Search results for: hetero-occurrences species distribution model

Authors: Rui Serôdio, Alexandra Serra, José Albino Lima, Luísa Catita, Paula Lopes

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We will present the outline of the Project SIA (Social Inclusion through Accessibility) focusing in one of its core components: how our applied research model contributes to define community participation as a pillar for strategic and political agenda amongst local authorities. Project ISA, supported by EU regional funding, was design as part of a broader model developed by SIMLab–Social Inclusion Monitoring Laboratory, in which the relation University-Community is a core element. The project illustrates how University of Porto developed a large scale project of applied psychology research in a close partnership with 18 municipalities that cover almost all regions of Portugal, and with a private architecture enterprise, specialized in inclusive accessibility and “design for all”. Three fundamental goals were defined: (1) creation of a model that would promote the effective civic participation of local citizens; (2) the “voice” of such participation should be both individual and collective; (3) the scientific and technical framework should serve as one of the bases for political decision on inclusive accessibility local planning. The two main studies were run in a standardized model across all municipalities and the samples of the three modalities of community participation were the following: individual participation based on 543 semi-structured interviews and 6373 inquiries; collective participation based on group session with 302 local citizens. We present some of the broader findings of Project SIA and discuss how they relate to our applied research model.

Keywords: applied psychology, collective identity, community participation, inclusive accessibility

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Authors: Jie Huo, Jonathan Wu

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Segmentation of anatomical structures in medical images is essential for scientific inquiry into the complex relationships between biological structure and clinical diagnosis, treatment and assessment. As a method of incorporating the prior knowledge and the anatomical structure similarity between a target image and atlases, multi-atlas segmentation has been successfully applied in segmenting a variety of medical images, including the brain, cardiac, and abdominal images. The basic idea of multi-atlas segmentation is to transfer the labels in atlases to the coordinate of the target image by matching the target patch to the atlas patch in the neighborhood. However, this technique is limited by the pairwise registration between target image and atlases. In this paper, a novel multi-atlas segmentation approach is proposed by introducing a dynamic energy model. First, the target is mapped to each atlas image by minimizing the dynamic energy function, then the segmentation of target image is generated by weighted fusion based on the energy. The method is tested on MICCAI 2012 Multi-Atlas Labeling Challenge dataset which includes 20 target images and 15 atlases images. The paper also analyzes the influence of different parameters of the dynamic energy model on the segmentation accuracy and measures the dice coefficient by using different feature terms with the energy model. The highest mean dice coefficient obtained with the proposed method is 0.861, which is competitive compared with the recently published method.

Keywords: brain MRI segmentation, dynamic energy model, multi-atlas segmentation, energy minimization

Procedia PDF Downloads 339

Authors: Dalyah Y. Al-Jamal, Maryam H. Eshtaiwi, Liyakathunisa Syed

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Connecting health services with technology has a huge demand as people health situations are becoming worse day by day. In fact, engaging new technologies such as Internet of Things (IOT) into the medical services can enhance the patient care services. Specifically, patients suffering from chronic diseases such as cardiac patients need a special care and monitoring. In reality, some efforts were previously taken to automate and improve the patient monitoring systems. However, the previous efforts have some limitations and lack the real-time feature needed for chronic kind of diseases. In this paper, an improved process model for patient monitoring system specialized for cardiac patients is presented. A survey was distributed and interviews were conducted to gather the needed requirements to improve the cardiac patient monitoring system. Business Process Model and Notation (BPMN) language was used to model the proposed process. In fact, the proposed system uses the IOT Technology to assist doctors to remotely monitor and follow-up with their heart patients in real-time. In order to validate the effectiveness of the proposed solution, simulation analysis was performed using Bizagi Modeler tool. Analysis results show performance improvements in the heart monitoring process. For the future, authors suggest enhancing the proposed system to cover all the chronic diseases.

Keywords: IoT, process model, remote patient monitoring system, smart watch

Procedia PDF Downloads 335

Authors: Kathia Melbouci, Sylvie Naudet Collette, Vincent Gay-Bellile, Omar Ait-Aider, Michel Dhome

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In this paper, we handle the problem of real time localization and mapping in indoor environment assisted by a partial prior 3D model, using an RGBD sensor. The proposed solution relies on a feature-based RGBD SLAM algorithm to localize the camera and update the 3D map of the scene. To improve the accuracy and the robustness of the localization, we propose to combine in a local bundle adjustment process, geometric information provided by a prior coarse 3D model of the scene (e.g. generated from the 2D floor plan of the building) along with RGBD data from a Kinect camera. The proposed approach is evaluated on a public benchmark dataset as well as on real scene acquired by a Kinect sensor.

