Search results for: Cox regression model

Authors: Jihane Saad, Thomas Lendormi, Caroline Le Marechal, Anne-marie Pourcher, Céline Druilhe, Jean-louis Lanoiselle

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Agricultural anaerobic digestion consists in the conversion of animal slurry and manure into biogas and digestate. They need, however, to be treated at 70 ºC during 60 min before anaerobic digestion according to the European regulation (EC n°1069/2009 & EU n°142/2011). The impact of such heat treatment on the outcome of bacteria has been poorly studied up to now. Moreover, a recent study¹ has shown that enterococci and clostridia are still detected despite the application of such thermal treatment, questioning the relevance of this approach for the hygienisation of digestate. The aim of this study is to establish the heat inactivation kinetics of two species of enterococci (Enterococcus faecalis and Enterococcus faecium) and two species of clostridia (Clostridioides difficile and Clostridium novyi as a non-toxic model for Clostridium botulinum of group III). A pure culture of each strain was prepared in a specific sterile medium at concentration of 10⁴ – 10⁷ MPN / mL (Most Probable number), depending on the bacterial species. Bacterial suspensions were then filled in sterilized capillary tubes and placed in a water or oil bath at desired temperature for a specific period of time. Each bacterial suspension was enumerated using a MPN approach, and tests were repeated three times for each temperature/time couple. The inactivation kinetics of the four indicator bacteria is described using the Weibull model and the classical Bigelow model of first-order kinetics. The Weibull model takes biological variation, with respect to thermal inactivation, into account and is basically a statistical model of distribution of inactivation times as the classical first-order approach is a special case of the Weibull model. The heat treatment at 70 ºC / 60 min contributes to a reduction greater than 5 log10 for E. faecium and E. faecalis. However, it results only in a reduction of about 0.7 log10 for C. difficile and an increase of 0.5 log10 for C. novyi. Application of treatments at higher temperatures is required to reach a reduction greater or equal to 3 log10 for C. novyi (such as 30 min / 100 ºC, 13 min / 105 ºC, 3 min / 110 ºC, and 1 min / 115 ºC), raising the question of the relevance of the application of heat treatment at 70 ºC / 60 min for these spore-forming bacteria. To conclude, the heat treatment (70 ºC / 60 min) defined by the European regulation is sufficient to inactivate non-sporulating bacteria. Higher temperatures (> 100 ºC) are required as far as spore-forming bacteria concerns to reach a 3 log10 reduction (sporicidal activity).

Keywords: heat treatment, enterococci, clostridia, inactivation kinetics

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Authors: Sushil Kumar, M. Dakshina Murty

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Thermal network modelling has proven to be important tool for thermal analysis of electrical machine. This article investigates numerical thermal network model and experimental performance of a large-scale AC motor. Experimental temperatures were measured using RTD in the stator which have been compared with the numerical data. Thermal network modelling fairly predicts the temperature of various components inside the large-scale AC motor. Results of stator winding temperature is compared with experimental results which are in close agreement with accuracy of 6-10%. This method of predicting hot spots within AC motors can be readily used by the motor designers for estimating the thermal hot spots of the machine.

Keywords: AC motor, thermal network, heat transfer, modelling

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Authors: Benjamin A. Ha, Marco Morselli, Xinhui Paige Zhang, Elizabeth A. C. Heath-Heckman, Jonathan B. Puritz, David K. Jacobs

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Next-generation sequencing has enhanced the ability to acquire massive amounts of sequence data to address classic population genetic questions for non-model organisms. Targeted approaches allow for cost effective or more precise analyses of relevant sequences; although, many such techniques require a known genome and it can be costly to purchase probes from a company. This is challenging for non-model organisms with no published genome and can be expensive for large population genetic studies. Expressed exome capture sequencing (EecSeq) synthesizes probes in the lab from expressed mRNA, which is used to capture and sequence the coding regions of genomic DNA from a pooled suite of samples. A normalization step produces probes to recover transcripts from a wide range of expression levels. This approach offers low cost recovery of a broad range of genes in the genome. This research project expands on EecSeq to investigate if mRNA from one taxon may be used to capture relevant sequences from a series of increasingly less closely related taxa. For this purpose, we propose to use the endangered Northern Tidewater goby, Eucyclogobius newberryi, a non-model organism that inhabits California coastal lagoons. mRNA will be extracted from E. newberryi to create probes and capture exomes from eight other taxa, including the more at-risk Southern Tidewater goby, E. kristinae, and more divergent species. Captured exomes will be sequenced, analyzed bioinformatically and phylogenetically, then compared to previously generated phylogenies across this group of gobies. This will provide an assessment of the utility of the technique in cross-species studies and for analyzing low genetic variation within species as is the case for E. kristinae. This method has potential applications to provide economical ways to expand population genetic and evolutionary biology studies for non-model organisms.

