Search results for: estimates

Authors: Minna-Maari Harmaala, Hanna Harilainen

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Estimates of the economic value of transitioning to circular economy models vary but it has been estimated to represent $1 trillion worth of new business into the global economy. In Europe alone, estimates claim that adopting circular-economy principles could not only have environmental and social benefits but also generate a net economic benefit of €1.8 trillion by 2030. Proponents of a circular economy argue that it offers a major opportunity to increase resource productivity, decrease resource dependence and waste, and increase employment and growth. A circular system could improve competitiveness and unleash innovation. Yet, most companies are not capturing these opportunities and thus the even abundant circular opportunities remain uncaptured even though they would seem inherently profitable. Service design in broad terms relates to developing an existing or a new service or service concept with emphasis and focus on the customer experience from the onset of the development process. Service design may even mean starting from scratch and co-creating the service concept entirely with the help of customer involvement. Service design methodologies provide a structured way of incorporating customer understanding and involvement in the process of designing better services with better resonance to customer needs. A business model is a depiction of how the company creates, delivers, and captures value; i.e. how it organizes its business. The process of business model development and adjustment or modification is also called business model innovation. Innovating business models has become a part of business strategy. Our hypothesis is that in addition to linear models still being easier to adopt and often with lower threshold costs, companies lack an understanding of how circular models can be adopted into their business and how customers will be willing and ready to adopt the new circular business models. In our research, we use robust service design methodology to develop circular economy solutions with two case study companies. The aim of the process is to not only develop the service concepts and portfolio, but to demonstrate the willingness to adopt circular solutions exists in the customer base. In addition to service design, we employ business model innovation methods to develop, test, and validate the new circular business models further. The results clearly indicate that amongst the customer groups there are specific customer personas that are willing to adopt and in fact are expecting the companies to take a leading role in the transition towards a circular economy. At the same time, there is a group of indifferents, to whom the idea of circularity provides no added value. In addition, the case studies clearly show what changes adoption of circular economy principles brings to the existing business model and how they can be integrated.

Keywords: business model innovation, circular economy, circular economy business models, service design

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Authors: Jiahao Tian, Michael D. Porter

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Law enforcement agencies are tasked with crime prevention and crime reduction under limited resources. Having an accurate temporal estimate of the crime rate would be valuable to achieve such a goal. However, estimation is usually complicated by the interval-censored nature of crime data. We cast the problem of intensity estimation as a Poisson regression using an EM algorithm to estimate the parameters. Two special penalties are added that provide smoothness over the time of day and day of the week. This approach presented here provides accurate intensity estimates and can also uncover day-of-week clusters that share the same intensity patterns. Anticipating where and when crimes might occur is a key element to successful policing strategies. However, this task is complicated by the presence of interval-censored data. The censored data refers to the type of data that the event time is only known to lie within an interval instead of being observed exactly. This type of data is prevailing in the field of criminology because of the absence of victims for certain types of crime. Despite its importance, the research in temporal analysis of crime has lagged behind the spatial component. Inspired by the success of solving crime-related problems with a statistical approach, we propose a statistical model for the temporal intensity estimation of crime with censored data. The model is built on Poisson regression and has special penalty terms added to the likelihood. An EM algorithm was derived to obtain maximum likelihood estimates, and the resulting model shows superior performance to the competing model. Our research is in line with the smart policing initiative (SPI) proposed by the Bureau Justice of Assistance (BJA) as an effort to support law enforcement agencies in building evidence-based, data-driven law enforcement tactics. The goal is to identify strategic approaches that are effective in crime prevention and reduction. In our case, we allow agencies to deploy their resources for a relatively short period of time to achieve the maximum level of crime reduction. By analyzing a particular area within cities where data are available, our proposed approach could not only provide an accurate estimate of intensities for the time unit considered but a time-variation crime incidence pattern. Both will be helpful in the allocation of limited resources by either improving the existing patrol plan with the understanding of the discovery of the day of week cluster or supporting extra resources available.

