Search results for: statistical estimation problem

Authors: Chaghoub Soraya, Zhang Xiaoyan

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This research presents the first constant approximation algorithm to the p-median network design problem with multiple cable types. This problem was addressed with a single cable type and there is a bifactor approximation algorithm for the problem. To the best of our knowledge, the algorithm proposed in this paper is the first constant approximation algorithm for the p-median network design with multiple cable types. The addressed problem is a combination of two well studied problems which are p-median problem and network design problem. The introduced algorithm is a random sampling approximation algorithm of constant factor which is conceived by using some random sampling techniques form the literature. It is based on a redistribution Lemma from the literature and a steiner tree problem as a subproblem. This algorithm is simple, and it relies on the notions of random sampling and probability. The proposed approach gives an approximation solution with one constant ratio without violating any of the constraints, in contrast to the one proposed in the literature. This paper provides a (21 + 2)-approximation algorithm for the p-median network design problem with multiple cable types using random sampling techniques.

Keywords: approximation algorithms, buy-at-bulk, combinatorial optimization, network design, p-median

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Authors: Gen Sakoda, Hideki Takayasu, Misako Takayasu

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Waste reduction is a fundamental problem for sustainability. Methods for waste reduction with point-of-sales (POS) data are proposed, utilizing the knowledge of a recent econophysics study on a statistical property of POS data. Concretely, the non-stationary time series analysis method based on the Particle Filter is developed, which considers abnormal fluctuation scaling known as Taylor's law. This method is extended for handling incomplete sales data because of stock-outs by introducing maximum likelihood estimation for censored data. The way for optimal stock determination with pricing the cost of waste reduction is also proposed. This study focuses on the examination of the methods for large sales numbers where Taylor's law is obvious. Numerical analysis using aggregated POS data shows the effectiveness of the methods to reduce food waste maintaining a high profit for large sales numbers. Moreover, the way of pricing the cost of waste reduction reveals that a small profit loss realizes substantial waste reduction, especially in the case that the proportionality constant  of Taylor’s law is small. Specifically, around 1% profit loss realizes half disposal at =0.12, which is the actual  value of processed food items used in this research. The methods provide practical and effective solutions for waste reduction keeping a high profit, especially with large sales numbers.

Keywords: food waste reduction, particle filter, point-of-sales, sustainable development goals, Taylor's law, time series analysis

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Authors: Xingxing Peng

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With the development of society, there are more and more online communication scenarios such as teleconference and online education. In the process of conference communication, the quality of voice communication is a very important part, and noise may cause the communication effect of participants to be greatly reduced. Therefore, voice noise reduction has an important impact on scenarios such as voice calls. This research focuses on the key technologies of the sound transmission process. The purpose is to maintain the audio quality to the maximum so that the listener can hear clearer and smoother sound. Firstly, to solve the problem that the traditional speech enhancement algorithm is not ideal when dealing with non-stationary noise, an adaptive speech noise reduction algorithm is studied in this paper. Traditional noise estimation methods are mainly used to deal with stationary noise. In this chapter, we study the spectral characteristics of different noise types, especially the characteristics of non-stationary Burst noise, and design a noise estimator module to deal with non-stationary noise. Noise features are extracted from non-speech segments, and the noise estimation module is adjusted in real time according to different noise characteristics. This adaptive algorithm can enhance speech according to different noise characteristics, improve the performance of traditional algorithms to deal with non-stationary noise, so as to achieve better enhancement effect. The experimental results show that the algorithm proposed in this chapter is effective and can better adapt to different types of noise, so as to obtain better speech enhancement effect.

