Search results for: double robust estimation

Authors: Seyedeh Mandan Kazzazi, Elena Kranioti

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In the field of human osteology, sex estimation is an important step in developing biological profile. There are a number of methods that can be used to estimate the sex of human remains varying from visual assessments to metric analysis of sexually dimorphic traits. Teeth are one of the most durable physical elements in human body that can be used for this purpose. The present study investigated the utility of cervical measurements for sex estimation through discriminant analysis. The permanent molar teeth of 75 skeletons (28 females and 52 males) from Hasanlu site in North-western Iran were studied. Cervical mesiodistal and buccolingual measurements were taken from both maxillary and mandibular first and second molars. Discriminant analysis was used to evaluate the accuracy of each diameter in assessing sex. The results showed that males had statistically larger teeth than females for maxillary and mandibular molars and both measurements (P < 0.05). The range of classification rate was from (75.7% to 85.5%) for the original and cross-validated data. The most dimorphic teeth were maxillary and mandibular second molars providing 85.5% and 83.3% correct classification rate respectively. The data generated from the present study suggested that cervical mesiodistal and buccolingual measurements of the molar teeth can be useful and reliable for sex estimation in Iranian archaeological populations.

Keywords: cervical measurements, Hasanlu, premolars, sex estimation

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Authors: Manlika Ratchagit

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This paper is concerned with robust mean square stability of uncertain stochastic switched discrete time-delay systems. The system to be considered is subject to interval time-varying delays, which allows the delay to be a fast time-varying function and the lower bound is not restricted to zero. Based on the discrete Lyapunov functional, a switching rule for the robust mean square stability for the uncertain stochastic discrete time-delay system is designed via linear matrix inequalities. Finally, some examples are exploited to illustrate the effectiveness of the proposed schemes.

Keywords: robust mean square stability, discrete-time stochastic systems, hybrid systems, interval time-varying delays, Lyapunov functional, linear matrix inequalities

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Authors: Ammara Mehmood, Aneela Zameer, Muhammad Asif Zahoor Raja, Muhammad Faisal Fateh

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In this work, the strength of bio-inspired computational intelligence based technique is exploited for parameter estimation for the periodic signals using Continuous Differential Evolution (CDE) by defining an error function in the mean square sense. Multidimensional and nonlinear nature of the problem emerging in sinusoidal signal models along with noise makes it a challenging optimization task, which is dealt with robustness and effectiveness of CDE to ensure convergence and avoid trapping in local minima. In the proposed scheme of Continuous Differential Evolution based Signal Parameter Estimation (CDESPE), unknown adjustable weights of the signal system identification model are optimized utilizing CDE algorithm. The performance of CDESPE model is validated through statistics based various performance indices on a sufficiently large number of runs in terms of estimation error, mean squared error and Thiel’s inequality coefficient. Efficacy of CDESPE is examined by comparison with the actual parameters of the system, Genetic Algorithm based outcomes and from various deterministic approaches at different signal-to-noise ratio (SNR) levels.

Keywords: parameter estimation, bio-inspired computing, continuous differential evolution (CDE), periodic signals

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Authors: Manlika Rajchakit

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This paper is concerned with robust mean square stability of uncertain stochastic switched discrete time-delay systems. The system to be considered is subject to interval time-varying delays, which allows the delay to be a fast time-varying function and the lower bound is not restricted to zero. Based on the discrete Lyapunov functional, a switching rule for the robust mean square stability for the uncertain stochastic discrete time-delay system is designed via linear matrix inequalities. Finally, some examples are exploited to illustrate the effectiveness of the proposed schemes.

Keywords: robust mean square stability, discrete-time stochastic systems, hybrid systems, interval time-varying delays, lyapunov functional, linear matrix inequalities

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Authors: Md Al Masum Bhuiyan, Maria C. Mariani, Osei K. Tweneboah

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In the present work, we develop a technique for estimating the volatility of financial time series by using stochastic differential equation. Taking the daily closing prices from developed and emergent stock markets as the basis, we argue that the incorporation of stochastic volatility into the time-varying parameter estimation significantly improves the forecasting performance via Maximum Likelihood Estimation. While using the technique, we see the long-memory behavior of data sets and one-step-ahead-predicted log-volatility with ±2 standard errors despite the variation of the observed noise from a Normal mixture distribution, because the financial data studied is not fully Gaussian. Also, the Ornstein-Uhlenbeck process followed in this work simulates well the financial time series, which aligns our estimation algorithm with large data sets due to the fact that this algorithm has good convergence properties.

