Search results for: sequential confidence estimation

Authors: So-Young Ju, Sung-Mi Jo, Eui-Rim Jeong

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In this paper, based on the conventional single carrier frequency domain equalization (SC-FDE) structure, we propose a new SC-FDE structure to cope with narrowband jammer. In the conventional SC-FDE structure, channel estimation is performed in the time domain. When a narrowband jammer exists, time-domain channel estimation is very difficult due to high power jamming interference, which degrades receiver performance. To relieve from this problem, a new SC-FDE frame is proposed to enable channel estimation under narrow band jamming environments. In this paper, we proposed a modified SC-FDE structure that can perform channel estimation in the frequency domain and verified the performance via computer simulation.

Keywords: channel estimation, jammer, pilot, SC-FDE

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Authors: Nigel P. Coutts, Stellina Z. Sim

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Research suggests that the pedagogy we utilize when teaching mathematics contributes to a negative attitude towards the discipline. Worried by this, we have explored teaching mathematics for understanding, fluency, and confidence. We investigated strategies to engage students with the beauty of mathematics, moving them beyond mimicry and memorization. The result is an integrated pedagogy and curriculum arrangement which combines concept-based mathematics with Number Talks, Visible Thinking Routines, and Teaching for Understanding. Our qualitative research shows that students self-report greater self-confidence and heightened engagement with mathematical thinking. Teacher reflections on student learning echo this finding. As a result of this, we advocate for teacher training in the implementation of a concept-based curriculum supplemented with Number Talk strategies.

Keywords: mathematical thinking, teaching for understanding, student confidence, concept-based learning, engagement

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Authors: Mohammad H. Almomani

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In this paper, we argue the effect of the initial sample size, and the increment in simulation samples on the performance of a sequential approach that used in selecting the top m designs when the number of alternative designs is very large. The sequential approach consists of two stages. In the first stage the ordinal optimization is used to select a subset that overlaps with the set of actual best k% designs with high probability. Then in the second stage the optimal computing budget is used to select the top m designs from the selected subset. We apply the selection approach on a generic example under some parameter settings, with a different choice of initial sample size and the increment in simulation samples, to explore the impacts on the performance of this approach. The results show that the choice of initial sample size and the increment in simulation samples does affect the performance of a selection approach.

Keywords: Large Scale Problems, Optimal Computing Budget Allocation, ordinal optimization, simulation optimization

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Authors: Hongkui Li, Tongli Lu , Jianwu Zhang

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This paper focuses on developing an estimation method of clutch drag torque in wet DCT. The modelling of clutch drag torque is investigated. As the main factor affecting the clutch drag torque, dynamic viscosity of oil is discussed. The paper proposes an estimation method of clutch drag torque based on recursive least squares by utilizing the dynamic equations of gear shifting synchronization process. The results demonstrate that the estimation method has good accuracy and efficiency.

Keywords: clutch drag torque, wet DCT, dynamic viscosity, recursive least squares

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Authors: Arun Sanjel, Greg Speegle

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Every second, massive amounts of data are generated, and Data Intensive Scalable Computing (DISC) frameworks have evolved into effective tools for analyzing such massive amounts of data. Since the underlying architecture of these distributed computing platforms is often new to users, building a DISC application can often be time-consuming and prone to errors. The automated conversion of a sequential program to a DISC program will consequently significantly improve productivity. However, synthesizing a user’s intended program from an input specification is complex, with several important applications, such as distributed program synthesizing and code refactoring. Existing works such as Tyro and Casper rely entirely on deductive synthesis techniques or similar program synthesis approaches. Our approach is to develop a data-driven synthesis technique to identify sequential components and translate them to equivalent distributed operations. We emphasize using reinforcement learning and unit testing as feedback mechanisms to achieve our objectives.