Keywords: speech noise reduction, speech enhancement, self-adaptation, Wiener filter algorithm

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Authors: Zahid Ullah, Atlas Khan

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The rapid growth of data in diverse domains has created an urgent need for effective utilization of mathematical and statistical sciences in data analytics. This abstract explores the journey from theory to practice, emphasizing the importance of harnessing mathematical and statistical innovations to unlock the full potential of data analytics. Drawing on a comprehensive review of existing literature and research, this study investigates the fundamental theories and principles underpinning mathematical and statistical sciences in the context of data analytics. It delves into key mathematical concepts such as optimization, probability theory, statistical modeling, and machine learning algorithms, highlighting their significance in analyzing and extracting insights from complex datasets. Moreover, this abstract sheds light on the practical applications of mathematical and statistical sciences in real-world data analytics scenarios. Through case studies and examples, it showcases how mathematical and statistical innovations are being applied to tackle challenges in various fields such as finance, healthcare, marketing, and social sciences. These applications demonstrate the transformative power of mathematical and statistical sciences in data-driven decision-making. The abstract also emphasizes the importance of interdisciplinary collaboration, as it recognizes the synergy between mathematical and statistical sciences and other domains such as computer science, information technology, and domain-specific knowledge. Collaborative efforts enable the development of innovative methodologies and tools that bridge the gap between theory and practice, ultimately enhancing the effectiveness of data analytics. Furthermore, ethical considerations surrounding data analytics, including privacy, bias, and fairness, are addressed within the abstract. It underscores the need for responsible and transparent practices in data analytics, and highlights the role of mathematical and statistical sciences in ensuring ethical data handling and analysis. In conclusion, this abstract highlights the journey from theory to practice in harnessing mathematical and statistical sciences in data analytics. It showcases the practical applications of these sciences, the importance of interdisciplinary collaboration, and the need for ethical considerations. By bridging the gap between theory and practice, mathematical and statistical sciences contribute to unlocking the full potential of data analytics, empowering organizations and decision-makers with valuable insights for informed decision-making.

Keywords: data analytics, mathematical sciences, optimization, machine learning, interdisciplinary collaboration, practical applications

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Authors: Ahmed Hammed, Wady Naanaa

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In this paper, we propose a general approach to deal with the problem of a convolutive mixture of images. We use a direct blind source separation method by adding only one non-statistical justified constraint describing the relationships between different mixing matrix at the aim to make its resolution easy. This method can be applied, provided that this constraint is known, to degraded document affected by the overlapping of text-patterns and images. This is due to chemical and physical reactions of the materials (paper, inks,...) occurring during the documents aging, and other unpredictable causes such as humidity, microorganism infestation, human handling, etc. We will demonstrate that this problem corresponds to a convolutive mixture of images. Subsequently, we will show how the validation of our method through numerical examples. We can so obtain clear images from unreadable ones which can be caused by pages superposition, a phenomenon similar to that we find every often in archival documents.

Keywords: blind source separation, convoluted mixture, degraded documents, text-patterns overlapping

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Authors: P. Priyanka, S. Shruthi, N. Guruprasad

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Health is a common theme in most cultures. In fact all communities have their concepts of health, as part of their culture. Health continues to be a neglected entity. Planning of Human diet should be done very careful by selecting the food items or groups of food items also the composition involved. Low price and good taste of foods are regarded as two major factors for optimal human nutrition. Linear programming techniques have been extensively used for human diet formulation for quiet good number of years. Through the process, we mainly apply “The Simplex Method” which is a very useful statistical tool based on the theorem of Elementary Row Operation from Linear Algebra and also incorporate some other necessary rules set by the Simplex Method to help solve the problem. The study done by us is an attempt to develop a programming model for optimal planning and best use of nutrient ingredients.

Keywords: diet formulation, linear programming, nutrient ingredients, optimization, simplex method

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Authors: Malika Fekih, Abdenour Bourabaa, Rafika Hariti, Mohamed Saighi

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In Algeria the global solar radiation and its components is not available for all locations due to which there is a requirement of using different models for the estimation of global solar radiation that use climatological parameters of the locations. Empirical constants for these models have been estimated and the results obtained have been tested statistically. The results show encouraging agreement between estimated and measured values.

