Search results for: reflection noise
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1930

Search results for: reflection noise

1300 Generation of High-Quality Synthetic CT Images from Cone Beam CT Images Using A.I. Based Generative Networks

Authors: Heeba A. Gurku

Abstract:

Introduction: Cone Beam CT(CBCT) images play an integral part in proper patient positioning in cancer patients undergoing radiation therapy treatment. But these images are low in quality. The purpose of this study is to generate high-quality synthetic CT images from CBCT using generative models. Material and Methods: This study utilized two datasets from The Cancer Imaging Archive (TCIA) 1) Lung cancer dataset of 20 patients (with full view CBCT images) and 2) Pancreatic cancer dataset of 40 patients (only 27 patients having limited view images were included in the study). Cycle Generative Adversarial Networks (GAN) and its variant Attention Guided Generative Adversarial Networks (AGGAN) models were used to generate the synthetic CTs. Models were evaluated by visual evaluation and on four metrics, Structural Similarity Index Measure (SSIM), Peak Signal Noise Ratio (PSNR) Mean Absolute Error (MAE) and Root Mean Square Error (RMSE), to compare the synthetic CT and original CT images. Results: For pancreatic dataset with limited view CBCT images, our study showed that in Cycle GAN model, MAE, RMSE, PSNR improved from 12.57to 8.49, 20.94 to 15.29 and 21.85 to 24.63, respectively but structural similarity only marginally increased from 0.78 to 0.79. Similar, results were achieved with AGGAN with no improvement over Cycle GAN. However, for lung dataset with full view CBCT images Cycle GAN was able to reduce MAE significantly from 89.44 to 15.11 and AGGAN was able to reduce it to 19.77. Similarly, RMSE was also decreased from 92.68 to 23.50 in Cycle GAN and to 29.02 in AGGAN. SSIM and PSNR also improved significantly from 0.17 to 0.59 and from 8.81 to 21.06 in Cycle GAN respectively while in AGGAN SSIM increased to 0.52 and PSNR increased to 19.31. In both datasets, GAN models were able to reduce artifacts, reduce noise, have better resolution, and better contrast enhancement. Conclusion and Recommendation: Both Cycle GAN and AGGAN were significantly able to reduce MAE, RMSE and PSNR in both datasets. However, full view lung dataset showed more improvement in SSIM and image quality than limited view pancreatic dataset.

Keywords: CT images, CBCT images, cycle GAN, AGGAN

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1299 Process of Revitalization of the City Centres in Poland: The Problem of Cooperation between Sectors

Authors: Ewa M. Boryczka

Abstract:

Contemporary city is a subject to rapid economic and social changes. Therefore it requires an active policy designed to meet the diverse needs of their residents, build competitive position and capacity to compete with other cities. Competitiveness of cities depends largely on their resources, but also to a large extent, on the policies and performance of local authorities. Cooperation with private and social sectors also plays an important role, as it affects the use of resources and builds an advantage over other cities. The subject of this article is city's contemporary problems of development with particular emphasis on central areas. This issue is a starting point for reflection on the process of urban regeneration in medium size cities in Poland, as well as cooperation between various actors and their roles in the revitalization processes of Polish cities' centres.

Keywords: city, cooperation between sectors, crisis of city centres, revitalization

Procedia PDF Downloads 447
1298 TiO2/PDMS Coating With Minimum Solar Absorption Loss for Passive Daytime Radiative Cooling

Authors: Bhrigu Rishi Mishra, Sreerag Sundaram, Nithin Jo Varghese, Karthik Sasihithlu

Abstract:

We have designed a TiO2/PDMS coating with 94% solar reflection, 96% IR emission, and 81.8 W/m2 cooling power for passive daytime radiative cooling using Kubelka Munk theory and CST microwave studio. To reduce solar absorption loss in 0.3-0.39 m wavelength region, a TiO2 thin film on top of the coating is used. Simulation using Ansys Lumerical shows that for a 20 m thick TiO2/PDMS coating, a TiO2 thin film of 84 nm increases the coating's reflectivity by 11% in the solar region.

Keywords: passive daytime radiative cooling, disordered metamaterial, Kudelka Munk theory, solar reflectivity

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1297 Mimesis in William Shakespeare's Selected Sonnets

Authors: Roselyn T. Bustos

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Literature is an imitation of life. It depicts man's culture as well as his struggles. In short, literature is a part of man's way of life- a reflection of his personal or vicarious experiences. Using the qualitative-descriptive content analysis, this study investigates the mimetic signification in the five select sonnets of William Shakespeare.An in- depth analysis of the poetic elements such as the figurative language used and the themes extracted is made to draw out the universal meaning of his works. It is found out that his select sonnets use figurative languages such as simile, metaphor, personification, and hyperbaton which becomes a potent element that allows his sonnets to convey the themes of love and perseverance. With these findings, it is concluded that William Shakespeare's sonnets are evidently written within the context of the universals and that they are worthy of wide readership not only because of him being a renowned English poet and playwright but most importantly of the realities his sonnets signify.