Keywords: coastal lagoons, endangered species, non-model organism, target capture method

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Authors: Mohammad Safaeipour, Yousef Amer

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This study directs its focus on developing a conceptual model to offer a systematic and integrated method to weigh the related measures and evaluate a competence of hospitals and rank of the selected hospitals that involve and consider the stakeholders’ key performance indicators (KPI’s). The Analytical Hierarchy Process (AHP) approach will use to weigh the dimensions and related sub- components. The weights and performance scores will combine by using the Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) and rank the selected hospitals. The results of this study provide interesting insight into the necessity of process improvement implementation in which hospital that received the lowest ranking score.

Keywords: performance measurement system, PMS, hospitals, AHP, TOPSIS

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Authors: Juliana A. Knocikova, Yann Bouret, Médéric Argentina, Laurent Counillon

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Cell volume, together with membrane potential and intracellular hydrogen ion concentration, is an essential biophysical parameter for normal cellular activity. Cell volumes can be altered by osmotically active compounds and extracellular tonicity. In this study, a simple mathematical model of osmotically induced cell swelling and shrinking is presented. Emphasis is given to water diffusion across the membrane. The mathematical description of the cellular behavior consists in a system of coupled ordinary differential equations. We compare experimental data of cell volume alterations driven by differences in osmotic pressure with mathematical simulations under hypotonic and hypertonic conditions. Implications for a future model are also discussed.

Keywords: eukaryotic cell, mathematical modeling, osmosis, volume alterations

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Authors: Kantha Siddhanth Gujjari, Shaani Singhal, Robert Andrew Danks, Adrian Praeger

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Background: Trigeminal neuralgia (TN) is a heterogenous pain syndrome characterised by short paroxysms of lancinating facial pain in the distribution of the trigeminal nerve, often triggered by usually innocuous stimuli. TN has a low prevalence of less than 0.1%, of which 80% to 90% is caused by compression of the trigeminal nerve from an adjacent artery or vein. The root entry zone of the trigeminal nerve is most sensitive to neurovascular conflict (NVC), causing dysmyelination. Whilst microvascular decompression (MVD) is an effective treatment for TN with NVC, all patients do not achieve long-term pain relief. Pre-operative scoring systems by Panczykowski and Hardaway have been proposed but have not been externally validated. These pre-operative scoring systems are composite scores calculated according to a subtype of TN, presence and degree of neurovascular conflict, and response to medical treatments. There is discordance in the assessment of NVC identified on pre-operative magnetic resonance imaging (MRI) between neurosurgeons and radiologists. To our best knowledge, the prognostic impact for MVD of this difference of interpretation has not previously been investigated in the form of a composite scoring system such as those suggested by Panczykowski and Hardaway. Aims: This study aims to identify prognostic factors and externally validate the proposed scoring systems by Panczykowski and Hardaway for TN. A secondary aim is to investigate the prognostic difference between a neurosurgeon's interpretation of NVC on MRI compared with a radiologist’s. Methods: This retrospective cohort study included 95 patients who underwent de novo MVD in a single neurosurgical unit in Melbourne. Data was recorded from patients’ hospital records and neurosurgeon’s correspondence from perioperative clinic reviews. Patient demographics, type of TN, distribution of TN, response to carbamazepine, neurosurgeon, and radiologist interpretation of NVC on MRI, were clearly described prospectively and preoperatively in the correspondence. Scoring systems published by Panczykowski et al. and Hardaway et al. were used to determine composite scores, which were compared with the recurrence of TN recorded during follow-up over 1-year. Categorical data analysed using Pearson chi-square testing. Independent numerical and nominal data analysed with logistical regression. Results: Logistical regression showed that a Panczykowski composite score of greater than 3 points was associated with a higher likelihood of pain-free outcome 1-year post-MVD with an OR 1.81 (95%CI 1.41-2.61, p=0.032). The composite score using neurosurgeon’s impression of NVC had an OR 2.96 (95%CI 2.28-3.31, p=0.048). A Hardaway composite score of greater than 2 points was associated with a higher likelihood of pain-free outcome 1 year post-MVD with an OR 3.41 (95%CI 2.58-4.37, p=0.028). The composite score using neurosurgeon’s impression of NVC had an OR 3.96 (95%CI 3.01-4.65, p=0.042). Conclusion: Composite scores developed by Panczykowski and Hardaway were validated for the prediction of response to MVD in TN. A composite score based on the neurosurgeon’s interpretation of NVC on MRI, when compared with the radiologist’s had a greater correlation with pain-free outcomes 1 year post-MVD.

