Search results for: predictive distribution

Authors: Waddah S. Abdullah, Khaled F. Al-Omari

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Electrokinetic remediation is one of the most influential and effective methods to decontaminate contaminated soils. Electroosmosis and electromigration are the processes of electrochemical extraction of contaminants from soils. The driving force that causes removing contaminants from soils (electroosmosis process or electromigration process) is voltage gradient. Therefore, the electric field distribution throughout the soil domain is extremely important to investigate and to determine the factors that help to establish a uniform electric field distribution in order to make the clean-up process work properly and efficiently. In this study, small-sized passive electrodes (made of graphite) were placed at predetermined locations within the soil specimen, and the voltage drop between these passive electrodes was measured in order to observe the electrical distribution throughout the tested soil specimens. The electrokinetic test was conducted on two types of soils; a sandy soil and a clayey soil. The electrical distribution throughout the soil domain was conducted with different tests properties; and the electrical field distribution was observed in three-dimensional pattern in order to establish the electrical distribution within the soil domain. The effects of density, applied voltages, and degree of saturation on the electrical distribution within the remediated soil were investigated. The distribution of the moisture content, concentration of the sodium ions, and the concentration of the calcium ions were determined and established in three-dimensional scheme. The study has shown that the electrical conductivity within soil domain depends on the moisture content and concentration of electrolytes present in the pore fluid. The distribution of the electrical field in the saturated soil was found not be affected by its density. The study has also shown that high voltage gradient leads to non-uniform electric field distribution within the electroremediated soil. Very importantly, it was found that even when the electric field distribution is uniform globally (i.e. between the passive electrodes), local non-uniformity could be established within the remediated soil mass. Cracks or air gaps formed due to temperature rise (because of electric flow in low conductivity regions) promotes electrical tortuosity. Thus, fracturing or cracking formed in the remediated soil mass causes disconnection of electric current and hence, no removal of contaminant occur within these areas.

Keywords: contaminant removal, electrical tortuousity, electromigration, electroosmosis, voltage distribution

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Authors: Matteo Calabrese, Martin Cimmino, Dimos Kapetis, Martina Manfrin, Donato Concilio, Giuseppe Toscano, Giovanni Ciandrini, Giancarlo Paccapeli, Gianluca Giarratana, Marco Siciliano, Andrea Forlani, Alberto Carrotta

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In this paper we describe a machine learning methodology for Predictive Maintenance (PdM) applied on woodworking industrial machines. PdM is a prominent strategy consisting of all the operational techniques and actions required to ensure machine availability and to prevent a machine-down failure. One of the challenges with PdM approach is to design and develop of an embedded smart system to enable the health status of the machine. The proposed approach allows screening simultaneously multiple connected machines, thus providing real-time monitoring that can be adopted with maintenance management. This is achieved by applying temporal feature engineering techniques and training an ensemble of classification algorithms to predict Remaining Useful Lifetime of woodworking machines. The effectiveness of the methodology is demonstrated by testing an independent sample of additional woodworking machines without presenting machine down event.

Keywords: predictive maintenance, machine learning, connected machines, artificial intelligence

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Authors: Abdel-Razzaq Mugdadi, Ruqayyah Sani

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The Kernel Distribution Function Estimator (KDFE) method is the most popular method for nonparametric estimation of the cumulative distribution function. The kernel and the bandwidth are the most important components of this estimator. In this investigation, we replace the kernel in the KDFE with a linear combination of kernels to obtain a new estimator based on the linear combination of kernels, the mean integrated squared error (MISE), asymptotic mean integrated squared error (AMISE) and the asymptotically optimal bandwidth for the new estimator are derived. We propose a new data-based method to select the bandwidth for the new estimator. The new technique is based on the Plug-in technique in density estimation. We evaluate the new estimator and the new technique using simulations and real-life data.

Keywords: estimation, bandwidth, mean square error, cumulative distribution function

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Authors: Duncan Oteki, Andebut Yeneneh, Daba Gedafa, Nabil Suleiman

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Most agencies lack the equipment required to measure the dynamic modulus (|E*|) of asphalt mixtures, necessitating the need to use predictive models. This study compared measured |E*| values for nine North Dakota asphalt mixes using the original Witczak, modified Witczak, and Hirsch models. The influence of temperature on the |E*| models was investigated, and Pavement ME simulations were conducted using measured |E*| and predictions from the most accurate |E*| model. The results revealed that the original Witczak model yielded the lowest Se/Sy and highest R² values, indicating the lowest bias and highest accuracy, while the poorest overall performance was exhibited by the Hirsch model. Using predicted |E*| as inputs in the Pavement ME generated conservative distress predictions compared to using measured |E*|. The original Witczak model was recommended for predicting |E*| for low-reliability pavements in North Dakota.

