Search results for: noise estimation

Authors: Esma Birisci, Ronald McGarvey

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One of the common problems in food service industry is demand uncertainty. This research presents a multi-criteria optimization approach to identify the efficient frontier of points lying between the minimum-waste and minimum-shortfall solutions within uncertain demand environment. It also addresses correlation across demands for items (e.g., hamburgers are often demanded with french fries). Reducing overproduction food waste (and its corresponding environmental impacts) and an aversion to shortfalls (leave some customer hungry) need to consider as two contradictory objectives in an all-you-care-to-eat environment food service operation. We identify optimal production adjustments relative to demand forecasts, demand thresholds for utilization of leftovers, and percentages of demand to be satisfied by leftovers, considering two alternative metrics for overproduction waste: mass; and greenhouse gas emissions. Demand uncertainty and demand correlations are addressed using a kernel density estimation approach. A statistical analysis of the changes in decision variable values across each of the efficient frontiers can then be performed to identify the key variables that could be modified to reduce the amount of wasted food at minimal increase in shortfalls. We illustrate our approach with an application to empirical data from Campus Dining Services operations at the University of Missouri.

Keywords: environmental studies, food waste, production planning, uncertain and correlated demand

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Authors: Renato Morbidelli, Carla Saltalippi, Alessia Flammini, Tommaso Picciafuoco, Corrado Corradini

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A considerable part of rainfall data to be used in the hydrological practice is available in aggregated form within constant time intervals. This can produce undesirable effects, like the underestimate of the annual maximum rainfall depth, Hd, associated with a given duration, d, that is the basic quantity in the development of rainfall depth-duration-frequency relationships and in determining if climate change is producing effects on extreme event intensities and frequencies. The errors in the evaluation of Hd from data characterized by a coarse temporal aggregation, ta, and a procedure to reduce the non-homogeneity of the Hd series are here investigated. Our results indicate that: 1) in the worst conditions, for d=ta, the estimation of a single Hd value can be affected by an underestimation error up to 50%, while the average underestimation error for a series with at least 15-20 Hd values, is less than or equal to 16.7%; 2) the underestimation error values follow an exponential probability density function; 3) each very long time series of Hd contains many underestimated values; 4) relationships between the non-dimensional ratio ta/d and the average underestimate of Hd, derived from continuous rainfall data observed in many stations of Central Italy, may overcome this issue; 5) these equations should allow to improve the Hd estimates and the associated depth-duration-frequency curves at least in areas with similar climatic conditions.

Keywords: central Italy, extreme events, rainfall data, underestimation errors

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Authors: Cosmas Nathanailides, Fotini Kakali, Kostas Karipoglou

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The filleting yield and the chemical composition of farmed sea bass (Dicentrarchus labrax); rainbow trout (Oncorynchus mykiss) and meagre (Argyrosomus regius) was investigated in farmed fish in NW Greece. The results provide an estimate of the quantity of fish required to produce one kilogram of fillet weight, an estimation which is required for the operational management of fish processing companies. Furthermore in this work, the ratio of feed input required to produce one kilogram of fish fillet (FFCR) is presented for the first time as a useful indicator of the ecological footprint of consuming farmed fish. The lowest lipid content appeared in meagre (1,7%) and the highest in trout (4,91%). The lowest fillet yield and fillet yield feed conversion ratio (FYFCR) was in meagre (FY=42,17%, FFCR=2,48), the best fillet yield (FY=53,8%) and FYFCR (2,10) was exhibited in farmed rainbow trout. This research has been co-financed by the European Union (European Social Fund – ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Research Funding Program: ARCHIMEDES III. Investing in knowledge society through the European Social Fund.

Keywords: farmed fish, flesh quality, filleting yield, lipid

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Authors: Areej Salaymeh, Loren Schwiebert, Stephen Remias, Jonathan Waddell

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Extracting information from new data sources has emerged as a crucial task in many traffic planning processes, such as identifying traffic patterns, route planning, traffic forecasting, and locating infrastructure improvements. Given the advanced technologies used to collect Global Positioning System (GPS) data from dedicated GPS devices, GPS equipped phones, and navigation tools, intelligent data analysis methodologies are necessary to mine this raw data. In this research, an automatic detection framework is proposed to help identify and classify the locations of stopped GPS waypoints into two main categories: signalized intersections or highway congestion. The Delaunay triangulation is used to perform this assessment in the clustering phase. While most of the existing clustering algorithms need assumptions about the data distribution, the effectiveness of the Delaunay triangulation relies on triangulating geographical data points without such assumptions. Our proposed method starts by cleaning noise from the data and normalizing it. Next, the framework will identify stoppage points by calculating the traveled distance. The last step is to use clustering to form groups of waypoints for signalized traffic and highway congestion. Next, a binary classifier was applied to find distinguish highway congestion from signalized stop points. The binary classifier uses the length of the cluster to find congestion. The proposed framework shows high accuracy for identifying the stop positions and congestion points in around 99.2% of trials. We show that it is possible, using limited GPS data, to distinguish with high accuracy.

