Search results for: model errors

Authors: Abdelrahman Abdelazim

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Most industries are looking for technologies that are easy to use, efficient and fast to accomplish. To implement these, factories tend to use advanced systems that could alter complicity to simplicity and rudimentary to advancement. Cloud Manufacturing is a new movement that aims to mirror and integrate cloud computing into manufacturing. Amongst cloud manufacturing various advantages are decreasing the human involvements and increasing the dependency on automated machines, which in turns decreases human errors and increases efficiency. A reliable and extraordinary performance processes with minimum errors are highly desired factors of today’s manufacturers. At the glance it seems to be the best alternative, however, the implementation of a cloud system can be very challenging. This work investigates cloud manufacturing in details, it outlines its advantages and disadvantages by converting a local factory in Kuwait to a cloud-ready system. Initially the flow of the factory’s manufacturing process has been analyzed identifying the bottlenecks and illustrating how cloud manufacturing can eliminate them. Following this an automation process has been analyzed and implemented. A comparison between the process before and after the adaptation has been carried out showing the effects on the cost, the output and the efficiency of the process.

Keywords: cloud manufacturing, automation, Kuwait industrial sector, advanced digital manufacturing

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Authors: Zhou Jianhong

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Model averaging is a desirable approach to deal with model uncertainty, which, however, has rarely been explored for Poisson regression. In this paper, we propose a model averaging procedure based on an unbiased estimator of the expected Kullback-Leibler distance for the Poisson regression. Simulation study shows that the proposed model average estimator outperforms some other commonly used model selection and model average estimators in some situations. Our proposed methods are further applied to a real data example and the advantage of this method is demonstrated again.

Keywords: model averaging, poission regression, Kullback-Leibler distance, statistics

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Authors: Valentina Zhang

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While facial expression is a complex and individualized behavior, all facial emotion recognition (FER) systems known to us rely on a single facial representation and are trained on universal data. We conjecture that: (i) different facial representations can provide different, sometimes complementing views of emotions; (ii) when employed collectively in a discussion group setting, they enable more accurate emotion reading which is highly desirable in autism care and other applications context sensitive to errors. In this paper, we first study FER using pixel-based DL vs semantics-based DL in the context of deepfake videos. Our experiment indicates that while the semantics-trained model performs better with articulated facial feature changes, the pixel-trained model outperforms on subtle or rare facial expressions. Armed with these findings, we have constructed an adaptive FER system learning from both types of models for dyadic or small interacting groups and further leveraging the synthesized group emotions as the ground truth for individualized FER training. Using a collection of group conversation videos, we demonstrate that FER accuracy and personalization can benefit from such an approach.

Keywords: neurodivergence care, facial emotion recognition, deep learning, ground truth for supervised learning

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Authors: Mariya V. Yanyukina, Michael A. Bolotov

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Assembling accuracy is the degree of accordance between the actual values of the parameters obtained during assembly, and the values specified in the assembly drawings and technical specifications. However, the assembling accuracy depends not only on the quality of the production process but also on the correctness of the assembly process. Therefore, preliminary calculations of assembly stages are carried out to verify the correspondence of real geometric parameters to their acceptable values. In the aviation industry, most calculations involve interacting dimensional chains. This greatly complicates the task. Solving such problems requires a special approach. The purpose of this article is to carry out the problem of improving the technology of assembly of aviation units by use of computer calculations. One of the actual examples of the assembly unit, in which there is an interacting dimensional chain, is the turbine wheel of gas turbine engine. Dimensional chain of turbine wheel is formed by geometric parameters of disk and set of blades. The interaction of the dimensional chain consists in the formation of two chains. The first chain is formed by the dimensions that determine the location of the grooves for the installation of the blades, and the dimensions of the blade roots. The second dimensional chain is formed by the dimensions of the airfoil shroud platform. The interaction of the dimensional chain of the turbine wheel is the interdependence of the first and second chains by means of power circuits formed by a plurality of middle parts of the turbine blades. The timeliness of the calculation of the dimensional chain of the turbine wheel is the need to improve the technology of assembly of this unit. The task at hand contains geometric and mathematical components; therefore, its solution can be implemented following the algorithm: 1) research and analysis of production errors by geometric parameters; 2) development of a parametric model in the CAD system; 3) creation of set of CAD-models of details taking into account actual or generalized distributions of errors of geometrical parameters; 4) calculation model in the CAE-system, loading of various combinations of models of parts; 5) the accumulation of statistics and analysis. The main task is to pre-simulate the assembly process by calculating the interacting dimensional chains. The article describes the approach to the solution from the point of view of mathematical statistics, implemented in the software package Matlab. Within the framework of the study, there are data on the measurement of the components of the turbine wheel-blades and disks, as a result of which it is expected that the assembly process of the unit will be optimized by solving dimensional chains.

