Search results for: machining error

Authors: Huai-Feng Wang, Meng-Lin Lou, Ru-Lin Zhang

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One good analysis method in seismic response analysis is direct time integration, which widely adopts Rayleigh damping. An approach is presented for selection of Rayleigh damping coefficients to be used in seismic analyses to produce a response that is consistent with Modal damping response. In the presented approach, the expression of the error of peak response, acquired through complete quadratic combination method, and Rayleigh damping coefficients was set up and then the coefficients were produced by minimizing the error. Two finite element modes of soil layers, excited by 28 seismic waves, were used to demonstrate the feasibility and validity.

Keywords: Rayleigh damping, modal damping, damping coefficients, seismic response analysis

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Authors: Isaac Kayode Ogunlade

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Data acquisition (DAQ) is the process by which physical phenomena from the real world are transformed into an electrical signal(s) that are measured and converted into a digital format for processing, analysis, and storage by a computer. The DAQ is designed using PIC18F4550 microcontroller, communicating with Personal Computer (PC) through USB (Universal Serial Bus). The research deployed initial knowledge of data acquisition system and embedded system to develop a weather data acquisition device using LM35 sensor to measure weather parameters and the use of Artificial Intelligence(Artificial Neural Network - ANN)and statistical approach(Autoregressive Integrated Moving Average – ARIMA) to predict precipitation (rainfall). The device is placed by a standard device in the Department of Meteorology, Federal University of Technology, Akure (FUTA) to know the performance evaluation of the device. Both devices (standard and designed) were subjected to 180 days with the same atmospheric condition for data mining (temperature, relative humidity, and pressure). The acquired data is trained in MATLAB R2012b environment using ANN, and ARIMAto predict precipitation (rainfall). Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Correction Square (R2), and Mean Percentage Error (MPE) was deplored as standardize evaluation to know the performance of the models in the prediction of precipitation. The results from the working of the developed device show that the device has an efficiency of 96% and is also compatible with Personal Computer (PC) and laptops. The simulation result for acquired data shows that ANN models precipitation (rainfall) prediction for two months (May and June 2017) revealed a disparity error of 1.59%; while ARIMA is 2.63%, respectively. The device will be useful in research, practical laboratories, and industrial environments.

Keywords: data acquisition system, design device, weather development, predict precipitation and (FUTA) standard device

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Authors: Sachin Pawar, Suman Patra, Goutam Mukhopadhyay

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The primary function of a shaft is to transfer power. The shaft can be cast or forged and then machined to the final shape. Manufacturing of ~5 m length and 0.6 m diameter shaft is very critical. More difficult is to maintain its straightness during heat treatment and machining operations, which involve thermal and mechanical loads, respectively. During the machining operation of a such forged mandrel shaft, a deflection of 3-4mm was observed. To remove this deflection shaft was pressed at both ends which led to the development of cracks in it. To investigate the root cause of the deflection and cracking, the sample was cut from the failed shaft. Possible causes were identified with the help of a cause and effect diagram. Chemical composition analysis, microstructural analysis, and hardness measurement were done to confirm whether the shaft meets the required specifications or not. Chemical composition analysis confirmed that the material grade was 42CrMo4. Microstructural analysis revealed the presence of untempered martensite, indicating improper heat treatment. Due to this, ductility and impact toughness values were considerably lower than the specification of the mentioned grade. Residual stress measurement of one more bent shaft manufactured by a similar route was done by portable X-ray diffraction(XRD) technique. For better understanding, measurements were done at twelve different locations along the length of the shaft. The occurrence of a high amount of undesirable tensile residual stresses close to the Ultimate Tensile Strength(UTS) of the material was observed. Untempered martensitic structure, lower ductility, lower impact strength, and presence of a high amount of residual stresses all confirmed the improper tempering heat treatment of the shaft. Tempering relieves the residual stresses. Based on the findings of this study, stress-relieving heat treatment was done to remove the residual stresses and deflection in the shaft successfully.

Keywords: residual stress, mandrel shaft, untempered martensite, portable XRD

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Authors: Fatima Babar, Majid I. Khan, Malik Najmus Saqib, Muhammad Tahir

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This article provides range based improvements over a well-known single-hop range free localization scheme, Approximate Point in Triangulation (APIT) by proposing an energy efficient Barycentric coordinate based Point-In-Triangulation (PIT) test along with PIT based trilateration. These improvements result in energy efficiency, reduced localization error and improved localization coverage compared to APIT and its variants. Moreover, we propose to embed Received signal strength indication (RSSI) based distance estimation in DV-Hop which is a multi-hop localization scheme. The proposed localization algorithm achieves energy efficiency and reduced localization error compared to DV-Hop and its available improvements. Furthermore, a hybrid multi-hop localization scheme is also proposed that utilize Barycentric coordinate based PIT test and both range based (Received signal strength indicator) and range free (hop count) techniques for distance estimation. Our experimental results provide evidence that proposed hybrid multi-hop localization scheme results in two to five times reduction in the localization error compare to DV-Hop and its variants, at reduced energy requirements.

