Search results for: neural style transfer for edge

Authors: Tasanee Satthapong

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The purpose of the study was to determine the relationship between learning style preferences, teaching style preferences, and learning with happiness of college students who were majors in five different academic areas at the Suansunandha Rajabhat University in Thailand. The selected participants were 729 students 1st year-5th year in Faculty of Education from Thai teaching, early childhood education, math and science teaching, and English teaching majors. The research instruments are the Grasha and Riechmann learning and teaching styles survey and the students’ happiness in learning survey, based on learning with happiness theory initiated by the Office of the National Education Commission. The results of this study: 1) The most students’ learning styles were participant style, followed by collaborative style, and independent style 2) Most students’ happiness in learning in all subjects areas were at the moderate level: Early Childhood Education subject had the highest scores, while Math subject was at the least scores. 3) No different of student’s happiness in learning were found between students who has learning styles that match and not match to teachers’ teaching styles.

Keywords: learning style, teaching style, learning with happiness

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Authors: Shyam Sajan, Kamal Bijlani

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The widespread effects of digital media help people to explore the world more and get entertained with no effort. People became fond of these kind of sedentary life style. The increase in sedentary time and a decrease in physical activities has negative impacts on human health. Even though the addiction to video games has been exploited in exergames, to make people exercise and enjoy game challenges, the contribution is restricted only to physical wellness. This paper proposes creation and implementation of a game with the help of digital media in a virtual environment. The game is designed by collaborating ideas from neural linguistic programming and Stroop effect that can also be used to identify a person’s mental state, to improve concentration and to eliminate various phobias. The multiplayer game is played in a virtual environment created with Kinect sensor, to make the game more motivating and interactive.

Keywords: exergaming, Kinect Sensor, Neural Linguistic Programming, Stroop Effect

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Authors: Masaki Sakai, Tsuyoshi Nakajima, Kazuya Takahashi

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In order to improve the productivity of a factory, it is often the case to create an inference model by collecting and analyzing operational data off-line and then to develop an edge application (EAP) that evaluates the quality of the products or diagnoses machine faults in real-time. To accelerate this development cycle, an edge application framework for the smart factory is proposed, which enables to create and modify EAPs based on prepared inference models. In the framework, the preprocessing component is the key part to make it work. This paper proposes a language for preprocessing of edge applications, called LaPEA, which can flexibly process several sensor data from machines into explanatory variables for an inference model, and proves that it meets the requirements for the preprocessing.

Keywords: edge application framework, edgecross, preprocessing language, smart factory

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Authors: Aviva Lvan, Lipaz Shamoa-Nir

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Recently, has increased the research interest in modern fatherhood especially, the increasing involvement of fathers in the family. However, there is a little research evidence on fathers to children with special needs. Therefore, the purpose of this study was to examine the effects of stress and coping style on involvement in school among fathers to children with special needs in inclusive education. We compared the fathers to children with special needs (N=72) with fathers to non-special needs children (N = 75), and found that higher stress levels, greater educational involvement and greater use of social support coping style, were found among fathers of children with special needs. In addition, mission coping style and emotional coping style predict involvement in the school and emotional coping style predicts high levels of stress. The above findings contribute to the investigation of changes in the perception of the role of fathers and their involvement in their children's lives especially, among fathers to children with special needs. From the applied aspect, the findings may increase the understanding of the role of fathers and their unique contribution to the social, emotional, and academic development of their children.

Keywords: coping style, educational involvement, special needs, stress

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Authors: Siti Ruhliah Lizarose Samion, Mohamed Sukri Mat Ali, Con Doolan

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The present work is an experimental investigation of adapting a passive treatment leading edge serrations over a rod-airfoil flow-induced noise generation. The leading edge serrations are bio-inspired from a barn-owl silent flight. The rod-airfoil configuration is a benchmark configuration taken to investigate airfoil-turbulence interaction noise (ATIN). Location of serrations placed and the wideness of serrations are the two parameters taken in this study. The ATIN is reduced up to 3.5 dB for a wide leading serrations case. A correlation is found between the wideness of serrations and the noise reduction mechanism of the airfoil.