Keywords: accuracy, assembly, interacting dimension chains, turbine

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Authors: Semion Kertzman, Pinhas Dannon

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Impulsive behaviour and the underlying brain processes are hypothesized to be central in the development and maintenance of pathological gambling. Inhibition ability can be differentially impaired in pathological gamblers (PGs). Aims: This study aimed to compare the ability of eight widely used inhibition measures to discriminate between PGs and healthy controls (HCs). Methods: PGs (N=51) and demographically matched HCs (N=51) performed cognitive inhibition (the Stroop), motor inhibition (the Go/NoGo) and reflective inhibition (the Matching Familiar Figures (MFFT)) tasks. Results: An augmented total interference response time in the Stroop task (η² =0.054), a large number of commission errors (η² =0.053) in the Go/NoGo task, and the total number of errors in the MFFT (η² =0.05) can discriminate PGs from HCs. Other measures are unable to differentiate between PGs and HCs. No significant correlations were observed between inhibition measures. Conclusion: Inhibition measures varied in the ability to discriminate PGs from HCs. Most inhibition measures were not relevant to gambling behaviour. PGs do not express rash, impulsive behaviour, such as quickly choosing an answer without thinking. In contrast, in PGs, inhibition impairment was related to slow-inaccurate performance.

Keywords: pathological gambling, impulsivity, neurocognition, addiction

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Authors: Marwa A. Nasser

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This is an empirical study that provides an investigation of the most significant errors of Egyptian learners in producing English consonants and Arabic consonants, and advice on how these can be remedied. The study adopts a descriptive approach and the analysis is based on audio recordings of two groups of people. The first group includes six volunteers of Egyptian learners belonging to the English Department at Faculty of Women who learn English as a foreign language. The other group includes six Egyptian learners who are studying Tajweed (how to recite Quran correctly). The audio recordings were examined, and sounds were analyzed in an attempt to highlight the most common error done by the learners while reading English or reading (or reciting) Quran. Results show that the two groups of learners have problems with certain phonemic contrasts. Both groups share common errors although both languages are different and not related (e.g. pre-aspiration of fortis stops, incorrect articulation of consonants and velarization of certain sounds).

Keywords: consonant articulations, Egyptian learners of English, Egyptian learners of Quran, empirical study, error analysis, pronunciation problems

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Authors: L. Madouni, M. Ould Ouali, N. E. Hannachi

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Two constitutive models for concrete are available in ABAQUS/Explicit, the Brittle Cracking Model and the Concrete Damaged Plasticity Model, and their suitability and limitations are well known. The aim of the present paper is to implement a damage-friction concrete constitutive model and to evaluate the performance of this model by comparing the predicted response with experimental data. The constitutive formulation of this material model is reviewed. In order to have consistent results, the parameter identification and calibration for the model have been performed. Several numerical simulations are presented in this paper, whose results allow for validating the capability of the proposed model for reproducing the typical nonlinear performances of concrete structures under different monotonic and cyclic load conditions. The results of the evaluation will be used for recommendations concerning the application and further improvements of the investigated model.

Keywords: Abaqus, concrete, constitutive model, numerical simulation

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Authors: Wilmer Osvaldo Martinez, Manuel Dario Hernandez, Juan Manuel Julio

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We propose to assess the performance of k forecast procedures by exploring the distributions of forecast errors and error losses. We argue that non systematic forecast errors minimize when their distributions are symmetric and unimodal, and that forecast accuracy should be assessed through stochastic loss order rather than expected loss order, which is the way it is customarily performed in previous work. Moreover, since forecast performance evaluation can be understood as a one way analysis of variance, we propose to explore loss distributions under two circumstances; when a strict (but unknown) joint stochastic order exists among the losses of all forecast alternatives, and when such order happens among subsets of alternative procedures. In spite of the fact that loss stochastic order is stronger than loss moment order, our proposals are at least as powerful as competing tests, and are robust to the correlation, autocorrelation and heteroskedasticity settings they consider. In addition, since our proposals do not require samples of the same size, their scope is also wider, and provided that they test the whole loss distribution instead of just loss moments, they can also be used to study forecast distributions as well. We illustrate the usefulness of our proposals by evaluating a set of real world forecasts.

Keywords: forecast evaluation, stochastic order, multiple comparison, non parametric test

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Authors: Breno Barrreto Silva, Agnieszka Otwinowska, Katarzyna Kutylowska