Keywords: asphalt mixture, binder, dynamic modulus, MEPDG, pavement ME, performance, prediction

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Authors: Sakhon Woothipatanapan, Surasit Prakobkit

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This paper presents a model for analysis the induced voltage of transmission lines (energized) acting on neighboring distribution lines (de-energized). From environmental restrictions, 22 kV distribution lines need to be installed under 115 kV transmission lines. With the installation of the two parallel circuits like this, they make the induced voltage which can cause harm to operators. This work was performed with the ATP-EMTP modeling to analyze such phenomenon before field testing. Simulation results are used to find solutions to prevent danger to operators who are on the pole.

Keywords: transmission system, distribution system, induced voltage, off-line operation

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Authors: Thanooja Naushad, Meena Natarajan, Tushar Vasant Kulkarni

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Background: The Lacey Assessment of Preterm Infants (LAPI) is used in clinical practice to identify premature babies at risk of neuromotor impairments, especially cerebral palsy. This study attempted to find the validity of the Lacey assessment of preterm infants to predict neuromotor outcomes of premature babies at 12 months corrected age and to compare its predictive ability with the brain ultrasound. Methods: This prospective cohort study included 89 preterm infants (45 females and 44 males) born below 35 weeks gestation who were admitted to the neonatal intensive care unit of a government hospital in Dubai. Initial assessment was done using the Lacey assessment after the babies reached 33 weeks postmenstrual age. Follow up assessment on neuromotor outcomes was done at 12 months (± 1 week) corrected age using two standardized outcome measures, i.e., infant neurological international battery and Alberta infant motor scale. Brain ultrasound data were collected retrospectively. Data were statistically analyzed, and the diagnostic accuracy of the Lacey assessment of preterm infants (LAPI) was calculated -when used alone and in combination with the brain ultrasound. Results: On comparison with brain ultrasound, the Lacey assessment showed superior specificity (96% vs. 77%), higher positive predictive value (57% vs. 22%), and higher positive likelihood ratio (18 vs. 3) to predict neuromotor outcomes at one year of age. The sensitivity of Lacey assessment was lower than brain ultrasound (66% vs. 83%), whereas specificity was similar (97% vs. 98%). A combination of Lacey assessment and brain ultrasound results showed higher sensitivity (80%), positive (66%), and negative (98%) predictive values, positive likelihood ratio (24), and test accuracy (95%) than Lacey assessment alone in predicting neurological outcomes. The negative predictive value of the Lacey assessment was similar to that of its combination with brain ultrasound (96%). Conclusion: Results of this study suggest that the Lacey assessment of preterm infants can be used as a supplementary assessment tool for premature babies in the neonatal intensive care unit. Due to its high specificity, Lacey assessment can be used to identify those babies at low risk of abnormal neuromotor outcomes at a later age. When used along with the findings of the brain ultrasound, Lacey assessment has better sensitivity to identify preterm babies at particular risk. These findings have applications in identifying premature babies who may benefit from early intervention services.

Keywords: brain ultrasound, lacey assessment of preterm infants, neuromotor outcomes, preterm

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Authors: A. Pietro Rimoldi, B. Anilkumar Gopinath, C. Minimol Korulla

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Coastal engineering structure is conventionally designed for a shorter planning horizon usually 20 years. These structures are subjected to different offshore climatic externalities like waves, tides, tsunamis etc. during the design life period. The probability of occurrence of these different offshore climatic externalities varies. The impact frequently caused by these externalities on the structures is of concern because it has a significant bearing on the capital /operating cost of the project. There can also be repeated short time occurrence of these externalities in the assumed planning horizon which can cause heavy damage to the conventional coastal structure which are mainly made of rock. A replacement of the damaged portion to prevent complete collapse is time consuming and expensive when dealing with hard rock structures. But if coastal structures are made of Geo-synthetic containment systems such replacement is quickly possible in the time period between two successive occurrences. In order to have a better knowledge and to enhance the predictive capacity of these occurrences, this study estimates risk of encounter within the design life period of various externalities based on the concept of exponential distribution. This gives an idea of the frequency of occurrences which in turn gives an indication of whether replacement is necessary and if so at what time interval such replacements have to be effected. To validate this theoretical finding, a pilot project has been taken up in the field so that the impact of the externalities can be studied both for a hard rock and a Geosynthetic tube structure. The paper brings out the salient feature of a case study which pertains to a project in which Geosynthetic tubes have been used for reformation of a seawall adjacent to a conventional rock structure in Alappuzha coast, Kerala, India. The effectiveness of the Geosystem in combatting the impact of the short-term externalities has been brought out.