Keywords: Delaunay triangulation, clustering, intelligent transportation systems, GPS data

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Authors: Abdul Hakim Chikho

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Most international codes allow the use of an equivalent lateral load method for designing practical buildings to withstand earthquake actions. This method requires calculating an approximation to the fundamental mode period of vibrations of these buildings. Several empirical equations have been suggested to calculate approximations to the fundamental periods of different types of structures. Most of these equations are knowing to provide an only crude approximation to the required fundamental periods and repeating the calculation utilizing a more accurate formula is usually required. In this paper, a new formula to calculate a satisfactory approximation of the fundamental period of a practical building is proposed. This formula takes into account the mass and the stiffness of the building therefore, it is more logical than the conventional empirical equations. In order to verify the accuracy of the proposed formula, several examples have been solved. In these examples, calculating the fundamental mode periods of several farmed buildings utilizing the proposed formula and the conventional empirical equations has been accomplished. Comparing the obtained results with those obtained from a dynamic computer has shown that the proposed formula provides a more accurate estimation of the fundamental periods of practical buildings. Since the proposed method is still simple to use and requires only a minimum computing effort, it is believed to be ideally suited for design purposes.

Keywords: earthquake, fundamental mode period, design, building

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Authors: Nato Kutaladze, George Mikuchadze, Giorgi Sokhadze

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Precipitation forecasts are one of the most demanding applications in numerical weather prediction (NWP). Georgia, as the whole Caucasian region, is characterized by very complex topography. The country territory is prone to flash floods and mudflows, quantitative precipitation estimation (QPE) and quantitative precipitation forecast (QPF) at any leading time are very important for Georgia. In this study, advanced research weather forecasting model’s skill in QPF is investigated over Georgia’s territory. We have analyzed several convection parameterization and microphysical scheme combinations for different rainy episodes and heavy rainy phenomena. We estimate errors and biases in accumulated 6 h precipitation using different spatial resolution during model performance verification for 12-hour and 24-hour lead time against corresponding rain gouge observations and satellite data. Various statistical parameters have been calculated for the 8-month comparison period, and some skills of model simulation have been evaluated. Our focus is on the formation and organization of convective precipitation systems in a low-mountain region. Several problems in connection with QPF have been identified for mountain regions, which include the overestimation and underestimation of precipitation on the windward and lee side of the mountains, respectively, and a phase error in the diurnal cycle of precipitation leading to the onset of convective precipitation in model forecasts several hours too early.

Keywords: extremal dependence index, false alarm, numerical weather prediction, quantitative precipitation forecasting

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Authors: Saleem Z. Ramadan

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This paper discusses the effects of using progressive Type-I right censoring on the design of the Simple Step Accelerated Life testing using Bayesian approach for Weibull life products under the assumption of cumulative exposure model. The optimization criterion used in this paper is to minimize the expected pre-posterior variance of the PTH percentile time of failures. The model variables are the stress changing time and the stress value for the first step. A comparison between the conventional and the progressive Type-I right censoring is provided. The results have shown that the progressive Type-I right censoring reduces the cost of testing on the expense of the test precision when the sample size is small. Moreover, the results have shown that using strong priors or large sample size reduces the sensitivity of the test precision to the censoring proportion. Hence, the progressive Type-I right censoring is recommended in these cases as progressive Type-I right censoring reduces the cost of the test and doesn't affect the precision of the test a lot. Moreover, the results have shown that using direct or indirect priors affects the precision of the test.

Keywords: reliability, accelerated life testing, cumulative exposure model, Bayesian estimation, progressive type-I censoring, Weibull distribution

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Authors: Lizhou Chen, Abdelhamid Belgaid, Assem Elsayed, Xiaoming Yang

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Compression index is essential in foundation settlement calculation. The traditional method for determining compression index is consolidation test which is expensive and time consuming. Many researchers have used regression methods to develop empirical equations for predicting compression index from soil properties. Based on a large number of compression index data collected from consolidation tests, the accuracy of some popularly empirical equations were assessed. It was found that primary compression index is significantly overestimated in some equations while it is underestimated in others. The sensitivity analyses of soil parameters including water content, liquid limit and void ratio were performed. The results indicate that the compression index obtained from void ratio is most accurate. The ANOVA (analysis of variance) demonstrates that the equations with multiple soil parameters cannot provide better predictions than the equations with single soil parameter. In other words, it is not necessary to develop the relationships between compression index and multiple soil parameters. Meanwhile, it was noted that secondary compression index is approximately 0.7-5.0% of primary compression index with an average of 2.0%. In the end, the proposed prediction equations using power regression technique were provided that can provide more accurate predictions than those from existing equations.

