bluuebunny/crossref_metadata_2025_split huggingface dataset:
System Identification Of Nonlinear Autoregressive Models In Monitoring Dengue Infection
Authors: Rahim H. Abdul , Ibrahim F. , Taib M. N. 
Published: November 2017

Abstract
This paper proposes system identification on application of nonlinear AR (NAR) based on Artificial Neural Network (ANN) for monitor of dengue infections. In building the model, three selection criteria, i.e. the final prediction error (FPE), Akaike’s Information Criteria (AIC), and Lipschitz number were used. Each of the models is divided into two approaches, which are unregularized approach and regularized approach. The findings indicate that NARMAX model with regularized approach yields better accuracy by 80.60%. The best parameters’ settings for this thesis can be found using the Lipschitz number criterion for the model order selection with artificial neural network structure of 4 trained using the Levenberg Marquardt algorithm.
The Use Of Optical Sensors To Estimate Pasture Quality
Authors: Pullanagari R.R. , Yule I. , King W. , Dalley D. , Dynes R. 
Published: November 2017

Abstract
Optical remote sensing tools are being used in a number of agricultural applications by recording an object’s transmission of electromagnetic energy from reflecting and radiating surfaces. This unique spectral information is used to characterize the features of green vegetation. With the development of proximal sensing tools, vegetation or crop health can be determined and monitored in real-time. This information provides an opportunity for precise management of input resources to optimise plant growth and reduce the potential for an adverse environmental effect.
Pasture management is of major importance in New Zealand. This paper describes the operation of multispectral (Crop Circle™ and CROPSCAN™) and hyper spectral sensors (ASD Field Spec® Pro) to explore the pasture quality and quantity. The ability to manage these factors is an important component in grazing, livestock management, and a key driver of animal performance and productivity. The results indicate that these sensors have the potential to assess vegetation characteristics.
Humidity sensor based on silver nanoparticles embedded in a polymeric coating
Authors: Rivero Pedro J. , Urrutia Aitor , Goicoechea Javier , Arregui Francisco J. , Matías Ignacio R. 
Published: November 2017

Abstract
In this work, it is presented a novel optical fiber humidity sensor based on silver nanoparticle-loaded polymeric coatings built onto an optical fiber core. The polymeric film was fabricated using the Layer-by-Layer assembly technique. The silver nanoparticles (Ag NPs) were characterized using transmission electron microscopy (TEM and UV-VIS spectroscopy. A Localized Surface Plasmon Resonance (LSPR) attenuation band is observed when the thickness of the coating increases, and showed a very good sensitivity to Relative Humidity (RH) variations, suitable for high performance applications such as human breathing monitoring.
Study on Light Response of Pachira Aquatica’S Leaf Via Surface Plasmon Resonance Technique
Authors: Li Yu-Chu M. , Chang Wei-Chin , Huang Chao-Ming , Tsai Tsung-Yen , Chen Yen-Hong A. 
Published: November 2017

Abstract
Light response of a pachira aquatica’s leaf at room temperature was investigated with a strong p-wave electromagnetic field by utilizing a surface plasmon resonance (SPR) based sensor technique of angular interrogation method for biological and chemical sensing. The essential principle of SPR biosensing is based on measurement of the change regarding leaf’s microstructure against the sensor’s metallic surface owing to the interaction with the strong p-wave electromagnetic field. The test result shows that the pachira aquatica’s leaf responds to each light lamp within 1 minute.
Continuous Time Identification and Decentralized Pid Controller of an Aerothermic Process
Authors: Ramzi M. , Youlal H. , Haloua M. 
Published: November 2017

