Search results for: quantile function model

Authors: Elmeida Effendy, Mustafa M. Amin, Nauli Aulia Lubis, P. J. Sirait

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Music therapy may have an effect on mental illnesses. This is a comparative, quasi-experimental study to examine the effect of music therapy added to standard care on Positive Negative Syndrome Scale, Cognitive Function and Quality of Life in female schizophrenic patients. 50 schizophrenic participants who were diagnosed with semistructured MINI ICD-X, were assigned into two groups received pharmacotherapy. Participants were assigned into each group of therapy by using matched allocation method. Music therapy added on to the first group. They received music therapy, using Mozart Sonata four times a week, over a period of six week. Positive and negative symptoms were measured by using Positive and Negative Syndrome Scale (PANSS). Cognitive function were measured by using Mini Mental State Examination (MMSE) and Montreal Cognitive Assessment (MOCA). All rating scale were administrated by certified skill residents every week after music therapy session. The participants who were received pharmaco-and-music therapy significantly showed greater response than who received pharmacotherapy only. The mean difference of response were -6,6164 (p=0,001) for PANNS, 2,911 (p=0,004) for MMSE, 3,618 (p=0,001) for MOCA, 4,599 (p=0,001) for SF-36. Music therapy have beneficial effects on PANSS, Cognitive Function and Quality of Life in schizophrenic patients.

Keywords: music therapy, rating scale, schizophrenia, symptoms

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Authors: Stefanie Siebenhütter

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Men and women use minority and majority languages differently and with varying confidence levels. This paper contrasts gendered differences in language use with socioeconomic status and age factors of minority language speakers in Southeast Asia. Language use and competence are conditioned by the variable of gender. Potential reasons for this variation by examining gendered language awareness and sociolinguistic attitudes will be given. Moreover, it is analyzed whether women in multilingual minority speakers’ society function as 'leaders of linguistic change', as represented in Labov’s sociolinguistic model. It is asked whether the societal role expectations in collectivistic cultures influence the model of linguistic change. The findings reveal speaking preferences and suggest predictions on the prospective language use, which is a stable situation of multilingualism. The study further exhibits differences between male and females identity-forming processes and shows why females are the leaders of (socio-) linguistic change.

Keywords: gender, identity construction, multilingual minorities, linguistic change, social networks

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Authors: T. Benazzouz, K. Auhmani

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This paper presents a Hospital 4.0 Maturity Assessment Model based on the Industry 4.0 concepts. The self-assessment model defines current and target states of digital transformation by considering multiple aspects of a hospital and a healthcare supply chain. The developed model was validated and evaluated on real-life cases. The resulting model consisted of 5 domains: Technology, Strategy 4.0, Human resources 4.0 & Culture 4.0, Supply chain 4.0 management, and Patient journeys management. Each domain is further divided into several sub-domains, totally 34 sub-domains are identified, that reflect different facets of a hospital 4.0 mature organization.

Keywords: hospital 4.0, Industry 4.0, maturity assessment model, supply chain 4.0, patient

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Authors: Cosmas Pandit Pagwiwoko, Ammar Khaled Abdelaziz Abdelsamia

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Flutter as a phenomenon of flow-induced and self-excited vibration has to be recognized considering its harmful effect on the structure especially in a stage of aircraft design. This phenomenon is also important for a wind energy harvester based on the fluttering surface due to its effective operational velocity range. This multi-physics occurrence can be presented by two governing equations in both fluid and structure simultaneously in respecting certain boundary conditions on the surface of the body. In this work, the equations are resolved separately by two distinct solvers, one-time step of each domain. The modelling and simulation of this flow-structure interaction in ANSYS show the effectiveness of this loosely coupled method in representing flutter phenomenon however the process is time-consuming for design purposes. Therefore, another technique using the same weak coupled aero-structure is proposed by using system dynamics approach. In this technique, the aerodynamic forces were calculated using singularity function for a range of frequencies and certain natural mode shapes are transformed into time domain by employing an approximation model of fraction rational function in Laplace variable. The representation of structure in a multi-degree-of-freedom coupled with a transfer function of aerodynamic forces can then be simulated in time domain on a block-diagram platform such as Simulink MATLAB. The dynamic response of flutter at certain velocity can be evaluated with another established flutter calculation in frequency domain k-method. In this method, a parameter of artificial structural damping is inserted in the equation of motion to assure the energy balance of flow and vibrating structure. The simulation in time domain is particularly interested as it enables to apply the structural non-linear factors accurately. Experimental tests on a fluttering airfoil in the wind tunnel are also conducted to validate the method.