Keywords: aerodynamic noise, leading edge serrations, rod-airfoil, experiment

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Authors: Abdulkader Helwan

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Rheumatoid joint inflammation is characterized as a perpetual incendiary issue which influences the joints by hurting body tissues Therefore, there is an urgent need for an effective intelligent identification system of knee Rheumatoid arthritis especially in its early stages. This paper is to develop a new intelligent system for the identification of Rheumatoid arthritis of the knee utilizing image processing techniques and neural classifier. The system involves two principle stages. The first one is the image processing stage in which the images are processed using some techniques such as RGB to gryascale conversion, rescaling, median filtering, background extracting, images subtracting, segmentation using canny edge detection, and features extraction using pattern averaging. The extracted features are used then as inputs for the neural network which classifies the X-ray knee images as normal or abnormal (arthritic) based on a backpropagation learning algorithm which involves training of the network on 400 X-ray normal and abnormal knee images. The system was tested on 400 x-ray images and the network shows good performance during that phase, resulting in a good identification rate 97%.

Keywords: rheumatoid arthritis, intelligent identification, neural classifier, segmentation, backpropoagation

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Authors: Rana Gill, Chandandeep Kaur

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Segmentation of images can be implemented using different fundamental algorithms like edge detection (discontinuity based segmentation), region growing (similarity based segmentation), iterative thresholding method. A comprehensive literature review relevant to the study gives description of different techniques for vehicle number plate detection and edge detection techniques widely used on different types of images. This research work is based on edge detection techniques and calculating threshold on the basis of five edge operators. Five operators used are Prewitt, Roberts, Sobel, LoG and Canny. Segmentation of characters present in different type of images like vehicle number plate, name plate of house and characters on different sign boards are selected as a case study in this work. The proposed methodology has seven stages. The proposed system has been implemented using MATLAB R2010a. Comparison of all the five operators has been done on the basis of their performance. From the results it is found that Canny operators produce best results among the used operators and performance of different edge operators in decreasing order is: Canny>Log>Sobel>Prewitt>Roberts.

Keywords: segmentation, edge detection, text, extracting characters

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Authors: Arazan Jane V., Badiang, Ronesito Jr. R., Clavesillas Cristine Joy H., Belleza Saramie S.

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This study examined the coaching style among the PE Teachers in terms of Autonomy, Supportive style, and Controlling Style. On the other hand, gives opportunities to an athlete to be independent, task-oriented, and acknowledge their feelings and perspective of each individual. A controlling coaching style is also portrayed by the rises and falls over an athlete's training development; when this variance is identified, it might harm training. The selection of the respondents of the study will use a random sample of High School PE teachers of the Division of Davao del Norte with a total of 78 High School PE teachers, which can be broken down into 70 High School PE Teachers for Quantitative data for the survey questionnaire and 8 PE Teachers for Qualitative data (IDI). In the quantitative phase, a set of survey questionnaires will be used to gather data from the participants—the extent of the Implementation Questionnaire. The tool will be a researcher-made questionnaire based on the Coaching Styles of selected High School PE teachers of Davao Del Norte. In the qualitative phase, an interview guide questionnaire will be used. Focus group discussions will be conducted to determine themes and patterns or participants' experiences and insights. The researchers conclude that the degree of coaching style among PE Teachers from the Division of Davao del Norte is high, as seen by the findings of this study, and that coaching style among these teachers is highly noticeable.

Keywords: supportive autonomy style, controlling style, live experiences, exemplified

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Authors: A. A. Behroozpoor, M. M. Mazarei

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In this paper, a fuzzy recurrent neural network is proposed for solving the classical quadratic control problem subject to linear equality and bound constraints. The convergence of the state variables of the proposed neural network to achieve solution optimality is guaranteed.

Keywords: REFERENCES [1] Xia, Y, A new neural network for solving linear and quadratic programming problems. IEEE Transactions on Neural Networks, 7(6), 1996, pp.1544–1548. [2] Xia, Y., & Wang, J, A recurrent neural network for solving nonlinear convex programs subject to linear constraints. IEEE Transactions on Neural Networks, 16(2), 2005, pp. 379–386. [3] Xia, Y., H, Leung, & J, Wang, A projection neural network and its application to constrained optimization problems. IEEE Transactions Circuits and Systems-I, 49(4), 2002, pp.447–458.B. [4] Q. Liu, Z. Guo, J. Wang, A one-layer recurrent neural network for constrained seudoconvex optimization and its application for dynamic portfolio optimization. Neural Networks, 26, 2012, pp. 99-109.