Keywords: cluster detection, EM algorithm, interval censoring, intensity estimation

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Authors: Elaine Cristina Barboza, Antonio Jaschke Machado

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This paper discusses micrometeorological aspects of the urban climate in three cities in Western São Paulo State: Presidente Prudente, Assis, and Iepê. Particular attention is paid to the method used to estimate the components of the energy balance at the surface. Estimates of convective fluxes showed that the Bowen ratio was an indicator of the local climate and that its magnitude varied between 0.3 and 0.7. Maximum values for the Bowen ratio occurred earlier in Iepê (11:00 am) than in Presidente Prudente (4:00 pm). The results indicate that the Bowen ratio is modulated by the radiation balance at the surface and by different clusters of vegetation.

Keywords: Bowen ratio, medium-sized cities, surface energy balance, urban climate

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Authors: Somveer Singh, Vineet Kumar Singh

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This work contributes a numerical method based on Legendre wavelet approximation for the treatment of partial integro-differential equation (PIDE). Operational matrices of Legendre wavelets reduce the solution of PIDE into the system of algebraic equations. Some useful results concerning the computational order of convergence and error estimates associated to the suggested scheme are presented. Illustrative examples are provided to show the effectiveness and accuracy of proposed numerical method.

Keywords: legendre wavelets, operational matrices, partial integro-differential equation, viscoelasticity

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Authors: Nitaya Buntao

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This paper considers the problems of interval estimation for rainfall mean of the lognormal distribution and the delta-lognormal distribution in Northeastern Thailand. We present here the modified generalized pivotal approach (MGPA) compared to the modified method of variance estimates recovery (MMOVER). The performance of each method is examined in term of coverage probabilities and average lengths by Monte Carlo simulation. An extensive simulation study indicates that the MMOVER performs better than the MGPA approach in terms of the coverage probability; it results in highly accurate coverage probability.

Keywords: rainfall mean, interval estimation, lognormal distribution, delta-lognormal distribution

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Authors: Hassan Al Salman, Ahmed Al Ghafli

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In this study we consider a nonlinear in time finite element approximation of a reaction diffusion system of lambda-omega type. We use a fixed point theorem to prove existence of the approximations. Then, we derive some essential stability estimates and discuss the uniqueness of the approximations. Also, we prove an optimal error bound in time for d=1, 2 and 3 space dimensions. Finally, we present some numerical experiments to verify the theoretical results.

Keywords: reaction diffusion system, finite element approximation, fixed point theorem, an optimal error bound

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Authors: Hamidreza Fazlollahi

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The Re ́nyi entropy comprises a group of data estimates that sums up the well-known Shannon entropy, acquiring a considerable lot of its properties. It appears as unqualified and restrictive entropy, relative entropy, or common data, and has found numerous applications in information theory. In the Re ́nyi’s argument, the area law of the black hole entropy plays a significant role. However, the total entropy can be modified by some quantum effects, motivated by the randomness of a system. In this note, by employing this modified entropy relation, we have derived corrections to Friedmann equations. Taking this entropy associated with the apparent horizon of the Friedmann-Robertson-Walker Universe and assuming the first law of thermodynamics, dE=T_A (dS)_A+WdV, satisfies the apparent horizon, we have reconsidered expanding Universe. Also, the second thermodynamics law has been examined.

Keywords: Friedmann equations, dark energy, first law of thermodynamics, Reyni entropy

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Authors: Mouhamed Mbouandi Njikam

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This work assesses the trade potential of countries in the Economic Community of Central Africa States (ECCAS). The gravity model of trade is used to evaluate the trade flows of member countries, and to compute the trade potential index of ECCAS during 1995-2010. The focus is on the removal of tariffs and non-tariff barriers in the sub-region. Estimates from the gravity model are used for the calculation of the sub-region’s commercial potential. Its three main findings are: (i) the background research shows a low level of integration in the sub-region and open economies; (ii) a low level of industrialization and diversification are the main factors reducing trade potential in the sub-region; (iii) the trade creation predominate on the deflections of trade between member countries.

Keywords: gravity model, ECCAS, trade flows, trade potential, regional cooperation

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Authors: Damanjit Kaur, Avani Bhatia

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Color constancy is significant for human vision since color is a pictorial cue that helps in solving different visions tasks such as tracking, object recognition, or categorization. Therefore, several computational methods have tried to simulate human color constancy abilities to stabilize machine color representations. Two different kinds of methods have been used, i.e., normalization and constancy. While color normalization creates a new representation of the image by canceling illuminant effects, color constancy directly estimates the color of the illuminant in order to map the image colors to a canonical version. Color constancy is the capability to determine colors of objects independent of the color of the light source. This research work studies the most of the well-known color constancy algorithms like white point and gray world.

