Search results for: path loss model

Authors: Huinan Zhang, Wenjie Jiang

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Accurate estimation of tropical cyclone intensity is of great importance for disaster prevention and mitigation. Existing techniques are largely based on satellite imagery data, and research and utilization of the inner thermal core structure characteristics of tropical cyclones still pose challenges. This paper presents a two-stage tropical cyclone intensity estimation network based on the fusion of coarse and fine-grained features from microwave brightness temperature data. The data used in this network are obtained from the thermal core structure of tropical cyclones through the Advanced Technology Microwave Sounder (ATMS) inversion. Firstly, the thermal core information in the pressure direction is comprehensively expressed through the maximal intensity projection (MIP) method, constructing coarse-grained thermal core images that represent the tropical cyclone. These images provide a coarse-grained feature range wind speed estimation result in the first stage. Then, based on this result, fine-grained features are extracted by combining thermal core information from multiple view profiles with a distributed network and fused with coarse-grained features from the first stage to obtain the final two-stage network wind speed estimation. Furthermore, to better capture the long-tail distribution characteristics of tropical cyclones, focal loss is used in the coarse-grained loss function of the first stage, and ordinal regression loss is adopted in the second stage to replace traditional single-value regression. The selection of tropical cyclones spans from 2012 to 2021, distributed in the North Atlantic (NA) regions. The training set includes 2012 to 2017, the validation set includes 2018 to 2019, and the test set includes 2020 to 2021. Based on the Saffir-Simpson Hurricane Wind Scale (SSHS), this paper categorizes tropical cyclone levels into three major categories: pre-hurricane, minor hurricane, and major hurricane, with a classification accuracy rate of 86.18% and an intensity estimation error of 4.01m/s for NA based on this accuracy. The results indicate that thermal core data can effectively represent the level and intensity of tropical cyclones, warranting further exploration of tropical cyclone attributes under this data.

Keywords: Artificial intelligence, deep learning, data mining, remote sensing

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Authors: E. Koyuncu

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The problem of Order Acceptance and Scheduling (OAS) is defined as a joint decision of which orders to accept for processing and how to schedule them. Any linear programming model representing real-world situation involves the parameters defined by the decision maker in an uncertain way or by means of language statement. Fuzzy data can be used to incorporate vagueness in the real-life situation. In this study, a fuzzy mathematical model is proposed for a single machine OAS problem, where the orders are defined by their fuzzy due dates, fuzzy processing times, and fuzzy sequence dependent setup times. The signed distance method, one of the fuzzy ranking methods, is used to handle the fuzzy constraints in the model.

Keywords: fuzzy mathematical programming, fuzzy ranking, order acceptance, single machine scheduling

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Authors: Abderazak Guettaf

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The mathematical models of the physical phenomena interacting in inductive plasma were described by the physics equations of the continuous mediums. A 3D model based on magnetic potential vector and electric scalar potential (A, V) formulation is used. The finished volume method is applied to electromagnetic equation, to obtain the field distribution inside the plasma. The numerical results of the method developed on a basic model designed starting from a real three-dimensional model were exposed. From the mathematical model 3D spreading assumptions and boundary conditions, we evaluated the electric field in the load and we have developed a numerical code made under the MATLAB environment, all verifying the effectiveness and validity of this code.

Keywords: electric field, 3D magnetic potential vector and electric scalar potential (A, V) formulation, finished volumes, annular plasma

Procedia PDF Downloads 485

Authors: Mohamed Belhorma, Aboubakar S. Bouchikhi, Belkacem Bounab

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This paper addresses modeling a Double A-Arm suspension, a three-dimensional nonlinear model has been developed using the multibody systems formalism. Dynamical study of the different components responses was done, particularly for the wheel assembly. To validate those results, the system was constructed and simulated by RecurDyn, a professional multibody dynamics simulation software. The model has been used as the Objectif function in an optimization algorithm for ride quality improvement.