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Research comparing lexical learning following the writing of sentences and longer texts with keywords is limited and contradictory. One possibility is that the recursivity of writing may enhance processing and increase lexical learning; another possibility is that the higher cognitive load of complex-text writing (e.g., essays), at least when timed, may hinder the learning of words. In our study, we selected 2 sets of 10 academic keywords matched for part of speech, length (number of characters), frequency (SUBTLEXus), and concreteness, and we asked 90 L1-Polish advanced-level English majors to use the keywords when writing sentences, timed (60 minutes) or untimed essays. First, all participants wrote a timed Control essay (60 minutes) without keywords. Then different groups produced Timed essays (60 minutes; n=33), Untimed essays (n=24), or Sentences (n=33) using the two sets of glossed keywords (counterbalanced). The comparability of the participants in the three groups was ensured by matching them for proficiency in English (LexTALE), and for few measures derived from the control essay: VocD (assessing productive lexical diversity), normed errors (assessing productive accuracy), words per minute (assessing productive written fluency), and holistic scores (assessing overall quality of production). We measured lexical learning (depth and breadth) via an adapted Vocabulary Knowledge Scale (VKS) and a free association test. Cognitive load was measured in the three essays (Control, Timed, Untimed) using normed number of errors and holistic scores (TOEFL criteria). The number of errors and essay scores were obtained from two raters (interrater reliability Pearson’s r=.78-91). Generalized linear mixed models showed no difference in the breadth and depth of keyword knowledge after writing Sentences, Timed essays, and Untimed essays. The task-based measurements found that Control and Timed essays had similar holistic scores, but that Untimed essay had better quality than Timed essay. Also, Untimed essay was the most accurate, and Timed essay the most error prone. Concluding, using keywords in Timed, but not Untimed, essays increased cognitive load, leading to more errors and lower quality. Still, writing sentences and essays yielded similar lexical learning, and differences in the cognitive load between Timed and Untimed essays did not affect lexical acquisition.

Keywords: learning academic words, writing essays, cognitive load, english as an L2

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Authors: Dalicia Bouallouche, Jean-Baptiste Vioix, Stéphane Millot, Eric Busvelle

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When researchers or logistics software developers deal with vehicle routing optimization, they mainly focus on minimizing the total travelled distance or the total time spent in the tours by the trucks, and maximizing the number of visited customers. They assume that the upstream real data given to carry the optimization of a transporter tours is free from errors, like customers’ real constraints, customers’ addresses and their GPS-coordinates. However, in real transporter situations, upstream data is often of bad quality because of address geocoding errors and the irrelevance of received addresses from the EDI (Electronic Data Interchange). In fact, geocoders are not exempt from errors and could give impertinent GPS-coordinates. Also, even with a good geocoding, an inaccurate address can lead to a bad geocoding. For instance, when the geocoder has trouble with geocoding an address, it returns those of the center of the city. As well, an obvious geocoding issue is that the mappings used by the geocoders are not regularly updated. Thus, new buildings could not exist on maps until the next update. Even so, trying to optimize tours with impertinent customers GPS-coordinates, which are the most important and basic input data to take into account for solving a vehicle routing problem, is not really useful and will lead to a bad and incoherent solution tours because the locations of the customers used for the optimization are very different from their real positions. Our work is supported by a logistics software editor Tedies and a transport company Upsilon. We work with Upsilon's truck routes data to carry our experiments. In fact, these trucks are equipped with TOMTOM GPSs that continuously save their tours data (positions, speeds, tachograph-information, etc.). We, then, retrieve these data to extract the real truck routes to work with. The aim of this work is to use the experience of the driver and the feedback of the real truck tours to validate GPS-coordinates of well geocoded addresses, and bring a correction to the badly geocoded addresses. Thereby, when a vehicle makes its tour, for each visited customer, the vehicle might have trouble with finding this customer’s address at most once. In other words, the vehicle would be wrong at most once for each customer’s address. Our method significantly improves the quality of the geocoding. Hence, we achieve to automatically correct an average of 70% of GPS-coordinates of a tour addresses. The rest of the GPS-coordinates are corrected in a manual way by giving the user indications to help him to correct them. This study shows the importance of taking into account the feedback of the trucks to gradually correct address geocoding errors. Indeed, the accuracy of customer’s address and its GPS-coordinates play a major role in tours optimization. Unfortunately, address writing errors are very frequent. This feedback is naturally and usually taken into account by transporters (by asking drivers, calling customers…), to learn about their tours and bring corrections to the upcoming tours. Hence, we develop a method to do a big part of that automatically.

Keywords: driver experience feedback, geocoding correction, real truck tours

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Authors: Muciz Özcan, Mustafa Sacid Endiz, Veysel Alver

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In this paper we present a new approach to the boom welding related to the mobile cranes manufacturing, implementing a new method in order to get homogeneous welding quality and reduced energy usage during booms production. We aim to get the realization of the same welding quality carried out on the boom in every region during the manufacturing process and to detect the possible welding errors whether they could be eliminated using laser sensors. We determine the position of the welding region directly through our system and with the help of the welding oscillator we are able to perform a proper boom welding. Errors that may occur in the welding process can be observed by monitoring and eliminated by means of an operator. The major modification in the production of the crane booms will be their form of the booms. Although conventionally, more than one welding is required to perform this process, with the suggested concept, only one particular welding is sufficient, which will be more energy and environment-friendly. Consequently, as only one welding is needed for the manufacturing of the boom, the particular welding quality becomes more essential. As a way to satisfy the welding quality, a welding manipulator was made and fabricated. By using this welding manipulator, the risks of involving dangerous gases formed during the welding process for the operator and the surroundings are diminished as much as possible.