Keywords: de novo microvascular decompression, neurovascular conflict, prognosis, trigeminal neuralgia

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Authors: M. Draman, S. Z. Muhamad Yassin, M. S. Alias, Z. Lambak, M. I. Zulkifli, S. N. Padhi, K. N. Baharim, F. Maskuriy, A. I. A. Rahim

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The performance of Malay automatic speech recognition (ASR) system for the call centre environment is presented. The system utilizes Kaldi toolkit as the platform to the entire library and algorithm used in performing the ASR task. The acoustic model implemented in this system uses a deep neural network (DNN) method to model the acoustic signal and the standard (n-gram) model for language modelling. With 80 hours of training data from the call centre recordings, the ASR system can achieve 72% of accuracy that corresponds to 28% of word error rate (WER). The testing was done using 20 hours of audio data. Despite the implementation of DNN, the system shows a low accuracy owing to the varieties of noises, accent and dialect that typically occurs in Malaysian call centre environment. This significant variation of speakers is reflected by the large standard deviation of the average word error rate (WERav) (i.e., ~ 10%). It is observed that the lowest WER (13.8%) was obtained from recording sample with a standard Malay dialect (central Malaysia) of native speaker as compared to 49% of the sample with the highest WER that contains conversation of the speaker that uses non-standard Malay dialect.

Keywords: conversational speech recognition, deep neural network, Malay language, speech recognition

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Authors: Ramiz M. Shubbar, Dong In Lee, Hatem A. Gzar, Arthur S. Rood

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Air pollution is one of the biggest environmental problems in Baghdad, Iraq. The Daura refinery located nearest the center of Baghdad, represents the largest industrial area, which transmits enormous amounts of pollutants, therefore study the gaseous pollutants and particulate matter are very important to the environment and the health of the workers in refinery and the people whom leaving in areas around the refinery. Actually, some studies investigated the studied area before, but it depended on the basic Gaussian equation in a simple computer programs, however, that kind of work at that time is very useful and important, but during the last two decades new largest production units were added to the Daura refinery such as, PU_3 (Power unit_3 (Boiler 11&12)), CDU_1 (Crude Distillation unit_70000 barrel_1), and CDU_2 (Crude Distillation unit_70000 barrel_2). Therefore, it is necessary to use new advanced model to study air pollution at the region for the new current years, and calculation the monthly emission rate of pollutants through actual amounts of fuel which consumed in production unit, this may be lead to accurate concentration values of pollutants and the behavior of dispersion or transport in study area. In this study to the best of author’s knowledge CALPUFF model was used and examined for first time in Iraq. CALPUFF is an advanced non-steady-state meteorological and air quality modeling system, was applied to investigate the pollutants concentration of SO2, NO2, CO, and PM1-10μm, at areas adjacent to Daura refinery which located in the center of Baghdad in Iraq. The CALPUFF modeling system includes three main components: CALMET is a diagnostic 3-dimensional meteorological model, CALPUFF (an air quality dispersion model), CALPOST is a post processing package, and an extensive set of preprocessing programs produced to interface the model to standard routinely available meteorological and geophysical datasets. The targets of this work are modeling and simulation the four pollutants (SO2, NO2, CO, and PM1-10μm) which emitted from Daura refinery within one year. Emission rates of these pollutants were calculated for twelve units includes thirty plants, and 35 stacks by using monthly average of the fuel amount consumption at this production units. Assess the performance of CALPUFF model in this study and detect if it is appropriate and get out predictions of good accuracy compared with available pollutants observation. CALPUFF model was investigated at three stability classes (stable, neutral, and unstable) to indicate the dispersion of the pollutants within deferent meteorological conditions. The simulation of the CALPUFF model showed the deferent kind of dispersion of these pollutants in this region depends on the stability conditions and the environment of the study area, monthly, and annual averages of pollutants were applied to view the dispersion of pollutants in the contour maps. High values of pollutants were noticed in this area, therefore this study recommends to more investigate and analyze of the pollutants, reducing the emission rate of pollutants by using modern techniques and natural gas, increasing the stack height of units, and increasing the exit gas velocity from stacks.

Keywords: CALPUFF, daura refinery, Iraq, pollutants

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Authors: Firman Riyudha, Endrik Mifta Shaiful

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The spread of drug users is one kind of behavioral epidemiology that becomes a threat to every country in the world. This problem caused various crisis simultaneously, including financial or economic crisis, social, health, until human crisis. Most drug users are teenagers at school age. A new deterministic model would be constructed to determine the dynamics of the spread of drug users by considering level of education in a susceptible population. Based on the analytical model, two equilibria points were obtained; there were E₀ (zero user) and E₁ (endemic equilibrium). Existence of equilibrium and local stability of equilibria depended on the Basic Reproduction Ratio (R₀). This parameter was defined as the expected rate of secondary prevalence and primary prevalence in virgin population along spreading primary prevalence. The zero-victim equilibrium would be locally asymptotically stable if R₀ < 1 while if R₀ > 1 the endemic equilibrium would be locally asymptotically stable. The result showed that R₀ was proportional to the rate of interaction of each susceptible population based on educational level with the users' population. It is concluded that there was a need to be given a control in interaction, so that drug users population could be minimized. Numerical simulations were also provided to support analytical results.