Keywords: climatic externalities, exponential distribution, geosystems, planning horizon

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Authors: Melissa C. Monney

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Psychological testing has been of interest to researchers for many years as useful tools in assessing and diagnosing various disorders as well as to assist in understanding human behavior. However, for over 20 years now, researchers and laypersons alike have been interested in using them for other purposes, such as determining factors in employee selection, promotion, and even termination. In recent years, psychological assessments have been useful in facilitating workplace decision processing, regarding employee circulation within organizations. This literature review explores four of the most commonly used psychological tests in workplace environments, namely cognitive ability, emotional intelligence, integrity, and personality tests, as organizations have used these tests to assess different factors of human behavior as predictive measures of future employee behaviors. The findings suggest that while there is much controversy and debate regarding the validity and reliability of these tests in workplace settings as they were not originally designed for these purposes, the use of such assessments in the workplace has been useful in decreasing costs and employee turnover as well as increase job satisfaction by ensuring the right employees are selected for their roles.

Keywords: cognitive ability, personality testing, predictive validity, workplace behavior

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Authors: R. Periyasamy, Deepak Joshi, Sneh Anand

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Foot posture assessment is important to evaluate foot type, causing gait and postural defects in all age groups. Although different methods are used for classification of foot arch type in clinical/research examination, there is no clear approach for selecting the most appropriate measurement system. Therefore, the aim of this study was to develop a system for evaluation of foot type as clinical decision-making aids for diagnosis of flat and normal arch based on the Arch Index (AI) and foot pressure distribution parameter - Power Ratio (PR) data. The accuracy of the system was evaluated for 27 subjects with age ranging from 24 to 65 years. Foot area measurements (hind foot, mid foot, and forefoot) were acquired simultaneously from foot pressure intensity image using portable PedoPowerGraph system and analysis of the image in frequency domain to obtain foot pressure distribution parameter - PR data. From our results, we obtain 100% classification accuracy of normal and flat foot by using the linear discriminant analysis method. We observe there is no misclassification of foot types because of incorporating foot pressure distribution data instead of only arch index (AI). We found that the mid-foot pressure distribution ratio data and arch index (AI) value are well correlated to foot arch type based on visual analysis. Therefore, this paper suggests that the proposed system is accurate and easy to determine foot arch type from arch index (AI), as well as incorporating mid-foot pressure distribution ratio data instead of physical area of contact. Hence, such computational tool based system can help the clinicians for assessment of foot structure and cross-check their diagnosis of flat foot from mid-foot pressure distribution.

Keywords: arch index, computational tool, static foot pressure intensity image, foot pressure distribution, linear discriminant analysis

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Authors: Herman Susilo, Rahmat Budiman

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Bali province is one of the most famous tourist destinations in Indonesia. As a central tourist destination, Bali is very concerned about the use of clean energy. Since Bali is an area that does not have natural resources, so all of its energy sources are imported from java island and other islands. As an example, currently, Pertagas is developing the use of LNG for the needs of the retail industry. Right now, LNG is transported from the LNG plant facility in Bontang (Kalimantan Province) using ISO Tanks which are transported by cargo ships and then transported by trucks to the island of Bali. After that, LNG from ISO Tank is breakbulk into LNG Cylinders for distribution to retail customers. The existing distribution scheme is very long and costly since the source of LNG is come from another island (Kalimantan) and is relatively far away. To solve this problem, we plan to build the mini-LNG plant on Java Island since there are lots of gas sources available. There are some small gas reserves (flared or stranded gas) that are not yet monetized and are less valuable (cheaper) because the volume is very small. After liquifying the gas from the gas field, the LNG is transported by the truck using ISO Tank. After that, LNG from ISO Tank is breakbulk into LNG Cylinders for distribution to retail customers. From this new LNG distribution scheme, there are 4-5 USD/MMBTU saving compared to the existing distribution scheme. It is hoped that with these cost savings, the number of retail LNG sales can increase rapidly.

