Search results for: interactive segmentation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1251

Search results for: interactive segmentation

1101 Improvement of Brain Tumors Detection Using Markers and Boundaries Transform

Authors: Yousif Mohamed Y. Abdallah, Mommen A. Alkhir, Amel S. Algaddal

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This was experimental study conducted to study segmentation of brain in MRI images using edge detection and morphology filters. For brain MRI images each film scanned using digitizer scanner then treated by using image processing program (MatLab), where the segmentation was studied. The scanned image was saved in a TIFF file format to preserve the quality of the image. Brain tissue can be easily detected in MRI image if the object has sufficient contrast from the background. We use edge detection and basic morphology tools to detect a brain. The segmentation of MRI images steps using detection and morphology filters were image reading, detection entire brain, dilation of the image, filling interior gaps inside the image, removal connected objects on borders and smoothen the object (brain). The results of this study were that it showed an alternate method for displaying the segmented object would be to place an outline around the segmented brain. Those filters approaches can help in removal of unwanted background information and increase diagnostic information of Brain MRI.

Keywords: improvement, brain, matlab, markers, boundaries

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1100 The Effect of Advertising on Brand Choices of Z Generation Children and Their Social Media Consumption Habits

Authors: Hüseyin Altubaş, Hasret Aktaş, A. Mücahid Zengin

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Children determine the direction of the power of consumption. They affect the decisions of their parents but they also reached to a significant purchasing power themselves. Children, who are turning interactive behavior to normal behavior are becoming the decision makers in a company’s survival. Companies that analyze this effective target audience can communicate successfully with children. Children, who are interactive individuals, are closer to advertising. They are almost talking better with advertising. They are not afraid to express their likings, as well as their dislikes. Children have an interactive lifestyle and they were exposed to the vast changes in technology after year 2000. They do not know a life without internet, they spend mobile life in internet. This Z generation is the new determinants of brands. Z generation finds it appropriate to be brand ambassadors and they completely changed traditional media and traditional consumer behavior. These children live social reality with virtual reality and they feed brands differently. Brands that interact with Z generation are affected by this feeding positively, while brands that keep interaction in traditional levels are affected negatively. In this research we examine the communication, advertising and brand behaviors of Z generation. We especially analyze this generation’s interaction with social media brands and their interactive attitudes.

Keywords: social media, Z generation, children, advertising, brand choice

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1099 The Potential Benefits of Multimedia Information Representation in Enhancing Students’ Critical Thinking and History Reasoning

Authors: Ang Ling Weay, Mona Masood

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This paper discusses the potential benefits of an interactive multimedia information representation in enhancing students’ critical thinking aligned with history reasoning in learning history between Secondary School students in Malaysia. Two modes of multimedia information representation implemented which are chronological and thematic information representation. A qualitative study of an unstructured interview was conducted among two history teachers, one history education lecturer, two i-think expert and program trainers and five form 4 secondary school students. The interview was to elicit their opinions on the implementation of thinking maps and interactive multimedia information representation in history learning. The key elements of interactive multimedia (e.g. multiple media, user control, interactivity, and use of timelines and concept maps) were then considered to improve the learning process. Findings of the preliminary investigation reveal that the interactive multimedia information representations have the potential benefits to be implemented as instructional resource in enhancing students’ higher order thinking skills (HOTs). This paper concludes by giving suggestions for future work.

Keywords: multimedia information representation, critical thinking, history reasoning, chronological and thematic information representation

Procedia PDF Downloads 321
1098 A Fuzzy Approach to Liver Tumor Segmentation with Zernike Moments

Authors: Abder-Rahman Ali, Antoine Vacavant, Manuel Grand-Brochier, Adélaïde Albouy-Kissi, Jean-Yves Boire

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In this paper, we present a new segmentation approach for liver lesions in regions of interest within MRI (Magnetic Resonance Imaging). This approach, based on a two-cluster Fuzzy C-Means methodology, considers the parameter variable compactness to handle uncertainty. Fine boundaries are detected by a local recursive merging of ambiguous pixels with a sequential forward floating selection with Zernike moments. The method has been tested on both synthetic and real images. When applied on synthetic images, the proposed approach provides good performance, segmentations obtained are accurate, their shape is consistent with the ground truth, and the extracted information is reliable. The results obtained on MR images confirm such observations. Our approach allows, even for difficult cases of MR images, to extract a segmentation with good performance in terms of accuracy and shape, which implies that the geometry of the tumor is preserved for further clinical activities (such as automatic extraction of pharmaco-kinetics properties, lesion characterization, etc).