Keywords: Localization, Trilateration, Triangulation, Wireless Sensor Networks

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Authors: Jongwan Kim

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Human Computer Interaction (HCI) is a subject covering the study, plan, and design of interactions between humans and computers. The prevalent use of digital mobile devices is increasing the need for education and research on HCI. This work is focused on a new education method geared towards reducing errors while developing application programs that incorporate role-changing brainstorming techniques during HCI design process. The proposed method has been applied to a capstone design course in the last spring semester. Students discovered some examples about UI design improvement and their error discovering and reducing capability was promoted. An UI design improvement, PC voice control for people with disabilities as an assistive technology examplar, will be presented. The improvement of these students' design ability will be helpful to the real field work.

Keywords: HCI, design process, error reducing education, role-changing brainstorming, assistive technology

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Authors: Himayatullah Khan, Alena Fedorova

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The present paper analyses the income-consumption relationships in Pakistan using annual time series data from 1980-81 to 2010-1. The paper uses the Augmented Dickey-Fuller test to check the unit root and stationarity in these two time series. The paper finds that the two time series are nonstationary but stationary at their first difference levels. The Augmented Engle-Granger test and the Cointegrating Regression Durbin-Watson test imply that the two time series of consumption and income are cointegrated and that long-run marginal propensity to consume is 0.88 which is given by the estimated (static) equilibrium relation. The paper also used the error correction mechanism to find out to model dynamic relationship. The purpose of the ECM is to indicate the speed of adjustment from the short-run equilibrium to the long-run equilibrium state. The results show that MPC is equal to 0.93 and is highly significant. The coefficient of Engle-Granger residuals is negative but insignificant. Statistically, the equilibrium error term is zero, which suggests that consumption adjusts to changes in GDP in the same period. The short-run changes in GDP have a positive impact on short-run changes in consumption. The paper concludes that we may interpret 0.93 as the short-run MPC. The pair-wise Granger Causality test shows that both GDP and consumption Granger cause each other.

Keywords: cointegrating regression, Augmented Dickey Fuller test, Augmented Engle-Granger test, Granger causality, error correction mechanism

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Authors: Hussam Elias, Ninovic Perez, Holger Hirsch

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The completion of the EMC regulations worldwide is growing steadily as the usage of electronics in our daily lives is increasing more than ever. In this paper, we introduce a novel method to perform the final phase of Electromagnetic compatibility (EMC) measurement and to reduce the required test time according to the norm EN 55032 by using a developed tool and the conventional neural network(CNN). The neural network was trained using real EMC measurements, which were performed in the Semi Anechoic Chamber (SAC) by CETECOM GmbH in Essen, Germany. To implement our proposed method, we wrote software to perform the radiated electromagnetic interference (EMI) measurements and use the CNN to predict and determine the position of the turntable that meets the maximum radiation value.

Keywords: conventional neural network, electromagnetic compatibility measurement, mean absolute error, position error

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Authors: M. N. Islam, B. Boswell, Y. R. Ginting

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The influence of canned cycles and cutting parameters on hole quality in cryogenic drilling has been investigated experimentally and analytically. A three-level, three-parameter experiment was conducted by using the design-of-experiment methodology. The three levels of independent input parameters were the following: for canned cycles—a chip-breaking canned cycle (G73), a spot drilling canned cycle (G81), and a deep hole canned cycle (G83); for feed rates—0.2, 0.3, and 0.4 mm/rev; and for cutting speeds—60, 75, and 100 m/min. The selected work and tool materials were aluminum 6061-6T and high-speed steel (HSS), respectively. For cryogenic cooling, liquid nitrogen (LN2) was used and was applied externally. The measured output parameters were the three widely used quality characteristics of drilled holes—diameter error, circularity, and surface roughness. Pareto ANOVA was applied for analyzing the results. The findings revealed that the canned cycle has a significant effect on diameter error (contribution ratio 44.09%) and small effects on circularity and surface finish (contribution ratio 7.25% and 6.60%, respectively). The best results for the dimensional accuracy and surface roughness were achieved by G81. G73 produced the best circularity results; however, for dimensional accuracy, it was the worst level.

