Search results for: causal estimation

Authors: Chengli Liu, C. K. M. Lee

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The tradition competitive newsvendor game assumes decision makers are rational. However, there are behavioral biases when people make decisions, such as loss aversion, mental accounting and overconfidence. Overestimation of a subject’s own performance is one type of overconfidence. The objective of this research is to analyze the impact of the overestimated demand in the newsvendor competitive game with two players. This study builds a competitive newsvendor game model where newsvendors have private information of their demands, which is overestimated. At the same time, demands of each newsvendor forecasted by a third party institution are available. This research shows that the overestimation leads to demand steal effect, which reduces the competitor’s order quantity. However, the overall supply of the product increases due to overestimation. This study illustrates the boundary condition for the overestimated newsvendor to have the equilibrium order drop due to the demand steal effect from the other newsvendor. A newsvendor who has higher critical fractile will see its equilibrium order decrease with the drop of estimation level from the other newsvendor.

Keywords: bias, competing newsvendor, Nash equilibrium, overestimation

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Authors: Mohammad Shams Esfand Abadi, Mohammad Ranjbar, Reza Ebrahimpour

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This work presents the distributed processing solution problem in a diffusion network based on the adapt then combine (ATC) and combine then adapt (CTA)selective partial update normalized least mean squares (SPU-NLMS) algorithms. Also, we extend this approach to dynamic selection affine projection algorithm (DS-APA) and ATC-DS-APA and CTA-DS-APA are established. The purpose of ATC-SPU-NLMS and CTA-SPU-NLMS algorithm is to reduce the computational complexity by updating the selected blocks of weight coefficients at every iteration. In CTA-DS-APA and ATC-DS-APA, the number of the input vectors is selected dynamically. Diffusion cooperation strategies have been shown to provide good performance based on these algorithms. The good performance of introduced algorithm is illustrated with various experimental results.

Keywords: selective partial update, affine projection, dynamic selection, diffusion, adaptive distributed networks

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Authors: Yin Ma, Xun Wang, Kelsey Austin

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Purpose – Building upon career construction theory and the conservation of resources theory, we developed a moderated mediation model to examine how the perceived university support impact students’ career adapting responses, namely, crystallization, exploration, decision and preparation, via the mediator career adaptability and moderator perceived parental support. Design/methodology/approach – The multi-stage sampling strategy was employed and survey data were collected. Structural equation modeling was used to perform the analysis. Findings – Perceived university support could directly promote students’ career adaptability, and promote three career adapting responses, namely, exploration, decision and preparation. It could also impact four career adapting responses via mediation effect of career adaptability. Its impact on students’ career adaptability can greatly increase when students’ receive parental related career support. Research limitations/implications – The cross-sectional design limits causal inference. Conducted in China, our findings should be cautiously interpreted in other countries due to cultural differences. Practical implications – University support is vital to students’ career adaptability and supports from parents can enhance this process. University-home collaboration is necessary to promote students’ career adapting responses. For students, seeking and utilizing as much supporting resources as possible is vital for their human resources development. On an organizational level, universities could benefit from our findings by introducing the practices which ask students to rate the career-related courses and encourage them to chat with parents regularly. Originality/ value – Using recently developed scale, current work contributes to the literature by investigating the impact of multiple contextual factors on students’ career adapting response. It also provide the empirical support for the role of human intervention in fostering career adapting responses.

Keywords: career adapability, university and parental support, China studies, sociology of education

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Authors: Raquel Nieto, Marta Vázquez, Anita Drumond, Luis Gimeno

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One of the hot spots of climate change is the increment of ocean evaporation. The best estimation of evaporation, OAFlux data, shows strong increasing trends in evaporation from the oceans since 1978, with peaks during the hemispheric winter and strongest along the paths of the global western boundary currents and any inner Seas. The transport of moisture from oceanic sources to the continents is the connection between evaporation from the ocean and precipitation over the continents. A key question is to try to relate evaporative source regions over the oceans where trends have occurred in the last decades with their sinks over the continents to check if there have been also any trends in the precipitation amount or its characteristics. A Lagrangian approach based on FLEXPART and ERA-interim data is used to establish this connection. The analyzed period was 1980 to 2012. Results show that there is not a general pattern, but a significant agreement was found in important areas of climate interest.

