Search results for: nested factor model

Authors: Dedah Ahmed Babou, Nicolas Bez

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The Min-Max autocorrelation factor (MAF) approach makes it possible to express in a space formed by spatially independent factors, spatiotemporal observations. These factors are ordered in decreasing order of spatial autocorrelation. The starting observations are thus expressed in the space formed by these factors according to temporal coordinates. Each vector of temporal coefficients expresses the temporal evolution of the weight of the corresponding factor. Applying this approach has enabled us to achieve the following results: (i) Define a spatially orthogonal space in which the projections of the raw data are determined; (ii) Define a limit threshold for the factors with the strongest structures in order to analyze the weight, and the temporal evolution of these different structures (iii) Study the correlation between the temporal evolution of the persistent spatial structures and that of the observed average abundance (iv) Propose prototypes of campaigns reflecting a high vs. low abundance (v) Propose a classification of campaigns that highlights seasonal and/or temporal similarities. These results were obtained by analyzing the octopus yield during the scientific campaigns of the oceanographic vessel Al Awam during the period 1989-2017 in the Mauritanian exclusive economic zone.

Keywords: spatiotemporal , autocorrelation, kriging, variogram, Octopus vulgaris

Procedia PDF Downloads 147

Authors: Sahar M. El-Gowilly, Mai M. Helmy, Hanan M. El-Gowelli

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Methotrexate (MTX) is widely used in treatment of cancers and autoimmune diseases. However, nephrotoxicity is one of its most important side effects. The peroxisome proliferator-activated receptor gamma agonist, pioglitazone, is known to exert antiinflammatory and reno-protective effects in various kidney injuries. The purpose of this study was to investigate the potential involvement of endothelial damage in MTX-induced renal injury and to elaborate the possible protective effect of pioglitazone against MTX-induced endothelial impairment. Compared with saline-treated rats, treatment with MTX (7 mg/kg for 3 day) caused significant elevations in serum levels of urea and creatinine, increased renal nitrate/nitrite level and impaired renovascular responsiveness of isolated perfused kidney to endothelium-dependent vasodilations induced by acetylcholine (0.01-2.43 nmol) and isoprenaline (1µmol). These effects were abolished by concurrent treatment with pioglitazone (2.5 mg/kg, for 5 days starting two days before MTX). Alternatively, MTX treatment did not affect endothelium-independent renovascular relaxation induced by sodium nitroprusside (0.001-10 μmole). The possibility that alterations in renal antioxidants, circulating cytokine and apoptotic factor (Fas) levels contributed to MTX-pioglitazone interaction was assessed. Pioglitazone treatment abrogated renal oxidative stress (decreased reduced glutathione and catalase activity and increased malondialdehyde), elevated serum cytokine (interleukin-6, interleukin-10, tumor necrosis factor-alpha and transforming growth factor-beta1) and Fas induced by MTX. Histologically, MTX caused defused tubular cells swelling and vacuolization associated with endothelial damage in renal arterioles. These effects disappeared upon co-treated with pioglitazone. Collectively, pioglitazone abolished MTX-induced endothelium dysfunction and nephrotoxicity via ameliorating oxidative stress and rectifying cytokines and Fas abnormalities caused by MTX.

Keywords: methotrexate, pioglitazone, endothelium, kidney

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Authors: Merey M. Sarsengeldin, Alexandr S. Kolokhmatov, Galiya Seidaliyeva, Alexandr Ozerov, Sanim T. Imatayeva

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This series of interdisciplinary studies is an attempt to investigate and develop a scalable model of fair socioeconomic relations on the base of blockchain using positive psychology techniques and Machine Learning algorithms for data analytics. In this particular study, we use hyperinteraction approach and intuition to investigate their influence on 'wisdom of crowds' via created mobile application which was created for the purpose of this research. Along with the public blockchain and private Decentralized Autonomous Organization (DAO) which were elaborated by us on the base of Ethereum blockchain, a model of fair financial relations of members of DAO was developed. We developed a smart contract, so-called, Fair Price Protocol and use it for implementation of model. The data obtained from mobile application was analyzed by ML algorithms. A model was tested on football matches.

Keywords: blockchain, Naïve Bayes algorithm, hyperinteraction, intuition, wisdom of crowd, decentralized autonomous organization

Procedia PDF Downloads 169

Authors: A. Buruzs, M. F. Hatwágner, L. T. Kóczy

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The aim of the present paper is to develop an integrated method that may provide assistance to decision makers during system planning, design, operation and evaluation. In order to support the realization of Circular Economy (CE), it is essential to evaluate local needs and conditions which help to select the most appropriate system components and resource needs. Each of these activities requires careful planning, however, the model of CE offers a comprehensive interdisciplinary framework. The aim of this research was to develop and to introduce a practical methodology for evaluation of local and regional opportunities to promote CE.