Keywords: SLAM, global localization, 3D sensor, bundle adjustment, 3D model

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Authors: Xiguan Jiangfan Yang

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This study investigates the tea consumption based on the Double-Hurdle model. The results of a CHNS survey of 12,745 samples in China offer two preliminary insights: First, we can’t apply the conclusions we get by using all samples to the men or women subgroups. Second, men and women are impacted by different demographic not only on the intention to drink tea, but also on the quantities of tea consumed. These two findings suggest that appropriate and corresponding marketing strategies should be developed to targeting on the different groups of tea consumers.

Keywords: Chinese, CHNS, Double-Hurdle model, tea consumption

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Authors: Ammar Maziz, Mostapha Tarfaoui, Said Rechak

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The high mechanical performance of composite pipes can be adversely affected by their low resistance to impact loads. Loads in dynamic origin are dangerous and cause consequences on the operation of pipes because the damage is often not detected and can affect the structural integrity of composite pipes. In this work, an advanced 3-D finite element (FE) model, based on the use of intralaminar damage models was developed and used to predict damage under low-velocity impact. The performance of the numerical model is validated with the confrontation with the results of experimental tests. The results show that at low impact energy, the damage happens mainly by matrix cracking and delamination. The model capabilities to simulate the low-velocity impact events on the full-scale composite structures were proved.

Keywords: composite materials, low velocity impact, FEA, dynamic behavior, progressive damage modeling

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Authors: Prajwal Prakash Vasisht, Sharath Rajamurthy, Nishanth Dara

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In a supervised machine learning approach, metrics such as precision, accuracy, and coverage can be calculated using ground truth labels to help in model tuning, evaluation, and selection. In an unsupervised setting, however, where the data has no ground truth, there are few interpretable metrics that can guide us to do the same. Our approach creates a framework to adapt the Intersection over Union metric, referred to as Adapted IoU, usually used to evaluate supervised learning models, into the unsupervised domain, which solves the problem by factoring in subject matter expertise and intuition about the ideal output from the model. This metric essentially provides a scale that allows us to compare the performance across numerous unsupervised models or tune hyper-parameters and compare different versions of the same model.

Keywords: general metric, unsupervised learning, classification, intersection over union

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Authors: Khizar Samiullah Samiullah, Riffat Yasin, Khurrum Feroz, Omer Draz, Memmona Nazish

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New fossil remains of artiodactyl have been recovered from three Late Miocene localities, Lava, Dhok Bun Ameer Khatoon and Hasnoot. These localities belong to lower and middle Siwalik Hills of Pakistan, the Chinji and Dhok Pathan Formation respectively and are remarkably rich in fossils of artiodactyl. The fauna mainly comprises various families of order Artiodactyla; Cervidae, Equidea, Proboscidea, Giraffidea, Rhinocerotidae, Tragulidea, Suidae and Primates. In Chinji Formation Lava and Dhok Bun Ameer Khatoon are located in district Chakwal while in Upper Dhok Pathan Formation the best fossils exposure site is Hasnoot which is located in District Jhelum, Punjab, Pakistan. Specimens described and discussed here include right and left maxilla, isolated upper premolars and molars which have been collected during extensive fieldwork. After morphological and comparative analysis the collection is attributed to Giraffokeryx, Giraffa, Listriodon, Dorcatherium, Selenoportax and Pachyportax. In this study evolutionary status, taxonomy and biogeographical distribution as well as the relationship of different Artiodactyls have been discussed comprehensively. The Palaeoenvironmental studies reveal the persistence of mosaics of diverse habitats ranging from tropical evergreen forest to subtropical ones, closed seasonal woodlands to wooded savannas during the deposition of these outcrops.