Keywords: flutter, flow-induced vibration, flow-structure interaction, non-linear structure

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Authors: Adel Khorramrouz, Monireh Ahmadi Bani, Ehsan Norouzi, Morvarid Lalenoor

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Background: Plantar pressure distribution measurement has been used for a long time to assess foot disorders. Plantar pressure is an important component affecting the foot and ankle function and Changes in plantar pressure distribution could indicate various foot and ankle disorders. Morphologic and mechanical properties of the foot may be important factors affecting the plantar pressure distribution. Accurate and early measurement may help to reduce the prevalence of pes planus. With recent developments in technology, new techniques such as machine learning have been used to assist clinicians in predicting patients with foot disorders. Significance of the study: This study proposes a neural network learning-based flat foot classification methodology using static foot pressure distribution. Methodologies: Data were collected from 895 patients who were referred to a foot clinic due to foot disorders. Patients with pes planus were labeled by an experienced physician based on clinical examination. Then all subjects (with and without pes planus) were evaluated for static plantar pressures distribution. Patients who were diagnosed with the flat foot in both feet were included in the study. In the next step, the leg length was normalized and the network was trained for plantar pressure mapping images. Findings: From a total of 895 image data, 581 were labeled as pes planus. A computational neural network (CNN) ran to evaluate the performance of the proposed model. The prediction accuracy of the basic CNN-based model was performed and the prediction model was derived through the proposed methodology. In the basic CNN model, the training accuracy was 79.14%, and the test accuracy was 72.09%. Conclusion: This model can be easily and simply used by patients with pes planus and doctors to predict the classification of pes planus and prescreen for possible musculoskeletal disorders related to this condition. However, more models need to be considered and compared for higher accuracy.

Keywords: foot disorder, machine learning, neural network, pes planus

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Authors: Sai Sankalp Vemavarapu

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This paper discusses the application of machine learning in the field of transportation engineering for predicting engineering properties of pavement more accurately and efficiently. Predicting the elastic properties aid us in assessing the current road conditions and taking appropriate measures to avoid any inconvenience to commuters. This improves the longevity and sustainability of the pavement layer while reducing its overall life-cycle cost. As an example, we have implemented differential evolution (DE) in the back-calculation of the elastic modulus of multi-layered pavement. The proposed DE global optimization back-calculation approach is integrated with a forward response model. This approach treats back-calculation as a global optimization problem where the cost function to be minimized is defined as the root mean square error in measured and computed deflections. The optimal solution which is elastic modulus, in this case, is searched for in the solution space by the DE algorithm. The best DE parameter combinations and the most optimum value is predicted so that the results are reproducible whenever the need arises. The algorithm’s performance in varied scenarios was analyzed by changing the input parameters. The prediction was well within the permissible error, establishing the supremacy of DE.

Keywords: cost function, differential evolution, falling weight deflectometer, genetic algorithm, global optimization, metaheuristic algorithm, multilayered pavement, pavement condition assessment, pavement layer moduli back calculation

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Authors: Jocelyn Li, Xiangyang Li

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We have employed THINC-it® to study the acute effects of Spravato on the cognitive function of patients with severe major depression disorder (MDD). The scores of the four tasks (Spotter, Symbol Check, Code Breaker, Trails) found in THINC-it® were used to measure cognitive function throughout treatment. The patients who participated in this study have tried more than 3 antidepressants without significant improvement before they began Spravato treatment. All patients received 3 doses of 28 mg Spravato 5 minutes apart (84 mg total per treatment) during this study with THINC-it®. The data were collected before the first Spravato administration (T0), 1 hour after the first Spravato administration (T1), and 2 hours after the first Spravato administration (T2) during each treatment. The following data were from 13 patients, with a total of 226 trials in a 2-3 month period. Spravato at 84 mg reduced the scores of Trails, Code Breaker, Symbol Check, and Spotter at T1 by 10-20% in all patients with one exception for a minority of patients in Spotter. At T2, the scores of Trails, Symbol Check, and Spotter were back to 97% of T0 while the score of Code Breaker was back to 92%. Interestingly, we found that the score of Spotter was consistently increased by 17% at T1 in the same 30% of patients in each treatment. We called this change reverse response while the pattern of the other patients, a decline (T1) and then recovery (T2), was called non-reverse response. We also compared the scores at T0 between the first visit and the fifth visit. The T0 scores of all four tasks were improved at visit 5 when compared to visit 1. The scores of Trails, Code Breaker, and Symbol Check at T0 were increased by 14%, 33%, and 14% respectively at visit 5. The score of Code Breaker, which had two trends, improved by 9% in reverse response patients compared to a 27% improvement in non-reverse response patients. To our knowledge, this is the first study done on the impact of Spravato on cognitive function change in major depression patients at this time frame. Whether we can predict future responses to Spravato with THINC-it® merits further study.