Keywords: circular economy, factors, fuzzy cognitive map, model reduction, sustainability

Procedia PDF Downloads 244

Authors: Bernd Engel, Hassan Raheem Hassan

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Rotary draw bending is a method used for tube forming. During the tube bending process, the neutral axis moves towards the inner arc and the wall thickness changes in the cross section of the tube. Wall thinning of the tube takes place at the extrados, whereas wall thickening of the tube occurs at the intrados. This paper investigates the tube bending with rotary draw bending process using thick-walled tubes and different material properties (16Mo3 and 10CrMo9-10). The experimental tests and finite element simulations are used to calculate the variable characteristics (wall thickness distribution, neutral axis shifting and longitudinal strain distribution). These results are compared with results of a plasto-mechanical model. Moreover, the cross section distortion is investigated in this study. This study helped to get bends with smaller wall factor for different material properties.

Keywords: rotary draw bending, thick wall tube, material properties, material influence

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Authors: Ana Paula Camelo, Keila Sanches

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The Geographically Weighted Regression (GWR) was proposed in geography literature to allow relationship in a regression model to vary over space. In Brazil, the agricultural exploitation of the Cerrado Biome is the main cause of deforestation. In this study, we propose a methodology using geostatistical methods to characterize the spatial dependence of deforestation in the Cerrado based on agricultural production indicators. Therefore, it was used the set of exploratory spatial data analysis tools (ESDA) and confirmatory analysis using GWR. It was made the calibration a non-spatial model, evaluation the nature of the regression curve, election of the variables by stepwise process and multicollinearity analysis. After the evaluation of the non-spatial model was processed the spatial-regression model, statistic evaluation of the intercept and verification of its effect on calibration. In an analysis of Spearman’s correlation the results between deforestation and livestock was +0.783 and with soybeans +0.405. The model presented R²=0.936 and showed a strong spatial dependence of agricultural activity of soybeans associated to maize and cotton crops. The GWR is a very effective tool presenting results closer to the reality of deforestation in the Cerrado when compared with other analysis.

Keywords: deforestation, geographically weighted regression, land use, spatial analysis

Procedia PDF Downloads 363

Authors: Reza Miresmaeili, Asghar Heydari Astaraee, Fereshteh Dolati

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In the present study, an analytical model based on dislocation density model was developed to simulate grain refinement in surface mechanical attrition treatment (SMAT). The correlation between SMAT time and development in plastic strain on one hand, and dislocation density evolution, on the other hand, was established to simulate the grain refinement in SMAT. A dislocation density-based constitutive material law was implemented using VUHARD subroutine. A random sequence of shots is taken into consideration for multiple impacts model using Python programming language by utilizing a random function. The simulation technique was to model each impact in a separate run and then transferring the results of each run as initial conditions for the next run (impact). The developed Finite Element (FE) model of multiple impacts describes the coverage evolution in SMAT. Simulations were run to coverage levels as high as 4500%. It is shown that the coverage implemented in the FE model is equal to the experimental coverage. It is depicted that numerical SMAT coverage parameter is adequately conforming to the well-known Avrami model. Comparison between numerical results and experimental measurements for residual stresses and depth of deformation layers confirms the performance of the established FE model for surface engineering evaluations in SMA treatment. X-ray diffraction (XRD) studies of grain refinement, including resultant grain size and dislocation density, were conducted to validate the established model. The full width at half-maximum in XRD profiles can be used to measure the grain size. Numerical results and experimental measurements of grain refinement illustrate good agreement and show the capability of established FE model to predict the gradient microstructure in SMA treatment.

Keywords: dislocation density, grain refinement, severe plastic deformation, simulation, surface mechanical attrition treatment

Procedia PDF Downloads 136

Authors: Tayebeh Sahraeibelverdi, Ahmad Shirazi Hadi Veladi, Mazdak Radmalekshah

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Optical sensors became attractive due to preciseness, low power consumption, and intrinsic electromagnetic interference-free characteristic. Among the waveguide optical sensors, cavity-based ones attended for the high Q-factor. Micro ring resonators as a potential platform have been investigated for various applications as biosensors to pressure sensors thanks to their sensitive ring structure responding to any small change in the refractive index. Furthermore, these small micron size structures can come in an array, bringing the opportunity to have any of the resonance in a specific wavelength and be addressed in this way. Another exciting application is applying a strain to the ring and making them an optical strain gauge where the traditional ones are based on the piezoelectric material. Making them in arrays needs electrical wiring and about fifty times bigger in size. Any physical element that impacts the waveguide cross-section, Waveguide elastic-optic property change, or ring circumference can play a role. In comparison, ring size change has a larger effect than others. Here an engineered ring structure is investigated to study the strain effect on the ring resonance wavelength shift and its potential for more sensitive strain devices. At the same time, these devices can measure any strain by mounting on the surface of interest. The idea is to change the" O" shape ring to a "C" shape ring with a small opening starting from 2π/360 or one degree. We used the Mode solution of Lumbrical software to investigate the effect of changing the ring's opening and the shift induced by applied strain. The designed ring radius is a three Micron silicon on isolator ring which can be fabricated by standard complementary metal-oxide-semiconductor (CMOS) micromachining. The measured wavelength shifts from1-degree opening of the ring to a 6-degree opening have been investigated. Opening the ring for 1-degree affects the ring's quality factor from 3000 to 300, showing an order of magnitude Q-factor reduction. Assuming a strain making the ring-opening from 1 degree to 6 degrees, our simulation results showing negligible Q-factor reduction from 300 to 280. A ring resonator quality factor can reach up to 108 where an order of magnitude reduction is negligible. The resonance wavelength shift showed a blue shift and was obtained to be 1581, 1579,1578,1575nm for 1-, 2-, 4- and 6-degree ring-opening, respectively. This design can find the direction of the strain-induced by applying the opening on different parts of the ring. Moreover, by addressing the specified wavelength, we can precisely find the direction. We can open a significant opportunity to find cracks and any surface mechanical property very specifically and precisely. This idea can be implemented on polymer ring resonators while they can come with a flexible substrate and can be very sensitive to any strain making the two ends of the ring in the slit part come closer or further.