Abstract
The interactions between input/output in multivariable processes represent a major challenge in the design of decentralized controllers. In this paper, a simple method for the design of decentralized PID controller is proposed. It consists to combine the conventional PID controller with the static decoupler approach. For each single loop, the individual controller is independently designed by applying the internal model control (IMC) tuning rules. To demonstrate the effectiveness of the proposed method, the PID controller with and without decoupling is implemented on an aerothermic process. It is a pilot scale heating and ventilation system equipped with a heater grid and a centrifugal blower, fully connected through the Humusoft MF624 data acquisition system for real time control. The outcome of the experimental results is that the main control objectives, such as set-point tracking and interactions rejection are well achieved. The experimental results have shown that the proposed method provides a significant improvement compared to conventional PID controller.
Non-Minimum Phase Model of Vertical Position Electro-Hydraulic Cylinder for Trajectory Zpetc
Authors: Ishak Norlela , Tajjudin Mazidah , Ismail Hashimah , Patrick Michael , Sam Yahaya Md , Adnan Ramli 
Published: November 2017

Abstract
Hydraulic actuator has been widely used in industrial applications due to its fast response and capability of moving heavy load. The nonlinear properties of hydraulic cylinder had challenged researchers to design a suitable controller for position control, motion control and tracking control. Based on these problems, we had done a real-time digital tracking control studies on electro-hydraulic cylinder using trajectory zero phase error tracking control (ZPETC) without factorization of zeros polynomial algorithm. With the proposed strategy, the controller parameters are determined using comparing coefficients methods. The electro-hydraulic system mathematical model is approximated using system identification technique with non-minimum phase system being considered. The real-time experimental result will be compared with simulation result using a model from a real plant.
Physical and Virtual Intelligent Sensors for Integrated Health Management Systems
Authors: Mahajan Ajay , Oesch Christopher , Padmanaban Haricharan , Utterback Lucas , Chitikeshi Sanjeevi , Figueroa Fernando 
Published: November 2017

Abstract
This paper describes the development of intelligent sensors as part of an integrated systems approach. The integrated systems approach treats the sensor as a complete system with its own sensing hardware (the traditional sensor), A/D converter, processing and storage capabilities, software drivers, self-assessment algorithms and communication protocols. The immediate application is the monitoring of rocket test stands, but the technology should be generally applicable to the Integrated Systems Health Monitoring (ISHM) vision. This paper outlines progress made in the development of intelligent sensors by describing the work done to date on Physical Intelligent Sensors (PIS) and Virtual Intelligent Sensors (VIS). The PIS as discussed here consists of a thermocouple used to read temperature in an analog form which is then converted into digital values. A microprocessor collects the sensor readings and runs numerous embedded event detection routines on the digital data. If any event, i.e. spike, drift, noise, is detected, it is reported, stored and sent to a remote system through an Ethernet connection. Hence the output of the PIS is data coupled with a confidence factor in the reliability of the data. The VIS discussed here is a virtual implantation of the PIS in C++. The VIS is designed to mirror the operations of the PIS; however, the VIS works on a computer at which digital data is provided as the input and is thus portable to any sensor system. This work lays the foundation for the next generation of smart devices that have embedded intelligence for distributed decision making capabilities.
Stochastic Goals in Financial Planning for a Two-Person Household
Authors: Pietrzyk Radosław , Rokita Paweł 
Published: November 2017

AbstractIn household financial planning two types of risk are typically being taken into account. These are life-length risk and risk connected with financing. In addition, also various types of events of insurance character, like health deterioration, are sometimes taken into account. There are, however, no models addressing stochastic nature of household financial goals. The last should not be confused with modelling factors that influence performance of financing the goals, which is a popular research topic. The problem of modelling goals themselves is, in turn, not so well explored. There are two main characteristics that describe a goal: magnitude and time. At least for some goals one or both of these characteristics may show a stochastic nature. This article puts forward a proposition of working goal time and magnitude into a household financial plan and taking their distributions into account when optimizing the plan. A model of two-person household is used. The decision variables of the optimization task are consumption-investment proportion and division of household investments between household members.
Conceptualizing Subjective Well-Being and its Many Dimensions – Implications for Data Collection in Official Statistics and for Policy Relevance
Authors: Mackie Christopher , Smith Conal 
Published: November 2017