Keywords: financial time series, maximum likelihood estimation, Ornstein-Uhlenbeck type models, stochastic volatility model

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Authors: Daliyah S. Aljutaili, Redna A. Almutlaq, Suha A. Alharbi, Dina M. Ibrahim

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All currencies around the world look very different from each other. For instance, the size, color, and pattern of the paper are different. With the development of modern banking services, automatic methods for paper currency recognition become important in many applications like vending machines. One of the currency recognition architecture’s phases is Feature detection and description. There are many algorithms that are used for this phase, but they still have some disadvantages. This paper proposes a feature detection algorithm, which merges the advantages given in the current SIFT and SURF algorithms, which we call, Speeded up Robust Scale-Invariant Feature Transform (SR-SIFT) algorithm. Our proposed SR-SIFT algorithm overcomes the problems of both the SIFT and SURF algorithms. The proposed algorithm aims to speed up the SIFT feature detection algorithm and keep it robust. Simulation results demonstrate that the proposed SR-SIFT algorithm decreases the average response time, especially in small and minimum number of best key points, increases the distribution of the number of best key points on the surface of the currency. Furthermore, the proposed algorithm increases the accuracy of the true best point distribution inside the currency edge than the other two algorithms.

Keywords: currency recognition, feature detection and description, SIFT algorithm, SURF algorithm, speeded up and robust features

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Authors: Esra Zengin, Sinan Akkar

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Reliable and accurate prediction of nonlinear structural response requires specification of appropriate earthquake ground motions to be used in nonlinear time history analysis. The current research has mainly focused on selection and manipulation of real earthquake records that can be seen as the most critical step in the performance based seismic design and assessment of the structures. Utilizing amplitude scaled ground motions that matches with the target spectra is commonly used technique for the estimation of nonlinear structural response. Representative ground motion ensembles are selected to match target spectrum such as scenario-based spectrum derived from ground motion prediction equations, Uniform Hazard Spectrum (UHS), Conditional Mean Spectrum (CMS) or Conditional Spectrum (CS). Different sets of criteria exist among those developed methodologies to select and scale ground motions with the objective of obtaining robust estimation of the structural performance. This study presents ground motion selection and scaling procedure that considers the spectral variability at target demand with the level of ground motion dispersion. The proposed methodology provides a set of ground motions whose response spectra match target median and corresponding variance within a specified period interval. The efficient and simple algorithm is used to assemble the ground motion sets. The scaling stage is based on the minimization of the error between scaled median and the target spectra where the dispersion of the earthquake shaking is preserved along the period interval. The impact of the spectral variability on nonlinear response distribution is investigated at the level of inelastic single degree of freedom systems. In order to see the effect of different selection and scaling methodologies on fragility curve estimations, results are compared with those obtained by CMS-based scaling methodology. The variability in fragility curves due to the consideration of dispersion in ground motion selection process is also examined.

Keywords: ground motion selection, scaling, uncertainty, fragility curve

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Authors: Liu Bijin

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Floating breakwaters have several advantages, including being environmentally friendly, easy to construct, and cost-effective regardless of water depth. They have a broad range of applications in coastal engineering. However, they face significant challenges due to the unstable effect of wave dissipation, structural vulnerability, and high mooring system requirements. This paper investigates the wave dissipation performance of a floating breakwater structure. The structure consists of double cylinders, double vertical plates, and horizontal connecting plates. The investigation is carried out using physical model tests and numerical simulation methods based on STAR-CCM+. This paper discusses the impact of wave elements, relative vertical plate heights, and relative horizontal connecting plate widths on the wave dissipation performance of the double-cylinder, double-plate floating breakwater (DCDPFB). The study also analyses the changes in local vorticity and velocity fields around the DCDPFB to determine the optimal structural dimensions. The study found that the relative width of the horizontal connecting plate, the relative height of the vertical plate, and the size of the semi-cylinder are the key factors affecting the wave dissipation performance of the DCDPFB. The transmittance coefficient is minimally affected by the wave height and the depth of water entry. The local vortex and velocity field formed around the DCDPFB are important factors for dissipating wave energy. The test section of the DCDPFB, constructed according to the relative optimal structural dimensions, showed good wave dissipation performance during offshore prototype tests. The test section of DCDPFB, constructed with optimal structural dimensions, exhibits excellent wave dissipation performance in offshore prototype tests.