Keywords: imitation, mimesis, potent, realities

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1296 Acceleration Techniques of DEM Simulation for Dynamics of Particle Damping

Authors: Masato Saeki

Abstract:

Presented herein is a novel algorithms for calculating the damping performance of particle dampers. The particle damper is a passive vibration control technique and has many practical applications due to simple design. It consists of granular materials constrained to move between two ends in the cavity of a primary vibrating system. The damping effect results from the exchange of momentum during the impact of granular materials against the wall of the cavity. This damping has the advantage of being independent of the environment. Therefore, particle damping can be applied in extreme temperature environments, where most conventional dampers would fail. It was shown experimentally in many papers that the efficiency of the particle dampers is high in the case of resonant vibration. In order to use the particle dampers effectively, it is necessary to solve the equations of motion for each particle, considering the granularity. The discrete element method (DEM) has been found to be effective for revealing the dynamics of particle damping. In this method, individual particles are assumed as rigid body and interparticle collisions are modeled by mechanical elements as springs and dashpots. However, the computational cost is significant since the equation of motion for each particle must be solved at each time step. In order to improve the computational efficiency of the DEM, the new algorithms are needed. In this study, new algorithms are proposed for implementing the high performance DEM. On the assumption that behaviors of the granular particles in the each divided area of the damper container are the same, the contact force of the primary system with all particles can be considered to be equal to the product of the divided number of the damper area and the contact force of the primary system with granular materials per divided area. This convenience makes it possible to considerably reduce the calculation time. The validity of this calculation method was investigated and the calculated results were compared with the experimental ones. This paper also presents the results of experimental studies of the performance of particle dampers. It is shown that the particle radius affect the noise level. It is also shown that the particle size and the particle material influence the damper performance.

Keywords: particle damping, discrete element method (DEM), granular materials, numerical analysis, equivalent noise level

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1295 Teacher Professional Development with Collaborative Action Research: Teachers' Responses to Research

Authors: Sumaya Saqr

Abstract:

Although many teachers regard academic research as the inclusive domain of academic researchers, teachers should contribute to the body of research guiding their own practice. Drawing on the qualitative analysis of 20 teachers’ reflection journals and interviews, this case study sheds light on the personal and professional benefits of teachers’ applications of collaborative action research in English language teaching context. The findings reveal that several aspects of teacher identity and classroom practice were changed. The present paper aspires to reveal the way in which collaborative action research process, as a learner-centered approach to staff development, would help teachers to become more independent and professionally autonomous and hence effecting change that is far greater than its initial purpose.

Keywords: change, collaborative action research, personal and professional benefits, professional development

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1294 Interruption Overload in an Office Environment: Hungarian Survey Focusing on the Factors that Affect Job Satisfaction and Work Efficiency

Authors: Fruzsina Pataki-Bittó, Edit Németh

Abstract:

On the one hand, new technologies and communication tools improve employee productivity and accelerate information and knowledge transfer, while on the other hand, information overload and continuous interruptions make it even harder to concentrate at work. It is a great challenge for companies to find the right balance, while there is also an ongoing demand to recruit and retain the talented employees who are able to adopt the modern work style and effectively use modern communication tools. For this reason, this research does not focus on the objective measures of office interruptions, but aims to find those disruption factors which influence the comfort and job satisfaction of employees, and the way how they feel generally at work. The focus of this research is on how employees feel about the different types of interruptions, which are those they themselves identify as hindering factors, and those they feel as stress factors. By identifying and then reducing these destructive factors, job satisfaction can reach a higher level and employee turnover can be reduced. During the research, we collected information from depth interviews and questionnaires asking about work environment, communication channels used in the workplace, individual communication preferences, factors considered as disruptions, and individual steps taken to avoid interruptions. The questionnaire was completed by 141 office workers from several types of workplaces based in Hungary. Even though 66 respondents are working at Hungarian offices of multinational companies, the research is about the characteristics of the Hungarian labor force. The most important result of the research shows that while more than one third of the respondents consider office noise as a disturbing factor, personal inquiries are welcome and considered useful, even if in such cases the work environment will not be convenient to solve tasks requiring concentration. Analyzing the sizes of the offices, in an open-space environment, the rate of those who consider office noise as a disturbing factor is surprisingly lower than in smaller office rooms. Opinions are more diverse regarding information communication technologies. In addition to the interruption factors affecting the employees' job satisfaction, the research also focuses on the role of the offices in the 21st century.