Keywords: drugs users, level education, mathematical model, stability

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Authors: Nadhia Maharany Siara, Muammal, Ilham Nurhakim, Rofifah Yusadi, M. Adie Putra Tanggara, I. Nyoman Suluh Wijaya

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Urbanization in urban areas has impact to the demand of land use for housing, and it began to occur development in the high-density area called Kampung Kota. Kampung Kota grows and develops without planning or organically. The existence of Kampung Kota, becoming identity of the city development in Indonesia, gives self-identity to the city planning in Indonesia, but the existence of Kampung Kota in the development of the city in Indonesia is often considered as a source of environment, health, and social problems. This cause negative perception about the sustainability of Kampung Kota. This research aims to identify morphology and sustainability level of Kampung Kota in Polehan Sub-District, Blimbing District, Malang City. So far, there have not been many studies that define sustainability of Kampung Kota especially from the perspective of Kampung Kota morphology as a part of urban housing areas. This research took place in in Polehan Sub-District, Blimbing District, Malang City which is one of the oldest Kampung Kota in Malang City. Identification of the sustainability level in this research is done by defining the morphology of Kampung Kota in Polehan Sub-District, Blimbing District, Malang City with a descriptive approach to the observation case (Kampung Kota Polehan Sub-District). After that, definition of sustainability level is defined by quantifying the spatial structure by using the criteria from the new urbanism model which consist of buildings and populations density, compactness, diversity and mix land uses and sustainable transportation. In this case, the use of new urbanism model approach is very appropriate. New Urbanism is a design-driven strategy that is based on traditional forms to minimize urban sprawl in the suburbs. The result obtained from this study is the hometown of the level of sustainability in Polehan Sub-District, Blimbing District, Malang City of 3.2 and can be considered to have a good sustainability.

Keywords: Kampung Kota, new urbanism model, sustainability, urban morphology

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Authors: Taner Ersoz, Filiz Ersoz, Seyma Ozbilge

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In this study, the clients who applied to a bank branch for loan were analyzed through data mining. The study was composed of the information such as amounts of loans received by personal and SME clients working with the bank branch, installment numbers, number of delays in loan installments, payments available in other banks and number of banks to which they are in debt between 2010 and 2013. The client risk profile was examined through Classification and Regression Tree (CART) analysis, one of the decision tree classification methods. At the end of the study, 5 different types of customers have been determined on the decision tree. The classification of these types of customers has been created with the rating of those posing a risk for the bank branch and the customers have been classified according to the risk ratings.

Keywords: client classification, loan suitability, risk rating, CART analysis

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Authors: Yasmeen Bassas, Sandra Kuebler, Allen Riddell

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Native language identification is one of the growing subfields in natural language processing (NLP). The task of native language identification (NLI) is mainly concerned with predicting the native language of an author’s writing in a second language. In this paper, we investigate the performance of two types of features; content-based features vs. content independent features, when they are evaluated on a different corpus (using social media data “Reddit”). In this NLI task, the predefined models are trained on one corpus (TOEFL), and then the trained models are evaluated on different data using an external corpus (Reddit). Three classifiers are used in this task; the baseline, linear SVM, and logistic regression. Results show that content-based features are more accurate and robust than content independent ones when tested within the corpus and across corpus.

Keywords: NLI, NLP, content-based features, content independent features, social media corpus, ML

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Authors: Qing Wu, Fei-Yan Li, Heng-Chang Zhang

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Multitask learning support vector machines (SVMs) have recently attracted increasing research attention. Given several related tasks, the single-task learning methods trains each task separately and ignore the inner cross-relationship among tasks. However, multitask learning can capture the correlation information among tasks and achieve better performance by training all tasks simultaneously. In addition, the asymmetric squared loss function can better improve the generalization ability of the models on the most asymmetric distributed data. In this paper, we first make two assumptions on the relatedness among tasks and propose two multitask learning proximal support vector machine algorithms, named MTL-a-PSVM and EMTL-a-PSVM, respectively. MTL-a-PSVM seeks a trade-off between the maximum expectile distance for each task model and the closeness of each task model to the general model. As an extension of the MTL-a-PSVM, EMTL-a-PSVM can select appropriate kernel functions for shared information and private information. Besides, two corresponding special cases named MTL-PSVM and EMTLPSVM are proposed by analyzing the asymmetric squared loss function, which can be easily implemented by solving linear systems. Experimental analysis of three classification datasets demonstrates the effectiveness and superiority of our proposed multitask learning algorithms.

Keywords: multitask learning, asymmetric squared loss, EMTL-a-PSVM, classification

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Authors: Udeh Anastasia Ifeoma

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The need to develop the rural areas in developing countries where there have been decades of neglect are on the increase. It is against this background that this paper examined the impact of micro finance contribution to Nigeria’s gross domestic product. Time series data for 12-years period 1999-2010 were collated from Central Bank of Nigeria published annual reports. The least squares (LS) regression was used to analyze the data. The result revealed that microfinance activities have negative and non-significant contribution to gross domestic product in Nigeria. The paper recommends that rural poverty is often a product of poor infrastructural facilities; therefore government should make a conscious effort towards industrializing the rural areas thereby motivating the micro finance institutions to locate their offices and extend credit facilities to rural areas thereby improving rural economic growth.