Keywords: ocean evaporation, Lagrangian approaches, contiental precipitation, Europe

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Authors: Kaori Narita, Juan de Dios Tena Horrillo, Claudio Detotto

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Decisions on replacement of leaders are of significance and high prevalence in any organization, and concerns many of its stakeholders, whether it is a leader in a political party or a CEO of a firm, as indicated by high media coverage of such events. This merits an investigation into the consequences and implications of a leadership change on the performances and behavior of organizations and their workers. Sport economics provides a fruitful field to explore these issues due to the high frequencies of managerial changes in professional sports clubs and the transparency and regularity of observations of team performance and players’ abilities. Much of the existing research on managerial change focuses on how this affects the performance of an organization. However, there is scarcely attention paid to the consequences of such events on the behavior of individuals within the organization. Changes in behavior and attitudes of a group of workers due to a managerial change could be of great interest in management science, psychology, and operational research. On the other hand, these changes cannot be observed in the final outcome of the organization, as this is affected by many other unobserved shocks, for example, the stress level of workers with the need to deal with a difficult situation. To fill this gap, this study shows the first attempt to evaluate the impact of managerial change on players’ behaviors such as attack intensity, aggressiveness, and efforts. The data used in this study is from the top tier Italian football league (“Serie A”), where an average of 13 within season replacements of head coaches were observed over the period of seasons from 2000/2001 to 2017/18. The preliminary estimation employs Pooled Ordinary Least Square (POLS) and club-season Fixed Effect (FE) in order to assess the marginal effect of having a new manager on the number of shots, corners and red/yellow cards after controlling for a home-field advantage, ex ante abilities and current positions in the league of a team and their opponent. The results from this preliminary estimation suggest that the teams do not show a significant difference in their behaviors before and after the managerial change. To build on these preliminary results, other methods, including propensity score matching and non-linear model estimates, will be used. Moreover, the study will further investigate these issues by considering other measurements of attack intensity, aggressiveness, and efforts, such as possessions, a number of fouls and the athletic performance of players, respectively. Finally, the study is going to investigate whether these results vary over the characteristics of a new head coach, for example, their age and experience as a manager and a player. Thus far, this study suggests that certain behaviours of individuals in an organisation are not immediately affected by a change in leadership. To confirm this preliminary finding and lead to a more solid conclusion, further investigation will be conducted in the aforementioned manner, and the results will be elaborated in the conference.

Keywords: behaviour, effort, manager characteristics, managerial change, sport economics

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Authors: Khadidja Bellifa, Sidi Mohamed Mekelleche

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Phenols and especially halogenated phenols represent a substantial part of the chemicals produced worldwide and are known as aquatic pollutants. Quantitative structure–toxicity relationship (QSTR) models are useful for understanding how chemical structure relates to the toxicity of chemicals. In the present study, the acute toxicities of 45 halogenated phenols to Tetrahymena Pyriformis are estimated using no cost semi-empirical quantum chemistry methods. QSTR models were established using the multiple linear regression technique and the predictive ability of the models was evaluated by the internal cross-validation, the Y-randomization and the external validation. Their structural chemical domain has been defined by the leverage approach. The results show that the best model is obtained with the AM1 method (R²= 0.91, R²CV= 0.90, SD= 0.20 for the training set and R²= 0.96, SD= 0.11 for the test set). Moreover, all the Tropsha’ criteria for a predictive QSTR model are verified.

Keywords: halogenated phenols, toxicity mechanism, hydrophobicity, electrophilicity index, quantitative stucture-toxicity relationships

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Authors: Carolyn Scott, Rachel Nugent

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The agricultural industry in Ireland and worldwide is one of the most dangerous occupations with respect to occupational health and safety accidents and fatalities. Many accident causation models have been developed in safety research to understand the underlying and contributory factors that lead to the occurrence of an accident. Due to the uniqueness of the agricultural sector, current accident causation theories cannot be applied. This paper presents an accident causation model named the Irish Farm Accident Causation Model (IFACM) which has been specifically tailored to the needs of Irish farms. The IFACM is a theoretical and practical model of accident causation that arranges the causal factors into a graphic representation of originating, shaping, and contributory factors that lead to accidents when unsafe acts and conditions are created that are not rectified by control measures. Causes of farm accidents were assimilated by means of a thorough literature review and were collated to form a graphical representation of the underlying causes of a farm accident. The IFACM was validated retrospectively through case study analysis and peer review. Participants in the case study (n=10) identified causes that led to a farm accident in which they were involved. A root cause analysis was conducted to understand the contributory factors surrounding the farm accident, traced back to the ‘root cause’. Experts relevant to farm safety accident causation in the agricultural industry have peer reviewed the IFACM. The accident causation process is complex. Accident prevention requires a comprehensive understanding of this complex process because to prevent the occurrence of accidents, the causes of accidents must be known. There is little research on the key causes and contributory factors of unsafe behaviours and accidents on Irish farms. The focus of this research is to gain a deep understanding of the causality of accidents on Irish farms. The results suggest that the IFACM framework is helpful for the analysis of the causes of accidents within the agricultural industry in Ireland. The research also suggests that there may be international applicability if further research is carried out. Furthermore, significant learning can be obtained from considering the underlying causes of accidents.

