Search results for: logit estimation

Authors: Qian Zhao, Shi-Qi Liu, Bo Guo, Zhi-Jun Cheng, Xiao-Yue Wu

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Cold standby redundancy is considered to be an effective mechanism for improving system reliability and is widely used in industrial engineering. However, because of the complexity of the reliability structure, there is little literature studying on the residual life of cold standby system consisting of complex components. In this paper, a simulation method is presented to predict the residual life of k-out-of-n cold standby system. In practical cases, failure information of a system is either unknown, partly unknown or completely known. Our proposed method is designed to deal with the three scenarios, respectively. Differences between the procedures are analyzed. Finally, numerical examples are used to validate the proposed simulation method.

Keywords: cold standby system, k-out-of-n, residual life, simulation sampling

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Authors: Priti S. Tidke, Chandragouda R. Patil

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The present study was designed to investigate the effect of Magnesia phosphorica, a biochemical medicine on urine screeing, biochemical, histopathological, and electron microscopic images in ethylene glycol induced nepholithiasis in rats.Male Wistar albino rats were divided into six groups and were orally administered saline once daily (IR-sham and IR-control) or Magnesia phosphorica 100 mg/kg twice daily for 24 days.The effect of various dilutions of biochemical Mag phos3x, 6x, 30x was determined on urine output by comparing the urine volume collected by keeping individual animals in metabolic cages. Calcium oxalate urolithiasis and hyperoxaluria in male Wistar rats was induced by oral administration of 0.75% Ethylene glycol p.o. daily for 24 days. Simultaneous administration of biochemical 3x, 6x, 30xMag phos (100mg/kg p.o. twice a day) along with ethylene glycol significantly decreased calcium oxalate, urea, creatinine, Calcium, Magnesium, Chloride, Phosphorus, Albumin, Alkaline Phosphatase content in urine compared with vehicle-treated control group.After the completion of treatment period animals were sacrificed, kidneys were removed and subjected to microscopic examination for possible stone formation. Histological estimation of kidney treated with biochemical Mag phos (3x, 6x, 30xMag phos 100 mg/kg, p.o.) along with ethylene glycol inhibited the growth of calculi and reduced the number of stones in kidney compared with control group. Biochemical Mag phos of 3x dilution and its crude equivalent also showed potent diuretic and antiurolithiatic activity in ethylene glycol induced urolithiasis. A significant decrease in the weight of stones was observed after treatment in animals which received biochemical Mag phos of 3x dilution and its crude equivalent in comparison with control groups. From this study, it can be proposed that the 3x dilution of biochemical Mag phos exhibits a significant inhibitory effect on crystal growth, with the improvement of kidney function and substantiates claims on the biological activity of twelve tissue remedies which can be proved scientifically through laboratory animal studies.

Keywords: Mag phos, Magnesia phosphorica, ciochemic medicine, urolithiasis, kidney stone, ethylene glycol

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Authors: Somveer Singh, Vineet Kumar Singh

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We present a new model based on viscoelasticity for the Non-Newtonian fluids.We use a matrix formulated algorithm to approximate solutions of a class of partial integro-differential equations with the given initial and boundary conditions. Some numerical results are presented to simplify application of operational matrix formulation and reduce the computational cost. Convergence analysis, error estimation and numerical stability of the method are also investigated. Finally, some test examples are given to demonstrate accuracy and efficiency of the proposed method.

Keywords: Legendre Wavelets, operational matrices, partial integro-differential equation, viscoelasticity