Keywords: Spravato, THINC-it, major depressive disorder, cognitive function

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Authors: Huilan Yao, Huaixin Zhang

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Simulations of the transition flow of model propellers are important for predicting hydrodynamic performance and studying scale effects. In this paper, the transition flow of a model propeller under different loadings are simulated using a transition model provided by STAR-CCM+, and the influence of turbulence intensity (TI) on the transition, especially friction and pressure components of propeller performance, was studied. Before that, the transition model was applied to simulate the transition flow of a flat plate and an airfoil. Predicted transitions agree well with experimental results. Then, the transition model was applied for propeller simulations in open water, and the influence of TI was studied. Under the heavy and moderate loadings, thrust and torque of the propeller predicted by the transition model (different TI) and two turbulence models are very close and agree well with measurements. However, under the light loading, only the transition model with low TI predicts the most accurate results. Above all, the friction components of propeller performance predicted by the transition model with different TI have obvious difference.

Keywords: transition flow, model propellers, hydrodynamic performance, numerical simulation

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Authors: Nia McRae, Robert Wright, Ghalib Bello

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Introduction: Postpartum depression is a prevalent mood disorder that is detrimental to the mental and physical health of mothers and their newborns. Lead (Pb) is a toxic metal that is associated with hormonal imbalance and mental impairments. The hormone changes that accompany pregnancy and childbirth may be exacerbated by Pb and increase new mothers’ susceptibility to postpartum depression. To the best of the author’s knowledge, this is the only study that investigates the association between prenatal Pb exposure and postpartum depression. Identifying risk factors can contribute to improved prevention and treatment strategies for postpartum depression. Methods: Data was derived from the Programming Research in Obesity, Growth, Environment and Social Stress (PROGRESS) study which is an ongoing longitudinal birth cohort. Postpartum depression was identified by a score of 13 or above on the 10-Item Edinburg Postnatal Depression Scale (EPDS) 6-months and 12-months postpartum. Pb was measured in the blood (BPb) in the second and third trimester and in the tibia and patella 1-month postpartum. Quantile regression models were used to assess the relationship between BPb and postpartum depression. Results: BPb in the second trimester was negatively associated with the 80th percentile of depression 6-months postpartum (β: -0.26; 95% CI: -0.51, -0.01). No significant association was found between BPb in the third trimester and depression 6-months postpartum. BPb in the third trimester exhibited an inverse relationship with the 60th percentile (β: -0.23; 95% CI: -0.41, -0.06), 70th percentile (β: -0.31; 95% CI: -0.52, -0.10), and 90th percentile of depression 12-months postpartum (β: -0.36; 95% CI: -0.69, -0.03). There was no significant association between BPb in the second trimester and depression 12-months postpartum. Bone Pb concentrations were not significantly associated with postpartum depression. Conclusion: The negative association between BPb and postpartum depression may support research which demonstrates lead is a nontherapeutic stimulant. Further research is needed to verify these results and identify effect modifiers.

Keywords: depression, lead, postpartum, prenatal

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Authors: Huang Bingling, Jia Yuhong, Liu Yanhui

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As an important part of aircraft, landing gears are responsible for taking-off and landing function. In recent years, big airplane's structural quality increases a lot. As a result, landing gears have stricter technical requirements than ever before such as structure strength and etc. If the structural strength of the landing gear is enhanced through traditional methods like increasing structural quality, the negative impacts on the landing gear's function would be very serious and even counteract the positive effects. Thus, in order to solve this problem, the impact of pre-rotating of landing gears on performance of landing gears is studied from the theoretical and experimental verification in this paper. By increasing the pre-rotating speed of the wheel, it can improve the performance of the landing gear and reduce the structural quality, the force of joint parts and other properties. In addition, the pre-rotating of the wheels also has other advantages, such as reduce the friction between wheels and ground and extend the life of the wheel. In this paper, the impact of the pre-rotating speed on landing gears and the connecting between landing gears performance and pre-rotating speed would be researched in detail. This paper is divided into three parts. In the first part, large airplane landing gear model is built by CATIA and LMS. As most general landing gear type in big plane, four-wheel landing gear is picked as model. The second part is to simulate the process of landing in LMS motion, and study the impact of pre-rotating of wheels on the aircraft`s properties, including the buffer stroke, efficiency, power; friction, displacement and relative speed between piston and sleeve; force and load distribution of tires. The simulation results show that the characteristics of the different pre-rotation speed are understood. The third part is conclusion. Through the data of the previous simulation and the relationship between the pre-rotation speed of the aircraft wheels and the performance of the aircraft, recommended speed interval is proposed. This paper is of great theoretical value to improve the performance of large airplane. It is a very effective method to improve the performance of aircraft by setting wheel pre-rotating speed. Do not need to increase the structural quality too much, eliminating the negative effects of traditional methods.

