Search results for: error analysis

Authors: Dileep Kumar Gupta, Rajendra Prasad, Pradeep Kumar, Varun Narayan Mishra, Ajeet Kumar Vishwakarma, Prashant K. Srivastava

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An approach was evaluated for the retrieval of soil moisture of bare soil surface using bistatic scatterometer data in the angular range of 200 to 700 at VV- and HH- polarization. The microwave data was acquired by specially designed X-band (10 GHz) bistatic scatterometer. The linear regression analysis was done between scattering coefficients and soil moisture content to select the suitable incidence angle for retrieval of soil moisture content. The 250 incidence angle was found more suitable. The support vector regression analysis was used to approximate the function described by the input-output relationship between the scattering coefficient and corresponding measured values of the soil moisture content. The performance of support vector regression algorithm was evaluated by comparing the observed and the estimated soil moisture content by statistical performance indices %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE). The values of %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were found 2.9451, 1.0986, and 0.9214, respectively at HH-polarization. At VV- polarization, the values of %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were found 3.6186, 0.9373, and 0.9428, respectively.

Keywords: bistatic scatterometer, soil moisture, support vector regression, RMSE, %Bias, NSE

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Authors: Benson Ade Eniola Afere

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Over the years, kernel density estimation has been extensively studied within the context of nonparametric density estimation. The fundamental components of kernel density estimation are the kernel function and the bandwidth. While the mathematical exploration of the kernel component has been relatively limited, its selection and development remain crucial. The Mean Integrated Squared Error (MISE), serving as a measure of discrepancy, provides a robust framework for assessing the effectiveness of any kernel function. A kernel function with a lower MISE is generally considered to perform better than one with a higher MISE. Hence, the primary aim of this article is to create kernels that exhibit significantly reduced MISE when compared to existing classical kernels. Consequently, this article introduces a cluster of hybrid polynomial kernel families. The construction of these proposed kernel functions is carried out heuristically by combining two kernels from the classical polynomial kernel family using probability axioms. We delve into the analysis of error propagation within these kernels. To assess their performance, simulation experiments, and real-life datasets are employed. The obtained results demonstrate that the proposed hybrid kernels surpass their classical kernel counterparts in terms of performance.

Keywords: classical polynomial kernels, cluster of families, global error, hybrid Kernels, Kernel density estimation, Monte Carlo simulation

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Authors: Jularat Chumnaul

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In forensic science, corpses from various homicides are different; there are both complete and incomplete, depending on causes of death or forms of homicide. For example, some corpses are cut into pieces, some are camouflaged by dumping into the river, some are buried, some are burned to destroy the evidence, and others. If the corpses are incomplete, it can lead to the difficulty of personally identifying because some tissues and bones are destroyed. To specify gender of the corpses from skeletal remains, the most precise method is DNA identification. However, this method is costly and takes longer so that other identification techniques are used instead. The first technique that is widely used is considering the features of bones. In general, an evidence from the corpses such as some pieces of bones, especially the skull and pelvis can be used to identify their gender. To use this technique, forensic scientists are required observation skills in order to classify the difference between male and female bones. Although this technique is uncomplicated, saving time and cost, and the forensic scientists can fairly accurately determine gender by using this technique (apparently an accuracy rate of 90% or more), the crucial disadvantage is there are only some positions of skeleton that can be used to specify gender such as supraorbital ridge, nuchal crest, temporal lobe, mandible, and chin. Therefore, the skeletal remains that will be used have to be complete. The other technique that is widely used for gender specifying in forensic science and archeology is skeletal measurements. The advantage of this method is it can be used in several positions in one piece of bones, and it can be used even if the bones are not complete. In this study, the classification and cluster analysis are applied to this technique, including the Kth Nearest Neighbor Classification, Classification Tree, Ward Linkage Cluster, K-mean Cluster, and Two Step Cluster. The data contains 507 particular individuals and 9 skeletal measurements (diameter measurements), and the performance of five methods are investigated by considering the apparent error rate (APER). The results from this study indicate that the Two Step Cluster and Kth Nearest Neighbor method seem to be suitable to specify gender from human skeletal remains because both yield small apparent error rate of 0.20% and 4.14%, respectively. On the other hand, the Classification Tree, Ward Linkage Cluster, and K-mean Cluster method are not appropriate since they yield large apparent error rate of 10.65%, 10.65%, and 16.37%, respectively. However, there are other ways to evaluate the performance of classification such as an estimate of the error rate using the holdout procedure or misclassification costs, and the difference methods can make the different conclusions.