Keywords: global solar radiation, empirical model, semi arid areas, climatological parameters

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Authors: Desta Brhanu Gebrehiwot

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The study aims to investigate the impact of land tenure arrangements on fertilizer use per hectare in Northern Ethiopia. Household and Plot level data are used for analysis. Land tenure contracts such as sharecropping and fixed rent arrangements have endogeneity. Different unobservable characteristics may affect renting-out decisions. Thus, the appropriate method of analysis was the instrumental variable estimation technic. Therefore, the family of instrumental variable estimation methods two-stage least-squares regression (2SLS, the generalized method of moments (GMM), Limited information maximum likelihood (LIML), and instrumental variable Tobit (IV-Tobit) was used. Besides, a method to handle a binary endogenous variable is applied, which uses a two-step estimation. In the first step probit model includes instruments, and in the second step, maximum likelihood estimation (MLE) (“etregress” command in Stata 14) was used. There was lower fertilizer use per hectare on sharecropped and fixed rented plots relative to owner-operated. The result supports the Marshallian inefficiency principle in sharecropping. The difference in fertilizer use per hectare could be explained by a lack of incentivized detailed contract forms, such as giving more proportion of the output to the tenant under sharecropping contracts, which motivates to use of more fertilizer in rented plots to maximize the production because most sharecropping arrangements share output equally between tenants and landlords.

Keywords: tenure-contracts, endogeneity, plot-level data, Ethiopia, fertilizer

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Authors: F. Esfandyari Darabad, Z. Samadi

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The volume of runoff caused by rainfall in the river basin has enticed the researchers in the fields of the water management resources. In this study, first of the hydrological data such as the rainfall and discharge of the Khiyav river basin of Meshkin city in the northwest of Iran collected and then the process of analyzing and reconstructing has been completed. The soil conservation service (scs) has developed a method for calculating the runoff, in which is based on the curve number specification (CN). This research implemented the following model in the Khiyav river basin of Meshkin city by the GIS techniques and concluded the following fact in which represents the usage of weight model in calculating the curve numbers that provides the possibility for the all efficient factors which is contributing to the runoff creation such as; the geometric characteristics of the basin, the basin soil characteristics, vegetation, geology, climate and human factors to be considered, so an accurate estimation of runoff from precipitation to be achieved as the result. The findings also exposed the accident-prone areas in the output of the Khiyav river basin so it was revealed that the Khiyav river basin embodies a high potential for the flood creation.

Keywords: curve number, khiyav river basin, runoff estimation, SCS

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Authors: Redvan Ghasemlounia, Elham Ansari, Hikmet Kerem Cigizoglu

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Hydrological modeling in arid and semi-arid regions is very important. Iran has many regions with these climate conditions such as Chaharmahal and Bakhtiari province that needs lots of attention with an appropriate management. Forecasting of hydrological parameters and estimation of hydrological events of catchments, provide important information that used for design, management and operation of water resources such as river systems, and dams, widely. Discharge in rivers is one of these parameters. This study presents the application and comparison of some estimation methods such as Feed-Forward Back Propagation Neural Network (FFBPNN), Multi Linear Regression (MLR), Gene Expression Programming (GEP) and Bayesian Network (BN) to predict the daily flow discharge of the Soolegan River, located at Chaharmahal and Bakhtiari province, in Iran. In this study, Soolegan, station was considered. This Station is located in Soolegan River at 51° 14՜ Latitude 31° 38՜ longitude at North Karoon basin. The Soolegan station is 2086 meters higher than sea level. The data used in this study are daily discharge and daily precipitation of Soolegan station. Feed Forward Back Propagation Neural Network(FFBPNN), Multi Linear Regression (MLR), Gene Expression Programming (GEP) and Bayesian Network (BN) models were developed using the same input parameters for Soolegan's daily discharge estimation. The results of estimation models were compared with observed discharge values to evaluate performance of the developed models. Results of all methods were compared and shown in tables and charts.