Keywords: color constancy, gray world, white patch, modified white patch

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Authors: Maysam Shahsavari, Seyed Jamalaldin Haddadi

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There are several methods to localize a mobile robot such as relative, absolute and probabilistic. In this paper, particle filter due to its simple implementation and the fact that it does not need to know to the starting position will be used. This method estimates the position of the mobile robot using a probabilistic distribution, relying on a known map of the environment instead of predicting it. Afterwards, it updates this estimation by reading input sensors and control commands. To receive information from the surrounding world, distance to obstacles, for example, a Kinect is used which is much cheaper than a laser range finder. Finally, after explaining the Adaptive Particle Filter method and its implementation in detail, we will compare this method with the dead reckoning method and show that this method is much more suitable for situations in which we have a map of the environment.

Keywords: particle filter, localization, methods, odometry, kinect

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Authors: Heather E. Ewart, Keith Jensen, Rebecca N. Cliffe

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Fragmentation and changes in the structural composition of tropical forests – as a result of intensifying anthropogenic disturbance – are increasing pressures on local biodiversity. Species with low dispersal abilities have some of the highest extinction risks in response to environmental change, as even small-scale environmental variation can substantially impact their space use and energetic balance. Understanding the implications of forest disturbance is therefore essential, ultimately allowing for more effective and targeted conservation initiatives. Here, the impact of different levels of forest disturbance on the space use, energetics, movement and behavior of 18 brown-throated sloths (Bradypus variegatus) were assessed in the South Caribbean of Costa Rica. A multi-scale framework was used to measure forest disturbance, including large-scale (landscape-level classifications) and fine-scale (within and surrounding individual home ranges) forest composition. Three landscape-level classifications were identified: primary forests (undisturbed), secondary forests (some disturbance, regenerating) and urban forests (high levels of disturbance and fragmentation). Finer-scale forest composition was determined using measurements of habitat structure and quality within and surrounding individual home ranges for each sloth (home range estimates were calculated using autocorrelated kernel density estimation [AKDE]). Measurements of forest quality included tree connectivity, density, diameter and height, species richness, and percentage of canopy cover. To determine space use, energetics, movement and behavior, six sloths in urban forests, seven sloths in secondary forests and five sloths in primary forests were tracked using a combination of Very High Frequency (VHF) radio transmitters and Global Positioning System (GPS) technology over an average period of 120 days. All sloths were also fitted with micro data-loggers (containing tri-axial accelerometers and pressure loggers) for an average of 30 days to allow for behavior-specific movement analyses (data analysis ongoing for data-loggers and primary forest sloths). Data-loggers included determination of activity budgets, circadian rhythms of activity and energy expenditure (using the vector of the dynamic body acceleration [VeDBA] as a proxy). Analyses to date indicate that home range size significantly increased with the level of forest disturbance. Female sloths inhabiting secondary forests averaged 0.67-hectare home ranges, while female sloths inhabiting urban forests averaged 1.93-hectare home ranges (estimates are represented by median values to account for the individual variation in home range size in sloths). Likewise, home range estimates for male sloths were 2.35 hectares in secondary forests and 4.83 in urban forests. Sloths in urban forests also used nearly double (median = 22.5) the number of trees as sloths in the secondary forest (median = 12). These preliminary data indicate that forest disturbance likely heightens the energetic requirements of sloths, a species already critically limited by low dispersal ability and rates of energy acquisition. Energetic and behavioral analyses from the data-loggers will be considered in the context of fine-scale forest composition measurements (i.e., habitat quality and structure) and are expected to reflect the observed home range and movement constraints. The implications of these results are far-reaching, presenting an opportunity to define a critical index of habitat connectivity for low dispersal species such as sloths.