Keywords: skeletal measurements, classification, cluster, apparent error rate

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Authors: D. Vidhyaprakash, A. Elango

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In real-time applications, wheeled mobile robots are increasingly used and operated in extreme and diverse conditions traversing challenging surfaces such as a pitted, uneven terrain, natural flat, smooth terrain, as well as wet and dry surfaces. In order to accomplish such tasks, it is critical that the motion control functions without wheel slip and odometry error during the navigation of the two-wheeled mobile robot (WMR). Wheel slip and odometry error are disrupting factors on overall WMR performance in the form of deviation from desired trajectory, navigation, travel time and budgeted energy consumption. The wheeled mobile robot’s ability to operate at peak performance on various work surfaces without wheel slippage and odometry error is directly connected to four main parameters, which are the range of payload distribution, speed, wheel diameter, and wheel width. This paper analyses the effects of those parameters on overall performance and is concerned with determining the ideal range of parameters for optimum performance.

Keywords: wheeled mobile robot, terrain, wheel slippage, odometryerror, trajectory

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Authors: John Gaber, Youssef Ahmed, Hossam A. Gabbar, Jing Ren

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Accidents at Nuclear Power Plants (NPPs) occur due to various factors, notable among them being poor safety management and poor safety culture. During abnormal situations, the likelihood of human error is many-fold higher due to the higher cognitive workload. The most common cause of human error and high cognitive workload is mental fatigue. Electroencephalography (EEG) is a method of gathering the electromagnetic waves emitted by a human brain. We propose a safety system by monitoring brainwaves for signs of mental fatigue using an EEG system. This requires an analysis of the mental model of the NPP operator, changes in brain wave power in response to certain stimuli, and the risk factors on mental fatigue and attention that NPP operators face when performing their tasks. We analyzed these factors and developed an EEG-based monitoring system, which aims to alert NPP operators when levels of mental fatigue and attention hinders their ability to maintain safety.

Keywords: brain imaging, EEG, power plant operator, psychology

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Authors: Yi-Hsiu Lai

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The present study aimed to elucidate the lexical-semantic processing for Chinese as second language (CSL) learners. Twenty L1 speakers of Chinese and twenty CSL learners in Taiwan participated in a picture naming task and a category fluency task. Based on their Chinese proficiency levels, these CSL learners were further divided into two sub-groups: ten CSL learners of elementary Chinese proficiency level and ten CSL learners of intermediate Chinese proficiency level. Instruments for the naming task were sixty black-and-white pictures: thirty-five object pictures and twenty-five action pictures. Object pictures were divided into two categories: living objects and non-living objects. Action pictures were composed of two categories: action verbs and process verbs. As in the naming task, the category fluency task consisted of two semantic categories – objects (i.e., living and non-living objects) and actions (i.e., action and process verbs). Participants were asked to report as many items within a category as possible in one minute. Oral productions were tape-recorded and transcribed for further analysis. Both error types and error frequency were calculated. Statistical analysis was further conducted to examine these error types and frequency made by CSL learners. Additionally, category effects, pictorial effects and L2 proficiency were discussed. Findings in the present study helped characterize the lexical-semantic process of Chinese naming in CSL learners of different Chinese proficiency levels and made contributions to Chinese vocabulary teaching and learning in the future.

Keywords: lexical-semantic processing, Mandarin Chinese, naming, category effects

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Authors: Nilgün Katrancı, Pınar Göv

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With the acceleration and assessment of quality and patient safety works in healthcare services in the 21st century, activities to reduce errors have gained importance. The prevention and reduction of unintended consequences related to healthcare services and errors made during the delivery of healthcare services can be achieved by understanding the causes of the errors. Communication is the basic reason most frequently seen in such cases. Nurses who communicate with patients more closely and for longer time play a more critical role in ensuring patient safety compared to other healthcare professionals. To reduce the risk of medical errors and increase the quality of care, it is important to raise the awareness of nurses about patient safety in training period. This descriptive study was conducted between February 2017 and May 2017 to assess intern students' attitudes towards and knowledge of patient safety and medical errors. The target population of the study consists of intern students at the Faculty of Nursing in Gaziantep University (N=180). The study did not apply any sample selection method, and the research group consisted of 90 female and 37 male senior students who were available and accepted to take part in the study (N=127). The study used personal information form and medical error attitude scale to collect data. The medical error attitude scale consists of 16 items and 3 sub-dimensions. The most frequently seen medical error in the clinics the interns worked at was found as ‘Failure to comply with asepsis rules’ with a rate of 67,7%. The most frequent case among reasons for not disclosing an error is ‘noticing and correcting the error before affecting the patient’ with the rate of 70,9%. The most frequently expressed implications of disclosing a serious error for the intern students participating in the study are ‘harming patient trust (78%)’ and ‘possibility of overreaction by patient (62,2%)’. According to the results of the study, the awareness of the students about the importance of medical errors and error reporting was found high (3,48 ± 0,49). Consequently, it is important to assess and positively improve the attitudes of nurses and other healthcare professionals towards medical errors for the determination of causes of medical errors and their prevention.