Procedia PDF Downloads 336

Authors: Neveen AlQasas, Daniel Johnson

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Membranes for water treatment are an established technology that attracts great attention due to its simplicity and cost effectiveness. However, membranes in operation suffer from the adverse effect of membrane fouling. Bio-fouling is a phenomenon that occurs at the water-membrane interface, and is a dynamic process that is initiated by the adsorption of dissolved organic material, including biomacromolecules, on the membrane surface. After initiation, attachment of microorganisms occurs, followed by biofilm growth. The biofilm blocks the pores of the membrane and consequently results in reducing the water flux. Moreover, the presence of a fouling layer can have a substantial impact on the membrane separation properties. Understanding the mechanism of the initiation phase of biofouling is a key point in eliminating the biofouling on membrane surfaces. The adhesion and attachment of different fouling materials is affected by the surface properties of the membrane materials. Therefore, surface properties of different polymeric materials had been studied in terms of their surface energies and Hansen solubility parameters (HSP). The difference between the combined HSP parameters (HSP distance) allows prediction of the affinity of two materials to each other. The possibilities of measuring the HSP of different polymer films via surface measurements, such as contact angle has been thoroughly investigated. Knowing the HSP of a membrane material and the HSP of a specific foulant, facilitate the estimation of the HSP distance between the two, and therefore the strength of attachment to the surface. Contact angle measurements using fourteen different solvents on five different polymeric films were carried out using the sessile drop method. Solvents were ranked as good or bad solvents using different ranking method and ranking was used to calculate the HSP of each polymeric film. Results clearly indicate the absence of a direct relation between contact angle values of each film and the HSP distance between each polymer film and the solvents used. Therefore, estimating HSP via contact angle alone is not sufficient. However, it was found if the surface tensions and viscosities of the used solvents are taken in to the account in the analysis of the contact angle values, a prediction of the HSP from contact angle measurements is possible. This was carried out via training of a neural network model. The trained neural network model has three inputs, contact angle value, surface tension and viscosity of solvent used. The model is able to predict the HSP distance between the used solvent and the tested polymer (material). The HSP distance prediction is further used to estimate the total and individual HSP parameters of each tested material. The results showed an accuracy of about 90% for all the five studied films

Keywords: surface characterization, hansen solubility parameter estimation, contact angle measurements, artificial neural network model, surface measurements

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Authors: Rui Teixeira, Alan O’Connor, Maria Nogal

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The statistical theory of extreme events is progressively a topic of growing interest in all the fields of science and engineering. The changes currently experienced by the world, economic and environmental, emphasized the importance of dealing with extreme occurrences with improved accuracy. When it comes to the design of offshore structures, particularly offshore wind turbines, the importance of efficiently characterizing extreme events is of major relevance. Extreme events are commonly characterized by extreme values theory. As an alternative, the accurate modeling of the tails of statistical distributions and the characterization of the low occurrence events can be achieved with the application of the Peak-Over-Threshold (POT) methodology. The POT methodology allows for a more refined fit of the statistical distribution by truncating the data with a minimum value of a predefined threshold u. For mathematically approximating the tail of the empirical statistical distribution the Generalised Pareto is widely used. Although, in the case of the exceedances of significant wave data (H_s) the 2 parameters Weibull and the Exponential distribution, which is a specific case of the Generalised Pareto distribution, are frequently used as an alternative. The Generalized Pareto, despite the existence of practical cases where it is applied, is not completely recognized as the adequate solution to model exceedances over a certain threshold u. References that set the Generalised Pareto distribution as a secondary solution in the case of significant wave data can be identified in the literature. In this framework, the current study intends to tackle the discussion of the application of statistical models to characterize exceedances of wave data. Comparison of the application of the Generalised Pareto, the 2 parameters Weibull and the Exponential distribution are presented for different values of the threshold u. Real wave data obtained in four buoys along the Irish coast was used in the comparative analysis. Results show that the application of the statistical distributions to characterize significant wave data needs to be addressed carefully and in each particular case one of the statistical models mentioned fits better the data than the others. Depending on the value of the threshold u different results are obtained. Other variables of the fit, as the number of points and the estimation of the model parameters, are analyzed and the respective conclusions were drawn. Some guidelines on the application of the POT method are presented. Modeling the tail of the distributions shows to be, for the present case, a highly non-linear task and, due to its growing importance, should be addressed carefully for an efficient estimation of very low occurrence events.

Keywords: extreme events, offshore structures, peak-over-threshold, significant wave data

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Authors: Sadam Alwadi

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Outlier values become a problem that frequently occurs in the data observation or recording process. Thus, the need for data imputation has become an essential matter. In this work, it will make use of the methods described in the prior work to detect the outlier values based on a collection of stock market data. In order to implement the detection and find some solutions that maybe helpful for investors, real closed price data were obtained from the Amman Stock Exchange (ASE). Tukey and Maximum Overlapping Discrete Wavelet Transform (MODWT) methods will be used to impute the detect the outlier values.

Keywords: outlier values, imputation, stock market data, detecting, estimation

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Authors: Garry A. Einicke, Langford B. White

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This paper describes an optimum filter and smoother for recovering a Markov process message from noisy measurements. The developments follow from an equivalence between a state space model and a hidden Markov chain. The ensuing filter and smoother employ transition probability matrices and approximate probability distribution vectors. The properties of the optimum solutions are retained, namely, the estimates are unbiased and minimize the variance of the output estimation error, provided that the assumed parameter set are correct. Methods for estimating unknown parameters from noisy measurements are discussed. Signal recovery examples are described in which performance benefits are demonstrated at an increased calculation cost.

