Search results for: Residual Earnings Model (REM)

Authors: Sumanpreet Kaur, Harjit Pal Singh, Vikas Khullar

Abstract:

In Wireless Sensor Network (WSN), the sensor containing motes (nodes) incorporate batteries that can lament at some extent. To upgrade the energy utilization, clustering is one of the prototypical approaches for split sensor motes into a number of clusters where one mote (also called as node) proceeds as a Cluster Head (CH). CH selection is one of the optimization techniques for enlarging stability and network lifespan. Deterministic Stable Election Protocol (DSEP) is an effectual clustering protocol that makes use of three kinds of nodes with dissimilar residual energy for CH election. Fuzzy Logic technology is used to expand energy level of DSEP protocol by using fuzzy inference system. This paper presents protocol DSEP using Fuzzy Logic (DSEP-FL) CH by taking into account four linguistic variables such as energy, concentration, centrality and distance to base station. Simulation results show that our proposed method gives more effective results in term of a lifespan of network and stability as compared to the performance of other clustering protocols.

Keywords: DSEP, fuzzy logic, energy model, WSN

Procedia PDF Downloads 202

Authors: Kingsley Nnaemeka Ogbu, Constantine Mbajiorgu

Abstract:

Vegetation has a marked effect on runoff and has become an important component in hydrologic model. The watershed Resources Management (WRM) model, a process-based, continuous, distributed parameter simulation model developed for hydrologic and soil erosion studies at the watershed scale lack a crop growth component. As such, this model assumes a constant parameter values for vegetation and hydraulic parameters throughout the duration of hydrologic simulation. Our approach is to develop a crop growth algorithm based on the original plant growth model used in the Environmental Policy Integrated Climate Model (EPIC) model. This paper describes the development of a single crop growth model which has the capability of simulating all crops using unique parameter values for each crop. Simulated crop growth processes will reflect the vegetative seasonality of the natural watershed system. An existing model was employed for evaluating vegetative resistance by hydraulic and vegetative parameters incorporated into the WRM model. The improved WRM model will have the ability to evaluate the seasonal variation of the vegetative roughness coefficient with depth of flow and further enhance the hydrologic model’s capability for accurate hydrologic studies.

Keywords: runoff, roughness coefficient, PAR, WRM model

Procedia PDF Downloads 371

Authors: Varun Agarwal

Abstract:

Introduction: With the advent of personalized medicine, histopathological review of whole slide images (WSIs) for cancer diagnosis presents an exceedingly time-consuming, complex task. Specifically, detecting metastatic regions in WSIs of sentinel lymph node biopsies necessitates a full-scanned, holistic evaluation of the image. Thus, digital pathology, low-level image manipulation algorithms, and machine learning provide significant advancements in improving the efficiency and accuracy of WSI analysis. Using Camelyon16 data, this paper proposes a deep learning pipeline to automate and ameliorate breast cancer metastasis localization and WSI classification. Methodology: The model broadly follows five stages -region of interest detection, WSI partitioning into image tiles, convolutional neural network (CNN) image-segment classifications, probabilistic mapping of tumor localizations, and further processing for whole WSI classification. Transfer learning is applied to the task, with the implementation of Inception-ResNetV2 - an effective CNN classifier that uses residual connections to enhance feature representation, adding convolved outputs in the inception unit to the proceeding input data. Moreover, in order to augment the performance of the transfer learning CNN, a stack of convolutional denoising autoencoders (CDAE) is applied to produce embeddings that enrich image representation. Through a saliency-detection algorithm, visual training segments are generated, which are then processed through a denoising autoencoder -primarily consisting of convolutional, leaky rectified linear unit, and batch normalization layers- and subsequently a contrast-normalization function. A spatial pyramid pooling algorithm extracts the key features from the processed image, creating a viable feature map for the CNN that minimizes spatial resolution and noise. Results and Conclusion: The simplified and effective architecture of the fine-tuned transfer learning Inception-ResNetV2 network enhanced with the CDAE stack yields state of the art performance in WSI classification and tumor localization, achieving AUC scores of 0.947 and 0.753, respectively. The convolutional feature retention and compilation with the residual connections to inception units synergized with the input denoising algorithm enable the pipeline to serve as an effective, efficient tool in the histopathological review of WSIs.

Keywords: breast cancer, convolutional neural networks, metastasis mapping, whole slide images

Procedia PDF Downloads 126

Authors: Masahiro Ohmura, Koh Kakusho, Takeshi Okadome

Abstract:

This paper presents a regression model with autocorrelated errors in which the inputs are social moods obtained by analyzing the adjectives in Twitter posts using a document topic model. The regression model predicts Dow Jones Industrial Average (DJIA) more precisely than autoregressive moving-average models.