Keywords: microfinance, rural economic growth, Nigeria, developing countries

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Authors: Shigeyuki Haruyama, Ken Kaminishi, Junji Kaneko, Tadayuki Kyoutani, Siti Ruhana Omar, Oke Oktavianty

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This study is used as a definition method to the value and function in manufacturing sector. In concurrence of discussion about present condition of modeling method, until now definition of 1D-CAE is ambiguity and not conceptual. Across all the physics fields, those methods are defined with the formulation of differential algebraic equation which only applied time derivation and simulation. At the same time, we propose semi-acausal modeling concept and differential algebraic equation method as a newly modeling method which the efficiency has been verified through the comparison of numerical analysis result between the semi-acausal modeling calculation and FEM theory calculation.

Keywords: system model, physical models, empirical models, conservation law, differential algebraic equation, object-oriented

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Authors: Yusuf S. Dambatta, Ahmed A. D. Sarhan

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Fused deposition modelling (FDM) is one of the most prominent rapid prototyping (RP) technologies which is being used to efficiently fabricate CAD 3D geometric models. However, the process is coupled with many drawbacks, of which the surface quality of the manufactured RP parts is among. Hence, studies relating to improving the surface roughness have been a key issue in the field of RP research. In this work, a technique of modelling the surface roughness in FDM is presented. Using experimentally measured surface roughness response of the FDM parts, an ANFIS prediction model was developed to obtain the surface roughness in the FDM parts using the main critical process parameters that affects the surface quality. The ANFIS model was validated and compared with experimental test results.

Keywords: surface roughness, fused deposition modelling (FDM), adaptive neuro fuzzy inference system (ANFIS), orientation

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Authors: Aniket Aaba Kadam, Manish Mangesh Panchal, Roushan Ashit Sharma

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This project focuses on the design and development of a lab-scale hybrid rocket motor to accurately determine the regression rate of a fuel/oxidizer combination consisting of solid paraffin and gaseous oxygen (GOX). Hybrid motors offer the advantage of on-demand thrust control over both solid and liquid systems in certain applications. The thermodynamic properties of the propellant combination were calculated using NASA CEA at different chamber pressures and corresponding O/F values to determine initial operating conditions with suitable peak temperatures and optimal O/F values. The project also includes the design of the injector orifice and the determination of the final design configurations of the motor casing, pressure control setup, and valve configuration. This research will be valuable in advancing the understanding of paraffin-based propulsion and improving the performance of hybrid rocket motors.

Keywords: hybrid rocket, NASA CEA, injector, thrust control

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Authors: Abdulla D. Alblooshi

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The stock market is a representation of human behavior and psychology, such as fear, greed, and discipline. Those are manifested in the form of price movements during the trading sessions. Therefore, predicting the stock movement and prices is a challenging effort. However, those trading sessions produce a large amount of data that can be utilized to train an AI agent for the purpose of predicting the stock movement. Predicting the stock market price action will be advantageous. In this paper, the stock movement data of three DFM listed stocks are studied using historical price movements and technical indicators value and used to train an agent using KNN and SVM methods to predict the future price movement. MATLAB Toolbox and a simple script is written to process and classify the information and output the prediction. It will also compare the different learning methods and parameters s using metrics like RMSE, MAE, and R².

Keywords: KNN, ANN, style, SVM, stocks, technical indicators, RSI, MACD, moving averages, RMSE, MAE

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Authors: Yari Vecchio, Margherita Masi, Jorgelina Di Pasquale

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Adoption of Precision Agriculture (PA) is involved in a multidimensional and complex scenario. The process of adopting innovations is complex and social inherently, influenced by other producers, change agents, social norms and organizational pressure. Complexity depends on factors that interact and influence the decision to adopt. Farm and operator characteristics, as well as organizational, informational and agro-ecological context directly affect adoption. This influence has been studied to measure drivers and to clarify 'bottlenecks' of the adoption of agricultural innovation. Making decision process involves a multistage procedure, in which individual passes from first hearing about the technology to final adoption. Awareness is the initial stage and represents the moment in which an individual learns about the existence of the technology. 'Static' concept of adoption has been overcome. Awareness is a precondition to adoption. This condition leads to not encountering some erroneous evaluations, arose from having carried out analysis on a population that is only in part aware of technologies. In support of this, the present study puts forward an empirical analysis among Italian farmers, considering awareness as a prerequisite for adoption. The purpose of the present work is to analyze both factors that affect the probability to adopt and determinants that drive an aware individual to not adopt. Data were collected through a questionnaire submitted in November 2017. A preliminary descriptive analysis has shown that high levels of adoption have been found among younger farmers, better educated, with high intensity of information, with large farm size and high labor-intensive, and whose perception of the complexity of adoption process is lower. The use of a logit model permits to appreciate the weight played by the intensity of labor and complexity perceived by the potential adopter in PA adoption process. All these findings suggest important policy implications: measures dedicated to promoting innovation will need to be more specific for each phase of this adoption process. Specifically, they should increase awareness of PA tools and foster dissemination of information to reduce the degree of perceived complexity of the adoption process. These implications are particularly important in Europe where is pre-announced the reform of Common Agricultural Policy, oriented to innovation. In this context, these implications suggest to the measures supporting innovation to consider the relationship between various organizational and structural dimensions of European agriculture and innovation approaches.