Keywords: program synthesis, distributed computing, reinforcement learning, unit testing, DISC

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Authors: Napat Hataivichian

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The effect of transition metal doping on Pt/Al2O3 catalyst used in propane dehydrogenation reaction at 500˚C was studied. The preparation methods investigated were sequential impregnation (Pt followed by the 2nd metal or the 2nd metal followed by Pt) and co-impregnation. The metal contents of these catalysts were fixed as the weight ratio of Pt per the 2nd metal of around 0.075. These catalysts were characterized by N2-physisorption, TPR, CO-chemisorption and NH3-TPD. It was found that the impregnated 2nd metal had an effect upon reducibility of Pt due to its interaction with transition metal-containing structure. This was in agreement with the CO-chemisorption result that the presence of Pt metal, which is a result from Pt species reduction, was decreased. The total acidity of bimetallic catalysts is decreased but the strong acidity is slightly increased. It was found that the stability of bimetallic catalysts prepared by co-impregnation and sequential impregnation where the 2nd metal was impregnated before Pt were better than that of monometallic catalyst (undoped Pt one) due to the forming of Pt sites located on the transition metal-oxide modified surface. Among all preparation methods, the sequential impregnation method- having Pt impregnated before the 2nd metal gave the worst stability because this catalyst lacked the modified Pt sites and some fraction of Pt sites was covered by the 2nd metal.

Keywords: alumina, dehydrogenation, platinum, transition metal

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Authors: Canan Duzan

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For most language learners, mastery of the speaking skill is the proof of the mastery of the foreign language. On the other hand, the speaking skill is considered as the most difficult aspect of language learning to develop for both learners and teachers. Especially in countries like Turkey where exposure to the target language is minimum and resources and opportunities provided for language practice are scarce, teaching and learning to speak the language become a real struggle for teachers and learners alike. Data collected from students, instructors, faculty members and the business sector in needs analysis studies conducted previously at Middle East Technical University (METU) consistently revealed the need for addressing the problem of lack of confidence in speaking English. Action was taken during the design of the only EAP speaking course offered in Modern Languages Department since lack of confidence is considered to be a serious barrier for effective communication and causes learners to suffer from insecurity, uncertainty and fear. “Confidence building” served as the guiding principle in the syllabus design, nature of the tasks created for the course and the assessment procedures to help learners become more confident speakers of English. In order to see the effectiveness of the decisions made during the design phase of the course and whether students become more confident speakers upon completion of the course, a case study was carried out with 100 students at METU. A questionnaire including both Likert-Scale and open-ended items were administered to students to collect data and this data were analyzed using the SPSS program. Group interviews were also carried out to gain more insight into the effectiveness of the course in terms of building speaking confidence. This presentation will explore the specific actions taken to develop students’ confidence based on the findings of program evaluation studies and to what extent the students believe these actions to be effective in improving their confidence. The unique design of this course and strategies adopted for confidence building are highly applicable in other EAP contexts and may yield similar positive results.

Keywords: confidence, EAP, speaking, strategy

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Authors: Patricia Heredia, Isabel Saz, Marta Fernández

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This article proposes that the decision regarding exporting and the choice of export channel are nested and non-independent decisions. We assume that firms make two sequential decisions before arriving at their final choice: the decision to access foreign markets and the decision about the type of channel. This hierarchical perspective of the choices involved in the process is appealing for two reasons. First, it supports the idea that people have a limited analytical capacity. Managers often break down a complex decision into a hierarchical process because this makes it more manageable. Secondly, it recognizes that important differences exist between entry modes. In light of the above, the objective of this study is to test different entry mode choice processes: independent decisions and nested and non-independent decisions. To do this, the methodology estimates and compares the following two models: (i) a simultaneous single-stage model with three entry mode choices (using a multinomial logit model); ii) a two-stage model with the export decision preceding the channel decision using a sequential logit model. The study uses resource-based factors in determining these decision processes concerning internationalization and the study carries out empirical analysis using a DOC Rioja sample of 177 firms.Using the Akaike and Schwarz Information Criteria, the empirical evidence supports the existence of a nested structure, where the decision about exporting precedes the export mode decision. The implications and contributions of the findings are discussed.