Keywords: stock market prediction, social moods, regression model, DJIA

Procedia PDF Downloads 542

Authors: Paola Bordon, Breno Braga

Abstract:

This paper investigates whether firms use university prestige to statistically discriminate among college graduates. The test is based on the employer learning literature which suggests that if firms use a characteristic for statistical discrimination, this variable should become less important for earnings as a worker gains labor market experience. In this framework, we use a regression discontinuity design to estimate a 19% wage premium for recent graduates of two of the most selective universities in Chile. However, we find that this premium decreases by 3 percentage points per year of labor market experience. These results suggest that employers use college selectivity as a signal of workers' quality when they leave school. However, as workers reveal their productivity throughout their careers, they become rewarded based on their true quality rather than the prestige of their college.

Keywords: employer learning, statistical discrimination, college returns, college selectivity

Procedia PDF Downloads 576

Authors: Adji Achmad Rinaldo Fernandes

Abstract:

SEM analysis is a complex multivariate analysis because it involves a number of exogenous and endogenous variables that are interconnected to form a model. The measurement model is divided into two, namely, the reflective model (reflecting) and the formative model (forming). Before carrying out further tests on SEM, there are assumptions that must be met, namely the linearity assumption, to determine the form of the relationship. There are three modeling approaches to path analysis, including parametric, nonparametric and semiparametric approaches. The aim of this research is to develop semiparametric SEM and obtain the best model. The data used in the research is secondary data as the basis for the process of obtaining simulation data. Simulation data was generated with various sample sizes of 100, 300, and 500. In the semiparametric SEM analysis, the form of the relationship studied was determined, namely linear and quadratic and determined one and two knot points with various levels of error variance (EV=0.5; 1; 5). There are three levels of closeness of relationship for the analysis process in the measurement model consisting of low (0.1-0.3), medium (0.4-0.6) and high (0.7-0.9) levels of closeness. The best model lies in the form of the relationship X1Y1 linear, and. In the measurement model, a characteristic of the reflective model is obtained, namely that the higher the closeness of the relationship, the better the model obtained. The originality of this research is the development of semiparametric SEM, which has not been widely studied by researchers.

Keywords: semiparametric SEM, measurement model, structural model, reflective model, formative model

Procedia PDF Downloads 34

Authors: Eunji Choi, Borang Park, Youngjae Choi, Jinwoo Moon

Abstract:

In this study, a predictive model for estimating the metabolism (MET) of human body was developed for the optimal control of indoor thermal environment. Human body images for indoor activities and human body joint coordinated values were collected as data sets, which are used in predictive model. A deep learning algorithm was used in an initial model, and its number of hidden layers and hidden neurons were optimized. Lastly, the model prediction performance was analyzed after the model being trained through collected data. In conclusion, the possibility of MET prediction was confirmed, and the direction of the future study was proposed as developing various data and the predictive model.

Keywords: deep learning, indoor quality, metabolism, predictive model

Procedia PDF Downloads 251

Authors: Alan Wan

Abstract:

In recent years, the body of literature on frequentist model averaging in statistics has grown significantly. Most of this work focuses on models with different mean structures but leaves out the variance consideration. In this paper, we consider a regression model with multiplicative heteroscedasticity and develop a model averaging method that combines maximum likelihood estimators of unknown parameters in both the mean and variance functions of the model. Our weight choice criterion is based on a minimisation of a plug-in estimator of the model average estimator's squared prediction risk. We prove that the new estimator possesses an asymptotic optimality property. Our investigation of finite-sample performance by simulations demonstrates that the new estimator frequently exhibits very favourable properties compared to some existing heteroscedasticity-robust model average estimators. The model averaging method hedges against the selection of very bad models and serves as a remedy to variance function misspecification, which often discourages practitioners from modeling heteroscedasticity altogether. The proposed model average estimator is applied to the analysis of two real data sets.

Keywords: heteroscedasticity-robust, model averaging, multiplicative heteroscedasticity, plug-in, squared prediction risk

Procedia PDF Downloads 378

Authors: Myung Hwan Na, Ho- Chun Song, EunHee Hong

Abstract:

We widely use normal linear mixed-effects model to analysis data in repeated measurement. In case of detecting heteroscedasticity and the non-normality of the population distribution at the same time, normal linear mixed-effects model can give improper result of analysis. To achieve more robust estimation, we use heavy tailed linear mixed-effects model which gives more exact and reliable analysis conclusion than standard normal linear mixed-effects model.