Keywords: compression index, clay, settlement, consolidation, secondary compression index, soil parameter

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Authors: Manana Kvetenadze, Dali Nikolaishvili

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The study revealed the territorial changes of Georgia before the Soviet and Post-Soviet periods. This includes the estimation of the country's borders, its administrative-territorial arrangement change as well as the establishment of territorial losses. Georgia’s old and new borders marked on the map are of great interest. The new boundary shows the condition of 1922 year, following the Soviet period. Neither on this map nor in other works Ivane Javakhishvili talks about what he implies in the old borders, though it is evident that this is the Pre-Soviet boundary until 1921 – i.e., before the period when historical Tao, Zaqatala, Lore, Karaia represented the parts of Georgia. According to cartometric-geographical terms, the work presents detailed analysis of Georgia’s borders, along with this the comparison of research results has been carried out: 1) At the boundary line on Soviet topographic maps, the maps of 100,000; 50,000 and 25,000 scales are used; 2) According to Ivane Javakhishvili’s work ('The borders of Georgia in terms of historical and contemporary issues'). During that research, we used multi-disciplined methodology and software. We used Arc GIS for Georeferencing maps, and after that, we compare all post-Soviet Union maps, in order to determine how the borders have changed. During this work, we also use many historical data. The features of the spatial distribution of the territorial administrative units of Georgia, as well as the distribution of administrative-territorial units of the objects depicted on the map, have been established. The results obtained are presented in the forms of thematic maps and diagrams.

Keywords: border, GIS, georgia, historical cartography, old maps

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Authors: Michael Josef Schwerer

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Background: The identification of unknown victims from mass disasters, violent crimes, or terrorist attacks is frequently facilitated through information from missing persons lists, portrait photos, old or recent pictures showing unique characteristics of a person such as scars or tattoos, or simply reference samples from blood relatives for DNA analysis. In contrast, the identification or at least the characterization of an unknown perpetrator from criminal or terrorist actions remains challenging, particularly in the absence of material or data for comparison, such as fingerprints, which had been previously stored in criminal records. In scenarios that result in high levels of destruction of the perpetrator’s corpse, for instance, blast or fire events, the chance for a positive identification using standard techniques is further impaired. Objectives: This study shows the forensic genetic procedures in the Legal Medicine Service of the German Air Force for the identification of unknown individuals, including such cases in which reference samples are not available. Scenarios requiring such efforts predominantly involve aircraft crash investigations, which are routinely carried out by the German Air Force Centre of Aerospace Medicine as one of the Institution’s essential missions. Further, casework by military police or military intelligence is supported based on administrative cooperation. In the talk, data from study projects, as well as examples from real casework, will be demonstrated and discussed with the audience. Methods: Forensic genetic identification in our laboratories involves the analysis of Short Tandem Repeats and Single Nucleotide Polymorphisms in nuclear DNA along with mitochondrial DNA haplotyping. Extended DNA analysis involves phenotypic markers for skin, hair, and eye color together with the investigation of a person’s biogeographic ancestry. Assessment of the biological age of an individual employs CpG-island methylation analysis using bisulfite-converted DNA. Forensic Investigative Genealogy assessment allows the detection of an unknown person’s blood relatives in reference databases. Technically, end-point-PCR, real-time PCR, capillary electrophoresis, pyrosequencing as well as next generation sequencing using flow-cell-based and chip-based systems are used. Results and Discussion: Optimization of DNA extraction from various sources, including difficult matrixes like formalin-fixed, paraffin-embedded tissues, degraded specimens from decomposed bodies or from decedents exposed to blast or fire events, provides soil for successful PCR amplification and subsequent genetic profiling. For cases with extremely low yields of extracted DNA, whole genome preamplification protocols are successfully used, particularly regarding genetic phenotyping. Improved primer design for CpG-methylation analysis, together with validated sampling strategies for the analyzed substrates from, e.g., lymphocyte-rich organs, allows successful biological age estimation even in bodies with highly degraded tissue material. Conclusions: Successful identification of unknown individuals or at least their phenotypic characterization using pigmentation markers together with age-informative methylation profiles, possibly supplemented by family tree search employing Forensic Investigative Genealogy, can be provided in specialized laboratories. However, standard laboratory procedures must be adapted to work with difficult and highly degraded sample materials.

Keywords: identification, forensic genetics, phenotypic markers, CPG methylation, biological age estimation, forensic investigative genealogy

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Authors: Jafar Mortadha, Imran Qureshi

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This research explains and compares the modern techniques used for measuring the flow angles of a flowing fluid with the traditional technique of using multi-hole pressure probes. In particular, the focus of the study is on four-hole probes, which offer great reliability and benefits in several applications where the use of modern measurement techniques is either inconvenient or impractical. Due to modern advancements in manufacturing, small multi-hole pressure probes can be made with high precision, which eliminates the need for calibrating every manufactured probe. This study aims to improve the range of calibration maps for a four-hole probe to allow high flow angles to be measured accurately. The research methodology comprises a literature review of the successful calibration definitions that have been implemented on five-hole probes. These definitions are then adapted and applied on a four-hole probe using a set of raw pressures data. A comparison of the different definitions will be carried out in Matlab and the results will be analyzed to determine the best calibration definition. Taking simplicity of implementation into account as well as the reliability of flow angles estimation, an adapted technique from a research paper written in 2002 offered the most promising outcome. Consequently, the method is seen as a good enhancement for four-hole probes and it can substitute for the existing calibration definitions that offer less accuracy.