Abstract
Subjective well-being encompasses several distinct but interacting aspects of people’s feelings, attitudes, and experiences. This paper assesses the state of the art for measuring these dimensions of people’s lives, which typically involves analyzing self-reports of subjective well-being collected in survey instruments; however, other potentially complementary, technology-driven tools are emerging as well. We first answer the question, “what is subjective well-being?” and unpack its multidimensionality. The role of national statistics offices in measuring subjective well-being and deriving official statistics is considered next. We conclude by discussing how different characteristics of well-being constructs shape their applicability to policy. The overarching conclusion is that–while methodological limitations are present and a number of fundamental research challenges remain–understanding of how to collect and interpret data on subjective well-being has made enormous strides in the last two decades, and policies for a wide range of domains are beginning to be usefully informed.
Sae Teaching Using Simulations
Authors: Burgard Jan Pablo , Münnich Ralf 
Published: November 2017

Abstract
The increasing interest in applying small area estimation methods urges the needs for training in small area estimation. To better understand the behaviour of small area estimators in practice, simulations are a feasible way for evaluating and teaching properties of the estimators of interest. By designing such simulation studies, students gain a deeper understanding of small area estimation methods. Thus, we encourage to use appropriate simulations as an additional interactive tool in teaching small area estimation methods.
Small Area Estimation in the German Census 2011
Authors: Münnich Ralf , Burgard Jan Pablo , Gabler Siegfried , Ganninger Matthias , Kolb Jan-Philipp 
Published: November 2017

Abstract
In 2011, Germany conducted the first census after the reunification. In contrast to a classical census, a register-assisted census was implemented using population register data and an additional sample. This paper provides an overview of how the sampling design recommendations were set up in order to fulfil legal requirements and to guarantee an optimal but still flexible source of information. The aim was to develop a design that fosters an accurate estimation of the main objective of the census, the total population counts. Further, the design should also adequately support the application of small area estimation methods. Some empirical results are given to provide an assessment of selected methods. The research was conducted within the German Census Sampling and Estimation research project, financially supported by the German Federal Statistical Office.
Development of Small Area Estimation in Official Statistics1
Authors: Kordos Jan 
Published: November 2017

Abstract
The author begins with a general assessment of the mission of the National Statistics Institutes (NSIs), main producers of official statistics, which are obliged to deliver high quality statistical information on the state and evolution of the population, the economy, the society and the environment. These statistical results must be based on scientific principles and methods. They must be made available to the public, politics, economy and research for decision-making and information purposes.
Next, before discussing general issues of small area estimation (SAE) in official statistics, the author reminds: the methods of sampling surveys, data collection, estimation procedures, and data quality assessment used for official statistics. Statistical information is published in different breakdowns with stable or even decreasing budget while being legally bound to control the response burden. Special attention is paid, from a practitioner point of view, to synthetic development of small area estimation in official statistics, beginning with international seminars and conferences devoted to SAE procedures and methods (starting with the Canadian symposium, 1985, and the Warsaw conference, 1992, to the Poznan conference, Poland, 2014), and some international projects (EURAREA, SAMPLE, BIAS, AMELI, ESSnet). Next, some aspects of development of SAE in official statistics are discussed. At the end some conclusions regarding quality of SAE procedures are considered.
Some Effective Estimation Procedures Under Non-Response in Two-Phase Successive Sampling
Authors: Singh G. N. , Khetan M. , Maurya S. 
Published: November 2017

Abstract
This work is designed to assess the effect of non-response in estimation of the current population mean in two-phase successive sampling on two occasions. Sub-sampling technique of non-respondents has been used and exponential methods of estimation under two-phase successive sampling arrangement have been proposed. Properties of the proposed estimation procedures have been examined. Empirical studies are carried out to justify the suggested estimation procedures and suitable recommendations have been made to the survey practitioners.
Transmuted Kumaraswamy Distribution
Authors: Khan Muhammad Shuaib , King Robert , Hudson Irene Lena 
Published: November 2017

