Search results for: measurement accuracy
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6125

Search results for: measurement accuracy

5405 Assessing an Instrument Usability: Response Interpolation and Scale Sensitivity

Authors: Betsy Ng, Seng Chee Tan, Choon Lang Quek, Peter Looker, Jaime Koh

Abstract:

The purpose of the present study was to determine the particular scale rating that stands out for an instrument. The instrument was designed to assess student perceptions of various learning environments, namely face-to-face, online and blended. The original instrument had a 5-point Likert items (1 = strongly disagree and 5 = strongly agree). Alternate versions were modified with a 6-point Likert scale and a bar scale rating. Participants consisted of undergraduates in a local university were involved in the usability testing of the instrument in an electronic setting. They were presented with the 5-point, 6-point and percentage-bar (100-point) scale ratings, in response to their perceptions of learning environments. The 5-point and 6-point Likert scales were presented in the form of radio button controls for each number, while the percentage-bar scale was presented with a sliding selection. Among these responses, 6-point Likert scale emerged to be the best overall. When participants were confronted with the 5-point items, they either chose 3 or 4, suggesting that data loss could occur due to the insensitivity of instrument. The insensitivity of instrument could be due to the discreet options, as evidenced by response interpolation. To avoid the constraint of discreet options, the percentage-bar scale rating was tested, but the participant responses were not well-interpolated. The bar scale might have provided a variety of responses without a constraint of a set of categorical options, but it seemed to reflect a lack of perceived and objective accuracy. The 6-point Likert scale was more likely to reflect a respondent’s perceived and objective accuracy as well as higher sensitivity. This finding supported the conclusion that 6-point Likert items provided a more accurate measure of the participant’s evaluation. The 5-point and bar scale ratings might not be accurately measuring the participants’ responses. This study highlighted the importance of the respondent’s perception of accuracy, respondent’s true evaluation, and the scale’s ease of use. Implications and limitations of this study were also discussed.

Keywords: usability, interpolation, sensitivity, Likert scales, accuracy

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5404 Real-Time Recognition of the Terrain Configuration to Improve Driving Stability for Unmanned Robots

Authors: Bongsoo Jeon, Jayoung Kim, Jihong Lee

Abstract:

Methods for measuring or estimating of ground shape by a laser range finder and a vision sensor (exteroceptive sensors) have critical weakness in terms that these methods need prior database built to distinguish acquired data as unique surface condition for driving. Also, ground information by exteroceptive sensors does not reflect the deflection of ground surface caused by the movement of UGVs. Therefore, this paper proposes a method of recognizing exact and precise ground shape using Inertial Measurement Unit (IMU) as a proprioceptive sensor. In this paper, firstly this method recognizes attitude of a robot in real-time using IMU and compensates attitude data of a robot with angle errors through analysis of vehicle dynamics. This method is verified by outdoor driving experiments of a real mobile robot.

Keywords: inertial measurement unit, laser range finder, real-time recognition of the ground shape, proprioceptive sensor

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5403 Dynamic Compensation for Environmental Temperature Variation in the Coolant Refrigeration Cycle as a Means of Increasing Machine-Tool Precision

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

Abstract:

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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5402 Predicting Options Prices Using Machine Learning

Authors: Krishang Surapaneni

Abstract:

The goal of this project is to determine how to predict important aspects of options, including the ask price. We want to compare different machine learning models to learn the best model and the best hyperparameters for that model for this purpose and data set. Option pricing is a relatively new field, and it can be very complicated and intimidating, especially to inexperienced people, so we want to create a machine learning model that can predict important aspects of an option stock, which can aid in future research. We tested multiple different models and experimented with hyperparameter tuning, trying to find some of the best parameters for a machine-learning model. We tested three different models: a Random Forest Regressor, a linear regressor, and an MLP (multi-layer perceptron) regressor. The most important feature in this experiment is the ask price; this is what we were trying to predict. In the field of stock pricing prediction, there is a large potential for error, so we are unable to determine the accuracy of the models based on if they predict the pricing perfectly. Due to this factor, we determined the accuracy of the model by finding the average percentage difference between the predicted and actual values. We tested the accuracy of the machine learning models by comparing the actual results in the testing data and the predictions made by the models. The linear regression model performed worst, with an average percentage error of 17.46%. The MLP regressor had an average percentage error of 11.45%, and the random forest regressor had an average percentage error of 7.42%

Keywords: finance, linear regression model, machine learning model, neural network, stock price

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5401 Engineering Method to Measure the Impact Sound Improvement with Floor Coverings

Authors: Katarzyna Baruch, Agata Szelag, Jaroslaw Rubacha, Bartlomiej Chojnacki, Tadeusz Kamisinski

Abstract:

Methodology used to measure the reduction of transmitted impact sound by floor coverings situated on a massive floor is described in ISO 10140-3: 2010. To carry out such tests, the standardised reverberation room separated by a standard floor from the second measuring room are required. The need to have a special laboratory results in high cost and low accessibility of this measurement. The authors propose their own engineering method to measure the impact sound improvement with floor coverings. This method does not require standard rooms and floor. This paper describes the measurement procedure of proposed engineering method. Further, verification tests were performed. Validation of the proposed method was based on the analytical model, Statistical Energy Analysis (SEA) model and empirical measurements. The received results were related to corresponding ones obtained from ISO 10140-3:2010 measurements. The study confirmed the usefulness of the engineering method.

