Search results for: Multi-level Threshold Method

Authors: R. Latif, W. Jenkal, A. Toumanari, A. Hatim

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This paper presents an efficient method of electrocardiogram signal denoising based on a hybrid approach. Two techniques are brought together to create an efficient denoising process. The first is an Adaptive Dual Threshold Filter (ADTF) and the second is the Discrete Wavelet Transform (DWT). The presented approach is based on three steps of denoising, the DWT decomposition, the ADTF step and the highest peaks correction step. This paper presents some application of the approach on some electrocardiogram signals of the MIT-BIH database. The results of these applications are promising compared to other recently published techniques.

Keywords: Hybrid technique, ADTF, DWT, tresholding, ECG signal.

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Authors: Imane El Karaoui, Mohammed Maaroufi, Hamid Chaikhy

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Doubly Fed Induction Generator (DFIG) is one of the most reliable wind generator. Major problem in wind power generation is to generate Sinusoidal signal with very low THD on variable speed caused by inverter two levels used. This paper presents a multi-level inverter whose objective is to reduce the THD and the dimensions of the output filter. This work proposes a three-level NPC-type inverter, the results simulation are presented demonstrating the efficiency of the proposed inverter.

Keywords: DFIG, multilevel inverter, NPC inverter , THD, Induction machine.

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Authors: Atefeh Bagherianziarat, Dana Hamplova

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The inverse social gradient in life satisfaction (LS) is a well-established research finding. Although objective aspects of inequality or individuals’ socioeconomic status are among the approved predictors of life satisfaction; however, less is known about the effect of subjective inequality and the interplay of these two aspects of inequality on life satisfaction. It is suggested that individuals’ perception of their socioeconomic status in society can moderate the link between their absolute socioeconomic status and life satisfaction. Nevertheless, this moderating link has not been affirmed to work likewise in societies with different welfare regimes associating with different levels of social inequality. In this study, we compared the moderative influence of subjective inequality on the link between objective inequality and LS. In particular, we focus on differences across welfare state regimes based on Esping-Andersen's theory. Also, we explored the moderative role of believing in the value of equality on the link between objective and subjective inequality on LS, in the given societies. Since our studied variables were measured at both individual and country levels, we applied a multilevel analysis to the European Social Survey data (round 9). The results showed that people in different regimes reported statistically meaningful different levels of LS that is explained to different extends by their household income and their perception of their income inequality. The findings of the study supported the previous findings of the moderator influence of perceived inequality on the link between objective inequality and LS. However, this link is different in various welfare state regimes. The results of the multilevel modeling showed that country-level subjective equality is a positive predictor for individuals’ LS, while the Gini coefficient that was considered as the indicator of absolute inequality has a smaller effect on LS. Also, country-level subjective equality moderates the confirmed link between individuals’ income and their LS. It can be concluded that both individual and country-level subjective inequality slightly moderate the effect of individuals’ income on their LS.

Keywords: individual values, life satisfaction, multi-level analysis, objective inequality, subjective inequality, welfare regimes status

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Authors: Mehran Yazdi, Zahra Adelpour, Batoul Bahraini, Yasaman Keshtkar Jahromi

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In this paper we use the property of co-occurrence matrix in finding parallel lines in binary pictures for fingerprint identification. In our proposed algorithm, we reduce the noise by filtering the fingerprint images and then transfer the fingerprint images to binary images using a proper threshold. Next, we divide the binary images into some regions having parallel lines in the same direction. The lines in each region have a specific angle that can be used for comparison. This method is simple, performs the comparison step quickly and has a good resistance in the presence of the noise.

Keywords: Parallel lines detection, co-occurrence matrix, fingerprint identification.

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Authors: Rania Minkara, Jean-Pierre Dubois

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The major problem that wireless communication systems undergo is multipath fading caused by scattering of the transmitted signal. However, we can treat multipath propagation as multiple channels between the transmitter and receiver to improve the signal-to-scattering-noise ratio. While using Single Input Multiple Output (SIMO) systems, the diversity receivers extract multiple signal branches or copies of the same signal received from different channels and apply gain combining schemes such as Root Mean Square Gain Combining (RMSGC). RMSGC asymptotically yields an identical performance to that of the theoretically optimal Maximum Ratio Combining (MRC) for values of mean Signal-to- Noise-Ratio (SNR) above a certain threshold value without the need for SNR estimation. This paper introduces an improvement of RMSGC using two different issues. We found that post-detection and de-noising the received signals improve the performance of RMSGC and lower the threshold SNR.