Keywords: farm safety, farm accidents, accident causation, root cause analysis

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Authors: Asima Shah, F. A. Masoodi, Adil Gani, Bilal Ahmad Ashwar

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The present study was designed to evaluate the effect of γ-rays on the antioxidant and antiproliferative potential of β-glucan isolated from oats. The β-glucan was irradiated with 0, 2, 6, and 10 kGy by gamma ray. The samples were characterized by FT-IR, GPC, and quantitative estimation by Megazyme β-glucan assay kit. The average molecular weight of non-irradiated β-glucan was 199 kDa that decreased to 70 kDa at 10 kGy. Both FT-IR spectrum and chemical analysis revealed that the extracted β-glucan was pure having minor impurities. Antioxidant activity was evaluated by DPPH, lipid peroxidation, reducing power, metal chelating ability and oxidative DNA damage assays. Results revealed that the antioxidant activity of β-glucan increased with the increase in irradiation dose. Irradiated β-glucan also exhibited dose dependent cancer cell growth inhibition with irradiation doses. The study revealed that low molecular weight β-glucan with enhanced antioxidant and antiproliferative activities can be produced by a simple irradiation method.

Keywords: γ-irradiation, antioxidant activity, antiproliferative activity, β-glucan, oats

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Authors: Sherine Farrag

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Currently-used MRI scanners in Cairo City possess static magnetic field (SMF) that varies from 0.25 up to 3T. More than half of them possess SMF of 1.5T. The SMF of the magnet determine the diagnostic power of a scanner, but not worker's exposure profile. This research paper presents an approach for numerical computation of induced electric fields and SAR values by estimation of fringe static magnetic fields. Iso-gauss line of MR was mapped and a polynomial function of the 7th degree was generated and tested. Induced current field due to worker motion in the SMF and SAR values for organs and tissues have been calculated. Results illustrate that the computation tool used permits quick accurate MRI iso-gauss mapping and calculation of SAR values which can then be used for assessment of occupational exposure profile of MRI operators.

Keywords: MRI occupational exposure, MRI safety, induced current density, specific absorption rate, static magnetic fields

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Authors: Pedro Mauricio Acosta, Carlos Andrés Caro

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This research presents the regionalization of IDF curves for the department of Boyacá, Colombia, which comprises 16 towns, including the provincial capital, Tunja. For regionalization adjustment parameters (U and alpha) of the IDF curves stations referred to in the studied area were used. Similar regionalization is used by the interpolation of intensities. In the case of regionalization by parameters found by the construction of the curves intensity, duration and frequency estimation methods using ordinary moments and maximum likelihood. Regionalization and interpolation of data were performed with the assistance of Arcgis software. Within the development of the project the best choice to provide a level of reliability such as to determine which of the options and ways to regionalize is best sought. The resulting isolines maps were made in the case of regionalization intensities, each map is associated with a different return period and duration in order to build IDF curves in the studied area. In the case of the regionalization maps parameters associated with each parameter were performed last.

Keywords: intensity duration, frequency curves, regionalization, hydrology

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Authors: Paula Simões, Isabel Natário

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This paper reviews a number of theoretical aspects for implementing an explicit spatial perspective in econometrics for modelling non-continuous data, in general, and count data, in particular. It provides an overview of the several spatial econometric approaches that are available to model data that are collected with reference to location in space, from the classical spatial econometrics approaches to the recent developments on spatial econometrics to model count data, in a Bayesian hierarchical setting. Considerable attention is paid to the inferential framework, necessary for structural consistent spatial econometric count models, incorporating spatial lag autocorrelation, to the corresponding estimation and testing procedures for different assumptions, to the constrains and implications embedded in the various specifications in the literature. This review combines insights from the classical spatial econometrics literature as well as from hierarchical modeling and analysis of spatial data, in order to look for new possible directions on the processing of count data, in a spatial hierarchical Bayesian econometric context.