Keywords: calibration definitions, calibration maps, flow measurement techniques, four-hole probes, multi-hole pressure probes

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Authors: Okay Gunes

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In this article, for the first time in the literature for this subject we propose a new method for the measuring of well-being inequality through a model composed of superimposing satisfaction waves. The displacement of households’ satisfactory state (i.e. satisfaction) is defined in a satisfaction string. The duration of the satisfactory state for a given period of time is measured in order to determine the relationship between utility and total satisfactory time, itself dependent on the density and tension of each satisfaction string. Thus, individual cardinal total satisfaction values are computed by way of a one-dimensional form for scalar sinusoidal (harmonic) moving wave function, using satisfaction waves with varying amplitudes and frequencies which allow us to measure well-being inequality. One advantage to using satisfaction waves is the ability to show that individual utility and consumption amounts would probably not commute; hence it is impossible to measure or to know simultaneously the values of these observables from the dataset. Thus, we crystallize the problem by using a Heisenberg-type uncertainty resolution for self-adjoint economic operators. We propose to eliminate any estimation bias by correlating the standard deviations of selected economic operators; this is achieved by replacing the aforementioned observed uncertainties with households’ perceived uncertainties (i.e. corrected standard deviations) obtained through the logarithmic psychophysical law proposed by Weber and Fechner.

Keywords: Heisenberg uncertainty principle, superimposing satisfaction waves, Weber–Fechner law, well-being inequality

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Authors: Roudane Mohamed

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In this study we are interested in improving the efficiency of a steam boiler to 4.5T/h and minimize fume discharge temperature by the addition of a heat exchanger against the current in the energy system, the output of the boiler. The mathematical approach to the problem is based on the use of heat transfer by convection and conduction equations. These equations have been chosen because of their extensive use in a wide range of application. A software and developed for solving the equations governing these phenomena and the estimation of the thermal characteristics of boiler through the study of the thermal characteristics of the heat exchanger by both LMTD and NUT methods. Subsequently, an analysis of the thermal performance of the steam boiler by studying the influence of different operating parameters on heat flux densities, temperatures, exchanged power and performance was carried out. The study showed that the behavior of the boiler is largely influenced. In the first regime (P = 3.5 bar), the boiler efficiency has improved significantly from 93.03 to 99.43 at the rate of 6.47% and 4.5%. For maximum speed, the change is less important, it is of the order of 1.06%. The results obtained in this study of great interest to industrial utilities equipped with smoke tube boilers for the preheating air temperature intervene to calculate the actual temperature of the gas so the heat exchanged will be increased and minimize temperature smoke discharge. On the other hand, this work could be used as a model of computation in the design process.

Keywords: numerical simulation, efficiency, fire tube, heat exchanger, convection and conduction

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Authors: Jiamin Huang, Shuliang Gui, Zengshan Tian, Fei Yan, Xiaodong Wu

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In recent years, with the rapid development of radio frequency technology, the differences between radar sensing and wireless communication in terms of receiving and sending channels, signal processing, data management and control are gradually shrinking. There has been a trend of integrated communication radar sensing. However, most of the existing radar imaging technologies based on communication signals are combined with synthetic aperture radar (SAR) imaging, which does not conform to the practical application case of the integration of communication and radar. Therefore, in this paper proposes a high-precision imaging method using communication signals based on the imaging mechanism of inverse synthetic aperture radar (ISAR) imaging. This method makes full use of the structural characteristics of the orthogonal frequency division multiplexing (OFDM) signal, so the sidelobe effect in distance compression is removed and combines radon transform and Fractional Fourier Transform (FrFT) parameter estimation methods to achieve ISAR imaging of non-cooperative targets. The simulation experiment and measured results verify the feasibility and effectiveness of the method, and prove its broad application prospects in the field of intelligent transportation.

Keywords: integration of communication and radar, OFDM, radon, FrFT, ISAR

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Authors: Robel Legese Meko

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Natural fibers have been used as end-of-life textiles and made into textile products which have become a well-proven and effective way of processing. Nowadays, resources to make primary synthetic fibers are becoming less and less as the world population is rising. Hence it is necessary to develop processes to fabricate textiles that are easily converted to composite materials. Acoustic comfort is closely related to the concept of sound absorption and includes protection against noise. This research paper presents an experimental study on sound absorption coefficients, for natural fiber composite materials: a natural fiber (Coir/Jute) with different blend proportions of raw materials mixed with rigid polyurethane foam as a binder. The natural fiber composite materials were characterized both acoustically (sound absorption coefficient SAC) and also in terms of heat transfer (thermal conductivity). The acoustic absorption coefficient was determined using the impedance tube method according to the ASTM Standard (ASTM E 1050). The influence of the structure of these materials on the sound-absorbing properties was analyzed. The experimental results signify that the porous natural coir/jute composites possess excellent performance in the absorption of high-frequency sound waves, especially above 2000 Hz, and didn’t induce a significant change in the thermal conductivity of the composites. Thus, the sound absorption performances of natural fiber composites based on coir/jute fiber materials promote environmentally friendly solutions.