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Authors: Li Chen

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For an aerofoil or hydrofoil in high Reynolds number flows, broadband noise is generated efficiently as the result of the turbulence convecting over the trailing edge. This noise can be related to the surface pressure fluctuations, which can be predicted by either CFD or empirical models. However, in reality, the aerofoil or hydrofoil often operates at an angle of attack. Under this situation, the flow is subjected to an Adverse-Pressure-Gradient (APG), and as a result, a flow separation may occur. This study is to assess trailing-edge noise models for such flows. In the present work, the trailing-edge noise from a 2D airfoil at 6 degree of angle of attach is investigated. Under this condition, the flow is experiencing a strong APG, and the flow separation occurs. The flow over the airfoil with a chord of 300 mm, equivalent to a Reynold Number 4x10⁵, is simulated using RANS with the SST k-ɛ turbulent model. The predicted surface pressure fluctuations are compared with the published experimental data and empirical models, and show a good agreement with the experimental data. The effect of the APG on the trailing edge noise is discussed, and the associated trailing edge noise is calculated.

Keywords: aero-acoustics, adverse-pressure gradient, computational fluid dynamics, trailing-edge noise

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Authors: Muhammad Atif, Cang Yan

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The enhancement of low-light images is a significant area of study aimed at enhancing the quality of captured images in challenging lighting environments. Recently, methods based on convolutional neural networks (CNN) have gained prominence as they offer state-of-the-art performance. However, many approaches based on CNN rely on increasing the size and complexity of the neural network. In this study, we propose an alternative method for improving low-light images using an autoencoder-based multiscale knowledge transfer model. Our method leverages the power of three autoencoders, where the encoders of the first two autoencoders are directly connected to the decoder of the third autoencoder. Additionally, the decoder of the first two autoencoders is connected to the encoder of the third autoencoder. This architecture enables effective knowledge transfer, allowing the third autoencoder to learn and benefit from the enhanced knowledge extracted by the first two autoencoders. We further integrate the proposed model into the PIX to PIX GAN framework. By integrating our proposed model as the generator in the GAN framework, we aim to produce enhanced images that not only exhibit improved visual quality but also possess a more authentic and realistic appearance. These experimental results, both qualitative and quantitative, show that our method is better than the state-of-the-art methodologies.

Keywords: low light image enhancement, deep learning, convolutional neural network, image processing

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Authors: Tim Farrelly

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In recent years, AI-powered object detection systems have opened the doors for innovative new applications and products, especially those operating in the real world or ‘on edge’ – namely, in sport. This paper investigates the viability of an ultra-low parameter convolutional neural network specially designed for the detection of footballs on ‘on the edge’ devices. The main contribution of this paper is the exploration of integrating new design features (depth-wise separable convolutional blocks and squeezed and excitation modules) into an ultra-low parameter network and demonstrating subsequent improvements in performance. The results show that tracking the ball from Full HD images with negligibly high accu-racy is possible in real-time.

Keywords: deep learning, object detection, machine vision applications, sport, network design

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Authors: Bingquan Shen

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Convolutional Neural Networks (CNN) have demonstrated their effectiveness in synthesizing 3D views of object instances at various viewpoints. Given the problem where one have limited viewpoints of a particular object for classification, we present a pose normalization architecture to transform the object to existing viewpoints in the training dataset before classification to yield better classification performance. We have demonstrated that this Pose Normalization Network (PNN) can capture the style of the target object and is able to re-render it to a desired viewpoint. Moreover, we have shown that the PNN improves the classification result for the 3D chairs dataset and ShapeNet airplanes dataset when given only images at limited viewpoint, as compared to a CNN baseline.