Keywords: spatial data analysis, spatial econometrics, Bayesian hierarchical models, count data

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Authors: El Andari Chifaa, Bouaziz Rached

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The central focus of this paper was to check whether the Okun’s law in Tunisia is valid or not. For this purpose, we have used quarterly time series data during the period 1990Q1-2014Q1. Firstly, we applied the error correction model instead of the difference version of Okun's Law, the Engle-Granger and Johansen test are employed to find out long run association between unemployment, production, and how error correction mechanism (ECM) is used for short run dynamic. Secondly, we used the gap version of Okun’s law where the estimation is done from three band pass filters which are mathematical tools used in macro-economic and especially in business cycles theory. The finding of the study indicates that the inverse relationship between unemployment and output is verified in the short and long term, and the Okun's law holds for the Tunisian economy, but with an Okun’s coefficient lower than required. Therefore, our empirical results have important implications for structural and cyclical policymakers in Tunisia to promote economic growth in a context of lower unemployment growth.

Keywords: Okun’s law, validity, unit root, cointegration, error correction model, bandpass filters

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Authors: Haowei Lu, Anaya Aaron

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Understanding historical solar generation and forecasting future solar generation from interconnected Distributed Energy Resources (DER) is crucial for utility planning and interconnection studies. The existing methodology, which relies on solar radiation, weather data, and common inverter models, is becoming less accurate. Rapid advancements in DER technologies have resulted in more diverse project sites, deviating from common patterns due to various factors such as DC/AC ratio, solar panel performance, tilt angle, and the presence of DC-coupled battery energy storage systems. In this paper, the authors review 10,000 DER projects within the system and analyze the Advanced Metering Infrastructure (AMI) data for various types to demonstrate the impact of different parameters. An updated methodology is proposed for redefining historical and future solar generation in distribution feeders.

Keywords: photovoltaic system, solar energy, fluctuations, energy storage, uncertainty

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Authors: N. Jinesh, K. Shankar

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This article presents a method of using the one dimensional piezo-electric patch on beam model for structural identification. A hybrid element constituted of one dimensional beam element and a PZT sensor is used with reduced material properties. This model is convenient and simple for identification of beams. Accuracy of this element is first verified against a corresponding 3D finite element model (FEM). The structural identification is carried out as an inverse problem whereby parameters are identified by minimizing the deviation between the predicted and measured voltage response of the patch, when subjected to excitation. A non-classical optimization algorithm Particle Swarm Optimization is used to minimize this objective function. The signals are polluted with 5% Gaussian noise to simulate experimental noise. The proposed method is applied on beam structure and identified parameters are stiffness and damping. The model is also validated experimentally.

Keywords: inverse problem, particle swarm optimization, PZT patches, structural identification

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Authors: Hidir S. Nogay

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In this study, two systems were created to predict interior temperature in induction motor. One of them consisted of a simple ANN model which has two layers, ten input parameters and one output parameter. The other one consisted of eight ANN models connected each other as cascaded. Cascaded ANN system has 17 inputs. Main reason of cascaded system being used in this study is to accomplish more accurate estimation by increasing inputs in the ANN system. Cascaded ANN system is compared with simple conventional ANN model to prove mentioned advantages. Dataset was obtained from experimental applications. Small part of the dataset was used to obtain more understandable graphs. Number of data is 329. 30% of the data was used for testing and validation. Test data and validation data were determined for each ANN model separately and reliability of each model was tested. As a result of this study, it has been understood that the cascaded ANN system produced more accurate estimates than conventional ANN model.

Keywords: cascaded neural network, internal temperature, inverter, three-phase induction motor

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Authors: Hang Lo Lee, Ki Il Song, Hee Hwan Ryu

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An accurate prediction of TBM(Tunnel Boring Machine) performance is very difficult for reliable estimation of the construction period and cost in preconstruction stage. For this purpose, the aim of this study is to analyze the evaluation process of various prediction models published since 2000 for TBM performance, and to select the optimal input parameters for the prediction model. A classification system of TBM performance prediction model and applied methodology are proposed in this research. Input and output parameters applied for prediction models are also represented. Based on these results, a statistical analysis is performed using the collected data from shield TBM tunnel in South Korea. By performing a simple regression and residual analysis utilizinFg statistical program, R, the optimal input parameters are selected. These results are expected to be used for development of prediction model of TBM performance.