Keywords: ANN, multi linear regression, Bayesian network, forecasting, discharge, gene expression programming

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Authors: Abubakar Sa’adatu Mohammed

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This paper reports on a study of problem solving differences between expert and novice Problem solvers for effective physics teaching. Significant differences were found both at the conceptual level and at the level of critical thinking, creative thinking and reasoning. It is suggested for a successful solution of a problem, conceptual knowledge alone may not be sufficient. There is the need of the knowledge of how the conceptual knowledge should be applied (problem solving skills). It is hoped that this research might contribute to efforts of exploring ways for students to acquire a powerful conceptual toolkit based on experts like problem solvers approach for effective teaching delivery.

Keywords: conceptual knowledge, procedural knowledge, critical thinking, creative thinking, reasoning ability

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Authors: Daria Beziakina, Elena Bulgakova

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The paper deals with cross-gender and cross-linguistic comparison of pitch characteristics for Tuvinian with two other Turkic languages - Uzbek and Azerbaijani, based on the results of statistical analysis of pitch parameter values and intonation patterns used by male and female speakers. The main goal of our work is to obtain the ranges of pitch parameter values typical for Tuvinian speakers for the purpose of automatic language identification. We also propose a cross-gender analysis of declarative intonation in the poorly studied Tuvinian language. The ranges of pitch parameter values were obtained by means of specially developed software that deals with the distribution of pitch values and allows us to obtain statistical language-specific pitch intervals.

Keywords: speech analysis, statistical analysis, speaker recognition, identification of person

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Authors: Arcady Ponosov

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A novel mathematical approach is suggested, which facilitates a compressed representation and efficient validation of parameter-rich ordinary differential equation models describing the dynamics of complex, especially biology-related, systems and which is based on identification of the system's latent variables. In particular, an efficient parameter estimation method for the compressed non-linear dynamical systems is developed. The method is applied to the so-called 'power-law systems' being non-linear differential equations typically used in Biochemical System Theory.

Keywords: generalized law of mass action, metamodels, principal components, synergetic systems

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Authors: Jasper Kevin C. Dionisio, Denise Mae M. Unsay

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In a manufacturing firm, controlling the process ensures that optimum efficiency, productivity, and quality in an organization are achieved. An operation with no standardized procedure yields a poor productivity, inefficiency, and an out of control process. This study focuses on controlling the small intestine processing of a chicken dressing plant through the use of Statistical Process Control (SPC). Since the operation does not employ a standard procedure and does not have an established standard time, the process through the assessment of the observed time of the overall operation of small intestine processing, through the use of X-Bar R Control Chart, is found to be out of control. In the solution of this problem, the researchers conduct a motion and time study aiming to establish a standard procedure for the operation. The normal operator was picked through the use of Westinghouse Rating System. Instead of utilizing the traditional motion and time study, the researchers used the X-Bar R Control Chart in determining the process average of the process that is used for establishing the standard time. The observed time of the normal operator was noted and plotted to the X-Bar R Control Chart. Out of control points that are due to assignable cause were removed and the process average, or the average time the normal operator conducted the process, which was already in control and free form any outliers, was obtained. The process average was then used in determining the standard time of small intestine processing. As a recommendation, the researchers suggest the implementation of the standard time established which is with consonance to the standard procedure which was adopted from the normal operator. With that recommendation, the whole operation will induce a 45.54 % increase in their productivity.

Keywords: motion and time study, process controlling, statistical process control, X-Bar R Control chart

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Authors: Balaji Sankar, Sadanand Kulkarni

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Compliant foil gas lubricated bearings are used for the support of light loads in the order of few kilograms at high speeds, in the order of 50,000 RPM. The stiffness of the foil bearings depends both on the stiffness of the compliant foil and on the lubricating gas film. The stiffness of the bearings plays a crucial role in the stable operation of the supported rotor over a range of speeds. This paper describes a numerical approach to estimate the stiffness of the bearings using pseudo spectral scheme. Methodology to obtain the stiffness of the foil bearing as a function of weight of the shaft is given and the results are presented.