Keywords: LNG, LNG retail, mini LNG, small scale LNG

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Authors: Najib K. Dankadai, Ahmad 'Athif Mohd Faudzi, Khairuddin Osman, Muhammad Rusydi Muhammad Razif, IIi Najaa Aimi Mohd Nordin

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Researches in soft actuators are now growing rapidly because of their adequacy to be applied in sectors like medical, agriculture, biological and welfare. This paper presents system identification (SI) and control of the force generated by a two chambers pneumatic soft actuator (PSA). A force mathematical model for the actuator was identified experimentally using data acquisition card and MATLAB SI toolbox. Two control techniques; a predictive functional control (PFC) and conventional proportional integral and derivative (PID) schemes are proposed and compared based on the identified model for the soft actuator flexible mechanism. Results of this study showed that both of the proposed controllers ensure accurate tracking when the closed loop system was tested with the step, sinusoidal and multi step reference input through MATLAB simulation although the PFC provides a better response than the PID.

Keywords: predictive functional control (PFC), proportional integral and derivative (PID), soft actuator, system identification

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Authors: Ansari Mohammad Reza, Hiroko Ono

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In this study, we investigated how much of the urban facilities are fairly distributing in the city of Kabul based on the factor of population. To find the answer to this question we simulated a fair model for the distribution of investigated facilities in the city which is proposed based on the consideration of two factors; the number of users for each facility and the average distance of reach of each facility. Then the model was evaluated to make sure about its efficiency. And finally, the two—the existing pattern and the simulation model—were compared to find the degree of bias in the existing pattern of distribution of facilities in the city. The result of the study clearly clarified that the facilities are not fairly distributed in Kabul city based on the factor of population. Our analysis also revealed that the education services and the parks are the most and the worst fair distributed facilities in this regard.

Keywords: Afghanistan, ArcGIS Software, Kabul City, fair distribution, urban facilities

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Authors: Jacky Liu

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This paper develops a team sports outcome prediction system with potential for wide-ranging applications across various disciplines. Despite significant advancements in predictive analytics, existing studies in sports outcome predictions possess considerable limitations, including insufficient feature engineering and underutilization of advanced machine learning techniques, among others. To address these issues, we extend the Sports Cross Industry Standard Process for Data Mining (SRP-CRISP-DM) framework and propose a unique, comprehensive predictive system, using National Basketball Association (NBA) data as an example to test this extended framework. Our approach follows a holistic methodology in feature engineering, employing both Time Series and Non-Time Series Data, as well as conducting Explanatory Data Analysis and Feature Selection. Furthermore, we contribute to the discourse on target variable choice in team sports outcome prediction, asserting that point spread prediction yields higher profits as opposed to game-winner predictions. Using machine learning algorithms, particularly XGBoost, results in a significant improvement in predictive accuracy of team sports outcomes. Applied to point spread betting strategies, it offers an astounding annual return of approximately 900% on an initial investment of $100. Our findings not only contribute to academic literature, but have critical practical implications for sports betting. Our study advances the understanding of team sports outcome prediction a burgeoning are in complex system predictions and pave the way for potential profitability and more informed decision making in sports betting markets.

Keywords: machine learning, team sports, game outcome prediction, sports betting, profits simulation

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Authors: Vishwesh Kulkarni, Nikhil Bellarykar

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Cellular complexity stems from the interactions among thousands of different molecular species. Thanks to the emerging fields of systems and synthetic biology, scientists are beginning to unravel these regulatory, signaling, and metabolic interactions and to understand their coordinated action. Reverse engineering of biological networks has has several benefits but a poor quality of data combined with the difficulty in reproducing it limits the applicability of these methods. A few years back, many of the commonly used predictive algorithms were tested on a network constructed in the yeast Saccharomyces cerevisiae (S. cerevisiae) to resolve this issue. The network was a synthetic network of five genes regulating each other for the so-called in vivo reverse-engineering and modeling assessment (IRMA). The network was constructed in S. cereviase since it is a simple and well characterized organism. The synthetic network included a variety of regulatory interactions, thus capturing the behaviour of larger eukaryotic gene networks on a smaller scale. We derive a new set of algorithms by solving a nonlinear optimization problem and show how these algorithms outperform other algorithms on these datasets.