Keywords: optimal filtering, smoothing, Markov chains

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Authors: Bo Liu, Chi-Man Pun

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A novel technique for digital forgery detection by signal noise inconsistency is proposed in this paper. The forged area spliced from the other picture contains some features which may be inconsistent with the rest part of the image. Noise pattern and the level is a possible factor to reveal such inconsistency. To detect such noise discrepancies, the test picture is initially segmented into small pieces. The noise pattern and level of each segment are then estimated by using various filters. The noise features constructed in this step are utilized in energy-based graph cut to expose forged area in the final step. Experimental results show that our method provides a good illustration of regions with noise inconsistency in various scenarios.

Keywords: forgery detection, splicing forgery, noise estimation, noise

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Authors: Autcha Araveeporn

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This paper presents a study about a nonparametric regression model consisting of a smoothing spline method and a penalized spline regression method. We also compare the techniques used for estimation and prediction of nonparametric regression model. We tried both methods with crude oil prices in dollars per barrel and the Stock Exchange of Thailand (SET) index. According to the results, it is concluded that smoothing spline method performs better than that of penalized spline regression method.

Keywords: nonparametric regression model, penalized spline regression method, smoothing spline method, Stock Exchange of Thailand (SET)

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Authors: Kurniawan Adha, Wan Ismail Wan Yusoff, Luluan Almanna Lubis

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Preventing hazardous events during oil and gas operation is an important contribution of accurate pore pressure data. The availability of pore pressure data also contribute in reducing the operation cost. Suggested methods in pore pressure estimation were mostly complex by the many assumptions and hypothesis used. Basic properties which may have significant impact on estimation model are somehow being neglected. To date, most of pore pressure determinations are estimated by data model analysis and rarely include laboratory analysis, stratigraphy study or core check measurement. Basically, this study developed a model that might be applied to investigate the changes of pore pressure and effective stress due to hydrocarbon production. In general, this paper focused velocity model effect of pore pressure and effective stress changes due to hydrocarbon production with illustrated by changes in saturation. The core samples from Miri field from Sarawak Malaysia ware used in this study, where the formation consists of sandstone reservoir. The study area is divided into sixteen (16) layers and encompassed six facies (A-F) from the outcrop that is used for stratigraphy sequence model. The experimental work was firstly involving data collection through field study and developing stratigraphy sequence model based on outcrop study. Porosity and permeability measurements were then performed after samples were cut into 1.5 inch diameter core samples. Next, velocity was analyzed using SONIC OYO and AutoLab 500. Three (3) scenarios of saturation were also conducted to exhibit the production history of the samples used. Results from this study show the alterations of velocity for different saturation with different actions of effective stress and pore pressure. It was observed that sample with water saturation has the highest velocity while dry sample has the lowest value. In comparison with oil to samples with oil saturation, water saturated sample still leads with the highest value since water has higher fluid density than oil. Furthermore, water saturated sample exhibits velocity derived parameters, such as poisson’s ratio and P-wave velocity over S-wave velocity (Vp/Vs) The result shows that pore pressure value ware reduced due to the decreasing of fluid content. The decreasing of pore pressure result may soften the elastic mineral frame and have tendency to possess high velocity. The alteration of pore pressure by the changes in fluid content or saturation resulted in alteration of velocity value that has proportionate trend with the effective stress.

Keywords: pore pressure, effective stress, production, miri formation

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Authors: A. Brahma

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Analysis of deferred deformations of concrete under sustained load shows that the creep has a leading role on deferred deformations of concrete structures. Knowledge of the creep characteristics of concrete is a Necessary starting point in the design of structures for crack control. Such knowledge will enable the designer to estimate the probable deformation in pre-stressed concrete or reinforced and the appropriate steps can be taken in design to accommodate this movement. In this study, we propose a prediction model that involves the acting principal parameters on the deferred behaviour of concrete structures. For the estimation of the model parameters Levenberg-Marquardt method has proven very satisfactory. A confrontation between the experimental results and the predictions of models designed shows that it is well suited to describe the evolution of the creep of concrete structures.