Keywords: circularity, diameter error, drilling canned cycle, pareto ANOVA, surface roughness

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Authors: Mohammad Heidari

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

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

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Authors: Vineeth G. Kuriakose, Joseph C. Chen, Ye Li

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The research follows a systematic approach to optimize the parameters for parts machined by turning and milling processes. The quality characteristic chosen is surface roughness since the surface finish plays an important role for parts that require surface contact. A tapered cylindrical surface is designed as a test specimen for the research. The material chosen for machining is aluminum alloy 6061 due to its wide variety of industrial and engineering applications. HAAS VF-2 TR computer numerical control (CNC) vertical machining center is used for milling and HAAS ST-20 CNC machine is used for turning in this research. Taguchi analysis is used to optimize the surface roughness of the machined parts. The L₉ Orthogonal Array is designed for four controllable factors with three different levels each, resulting in 18 experimental runs. Signal to Noise (S/N) Ratio is calculated for achieving the specific target value of 75 ± 15 µin. The controllable parameters chosen for turning process are feed rate, depth of cut, coolant flow and finish cut and for milling process are feed rate, spindle speed, step over and coolant flow. The uncontrollable factors are tool geometry for turning process and tool material for milling process. Hypothesis testing is conducted to study the significance of different uncontrollable factors on the surface roughnesses. The optimal parameter settings were identified from the Taguchi analysis and the process capability C_p and the process capability index C_pk were improved from 1.76 and 0.02 to 3.70 and 2.10 respectively for turning process and from 0.87 and 0.19 to 3.85 and 2.70 respectively for the milling process. The surface roughnesses were improved from 60.17 µin to 68.50 µin, reducing the defect rate from 52.39% to 0% for the turning process and from 93.18 µin to 79.49 µin, reducing the defect rate from 71.23% to 0% for the milling process. The purpose of this study is to efficiently utilize the Taguchi design analysis to improve the surface roughness.

Keywords: surface roughness, Taguchi parameter design, CNC turning, CNC milling

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Authors: Sanaa Rashed Abdallah, Yasser F. Hassan

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The paper will introduce an approach where a rough sets, gene expression programming and rough neural networks are used cooperatively for learning and classification support. The Objective of gene expression programming rough neural networks (GEP-RNN) approach is to obtain new classified data with minimum error in training and testing process. Starting point of gene expression programming rough neural networks (GEP-RNN) approach is an information system and the output from this approach is a structure of rough neural networks which is including the weights and thresholds with minimum classification error.

Keywords: rough sets, gene expression programming, rough neural networks, classification

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Authors: D. O. Ramadan, R. S. Dwyer-Joyce

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The measurement of the interface conditions in a cutting tool contact is essential information for performance monitoring and control. This interface provides the path for the heat flux to the cutting tool. This elevate in the cutting tool temperature leads to motivate the mechanism of tool wear, thus affect the life of the cutting tool and the productivity. This zone is representative by the tool-chip interface. Therefore, understanding and monitoring this interface is considered an important issue in machining. In this paper, an acoustic emission (AE) technique was used to find the correlation between AE parameters and the tool-chip interface. For this reason, a response surface design (RSD) has been used to analyse and optimize the machining parameters. The experiment design was based on the face centered, central composite design (CCD) in the Minitab environment. According to this design, a series of orthogonal cutting experiments for different cutting conditions were conducted on a Triumph 2500 lathe machine to study the sensitivity of the acoustic emission (AE) signal to change in tool-chip contact length. The cutting parameters investigated were the cutting speed, depth of cut, and feed and the experiments were performed for 6082-T6 aluminium tube. All the orthogonal cutting experiments were conducted unlubricated. The tool-chip contact area was investigated using a scanning electron microscope (SEM). The results obtained in this paper indicate that there is a strong dependence of the root mean square (RMS) on the cutting speed, where the RMS increases with increasing the cutting speed. A dependence on the tool-chip contact length has been also observed. However there was no effect observed of changing the cutting depth and feed on the RMS. These dependencies have been clarified in terms of the strain and temperature in the primary and secondary shear zones, also the tool-chip sticking and sliding phenomenon and the effect of these mechanical variables on dislocation activity at high strain rates. In conclusion, the acoustic emission technique has the potential to monitor in situ the tool-chip interface in turning and consequently could indicate the approaching end of life of a cutting tool.