Keywords: floating breakwater, wave dissipation performance, transmittance coefficient, model test

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Authors: Lassaad Smirani

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In this paper we propose a Neurosymbolic Learning System (NLS) as a channel estimator for Long Term Evolution Advanced (LTE-A) uplink. The proposed system main idea based on Neural Network has modules capable of performing bidirectional information transfer between symbolic module and connectionist module. We demonstrate various strengths of the NLS especially the ability to integrate theoretical knowledge (rules) and experiential knowledge (examples), and to make an initial knowledge base (rules) converted into a connectionist network. Also to use empirical knowledge witch by learning will have the ability to revise the theoretical knowledge and acquire new one and explain it, and finally the ability to improve the performance of symbolic or connectionist systems. Compared with conventional SC-FDMA channel estimation systems, The performance of NLS in terms of complexity and quality is confirmed by theoretical analysis and simulation and shows that this system can make the channel estimation accuracy improved and bit error rate decreased.

Keywords: channel estimation, SC-FDMA, neural network, hybrid system, BER, LTE-A

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Authors: Hasik Lee, Seung-Young Kho

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Nowadays, automatic fare collection (AFC) system is widely used in many countries. However, smart card data from many of cities does not contain alighting information which is necessary to build OD matrices. Therefore, in order to utilize smart card data, destinations of passengers should be estimated. In this paper, kernel density estimation was used to forecast probabilities of alighting stations of bus passengers and applied to smart card data in Seoul, Korea which contains boarding and alighting information. This method was also validated with actual data. In some cases, stochastic method was more accurate than deterministic method. Therefore, it is sufficiently accurate to be used to build OD matrices.

Keywords: destination estimation, Kernel density estimation, smart card data, validation

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Authors: Sandeep Reddy, Sonia Allan, Simon Coghlan, Paul Cooper

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Artificial Intelligence (AI) and its application in medicine has generated ample interest amongst policymakers and clinicians. Successes with AI in medical imaging interpretation and clinical decision support are paving the way for its incorporation into routine healthcare delivery. While there has been a focus on the development of ethical principles to guide its application in healthcare, challenges of this application go beyond what ethics principles can address thus requiring robust governance frameworks. Also, while ethical challenges of medical artificial intelligence are being discussed, the ethics of deploying AI in lower-income countries receive less attention than in other developed economies. This creates an imperative not only for sound ethical guidelines but also for robust governance frameworks to regulate AI in medicine around the world. In this article, we discuss what components need to be considered in developing these governance frameworks and who should lead this worldwide effort.

Keywords: artificial intelligence, global health, governance, ethics

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Authors: Kalu Ram Meena, Aditi Kar Gangopadhyay, Satrajit Mandal

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Two normal populations with different means and same variance are considered, where the variances are known. The population with the smaller sample mean is selected. Various estimators are constructed for the mean of the selected normal population. Finally, they are compared with respect to the bias and MSE risks by the method of Monte-Carlo simulation and their performances are analysed with the help of graphs.

Keywords: estimation after selection, Brewster-Zidek technique, estimators, selected populations

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Authors: Xiaowei Zhang, Min Xu, Saeid Habibi, Fengjun Yan, Ryan Ahmed