Keywords: TBM performance prediction model, classification system, simple regression analysis, residual analysis, optimal input parameters

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Authors: Gopalasingam Daisan

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Landmines and ammunitions have been creating a significant threat to the people and animals, after the war, the landmines remain in the land and it plays a vital role in civilian’s security. Especially the Children are at the highest risk because they are curious. After all, an unexploded bomb can look like a tempting toy to an inquisitive child. The initial step of designing the UAS (Unmanned Aircraft Systems) for landmine detection is to choose an appropriate and effective sensor to locate the landmines and other unexploded ammunitions. The sensor weight and other components related to the sensor supporting device’s weight are taken as a payload weight. The mission requirement is to find the landmines in a particular area by making a proper path that will cover all the vicinity in the desired area. The weight estimation of the UAV (Unmanned Aerial Vehicle) can be estimated by various techniques discovered previously with good accuracy at the first phase of the design. The next crucial part of the design is to calculate the power requirement and the wing loading calculations. The matching plot techniques are used to determine the thrust-to-weight ratio, and this technique makes this process not only easiest but also precisely. The wing loading can be calculated easily from the stall equation. After these calculations, the wing area is determined from the wing loading equation and the required power is calculated from the thrust to weight ratio calculations. According to the power requirement, an appropriate engine can be selected from the available engine from the market. And the wing geometric parameter is chosen based on the conceptual sketch. The important steps in the wing design to choose proper aerofoil and which will ensure to create sufficient lift coefficient to satisfy the requirements. The next component is the tail; the tail area and other related parameters can be estimated or calculated to counteract the effect of the wing pitching moment. As the vertical tail design depends on many parameters, the initial sizing only can be done in this phase. The fuselage is another major component, which is selected based on the slenderness ratio, and also the shape is determined on the sensor size to fit it under the fuselage. The landing gear is one of the important components which is selected based on the controllability and stability requirements. The minimum and maximum wheel track and wheelbase can be determined based on the crosswind and overturn angle requirements. The minor components of the landing gear design and estimation are not the focus of this project. Another important task is to calculate the weight of the major components and it is going to be estimated using empirical relations and also the mass is added to each such component. The CG and moment of inertia are also determined to each component separately. The sensitivity of the weight calculation is taken into consideration to avoid extra material requirements and also reduce the cost of the design. Finally, the aircraft performance is calculated, especially the V-n (velocity and load factor) diagram for different flight conditions such as not disturbed and with gust velocity.

Keywords: landmine, UAS, matching plot, optimization

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Authors: Thuraya Ahmed Al Shidhani, Yahya Al Farsi, Alya Al Husni, Samir Al Adawi

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Background: Knee osteoarthritis (knee OA) represents a major public health burden worldwide, particularly among older adults. However, little has been documented from Arabian Gulf countries, which have left an information gap. Objective: This study describes the socio-demographic, clinical risk factors, and use of herbal medicine among men and women seeking consultation for knee OA at two secondary healthcare facilities in Muscat, Oman. Methods: A cross-sectional study was conducted among 213 Omani adults with knee OA attending a referral polyclinic in Muscat, Oman, over 12 months from January to December. Socio-demographic data were collected from the participants who are seeking consultation for knee OA. Results: Among the 213 study participants, 171 were females and 42 males. The females were comparatively older than the males, had lower education and lower-income, and more overweight. The majority of the participants were normal weight or underweight. About one-third of participants reported OA in other joints as well. Most participants recalled that they had knee OA for less than a year. About 12% reported a history of trauma. The majority (63%) concurrently had other chronic illnesses, and 33% reported having at least one complication. About 22% were using herbal medicines. About 77% are using herbal local applications in form of powder and creams. Conclusion: This study, to our knowledge, is the first to explore socio-demographic characteristics, clinical risk factors and use of herbal medicine among sufferers of knee OA in Oman. Knee OA tended to occur among our participants at younger ages than reported elsewhere, while obesity appeared orthogonal to the severity of knee OA. Women were more affected than men. About one quarter of Omani patients are using herbal medicine. More studies are needed to understand the causal factors and development of knee OA in Oman. Targeted health education and rehabilitation programs are needed, particularly among Omani women, to improve their physical quality of life.

