Search results for: image narrative
1679 Riesz Mixture Model for Brain Tumor Detection
Authors: Mouna Zitouni, Mariem Tounsi
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This research introduces an application of the Riesz mixture model for medical image segmentation for accurate diagnosis and treatment of brain tumors. We propose a pixel classification technique based on the Riesz distribution, derived from an extended Bartlett decomposition. To our knowledge, this is the first study addressing this approach. The Expectation-Maximization algorithm is implemented for parameter estimation. A comparative analysis, using both synthetic and real brain images, demonstrates the superiority of the Riesz model over a recent method based on the Wishart distribution.Keywords: EM algorithm, segmentation, Riesz probability distribution, Wishart probability distribution
Procedia PDF Downloads 171678 The Impact of Social Customer Relationship Management on Brand Loyalty and Reducing Co-Destruction of Value by Customers
Authors: Sanaz Farhangi, Habib Alipour
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The main objective of this paper is to explore how social media as a critical platform would increase the interactions between the tourism sector and stakeholders. Nowadays, human interactions through social media in many areas, especially in tourism, provide various experiences and information that users share and discuss. Organizations and firms can gain customer loyalty through social media platforms, albeit consumers' negative image of the product or services. Such a negative image can be reduced through constant communication between produces and consumers, especially with the availability of the new technology. Therefore, effective management of customer relationships in social media creates an extraordinary opportunity for organizations to enhance value and brand loyalty. In this study, we seek to develop a conceptual model for addressing factors such as social media, SCRM, and customer engagement affecting brand loyalty and diminish co-destruction. To support this model, we scanned the relevant literature using a comprehensive category of ideas in the context of marketing and customer relationship management. This will allow exploring whether there is any relationship between social media, customer engagement, social customer relationship management (SCRM), co-destruction, and brand loyalty. SCRM has been explored as a moderating factor in the relationship between customer engagement and social media to secure brand loyalty and diminish co-destruction of the company’s value. Although numerous studies have been conducted on the impact of social media on customers and marketing behavior, there are limited studies for investigating the relationship between SCRM, brand loyalty, and negative e-WOM, which results in the reduction of the co-destruction of value by customers. This study is an important contribution to the tourism and hospitality industry in orienting customer behavior in social media using SCRM. This study revealed that through social media platforms, management can generate discussion and engagement about the product and services, which facilitates customers feeling in an appositive way towards the firm and its product. Study has also revealed that customers’ complaints through social media have a multi-purpose effect; it can degrade the value of the product, but at the same time, it will motivate the firm to overcome its weaknesses and correct its shortcomings. This study has also implications for the managers and practitioners, especially in the tourism and hospitality sector. Future research direction and limitations of the research were also discussed.Keywords: brand loyalty, co-destruction, customer engagement, SCRM, tourism and hospitality
Procedia PDF Downloads 1161677 Understanding the Popularity of Historical Conservation in China: The Depoliticized Narratives as a Counter-Insurgency Strategy in Guangzhou
Authors: Luxi Chen
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The land finance in China in recent years has propelled urban renewals in the name of historical conservation and led to massive gentrification and compulsory relocation. Such inequalities cause insurgence. Drawing on public planning information, ethnographic field notes, and online interview data about Guangzhou's Enninglu Area, this paper aims to present how such insurgence has been contained and put down gradually through depoliticization narratives represented by "improving living conditions," "conserving historical culture," and "public participation”. This paper's findings include that 1) Besides economic growth, maintaining social stability in alignment with the central government are equally important to local government, reveals the latter efforts to mediate the growth coalition, residents, media, and academics so as to reconstruct the interface between state and society; 2) To empower the insurgence, the media and academics use public interests for propaganda, that diverts attention away from its political dimension; 3) In response, the government introduces improved regulations and planning, turning social inequalities into technical inadequacy so as to become the defender of public interests, which justifies the incoming renewal and prevents public questioning. By comparing regime changes among governments, developers, residents, media, and academics caused by renewal policies, this paper presents the depoliticized narrative as a counter-insurgence strategy to contain social conflicts and to boost inner-city renewal.Keywords: inner city renewal, depoliticization, historical conservation, public participation