Keywords: healthcare service, intern student, medical error, patient safety

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Authors: Robbie C. Murchison, Ibrahim Küçükdemiral, Andrew Cowell

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Thermal effects are the largest source of dimensional error in precision machining, and a major proportion is caused by ambient temperature variation. The use of coolant is a primary means of mitigating these effects, but there has been limited work on coolant temperature control. This research critically explored whether CNC-machine coolant refrigeration systems adapted to actively compensate for ambient temperature variation could increase machining accuracy. Accuracy data were collected from operators’ checklists for a CNC 5-axis mill and statistically reduced to bias and precision metrics for observations of one day over a sample period of 27 days. Temperature data were collected using three USB dataloggers in ambient air, the chiller inflow, and the chiller outflow. The accuracy and temperature data were analysed using Pearson correlation, then the thermodynamics of the system were described using system identification with MATLAB. It was found that 75% of thermal error is reflected in the hot coolant temperature but that this is negligibly dependent on ambient temperature. The effect of the coolant refrigeration process on hot coolant outflow temperature was also found to be negligible. Therefore, the evidence indicated that it would not be beneficial to adapt coolant chillers to compensate for ambient temperature variation. However, it is concluded that hot coolant outflow temperature is a robust and accessible source of thermal error data which could be used for prevention strategy evaluation or as the basis of other thermal error strategies.

Keywords: CNC manufacturing, machine-tool, precision machining, thermal error

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Authors: Timothy Kayode Samson, Adedoyin Isola Lawal

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The past five years have shown a sharp increase in public interest in the crypto market, with its market capitalization growing from $100 billion in June 2017 to $2158.42 billion on April 5, 2022. Despite the outrageous nature of the volatility of cryptocurrencies, the use of skewed error innovation distributions in modelling the volatility behaviour of these digital currencies has not been given much research attention. Hence, this study models the volatility of 5 largest cryptocurrencies by market capitalization (Bitcoin, Ethereum, Tether, Binance coin, and USD Coin) using four variants of GARCH models (GJR-GARCH, sGARCH, EGARCH, and APARCH) estimated using three skewed error innovation distributions (skewed normal, skewed student- t and skewed generalized error innovation distributions). Daily closing prices of these currencies were obtained from Yahoo Finance website. Finding reveals that the Binance coin reported higher mean returns compared to other digital currencies, while the skewness indicates that the Binance coin, Tether, and USD coin increased more than they decreased in values within the period of study. For both Bitcoin and Ethereum, negative skewness was obtained, meaning that within the period of study, the returns of these currencies decreased more than they increased in value. Returns from these cryptocurrencies were found to be stationary but not normality distributed with evidence of the ARCH effect. The skewness parameters in all best forecasting models were all significant (p<.05), justifying of use of skewed error innovation distributions with a fatter tail than normal, Student-t, and generalized error innovation distributions. For Binance coin, EGARCH-sstd outperformed other volatility models, while for Bitcoin, Ethereum, Tether, and USD coin, the best forecasting models were EGARCH-sstd, APARCH-sstd, EGARCH-sged, and GJR-GARCH-sstd, respectively. This suggests the superiority of skewed Student t- distribution and skewed generalized error distribution over the skewed normal distribution.

Keywords: skewed generalized error distribution, skewed normal distribution, skewed student t- distribution, APARCH, EGARCH, sGARCH, GJR-GARCH

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Authors: Young Hee Geum

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We propose the numerical method defined by xn+1 = xn − λ[f(xn − μh(xn))/]f'(xn) , n ∈ N, and determine the control parameter λ and μ to converge cubically. In addition, we derive the asymptotic error constant. Applying this proposed scheme to various test functions, numerical results show a good agreement with the theory analyzed in this paper and are proven using Mathematica with its high-precision computability.

Keywords: asymptotic error constant, iterative method, multiple root, root-finding

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Authors: Papitchaya Papangkorn