Keywords: Artiodactyla, fossil dentition, late Miocene, lower and middle Siwaliks

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Authors: Nor Fazlina Iryani Abdul Hamid, Mohamad Khatim Hasan

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Evolution of software quality measurement has been started since McCall introduced his quality model in year 1977. Starting from there, several software quality models and software quality measurement methods had emerged but none of them focused on telecommunication industry. In this paper, the implementation of software quality measurement system for telecommunication industry was compulsory to accommodate the rapid growth of telecommunication industry. The quality value of the telecommunication related software could be calculated using this system by entering the required parameters. The system would calculate the quality value of the measured system based on predefined quality metrics and aggregated by referring to the quality model. It would classify the quality level of the software based on Net Satisfaction Index (NSI). Thus, software quality measurement system was important to both developers and users in order to produce high quality software product for telecommunication industry.

Keywords: software quality, quality measurement, quality model, quality metric, net satisfaction index

Procedia PDF Downloads 596

Authors: Mohamed A. Hammad, Dzul Azri Mohamed Noor, Syed Azhar Syed Sulaiman, Majed Ahmed Al-Mansoub, Muhammad Qamar

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There is a progressive increase in the prevalence of early onset Type 2 diabetes mellitus. Early detection of Type 2 diabetes enhances the length and/or quality of life which might result from a reduction in the severity, frequency or prevent or delay of its long-term complications. The study aims to determine the onset age for the first diagnosis of Type 2 diabetes mellitus. A retrospective study conducted in the endocrine clinic at Hospital Pulau Pinang in Penang, Malaysia, January- December 2016. Records of 519 patients with Type 2 diabetes mellitus were screened to collect demographic data and determine the age of first-time diabetes mellitus diagnosis. Patients classified according to the age of diagnosis, gender, and ethnicity. The study included 519 patients with age (55.6±13.7) years, female 265 (51.1%) and male 254 (48.9%). The ethnicity distribution was Malay 191 (36.8%), Chinese 189 (36.4%) and Indian 139 (26.8%). The age of Type 2 diabetes diagnosis was (42±14.8) years. The female onset of diabetes mellitus was at age (41.5±13.7) years, while male (42.6±13.7) years. Distribution of diabetic onset by ethnicity was Malay at age (40.7±13.7) years, Chinese (43.2±13.7) years and Indian (42.3±13.7) years. Diabetic onset was classified by age as follow; ≤20 years’ cohort was 33 (6.4%) cases. Group >20- ≤40 years was 190 (36.6%) patients, and category >40- ≤60 years was 270 (52%) subjects. On the other hand, the group >60 years was 22 (4.2%) patients. The range of diagnosis was between 10 and 73 years old. Conclusion: Malay and female have an earlier onset of diabetes than Indian, Chinese and male. More than half of the patients had diabetes between 40 and 60 years old. Diabetes mellitus is becoming more common in younger age <40 years. The age at diagnosis of Type 2 diabetes mellitus has decreased with time.

Keywords: age of onset, diabetes diagnosis, diabetes mellitus, Malaysia, outpatients, type 2 diabetes, retrospective study

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Authors: Sourour Chaabane, Davide Clematis, Marco Panizza

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This study investigates the oxidation of Erythrosine B (EB) food dye by a homogeneous electro-Fenton process using iron (II) sulfate heptahydrate as a catalyst, carbon felt as cathode, and Ti/RuO2. The treated synthetic wastewater contains 100 mg L⁻¹ of EB and has a pH = 3. The effects of three independent variables have been considered for process optimization, such as applied current intensity (0.1 – 0.5 A), iron concentration (1 – 10 mM), and stirring rate (100 – 1000 rpm). Their interactions were investigated considering response surface methodology (RSM) based on Doehlert design as optimization method. EB removal efficiency and energy consumption were considered model responses after 30 minutes of electrolysis. Analysis of variance (ANOVA) revealed that the quadratic model was adequately fitted to the experimental data with R² (0.9819), adj-R² (0.9276) and low Fisher probability (< 0.0181) for EB removal model, and R² (0.9968), adj-R² (0.9872) and low Fisher probability (< 0.0014) relative to the energy consumption model reflected a robust statistical significance. The energy consumption model significantly depends on current density, as expected. The foregoing results obtained by RSM led to the following optimal conditions for EB degradation: current intensity of 0.2 A, iron concentration of 9.397 mM, and stirring rate of 500 rpm, which gave a maximum decolorization rate of 98.15 % with a minimum energy consumption of 0.74 kWh m⁻³ at 30 min of electrolysis.