Procedia PDF Downloads 2351676 Artificial Intelligence Based Method in Identifying Tumour Infiltrating Lymphocytes of Triple Negative Breast Cancer
Authors: Nurkhairul Bariyah Baharun, Afzan Adam, Reena Rahayu Md Zin
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Tumor microenvironment (TME) in breast cancer is mainly composed of cancer cells, immune cells, and stromal cells. The interaction between cancer cells and their microenvironment plays an important role in tumor development, progression, and treatment response. The TME in breast cancer includes tumor-infiltrating lymphocytes (TILs) that are implicated in killing tumor cells. TILs can be found in tumor stroma (sTILs) and within the tumor (iTILs). TILs in triple negative breast cancer (TNBC) have been demonstrated to have prognostic and potentially predictive value. The international Immune-Oncology Biomarker Working Group (TIL-WG) had developed a guideline focus on the assessment of sTILs using hematoxylin and eosin (H&E)-stained slides. According to the guideline, the pathologists use “eye balling” method on the H&E stained- slide for sTILs assessment. This method has low precision, poor interobserver reproducibility, and is time-consuming for a comprehensive evaluation, besides only counted sTILs in their assessment. The TIL-WG has therefore recommended that any algorithm for computational assessment of TILs utilizing the guidelines provided to overcome the limitations of manual assessment, thus providing highly accurate and reliable TILs detection and classification for reproducible and quantitative measurement. This study is carried out to develop a TNBC digital whole slide image (WSI) dataset from H&E-stained slides and IHC (CD4+ and CD8+) stained slides. TNBC cases were retrieved from the database of the Department of Pathology, Hospital Canselor Tuanku Muhriz (HCTM). TNBC cases diagnosed between the year 2010 and 2021 with no history of other cancer and available block tissue were included in the study (n=58). Tissue blocks were sectioned approximately 4 µm for H&E and IHC stain. The H&E staining was performed according to a well-established protocol. Indirect IHC stain was also performed on the tissue sections using protocol from Diagnostic BioSystems PolyVue™ Plus Kit, USA. The slides were stained with rabbit monoclonal, CD8 antibody (SP16) and Rabbit monoclonal, CD4 antibody (EP204). The selected and quality-checked slides were then scanned using a high-resolution whole slide scanner (Pannoramic DESK II DW- slide scanner) to digitalize the tissue image with a pixel resolution of 20x magnification. A manual TILs (sTILs and iTILs) assessment was then carried out by the appointed pathologist (2 pathologists) for manual TILs scoring from the digital WSIs following the guideline developed by TIL-WG 2014, and the result displayed as the percentage of sTILs and iTILs per mm² stromal and tumour area on the tissue. Following this, we aimed to develop an automated digital image scoring framework that incorporates key elements of manual guidelines (including both sTILs and iTILs) using manually annotated data for robust and objective quantification of TILs in TNBC. From the study, we have developed a digital dataset of TNBC H&E and IHC (CD4+ and CD8+) stained slides. We hope that an automated based scoring method can provide quantitative and interpretable TILs scoring, which correlates with the manual pathologist-derived sTILs and iTILs scoring and thus has potential prognostic implications.Keywords: automated quantification, digital pathology, triple negative breast cancer, tumour infiltrating lymphocytes
Procedia PDF Downloads 1161675 Navigating the Cacophony of Human Rights Claims and Chains of Fraud in Nigeria: The Anti-Corruption War Perspective
Authors: Mike Omilusi
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Since the Buhari administration came to power, it has gained the people’s confidence with its anti-corruption efforts. Making culprits account for their past unlawful deeds, in a very determined and aggressive manner ever witnessed in the nation’s political history, generates different reactions among Nigerians. However, some questions remain pertinent to this study: Are Nigerians really advocating persecution or prosecution in respect of the graft suspects? Do they want conviction without being convinced? Is their outburst propelled by emotions and revengeful anticipation of having suspected looters of the nation’s commonwealth behind bars? Can the war be successfully fought without resorting to impunity? Relying extensively on secondary sources with the aid of descriptive and narrative tools, this study seeks to interrogate the claim of fundamental human rights in the face of wanton looting of the nation’s resources. If, as opined by President Buhari, corruption is a crime against humanity, then it is argued that those who commit such crime should be subjected to penalties prescribed by law. Such crime -as corruption in this study- deprives the citizens of welfare, social amenities and good things of life. In this instance, it also poses threats to national security, having misappropriated funds meant for the war against the Boko Haram terrorism as revealed by the anti-corruption agency in the country. A theoretically-driven investigation, this essay raises some expectations within the context of good governance-propelled anti-corruption crusade, making modest recommendations as to how corruption should be prevented and combated within the confine of rule of law.Keywords: corruption, rule of law, human rights, prosecution, commonwealth