Keywords: optical ring resonator, strain gauge, strain sensor, surface mechanical property analysis

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Authors: Tory Erickson

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The "Bidirectional Spacetime with Spatial Covariance and Wave-Particle Duality in Spacetime Flow" (BST-SCWPDF) Model introduces a framework aimed at unifying general relativity (GR) and quantum mechanics (QM). By proposing a concept of bidirectional spacetime, this model suggests that time can flow in more than one direction, thus offering a perspective on temporal dynamics. Integrated with spatial covariance and wave-particle duality in spacetime flow, the BST-SCWPDF Model resolves long-standing discrepancies between GR and QM. This unified theory has profound implications for quantum gravity, potentially offering insights into quantum entanglement, the collapse of the wave function, and the fabric of spacetime itself. The Bidirectional Spacetime with Spatial Covariance and Wave-Particle Duality in Spacetime Flow" (BST-SCWPDF) Model offers researchers a framework for a better understanding of theoretical physics.

Keywords: astrophysics, quantum mechanics, general relativity, unification theory, theoretical physics

Procedia PDF Downloads 87

Authors: Tahmidul Islam

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Propensity Score Matching (PSM) technique has been widely used for estimating causal effect of treatment in observational studies. One major step of implementing PSM is estimating the propensity score (PS). Logistic regression model with additive linear terms of covariates is most used technique in many studies. Logistics regression model is also used with cubic splines for retaining flexibility in the model. However, choosing the functional form of the logistic regression model has been a question since the effectiveness of PSM depends on how accurately the PS been estimated. In many situations, the linearity assumption of linear logistic regression may not hold and non-linear relation between the logit and the covariates may be appropriate. One can estimate PS using machine learning techniques such as random forest, neural network etc for more accuracy in non-linear situation. In this study, an attempt has been made to compare the efficacy of Generalized Additive Model (GAM) in various linear and non-linear settings and compare its performance with usual logistic regression. GAM is a non-parametric technique where functional form of the covariates can be unspecified and a flexible regression model can be fitted. In this study various simple and complex models have been considered for treatment under several situations (small/large sample, low/high number of treatment units) and examined which method leads to more covariate balance in the matched dataset. It is found that logistic regression model is impressively robust against inclusion quadratic and interaction terms and reduces mean difference in treatment and control set equally efficiently as GAM does. GAM provided no significantly better covariate balance than logistic regression in both simple and complex models. The analysis also suggests that larger proportion of controls than treatment units leads to better balance for both of the methods.

Keywords: accuracy, covariate balances, generalized additive model, logistic regression, non-linearity, propensity score matching

Procedia PDF Downloads 367

Authors: O. J. Akinsola, Yinan Zheng, Rose Anorlu, F. T. Ogunsola, Lifang Hou, Robert Leo-Murphy