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Matching the expectations of teachers and learners is significant for successful language learning. Moreover, teachers should discover what their learners think and feel about what and how they want to learn. Therefore, this study investigates International College, Suan Sunandha Rajabhat University students’ preferences toward error corrections in order to help SSRUIC teachers match their expectations and their learners because it is important for successful language learning. This study examined the learners’ attitude and preference toward error correction through 50 first year SSRUIC students both male (25) and female (25) in Bangkok, Thailand. The data were collected from a questionnaire and interviews to investigate the necessity and frequency, timing, type of errors, method of corrective feedback, and person who gives error correction in order to answer the overall research question and sub-questions. The findings indicate five suggestions regarding the overall research question. Firstly, errors should be treated, and always be treated. Secondly, treating errors after finish speaking is the most appropriate time. Thirdly, “errors that may cause problems in an understanding of listener” and “frequent spoken errors” should be treated. Fourthly, repetition and explicit feedback were the most popular types of feedback among males, whereas metalinguistic feedback was the most favoured types amongst females. Finally, teachers were the most preferred person to deliver corrective feedback for the learners. Although the results of the study are difficult to generalize to a larger population, which are Thai EFL learners because of the small sample, the findings provide useful information that may contribute to understanding of SSRUIC learners’ preferences toward error corrections and it might reduce the gap between what teachers employ and what students expect when receiving corrective feedback. The reduction of this gap may be useful for the learning process and could enhance the efforts of both teachers and learners in a Thai context.

Keywords: attitude, corrective feedback, error, preference

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Authors: Rashi Jain

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The LTE systems employ Orthogonal Frequency Division Multiplexing (OFDM) as the multiple access technology for the Downlink channels. For enhanced performance, accurate channel estimation is required. Various algorithms such as Least Squares (LS), Minimum Mean Square Error (MMSE) and Recursive Least Squares (RLS) can be employed for the purpose. The paper proposes channel estimation algorithm based on Kalman Filter for LTE-Downlink system. Using the frequency domain pilots, the initial channel response is obtained using the LS criterion. Then Kalman Filter is employed to track the channel variations in time-domain. To suppress the noise within a symbol, threshold processing is employed. The paper draws comparison between the LS, MMSE, RLS and Kalman filter for channel estimation. The parameters for evaluation are Bit Error Rate (BER), Mean Square Error (MSE) and run-time.

Keywords: LTE, channel estimation, OFDM, RLS, Kalman filter, threshold

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Authors: T. Gangadhararao, K. Krishna Kishore

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Motion Estimation (ME) plays a critical role in a video coder, testing such a module is of priority concern. While focusing on the testing of ME in a video coding system, this work presents an error detection and data recovery (EDDR) design, based on the residue-and-quotient (RQ) code, to embed into ME for video coding testing applications. An error in processing Elements (PEs), i.e. key components of a ME, can be detected and recovered effectively by using the proposed EDDR design. The proposed EDDR design for ME testing can detect errors and recover data with an acceptable area overhead and timing penalty.

Keywords: area overhead, data recovery, error detection, motion estimation, reliability, residue-and-quotient (RQ) code

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Authors: Dylan Elliott, Katya Pertsova

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Preposition errors are some of the most common errors created by L2 speakers. In addition, improving error correction and detection methods remains an open issue in the realm of Natural Language Processing (NLP). This research investigates whether the bidirectional encoder representations from the transformers model (BERT) have the potential to correct preposition errors accurately enough to be useful in error correction software. This research finds that BERT performs strongly when the scope of its error correction is limited to preposition choice. The researchers used an open-source BERT model and over three hundred thousand edited sentences from Wikipedia, tagged for part of speech, where only a preposition edit had occurred. To test BERT’s ability to detect errors, a technique known as multi-level masking was used to generate suggestions based on sentence context for every prepositional environment in the test data. These suggestions were compared with the original errors in the data and their known corrections to evaluate BERT’s performance. The suggestions were further analyzed to determine if BERT more often agreed with the judgements of the Wikipedia editors. Both the untrained and fined-tuned models were compared. Finetuning led to a greater rate of error-detection which significantly improved recall, but lowered precision due to an increase in false positives or falsely flagged errors. However, in most cases, these false positives were not errors in preposition usage but merely cases where more than one preposition was possible. Furthermore, when BERT correctly identified an error, the model largely agreed with the Wikipedia editors, suggesting that BERT’s ability to detect misused prepositions is better than previously believed. To evaluate to what extent BERT’s false positives were grammatical suggestions, we plan to do a further crowd-sourcing study to test the grammaticality of BERT’s suggested sentence corrections against native speakers’ judgments.

Keywords: BERT, grammatical error correction, preposition error detection, prepositions

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Authors: Amine M. Benmehaia, Amine Oulmane