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Recently, Electric Vehicles (EVs) have received extensive consideration since they offer a more sustainable and greener transportation alternative compared to fossil-fuel propelled vehicles. Lithium-Ion (Li-ion) batteries are increasingly being deployed in EVs because of their high energy density, high cell-level voltage, and low rate of self-discharge. Since Li-ion batteries represent the most expensive component in the EV powertrain, accurate monitoring and control strategies must be executed to ensure their prolonged lifespan. The Battery Management System (BMS) has to accurately estimate parameters such as the battery State-of-Charge (SOC), State-of-Health (SOH), and Remaining Useful Life (RUL). In order for the BMS to estimate these parameters, an accurate and control-oriented battery model has to work collaboratively with a robust state and parameter estimation strategy. Since battery physical parameters, such as the internal resistance and diffusion coefficient change depending on the battery state-of-life (SOL), the BMS has to be adaptive to accommodate for this change. In this paper, an extensive battery aging study has been conducted over 12-months period on 5.4 Ah, 3.7 V Lithium polymer cells. Instead of using fixed charging/discharging aging cycles at fixed C-rate, a set of real-world driving scenarios have been used to age the cells. The test has been interrupted every 5% capacity degradation by a set of reference performance tests to assess the battery degradation and track model parameters. As battery ages, the combined model parameters are optimized and tracked in an offline mode over the entire batteries lifespan. Based on the optimized model, a state and parameter estimation strategy based on the Extended Kalman Filter (EKF) and the relatively new Smooth Variable Structure Filter (SVSF) have been applied to estimate the SOC at various states of life.

Keywords: lithium-ion batteries, genetic algorithm optimization, battery aging test, parameter identification

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Authors: Ludovic Fabre, Paola Melani, Patrick Lemaire

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The goal of this study was to test whether and how emotions influence drone operators in estimation skills. The empirical study was run in the context of numerical estimation. Participants saw a two-digit number together with a collection of cars. They had to indicate whether the stimuli collection was larger or smaller than the number. The two-digit numbers ranged from 12 to 27, and collections included 3-36 cars. The presentation of the collections was dynamic (each car moved 30 deg. per second on the right). Half the collections were smaller collections (including fewer than 20 cars), and the other collections were larger collections (i.e., more than 20 cars). Splits between the number of cars in a collection and the two-digit number were either small (± 1 or 2 units; e.g., the collection included 17 cars and the two-digit number was 19) or larger (± 8 or 9 units; e.g., 17 cars and '9'). Half the collections included more items (and half fewer items) than the number indicated by the two-digit number. Before and after each trial, participants saw an image inducing negative emotions (e.g., mutilations) or neutral emotions (e.g., candle) selected from International Affective Picture System (IAPS). At the end of each trial, participants had to say if the second picture was the same as or different from the first. Results showed different effects of emotions on RTs and percent errors. Participants’ performance was modulated by emotions. They were slower on negative trials compared to the neutral trials, especially on the most difficult items. They errored more on small-split than on large-split problems. Moreover, participants highly overestimated the number of cars when in a negative emotional state. These findings suggest that emotions influence numerical estimation, that effects of emotion in estimation interact with stimuli characteristics. They have important implications for understanding the role of emotions on estimation skills, and more generally, on how emotions influence cognition.

Keywords: drone operators, emotion, numerical estimation, arithmetic

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Authors: Mikiyas Adugna

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Effort estimation is among the activities carried out in software development processes. An accurate model of estimation leads to project success. The method of agile effort estimation is a complex task because of the dynamic nature of software development. Researchers are still conducting studies on agile effort estimation to enhance prediction accuracy. Due to these reasons, we investigated and proposed a model on LASSO and Elastic Net regression to enhance estimation accuracy. The proposed model has major components: preprocessing, train-test split, training with default parameters, and cross-validation. During the preprocessing phase, the entire dataset is normalized. After normalization, a train-test split is performed on the dataset, setting training at 80% and testing set to 20%. We chose two different phases for training the two algorithms (Elastic Net and LASSO) regression following the train-test-split. In the first phase, the two algorithms are trained using their default parameters and evaluated on the testing data. In the second phase, the grid search technique (the grid is used to search for tuning and select optimum parameters) and 5-fold cross-validation to get the final trained model. Finally, the final trained model is evaluated using the testing set. The experimental work is applied to the agile story point dataset of 21 software projects collected from six firms. The results show that both Elastic Net and LASSO regression outperformed the compared ones. Compared to the proposed algorithms, LASSO regression achieved better predictive performance and has acquired PRED (8%) and PRED (25%) results of 100.0, MMRE of 0.0491, MMER of 0.0551, MdMRE of 0.0593, MdMER of 0.063, and MSE of 0.0007. The result implies LASSO regression algorithm trained model is the most acceptable, and higher estimation performance exists in the literature.