Keywords: double A-Arm suspension, multibody systems, ride quality optimization, dynamic simulation

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Authors: Nicolò Vaiana, Giorgio Serino

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In this paper, an advanced Nonlinear Exponential Model (NEM), able to simulate the uniaxial dynamic behavior of seismic isolators having a continuously decreasing tangent stiffness with increasing displacement in the relatively large displacements range and a hardening or softening behavior at large displacements, is presented. The mathematical model is validated by comparing the experimental force-displacement hysteresis loops obtained during cyclic tests, conducted on a helical wire rope isolator and a recycled rubber-fiber reinforced bearing, with those predicted analytically. Good agreement between the experimental and simulated results shows that the proposed model can be an effective numerical tool to predict the force-displacement relationship of seismic isolation devices within the large displacements range. Compared to the widely used Bouc-Wen model, unable to simulate the response of seismic isolators at large displacements, the proposed one allows to avoid the numerical solution of a first order nonlinear ordinary differential equation for each time step of a nonlinear time history analysis, thus reducing the computation effort. Furthermore, the proposed model can simulate the smooth transition of the hysteresis loops from small to large displacements by adopting only one set of five parameters determined from the experimental hysteresis loops having the largest amplitude.

Keywords: base isolation, hardening behavior, nonlinear exponential model, seismic isolators, softening behavior

Procedia PDF Downloads 321

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

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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 239

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

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Authors: Nuha Alamro

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Besides achieving of weight loss, Bariatric surgery (BS) shown metabolic improvement including reduction of cardiovascular disease, insulin resistance and diabetes. This study aimed to measure BS effects on Framingham Risk Score (FRS) and metabolic syndrome (MetS) among patients who underwent BS. Additionally, to determine the effect of BS on TSH among euthyroid obese patients. A Retrospective follow-up study was conducted in King Abdullah Medical City. A total of 160 participants who underwent BS and completed one year of follow ups. Medical history, biochemical, anthropometric, and hormonal parameters were evaluated at baseline and 3-12 months after BS. International Diabetes Federation (IDF) criteria were used to diagnose MetS pre and postoperative. The mean age of participants was 41.9 ± 10.6 with Body Mass Index (BMI) of 48.8 ± 7.3. After 3 months, Systolic, Diastolic blood pressure (SBP, DBP), glycated haemoglobin (HBA1C), Low-density lipoprotein (LDL), cholesterol, triglycerides and Thyroid stimulating hormone (TSH) were significantly decrease (P < 0.001). Significant decrease was seen in Mets, BMI, FRS, SBP, DBP, HBA1C, LDL, triglycerides, cholesterol, liver enzyme, with significant increase in high-density lipoprotein (HDL) level 12 months post-op (P < 0.001). After 1 year, the prevalence of MetS, DM, HTN, FRS were significantly decrease from 72.5%, 43.1%, 78.1%, 11.4 to 16.3%, 9.4%, 22.5% and 5.4, respectively. Besides achieving substantial weight loss, MetS resolution was linked to improvement in cardiovascular risk profile.

Keywords: bariatric surgery, cardiovascular disease, metabolic syndrome, thyroid stimulating hormone

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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

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Authors: Donna-Marie Phyllis Lanton

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Sarcopenia is a well-known geriatric syndrome characterized by the progressive and generalized loss of muscle quantity or quality. The incidence of sarcopenia increases with age and is associated with adverse outcomes such as the increased risk of falls, cognitive impairment, loss of independence, diminished quality of life, increased health costs, need for care in a skilled nursing facility, and increased mortality. Physical activity, including resistance training, is the most prevalent recommendation for treating and preventing sarcopenia. Residents (N = 23) of a skilled nursing facility in East Orlando, Florida, participated in a 90-day strength training program designed using the PARIHS framework to improve measures of muscle mass, muscle strength, physical performance, and quality of life. Residents engaged in both resistance and balance exercises for 1 hour two times a week. Baseline data were collected and compared to data at Days 30, 60, and 90. T tests indicated significant gains on all measures from baseline to 90 days: muscle mass increased by 1.2 (t[22] = 2.85, p = .009), grip strength increased by 4.02 (t[22] = 8.15, p < .001), balance increased by 2.13 (t[22] = 18.64, p < .001), gait speed increased by 1.83 (t[22] = 17.84, p < .001), chair speed increased 1.87 (t[22] = 16.36, p < .001), and quality of life score increased by 17.5 (t[22] = 19.26, p < .001). For residents with sarcopenia in skilled nursing facilities, a 90-day strength training program with resistance and balance exercises may provide an option for decreasing the incidence of sarcopenia among that population

Keywords: muscle mass, muscle strength, older adults, PARIHS framework

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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

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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

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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

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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 229

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: 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