Keywords: sequential logit model, two-stage choice process, export mode, wine industry

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Authors: Callie Mady

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This study investigated the Canadian French as an additional language teacher candidates’ confidence and language maintenance strategies by means of questionnaires and interviews pre- and post- a Francophone home-stay practicum experience. Teacher French language proficiency is one of the components of teacher knowledge that can influence students’ French as an additional language acquisition. Although advantageous, seeking opportunities to use French in a French milieu comes with challenges. Teachers, for example, have been found to be hesitant to speak French with native speakers for fear of judgment. Another identified challenge to spending time in a French milieu is finances; while teachers have recognized the value of such an experience, cost is prohibitive. In recognition of the potential barriers and the need to maintain/improve the French proficiency of 'French as an additional language' teachers, this study provided a two-week home stay in a Francophone environment for teacher candidates of French as an additional language with financial subsidies for their participation. Through the post-experience interviews, the French as an additional language teacher candidates revealed an improvement in French proficiency. Similarly, the teacher candidates cited an increase in confidence in the interviews and through the questionnaire. They linked this increase in proficiency and confidence to their experiences with their host families and other Francophone members of the community. This study highlights the provision of immersion experiences as means to support teachers’ language confidence and proficiency.

Keywords: French as an additional language education, teacher language confidence, teacher language maintenance, teacher language proficiency

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Authors: Felipe Haro, Soheila Antar

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This paper introduces a custom optimization experiment developed in AnyLogic, based on genetic algorithms, designed to ensure reliable optimization results by incorporating Montecarlo simulations and achieving a specified confidence level. To validate the custom experiment, we compared its performance with AnyLogic's built-in OptQuest optimization method across three distinct problems. Statistical analyses, including Welch's t-test, were conducted to assess the differences in performance. The results demonstrate that while the custom experiment shows advantages in certain scenarios, both methods perform comparably in others, confirming the custom approach as a reliable and effective tool for optimization under uncertainty.

Keywords: optimization, confidence intervals, Montecarlo simulation, optQuest, AnyLogic

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Authors: Somayeh Komeylian

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The direction of arrival (DoA) estimation is the crucial aspect of the radar technologies for detecting and dividing several signal sources. In this scenario, the antenna array output modeling involves numerous parameters including noise samples, signal waveform, signal directions, signal number, and signal to noise ratio (SNR), and thereby the methods of the DoA estimation rely heavily on the generalization characteristic for establishing a large number of the training data sets. Hence, we have analogously represented the two different optimization models of the DoA estimation; (1) the implementation of the decision directed acyclic graph (DDAG) for the multiclass least-squares support vector machine (LS-SVM), and (2) the optimization method of the deep neural network (DNN) radial basis function (RBF). We have rigorously verified that the LS-SVM DDAG algorithm is capable of accurately classifying DoAs for the three classes. However, the accuracy and robustness of the DoA estimation are still highly sensitive to technological imperfections of the antenna arrays such as non-ideal array design and manufacture, array implementation, mutual coupling effect, and background radiation and thereby the method may fail in representing high precision for the DoA estimation. Therefore, this work has a further contribution on developing the DNN-RBF model for the DoA estimation for overcoming the limitations of the non-parametric and data-driven methods in terms of array imperfection and generalization. The numerical results of implementing the DNN-RBF model have confirmed the better performance of the DoA estimation compared with the LS-SVM algorithm. Consequently, we have analogously evaluated the performance of utilizing the two aforementioned optimization methods for the DoA estimation using the concept of the mean squared error (MSE).

Keywords: DoA estimation, Adaptive antenna array, Deep Neural Network, LS-SVM optimization model, Radial basis function, and MSE

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Authors: Archana Rao R., Deepak P., Chayashree P. D., Darshan H. S.