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The supply response of agricultural commodities to changes in price incentives is an important issue for the success of any policy reform in the agricultural sector. This study aims to quantify the responsiveness of producers of some livestock commodities to price incentives in Algerian context. Time series analysis is used on annual data for a period of 52 years (1966-2018). Both co-integration and vector error correction model (VECM) are used through the Nerlove model of partial adjustment. The study attempts to determine the long-run and short-run relationships along with the magnitudes of disequilibria in the selected commodities. Results show that the short-run price elasticities are low in cow and sheep meat sectors (8.7 and 8% respectively), while their respective long-run elasticities are 16.5 and 10.5, whereas eggs and milk have very high short-run price elasticities (82 and 90% respectively) with long-run elasticities of 40 and 46 respectively. The error correction coefficient, reflecting the speed of adjustment towards the long-run equilibrium, is statistically significant and have the expected negative sign. Its estimates are 12.7 for cow meat, 33.5 for sheep meat, 46.7 for eggs and 8.4 for milk. It seems that cow meat and milk producers have a weak feedback of about 12.7% and 8.4% respectively of the previous year's disequilibrium from the long-run price elasticity, whereas sheep meat and eggs producers adjust to correct long run disequilibrium with a high speed of adjustment (33.5% and 46.7 % respectively). The implication of this is that much more in-depth research is needed to identify those factors that affect agricultural supply and to describe the effect of factors that shift supply in response to price incentives. This could provide valuable information for government in the use of appropriate policy measures.

Keywords: Algeria, cointegration, livestock, supply response, vector error correction model

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Authors: M. Z. Kurian, M. V. Chidananda Murthy, H. S. Guruprasad

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An approach to super-resolve the low-resolution (LR) image is presented in this paper which is very useful in multimedia communication, medical image enhancement and satellite image enhancement to have a clear view of the information in the image. The proposed Advanced B-Spline method generates a high-resolution (HR) image from single LR image and tries to retain the higher frequency components such as edges in the image. This method uses B-Spline technique and Crispening. This work is evaluated qualitatively and quantitatively using Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR). The method is also suitable for real-time applications. Different combinations of decimation and super-resolution algorithms in the presence of different noise and noise factors are tested.

Keywords: advanced b-spline, image super-resolution, mean square error (MSE), peak signal to noise ratio (PSNR), resolution down converter

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Authors: Marylene N. Tizon

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English instructors pay attention on errors committed by students as errors show whether they know or master their oral skills and what difficulties they may have in the process of learning the English language. This descriptive quantitative study aimed at identifying and categorizing the oral presentation errors of the purposively chosen 118 English 2A students enrolled during the first semester of school year 2013 – 2014. The analysis of the data for this study was undertaken using the errors committed by the students in their presentation. Marking and classifying of errors were made by first classifying them into linguistic grammatical errors then all errors were categorized further into Surface Structure Errors Taxonomy with the use of Frequency and Percentage distribution. From the analysis of the data, the researcher found out: Errors in tenses of the verbs (71 or 16%) and in addition 167 or 37% were most frequently uttered by the students. And Question and negation mistakes (12 or 3%) and misordering errors (28 or 7%) were least frequently enunciated by the students. Thus, the respondents in this study most frequently enunciated errors in tenses and in addition while they uttered least frequently the errors in question, negation, and misordering.

Keywords: grammatical error, oral presentation error, surface structure errors taxonomy, descriptive quantitative design, Philippines, Asia

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Authors: Maassoumeh Bemani Naeini

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Studies on interlanguage have long been engaged in describing the phenomenon of variation in SLA. Pursuing the same goal and particularly addressing the role of linguistic features, this study describes the use of Persian morphology in the interlanguage of two adult English-speaking learners of Persian L2. Taking the general approach of a combination of contrastive analysis, error analysis and interlanguage analysis, this study focuses on the identification and prediction of some possible instances of transfer from English L1 to Persian L2 across six elicitation tasks aiming to investigate whether any of contextual features may variably influence the learners’ order of morpheme accuracy in the areas of copula, possessives, articles, demonstratives, plural form, personal pronouns, and genitive cases.  Results describe the existence of task variation in the interlanguage system of Persian L2 learners.

Keywords: English L1, Interlanguage Analysis, Persian L2, SLA variation

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Authors: Husain Rajib, K. S. Kishor, D. G. Jewel

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Background: Uncorrected refractive error is a common cause of preventable visual impairment in pediatric age group which can be lead to blindness but early detection of visual impairment can reduce the problem that will have good effective in education and more involve in social activities. Glasses are the cheapest and commonest form of correction of refractive errors. To achieve this, patient must exhibit good compliance to spectacle wear. Patient’s attitude and perception of glasses and eye health could affect compliance. Material and method: A Prospective community based cross sectional study was designed in order to evaluate the knowledge, attitude and practices about refractive errors and eye health amongst the primary school going children. Result: Among 140 respondents, 72 were males and 68 were females. We found 50 children were myopic and out of them 26 were male and 24 were female, 27 children were hyperopic and out of them 14 were male and 13 were female. About 63 children were astigmatic and out of them 32 were male and 31 were female. The level of knowledge, attitude was satisfactory. The attitude of the students, teachers and parents was cooperative which helps to do cycloplegic refraction. Practice was not satisfactory due to social stigma and information gap. Conclusion: Knowledge of refractive error and acceptance of glasses for the correction of uncorrected refractive error. Public awareness program such as vision screening program, eye camp, and teachers training program are more beneficial for wearing and prescribing spectacle.