Procedia PDF Downloads 258

Authors: Banafsheh Aghamohammadi, Masoud Honarvar, Babak Ghiassi Tarzi

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Usage of different components has been considered to improve the quality and nutritional properties of cakes in recent years. The effects of applying some sweeteners, instead of sugar, have been evaluated in cakes and many bread formulas up to now; but there has not been any research about the usage of by-products of sugar factories such as Wash and Green-A Syrups in cake formulas. In this research, the effects of substituting 25%, 50%, 75% and 100% of sugar with Wash and Green-A Syrups on some dough and cake properties, such as pH, viscosity, density, volume, weight loss, moisture, water activity, texture, staling, color and sensory evaluations, are studied. The results of these experiments showed that the pH values were not significantly different among any of the all cake batters and also most of the cake samples. Although differences among viscosity and specific gravity of all treatments were both significant and insignificant, these two parameters resulted in higher volume in all samples than the blank one. The differences in weight loss, moisture content and water activity of samples were insignificant. Evaluating of texture showed that the softness of most of samples is increased and the staling is decreased. Crumb color and sensory evaluations of samples were also affected by the replacement of sucrose with Wash and Green-A Syrups. According to the results, we can increase the shelf life and improve the quality and nutritional values of cake by using these kinds of syrups in the formulation.

Keywords: cake, green-A syrup, quality tests, sensory evaluation, wash syrup

Procedia PDF Downloads 172

Authors: B. Kriheli, E. Levner, T. C. E. Cheng, C. T. Ng

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During the last decades, research interest in planning, scheduling, and control of emergency response operations, especially people rescue and evacuation from the dangerous zone of marine accidents, has increased dramatically. Until the survivors (called ‘targets’) are found and saved, it may cause loss or damage whose extent depends on the location of the targets and the search duration. The problem is to efficiently search for and detect/rescue the targets as soon as possible with the help of intelligent mobile robots so as to maximize the number of saved people and/or minimize the search cost under restrictions on the amount of saved people within the allowable response time. We consider a special situation when the autonomous mobile robots (AMR), e.g., unmanned aerial vehicles and remote-controlled robo-ships have no operator on board as they are guided and completely controlled by on-board sensors and computer programs. We construct a mathematical model for the search process in an uncertain environment and provide a new fast algorithm for scheduling the activities of the autonomous robots during the search-and rescue missions after an accident at sea. We presume that in the unknown environments, the AMR’s search-and-rescue activity is subject to two types of error: (i) a 'false-negative' detection error where a target object is not discovered (‘overlooked') by the AMR’s sensors in spite that the AMR is in a close neighborhood of the latter and (ii) a 'false-positive' detection error, also known as ‘a false alarm’, in which a clean place or area is wrongly classified by the AMR’s sensors as a correct target. As the general resource-constrained discrete search problem is NP-hard, we restrict our study to finding local-optimal strategies. A specificity of the considered operational research problem in comparison with the traditional Kadane-De Groot-Stone search models is that in our model the probability of the successful search outcome depends not only on cost/time/probability parameters assigned to each individual location but, as well, on parameters characterizing the entire history of (unsuccessful) search before selecting any next location. We provide a fast approximation algorithm for finding the AMR route adopting a greedy search strategy in which, in each step, the on-board computer computes a current search effectiveness value for each location in the zone and sequentially searches for a location with the highest search effectiveness value. Extensive experiments with random and real-life data provide strong evidence in favor of the suggested operations research model and corresponding algorithm.

Keywords: disaster management, intelligent robots, scheduling algorithm, search-and-rescue at sea

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Authors: Mallikarjunachari Gangapuram

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The design of stimuli-responsive hydrogel nanocomposite thin films is gaining significant attention in these days due to its wide variety of applications. Soft microrobots, drug delivery, biosensors, regenerative medicine, bacterial adhesion, energy storage and wound dressing are few advanced applications in different fields. In this research work, the nanomechanical properties of composite thin films of 20 microns were tuned by applying homogeneous external DC, and AC magnetic fields of magnitudes 0.05 T and 0.1 T. Polyvinyl alcohol (PVA) used as a matrix material and elliptical hematite nanoparticles (ratio of the length of the major axis to the length of the minor axis is 140.59 ± 1.072 nm/52.84 ± 1.072 nm) used as filler materials to prepare the nanocomposite thin films. Both quasi-static nanoindentation, Nano Dynamic Mechanical Analysis (Nano-DMA) tests were performed to characterize the viscoelastic properties of PVA, PVA+Hematite (0.1% wt, 2% wt and 4% wt) nanocomposites. Different properties such as storage modulus, loss modulus, hardness, and Er/H were carefully analyzed. The increase in storage modulus, hardness, Er/H and a decrease in loss modulus were observed with increasing concentration and DC magnetic field followed by AC magnetic field. Contact angle and ATR-FTIR experiments were conducted to understand the molecular mechanisms such as hydrogen bond formation, crosslinking density, and particle-particle interactions. This systematic study is helpful in design and modeling of magnetic responsive hydrogel nanocomposite thin films for biomedical applications.