Keywords: information overload, interruption, job satisfaction, office environment, work efficiency

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1293 Classification of Coughing and Breathing Activities Using Wearable and a Light-Weight DL Model

Authors: Subham Ghosh, Arnab Nandi

Abstract:

Background: The proliferation of Wireless Body Area Networks (WBAN) and Internet of Things (IoT) applications demonstrates the potential for continuous monitoring of physical changes in the body. These technologies are vital for health monitoring tasks, such as identifying coughing and breathing activities, which are necessary for disease diagnosis and management. Monitoring activities such as coughing and deep breathing can provide valuable insights into a variety of medical issues. Wearable radio-based antenna sensors, which are lightweight and easy to incorporate into clothing or portable goods, provide continuous monitoring. This mobility gives it a substantial advantage over stationary environmental sensors like as cameras and radar, which are constrained to certain places. Furthermore, using compressive techniques provides benefits such as reduced data transmission speeds and memory needs. These wearable sensors offer more advanced and diverse health monitoring capabilities. Methodology: This study analyzes the feasibility of using a semi-flexible antenna operating at 2.4 GHz (ISM band) and positioned around the neck and near the mouth to identify three activities: coughing, deep breathing, and idleness. Vector network analyzer (VNA) is used to collect time-varying complex reflection coefficient data from perturbed antenna nearfield. The reflection coefficient (S11) conveys nuanced information caused by simultaneous variations in the nearfield radiation of three activities across time. The signatures are sparsely represented with gaussian windowed Gabor spectrograms. The Gabor spectrogram is used as a sparse representation approach, which reassigns the ridges of the spectrogram images to improve their resolution and focus on essential components. The antenna is biocompatible in terms of specific absorption rate (SAR). The sparsely represented Gabor spectrogram pictures are fed into a lightweight deep learning (DL) model for feature extraction and classification. Two antenna locations are investigated in order to determine the most effective localization for three different activities. Findings: Cross-validation techniques were used on data from both locations. Due to the complex form of the recorded S11, separate analyzes and assessments were performed on the magnitude, phase, and their combination. The combination of magnitude and phase fared better than the separate analyses. Various sliding window sizes, ranging from 1 to 5 seconds, were tested to find the best window for activity classification. It was discovered that a neck-mounted design was effective at detecting the three unique behaviors.

Keywords: activity recognition, antenna, deep-learning, time-frequency

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1292 Stepanovia osogoviensis sp. n. (Hymenoptera: Eulophidae) in Galls of Diplolepis rosae from Bulgaria

Authors: Ivaylo A. Todorov, Peter S. Boyadzhiev

Abstract:

A new distinctive species of Stepanovia Kostjukov (Hymenoptera: Eulophidae: Tetrastichinae) was reared in laboratory from mature galls of Diplolepis rosae (Linnaeus) (Cynipidae). The galls were collected from Rosa sp. bushes growing in Osogovo Mt. in Western Bulgaria. The new species is close to Stepanovia rosae Boyadzhiev & Todorov but differs in POL and OOL characteristics, width of antennae, forewings and ovipositor sheaths characteristics, different U-shaped pale stripe above clypeus and the length of the ventral plaque on male antenna. The taxonomically important morphological features are illustrated and compared with the rest species of the genus using Scanning electron microscopy and light reflection by compound microscopy. Images of male genitalia are also prepared.

Keywords: Eulophidae, Diplolepis rosae, galls, Stepanovia osogoviensis, Bulgaria

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1291 Scar Removal Stretegy for Fingerprint Using Diffusion

Authors: Mohammad A. U. Khan, Tariq M. Khan, Yinan Kong

Abstract:

Fingerprint image enhancement is one of the most important step in an automatic fingerprint identification recognition (AFIS) system which directly affects the overall efficiency of AFIS. The conventional fingerprint enhancement like Gabor and Anisotropic filters do fill the gaps in ridge lines but they fail to tackle scar lines. To deal with this problem we are proposing a method for enhancing the ridges and valleys with scar so that true minutia points can be extracted with accuracy. Our results have shown an improved performance in terms of enhancement.

Keywords: fingerprint image enhancement, removing noise, coherence, enhanced diffusion

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1290 Augmented Reality and Storytelling in Cities: An Application to Lisbon Street Art

Authors: Francisco Guimarães, Mauro Figueiredo, José Rodrigues

Abstract:

Cities are spaces of memory with several zones (parts of cities) with their own history and cultural events. Today, cities are also marked by a form of intangible cultural heritage like street art, which creates a visual culture based on the process of reflection about the city and the world. To link these realities and create a personal user interaction with this cultural heritage it is important to capture the story and aesthetics, and find alternatives to immerse the user in these spaces of memory. To that end, this article presents a project which combines Augmented Reality technologies and concepts of Transmedia Storytelling applied to Lisbon City, using Street Art artifacts as markers in a framework of digital media-art.