Keywords: concrete structure, creep, modelling, prediction

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Authors: Meriem Taleb, Ghania Tail, Fatma Zohra Kara, Brahim Djedouani, T. Moussa

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Forensic entomology has grown immensely as a discipline in the past thirty years. The main purpose of forensic entomology is to establish the post mortem interval or PMI. Three days after the death, insect evidence is often the most accurate and sometimes the only method of determining elapsed time since death. This work presents the estimation of the PMI in an experiment to test the reliability of the accumulated degree days (ADD) method and the application of this method in a real case. The study was conducted at the Laboratory of Entomology at the National Institute for Criminalistics and Criminology of the National Gendarmerie, Algeria. The domestic rabbit Oryctolagus cuniculus L. was selected as the animal model. On 08th July 2012, the animal was killed. Larvae were collected and raised to adulthood. Estimation of oviposition time was calculated by summing up average daily temperatures minus minimum development temperature (also specific to each species). When the sum is reached, it corresponds to the oviposition day. Weather data were obtained from the nearest meteorological station. After rearing was accomplished, three species emerged: Lucilia sericata, Chrysomya albiceps, and Sarcophaga africa. For Chrysomya albiceps species, a cumulation of 186°C is necessary. The emergence of adults occured on 22nd July 2012. A value of 193.4°C is reached on 9th August 2012. Lucilia sericata species require a cumulation of 207°C. The emergence of adults occurred on 23rd, July 2012. A value of 211.35°C is reached on 9th August 2012. We should also consider that oviposition may occur more than 12 hours after death. Thus, the obtained PMI is in agreement with the actual time of death. We illustrate the use of this method during the investigation of a case of a decaying human body found on 03rd March 2015 in Bechar, South West of Algerian desert. Maggots were collected and sent to the Laboratory of Entomology. Lucilia sericata adults were identified on 24th March 2015 after emergence. A sum of 211.6°C was reached on 1st March 2015 which corresponds to the estimated day of oviposition. Therefore, the estimated date of death is 1st March 2015 ± 24 hours. The estimated PMI by accumulated degree days (ADD) method seems to be very precise. Entomological evidence should always be used in homicide investigations when the time of death cannot be determined by other methods.

Keywords: forensic entomology, accumulated degree days, postmortem interval, diptera, Algeria

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Authors: Oksana Domkina

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According to the modern economic theory, human capital became one of the main production factors and the most promising direction of investment, as such investment provides opportunity of obtaining high and long-term economic and social effects. Informational technology (IT) sector is the representative of this new economy which is most dependent on human capital as the main competitive factor. So the question for this sector is not whether investment in development of personal should be made, but what are the most effective ways of executing it and who has to pay for the education: Worker, company or government. In this paper we examine the IT sector, describe the labor market of IT workers and its development, and analyze the risks that IT companies may face if they invest in the development of their workers and what factors influence it. The main problem and difficulty of quantitative estimation of risk of investment in human capital of a company and its forecasting is human factor. Human behavior is often unpredictable and complex, so it requires specific approaches and methods of assessment. To build a comprehensive method of estimation of the risk of investment in human capital of a company considering human factor, we decided to use the method of analytic hierarchy process (AHP), that initially was created and developed. We separated three main group of factors: Risks related to the worker, related to the company, and external factors. To receive data for our research, we conducted a survey among the HR departments of Ukrainian IT companies used them as experts for the AHP method. Received results showed that IT companies mostly invest in the development of their workers, although several hire only already qualified personnel. According to the results, the most significant risks are the risk of ineffective training and the risk of non-investment that are both related to the firm. The analysis of risk factors related to the employee showed that, the factors of personal reasons, motivation, and work performance have almost the same weights of importance. Regarding internal factors of the company, there is a high role of the factor of compensation and benefits, factors of interesting projects, team, and career opportunities. As for the external environment, one of the most dangerous factor of risk is competitor activities, meanwhile the political and economical situation factor also has a relatively high weight, which is easy to explain by the influence of severe crisis in Ukraine during 2014-2015. The presented method allows to take into consideration all main factors that affect the risk of investment in human capital of a company. This gives a base for further research in this field and allows for a creation of a practical framework for making decisions regarding the personnel development strategy and specific employees' development plans for the HR departments.

Keywords: risks, personnel development, investment in development, factors of risk, risk of investment in development, IT, analytic hierarchy process, AHP

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Authors: Daniil Karzanov

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This paper studies the effect of quarterly earnings reports on the stock price. The profitability of the stock is modeled by geometric Brownian diffusion and the Constant Elasticity of Variance model. We fit several variations of stochastic differential equations to the pre-and after-report period using the Maximum Likelihood Estimation and Grid Search of parameters method. By examining the change in the model parameters after reports’ publication, the study reveals that the reports have enough evidence to be a structural breakpoint, meaning that all the forecast models exploited are not applicable for forecasting and should be refitted shortly.