Keywords: hematite, hydrogel, nanoindentation, nano-DMA

Procedia PDF Downloads 189

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 146

Authors: A. Dudek, P. Tylec, G. Torbicz, P. Duda, K. Proniewska, P. Major, M. Pedziwiatr

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Background: Conservative treatments of obesity, based only on a proper diet and physical activity, without the support of an interdisciplinary team of specialist does not bring satisfactory bariatric results. Long-term maintenance of a proper metabolic results after rapid weight loss due to bariatric surgery requires engagement from patients. Mobile health tool may offer alternative model that enhance participant engagement in keeping the therapy. Objective: We aimed to assess the influence of constant monitoring and subsequent motivational alerts in perioperative period and on post-operative effects in the bariatric patients. As well as the study was designed to identify factors conductive urge to change lifestyle after surgery. Methods: This prospective clinical control study was based on a usage of a designed prototype of bariatric mHealth system. The prepared application comprises central data management with a comprehensible interface dedicated for patients and data transfer module as a physician’s platform. Motivation system of a platform consist of motivational alerts, graphic outcome presentation, and patient communication center. Generated list of patients requiring urgent consultation and possibility of a constant contact with a specialist provide safety zone. 31 patients were enrolled in continuous monitoring program during a 6-month period along with typical follow-up visits. After one year follow-up, all patients were examined. Results: There were 20 active users of the proposed monitoring system during the entire duration of the study. After six months, 24 patients took a part in a control by telephone questionnaires. Among them, 75% confirmed that the application concept was an important element in the treatment. Active users of the application indicated as the most valuable features: motivation to continue treatment (11 users), graphical presentation of weight loss, and other parameters (7 users), the ability to contact a doctor (3 users). The three main drawbacks are technical errors (9 users), tedious questionnaires inside the application (5 users), and time-consuming tasks inside the system (2 users). Conclusions: Constant monitoring and successive motivational alerts to continue treatment is an appropriate tool in the treatment after bariatric surgery, mainly in the early post-operative period. Graphic presentation of data and continuous connection with a clinical staff seemed to be an element of motivation to continue treatment and a sense of security.

Keywords: bariatric surgery, mHealth, mobile health tool, obesity

Procedia PDF Downloads 110

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

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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: Tangyie Evani, Edmond Biloa, Emmanuel Nforbi, Lem Lilian Atanga, Kom Beatrice

Abstract:

The dynamics of languages in contact necessitates a close study of how its users negotiate meanings from shared values in the process of cross-cultural communication. A transverse analysis of the situation demonstrates the existence of complex efforts on connecting cultural knowledge to cross-linguistic competencies within a widening range of communicative exchanges. This paper sets to examine the psychology of cross-cultural communication in a multi-linguistic setting like Cameroon where many local and international languages are in close contact. The paper equally analyses the pertinence of existing macro sociological concepts as fundamental knowledge traits in literal and idiomatic cross semantic mapping. From this point, the article presents a path model of connecting sociolinguistics to the increasing adoption of a widening range of communicative genre piloted by the on-going globalisation trends with its high-speed information technology machinery. By applying a cross cultural analysis frame, the paper will be contributing to a better understanding of the fundamental changes in the nature and goals of cross-cultural knowledge in pragmatics of communication and cultural acceptability’s. It emphasises on the point that, in an era of increasing global interchange, a comprehensive inclusive global culture through bridging gaps in cross-cultural communication would have significant potentials to contribute to achieving global social development goals, if inadequacies in language constructs are adjusted to create avenues that intertwine with sociocultural beliefs, ensuring that meaningful and context bound sociolinguistic values are observed within the global arena of communication.

Keywords: cross-cultural communication, customary language, literalisms, primary meaning, subclasses, transubstantiation

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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 475