Keywords: agile software development, effort estimation, elastic net regression, LASSO

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Authors: Yong Ren, Yaping Zhang

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A numerical model has been developed to investigate the thermally triggered release kinetics for drug delivery using phase change material as shell of microcapsules. Biocompatible material n-Eicosane is used as demonstration. PCM shell of microcapsule will remain in solid form after the drug is taken, so the drug will be encapsulated by the shell, and will not be released until the target body part of lesion is exposed to external heat source, which will thermally trigger the release kinetics, leading to solid-to-liquid phase change. The findings can lead to better understanding on the key effects influencing the phase change process for drug delivery applications. The facile approach to release drug from core/shell structure of microcapsule can be well integrated with organic solvent free fabrication of microcapsules, using double emulsion as template in microfluidic aqueous two phase system.

Keywords: phase change material, drug release kinetics, double emulsion, microfluidics

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Authors: Mohamed Raouf Benmakrelouf, Joseph Rynkiewicz

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Targeted maximum likelihood estimation (TMLE) is well-established method for causal effect estimation with desirable statistical properties. TMLE is a doubly robust maximum likelihood based approach that includes a secondary targeting step that optimizes the target statistical parameter. A causal interpretation of the statistical parameter requires assumptions of the Rubin causal framework. The causal effect of binary variable, E, on outcomes, Y, is defined in terms of comparisons between two potential outcomes as E[YE=1 − YE=0]. Our aim in this paper is to present an adaptation of TMLE methodology to estimate the causal effect of a non-binary categorical variable, providing a large application. We propose coding on the initial data in order to operate a binarization of the interest variable. For each category, we get a transformation of the non-binary interest variable into a binary variable, taking value 1 to indicate the presence of category (or group of categories) for an individual, 0 otherwise. Such a dummy variable makes it possible to have a pair of potential outcomes and oppose a category (or a group of categories) to another category (or a group of categories). Let E be a non-binary interest variable. We propose a complete disjunctive coding of our variable E. We transform the initial variable to obtain a set of binary vectors (dummy variables), E = (Ee : e ∈ {1, ..., |E|}), where each vector (variable), Ee, takes the value of 0 when its category is not present, and the value of 1 when its category is present, which allows to compute a pairwise-TMLE comparing difference in the outcome between one category and all remaining categories. In order to illustrate the application of our strategy, first, we present the implementation of TMLE to estimate the causal effect of non-binary variable on outcome using simulated data. Secondly, we apply our TMLE adaptation to survey data from the French Political Barometer (CEVIPOF), to estimate the causal effect of education level (A five-level variable) on a potential vote in favor of the French extreme right candidate Jean-Marie Le Pen. Counterfactual reasoning requires us to consider some causal questions (additional causal assumptions). Leading to different coding of E, as a set of binary vectors, E = (Ee : e ∈ {2, ..., |E|}), where each vector (variable), Ee, takes the value of 0 when the first category (reference category) is present, and the value of 1 when its category is present, which allows to apply a pairwise-TMLE comparing difference in the outcome between the first level (fixed) and each remaining level. We confirmed that the increase in the level of education decreases the voting rate for the extreme right party.

Keywords: statistical inference, causal inference, super learning, targeted maximum likelihood estimation

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Authors: Damian Janecki, Anna Jaskólska, Jarosław Marusiak, Artur Jaskólski

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The aim of this study was to assess double to single twitch ratio after two bouts of eccentric exercise of the elbow flexors. Maximal isometric torque, single and double twitch responses and low-frequency fatigue were assessed on the elbow flexors in 19 untrained male volunteers before, immediately after, 24 and 48 hours following two bouts of eccentric exercise consisted of 30 repetitions of lowering a dumbbell adjusted to ~75% of each individual's maximal isometric torque. Maximal isometric torque and electrically evoked responses decreased significantly in all measurements after the first bout of eccentric exercise (P<0.05). In measurements performed at 24 and 48 hours after the second bout both maximal voluntary isometric torque and electrically evoked contractions were significantly higher than in measurements performed after the fist bout (P<0.05). Although low-frequency fatigue significantly increased up to 48 hours after each bout of eccentric exercise, its values at 24 and 48 hours after the second bout were significantly lower than at respective time points after the first bout (P<0.05). Smaller changes in double to single twitch ratio at 24 and 48 hours after the second bout of eccentric exercise reflects repeated bout effect that confers protection against subsequent exercise-induced muscle damage.