Keywords: electrofenton, erythrosineb, dye, response serface methdology, carbon felt

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Authors: Xia Yang, Zheng Yang, Haiyong Sun, Yan Fang, Jingyu Liu, Jia Song

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The smart contract in Ethereum is a unique program deployed on the Ethereum Virtual Machine (EVM) to help manage cryptocurrency. The security of this smart contract is critical to Ethereum’s operation and highly sensitive. In this paper, we present a formal model for smart contract, using the separated term-obligation (STO) strategy to formalize and verify the smart contract. We use the IBM smart sponsor contract (SSC) as an example to elaborate the detail of the formalizing process. We also propose a formal smart sponsor contract model (FSSCM) and verify SSC’s security properties with an interactive theorem prover Coq. We found the 'Unchecked-Send' vulnerability in the SSC, using our formal model and verification method. Finally, we demonstrate how we can formalize and verify other smart contracts with this approach, and our work indicates that this formal verification can effectively verify the correctness and security of smart contracts.

Keywords: smart contract, formal verification, Ethereum, Coq

Procedia PDF Downloads 698

Authors: Svetlana Guryeva, Inna Kornienko, Elena Petersen

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At present, translational medicine is a rapidly developing branch of biomedicine. The main idea of translational medicine is a practical application of fundamental research. One of the possible applications for translational medicine is researching therapies that improve human age-related organism condition. To fill the gap between experiments and clinical practice, it is necessary to create the standardized system for the investigation of different effects on cellular aging models. In this study, primary human fibroblasts derived from patients of different ages were used as a cellular aging model. The senescence-associated β-galactosidase activity, lipofuscin, γ-H2AX, the reactive oxygen species level, and cell death markers (annexin V/propidium iodide) were used as biomarkers of the cell functional state. The effects of damaging exposures (oxidative stress and heat shock), potential positive factors (metformin and acetaminophen), and their combinations were investigated using the described biomarkers. Oxidative stress and heat shock caused the increase in the levels of all biomarkers, and only the cells from young patients partly coped with stress 3 days after the exposures. Metformin improved the state of pretreatment cells from young and old patients. The acetaminophen did not show significant changes in the biomarker levels compare to the action of metformin. This study proved the opportunity to develop a standardized screening system based on biomarkers of the cell functional state to identify potential positive or negative effects of some physical and chemical exposures. Moreover, such a system can be useful for the aims of regenerative medicine to determine the effect of cell pretreatment before transplantation.

Keywords: biomarkers, primary fibroblasts, regenerative medicine, senescence, test system, translational medicine

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Authors: Farnaz Fotovvatikhah, Javad Akbari

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Test time of a test architecture is an important factor which depends on the architecture's delay and test patterns. Here a new architecture to store the test results based on network on chip is presented. In addition, simple analytical model is proposed to calculate link test time for built in self-tester (BIST) and external tester (Ext) in multiprocessor systems. The results extracted from the model are verified using FPGA implementation and experimental measurements. Systems consisting 16, 25, and 36 processors are implemented and simulated and test time is calculated. In addition, BIST and Ext are compared in terms of test time at different conditions such as at different number of test patterns and nodes. Using the model the maximum frequency of testing could be calculated and the test structure could be optimized for high speed testing.

Keywords: test, nano on-chip network, JTAG, modelling

Procedia PDF Downloads 492

Authors: Mohamed El Hachimi, Abdelhakim Ballouk, Ilyas Khelafa, Abdelaziz Mouhou

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Introduction: Type 1 diabetes occurs when beta cells are destroyed by the body's own immune system. Treatment of type 1 diabetes mellitus could be greatly improved by applying a closed-loop control strategy to insulin delivery, also known as an Artificial Pancreas (AP). Method: In this paper, we present a new formulation of the cost function for a Model Predictive Control (MPC) utilizing a technic which accelerates the speed of control of the AP and tackles the nonlinearity of the control problem via asymmetric objective functions. Finding: The finding of this work consists in a new Model Predictive Control algorithm that leads to good performances like decreasing the time of hyperglycaemia and avoiding hypoglycaemia. Conclusion: These performances are validated under in silico trials.