Keywords: boom welding, seam tracking, energy saving, global warming

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Authors: Waad Al Saleemi, Badriya Al Adawi, Zaaima Al Jabri, Sahim Al Ghafri, Jalila Al Hadhramia

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Objectives: Using standard lab methods, a positive blood culture requires a minimum of two days (two occasions of overnight incubation) to obtain a final identification (ID) and antimicrobial susceptibility results (AST) report. In this study, we aimed to evaluate the accuracy and precision of identification and antimicrobial susceptibility testing of an alternative method (direct method) that will reduce the turnaround time by 24 hours. This method involves the direct inoculation of positive blood culture broths into the Phoenix system using serum separation tubes (SST). Method: This prospective study included monomicrobial-positive blood cultures obtained from January 2022 to May 2023 in SQUH. Blood cultures containing a mixture of organisms, fungi, or anaerobic organisms were excluded from this study. The result of the new “direct method” under study was compared with the current “standard method” used in the lab. The accuracy and precision were evaluated for the ID and AST using Clinical and Laboratory Standards Institute (CLSI) recommendations. The categorical agreement, essential agreement, and the rates of very major errors (VME), major errors (ME), and minor errors (MIE) for both gram-negative and gram-positive bacteria were calculated. Passing criteria were set according to CLSI. Result: The results of ID and AST were available for a total of 158 isolates. Of 77 isolates of gram-negative bacteria, 71 (92%) were correctly identified at the species level. Of 70 isolates of gram-positive bacteria, 47(67%) isolates were correctly identified. For gram-negative bacteria, the essential agreement of the direct method was ≥92% when compared to the standard method, while the categorical agreement was ≥91% for all tested antibiotics. The precision of ID and AST were noted to be 100% for all tested isolates. For gram-positive bacteria, the essential agreement was >93%, while the categorical agreement was >92% for all tested antibiotics except moxifloxacin. Many antibiotics were noted to have an unacceptable higher rate of very major errors including penicillin, cotrimoxazole, clindamycin, ciprofloxacin, and moxifloxacin. However, no error was observed in the results of vancomycin, linezolid, and daptomycin. Conclusion: The direct method of ID and AST for positive blood cultures using SST is reliable for gram negative bacteria. It will significantly decrease the turnaround time and will facilitate antimicrobial stewardship.

Keywords: bloodstream infection, oman, direct ast, blood culture, rapid identification, antimicrobial susceptibility, phoenix, direct inoculation

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Authors: Aaditya U. Jhamb

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Due to the current energy crisis that many countries are battling, energy-efficient buildings are the subject of extensive research in the modern technological era because of growing worries about energy consumption and its effects on the environment. The paper explores 8 factors that help determine energy efficiency for a building: (relative compactness, surface area, wall area, roof area, overall height, orientation, glazing area, and glazing area distribution), with Tsanas and Xifara providing a dataset. The data set employed 768 different residential building models to anticipate heating and cooling loads with a low mean squared error. By optimizing these characteristics, machine learning algorithms may assess and properly forecast a building's heating and cooling loads, lowering energy usage while increasing the quality of people's lives. As a result, the paper studied the magnitude of the correlation between these input factors and the two output variables using various statistical methods of analysis after determining which input variable was most closely associated with the output loads. The most conclusive model was the Decision Tree Regressor, which had a mean squared error of 0.258, whilst the least definitive model was the Isotonic Regressor, which had a mean squared error of 21.68. This paper also investigated the KNN Regressor and the Linear Regression, which had to mean squared errors of 3.349 and 18.141, respectively. In conclusion, the model, given the 8 input variables, was able to predict the heating and cooling loads of a residential building accurately and precisely.

Keywords: energy efficient buildings, heating load, cooling load, machine learning models

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Authors: Arslan Murtaza

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Model Driven Architecture (MDA) is technique presented by OMG (Object Management Group) for software development in which different models are proposed and converted them into code. The main plan is to identify task by using PIM (Platform Independent Model) and transform it into PSM (Platform Specific Model) and then converted into code. In this review paper describes some challenges and issues that are faced in MDA, type and transformation of models (e.g. CIM, PIM and PSM), and evaluation of MDA-based methodologies.

Keywords: OMG, model driven rrchitecture (MDA), computation independent model (CIM), platform independent model (PIM), platform specific model(PSM), MDA-based methodologies

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Authors: Khaled Karim

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Although a large number of studies have examined the effectiveness of written corrective feedback (WCF) in L2 writing, very few studies have investigated students’ attitudes towards the feedback and their perspectives regarding the usefulness of different types of feedback. Using prompted stimulated recall interviews, this study investigated ESL students’ perceptions and attitudes towards the CF they received as well as their preferences and reactions to the corrections. 24 ESL students first received direct (e.g., providing target forms after crossing out erroneous forms) and indirect (e.g., underlining and underline+metalinguistic) CF on four written tasks and then participated in an interview with the researcher. The analysis revealed that both direct and indirect CF were judged to be useful strategies for correction but in different ways. Underline only CF helped them think about the nature and type of the errors they made while metalinguistic CF was useful as it provided clues about the nature and type of the errors. Most participants indicated that indirect correction needed sufficient prior knowledge of the form to be effective. The majority of the students found the combination of underlining with metalinguistic information as the most effective method of providing feedback. Detailed findings will be presented, and pedagogical implications of the study will be discussed.

