Search results for: recharge estimation

Authors: Hyon I. Paek, Sang Rim Kim, Hyon A. Ryu

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In functional linear regression, one typical problem is to reduce dimension. Compared with multivariate linear regression, functional linear regression is regarded as an infinite-dimensional case, and the main task is to reduce dimensions of functional response and functional predictors. One common approach is to adapt functional principal component analysis (FPCA) on functional predictors and then use a few leading functional principal components (FPC) to predict the functional model. The leading FPCs estimated by the typical FPCA explain a major variation of the functional predictor, but these leading FPCs may not be mostly correlated with the functional response, so they may not be significant in the prediction for response. In this paper, we propose a supervised functional principal component analysis method for a functional response model with FPCs obtained by considering the correlation of the functional response. Our method would have a better prediction accuracy than the typical FPCA method.

Keywords: supervised, functional principal component analysis, functional response, functional linear regression

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Authors: Saleh Alagla, Murya Habbash

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The paper investigates whether the board of directors plays a monitoring role or not in CEO compensation for the UK firms during the eve of the recent financial crisis, 2004-2008. The use of heteroscedastic and autocorrelated error consistent estimation of the panel data shows, surprisingly, that four board characteristics variables are found to play a significant role in increasing the level of CEO compensation. This insightful result would suggest evidence of the managerial power theory in general and the cronyism hypothesis in particular. Moreover, the interesting evidence supporting managerial power perspective is that CEO-Chair duality reduces long-term compensation while increasing short-term compensation, thus suggesting that CEOs are risk averse who prefer short-term compensation to long-term compensation. Finally, consistent with the agency perspective board size is found to increase all compensation variables as expected.

Keywords: corporate governance, CEO compensation, board of directors, internal governance mechanisms, agency theory, managerial power theory, cronyism hypothesis

Procedia PDF Downloads 784

Authors: K. Assis, K. P. Chong, A. S. Idris, C. M. Ho

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Oil palm or Elaeis guineensis is considered as the golden crop in Malaysia. But oil palm industry in this country is now facing with the most devastating disease called as Ganoderma Basal Stem Rot disease. The objective of this paper is to analyze the economic loss due to this disease. There were three commercial oil palm sites selected for collecting the required data for economic analysis. Yield parameter used to measure the loss was the total weight of fresh fruit bunch in six months. The predictors include disease severity, change in disease severity, number of infected neighbor palms, age of palm, planting generation, topography, and first order interaction variables. The estimation model of yield loss was identified by using backward elimination based regression method. Diagnostic checking was conducted on the residual of the best yield loss model. The value of mean absolute percentage error (MAPE) was used to measure the forecast performance of the model. The best yield loss model was then used to estimate the economic loss by using the current monthly price of fresh fruit bunch at mill gate.

Keywords: ganoderma, oil palm, regression model, yield loss, economic loss

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Authors: Yiyang Su, Jörg Neumann, Jan Wetzlich, Florian Thiel

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Smart grid is a term used to describe the next generation power grid. New challenges such as integration of renewable and decentralized energy sources, the requirement for continuous grid estimation and optimization, as well as the use of two-way flows of energy have been brought to the power gird. In order to achieve efficient, reliable, sustainable, as well as secure delivery of electric power more and more information and communication technologies are used for the monitoring and the control of power grids. Consequently, the need for cybersecurity is dramatically increased and has converged into several standards which will be presented here. These standards for the smart grid must be designed to satisfy both performance and reliability requirements. An in depth investigation of the effect of retrospectively embedded security in existing grids on it’s dynamic behavior is required. Therefore, a retrofitting plan for existing meters is offered, and it’s performance in a test low voltage microgrid is investigated. As a result of this, integration of security measures into measurement architectures of smart grids at the design phase is strongly recommended.