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Cognitive abilities in bilinguals have been widely studied over the last few decades. Bilingualism has been found to extensively facilitate the ability to store and manipulate information in Working Memory (WM). The mechanism of WM includes primary memory, attentional control, and secondary memory, each of which makes a contribution to WM. Many researches have been done in an attempt to measure WM capabilities through both verbal (phonological) and nonverbal tasks (visuospatial). Since there is a lot of speculations regarding the relationship between WM and bilingualism, further investigation is required to understand the nature of WM in bilinguals, i.e., with respect to sequential and simultaneous bilinguals. Hence the present study aimed to highlight the verbal working memory abilities in sequential and simultaneous bilinguals with respect to the processing and recall abilities of nouns and verbs. Two groups of bilinguals aged between 18-30 years were considered for the study. Group 1 consisted of 20 (10 males and 10 females) sequential bilinguals who had acquired L1 (Kannada) before the age of 3 and had exposure to L2 (English) for a period of 8-10 years. Group 2 consisted of 20 (10 males and 10 females) simultaneous bilinguals who have acquired both L1 and L2 before the age of 3. Working memory abilities were assessed using two tasks, and a set of stimuli which was presented in gradation of complexity and the stimuli was inclusive of frequent and infrequent nouns and verbs. The tasks involved the participants to judge the correctness of the sentence and simultaneously remember the last word of each sentence and the participants are instructed to recall the words at the end of each set. The results indicated no significant difference between sequential and simultaneous bilinguals in processing the nouns and verbs, and this could be attributed to the proficiency level of the participants in L1 and the alike cognitive abilities between the groups. And recall of nouns was better compared to verbs, maybe because of the complex argument structure involved in verbs. Similarly, authors found a frequency of occurrence of nouns and verbs also had an effect on WM abilities. The difference was also found across gradation due to the load imposed on the central executive function and phonological loop.

Keywords: bilinguals, nouns, verbs, working memory

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Authors: Seda Yavuz, Anıl Çelebi, Aysun Taşyapı Çelebi, Oğuzhan Urhan

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Nowadays, demand for using real-time video transmission capable devices is ever-increasing. So, high resolution videos have made efficient video compression techniques an essential component for capturing and transmitting video data. Motion estimation has a critical role in encoding raw video. Hence, various motion estimation methods are introduced to efficiently compress the video. Low bit‑depth representation based motion estimation methods facilitate computation of matching criteria and thus, provide small hardware footprint. In this paper, a hardware implementation of a two-bit transformation based low-complexity motion estimation method using local binary pattern approach is proposed. Image frames are represented in two-bit depth instead of full-depth by making use of the local binary pattern as a binarization approach and the binarization part of the hardware architecture is explained in detail. Experimental results demonstrate the difference between the proposed hardware architecture and the architectures of well-known low-complexity motion estimation methods in terms of important aspects such as resource utilization, energy and power consumption.

Keywords: binarization, hardware architecture, local binary pattern, motion estimation, two-bit transform

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Authors: Ana Staneva, Vessela Stoimenova

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A parametric estimation of the MBP with Power Series offspring distribution family is considered in this paper. The MLE for the parameters is obtained in the case when the observable data are incomplete and consist only with the generation sizes of the family tree of MBP. The parameter estimation is calculated by using the Monte Carlo EM algorithm. The estimation for the posterior distribution and for the offspring distribution parameters are calculated by using the Bayesian approach and the Gibbs sampler. The article proposes various examples with bivariate branching processes together with computational results, simulation and an implementation using R.

Keywords: Bayesian, branching processes, EM algorithm, Gibbs sampler, Monte Carlo methods, statistical estimation

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Authors: Xiang Jia, Zhijun Cheng

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The residual lifetime of a product is the operation time between the current time and the time point when the failure happens. The residual lifetime estimation is rather important in reliability analysis. To predict the residual lifetime, it is necessary to assume or verify a particular distribution that the lifetime of the product follows. And the two-parameter Weibull distribution is frequently adopted to describe the lifetime in reliability engineering. Due to the time constraint and cost reduction, a life testing experiment is usually terminated before all the units have failed. Then the censored data is usually collected. In addition, other information could also be obtained for reliability analysis. The expert judgements are considered as it is common that the experts could present some useful information concerning the reliability. Therefore, the residual lifetime is estimated for Weibull distribution by fusing the censored data and expert judgements in this paper. First, the closed-forms concerning the point estimate and confidence interval for the residual lifetime under the Weibull distribution are both presented. Next, the expert judgements are regarded as the prior information and how to determine the prior distribution of Weibull parameters is developed. For completeness, the cases that there is only one, and there are more than two expert judgements are both focused on. Further, the posterior distribution of Weibull parameters is derived. Considering that it is difficult to derive the posterior distribution of residual lifetime, a sample-based method is proposed to generate the posterior samples of Weibull parameters based on the Monte Carlo Markov Chain (MCMC) method. And these samples are used to obtain the Bayes estimation and credible interval for the residual lifetime. Finally, an illustrative example is discussed to show the application. It demonstrates that the proposed method is rather simple, satisfactory, and robust.