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Cervical Cancer (CC) is the 2nd most common cancer among women living in low and middle-income countries, with no associated symptoms during formative periods. With the advancement and innovative medical research, there are numerous preventive measures being utilized, but the incidence of cervical cancer cannot be truncated with the application of only screening tests. The mortality associated with this invasive cervical cancer can be nipped in the bud through the important role of early-stage detection. This study research selected an array of different top features selection techniques which was aimed at developing a model that could validly diagnose the risk factors of cervical cancer. A retrospective clinic-based cohort study was conducted on 178 HIV-associated cervical cancer patients in Lagos University teaching Hospital, Nigeria (U54 data repository) in April 2022. The outcome measure was the automated prediction of the HIV-associated cervical cancer cases, while the predictor variables include: demographic information, reproductive history, birth control, sexual history, cervical cancer screening history for invasive cervical cancer. The proposed technique was assessed with R and Python programming software to produce the model by utilizing the classification algorithms for the detection and diagnosis of cervical cancer disease. Four machine learning classification algorithms used are: the machine learning model was split into training and testing dataset into ratio 80:20. The numerical features were also standardized while hyperparameter tuning was carried out on the machine learning to train and test the data. Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), and K-Nearest Neighbor (KNN). Some fitting features were selected for the detection and diagnosis of cervical cancer diseases from selected characteristics in the dataset using the contribution of various selection methods for the classification cervical cancer into healthy or diseased status. The mean age of patients was 49.7±12.1 years, mean age at pregnancy was 23.3±5.5 years, mean age at first sexual experience was 19.4±3.2 years, while the mean BMI was 27.1±5.6 kg/m2. A larger percentage of the patients are Married (62.9%), while most of them have at least two sexual partners (72.5%). Age of patients (OR=1.065, p<0.001**), marital status (OR=0.375, p=0.011**), number of pregnancy live-births (OR=1.317, p=0.007**), and use of birth control pills (OR=0.291, p=0.015**) were found to be significantly associated with HIV-associated cervical cancer. On top ten 10 features (variables) considered in the analysis, RF claims the overall model performance, which include: accuracy of (72.0%), the precision of (84.6%), a recall of (84.6%) and F1-score of (74.0%) while LR has: an accuracy of (74.0%), precision of (70.0%), recall of (70.0%) and F1-score of (70.0%). The RF model identified 10 features predictive of developing cervical cancer. The age of patients was considered as the most important risk factor, followed by the number of pregnancy livebirths, marital status, and use of birth control pills, The study shows that data mining techniques could be used to identify women living with HIV at high risk of developing cervical cancer in Nigeria and other sub-Saharan African countries.

Keywords: associated cervical cancer, data mining, random forest, logistic regression

Procedia PDF Downloads 83

Authors: Shukri Dughman, Anthony Rossiter

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This paper builds on earlier work which demonstrated that Model Predictive Control (MPC) may give a poor choice of default feed forward compensator. By first demonstrating the impact of future information of target changes on the performance, this paper proposes a pragmatic method for identifying the amount of future information on the target that can be utilised effectively in both finite and infinite horizon algorithms. Numerical illustrations in MATLAB give evidence of the efficacy of the proposal.

Keywords: model predictive control, tracking control, advance knowledge, feed forward

Procedia PDF Downloads 547

Authors: Xiaoying Guo, Xiangyun Wang, Chunhua Jia

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Web page has been one of the most important way of knowing the world. Humans catch a lot of information from it everyday. Thus, understanding where human looks when they surfing the web pages is rather important. In normal scenes, the down-top features and top-down tasks significantly affect humans’ eye movement. In this paper, we investigated if the conventional visual salience algorithm can properly predict humans’ visual attractive region when they viewing the web pages. First, we obtained the eye movement data when the participants viewing the web pages using an eye tracker. By the analysis of eye movement data, we studied the influence of visual saliency and thinking way on eye-movement pattern. The analysis result showed that thinking way affect human’ eye-movement pattern much more than visual saliency. Second, we compared the results of web page visual salience region extracted by Itti model and Spectral Residual (SR) model. The results showed that Spectral Residual (SR) model performs superior than Itti model by comparison with the heat map from eye movements. Considering the influence of mind habit on humans’ visual region of interest, we introduced one of the most important cue in mind habit-fixation position to improved the SR model. The result showed that the improved SR model can better predict the human visual region of interest in web pages.

Keywords: web page salience region, eye-tracker, spectral residual, visual salience

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Authors: Hakiki Kheira, Belhamiti Omar

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In this paper, we propose a new compartmental fractional order model for the simulation of epidemic obesity dynamics. Using the Legendre wavelet method combined with the decoupling and quasi-linearization technique, we demonstrate the validity and applicability of our model. We also present some fractional differential illustrative examples to demonstrate the applicability and efficiency of the method. The fractional derivative is described in the Caputo sense.

Keywords: Caputo derivative, epidemiology, Legendre wavelet method, obesity

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Authors: Ghasem Sharifi, Hamed Shahmohamadi Ousaloo, Milad Azimi, Mehran Mirshams

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The ever-increasing use of satellites demands a search for increasingly accurate and reliable pointing systems. Reaction wheels are rotating devices used commonly for the attitude control of the spacecraft since provide a wide range of torque magnitude and high reliability. The numerical modeling of this device can significantly enhance the accuracy of the satellite control in space. Modeling the wheel rotation in the presence of the various frictions is one of the critical parts of this approach. This paper presents a Dynamic Model Control of a Reaction Wheel (DMCR) in the current control mode. In current-mode, the required current is delivered to the coils in order to achieve the desired torque. During this research, all the friction parameters as viscous and coulomb, motor coefficient, resistance and voltage constant are identified. In order to model identification of a reaction wheel, numerous varying current commands apply on the particular wheel to verify the estimated model. All the parameters of DMCR are identified by classical Levenberg-Marquardt (CLM) optimization method. The experimental results demonstrate that the developed model has an appropriate precise and can be used in the satellite control simulation.