Keywords: building acoustic, impact noise, impact sound insulation, impact sound transmission, reduction of impact sound

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5400 Towards Modern Approaches of Intelligence Measurement for Clinical and Educational Practices

Authors: Alena Kulikova, Tatjana Kanonire

Abstract:

Intelligence research is one of the oldest fields of psychology. Many factors have made a research on intelligence, defined as reasoning and problem solving [1, 2], a very acute and urgent problem. Thus, it has been repeatedly shown that intelligence is a predictor of academic, professional, and social achievement in adulthood (for example, [3]); Moreover, intelligence predicts these achievements better than any other trait or ability [4]. The individual level, a comprehensive assessment of intelligence is a necessary criterion for the diagnosis of various mental conditions. For example, it is a necessary condition for psychological, medical and pedagogical commissions when deciding on educational needs and the most appropriate educational programs for school children. Assessment of intelligence is crucial in clinical psychodiagnostic and needs high-quality intelligence measurement tools. Therefore, it is not surprising that the development of intelligence tests is an essential part of psychological science and practice. Many modern intelligence tests have a long history and have been used for decades, for example, the Stanford-Binet test or the Wechsler test. However, the vast majority of these tests are based on the classic linear test structure, in which all respondents receive all tasks (see, for example, a critical review by [5]). This understanding of the testing procedure is a legacy of the pre-computer era, in which blank testing was the only diagnostic procedure available [6] and has some significant limitations that affect the reliability of the data obtained [7] and increased time costs. Another problem with measuring IQ is that classical line-structured tests do not fully allow to measure respondent's intellectual progress [8], which is undoubtedly a critical limitation. Advances in modern psychometrics allow for avoiding the limitations of existing tools. However, as in any rapidly developing industry, at the moment, psychometrics does not offer ready-made and straightforward solutions and requires additional research. In our presentation we would like to discuss the strengths and weaknesses of the current approaches to intelligence measurement and highlight “points of growth” for creating a test in accordance with modern psychometrics. Whether it is possible to create the instrument that will use all achievements of modern psychometric and remain valid and practically oriented. What would be the possible limitations for such an instrument? The theoretical framework and study design to create and validate the original Russian comprehensive computer test for measuring the intellectual development in school-age children will be presented.

Keywords: Intelligence, psychometrics, psychological measurement, computerized adaptive testing, multistage testing

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5399 Modification of Newton Method in Two Point Block Backward Differentiation Formulas

Authors: Khairil I. Othman, Nur N. Kamal, Zarina B. Ibrahim

Abstract:

In this paper, we present modified Newton method as a new strategy for improving the efficiency of Two Point Block Backward Differentiation Formulas (BBDF) when solving stiff systems of ordinary differential equations (ODEs). These methods are constructed to produce two approximate solutions simultaneously at each iteration The detailed implementation of the predictor corrector BBDF with PE(CE)2 with modified Newton are discussed. The proposed modification of BBDF is validated through numerical results on some standard problems found in the literature and comparisons are made with the existing Block Backward Differentiation Formula. Numerical results show the advantage of using the new strategy for solving stiff ODEs in improving the accuracy of the solution.

Keywords: newton method, two point, block, accuracy

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5398 The Identification of Combined Genomic Expressions as a Diagnostic Factor for Oral Squamous Cell Carcinoma

Authors: Ki-Yeo Kim

Abstract:

Trends in genetics are transforming in order to identify differential coexpressions of correlated gene expression rather than the significant individual gene. Moreover, it is known that a combined biomarker pattern improves the discrimination of a specific cancer. The identification of the combined biomarker is also necessary for the early detection of invasive oral squamous cell carcinoma (OSCC). To identify the combined biomarker that could improve the discrimination of OSCC, we explored an appropriate number of genes in a combined gene set in order to attain the highest level of accuracy. After detecting a significant gene set, including the pre-defined number of genes, a combined expression was identified using the weights of genes in a gene set. We used the Principal Component Analysis (PCA) for the weight calculation. In this process, we used three public microarray datasets. One dataset was used for identifying the combined biomarker, and the other two datasets were used for validation. The discrimination accuracy was measured by the out-of-bag (OOB) error. There was no relation between the significance and the discrimination accuracy in each individual gene. The identified gene set included both significant and insignificant genes. One of the most significant gene sets in the classification of normal and OSCC included MMP1, SOCS3 and ACOX1. Furthermore, in the case of oral dysplasia and OSCC discrimination, two combined biomarkers were identified. The combined genomic expression achieved better performance in the discrimination of different conditions than in a single significant gene. Therefore, it could be expected that accurate diagnosis for cancer could be possible with a combined biomarker.