Keywords: Bit error rate, de-noising, pre-detection, root-meansquare gain combining, single-input multiple-output channels.

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Authors: Victor Breux, Jérôme Boutet, Alain Goret, Viviane Cattin

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Early detection of anomalies in data centers is important to reduce downtimes and the costs of periodic maintenance. However, there is little research on this topic and even fewer on the fusion of sensor data for the detection of abnormal events. The goal of this paper is to propose a method for anomaly detection in data centers by combining sensor data (temperature, humidity, power) and deep learning models. The model described in the paper uses one autoencoder per sensor to reconstruct the inputs. The auto-encoders contain Long-Short Term Memory (LSTM) layers and are trained using the normal samples of the relevant sensors selected by correlation analysis. The difference signal between the input and its reconstruction is then used to classify the samples using feature extraction and a random forest classifier. The data measured by the sensors of a data center between January 2019 and May 2020 are used to train the model, while the data between June 2020 and May 2021 are used to assess it. Performances of the model are assessed a posteriori through F1-score by comparing detected anomalies with the data center’s history. The proposed model outperforms the state-of-the-art reconstruction method, which uses only one autoencoder taking multivariate sequences and detects an anomaly with a threshold on the reconstruction error, with an F1-score of 83.60% compared to 24.16%.

Keywords: Anomaly detection, autoencoder, data centers, deep learning.

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Authors: Zeinab Galavani, Reza Rezaei-Nasirabad, Rasoul Sadighi-Bonabi

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Using a force balanced translational-radial dynamics, phase space of the moving single bubble sonoluminescence (m- SBSL) in 85% wt sulfuric acid has been numerically calculated. This phase space is compared with that of single bubble sonoluminescence (SBSL) in pure water which has been calculated by using the mere radial dynamics. It is shown that in 85% wt sulfuric acid, in a general agreement with experiment, the bubble-s positional instability threshold lays under the shape instability threshold. At the onset of spatial instability of moving sonoluminescing (SL) bubble in 85% wt sulfuric acid, temporal effects of the hydrodynamic force on the bubble translational-radial dynamics have been investigated. The appearance of non-zero history force on the moving SL bubble is because of proper condition which was produced by high viscosity of acid. Around the moving bubble collapse due to the rapid contraction of the bubble wall, the inertial based added mass force overcomes the viscous based history force and induces acceleration on the bubble translational motion.

Keywords: Bjerknes force, History force, Reynolds number, Sonoluminescence.

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Authors: Chinnaiah Madduri, Raghu V. Prakash

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This paper presents the results of corrosion fatigue crack growth behaviour of a Ni-Cr-Mn steel commonly used in marine applications. The effect of mechanical variables such as frequency and load ratio on fatigue crack growth rate at various stages has been studied using compact tension (C(T)) specimens along the rolling direction of steel plate under 3.5% saturated NaCl aqueous environment. The significance of crack closure on corrosion fatigue, and the validity of Elber-s empirical linear crack closure model with the ASTM compliance offset method have been examined. Fatigue crack growth rate is higher and threshold stress intensities are lower in aqueous environment compared to the lab air conditions. It is also observed that the crack growth rate increases at lower frequencies. The higher stress ratio promotes the crack growth. The effect of oxidization and corrosion pit formation is very less as the stress ratio is increased. It is observed that as stress ratios are increased, the Elber-s crack closure model agrees well with the crack closure estimated by the ASTM compliance offset method for tests conducted at 5Hz frequency compared to tests conducted at 1Hz in corrosive environment.

Keywords: Corrosion fatigue, oxide induced crack closure, Elber's crack closure, ASTM compliance offset method.