Keywords: stock market, earnings reports, financial time series, structural breaks, stochastic differential equations

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Authors: Yuanyuan Liu, Yuanqing Wang, Di Li

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Carbon dioxide (CO2) emissions mitigation from road construction activities is one of the potential pathways to deal with climate change due to its higher use of materials, machinery energy consumption, and high quantity of vehicle and equipment fuels for transportation and on-site construction activities. Aiming to assess the environmental impact of the road infrastructure construction activities and to identify hotspots of emissions sources, this study developed a life-cycle CO2 emissions assessment framework covering three stages of material production, to-site and on-site transportation under the guidance of the principle of LCA ISO14040. Then streamlined inventory analysis on sub-processes of each stage was conducted based on the budget files from cases of highway projects in China. The calculation results were normalized into functional unit represented as ton per km per lane. Then a comparison between the amount of emissions from each stage, and sub-process was made to identify the major contributor in the whole highway lifecycle. In addition, the calculating results were used to be compared with results in other countries for understanding the level of CO2 emissions associated with Chinese road infrastructure in the world. The results showed that materials production stage produces the most of the CO2 emissions (for more than 80%), and the production of cement and steel accounts for large quantities of carbon emissions. Life cycle CO2 emissions of fuel and electric energy associated with to-site and on-site transportation vehicle and equipment are a minor component of total life cycle CO2 emissions from highway project construction activities. Bridges and tunnels are dominant large carbon contributor compared to the road segments. The life cycle CO2 emissions of road segment in highway project in China are slightly higher than the estimation results of highways in European countries and USA, about 1500 ton per km per lane. In particularly, the life cycle CO2 emissions of road pavement in majority cities all over the world are about 500 ton per km per lane. However, there is obvious difference between the cities when the estimation on life cycle CO2 emissions of highway projects included bridge and tunnel. The findings of the study could offer decision makers a more comprehensive reference to understand the contribution of road infrastructure to climate change, especially understand the contribution from road infrastructure construction activities in China. In addition, the identified hotspots of emissions sources provide the insights of how to reduce road carbon emissions for development of sustainable transportation.

Keywords: carbon dioxide emissions, construction activities, highway, life cycle assessment

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Authors: Chia-Ling Li

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The scope of this article includes the production of 10,000 metric tons of non-phthalate per annum. The production process will include hydrogenation, separation, purification, and recycling of unprocessed feedstock. Based on experimental data, conversion and selectivity were chosen as reaction model parameters. The synthesis and separation processes of non-phthalate and phthalate were established by using Aspen Plus software. The article will be divided into six parts: estimation of physical properties, integration of production processes, purification case study, utility consumption, economic feasibility study and identification of bottlenecks. The purities of products was higher than 99.9 wt. %. Process parameters have important guiding significance to the commercialization of hydrogenation of phthalate.

Keywords: economic analysis, hydrogenation, non-phthalate, process simulation

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Authors: Mohammad A. Obeidat, Ayman M. Mansour

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Capturing the dynamic behavior of the heart to improve control performance, enhance robustness, and support diagnosis is very important in establishing real time models for the heart. Control Techniques and strategies have been utilized to improve system costs, reliability, and estimation accuracy for different types of systems such as biomedical, industrial, and other systems that required tuning input/output relation and/or monitoring. Simulations are performed to illustrate potential applications of the technology. In this research, a new control technology scheme is used to enhance the performance of the Af system and meet the design specifications.

Keywords: atrial fibrillation, dynamic behavior, closed loop, signal, filter

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Authors: Afroze Ibrahim Baqapuri, Ilya Trofimov

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Sponsored search is a multi-billion dollar industry and makes up a major source of revenue for search engines (SE). Click-through-rate (CTR) estimation plays a crucial role for ads selection, and greatly affects the SE revenue, advertiser traffic and user experience. We propose a novel architecture of solving CTR prediction problem by combining artificial neural networks (ANN) with decision trees. First, we compare ANN with respect to other popular machine learning models being used for this task. Then we go on to combine ANN with MatrixNet (proprietary implementation of boosted trees) and evaluate the performance of the system as a whole. The results show that our approach provides a significant improvement over existing models.

Keywords: neural networks, sponsored search, web advertisement, click prediction, click-through rate

Procedia PDF Downloads 572

Authors: Ruxandra Aursulesei, David O’Callaghan, Cian Ryan, Diarmaid O’Cualain, Viktor Varkarakis, Alina Sultana, Joseph Lemley

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Human errors caused by drowsiness are among the leading causes of road accidents. Neurobiological research gives information about the electrical signals emitted by neurons firing within the brain. Electrical signal frequencies can be determined by attaching bio-sensors to the head surface. By observing the electrical impulses and the rhythmic interaction of neurons with each other, we can predict the mental state of a person. In this paper, we aim to better understand intersubject and intrasubject variability in terms of electrophysiological patterns that occur at the onset of drowsiness and their evolution with the decreasing of vigilance. The purpose is to lay the foundations for an algorithm that detects the onset of drowsiness before the physical signs become apparent.