Keywords: augmented reality, cultural heritage, street art, transmedia storytelling, digital media-art

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1289 Women Characters in Pakistani Films: A Critical Evaluation

Authors: Ali Arshad

Abstract:

The study examines the depiction of women characters in Urdu and Punjabi films. It is a critical evaluation of forty-eight Pakistani films. It explores the characters of women portrays in Urdu and Punjabi film of Pakistan. Using content analysis as methodology with feminist research that helps to investigate the phenomena and supports the study. Finding of the study shows that women characters in Urdu and Punjabi films are not the reflection of true Pakistani women rather this picture represents a negative image of Pakistani women in viewers mind. These characters don’t address the women’s issues nor do they present the solutions to these problems faced by Pakistani women. The characters of Pakistani women are not free from male prejudice, and these films do not portray the social and political role perform by actual Pakistani women. The analysis shows that the characters of women in Urdu and Punjabi films are based on the assumptions.

Keywords: women, Pakistani, film, characters

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1288 The Impact of Drama Education on Creativity Development at Preschool Children

Authors: Vladimíra Hornáčková

Abstract:

This paper points out at the importance of creativity development in children of preschool age and analyses certain conditions and pedagogical principles which should be respected during the development of creativity in kindergartens. Research survey focuses on the development of creativity reflection at children in kindergartens at preschool age and based on a test of creativity it compares creativity of children in experimental and control groups. The goal is to find out if there are any differences among children in experimental and control classrooms in kindergartens; wherein experimental groups, there is preschool education with the use of drama education while in control groups there is not. On the basis of certain aspects, the gained data is compared through descriptive methods and correlations. Research results refer to reserves in creativity development in modern pre-primary education in the context of implemented and expected changes in didactic approach in the education of kindergartens.

Keywords: preschool child, drama in education, research, test of creativity

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1287 The Influence of Gilles Deleuze and Felix Guattari's Thoughts and Ideas on Post-Modern Architecture

Authors: A. Nabi, S. Panahi

Abstract:

In the recent years, due to the countless changes in the world and various sciences, architecture has faced a new approach and different concepts more than any other times. The direct influence of philosophy on architecture is one of the features of contemporary architecture. Linking these two learnings directly together needs deep reflection. Gilles Deleuze and Félix Guattari are among the people who greatly influenced the thinking of future architects and artists by bringing up new concepts. If we focus on the works of these architects and artists whose works resemble anti-Platonism and who subvert the western philosophy, we can extract concepts which we can see their influence on art and architecture. Using content analysis, this study has come to this conclusion that the ideas of Deleuze and Guattari could influence the contemporary architecture.

Keywords: Gilles Deleuze, Felix Guattari, anti-platonism, post-modern architecture, folding

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1286 Rituals in Rock Art: Case Study of Bronze Age Rock Art of Gobustan

Authors: Rahman Abdullayev

Abstract:

Rituals took place during the rock art production or in the rock art sites can be found reflection in contemporary culture. But the form of rituals was conducted in association with rock art production still uncertain. The main purpose of this research is to define the form of ritual activities that took place in the rock art sites, by the example of Bronze Age rock art of Gobustan. For ritual activity location of the rocks which were selected for making petroglyphs has important significance. Thus, not all the rocks which were suitable for rock art were used for this purpose. If in Upper Paleolithic, Mesolithic, Neolithic periods Gobustan inhabitants executed petroglyphs on the wall of rock shelters, but in Bronze Age they made it on rocks which are in front of the large, open spaces. A recent study of the location of Bronze Age rock art of Gobustan and involving ethnographic information to the interpretation of drawings allows defining the form of rituals which took place in Gobustan at Bronze Age.

Keywords: Bronze Age, Gobustan, ritual, rock art

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1285 Construction of the Large Scale Biological Networks from Microarrays

Authors: Fadhl Alakwaa

Abstract:

One of the sustainable goals of the system biology is understanding gene-gene interactions. Hence, gene regulatory networks (GRN) need to be constructed for understanding the disease ontology and to reduce the cost of drug development. To construct gene regulatory from gene expression we need to overcome many challenges such as data denoising and dimensionality. In this paper, we develop an integrated system to reduce data dimension and remove the noise. The generated network from our system was validated via available interaction databases and was compared to previous methods. The result revealed the performance of our proposed method.

Keywords: gene regulatory network, biclustering, denoising, system biology

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1284 Automatic Target Recognition in SAR Images Based on Sparse Representation Technique

Authors: Ahmet Karagoz, Irfan Karagoz

Abstract:

Synthetic Aperture Radar (SAR) is a radar mechanism that can be integrated into manned and unmanned aerial vehicles to create high-resolution images in all weather conditions, regardless of day and night. In this study, SAR images of military vehicles with different azimuth and descent angles are pre-processed at the first stage. The main purpose here is to reduce the high speckle noise found in SAR images. For this, the Wiener adaptive filter, the mean filter, and the median filters are used to reduce the amount of speckle noise in the images without causing loss of data. During the image segmentation phase, pixel values are ordered so that the target vehicle region is separated from other regions containing unnecessary information. The target image is parsed with the brightest 20% pixel value of 255 and the other pixel values of 0. In addition, by using appropriate parameters of statistical region merging algorithm, segmentation comparison is performed. In the step of feature extraction, the feature vectors belonging to the vehicles are obtained by using Gabor filters with different orientation, frequency and angle values. A number of Gabor filters are created by changing the orientation, frequency and angle parameters of the Gabor filters to extract important features of the images that form the distinctive parts. Finally, images are classified by sparse representation method. In the study, l₁ norm analysis of sparse representation is used. A joint database of the feature vectors generated by the target images of military vehicle types is obtained side by side and this database is transformed into the matrix form. In order to classify the vehicles in a similar way, the test images of each vehicle is converted to the vector form and l₁ norm analysis of the sparse representation method is applied through the existing database matrix form. As a result, correct recognition has been performed by matching the target images of military vehicles with the test images by means of the sparse representation method. 97% classification success of SAR images of different military vehicle types is obtained.