Keywords: convolutional neural networks, object classification, pose normalization, viewpoint invariant

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Authors: Ghulam Zahra

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Parenting style affects the morality of their children. There is plenty of evidence to support the effect of parenting styles on the morality of their children. Therefore, this research is considered essential and suitable. Thus, the main objective of this study was to assess the correlation between the parenting style of mothers and the moral development of primary school students. The population consisted of all primary school students enrolled in the province of Punjab. The sample was comprised of twelve hundred thirty-nine primary school students. One questionnaire was adapted to explore the parenting styles of mothers and to assess the level of students’ level of morality; a moral development scale was adopted. The conclusions showed that there was a significant correlation exist among authoritarian parenting style, permissive parenting, and moral developments. Based on findings, it is recommended that parents should follow a warm style of parenting for the sake of the moral development of their children.

Keywords: maternal parenting style, moral development, authoritative parenting, authoritarian parenting, permissive parenting

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Authors: Yuanchao Sang, Zhihao Gong, Longsheng Chen, Long Chen

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Clothing fashion represents a human’s aesthetic appreciation towards everyday outfits and appetite for fashion, and it reflects the development of status in society, humanity, and economics. However, modelling fashion by machine is extremely challenging because fashion is too abstract to be efficiently described by machines. Even human beings can hardly reach a consensus about fashion. In this paper, we are dedicated to answering a fundamental fashion-related problem: what image feature best describes clothing fashion? To address this issue, we have designed and evaluated various image features, ranging from traditional low-level hand-crafted features to mid-level style awareness features to various current popular deep neural network-based features, which have shown state-of-the-art performance in various vision tasks. In summary, we tested the following 9 feature representations: color, texture, shape, style, convolutional neural networks (CNNs), CNNs with distance metric learning (CNNs&DML), AutoEncoder, CNNs with multiple layer combination (CNNs&MLC) and CNNs with dynamic feature clustering (CNNs&DFC). Finally, we validated the performance of these features on two publicly available datasets. Quantitative and qualitative experimental results on both intra-domain and inter-domain fashion clothing image retrieval showed that deep learning based feature representations far outweigh traditional hand-crafted feature representation. Additionally, among all deep learning based methods, CNNs with explicit feature clustering performs best, which shows feature clustering is essential for discriminative fashion feature representation.

Keywords: convolutional neural network, feature representation, image processing, machine modelling

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Authors: Meseret Mulugeta, Alemmebrat Kiflu, Belaynehchikle

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The purpose of the present study was to examine the preferred leadership style and motivation of premier league volleyball players. The sample encompassed 46 female premier league volleyball players whose ages ranged between 15 and 35 years. The data were collected using standardized questionnaires. The questionnaires were distributed to 46 female players from five volleyball clubs in the Premier League. To evaluate the motivational level of the players, the Sports Motivation Scale (SMS-6) was used. The leadership scale for sport was used to evaluate leadership. Descriptive statistics and the person correlation coefficient (P <0.05) were used to validate the relationship between leadership style and motivation. The result showed that there is a meaningful and significant relationship between leadership style and motivation. Concerning preferred coaching styles, the most preferred style was training and instruction, with a mean score of 4.10, and the least preferred style was autocratic, with a mean score of 3.37. The result of the Pearson correlation coefficient showed that the correlation between motivation types and leadership styles showed that motivation was significantly and positively correlated with all independent variables except autocratic leadership style, which is negatively correlated with motivation. This study’s nobility is to provide evidence for the most effective coaching to practice the training and instruction behaviour and social support behaviour leadership styles and refrain from using the autocratic leadership style.

Keywords: autocratic, training and instruction, motivation, leadership style

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Authors: Najmeh Mohsenifar, Narjes Mohsenifar, Abbas Kargar

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In this paper, has been presented a stable method for predicting the ECG signals through the RBF neural networks, by the PSO algorithm. In spite of quasi-periodic ECG signal from a healthy person, there are distortions in electro cardiographic data for a patient. Therefore, there is no precise mathematical model for prediction. Here, we have exploited neural networks that are capable of complicated nonlinear mapping. Although the architecture and spread of RBF networks are usually selected through trial and error, the PSO algorithm has been used for choosing the best neural network. In this way, 2 second of a recorded ECG signal is employed to predict duration of 20 second in advance. Our simulations show that PSO algorithm can find the RBF neural network with minimum MSE and the accuracy of the predicted ECG signal is 97 %.