Keywords: electroencephalography, drowsiness, ADAS, annotations, clinician

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Authors: Akram Khaleghei, Ghosheh Balagh, Viliam Makis

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In this paper, we investigate the residual life prediction problem for a partially observable system subject to two failure modes, namely a catastrophic failure and a failure due to the system degradation. The system is subject to condition monitoring and the degradation process is described by a hidden Markov model with unknown parameters. The parameter estimation procedure based on an EM algorithm is developed and the formulas for the conditional reliability function and the mean residual life are derived, illustrated by a numerical example.

Keywords: partially observable system, hidden Markov model, competing risks, residual life prediction

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Authors: Ju-Hong Lee, Ching-Wei Liao

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An adaptive array beamformer is designed for automatically preserving the desired signals while cancelling interference and noise. Providing robustness against model mismatches and tracking possible environment changes calls for robust adaptive beamforming techniques. The design criterion yields the well-known generalized sidelobe canceller (GSC) beamformer. In practice, the knowledge of the desired steering vector can be imprecise, which often occurs due to estimation errors in the DOA of the desired signal or imperfect array calibration. In these situations, the SOI is considered as interference, and the performance of the GSC beamformer is known to degrade. This undesired behavior results in a reduction of the array output signal-to-interference plus-noise-ratio (SINR). Therefore, it is worth developing robust techniques to deal with the problem due to local scattering environments. As to the implementation of adaptive beamforming, the required computational complexity is enormous when the array beamformer is equipped with massive antenna array sensors. To alleviate this difficulty, a generalized sidelobe canceller (GSC) with partially adaptivity for less adaptive degrees of freedom and faster adaptive response has been proposed in the literature. Unfortunately, it has been shown that the conventional GSC-based adaptive beamformers are usually very sensitive to the mismatch problems due to local scattering situations. In this paper, we present an effective GSC-based beamformer against the mismatch problems mentioned above. The proposed GSC-based array beamformer adaptively estimates the actual direction of the desired signal by using the presumed steering vector and the received array data snapshots. We utilize the predefined steering vector and a presumed angle tolerance range to carry out the required estimation for obtaining an appropriate steering vector. A matrix associated with the direction vector of signal sources is first created. Then projection matrices related to the matrix are generated and are utilized to iteratively estimate the actual direction vector of the desired signal. As a result, the quiescent weight vector and the required signal blocking matrix required for performing adaptive beamforming can be easily found. By utilizing the proposed GSC-based beamformer, we find that the performance degradation due to the considered local scattering environments can be effectively mitigated. To further enhance the beamforming performance, a signal subspace projection matrix is also introduced into the proposed GSC-based beamformer. Several computer simulation examples show that the proposed GSC-based beamformer outperforms the existing robust techniques.

Keywords: adaptive antenna beamforming, local scattering, signal blocking, steering mismatch

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Authors: Farzaneh Khorram, Xavier Emery

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In this paper, it is aimed to create a crushing consumption energy (CCE) block model and determine the blocks with the potential to have the maximum grinding process energy consumption for the study area. For this purpose, a joint estimate (co-kriging) and joint simulation (turning band method and plurigaussian methods) to predict the CCE based on its correlation with SAG power index (SPI), A×B, and ball mill bond work Index (BWI). The analysis shows that TBCOSIM and plurigaussian have the more realistic results compared to cokriging. It seems logical due to the nature of the data geometallurgical and the linearity of the kriging method and the smoothing effect of kriging.

Keywords: plurigaussian, turning band, cokriging, geometallurgy

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Authors: Muzaffer Borekci, Murat Serdar Kirçil

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Predicting the collapse potential of a structure during earthquakes is an important issue in earthquake engineering. Many researchers proposed different methods to assess the collapse potential of structures under the effect of strong ground motions. However most of them did not consider degradation and softening effect in hysteretic behavior. In this study, collapse potential of SDOF systems caused by dynamic instability with stiffness and strength degradation has been investigated. An equation was proposed for the estimation of collapse period of SDOF system which is a limit value of period for dynamic instability. If period of the considered SDOF system is shorter than the collapse period then the relevant system exhibits dynamic instability and collapse occurs.

Keywords: collapse, degradation, dynamic instability, seismic response

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Authors: Sayyed Abdolmajid Jalaee Esfand Abadi, Sepideh Samimi

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Since one of the major difficulties to develop small manufacturing enterpriser in developing countries is the limitations of financing activities, this paper want to answer the question: “what is the role and status of micro finance in improving the labor productivity of small industries in Iran?” The results of panel data estimation show that micro finance in Iran has not yet been able to work efficiently and provide the required credit and investment. Also, reducing economy’s dependence on oil revenues reduced and increasing its reliance on domestic production and exports of industrial production can increase the productivity of workforce in Iranian small industries.