Keywords: adoption, awareness, complexity, precision agriculture

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Authors: M. N. Nwodo, Y. P. Cheng, N. H. Minh

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In the process of recovering oil in weak sandstone formations, the strength of sandstones around the wellbore is weakened due to the increase of effective stress/load from the completion activities around the cavity. The weakened and de-bonded sandstone may be eroded away by the produced fluid, which is termed sand production. It is one of the major trending subjects in the petroleum industry because of its significant negative impacts, as well as some observed positive impacts. For efficient sand management therefore, there has been need for a reliable study tool to understand the mechanism of sanding. One method of studying sand production is the use of the widely recognized Discrete Element Method (DEM), Particle Flow Code (PFC3D) which represents sands as granular individual elements bonded together at contact points. However, there is limited knowledge of the particle-scale behavior of the weak sandstone, and the parameters that affect sanding. This paper aims to investigate the reliability of using PFC3D and a simple Darcy flow in understanding the sand production behavior of a weak sandstone. An isotropic tri-axial test on a weak oil sandstone sample was first simulated at a confining stress of 1MPa to calibrate and validate the parallel bond models of PFC3D using a 10m height and 10m diameter solid cylindrical model. The effect of the confining stress on the number of bonds failure was studied using this cylindrical model. With the calibrated data and sample material properties obtained from the tri-axial test, simulations without and with fluid flow were carried out to check on the effect of Darcy flow on bonds failure using the same model geometry. The fluid flow network comprised of every four particles connected with tetrahedral flow pipes with a central pore or flow domain. Parametric studies included the effects of confining stress, and fluid pressure; as well as validating flow rate – permeability relationship to verify Darcy’s fluid flow law. The effect of model size scaling on sanding was also investigated using 4m height, 2m diameter model. The parallel bond model successfully calibrated the sample’s strength of 4.4MPa, showing a sharp peak strength before strain-softening, similar to the behavior of real cemented sandstones. There seems to be an exponential increasing relationship for the bigger model, but a curvilinear shape for the smaller model. The presence of the Darcy flow induced tensile forces and increased the number of broken bonds. For the parametric studies, flow rate has a linear relationship with permeability at constant pressure head. The higher the fluid flow pressure, the higher the number of broken bonds/sanding. The DEM PFC3D is a promising tool to studying the micromechanical behavior of cemented sandstones.

Keywords: discrete element method, fluid flow, parametric study, sand production/bonds failure

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Authors: Ali Kassem, Ehab Fawzy, Mahmoud Sef el-eslam, Fatma Salah- Eldeen, El zahraa Mohamed

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Introduction: The combination of interferon (INF) and ribavirin is the preferred treatment for chronic hepatitis C viral (HCV) infection. However, nonresponse to this therapy remains common and is associated with several factors such as HCV genotype and HCV viral load in addition to host factors such as sex, HLA type and cytokine polymorphisms. Aim of the work: The aim of this study was to determine predictors of response to (INF) therapy in chronic HCV infected patients treated with INF alpha and ribavirin combination therapy. Patients and Methods: The present study included 110 patients (62 males, 48 females) with chronic HCV infection. Their ages ranged from 20-59 years. Inclusion criteria were organized according to the protocol of the Egyptian National Committee for control of viral hepatitis. Patients included in this study were recruited to receive INF ribavirin combination therapy; 54 patients received pegylated NF α-2a (180 μg) and weight based ribavirin therapy (1000 mg if < 75 kg, 1200 mg if > 75 kg) for 48 weeks and 53 patients received pegylated INF α-2b (1.5 ug/kg/week) and weight based ribavirin therapy (800 mg if < 65 kg, 1000 mg if 65-75 kg and 1200 mg if > 75kg). One hundred and seven liver biopsies were included in the study and submitted to histopathological examination. Hematoxylin and eosin (H&E) stained sections were done to assess both the grade and the stage of chronic viral hepatitis, in addition to the degree of steatosis. Modified hepatic activity index (HAI) grading, modified Ishak staging and Metavir grading and staging systems were used. Laboratory follow up including: HCV PCR at the 12th week to assess the early virologic response (EVR) and at the 24th week were done. At the end of the course: HCV PCR was done at the end of the course and tested 6 months later to document end virologic response (ETR) and sustained virologic response (SVR) respectively. Results One hundred seven patients; 62 males (57.9 %) and 45 females (42.1%) completed the course and included in this study. The age of patients ranged from 20-59 years with a mean of 40.39±10.03 years. Six months after the end of treatment patients were categorized into two groups: Group (1): patients who achieved sustained virological response (SVR). Group (2): patients who didn't achieve sustained virological response (non SVR) including non-responders, breakthrough and relapsers. In our study, 58 (54.2%) patients showed SVR, 18 (16.8%) patients were non-responders, 15 (14%) patients showed break-through and 16 (15 %) patients were relapsers. Univariate binary regression analysis of the possible risk factors of non SVR showed that the significant factors were higher age, higher fasting insulin level, higher Metavir stage and higher grade of hepatic steatosis. Multivariate binary regression analysis showed that the only independent risk factor for non SVR was high fasting insulin level. Conclusion: Younger age, lower Metavir stage, lower steatosis grade and lower fasting insulin level are good predictors of SVR and could be used in predicting the treatment response of pegylated interferon/ribavirin therapy.