Keywords: reliability, tires, field data, linear mixed-effects model

Procedia PDF Downloads 562

Authors: Gaurav D. Sonawane, Vikas G. Sargade

Abstract:

The present investigation is a study of the effect of advanced Physical Vapor Deposition (PVD) coatings on cutting temperature residual stresses and surface roughness during Duplex Stainless Steel (DSS) 2205 turning. Austenite stabilizers like nickel, manganese, and molybdenum reduced the cost of DSS. Surface Integrity (SI) plays an important role in determining corrosion resistance and fatigue life. Resistance to various types of corrosion makes DSS suitable for applications with critical environments like Heat exchangers, Desalination plants, Seawater pipes and Marine components. However, lower thermal conductivity, poor chip control and non-uniform tool wear make DSS very difficult to machine. Cemented carbide tools (M grade) were used to turn DSS in a dry environment. AlTiN and AlTiCrN coatings were deposited using advanced PVD High Pulse Impulse Magnetron Sputtering (HiPIMS) technique. Experiments were conducted with cutting speed of 100 m/min, 140 m/min and 180 m/min. A constant feed and depth of cut of 0.18 mm/rev and 0.8 mm were used, respectively. AlTiCrN coated tools followed by AlTiN coated tools outperformed uncoated tools due to properties like lower thermal conductivity, higher adhesion strength and hardness. Residual stresses were found to be compressive for all the tools used for dry turning, increasing the fatigue life of the machined component. Higher cutting temperatures were observed for coated tools due to its lower thermal conductivity, which results in very less tool wear than uncoated tools. Surface roughness with uncoated tools was found to be three times higher than coated tools due to lower coefficient of friction of coating used.

Keywords: cutting temperature, DSS2205, dry turning, HiPIMS, surface integrity

Procedia PDF Downloads 128

Authors: R. Maher, D. Marchant, F. Fazel

Abstract:

Choking in sport has been defined as ‘an acute performance breakdown’, and is generally explained through a range of contributory antecedents, factors, and explanatory theories. The influence of mental antecedents on an athlete’s performance under pressure has been widely examined through numerous studies. Researchers have only recently begun to investigate the influence of physical effort and associated residual fatigue as a potential contributor to choking in sport. Consequently, the initial aim of the present study was to examine the extent to which both physical exertion and pressure affect free-throw shooting performance. It was hypothesized that the free-throw shooting scores would decline under manipulated conditions. Design and Methods: Using a within-subjects design, 50 student-athletes were assigned to four manipulated conditions: (a) higher pressure-running, (b) higher pressure-no running, (c) lower pressure-running, and (d) lower pressure-no running. The physical exertion was manipulated by including a 56 meter shuttle-run in two of the running conditions. The pressure was manipulated with the presence of an audience, video-recording, performance contingent rewards, and weighting successful shots in the higher pressure conditions. A repeated measure analysis of variance was used to analyse the data. Results: The free-throw performance significantly deteriorated under manipulated physical exertion F (1, 49) = 10.13, p = .003, ηp 2 = .17 and pressure conditions F (1, 49) = 5.25, p = .02, ηp 2 = .09. The lowest free-throw scores were observed in the higher pressure-running condition, whereas the highest free-throw scores were reported in the lower pressure-no running condition. Conclusions: Physical exertion and the associated residual fatigue were contributors to choking. The results of the present study herald a new concept in choking research and yield a practical platform for use by athletes, coaches, and sport psychologists to better manage the psychological and physiological aspects of performance under pressure.

Keywords: anxiety, basketball, choking, fatigue, free-throw shooting, physical exertion

Procedia PDF Downloads 283

Authors: Auezhan Amanov, Inho Cho, Young-Sik Pyun

Abstract:

Control element drive mechanism (CEDM) nozzle is manufactured as welded on the reactor vessel and currently uses Alloy 690 material. The top of the reactor is equipped with about 100 CEDM nozzles with an internal diameter of about 70 mm. Relatively large Inlet/Outlet nozzles are equipped with two outlet nozzles and four inlet nozzles on the reactor wall. The inner diameter of the nozzle is vulnerable to stress corrosion cracking (SCC), and in order to solve this problem, an ultrasonic nanocrystal surface modification (UNSM) treatment is performed on the inner diameter of the nozzle and the weld surface. The ultimate goal is to improve the service life of parts by applying compressive residual stress and suppressing primary water stress corrosion cracking (PWSCC). The main purpose is to design and fabricate a UNSM treatment device for the internal diameter processing of CEDM nozzles and inlet/outlet nozzles. In order to develop the system, the basic technology such as the development of UNSM tooling is developed and the mechanical properties and fatigue performance of before and after UNSM treatment of reactor nozzle material made of Ni-based alloys using the specimen are compared and evaluated. The inner diameter of the nozzle was treated by a newly developed UNSM treatment under the optimized treatment parameters. It was found that the mechanical properties and fatigue performance of nozzle were improved in comparison with the untreated nozzle, which may be attributed to the increase in hardness, induced compressive residual stress.