Keywords: coir/jute fiber, sound absorption coefficients, compression molding, impedance tube, thermal insulating properties, SEM analysis

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Authors: Pi-Hsia Hung

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The development of mathematical competency has individual benefits as well as benefits to the wider society. Children who begin school behind their peers in their understanding of number, counting, and simple arithmetic are at high risk of staying behind throughout their schooling. The development of effective strategies for improving the educational trajectory of these individuals will be contingent on identifying areas of early quantitative knowledge that influence later mathematics achievement. A computer-based quantity assessment was developed in this study to investigate the characteristics of 2nd and 3rd grade slow learners in quantity. The concept of quantification involves understanding measurements, counts, magnitudes, units, indicators, relative size, and numerical trends and patterns. Fifty-five tasks of quantitative reasoning—such as number sense, mental calculation, estimation and assessment of reasonableness of results—are included as quantity problem solving. Thus, quantity is defined in this study as applying knowledge of number and number operations in a wide variety of authentic settings. Around 1000 students were tested and categorized into 4 different performance levels. Students’ quantity ability correlated higher with their school math grade than other subjects. Around 20% students are below basic level. The intervention design implications of the preliminary item map constructed are discussed.

Keywords: mathematics assessment, mathematical cognition, quantity, number sense, validity

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Authors: Gautam Kumar Saharia, Sagardeep Talukdar, Riki Dutta, Sudipta Nandy

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The physics-informed neural network (PINN) method opens up an approach for numerically solving nonlinear partial differential equations leveraging fast calculating speed and high precession of modern computing systems. We construct the PINN based on a strong universal approximation theorem and apply the initial-boundary value data and residual collocation points to weekly impose initial and boundary conditions to the neural network and choose the optimization algorithms adaptive moment estimation (ADAM) and Limited-memory Broyden-Fletcher-Golfard-Shanno (L-BFGS) algorithm to optimize learnable parameter of the neural network. Next, we improve the PINN with a weighted loss function to obtain both the bright and dark soliton solutions of the Fokas-Lenells equation (FLE). We find the proposed scheme of adjustable weight coefficients into PINN has a better convergence rate and generalizability than the basic PINN algorithm. We believe that the PINN approach to solve the partial differential equation appearing in nonlinear optics would be useful in studying various optical phenomena.

Keywords: deep learning, optical soliton, physics informed neural network, partial differential equation

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Authors: Jayanth C., Anirudh Sai Yetikuri, Kavitha S. N.

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This paper explores the development and application of computer vision and machine learning techniques for real-time pose detection, facial recognition, and number plate extraction. Utilizing MediaPipe for pose estimation, the research presents methods for detecting hand raises and ducking postures through real-time video analysis. Complementarily, facial recognition is employed to compare and verify individual identities using the face recognition library. Additionally, the paper demonstrates a robust approach for extracting and storing vehicle number plates from images, integrating Optical Character Recognition (OCR) with a database management system. The study highlights the effectiveness and versatility of these technologies in practical scenarios, including security and surveillance applications. The findings underscore the potential of combining computer vision techniques to address diverse challenges and enhance automated systems for both individual and vehicular identification. This research contributes to the fields of computer vision and machine learning by providing scalable solutions and demonstrating their applicability in real-world contexts.

Keywords: computer vision, pose detection, facial recognition, number plate extraction, machine learning, real-time analysis, OCR, database management

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Authors: Adel Ahmadi Hosseini, Fatemeh Tavanaei, Alessandro Navarra, Ferri Hassani

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Mining engineering, as a part of geoscience, must address modern concerns. Traditional mining methods incorporate drill and blast technologies, which are followed by different issues, including excessive noise, vibration, air pollution, and safety hazards. Over the past two decades, mining engineers have sought alternative solutions to move from drill and blast to continuous methods to prevent such issues and improve sustainability in mining. Among the suggested methods, microwave treatment has shown promising results by creating micro/macro cracks in the rock structure prior to the operations. This research utilizes an energy-based analysis methodology to evaluate the efficiency of the microwave treatment in improving mining operations. The data analysis shows that increasing the input microwave energy dosage intensifies the rock damage. However, this approach can decrease the energy efficiency of the method by more than 50% in some cases. In this study, rock samples were treated with three power levels (3 kW, 7 kW, and 12 kW) and two energy dosages (20 kWh/t and 50 kWh/t), resulting in six conditions. To evaluate the impact of microwave treatment on the geomechanical behavior of the rocks, Unconfined Compressive Strength (UCS) tests were conducted on the microwave-treated samples, yielding stress-strain curves. Using the stress-strain curves, the effect of the different powers and energy dosages of microwaves are discussed. This research shows the potential of using microwave treatment to lead the industry to more sustainable mining.