Keywords: synthetic gene network, network identification, optimization, nonlinear modeling

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Authors: Cornelius Femi Popoola

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This study investigated logistics information systems in the distribution of flour in Nigeria. A case study design was used and 50 staff of Honeywell Flour Mill was sampled for the study. Data generated through a questionnaire were analysed using correlation and regression analysis. The findings of the study revealed that logistic information systems such as e-commerce, interactive telephone systems and electronic data interchange positively correlated with the distribution of flour in Honeywell Flour Mill. Finding also deduced that e-commerce, interactive telephone systems and electronic data interchange jointly and positively contribute to the distribution of flour in Honeywell Flour Mill in Nigeria (R = .935; Adj. R2 = .642; F (3,47) = 14.739; p < .05). The study therefore recommended that Honeywell Flour Mill should upgrade their logistic information systems to computer-to-computer communication of business transactions and documents, as well adopt new technology such as, tracking-and-tracing systems (barcode scanning for packages and palettes), tracking vehicles with Global Positioning System (GPS), measuring vehicle performance with ‘black boxes’ (containing logistic data), and Automatic Equipment Identification (AEI) into their systems.

Keywords: e-commerce, electronic data interchange, flour distribution, information system, interactive telephone systems

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Authors: Ahmed Hamza Yache

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The main purpose of this study is to estimate the distribution of shear forces in building structures with asymmetries in the plan submitted to seismic forces can cause, in this case, simultaneous deformations of translation and torsion. To this end, the distribution of shear forces is obtained by seismic forces calculated from the equivalent static method of the Algerian earthquake code RPA 99 (2003 version) and spectral modal analysis for an irregular building plan without kinks. Comparison of the results obtained by these two methods used to highlight the difference in terms of distributions of shear forces in such structures.

Keywords: structure, irregular, code, seismic, method, force, period

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Authors: Jun Su Park, Byung Kwan Oh, Jin Woo Hwang, Yousok Kim, Hyo Seon Park

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For the structural safety, the maximum stress calculated from the stress distribution of a structure is widely used. The stress distribution can be estimated by deformed shape of the structure obtained from measurement. Although the estimation of stress is strongly affected by the location and number of sensing points, most studies have conducted the stress estimation without reasonable basis on sensing plan such as the location and number of sensors. In this paper, an optimal sensing technique for estimating the stress distribution is proposed. This technique proposes the optimal location and number of sensing points for a 2-D frame structure while minimizing the error of stress distribution between analytical model and estimation by cubic smoothing splines using genetic algorithm. To verify the proposed method, the optimal sensor measurement technique is applied to simulation tests on 2-D steel frame structure. The simulation tests are performed under various loading scenarios. Through those tests, the optimal sensing plan for the structure is suggested and verified.

Keywords: genetic algorithm, optimal sensing, optimizing sensor placements, steel frame structure

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Authors: Bachir Chemani, Rachid Halfaoui

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The aim of study was to evaluate pressure distribution characteristics of the elastic textile bandages using two instrumental techniques: a prototype Instrument and a load Transference. The prototype instrument which simulates shape of real leg has pressure sensors which measure bandage pressure. Using this instrument, the results show that elastic textile bandages presents different pressure distribution characteristics and none produces a uniform distribution around lower limb. The load transference test procedure is used to determine whether a relationship exists between elastic textile bandage structure and pressure distribution characteristics. The test procedure assesses degree of load, directly transferred through a textile when loads series are applied to bandaging surface. A range of weave fabrics was produced using needle weaving machine and a sewing technique. A textile bandage was developed with optimal characteristics far superior pressure distribution than other bandages. From results, we find that theoretical pressure is not consistent exactly with practical pressure. It is important in this study to make a practical application for specialized nurses in order to verify the results and draw useful conclusions for predicting the use of this type of elastic band.

Keywords: textile, cotton, pressure, venous ulcers, elastic

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Authors: Kanyarat Bussaban, Siriporn Poolsuwan

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This study is conducted with the objective to prove how the distorted distribution of welfare affects the quality of school-age children lives differently in the case of an urban community in Bangkok. 334 samples are households from Suan Oi and Ratchapatubtim communities. The study of sample communities found the difference between two community areas that are close. The people of Suan Oi community are economically better off people than the people of the Ratchapatubtim community. They share the benefits of using most services except the welfare of a child’s education. The resulting analysis of the variability in quality of life of the school age children indicate that heads of the households are women looking for quality of life benefits when the compulsory school age is less. A study of the two communities suggests that the inequality in income distribution currently affects the quality of life of school-age children.