Keywords: expert judgements, information fusion, residual lifetime, Weibull distribution

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Authors: Aman Sharma, Sonali Sengupta

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The study explores the utility of Bayesian optimization in tuning the physical and chemical parameters of reactions in an offline experimental setup. A comparative analysis of the influence of the acquisition function on the optimization performance is also studied. For proxy first and second-order reactions, the results are indifferent to the acquisition function used, whereas, while studying the parameters for oxidative desulphurization of thiophene in an offline setup, upper confidence bound (UCB) provides faster convergence along with a marginal trade-off in the maximum conversion achieved. The work also demarcates the critical number of independent parameters and input observations required for both sequential and offline reaction setups to yield tangible results.

Keywords: acquisition function, Bayesian optimization, desulfurization, kinetics, thiophene

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Authors: Yi-Chuan Cheng, Li-Chi Huang, Yu-Shan Chang

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Introduction: The main purpose of this study was to explore the relationship between the learning number, care knowledge, care skills and maternal confidence in preterm infant care in Taiwan. Background: Preterm infants care has been stressful for mother caring at home. Many programs have been applied for improving the infant care maternal confident. But less to know the learning behavior in mothers of preterm infant. Methods: The sample consisted of 55 mothers with preterm infants were recruited in a neonatal intermediate unit at a medical center in central Taiwan. The self-reported questionnaires including knowledge and skills of preterm infant care scales and maternal confidence scale were used to evaluation, which were conducted during hospitalization, before hospital discharge, and one month after discharge. We performed by using Pearson correlation of the collected data using SPSS 18. Results: The study showed that the learning number and knowledge in preterm infant care was a significant positive correlation (r = .40), and the skills and confidence preterm infant care was positively correlated (r = .89). Conclusions: Study results showed the mother had more learning number in preterm infant care will be stronger knowledge, and the skills and confidence in preterm infant care were also positively correlated. Thus, we found the learning behavior change significant care knowledge. And the maternal confidence change significant with skill on preterm infant’s care. But bondage still needs further study and develop the participation in hospital-based instructional programs, which could lead to greater long-term retention of learning.

Keywords: learning behavior, care knowledge, care skills, maternal confidence

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Authors: Phong Nguyen, Phap Nguyen, Thang Nguyen

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High Efficiency Video Coding (HEVC) or H.265 Standard fulfills the demand of high resolution video storage and transmission since it achieves high compression ratio. However, it requires a huge amount of calculation. Since Motion Estimation (ME) block composes about 80 % of calculation load of HEVC, there are a lot of researches to reduce the computation cost. In this paper, we propose a new algorithm to lower the number of Motion Estimation’s searching points. The number of computing points in search pattern is down from 77 for Diamond Pattern and 81 for Square Pattern to only 31. Meanwhile, the Peak Signal to Noise Ratio (PSNR) and bit rate are almost equal to those of conventional patterns. The motion estimation time of new algorithm reduces by at 68.23%, 65.83%compared to the recommended search pattern of diamond pattern, square pattern, respectively.