Keywords: oral squamous cell carcinoma, combined biomarker, microarray dataset, correlated genes

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5397 Effects of Foam Rolling with Different Application Volumes on the Isometric Force of the Calf Muscle with Consideration of Muscle Activity

Authors: T. Poppendieker, H. Maurer, C. Segieth

Abstract:

Over the past ten years, foam rolling has become a new trend in the fitness and health market. It is also a frequently used technique for self-massage. However, the scope of effects from foam rolling has only recently started to be researched and understood. The focus of this study is to examine the effects of prolonged foam rolling on muscle performance. Isometric muscle force was used as a parameter to determine an improving impact of the myofascial roller in two different application volumes. Besides the maximal muscle force, data were also collected on muscle activation during all tests. Twenty-four (17 females, 7 males) healthy students with an average age of 23.4 ± 2.8 years were recruited. The study followed a cross-over pre-/post design in which the order of conditions was counterbalanced. The subjects performed a one-minute and three-minute foam rolling application set on two separate days. Isometric maximal muscle force of the dominant calf was tested before and after the self-myofascial release application. The statistic software program SPSS 22 was used to analyze the data of the maximal isometric force of the calf muscle by a 2 x 2 (time of measurement x intervention) analysis of variance with repeated measures. The statistic significance level was set at p ≤ 0.05. Neither for the main effect of time of measurement (F(1,23) = .93, p = .36, f = .20) nor for the interaction of time of measurement x intervention (F(1,23) = 1.99, p = .17, f = 0.29) significant p-values were found. However, the effect size indicates a mean interaction effect with a tendency of greater pre-post improvements under the three-minute foam rolling condition. Changes in maximal force did not correlate with changes in EMG-activity (r = .02, p = .95 in the short and r = -.11, p = .65 in the long rolling condition). Results support findings of previous studies and suggest a positive potential for use of the foam roll as a means for keeping muscle force at least at the same performance level while leading to an increase in flexibility.

Keywords: application volume differences, foam rolling, isometric maximal force, self-myofascial release

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5396 Investigation of Dynamic Characteristic of Planetary Gear Set Based On Three-Axes Torque Measurement

Authors: Masao Nakagawa, Toshiki Hirogaki, Eiichi Aoyama, Mohamed Ali Ben Abbes

Abstract:

A planetary gear set is widely used in hybrid vehicles as the power distribution system or in electric vehicles as the high reduction system, but due to its complexity with planet gears, its dynamic characteristic is not fully understood. There are many reports on two-axes driving or displacement of the planet gears under these conditions, but only few reports deal with three-axes driving. A three-axes driving condition is tested using three-axes torque measurement and focuses on the dynamic characteristic around the planet gears in this report. From experimental result, it was confirmed that the transition forces around the planet gears were balanced and the torques were also balanced around the instantaneous rotation center. The meshing frequency under these conditions was revealed to be the harmonics of two meshing frequencies; meshing frequency of the ring gear and that of the planet gears. The input power of the ring gear is distributed to the carrier and the sun gear in the dynamic sequential change of three fixed conditions; planet, star and solar modes.

Keywords: dynamic characteristic, gear, planetary gear set, torque measuring

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5395 U-Net Based Multi-Output Network for Lung Disease Segmentation and Classification Using Chest X-Ray Dataset

Authors: Jaiden X. Schraut

Abstract:

Medical Imaging Segmentation of Chest X-rays is used for the purpose of identification and differentiation of lung cancer, pneumonia, COVID-19, and similar respiratory diseases. Widespread application of computer-supported perception methods into the diagnostic pipeline has been demonstrated to increase prognostic accuracy and aid doctors in efficiently treating patients. Modern models attempt the task of segmentation and classification separately and improve diagnostic efficiency; however, to further enhance this process, this paper proposes a multi-output network that follows a U-Net architecture for image segmentation output and features an additional CNN module for auxiliary classification output. The proposed model achieves a final Jaccard Index of .9634 for image segmentation and a final accuracy of .9600 for classification on the COVID-19 radiography database.

Keywords: chest X-ray, deep learning, image segmentation, image classification

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5394 Defects Classification of Stator Coil Generators by Phase Resolve Partial Discharge

Authors: Chun-Yao Lee, Nando Purba, Benny Iskandar

Abstract:

This paper proposed a phase resolve partial discharge (PRPD) shape method to classify types of defect stator coil generator by using off-line PD measurement instrument. The recorded PRPD, by using the instruments MPD600, can illustrate the PRPD patterns of partial discharge of unit’s defects. In the paper, two of large units, No.2 and No.3, in Inalum hydropower plant, North Sumatera, Indonesia is adopted in the experimental measurement. The proposed PRPD shape method is to mark auxiliary lines on the PRPD patterns. The shapes of PRPD from two units are marked with the proposed method. Then, four types of defects in IEC 60034-27 standard is adopted to classify the defect types of the two units, which types are microvoids (S1), delamination tape layer (S2), slot defect (S3) and internal delamination (S4). Finally, the two units are actually inspected to validate the availability of the proposed PRPD shape method.