Keywords: biodiversity conservation, forest disturbance, movement ecology, sloths

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Authors: Anna Wiltshire, Rebecca Markham

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Over the last decade, a growing body of evidence has indicated that children with disabilities are often amongst the most excluded and vulnerable in society. The World Bank estimates that 20% of those living in poverty in developing countries are disabled which means that those with the least bear the greatest burden. Furthermore, children with disabilities in Africa have to face a multitude of difficulties ranging from the physical to the psychological. Misconceptions and cultural beliefs are used to justify violence against, or complete shunning of these individuals and their families. In addition, discrimination can prevent access to both education and health services, further compromising these individuals. All children, irrespective of their disability should be able to enjoy human rights without discrimination, but this is often not the case. This poster explores how and why children with disabilities in Africa are subject to violations of their human rights, and suggests ways of addressing these problems.

Keywords: Africa, children, disability, discrimination, human rights

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Authors: Karim Adinehvand, Bakhtiar Azadbakht, Amin Sahebnasagh

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Relation to high absorption fraction of Tc SESTAMIBI by internal organs in heart scan, and these organs are near to generation organs (Ovaries and uterus). In this study, Liver is specified as source organ. Method: we have set amount of absorbed fraction radiopharmaceutical in position of Liver in RANDO-phantom in form of elliptical surfaces, then absorbed dose to ovaries and uterus measured by TLD-100 that had set at position of these organs in RANDO-phantom. Calculation had done by MIRD method. Results from direct measurement and MIRD method are too similar. The absorbed dose to uterus and ovaries for Rest are 26.05µGyMBq-1, 17.23µGyMBq-1 and for Stress are 2.04µGyMBq-1, 1.35µGyMBq-1 respectively.

Keywords: absorbed dose, TLD, MIRD, RANDO-phantom, Tc-99m

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Authors: Jose Funes, Jeff Sauer, Laixiang Sun

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This research examines determinants of multifamily housing development and spillovers in the District of Columbia. A range of socioeconomic factors related to income distribution, productivity, and land use policies are thought to influence the development in contemporary U.S. multifamily housing markets. The analysis leverages data from the American Community Survey to construct panel datasets spanning from 2010 to 2019. Using spatial regression, we identify several socioeconomic measures and land use policies both positively and negatively associated with new housing supply. We contextualize housing estimates related to race in relation to uneven development in the contemporary D.C. housing supply.

Keywords: neighborhood effect, sorting, spatial spillovers, multifamily housing

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Authors: Ayad Asaad Ibrahim

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Myoelectrically controlled prostheses are becoming more and more popular, for below-elbow amputation, the wrist flexor and extensor muscle group, while for above-elbow biceps and triceps brachii muscles are used for control of the prosthesis. A two site multi-function controller is presented. Two stainless steel bipolar electrode pairs are used to monitor the activities in both muscles. The detected signals are processed by new pre-whitening technique to identify the accurate tension estimation in these muscles. These estimates will activate the relevant prosthesis control signal, with a time constant of 200 msec. It is ensured that the tension states in the control muscle to activate a particular prosthesis function are similar to those used to activate normal functions in the natural hand. This facilitates easier training.

Keywords: prosthesis, biosignal processing, pre-whitening, myoelectric controller

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Authors: Sungsik Jo, Hyeonwoo Kim, Iksu Choi, Hunmo Kim

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In the SHP, LVDT sensor is for detecting the length changes of the EHA output, and the thrust of the EHA is controlled by the pressure sensor. Sensor is possible to cause hardware fault by internal problem or external disturbance. The EHA of SHP is able to be uncontrollable due to control by feedback from uncertain information, on this paper; the sliding mode observer algorithm estimates the original sensor output information in permanent sensor fault. The proposed algorithm shows performance to recovery fault of disconnection and short circuit basically, also the algorithm detect various of sensor fault mode.

Keywords: smart hybrid powerpack (SHP), electro hydraulic actuator (EHA), permanent sensor fault tolerance, sliding mode observer (SMO), graphic user interface (GUI)

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Authors: Lubna Naz, Munir Ahmad, G. M. Arif