Procedia PDF Downloads 2031674 Assessment of Seeding and Weeding Field Robot Performance
Authors: Victor Bloch, Eerikki Kaila, Reetta Palva
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Field robots are an important tool for enhancing efficiency and decreasing the climatic impact of food production. There exists a number of commercial field robots; however, since this technology is still new, the robot advantages and limitations, as well as methods for optimal using of robots, are still unclear. In this study, the performance of a commercial field robot for seeding and weeding was assessed. A research 2-ha sugar beet field with 0.5m row width was used for testing, which included robotic sowing of sugar beet and weeding five times during the first two months of the growing. About three and five percent of the field were used as untreated and chemically weeded control areas, respectively. The plant detection was based on the exact plant location without image processing. The robot was equipped with six seeding and weeding tools, including passive between-rows harrow hoes and active hoes cutting inside rows between the plants, and it moved with a maximal speed of 0.9 km/h. The robot's performance was assessed by image processing. The field images were collected by an action camera with a height of 2 m and a resolution 27M pixels installed on the robot and by a drone with a 16M pixel camera flying at 4 m height. To detect plants and weeds, the YOLO model was trained with transfer learning from two available datasets. A preliminary analysis of the entire field showed that in the areas treated by the robot, the weed average density varied across the field from 6.8 to 9.1 weeds/m² (compared with 0.8 in the chemically treated area and 24.3 in the untreated area), the weed average density inside rows was 2.0-2.9 weeds / m (compared with 0 on the chemically treated area), and the emergence rate was 90-95%. The information about the robot's performance has high importance for the application of robotics for field tasks. With the help of the developed method, the performance can be assessed several times during the growth according to the robotic weeding frequency. When it’s used by farmers, they can know the field condition and efficiency of the robotic treatment all over the field. Farmers and researchers could develop optimal strategies for using the robot, such as seeding and weeding timing, robot settings, and plant and field parameters and geometry. The robot producers can have quantitative information from an actual working environment and improve the robots accordingly.Keywords: agricultural robot, field robot, plant detection, robot performance
Procedia PDF Downloads 871673 Chloroform-Formic Acid Solvent Systems for Nanofibrous Polycaprolactone Webs
Authors: I. Yalcin Enis, J. Vojtech, T. Gok Sadikoglu
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In this study, polycaprolactone (PCL) was dissolved in chloroform: ethanol solvent system at a concentration of 18 w/v %. 1, 2, 4, and 6 droplets of formic acid were added to the prepared 10ml PCL-chloroform:ethanol solutions separately. Fibrous webs were produced by electrospinning technique. Morphology of the webs was investigated by using scanning electron microscopy (SEM) whereas fiber diameters were measured by Image J Software System. The effect of formic acid addition to the mostly used chloroform solvent on fiber morphology was examined.Keywords: chloroform, electrospinning, formic acid polycaprolactone, fiber
Procedia PDF Downloads 2761672 GPU-Based Back-Projection of Synthetic Aperture Radar (SAR) Data onto 3D Reference Voxels
Authors: Joshua Buli, David Pietrowski, Samuel Britton
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Processing SAR data usually requires constraints in extent in the Fourier domain as well as approximations and interpolations onto a planar surface to form an exploitable image. This results in a potential loss of data requires several interpolative techniques, and restricts visualization to two-dimensional plane imagery. The data can be interpolated into a ground plane projection, with or without terrain as a component, all to better view SAR data in an image domain comparable to what a human would view, to ease interpretation. An alternate but computationally heavy method to make use of more of the data is the basis of this research. Pre-processing of the SAR data is completed first (matched-filtering, motion compensation, etc.), the data is then range compressed, and lastly, the contribution from each pulse is determined for each specific point in space by searching the time history data for the reflectivity values for each pulse summed over the entire collection. This results in a per-3D-point reflectivity using the entire collection domain. New advances in GPU processing have finally allowed this rapid