Keywords: ESL writing, error correction, feedback, written corrective feedback

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Authors: Mohamed Rabhi, Kouider Halim Benrahou

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The rheological properties of the carbonyl-methylcellulose (CMC), of different concentrations (25000, 50000, 60000, 80000 and 100000 ppm) and different temperatures were studied. We found that the rheological behavior of all CMC solutions presents a pseudo-plastic behavior, it follows the model of Ostwald-de Waele. The objective of this work is the modeling of flow by the CMC Cross model. The Cross model gives us the variation of the viscosity according to the shear rate. This model allowed us to adjust more clearly the rheological characteristics of CMC solutions. A comparison between the Cross model and the model of Ostwald was made. Cross the model fitting parameters were determined by a numerical simulation to make an approach between the experimental curve and those given by the two models. Our study has shown that the model of Cross, describes well the flow of "CMC" for low concentrations.

Keywords: CMC, rheological modeling, Ostwald model, cross model, viscosity

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Authors: Viet-Hung Truong, Seung-Eock Kim

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Rain–wind induced vibration of inclined cable is a special aerodynamic phenomenon because it is easily influenced by many factors, especially the distribution of rivulet and wind velocity. This paper proposes a new 3D model of inclined cable, based on single degree-of-freedom model. Aerodynamic forces are firstly established and verified with the existing results from a 2D model. The 3D model of inclined cable is developed. The 3D model is then applied to assess the effects of wind velocity distribution and the continuity of rivulets on the cable. Finally, an inclined cable model with small sag is investigated.

Keywords: 3D model, rain - wind induced vibration, rivulet, analytical model

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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: Kuo-Kai Lin, Po-Lun Chang

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Background: The Emergency Care Research Institute released a list for the top 10 medical technology hazards in 2017, with the following hazard topping the list: ‘infusion errors can be deadly if simple safety steps are overlooked.’ In addition, hospitals use various assessment items to evaluate the safety of their medical equipment, confirming the importance of medical equipment safety. In recent years, the topic of patient safety has garnered increasing attention. Accordingly, various agencies have established patient safety-related committees to coordinate, collect, and analyze information regarding abnormal events associated with medical practice. Activities to promote and improve employee training have been introduced to diminish the recurrence of medical malpractice. Objective: To allow nursing personnel to acquire the skills needed to operate common medical equipment and update and review such skills whenever necessary to elevate medical care quality and reduce patient injuries caused by medical equipment operation errors. Method: In this study, a quasi-experimental design was adopted and nurses from a regional teaching hospital were selected as the study sample. Online videos instructing the operation method of common medical equipment were made and quick response codes were designed for the nursing personnel to quickly access the videos when necessary. Senior nursing supervisors and equipment experts were invited to formulate a ‘Scale-based Questionnaire for Assessing Nursing Personnel’s Operational Knowledge of Common Medical Equipment’ to evaluate the nursing personnel’s literacy regarding the operation of the medical equipment. From March to October 2017, an employee training on medical equipment operation and a practice course (simulation course) were implemented, after which the effectiveness of the training and practice course were assessed. Results: Prior to and after the training and practice course, the 66 participating nurses scored 58 and 87 on ‘operational knowledge of common medical equipment,’ respectively (showing a significant statistical difference; t = -9.407, p < .001); 53.5 and 86.3 on ‘operational knowledge of 12-lead electrocardiography’ (z = -2.087, p < .01), respectively; 40 and 79.5 on ‘operational knowledge of cardiac defibrillators’ (z = -3.849, p < .001), respectively; 90 and 98 on ‘operational knowledge of Abbott pumps’ (z = -1.841, p = 0.066), respectively; and 8.7 and 13.7 on ‘perceived competence’ (showing a significant statistical difference; t = -2.77, p < .05). In the participating hospital, medical equipment operation errors were observed in both 2016 and 2017. However, since the implementation of the intervention, medical equipment operation errors have not yet been observed up to October 2017, which can be regarded as the secondary outcome of this study. Conclusion: In this study, innovative teaching strategies were adopted to effectively enhance the professional literacy and skills of nursing personnel in operating medical equipment. The training and practice course also elevated the nursing personnel’s related literacy and perceived competence of operating medical equipment. The nursing personnel was thus able to accurately operate the medical equipment and avoid operational errors that might jeopardize patient safety.