Keywords: chronic HCV infection, interferon ribavirin combination therapy, predictors to antiviral therapy, treatment response

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Authors: Gozel Judakova, Markus Bause

Abstract:

We present and analyze reliable numerical techniques for simulating complex flow and transport phenomena related to natural gas transportation in pipelines. Such kind of problems are of high interest in the field of petroleum and environmental engineering. Modeling and understanding natural gas flow and transformation processes during transportation is important for the sake of physical realism and the design and operation of pipeline systems. In our approach a two fluid flow model based on a system of coupled hyperbolic conservation laws is considered for describing natural gas flow undergoing hydratization. The accurate numerical approximation of two-phase gas flow remains subject of strong interest in the scientific community. Such hyperbolic problems are characterized by solutions with steep gradients or discontinuities, and their approximation by standard finite element techniques typically gives rise to spurious oscillations and numerical artefacts. Recently, stabilized and discontinuous Galerkin finite element techniques have attracted researchers’ interest. They are highly adapted to the hyperbolic nature of our two-phase flow model. In the presentation a streamline upwind Petrov-Galerkin approach and a discontinuous Galerkin finite element method for the numerical approximation of our flow model of two coupled systems of Euler equations are presented. Then the efficiency and reliability of stabilized continuous and discontinous finite element methods for the approximation is carefully analyzed and the potential of the either classes of numerical schemes is investigated. In particular, standard benchmark problems of two-phase flow like the shock tube problem are used for the comparative numerical study.

Keywords: discontinuous Galerkin method, Euler system, inviscid two-fluid model, streamline upwind Petrov-Galerkin method, twophase flow

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Authors: Matza Gusto Andika, Malinda Sabrina, Syarie Fatunnisa

Abstract:

Aerodynamic and aeroelastics studies on the hanger bridge profile are important to analyze the aerodynamic phenomenon and Aeroelastics stability of hanger. Wind tunnel tests were conducted on a model of H-beam profile from hanger bridge. The purpose of this study is to investigate steady aerodynamic characteristics such as lift coefficient (Cl), drag coefficient (Cd), and moment coefficient (Cm) under the different angle of attack for preliminary prediction of aeroelastics stability problems. After investigation the steady aerodynamics characteristics from the model, dynamic testing is also conducted in wind tunnel to know the aeroelastics phenomenon which occurs at the H-beam hanger bridge profile. The studies show that the torsional vortex induced vibration occur when the wind speed is 7.32 m/s until 9.19 m/s with maximum amplitude occur when the wind speed is 8.41 m/s. The result of wind tunnel testing is matching to hanger vibration where occur in the field, so wind tunnel studies has successful to model the problem. In order that the H-beam profile is not good enough for the hanger bridge and need to be modified to minimize the Aeroelastics problem. The modification can be done with structure dynamics modification or aerodynamics modification.

Keywords: aerodynamics, aeroelastic, hanger bridge, h-beam profile, vortex induced vibration, wind tunnel

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Authors: Ahmed Fradi

Abstract:

In a digital world in perpetual evolution and acceleration, data more and more voluminous, rich and varied, the new software solutions emerged with the Big Data phenomenon offer new opportunities to the company enabling it not only to optimize its business and to evolve its production model, but also to reorganize itself to increase competitiveness and to identify new strategic axes. Design and manufacturing industrial companies, like the others, face these challenges, data represent a major asset, provided that they know how to capture, refine, combine and analyze them. The objective of our paper is to propose a solution allowing geometric and topological information extraction from 3D CAD model (precisely STEP files) databases, with specific algorithm based on the programming paradigm MapReduce. Our proposal is the first step of our future approach to 3D CAD object retrieval.