Keywords: partial discharge (PD), stator coil, defect, phase resolve pd (PRPD)

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5393 Post-Earthquake Road Damage Detection by SVM Classification from Quickbird Satellite Images

Authors: Moein Izadi, Ali Mohammadzadeh

Abstract:

Detection of damaged parts of roads after earthquake is essential for coordinating rescuers. In this study, an approach is presented for the semi-automatic detection of damaged roads in a city using pre-event vector maps and both pre- and post-earthquake QuickBird satellite images. Damage is defined in this study as the debris of damaged buildings adjacent to the roads. Some spectral and texture features are considered for SVM classification step to detect damages. Finally, the proposed method is tested on QuickBird pan-sharpened images from the Bam City earthquake and the results show that an overall accuracy of 81% and a kappa coefficient of 0.71 are achieved for the damage detection. The obtained results indicate the efficiency and accuracy of the proposed approach.

Keywords: SVM classifier, disaster management, road damage detection, quickBird images

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5392 Three-Dimensional Measurement and Analysis of Facial Nerve Recess

Authors: Kang Shuo-Shuo, Li Jian-Nan, Yang Shiming

Abstract:

Purpose: The three-dimensional anatomical structure of the facial nerve recess and its relationship were measured by high-resolution temporal bone CT to provide imaging reference for cochlear implant operation. Materials and Methods: By analyzing the high-resolution CT of 160 cases (320 pleural ears) of the temporal bone, the following parameters were measured at the axial window niche level: 1. The distance between the facial nerve and chordae tympani nerve d1; 2. Distance between the facial nerve and circular window niche d2; 3. The relative Angle between the facial nerve and the circular window niche a; 4. Distance between the middle point of the face recess and the circular window niche d3; 5. The relative angle between the middle point of the face recess and the circular window niche b. Factors that might influence the anatomy of the facial recess were recorded, including the patient's sex, age, and anatomical variation (e.g., vestibular duct dilation, mastoid gas type, mothoid sinus advancement, jugular bulbar elevation, etc.), and the correlation between these factors and the measured facial recess parameters was analyzed. Result: The mean value of face-drum distance d1 is (3.92 ± 0.26) mm, the mean value of face-niche distance d2 is (5.95 ± 0.62) mm, the mean value of face-niche Angle a is (94.61 ± 9.04) °, and the mean value of fossa - niche distance d3 is (6.46 ± 0.63) mm. The average fossa-niche Angle b was (113.47 ± 7.83) °. Gender, age, and anterior sigmoid sinus were the three factors affecting the width of the opposite recess d1, the Angle of the opposite nerve relative to the circular window niche a, and the Angle of the facial recess relative to the circular window niche b. Conclusion: High-resolution temporal bone CT before cochlear implantation can show the important anatomical relationship of the facial nerve recess, and the measurement results have clinical reference value for the operation of cochlear implantation.

Keywords: cochlear implantation, recess of facial nerve, temporal bone CT, three-dimensional measurement

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5391 Upon One Smoothing Problem in Project Management

Authors: Dimitri Golenko-Ginzburg

Abstract:

A CPM network project with deterministic activity durations, in which activities require homogenous resources with fixed capacities, is considered. The problem is to determine the optimal schedule of starting times for all network activities within their maximal allowable limits (in order not to exceed the network's critical time) to minimize the maximum required resources for the project at any point in time. In case when a non-critical activity may start only at discrete moments with the pregiven time span, the problem becomes NP-complete and an optimal solution may be obtained via a look-over algorithm. For the case when a look-over requires much computational time an approximate algorithm is suggested. The algorithm's performance ratio, i.e., the relative accuracy error, is determined. Experimentation has been undertaken to verify the suggested algorithm.

Keywords: resource smoothing problem, CPM network, lookover algorithm, lexicographical order, approximate algorithm, accuracy estimate

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5390 Measuring Housing Quality Using Geographic Information System (GIS)

Authors: Silvija ŠIljeg, Ante ŠIljeg, Ivan Marić

Abstract:

Measuring housing quality is being done on objective and subjective level using different indicators. During the research 5 urban and housing indicators formed according to 58 variables from different housing, domains were used. The aims of the research were to measure housing quality based on GIS approach and to detect critical points of housing in the example of Croatian coastal Town Zadar. The purposes of GIS in the research are to generate models of housing quality indexes by standardisation and aggregation of variables and to examine accuracy model of housing quality index. Analysis of accuracy has been done on the example of variable referring to educational objects availability. By defining weighted coefficients and using different GIS methods high, middle and low housing quality zones were determined. Obtained results can be of use to town planners, spatial planners and town authorities in the process of generating decisions, guidelines, and spatial interventions.