Keywords: electrocardiogram, RBF artificial neural network, PSO algorithm, predict, accuracy

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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: Christopher Godwin Udomboso, Angela Unna Chukwu, Isaac Kwame Dontwi

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In selecting a Statistical Neural Network model, the Network Information Criterion (NIC) has been observed to be sample biased, because it does not account for sample sizes. The selection of a model from a set of fitted candidate models requires objective data-driven criteria. In this paper, we derived and investigated the Adjusted Network Information Criterion (ANIC), based on Kullback’s symmetric divergence, which has been designed to be an asymptotically unbiased estimator of the expected Kullback-Leibler information of a fitted model. The analyses show that on a general note, the ANIC improves model selection in more sample sizes than does the NIC.

Keywords: statistical neural network, network information criterion, adjusted network, information criterion, transfer function

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Authors: Zuoji Huang, Haiming Qian, Chunlin Wang, Jinyan Sun, Nan Xu

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In this paper, the strategy to extract double road edge lines from acquired road stripe image was explored. The workflow is as follows: the road stripes are acquired by probabilistic boosting tree algorithm and morphological algorithm immediately, and road centerlines are detected by thinning algorithm, so the initial road edge lines can be acquired along the road centerlines. Then we refine the results with big variation of local curvature of centerlines. Specifically, the energy function of edge line is constructed by gradient feature and spectral information, and Dijkstra algorithm is used to optimize the initial road edge lines. The Snake model is constructed to solve the fracture problem of intersection, and the discrete dynamic programming algorithm is used to solve the model. After that, we could get the final road network. Experiment results show that the strategy proposed in this paper can be used to extract the continuous and smooth road edge lines from high-resolution remote sensing images with an accuracy of 88% in our study area.

Keywords: road edge lines extraction, energy function, intersection fracture, Snake model

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Authors: Jamaludin Tarkim, Yoga Teguh Guntara, Maftuhah

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Islamic leadership style is model of leadership style applied by the Prophet Muhammad SAW. Islamic leadership style is applied, namely Syura (deliberation), ‘Adl bil qisth (justice, with equality), and Hurriyyah al-kalam (freedom of expression) and along with the values of Islam in the Islamic leadership style. This research aims to gain an overview of the experience of Head Nurse in the implementation of Islamic leadership style. This research is a qualitative one with descriptive phenomenology design through in-depth interviews. Participants were occupied as Head Nurse at the Hospital room Syarif Hidayatullah, set directly (purposive) with the principle of suitability (appropriateness) and sufficiency (adequacy). Retrieval of data and research conducted during the month of June 2014. Data collected in the form of recording in-depth interviews and analysis with Collazi method. This research identified four themes Syura (deliberation);‘Adl bil qisth (justice, with equality); Hurriyyah al-kalam (freedom of expression) and along with the values of Islam in the Islamic leadership style. The results of this research can provide a review of the Head Room experience in the application of Islamic leadership style at Syarif Hidayatullah Hospital already skilled leadership during the process, but the application is still not maximized. Required further research on in-depth exploration of how to get more comprehensive results from room Head Nurse experience in the application of Islamic leadership style, as well as subsequent researchers can choose a wider scope and complex so get more complete data.

Keywords: experience, Islamic leadership style, head nurse, nursing management

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Authors: Muhammad Kamran Asif

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MPLS stands for Multi-Protocol Label Switching. It is the technology which replaces ATM (Asynchronous Transfer Mode) and frame relay. In this paper, we have designed a full fledge small scale MPLS based service provider network core network model, which provides communication services (e.g. voice, video and data) to the customer more efficiently using label switching technique. Using MPLS VPN provides security to the customers which are either on LAN or WAN. It protects its single customer sites from being attacked by any intruder from outside world along with the provision of concept of extension of a private network over an internet. In this paper, we tried to implement a service provider network using minimum available resources i.e. five 3800 series CISCO routers comprises of service provider core, provider edge routers and customer edge routers. The customers on the one end of the network (customer side) is capable of sending any kind of data to the customers at the other end using service provider cloud which is MPLS VPN enabled. We have also done simulation and emulation for the model using GNS3 (Graphical Network Simulator-3) and achieved the real time scenarios. We have also deployed a NMS system which monitors our service provider cloud and generates alarm in case of any intrusion or malfunctioning in the network. Moreover, we have also provided a video help desk facility between customers and service provider cloud to resolve the network issues more effectively.