Keywords: motion estimation, wide diamond, search pattern, H.265, test zone search, HM software

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Authors: Ing-Jen Hung, Tzu-Chien Wang

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Nowadays, customers can interact with firms through miscellaneous online ads on different channels easily. In other words, customer now has innumerable options and limitless time to accomplish their commercial activities with firms, individualizing their own online customer journey. This kind of convenience emphasizes the importance of online advertisement allocation on different channels. Therefore, profound understanding of customer behavior can make considerable benefit from optimizing fund allocation on diverse ad channels. To achieve this objective, multiple firms utilize numerical methodology to create data-driven advertisement policy. In our research, we aim to exploit online customer click data to discover the correlations between each channel and their sequential relations. We use LSTM to deal with sequential property of our data and compare its accuracy with other non-sequential methods, such as CART decision tree, logistic regression, etc. Besides, we also classify our customers into several groups by their behavioral characteristics to perceive the differences between all groups as customer portrait. As a result, we discover distinct customer journey under each customer portrait. Our article provides some insights into marketing research and can help firm to formulate online advertising criteria.

Keywords: LSTM, customer journey, marketing, channel ads

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Authors: Chin-Yun Chen

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Numerical integration is an essential tool for deriving different physical quantities in engineering and science. The effectiveness of a numerical integrator depends on different factors, where the crucial one is the error estimation. This work presents an error estimator that combines a derivative free method to improve the performance of verified numerical quadrature.

Keywords: numerical quadrature, error estimation, derivative free method, interval computation

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Authors: Y. T. Lee, J. H. Na, S. H. Kim, S. U. Hong

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In this study, an experimental research for estimation of slab depth, column size and location of rebar of concrete specimen is conducted using the Impact Echo Method (IE) based on stress wave among non-destructive test methods. Estimation of slab depth had total length of 1800×300 and 6 different depths including 150 mm, 180 mm, 210 mm, 240 mm, 270 mm and 300 mm. The concrete column specimen was manufactured by differentiating the size into 300×300×300 mm, 400×400×400 mm and 500×500×500 mm. In case of the specimen for estimation of rebar, rebar of ∅22 mm was used in a specimen of 300×370×200 and arranged at 130 mm and 150 mm from the top to the rebar top. As a result of error rate of slab depth was overall mean of 3.1%. Error rate of column size was overall mean of 1.7%. Mean error rate of rebar location was 1.72% for top, 1.19% for bottom and 1.5% for overall mean showing relative accuracy.

Keywords: impact echo method, estimation, slab depth, column size, rebar location, concrete

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Authors: Christian Meinecke, Bernd Scholz-Reiter

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The integrated problem of production and distribution scheduling is relevant in many industrial applications. Thus, many heuristics to solve this integrated problem have been developed in the last decade. Most of these heuristics use a sequential working principal or a single decomposition and integration approach to separate and solve sub-problems. A heuristic using a multi-step decomposition and integration approach is presented in this paper and evaluated in a case study. The result show significant improved results compared with sequential scheduling heuristics.

Keywords: production and outbound distribution, integrated planning, heuristic, decomposition, integration

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Authors: Cleto J. Sauer Jr., Rita C. Sauer, Chaider G. Andrade, Dóris F. Rabelo

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Some patients with COVID-19 disease and difficult airway characteristics undergo to endotracheal intubation (ETI) procedure. The tracheal introducer, known as the bougie guide, can aid ETI in patients with difficult airway pattern. Realistic simulation (RS) is a methodology utilized for healthcare professionals training. To improve skills in using the bougie guide of physicians from Recôncavo da Bahia region in Brazil, during COVID-19 outbreak, RS training was carried out. Simulated scenario included the Nasco Lifeform realistic simulator for ETI and a bougie guide introducer. Training was a capacitation program organized by the Health Department of Bahia State. Objective: To report effects in participants´ self-confidence perception for using bougie guide after a RS based training. Methods: Descriptive study, secondary data extracted from questionnaires. Priority workplace and previous knowledge about bougie were reported on a preparticipation formulary. Participants also completed pre- and post-training qualitative self-assessment (10-point Likert scale) regarding to self-confidence in using bougie guide. Distribution analysis for qualitative data was performed with Wilcoxon Signed Rank Test, and self-confidence increase analysis in frequency contingency tables with Fisher's exact test. Results: From May to June 2020 a total of 36 physicians participated of training, 25 (69%) from primary care setting, 32 (89%) with no previous knowledge about the bougie guide utilization. For those who had previous knowledge about bougie pre-training self-confidence median was 6,5, and 2 for participants who had not. In overall there was an increase in self-confidence median for bougie utilization. Median (variation) before and after training was 2.5 (1-7) vs. 8 (4-10) (p <0.0001). Among those who had no previous knowledge about bougie (n = 32) an increase in self-confidence greater than 3 points for bougie utilization was reported by 31 vs. 1 participants (p = 0.71). Conclusions: Most of participants had no previous knowledge about using the bougie guide. RS training contributed to self-confidence increase for using bougie for ETI procedure. RS methodology can contribute for training in using the bougie guide for ETI procedure during COVID-19 outbreak.