Keywords: cyber security, performance, protocols, security standards, smart grid

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Authors: M. Gangadharappa, M. Ravi Kumar, H. N. Reddappa

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The mechanical properties and morphological analysis of Al6061-Red mud particulate composites were investigated. The compositions of the composite include a matrix of Al6061 and the red mud particles of 53-75 micron size as reinforcement ranging from 0% to 12% at an interval of 2%. Stir casting technique was used to fabricate Al6061-Red mud composites. Density measurement, estimation of percentage porosity, tensile properties, fracture toughness, hardness value, impact energy, percentage elongation and percentage reduction in area. Further, the microstructures and SEM examinations were investigated to characterize the composites produced. The result shows that a uniform dispersion of the red mud particles along the grain boundaries of the Al6061 alloy. The tensile strength and hardness values increases with the addition of Red mud particles, but there is a slight decrease in the impact energy values, values of percentage elongation and percentage reduction in area as the reinforcement increases. From these results of investigation, we concluded that the red mud, an industrial waste can be used to enhance the properties of Al6061 alloy for engineering applications.

Keywords: Al6061, red mud, tensile strength, hardness and microstructures

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Authors: Fabio Oettl, Sebastian Hoerbrand, Tobias Wittmeir, Johannes Schilp

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By combining the additive manufacturing (AM)- process with digital concepts, like the digital twin (DT) or the downsized and basing concept of the digital part file (DPF), the competitiveness of additive manufacturing is enhanced and new use cases like decentral production are enabled. But in literature, one can´t find any quantitative approach for valuing the usage of a DT or DPF in AM. Out of this fact, such an approach will be developed within this paper in order to further promote or dissuade the usage of these concepts. The focus is set on the production as an early lifecycle phase, which means that the AM-production process gets analyzed regarding the potential advantages of using DPF in AM. These advantages are transferred to a monetary value with this approach. By calculating the costs of the DPF, an overall monetary value is a result. Thereon a tool, based on a simulation environment is constructed, where the algorithms are transformed into a program. The results of applying this tool show that an overall value of 20,81 € for the DPF can be realized for one special use case. For the future application of the DPF there is the recommendation to integrate especially sustainable information because out of this, a higher value of the DPF can be expected.

Keywords: additive manufacturing, digital concept costs, digital part file, digital twin, monetary value estimation

Procedia PDF Downloads 184

Authors: Ishapathik Das, Sumen Sen, N. Rao Chaganty, Pooja Sengupta

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Dependent multivariate count data occur in several research studies. These data can be modeled by a multivariate Poisson or Negative binomial distribution constructed using copulas. However, when some of the counts are inflated, that is, the number of observations in some cells are much larger than other cells, then the copula based multivariate Poisson (or Negative binomial) distribution may not fit well and it is not an appropriate statistical model for the data. There is a need to modify or adjust the multivariate distribution to account for the inflated frequencies. In this article, we consider the situation where the frequencies of two cells are higher compared to the other cells, and develop a doubly inflated multivariate Poisson distribution function using multivariate Gaussian copula. We also discuss procedures for regression on covariates for the doubly inflated multivariate count data. For illustrating the proposed methodologies, we present a real data containing bivariate count observations with inflations in two cells. Several models and linear predictors with log link functions are considered, and we discuss maximum likelihood estimation to estimate unknown parameters of the models.

Keywords: copula, Gaussian copula, multivariate distributions, inflated distributios

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Authors: Riznaldi Akbar

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In this study, we compared the performance of the Artificial Neural Network (ANN) model with back-propagation algorithm in correctly predicting in-sample and out-of-sample external debt crisis in Indonesia. We found that exchange rate, foreign reserves, and exports are the major determinants to experiencing external debt crisis. The ANN in-sample performance provides relatively superior results. The ANN model is able to classify correctly crisis of 89.12 per cent with reasonably low false alarms of 7.01 per cent. In out-of-sample, the prediction performance fairly deteriorates compared to their in-sample performances. It could be explained as the ANN model tends to over-fit the data in the in-sample, but it could not fit the out-of-sample very well. The 10-fold cross-validation has been used to improve the out-of-sample prediction accuracy. The results also offer policy implications. The out-of-sample performance could be very sensitive to the size of the samples, as it could yield a higher total misclassification error and lower prediction accuracy. The ANN model could be used to identify past crisis episodes with some accuracy, but predicting crisis outside the estimation sample is much more challenging because of the presence of uncertainty.