Keywords: inequality, income distribution, quality of school-age children lives, welfare state

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Authors: Ceshi Sun, Yueyu Zhao, Yaobing Zhao, Zhiqiang Wang, Jian Peng, Pengxin Guo

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With the rapid development of transportation, there are more than 100 cable-stayed bridges with main span larger than 300 m in China. In order to ascertain the statistical relationships among the design parameters of stay cables and their distribution characteristics, 1500 cables were selected from 25 practical long-span cable-stayed bridges. A new relationship between the first order frequency and the length of cable was found by conducting the curve fitting. Then, based on this relationship other interesting relationships were deduced. Several probability density functions (PDFs) were used to investigate the distributions of the parameters of first order frequency, stress level and the Irvine parameter. It was found that these parameters obey the Lognormal distribution, the Weibull distribution and the generalized Pareto distribution, respectively. Scatter diagrams of the three parameters were plotted and their 95% confidence intervals were also investigated.

Keywords: cable, cable-stayed bridge, long-span, statistical analysis

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Authors: H. J. Wattimanela, U. S. Passaribu, N. T. Puspito, S. W. Indratno

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Banda Sea collision zone (BSCZ) of is the result of the interaction and convergence of Indo-Australian plate, Eurasian plate and Pacific plate. This location in the eastern part of Indonesia. This zone has a very high seismic activity. In this research, we will be calculated rate (λ) and Mean Square Eror (MSE). By this result, we will identification of Poisson distribution of earthquakes in the BSCZ with the point process approach. Chi-square test approach and test Anscombe made in the process of identifying a Poisson distribution in the partition area. The data used are earthquakes with Magnitude ≥ 6 SR and its period 1964-2013 and sourced from BMKG Jakarta. This research is expected to contribute to the Moluccas Province and surrounding local governments in performing spatial plan document related to disaster management.

Keywords: molluca banda sea collision zone, earthquakes, mean square error, poisson distribution, chi-square test, anscombe test

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Authors: Haonan Hu, Shuge Lei, Dasheng Sun, Huabin Zhang, Kehong Yuan, Jian Dai, Jijun Tang

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This paper focuses on the classification task of breast ultrasound images and conducts research on the reliability measurement of classification results. A dual-channel evaluation framework was developed based on the proposed inference reliability and predictive reliability scores. For the inference reliability evaluation, human-aligned and doctor-agreed inference rationals based on the improved feature attribution algorithm SP-RISA are gracefully applied. Uncertainty quantification is used to evaluate the predictive reliability via the test time enhancement. The effectiveness of this reliability evaluation framework has been verified on the breast ultrasound clinical dataset YBUS, and its robustness is verified on the public dataset BUSI. The expected calibration errors on both datasets are significantly lower than traditional evaluation methods, which proves the effectiveness of the proposed reliability measurement.

Keywords: medical imaging, ultrasound imaging, XAI, uncertainty measurement, trustworthy AI

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Authors: Nasim Nosoudi, Amir Zadeh, Hunter White, Joshua Conrad, Joon W. Shim

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De novo Malignancy has become one of the major causes of death after transplantation, so early cancer diagnosis and detection can drastically improve survival rates post-transplantation. Most previous work focuses on using artificial intelligence (AI) to predict transplant success or failure outcomes. In this work, we focused on predicting de novo malignancy after liver transplantation using AI. We chose the patients that had malignancy after liver transplantation with no history of malignancy pre-transplant. Their donors were cancer-free as well. We analyzed 254,200 patient profiles with post-transplant malignancy from the US Organ Procurement and Transplantation Network (OPTN). Several popular data mining methods were applied to the resultant dataset to build predictive models to characterize de novo malignancy after liver transplantation. Recipient's bilirubin, creatinine, weight, gender, number of days recipient was on the transplant waiting list, Epstein Barr Virus (EBV), International normalized ratio (INR), and ascites are among the most important factors affecting de novo malignancy after liver transplantation

Keywords: De novo malignancy, bilirubin, data mining, transplantation

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Authors: M. A. C. S. Sampath Fernando, James M. Curran, Renate Meyer