Keywords: microwave treatment, microwave energy dosage, sustainable mining, rock fragmentation

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Authors: Da-Ming Huang, Ya-Ting Tsai, Shyh-Hau Wang

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Ultrasound signals backscattered from the soft tissues are mainly depending on the size, density, distribution, and other elastic properties of scatterers in the interrogated sample volume. The quantitative analysis of ultrasonic backscattering is frequently implemented using the statistical approach due to that of backscattering signals tends to be with the nature of the random variable. Thus, the statistical analysis, such as Nakagami statistics, has been applied to characterize the density and distribution of scatterers of a sample. Yet, the accuracy of statistical analysis could be readily affected by the receiving signals associated with the nature of incident ultrasound wave and acoustical properties of samples. Thus, in the present study, efforts were made to explore such effects as the ultrasound operational modes and attenuation of biological tissue on the estimation of corresponding Nakagami statistical parameter (m parameter). In vitro measurements were performed from healthy and pathological fibrosis porcine livers using different single-element ultrasound transducers and duty cycles of incident tone burst ranging respectively from 3.5 to 7.5 MHz and 10 to 50%. Results demonstrated that the estimated m parameter tends to be sensitively affected by the use of ultrasound operational modes as well as the tissue attenuation. The healthy and pathological tissues may be characterized quantitatively by m parameter under fixed measurement conditions and proper calibration.

Keywords: ultrasound backscattering, statistical analysis, operational mode, attenuation

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Authors: Abdullah AlGhazali, Richard Fairchild, Yilmaz Guney

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We examine the effect of managerial overconfidence on UK firms’ payout policy for the period 2000 to 2012. The analysis incorporates, in addition to common firm-specific factors, a wide range of corporate governance factors and managerial characteristics that have been documented to affect the relationship between overconfidence and payout policy. Our results are robust to several estimation considerations. The findings show that the influence of overconfident CEOs on the amount of, and the propensity to pay, dividends is significant within the UK context. Specifically, we detect that there is a reduction in dividend payments in firms managed by overconfident managers compared to their non-overconfident counterparts. Moreover, we affirm that cash flows, firm size and profitability are positively correlated, while leverage, firm growth and investment are negatively correlated with the amount of and propensity to pay dividends. Interestingly, we demonstrate that firms with the potential for undervaluation reduce dividend payments. Some of the corporate governance factors are shown to motivate firms to pay more dividends while these factors seem to have no influence on the propensity to pay dividends. The results also show that in general higher overconfidence leads to more share repurchases but the lower total payout. Overall, managerial overconfidence should be considered as an important factor influencing payout policy in addition to other known factors.

Keywords: dividends, repurchases, UK firms, overconfidence, corporate governance, undervaluation

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Authors: Waleed A. Basuliman, Khalid S. AlSaleh, Mohamed Z. Ramadan

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Applying the anthropometric dimensions is considered one of the important factors when designing any human-machine system. In this study, the estimation of anthropometric dimensions has been improved by developing artificial neural network that aims to predict the anthropometric measurements of the male in Saudi Arabia. A total of 1427 Saudi males from age 6 to 60 participated in measuring twenty anthropometric dimensions. These anthropometric measurements are important for designing the majority of work and life applications in Saudi Arabia. The data were collected during 8 months from different locations in Riyadh City. Five of these dimensions were used as predictors variables (inputs) of the model, and the remaining fifteen dimensions were set to be the measured variables (outcomes). The hidden layers have been varied during the structuring stage, and the best performance was achieved with the network structure 6-25-15. The results showed that the developed Neural Network model was significantly able to predict the body dimensions for the population of Saudi Arabia. The network mean absolute percentage error (MAPE) and the root mean squared error (RMSE) were found 0.0348 and 3.225 respectively. The accuracy of the developed neural network was evaluated by compare the predicted outcomes with a multiple regression model. The ANN model performed better and resulted excellent correlation coefficients between the predicted and actual dimensions.

Keywords: artificial neural network, anthropometric measurements, backpropagation, real anthropometric database

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Authors: Jiangxia Han, Liang Xue, Keda Chen

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Despite the significant progress over the last decades in reservoir simulation using numerical discretization, meshing is complex. Moreover, the high degree of freedom of the space-time flow field makes the solution process very time-consuming. Therefore, we present Physics-Informed Convolutional Neural Networks(PICNN) as a hybrid scientific theory and data method for reservoir modeling. Besides labeled data, the model is driven by the scientific theories of the underlying problem, such as governing equations, boundary conditions, and initial conditions. PICNN integrates governing equations and boundary conditions into the network architecture in the form of a customized convolution kernel. The loss function is composed of data matching, initial conditions, and other measurable prior knowledge. By customizing the convolution kernel and minimizing the loss function, the neural network parameters not only fit the data but also honor the governing equation. The PICNN provides a methodology to model and history-match flow and transport problems in porous media. Numerical results demonstrate that the proposed PICNN can provide an accurate physical solution from a limited dataset. We show how this method can be applied in the context of a forward simulation for continuous problems. Furthermore, several complex scenarios are tested, including the existence of data noise, different work schedules, and different good patterns.