Keywords: experimental modeling, friction parameters, model identification, reaction wheel

Procedia PDF Downloads 233

Authors: Mohammad Sahadet Hossain, Shamsil Arifeen, Mehrab Hossian Likhon

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In this paper, we analyze a linear time invariant (LTI) descriptor system of large dimension. Since these systems are difficult to simulate, compute and store, we attempt to reduce this large system using Low Rank Cholesky Factorized Alternating Directions Implicit (LRCF-ADI) iteration followed by Square Root Balanced Truncation. LRCF-ADI solves the dual Lyapunov equations of the large system and gives low-rank Cholesky factors of the gramians as the solution. Using these cholesky factors, we compute the Hankel singular values via singular value decomposition. Later, implementing square root balanced truncation, the reduced system is obtained. The bode plots of original and lower order systems are used to show that the magnitude and phase responses are same for both the systems.

Keywords: low-rank cholesky factor alternating directions implicit iteration, LTI Descriptor system, Lyapunov equations, Square-root balanced truncation

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Authors: Dejen Alemu, Murray E. Jennex, Temtim Assefa

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This paper is investigated to understand the design, the use, and the consequence of Knowledge Management System (KMS) for knowledge systems sharing and integration. A KMS for knowledge systems sharing and integration is designed to meet the challenges raised by knowledge management researchers and practitioners: the technical, the human, and social factors. Agricultural KMS involves various members coming from different Communities of Practice (CoPs) who possess their own knowledge of multiple practices which need to be combined in the system development. However, the current development of the technology ignored the indigenous knowledge of the local communities, which is the key success factor for agriculture. This research employed the multi-methodological approach to KMS research in action research perspective which consists of four strategies: theory building, experimentation, observation, and system development. Using the KMS development practice of Ethiopian agricultural transformation agency as a case study, this research employed an interpretive analysis using primary qualitative data acquired through in-depth semi-structured interviews and participant observations. The Orlikowski's structuration model of technology has been used to understand the design, the use, and the consequence of the KMS. As a result, the research identified three basic components for the architecture of the shared KMS, namely, the people, the resources, and the implementation subsystems. The KMS were developed using web 2.0 tools to promote knowledge sharing and integration among diverse groups of users in a distributed environment. The use of a shared KMS allows users to access diverse knowledge from a number of users in different groups of participants, enhances the exchange of different forms of knowledge and experience, and creates high interaction and collaboration among participants. The consequences of a shared KMS on the social system includes, the elimination of hierarchical structure, enhance participation, collaboration, and negotiation among users from different CoPs having common interest, knowledge and skill development, integration of diverse knowledge resources, and the requirement of policy and guideline. The research contributes methodologically for the application of system development action research for understanding a conceptual framework for KMS development and use. The research have also theoretical contribution in extending structuration model of technology for the incorporation of variety of knowledge and practical implications to provide management understanding in developing strategies for the potential of web 2.0 tools for sharing and integration of indigenous knowledge.

Keywords: communities of practice, indigenous knowledge, participation, structuration model of technology, Web 2.0 tools

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Authors: Junjie Zhong, Kai Hong, Lei Wang

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Passage Retrieval (PR) plays an important role in many Natural Language Processing (NLP) tasks. Traditional efficient retrieval models relying on exact term-matching, such as TF-IDF or BM25, have nowadays been exceeded by pre-trained language models which match by semantics. Though they gain effectiveness, deep language models often require large memory as well as time cost. To tackle the trade-off between efficiency and effectiveness in PR, this paper proposes Graph Passage Retriever (GraphPR), a graph-based model inspired by the development of graph learning techniques. Different from existing works, GraphPR is end-to-end and integrates both term-matching information and semantics. GraphPR constructs a passage-level graph from BM25 retrieval results and trains a GCN-like model on the graph with graph-based objectives. Passages were regarded as nodes in the constructed graph and were embedded in dense vectors. PR can then be implemented using embeddings and a fast vector-similarity search. Experiments on a variety of real-world retrieval datasets show that the proposed model outperforms related models in several evaluation metrics (e.g., mean reciprocal rank, accuracy, F1-scores) while maintaining a relatively low query latency and memory usage.

Keywords: efficiency, effectiveness, graph learning, language model, passage retrieval, term-matching model

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Authors: Haïfa Ben Mna, Ayed Added

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To evaluate the trace metals contamination status in the Gulf of Tunis, forty one sediment samples were analyzed using different approaches. According to certain contamination and ecological risk indices (Contamination Factor, Geoaccumulation index and Ecological risk index), Hg has the highest contamination level while pollution by Ni, Pb, Cd and Cr was absent. The highest concentrations of trace metals were found in sediments collected from the offshore and coastal areas located opposite the main exchange points with the gulf particularly, the Mejerda and Meliane Rivers, the Khalij Channel, Ghar El Melh and El Malah lagoons, Tunis Lake and Sebkhat Ariana. However, further ecological indices (Potential ecological risk index, Toxic unit and Mean effect-range median quotient) and comparison with sediment quality guidelines suggest that in addition to Mercury, Cr, Pb and Ni concentrations are detrimental to biota in both the offshore and areas near to the exchange points with the gulf. Moreover, in these areas the results from sequential extraction and individual contamination factor calculation pointed to the mobility and bioavailability of Cr, Pb and Ni.