Keywords: debt crisis, external debt, artificial neural network, ANN

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Authors: DEVASHISH KHULBE, MANU PATHAK

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The rise in popularity of major social media platforms have enabled people to share photos and textual information about their daily life. One of the popular topics about which information is shared is food. Since a lot of media about food are attributed to particular locations and restaurants, information like spatio-temporal popularity of various cuisines can be analyzed. Tracking the popularity of food types and retail locations across space and time can also be useful for business owners and restaurant investors. In this work, we present an approach using off-the shelf machine learning techniques to identify trends and popularity of cuisine types in an area using geo-tagged data from social media, Google images and Yelp. After adjusting for time, we use the Kernel Density Estimation to get hot spots across the location and model the dependencies among food cuisines popularity using Bayesian Networks. We consider the Manhattan borough of New York City as the location for our analyses but the approach can be used for any area with social media data and information about retail businesses.

Keywords: Web Mining, Geographic Information Systems, Business popularity, Spatial Data Analyses

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Authors: Sudhir Kumar Tiwari

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The paper demonstrates a methodology that can be used at an early design stage of any conventional aircraft. This research activity assesses the feasibility derivation of methodology for aircraft loads estimation during the various phases of design for a transport category aircraft by utilizing potential of using commercial finite element analysis software, which may drive significant time saving. Early Design phase have limited data and quick changing configuration results in handling of large number of load cases. It is useful to idealize the aircraft as a connection of beams, which can be very accurately modelled using finite element analysis (beam elements). This research explores the correct approach towards idealizing an aircraft using beam elements. FEM Techniques like inertia relief were studied for implementation during course of work. The correct boundary condition technique envisaged for generation of shear force, bending moment and torque diagrams for the aircraft. The possible applications of this approach are the aircraft design process, which have been investigated.

Keywords: multi-disciplinary optimization, aircraft load, finite element analysis, stick model

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Authors: Qian Zhang, Dongkai Shen, Yan Shi

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A new mechanical ventilator with automatic secretion clearance function can improve the secretion clearance safely and efficiently. However, in recent modeling studies on various mechanical ventilators, it was considered that human had one lung, and the coupling effect of double lungs was never illustrated. In this paper, to expound the coupling effect of double lungs, a mathematical model of a ventilation system of a bi-level positive airway pressure (BiPAP) controlled ventilator with secretion clearance was set up. Moreover, an experimental study about the mechanical ventilation system of double lungs on BiPAP ventilator was conducted to verify the mathematical model. Finally, the coupling effect of double lungs of the mathematical ventilation was studied by simulation and orthogonal experimental design. This paper adds to previous studies and can be referred to optimization methods in medical researches.

Keywords: double lungs, coupling effect, secretion clearance, orthogonal experimental design

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Authors: S. Zolghadri, M. Mousavi-Daramoroudi, H. Yousefnia, F. Abbasi-Davani

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In this study, the absorbed dose of human organs after injection of ¹⁷⁷Lu-DOTATOC was studied based on the biodistribution of the complex in adenocarcinoma breast cancer bearing mice. For this purpose, the biodistribution of the radiolabelled complex was studied and compartmental modeling was applied to calculate the absorbed dose with high precision. As expected, ¹⁷⁷Lu-DOTATOC illustrated a notable specific uptake in tumor and pancreas, organs with high level of somatostatin receptor on their surface and the effectiveness of the radio-conjugate for targeting of the breast adenocarcinoma tumors was indicated. The elicited results of modeling were the exponential equations, and those are utilized for obtaining the cumulated activity data by taking their integral. The results also exemplified that non-target absorbed-doses such as the liver, spleen and pancreas were approximately 0.008, 0.004, and 0.039, respectively. While these values were so much lower than target (tumor) absorbed-dose, it seems due to this low toxicity, this complex is a good agent for therapy.

Keywords: ¹⁷⁷Lu, breast cancer, compartmental modeling, dosimetry

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Authors: Tomas Menard

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The design of control-law for engineering systems has been investigated for many decades. While many results are concerned with continuous systems with continuous output, nowadays, many controlled systems have to transmit their output measurements through network, hence making it discrete-time. But it is well known that the sampling of a system whose control-law is based on the continuous output may render the system unstable, especially when this sampling period is long compared to the system dynamics. The control design then has to be adapted in order to cope with this issue. In this paper, we consider systems which can be modeled as double integrator with uncertainty on the input since many mechanical systems can be put under such form. We present a control scheme based on an observer using only discrete time measurement and which provides continuous time estimation of the state, combined with a continuous control law, which stabilized a system with second-order dynamics even in the presence of uncertainty. It is further shown that arbitrarily long sampling periods can be dealt with properly setting the control scheme parameters.