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Authors: N. Shen, T. T. Le, H. Y. Yu, Z. X. Chen, K. T. Win, N. Singh, G. Q. Lo, D. -L. Kwong

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In this paper, we present a vertical nanowire thin film transistor with gate-all-around architecture, fabricated using CMOS compatible processes. A novel method of fabricating polysilicon vertical nanowires of diameter as small as 30 nm using wet-etch is presented. Both n-type and p-type vertical poly-silicon nanowire transistors exhibit superior electrical characteristics as compared to planar devices. On a poly-crystalline nanowire of 30 nm diameter, high Ion/Ioff ratio of 106, low drain-induced barrier lowering (DIBL) of 50 mV/V, and low sub-threshold slope SS~100mV/dec are demonstrated for a device with channel length of 100 nm.

Keywords: Nanowire (NW), Gate-all-around (GAA), polysilicon (poly-Si), thin-film transistor (TFT).

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Authors: Zhang Xiaodong, Tang Zixin, Liu Xin

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In order to avoid self-collision of space manipulators during operation process, a real-time detection method is proposed in this paper. The manipulator is fitted into a cylinder-enveloping surface, and then, a kind of detection algorithm of collision between cylinders is analyzed. The collision model of space manipulator self-links can be detected by using this algorithm in real-time detection during the operation process. To ensure security of the operation, a safety threshold is designed. The simulation and experiment results verify the effectiveness of the proposed algorithm for a 7-DOF space manipulator.

Keywords: Space manipulator, Collision detection, Self-collision, the real-time collision detection.

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Authors: B. S. Raghavendra, D. Narayana Dutt

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Electroencephalogram (EEG) recordings are often contaminated with ocular and muscle artifacts. In this paper, the canonical correlation analysis (CCA) is used as blind source separation (BSS) technique (BSS-CCA) to decompose the artifact contaminated EEG into component signals. We combine the BSSCCA technique with wavelet filtering approach for minimizing both ocular and muscle artifacts simultaneously, and refer the proposed method as wavelet enhanced BSS-CCA. In this approach, after careful visual inspection, the muscle artifact components are discarded and ocular artifact components are subjected to wavelet filtering to retain high frequency cerebral information, and then clean EEG is reconstructed. The performance of the proposed wavelet enhanced BSS-CCA method is tested on real EEG recordings contaminated with ocular and muscle artifacts, for which power spectral density is used as a quantitative measure. Our results suggest that the proposed hybrid approach minimizes ocular and muscle artifacts effectively, minimally affecting underlying cerebral activity in EEG recordings.

Keywords: Blind source separation, Canonical correlationanalysis, Electroencephalogram, Muscle artifact, Ocular artifact, Power spectrum, Wavelet threshold.

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Authors: Waqqas-ur-Rehman Butt, Martin Servin, Marion Pause

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In recent years, object detection has gained much attention and very encouraging research area in the field of computer vision. The robust object boundaries detection in an image is demanded in numerous applications of human computer interaction and automated surveillance systems. Many methods and approaches have been developed for automatic object detection in various fields, such as automotive, quality control management and environmental services. Inappropriately, to the best of our knowledge, object detection under illumination with shadow consideration has not been well solved yet. Furthermore, this problem is also one of the major hurdles to keeping an object detection method from the practical applications. This paper presents an approach to automatic object detection in images under non-standardized environmental conditions. A key challenge is how to detect the object, particularly under uneven illumination conditions. Image capturing conditions the algorithms need to consider a variety of possible environmental factors as the colour information, lightening and shadows varies from image to image. Existing methods mostly failed to produce the appropriate result due to variation in colour information, lightening effects, threshold specifications, histogram dependencies and colour ranges. To overcome these limitations we propose an object detection algorithm, with pre-processing methods, to reduce the interference caused by shadow and illumination effects without fixed parameters. We use the Y CrCb colour model without any specific colour ranges and predefined threshold values. The segmented object regions are further classified using morphological operations (Erosion and Dilation) and contours. Proposed approach applied on a large image data set acquired under various environmental conditions for wood stack detection. Experiments show the promising result of the proposed approach in comparison with existing methods.

Keywords: Image processing, Illumination equalization, Shadow filtering, Object detection, Colour models, Image segmentation.