Keywords: MPLS, VPN, NMS, ATM, asynchronous transfer mode

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Authors: Diego De Almeida Pereira, Diana Borchenko

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Artificial neural networks are used for many applications as they are able to learn complex nonlinear relationships between input and output data. As the number of neurons and layers in a neural network increases, it is possible to represent more complex behaviors. The present study proposes that artificial neural networks are a valuable tool for architecture and engineering professionals concerned with understanding how buildings influence human and social well-being based on theories of environmental psychology.

Keywords: environmental psychology, architecture, neural networks, human and social well-being

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Authors: Arthur D. Wiedemann, Christopher Fuller, Kyle A. Pascioni

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With the introduction of electric motors, small unmanned aerial vehicle designers have to consider trade-offs between acoustic noise and thrust generated. Currently, there are few low-computational tools available for predicting acoustic noise emitted by a propeller into the far-field. Artificial neural networks offer a highly non-linear and adaptive model for predicting isolated and interactive tonal noise. But neural networks require large data sets, exceeding practical considerations in modeling experimental results. A methodology known as physics guided machine learning has been applied in this study to reduce the required data set to train the network. After building and evaluating several neural networks, the best model is investigated to determine how the network successfully predicts the acoustic waveform. Lastly, a post-network transfer function is developed to remove discontinuity from the predicted waveform. Overall, methodologies from physics guided machine learning show a notable improvement in prediction performance, but additional loss functions are necessary for constructing predictive networks on small datasets.

Keywords: aeroacoustics, machine learning, propeller, rotor, neural network, physics guided machine learning

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Authors: Li-Ting Chen, Chih-Tao Cheng, I-Ping Huang, Jen-Ho Chang, Nien-Tzu Chang, Fei-Hsiu Hsiao

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Background: Insecurity adult attachment style may be triggered by cancer threat, which in turn influences depression symptoms. Dispositional mindfulness may have benefits of insecure attachment on depression for colorectal patient transfer to survivor. Objective: This study examined the mediating and moderating effects of quality of life (QOL) and dispositional mindfulness on the relationship between insecure attachment style and depression symptoms. Methods: A cross-sectional study design was used. Data were collected using the QOL functional and symptoms (EORTC-C30 and EORTC CR29), dispositional mindfulness (FFMQ), Short form of Experience in Close Relationships Revised Questionnaire (SF-ECRRQ), and depressive symptoms (BDI-II scale). Results: Of the 90 CRC survivors who participated, the indirect effect of both ECR anxiety (β=0.23, CI=0.05-0.44) and ECR avoidance (β=0.12, CI=0.02-0.24) on depression were significantly mediated through EORTC-C29 colorectal symptoms. Three components of dispositional mindfulness (i.e., acting of awareness, non-judging, non-reactivity) as the moderator in the relationship between ECR anxiety and depressive symptoms. Acting of awareness was a moderator in the relationship between ECR avoidance and depressive symptoms. Conclusions: There are two pathways from insecure attachment to depression: through the mediator of colorectal symptoms and the moderator of dispositional mindfulness. Cancer symptom management and mindfulness practices could improve the impact of insecure attachment on depression among CRC patients in a post-treatment transition period.

Keywords: acting of awareness, attachment style, colorectal cancer, disposisitonal mindfulness, depression

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Authors: Ahmed Alaoui

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This paper contributes to the ongoing debate as to the relevance of translation studies to professional practitioners. It exposes the various misconceptions permeating the links between theory and practice in the translation landscape in the Arab World. It is a thesis of this paper that specialization in translation should be redefined; taking account of the fact, that specialized knowledge alone is neither crucial nor sufficient in technical translation. It should be tested against the readability of the translated text, the appropriateness of its style and the usability of its content by end-users to carry out their intended tasks. The paper also proposes a preliminary model to establish a working link between theory and practice from the perspective of professional trainers and practitioners, calling for the latter to participate in the production of knowledge in a systematic fashion. While this proposal is driven by a rather intuitive conviction, a research line is needed to specify the methodological moves to establish the mediation strategies that would relate the components in the model of knowledge transfer proposed in this paper.