Keywords: medical equipment, digital teaching plan, simulation-based teaching plan, operational knowledge, patient safety

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Authors: Chong-Yang Qiao

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Mobile augmented reality (MAR) tracking targets from the surroundings and aids operators for interactive data and procedures visualization, potential equipment and system understandably. Operators remotely communicate and coordinate with each other for the continuous tasks, information and data exchange between control room and work-site. In the routine work, distributed control system (DCS) monitoring and work-site manipulation require operators interact in real-time manners. The critical question is the improvement of user experience in cooperative works through applying Augmented Reality in the traditional industrial field. The purpose of this exploratory study is to find the cognitive model for the multiple task performance by MAR. In particular, the focus will be on the comparison between different tasks and environment factors which influence information processing. Three experiments use interface and interaction design, the content of start-up, maintenance and stop embedded in the mobile application. With the evaluation criteria of time demands and human errors, and analysis of the mental process and the behavior action during the multiple tasks, heuristic evaluation was used to find the operators performance with different situation factors, and record the information processing in recognition, interpretation, judgment and reasoning. The research will find the functional properties of MAR and constrain the development of the cognitive model. Conclusions can be drawn that suggest MAR is easy to use and useful for operators in the remote collaborative works.

Keywords: mobile augmented reality, remote collaboration, user experience, cognition model

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Authors: N. Borjalilu, P. Rabiei, A. Enjoo

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Flight Data Monitoring (FDM) program assists an operator in aviation industries to identify, quantify, assess and address operational safety risks, in order to improve safety of flight operations. FDM is a powerful tool for an aircraft operator integrated into the operator’s Safety Management System (SMS), allowing to detect, confirm, and assess safety issues and to check the effectiveness of corrective actions, associated with human errors. This article proposes a model for safety risk assessment level of flight data in a different aspect of event focus based on fuzzy set values. It permits to evaluate the operational safety level from the point of view of flight activities. The main advantages of this method are proposed qualitative safety analysis of flight data. This research applies the opinions of the aviation experts through a number of questionnaires Related to flight data in four categories of occurrence that can take place during an accident or an incident such as: Runway Excursions (RE), Controlled Flight Into Terrain (CFIT), Mid-Air Collision (MAC), Loss of Control in Flight (LOC-I). By weighting each one (by F-TOPSIS) and applying it to the number of risks of the event, the safety risk of each related events can be obtained.

Keywords: F-topsis, fuzzy set, flight data monitoring (FDM), flight safety

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Authors: Luis Amador Jimenez, Md. Shohel Amin

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Pavement performance models are based on projections of observed traffic loads, which makes uncertain to study funding strategies in the long run if history does not repeat. Neural networks can be used to estimate deterioration rates but the learning rate and momentum have not been properly investigated, in addition, economic evolvement could change traffic flows. This study addresses both issues through a case study for roads of Montreal that simulates traffic for a period of 50 years and deals with the measurement error of the pavement deterioration model. Travel demand models are applied to simulate annual average daily traffic (AADT) every 5 years. Accumulated equivalent single axle loads (ESALs) are calculated from the predicted AADT and locally observed truck distributions combined with truck factors. A back propagation Neural Network (BPN) method with a Generalized Delta Rule (GDR) learning algorithm is applied to estimate pavement deterioration models capable of overcoming measurement errors. Linear programming of lifecycle optimization is applied to identify M&R strategies that ensure good pavement condition while minimizing the budget. It was found that CAD 150 million is the minimum annual budget to good condition for arterial and local roads in Montreal. Montreal drivers prefer the use of public transportation for work and education purposes. Vehicle traffic is expected to double within 50 years, ESALS are expected to double the number of ESALs every 15 years. Roads in the island of Montreal need to undergo a stabilization period for about 25 years, a steady state seems to be reached after.

Keywords: pavement management system, traffic simulation, backpropagation neural network, performance modeling, measurement errors, linear programming, lifecycle optimization

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Authors: Go Bong Choi, Shin Je Lee, Sung Jin Yoo, Gibaek Lee, Jong Min Lee

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In South Korea, it is difficult to obtain data for statistical pipe assessment. In this paper, to address these issues, we find that various statistical model presented before is how data mixed with noise and are whether apply in South Korea. Three major type of model is studied and if data is presented in the paper, we add noise to data, which affects how model response changes. Moreover, we generate data from model in paper and analyse effect of noise. From this we can find robustness and applicability in Korea of each model.

Keywords: proportional hazard model, survival model, water main deterioration, ecological sciences

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Authors: Yehjune Heo

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As biometric systems become widely deployed, the security of identification systems can be easily attacked by various spoof materials. This paper contributes to finding a reliable and practical anti-spoofing method using Convolutional Neural Networks (CNNs) based on the types of loss functions and optimizers. The types of CNNs used in this paper include AlexNet, VGGNet, and ResNet. By using various loss functions including Cross-Entropy, Center Loss, Cosine Proximity, and Hinge Loss, and various loss optimizers which include Adam, SGD, RMSProp, Adadelta, Adagrad, and Nadam, we obtained significant performance changes. We realize that choosing the correct loss function for each model is crucial since different loss functions lead to different errors on the same evaluation. By using a subset of the Livdet 2017 database, we validate our approach to compare the generalization power. It is important to note that we use a subset of LiveDet and the database is the same across all training and testing for each model. This way, we can compare the performance, in terms of generalization, for the unseen data across all different models. The best CNN (AlexNet) with the appropriate loss function and optimizers result in more than 3% of performance gain over the other CNN models with the default loss function and optimizer. In addition to the highest generalization performance, this paper also contains the models with high accuracy associated with parameters and mean average error rates to find the model that consumes the least memory and computation time for training and testing. Although AlexNet has less complexity over other CNN models, it is proven to be very efficient. For practical anti-spoofing systems, the deployed version should use a small amount of memory and should run very fast with high anti-spoofing performance. For our deployed version on smartphones, additional processing steps, such as quantization and pruning algorithms, have been applied in our final model.