Keywords: convolutional neural networks, deep learning, flow and transport in porous media, physics-informed neural networks, reservoir simulation

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Authors: Sujoy Das, M. M. Ghosh

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The thermal conductivity of a fluid can be significantly enhanced by dispersing nano-sized particles in it, and the resultant fluid is termed as "nanofluid". A theoretical model for estimating the thermal conductivity of a nanofluid has been proposed here. It is based on the mechanism that evenly dispersed nanoparticles within a nanofluid undergo Brownian motion in course of which the nanoparticles repeatedly collide with the heat source. During each collision a rapid heat transfer occurs owing to the solid-solid contact. Molecular dynamics (MD) simulation of the collision of nanoparticles with the heat source has shown that there is a pulse-like pick up of heat by the nanoparticles within 20-100 ps, the extent of which depends not only on thermal conductivity of the nanoparticles, but also on the elastic and other physical properties of the nanoparticle. After the collision the nanoparticles undergo Brownian motion in the base fluid and release the excess heat to the surrounding base fluid within 2-10 ms. The Brownian motion and associated temperature variation of the nanoparticles have been modeled by stochastic analysis. Repeated occurrence of these events by the suspended nanoparticles significantly contributes to the characteristic thermal conductivity of the nanofluids, which has been estimated by the present model for a ethylene glycol based nanofluid containing Cu-nanoparticles of size ranging from 8 to 20 nm, with Gaussian size distribution. The prediction of the present model has shown a reasonable agreement with the experimental data available in literature.

Keywords: brownian dynamics, molecular dynamics, nanofluid, thermal conductivity

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Authors: Kalandi Charan Pradhan

Abstract:

In this study, we investigate does weather variation determine temporary labour migration using 210 sample households from six Semi-Arid Tropic (SAT) villages for the period of 2005-2014 in India. The study has made an attempt to examine how households use temporary labour migration as a coping mechanism to minimise the risk rather than maximize the utility of the households. The study employs panel Logit regression model to predict the probability of household having at least one temporary labour migrant. As per as econometrics result, it is found that along with demographic and socioeconomic factors; weather variation plays an important role to determine the decision of migration at household level. In order to capture the weather variation, the study uses mean crop yield deviation over the study periods. Based on the random effect logit regression result, the study found that there is a concave relationship between weather variation and decision of temporary labour migration. This argument supports the theory of New Economics of Labour Migration (NELM), which highlights the decision of labour migration not only maximise the households’ utility but it helps to minimise the risks.

Keywords: temporary migration, socioeconomic factors, weather variation, crop yield, logit estimation

Procedia PDF Downloads 223

Authors: Amir Hossein Haji, Nabeel Al-Rawahi, Gholamreza Vakili-Nezhaad

Abstract:

An innovative design has been examined for a gas-oil separator based on pressure reduction over an airfoil surface. The primary motivations are to shorten the release trajectory of the bubbles by minimizing the thickness of the oil layer as well as improving uniform pressure reduction zones. Restricted airflow over an airfoil is investigated for its effect on the pressure drop enhancement and the maximum attainable attack angle prior to the stall condition. Aerodynamic separation is delayed based on numerical simulation of Wortmann FX 63137 Airfoil in a confined domain using FLUENT 6.3.26. The proposed set up results in higher pressure drop compared with the free stream case. With the aim of optimum power consumption we have pursued further restriction to an air jet case over the airfoil. Then, a curved strip model is suggested for the air jet which can be applied as an analysis/design tool for the best performance conditions. Pressure reduction is shown to be inversely proportional to the curvature of the upper airfoil profile. This reduction occurs within the tracking zones where the air jet is effectively attached to the airfoil surface. The zero slope condition is suggested to estimate the onset of these zones after which the minimum curvature should be searched. The corresponding zero slope curvature is applied for estimation of the maximum pressure drop which shows satisfactory agreement with the simulation results.

Keywords: airfoil, air jet, curved fluid flow, gas-oil separator

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Authors: Meseret Habtamu, Mekuria Argaw

Abstract:

Urban forests can help to improve the microclimate and air quality. Urban forests in Addis Ababa are important sinks for GHGs as the number of vehicles and the traffic constrain is steadily increasing. The objective of this study was to characterize the vegetation types in selected public parks and to estimate the carbon stock potential of urban forests by assessing carbon in the above, below ground biomass, in the litter and soil. Species which vegetation samples were taken using a systematic transect sampling within value DBH ≥ 5cm were recorded to measure the above, the below ground biomass and the amount of C stored. Allometric models (Y= 34.4703 - 8.0671(DBH) + 0.6589(DBH2) were used to calculate the above ground and Below ground biomass (BGB) = AGB × 0.2 and sampling of soil and litter was based on quadrates. There were 5038 trees recorded from the selected study sites with DBH ≥ 5cm. Most of the Parks had large number of indigenous species, but the numbers of exotic trees are much larger than the indigenous trees. The mean above ground and below ground biomass is 305.7 ± 168.3 and 61.1± 33.7 respectively and the mean carbon in the above ground and below ground biomass is 143.3±74.2 and 28.1 ± 14.4 respectively. The mean CO2 in the above ground and below ground biomass is 525.9 ± 272.2 and 103.1 ± 52.9 respectively. The mean carbon in dead litter and soil carbon were 10.5 ± 2.4 and 69.2t ha-1 respectively. Urban trees reduce atmospheric carbon dioxide (CO2) through sequestration which is important for climate change mitigation, they are also important for recreational, medicinal value and aesthetic and biodiversity conservation.