Keywords: microfinance, small manufacturing enterprises (SME), workforce productivity, Iran, panel data

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Authors: Cristian Patrascioiu, Loredana Negoita

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This paper is focused on modeling and simulation of the tubular heaters. The paper is structured in four parts: the structure of the tubular convection section, the heat transfer model, the adaptation of the mathematical model and the solving model. The main hypothesis of the heat transfer modeling is that the heat exchanger of the convective tubular heater is a lumped system. In the same time, the model uses the heat balance relations, Newton’s law and criteria relations. The numerical program achieved allows for the estimation of the burn gases outlet temperature and the heated flow outlet temperature.

Keywords: heat exchanger, mathematical modelling, nonlinear equation system, Newton-Raphson algorithm

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Authors: Karolína Vozková, Matěj Kuc

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This paper deals with the impact of decrease in interest rates on the performance of commercial and cooperative banks in the Eurozone measured by net interest margin. The analysis was performed on balanced dataset of 268 commercial and 726 cooperative banks spanning the 2008-2015 period. We employed Fixed Effects estimation panel method. As expected, we found a negative relationship between market rates and net interest margin. Our results suggest that the impact of negative interest income differs across individual banking business models. More precisely, those cooperative banks were much more hit by the decrease of market interest rates which might be due to their ownership structure and more restrictive business regulation.

Keywords: cooperative banks, performance, negative interest rates, risk management

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Authors: Jignasha Derasari, Patel Krishna M, Modi Jignasa G.

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Chemical stability of pharmaceutical molecules is a matter of great concern as it affects the safety and efficacy of the drug product.Stability testing data provides the basis to understand how the quality of a drug substance and drug product changes with time under the influence of various environmental factors. Besides this, it also helps in selecting proper formulation and package as well as providing proper storage conditions and shelf life, which is essential for regulatory documentation. The ICH guideline states that stress testing is intended to identify the likely degradation products which further help in determination of the intrinsic stability of the molecule and establishing degradation pathways, and to validate the stability indicating procedures. A simple, accurate and precise stability indicating RP- HPLC method was developed and validated for simultaneous estimation of Amiloride Hydrochloride and Furosemide in tablet dosage form. Separation was achieved on an Phenomenexluna ODS C18 (250 mm × 4.6 mm i.d., 5 µm particle size) by using a mobile phase consisting of Ortho phosphoric acid: Acetonitrile (50:50 %v/v) at a flow rate of 1.0 ml/min (pH 3.5 adjusted with 0.1 % TEA in Water) isocratic pump mode, Injection volume 20 µl and wavelength of detection was kept at 283 nm. Retention time for Amiloride Hydrochloride and Furosemide was 1.810 min and 4.269 min respectively. Linearity of the proposed method was obtained in the range of 40-60 µg/ml and 320-480 µg/ml and Correlation coefficient was 0.999 and 0.998 for Amiloride hydrochloride and Furosemide, respectively. Forced degradation study was carried out on combined dosage form with various stress conditions like hydrolysis (acid and base hydrolysis), oxidative and thermal conditions as per ICH guideline Q2 (R1). The RP- HPLC method has shown an adequate separation for Amiloride hydrochloride and Furosemide from its degradation products. Proposed method was validated as per ICH guidelines for specificity, linearity, accuracy; precision and robustness for estimation of Amiloride hydrochloride and Furosemide in commercially available tablet dosage form and results were found to be satisfactory and significant. The developed and validated stability indicating RP-HPLC method can be used successfully for marketed formulations. Forced degradation studies help in generating degradants in much shorter span of time, mostly a few weeks can be used to develop the stability indicating method which can be applied later for the analysis of samples generated from accelerated and long term stability studies. Further, kinetic study was also performed for different forced degradation parameters of the same combination, which help in determining order of reaction.