Keywords: refractive error, stigma, knowledge, attitude, practice

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Authors: Leticia Cervantes, Edith Garcia, Oscar Castillo

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At today, there are several control problems where the main objective is to obtain the best control in the study to decrease the error in the application. Many techniques can use to control these problems such as Neural Networks, PID control, Fuzzy Logic, Optimization techniques and many more. In this case, fuzzy logic with fuzzy system and an optimization technique are used to control the case of study. In this case, Ant Lion Optimization is used to optimize a fuzzy system to control the velocity of a simple treadmill. The main objective is to achieve the control of the velocity in the control problem using the ALO optimization. First, a simple fuzzy system was used to control the velocity of the treadmill it has two inputs (error and error change) and one output (desired speed), then results were obtained but to decrease the error the ALO optimization was developed to optimize the fuzzy system of the treadmill. Having the optimization, the simulation was performed, and results can prove that using the ALO optimization the control of the velocity was better than a conventional fuzzy system. This paper describes some basic concepts to help to understand the idea in this work, the methodology of the investigation (control problem, fuzzy system design, optimization), the results are presented and the optimization is used for the fuzzy system. A comparison between the simple fuzzy system and the optimized fuzzy systems are presented where it can be proving the optimization improved the control with good results the major findings of the study is that ALO optimization is a good alternative to improve the control because it helped to decrease the error in control applications even using any control technique to optimized, As a final statement is important to mentioned that the selected methodology was good because the control of the treadmill was improve using the optimization technique.

Keywords: ant lion optimization, control problem, fuzzy control, fuzzy system

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Authors: Beema Akbar, Varun P. Gopi, V. Suresh Babu

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Colon cancer causes the deaths of about half a million people every year. The common method of its detection is histopathological tissue analysis, it leads to tiredness and workload to the pathologist. A novel method is proposed that combines both structural and statistical pattern recognition used for the detection of colon cancer. This paper presents a comparison among the different classifiers such as Multilayer Perception (MLP), Sequential Minimal Optimization (SMO), Bayesian Logistic Regression (BLR) and k-star by using classification accuracy and error rate based on the percentage split method. The result shows that the best algorithm in WEKA is MLP classifier with an accuracy of 83.333% and kappa statistics is 0.625. The MLP classifier which has a lower error rate, will be preferred as more powerful classification capability.

Keywords: colon cancer, histopathological image, structural and statistical pattern recognition, multilayer perception

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Authors: Guillaume Leduc

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In this paper, we describe a broad setting under which the error of the approximation can be quantified, controlled, and for which convergence occurs at a speed of n⁻¹ for European and American options. We describe how knowledge of the error allows for arbitrarily fast acceleration of the convergence.

Keywords: random walk approximation, European and American options, rate of convergence, option pricing

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Authors: Eunsu Jang, Kang Park

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In developing an armored ground combat vehicle (AGCV), it is a very important step to analyze the vulnerability (or the survivability) of the AGCV against enemy’s attack. In the vulnerability analysis, the penetration equations are usually used to get the penetration depth and check whether a bullet can penetrate the armor of the AGCV, which causes the damage of internal components or crews. The penetration equations are derived from penetration experiments which require long time and great efforts. However, they usually hold only for the specific material of the target and the specific type of the bullet used in experiments. Thus, penetration simulation using ANSYS can be another option to calculate penetration depth. However, it is very important to model the targets and select the input parameters in order to get an accurate penetration depth. This paper performed a sensitivity analysis of input parameters of ANSYS on the accuracy of the calculated penetration depth. Two conflicting objectives need to be achieved in adopting ANSYS in penetration analysis: maximizing the accuracy of calculation and minimizing the calculation time. To maximize the calculation accuracy, the sensitivity analysis of the input parameters for ANSYS was performed and calculated the RMS error with the experimental data. The input parameters include mesh size, boundary condition, material properties, target diameter are tested and selected to minimize the error between the calculated result from simulation and the experiment data from the papers on the penetration equation. To minimize the calculation time, the parameter values obtained from accuracy analysis are adjusted to get optimized overall performance. As result of analysis, the followings were found: 1) As the mesh size gradually decreases from 0.9 mm to 0.5 mm, both the penetration depth and calculation time increase. 2) As diameters of the target decrease from 250mm to 60 mm, both the penetration depth and calculation time decrease. 3) As the yield stress which is one of the material property of the target decreases, the penetration depth increases. 4) The boundary condition with the fixed side surface of the target gives more penetration depth than that with the fixed side and rear surfaces. By using above finding, the input parameters can be tuned to minimize the error between simulation and experiments. By using simulation tool, ANSYS, with delicately tuned input parameters, penetration analysis can be done on computer without actual experiments. The data of penetration experiments are usually hard to get because of security reasons and only published papers provide them in the limited target material. The next step of this research is to generalize this approach to anticipate the penetration depth by interpolating the known penetration experiments. This result may not be accurate enough to be used to replace the penetration experiments, but those simulations can be used in the early stage of the design process of AGCV in modelling and simulation stage.