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This study analyzes static and dynamic welfare impacts of food price changes for various landholding groups in Pakistan. The study uses three classifications of land ownership, landless, small landowners and large landowners, for analysis. The study uses Panel Survey, Pakistan Rural Household Survey (PRHS) of Pakistan Institute of Development Economics Islamabad, of rural households from two largest provinces (Sindh and Punjab) of Pakistan. The study uses all three waves (2001, 2004 and 2010) of PRHS. This research work makes three important contributions in literature. First, this study uses Quadratic Almost Ideal Demand System (QUAIDS) to estimate demand functions for eight food groups-cereals, meat, milk and milk products, vegetables, cooking oil, pulses and other food. The study estimates food demand functions with Nonlinear Seemingly Unrelated (NLSUR), and employs Lagrange Multiplier and test on the coefficient of squared expenditure term to determine inclusion of squared expenditure term. Test results support the inclusion of squared expenditure term in the food demand model for each of landholding groups (landless, small landowners and large landowners). This study tests for endogeneity and uses control function for its correction. The problem of observed zero expenditure is dealt with a two-step procedure. Second, it creates low price and high price periods, based on literature review. It uses elasticity coefficients from QUAIDS to analyze static and dynamic welfare effects (first and second order Tylor approximation of expenditure function is used) of food price changes across periods. The study estimates compensation variation (CV), money metric loss from food price changes, for landless, small and large landowners. Third, this study compares the findings on welfare implications of food price changes based on QUAIDS with the earlier research in Pakistan, which used other specification of the demand system. The findings indicate that dynamic welfare impacts of food price changes are lower as compared to static welfare impacts for all landholding groups. The static and dynamic welfare impacts of food price changes are highest for landless. The study suggests that government should extend social security nets to landless poor and categorically to vulnerable landless (without livestock) to redress the short-term impact of food price increase. In addition, the government should stabilize food prices and particularly cereal prices in the long- run.

Keywords: QUAIDS, Lagrange multiplier, NLSUR, and Tylor approximation

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Authors: Dongxu Chen, Yipeng Li

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This paper presents an information geometry NonlocalMeans(NLM) algorithm for Poisson denoising. NLM estimates a noise-free pixel as a weighted average of image pixels, where each pixel is weighted according to the similarity between image patches in Euclidean space. In this work, every pixel is a Poisson distribution locally estimated by Maximum Likelihood (ML), all distributions consist of a statistical manifold. A NLM denoising algorithm is conducted on the statistical manifold where Fisher information matrix can be used for computing distribution geodesics referenced as the similarity between patches. This approach was demonstrated to be competitive with related state-of-the-art methods.

Keywords: image denoising, Poisson noise, information geometry, nonlocal-means

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Authors: Yoshimoto Kurihara, Tad Gonsalves

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Currently, in the field of object posture estimation, there is research on estimating the position and angle of an object by storing a 3D model of the object to be estimated in advance in a computer and matching it with the model. However, in this research, we have succeeded in creating a module that is much simpler, smaller in scale, and faster in operation. Our 6D pose estimation model consists of two different networks – a classification network and a regression network. From a single RGB image, the trained model estimates the class of the object in the image, the coordinates of the object, and its rotation angle in 3D space. In addition, we compared the estimation accuracy of each camera position, i.e., the angle from which the object was captured. The highest accuracy was recorded when the camera position was 75°, the accuracy of the classification was about 87.3%, and that of regression was about 98.9%.

Keywords: 6D posture estimation, image recognition, deep learning, AlexNet

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Authors: Lu Liao

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This paper studies the impact of private labels on the advertising incentives of national brands. The worldwide expansion of private labels over the past two decades not only transformed the choice sets of consumers but also forced manufacturers of national brands to design new marketing strategies to maintain their market positions. This paper first develops a consumer demand model that incorporates spillover effects of advertising for antacids, including private labels and finds positive spillovers of national brands’ advertising on demand for private label antacids. With the demand estimates, it provides a simulation for the equilibrium prices and advertising levels for leading national brands in a counterfactual where private labels are eliminated to quantify national brands’ advertising incentives as a response to the rise of private labels.

Keywords: advertising, private label, marketing, demand

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Authors: Jerome Blackman, Pamela Franklin, Volha Roshchanka

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The US coal mining sector accounts for 6% of total US Methane emissions (2021). 60% of US coal mining methane emissions come from active underground mine ventilation systems. Abandoned mines contribute about 13% of methane emissions from coal mining. While there are thousands of abandoned underground coal mines in the US, the Environmental Protection Agency (EPA) estimates that fewer than 100 have sufficient methane resources for viable methane recovery and use projects. Many abandoned mines are in remote areas far from potential energy customers and may be flooded, further complicating methane recovery. Because these mines are no longer active, recovery projects can be simpler to implement.