Keywords: defuzzification, floating search, fuzzy clustering, Zernike moments

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1097 Computer Aided Diagnostic System for Detection and Classification of a Brain Tumor through MRI Using Level Set Based Segmentation Technique and ANN Classifier

Authors: Atanu K Samanta, Asim Ali Khan

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Due to the acquisition of huge amounts of brain tumor magnetic resonance images (MRI) in clinics, it is very difficult for radiologists to manually interpret and segment these images within a reasonable span of time. Computer-aided diagnosis (CAD) systems can enhance the diagnostic capabilities of radiologists and reduce the time required for accurate diagnosis. An intelligent computer-aided technique for automatic detection of a brain tumor through MRI is presented in this paper. The technique uses the following computational methods; the Level Set for segmentation of a brain tumor from other brain parts, extraction of features from this segmented tumor portion using gray level co-occurrence Matrix (GLCM), and the Artificial Neural Network (ANN) to classify brain tumor images according to their respective types. The entire work is carried out on 50 images having five types of brain tumor. The overall classification accuracy using this method is found to be 98% which is significantly good.

Keywords: brain tumor, computer-aided diagnostic (CAD) system, gray-level co-occurrence matrix (GLCM), tumor segmentation, level set method

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1096 Hindi Speech Synthesis by Concatenation of Recognized Hand Written Devnagri Script Using Support Vector Machines Classifier

Authors: Saurabh Farkya, Govinda Surampudi

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Optical Character Recognition is one of the current major research areas. This paper is focussed on recognition of Devanagari script and its sound generation. This Paper consists of two parts. First, Optical Character Recognition of Devnagari handwritten Script. Second, speech synthesis of the recognized text. This paper shows an implementation of support vector machines for the purpose of Devnagari Script recognition. The Support Vector Machines was trained with Multi Domain features; Transform Domain and Spatial Domain or Structural Domain feature. Transform Domain includes the wavelet feature of the character. Structural Domain consists of Distance Profile feature and Gradient feature. The Segmentation of the text document has been done in 3 levels-Line Segmentation, Word Segmentation, and Character Segmentation. The pre-processing of the characters has been done with the help of various Morphological operations-Otsu's Algorithm, Erosion, Dilation, Filtration and Thinning techniques. The Algorithm was tested on the self-prepared database, a collection of various handwriting. Further, Unicode was used to convert recognized Devnagari text into understandable computer document. The document so obtained is an array of codes which was used to generate digitized text and to synthesize Hindi speech. Phonemes from the self-prepared database were used to generate the speech of the scanned document using concatenation technique.

Keywords: Character Recognition (OCR), Text to Speech (TTS), Support Vector Machines (SVM), Library of Support Vector Machines (LIBSVM)

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1095 Modular, Responsive, and Interactive Green Walls - A Case Study

Authors: Flaviu Mihai Frigura-Lliasa, Andreea Anamaria Anghel, Attila Simo

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Due to the beauty, usefulness, science, constantly changing, constantly evolving features, and most of the time, mystery it involves, nature-based art is seen as a both modern and timeless direction that has been extensively used in design. The goal of the team's activities was to experiment with ways of fusing the two most common contemporary ways of referring to green installations, that is, either in a pure artistic or in an ecological manner, and creating a living, dynamic, interactive installation capable of both receiving and interpreting external factors, such as natural and human stimuli, that would not only determine some of the mechanism's presets. By consequent, a complex experiment made up of various research and project stages was elaborated in order to transform an idea into an actual interactive green installation within months thanks to the interaction, teamwork, and design processes undertaken throughout the academic years by both university lecturers and some of our students. The outcomes would lead to the development of a dynamic artwork called "Modgrew" as well as the introduction of experiment-based learning at the Timisoara Faculty of Architecture and Urban Planning, as well as at the Faculty of Electrical and Power Engineering, for the green wall automation issues.

Keywords: green design, living walls, modular structure, interactive proof of concept

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1094 Enhancing the Pricing Expertise of an Online Distribution Channel

Authors: Luis N. Pereira, Marco P. Carrasco

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Dynamic pricing is a revenue management strategy in which hotel suppliers define, over time, flexible and different prices for their services for different potential customers, considering the profile of e-consumers and the demand and market supply. This means that the fundamentals of dynamic pricing are based on economic theory (price elasticity of demand) and market segmentation. This study aims to define a dynamic pricing strategy and a contextualized offer to the e-consumers profile in order to improve the number of reservations of an online distribution channel. Segmentation methods (hierarchical and non-hierarchical) were used to identify and validate an optimal number of market segments. A profile of the market segments was studied, considering the characteristics of the e-consumers and the probability of reservation a room. In addition, the price elasticity of demand was estimated for each segment using econometric models. Finally, predictive models were used to define rules for classifying new e-consumers into pre-defined segments. The empirical study illustrates how it is possible to improve the intelligence of an online distribution channel system through an optimal dynamic pricing strategy and a contextualized offer to the profile of each new e-consumer. A database of 11 million e-consumers of an online distribution channel was used in this study. The results suggest that an appropriate policy of market segmentation in using of online reservation systems is benefit for the service suppliers because it brings high probability of reservation and generates more profit than fixed pricing.