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Authors: Doo-chul Choi, Yong-Ju Jeon, Jong Pil Yun, Sung Wook Yun, Sang Woo Kim

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In this study, we developed an algorithm for detecting seam cracks in a steel plate. Seam cracks are generated in the edge region of a steel plate. We used the Gabor filter and an adaptive double threshold method to detect them. To reduce the number of pseudo defects, features based on the shape of seam cracks were used. To evaluate the performance of the proposed algorithm, we tested 989 images with seam cracks and 9470 defect-free images. Experimental results show that the proposed algorithm is suitable for detecting seam cracks. However, it should be improved to increase the true positive rate.

Keywords: Defect detection, Gabor filter, machine vision, surface inspection.

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Authors: S. M. Thahab, H. Abu Hassan, Z. Hassan

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The InAlGaN alloy has only recently began receiving serious attention into its growth and application. High quality InGaN films have led to the development of light emitting diodes (LEDs) and blue laser diodes (LDs). The quaternary InAlGaN however, represents a more versatile material since the bandgap and lattice constant can be independently varied. We report an ultraviolet (UV) quaternary InAlGaN multi-quantum wells (MQWs) LD study by using the simulation program of Integrated System Engineering (ISE TCAD). Advanced physical models of semiconductor properties were used in order to obtain an optimized structure. The device performance which is affected by piezoelectric and thermal effects was studied via drift-diffusion model for carrier transport, optical gain and loss. The optical performance of the UV LD with different numbers of quantum wells was numerically investigated. The main peak of the emission wavelength for double quantum wells (DQWs) was shifted from 358 to 355.8 nm when the forward current was increased. Preliminary simulated results indicated that better output performance and lower threshold current could be obtained when the quantum number is four, with output power of 130 mW and threshold current of 140 mA.

Keywords: Nitride semiconductors, InAlGaN quaternary, UVLD, numerical simulation.

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Authors: Rawya Rizk, Rehab Abdel-Kader, Rabab Ramadan

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Unlike the best effort service provided by the internet today, next-generation wireless networks will support real-time applications. This paper proposes an adaptive early packet discard (AEPD) policy to improve the performance of the real time TCP traffic over ATM networks and avoid the fragmentation problem. Three main aspects are incorporated in the proposed policy. First, providing quality-of-service (QoS) guaranteed for real-time applications by implementing a priority scheduling. Second, resolving the partially corrupted packets problem by differentiating the buffered cells of one packet from another. Third, adapting a threshold dynamically using Fuzzy logic based on the traffic behavior to maintain a high throughput under a variety of load conditions. The simulation is run for two priority classes of the input traffic: real time and non-real time classes. Simulation results show that the proposed AEPD policy improves throughput and fairness over that using static threshold under the same traffic conditions.

Keywords: Early packet discard, Fuzzy logic, packet dropping policies, quality-of-service (QoS), TCP over ATM

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Authors: Seema Biday, Udhav Bhosle

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Repeated observation of a given area over time yields potential for many forms of change detection analysis. These repeated observations are confounded in terms of radiometric consistency due to changes in sensor calibration over time, differences in illumination, observation angles and variation in atmospheric effects. This paper demonstrates applicability of an empirical relative radiometric normalization method to a set of multitemporal cloudy images acquired by Resourcesat1 LISS III sensor. Objective of this study is to detect and remove cloud cover and normalize an image radiometrically. Cloud detection is achieved by using Average Brightness Threshold (ABT) algorithm. The detected cloud is removed and replaced with data from another images of the same area. After cloud removal, the proposed normalization method is applied to reduce the radiometric influence caused by non surface factors. This process identifies landscape elements whose reflectance values are nearly constant over time, i.e. the subset of non-changing pixels are identified using frequency based correlation technique. The quality of radiometric normalization is statistically assessed by R2 value and mean square error (MSE) between each pair of analogous band.

Keywords: Correlation, Frequency domain, Multitemporal, Relative Radiometric Correction

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Authors: Zhengsheng Wang, Jing Qi, Chuntao Liu, Yuanjun Li

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The harmonic Arnoldi method can be used to find interior eigenpairs of large matrices. However, it has been shown that this method may converge erratically and even may fail to do so. In this paper, we present a new method for computing interior eigenpairs of large nonsymmetric matrices, which is called weighted harmonic Arnoldi method. The implementation of the method has been tested by numerical examples, the results show that the method converges fast and works with high accuracy.