Keywords: abandoned mines, coal mine methane, coal mining, methane emissions, methane mitigation, recovery and use

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Authors: Kiyoumars Roushangar, Saeid Sadaghian

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Although accurate sediment load prediction is very important in planning, designing, operating and maintenance of water resources structures, the transport mechanism is complex, and the deterministic transport models are based on simplifying assumptions often lead to large prediction errors. In this research, firstly, two intelligent ANN methods, Radial Basis and General Regression Neural Networks, are adopted to model of total sediment load transport into Madani Dam reservoir (north of Iran) using the measured data and then applicability of the sediment transport methods developed by Engelund and Hansen, Ackers and White, Yang, and Toffaleti for predicting of sediment load discharge are evaluated. Based on comparison of the results, it is found that the GRNN model gives better estimates than the sediment rating curve and mentioned classic methods.

Keywords: sediment transport, dam reservoir, RBF, GRNN, prediction

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Authors: Shumaila Zeb

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The proposed study aims to investigate insolvency risk of commercial banks of Pakistan. Furthermore, it empirically estimates the effect of already implemented financial regulations on the insolvency risk of banks. To carry out the empirical analysis, a balanced bank-level panel data covering the period 2008-2016 is used. The Z-score is used for calculating the insolvency risk of each bank. The panel regression is used to investigate the relationship between financial regulations and insolvency risk of banks. The empirics reveal that the financial regulations enforced by State Bank of Pakistan have significant impacts on the insolvency risk of banks. The results further indicate that loan ratio and reserve ratio are positively and significantly related to the insolvency risk of banks.

Keywords: insolvency risk, Z-score, financial regulations, banks

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Authors: Z. Masoumi, B. Moaveni

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This article is about first step of structural health monitoring by identifying structural system in the presence of unknown input. In the structural system identification, identification of structural parameters such as stiffness and damping are considered. In this study, the Kalman filter (KF) design for structural systems with unknown excitation is expressed. External excitations, such as earthquakes, wind or any other forces are not measured or not available. The purpose of this filter is its strengths to estimate the state variables of the system in the presence of unknown input. Also least squares estimation (LSE) method with unknown input is studied. Estimates of parameters have been adopted. Finally, using two examples advantages and drawbacks of both methods are studied.

Keywords: Kalman filter (KF), least square estimation (LSE), structural health monitoring (SHM), structural system identification

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Authors: A. D. Rao, Sachiko Mohanty

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The Internal Waves (IWs) are generated by the flow of barotropic tide over the rapidly varying and steep topographic features like continental shelf slope, subsurface ridges, and the seamounts, etc. The IWs of the tidal frequency are generally known as internal tides. These waves have a significant influence on the vertical density and hence causes mixing in the region. Such waves are also important in submarine acoustics, underwater navigation, offshore structures, ocean mixing and biogeochemical processes, etc. over the shelf-slope region. The seasonal variability of internal tides in the Bay of Bengal with special emphasis on its energetics is examined by using three-dimensional MITgcm model. The numerical simulations are performed for different periods covering August-September, 2013; November-December, 2013 and March-April, 2014 representing monsoon, post-monsoon and pre-monsoon seasons respectively during which high temporal resolution in-situ data sets are available. The model is initially validated through the spectral estimates of density and the baroclinic velocities. From the estimates, it is inferred that the internal tides associated with semi-diurnal frequency are more dominant in both observations and model simulations for November-December and March-April. However, in August, the estimate is found to be maximum near-inertial frequency at all the available depths. The observed vertical structure of the baroclinic velocities and its magnitude are found to be well captured by the model. EOF analysis is performed to decompose the zonal and meridional baroclinic tidal currents into different vertical modes. The analysis suggests that about 70-80% of the total variance comes from Mode-1 semi-diurnal internal tide in both observations as well as in the model simulations. The first three modes are sufficient to describe most of the variability for semidiurnal internal tides, as they represent 90-95% of the total variance for all the seasons. The phase speed, group speed, and wavelength are found to be maximum for post-monsoon season compared to other two seasons. The model simulation suggests that the internal tide is generated all along the shelf-slope regions and propagate away from the generation sites in all the months. The model simulated energy dissipation rate infers that its maximum occurs at the generation sites and hence the local mixing due to internal tide is maximum at these sites. The spatial distribution of available potential energy is found to be maximum in November (20kg/m²) in northern BoB and minimum in August (14kg/m²). The detailed energy budget calculation are made for all the seasons and results are analysed.