Keywords: control element drive mechanism nozzle, fatigue, Ni-based alloy, ultrasonic nanocrystal surface modification, UNSM

Procedia PDF Downloads 107

Authors: M. Mulumpwa, W. W. L. Jere, M. Lazaro, A. H. N. Mtethiwa

Abstract:

The study considered Seasonal Autoregressive Integrated Moving Average (SARIMA) processes to select an appropriate stochastic model to forecast the monthly data from the Lake Malawi water levels for the period 1986 through 2015. The appropriate model was chosen based on SARIMA (p, d, q) (P, D, Q)S. The Autocorrelation function (ACF), Partial autocorrelation (PACF), Akaike Information Criteria (AIC), Bayesian Information Criterion (BIC), Box–Ljung statistics, correlogram and distribution of residual errors were estimated. The SARIMA (1, 1, 0) (1, 1, 1)12 was selected to forecast the monthly data of the Lake Malawi water levels from August, 2015 to December, 2021. The plotted time series showed that the Lake Malawi water levels are decreasing since 2010 to date but not as much as was the case in 1995 through 1997. The future forecast of the Lake Malawi water levels until 2021 showed a mean of 474.47 m ranging from 473.93 to 475.02 meters with a confidence interval of 80% and 90% against registered mean of 473.398 m in 1997 and 475.475 m in 1989 which was the lowest and highest water levels in the lake respectively since 1986. The forecast also showed that the water levels of Lake Malawi will drop by 0.57 meters as compared to the mean water levels recorded in the previous years. These results suggest that the Lake Malawi water level may not likely go lower than that recorded in 1997. Therefore, utilisation and management of water-related activities and programs among others on the lake should provide room for such scenarios. The findings suggest a need to manage the Lake Malawi jointly and prudently with other stakeholders starting from the catchment area. This will reduce impacts of anthropogenic activities on the lake’s water quality, water level, aquatic and adjacent terrestrial ecosystems thereby ensuring its resilience to climate change impacts.

Keywords: forecasting, Lake Malawi, water levels, water level fluctuation, climate change, anthropogenic activities

Procedia PDF Downloads 223

Authors: Abdoullah Fath-Allah, Laila Cheikhi, Rafa E. Al-Qutaish, Ali Idri

Abstract:

The e-government emerging concept transforms the way in which the citizens are dealing with their governments. Thus, the citizens can execute the intended services online anytime and anywhere. This results in great benefits for both the governments (reduces the number of officers) and the citizens (more flexibility and time saving). Therefore, building a maturity model to assess the e-government portals becomes desired to help in the improvement process of such portals. This paper aims at proposing an e-government maturity model based on the measurement of the best practices’ presence. The main benefit of such maturity model is to provide a way to rank an e-government portal based on the used best practices, and also giving a set of recommendations to go to the higher stage in the maturity model.

Keywords: best practices, e-government portal, maturity model, quality model

Procedia PDF Downloads 329

Authors: Long Long Chen, Xinwei Liao, Shanfa Tang, Shaojing Jiang, Ruijia Tang, Rui Wang, Shu Yun Feng, Si Yao Wang

Abstract:

Tight oil reservoirs have poor physical properties, insufficient formation energy, and low natural productivity; it is necessary to effectively improve their crude oil recovery. CO₂ flooding is an important technical means to enhance oil recovery and achieve effective CO₂ storage in tight oil reservoirs, but its heterogeneity is strong, which makes CO₂ flooding prone to gas channeling and poor recovery. Aiming at the problem of gas injection channeling, combined with the excellent performance of low interfacial tension viscoelastic fluid (GOBTK), the research on CO₂-low interfacial tension viscoelastic fluid synergistic oil displacement in tight reservoirs was carried out, and the synergy of CO₂ and low interfacial tension viscoelastic fluid was discussed. Oil displacement mechanism. Experiments show that GOBTK has good injectability in tight oil reservoirs (Kg=0.141～0.793mD); CO₂-0.4% GOBTK synergistic flooding can improve the recovery factor of low permeability layers (31.41%) under heterogeneous (gradient difference of 10) conditions the) effect is better than that of CO₂ flooding (0.56%) and 0.4% GOBT-water flooding (20.99%); CO₂-GOBT synergistic oil displacement mechanism includes: 1) The formation of CO₂ foam increases the flow resistance of viscoelastic fluid, forcing the displacement fluid to flow 2) GOBTK can emulsify and disperse residual oil into small oil droplets, and smoothly pass through narrow pores to produce; 3) CO₂ dissolved in GOBTK synergistically enhances the water wettability of the core, and the use of viscosity Elastomeric fluid injection and stripping of residual oil; 4) CO₂-GOBTK synergy superimposes multiple mechanisms, effectively improving the swept volume and oil washing efficiency of the injected fluid to the reservoir.

Keywords: tight oil reservoir, CO₂ flooding, low interfacial tension viscoelastic fluid flooding, synergistic oil displacement, EOR mechanism

Procedia PDF Downloads 172

Authors: Mohammad Moridzadeh, Gholamreza Mesri

Abstract:

The effectiveness of lime treatment of soils has been commonly evaluated in terms of improved workability and increased undrained unconfined compressive strength in connection to road and airfield construction. The most common method of strength measurement has been the unconfined compression test. However, if the objective of lime treatment is to improve long-term stability of first-time or reactivated landslides in stiff clays and shales, permanent changes in the size and shape of clay particles must be realized to increase drained frictional resistance. Lime-soil interactions that may produce less platy and larger soil particles begin and continue with time under the highly alkaline pH environment. In this research, pH measurements are used to monitor chemical environment and progress of reactions. Atterberg limits are measured to identify changes in particle size and shape indirectly. Also, fully softened and residual strength measurements are used to examine an improvement in frictional resistance due to lime-soil interactions. The main variables are soil plasticity and mineralogy, lime content, water content, and curing period. Lime effect on frictional resistance is examined using samples of clays with different mineralogy and characteristics which may react with lime to various extents. Drained direct shear tests on reconstituted lime-treated clay specimens with various properties have been performed to measure fully softened shear strength. To measure residual shear strength, drained multiple reversal direct shear tests on precut specimens were conducted. This way, soil particles are oriented along the direction of shearing to the maximum possible extent and provide minimum frictional resistance. This is applicable to reactivated and part of first-time landslides. The Brenna clay, which is the highly plastic lacustrine clay of Lake Agassiz causing slope instability along the banks of the Red River, is one of the soil samples used in this study. The Brenna Formation characterized as a uniform, soft to firm, dark grey, glaciolacustrine clay with little or no visible stratification, is full of slickensided surfaces. The major source of sediment for the Brenna Formation was the highly plastic montmorillonitic Pierre Shale bedrock. The other soil used in this study is one of the main sources of slope instability in Harris County Flood Control District (HCFCD), i.e. the Beaumont clay. The shear strengths of untreated and treated clays were obtained under various normal pressures to evaluate the shear envelope nonlinearity.

Keywords: Brenna clay, friction resistance, lime treatment, residual

Procedia PDF Downloads 155

Authors: Magdalena B. Kaziuk, Waldemar Kosiba

Abstract:

Background: In the XXI century we have to deal with the epidemic of obesity which is important risk factor for the cardiovascular and kidney diseases. Lipo proteins are directly involved in the atherosclerotic process. Non-high-density lipo protein (non-HDL) began following widespread recognition of its superiority over LDL as a measurement of vascular event risk. Non-HDL includes residual risk which persists in patients after achieved recommended level of LDL. Materials and Methods: The study covered 111 patients (52 females, 59 males, age 51,91±14 years), hospitalized on the intern department. Body composition was assessed using the bioimpendance method and anthropometric measurements. Physical activity data were collected during the interview. The nutritional status and the obesity type were determined with the Waist to Height Ratio and the Waist to Hip Ratio. A function of the kidney was evaluated by calculating the estimated glomerular filtration rate (eGFR) using MDRD formula. Non-HDL was calculated as a difference between concentration of the Total and HDL cholesterol. Results: 10% of patients were found to be underweight; 23.9 % had correct body weight; 15,08 % had overweight, while the remaining group had obesity: 51,02 %. People with the android shape have higher non-HDL cholesterol versus with the gynoid shape (p=0.003). The higher was non-HDL, the lower eGFR had studied subjects (p < 0.001). Significant correlation was found between high non-HDL and incorrect dietary habits in patients avoiding eating vegetables, fruits and having low physical activity (p < 0.005). Conclusions: Android type of figure raises the residual risk of the heart disease associated with higher levels of non-HDL. Increasing physical activity in these patients reduces the level of non-HDL. Non-HDL seems to be the best predictor among all cholesterol measures for the cardiovascular events and worsening eGFR.

Keywords: obesity, non-HDL cholesterol, glomerular filtration rate, lifestyle

Procedia PDF Downloads 368

Authors: I. C. Tolias, A. G. Venetsanos, N. Markatos

Abstract:

In the present work, CFD simulations of a large scale open deflagration experiment are performed. Stoichiometric hydrogen-air mixture occupies a 20 m hemisphere. Two combustion models are compared and are evaluated against the experiment. The Eddy Dissipation Model and a Multi-physics combustion model which is based on Yakhot’s equation for the turbulent flame speed. The values of models’ critical parameters are investigated. The effect of the turbulence model is also examined. k-ε model and LES approach were tested.

Keywords: CFD, deflagration, hydrogen, combustion model

Procedia PDF Downloads 499

Authors: J. Rhodes, V. Cheng, P. Lok

Abstract:

The aim of this study is to develop a parsimonious model that explains the effect of different stimulus on a tourist’s intention to visit a new destination. The model consists of destination trust and interest as the mediating variables. The model was tested using two different types of stimulus; both studies empirically supported the proposed model. Furthermore, the first study revealed that advertising has a stronger effect than positive online reviews. The second study found that the peripheral route of the elaboration likelihood model has a stronger influence power than the central route in this context.