Keywords: foil bearing, simulation, numerical, stiffness estimation

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Authors: Marcos Valdez Alexander Junior, Igor Aguilar-Alonso

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Malnutrition is the root of different diseases that universally affect everyone, diseases such as obesity and malnutrition. The objective of this research is to predict the calories of the food to be eaten, developing a smart mobile application to show the user if a meal is balanced. Due to the large percentage of obesity and malnutrition in Peru, the present work is carried out. The development of the intelligent application is proposed with a three-layer architecture, and for the prediction of the nutritional value of the food, the use of pre-trained models based on convolutional neural networks is proposed.

Keywords: volume estimation, calorie estimation, artificial vision, food nutrition

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Authors: Mahnaz Hosseinzadeh, Mohammad Reza Mehregan

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In this paper, we have developed a morphological field to assist multi- methodology (combining methodologies together in whole or part) in Operations Research (OR) for the problem contexts in Iranian organizations. So, we have attempted to identify some dimensions for problem context according to Iranian organizational problems. Then, a general morphological program is designed which helps the OR practitioner to determine the suitable OR methodology as output for any configuration of conditions in a problem context as input and to reveal the fields necessary to be improved in OR. Applying such a program would have interesting results for OR practitioners.

Keywords: hard, soft and emancipatory operations research, General Morphological Analysis (GMA), multi-methodology, problem context

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Authors: Hassan Manouzi, Taous-Meriem Laleg-Kirati

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In this paper we study mathematically the eigenvalue problem for stochastic elliptic partial differential equation of Wick type. Using the Wick-product and the Wiener-Ito chaos expansion, the stochastic eigenvalue problem is reformulated as a system of an eigenvalue problem for a deterministic partial differential equation and elliptic partial differential equations by using the Fredholm alternative. To reduce the computational complexity of this system, we shall use a decomposition-coordination method. Once this approximation is performed, the statistics of the numerical solution can be easily evaluated.

Keywords: eigenvalue problem, Wick product, SPDEs, finite element, Wiener-Ito chaos expansion

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Authors: Chulsang Yoo, Gildo Kim

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Dual polarization radar provides comprehensive information about rainfall by measuring multiple parameters. In Korea, for the rainfall estimation, JPOLE and CSU-HIDRO algorithms are generally used. This study evaluated the local applicability of JPOLE and CSU-HIDRO algorithms in Korea by using the observed rainfall data collected on August, 2014 by the Biseulsan dual polarization radar data and KMA AWS. A total of 11,372 pairs of radar-ground rain rate data were classified according to thresholds of synthetic algorithms into suitable and unsuitable data. Then, evaluation criteria were derived by comparing radar rain rate and ground rain rate, respectively, for entire, suitable, unsuitable data. The results are as follows: (1) The radar rain rate equation including KDP, was found better in the rainfall estimation than the other equations for both JPOLE and CSU-HIDRO algorithms. The thresholds were found to be adequately applied for both algorithms including specific differential phase. (2) The radar rain rate equation including horizontal reflectivity and differential reflectivity were found poor compared to the others. The result was not improved even when only the suitable data were applied. Acknowledgments: This work was supported by the Basic Science Research Program through the National Research Foundation of Korea, funded by the Ministry of Education (NRF-2013R1A1A2011012).