Keywords: automatic target recognition, sparse representation, image classification, SAR images

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1283 Global Stability Of Nonlinear Itô Equations And N. V. Azbelev's W-method

Authors: Arcady Ponosov., Ramazan Kadiev

Abstract:

The work studies the global moment stability of solutions of systems of nonlinear differential Itô equations with delays. A modified regularization method (W-method) for the analysis of various types of stability of such systems, based on the choice of the auxiliaryequations and applications of the theory of positive invertible matrices, is proposed and justified. Development of this method for deterministic functional differential equations is due to N.V. Azbelev and his students. Sufficient conditions for the moment stability of solutions in terms of the coefficients for sufficiently general as well as specific classes of Itô equations are given.

Keywords: asymptotic stability, delay equations, operator methods, stochastic noise

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1282 Financial Crises in the Context of Behavioral Finance

Authors: Nousheen Tariq Bhutta, Syed Zulfiqar Ali Shah

Abstract:

Financial crises become a key impediment towards the development of countries especially in emerging economies. Based on standard finance, many researchers investigated the financial crises in different countries in order to find the underlying reason regarding occurrence these event; however they were unable to provide it. In this essence behavioral finance may be helpful in providing answers to some queries regarding occurrence and prevention of financial crises. In this paper, we explore the some psychological factors comprises of our inspiration, emotion, cognition and culture along with their reflection companies, financial markets and governments that present some supportive arguments. Moreover, we compared the views of Keynes and Minsky in order to validate the underling justification towards occurrence of financial crises and their prevention in future. This study helps the practitioners and policy makers through providing valuable recommendation in order to protect the economies.

Keywords: financial crises, behavioral finance, financial markets, emerging economies

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1281 Creating a Virtual Perception for Upper Limb Rehabilitation

Authors: Nina Robson, Kenneth John Faller II, Vishalkumar Ahir, Arthur Ricardo Deps Miguel Ferreira, John Buchanan, Amarnath Banerjee

Abstract:

This paper describes the development of a virtual-reality system ARWED, which will be used in physical rehabilitation of patients with reduced upper extremity mobility to increase limb Active Range of Motion (AROM). The ARWED system performs a symmetric reflection and real-time mapping of the patient’s healthy limb on to their most affected limb, tapping into the mirror neuron system and facilitating the initial learning phase. Using the ARWED, future experiments will test the extension of the action-observation priming effect linked to the mirror-neuron system on healthy subjects and then stroke patients.

Keywords: physical rehabilitation, mirror neuron, virtual reality, stroke therapy

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1280 Backward-Facing Step Measurements at Different Reynolds Numbers Using Acoustic Doppler Velocimetry

Authors: Maria Amelia V. C. Araujo, Billy J. Araujo, Brian Greenwood

Abstract:

The flow over a backward-facing step is characterized by the presence of flow separation, recirculation and reattachment, for a simple geometry. This type of fluid behaviour takes place in many practical engineering applications, hence the reason for being investigated. Historically, fluid flows over a backward-facing step have been examined in many experiments using a variety of measuring techniques such as laser Doppler velocimetry (LDV), hot-wire anemometry, particle image velocimetry or hot-film sensors. However, some of these techniques cannot conveniently be used in separated flows or are too complicated and expensive. In this work, the applicability of the acoustic Doppler velocimetry (ADV) technique is investigated to such type of flows, at various Reynolds numbers corresponding to different flow regimes. The use of this measuring technique in separated flows is very difficult to find in literature. Besides, most of the situations where the Reynolds number effect is evaluated in separated flows are in numerical modelling. The ADV technique has the advantage in providing nearly non-invasive measurements, which is important in resolving turbulence. The ADV Nortek Vectrino+ was used to characterize the flow, in a recirculating laboratory flume, at various Reynolds Numbers (Reh = 3738, 5452, 7908 and 17388) based on the step height (h), in order to capture different flow regimes, and the results compared to those obtained using other measuring techniques. To compare results with other researchers, the step height, expansion ratio and the positions upstream and downstream the step were reproduced. The post-processing of the AVD records was performed using a customized numerical code, which implements several filtering techniques. Subsequently, the Vectrino noise level was evaluated by computing the power spectral density for the stream-wise horizontal velocity component. The normalized mean stream-wise velocity profiles, skin-friction coefficients and reattachment lengths were obtained for each Reh. Turbulent kinetic energy, Reynolds shear stresses and normal Reynolds stresses were determined for Reh = 7908. An uncertainty analysis was carried out, for the measured variables, using the moving block bootstrap technique. Low noise levels were obtained after implementing the post-processing techniques, showing their effectiveness. Besides, the errors obtained in the uncertainty analysis were relatively low, in general. For Reh = 7908, the normalized mean stream-wise velocity and turbulence profiles were compared directly with those acquired by other researchers using the LDV technique and a good agreement was found. The ADV technique proved to be able to characterize the flow properly over a backward-facing step, although additional caution should be taken for measurements very close to the bottom. The ADV measurements showed reliable results regarding: a) the stream-wise velocity profiles; b) the turbulent shear stress; c) the reattachment length; d) the identification of the transition from transitional to turbulent flows. Despite being a relatively inexpensive technique, acoustic Doppler velocimetry can be used with confidence in separated flows and thus very useful for numerical model validation. However, it is very important to perform adequate post-processing of the acquired data, to obtain low noise levels, thus decreasing the uncertainty.