Keywords: housing quality, GIS, housing quality index, indicators, models of housing quality

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5389 Role of Pulp Volume Method in Assessment of Age and Gender in Lucknow, India, an Observational Study

Authors: Anurag Tripathi, Sanad Khandelwal

Abstract:

Age and gender determination are required in forensic for victim identification. There is secondary dentine deposition throughout life, resulting in decreased pulp volume and size. Evaluation of pulp volume using Cone Beam Computed Tomography (CBCT)is a noninvasive method to evaluate the age and gender of an individual. The study was done to evaluate the efficacy of pulp volume method in the determination of age and gender.Aims/Objectives: The study was conducted to estimate age and determine sex by measuring tooth pulp volume with the help of CBCT. An observational study of one year duration on CBCT data of individuals was conducted in Lucknow. Maxillary central incisors (CI) and maxillary canine (C) of the randomly selected samples were assessed for measurement of pulp volume using a software. Statistical analysis: Chi Square Test, Arithmetic Mean, Standard deviation, Pearson’s Correlation, Linear & Logistic regression analysis. Results: The CBCT data of Ninety individuals with age range between 18-70 years was evaluated for pulp volume of central incisor and canine (CI & C). The Pearson correlation coefficient between the tooth pulp volume (CI & C) and chronological age suggested that pulp volume decreased with age. The validation of the equations for sex determination showed higher prediction accuracy for CI (56.70%) and lower for C (53.30%).Conclusion: Pulp volume obtained from CBCT is a reliable indicator for age estimation and gender prediction.

Keywords: forensic, dental age, pulp volume, cone beam computed tomography

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5388 Impact of Integrated Signals for Doing Human Activity Recognition Using Deep Learning Models

Authors: Milagros Jaén-Vargas, Javier García Martínez, Karla Miriam Reyes Leiva, María Fernanda Trujillo-Guerrero, Francisco Fernandes, Sérgio Barroso Gonçalves, Miguel Tavares Silva, Daniel Simões Lopes, José Javier Serrano Olmedo

Abstract:

Human Activity Recognition (HAR) is having a growing impact in creating new applications and is responsible for emerging new technologies. Also, the use of wearable sensors is an important key to exploring the human body's behavior when performing activities. Hence, the use of these dispositive is less invasive and the person is more comfortable. In this study, a database that includes three activities is used. The activities were acquired from inertial measurement unit sensors (IMU) and motion capture systems (MOCAP). The main objective is differentiating the performance from four Deep Learning (DL) models: Deep Neural Network (DNN), Convolutional Neural Network (CNN), Recurrent Neural Network (RNN) and hybrid model Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM), when considering acceleration, velocity and position and evaluate if integrating the IMU acceleration to obtain velocity and position represent an increment in performance when it works as input to the DL models. Moreover, compared with the same type of data provided by the MOCAP system. Despite the acceleration data is cleaned when integrating, results show a minimal increase in accuracy for the integrated signals.

Keywords: HAR, IMU, MOCAP, acceleration, velocity, position, feature maps

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5387 A Multimodal Measurement Approach Using Narratives and Eye Tracking to Investigate Visual Behaviour in Perceiving Naturalistic and Urban Environments

Authors: Khizar Z. Choudhrya, Richard Coles, Salman Qureshi, Robert Ashford, Salim Khan, Rabia R. Mir

Abstract:

Abstract: The majority of existing landscape research has been derived by conducting heuristic evaluations, without having empirical insight of real participant visual response. In this research, a modern multimodal measurement approach (using narratives and eye tracking) was applied to investigate visual behaviour in perceiving naturalistic and urban environments. This research is unique in exploring gaze behaviour on environmental images possessing different levels of saliency. Eye behaviour is predominantly attracted by salient locations. The concept of methodology of this research on naturalistic and urban environments is drawn from the approaches in market research. Borrowing methodologies from market research that examine visual responses and qualities provided a critical and hitherto unexplored approach. This research has been conducted by using mixed methodological quantitative and qualitative approaches. On the whole, the results of this research corroborated existing landscape research findings, but they also identified potential refinements. The research contributes both methodologically and empirically to human-environment interaction (HEI). This study focused on initial impressions of environmental images with the help of eye tracking. Taking under consideration the importance of the image, this study explored the factors that influence initial fixations in relation to expectations and preferences. In terms of key findings of this research it is noticed that each participant has his own unique navigation style while surfing through different elements of landscape images. This individual navigation style is given the name of ‘visual signature’. This study adds the necessary clarity that would complete the picture and bring an insight for future landscape researchers.

Keywords: human-environment interaction (HEI), multimodal measurement, narratives, eye tracking

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5386 Feasibility Study and Experiment of On-Site Nuclear Material Identification in Fukushima Daiichi Fuel Debris by Compact Neutron Source

Authors: Yudhitya Kusumawati, Yuki Mitsuya, Tomooki Shiba, Mitsuru Uesaka

Abstract:

After the Fukushima Daiichi nuclear power reactor incident, there are a lot of unaccountable nuclear fuel debris in the reactor core area, which is subject to safeguard and criticality safety. Before the actual precise analysis is performed, preliminary on-site screening and mapping of nuclear debris activity need to be performed to provide a reliable data on the nuclear debris mass-extraction planning. Through a collaboration project with Japan Atomic Energy Agency, an on-site nuclear debris screening system by using dual energy X-Ray inspection and neutron energy resonance analysis has been established. By using the compact and mobile pulsed neutron source constructed from 3.95 MeV X-Band electron linac, coupled with Tungsten as electron-to-photon converter and Beryllium as a photon-to-neutron converter, short-distance neutron Time of Flight measurement can be performed. Experiment result shows this system can measure neutron energy spectrum up to 100 eV range with only 2.5 meters Time of Flightpath in regards to the X-Band accelerator’s short pulse. With this, on-site neutron Time of Flight measurement can be used to identify the nuclear debris isotope contents through Neutron Resonance Transmission Analysis (NRTA). Some preliminary NRTA experiments have been done with Tungsten sample as dummy nuclear debris material, which isotopes Tungsten-186 has close energy absorption value with Uranium-238 (15 eV). The results obtained shows that this system can detect energy absorption in the resonance neutron area within 1-100 eV. It can also detect multiple elements in a material at once with the experiment using a combined sample of Indium, Tantalum, and silver makes it feasible to identify debris containing mixed material. This compact neutron Time of Flight measurement system is a great complementary for dual energy X-Ray Computed Tomography (CT) method that can identify atomic number quantitatively but with 1-mm spatial resolution and high error bar. The combination of these two measurement methods will able to perform on-site nuclear debris screening at Fukushima Daiichi reactor core area, providing the data for nuclear debris activity mapping.

Keywords: neutron source, neutron resonance, nuclear debris, time of flight

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5385 The Quality of Economic Growth Regency and Cities in West Java Province: Inclusive Economic Growth

Authors: Fryanto Anugrah Rhamdhani Rhamdhani, Hana Riana Permatasari

Abstract:

The aim of this study analyzes the inclusive of economic growth and analyzes the inclusive of economic growth determinant in regency and city (West Java Province). The background this study Economic Growth can do not afford to reduce poverty, Disparity and expand The Workforce. Referring Central Bureau Of Statistic West Java Province report in 2015 recorded only 5 regions able reduce poverty, 3 regions able reduce Gini Ratio and 7 regions able Workforce Absorption, meanwhile, 11 regions was improved Economic Growth. The Inclusive of Economic Growth definition based on various literature means the quality Economic Growth able reduce Poverty, Gini Ratio, and Workforce absorption. This study adopted the measurement Inclusive Economic of Growth Klassen and analyzes factor in Term Reducing Poverty, Gini Ratio, and the workforce Absorption. Data used panels data composite time series and cross-section including 25 regency and cities regions from Central Bureau Of Statistic West Java Province during 2014-2015. As a result, the measurement inclusive economic of growth Klassen 2014-2015 from 25 regency and cities shows all region does not inclusive reducing Poverty, only 2 regions able reduce Gini Ratio and 3 regions able increase Workforce absorption. Different from the result the measurement Inclusive Economic of Growth for workforce absorption, several regions shows a negative coefficient indicates Economic Growth decline Workforce absorption. The outcome of this study analyzes factor of Inclusive economic of Growth, so that give recommendations for government achieve inclusive economic of growth toward Sustainable Economic. Can be Concluded above low-quality Economic Growth, that due to all region does not inclusive Economic of Growth.

Keywords: inclusive economic growth, Gini ratio, poverty, workforce

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5384 An Intelligent Steerable Drill System for Orthopedic Surgery

Authors: Wei Yao

Abstract:

A steerable and flexible drill is needed in orthopaedic surgery. For example, osteoarthritis is a common condition affecting millions of people for which joint replacement is an effective treatment which improves the quality and duration of life in elderly sufferers. Conventional surgery is not very accurate. Computer navigation and robotics can help increase the accuracy. For example, In Total Hip Arthroplasty (THA), robotic surgery is currently practiced mainly on acetabular side helping cup positioning and orientation. However, femoral stem positioning mostly uses hand-rasping method rather than robots for accurate positioning. The other case for using a flexible drill in surgery is Anterior Cruciate Ligament (ACL) Reconstruction. The majority of ACL Reconstruction failures are primarily caused by technical mistakes and surgical errors resulting from drilling the anatomical bone tunnels required to accommodate the ligament graft. The proposed new steerable drill system will perform orthopedic surgery through curved tunneling leading to better accuracy and patient outcomes. It may reduce intra-operative fractures, dislocations, early failure and leg length discrepancy by making possible a new level of precision. This technology is based on a robotically assisted, steerable, hand-held flexible drill, with a drill-tip tracking device and a multi-modality navigation system. The critical differentiator is that this robotically assisted surgical technology now allows the surgeon to prepare 'patient specific' and more anatomically correct 'curved' bone tunnels during orthopedic surgery rather than drilling straight holes as occurs currently with existing surgical tools. The flexible and steerable drill and its navigation system for femoral milling in total hip arthroplasty had been tested on sawbones to evaluate the accuracy of the positioning and orientation of femoral stem relative to the pre-operative plan. The data show the accuracy of the navigation system is better than traditional hand-rasping method.

