross-platform, information propagation

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Authors: Yiqi Wu, Simon Tait, Andrew Nichols

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Management of UK railway drainage assets is challenging due to the large amounts of historical assets with long asset life cycles. A major concern for asset managers is to maintain the required performance economically and efficiently while complying with the relevant regulation and legislation. As the majority of the drainage assets are buried underground and are often difficult or costly to examine, it is important for asset managers to understand and model the degradation process in order to foresee the upcoming reduction in asset performance and conduct proactive maintenance accordingly. In this research, a Markov chain approach is used to model the deterioration process of rail drainage assets. The study is based on historical condition scores and characteristics of drainage assets across the whole railway network in England, Scotland, and Wales. The model is used to examine the effect of various characteristics on the probabilities of degradation, for example, the regional difference in probabilities of degradation, and how material and shape can influence the deterioration process for chambers, channels, and pipes.

Keywords: deterioration, degradation, markov models, probability, railway drainage

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Authors: Carlos A. C. G. Neto, Natan C. G. Silva, Thais O. Costa, Luciana R. B. Goncalves, Maria v. P. Rocha

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Galactosidases are enzymes responsible for catalyzing lactose hydrolysis reactions and also favoring transgalactosylation reactions for the production of prebiotics, among which lactulose stands out. These enzymes, when immobilized, can have some enzymatic characteristics substantially improved, and the coating of supports with multifunctional polymers in immobilization processes is a promising alternative in order to extend the useful life of the biocatalysts, for example, the coating with polyethyleneimine (PEI). PEI is a flexible polymer that suits the structure of the enzyme, giving greater stability, especially for multimeric enzymes such as β-galactosidases and also protects it from environmental variations, for example, pH and temperature. In addition, it can substantially improve the immobilization parameters and also the efficiency of enzymatic reactions. In this context, the aim of the present work was first to develop biocatalysts of β-galactosidase from Kluyveromyces lactis immobilized on PEI coated agarose, determining the immobilization parameters, its operational and thermal stability, and then to apply it in the hydrolysis of lactose and synthesis of lactulose, using whey as a substrate. This immobilization strategy was chosen in order to improve the catalytic efficiency of the enzyme in the transgalactosylation reaction for the production of prebiotics, and there are few studies with β-galactosidase from this strain. The immobilization of β-galactosidase in agarose previously functionalized with 48% (w/v) glycidol and then coated with 10% (w/v) PEI solution was evaluated using an enzymatic load of 10 mg/g of protein. Subsequently, the hydrolysis and transgalactosylation reactions were conducted at 50 °C, 120 RPM for 20 minutes, using whey (66.7 g/L of lactose) supplemented with 133.3 g/L fructose at a ratio of 1:2 (lactose/fructose). Operational stability studies were performed in the same conditions for 10 cycles. Thermal stabilities of biocatalysts were conducted at 50 ºC in 50 mM phosphate buffer, pH 6.6, with 0.1 mM MnCl2. The biocatalysts whose supports were coated were named AGA_GLY_PEI_GAL, and those that were not coated were named AGA_GLY_GAL. The coating of the support with PEI considerably improved immobilization yield (2.6-fold), the biocatalyst activity (1.4-fold), and efficiency (2.2-fold). The biocatalyst AGA_GLY_PEI_GAL was better than AGA_GLY_GAL in hydrolysis and transgalactosylation reactions, converting 88.92% of lactose at 5 min of reaction and obtaining a residual concentration of 5.24 g/L. Besides that, it was produced 13.90 g/L lactulose in the same time interval. AGA_GLY_PEI_GAL biocatalyst was stable during the 10 cycles evaluated, converting approximately 80% of lactose and producing 10.95 g/L of lactulose even after the tenth cycle. However, the thermal stability of AGA_GLY_GAL biocatalyst was superior, with a half-life time 5 times higher, probably because the enzyme was immobilized by covalent bonding, which is stronger than adsorption (AGA_GLY_PEI_GAL). Therefore, the strategy of coating the supports with PEI has proven to be effective for the immobilization of β-galactosidase from K. lactis, considerably improving the immobilization parameters, as well as the enzyme, catalyzed reactions. In addition, the use of whey as a raw material for lactulose production has proved to be an industrially advantageous alternative.