Keywords: large airplane, landing gear, pre-rotating, simulation

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Authors: Mohamed Jama Madar, Oso Wilis

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E-learning is the application of information technology in the teaching and learning process. This paper presents the Funnel model as a solution for the problems of implementation of e-learning in tertiary education institutions. While existing models such as TAM, theory-based e-learning and pedagogical model have been used over time, they have generally been found to be inadequate because of their tendencies to treat materials development, instructional design, technology, delivery and governance as separate and isolated entities. Yet it is matching components that bring framework of e-learning strategic implementation. The Funnel model enhances all these into one and applies synchronously and asynchronously to e-learning implementation where the only difference is modalities. Such a model for e-learning implementation has been lacking. The proposed Funnel model avoids ad-ad-hoc approach which has made other systems unused or inefficient, and compromised educational quality. Therefore, the proposed Funnel model should help tertiary education institutions adopt and develop effective and efficient e-learning system which meets users’ requirements.

Keywords: e-learning, pedagogical, technology, strategy

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Authors: Stefanie Siebenhütter

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Male and female speakers use language differently and with varying confidence levels. This paper contrasts gendered differences in language use with socioeconomic status and age factors. It specifically examines how Kui minority language use and competence are conditioned by the variable of gender and discusses potential reasons for this variation by examining gendered language awareness and sociolinguistic attitudes. Moreover, it discusses whether women in Kui society function as 'leaders of linguistic change', as represented in Labov’s sociolinguistic model. It discusses whether societal role expectations in collectivistic cultures influence the model of linguistic change. The findings reveal current Kui speaking preferences and give predictions on the prospective language use, which is a stable situation of multilingualism because the current Kui speakers will socialize and teach the prospective Kui speakers in the near future. It further confirms that Lao is losing importance in Kui speaker’s (female’s) daily life.

Keywords: gender, identity construction, language change, minority language, multilingualism, sociolinguistics, social Networks

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Authors: Abdullah Ali H. Ahmadini, Firoz Ahmad, Intekhab Alam

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Geometric programming problem (GPP) is a well-known non-linear optimization problem having a wide range of applications in many engineering problems. The structure of GPP is quite dynamic and easily fit to the various decision-making processes. The aim of this paper is to highlight the bounded solution method for GPP with special reference to variation among right-hand side parameters. Thus this paper is taken the advantage of two-level mathematical programming problems and determines the solution of the objective function in a specified interval called lower and upper bounds. The beauty of the proposed bounded solution method is that it does not require sensitivity analyses of the obtained optimal solution. The value of the objective function is directly calculated under varying parameters. To show the validity and applicability of the proposed method, a numerical example is presented. The system reliability optimization problem is also illustrated and found that the value of the objective function lies between the range of lower and upper bounds, respectively. At last, conclusions and future research are depicted based on the discussed work.

Keywords: varying parameters, geometric programming problem, bounded solution method, system reliability optimization

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Authors: K. A. Adepoju, O. I. Shittu, A. U. Chukwu

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In this paper, a new four-parameter generalized version of the Fisher Snedecor distribution called Beta- F distribution is introduced. The comprehensive account of the statistical properties of the new distributions was considered. Formal expressions for the cumulative density function, moments, moment generating function and maximum likelihood estimation, as well as its Fisher information, were obtained. The flexibility of this distribution as well as its robustness using cancer remission time data was demonstrated. The new distribution can be used in most applications where the assumption underlying the use of other lifetime distributions is violated.

Keywords: fisher-snedecor distribution, beta-f distribution, outlier, maximum likelihood method

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Authors: Subhojyoti Chatterjee, Peter J. Mahon, Feng Wang