Keywords: artificial pancreas, control algorithm, biomedical control, MPC, objective function, nonlinearity

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Authors: Kolja Them, Johannes Salamon, Harald Ittrich, Michael Kaul, Tobias Knopp

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Superparamagnetic iron oxide nanoparticles (SPIONs) are nanoscale magnets which can be biologically functionalized for biomedical applications. Stem cell therapies to repair damaged tissue, magnetic fluid hyperthermia for cancer therapy and targeted drug delivery based on SPIONs are prominent examples where the visualization of a preferably low concentrated SPION distribution is essential. In 2005 a new method for tomographic SPION imaging has been introduced. The method named magnetic particle imaging (MPI) takes advantage of the nanoparticles magnetization change caused by an oscillating, external magnetic field and allows to directly image the time-dependent nanoparticle distribution. The SPION magnetization can be changed by the electron spin dynamics as well as by a mechanical rotation of the nanoparticle. In this work different calibration methods in MPI are investigated for image reconstruction of magnetically labeled stem cells. It is shown that a calibration using rotationally immobilized SPIONs provides a higher quality of stem cell images with fewer artifacts than a calibration using mobile SPIONs. The enhancement of the image quality and the reduction of artifacts enables the localization and identification of a smaller number of magnetically labeled stem cells. This is important for future medical applications where low concentrations of functionalized SPIONs interacting with biological matter have to be localized.

Keywords: biomedical imaging, iron oxide nanoparticles, magnetic particle imaging, stem cell imaging

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Authors: K. R. Sultana, K. Pope, Y. S. Muzychka

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In recent years, the research of heat transfer or phase change phenomena of liquid water droplets experiences a growing interest in aircraft icing, power transmission line icing, marine icing and wind turbine icing applications. This growing interest speeding up the research from single to multiple droplet phenomena. Impingements of multiple droplets and the resulting solidification phenomena after impact on a very cold surface is computationally studied in this paper. The model used in the current study solves the flow equation, composed of energy balance and the volume fraction equations. The main aim of the study is to investigate the effects of several thermo-physical properties (density, thermal conductivity and specific heat) on droplets freezing. The outcome is examined by various important factors, for instance, liquid fraction, total freezing time, droplet temperature and total heat transfer rate in the interface region. The liquid fraction helps to understand the complete phase change phenomena during solidification. Temperature distribution and heat transfer rate help to demonstrate the overall thermal exchange behaviors between the droplets and substrate surface. Findings of this research provide an important technical achievement for ice modeling and prediction studies.

Keywords: droplets, CFD, thermos-physical properties, solidification

Procedia PDF Downloads 246

Authors: Peter K. Galenko, Stefanie Koch, Markus Rettenmayr, Robert Wonneberger, Evgeny V. Kharanzhevskiy, Maria Zamoryanskaya, Vladimir Ankudinov

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We analyze the structure of undercooled melts, crystal growth kinetics and amorphous/crystalline microstructure of rapidly solidifying glass-forming Pd-based and CuZr-based alloys. A dendrite growth model is developed using a combination of the kinetic phase-field model and mesoscopic sharp interface model. The model predicts features of crystallization kinetics in alloys from thermodynamically controlled growth (governed by the Gibbs free energy change on solidification) to the kinetically limited regime (governed by atomic attachment-detachment processes at the solid/liquid interface). Comparing critical undercoolings observed in the crystallization kinetics with experimental data on melt viscosity, atomistic simulation's data on liquid microstructure and theoretically predicted dendrite growth velocity allows us to conclude that the dendrite growth kinetics strongly depends on the cluster structure changes of the melt. The obtained data of theoretical and experimental investigations are used for interpretation of microstructure of samples processed in electro-magnetic levitator on board International Space Station in the frame of the project "MULTIPHAS" (European Space Agency and German Aerospace Center, 50WM1941) and "KINETIKA" (ROSKOSMOS).

Keywords: dendrite, kinetics, model, solidification

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Authors: Nina Philipova

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The influence of the geometric parameters of trapezoidal labyrinth channel on the pressure losses along the labyrinth length is investigated in this work. The impact of the dentate height is studied at fixed values of the dentate angle and the dentate spacing. The objective of the work presented in this paper is to derive a mathematical model of the pressure losses along the labyrinth length depending on the dentate height. The numerical simulations of the water flow movement are performed by using Commercial codes ANSYS GAMBIT and FLUENT. Dripper inlet pressure is set up to be 1 bar. As a result, the mathematical model of the pressure losses is determined as a second-order polynomial by means Commercial code STATISTIKA. Bi-objective optimization is performed by using the mean algebraic function of utility. The optimum value of the dentate height is defined at fixed values of the dentate angle and the dentate spacing. The derived model of the pressure losses and the optimum value of the dentate height are used as a basis for a more successful emitter design.