Keywords: Acoustic emission, tool-chip interface, orthogonal cutting, monitoring

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Authors: Hyeon-Kyo Lim, Tong-Il Jang, Yong-Hee Lee

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Human error is one of the most dreaded factors that may result in unexpected accidents, especially in nuclear power plants. For accident prevention, it is quite indispensable to analyze and to manage the influence of any factor which may raise the possibility of human errors. Out of lots factors, stress has been reported to have a significant influence on human performance. Therefore, this research aimed to develop a work-related stress management program which can guarantee Fitness-for-Duty (FFD) of the workers in nuclear power plants, especially those working in main control rooms. Major stress factors were elicited through literal surveys and classified into major categories such as demands, supports, and relationships. To manage those factors, a test and intervention program based on 4-level approaches was developed over the whole employment cycle including selection and screening of workers, job allocation, and job rotation. In addition, a managerial care program was introduced with the concept of Employee-Assistance-Program (EAP) program. Reviews on the program conducted by ex-operators in nuclear power plants showed responses in the affirmative, and suggested additional treatment to guarantee high performance of human workers, not in normal operations but also in emergency situations.

Keywords: human error, work performance, work stress, Fitness-For-Duty (FFD), Employee Assistance Program (EAP)

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Authors: H. Mansor, S.B. Mohd-Noor, N. I. Othman, N. Tazali, R. I. Boby

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This paper presents an improved robust Proportional Derivative controller for a 3-Degree-of-Freedom (3-DOF) bench-top helicopter by using adaptive methodology. Bench-top helicopter is a laboratory scale helicopter used for experimental purposes which is widely used in teaching laboratory and research. Proportional Derivative controller has been developed for a 3-DOF bench-top helicopter by Quanser. Experiments showed that the transient response of designed PD controller has very large steady state error i.e., 50%, which is very serious. The objective of this research is to improve the performance of existing pitch angle control of PD controller on the bench-top helicopter by integration of PD controller with adaptive controller. Usually standard adaptive controller will produce zero steady state error; however response time to reach desired set point is large. Therefore, this paper proposed an adaptive with deadbeat algorithm to overcome the limitations. The output response that is fast, robust and updated online is expected. Performance comparisons have been performed between the proposed self-tuning deadbeat PD controller and standard PD controller. The efficiency of the self-tuning dead beat controller has been proven from the tests results in terms of faster settling time, zero steady state error and capability of the controller to be updated online.

Keywords: adaptive control, deadbeat control, bench-top helicopter, self-tuning control

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Authors: Yan Cheng, Yijun Shao, James Rudolph, Charlene R. Weir, Beth Sahlmann, Qing Zeng-Treitler

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Supervised predictive models require labeled data for training purposes. Complete and accurate labeled data, i.e., a ‘gold standard’, is not always available, and imperfectly labeled data may need to serve as an alternative. An important question is if the accuracy of the labeled data creates a performance ceiling for the trained model. In this study, we trained several models to recognize the presence of delirium in clinical documents using data with annotations that are not completely accurate (i.e., weakly-supervised learning). In the external evaluation, the support vector machine model with a linear kernel performed best, achieving an area under the curve of 89.3% and accuracy of 88%, surpassing the 80% accuracy of the training sample. We then generated a set of simulated data and carried out a series of experiments which demonstrated that models trained on imperfect data can (but do not always) outperform the accuracy of the training data, e.g., the area under the curve for some models is higher than 80% when trained on the data with an error rate of 40%. Our experiments also showed that the error resistance of linear modeling is associated with larger sample size, error type, and linearity of the data (all p-values < 0.001). In conclusion, this study sheds light on the usefulness of imperfect data in clinical research via weakly-supervised learning.

Keywords: weakly-supervised learning, support vector machine, prediction, delirium, simulation

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Authors: Matthias Steffan, Franz Haas

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The production process grinding is one of the latest steps in a value-added manufacturing chain. Within this step, workpiece geometry and surface roughness are determined. Up to this process stage, considerable costs and energy have already been spent on components. According to the current state of the art, therefore, large safety reserves are calculated in order to guarantee a process capability. Especially for non-circular grinding, this fact leads to considerable losses of process efficiency. With present technology, various non-circular geometries on a workpiece must be grinded subsequently in an oscillating process where X- and Q-axis of the machine are coupled. With the approach of RPM-Synchronous Noncircular Grinding, such workpieces can be machined in an ordinary plung grinding process. Therefore, the workpieces and the grinding wheels revolutionary rate are in a fixed ratio. A non-circular grinding wheel is used to transfer its geometry onto the workpiece. The authors use a worldwide unique machine tool that was especially designed for this technology. Highest revolution rates on the workpiece spindle (up to 4500 rpm) are mandatory for the success of this grinding process. This grinding approach is performed in a two-step process. For roughing, a highly porous vitrified bonded grinding wheel with medium grain size is used. It ensures high specific material removal rates for efficiently producing the non-circular geometry on the workpiece. This process step is adapted by a force control algorithm, which uses acquired data from a three-component force sensor located in the dead centre of the tailstock. For finishing, a grinding wheel with a fine grain size is used. Roughing and finishing are performed consecutively among the same clamping of the workpiece with two locally separated grinding spindles. The approach of RPM-Synchronous Noncircular Grinding shows great efficiency enhancement in non-circular grinding. For the first time, three-dimensional non-circular shapes can be grinded that opens up various fields of application. Especially automotive industries show big interest in the emerging trend in finishing machining.