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Resveratrol (RvL), a phenolic compound, is a key ingredient in wine and tomatoes that has been studied over the years because of its important bioactivities such as anti-oxidant, anti-aging and antimicrobial properties. Out of the two isomeric forms of resveratrol i.e. trans and cis, the health benefit is primarily associated with the trans form. Thus, studying the structural properties of the isomers will not only provide an insight into understanding the RvL isomers, but will also help in designing parameters for differentiation in order to achieve 99.9% purity of trans-RvL. In the present study, density function theory (DFT) study is conducted, using the B3LYP/6-311++G** model to explore the through bond and through space intramolecular interactions. Properties such as vibrational spectroscopy (IR and Raman), nuclear magnetic resonance (NMR) spectra, excess orbital energy spectrum (EOES), energy based decomposition analyses (EDA) and Fukui function are calculated. It is discovered that the structure of trans-RvL, although it is C1 non-planar, the backbone non-H atoms are nearly in the same plane; whereas the cis-RvL consists of two major planes of R1 and R2 that are not in the same plane. The absence of planarity gives rise to a H-bond of 2.67Å in cis-RvL. Rotation of the C(5)-C(8) single bond in trans-RvL produces higher energy barriers since it may break the (planar) entire conjugated structure; while such rotation in cis-RvL produces multiple minima and maxima depending on the positions of the rings. The calculated FT-IR spectrum shows very different spectral features for trans and cis-RvL in the region 900 – 1500 cm-1, where the spectral peaks at 1138-1158 cm-1 are split in cis-RvL compared to a single peak at 1165 cm-1 in trans-RvL. In the Raman spectra, there is significant enhancement of cis-RvL in the region above 3000cm-1. Further, the carbon chemical environment (13C NMR) of the RvL molecule exhibit a larger chemical shift for cis-RvL compared to trans-RvL (Δδ = 8.18 ppm) for the carbon atom C(11), indicating that the chemical environment of the C group in cis-RvL is more diverse than its other isomer. The energy gap between highest occupied molecular orbital (HOMO) and the lowest occupied molecular orbital (LUMO) is 3.95 eV for trans and 4.35 eV for cis-RvL. A more detailed inspection using the recently developed EOES revealed that most of the large energy differences i.e. Δεcis-trans > ±0.30 eV, in their orbitals are contributed from the outer valence shell. They are MO60 (HOMO), MO52-55 and MO46. The active sites that has been captured by Fukui function (f + > 0.08) are associated with the stilbene C=C bond of RvL and cis-RvL is more active at these sites than in trans-RvL, as cis orientation breaks the large conjugation of trans-RvL so that the hydroxyl oxygen’s are more active in cis-RvL. Finally, EDA highlights the interaction energy (ΔEInt) of the phenolic compound, where trans is preferred over the cis-RvL (ΔΔEi = -4.35 kcal.mol-1) isomer. Thus, these quantum mechanics results could help in unwinding the diversified beneficial activities associated with resveratrol.

Keywords: resveratrol, FT-IR, Raman, NMR, excess orbital energy spectrum, energy decomposition analysis, Fukui function

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Authors: Moez Yeddes

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The property of opacity is widely used in the formal verification of security in computer systems and protocols. Opacity is a general language-theoretic scheme of many security properties of systems. Opacity is parametrized with framework in which several security properties of a system can be expressed. A secret behaviour of a system is opaque if a passive attacker can never deduce its occurrence from the system observation. Instead of considering the case of static observability where the set of observable events is fixed off-line or dynamic observability where the set of observable events changes over time depending on the history of the trace, we introduce Orwellian partial observability where unobservable events are not revealed provided that downgrading events never occurs in the future of the trace. Orwellian partial observability is needed to model intransitive information flow. This Orwellian observability is knwon as ipurge function. We show in previous work how to verify opacity for regular secret is opaque for a regular language L w.r.t. an Orwellian projection is PSPACE-complete while it has been proved undecidable even for a regular language L w.r.t. a general Orwellian observation function. In this paper, we address two problems of opacification of a regular secret ϕ for a regular language L w.r.t. an Orwellian projection: Given L and a secret ϕ ∈ L, the first problem consist to compute some minimal regular super-language M of L, if it exists, such that ϕ is opaque for M and the second consists to compute the supremal sub-language M′ of L such that ϕ is opaque for M′. We derive both language-theoretic characterizations and algorithms to solve these two dual problems.

Keywords: security policies, opacity, formal verification, orwellian observation

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Authors: M. A. Ansari, A. Hussain, A. Uddin

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A side weir is a flow diversion structure provided in the side wall of a channel to divert water from the main channel to a branch channel. The trapezoidal labyrinth weir is a special type of weir in which crest length of the weir is increased to pass higher discharge. Experimental and numerical studies related to the coefficient of discharge of trapezoidal labyrinth weir in an open channel have been presented in the present study. Group Method of Data Handling (GMDH) with the transfer function of quadratic polynomial has been used to predict the coefficient of discharge for the side trapezoidal labyrinth weir. A new model is developed for coefficient of discharge of labyrinth weir by regression method. Generalized models for predicting the coefficient of discharge for labyrinth weir using Group Method of Data Handling (GMDH) network have also been developed. The prediction based on GMDH model is more satisfactory than those given by traditional regression equations.