Keywords: drip irrigation, labyrinth channel hydrodynamics, numerical simulations, Reynolds stress model

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Authors: Megha Agarwal

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The research paper is an effort to compare the earnings based and cash flow based methods of valuation of an enterprise. The theoretically equivalent methods based on either earnings such as Residual Earnings Model (REM), Abnormal Earnings Growth Model (AEGM), Residual Operating Income Method (ReOIM), Abnormal Operating Income Growth Model (AOIGM) and its extensions multipliers such as price/earnings ratio, price/book value ratio; or cash flow based models such as Dividend Valuation Method (DVM) and Free Cash Flow Method (FCFM) all provide different estimates of valuation of the Indian giant corporate Reliance India Limited (RIL). An ex-post analysis of published accounting and financial data for four financial years from 2008-09 to 2011-12 has been conducted. A comparison of these valuation estimates with the actual market capitalization of the company shows that the complex accounting based model AOIGM provides closest forecasts. These different estimates may be derived due to inconsistencies in discount rate, growth rates and the other forecasted variables. Although inputs for earnings based models may be available to the investor and analysts through published statements, precise estimation of free cash flows may be better undertaken by the internal management. The estimation of value from more stable parameters as residual operating income and RNOA could be considered superior to the valuations from more volatile return on equity.

Keywords: earnings, cash flows, valuation, Residual Earnings Model (REM)

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Authors: Jingjue Bao, Ye Li, Yujie Qi

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The explosive growth of ride-hailing has reshaped residents' travel behavior and plays a crucial role in urban mobility within the built environment. Contributing to the research of the spatial variation of ride-hailing demand and its relationship to the built environment and socioeconomic factors, this study utilizes multi-source data from Haikou, China, to construct a Multi-scale Geographically Weighted Regression model (MGWR), considering spatial scale heterogeneity. The regression results showed that MGWR model was demonstrated superior interpretability and reliability with an improvement of 3.4% on R2 and from 4853 to 4787 on AIC, compared with Geographically Weighted Regression model (GWR). Furthermore, to precisely identify the surrounding environment of sampling point, DeepLabv3+ model is employed to segment street-level images. Features extracted from these images are incorporated as variables in the regression model, further enhancing its rationality and accuracy by 7.78% improvement on R2 compared with the MGWR model only considered region-level variables. By integrating multi-scale geospatial data and utilizing advanced computer vision techniques, this study provides a comprehensive understanding of the spatial dynamics between ride-hailing demand and the urban built environment. The insights gained from this research are expected to contribute significantly to urban transportation planning and policy making, as well as ride-hailing platforms, facilitating the development of more efficient and effective mobility solutions in modern cities.

Keywords: travel behavior, ride-hailing, spatial relationship, built environment, street-level image

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Authors: Vedat Senol, Gursoy Turan, Anders Helmersson, Vortechz Andersson

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In developing a mathematical model of a real structure, the simulation results of the model may not match the real structural response. This is a general problem that arises during dynamic motion of the structure, which may be modeled by means of parameter variations in the stiffness, damping, and mass matrices. These changes in parameters need to be estimated, and the mathematical model is updated to obtain higher control performances and robustness. In this study, a linear fractional transformation (LFT) is utilized for uncertainty modeling. Further, a general approach to the design of an H∞ control of a magneto-rheological damper (MRD) for vibration reduction in a building with mass, damping, and stiffness uncertainties is presented.

Keywords: uncertainty modeling, structural control, MR Damper, H∞, robust control

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Authors: Z. Jovanovic, Z. Masonicic, S. Dragutinovic, Z. Sakota

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In this paper, a methodology for noise reduction of motor vehicles in use is presented. The methodology relies on synergic model of noise generation as a function of time. The arbitrary number of motor vehicle noise sources act in concert yielding the generation of the overall noise level of motor vehicle thereafter. The number of noise sources participating in the overall noise level of motor vehicle is subjected to the constraint of the calculation of the acoustic potential of each noise source under consideration. It is the prerequisite condition for the calculation of the acoustic potential of the whole vehicle. The recast form of pertinent set of equations describing the synergic model is laid down and solved by dint of Gauss method. The bunch of results emerged and some of them i.e. those ensuing from model application to MDD FAP Priboj motor vehicle in use are particularly elucidated.