Keywords: bougie, confidence, COVID-19, endotracheal intubation, realistic simulation

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Authors: Hao Chen, Bo Guo, Ping Jiang

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Residual life (RL) estimation based on multi-phase nonlinear Wiener process was studied in this paper, which is significant for complicated products with small samples. Firstly, nonlinear Wiener model with random parameter was introduced and multi-phase nonlinear Wiener model was proposed to model degradation process of products that were nonlinear and separated into different phases. Then the multi-phase RL probability density function based on the presented model was derived approximately in a closed form and parameters estimation was achieved with the method of maximum likelihood estimation (MLE). Finally, the method was applied to estimate the RL of high voltage plus capacitor. Compared with the other three different models by log-likelihood function (Log-LF) and Akaike information criterion (AIC), the results show that the proposed degradation model can capture degradation process of high voltage plus capacitors in a better way and provide a more reliable result.

Keywords: multi-phase nonlinear wiener process, residual life estimation, maximum likelihood estimation, high voltage plus capacitor

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

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This work is devoted to the study of modeling geophysical time series. A stochastic technique with time-varying parameters is used to forecast the volatility of data arising in geophysics. In this study, the volatility is defined as a logarithmic first-order autoregressive process. We observe that the inclusion of log-volatility into the time-varying parameter estimation significantly improves forecasting which is facilitated via maximum likelihood estimation. This allows us to conclude that the estimation algorithm for the corresponding one-step-ahead suggested volatility (with ±2 standard prediction errors) is very feasible since it possesses good convergence properties.

Keywords: Augmented Dickey Fuller Test, geophysical time series, maximum likelihood estimation, stochastic volatility model

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Authors: Jianyong Xue, Olivier L. Georgeon, Salima Hassas

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During the initial phase of cognitive development, infants exhibit amazing abilities to generate novel behaviors in unfamiliar situations, and explore actively to learn the best while lacking extrinsic rewards from the environment. These abilities set them apart from even the most advanced autonomous robots. This work seeks to contribute to understand and replicate some of these abilities. We propose the Bottom-up hiErarchical sequential Learning algorithm with Constructivist pAradigm (BEL-CA) to design agents capable of learning autonomously and continuously through interactions. The algorithm implements no assumption about the semantics of input and output data. It does not rely upon a model of the world given a priori in the form of a set of states and transitions as well. Besides, we propose a toolkit to analyze the learning process at run time called GAIT (Generating and Analyzing Interaction Traces). We use GAIT to report and explain the detailed learning process and the structured behaviors that the agent has learned on each decision making. We report an experiment in which the agent learned to successfully interact with its environment and to avoid unfavorable interactions using regularities discovered through interaction.

Keywords: cognitive development, constructivist learning, hierarchical sequential learning, self-adaptation

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Authors: I. Gahlouz, A. Chellil

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The paper concerns the estimation of system components faults by using an unknown inputs observer. To reach this goal, we used the Bond Graph approach to physical modelling. We showed that this graphical tool is allowing the representation of system components faults as unknown inputs within the state representation of the considered physical system. The study of the causal and structural features of the system (controllability, observability, finite structure, and infinite structure) based on the Bond Graph approach was hence fulfilled in order to design an unknown inputs observer which is used for the system component fault estimation.