Keywords: anti-spoofing, CNN, fingerprint recognition, loss function, optimizer

Procedia PDF Downloads 104

Authors: Anila Xhahysa, Migena Ceyhan, Neki Kuka, Klajdi Qoshi, Damiano Koxhaj

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The seismic event catalog has been updated in the framework of a bilateral project supported by the Central European Investment Fund and with the extensive support of Global Earthquake Model Foundation to update Albania's national seismic hazard model. The earthquake catalogue prepared within this project covers the Western Balkan area limited by 38.0° - 48°N, 12.5° - 24.5°E and includes 41,806 earthquakes that occurred in the region between 510 BC and 2022. Since the moment magnitude characterizes the earthquake size accurately and the selected ground motion prediction equations for the seismic hazard assessment employ this scale, it was chosen as the uniform magnitude scale for the catalogue. Therefore, proxy values of moment magnitude had to be obtained by using new magnitude conversion equations between the local and other magnitude types to this unified scale. The Global Centroid Moment Tensor Catalogue was considered the most authoritative for moderate to large earthquakes for moment magnitude reports; hence it was used as a reference for calibrating other sources. The best fit was observed when compared to some regional agencies, whereas, with reports of moment magnitudes from Italy, Greece and Turkey, differences were observed in all magnitude ranges. For teleseismic magnitudes, to account for the non-linearity of the relationships, we used the exponential model for the derivation of the regression equations. The obtained regressions for the surface wave magnitude and short-period body-wave magnitude show considerable differences with Global Earthquake Model regression curves, especially for low magnitude ranges. Moreover, a conversion relation was obtained between the local magnitude of Albania and the corresponding moment magnitude as reported by the global and regional agencies. As errors were present in both variables, the Deming regression was used.

Keywords: regression, seismic catalogue, local magnitude, tele-seismic magnitude, moment magnitude

Procedia PDF Downloads 38

Authors: Fariza Yunus, Jasmee Jaafar, Zamalia Mahmud, Nurul Nisa’ Khairul Azmi, Nursalleh K. Chang, Nursalleh K. Chang

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Variation of air temperature from one place to another is cause by air temperature controls. In general, the most important control of air temperature is elevation. Another significant independent variable in estimating air temperature is the location of meteorological stations. Distances to coastline and land use type are also contributed to significant variations in the air temperature. On the other hand, in homogeneous terrain direct interpolation of discrete points of air temperature work well to estimate air temperature values in un-sampled area. In this process the estimation is solely based on discrete points of air temperature. However, this study presents that air temperature controls also play significant roles in estimating air temperature over homogenous terrain of Peninsular Malaysia. An Inverse Distance Weighting (IDW) interpolation technique was adopted to generate continuous data of air temperature. This study compared two different datasets, observed mean monthly data of T, and estimation error of T–T’, where T’ estimated value from a multiple regression model. The multiple regression model considered eight independent variables of elevation, latitude, longitude, coastline, and four land use types of water bodies, forest, agriculture and build up areas, to represent the role of air temperature controls. Cross validation analysis was conducted to review accuracy of the estimation values. Final results show, estimation values of T–T’ produced lower errors for mean monthly mean air temperature over homogeneous terrain in Peninsular Malaysia.

Keywords: air temperature control, interpolation analysis, peninsular Malaysia, regression model, air temperature

Procedia PDF Downloads 350

Authors: H. K. V. Narayan

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This study was conducted at Tata Memorial Hospital (TMH), Mumbai, India. The study was to evaluate the impact of adapting Smart Card (SC) for clinical and business transactions in order to reduce Lead times and to enforce business rules of the hospital. The objective for implementing the Smart Card was to improve the patient perception of quality in terms of structures process and outcomes and also to improve the productivity of the Institution. The Smart Card was implemented in phases from 2011 and integrated with the Hospital Information System (HIS/EMR). The implementation was a learning curve for all the stake holders as software obviated the need to use hardcopies of transactions. The acceptability to the stake holders was challenge in change management. The study assessed the impact 3 years into the implementation and the observed trends have suggested that it has decreased the lead times for services and increased the no of transactions and thereby the productivity. Patients who used to complain of multiple queues and cumbersome transactions now compliment the administration for effective use of Information and Communication Technology.