Keywords: knowledge transfer, misconceptions, specialized texts, translation theory, translation practice

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Authors: Mohammad Reza Rahimi Khoygani, Reza Ghasemi

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In this paper, designing direct adaptive neural controller is applied for a class of a nonlinear pendulum dynamic system. The radial basis function (RBF) is used for the Neural network (NN). The adaptive neural controller is robust in presence of external and internal uncertainties. Both the effectiveness of the controller and robustness against disturbances are the merits of this paper. The promising performance of the proposed controllers investigates in simulation results.

Keywords: adaptive control, pendulum dynamical system, nonlinear control, adaptive neural controller, nonlinear dynamical, neural network, RBF, driven pendulum, position control

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Authors: Yi-Wei Huang

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Eileen Chang is a well-known writer of modern Chinese literature. She is also a translator that publishes her self-translation The Rice Sprout Song. The purpose of the study is to identify the style of Eileen Chang’s self-translations by corpora, especially in the case of The Rice Sprout Song. The Rice Sprout Song is first written in English and then translated into Chinese by the author herself. The procedure of translation is complicated due to the bilingual transition by the same person. Therefore, the aim of the study is to identify Eileen Chang’s style on her self-translation by comparing her works The Old Man and the Sea, The Rice Sprout Song, and The Rouge of The North. The study uses computer-aided software like AntConc, Notepad++, StanfordCoreNLP, and Python to analyze the style of the works, especially focuses on reduplications and the composition of the sentences. Reduplications are commonly seen in Eileen Chang’s works, and they often appear with colors or onomatopoeia. With these criteria, the style of self-translating can be detected and analyzed.

Keywords: corpora, Eileen Chang, reduplications, self-translation

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Authors: Zeyu Zhou, Xiaojun Bi

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Due to the limited environmental parameters and the limited resolution of the sensor, the universal existence of the mixed pixels in the process of remote sensing images restricts the spatial resolution of the remote sensing images. Sub-pixel mapping technology can effectively improve the spatial resolution. As the bilinear interpolation algorithm inevitably produces the edge blur effect, which leads to the inaccurate sub-pixel mapping results. In order to avoid the edge blur effect that affects the sub-pixel mapping results in the interpolation process, this paper presents a new edge-directed interpolation algorithm which uses the covariance adaptive interpolation algorithm on the edge of the low-resolution image and uses bilinear interpolation algorithm in the low-resolution image smooth area. By using the edge-directed interpolation algorithm, the super-resolution of the image with low resolution is obtained, and we get the percentage of each sub-pixel under a certain type of high-resolution image. Then we rely on the probability value as a soft attribute estimate and carry out sub-pixel scale under the ‘hard classification’. Finally, we get the result of sub-pixel mapping. Through the experiment, we compare the algorithm and the bilinear algorithm given in this paper to the results of the sub-pixel mapping method. It is found that the sub-pixel mapping method based on the edge-directed interpolation algorithm has better edge effect and higher mapping accuracy. The results of the paper meet our original intention of the question. At the same time, the method does not require iterative computation and training of samples, making it easier to implement.

Keywords: remote sensing images, sub-pixel mapping, bilinear interpolation, edge-directed interpolation

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Authors: Terence Soule, Tami Al Ghamdi

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To study how the partial knowledge transfer may affect the Genetic Algorithm (GA) performance, we model the Transfer Learning (TL) process using GA as the model solver. The objective of the TL is to transfer the knowledge from one problem to another related problem. This process imitates how humans think in their daily life. In this paper, we proposed to study a case where the knowledge transferred from the S problem has less information than what the T problem needs. We sampled the transferred population using different strategies of TL. The results showed transfer part of the knowledge is helpful and speeds the GA process of finding a solution to the problem.

Keywords: transfer learning, partial transfer, evolutionary computation, genetic algorithm

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