Keywords: ANSYS, input parameters, penetration depth, sensitivity analysis

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Authors: Mohammad Heidari

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In this paper a method for high strength steel is proposed of residual stresses in autofrettaged tubes by combination of artificial neural networks is presented. Many different thick walled cylinders that were subjected to different conditions were studied. At first, the residual stress is calculated by analytical solution. Then by changing of the parameters that influenced in residual stresses such as percentage of autofrettage, internal pressure, wall ratio of cylinder, material property of cylinder, bauschinger and hardening effect factor, a neural network is created. These parameters are the input of network. The output of network is residual stress. Numerical data, employed for training the network and capabilities of the model in predicting the residual stress has been verified. The output obtained from neural network model is compared with numerical results, and the amount of relative error has been calculated. Based on this verification error, it is shown that the radial basis function of neural network has the average error of 2.75% in predicting residual stress of thick wall cylinder. Further analysis of residual stress of thick wall cylinder under different input conditions has been investigated and comparison results of modeling with numerical considerations shows a good agreement, which also proves the feasibility and effectiveness of the adopted approach.

Keywords: thick walled cylinder, residual stress, radial basis, artificial neural network

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Authors: Bin Mu, Site Li, Shijin Yuan

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Under the circumstance of environment deterioration, people are increasingly concerned about the quality of the environment, especially air quality. As a result, it is of great value to give accurate and timely forecast of AQI (air quality index). In order to simplify influencing factors of air quality in a city, and forecast the city’s AQI tomorrow, this study used MATLAB software and adopted the method of constructing a mathematic model of PCA-GABP to provide a solution. To be specific, this study firstly made principal component analysis (PCA) of influencing factors of AQI tomorrow including aspects of weather, industry waste gas and IAQI data today. Then, we used the back propagation neural network model (BP), which is optimized by genetic algorithm (GA), to give forecast of AQI tomorrow. In order to verify validity and accuracy of PCA-GABP model’s forecast capability. The study uses two statistical indices to evaluate AQI forecast results (normalized mean square error and fractional bias). Eventually, this study reduces mean square error by optimizing individual gene structure in genetic algorithm and adjusting the parameters of back propagation model. To conclude, the performance of the model to forecast AQI is comparatively convincing and the model is expected to take positive effect in AQI forecast in the future.

Keywords: AQI forecast, principal component analysis, genetic algorithm, back propagation neural network model

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Authors: M. Vassou, A. Karasimos

Abstract:

A primary concern in the field of Second Language Acquisition (SLA) research is to determine the innate mechanisms of second language learning and acquisition through the systematic study of a learner's interlanguage. Errors emerge while a learner attempts to communicate using the target-language and can be seen either as the observable linguistic product of the latent cognitive and language process of mental representations or as an indispensable learning mechanism. Therefore, the study of the learner’s erroneous forms may depict the various strategies and mechanisms that take place during the language acquisition process resulting in deviations from the target-language norms and difficulties in communication. Mapping the erroneous utterances of a late adult learner in the process of acquiring Greek as a second language constitutes one of the main aims of this study. For our research purposes, we created an error-tagged learner corpus composed of the participant’s written texts produced throughout a period of a 4- year instructed language acquisition. Error analysis and interlanguage theory constitute the methodological and theoretical framework, respectively. The research questions pertain to the learner's most frequent errors per linguistic category and per year as well as his choices concerning the Greek Article System. According to the quantitative analysis of the data, the most frequent errors are observed in the categories of the stress system and syntax, whereas a significant fluctuation and/or gradual reduction throughout the 4 years of instructed acquisition indicate the emergence of developmental stages. The findings with regard to the article usage bespeak fossilization of erroneous structures in certain contexts. In general, our results point towards the existence and further development of an established learner’s (inter-) language system governed not only by mother- tongue and target-language influences but also by the learner’s assumptions and set of rules as the result of a complex cognitive process. It is expected that this study will contribute not only to the knowledge in the field of Greek as a second language and SLA generally, but it will also provide an insight into the cognitive mechanisms and strategies developed by multilingual learners of late adulthood.