Keywords: Harmonic Arnoldi method, weighted harmonic Arnoldi method, eigenpair, interior eigenproblem, non symmetric matrix.

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Authors: Jin Sup Kim, Woo Young Jung, Minho Kwon

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In general dynamic analyses, lower mode response is of interest, however the higher modes of spatially discretized equations generally do not represent the real behavior and not affects to global response much. Some implicit algorithms, therefore, are introduced to filter out the high-frequency modes using intended numerical error. The objective of this study is to introduce the P-method and PC α-method to compare that with dissipation method and Newmark method through the stability analysis and numerical example. PC α-method gives more accuracy than other methods because it based on the α-method inherits the superior properties of the implicit α-method. In finite element analysis, the PC α-method is more useful than other methods because it is the explicit scheme and it achieves the second order accuracy and numerical damping simultaneously.

Keywords: Dynamic, α-Method, P-Method, PC α-Method, Newmark method.

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Authors: Dejan Stantic, Jun Jo

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ECG contains very important clinical information about the cardiac activities of the heart. Often the ECG signal needs to be captured for a long period of time in order to identify abnormalities in certain situations. Such signal apart of a large volume often is characterised by low quality due to the noise and other influences. In order to extract features in the ECG signal with time-varying characteristics at first need to be preprocessed with the best parameters. Also, it is useful to identify specific parts of the long lasting signal which have certain abnormalities and to direct the practitioner to those parts of the signal. In this work we present a method based on wavelet transform, standard deviation and variable threshold which achieves 100% accuracy in identifying the ECG signal peaks and heartbeat as well as identifying the standard deviation, providing a quick reference to abnormalities.

Keywords: Electrocardiogram-ECG, Arrhythmia, Signal Processing, Wavelet Transform, Standard Deviation

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Authors: M. H. Korayem, K. Khoshhal, H. Aliakbarpour

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In this paper, a vision based system has been used for controlling an industrial 3P Cartesian robot. The vision system will recognize the target and control the robot by obtaining images from environment and processing them. At the first stage, images from environment are changed to a grayscale mode then it can diverse and identify objects and noises by using a threshold objects which are stored in different frames and then the main object will be recognized. This will control the robot to achieve the target. A vision system can be an appropriate tool for measuring errors of a robot in a situation where the experimental test is conducted for a 3P robot. Finally, the international standard ANSI/RIA R15.05-2 is used for evaluating the path-related characteristics of the robot. To evaluate the performance of the proposed method experimental test is carried out.

Keywords: Robot, Vision, Experiment, Standard.

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Authors: Tae Kyung Kim, Hee Suk Seo

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Sensor networks are often deployed in unattended environments, thus leaving these networks vulnerable to false data injection attacks in which an adversary injects forged reports into the network through compromised nodes, with the goal of deceiving the base station or depleting the resources of forwarding nodes. Several research solutions have been recently proposed to detect and drop such forged reports during the forwarding process. Each design can provide the equivalent resilience in terms of node compromising. However, their energy consumption characteristics differ from each other. Thus, employing only a single filtering scheme for a network is not a recommendable strategy in terms of energy saving. It's very important the threshold determination for message authentication to identify. We propose the recursive contract net protocols which less energy level of terminal node in wireless sensor network.

Keywords: Data filtering, recursive CNP, simulation.

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Authors: Kasra Afsahi, Maryam Soheilifar, Nazanin Vahed, Omid Seyed Esmaeili, S. Hossein Hosseini

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The most common cause of shoulder pain occurs when rotator cuff tendons become trapped under the bony area in the shoulder. This pilot study was performed to evaluate the feasibility of Virtual Reality based rehabilitation of shoulder impingement syndrome in athletes. Three consecutive patients with subacromial impingement syndrome were enrolled. The participants were rehabilitated for 5 times a week for 4 weeks, 20 sessions in total (with duration of each session being 60 minutes). In addition to the conventional rehabilitation program, a 10-minute game-based virtual reality exercise was administered. Primary outcome measures were range of motion evaluated with goniometer, pain sensation, disability intensity using ‘The Disabilities of the Arm, Shoulder and Hand Questionnaire’, muscle strength using ‘dynamometer’; pain threshold with 'algometer' and level of satisfaction. There were significant improvements in the range of motion, pain sensation, disability, pain threshold and muscle strength compared to basis (P < 0.05). There were no major adverse effects. This study showed the usefulness of VR therapy as an adjunct to conventional physiotherapy in improving function in patients with shoulder impingement syndrome.