Keywords: dynamic pricing, e-consumers segmentation, online reservation systems, predictive analytics

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1093 Document Analysis for Modelling iTV Advertising towards Impulse Purchase

Authors: Azizah Che Omar

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The study provides a systematic literature review which analyzed the literature for the purpose of looking for concepts, theories, approaches and guidelines in order to propose a conceptual design model of interactive television advertising toward impulse purchase (iTVAdIP). An extensive review of literature was purposely carried out to understand the concepts of interactive television (iTV). Therefore, some elements; iTV guidelines, advertising theories, persuasive approaches, and the impulse purchase elements were analyzed to reach the scope of this work. The extensive review was also a necessity to achieve the objective of this study, which was to determine the concept of iTVAdIP design model. Through systematic review analysis, this study discovered that all the previous models did not emphasize the conceptual design model of interactive television advertising. As a result, the finding showed that the concept of the proposed model should contain the iTV guidelines, advertising theory, persuasive approach and impulse purchase elements. In addition, a summary diagram for the development of the proposed model is depicted to provide clearer understanding towards the concepts of conceptual design model of iTVAdIP.

Keywords: impulse purchase, interactive television advertising, human computer interaction, advertising theories

Procedia PDF Downloads 344
1092 A Review on Artificial Neural Networks in Image Processing

Authors: B. Afsharipoor, E. Nazemi

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Artificial neural networks (ANNs) are powerful tool for prediction which can be trained based on a set of examples and thus, it would be useful for nonlinear image processing. The present paper reviews several paper regarding applications of ANN in image processing to shed the light on advantage and disadvantage of ANNs in this field. Different steps in the image processing chain including pre-processing, enhancement, segmentation, object recognition, image understanding and optimization by using ANN are summarized. Furthermore, results on using multi artificial neural networks are presented.

Keywords: neural networks, image processing, segmentation, object recognition, image understanding, optimization, MANN

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1091 Counting People Utilizing Space-Time Imagery

Authors: Ahmed Elmarhomy, K. Terada

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An automated method for counting passerby has been proposed using virtual-vertical measurement lines. Space-time image is representing the human regions which are treated using the segmentation process. Different color space has been used to perform the template matching. A proper template matching has been achieved to determine direction and speed of passing people. Distinguish one or two passersby has been investigated using a correlation between passerby speed and the human-pixel area. Finally, the effectiveness of the presented method has been experimentally verified.

Keywords: counting people, measurement line, space-time image, segmentation, template matching

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1090 Designing Interactive Applications for Social Anxiety Scenario Stories for Children with Autism

Authors: Wen Huei Chou, Yi-Ting Chen

Abstract:

Individuals with Autism Spectrum Disorder (ASD) often struggle with social interactions and communication. It is challenging for them to understand social cues such as facial expressions, body language, and tone of voice in social settings, leading to social conflicts and misunderstandings. Over time, feelings of frustration and anxiety can make them reluctant to engage in social situations and worsen their communication barriers. This study focused on children with autism who also experience social anxiety. Through focus group interviews with parents of children with autism and occupational therapists, it explores the reasons and scenarios behind the development of social anxiety in these children. Social scenario stories and interactive applications tailored for children with autism were designed and developed. In addition, working with the educational robots, coping strategies for various emotional situations were elaborated on, and children were helped to understand their emotions.

Keywords: autism spectrum disorder, social anxiety, robot, social scenario story, interactive applications

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1089 Using Electronic Books to Enhance the Museum Visitors' Experience

Authors: Elvin Karaaslan Klose

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Museums are important sites of informal, often semi-structured and self-paced learning. Challenged by digital alternatives and increased expectations from their visitors, museums have to adapt to the digital age by enriching their collection and educational content with additional options for interactivity. One such option lies in the concept of the electronic book, which can be used either on dedicated devices or downloaded by visitors before entering the exhibition area. These electronic books serve as an alternative or supplement to the classic audio guide and provide visitors with information about artifacts as well as background stories and factoids about the subjects of the exhibition. Bringing such interactive elements into the museum experience has been shown to increase information retention and enjoyment among young aged visitors and adults. This article aims to bring together both theoretical frameworks and practical examples of how interactive media in the form of electronic books can be used to enhance the experience of the museum visitor.