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Model assessment, in the Bayesian context, involves evaluation of the goodness-of-fit and the comparison of several alternative candidate models for predictive accuracy and improvements. In posterior predictive checks, the data simulated under the fitted model is compared with the actual data. Predictive model accuracy is estimated using information criteria such as the Akaike information criterion (AIC), the Bayesian information criterion (BIC), the Deviance information criterion (DIC), and the Watanabe-Akaike information criterion (WAIC). The goal of an information criterion is to obtain an unbiased measure of out-of-sample prediction error. Since posterior checks use the data twice; once for model estimation and once for testing, a bias correction which penalises the model complexity is incorporated in these criteria. Cross-validation (CV) is another method used for examining out-of-sample prediction accuracy. Leave-one-out cross-validation (LOO-CV) is the most computationally expensive variant among the other CV methods, as it fits as many models as the number of observations. Importance sampling (IS), truncated importance sampling (TIS) and Pareto-smoothed importance sampling (PSIS) are generally used as approximations to the exact LOO-CV and utilise the existing MCMC results avoiding expensive computational issues. The reciprocals of the predictive densities calculated over posterior draws for each observation are treated as the raw importance weights. These are in turn used to calculate the approximate LOO-CV of the observation as a weighted average of posterior densities. In IS-LOO, the raw weights are directly used. In contrast, the larger weights are replaced by their modified truncated weights in calculating TIS-LOO and PSIS-LOO. Although, information criteria and LOO-CV are unable to reflect the goodness-of-fit in absolute sense, the differences can be used to measure the relative performance of the models of interest. However, the use of these measures is only valid under specific circumstances. This study has developed 11 models using normal, log-normal, gamma, and student’s t distributions to improve the PCR stutter prediction with forensic data. These models are comprised of four with profile-wide variances, four with locus specific variances, and three which are two-component mixture models. The mean stutter ratio in each model is modeled as a locus specific simple linear regression against a feature of the alleles under study known as the longest uninterrupted sequence (LUS). The use of AIC, BIC, DIC, and WAIC in model comparison has some practical limitations. Even though, IS-LOO, TIS-LOO, and PSIS-LOO are considered to be approximations of the exact LOO-CV, the study observed some drastic deviations in the results. However, there are some interesting relationships among the logarithms of pointwise predictive densities (lppd) calculated under WAIC and the LOO approximation methods. The estimated overall lppd is a relative measure that reflects the overall goodness-of-fit of the model. Parallel log-likelihood profiles for the models conditional on equal posterior variances in lppds were observed. This study illustrates the limitations of the information criteria in practical model comparison problems. In addition, the relationships among LOO-CV approximation methods and WAIC with their limitations are discussed. Finally, useful recommendations that may help in practical model comparisons with these methods are provided.

Keywords: cross-validation, importance sampling, information criteria, predictive accuracy

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Authors: Moh'd Alodat

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In this paper, we discuss the power function distribution and derive the maximum likelihood estimator of its parameter as well as the reliability parameter. We derive the large sample properties of the estimators based on the selective order statistic scheme. We conduct simulation studies to investigate the significance of the selective order statistic scheme in our setup and to compare the efficiency of the new proposed estimators.

Keywords: fisher information, maximum likelihood estimator, power function distribution, ranked set sampling, selective order statistics sampling

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Authors: Guilherme Henrique Gabriel, Lucí Hidalgo Nunes

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An important feature of rainfall regimes is the variability, which is subject to the atmosphere’s general and regional dynamics, geographical position and relief. Despite being inherent to the climate system, it can harshly impact virtually all human activities. In turn, global climate change has the ability to significantly affect smaller-scale rainfall regimes by altering their current variability patterns. In this regard, it is useful to know if regional climates are changing over time and whether it is possible to link these variations to climate change trends observed globally. This study is part of an international project (Metropole-FAPESP, Proc. 2012/51876-0 and Proc. 2015/11035-5) and the objective was to identify and evaluate possible changes in rainfall behavior in the state of São Paulo, southeastern Brazil, using rainfall data from 79 rain gauges for the last forty years. Cluster analysis and gamma distribution parameters were used for evaluating spatial and temporal trends, and the outcomes are presented by means of geographic information systems tools. Results show remarkable changes in rainfall distribution patterns in São Paulo over the years: changes in shape and scale parameters of gamma distribution indicate both an increase in the irregularity of rainfall distribution and the probability of occurrence of extreme events. Additionally, the spatial outcome of cluster analysis along with the gamma distribution parameters suggest that changes occurred simultaneously over the whole area, indicating that they could be related to remote causes beyond the local and regional ones, especially in a current global climate change scenario.

Keywords: climate change, cluster analysis, gamma distribution, rainfall

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Authors: Masood Roohi, Amir Taghavipour

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This paper describes a strategy to develop an energy management system (EMS) for a charge-sustaining power-split hybrid electric vehicle. This kind of hybrid electric vehicles (HEVs) benefit from the advantages of both parallel and series architecture. However, it gets relatively more complicated to manage power flow between the battery and the engine optimally. The applied strategy in this paper is based on nonlinear model predictive control approach. First of all, an appropriate control-oriented model which was accurate enough and simple was derived. Towards utilization of this controller in real-time, the problem was solved off-line for a vast area of reference signals and initial conditions and stored the computed manipulated variables inside look-up tables. Look-up tables take a little amount of memory. Also, the computational load dramatically decreased, because to find required manipulated variables the controller just needed a simple interpolation between tables.