Keywords: advertising, electronic word-of-mouth, elaboration likelihood model, intention to visit, trust

Procedia PDF Downloads 455

Authors: Morgan Johansson, Joosef Leppanen, Mathias Flansbjer, Fabio Lozano, Josef Makdesi

Abstract:

Concrete is commonly used for protective structures and how impact loading affects different types of concrete structures is an important issue. Often the knowledge gained from static loading is also used in the design of impulse loaded structures. A large plastic deformation capacity is essential to obtain a large energy absorption in an impulse loaded structure. However, the structural response of an impact loaded concrete beam may be very different compared to a statically loaded beam. Consequently, the plastic deformation capacity and failure modes of the concrete structure can be different when subjected to dynamic loads; and hence it is not sure that the observations obtained from static loading are also valid for dynamic loading. The aim of this paper is to investigate the residual plastic deformation capacity in reinforced concrete beams subjected to drop weight impact tests. A test-series consisting of 18 simply supported beams (0.1 x 0.1 x 1.18 m, ρs = 0.7%) with a span length of 1.0 m and subjected to a point load in the beam mid-point, was carried out. 2x6 beams were first subjected to drop weight impact tests, and thereafter statically tested until failure. The drop in weight had a mass of 10 kg and was dropped from 2.5 m or 5.0 m. During the impact tests, a high-speed camera was used with 5 000 fps and for the static tests, a camera was used with 0.5 fps. Digital image correlation (DIC) analyses were conducted and from these the velocities of the beam and the drop weight, as well as the deformations and crack propagation of the beam, were effectively measured. Additionally, for the static tests, the applied load and midspan deformation were measured. The load-deformation relations for the beams subjected to an impact load were compared with 6 reference beams that were subjected to static loading only. The crack pattern obtained were compared using DIC, and it was concluded that the resulting crack formation depended much on the test method used. For the static tests, only bending cracks occurred. For the impact loaded beams, though, distinctive diagonal shear cracks also formed below the zone of impact and less wide shear cracks were observed in the region half-way to the support. Furthermore, due to wave propagation effects, bending cracks developed in the upper part of the beam during initial loading. The results showed that the plastic deformation capacity increased for beams subjected to drop weight impact tests from a high drop height of 5.0 m. For beams subjected to an impact from a low drop height of 2.5 m, though, the plastic deformation capacity was in the same order of magnitude as for the statically loaded reference beams. The beams tested were designed to fail due to bending when subjected to a static load. However, for the impact tested beams, one beam exhibited a shear failure at a significantly reduced load level when it was tested statically; indicating that there might be a risk of reduced residual load capacity for impact loaded structures.

Keywords: digital image correlation (DIC), drop weight impact, experiments, plastic deformation capacity, reinforced concrete

Procedia PDF Downloads 141

Authors: Ahmad Sarfaraz, Raiyad Herwies

Abstract:

In this paper, a multi-criteria decision making analysis is used to help any organization selects the best KM tool that fits and serves its needs. The AHP model is used based on a previous study to highlight and identify the main criteria and sub-criteria that are incorporated in the selection process. Different KM tools alternatives with different criteria are compared and weighted accurately to be incorporated in the GP model. The main goal is to combine the GP model with the AHP model to ensure that selecting the KM tool considers the resource constraints. Two important issues are discussed in this paper: how different factors could be taken into consideration in forming the AHP model, and how to incorporate the AHP results into the GP model for better results.

Keywords: knowledge management, analytical hierarchy process, goal programming, multi-criteria decision making

Procedia PDF Downloads 381

Authors: Lu Zhao, Nadir Farhi, Yeltsin Valero, Zoi Christoforou, Nadia Haddadou

Abstract:

In this paper, a long short-term memory (LSTM) neural network model is proposed to replicate simultaneously car-following and lane-changing behaviors in road networks. By combining two kinds of LSTM layers and three input designs of the neural network, six variants of the LSTM model have been created. These models were trained and tested on the NGSIM 101 dataset, and the results were evaluated in terms of longitudinal speed and lateral position, respectively. Then, we compared the LSTM model with a classical car-following model (the intelligent driving model (IDM)) in the part of speed decision. In addition, the LSTM model is compared with a model using classical neural networks. After the comparison, the LSTM model demonstrates higher accuracy than the physical model IDM in terms of car-following behavior and displays better performance with regard to both car-following and lane-changing behavior compared to the classical neural network model.

Keywords: traffic modeling, neural networks, LSTM, car-following, lane-change

Procedia PDF Downloads 250

Authors: Noga Bregman

Abstract:

Accurate and efficient earthquake detection and phase picking are crucial for seismic hazard assessment and emergency response. This study introduces EQMamba, a deep-learning method that combines the strengths of the Earthquake Transformer and the Mamba model for simultaneous earthquake detection and phase picking. EQMamba leverages the computational efficiency of Mamba layers to process longer seismic sequences while maintaining a manageable model size. The proposed architecture integrates convolutional neural networks (CNNs), bidirectional long short-term memory (BiLSTM) networks, and Mamba blocks. The model employs an encoder composed of convolutional layers and max pooling operations, followed by residual CNN blocks for feature extraction. Mamba blocks are applied to the outputs of BiLSTM blocks, efficiently capturing long-range dependencies in seismic data. Separate decoders are used for earthquake detection, P-wave picking, and S-wave picking. We trained and evaluated EQMamba using a subset of the STEAD dataset, a comprehensive collection of labeled seismic waveforms. The model was trained using a weighted combination of binary cross-entropy loss functions for each task, with the Adam optimizer and a scheduled learning rate. Data augmentation techniques were employed to enhance the model's robustness. Performance comparisons were conducted between EQMamba and the EQTransformer over 20 epochs on this modest-sized STEAD subset. Results demonstrate that EQMamba achieves superior performance, with higher F1 scores and faster convergence compared to EQTransformer. EQMamba reached F1 scores of 0.8 by epoch 5 and maintained higher scores throughout training. The model also exhibited more stable validation performance, indicating good generalization capabilities. While both models showed lower accuracy in phase-picking tasks compared to detection, EQMamba's overall performance suggests significant potential for improving seismic data analysis. The rapid convergence and superior F1 scores of EQMamba, even on a modest-sized dataset, indicate promising scalability for larger datasets. This study contributes to the field of earthquake engineering by presenting a computationally efficient and accurate method for simultaneous earthquake detection and phase picking. Future work will focus on incorporating Mamba layers into the P and S pickers and further optimizing the architecture for seismic data specifics. The EQMamba method holds the potential for enhancing real-time earthquake monitoring systems and improving our understanding of seismic events.

Keywords: earthquake, detection, phase picking, s waves, p waves, transformer, deep learning, seismic waves

Procedia PDF Downloads 39

Authors: Jin Hwa Yang, Hwang Bae, Sung Uk Ryu, Byong Guk Jeon, Sung Jae Yi, Hyun Sik Park

Abstract:

Experimental studies using a large-scale thermal-hydraulic integral test facility, System–integrated Modular Advanced Reactor Integral Test Loop (SMART-ITL), have been carried out to validate the performance of the prototype, SMART. After Fukushima accident, the passive safety systems have been dealt as important designs for retaining of nuclear safety. One of the concerned scenarios for evaluating the passive safety system is a Complete Loss of Coolant Flow (CLOF). The flowrate of coolant in the primary system is maintained by Reactor Coolant Pump (RCP). When the supply of electric power of RCP is shut off, the flowrate of coolant decreases sharply, and the temperature of the coolant increases rapidly. Therefore, the reactor trip signal is activated to prevent the over-heating of the core. In this situation, Passive Residual Heat Removal System (PRHRS) plays a significant role to assure the soundness of the SMART. The PRHRS using a two-phase natural circulation is a passive safety system in the SMART to eliminate the heat of steam generator in the secondary system with heat exchanger submarined in the Emergency Cooling Tank (ECT). As the RCPs continue to coast down, inherent natural circulation in the primary system transfers heat to the secondary system. The transferred heat is removed by PRHRS in the secondary system. In this paper, the progress of the CLOF accident is described with experimental data of transient condition performed by SMART-ITL. Finally, the capability of passive safety system and inherent natural circulation will be evaluated.

Keywords: CLOF, natural circulation, PRHRS, SMART-ITL

Procedia PDF Downloads 436

Authors: Asad Naeem, Mohamed Nour Eldin, Jinkoo Kim

Abstract:

In this study, the seismic performance and life cycle cost (LCC) are evaluated of the structure retrofitted with the damped cable system (DCS). The DCS is a seismic retrofit system composed of a high-strength steel cable and pressurized viscous dampers. The analysis model of the system is first derived using various link elements in SAP2000, and fragility curves of the structure retrofitted with the DCS and viscous dampers are obtained using incremental dynamic analyses. The analysis results show that the residual displacements of the structure equipped with the DCS are smaller than those of the structure with retrofitted with only conventional viscous dampers, due to the enhanced stiffness/strength and self-centering capability of the damped cable system. The fragility analysis shows that the structure retrofitted with the DCS has the least probability of reaching the specific limit states compared to the bare structure and the structure with viscous damper. It is also observed that the initial cost of the DCS method required for the seismic retrofit is smaller than that of the structure with viscous dampers and that the LCC of the structure equipped with the DCS is smaller than that of the structure with viscous dampers.

Keywords: damped cable system, fragility curve, life cycle cost, seismic retrofit, self-centering

Procedia PDF Downloads 542

Authors: Coskun Serefoglu

Abstract:

The study aims to analyse how a traditional sector such as agri-food could be mobilized through regional innovation strategies. A principal component analysis as well as qualitative information, such as in-depth interviews, focus group and surveys, were employed to find the priority sectors. An agri-food model was developed which includes both a linear model and interactive model. The model consists of two main components, one of which is technological integration and the other one is agricultural extension which is based on Land-grant university approach of U.S. which is not a common practice in Turkey.