Keywords: biceps brachii, electrical stimulation, lenghtening contractions, repeated bout effect

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Authors: Kuen-Ming Shu, Jyun-Wei Chen

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Encapsulated O-rings are specifically designed to address the problem of sealing the most hostile chemicals and extreme temperature applications. Ultrasonic vibration hot embossing and ultrasonic welding techniques provide a fast and reliable method to fabricate encapsulated O-ring. This paper performs the design and analysis method of the acoustic horns with double extrusion to process tube double side flange simultaneously. The paper deals with study through Finite Element Method (FEM) of ultrasonic stepped horn used to process a capsulated O-ring, the theoretical dimensions of horns, and their natural frequencies and amplitudes are obtained through the simulations of COMOSOL software. Furthermore, real horns were fabricated, tested and verified to proof the practical utility of these horns.

Keywords: encapsulated O-rings, ultrasonic vibration hot embossing, flange making, acoustic horn, finite element analysis

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Authors: Md. Danish Eqbal, Venkat Gundabala

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Microparticles and microcapsules are basically used as a carrier for cells, tissues, drugs, and chemicals. Due to its biocompatibility, non-toxicity and biodegradability, alginate based microparticles have numerous applications in drug delivery, tissue engineering, organ repair and transplantation, etc. The production of uniform monodispersed microparticles was a challenge for the past few decades. However, emergence of microfluidics has provided controlled methods for the generation of the uniform monodispersed microparticles. In this work, we present a successful method for the generation of both microparticles and microcapsules (single and double core) using merging approach of two droplets, completely inside the microfluidic device. We have fabricated hybrid glass- PDMS (polydimethylsiloxane) based microfluidic device which has coflow geometry as well as the T junction channel. Coflow is used to generate the single as well as double oil-alginate emulsion in oil and T junction helps to form the calcium chloride droplets in oil. The basic idea is to match the frequency of the alginate droplets and calcium chloride droplets perfectly for controlled generation. Using the merging of droplets technique, we have successfully generated the microparticles and the microcapsules having single core as well as double and multiple cores. The cores in the microcapsules are very stable, well separated from each other and very intact as seen through cross-sectional confocal images. The size and the number of the cores along with the thickness of the shell can be easily controlled by controlling the flowrate of the liquids.

Keywords: double-core, droplets, microcapsules, microparticles

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Authors: Wararit Panichkitkosolkul

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The unit root tests based on the robust estimator for the first-order autoregressive process are proposed and compared with the unit root tests based on the ordinary least squares (OLS) estimator. The percentiles of the null distributions of the unit root test are also reported. The empirical probabilities of Type I error and powers of the unit root tests are estimated via Monte Carlo simulation. Simulation results show that all unit root tests can control the probability of Type I error for all situations. The empirical power of the unit root tests based on the robust estimator are higher than the unit root tests based on the OLS estimator.

Keywords: autoregressive, ordinary least squares, type i error, power of the test, Monte Carlo simulation

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Authors: David Ross Cameron

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In an attempt to alleviate the educational planning problem, double-shift schools have been created throughout various regions in Jordan, namely communities closer to the Syrian border, where a large portion of the refugee population settled, allowing Jordanians to attend the morning-shift and Syrians to attend the afternoon-shift. Subsequently, overcrowded classrooms have added a significant amount of stress on school facilities and teacher capacities. Established national policies and the implementation of inclusive educational practices have been jeopardized. In particular, teachers’ and student’s attitudes of the importance of inclusive education provisions in the classroom have deteriorated. To have a more comprehensive understanding of the current situation and possible plan for intervention, a focus study was carried out at a double-shift Jordanian/Syrian girls’ public school in Irbid, Jordan. Interviews and surveys of 29 students with physical, learning, emotional and behavioral disabilities, 33 students without any special needs and nine teachers were included with a mixed-method social research approach to highlight the current attitudes that students and teachers held and factors that contributed to shaping their inclinations and beliefs of inclusive education.