Keywords: efficiency enhancement, finishing machining, non-circular grinding, rpm-synchronous grinding

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Authors: Tayo P. Ogundunmade, Adedayo A. Adepoju

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Terrorist attacks in liberal democracies bring about a few pessimistic results, for example, sabotaged public support in the governments they target, disturbing the peace of a protected environment underwritten by the state, and a limitation of individuals from adding to the advancement of the country, among others. Hence, seeking for techniques to understand the different factors involved in terrorism and how to deal with those factors in order to completely stop or reduce terrorist activities is the topmost priority of the government in every country. This research aim is to develop an efficient deep learning-based predictive model for the prediction of future terrorist activities in Nigeria, addressing low-quality prediction accuracy problems associated with the existing solution methods. The proposed predictive AI-based model as a counterterrorism tool will be useful by governments and law enforcement agencies to protect the lives of individuals in society and to improve the quality of life in general. A Heterogeneous Bayesian Neural Network (HETBNN) model was derived with Gaussian error normal distribution. Three primary transfer functions (HOTTFs), as well as two derived transfer functions (HETTFs) arising from the convolution of the HOTTFs, are namely; Symmetric Saturated Linear transfer function (SATLINS ), Hyperbolic Tangent transfer function (TANH), Hyperbolic Tangent sigmoid transfer function (TANSIG), Symmetric Saturated Linear and Hyperbolic Tangent transfer function (SATLINS-TANH) and Symmetric Saturated Linear and Hyperbolic Tangent Sigmoid transfer function (SATLINS-TANSIG). Data on the Terrorist activities in Nigeria gathered through questionnaires for the purpose of this study were used. Mean Square Error (MSE), Mean Absolute Error (MAE) and Test Error are the forecast prediction criteria. The results showed that the HETFs performed better in terms of prediction and factors associated with terrorist activities in Nigeria were determined. The proposed predictive deep learning-based model will be useful to governments and law enforcement agencies as an effective counterterrorism mechanism to understand the parameters of terrorism and to design strategies to deal with terrorism before an incident actually happens and potentially causes the loss of precious lives. The proposed predictive AI-based model will reduce the chances of terrorist activities and is particularly helpful for security agencies to predict future terrorist activities.

Keywords: activation functions, Bayesian neural network, mean square error, test error, terrorism

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Authors: Alina Mirza, Sumrin M. Kabir, Shahzad A. Sheikh

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The Orthogonal Frequency Division Multiplexing (OFDM) with high data rate, high spectral efficiency and its ability to mitigate the effects of multipath makes them most suitable in wireless application. Impulsive noise distorts the OFDM transmission and therefore methods must be investigated to suppress this noise. In this paper, a State Space Recursive Least Square (SSRLS) algorithm based adaptive impulsive noise suppressor for OFDM communication system is proposed. And a comparison with another adaptive algorithm is conducted. The state space model-dependent recursive parameters of proposed scheme enables to achieve steady state mean squared error (MSE), low bit error rate (BER), and faster convergence than that of some of existing algorithm.

Keywords: OFDM, impulsive noise, SSRLS, BER

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Authors: Huan Ting Liao

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In a typical manufacturing environment, computer numerical control (CNC) machining is essential for automating production through precise computer-controlled tool operations, significantly enhancing efficiency and ensuring consistent product quality. However, traditional CNC production lines often rely on manual loading and unloading, limiting operational efficiency and scalability. Although automated loading systems have been developed, they frequently lack sufficient intelligence and configuration efficiency, requiring extensive setup adjustments for different products and impacting overall productivity. This research addresses the job shop scheduling problem (JSSP) in CNC machining environments, aiming to minimize total completion time (makespan) and maximize CNC machine utilization. We propose a novel approach using reinforcement learning (RL), specifically the Q-learning algorithm, to optimize scheduling decisions. The study simulates the JSSP, incorporating robotic arm operations, machine processing times, and work order demand allocation to determine optimal processing sequences. The Q-learning algorithm enhances machine utilization by dynamically balancing workloads across CNC machines, adapting to varying job demands and machine states. This approach offers robust solutions for complex manufacturing environments by automating decision-making processes for job assignments. Additionally, we evaluate various layout configurations to identify the most efficient setup. By integrating RL-based scheduling optimization with layout analysis, this research aims to provide a comprehensive solution for improving manufacturing efficiency and productivity in CNC-based job shops. The proposed method's adaptability and automation potential promise significant advancements in tackling dynamic manufacturing challenges.