Keywords: CSU-HIDRO algorithm, dual polarization radar, JPOLE algorithm, radar rainfall estimation algorithm

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Authors: Sarwat Sultan, Shahzad Gul

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This study was carried out to see the mediating role of problem solving styles (sensing, intuitive, feeling, and thinking) in the predictive relationship of gratitude with subjective well-being. A sample of 454 college students aged 20-26 years old participated in this study and provided data on the measures of gratitude, problem solving styles, and subjective well-being. Results indicated the significant relationships of gratitude with subjective well-being and problem solving styles of intuitive and thinking. Results further indicated the positive link of intuitive and thinking styles with subjective well-being. Findings also provided the evidence for the significant mediating role of problem solving styles in the relationship of gratitude with subjective well-being. The implication for this study is likely to enhance the medium to long term effects of gratitude on subjective well-being among students and as well as assessing its value in promoting psychological health and problem solving strategies among students.

Keywords: gratitude, subjective well-being, problem solving styles, college students

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Authors: Khanh To Duc, Monica Chiogna, Gianfranco Adimari

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With three diagnostic categories, assessment of the performance of diagnostic tests is achieved by the analysis of the receiver operating characteristic (ROC) surface, which generalizes the ROC curve for binary diagnostic outcomes. The volume under the ROC surface (VUS) is a summary index usually employed for measuring the overall diagnostic accuracy. When the true disease status can be exactly assessed by means of a gold standard (GS) test, unbiased nonparametric estimators of the ROC surface and VUS are easily obtained. In practice, unfortunately, disease status verification via the GS test could be unavailable for all study subjects, due to the expensiveness or invasiveness of the GS test. Thus, often only a subset of patients undergoes disease verification. Statistical evaluations of diagnostic accuracy based only on data from subjects with verified disease status are typically biased. This bias is known as verification bias. Here, we consider the problem of correcting for verification bias when continuous diagnostic tests for three-class disease status are considered. We assume that selection for disease verification does not depend on disease status, given test results and other observed covariates, i.e., we assume that the true disease status, when missing, is missing at random. Under this assumption, we discuss several solutions for ROC surface analysis based on imputation and re-weighting methods. In particular, verification bias-corrected estimators of the ROC surface and of VUS are proposed, namely, full imputation, mean score imputation, inverse probability weighting and semiparametric efficient estimators. Consistency and asymptotic normality of the proposed estimators are established, and their finite sample behavior is investigated by means of Monte Carlo simulation studies. Two illustrations using real datasets are also given.

Keywords: imputation, missing at random, inverse probability weighting, ROC surface analysis

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Authors: Iffat Ara Ebu, Fahmida Islam, Mohammad Abdus Shahid Rafi, Mahfuzur Rahman, Umar Iqbal, John Ball

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The application of multi-sensor fusion for enhanced distance estimation accuracy in dynamic environments is crucial for advanced driver assistance systems (ADAS) and autonomous vehicles. Limitations of single sensors such as cameras or radar in adverse conditions motivate the use of combined camera and radar data to improve reliability, adaptability, and object recognition. A multi-sensor fusion approach using an extended Kalman filter (EKF) is proposed to combine sensor measurements with a dynamic system model, achieving robust and accurate distance estimation. The research utilizes the Mississippi State University Autonomous Vehicular Simulator (MAVS) to create a controlled environment for data collection. Data analysis is performed using MATLAB. Qualitative (visualization of fused data vs ground truth) and quantitative metrics (RMSE, MAE) are employed for performance assessment. Initial results with simulated data demonstrate accurate distance estimation compared to individual sensors. The optimal sensor measurement noise variance and plant noise variance parameters within the EKF are identified, and the algorithm is validated with real-world data from a Chevrolet Blazer. In summary, this research demonstrates that multi-sensor fusion with an EKF significantly improves distance estimation accuracy in dynamic environments. This is supported by comprehensive evaluation metrics, with validation transitioning from simulated to real-world data, paving the way for safer and more reliable autonomous vehicle control.