Keywords: knee joint, osteoarthritis, herbal medicine, Oman

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Authors: Yan-Ren Chen, Jenn-Kaie Lain

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This paper proposes a novel indoor positioning algorithm based on visible light communications, implemented by light-emitting diode fixtures. In the proposed positioning algorithm, distances between light-emitting diode fixtures and mobile terminal are derived from the assumption of ideal Lambertian optic radiation model, and Trilateration positioning method is proceeded immediately to get the coordinates of mobile terminal. The proposed positioning algorithm directly obtains distance information from the optical signal modeling, and therefore, statistical distribution of received signal strength at different positions in interior space has no need to be pre-established. Numerically, simulation results have shown that the proposed indoor positioning algorithm can provide accurate location coordinates estimation.

Keywords: indoor positioning, received signal strength, trilateration, visible light communications

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Authors: Ossama Abdelmotaal, Olfat Shaker, Tarek Salman, Lamiaa Nabeel, Mostafa Shabayek

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Colorectal Cancer (CRC) is an important worldwide health problem. Colonoscopy is used in detecting CRC suffer from drawbacks where colonoscopy is an invasive method. This study validates easier and less time-consuming techniques to evaluate the usefulness of detecting miRNA-21, miRNA-215 and miRNA-378 in the sera of colorectal cancer patients as new diagnostic tools. This study includes malignant (Colo Rectal Cancer patients, n= 64)) and healthy (n=27) groups. The studied groups were subjected to colonoscopic examination and estimation of miRNA-21, miRNA-215 and miRNA-378 in sera by RT-PCR. miRNA-21 showed the statistically significantly highest median fold change. miRNA-378 showed statistically significantly lower value (Both showed over-expression). miRNA-215 showed the statistically significantly lowest median fold change (It showed down-regulation). Overall the miRNA (21-215 and 378) appear to be promising method of detecting CRC and evaluating its stages.

Keywords: colorectal cancer, miRNA-21, miRNA-215, miRNA-378

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Authors: Alam Ali, Ashok Kumar Pathak

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Path analysis is a statistical technique used to evaluate the strength of the direct and indirect effects of variables. One or more structural regression equations are used to estimate a series of parameters in order to find the better fit of data. Sometimes, exogenous variables do not show a significant strength of their direct and indirect effect when the assumption of classical regression (ordinary least squares (OLS)) are violated by the nature of the data. The main motive of this article is to investigate the efficacy of the copula-based regression approach over the classical regression approach and calculate the direct and indirect effects of variables when data violates the OLS assumption and variables are linked through an elliptical copula. We perform this study using a well-organized numerical scheme. Finally, a real data application is also presented to demonstrate the performance of the superiority of the copula approach.

Keywords: path analysis, copula-based regression models, direct and indirect effects, k-fold cross validation technique

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Authors: L. Bikulciene, E. Venskaityte, G. Jarusevicius

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Non-stationary and nonlinear signals generated by living complex systems defy traditional mechanistic approaches, which are based on homeostasis. Previous our studies have shown that the evaluation of the interactions of physiological signals by using special analysis methods is suitable for observation of physiological processes. It is demonstrated the possibility of using deep physiological model, based interpretation of the changes of the human body’s functional states combined with an application of the analytical method based on matrix theory for the physiological signals analysis, which was applied on high risk cardiac patients. It is shown that evaluation of cardiac signals interactions show peculiar for each individual functional changes at the onset of hemodynamic restoration procedure. Therefore we suggest that the alterations of functional state of the body, after patients overcome surgery can be complemented by the data received from the suggested approach of the evaluation of functional variables interactions.

Keywords: cardiac diseases, complex systems theory, ECG analysis, matrix analysis

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Authors: Kaige Shi, Chao Jiang, Xin Li

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The swirl gripper is an electrically activated noncontact handling device that uses swirling airflow to generate a lifting force. This force can be used to pick up a workpiece placed underneath the swirl gripper without any contact. It is applicable, for example, in the semiconductor wafer production line, where contact must be avoided during the handling and moving of a workpiece to minimize damage. When a workpiece levitates underneath a swirl gripper, the gap height between them is crucial for safe handling. Therefore, in this paper, we propose a method to estimate the levitation gap height by detecting pressure at two points. The method is based on theoretical model of the swirl gripper, and has been experimentally verified. Furthermore, the force between the gripper and the workpiece can also be estimated using the detected pressure. As a result, the nonlinear relationship between the force and gap height can be linearized by adjusting the rotating speed of the fan in the swirl gripper according to the estimated force and gap height. The linearized relationship is expected to enhance handling stability of the workpiece.