Keywords: dynamical system, control law design, sampled output, observer design

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Authors: Magdi M. E. Zumrawi, Mohamed Awad

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Determination of Resilient Modulus (M_R) is quite important for characterizing materials in pavement design and evaluation. The main focus of this study is to develop a correlation that predict the resilient modulus of subgrade soils from simple and easy measured soil index properties. To achieve this objective, three subgrade soils representing typical Khartoum soils were selected and tested in the laboratory for measuring resilient modulus. Other basic laboratory tests were conducted on the soils to determine their physical properties. Several soil samples were prepared and compacted at different moisture contents and dry densities and then tested using resilient modulus testing machine. Based on experimental results, linear relationship of M_R with the consistency factor ‘F_c’ which is a combination of dry density, void ratio and consistency index had been developed. The results revealed that very good linear relationship found between the M_R and the consistency factor with a coefficient of linearity (R²) more than 0.9. The consistency factor could be used for the prediction of the M_R of compacted subgrade soils with precise and reliable results.

Keywords: Consistency factor, resilient modulus, subgrade soil, properties

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Authors: Anna Guitart Atienza, Ana Fernández del Río, Madhav Nekkar, Jelena Ljubicic, África Periáñez, Eura Shin, Lauren Bellhouse

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The use of digital devices in healthcare or mobile health (mHealth) has increased in recent years due to the advances in digital technology, making it possible to nudge healthy behaviors through individual interventions. In addition, mHealth is becoming essential in poor-resource settings due to the widespread use of smartphones in areas where access to professional healthcare is limited. In this work, we evaluate mHealth interventions in low-income countries with a focus on causal inference. Counterfactuals estimation and other causal computations are key to determining intervention success and assisting in empirical decision-making. Our main purpose is to personalize treatment recommendations and triage patients at the individual level in order to maximize the entire intervention's impact on the desired outcome. For this study, collected data includes mHealth individual logs from front-line healthcare workers, electronic health records (EHR), and external variables data such as environmental, demographic, and geolocation information.

Keywords: causal inference, mHealth, intervention, personalization

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Authors: Riad

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As present world needs more and more energy in a low cost way, it needs to find out the optimal way of power generation. In the sense of low cost, renewable energy is one of the greatest sources of power generation. Water vapour of sea/river/lake can be used for power generation by using the greenhouse effect in a large flat type water chamber floating on the water surface. The water chamber will always be kept half filled. When water evaporates by sunlight, the high pressured gaseous water will be stored in the chamber. By passing through a pipe and by using aerodynamics it can be used for power generation. The water level of the chamber is controlled by some means. As a large amount of water evaporates, an estimation can be highlighted, approximately 3 to 4 thousand gallons of water evaporates from per acre of surface (this amount will be more by greenhouse effect). This large amount of gaseous water can be utilized for power generation by passing through a pipe. This method can be a source of power generation.

Keywords: renewable energy, greenhouse effect, water chamber, water vapour

Procedia PDF Downloads 341

Authors: Yasir Khan

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The continued growth in international students coming to China for higher education had a significant positive impact on trade and GDP in China. Student mobility may expend trade with their country of origin, owing to superior knowledge, or preferential access to market opportunities. We test this hypothesis using Chinese trade data from 1999 to 2017. In fully-modify (OLS) and dynamic (OLS) testing estimation, we find that a 1.24 percent increase in student inward mobility is associated with a 1 percent increase in Chinese export trade. On the other hand, we find that a 1.18 percent increase in the student inward mobility to China is associated with a 1 percent increase in import trade. In addition, we find that a 1.13 percent increase in international student inward mobility is associated with a 1 percent increase in the GDP. The outcome suggests that international students have a strong influence on Gross Domestic Product (GDP), exports and imports trade. However, the study holds that the government should attach great attachment and importance to the role of international students in the export and import trade.