Keywords: sediment, trace metals, contamination assessment, ecological risk, Tunis gulf

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Authors: Quy Dang Nguyen, Reza Nakhaie Jazar

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The paper investigates vibration dynamics of tire-road separation for a quarter-car model; this separation model is developed to be close to the real situation considering the tire is able to separate from the ground plane. A set of piecewise linear mathematical models is developed and matches the in-contact and no-contact states to be considered as mother models for further investigations. The bound dynamics are numerically simulated in the time response and phase portraits. The separation analysis may determine which values of suspension parameters can delay and avoid the no-contact phenomenon, which results in improving ride comfort and eliminating the potentially dangerous oscillation. Finally, model verification is carried out in the MSC-ADAMS environment.

Keywords: quarter-car vibrations, tire-road separation, separation analysis, separation dynamics, ride comfort, ADAMS validation

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Authors: Petra Buzkova, Milos Kopa

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Reliability of the credit default swap market had been questioned repeatedly during the EMU debt crisis. The article examines whether this development influenced sovereign EMU CDS prices in general. We regress the CDS market price on a model risk neutral CDS price obtained from an adopted reduced form valuation model in the 2009-2013 period. We look for a break point in the single-equation and multi-equation econometric models in order to show the changes in relations between CDS market and model prices. Our results differ according to the risk profile of a country. We find that in the case of riskier countries, the relationship between the market and model price changed when market participants started to question the ability of CDS contracts to protect their buyers. Specifically, it weakened after the change. In the case of less risky countries, the change happened earlier and the effect of a weakened relationship is not observed.

Keywords: chow stability test, credit default swap, debt crisis, reduced form valuation model, seemingly unrelated regression

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Authors: Weiwen Li, Hao Huang, Chengmao You, Jianji Liao, Lei Wang, Lina An

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Zooplankton are a central issue in the ecology which makes a great contribution to maintaining the balance of an ecosystem. It is critical in promoting the material cycle and energy flow within the ecosystems. A generalized additive model (GAM) was applied to analyze the relationships between the density (individuals per m³) of zooplankton and other variables in West Daya Bay. All data used in this analysis (the survey month, survey station (longitude and latitude), the depth of the water column, the superficial concentration of chlorophyll a, the benthonic concentration of chlorophyll a, the number of zooplankton species and the number of zooplankton species) were collected through monthly scientific surveys during January to December 2016. GLM model (generalized linear model) was used to choose the significant variables’ impact on the density of zooplankton, and the GAM was employed to analyze the relationship between the density of zooplankton and the significant variables. The results showed that the density of zooplankton increased with an increase of the benthonic concentration of chlorophyll a, but decreased with a decrease in the depth of the water column. Both high numbers of zooplankton species and the overall total number of zooplankton individuals led to a higher density of zooplankton.

Keywords: density, generalized linear model, generalized additive model, the West Daya Bay, zooplankton

Procedia PDF Downloads 151

Authors: Tomohiko Utsuki

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Currently, brain resuscitation becomes increasingly important due to revising various clinical guidelines pertinent to emergency care. In brain resuscitation, the control of brain temperature (BT), intracranial pressure (ICP), and cerebral blood flow (CBF) is required for stabilizing physiological state of brain, and is described as the essential treatment points in many guidelines of disorder and/or disease such as brain injury, stroke, and encephalopathy. Thus, an integrated control system of BT, ICP, and CBF will greatly contribute to alleviating the burden on medical staff and improving treatment effect in brain resuscitation. In order to develop such a control system, models related to BT, ICP, and CBF are required for control simulation, because trial and error experiments using patients are not ethically allowed. A static model of cerebral blood circulation from intracranial arteries and vertebral artery to jugular veins has already constructed and verified. However, it is impossible to represent the pooling of blood in blood vessels, which is one cause of cerebral hypertension in this model. And, it is also impossible to represent the pulsing motion of blood vessels caused by blood pressure change which can have an affect on the change of cerebral tissue pressure. Thus, a dynamic model of cerebral blood circulation is constructed in consideration of the elasticity of the blood vessel and the inertia of the blood vessel wall. The constructed dynamic model was numerically analyzed using the normal data, in which each arterial blood flow in cerebral blood circulation, the distribution of blood pressure in the Circle of Willis, and the change of blood pressure along blood flow were calculated for verifying against physiological knowledge. As the result, because each calculated numerical value falling within the generally known normal range, this model has no problem in representing at least the normal physiological state of the brain. It is the next task to verify the accuracy of the present model in the case of disease or disorder. Currently, the construction of a migration model of extracellular fluid and a model of heat transfer in cerebral tissue are in progress for making them parts of an integrated model of brain physiological state, which is necessary for developing an future integrated control system of BT, ICP and CBF. The present model is applicable to constructing the integrated model representing at least the normal condition of brain physiological state by uniting with such models.