Keywords: noise abatement, MV noise sources, noise source identification, muffler

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Authors: Reza Mohammadzadeh

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The major challenges in geotechnical engineering in underground spaces arise from uncertainties and different probabilities. The collection, collation, and collaboration of existing data to incorporate them in analysis and design for given prospect evaluation would be a reliable, practical problem solving method under uncertainty. Machine learning (ML) is a subfield of artificial intelligence in statistical science which applies different techniques (e.g., Regression, neural networks, support vector machines, decision trees, random forests, genetic programming, etc.) on data to automatically learn and improve from them without being explicitly programmed and make decisions and predictions. In this paper, a conceptual database schema of geotechnical risks in underground coal mining based on a cloud system architecture has been designed. A new approach of risk assessment using a three-dimensional risk matrix supported by the level of knowledge (LoK) has been proposed in this model. Subsequently, the model workflow methodology stages have been described. In order to train data and LoK models deployment, an ML platform has been implemented. IBM Watson Studio, as a leading data science tool and data-driven cloud integration ML platform, is employed in this study. As a Use case, a data set of geotechnical hazards and risk assessment in underground coal mining were prepared to demonstrate the performance of the model, and accordingly, the results have been outlined.

Keywords: data model, geotechnical risks, machine learning, underground coal mining

Procedia PDF Downloads 280

Authors: Emmanuel Chibuogu Asogwa, Tochukwu Sunday Belonwu

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An urgent demand for creative solutions has been created by the rapid expansion of medical knowledge, the complexity of patient care, and the requirement for more precise decision-making. As a solution to this problem, the creation of a Medical Intelligent Process Model (MIPM) utilizing ontology-based appears as a promising way to overcome this obstacle and unleash the full potential of healthcare systems. The development of a Medical Intelligent Process Model (MIPM) using ontology-based techniques is motivated by a lack of quick access to relevant medical information and advanced tools for treatment planning and clinical decision-making, which ontology-based techniques can provide. The aim of this work is to develop a structured and knowledge-driven framework that leverages ontology, a formal representation of domain knowledge, to enhance various aspects of healthcare. Object-Oriented Analysis and Design Methodology (OOADM) were adopted in the design of the system as we desired to build a usable and evolvable application. For effective implementation of this work, we used the following materials/methods/tools: the medical dataset for the test of our model in this work was obtained from Kaggle. The ontology-based technique was used with Confusion Matrix, MySQL, Python, Hypertext Markup Language (HTML), Hypertext Preprocessor (PHP), Cascaded Style Sheet (CSS), JavaScript, Dreamweaver, and Fireworks. According to test results on the new system using Confusion Matrix, both the accuracy and overall effectiveness of the medical intelligent process significantly improved by 20% compared to the previous system. Therefore, using the model is recommended for healthcare professionals.

Keywords: ontology-based, model, database, OOADM, healthcare

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Authors: B. R. Shen, J. R. Wang, J. H. Yang, S. W. Chen, C. Shih, Y. Chiang, Y. F. Chang, Y. H. Huang

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In this research, TRACE code with the interface code-SNAP was used to simulate and analyze the SBO (station blackout) accident which occurred in Maanshan PWR (pressurized water reactor) nuclear power plant (NPP). There are four main steps in this research. First, the SBO accident data of Maanshan NPP were collected. Second, the TRACE/SNAP model of Maanshan NPP was established by using these data. Third, this TRACE/SNAP model was used to perform the simulation and analysis of SBO accident. Finally, the simulation and analysis of SBO with mitigation equipments was performed. The analysis results of TRACE are consistent with the data of Maanshan NPP. The mitigation equipments of Maanshan can maintain the safety of Maanshan in the SBO according to the TRACE predictions.

Keywords: pressurized water reactor (PWR), TRACE, station blackout (SBO), Maanshan

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Authors: Aber Aboalgasm, Rupert Ward, Ruth Taylor, Jonathan Glazzard

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Teaching art by digital means is a big challenge for the majority of teachers of art and artistic design courses in primary education schools. These courses can clearly identify relationships between art, technology, and creativity in the classroom .The aim of this article is to present a modern way of teaching art, using digital tools in the art classroom in order to improve creative ability in pupils aged between 9 and 11 years; it also presents a conceptual model for creativity based on digital art. The model could be useful for pupils interested in learning drawing and using an e-drawing package, and for teachers who are interested in teaching their students modern digital art, and improving children’s creativity. This model is designed to show the strategy of teaching art through technology, in order for children to learn how to be creative. This will also help education providers to make suitable choices about which technological approaches they should choose to teach students and enhance their creative ability. It is also expected that use of this model will help to develop social interactive qualities that may improve intellectual ability.