Keywords: electronic books, interactive media, arts education, museum education

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1088 Segmentation Using Multi-Thresholded Sobel Images: Application to the Separation of Stuck Pollen Grains

Authors: Endrick Barnacin, Jean-Luc Henry, Jimmy Nagau, Jack Molinie

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Being able to identify biological particles such as spores, viruses, or pollens is important for health care professionals, as it allows for appropriate therapeutic management of patients. Optical microscopy is a technology widely used for the analysis of these types of microorganisms, because, compared to other types of microscopy, it is not expensive. The analysis of an optical microscope slide is a tedious and time-consuming task when done manually. However, using machine learning and computer vision, this process can be automated. The first step of an automated microscope slide image analysis process is segmentation. During this step, the biological particles are localized and extracted. Very often, the use of an automatic thresholding method is sufficient to locate and extract the particles. However, in some cases, the particles are not extracted individually because they are stuck to other biological elements. In this paper, we propose a stuck particles separation method based on the use of the Sobel operator and thresholding. We illustrate it by applying it to the separation of 813 images of adjacent pollen grains. The method correctly separated 95.4% of these images.

Keywords: image segmentation, stuck particles separation, Sobel operator, thresholding

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1087 The Effect of Head Posture on the Kinematics of the Spine During Lifting and Lowering Tasks

Authors: Mehdi Nematimoez

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Head posture is paramount to retaining gaze and balance in many activities; its control is thus important in many activities. However, little information is available about the effects of head movement restriction on other spine segment kinematics and movement patterns during lifting and lowering tasks. The aim of this study was to examine the effects of head movement restriction on relative angles and their derivatives using the stepwise segmentation approach during lifting and lowering tasks. Ten healthy men lifted and lowered a box using two styles (stoop and squat), with two loads (i.e., 10 and 20% of body weight); they performed these tasks with two instructed head postures (1. Flexing the neck to keep contact between chin and chest over the task cycle; 2. No instruction, free head posture). The spine was divided into five segments, tracked by six cluster markers (C7, T3, T6, T9, T12, and L5). Relative angles between spine segments and their derivatives (first and second) were analyzed by a stepwise segmentation approach to consider the effect of each segment on the whole spine. Accordingly, head posture significantly affected the derivatives of the relative angles and manifested latency in spine segments movement, i.e., cephalad-to-caudad or caudad-to-cephalad patterns. The relative angles for C7-T3 and T3-T6 increased over the cycle of all lifting and lowering tasks; nevertheless, in lower segments increased significantly when the spine moved into upright standing. However, these effects were clearer during lifting than lowering. Conclusively, the neck flexion can unevenly increase the flexion angles of spine segments from cervical to lumbar over lifting and lowering tasks; furthermore, stepwise segmentation reveals potential for assessing the segmental contribution in spine ROM and movement patterns.

Keywords: head movement restriction, spine kinematics, lifting, lowering, stepwise segmentation

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1086 Active Contours for Image Segmentation Based on Complex Domain Approach

Authors: Sajid Hussain

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The complex domain approach for image segmentation based on active contour has been designed, which deforms step by step to partition an image into numerous expedient regions. A novel region-based trigonometric complex pressure force function is proposed, which propagates around the region of interest using image forces. The signed trigonometric force function controls the propagation of the active contour and the active contour stops on the exact edges of the object accurately. The proposed model makes the level set function binary and uses Gaussian smoothing kernel to adjust and escape the re-initialization procedure. The working principle of the proposed model is as follows: The real image data is transformed into complex data by iota (i) times of image data and the average iota (i) times of horizontal and vertical components of the gradient of image data is inserted in the proposed model to catch complex gradient of the image data. A simple finite difference mathematical technique has been used to implement the proposed model. The efficiency and robustness of the proposed model have been verified and compared with other state-of-the-art models.

Keywords: image segmentation, active contour, level set, Mumford and Shah model

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1085 A Case Study on English Camp in UNISSA: An Approach towards Interactive Learning Outside the Classroom

Authors: Liza Mariah Hj. Azahari

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This paper will look at a case study on English Camp which was an activity coordinated at the Sultan Sharif Ali Islamic University in 2011. English Camp is a fun and motivation filled activity which brings students and teachers together outside of the classroom setting into a more diverse environment. It also enables teacher and students to gain proximate time together for a mutual purpose which is to explore the language in a more dynamic and relaxed way. First of all, the study will look into the background of English Camp, and how it was introduced and implemented from different contexts. Thereafter, it will explain the objectives of the English Camp coordinated at our university, UNISSA, and what types of activities were conducted. It will then evaluate the effectiveness of the camp as to what extent it managed to meet its motto, which was to foster dynamic interactive learning of English Language. To conclude, the paper presents a potential for further research on the topic as well as a guideline for educators who wish to coordinate the activity. Proposal for collaboration in this activity is further highlighted and encouraged within the paper for future implementation and endeavor.