Keywords: swirl gripper, noncontact handling, levitation, gap height estimation

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Authors: Panudet Saengseedam, Nanthachai Kantanantha

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This paper proposes a linear mixed model (LMM) with spatial effects to forecast rice and cassava yields in Thailand at the same time. A multivariate conditional autoregressive (MCAR) model is assumed to present the spatial effects. A Bayesian method is used for parameter estimation via Gibbs sampling Markov Chain Monte Carlo (MCMC). The model is applied to the rice and cassava yields monthly data which have been extracted from the Office of Agricultural Economics, Ministry of Agriculture and Cooperatives of Thailand. The results show that the proposed model has better performance in most provinces in both fitting part and validation part compared to the simple exponential smoothing and conditional auto regressive models (CAR) from our previous study.

Keywords: Bayesian method, linear mixed model, multivariate conditional autoregressive model, spatial time series

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Authors: K. Allaw, J. Adjizian Gerard, M. Chehayeb, A. Raad, W. Fahs, A. Badran, A. Fakherdin, H. Madi, N. Badaro Saliba

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Population estimation using Geographic Information System (GIS) and remote sensing faces many obstacles such as the determination of permanent residents. A permanent resident is an individual who stays and works during all four seasons in his village. So, all those who move towards other cities or villages are excluded from this category. The aim of this study is to identify the factors affecting the percentage of permanent residents in a village and to determine the attributed weight to each factor. To do so, six factors have been chosen (slope, precipitation, temperature, number of services, time to Central Business District (CBD) and the proximity to conflict zones) and each one of those factors has been evaluated using one of the following data: the contour lines map of 50 m, the precipitation map, four temperature maps and data collected through surveys. The weighting procedure has been done using decision tree method. As a result of this procedure, temperature (50.8%) and percentage of precipitation (46.5%) are the most influencing factors.

Keywords: remote sensing, GIS, permanent residence, decision tree, Lebanon

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Authors: Naci Büyükkaracığan

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Today, the need for water sources is swiftly increasing due to population growth. At the same time, it is known that some regions will face with shortage of water and drought because of the global warming and climate change. In this context, evaluation and analysis of hydrological data such as the observed trends, drought and flood prediction of short term flow has great deal of importance. The most accurate selection probability distribution is important to describe the low flow statistics for the studies related to drought analysis. As in many basins In Turkey, Gediz River basin will be affected enough by the drought and will decrease the amount of used water. The aim of this study is to derive appropriate probability distributions for frequency analysis of annual minimum flows at 6 gauging stations of the Gediz Basin. After applying 10 different probability distributions, six different parameter estimation methods and 3 fitness test, the Pearson 3 distribution and general extreme values distributions were found to give optimal results.

Keywords: Gediz Basin, goodness-of-fit tests, minimum flows, probability distribution

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Authors: B. Zerouali, M. Kara, B. Hamaidi, H. Mahdjoub, S. Rouabhia

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In this paper, a safety analysis for crude oil tanks to prevent undesirable events that may cause catastrophic accidents. The estimation of the probability of damage to industrial systems is carried out through a series of steps, and in accordance with a specific methodology. In this context, this work involves developing an assessment tool and risk analysis at the level of crude oil tanks system, based primarily on identification of various potential causes of crude oil tanks fire and explosion by the use of Fault Tree Analysis (FTA), then improved risk modelling by Bayesian Networks (BNs). Bayesian approach in the evaluation of failure and quantification of risks is a dynamic analysis approach. For this reason, have been selected as an analytical tool in this study. Research concludes that the Bayesian networks have a distinct and effective method in the safety analysis because of the flexibility of its structure; it is suitable for a wide variety of accident scenarios.