Keywords: dynamic model, cerebral blood circulation, brain resuscitation, automatic control

Procedia PDF Downloads 153

Authors: Endang Purwati Rahayuningsih

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The aim of this study is Enteropathogenic Eschericia coli O157 (EPEC) is one of the pathogen that can cause inflamation and damage intestinal mucosa, which is leading diarrhea. Inflamation in the intestinal mucosa proved by the presence of secretory Immunoglobulin A (sIgA) on the feces. Isolate dadih is Pediococcus pentosaceus (P. pentosaceus) as a probiotic lactic acid bacteria (LAB) is very usefull to improve sIgA and intestinal mucosa. The objective, to determine the dose and duration administration of P. pentosaceus for bowel frequence, sIgA level and height of illeum villi in mice EPEC-induced diarrhea. Method, using Complete Randomized design studies in mice EPEC-induced diarrhea. Mice was classified into 2 factors. A factor (dose of probiotic) and B factor (duration of probiotic observation) consisted of 0 hour, 12 hours, 24 hours and 36 hours. A factor consisted of negative control, positive control (mice induced by EPEC) and 3 different dose experimental mice. The results were a very significant interaction between dose and duration administration of P. pentosaceus. Mean of the most frequent defecation of mice EPEC-induced was 55 graetly reduced into 12 ,after 24 hours administration P. pentosaceus dose 2 x 1010 cfu/g, Mean of sIgA level of mice induced EPEC was 1,60 μg/ml, very significant different (p<0,01). Mean of sIgA level after 24 administration P. pentosaceus dose 2 x 1010cfu/g was 2,65 μg/ml. Mean of height of illeum villi after induced EPEC 53,04 μm with very significant different after 24 hours administration P. pentosaceus dose 2 x 1010cfu/g (142,881μm). This study concluded that P. pentosaceus dose 2 x 1010cfu/g after 24 hours is very beneficial to reduced bowel frequence, increase sIgA level and improve the height illeum villi of mice EPEC-induced diarrhea.

Keywords: Pediococcus pentosaceus, sIgA, enteropathogenic Eschericia coli O157, diarrhea, illeum villi

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Authors: Mostafa Sefidgar, Sohrab Zendehboudi, Hossein Bazmara, Madjid Soltani

Abstract:

Based on findings from clinical applications, most drug treatments fail to eliminate malignant tumors completely even though drug delivery through systemic administration may inhibit their growth. Therefore, better understanding of tumor formation is crucial in developing more effective therapeutics. For this purpose, nowadays, solid tumor modeling and simulation results are used to predict how therapeutic drugs are transported to tumor cells by blood flow through capillaries and tissues. A solid tumor is investigated as a porous media for fluid flow simulation. Most of the studies use Darcy model for porous media. In Darcy model, the fluid friction is neglected and a few simplified assumptions are implemented. In this study, the effect of these assumptions is studied by considering Brinkman model. A multi scale mathematical method which calculates fluid flow to a solid tumor is used in this study to investigate how neglecting fluid friction affects the solid tumor simulation. In this work, the mathematical model in our previous studies is developed by considering two model of momentum equation for porous media: Darcy and Brinkman. The mathematical method involves processes such as fluid flow through solid tumor as porous media, extravasation of blood flow from vessels, blood flow through vessels and solute diffusion, convective transport in extracellular matrix. The sprouting angiogenesis model is used for generating capillary network and then fluid flow governing equations are implemented to calculate blood flow through the tumor-induced capillary network. Finally, the two models of porous media are used for modeling fluid flow in normal and tumor tissues in three different shapes of tumors. Simulations of interstitial fluid transport in a solid tumor demonstrate that the simplifications used in Darcy model affect the interstitial velocity and Brinkman model predicts a lower value for interstitial velocity than the values that Darcy model does.

Keywords: solid tumor, porous media, Darcy model, Brinkman model, drug delivery

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Authors: John Vergara, Giuseppe Palmese

Abstract:

Fundamental studies aimed at elucidating the key contributions to corrosion performance are needed to make progress toward effective and environmentally compliant corrosion control. Epoxy/amine systems are typically employed as barrier coatings for corrosion control. However, the hardening agents used for coating applications can be very complex, making fundamental studies of water and oxygen permeability challenging to carry out. Creating model building blocks for epoxy/amine coatings is the first step in carrying out these studies. We will demonstrate the synthesis and characterization of model amine building blocks from saturated fatty acids and simple amines such as diethylenetriamine (DETA) and Bis(3-aminopropyl)amine. The structure-property relationship of thermosets made from these model amines and Diglycidyl ether of bisphenol A (DGBEA) will be discussed.