Keywords: navigation, robotic orthopedic surgery, steerable drill, tracking

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5383 MIM and Experimental Studies of the Thermal Drift in an Ultra-High Precision Instrument for Dimensional Metrology

Authors: Kamélia Bouderbala, Hichem Nouira, Etienne Videcoq, Manuel Girault, Daniel Petit

Abstract:

Thermal drifts caused by the power dissipated by the mechanical guiding systems constitute the main limit to enhance the accuracy of an ultra-high precision cylindricity measuring machine. For this reason, a high precision compact prototype has been designed to simulate the behaviour of the instrument. It ensures in situ calibration of four capacitive displacement probes by comparison with four laser interferometers. The set-up includes three heating wires for simulating the powers dissipated by the mechanical guiding systems, four additional heating wires located between each laser interferometer head and its respective holder, 19 Platinum resistance thermometers (Pt100) to observe the temperature evolution inside the set-up and four Pt100 sensors to monitor the ambient temperature. Both a Reduced Model (RM), based on the Modal Identification Method (MIM) was developed and optimized by comparison with the experimental results. Thereafter, time dependent tests were performed under several conditions to measure the temperature variation at 19 fixed positions in the system and compared to the calculated RM results. The RM results show good agreement with experiment and reproduce as well the temperature variations, revealing the importance of the RM proposed for the evaluation of the thermal behaviour of the system.

Keywords: modal identification method (MIM), thermal behavior and drift, dimensional metrology, measurement

Procedia PDF Downloads 396
5382 Accuracy of Autonomy Navigation of Unmanned Aircraft Systems through Imagery

Authors: Sidney A. Lima, Hermann J. H. Kux, Elcio H. Shiguemori

Abstract:

The Unmanned Aircraft Systems (UAS) usually navigate through the Global Navigation Satellite System (GNSS) associated with an Inertial Navigation System (INS). However, GNSS can have its accuracy degraded at any time or even turn off the signal of GNSS. In addition, there is the possibility of malicious interferences, known as jamming. Therefore, the image navigation system can solve the autonomy problem, because if the GNSS is disabled or degraded, the image navigation system would continue to provide coordinate information for the INS, allowing the autonomy of the system. This work aims to evaluate the accuracy of the positioning though photogrammetry concepts. The methodology uses orthophotos and Digital Surface Models (DSM) as a reference to represent the object space and photograph obtained during the flight to represent the image space. For the calculation of the coordinates of the perspective center and camera attitudes, it is necessary to know the coordinates of homologous points in the object space (orthophoto coordinates and DSM altitude) and image space (column and line of the photograph). So if it is possible to automatically identify in real time the homologous points the coordinates and attitudes can be calculated whit their respective accuracies. With the methodology applied in this work, it is possible to verify maximum errors in the order of 0.5 m in the positioning and 0.6º in the attitude of the camera, so the navigation through the image can reach values equal to or higher than the GNSS receivers without differential correction. Therefore, navigating through the image is a good alternative to enable autonomous navigation.

Keywords: autonomy, navigation, security, photogrammetry, remote sensing, spatial resection, UAS

Procedia PDF Downloads 192
5381 A Method to Enhance the Accuracy of Digital Forensic in the Absence of Sufficient Evidence in Saudi Arabia

Authors: Fahad Alanazi, Andrew Jones

Abstract:

Digital forensics seeks to achieve the successful investigation of digital crimes through obtaining acceptable evidence from digital devices that can be presented in a court of law. Thus, the digital forensics investigation is normally performed through a number of phases in order to achieve the required level of accuracy in the investigation processes. Since 1984 there have been a number of models and frameworks developed to support the digital investigation processes. In this paper, we review a number of the investigation processes that have been produced throughout the years and introduce a proposed digital forensic model which is based on the scope of the Saudi Arabia investigation process. The proposed model has been integrated with existing models for the investigation processes and produced a new phase to deal with a situation where there is initially insufficient evidence.

Keywords: digital forensics, process, metadata, Traceback, Sauid Arabia

Procedia PDF Downloads 360
5380 Fault Diagnosis of Nonlinear Systems Using Dynamic Neural Networks

Authors: E. Sobhani-Tehrani, K. Khorasani, N. Meskin

Abstract:

This paper presents a novel integrated hybrid approach for fault diagnosis (FD) of nonlinear systems. Unlike most FD techniques, the proposed solution simultaneously accomplishes fault detection, isolation, and identification (FDII) within a unified diagnostic module. At the core of this solution is a bank of adaptive neural parameter estimators (NPE) associated with a set of single-parameter fault models. The NPEs continuously estimate unknown fault parameters (FP) that are indicators of faults in the system. Two NPE structures including series-parallel and parallel are developed with their exclusive set of desirable attributes. The parallel scheme is extremely robust to measurement noise and possesses a simpler, yet more solid, fault isolation logic. On the contrary, the series-parallel scheme displays short FD delays and is robust to closed-loop system transients due to changes in control commands. Finally, a fault tolerant observer (FTO) is designed to extend the capability of the NPEs to systems with partial-state measurement.