Keywords: smart card, high availability of health care information, reduction in potential medical errors due to elimination of transcription errors, reduction in no of queues, increased transactions, augmentation of revenue

Procedia PDF Downloads 257

Authors: Fatemeh Jannesarvatan, Ghazaal Parastooei, Jimmy frerejan, Saedeh Mokhtari, Peter Van Rosmalen

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Medical and dental education increasingly emphasizes the acquisition, integration, and coordination of complex knowledge, skills, and attitudes that can be applied in practical situations. Instructional design approaches have focused on using real-life tasks in order to facilitate complex learning in both real and simulated environments. The Four component instructional design (4C/ID) model has become a useful guideline for designing instructional materials that improve learning transfer, especially in health profession education. The objective of this study was to apply the 4C/ID model in the creation of virtual patients (VPs) that dental students can use to practice their clinical management and clinical reasoning skills. The study first explored the context and concept of complication factors and common errors for novices and how they can affect the design of a virtual patient program. The study then selected key dental information and considered the content needs of dental students. The design of virtual patients was based on the 4C/ID model's fundamental principles, which included: Designing learning tasks that reflect real patient scenarios and applying different levels of task complexity to challenge students to apply their knowledge and skills in different contexts. Creating varied learning materials that support students during the VP program and are closely integrated with the learning tasks and students' curricula. Cognitive feedback was provided at different levels of the program. Providing procedural information where students followed a step-by-step process from history taking to writing a comprehensive treatment plan. Four virtual patients were designed using the 4C/ID model's principles, and an experimental design was used to test the effectiveness of the principles in achieving the intended educational outcomes. The 4C/ID model provides an effective framework for designing engaging and successful virtual patients that support the transfer of knowledge and skills for dental students. However, there are some challenges and pitfalls that instructional designers should take into account when developing these educational tools.

Keywords: 4C/ID model, virtual patients, education, dental, instructional design

Procedia PDF Downloads 50

Authors: Sabyasachi Mukhopadhyay, Joseph Ogutu, Gundula Bartzke, Hans-Peter Piepho

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Rainfall is a critical component of climate governing vegetation growth and production, forage availability and quality for herbivores. However, reliable rainfall measurements are not always available, making it necessary to predict rainfall values for particular locations through time. Predicting rainfall in space and time can be a complex and challenging task, especially where the rain gauge network is sparse and measurements are not recorded consistently for all rain gauges, leading to many missing values. Here, we develop a flexible Bayesian model for predicting rainfall in space and time and apply it to Narok County, situated in southwestern Kenya, using data collected at 23 rain gauges from 1965 to 2015. Narok County encompasses the Maasai Mara ecosystem, the northern-most section of the Mara-Serengeti ecosystem, famous for its diverse and abundant large mammal populations and spectacular migration of enormous herds of wildebeest, zebra and Thomson's gazelle. The model incorporates geographical and meteorological predictor variables, including elevation, distance to Lake Victoria and minimum temperature. We assess the efficiency of the model by comparing it empirically with the established Gaussian process, Kriging, simple linear and Bayesian linear models. We use the model to predict total monthly rainfall and its standard error for all 5 * 5 km grid cells in Narok County. Using the Monte Carlo integration method, we estimate seasonal and annual rainfall and their standard errors for 29 sub-regions in Narok. Finally, we use the predicted rainfall to predict large herbivore biomass in the Maasai Mara ecosystem on a 5 * 5 km grid for both the wet and dry seasons. We show that herbivore biomass increases with rainfall in both seasons. The model can handle data from a sparse network of observations with many missing values and performs at least as well as or better than four established and widely used models, on the Narok data set. The model produces rainfall predictions consistent with expectation and in good agreement with the blended station and satellite rainfall values. The predictions are precise enough for most practical purposes. The model is very general and applicable to other variables besides rainfall.

Keywords: non-stationary covariance function, gaussian process, ungulate biomass, MCMC, maasai mara ecosystem

Procedia PDF Downloads 257

Authors: Mingyang Sun, Guozheng Yan, Dasheng Liu, Lei Yang

Abstract:

Driven by the demand of intelligent monitoring in rehabilitation centers or hospitals, a high accuracy real-time location system based on UWB (ultra-wideband) technology was proposed. The system measures precise location of a specific person, traces his movement and visualizes his trajectory on the screen for doctors or administrators. Therefore, doctors could view the position of the patient at any time and find them immediately and exactly when something emergent happens. In our design process, different algorithms were discussed, and their errors were analyzed. In addition, we discussed about a , simple but effective way of correcting the antenna delay error, which turned out to be effective. By choosing the best algorithm and correcting errors with corresponding methods, the system attained a good accuracy. Experiments indicated that the ranging error of the system is lower than 7 cm, the locating error is lower than 20 cm, and the refresh rate exceeds 5 times per second. In future works, by embedding the system in wearable IoT (Internet of Things) devices, it could provide not only physical parameters, but also the activity status of the patient, which would help doctors a lot in performing healthcare.

Keywords: intelligent monitoring, ultra-wideband technology, real-time location, IoT devices, smart healthcare

Procedia PDF Downloads 101