Keywords: job shop scheduling problem, reinforcement learning, operations sequence, layout optimization, q-learning

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Authors: P. Kooche Baghy, S. Eskandari, E.javanmard

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Neural network has been used as a predictive means of cold rolling force in this dissertation. Thus, imposed average force on rollers as a mere input and five pertaining parameters to its as a outputs are regarded. According to our study, feed-forward multilayer perceptron network has been selected. Besides, Bayesian algorithm based on the feed-forward back propagation method has been selected due to noisy data. Further, 470 out of 585 all tests were used for network learning and others (115 tests) were considered as assessment criteria. Eventually, by 30 times running the MATLAB software, mean error was obtained 3.84 percent as a criteria of network learning. As a consequence, this the mentioned error on par with other approaches such as numerical and empirical methods is acceptable admittedly.

Keywords: artificial neural network, Bayesian, cold rolling, force evaluation

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Authors: Jihoon Park, Sungkon Yu, Byungjo Jung

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Although various optical tissue phantoms (OTPs) simulating human skin have been actively studied, their completeness is unclear because skin tissue has the intricate optical property and complicated structure disturbing the optical simulation. In this study, we designed multilayer OTP mimicking skin structure, and fabricated OTP models simulating skin-blood vessel and skin pigmentation in the skin, which are useful in Biomedical optics filed. The OTPs were characterized with the optical property and the cross-sectional structure, and analyzed by using various optical tools such as a laser speckle imaging system, OCT and a digital microscope to show the practicality. The measured optical property was within 5% error, and the thickness of each layer was uniform within 10% error in micrometer scale.

Keywords: blood vessel, optical tissue phantom, optical property, skin tissue, pigmentation

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Authors: Arburim Iseni, Afrim Aliti, Nagri Rexhepi

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This paper focuses mainly on an important aspect of student-linguistic errors. It aims to explore the nature of Albanian intermediate level or B1 students’ language errors and mistakes and attempts to trace the possible sources or causes by classifying the error samples into both inter lingual and intra lingual errors. The hypothesis that intra lingua errors may be determined or induced somehow by the native language influence seems to be confirmed by the significant number of errors found in Albanian EFL students in the Study Program of the English Language and Literature at the State University of Tetova. Findings of this study have revealed that L1 interference first and then ignorance of the English Language grammar rules constitute the main sources or causes of errors, even though carelessness cannot be ruled out. Although we have conducted our study with 300 students of intermediate or B1 level, we believe that this hypothesis would need to be confirmed by further research, maybe with a larger number of students with different levels in order to draw more steady and accurate conclusions. The analysis of the questionnaires was done according to quantitative and qualitative research methods. This study was also conducted by taking written samples on different topics from our students and then distributing them with comments to the students and University teachers as well. These questionnaires were designed to gather information among 300 students and 48 EFL teachers, all of whom teach in the Study Program of English Language and Literature at the State University of Tetova. From the analyzed written samples of the students and face-to-face interviews, we could get useful insights into some important aspects of students’ error-making and error-correction. These different research methodologies were used in order to comprise a holistic research and the findings of the questionnaires helped us to come up with some more steady solutions in order to minimize the potential gap between students and teachers.

Keywords: L1 & L2, Linguistics, Applied linguistics, SLA, Albanian EFL students and teachers, Errors and Mistakes, Students’ Assessment and Self-Assessment

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Authors: L. Siva Rama Krishna, Sriram Venkatesh, M. Sastish Kumar, M. Uma Maheswara Chary

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Rapid Prototyping (RP) is a technology that produces models and prototype parts from 3D CAD model data, CT/MRI scan data, and model data created from 3D object digitizing systems. There are several RP process like Stereolithography (SLA), Solid Ground Curing (SGC), Selective Laser Sintering (SLS), Fused Deposition Modelling (FDM), 3D Printing (3DP) among them SLS and FDM RP processes are used to fabricate pattern of custom cranial implant. RP technology is useful in engineering and biomedical application. This is helpful in engineering for product design, tooling and manufacture etc. RP biomedical applications are design and development of medical devices, instruments, prosthetics and implantation; it is also helpful in planning complex surgical operation. The traditional approach limits the full appreciation of various bony structure movements and therefore the custom implants produced are difficult to measure the anatomy of parts and analyse the changes in facial appearances accurately. Cranioplasty surgery is a surgical correction of a defect in cranial bone by implanting a metal or plastic replacement to restore the missing part. This paper aims to do a comparative study on the dimensional error of CAD and SLS RP Models for reconstruction of cranial defect by comparing the virtual CAD with the physical RP model of a cranial defect.