Keywords: capacity building, development, double-shift, Irbid, inclusive education, Jordan, pedagogy, planning, policy, refugee, special education, special needs, vulnerable population

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Authors: K. Ebrahimi, Sh. Shahid, M. Mohammadi Ghaleni, M. H. Omid

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The longitudinal dispersion coefficient is a crucial parameter for 1-D water quality analysis of riverine flows. So far, different types of empirical equations for estimation of the coefficient have been developed, based on various case studies. The main objective of this paper is to develop an empirical equation for estimation of the coefficient for a riverine flow. For this purpose, a set of tracer experiments was conducted, involving salt tracer, at three sections located in downstream of a lengthy canal. Tracer data were measured in three mixing lengths along the canal including; 45, 75 and 100m. According to the results, the obtained coefficients from new developed empirical equation gave an encouraging level of agreement with the theoretical values.

Keywords: coefficients, dispersion, river, tracer, water quality

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Authors: S. M. Kulkarni, D. S. Bormane, S. L. Nalbalwar

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The rapid development in the technology have dramatic impact on the medical health care field. Medical data base obtained with latest machines like CT Machine, MRI scanner requires large amount of memory storage and also it requires large bandwidth for transmission of data in telemedicine applications. Thus, there is need for video compression. As the database of medical images contain number of frames (slices), hence while coding of these images there is need of motion estimation. Motion estimation finds out movement of objects in an image sequence and gets motion vectors which represents estimated motion of object in the frame. In order to reduce temporal redundancy between successive frames of video sequence, motion compensation is preformed. In this paper three step search (TSS) block matching algorithm is implemented on different types of video sequences. It is shown that three step search algorithm produces better quality performance and less computational time compared with exhaustive full search algorithm.

Keywords: block matching, exhaustive search motion estimation, three step search, video compression

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Authors: R. Rama Kishore, Sunesh

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Nowadays, robust and secure watermarking algorithm and its optimization have been need of the hour. A watermarking algorithm is presented to achieve the copy right protection of the owner based on visual cryptography, histogram shape property and entropy. In this, both host image and watermark are preprocessed. Host image is preprocessed by using Butterworth filter, and watermark is with visual cryptography. Applying visual cryptography on water mark generates two shares. One share is used for embedding the watermark, and the other one is used for solving any dispute with the aid of trusted authority. Usage of histogram shape makes the process more robust against geometric and signal processing attacks. The combination of visual cryptography, Butterworth filter, histogram, and entropy can make the algorithm more robust, imperceptible, and copy right protection of the owner.

Keywords: digital watermarking, visual cryptography, histogram, butter worth filter

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Authors: Felix Aberu

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The high rate of greenhouse gas (CO₂) emission and increased concentration of Carbon Dioxide in the atmosphere are not unconnected to both human and natural activities. This has caused climate change and global warming in the world. The adverse effect of these climatic changes has no doubt threatened human existence. Hence, this study examined the effects of environmental and climate influence on mortality and morbidity rates, with particular reference to the world’s leading CO₂ emission countries, using both the pre-estimation, estimation, and post-estimation techniques for more dependable outcomes. Hence, the System Generalized Method of Moments (SGMM) was adopted as the main estimation technique for the data analysis from 1996 to 2023. The coefficient of carbon emissions confirmed a positive and significant relationship among CO₂ emission, mortality, and morbidity rates in the world’s leading CO₂ emissions countries, which implies that carbon emission has contributed to mortality and morbidity rates in the world. Therefore, significant action should be taken to facilitate the expansion of environmental protection and sustainability initiatives in any CO₂ emissions nations of the world.

Keywords: environmental, mortality, morbidity, health outcomes, carbon emissions

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Authors: Nataša Todorović, Jovana Nikolov

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Despite the great interest in β⁻β⁻ decay, β⁺β⁺ decays are rarely investigated due to the low probability of detecting these processes with available low-level equipment. If β⁺β⁺, β⁺EC, or ECEC decay occurs in a thin sample of a material, the positrons will be stopped and annihilated inside the material, leading to the emission of two or four coincidence gamma photons energy of 511 keV. The paper presents the results of measurements of double beta decay of ⁶⁴Zn, ⁵⁰Cr, and ⁵⁴Fe isotopes. In the first experiment, 511-keV gamma rays originating from the annihilation of positrons in natural zinc were measured by a coincidence technique to obtain a non-zero value for the (0ν+2ν) half-life. In the second experiment, the result of measuring double beta decay of ⁵⁰Cr is presented, which suggests a result other than zero at 95% CL and gives the lowest limit for the half-life of this process. In the third experiment, neutrino-less ECEC decay of ⁵⁴Fe was examined. Under the decay theory, gamma rays are emitted whose energy does not coincide with the energies of gamma rays emitted by nuclei from known discrete excited states. Iron shield of an internal volume of 1 m³ and thickness of 25 cm served as a source for measuring the (0ν+2ν) process in ⁵⁴Fe, whose yield in natural iron is 5.4%. We obtain the lower limit for the half-life for ⁵⁴Fe: T(0ν, K, K)>4.4x10²⁰ yr, T(0ν, K, L)>4.1x10²⁰ yr, and T(0ν, L, L)>5.0x10²⁰ yr. For ⁵⁰Cr limit for the half-life is T(0ν+2ν)>1.3(6)x10¹⁸ yr, and for ⁶⁴Zn T(0ν+2ν, ECβ+)=1.1(0.9)x10⁹ years.