Keywords: digital tools, motivation, creative activity, education

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Authors: Akshay Paranjape, Nils Plettenberg, Robert Schmitt

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Producing faulty products can be costly for manufacturing companies and wastes resources. To reduce scrap rates in manufacturing, process parameters can be optimized using machine learning. Thus far, research mainly focused on optimizing specific processes using traditional algorithms. To develop a framework that enables real-time optimization based on a predictive model for an arbitrary production process, this study explores the application of reinforcement learning (RL) in this field. Based on a thorough review of literature about RL and process parameter optimization, a model based on maximum a posteriori policy optimization that can handle both numerical and categorical parameters is proposed. A case study compares the model to state–of–the–art traditional algorithms and shows that RL can find optima of similar quality while requiring significantly less time. These results are confirmed in a large-scale validation study on data sets from both production and other fields. Finally, multiple ways to improve the model are discussed.

Keywords: reinforcement learning, production process optimization, evolutionary algorithms, policy optimization, actor critic approach

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Authors: Mohamed Malek Khenissi, Mohamed Montassar Ben Slama, Anis Belhaj Mohamed, Moncef Saidi

Abstract:

Northern Tunisia is well known by its different and complex structural and geological zones that have been the result of a geodynamic history that extends from the early Mesozoic era to the actual period. One of these zones is the salt province, where the Halokinesis process is manifested by a number of NE/SW salt structures such as Jebel Ech-Cheid which represents masses of materials characterized by a high plasticity and low density. The salt masses extrusions that have been developed due to an extension that started from the late Triassic to late Cretaceous. The evolution of salt bodies within sedimentary basins have not only contributed to modify the architecture of the basin, but it also has certain geochemical effects which touch mainly source rocks that surround it. It has been demonstrated that the presence of salt structures within sedimentary basins can influence its temperature distribution and thermal history. Moreover, it has been creating heat flux anomalies that may affect the maturity of organic matter and the timing of hydrocarbon generation. Field samples of the Bahloul source rock (Cenomanan-Tunonian) were collected from different sights from all around Ech Cheid salt structure and evaluated using Rock-eval pyrolysis and GC/MS techniques in order to assess the degree of maturity evolution and the heat flux anomalies in the different zones analyze. The Total organic Carbon (TOC) values range between 1 to 9% and the (Tmax) ranges between 424 and 445°C, also the distribution of the source rock biomarkers both saturated and aromatic changes in a regular fashions with increasing maturity and this are shown in the chromatography results such as Ts/(Ts+Tm) ratios, 22S/(22S+22R) values for C31 homohopanes, ββ/(ββ+αα)20R and 20S/(20S+20R) ratios for C29 steranes which gives a consistent maturity indications and assessment of the field samples. These analyses are carried to interpret the maturity evolution and the heat flux around Ech Cheid salt structure through the geological history. These analyses also aim to demonstrate that the salt structure can have a direct effect on the geothermal gradient of the basin and on the maturity of the Bahloul Formation source rock. The organic matter has reached different stages of thermal maturity, but delineate a general increasing maturity trend. Our study confirms that the J. Ech Cheid salt body have on the first hand: a huge influence on the local distribution of anoxic depocentre at least within Cenomanian-Turonian time. In the second hand, the thermal anomaly near the salt mass has affected the maturity of Bahloul Formation.

Keywords: Bahloul formation, depocentre, GC/MS, rock-eval

Procedia PDF Downloads 244

Authors: Y. Galerkin, K. Soldatova, A. Drozdov

Abstract:

The 6th version of Universal modeling method for centrifugal compressor stage calculation is described. Identification of the new mathematical model was made. As a result of identification the uniform set of empirical coefficients is received. The efficiency definition error is 0,86 % at a design point. The efficiency definition error at five flow rate points (except a point of the maximum flow rate) is 1,22 %. Several variants of the stage with 3D impellers designed by 6th version program and quasi three-dimensional calculation programs were compared by their gas dynamic performances CFD (NUMECA FINE TURBO). Performance comparison demonstrated general principles of design validity and leads to some design recommendations.

Keywords: compressor design, loss model, performance prediction, test data, model stages, flow rate coefficient, work coefficient

Procedia PDF Downloads 414