Keywords: building block, amine, synthesis, characterization

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Authors: Aakansha Gupta, Neha Vadnere, Tapasvi Soni, M. Anbarsi

Abstract:

Protein secondary structure prediction is one of the most important goals pursued by bioinformatics and theoretical chemistry; it is highly important in medicine and biotechnology. Some aspects of protein functions and genome analysis can be predicted by secondary structure prediction. This is used to help annotate sequences, classify proteins, identify domains, and recognize functional motifs. In this paper, we represent protein secondary structure as a mathematical model. To extract and predict the protein secondary structure from the primary structure, we require a set of parameters. Any constants appearing in the model are specified by these parameters, which also provide a mechanism for efficient and accurate use of data. To estimate these model parameters there are many algorithms out of which the most popular one is the EM algorithm or called the Expectation Maximization Algorithm. These model parameters are estimated with the use of protein datasets like RS126 by using the Bayesian Probabilistic method (data set being categorical). This paper can then be extended into comparing the efficiency of EM algorithm to the other algorithms for estimating the model parameters, which will in turn lead to an efficient component for the Protein Secondary Structure Prediction. Further this paper provides a scope to use these parameters for predicting secondary structure of proteins using machine learning techniques like neural networks and fuzzy logic. The ultimate objective will be to obtain greater accuracy better than the previously achieved.

Keywords: model parameters, expectation maximization algorithm, protein secondary structure prediction, bioinformatics

Procedia PDF Downloads 481

Authors: Haidy S. Ghali, Engy Serag, A. Samer Ezeldin

Abstract:

Copper is an essential raw material used in the construction industry. During the year 2021 and the first half of 2022, the global market suffered from a significant fluctuation in copper raw material prices due to the aftermath of both the COVID-19 pandemic and the Russia-Ukraine war, which exposed its consumers to an unexpected financial risk. Thereto, this paper aims to develop two ANN-LSTM price prediction models, using Python, that can forecast the average monthly copper prices traded in the London Metal Exchange; the first model is a multivariate model that forecasts the copper price of the next 1-month and the second is a univariate model that predicts the copper prices of the upcoming three months. Historical data of average monthly London Metal Exchange copper prices are collected from January 2009 till July 2022, and potential external factors are identified and employed in the multivariate model. These factors lie under three main categories: energy prices and economic indicators of the three major exporting countries of copper, depending on the data availability. Before developing the LSTM models, the collected external parameters are analyzed with respect to the copper prices using correlation and multicollinearity tests in R software; then, the parameters are further screened to select the parameters that influence the copper prices. Then, the two LSTM models are developed, and the dataset is divided into training, validation, and testing sets. The results show that the performance of the 3-Month prediction model is better than the 1-Month prediction model, but still, both models can act as predicting tools for diverse economic situations.

Keywords: copper prices, prediction model, neural network, time series forecasting

Procedia PDF Downloads 113

Authors: Xiuguo Zhao, He Li, Alireza Yazdani, Xiaoning Zheng, Xinxi Xu

Abstract:

Wound infected poses a serious threat to the surgery on the patient during the process of surgery. Understanding the bacteria-carrying particles (BCPs) transportation and deposition in the open surgical wound model play essential role in protecting wound against being infected. Therefore BCPs transportation and deposition in the surgical wound model were investigated using force-coupling method (FCM) based computational fluid dynamics. The BCPs deposition in the wound was strongly associated with BCPs diameter and concentration. The results showed that the rise on the BCPs deposition was increasing not only with the increase of BCPs diameters but also with the increase of the BCPs concentration. BCPs deposition morphology was impacted by the combination of size distribution, airflow patterns and model geometry. The deposition morphology exhibited the characteristic with BCPs deposition on the sidewall in wound model and no BCPs deposition on the bottom of the wound model mainly because the airflow movement in one direction from up to down and then side created by laminar system constructing airflow patterns and then made BCPs hard deposit in the bottom of the wound model due to wound geometry limit. It was also observed that inertial impact becomes a main mechanism of the BCPs deposition. This work may contribute to next study in BCPs deposition limit, as well as wound infected estimation in surgical-site infections.

Keywords: BCPs deposition, computational fluid dynamics, force-coupling method (FCM), numerical simulation, open surgical wound model

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Authors: Maryam Gallab, Hafida Bouloiz, Youness Chater, Mohamed Tkiouat

Abstract:

The aim of this paper is to present a model based on multi-agent systems in order to manage the maintenance activities and to ensure the reliability and availability of machines just with the required resources (operators, tools). The interest of the simulation is to solve the complexity of the system and to find results without cost or wasting time. An implementation of the model is carried out on the AnyLogic platform to display the defined performance indicators.

Keywords: maintenance, complexity, simulation, multi-agent systems, AnyLogic platform

Procedia PDF Downloads 305