Keywords: neutrinoless double beta decay, half-life, ⁶⁴Zn, ⁵⁰Cr, and, ⁵⁴Fe

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Authors: Norazam Arbin, Habibis Saleh, Ammar Alsabery, Ishak Hashim

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Double-diffusive natural convection in an open top cavity with partial vertical heating and salting sources is investigated numerically. Different temperatures and concentrations are applied at the source location on the right and left walls while the other remains adiabatic except at the open top surface. Various combinations of sources arrangements are imposed at the vertical walls in order to observe the significant impact to the convection. An iterative finite different method is used to solve the dimensionless governing equations. The effects of Marangoni number and sources arrangements on the contours of streamlines, isotherms, and concentrations are visualized as the outcome of the numerical solutions. The average Nusselt and Sherwood number are presented for various sources arrangements. It is clearly observed that the sources arrangements gave major impact on the heat and mass transfer rates. A horizontal-like pattern is found for sources arrangements that near the top-free surface.

Keywords: double-diffusive, Marangoni effect, partial heating, salting

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Authors: Ahmed H. Amer, A. Amar, Sh. Hamada, I. I. Bondouk, F. A. El-Hussiny

Abstract:

Elastic scattering of α-particles from 9Be and 11B nuclei at different alpha energies have been analyzed. Optical model parameters (OMPs) of α-particles elastic scattering by these nuclei at different energies have been obtained. In the present calculations, the real part of the optical potential are derived by folding of nucleon-nucleon (NN) interaction into nuclear matter density distribution of the projectile and target nuclei using computer code FRESCO. A density-dependent version of the M3Y interaction (CDM3Y6), which is based on the G-matrix elements of the Paris NN potential, has been used. Volumetric integrals of the real and imaginary potential depth (JR, JW) have been calculated and found to be energy dependent. Good agreement between the experimental data and the theoretical predictions in the whole angular range. In double folding (DF) calculations, the obtained normalization coefficient Nr is in the range 0.70–1.32.

Keywords: elastic scattering, optical model, double folding model, density distribution

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Authors: Sheam-Chyun Lin, Wei-Kai Chen, Hung-Cheng Yen, Yung-Jen Cheng, Yu-Cheng Chen

Abstract:

Result from the constant dwindle in natural resources, the alternative way to reduce the costs in our daily life would be urgent to be found in the near future. As the ancient technique based on the theory of solar chimney since roman times, the double-skin façade are simply composed of two large glass panels in purpose of daylighting and also natural ventilation in the daytime. Double-skin façade is generally installed on the exterior side of buildings as function as the window, so there’s always a huge amount of passive solar energy the façade would receive to induce the airflow every sunny day. Therefore this article imposes a domestic double-skin window for residential usage and attempts to improve the volume flow rate inside the cavity between the panels by the frame geometry design, the installation of outlet guide plate and the solar energy collection system. Note that the numerical analyses are applied to investigate the characteristics of flow field, and the boundary conditions in the simulation are totally based on the practical experiment of the original prototype. Then we redesign the prototype from the knowledge of the numerical results and fluid dynamic theory, and later the experiments of modified prototype will be conducted to verify the simulation results. The velocities at the inlet of each case are increase by 5%, 45% and 15% from the experimental data, and also the numerical simulation results reported 20% improvement in volume flow rate both for the frame geometry design and installation of outlet guide plate.

Keywords: solar energy, double-skin façades, thermal buoyancy, fluid machinery

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