Keywords: sensor fusion, EKF, MATLAB, MAVS, autonomous vehicle, ADAS

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Authors: R. Niranchana, K. Meena Alias Jeyanthi

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As a result of the present climate change dilemma, the energy balancing strategy is to construct a sustainable environment has become a top concern for researchers worldwide. The environment itself has always been a solution from the earliest days of human evolution. Carbon capture begins with its accurate estimation and monitoring credit inventories, and its efficient use. Sustainable urban planning with deliverables of re-use energy models might benefit from assessment methods like biomass carbon credit ranking. The term "biomass energy" refers to the various ways in which living organisms can potentially be converted into a source of energy. The approaches that can be applied to biomass and an algorithm for evaluating carbon credits are presented in this paper. The micro-climate evaluation using Computational Fluid dynamics was carried out across the location (1 km x1 km) at Dindigul, India (10°24'58.68" North, 77°54.1.80 East). Sustainable Urban design must be carried out considering environmental and physiological convection, conduction, radiation and evaporative heat exchange due to proceeding solar access and wind intensities.

Keywords: biomass, climate assessment, urban planning, multi-regression, carbon estimation algorithm

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Authors: R. Ouafi, F. Ouafi

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We study the problem of cutting a rectangular material entity into smaller sub-entities of trapezoidal forms with minimum waste of the material. This problem will be denoted TCP (Trapezoidal Cutting Problem). The TCP has many applications in manufacturing processes of various industries: pipe line design (petro chemistry), the design of airfoil (aeronautical) or cuts of the components of textile products. We introduce an orthogonal build to provide the optimal horizontal and vertical homogeneous strips. In this paper we develop a general heuristic search based upon orthogonal build. By solving two one-dimensional knapsack problems, we combine the horizontal and vertical homogeneous strips to give a non orthogonal cutting pattern.

Keywords: combinatorial optimization, cutting problem, heuristic

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Authors: Ismail El Gayar, Ossama Ismail, Yousri El Gamal

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This paper presented a technique to solve one of the transportation problems that faces us in real life which is the Bus Scheduling Problem. Most of the countries using buses in schools, companies and traveling offices as an example to transfer multiple passengers from many places to specific place and vice versa. This transferring process can cost time and money, so we build a decision support system that can solve this problem. In this paper, a genetic algorithm with the shortest path technique is used to generate a competitive solution to other well-known techniques. It also presents a comparison between our solution and other solutions for this problem.

Keywords: bus scheduling problem, decision support system, genetic algorithm, shortest path

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Authors: Mahdy ‎Esmailian, Mahdi ‎Doostparast, Ahmad ‎Parsian

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‎In this article‎, ‎sequential order statistics (SOS) censoring type II samples coming from the generalized Pareto distribution are considered‎. ‎Maximum likelihood (ML) estimators of the unknown parameters are derived on the basis of the available multiple SOS data‎. ‎Necessary conditions for existence and uniqueness of the derived ML estimates are given‎. Due to complexity in the proposed likelihood function‎, ‎a useful re-parametrization is suggested‎. ‎For illustrative purposes‎, ‎a Monte Carlo simulation study is conducted and an illustrative example is analysed‎.

Keywords: bayesian estimation‎, generalized pareto distribution‎, ‎maximum likelihood estimation‎, sequential order statistics

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Authors: Dongjoo Kim, Chang-Sik Son, Won-Seok Kang

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Adequate sleep affects various parts of one’s overall physical and mental life. As one of the methods in determining the appropriate amount of sleep, this research presents a heart rate based sleep quality index. In order to evaluate sleep quality using the heart rate, sleep data from 280 subjects taken over one month are used. Their sleep data are categorized by a three-part heart rate range. After categorizing, some features are extracted, and the statistical significances are verified for these features. The results show that some features of this sleep quality index model have statistical significance. Thus, this heart rate based sleep quality index may be a useful discriminator of sleep.