Keywords: Big Data, MapReduce, 3D object retrieval, CAD, STEP format

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Authors: Yehjune Heo

Abstract:

As biometric systems become widely deployed, the security of identification systems can be easily attacked by various spoof materials. This paper contributes to finding a reliable and practical anti-spoofing method using Convolutional Neural Networks (CNNs) based on the types of loss functions and optimizers. The types of CNNs used in this paper include AlexNet, VGGNet, and ResNet. By using various loss functions including Cross-Entropy, Center Loss, Cosine Proximity, and Hinge Loss, and various loss optimizers which include Adam, SGD, RMSProp, Adadelta, Adagrad, and Nadam, we obtained significant performance changes. We realize that choosing the correct loss function for each model is crucial since different loss functions lead to different errors on the same evaluation. By using a subset of the Livdet 2017 database, we validate our approach to compare the generalization power. It is important to note that we use a subset of LiveDet and the database is the same across all training and testing for each model. This way, we can compare the performance, in terms of generalization, for the unseen data across all different models. The best CNN (AlexNet) with the appropriate loss function and optimizers result in more than 3% of performance gain over the other CNN models with the default loss function and optimizer. In addition to the highest generalization performance, this paper also contains the models with high accuracy associated with parameters and mean average error rates to find the model that consumes the least memory and computation time for training and testing. Although AlexNet has less complexity over other CNN models, it is proven to be very efficient. For practical anti-spoofing systems, the deployed version should use a small amount of memory and should run very fast with high anti-spoofing performance. For our deployed version on smartphones, additional processing steps, such as quantization and pruning algorithms, have been applied in our final model.

Keywords: anti-spoofing, CNN, fingerprint recognition, loss function, optimizer

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Authors: Jiaqi Dong, Qing-Hua Qin, Yi Xiao

Abstract:

Some of the most fundamental challenges of elastic metamaterials (EMMs) optimization can be attributed to the high consumption of computational power resulted from finite element analysis (FEA) simulations that render the optimization process inefficient. Furthermore, due to the inherent mesh dependence of FEA, minuscule geometry features, which often emerge during the later stages of optimization, induce very fine elements, resulting in enormously high time consumption, particularly when repetitive solutions are needed for computing the objective function. In this study, a surrogate modelling algorithm is developed to reduce computational time in structural optimization of EMMs. The surrogate model is constructed based on a multilayer feedforward artificial neural network (ANN) architecture, trained with prepopulated eigenfrequency data prepopulated from FEA simulation and optimized through regime selection with genetic algorithm (GA) to improve its accuracy in predicting the location and width of the primary elastic band gap. With the optimized ANN surrogate at the core, a Nelder-Mead (NM) algorithm is established and its performance inspected in comparison to the FEA solution. The ANNNM model shows remarkable accuracy in predicting the band gap width and a reduction of time consumption by 47%.

Keywords: artificial neural network, machine learning, mechanical metamaterials, Nelder-Mead optimization

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Authors: N. Sopipan

Abstract:

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: Tusar Kanti Dash, Ganapati Panda

Abstract:

The evaluation of speech quality and intelligence is critical to the overall effectiveness of the Speech Enhancement Algorithms. Several intrusive and non-intrusive measures are employed to calculate these parameters. Non-Intrusive Evaluation is most challenging as, very often, the reference clean speech data is not available. In this paper, a novel non-intrusive speech evaluation measure is proposed using audio features derived from the Stockwell transform. These features are used with the Light Gradient Boosting Machine for the effective prediction of speech quality and intelligibility. The proposed model is analyzed using noisy and reverberant speech from four databases, and the results are compared with the standard Intrusive Evaluation Measures. It is observed from the comparative analysis that the proposed model is performing better than the standard Non-Intrusive models.

Keywords: non-Intrusive speech evaluation, S-transform, light GBM, speech quality, and intelligibility

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Authors: Farhan Beg

Abstract:

A space vector based pulse width modulation control technique for the three-phase PWM converter is proposed in this paper. The proposed control scheme is based on a synchronous reference frame model. High performance and efficiency is obtained with regards to the DC bus voltage and the power factor considerations of the PWM rectifier thus leading to low losses. MATLAB/SIMULINK are used as a platform for the simulations and a SIMULINK model is presented in the paper. The results show that the proposed model demonstrates better performance and properties compared to the traditional SPWM method and the method improves the dynamic performance of the closed loop drastically. For the space vector based pulse width modulation, sine signal is the reference waveform and triangle waveform is the carrier waveform. When the value of sine signal is larger than triangle signal, the pulse will start producing to high; and then when the triangular signals higher than sine signal, the pulse will come to low. SPWM output will change by changing the value of the modulation index and frequency used in this system to produce more pulse width. When more pulse width is produced, the output voltage will have lower harmonics contents and the resolution will increase.

Keywords: power factor, SVPWM, PWM rectifier, SPWM

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Authors: Rizwan Ali, Hammad Zafar

Abstract:

The purpose of this research is to investigate the mediation effect of customer satisfaction in the relationship between service quality, corporate image to customer loyalty, in Pakistan banking sector. The population of this research is banking customers and sample size of 210 respondents. This research uses the SPSS, Correlation, ANOVA and regression analysis techniques along with AMOS methods. The service quality and corporate image applied by the banks are not all variables can directly affect customer loyalty, but must first going through satisfaction. Which means that banks must first need to understand what the customer basic needs through variable service quality and corporate image so that the customers feel loyal when the level of satisfaction is resolved. The service quality provided by the banking industry needs to be improved in order to improve customer satisfaction and loyalty of banking services, especially for banks in Pakistan.

Keywords: customer loyalty, service quality, corporate image, customer satisfaction

Procedia PDF Downloads 91