Abstract
The Kumaraswamy distribution is the most widely applied statistical distribution in hydrological problems and many natural phenomena. We propose a generalization of the Kumaraswamy distribution referred to as the transmuted Kumaraswamy (TKw) distribution. The new transmuted distribution is developed using the quadratic rank transmutation map studied by Shaw et al. (2009). A comprehensive account of the mathematical properties of the new distribution is provided. Explicit expressions are derived for the moments, moment generating function, entropy, mean deviation, Bonferroni and Lorenz curves, and formulated moments for order statistics. The TKw distribution parameters are estimated by using the method of maximum likelihood. Monte Carlo simulation is performed in order to investigate the performance of MLEs. The flood data and HIV/AIDS data applications illustrate the usefulness of the proposed model.
Heteroscedastic Discriminant Analysis Combined with Feature Selection for Credit Scoring
Authors: Stąpor Katarzyna , Smolarczyk Tomasz , Fabian Piotr 
Published: November 2017

Abstract
Credit granting is a fundamental question and one of the most complex tasks that every credit institution is faced with. Typically, credit scoring databases are often large and characterized by redundant and irrelevant features. An effective classification model will objectively help managers instead of intuitive experience. This study proposes an approach for building a credit scoring model based on the combination of heteroscedastic extension (Loog, Duin, 2002) of classical Fisher Linear Discriminant Analysis (Fisher, 1936, Krzyśko, 1990) and a feature selection algorithm that retains sufficient information for classification purpose. We have tested five feature subset selection algorithms: two filters and three wrappers. To evaluate the accuracy of the proposed credit scoring model and to compare it with the existing approaches we have used the German credit data set from the study (Chen, Li, 2010). The results of our study suggest that the proposed hybrid approach is an effective and promising method for building credit scoring models.
Small Area Estimation of Income under Spatial Sar Model
Authors: Kubacki Jan , Jędrzejczak Alina 
Published: November 2017

Abstract
The paper presents the method of hierarchical Bayes (HB) estimation under small area models with spatially correlated random effects and a spatial structure implied by the Simultaneous Autoregressive (SAR) process. The idea was to improve the spatial EBLUP by incorporating the HB approach into the estimation algorithm. The computation procedure applied in the paper uses the concept of sampling from a posterior distribution under generalized linear mixed models implemented in WinBUGS software and adapts the idea of parameter estimation for small areas by means of the HB method in the case of known model hyperparameters. The illustration of the approach mentioned above was based on a real-world example concerning household income data. The precision of the direct estimators was determined using own three-stage procedure which employs Balanced Repeated Replication, bootstrap and Generalized Variance Function. Additional simulations were conducted to show the influence of the spatial autoregression coefficient on the estimation error reduction. The computations performed by ‘sae’ package for R project and a special procedure for WinBUGS reveal that the method provides reliable estimates of small area means. For high spatial correlation between domains, noticeable MSE reduction was observed, which seems more evident for HB-SAR method as compared with the traditional spatial EBLUP. In our opinion, the Gibbs sampler, revealing the simultaneous nature of processes, especially for random effects, can be a good starting point for the simulations based on stochastic SAR processes.
Modelling Road Traffic Crashes Using Spatial Autoregressive Model With Additional Endogenous Variable
Authors: Olubusoye Olusanya Elisa , Korter Grace Oluwatoyin , Salisu Afees Adebare 
Published: November 2017

Abstract
Road traffic crashes have become a global issue of concern because of the number of deaths and injuries. The model of interest is a linear cross sectional Spatial Autoregressive (SAR) model with additional endogenous variables, exogenous variables and SAR disturbances. The focus is on RTC in Oyo state, Nigeria. The number of RTC in each LGA of the state is the dependent variable. A 33×33 weights matrix; travel density; land area and major road length of each LGA were used as exogenous variables and population was the IV. The objective is to determine the hotspots and examine whether the number of RTC cases in a given LGA is affected by the number of RTC cases of neighbouring LGAs and an instrumental variable. The hotspots include Oluyole, Ido, Akinyele, Egbeda, Atiba, Oyo East, and Ogbomosho South LGAs. The study concludes that the number of RTC in a given LGA is affected by the number of RTC in contiguous LGAs. The policy implication is that road safety and security measures must be administered simultaneously to LGAs with high concentration of RTC and their neighbours to achieve significant remedial effect.
Evaluation of the EU Countries’ Innovative Potential – Multivariate Approach
Authors: Roszko-Wójtowicz Elżbieta , Białek Jacek 
Published: November 2017