Keywords: biodiversity, carbon sequestration, climate change, urban forests

Procedia PDF Downloads 229

Authors: Zehai Yu, Hui Zhu, Linglong Lin, Huawei Liang, Biao Yu, Weixin Huang

Abstract:

With the development of intelligent vehicle systems, a high-precision road map is increasingly needed in many aspects. The automatic lane lines extraction and modeling are the most essential steps for the generation of a precise lane-level road map. In this paper, an automatic lane-level road map generation system is proposed. To extract the road markings on the ground, the multi-region Otsu thresholding method is applied, which calculates the intensity value of laser data that maximizes the variance between background and road markings. The extracted road marking points are then projected to the raster image and clustered using a two-stage clustering algorithm. Lane lines are subsequently recognized from these clusters by the shape features of their minimum bounding rectangle. To ensure the storage efficiency of the map, the lane lines are approximated to cubic polynomial curves using a Bayesian estimation approach. The proposed lane-level road map generation system has been tested on urban and expressway conditions in Hefei, China. The experimental results on the datasets show that our method can achieve excellent extraction and clustering effect, and the fitted lines can reach a high position accuracy with an error of less than 10 cm.

Keywords: curve fitting, lane-level road map, line recognition, multi-thresholding, two-stage clustering

Procedia PDF Downloads 128

Authors: Serin Darwish, Hakim Saibi, Amir Gabr

Abstract:

The United Arab Emirates (UAE) is situated within an arid zone where the climate is arid and the recharge of the groundwater is very low. Groundwater is the primary source of water in the United Arab Emirates. However, rapid expansion, population growth, agriculture, and industrial activities have negatively affected these limited water resources. The shortage of water resources has become a serious concern due to the over-pumping of groundwater to meet demand. In addition to the deficit of groundwater, the UAE has one of the highest per capita water consumption rates in the world. In this study, a combination of time-lapse measurements of microgravity and depth to groundwater level in selected wells in Al Ain city was used to estimate the variations in groundwater storage. Al-Ain is the second largest city in Abu Dhabi Emirates and the third largest city in the UAE. The groundwater in this region has been overexploited. Relative gravity measurements were acquired using the Scintrex CG-6 Autograv. This latest generation gravimeter from Scintrex Ltd provides fast, precise gravity measurements and automated corrections for temperature, tide, instrument tilt and rejection of data noise. The CG-6 gravimeter has a resolution of 0.1μGal. The purpose of this study is to measure the groundwater storage changes in the shallow aquifers based on the application of microgravity method. The gravity method is a nondestructive technique that allows collection of data at almost any location over the aquifer. Preliminary results indicate a possible relationship between microgravity and water levels, but more work needs to be done to confirm this. The results will help to develop the relationship between monthly microgravity changes with hydrological and hydrogeological changes of shallow phreatic. The study will be useful in water management considerations and additional future investigations.

Keywords: Al-Ain, arid region, groundwater, microgravity

Procedia PDF Downloads 152

Authors: Anwar Ul Haque, Waqar Asrar, Erwin Sulaeman, Jaffar S. M. Ali

Abstract:

Pressure distribution data of the standard airfoils is usually used for the calibration purposes in subsonic wind tunnels. Results of such experiments are quite old and obtained by using the model in the spanwise direction. In this manuscript, pressure distribution over NACA 4412 airfoil model was presented by placing the 3D model in the lateral direction. The model is made of metal with pressure ports distributed longitudinally as well as in the lateral direction. The pressure model was attached to the floor of the tunnel with the help of the base plate to give the specified angle of attack to the model. Before the start of the experiments, the pressure tubes of the respective ports of the 128 ports pressure scanner are checked for leakage, and the losses due to the length of the pipes were also incorporated in the results for the specified pressure range. Growth rate maps of the boundary layer thickness were also plotted. It was found that with the increase in the velocity, the dynamic pressure distribution was also increased for the alpha seep. Plots of pressure distribution so obtained were overlapped with those obtained by using XFLR software, a low fidelity tool. It was found that at moderate and high angles of attack, the distribution of the pressure coefficients obtained from the experiments is high when compared with the XFLR ® results obtained along with the span of the wing. This under-prediction by XFLR ® is more obvious on the windward than on the leeward side.

Keywords: subsonic flow, boundary layer, wind tunnel, pressure testing

Procedia PDF Downloads 320