Keywords: international student mobility, China, export, import, GDP, FMOLS, DOLS

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Authors: G. N. Tiwari, Shyam

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Photovoltaic thermal (PVT) roof type greenhouse dryer installed above the wind tower of SODHA BERS COMPLEX, Varanasi has been analyzed for all types of weather conditions. The product to be dried has been kept at three different trays. The upper tray receives energy from the PV cover while the bottom tray receives thermal energy from the hot air of the wind tower. The annual energy estimation has been done for the all types of weather condition of composite climate of northern India. It has been found that maximum energy saving is observed for c type of weather condition whereas minimum energy saving is observed for a type of weather condition. The energy saving on overall thermal energy basis and exergy basis are 1206.8 kWh and 360 kWh respectively for c type of weather condition. The energy saving from all types of weather condition are found to be 3175.3 kWh and 957.6 kWh on overall thermal energy and overall exergy basis respectively.

Keywords: exergy, greenhouse, photovoltaic thermal, solar dryer

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Authors: Nicole Merkle, Stefan Zander

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Ambient Assisted Living (AAL) describes a technological and methodological stack of (e.g. formal model-theoretic semantics, rule-based reasoning and machine learning), different aspects regarding the behavior, activities and characteristics of humans. Hence, a semantic representation of the user environment and its relevant elements are required in order to allow assistive agents to recognize situations and deduce appropriate actions. Furthermore, the user and his/her characteristics (e.g. physical, cognitive, preferences) need to be represented with a high degree of expressiveness in order to allow software agents a precise evaluation of the users’ context models. The correct interpretation of these context models highly depends on temporal, spatial circumstances as well as individual user preferences. In most AAL approaches, model representations of real world situations represent the current state of a universe of discourse at a given point in time by neglecting transitions between a set of states. However, the AAL domain currently lacks sufficient approaches that contemplate on the dynamic adaptions of context-related representations. Semantic representations of relevant real-world excerpts (e.g. user activities) help cognitive, rule-based agents to reason and make decisions in order to help users in appropriate tasks and situations. Furthermore, rules and reasoning on semantic models are not sufficient for handling uncertainty and fuzzy situations. A certain situation can require different (re-)actions in order to achieve the best results with respect to the user and his/her needs. But what is the best result? To answer this question, we need to consider that every smart agent requires to achieve an objective, but this objective is mostly defined by domain experts who can also fail in their estimation of what is desired by the user and what not. Hence, a smart agent has to be able to learn from context history data and estimate or predict what is most likely in certain contexts. Furthermore, different agents with contrary objectives can cause collisions as their actions influence the user’s context and constituting conditions in unintended or uncontrolled ways. We present an approach for dynamically updating a semantic model with respect to the current user context that allows flexibility of the software agents and enhances their conformance in order to improve the user experience. The presented approach adapts rules by learning sensor evidence and user actions using probabilistic reasoning approaches, based on given expert knowledge. The semantic domain model consists basically of device-, service- and user profile representations. In this paper, we present how this semantic domain model can be used in order to compute the probability of matching rules and actions. We apply this probability estimation to compare the current domain model representation with the computed one in order to adapt the formal semantic representation. Our approach aims at minimizing the likelihood of unintended interferences in order to eliminate conflicts and unpredictable side-effects by updating pre-defined expert knowledge according to the most probable context representation. This enables agents to adapt to dynamic changes in the environment which enhances the provision of adequate assistance and affects positively the user satisfaction.

Keywords: ambient intelligence, machine learning, semantic web, software agents

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Authors: Harisudha Kuresan, Dhanalakshmi Samiappan, T. Rama Rao

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In modern telecommunication applications, Glottal Closure Instants location finding is important and is directly evaluated from the speech waveform. Here, we study the GCI using Speech Event Detection using Residual Excitation and the Mean Based Signal (SEDREAMS) algorithm. Speech coding uses parameter estimation using audio signal processing techniques to model the speech signal combined with generic data compression algorithms to represent the resulting modeled in a compact bit stream. This paper proposes a sub-band coder SBC, which is a type of transform coding and its performance for GCI detection using SEDREAMS are evaluated. In SBCs code in the speech signal is divided into two or more frequency bands and each of these sub-band signal is coded individually. The sub-bands after being processed are recombined to form the output signal, whose bandwidth covers the whole frequency spectrum. Then the signal is decomposed into low and high-frequency components and decimation and interpolation in frequency domain are performed. The proposed structure significantly reduces error, and precise locations of Glottal Closure Instants (GCIs) are found using SEDREAMS algorithm.