Keywords: amiloride hydrochloride, furosemide, kinetic study, stability indicating RP-HPLC method validation

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Authors: Yari Vecchio, Margherita Masi, Jorgelina Di Pasquale

Abstract:

Adoption of Precision Agriculture (PA) is involved in a multidimensional and complex scenario. The process of adopting innovations is complex and social inherently, influenced by other producers, change agents, social norms and organizational pressure. Complexity depends on factors that interact and influence the decision to adopt. Farm and operator characteristics, as well as organizational, informational and agro-ecological context directly affect adoption. This influence has been studied to measure drivers and to clarify 'bottlenecks' of the adoption of agricultural innovation. Making decision process involves a multistage procedure, in which individual passes from first hearing about the technology to final adoption. Awareness is the initial stage and represents the moment in which an individual learns about the existence of the technology. 'Static' concept of adoption has been overcome. Awareness is a precondition to adoption. This condition leads to not encountering some erroneous evaluations, arose from having carried out analysis on a population that is only in part aware of technologies. In support of this, the present study puts forward an empirical analysis among Italian farmers, considering awareness as a prerequisite for adoption. The purpose of the present work is to analyze both factors that affect the probability to adopt and determinants that drive an aware individual to not adopt. Data were collected through a questionnaire submitted in November 2017. A preliminary descriptive analysis has shown that high levels of adoption have been found among younger farmers, better educated, with high intensity of information, with large farm size and high labor-intensive, and whose perception of the complexity of adoption process is lower. The use of a logit model permits to appreciate the weight played by the intensity of labor and complexity perceived by the potential adopter in PA adoption process. All these findings suggest important policy implications: measures dedicated to promoting innovation will need to be more specific for each phase of this adoption process. Specifically, they should increase awareness of PA tools and foster dissemination of information to reduce the degree of perceived complexity of the adoption process. These implications are particularly important in Europe where is pre-announced the reform of Common Agricultural Policy, oriented to innovation. In this context, these implications suggest to the measures supporting innovation to consider the relationship between various organizational and structural dimensions of European agriculture and innovation approaches.

Keywords: adoption, awareness, complexity, precision agriculture

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Authors: Muhammad Ade Andriansyah Efendi, Ika Monika

Abstract:

Mini coal gasifier (GasMin) is a small reactor that could convert coal into combustible gas or producer gas which is designed to fulfill energy needs of small-scale industries. The producer gas can be utilized for both external and internal combustion. The design of coal gasifier is suitable for community require because it is easy to handle, affordable and environmentally friendly. The feasibility study shows that the substitution of 12 kg LPG or specially 50 kg LPG into GasMin of 20 kg coal capacity per hour is very attractive. The estimation price of 20 kg coal per hour capacity GasMin is 40 million rupiahs. In the year 2016, the implementation of GasMin conducted at alumunium industry and batik industry at Yogyakarta, Indonesia.

Keywords: biomass, coal, energy, gasification

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Authors: Baqir Khawari

Abstract:

This study critically examines the influence of remittances on household poverty and income inequality in Mazar-i-Sharif, Balkh Province, Afghanistan, utilizing robust OLS and Logit models with a rigorous multi-random sampling method. The empirical findings reveal that a 1% increase in per capita international remittances is associated with a substantial 0.071% and 0.059% rise in per capita income during the fiscal years 2019/20 and 2020/21, respectively. Furthermore, this increase significantly mitigates the per capita depth of poverty by 0.0272% and 0.025% and the severity of poverty by 0.0149% and 0.0145% over the same periods. Notably, the impact of international remittances on poverty alleviation surpasses that of internal remittances. In addressing income inequality, the analysis demonstrates that remittances contribute to a reduction in the Gini coefficient by 2% in 2019/20 and 7% in 2020/21, underscoring their pivotal role in promoting equitable economic distribution. However, the COVID-19 pandemic has posed significant challenges, diminishing remittance flows and, consequently, their positive effects on household welfare. The logistic regression results further corroborate these findings, indicating that increased per capita remittances, both international and internal, markedly decrease the likelihood of households falling below the poverty line. Specifically, a 1% rise in per capita external remittances reduces this likelihood by 4.5% in 2019/20 and by 3.7% in 2020/21, while internal remittances decrease it by 3% and 2.4%, respectively. The study also explores the demographic determinants of poverty. Larger household sizes and older household heads correlate positively with poverty, whereas higher education levels among household heads and members, and a greater proportion of male members, correlate negatively with poverty incidence and severity. Female-headed households are disproportionately affected by poverty, exacerbated by socio-cultural restrictions. Despite these adversities, the data suggest that remittances are a crucial instrument for poverty alleviation and income inequality reduction in Afghanistan. The findings advocate for policy interventions aimed at enhancing formal remittance channels, promoting education, and empowering women. Effective governance and sustained international assistance are essential to harness the full potential of remittances in combating poverty and inequality. This study highlights the need for strategic, multifaceted approaches to foster sustainable economic development in Afghanistan’s challenging socio-political context.

Keywords: migration, remittances, poverty, inequality, COVID-19, Afghanistan

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