Keywords: available potential energy, baroclinic energy flux, internal tides, Bay of Bengal

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Authors: Laurent Maurin, Mervi Toivanen

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This paper estimates euro area banks’ internal target capital ratios and investigates whether banks’ adjustment to the targets have an impact on credit supply and holding of securities during the financial crisis in 2005-2011. Using data on listed banks and country-specific macro-variables a partial adjustment model is estimated in a panel context. The results indicate, firstly, that an increase in the riskiness of banks’ balance sheets influences positively on the target capital ratios. Secondly, the adjustment towards higher equilibrium capital ratios has a significant impact on banks’ assets. The impact is found to be more size-able on security holdings than on loans, thereby suggesting a pecking order.

Keywords: Euro area, capital ratios, credit supply, partial adjustment model

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Authors: Teboho J. Mosikari, Johannes T. Tsoku, Diteboho L. Xaba

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The increase of capital mobility across emerging economies has become an interesting topic for many economic policy makers. The current study tests the validity of Feldstein–Horioka puzzle for 5 BRICS countries. The sample period of the study runs from 2001 to 2014. The study uses the following parameter estimates well known as the Fully Modified OLS (FMOLS), and Dynamic OLS (DOLS). The results of the study show that investment and savings are cointegrated in the long run. The parameters estimated using FMOLS and DOLS are 0.85 and 0.74, respectively. These results imply that policy makers within BRICS countries have to consider flexible monetary and fiscal policy instruments to influence the mobility of capital with the bloc.

Keywords: Feldstein and Horioka puzzle, saving and investment, panel models, BRICS countries

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Authors: Vikram Saini, Lillie Dewan

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This paper presents the iterative schemes based on Least square, Hierarchical Least Square and Stochastic Approximation Gradient method for the Identification of Wiener model with parametric structure. A gradient method is presented for the parameter estimation of wiener model with noise conditions based on the stochastic approximation. Simulation results are presented for the Wiener model structure with different static non-linear elements in the presence of colored noise to show the comparative analysis of the iterative methods. The stochastic gradient method shows improvement in the estimation performance and provides fast convergence of the parameters estimates.

Keywords: hard non-linearity, least square, parameter estimation, stochastic approximation gradient, Wiener model

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Authors: Divvela Vishnu Sai Kumar, Deepak Arora, Sheenu Rizvi

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Forecasting a cyclone through satellite images consists of the estimation of the intensity of the cyclone and predicting it before a cyclone comes. This research work can help people to take safety measures before the cyclone comes. The prediction of the intensity of a cyclone is very important to save lives and minimize the damage caused by cyclones. These cyclones are very costliest natural disasters that cause a lot of damage globally due to a lot of hazards. Authors have proposed five different CNN (Convolutional Neural Network) models that estimate the intensity of cyclones through INSAT-3D IR images. There are a lot of techniques that are used to estimate the intensity; the best model proposed by authors estimates intensity with a root mean squared error (RMSE) of 10.02 kts.

Keywords: estimating cyclone intensity, deep learning, convolution neural network, prediction models

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Authors: Yogita Mishra, Arijit Roy, Dhruval Bhavsar

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The study estimates the nitrogen concentration in selected vegetation community’s i.e. chir pine (pinusroxburghii) by using hyperspectral satellite data and also identified the appropriate spectral bands and nitrogen indices. The Short Wave InfraRed reflectance spectrum at 1790 nm and 1680 nm shows the maximum possible absorption by nitrogen in selected species. Among the nitrogen indices, log normalized nitrogen index performed positively and negatively too. The strong positive correlation is taken out from 1510 nm and 760 nm for the pinusroxburghii for leaf nitrogen concentration and leaf nitrogen mass while using NDNI. The regression value of R² developed by using linear equation achieved maximum at 0.7525 for the analysis of satellite image data and R² is maximum at 0.547 for ground truth data for pinusroxburghii respectively.

Keywords: hyperspectral, NDNI, nitrogen concentration, regression value

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