Keywords: ADV, experimental data, multiple Reynolds number, post-processing

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1279 An Intelligent Text Independent Speaker Identification Using VQ-GMM Model Based Multiple Classifier System

Authors: Ben Soltane Cheima, Ittansa Yonas Kelbesa

Abstract:

Speaker Identification (SI) is the task of establishing identity of an individual based on his/her voice characteristics. The SI task is typically achieved by two-stage signal processing: training and testing. The training process calculates speaker specific feature parameters from the speech and generates speaker models accordingly. In the testing phase, speech samples from unknown speakers are compared with the models and classified. Even though performance of speaker identification systems has improved due to recent advances in speech processing techniques, there is still need of improvement. In this paper, a Closed-Set Tex-Independent Speaker Identification System (CISI) based on a Multiple Classifier System (MCS) is proposed, using Mel Frequency Cepstrum Coefficient (MFCC) as feature extraction and suitable combination of vector quantization (VQ) and Gaussian Mixture Model (GMM) together with Expectation Maximization algorithm (EM) for speaker modeling. The use of Voice Activity Detector (VAD) with a hybrid approach based on Short Time Energy (STE) and Statistical Modeling of Background Noise in the pre-processing step of the feature extraction yields a better and more robust automatic speaker identification system. Also investigation of Linde-Buzo-Gray (LBG) clustering algorithm for initialization of GMM, for estimating the underlying parameters, in the EM step improved the convergence rate and systems performance. It also uses relative index as confidence measures in case of contradiction in identification process by GMM and VQ as well. Simulation results carried out on voxforge.org speech database using MATLAB highlight the efficacy of the proposed method compared to earlier work.

Keywords: feature extraction, speaker modeling, feature matching, Mel frequency cepstrum coefficient (MFCC), Gaussian mixture model (GMM), vector quantization (VQ), Linde-Buzo-Gray (LBG), expectation maximization (EM), pre-processing, voice activity detection (VAD), short time energy (STE), background noise statistical modeling, closed-set tex-independent speaker identification system (CISI)

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1278 Social Work Students’ Reflection of Their Field Internship: A Study of Dhofar Region in Oman

Authors: Reem Abuiyada

Abstract:

This paper is an attempt to review the pursuance of social-work field practice run by the department of social work, Dhofar University, situated in Dhofar region, Sultanate of Oman. It assesses the students’ engagement in social work in local community training that equips them to practice their allocated tasks and management skills that in turn made them more educated in fieldwork concepts, and especially in helping to overcome the challenges experienced by the Omani community to bring them positive changes. Besides, this paper evaluates the efficacy of fieldwork practice from the students' standpoints in higher education. And, it assumes the fact that this practice helped the students in giving equal significance to academic instruction, preparing for them to face the futuristic professions in an effective way.

Keywords: social work field training, students, Dhofar University, Oman, education

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1277 On the Influence of Sleep Habits for Predicting Preterm Births: A Machine Learning Approach

Authors: C. Fernandez-Plaza, I. Abad, E. Diaz, I. Diaz

Abstract:

Births occurring before the 37th week of gestation are considered preterm births. A threat of preterm is defined as the beginning of regular uterine contractions, dilation and cervical effacement between 23 and 36 gestation weeks. To author's best knowledge, the factors that determine the beginning of the birth are not completely defined yet. In particular, the incidence of sleep habits on preterm births is weekly studied. The aim of this study is to develop a model to predict the factors affecting premature delivery on pregnancy, based on the above potential risk factors, including those derived from sleep habits and light exposure at night (introduced as 12 variables obtained by a telephone survey using two questionnaires previously used by other authors). Thus, three groups of variables were included in the study (maternal, fetal and sleep habits). The study was approved by Research Ethics Committee of the Principado of Asturias (Spain). An observational, retrospective and descriptive study was performed with 481 births between January 1, 2015 and May 10, 2016 in the University Central Hospital of Asturias (Spain). A statistical analysis using SPSS was carried out to compare qualitative and quantitative variables between preterm and term delivery. Chi-square test qualitative variable and t-test for quantitative variables were applied. Statistically significant differences (p < 0.05) between preterm vs. term births were found for primiparity, multi-parity, kind of conception, place of residence or premature rupture of membranes and interruption during nights. In addition to the statistical analysis, machine learning methods to look for a prediction model were tested. In particular, tree based models were applied as the trade-off between performance and interpretability is especially suitable for this study. C5.0, recursive partitioning, random forest and tree bag models were analysed using caret R-package. Cross validation with 10-folds and parameter tuning to optimize the methods were applied. In addition, different noise reduction methods were applied to the initial data using NoiseFiltersR package. The best performance was obtained by C5.0 method with Accuracy 0.91, Sensitivity 0.93, Specificity 0.89 and Precision 0.91. Some well known preterm birth factors were identified: Cervix Dilation, maternal BMI, Premature rupture of membranes or nuchal translucency analysis in the first trimester. The model also identifies other new factors related to sleep habits such as light through window, bedtime on working days, usage of electronic devices before sleeping from Mondays to Fridays or change of sleeping habits reflected in the number of hours, in the depth of sleep or in the lighting of the room. IF dilation < = 2.95 AND usage of electronic devices before sleeping from Mondays to Friday = YES and change of sleeping habits = YES, then preterm is one of the predicting rules obtained by C5.0. In this work a model for predicting preterm births is developed. It is based on machine learning together with noise reduction techniques. The method maximizing the performance is the one selected. This model shows the influence of variables related to sleep habits in preterm prediction.

Keywords: machine learning, noise reduction, preterm birth, sleep habit

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1276 Speaker Identification by Atomic Decomposition of Learned Features Using Computational Auditory Scene Analysis Principals in Noisy Environments

Authors: Thomas Bryan, Veton Kepuska, Ivica Kostanic

Abstract:

Speaker recognition is performed in high Additive White Gaussian Noise (AWGN) environments using principals of Computational Auditory Scene Analysis (CASA). CASA methods often classify sounds from images in the time-frequency (T-F) plane using spectrograms or cochleargrams as the image. In this paper atomic decomposition implemented by matching pursuit performs a transform from time series speech signals to the T-F plane. The atomic decomposition creates a sparsely populated T-F vector in “weight space” where each populated T-F position contains an amplitude weight. The weight space vector along with the atomic dictionary represents a denoised, compressed version of the original signal. The arraignment or of the atomic indices in the T-F vector are used for classification. Unsupervised feature learning implemented by a sparse autoencoder learns a single dictionary of basis features from a collection of envelope samples from all speakers. The approach is demonstrated using pairs of speakers from the TIMIT data set. Pairs of speakers are selected randomly from a single district. Each speak has 10 sentences. Two are used for training and 8 for testing. Atomic index probabilities are created for each training sentence and also for each test sentence. Classification is performed by finding the lowest Euclidean distance between then probabilities from the training sentences and the test sentences. Training is done at a 30dB Signal-to-Noise Ratio (SNR). Testing is performed at SNR’s of 0 dB, 5 dB, 10 dB and 30dB. The algorithm has a baseline classification accuracy of ~93% averaged over 10 pairs of speakers from the TIMIT data set. The baseline accuracy is attributable to short sequences of training and test data as well as the overall simplicity of the classification algorithm. The accuracy is not affected by AWGN and produces ~93% accuracy at 0dB SNR.

Keywords: time-frequency plane, atomic decomposition, envelope sampling, Gabor atoms, matching pursuit, sparse dictionary learning, sparse autoencoder

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1275 A Polyphonic Look at Trends

Authors: Turquesa Topper

Abstract:

The reflection focuses on recording and explaining the considerations, conceptualizations and methodological approach with which from the University, that is to say, from the academic field, the study of Trends is addressed with the intention of training professionals in the area, an area that requires disciplinary boundaries and builds a polyphonic vision. When referring to the objective of our Laboratory the detection of aesthetic trends of consumption, we find ourselves in the requirement to define our object: trends, aesthetic trends of consumption, more specifically. The pages cover a conception of trends from a theoretical framework that incorporates contributions from linguistics, semiotics, sociology, cultural studies and project disciplines, in order to consolidate a polyphonic look. The text investigates in the pre-discursive aspect of the trends, in the circulation of the notion of style and in the dynamics of affirmation - denial as the constitutive dynamics of Fashion linked to any process of innovation. From such inquiry, it is presented to Fashion as a system that operates directly on the construction of socio-individual identities unfolding through the liquefaction of signs in trends.