Keywords: English camp, UNISSA, interactive learning, outside

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1084 An Automated System for the Detection of Citrus Greening Disease Based on Visual Descriptors

Authors: Sidra Naeem, Ayesha Naeem, Sahar Rahim, Nadia Nawaz Qadri

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Citrus greening is a bacterial disease that causes considerable damage to citrus fruits worldwide. Efficient method for this disease detection must be carried out to minimize the production loss. This paper presents a pattern recognition system that comprises three stages for the detection of citrus greening from Orange leaves: segmentation, feature extraction and classification. Image segmentation is accomplished by adaptive thresholding. The feature extraction stage comprises of three visual descriptors i.e. shape, color and texture. From shape feature we have used asymmetry index, from color feature we have used histogram of Cb component from YCbCr domain and from texture feature we have used local binary pattern. Classification was done using support vector machines and k nearest neighbors. The best performances of the system is Accuracy = 88.02% and AUROC = 90.1% was achieved by automatic segmented images. Our experiments validate that: (1). Segmentation is an imperative preprocessing step for computer assisted diagnosis of citrus greening, and (2). The combination of shape, color and texture features form a complementary set towards the identification of citrus greening disease.

Keywords: citrus greening, pattern recognition, feature extraction, classification

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1083 Object-Based Image Analysis for Gully-Affected Area Detection in the Hilly Loess Plateau Region of China Using Unmanned Aerial Vehicle

Authors: Hu Ding, Kai Liu, Guoan Tang

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The Chinese Loess Plateau suffers from serious gully erosion induced by natural and human causes. Gully features detection including gully-affected area and its two dimension parameters (length, width, area et al.), is a significant task not only for researchers but also for policy-makers. This study aims at gully-affected area detection in three catchments of Chinese Loess Plateau, which were selected in Changwu, Ansai, and Suide by using unmanned aerial vehicle (UAV). The methodology includes a sequence of UAV data generation, image segmentation, feature calculation and selection, and random forest classification. Two experiments were conducted to investigate the influences of segmentation strategy and feature selection. Results showed that vertical and horizontal root-mean-square errors were below 0.5 and 0.2 m, respectively, which were ideal for the Loess Plateau region. The segmentation strategy adopted in this paper, which considers the topographic information, and optimal parameter combination can improve the segmentation results. Besides, the overall extraction accuracy in Changwu, Ansai, and Suide achieved was 84.62%, 86.46%, and 93.06%, respectively, which indicated that the proposed method for detecting gully-affected area is more objective and effective than traditional methods. This study demonstrated that UAV can bridge the gap between field measurement and satellite-based remote sensing, obtaining a balance in resolution and efficiency for catchment-scale gully erosion research.

Keywords: unmanned aerial vehicle (UAV), object-analysis image analysis, gully erosion, gully-affected area, Loess Plateau, random forest

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1082 Effectiveness of Interactive Integrated Tutorial in Teaching Medical Subjects to Dental Students: A Pilot Study

Authors: Mohammad Saleem, Neeta Kumar, Anita Sharma, Sazina Muzammil

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It is observed that some of the dental students in our setting take less interest in medical subjects. Various teaching methods are focus of research interest currently and being tried to generate interest among students. An approach of interactive integrated tutorial was used to assess its feasibility in teaching medical subjects to dental undergraduates. The aim was to generate interest and promote active self-learning among students. The objectives were to (1) introduce the integrated interactive learning method through two departments, (2) get feedback from the students and faculty on feasibility and effectiveness of this method. Second-year students in Bachelor of Dental Surgery course were divided into two groups. Each group was asked to study physiology and pathology of a common and important condition (anemia and hypertension) in a week’s time. During the tutorial, students asked questions on physiology and pathology of that condition from each other in the presence of teachers of both physiology and pathology departments. The teachers acted only as facilitators. After the session, the feedback from students and faculty on this alternative learning method was obtained. Results: Majority of the students felt that this method of learning is enjoyable, helped to develop reasoning skills and ability to correlate and integrate the knowledge from two related fields. Majority of the students felt that this kind of learning led to better understanding of the topic and motivated them towards deep learning. Teachers observed that the study promoted interdepartmental cross-discipline collaboration and better students’ linkages. Conclusion: Interactive integrated tutorial is effective in motivating dental students for better and deep learning of medical subjects.