Keywords: discharge coefficient, group method of data handling, open channel, side labyrinth weir

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Authors: Serdal Pamuk, Irem Cay

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Our model is based on the theory of reinforced random walks coupled with Michealis-Menten mechanisms which view endothelial cell receptors as the catalysts for transforming both tumor and macrophage derived tumor angiogenesis factor (TAF) into proteolytic enzyme which in turn degrade the basal lamina. The model consists of two main parts. First part has seven differential equations (DE’s) in one space dimension over the capillary, whereas the second part has the same number of DE’s in two space dimensions in the extra cellular matrix (ECM). We connect these two parts via some boundary conditions to move the cells into the ECM in order to initiate capillary formation. But, when does this movement begin? To address this question we estimate the thresholds that activate the transport equations in the capillary. We do this by using steady-state analysis of TAF equation under some assumptions. Once these equations are activated endothelial, pericyte and macrophage cells begin to move into the ECM for the initiation of angiogenesis. We do believe that our results play an important role for the mechanisms of cell migration which are crucial for tumor angiogenesis. Furthermore, we estimate the long time tendency of these three cells, and find that they tend to the transition probability functions as time evolves. We provide our numerical solutions which are in good agreement with our theoretical results.

Keywords: angiogenesis, capillary formation, mathematical analysis, steady-state, transition probability function

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Authors: N. Anand, P. S. Nayyer, V. Rana, S. Verma

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Background: Diabetes mellitus is a group of disorders characterized by hyperglycemia and associated with microvascular and macrovascular complications. Among the lesser known complications is the involvement of respiratory system. Changes in pulmonary volume, diffusion and elastic properties of lungs as well as the performance of the respiratory muscles lead to a restrictive pattern in lung functions. The present study was aimed to determine the changes in various parameters of pulmonary function tests amongst patients with Type 2 Diabetes Mellitus and also try to study the effect of duration of Diabetes Mellitus on pulmonary function tests. Methods: It was a cross sectional study performed at Dr Baba Saheb Ambedkar Hospital and Medical College in, Delhi, A Tertiary care referral centre which included 200 patients divided into 2 groups. The first group included diagnosed patients with diabetes and the second group included controls. Cases and controls symptomatic for any acute or chronic Respiratory or Cardiovascular illness or a history of smoking were excluded. Both the groups were subjected to spirometry to evaluate for the pulmonary function tests. Result: The mean Forced Vital Capacity (FVC), Forced Expiratory Volume in first second (FEV1), Peak Expiratory Flow Rate(PEFR) was found to be significantly decreased ((P < 0.001) as compared to controls while the mean ratio of Forced Expiratory Volume in First second to Forced Vital Capacity was not significantly decreased( p>0.005). There was no correlation seen with duration of the disease. Conclusion: Forced Vital Capacity (FVC), Forced Expiratory Volume in first second (FEV1), Peak Expiratory Flow Rate(PEFR) were found to be significantly decreased in patients of Diabetes mellitus while ratio of Forced Expiratory Volume in First second to Forced Vital Capacity (FEV1/FVC) was not significantly decreased. The duration of Diabetes mellitus was not found to have any statistically significant effect on Pulmonary function tests (p > 0.005).

Keywords: diabetes mellitus, pulmonary function tests, forced vital capacity, forced expiratory volume in first second

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Authors: Luis C. Parra

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

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

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Authors: Komal Rathore, Aydin Sunol, Gita Iranipour, Luke Mulford

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Advanced wastewater treatment plants have complex biological kinetics, time variant influent flow rates and long processing times. Due to these factors, the modeling and operational control of advanced wastewater treatment plants become complicated. However, development of a robust model for advanced wastewater treatment plants has become necessary in order to increase the efficiency of the plants, reduce energy costs and meet the discharge limits set by the government. A dynamic model was designed using the Envirosim (Canada) platform software called BioWin for several wastewater treatment plants in Hillsborough County, Florida. Proper control strategies for various parameters such as mixed liquor suspended solids, recycle activated sludge and waste activated sludge were developed for models to match the plant performance. The models were tuned using both the influent and effluent data from the plant and their laboratories. The plant SCADA was used to predict the influent wastewater rates and concentration profiles as a function of time. The kinetic parameters were tuned based on sensitivity analysis and trial and error methods. The dynamic models were validated by using experimental data for influent and effluent parameters. The dissolved oxygen measurements were taken to validate the model by coupling them with Computational Fluid Dynamics (CFD) models. The Biowin models were able to exactly mimic the plant performance and predict effluent behavior for extended periods. The models are useful for plant engineers and operators as they can take decisions beforehand by predicting the plant performance with the use of BioWin models. One of the important findings from the model was the effects of recycle and wastage ratios on the mixed liquor suspended solids. The model was also useful in determining the significant kinetic parameters for biological wastewater treatment systems.