Keywords: SEDREAMS, GCI, SBC, GOI

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Authors: M. Abu Hanif, Anika Tabassum, Fuad Hasan Ovi, Ishrat Islam

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Water is essential for life. Enormous quantities of water are cycled each year through hydrologic cycle but only a fraction of circulated water is available each year for human use. Dhaka, the capital of Bangladesh is the 19th mega city in the world with a population of over 14 million (World City Information, 2011). As a result the growth of urban population is increasing rapidly; the city is not able to manage with altering situations due to resource limitations and management capacity. Water crisis has become an acute problem faced by the inhabitants of Dhaka city. It is found that total water demand in Dhaka city is 2,240 million liter per day (MLD) whereas supply is 2,150 (MLD). According to Dhaka Water Supply and Sewerage Authority about 87 percent of this supply comes from groundwater resources and rest 13 percent from surface water. According to Dhaka Water Supply and Sewerage Authority it has been found that the current groundwater depletion rate is 3.52 meter per year. Such a fast depletion of the water table will result in intrusion of southern saline water into the groundwater reservoir, depriving this mega city of pure drinking water. This study mainly focus on the potential of Rainwater Harvesting System(RWHS) in Kazipara area of Dhaka city, determine the perception level of local people in installation of rainwater harvesting system in their building and identify the factors regarding willingness of owner in installing rainwater harvesting system. As most of the residential area of Dhaka city is unplanned with small plots, Kazipara area has been chosen as study area which depicts similar characteristics. In this study only roof top area is considered as catchment area and potential of rainwater harvesting has been calculated. From the calculation it is found that harvested rainwater can serve the 66% of demand of water for toilet flushing and cleaning purposes for the people of Kazipara. It is also observed that if only rooftop rainwater harvesting applied to all the structures of the study area then two third of surface runoff would be reduced than present surface runoff. In determining the perception of local people only owners of the buildings were. surveyed. From the questionnaire survey it is found that around 75% people have no idea about the rainwater harvesting system. About 83% people are not willing to install rainwater harvesting system in their dwelling. The reasons behind the unwillingness are high cost of installation, inadequate space, ignorance about the system, etc. Among 16% of the willing respondents who are interested in installing RWHS system, it was found that higher income, bigger size of buildings are important factors in willingness of installing rainwater harvesting system. Majority of the respondents demanded for both technical and economical support to install the system in their buildings. Government of Bangladesh has taken some initiatives to promote rainwater harvesting in urban areas. It is very much necessary to incorporate rainwater harvesting device and artificial recharge system in every building of Dhaka city to make Dhaka city self sufficient in water supply management and to solve water crisis problem of megacity like as Dhaka city.

Keywords: rainwater harvesting, water table, willingness, storm water

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Authors: Harshith Gowda K. S, Tejaskumar N, Shubhanga R. B, Gowtham N, Deekshith Gowda H. S

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Phasor measurement units (PMU) are playing an important role in the current power system for state estimation. It is necessary to have complete observability of the power system while minimizing the cost. For this purpose, the optimal location of the phasor measurement units in the power system is essential. In a bus system, zero injection buses need to be evaluated to minimize the number of PMUs. In this paper, the optimization problem is formulated using mixed integer programming to obtain the optimal location of the PMUs with increased observability. The formulation consists of with and without zero injection bus as constraints. The formulated problem is simulated using a CPLEX solver in the GAMS software package. The proposed method is tested on IEEE 30, IEEE 39, IEEE 57, and IEEE 118 bus systems. The results obtained show that the number of PMUs required is minimal with increased observability.