Keywords: hybrid fault diagnosis, dynamic neural networks, nonlinear systems, fault tolerant observer

Procedia PDF Downloads 402
5379 Automatic Number Plate Recognition System Based on Deep Learning

Authors: T. Damak, O. Kriaa, A. Baccar, M. A. Ben Ayed, N. Masmoudi

Abstract:

In the last few years, Automatic Number Plate Recognition (ANPR) systems have become widely used in the safety, the security, and the commercial aspects. Forethought, several methods and techniques are computing to achieve the better levels in terms of accuracy and real time execution. This paper proposed a computer vision algorithm of Number Plate Localization (NPL) and Characters Segmentation (CS). In addition, it proposed an improved method in Optical Character Recognition (OCR) based on Deep Learning (DL) techniques. In order to identify the number of detected plate after NPL and CS steps, the Convolutional Neural Network (CNN) algorithm is proposed. A DL model is developed using four convolution layers, two layers of Maxpooling, and six layers of fully connected. The model was trained by number image database on the Jetson TX2 NVIDIA target. The accuracy result has achieved 95.84%.

Keywords: ANPR, CS, CNN, deep learning, NPL

Procedia PDF Downloads 307
5378 Technological Enhancements in Supply Chain Management Post COVID-19

Authors: Miran Ismail

Abstract:

COVID-19 has caused widespread disruption in all economical sectors and industries around the world. The COVID-19 lockdown measures have resulted in production halts, restrictions on persons and goods movement, border closures, logistical constraints, and a slowdown in trade and economic activity. The main subject of this paper is to leverage technology to manage the supply chain effectively and efficiently through the usage of artificial intelligence. The research methodology is based on empirical data collected through a questionnaire survey. One of the approaches utilized is a case study of industrial organizations that face obstacles such as high operational costs, large inventory levels, a lack of well-established supplier relationships, human behavior, and system issues. The main contribution of this research to the body of knowledge is the empirical insights and on supply chain sustainability performance measurement. The results provide guidelines for the selection of advanced technologies to support supply chain processes and for the design of sustainable performance measurement systems.

Keywords: information technology, artificial intelligence, supply chain management, industrial organizations

Procedia PDF Downloads 125
5377 A Comparative Soft Computing Approach to Supplier Performance Prediction Using GEP and ANN Models: An Automotive Case Study

Authors: Seyed Esmail Seyedi Bariran, Khairul Salleh Mohamed Sahari

Abstract:

In multi-echelon supply chain networks, optimal supplier selection significantly depends on the accuracy of suppliers’ performance prediction. Different methods of multi criteria decision making such as ANN, GA, Fuzzy, AHP, etc have been previously used to predict the supplier performance but the “black-box” characteristic of these methods is yet a major concern to be resolved. Therefore, the primary objective in this paper is to implement an artificial intelligence-based gene expression programming (GEP) model to compare the prediction accuracy with that of ANN. A full factorial design with %95 confidence interval is initially applied to determine the appropriate set of criteria for supplier performance evaluation. A test-train approach is then utilized for the ANN and GEP exclusively. The training results are used to find the optimal network architecture and the testing data will determine the prediction accuracy of each method based on measures of root mean square error (RMSE) and correlation coefficient (R2). The results of a case study conducted in Supplying Automotive Parts Co. (SAPCO) with more than 100 local and foreign supply chain members revealed that, in comparison with ANN, gene expression programming has a significant preference in predicting supplier performance by referring to the respective RMSE and R-squared values. Moreover, using GEP, a mathematical function was also derived to solve the issue of ANN black-box structure in modeling the performance prediction.

Keywords: Supplier Performance Prediction, ANN, GEP, Automotive, SAPCO

Procedia PDF Downloads 421
5376 Evaluate the Possibility of Using ArcGIS Basemaps as GCP for Large Scale Maps

Authors: Jali Octariady, Ida Herliningsih, Ade K. Mulyana, Annisa Fitria, Diaz C. K. Yuwana

Abstract:

Awareness of the importance large-scale maps for development of a country is growing in all walks of life, especially for governments in Indonesia. Various parties, especially local governments throughout Indonesia demanded for immediate availability the large-scale maps of 1:5000 for regional development. But in fact, the large-scale maps of 1:5000 is only available less than 5% of the entire territory of Indonesia. Unavailability precise GCP at the entire territory of Indonesia is one of causes of slow availability the large scale maps of 1:5000. This research was conducted to find an alternative solution to this problem. This study was conducted to assess the accuracy of ArcGIS base maps coordinate when it shall be used as GCP for creating a map scale of 1:5000. The study was conducted by comparing the GCP coordinate from Field survey using GPS Geodetic than the coordinate from ArcGIS basemaps in various locations in Indonesia. Some areas are used as a study area are Lombok Island, Kupang City, Surabaya City and Kediri District. The differences value of the coordinates serve as the basis for assessing the accuracy of ArcGIS basemaps coordinates. The results of the study at various study area show the variation of the amount of the coordinates value given. Differences coordinate value in the range of millimeters (mm) to meters (m) in the entire study area. This is shown the inconsistency quality of ArcGIS base maps coordinates. This inconsistency shows that the coordinate value from ArcGIS Basemaps is careless. The Careless coordinate from ArcGIS Basemaps indicates that its cannot be used as GCP for large-scale mapping on the entire territory of Indonesia.

Keywords: accuracy, ArcGIS base maps, GCP, large scale maps

Procedia PDF Downloads 374