Keywords: estimation, bond graph, controllability, observability

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Authors: Navid Daryasafar, Nima Farshidfar

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In this article, we make attempt to hide error in video with an emphasis on the time-wise use of autoregressive (AR) models. To resolve this problem, we assume that all information in one or more video frames is lost. Then, lost frames are estimated using analogous Pixels time information in successive frames. Accordingly, after presenting autoregressive models and how they are applied to estimate lost frames, two general methods are presented for using these models. The first method which is the same standard method of autoregressive models estimates lost frame in unidirectional form. Usually, in such condition, previous frames information is used for estimating lost frame. Yet, in the second method, information from the previous and next frames is used for estimating the lost frame. As a result, this method is known as bidirectional estimation. Then, carrying out a series of tests, performance of each method is assessed in different modes. And, results are compared.

Keywords: error steganography, unidirectional estimation, bidirectional estimation, AR linear estimation

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Authors: Nurbanu Guzey, S. Jagannathan

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Locating radio controlled (RC) devices using their unintended emissions has a great interest considering security concerns. Weak nature of these emissions requires near field localization approach since it is hard to detect these signals in far field region of array. Instead of only angle estimation, near field localization also requires range estimation of the source which makes this method more complicated than far field models. Challenges of locating such devices in a near field region and real time environment are analyzed in this paper. An ESPRIT like near field localization scheme is utilized for both angle and range estimation. 1-D search with symmetric subarrays is provided. Two 7 element uniform linear antenna arrays (ULA) are employed for locating RC source. Experiment results of location estimation for one unintended emitting walkie-talkie for different positions are given.

Keywords: localization, angle of arrival (AoA), range estimation, array signal processing, ESPRIT, Uniform Linear Array (ULA)

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Authors: Cleto J. Sauer Jr., Rita C. Sauer, Chaider G. Andrade, Doris F. Rabelo

Abstract:

Introduction: Endotracheal Intubation (ETI) is a procedure for clinical management of patients with severe clinical presentation of COVID-19 disease. Realistic simulation (RS) is an active learning methodology utilized for clinical skill's improvement. To improve ETI skills of public health network's physicians from Recôncavo da Bahia region in Brazil, during COVID-19 outbreak, RS training was planned and carried out. Training scenario included the Nasco Lifeform realistic simulator, and three actions were simulated: ETI procedure, sedative drugs management, and bougie guide utilization. Training intervention occurred between May and June 2020, as an interinstitutional cooperation between the Health's Department of Bahia State and the Federal University from Recôncavo da Bahia. Objective: The main objective is to report the effects on participants' self-confidence perception for ETI procedure after RS based training. Methods: This is a descriptive study, with secondary data extracted from questionnaires applied throughout RS training. Priority workplace, time from last intubation, and knowledge about bougie were reported on a preparticipation questionnaire. Additionally, participants completed pre- and post-training qualitative self-assessment (10-point Likert scale) regarding self-confidence perception in performing each of simulated actions. Distribution analysis for qualitative data was performed with Wilcoxon Signed Rank Test, and self-confidence increase analysis in frequency contingency tables with Fisher's Exact Test. Results: 36 physicians participated of training, 25 (69%) from primary care setting, 25 (69%) performed ETI over a year ago, and only 4 (11%) had previous knowledge about the bougie guide utilization. There was an increase in self-confidence medians for all three simulated actions. Medians (variation) for self-confidence before and after training, for each simulated action were as follows: ETI [5 (1-9) vs. 8 (6-10) (p < 0.0001)]; Sedative drug management [5 (1-9) vs. 8 (4-10) (p < 0.0001)]; Bougie guide utilization [2.5 (1-7) vs. 8 (4-10) (p < 0.0001)]. Among those who performed ETI over a year ago (n = 25), an increase in self-confidence greater than 3 points for ETI was reported by 23 vs. 2 physicians (p = 0.0002), and by 21 vs. 4 (p = 0.03) for sedative drugs management. Conclusions: RS training contributed to self-confidence increase in performing ETI. Among participants who performed ETI over a year, there was a significant association between RS training and increase of more than 3 points in self-confidence, both for ETI and sedative drug management. Training with RS methodology is suitable for ETI confidence enhancement during COVID-19 outbreak.

Keywords: confidence, COVID-19, endotracheal intubation, realistic simulation

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