Keywords: Greek as a second language, error analysis, interlanguage, late adult learner

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Authors: Mohamed O. Babana

Abstract:

In wireless channel multipath is the propagation phenomena where the transmitted signal arrive at the receiver side with many of paths, the signal at these paths arrive with different time delay the results is random signal fading due to intersymbols interference(ISI). This paper deals with identification of orthogonal frequency division multiplexing (OFDM) technology, and how it is used to overcome intersymbol interference due to multipath. Also investigates the effect of Additive White Gaussian Noise Channel (AWGN) on OFDM using multi-level modulation of Phase Shift Keying (PSK), computer simulation to calculate the bit error rate (BER) under AWGN channel is applied. A comparison study is carried out to obtain the Bit Error Rate performance for OFDM to identify the best multi-level modulation of PSK.

Keywords: intersymbol interference(ISI), bit error rate(BER), modulation, multiplexing, simulation

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Authors: João Rato, Nuno Costa

Abstract:

The human verbal communication is a two-way process which requires a mutual understanding that will result in some considerations. This kind of communication, also called dialogue, besides the supposed human agents it can also be performed between human agents and machines. The interaction between Men and Machines, by means of a natural language, has an important role concerning the improvement of the communication between each other. Aiming at knowing the performance of some speech recognition systems, this document shows the results of the accomplished tests according to the Word Error Rate evaluation method. Besides that, it is also given a set of information linked to the systems of Man-Machine communication. After this work has been made, conclusions were drawn regarding the Speech Recognition Systems, among which it can be mentioned their poor performance concerning the voice interpretation in noisy environments.

Keywords: automatic speech recognition, man-machine conversation, speech recognition, spoken dialogue systems, word error rate

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Authors: Pisut Boonkaew, Jatuporn Thongsri

Abstract:

In hard disk drive manufacturing industry, the process of reducing an unnecessary part and qualifying the quality of part before assembling is important. Thus, clamp was designed and fabricated as a fixture for holding in testing process. Basically, testing by trial and error consumes a long time to improve. Consequently, the simulation was brought to improve the part and reduce the time taken. The problem is the present clamp has a low life expectancy because of the critical stress that occurred. Hence, the simulation was brought to study the behavior of stress and compressive force to improve the clamp expectancy with all probability of designs which are present up to 27 designs, which excluding the repeated designs. The probability was calculated followed by the full fractional rules of six sigma methodology which was provided correctly. The six sigma methodology is a well-structured method for improving quality level by detecting and reducing the variability of the process. Therefore, the defective will be decreased while the process capability increasing. This research focuses on the methodology of stress and fatigue reduction while compressive force still remains in the acceptable range that has been set by the company. In the simulation, ANSYS simulates the 3D CAD with the same condition during the experiment. Then the force at each distance started from 0.01 to 0.1 mm will be recorded. The setting in ANSYS was verified by mesh convergence methodology and compared the percentage error with the experimental result; the error must not exceed the acceptable range. Therefore, the improved process focuses on degree, radius, and length that will reduce stress and still remain in the acceptable force number. Therefore, the fatigue analysis will be brought as the next process in order to guarantee that the lifetime will be extended by simulating through ANSYS simulation program. Not only to simulate it, but also to confirm the setting by comparing with the actual clamp in order to observe the different of fatigue between both designs. This brings the life time improvement up to 57% compared with the actual clamp in the manufacturing. This study provides a precise and trustable setting enough to be set as a reference methodology for the future design. Because of the combination and adaptation from the six sigma method, finite element, fatigue and linear regressive analysis that lead to accurate calculation, this project will able to save up to 60 million dollars annually.

Keywords: clamp, finite element analysis, structural, six sigma, linear regressive analysis, fatigue analysis, probability

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Authors: Hasan Basaran, Emre Unal

Abstract:

Formation flying of satellites is a mission that involves a relative position keeping of different satellites in the constellation. In this study, different control algorithms are compared with one another in terms of ΔV, velocity increment, and tracking error. Various control methods, covering continuous and impulsive approaches are implemented and tested for satellites flying in low Earth orbit. Feedback linearization, sliding mode control, and model predictive control are designed and compared with an impulsive feedback law, which is based on mean orbital elements. Feedback linearization and sliding mode control approaches have identical mathematical models that include second order Earth oblateness effects. The model predictive control, on the other hand, does not include any perturbations and assumes circular chief orbit. The comparison is done with 4 different initial errors and achieved with velocity increment, root mean square error, maximum steady state error, and settling time. It was observed that impulsive law consumed the least ΔV, while produced the highest maximum error in the steady state. The continuous control laws, however, consumed higher velocity increments and produced lower amounts of tracking errors. Finally, the inversely proportional relationship between tracking error and velocity increment was established.

Keywords: chief-deputy satellites, feedback linearization, follower-leader satellites, formation flight, fuel consumption, model predictive control, rendezvous, sliding mode

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