Keywords: β-galactosidase, immobilization, lactulose, polyethylenimine, whey

Procedia PDF Downloads 115

Authors: Natalia Ortega

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Safety Culture (SCU) involves various perceptual, psychological, behavioral, and managerial factors. It has been shown that creating and maintaining an SCU is one way to reduce and prevent accidents and fatalities. In the construction sector, safety attitude, knowledge, and a supportive environment are predictors of safety behavior. The highest possible proportion of safety behavior among employees can be achieved by improving their safety attitude and knowledge. Accordingly, top management's commitment to safety is vital in shaping employees' safety attitude; therefore, the first step to improving employees' safety attitude is the genuine commitment of top management to safety. One of the factors affecting the successful implementation of health and safety promotion programs is the construction industry's subcontracting model. The contractual model's complexity, combined with the need for coordination among diverse stakeholders, makes it challenging to implement, manage, and follow up on health and well-being initiatives. The Systems theoretic accident model and process (STAMP) concept has expanded global consideration in recent years, increasing research attention. STAMP focuses attention on the role of constraints in safety management. The findings discover a growth of the research field from the definition in 2004 by Leveson and is being used across multiple domains. A systematic literature review of this novel model aims to meet the safety goals for human space exploration with a powerful and different approach to safety management, safety-driven design, and decision-making. Around two hundred studies have been published about applying the model. However, every single model for safety requires time to transform into research and practice, be tested and debated, and grow further and mature.

Keywords: stamp, risk management, accident prevention, safety culture, systems thinking, construction industry, safety

Procedia PDF Downloads 76

Authors: Samar Alkindy

Abstract:

Purpose: The BIM model has been used to support the planning of different construction projects in the industry by showing the different stages of the construction process. The model has been instrumental in identifying some of the common errors in the construction process through the spatial arrangement. The continuous use of the BIM model in the construction industry has resulted in various radical changes such as virtual prototyping. Construction virtual prototyping is a highly advanced technology that incorporates a BIM model with realistic graphical simulations, and facilitates the simulation of the project before a product is built in the factory. The paper presents virtual prototyping in the construction industry by examining its application, challenges and benefits to a construction project. Methodology approach: A case study was conducted for this study in four major construction projects, which incorporate virtual construction prototyping in several stages of the construction project. Furthermore, there was the administration of interviews with the project manager and engineer and the planning manager. Findings: Data collected from the methodological approach shows a positive response for virtual construction prototyping in construction, especially concerning communication and visualization. Furthermore, the use of virtual prototyping has increased collaboration and efficiency between construction experts handling a project. During the planning stage, virtual prototyping has increased accuracy, reduced planning time, and reduced the amount of rework during the implementation stage. Irrespective of virtual prototyping being a new concept in the construction industry, the findings outline that the approach will benefit the management of construction projects.

Keywords: construction operations, construction planning, process simulation, virtual prototyping

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Authors: Derin Ureten

Abstract:

Plastic pollution does not disappear, it gets smaller and smaller through photolysis which are caused mainly by sun’s radiation, thermal oxidation, thermal degradation, and biodegradation which is the action of organisms digesting larger plastics. All plastic pollutants have exceedingly harmful effects on the environment. Together with the COVID-19 pandemic, the number of plastic products such as masks and gloves flowing into the environment has increased more than ever. However, microplastics are not the only pollutants in water, one of the most tenacious and toxic pollutants are heavy metals. Heavy metal solutions are also capable of causing varieties of health problems in organisms such as cancer, organ damage, nervous system damage, and even death. The aim of this research is to prove that microplastics can be used in wastewater treatment systems by proving that they could adsorb heavy metals in solutions. Experiment for this research will include two heavy metal solutions; one including microplastics in a heavy metal contaminated water solution, and one that just includes heavy metal solution. After being sieved, absorbance of both mediums will be measured with the help of a spectrometer. Iron (III) chloride (FeCl3) will be used as the heavy metal solution since the solution becomes darker as the presence of this substance increases. The experiment will be supported by Pure Nile Red powder in order to observe if there are any visible differences under the microscope. Pure Nile Red powder is a chemical that binds to hydrophobic materials such as plastics and lipids. If proof of adsorbance could be observed by the rates of the solutions' final absorbance rates and visuals ensured by the Pure Nile Red powder, the experiment will be conducted with different temperature levels in order to analyze the most accurate temperature level to proceed with removal of heavy metals from water. New wastewater treatment systems could be generated with the help of microplastics, for water contaminated with heavy metals.

Keywords: microplastics, heavy metal, pollution, adsorbance, wastewater treatment

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Authors: Baya Takhedmit, Karim Abbas, Sofiane Ouazine

Abstract:

The vacations queues are often employed to model many real situations such as computer systems, communication networks, manufacturing and production systems, transportation systems and so forth. These queueing models are solved at fixed parameters values. However, the parameter values themselves are determined from a finite number of observations and hence have uncertainty associated with them (epistemic uncertainty). In this paper, we consider the M/G/1/N queue with server vacation and exhaustive discipline where we assume that the vacation parameter values have uncertainty. We use the Taylor series expansions approach to estimate the expectation and variance of model output, due to epistemic uncertainties in the model input parameters.