Keywords: hybrid electric vehicles, energy management system, nonlinear model predictive control, real-time

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Authors: Muhammad Arif Mahmood, Andrei C. Popescu, Mihai Oane, Diana Chioibascu, Carmen Ristoscu, Ion N. Mihailescu

Abstract:

Powder flow and temperature distributions are recognized as influencing factors during laser melting deposition (LMD) process, that not only affect the consolidation rate but also characteristics of the deposited layers. Herewith, two simplified analytical models will be presented to simulate the powder flow with the inclusion of powder particles size distribution in Gaussian form, under three powder jet nozzles, and temperature analyses during LMD process. The output of the 1st model will serve as the input in the 2nd model. The models will be validated with experimental data, i.e., weight measurement method for powder particles distribution and infrared imaging for temperature analyses. This study will increase the cost-efficiency of the LMD process by adjustment of the operating parameters for reaching optimal powder debit and energy. This research has received funds under the Marie Sklodowska-Curie grant agreement No. 764935, from the European Union’s Horizon 2020 research and innovation program.

Keywords: laser additive manufacturing, powder particles size distribution in Gaussian form, powder stream distribution, temperature analyses

Procedia PDF Downloads 109

Authors: Nour Ismail, Sahar El Kardawy, Bassant Badwy

Abstract:

Radiofrequency (RF) lesioning of nerves have been commonly used to alleviate chronic pain, where RF current preventing transmission of pain signals through the nerve by heating the nerve causing the pain. There are some factors that affect the temperature distribution and the nerve lesion size, one of these factors is the inhomogeneities in the tissue medium. Our objective is to calculate the temperature distribution and the nerve lesion size in a nonhomogenous medium surrounding the RF electrode. A two 3-D finite element models are used to compare the temperature distribution in the homogeneous and nonhomogeneous medium. Also the effect of temperature-dependent electric conductivity on maximum temperature and lesion size is observed. Results show that the presence of a nonhomogeneous medium around the RF electrode has a valuable effect on the temperature distribution and lesion size. The dependency of electric conductivity on tissue temperature increased lesion size.

Keywords: finite element model, nerve lesioning, pain relief, radiofrequency lesion

Procedia PDF Downloads 382

Authors: Shoumodip Roy, Ankit Singhania, K. R. K. Rao, Ravi Shankar, M. K. Agarwal, R. V. Ramna, Uttam Singh

Abstract:

The productivity of a blast furnace and the quality of the hot metal produced are significantly dependent on the smoothness and stability of furnace operation. The permeability of the furnace bed, as well as the gas flow pattern, influences the steady control of process parameters. The softening – melting zone that is formed inside the furnace contributes largely in distribution of the gas flow and the bed permeability. A better shape of softening-melting zone enhances the performance of blast furnace, thereby reducing the fuel rates and improving furnace life. Therefore, predictive model of the softening- melting zone profile can be utilized to control and improve the furnace operation. The shape of softening-melting zone depends upon the physical and chemical properties of the agglomerates and iron ore charged in the furnace. The variations in the agglomerate proportion in the burden at G Blast furnace disturbed the furnace stability. During such circumstances, it was analyzed that a w-shape softening-melting zone profile was formed inside the furnace. The formation of w-shape zone resulted in poor bed permeability and non-uniform gas flow. There was a significant increase in the heat loss at the lower zone of the furnace. The fuel demand increased, and the huge production loss was incurred. Therefore, visibility of softening-melting zone profile was necessary in order to pro-actively optimize the process parameters and thereby to operate the furnace smoothly. Using stave temperatures, a model was developed that predicted the shape of the softening-melting zone inside the furnace. It was observed that furnace operated smoothly during inverse V-shape of the zone and vice-versa during w-shape. This model helped to control the heat loss, optimize the burden distribution and lower the fuel rate at G Blast Furnace, TSL Jamshedpur. As a result of furnace stabilization productivity increased by 10% and fuel rate reduced by 80 kg/thm. Details of the process have been discussed in this paper.

Keywords: agglomerate, blast furnace, permeability, softening-melting

Procedia PDF Downloads 220