Keywords: fashion, methodology, narrative, trends

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1274 Performance of High Efficiency Video Codec over Wireless Channels

Authors: Mohd Ayyub Khan, Nadeem Akhtar

Abstract:

Due to recent advances in wireless communication technologies and hand-held devices, there is a huge demand for video-based applications such as video surveillance, video conferencing, remote surgery, Digital Video Broadcast (DVB), IPTV, online learning courses, YouTube, WhatsApp, Instagram, Facebook, Interactive Video Games. However, the raw videos posses very high bandwidth which makes the compression a must before its transmission over the wireless channels. The High Efficiency Video Codec (HEVC) (also called H.265) is latest state-of-the-art video coding standard developed by the Joint effort of ITU-T and ISO/IEC teams. HEVC is targeted for high resolution videos such as 4K or 8K resolutions that can fulfil the recent demands for video services. The compression ratio achieved by the HEVC is twice as compared to its predecessor H.264/AVC for same quality level. The compression efficiency is generally increased by removing more correlation between the frames/pixels using complex techniques such as extensive intra and inter prediction techniques. As more correlation is removed, the chances of interdependency among coded bits increases. Thus, bit errors may have large effect on the reconstructed video. Sometimes even single bit error can lead to catastrophic failure of the reconstructed video. In this paper, we study the performance of HEVC bitstream over additive white Gaussian noise (AWGN) channel. Moreover, HEVC over Quadrature Amplitude Modulation (QAM) combined with forward error correction (FEC) schemes are also explored over the noisy channel. The video will be encoded using HEVC, and the coded bitstream is channel coded to provide some redundancies. The channel coded bitstream is then modulated using QAM and transmitted over AWGN channel. At the receiver, the symbols are demodulated and channel decoded to obtain the video bitstream. The bitstream is then used to reconstruct the video using HEVC decoder. It is observed that as the signal to noise ratio of channel is decreased the quality of the reconstructed video decreases drastically. Using proper FEC codes, the quality of the video can be restored up to certain extent. Thus, the performance analysis of HEVC presented in this paper may assist in designing the optimized code rate of FEC such that the quality of the reconstructed video is maximized over wireless channels.

Keywords: AWGN, forward error correction, HEVC, video coding, QAM

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1273 Me and My Selfie: Identity Building Through Self Representation in Social Media

Authors: Revytia Tanera

Abstract:

This research is a pilot study to examine the rise of selfie trend in dealing with individual self representation and identity building in social media. The symbolic interactionism theory is used as the concept of the desired self image, and Cooley’s looking glass-self concept is used to analyze the mechanical reflection of ourselves; how do people perform their “digital self” in social media. In-depth interviews were conducted in the study with a non-random sample who owns a smartphone with a front camera feature and are active in social media. This research is trying to find out whether the selfie trend brings any influence on identity building on each individual. Through analysis of interview results, it can be concluded that people take selfie photos in order to express themselves and to boost their confidence. This study suggests a follow up and more in depth analysis on identity and self representation from various age groups.

Keywords: self representation, selfie, social media, symbolic interaction, looking glass-self

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1272 Bleeding-Heart Altruists and Calculating Utilitarians: Applying Process Dissociation to Self-sacrificial Dilemmas

Authors: David Simpson, Kyle Nash

Abstract:

There is considerable evidence linking slow, deliberative reasoning (system 2) with utilitarian judgments in dilemmas involving the sacrificing of another person for the greater good (other-sacrificial dilemmas). Joshua Greene has argued, based on this kind of evidence, that system 2 drives utilitarian judgments. However, the evidence on whether system 2 is associated with utilitarian judgments in self-sacrificial dilemmas is more mixed. We employed process dissociation to measure a self-sacrificial utilitarian (SU) parameter and an other-sacrificial (OU) utilitarian parameter. It was initially predicted that contra Greene, the cognitive reflection test (CRT) would only be positively correlated with the OU parameter and not the SU parameter. However, Greene’s hypothesis was corroborated: the CRT positively correlated with both the OU parameter and the SU parameter. By contrast, the CRT did not correlate with the other two moral parameters we extracted (altruism and deontology).

Keywords: dual-process model, utilitarianism, altruism, reason, emotion, process dissociation

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1271 Sigma-Delta ADCs Converter a Study Case

Authors: Thiago Brito Bezerra, Mauro Lopes de Freitas, Waldir Sabino da Silva Júnior

Abstract:

The Sigma-Delta A/D converters have been proposed as a practical application for A/D conversion at high rates because of its simplicity and robustness to imperfections in the circuit, also because the traditional converters are more difficult to implement in VLSI technology. These difficulties with conventional conversion methods need precise analog components in their filters and conversion circuits, and are more vulnerable to noise and interference. This paper aims to analyze the architecture, function and application of Analog-Digital converters (A/D) Sigma-Delta to overcome these difficulties, showing some simulations using the Simulink software and Multisim.

Keywords: analysis, oversampling modulator, A/D converters, sigma-delta

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