Keywords: sleep, sleep quality, heart rate, statistical analysis

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Authors: H. Nouri, I. E. Achouri, A. Grimes, H. Ait Said, M. Aissou, Y. Zebboudj

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This paper aims to analysis the behaviour of DC corona discharge in wire-to-plate electrostatic precipitators (ESP). Current-voltage curves are particularly analysed. Experimental results show that discharge current is strongly affected by the applied voltage. The proposed method of current identification is to use the method of least squares. Least squares problems that of into two categories: linear or ordinary least squares and non-linear least squares, depending on whether or not the residuals are linear in all unknowns. The linear least-squares problem occurs in statistical regression analysis; it has a closed-form solution. A closed-form solution (or closed form expression) is any formula that can be evaluated in a finite number of standard operations. The non-linear problem has no closed-form solution and is usually solved by iterative.

Keywords: electrostatic precipitator, current-voltage characteristics, least squares method, electric field, magnetic field

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Authors: Inyeol Paik, Ah-Ryang Kim

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In this research, a statistical analysis is carried out to examine the statistical properties of the formula given in the design code for concrete structures. The design formulas of the Korea highway bridge design code - the limit state design method (KHBDC) which is the current national bridge design code and the design code for concrete structures by Korea Concrete Institute (KCI) are applied for the analysis. The safety levels provided by the strength formulas of the design codes are defined based on the probabilistic and statistical theory.KHBDC is a reliability-based design code. The load and resistance factors of this code were calibrated to attain the target reliability index. It is essential to define the statistical properties for the design formulas in this calibration process. In general, the statistical characteristics of a member strength are due to the following three factors. The first is due to the difference between the material strength of the actual construction and that used in the design calculation. The second is the difference between the actual dimensions of the constructed sections and those used in design calculation. The third is the difference between the strength of the actual member and the formula simplified for the design calculation. In this paper, the statistical study is focused on the third difference. The formulas for calculating the shear strength of concrete members are presented in different ways in KHBDC and KCI. In this study, the statistical properties of design formulas were obtained through comparison with the database which comprises the experimental results from the reference publications. The test specimen was either reinforced with the shear stirrup or not. For an applied database, the bias factor was about 1.12 and the coefficient of variation was about 0.18. By applying the statistical properties of the design formula to the reliability analysis, it is shown that the resistance factors of the current design codes satisfy the target reliability indexes of both codes. Also, the minimum resistance factors of the KHBDC which is written in the material resistance factor format and KCE which is in the member resistance format are obtained and the results are presented. A further research is underway to calibrate the resistance factors of the high strength and high-performance concrete design guide.

Keywords: concrete design code, reliability analysis, resistance factor, shear strength, statistical property

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Authors: Balimu Mwiya, Mundia Muya, Chabota Kaliba, Peter Mukalula

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Factors affecting construction unit cost vary depending on a country’s political, economic, social and technological inclinations. Factors affecting construction costs have been studied from various perspectives. Analysis of cost factors requires an appreciation of a country’s practices. Identified cost factors provide an indication of a country’s construction economic strata. The purpose of this paper is to identify the essential factors that affect unit cost estimation and their breakdown using artificial neural networks. Twenty-five (25) identified cost factors in road construction were subjected to a questionnaire survey and employing SPSS factor analysis the factors were reduced to eight. The 8 factors were analysed using the neural network (NN) to determine the proportionate breakdown of the cost factors in a given construction unit rate. NN predicted that political environment accounted 44% of the unit rate followed by contractor capacity at 22% and financial delays, project feasibility, overhead and profit each at 11%. Project location, material availability and corruption perception index had minimal impact on the unit cost from the training data provided. Quantified cost factors can be incorporated in unit cost estimation models (UCEM) to produce more accurate estimates. This can create improvements in the cost estimation of infrastructure projects and establish a benchmark standard to assist the process of alignment of work practises and training of new staff, permitting the on-going development of best practises in cost estimation to become more effective.

Keywords: construction cost factors, neural networks, roadworks, Zambian construction industry

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