Keywords: BioWin, kinetic modeling, flowsheet simulation, dynamic modeling

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Authors: Ranjith Maniyeri, Ahamed C. Saleel

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Two-dimensional fluid flow over a stationary circular cylinder is one of the bench mark problem in the field of fluid-structure interaction in computational fluid dynamics (CFD). Motivated by this, in the present work, a two-dimensional computational model is developed using an improved version of immersed boundary method which combines the feedback forcing scheme of the virtual boundary method with Peskin’s regularized delta function approach. Lagrangian coordinates are used to represent the cylinder and Eulerian coordinates are used to describe the fluid flow. A two-dimensional Dirac delta function is used to transfer the quantities between the sold to fluid domain. Further, continuity and momentum equations governing the fluid flow are solved using fractional step based finite volume method on a staggered Cartesian grid system. The developed code is validated by comparing the values of drag coefficient obtained for different Reynolds numbers with that of other researcher’s results. Also, through numerical simulations for different Reynolds numbers flow behavior is well captured. The stability analysis of the improved version of immersed boundary method is tested for different values of feedback forcing coefficients.

Keywords: Feedback Forcing Scheme, Finite Volume Method, Immersed Boundary Method, Navier-Stokes Equations

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Authors: Vanessa Matias Leite, Jandira Guenka Palma, Flávio Henrique de Oliveira

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This paper presents a model-oriented development approach to software development in the Model-View-Controller (MVC) architectural standard. This approach aims to expose a process of extractions of information from the models, in which through rules and syntax defined in this work, assists in the design of the initial model and its future conversions. The proposed paper presents a syntax based on the natural language, according to the rules agreed in the classic grammar of the Portuguese language, added to the rules of conversions generating models that follow the norms of the Object Management Group (OMG) and the Meta-Object Facility MOF.

Keywords: BNF Syntax, model driven architecture, model-view-controller, transformation, UML

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Authors: Dolgormaa Munkhbaatar, Munkhsaikhan Adiya, Tseedulam Khuut

Abstract:

We performed an inversion method to determine the 1D-velocity model with station corrections of the Gobi-Altai area in the southern part of Mongolia using earthquake data collected in the National Data Center during the last 10 years. In this study, the concept of the new 1D model has been employed to minimize the average RMS of a set of well-located earthquakes, recorded at permanent (between 2006 and 2016) and temporary seismic stations (between 2014 and 2016), compute solutions for the coupled hypocenter and 1D velocity model. We selected 4800 events with RMS less than 0.5 seconds and with a maximum GAP of 170 degrees and determined velocity structures. Also, we relocated all possible events located in the Gobi-Altai area using the new 1D velocity model and achieved constrained hypocentral determinations for events within this area. We concluded that the estimated new 1D velocity model is a relatively low range compared to the previous velocity model in a significant improvement intend to, and the quality of the information basis for future research center locations to determine the earthquake epicenter area with this new transmission model.

Keywords: 1D velocity model, earthquake, relocation, Velest

Procedia PDF Downloads 167

Authors: Peng Wang, Tigang Jiang

Abstract:

The computer based lip reading method of different languages cannot be universal. At present, for the research of Chinese lip reading, whether the work on data sets or recognition algorithms, is far from mature. In this paper, we study the Chinese lipreading method based on machine learning, and propose a Chinese Sentence-level lip-reading network (CNLipNet) model which consists of spatio-temporal convolutional neural network(CNN), recurrent neural network(RNN) and Connectionist Temporal Classification (CTC) loss function. This model can map variable-length sequence of video frames to Chinese Pinyin sequence and is trained end-to-end. More over, We create CNLRS, a Chinese Lipreading Dataset, which contains 5948 samples and can be shared through github. The evaluation of CNLipNet on this dataset yielded a 41% word correct rate and a 70.6% character correct rate. This evaluation result is far superior to the professional human lip readers, indicating that CNLipNet performs well in lipreading.

Keywords: lipreading, machine learning, spatio-temporal, convolutional neural network, recurrent neural network

Procedia PDF Downloads 128

Authors: Gong Zhilin, Jing Yang, Jian Yin

Abstract:

The purpose of this paper is to develop a novel system for credit card fraud detection based on sequential modeling of data using hybrid deep learning models. The projected model encapsulates five major phases are pre-processing, imbalance-data handling, feature extraction, optimal feature selection, and fraud detection with an ensemble classifier. The collected raw data (input) is pre-processed to enhance the quality of the data through alleviation of the missing data, noisy data as well as null values. The pre-processed data are class imbalanced in nature, and therefore they are handled effectively with the K-means clustering-based SMOTE model. From the balanced class data, the most relevant features like improved Principal Component Analysis (PCA), statistical features (mean, median, standard deviation) and higher-order statistical features (skewness and kurtosis). Among the extracted features, the most optimal features are selected with the Self-improved Arithmetic Optimization Algorithm (SI-AOA). This SI-AOA model is the conceptual improvement of the standard Arithmetic Optimization Algorithm. The deep learning models like Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), and optimized Quantum Deep Neural Network (QDNN). The LSTM and CNN are trained with the extracted optimal features. The outcomes from LSTM and CNN will enter as input to optimized QDNN that provides the final detection outcome. Since the QDNN is the ultimate detector, its weight function is fine-tuned with the Self-improved Arithmetic Optimization Algorithm (SI-AOA).