Keywords: active learning, education, integrated, interactive, self-learning, tutorials

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1081 An Accurate Brain Tumor Segmentation for High Graded Glioma Using Deep Learning

Authors: Sajeeha Ansar, Asad Ali Safi, Sheikh Ziauddin, Ahmad R. Shahid, Faraz Ahsan

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Gliomas are most challenging and aggressive type of tumors which appear in different sizes, locations, and scattered boundaries. CNN is most efficient deep learning approach with outstanding capability of solving image analysis problems. A fully automatic deep learning based 2D-CNN model for brain tumor segmentation is presented in this paper. We used small convolution filters (3 x 3) to make architecture deeper. We increased convolutional layers for efficient learning of complex features from large dataset. We achieved better results by pushing convolutional layers up to 16 layers for HGG model. We achieved reliable and accurate results through fine-tuning among dataset and hyper-parameters. Pre-processing of this model includes generation of brain pipeline, intensity normalization, bias correction and data augmentation. We used the BRATS-2015, and Dice Similarity Coefficient (DSC) is used as performance measure for the evaluation of the proposed method. Our method achieved DSC score of 0.81 for complete, 0.79 for core, 0.80 for enhanced tumor regions. However, these results are comparable with methods already implemented 2D CNN architecture.

Keywords: brain tumor segmentation, convolutional neural networks, deep learning, HGG

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1080 The Bicoid Gradient in the Drosophila Embryo: 3D Modelling with Realistic Egg Geometries

Authors: Alexander V. Spirov, David M. Holloway, Ekaterina M. Myasnikova

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Segmentation of the early Drosophila embryo results from the dynamic establishment of spatial gene expression patterns. Patterning occurs on an embryo geometry which is a 'deformed' prolate ellipsoid, with anteroposterior and dorsal-ventral major and minor axes, respectively. Patterning is largely independent along each axis, but some interaction can be seen in the 'bending' of the segmental expression stripes. This interaction is not well understood. In this report, we investigate how 3D geometrical features of the early embryo affect the segmental expression patterning. Specifically, we study the effect of geometry on formation of the Bicoid primary morphogenetic gradient. Our computational results demonstrate that embryos with a much longer ventral than dorsal surface ('bellied') can produce curved Bicoid concentration contours which could activate curved stripes in the downstream pair-rule segmentation genes. In addition, we show that having an extended source for Bicoid in the anterior of the embryo may be necessary for producing the observed exponential form of the Bicoid gradient along the anteroposterior axis.

Keywords: Drosophila embryo, bicoid morphogenetic gradient, exponential expression profile, expression surface form, segmentation genes, 3D modelling

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1079 An Examination of Teachers’ Interactive Whiteboards Use within the Scope of Technological, Pedagogical, and Content Knowledge (TPACK)

Authors: Ismail Celik, Pavlo Antonenko, Seyit Ahmet Kiray, Ismail Sahin

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The aim of the present study was to thoroughly investigate the teachers’ interactive whiteboards (IWBs) use within the scope of the technological pedagogical and content knowledge (TPACK) framework based on the school practice observations of in-service teachers collected by pre-service teachers. In this study, teachers’ use of IWBs in their classes was investigated by using phenomenography, which is a qualitative research method design. The participants of this study consisted of teachers working in a province of Turkey. Within the scope of the study, 337 teachers from 61 different schools were observed by preservice teachers during School Experience classes. The teachers use the IWBs to review the points not understood by the students, to share knowledge, to enhance motivation, to maintain student participation/practice and for in-process, formative assessment. The problems teachers face while using the IWBs can be IWB-based (touchscreen problems/frozen image/lack of software), administration-based, student-based and teacher-based (lack of knowledge of use, need for technical support). It is considered that technological knowledge (TK) is important in solving the problems experienced with IWBs, and technological pedagogy knowledge (TPK) and technological content knowledge (TCK) are important in using the IWBs in an interactive and pedagogically meaningful way that uses IWBs affordances and is relevant to the instructional objectives.