Keywords: epistemic uncertainty, M/G/1/N queue with vacations, non-parametric sensitivity analysis, Taylor series expansion

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Authors: H. Mohammadi Majd, M. Jalali Azizpour, V. Tavaf, A. Jaderi

Abstract:

In upsetting processes contact friction significantly influence metal flow, stress-strain state and process parameters. Furthermore, tribological conditions influence workpiece deformation and its dimensional precision. A viscoplastic constitutive law, the Anand model, was applied to represent the inelastic deformation behavior in upsetting process. This paper presents research results of the influence of contact friction coefficient on a workpiece deformation in upsetting process.finite element parameters. This technique was tested for three different specimens simulations of the upsetting and the corresponding material and can be successfully employed to predict the deformation of the upsetting process.

Keywords: friction, upsetting, barreling, Anand model

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Authors: Grienggrai Rajchakit

Abstract:

As we all know that coronavirus is announced as a pandemic in the world by WHO. It is speeded all over the world with few days of time. To control this spreading, every citizen maintains social distance and self-preventive measures are the best strategies. As of now, many researchers and scientists are continuing their research in finding out the exact vaccine. The machine learning model finds that the coronavirus disease behaves in an exponential manner. To abolish the consequence of this pandemic, an efficient step should be taken to analyze this disease. In this paper, a recurrent neural network model is chosen to predict the number of active cases in a particular state. To make this prediction of active cases, we need a database. The database of COVID-19 is downloaded from the KAGGLE website and is analyzed by applying a recurrent LSTM neural network with univariant features to predict the number of active cases of patients suffering from the corona virus. The downloaded database is divided into training and testing the chosen neural network model. The model is trained with the training data set and tested with a testing dataset to predict the number of active cases in a particular state; here, we have concentrated on Andhra Pradesh state.

Keywords: COVID-19, coronavirus, KAGGLE, LSTM neural network, machine learning

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Authors: Asrat M.Belachew, Tiago Pereira, Institute of Mathematics, Computer Sciences, Avenida Trabalhador São Carlense, 400, São Carlos, 13566-590, Brazil

Abstract:

Infectious diseases are among the most prominent threats to human beings. They cause morbidity and mortality to an individual and collapse the social, economic, and political systems of the whole world collectively. Mathematical models are fundamental tools and provide a comprehensive understanding of how infectious diseases spread and designing the control strategy to mitigate infectious diseases from the host population. Modeling the spread of infectious diseases using a compartmental model of inhomogeneous populations is good in terms of complexity. However, in the real world, there is a situation that accounts for heterogeneity, such as ages, locations, and contact patterns of the population which are ignored in a homogeneous setting. In this work, we study how classical an SEIR infectious disease spreading of the compartmental model can be extended by incorporating the mobility of population between heterogeneous cities during an outbreak of infectious disease. We have formulated an SEIR multi-cities epidemic spreading model using a system of 4k ordinary differential equations to describe the disease transmission dynamics in k-cities during the day and night. We have shownthat the model is epidemiologically (i.e., variables have biological interpretation) and mathematically (i.e., a unique bounded solution exists all the time) well-posed. We constructed the next-generation matrix (NGM) for the model and calculated the basic reproduction number R0for SEIR-epidemic spreading model with cities mobility. R0of the disease depends on the spectral radius mobility operator, and it is a threshold between asymptotic stability of the disease-free equilibrium and disease persistence. Using the eigenvalue perturbation theorem, we showed that sending a fraction of the population between cities decreases the reproduction number of diseases in interconnected cities. As a result, disease transmissiondecreases in the population.

Keywords: SEIR-model, mathematical model, city mobility, epidemic spreading

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Authors: Jingling Li, Yi Zhang, Wei Liang, Tao Cui, Jun Li

Abstract:

Compared with terrestrial network, the traffic of spatial information network has both self-similarity and short correlation characteristics. By studying its traffic prediction method, the resource utilization of spatial information network can be improved, and the method can provide an important basis for traffic planning of a spatial information network. In this paper, considering the accuracy and complexity of the algorithm, the spatial information network traffic is decomposed into approximate component with long correlation and detail component with short correlation, and a time series hybrid prediction model based on wavelet decomposition is proposed to predict the spatial network traffic. Firstly, the original traffic data are decomposed to approximate components and detail components by using wavelet decomposition algorithm. According to the autocorrelation and partial correlation smearing and truncation characteristics of each component, the corresponding model (AR/MA/ARMA) of each detail component can be directly established, while the type of approximate component modeling can be established by ARIMA model after smoothing. Finally, the prediction results of the multiple models are fitted to obtain the prediction results of the original data. The method not only considers the self-similarity of a spatial information network, but also takes into account the short correlation caused by network burst information, which is verified by using the measured data of a certain back bone network released by the MAWI working group in 2018. Compared with the typical time series model, the predicted data of hybrid model is closer to the real traffic data and has a smaller relative root means square error, which is more suitable for a spatial information network.

Keywords: spatial information network, traffic prediction, wavelet decomposition, time series model

Procedia PDF Downloads 140