Keywords: credit card, data mining, fraud detection, money transactions

Procedia PDF Downloads 131

Authors: Carlos Gonzales, Zaida Quiroz, Marcos Prates

Abstract:

Several spatial variables collected at the same location that share a common spatial distribution can be modeled simultaneously through a multivariate geostatistical model that takes into account the correlation between these variables and the spatial autocorrelation. The main goal of this model is to perform spatial prediction of these variables in the region of study. Here we focus on a geostatistical multivariate formulation that relies on sharing common spatial random effect terms. In particular, the first response variable can be modeled by a mean that incorporates a shared random spatial effect, while the other response variables depend on this shared spatial term, in addition to specific random spatial effects. Each spatial random effect is defined through a Gaussian process with a valid covariance function, but in order to improve the computational efficiency when the data are large, each Gaussian process is approximated to a Gaussian random Markov field (GRMF), specifically to the block nearest neighbor Gaussian process (Block-NNGP). This approach involves dividing the spatial domain into several dependent blocks under certain constraints, where the cross blocks allow capturing the spatial dependence on a large scale, while each individual block captures the spatial dependence on a smaller scale. The multivariate geostatistical model belongs to the class of Latent Gaussian Models; thus, to achieve fast Bayesian inference, it is used the integrated nested Laplace approximation (INLA) method. The good performance of the proposed model is shown through simulations and applications for massive data.

Keywords: Block-NNGP, geostatistics, gaussian process, GRMF, INLA, multivariate models.

Procedia PDF Downloads 97

Authors: Aravind Bagade Shankaranarayana, Parampalli Geetha, Pallavi Gupta

Abstract:

Objective: This study intends to evaluate sexual dysfunction qualitatively and quantitatively in males suffering from primary obesity through a single centered, observational study. Design and Methods: Sexual function of 33 obese males from the outpatient department of the hospital was assessed using IIEF questionnaire and semen analysis and the results were assessed for statistical significance. Results: A varying degree of sexual dysfunction was observed in four out of five areas of sexual functioning viz. erectile function (p<0.02), orgasmic function (p<0.02), sexual desire (p<0.08) and overall satisfaction (p<0.000) in obese individuals. Statistically significant dysfunction was not observed in intercourse satisfaction. Semen analysis was normal in 19 individuals (63.3%) and abnormal in 11 individuals (36.7%), with statistically insignificant p value 0.144, suggesting mild to moderate variation in semen parameters. Conclusions: Varying degree of sexual dysfunction is present in obese males, suggesting that obesity has a possible role in reducing the quality of sexual functioning in males as indicated in the classical Ayurvedic literature.

Keywords: erectile dysfunction, krucchra vyavaya, obesity, sthoulya

Procedia PDF Downloads 330

Authors: Jie Bai, Yongsheng Gao, Shengxin Wang, Jie Zhao

Abstract:

Through the establishment of the elbow biomechanical model, it can provide theoretical guide for rehabilitation therapy on the upper limb of the human body. A biomechanical model of the elbow joint can be built by the connection of muscle force model and elbow dynamics. But there are many undetermined coefficients in the model like the optimal joint angle and optimal muscle force which are usually specified as the experimental parameters of other workers. Because of the individual differences, there is a certain deviation of the final result. To this end, the RMS value of the deviation between the actual angle and calculated angle is considered. A set of coefficients which lead to the minimum RMS value will be chosen to be the optimal parameters. The direct search method and the conjugacy search method are used to get the optimal parameters, thus the model can be more accurate and mode adaptability.

Keywords: elbow biomechanical model, RMS, direct search, conjugacy search

Procedia PDF Downloads 549

Authors: Mehdi Fuladipanah

Abstract:

Stepped spillway includes several steps from the crest to the toe. The steps of stepped spillway could cause to decrease the energy with making energy distribution in the longitude mode and also to reduce the outcome speed. The aim of this study was to stimulate the stepped spillway combined with stilling basin-step using Fluent model and the turbulent superficial flow using RNG, K-ε. The free surface of the flow was monitored by VOF model. The velocity and the depth of the flow were measured by tail water depth by the numerical model and then the dissipated energy was calculated along the spillway. The results indicated that the stilling basin-step complex may cause energy dissipation increment in the stepped spillway. Also, the numerical model was suggested as an effective method to predict the circular and complicated flows in the stepped spillways.

Keywords: stepped spillway, fluent model, VOF model, K-ε model, energy distribution

Procedia PDF Downloads 372