Keywords: Shoulder impingement syndrome, VR therapy, feasibility, rehabilitation.

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Authors: M. Shaker, S. Minaei, M. H. Khoshtaghaza, A. Banakar, A. Jafari

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In this study a system of machine vision and singulation was developed to separate paddy from rice and determine paddy husking and rice breakage percentages. The machine vision system consists of three main components including an imaging chamber, a digital camera, a computer equipped with image processing software. The singulation device consists of a kernel holding surface, a motor with vacuum fan, and a dimmer. For separation of paddy from rice (in the image), it was necessary to set a threshold. Therefore, some images of paddy and rice were sampled and the RGB values of the images were extracted using MATLAB software. Then mean and standard deviation of the data were determined. An Image processing algorithm was developed using MATLAB to determine paddy/rice separation and rice breakage and paddy husking percentages, using blue to red ratio. Tests showed that, a threshold of 0.75 is suitable for separating paddy from rice kernels. Results from the evaluation of the image processing algorithm showed that the accuracies obtained with the algorithm were 98.36% and 91.81% for paddy husking and rice breakage percentage, respectively. Analysis also showed that a suction of 45 mmHg to 50 mmHg yielding 81.3% separation efficiency is appropriate for operation of the kernel singulation system.

Keywords: Computer vision, rice kernel, husking, breakage.

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Authors: I. Parkova, A. Vališevskis, A. Viļumsone

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Nocturnal enuresis or bed-wetting is intermittent incontinence during sleep of children after age 5 that may precipitate wide range of behavioral and developmental problems. One of the non-pharmacological treatment methods is the use of a bed-wetting alarm system. In order to improve comfort conditions of nocturnal enuresis alarm system, modular moisture sensor should be replaced by a textile sensor. In this study behavior and moisture detection speed of woven and sewn sensors were compared by analyzing change in electrical resistance after solution (salt water) was dripped on sensor samples. Material of samples has different structure and yarn location, which affects solution detection rate. Sensor system circuit was designed and two sensor tests were performed: system activation test and false alarm test to determine the sensitivity of the system and activation threshold. Sewn sensor had better result in system’s activation test – faster reaction, but woven sensor had better result in system’s false alarm test – it was less sensitive to perspiration simulation. After experiments it was found that the optimum switching threshold is 3V in case of 5V input voltage, which provides protection against false alarms, for example – during intensive sweating.

Keywords: Conductive yarns, moisture textile sensor.

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Authors: Bing-Fei Wu, Yen-Lin Chen, Chung-Cheng Chiu

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In this study, a new criterion for determining the number of classes an image should be segmented is proposed. This criterion is based on discriminant analysis for measuring the separability among the segmented classes of pixels. Based on the new discriminant criterion, two algorithms for recursively segmenting the image into determined number of classes are proposed. The proposed methods can automatically and correctly segment objects with various illuminations into separated images for further processing. Experiments on the extraction of text strings from complex document images demonstrate the effectiveness of the proposed methods.1

Keywords: image segmentation, multilevel thresholding, clustering, discriminant analysis

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Authors: J.S.C. Prentice

Abstract:

The RK1GL2X3 method is a numerical method for solving initial value problems in ordinary differential equations, and is based on the RK1GL2 method which, in turn, is a particular case of the general RKrGLm method. The RK1GL2X3 method is a fourth-order method, even though its underlying Runge-Kutta method RK1 is the first-order Euler method, and hence, RK1GL2X3 is considerably more efficient than RK1. This enhancement is achieved through an implementation involving triple-nested two-point Gauss- Legendre quadrature.

Keywords: RK1GL2X3, RK1GL2, RKrGLm, Runge-Kutta, Gauss-Legendre, initial value problem, local error, global error.