Keywords: TPACK, technology integration, interactive whiteboard, technology in education

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1078 Interactive Teaching and Learning Resources for Bilingual Education

Authors: Sarolta Lipóczi, Ildikó Szabó

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The use of ICT in European Schools has increased over the last decade but there is still room for improvement. Also interactive technology is often used below its technical and pedagogical potentials. The pedagogical potential of interactive technology in classrooms has not yet reached classrooms in different countries and in a substantial way. To develop these materials cooperation between educational researchers and teachers from different backgrounds is necessary. INTACT project brings together experts from science education, mathematics education, social science education and foreign language education – with a focus on bilingual education – and teachers in secondary and primary schools to develop a variety of pedagogically qualitative interactive teaching and learning resources. Because of the backgrounds of the consortium members INTACT project focuses on the areas of science, mathematics and social sciences. To combine these two features (science/math and foreign language) the project focuses on bilingual education. A big issue supported by ‘interactiveness’ is social and collaborative learning. The easy way to communicate and collaborate offered by web 2.0 tools, mobile devices connected to the learning material allows students to work and learn together. There will be a wide range of possibilities for school co-operations at regional, national and also international level that allows students to communicate and cooperate with other students beyond the classroom boarders while using these interactive teaching materials. Opening up the learning scenario enhance the social, civic and cultural competences of the students by advocating their social skills and improving their cultural appreciation for other nations in Europe. To enable teachers to use the materials in indented ways descriptions of successful learning scenarios (i.e. using design patterns) will be provided as well. These materials and description will be made available to teachers by teacher trainings, teacher journals, booklets and online materials. The resources can also be used in different settings including the use of a projector and a touchpad or other technical interactive devices for the input i.e. mobile phones. Kecskemét College as a partner of INTACT project has developed two teaching and learning resources in the area of foreign language teaching. This article introduces these resources as well.

Keywords: bilingual educational settings, international cooperation, interactive teaching and learning resources, work across culture

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1077 Potassium-Phosphorus-Nitrogen Detection and Spectral Segmentation Analysis Using Polarized Hyperspectral Imagery and Machine Learning

Authors: Nicholas V. Scott, Jack McCarthy

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Military, law enforcement, and counter terrorism organizations are often tasked with target detection and image characterization of scenes containing explosive materials in various types of environments where light scattering intensity is high. Mitigation of this photonic noise using classical digital filtration and signal processing can be difficult. This is partially due to the lack of robust image processing methods for photonic noise removal, which strongly influence high resolution target detection and machine learning-based pattern recognition. Such analysis is crucial to the delivery of reliable intelligence. Polarization filters are a possible method for ambient glare reduction by allowing only certain modes of the electromagnetic field to be captured, providing strong scene contrast. An experiment was carried out utilizing a polarization lens attached to a hyperspectral imagery camera for the purpose of exploring the degree to which an imaged polarized scene of potassium, phosphorus, and nitrogen mixture allows for improved target detection and image segmentation. Preliminary imagery results based on the application of machine learning algorithms, including competitive leaky learning and distance metric analysis, to polarized hyperspectral imagery, suggest that polarization filters provide a slight advantage in image segmentation. The results of this work have implications for understanding the presence of explosive material in dry, desert areas where reflective glare is a significant impediment to scene characterization.

Keywords: explosive material, hyperspectral imagery, image segmentation, machine learning, polarization

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1076 Heart Murmurs and Heart Sounds Extraction Using an Algorithm Process Separation

Authors: Fatima Mokeddem

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The phonocardiogram signal (PCG) is a physiological signal that reflects heart mechanical activity, is a promising tool for curious researchers in this field because it is full of indications and useful information for medical diagnosis. PCG segmentation is a basic step to benefit from this signal. Therefore, this paper presents an algorithm that serves the separation of heart sounds and heart murmurs in case they exist in order to use them in several applications and heart sounds analysis. The separation process presents here is founded on three essential steps filtering, envelope detection, and heart sounds segmentation. The algorithm separates the PCG signal into S1 and S2 and extract cardiac murmurs.

Keywords: phonocardiogram signal, filtering, Envelope, Detection, murmurs, heart sounds

Procedia PDF Downloads 114
1075 Receptiveness of Market Segmentation Towards Online Shopping Attitude: A Quality Management Strategy for Online Passenger Car Market

Authors: Noor Hasmini Abdghani, Nik Kamariah Nikmat, Nor Hayati Ahmad

Abstract:

Rapid growth of the internet technology led to changes in the consumer lifestyles. This involved customer buying behaviour-based internet that create new kind of buying strategy. Hence, it has summoned many of world firms including Malaysia to generate new quality strategy in preparation to face new customer buying lifestyles. Particularly, this study focused on identifying online customer segment of automobile passenger car customers. Secondly, the objective is to understand online customer’s receptiveness towards internet technologies. This study distributed 700 questionnaires whereby 582 were returned representing 83% response rate. The data were analysed using factor and regression analyses. The result from the factor analysis precipitates four online passenger car segmentations in Malaysia, which are: Segment (1)- Automobile Online shopping Preferences, Segment (2)- Automobile Online Brand Comparison, Segment (3)- Automobile Online Information Seeking and Segment (4)- Automobile Offline Shopping Preferences. In understanding the online customer’s receptiveness towards internet, the regression result shows that there is significant relationship between each of four segments of online passenger car customer with attitude towards automobile online shopping. This implies that, for online customers to have receptiveness toward internet technologies, he or she must have preferences toward online shopping or at least prefer to browse any related information online even if the actual purchase is made at the traditional store. With this proposed segmentation strategy, the firms especially the automobile firms will be able to understand their online customer behavior. At least, the proposed segmentation strategy will help the firms to strategize quality management approach for their online customers’ buying decision making.