AbstractThe aim of the article is to work out a synthetic measure for estimating country’s innovation potential (CIP) of EU economies. For the purpose of the research, data from the European Statistical Office (Eurostat) are used and several indicators are organized by four different areas of analysis, i.e. investment expenditure, education, labour market and effects. Applying multi-dimensional statistics allows us to reduce the primary set of diagnostics variables and, simultaneously, identify those which best describe the potential. The final step is linear ordering of EU countries according to their innovative potential on the basis of CIP synthetic measure. The rating is compared with other ratings based on the recognizedSummary Innovation IndexandGlobal Innovation Index.The main conclusion is that the methodology of innovativeness assessment remains an open issue and requires further research. The most important task is the selection of indicators, followed by statistical verification in relation to their importance to innovativeness. The results show that there is a tendency to between the author’s ratings and other already published ratings of innovativeness.
A Three-Parameter Weighted Lindley Distribution and its Applications to Model Survival Time
Authors: Shanker Rama , Shukla Kamlesh Kumar , Mishra Amarendra 
Published: November 2017

AbstractIn this paper a three-parameter weighted Lindley distribution, including Lindley distribution introduced by Lindley (1958), a two-parameter gamma distribution, a two-parameter weighted Lindley distribution introduced by Ghitany et al. (2011) and exponential distribution as special cases, has been suggested for modelling lifetime data from engineering and biomedical sciences. The structural properties of the distribution including moments, coefficient of variation, skewness, kurtosis and index of dispersion have been derived and discussed. The reliability properties, including hazard rate function and mean residual life function, have been discussed. The estimation of its parameters has been discussed using the maximum likelihood method and the applications of the distribution have been explained through some survival time data of a group of patients suffering from head and neck cancer, and the fit has been compared with a one-parameter Lindley distribution and a two-parameter weighted Lindley distribution.
ANÁLISE DA PREVALÊNCIA PARASITOLÓGICA EM AMOSTRAS FECAIS DE CRIANÇAS DE UMA ESCOLA DA REDE PÚBLICA DO ESTADO DE MINAS GERAIS
Authors: Da Silva Patrick Leonardo Nogueira , Cerqueira Fagner Alves , Ferraz Raphael Santos , Vaz Maria Dolores Tiago , Fonseca José Ronivon 
Published: November 2017

<p>Introdução: as infecções parasitárias configuram um grave problema de saúde pública no Brasil, principalmente entre crianças, em decorrência de condições socioeconômicas e higiênico-sanitárias. Objetivo: analisar a prevalência parasitológica em amostras fecais de crianças de uma escola da rede pública do Estado de Minas Gerais. Método: trata-se de um estudo descritivo, exploratório, analítico, prospectivo, com abordagem quantitativa, realizada com 28 crianças com idade entre 6-10 anos de uma escola da rede pública. Foram analisadas amostras de fezes pelo método de Hoffman, Pons e Janer. Resultados: observou-se que 78,5% (n=22) das amostras apresentaram positividade parasitológica em ambos os sexos. Houve prevalência infecciosa de crianças do sexo feminino (n=18; 63,7%) as quais encontram-se com 6 anos de idade (n=14; 50,0%). As espécies de maior prevalência foram: <em>Giardia lamblia</em> (n=9; 31,8%), <em>Entamoeba coli</em> (n=6; 22,7%), <em>Hymenolepis nana</em> (n=6; 22,7%). Conclusão: as condições precárias ocasionadas pela deficiência de administrações públicas fazem com que famílias de renda baixa se aglomerem em regiões com pouco saneamento básico, tornando-se fácil a contaminação por parasitas. </p>