Keywords: regional innovation strategy, interactive model, agri-food sector, local development, planning, regional development

Procedia PDF Downloads 146

Authors: Sasiporn Rattanasupha, Settapat Chinviriyasit

Abstract:

The treatment function adopts a continuous and differentiable function which can describe the effect of delayed treatment when the number of infected individuals increases and the medical condition is limited. In this paper, the SEIR epidemic model with treatment function is studied to investigate the dynamics of the model due to the effect of treatment. It is assumed that the treatment rate is proportional to the number of infective patients. The stability of the model is analyzed. The model is simulated to illustrate the analytical results and to investigate the effects of treatment on the spread of infection.

Keywords: basic reproduction number, local stability, SEIR epidemic model, treatment function

Procedia PDF Downloads 517

Authors: M. Dezyani, R. Ezzati bbelvirdi, M. Shakerian, H. Mirzaei

Abstract:

Sodium Hexametaphosphate (SHMP) is commonly used as an Emulsifying Salt (ES) in process cheese, although rarely as the sole ES. It appears that no published studies exist on the effect of SHMP concentration on the properties of process cheese when pH is kept constant; pH is well known to affect process cheese functionality. The detailed interactions between the added phosphate, Casein (CN), and indigenous Ca phosphate are poorly understood. We studied the effect of the concentration of SHMP (0.25-2.75%) and holding time (0-20 min) on the textural and Rheological properties of pasteurized process Cheddar cheese using a central composite rotatable design. All cheeses were adjusted to pH 5.6. The meltability of process cheese (as indicated by the decrease in loss tangent parameter from small amplitude oscillatory rheology, degree of flow, and melt area from the Schreiber test) decreased with an increase in the concentration of SHMP. Holding time also led to a slight reduction in meltability. Hardness of process cheese increased as the concentration of SHMP increased. Acid-base titration curves indicated that the buffering peak at pH 4.8, which is attributable to residual colloidal Ca phosphate, was shifted to lower pH values with increasing concentration of SHMP. The insoluble Ca and total and insoluble P contents increased as concentration of SHMP increased. The proportion of insoluble P as a percentage of total (indigenous and added) P decreased with an increase in ES concentration because of some of the (added) SHMP formed soluble salts. The results of this study suggest that SHMP chelated the residual colloidal Ca phosphate content and dispersed CN; the newly formed Ca-phosphate complex remained trapped within the process cheese matrix, probably by cross-linking CN. Increasing the concentration of SHMP helped to improve fat emulsification and CN dispersion during cooking, both of which probably helped to reinforce the structure of process cheese.

Keywords: Iranian processed cheese, emulsifying salt, rheology, texture

Procedia PDF Downloads 429

Authors: Rakesh Kumar Mishra, Tarun Kumar Dan

Abstract:

Lead-Lag based Internal Model Control method is proposed based on Internal Model Control (IMC) strategy. In this paper, we have designed the Lead-Lag based Internal Model Control for binary distillation column for SISO process (considering only bottom product). The transfer function has been taken from Wood and Berry model. We have find the composition control and disturbance rejection using Lead-Lag based IMC and comparing with the response of simple Internal Model Controller.

Keywords: SISO, lead-lag, internal model control, wood and berry, distillation column

Procedia PDF Downloads 640

Authors: Gaurav Gupta, Jitendra Mahakud

Abstract:

This study focuses on the significance of internal financing constraints on the determination of corporate fixed investments in the case of Indian manufacturing companies. Financing constraints companies which have less internal fund or retained earnings face more transaction and borrowing costs due to imperfections in the capital market. The period of study is 1999-2000 to 2013-2014 and we consider 618 manufacturing companies for which the continuous data is available throughout the study period. The data is collected from PROWESS data base maintained by Centre for Monitoring Indian Economy Pvt. Ltd. Panel data methods like fixed effect and random effect methods are used for the analysis. The Likelihood Ratio test, Lagrange Multiplier test, and Hausman test results conclude the suitability of the fixed effect model for the estimation. The cash flow and liquidity of the company have been used as the proxies for the internal financial constraints. In accordance with various theories of corporate investments, we consider other firm specific variable like firm age, firm size, profitability, sales and leverage as the control variables in the model. From the econometric analysis, we find internal cash flow and liquidity have the significant and positive impact on the corporate investments. The variables like cost of capital, sales growth and growth opportunities are found to be significantly determining the corporate investments in India, which is consistent with the neoclassical, accelerator and Tobin’s q theory of corporate investment. To check the robustness of results, we divided the sample on the basis of cash flow and liquidity. Firms having cash flow greater than zero are put under one group, and firms with cash flow less than zero are put under another group. Also, the firms are divided on the basis of liquidity following the same approach. We find that the results are robust to both types of companies having positive and negative cash flow and liquidity. The results for other variables are also in the same line as we find for the whole sample. These findings confirm that internal financing constraints play a significant role for determination of corporate investment in India. The findings of this study have the implications for the corporate managers to focus on the projects having higher expected cash inflows to avoid the financing constraints. Apart from that, they should also maintain adequate liquidity to minimize the external financing costs.

Keywords: cash flow, corporate investment, financing constraints, panel data method

Procedia PDF Downloads 240