Keywords: PMU, observability, mixed integer programming (MIP), zero injection buses (ZIB)

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Authors: Riktesh Srivastava

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Online Shopping have established an astonishing evolution in the last few years. And it is now apparent that B2C architecture is becoming progressively imperative channel for even traditional brick and mortar type traders as well. In this completion knowing customers and predicting behavior are extremely important. More important, when any customer logs onto the B2C architecture, the traces of their buying patterns can be stored and used for future predictions. Such a prediction is called Customer Lifetime Value (CLV). Earlier, we used Net Present Value to do so, however, it ignores two important aspects of B2C architecture, “market risks” and “big amount of customer data”. Now, we use RFM- Recency, Frequency and Monetary Value to estimate the CLV, and as the term exemplifies, market risks, is well sheltered. Big Data Analysis is also roofed in RFM, which gives real exploration of the Big Data and lead to a better estimation for future cash flow from customers. In the present paper, 6 factors (collected from varied sources) are used to determine as to what attracts the customers to the B2C architecture. For these 6 factors, RFM is computed for 3 years (2013, 2014 and 2015) respectively. CLV and Revenue are the two parameters defined using RFM analysis, which gives the clear picture of the future predictions.

Keywords: CLV, RFM, revenue, recency, frequency, monetary value

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Authors: Yu Liang, Wei Wei

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Spatial representation of numbers and numerical magnitude are important for preschoolers’ mathematical ability. Mental number line, a typical index to measure numbers spatial representation, and numerical comparison are both related to arithmetic obviously. However, they seem to rely on different mechanisms and probably influence arithmetic through different mechanisms. In line with this idea, preschool children were trained with two tasks to investigate which one is more important for approximate arithmetic. The training of numerical processing and number line estimation were proved to be effective. They both improved the ability of approximate arithmetic. When the difficulty of approximate arithmetic was taken into account, the performance in number line training group was not significantly different among three levels. However, two harder levels achieved significance in numerical comparison training group. Thus, comparing spatial representation ability, symbolic approximation arithmetic relies more on numerical magnitude. Educational implications of the study were discussed.

Keywords: approximate arithmetic, mental number line, numerical magnitude, preschooler

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Authors: Kharouf Malika, Chkeir Aly, Khac Tuan Huynh

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Detecting change points in time series data is a challenging problem, especially in scenario where there is limited prior knowledge regarding the data’s distribution and the nature of the transitions. We present a method designed for detecting changes in the covariance structure of high-dimensional time series data, where the number of variables closely matches the data length. Our objective is to achieve unbiased test statistic estimation under the null hypothesis. We delve into the utilization of Random Matrix Theory to analyze the behavior of our test statistic within a high-dimensional context. Specifically, we illustrate that our test statistic converges pointwise to a normal distribution under the null hypothesis. To assess the effectiveness of our proposed approach, we conduct evaluations on a simulated dataset. Furthermore, we employ our method to examine changes aimed at detecting frailty in the elderly.

Keywords: change point detection, hypothesis tests, random matrix theory, frailty in elderly

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Authors: Péter Tanos, József Kovács, Angéla Anda, Gábor Várbíró, Sándor Molnár, István Gábor Hatvani

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The River Tisza is the second largest river in Central Europe. In this study, Morlet wavelet spectrum (periodicity) analysis was used with chemical, biological and physical water quality data for the Hungarian section of the River Tisza. In the research 15, water quality parameters measured at 14 sampling sites in the River Tisza and 4 sampling sites in the main artificial changes were assessed for the time period 1993 - 2005. Results show that annual periodicity was not always to be found in the water quality parameters, at least at certain sampling sites. Periodicity was found to vary over space and time, but in general, an increase was observed in the company of higher trophic states of the river heading downstream.

Keywords: annual periodicity water quality, spatiotemporal variability of periodic behavior, Morlet wavelet spectrum analysis, River Tisza

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Authors: Jenifer Alam, Rima Chatterjee

Abstract:

Upper Assam sedimentary basin is one of the oldest commercially producing basins of India. Being in a tectonically active zone, estimation of tectonic strain and stress magnitudes has vast application in hydrocarbon exploration and exploitation. This East North East –West South West trending shelf-slope basin encompasses the Bramhaputra valley extending from Mikir Hills in the southwest to the Naga foothills in the northeast. Assam Shelf lying between the Main Boundary Thrust (MBT) and Naga Thrust area is comparatively free from thrust tectonics and depicts normal faulting mechanism. The study area is bounded by the MBT and Main Central Thrust in the northwest. The Belt of Schuppen in the southeast, is bordered by Naga and Disang thrust marking the lower limit of the study area. The entire Assam basin shows low-level seismicity compared to other regions of northeast India. Pore pressure (PP), vertical stress magnitude (SV) and horizontal stress magnitudes have been estimated from two wells - N1 and T1 located in Upper Assam. N1 is located in the Assam gap below the Bramhaputra river while T1, lies in the Belt of Schuppen. N1 penetrates geological formations from top Alluvial through Dhekiajuli, Girujan, Tipam, Barail, Kopili, Sylhet and Langpur to the granitic basement while T1 in trusted zone crosses through Girujan Suprathrust, Tipam Suprathrust, Barail Suprathrust to reach Naga Thrust. Normal compaction trend is drawn through shale points through both wells for estimation of PP using the conventional Eaton sonic equation with an exponent of 1.0 which is validated with Modular Dynamic Tester and mud weight. Observed pore pressure gradient ranges from 10.3 MPa/km to 11.1 MPa/km. The SV has a gradient from 22.20 to 23.80 MPa/km. Minimum and maximum horizontal principal stress (Sh and SH) magnitudes under isotropic conditions are determined using poroelastic model. This approach determines biaxial tectonic strain utilizing static Young’s Modulus, Poisson’s Ratio, SV, PP, leak off test (LOT) and SH derived from breakouts using prior information on unconfined compressive strength. Breakout derived SH information is used for obtaining tectonic strain due to lack of measured SH data from minifrac or hydrofracturing. Tectonic strain varies from 0.00055 to 0.00096 along x direction and from -0.0010 to 0.00042 along y direction. After obtaining tectonic strains at each well, the principal horizontal stress magnitudes are calculated from linear poroelastic model. The magnitude of Sh and SH gradient in normal faulting region are 12.5 and 16.0 MPa/km while in thrust faulted region the gradients are 17.4 and 20.2 MPa/km respectively. Model predicted Sh and SH matches well with the LOT data and breakout derived SH data in both wells. It is observed from this study that the stresses SV>SH>Sh prevailing in the shelf region while near the Naga foothills the regime changes to SH≈SV>Sh area corresponds to normal faulting regime. Hence this model is a reliable tool for predicting stress magnitudes from well logs under active tectonic regime in Upper Assam Basin.

Keywords: Eaton, strain, stress, poroelastic model

Procedia PDF Downloads 188

Authors: Ibrahim Shaker, Amr El Hossany, Moustafa Osman, Mohamed El Raey

Abstract:

This paper will explore integration model between GIS–SCADA system and enclosure quantification model to approach the impact of failure-safe event. There are real demands to identify spatial objects and improve control system performance. Nevertheless, the employed methodology is predicting electro-mechanic operations and corresponding time to environmental incident variations. Open processing, as object systems technology, is presented for integration enclosure database with minimal memory size and computation time via connectivity drivers such as ODBC:JDBC during main stages of GIS–SCADA connection. The function of Geographic Information System is manipulating power distribution in contrast to developing issues. In other ward, GIS-SCADA systems integration will require numerical objects of process to enable system model calibration and estimation demands, determine of past events for analysis and prediction of emergency situations for response training.

Keywords: air dispersion model, environmental management, SCADA systems, GIS system, integration power system

Procedia PDF Downloads 348

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

Abstract:

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

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

Procedia PDF Downloads 146

Authors: Jan-Tore H. Horn, Jørgen Juncher Jensen

Abstract:

Uncertainties related to fatigue damage estimation of non-linear systems are highly dependent on the tail behaviour and extreme values of the stress range distribution. By using a combination of the First Order Reliability Method (FORM) and Monte Carlo simulations (MCS), the accuracy of the fatigue estimations may be improved for the same computational efforts. The method is applied to a bottom-fixed, monopile-supported large offshore wind turbine, which is a non-linear and dynamically sensitive system. Different curve fitting techniques to the fatigue damage distribution have been used depending on the sea-state dependent response characteristics, and the effect of a bi-linear S-N curve is discussed. Finally, analyses are performed on several environmental conditions to investigate the long-term applicability of this multistep method. Wave loads are calculated using state-of-the-art theory, while wind loads are applied with a simplified model based on rotor thrust coefficients.

Keywords: fatigue damage, FORM, monopile, Monte Carlo, simulation, wind turbine

Procedia PDF Downloads 242