Keywords: rapid prototyping, selective laser sintering, cranial defect, dimensional error

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Authors: Omaima E. S. Mohammed, Amira A. A. Abdallah, Amal A. M. El Borady

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Background: Core stability training has recently attracted attention for improving muscle performance. Purpose: This study investigated the effect of beginners' core stability exercises on trunk active repositioning error at 30° and 60° trunk flexion. Methods: Forty healthy males participated in the study. They were divided into two equal groups; experimental “group I” and control “group II”. Their mean age, weight and height were 19.35±1.11 vs 20.45±1.64 years, 70.15±6.44 vs 72.45±6.91 kg and 174.7±7.02 vs 176.3±7.24 cm for group I vs group II. Data were collected using the Biodex Isokinetic system at an angular velocity of 60º/s. The participants were tested twice; before and after a 6-week period during which group I performed a core stability training program. Results: The Mixed 3-way ANOVA revealed significant increases (p<0.05) in the absolute error (AE) at 30˚ compared with 60˚ flexion in the pre-test condition of group I and II and the post-test condition of group II. Moreover, there were significant decreases (p<0.05) in the AE in the post-test condition compared with the pre-test in group I at both 30˚ and 60˚ flexion with no significant differences for group II. Finally, there were significant decreases (p<0.05) in the AE in group I compared with group II in the post-test condition at 30˚ and 60˚ flexion with no significant differences for the pre-test condition Interpretation/Conclusion: The improvement in trunk proprioception indicated by the decrease in the active repositioning error in the experimental group recommends including core stability training in the exercise programs that aim to improve trunk proprioception.

Keywords: core stability, isokinetic, trunk proprioception, biomechanics

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Authors: Vanessa Vasconcelos, Mariza A. S. Bigonha

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In order to facilitate both processes, this paper presents HaskellFL, a tool that uses fault localization techniques to locate a logical error in Haskell code. The Haskell subset used in this work is sufficiently expressive for those studying functional programming to get immediate help debugging their code and to answer questions about key concepts associated with the functional paradigm. HaskellFL was tested against functional programming assignments submitted by students enrolled at the functional programming class at the Federal University of Minas Gerais and against exercises from the Exercism Haskell track that are publicly available on GitHub. Furthermore, the EXAM score was chosen to evaluate the tool’s effectiveness, and results showed that HaskellFL reduced the effort needed to locate an error for all tested scenarios. Results also showed that the Ochiai method was more effective than Tarantula.

Keywords: debug, fault localization, functional programming, Haskell

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Authors: Heiko Diefenbach, Christoph H. Glock

Abstract:

Order picking, i.e., the order-based retrieval of items in a warehouse, is an important time- and cost-intensive process for many logistic systems. Despite the ongoing trend of automation, most order picking systems are still manual picker-to-parts systems, where human pickers walk through the warehouse to collect ordered items. Human work in warehouses is not free from errors, and order pickers may at times pick the wrong or the incorrect number of items. Errors can cause additional costs and significant correction efforts. Moreover, age might increase a person’s likelihood to make mistakes. Hence, the negative impact of picking errors might increase for an aging workforce currently witnessed in many regions globally. A significant amount of research has focused on making order picking systems more efficient. Among other factors, storage assignment, i.e., the assignment of items to storage locations (e.g., shelves) within the warehouse, has been subject to optimization. Usually, the objective is to assign items to storage locations such that order picking times are minimized. Surprisingly, there is a lack of research concerned with picking errors and respective prevention approaches. This paper hypothesize that the storage assignment of items can affect the probability of pick errors. For example, storing similar-looking items apart from one other might reduce confusion. Moreover, storing items that are hard to count or require a lot of counting at easy-to-access and easy-to-comprehend self heights might reduce the probability to pick the wrong number of items. Based on this hypothesis, the paper discusses how to incorporate error-prevention measures into mathematical models for storage assignment optimization. Various approaches with respective benefits and shortcomings are presented and mathematically modeled. To investigate the newly developed models further, they are compared to conventional storage assignment strategies in a computational study. The study specifically investigates how the importance of error prevention increases with pickers being more prone to errors due to age, for example. The results suggest that considering error-prevention measures for storage assignment can reduce error probabilities with only minor decreases in picking efficiency. The results might be especially relevant for an aging workforce.