Keywords: bayesian networks, crude oil tank, fault tree, prediction, safety

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Authors: Linyu Wang, Jiahui Ma, Jianhong Xiang, Hanyu Jiang

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the traditional greedy compressed sensing algorithm needs to know the signal sparsity when recovering the signal, but the signal sparsity in the practical application can not be obtained as a priori information, and the recovery accuracy is low, which does not meet the needs of practical application. To solve this problem, this paper puts forward Piecewise adaptive backtracking orthogonal least squares algorithm. The algorithm is divided into two stages. In the first stage, the sparsity pre-estimation strategy is adopted, which can quickly approach the real sparsity and reduce time consumption. In the second stage iteration, the correction strategy and adaptive step size are used to accurately estimate the sparsity, and the backtracking idea is introduced to improve the accuracy of signal recovery. Through experimental simulation, the algorithm can accurately recover the estimated signal with fewer iterations when the sparsity is unknown.

Keywords: compressed sensing, greedy algorithm, least square method, adaptive reconstruction

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Authors: Jane N. O'Sullivan

Abstract:

In most studies relating change in fertility to potentially causal factors (such as girls’ educational attainment, infant mortality or urbanization), the presence or nature of family planning efforts are not examined, potentially misattributing their contributions. Modest impacts of voluntary family planning programs on fertility change have been claimed, citing the near-term effects of historical quasi-experimental projects – notably in Bangladesh and in Ghana – where recipients and non-recipients could be contrasted. By their nature, such experiments lacked the wider cultural impacts of national programs. Concurrently, analyses relating population growth with economic advancement have been equivocal, discrediting previous widespread concern which prevailed before the 1980s. This neutral view has been revised more recently with demographic dividend theory crediting higher working-age proportion with some economic stimulus if supported by sufficient institutional and human capacity. In this study of country-level data, cross-country comparisons spanning six decades relate fertility decline with family planning effort, GDP per capita and female education, finding that the timing of rapid fertility decline aligns with commencement of voluntary family planning programs, while economic betterment came after substantial fertility fall. The relationship between fertility and primary education completion was inconsistent, with potential channels of causation operating in both directions. GDP per capita was unrelated to rate of fertility decline, but total fertility rates above three children per woman strongly impeded enrichment. By synchronizing countries with respect to their fertility transition, strong relationships are revealed which suggest lower fertility enables economic betterment, rather than the other way around. These results argue in favour of elevating voluntary family planning as a development priority.

Keywords: economic advance, family planning effort, fertility decline, population growth rate

Procedia PDF Downloads 122

Authors: Tasneem Imam, Justine S. Gibson, Mohammad Foysal, Shetu B. Das, Rashed Mahmud, Suman D. Gupta, Ahasanul Hoque, Guillaume Fournie, Joerg Henning

Abstract:

Commercial chicken production is an import livestock industry in Bangladesh. Antimicrobials are commonly used to control and prevent infectious diseases. It was hypothesized that inadequate biosecurity practices might promote antimicrobial usage on commercial chicken farms. A cross-sectional study was carried out to evaluate antimicrobial usage and farm biosecurity practices implemented on 57 layer and 83 broiler farms in eight sub-districts of the Chattogram district in Bangladesh. A questionnaire was used to collect data on antimicrobial usage and biosecurity practices on these farms. A causal framework was used to guide the development of a multi-level mixed-effects logistic regression analysis to evaluate the total and direct effects of practiced biosecurity management on prophylactic and therapeutic administration of antimicrobials. A total of 24 antimicrobials were administered in the current production cycle at the time of the survey. The most administered antimicrobials on layer farms were ciprofloxacin (37.0% of farms), amoxicillin (33.3%), and tiamulin (31.5%); however, on broiler farms, colistin (56.6% of farms), doxycycline (50.6%), and neomycin (38.6%) were most used. Only 15.3% of commercial farmers used antimicrobials entirely for therapeutic purposes, whereas 84.7% administered antimicrobials prophylactically. Inadequate biosecurity practices were more common among commercial broiler farmers compared to layer farmers. For example, only 2.4% of broiler farmers used footbaths before entering sheds compared to 22.2% of the layer farmers (p < 0.001). Farms that used antimicrobials only for therapeutic purposes (vs prophylactic) implemented more frequently adequate disease control measures, such as separating sick birds from healthy birds. This research highlighted that the prophylactic application of antimicrobials is often conducted to substitute poor biosecurity practices on commercial chicken farms. Awareness programs for farmers are crucial to inform them about the risk associated with antimicrobial usage and to highlight the economic benefits of implementing cost-effective biosecurity measures to control infectious poultry diseases.

Keywords: antimicrobial, biosecurity, broiler, layer

Procedia PDF Downloads 143