Keywords: Automobile, Market Segmentation, Online Shopping Attitude, Quality Management Strategy

Procedia PDF Downloads 517
1074 Thermal Image Segmentation Method for Stratification of Freezing Temperatures

Authors: Azam Fazelpour, Saeed R. Dehghani, Vlastimil Masek, Yuri S. Muzychka

Abstract:

The study uses an image analysis technique employing thermal imaging to measure the percentage of areas with various temperatures on a freezing surface. An image segmentation method using threshold values is applied to a sequence of image recording the freezing process. The phenomenon is transient and temperatures vary fast to reach the freezing point and complete the freezing process. Freezing salt water is subjected to the salt rejection that makes the freezing point dynamic and dependent on the salinity at the phase interface. For a specific area of freezing, nucleation starts from one side and end to another side, which causes a dynamic and transient temperature in that area. Thermal cameras are able to reveal a difference in temperature due to their sensitivity to infrared radiance. Using Experimental setup, a video is recorded by a thermal camera to monitor radiance and temperatures during the freezing process. Image processing techniques are applied to all frames to detect and classify temperatures on the surface. Image processing segmentation method is used to find contours with same temperatures on the icing surface. Each segment is obtained using the temperature range appeared in the image and correspond pixel values in the image. Using the contours extracted from image and camera parameters, stratified areas with different temperatures are calculated. To observe temperature contours on the icing surface using the thermal camera, the salt water sample is dropped on a cold surface with the temperature of -20°C. A thermal video is recorded for 2 minutes to observe the temperature field. Examining the results obtained by the method and the experimental observations verifies the accuracy and applicability of the method.

Keywords: ice contour boundary, image processing, image segmentation, salt ice, thermal image

Procedia PDF Downloads 292
1073 Colour Segmentation of Satellite Imagery to Estimate Total Suspended Solid at Rawa Pening Lake, Central Java, Indonesia

Authors: Yulia Chalri, E. T. P. Lussiana, Sarifuddin Madenda, Bambang Trisakti, Yuhilza Hanum

Abstract:

Water is a natural resource needed by humans and other living creatures. The territorial water of Indonesia is 81% of the country area, consisting of inland waters and the sea. The research object is inland waters in the form of lakes and reservoirs, since 90% of inland waters are in them, therefore the water quality should be monitored. One of water quality parameters is Total Suspended Solid (TSS). Most of the earlier research did direct measurement by taking the water sample to get TSS values. This method takes a long time and needs special tools, resulting in significant cost. Remote sensing technology has solved a lot of problems, such as the mapping of watershed and sedimentation, monitoring disaster area, mapping coastline change, and weather analysis. The aim of this research is to estimate TSS of Rawa Pening lake in Central Java by using the Lansat 8 image. The result shows that the proposed method successfully estimates the Rawa Pening’s TSS. In situ TSS shows normal water quality range, and so does estimation result of segmentation method.

Keywords: total suspended solid (TSS), remote sensing, image segmentation, RGB value

Procedia PDF Downloads 383
1072 Designing an Online Case-Based Library for Technology Integration in Teacher Education

Authors: Mustafa Tevfik Hebebci, Sirin Kucuk, Ismail Celik, A. Oguz Akturk, Ismail Sahin, Fetah Eren

Abstract:

The purpose of this paper is to introduce an interactive online case-study library website developed in a national project. The design goal of the website is to provide interactive, enhanced, case-based and online educational resource for educators through the purpose and within the scope of a national project. The ADDIE instructional design model was used in the development of the website for interactive case-based library. This library is developed on a web-based platform, which is important in terms of manageability, accessibility, and updateability of data. Users are able to sort the displayed case-studies by their titles, dates, ratings, view counts, etc. The usability test is used and the expert opinion is taken for the evaluation of the website. This website is a tool to integrate technology into education. It is believed that this website will be beneficial for pre-service and in-service teachers in terms of their professional developments.

Keywords: ADDIE, case-based library, design, technology integration

Procedia PDF Downloads 416