Keywords: an aging workforce, error prevention, order picking, storage assignment

Procedia PDF Downloads 204

Authors: Jae-Hyun Choi, Sung-Soo Bae, Sangyoung Yoon, Hong-Ku Yun, Jiyoung Kwahk

Abstract:

This study was conducted to investigate the effect of ocular dominance on recognition performance using a single-lens smart display designed for cycling. A total of 36 bicycle riders who have been cycling consistently were recruited and participated in the experiment. The participants were asked to perform tasks riding a bicycle on a stationary stand for safety reasons. Independent variables of interest include ocular dominance, bike usage, age group, and information layout. Recognition time (i.e., the time required to identify specific information measured with an eye-tracker), error rate (i.e. false answer or failure to identify the information in 5 seconds), and user preference scores were measured and statistical tests were conducted to identify significant results. Recognition time and error ratio showed significant difference by ocular dominance factor, while the preference score did not. Recognition time was faster when the single-lens see-through display on the dominant eye (average 1.12sec) than on the non-dominant eye (average 1.38sec). Error ratio of the information recognition task was significantly lower when the see-through display was worn on the dominant eye (average 4.86%) than on the non-dominant eye (average 14.04%). The interaction effect of ocular dominance and age group was significant with respect to recognition time and error ratio. The recognition time of the users in their 40s was significantly longer than the other age groups when the display was placed on the non-dominant eye, while no difference was observed on the dominant eye. Error ratio also showed the same pattern. Although no difference was observed for the main effect of ocular dominance and bike usage, the interaction effect between the two variables was significant with respect to preference score. Preference score of daily bike users was higher when the display was placed on the dominant eye, whereas participants who use bikes for leisure purposes showed the opposite preference patterns. It was found more effective and efficient to wear a see-through display on the dominant eye than on the non-dominant eye, although user preference was not affected by ocular dominance. It is recommended to wear a see-through display on the dominant eye since it is safer by helping the user recognize the presented information faster and more accurately, even if the user may not notice the difference.

Keywords: eye tracking, information recognition, ocular dominance, smart headware, wearable device

Procedia PDF Downloads 272

Authors: Nelson Bii, Christopher Ouma, John Odhiambo

Abstract:

Non-response is a potential source of errors in sample surveys. It introduces bias and large variance in the estimation of finite population parameters. Regression models have been recognized as one of the techniques of reducing bias and variance due to random non-response using auxiliary data. In this study, it is assumed that random non-response occurs in the survey variable in the second stage of cluster sampling, assuming full auxiliary information is available throughout. Auxiliary information is used at the estimation stage via a regression model to address the problem of random non-response. In particular, the auxiliary information is used via an improved Nadaraya-Watson kernel regression technique to compensate for random non-response. The asymptotic bias and mean squared error of the estimator proposed are derived. Besides, a simulation study conducted indicates that the proposed estimator has smaller values of the bias and smaller mean squared error values compared to existing estimators of finite population mean. The proposed estimator is also shown to have tighter confidence interval lengths at a 95% coverage rate. The results obtained in this study are useful, for instance, in choosing efficient estimators of the finite population mean in demographic sample surveys.

Keywords: mean squared error, random non-response, two-stage cluster sampling, confidence interval lengths

Procedia PDF Downloads 139

Authors: Karim Matter, Heba Fayed, Ahmed Abd-Elaziz, Moustafa Hussein

Abstract:

Due to the exponential growth of mobile devices and wireless services, a huge demand for radiofrequency has increased. The presence of several frequencies causes interference between cells, which must be minimized to get the lower Bit Error Rate (BER). For this reason, it is of great interest to use visible light communication (VLC). This paper suggests a VLC system that decreases the BER by applying a new LED distribution with a hexagonal shape using a Frequency Reuse (FR) concept to mitigate the interference between the reused frequencies inside the hexagonal shape. The BER is measured in two scenarios, Line of Sight (LoS) and Non-Line of Sight (Non-LoS), for each technique that we used. The recommended values of BER in the proposed model for Soft Frequency Reuse (SFR) in the case of Los at 4, 8, and 10 dB signal to noise ratio (SNR), are 3.6×10⁻⁶, 6.03×10⁻¹³, and 2.66×10⁻¹⁸, respectively.

Keywords: visible light communication (VLC), field of view (FoV), hexagonal array, frequency reuse

Procedia PDF Downloads 160

Authors: Y. Galerkin, K. Soldatova, A. Drozdov

Abstract:

The 6th version of Universal modeling method for centrifugal compressor stage calculation is described. Identification of the new mathematical model was made. As a result of identification the uniform set of empirical coefficients is received. The efficiency definition error is 0,86 % at a design point. The efficiency definition error at five flow rate points (except a point of the maximum flow rate) is 1,22 %. Several variants of the stage with 3D impellers designed by 6th version program and quasi three-dimensional calculation programs were compared by their gas dynamic performances CFD (NUMECA FINE TURBO). Performance comparison demonstrated general principles of design validity and leads to some design recommendations.

Keywords: compressor design, loss model, performance prediction, test data, model stages, flow rate coefficient, work coefficient

Procedia PDF Downloads 412