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Authors: Eka PW, T. Okazaki, Y. Murakami, N., Hozumi, M. Nagao

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The breakdown strength characteristic of Low Density Polyethylene films (LDPE) under DC voltage application and the effect of water absorption have been studied. Mainly, our experiment was investigated under two conditions; dry and heavy water absorption. Under DC ramp voltage, the result found that the breakdown strength under heavy water absorption has a lower value than dry condition. In order to clarify the effect, the temperature rise of film was observed using non contact thermograph until the occurrence of the electrical breakdown and the conduction current of the sample was also measured in correlation with the thermograph measurement. From the observations, it was shown that under the heavy water absorption, the hot spot in the samples appeared at lower voltage. At the same voltage the temperature of the hot spot and conduction current was higher than that under the dry condition. The measurement result has a good correlation between the existence of a critical field for conduction current and thermograph observation. In case of the heavy water absorption, the occurrence of the threshold field was earlier than the dry condition as result lead to higher of conduction current and the temperature rise appears after threshold field was significantly increased in increasing of field. The higher temperature rise was caused by the higher current conduction as the result the insulation leads to breakdown to the lower field application.

Keywords: Low density polyethylene, heavy water absorption, conduction current, temperature rise.

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Authors: Dor Oppenheim, Yael Edan, Guy Shani

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This paper presents an image analysis algorithm to detect and count yellow tomato flowers in a greenhouse with uneven illumination conditions, complex growth conditions and different flower sizes. The algorithm is designed to be employed on a drone that flies in greenhouses to accomplish several tasks such as pollination and yield estimation. Detecting the flowers can provide useful information for the farmer, such as the number of flowers in a row, and the number of flowers that were pollinated since the last visit to the row. The developed algorithm is designed to handle the real world difficulties in a greenhouse which include varying lighting conditions, shadowing, and occlusion, while considering the computational limitations of the simple processor in the drone. The algorithm identifies flowers using an adaptive global threshold, segmentation over the HSV color space, and morphological cues. The adaptive threshold divides the images into darker and lighter images. Then, segmentation on the hue, saturation and volume is performed accordingly, and classification is done according to size and location of the flowers. 1069 images of greenhouse tomato flowers were acquired in a commercial greenhouse in Israel, using two different RGB Cameras – an LG G4 smartphone and a Canon PowerShot A590. The images were acquired from multiple angles and distances and were sampled manually at various periods along the day to obtain varying lighting conditions. Ground truth was created by manually tagging approximately 25,000 individual flowers in the images. Sensitivity analyses on the acquisition angle of the images, periods throughout the day, different cameras and thresholding types were performed. Precision, recall and their derived F1 score were calculated. Results indicate better performance for the view angle facing the flowers than any other angle. Acquiring images in the afternoon resulted with the best precision and recall results. Applying a global adaptive threshold improved the median F1 score by 3%. Results showed no difference between the two cameras used. Using hue values of 0.12-0.18 in the segmentation process provided the best results in precision and recall, and the best F1 score. The precision and recall average for all the images when using these values was 74% and 75% respectively with an F1 score of 0.73. Further analysis showed a 5% increase in precision and recall when analyzing images acquired in the afternoon and from the front viewpoint.

Keywords: Agricultural engineering, computer vision, image processing, flower detection.

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Authors: Mohammed Salem Alzahrani

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In this paper the optimality of the solution of an existing real word assignment problem known as the seat assignment problem using Seat Assignment Method (SAM) is discussed. SAM is the newly driven method from three existing methods, Hungarian Method, Northwest Corner Method and Least Cost Method in a special way that produces the easiness & fairness among all methods that solve the seat assignment problem.

Keywords: Assignment Problem, Hungarian Method, Least Cost Method, Northwest Corner Method, Seat Assignment Method (SAM), A Real Word Assignment Problem.

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Authors: Seifedine Kadry

Abstract:

In this article, our objective is the analysis of the resolution of non-linear differential systems by combining Newton and Continuation (N-C) method. The iterative numerical methods converge where the initial condition is chosen close to the exact solution. The question of choosing the initial condition is answered by N-C method.

Keywords: Continuation Method, Newton Method, Finite Difference Method, Numerical Analysis and Non-Linear partial Differential Equation.

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