projection of acquired SAR data onto any desired reference surface (called backprojection). Mathematically, the computations are fast and easy to implement, despite limitations in SAR phase history data size and 3D-point cloud size. Backprojection processing algorithms are embarrassingly parallel since each 3D point in the scene has the same reflectivity calculation applied for all pulses, independent of all other 3D points and pulse data under consideration. Therefore, given the simplicity of the single backprojection calculation, the work can be spread across thousands of GPU threads allowing for accurate reflectivity representation of a scene. Furthermore, because reflectivity values are associated with individual three-dimensional points, a plane is no longer the sole permissible mapping base; a digital elevation model or even a cloud of points (collected from any sensor capable of measuring ground topography) can be used as a basis for the backprojection technique. This technique minimizes any interpolations and modifications of the raw data, maintaining maximum data integrity. This innovative processing will allow for SAR data to be rapidly brought into a common reference frame for immediate exploitation and data fusion with other three-dimensional data and representations.Keywords: backprojection, data fusion, exploitation, three-dimensional, visualization
Procedia PDF Downloads 851671 Parallel Version of Reinhard’s Color Transfer Algorithm
Authors: Abhishek Bhardwaj, Manish Kumar Bajpai
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An image with its content and schema of colors presents an effective mode of information sharing and processing. By changing its color schema different visions and prospect are discovered by the users. This phenomenon of color transfer is being used by Social media and other channel of entertainment. Reinhard et al’s algorithm was the first one to solve this problem of color transfer. In this paper, we make this algorithm efficient by introducing domain parallelism among different processors. We also comment on the factors that affect the speedup of this problem. In the end by analyzing the experimental data we claim to propose a novel and efficient parallel Reinhard’s algorithm.Keywords: Reinhard et al’s algorithm, color transferring, parallelism, speedup
Procedia PDF Downloads 6141670 Environmental Virtue Ethics for the Anthropocene in Barbara Kingsolver’s Animal Dreams
Authors: Xu Lan, Zainor Izat Zainal
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Human intervention in Earth’s macro system has ushered in the age of the Anthropocene, prompting introspection among humans, the action agent. This epoch demands a reawakening of human conscience and inner motivation to mitigate the irreversible trend so as to shape the trajectory of the Anthropocene. Environmental virtue ethics claims that the fundamental cause of environmental crisis lies in humans themselves. Rather than focusing more on what humans should do, environmental virtue ethics seeks to specify environmental virtues to appeal to what kind of person a human should be. Renowned Pulitzer Prize-winning author Barbara Kingsolver illustrates her contentions about environmental ethics through the narrative of Codi and her sister Hallie’s environmental choices and actions in Animal Dreams (1990). This study adopts a textual analysis approach of the character traits exhibited by Codi and Hallie that are constitutive of making them environmentally virtuous, exploring how emotions and inner motivations drive actions. This paper is informed by Ronald Sandler’s (2007) virtues of sustainability, virtues of communion with nature, and virtues of environmental stewardship and activism. It aims to examine how Codi and Hallie’s character traits are built around these virtues. Furthermore, this study underscores the importance of internalizing principles and cultivating virtues for the environment and humans’ flourishing in the Anthropocene. As a tentative practice in applying environmental virtue ethics to examine environmental virtues for the Anthropocene, this study reveals Kingsolver’s endeavor of setting environmental virtue exemplars from fictional characters to inspire humans’ long-term and stable contribution to a better future.Keywords: anthopocene, environmental ethics, environmental virtues, virtue ethics
Procedia PDF Downloads 341669 Remote Sensing Application in Environmental Researches: Case Study of Iran Mangrove Forests Quantitative Assessment
Authors: Neda Orak, Mostafa Zarei
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Environmental assessment is an important session in environment management. Since various methods and techniques have been produces and implemented. Remote sensing (RS) is widely used in many scientific and research fields such as geology, cartography, geography, agriculture, forestry, land use planning, environment, etc. It can show earth surface objects cyclical changes. Also, it can show earth phenomena limits on basis of electromagnetic reflectance changes and deviations records. The research has been done on mangrove forests assessment by RS techniques. Mangrove forests quantitative analysis in Basatin and Bidkhoon estuaries was the aim of this research. It has been done by Landsat satellite images from 1975- 2013 and match to ground control points. This part of mangroves are the last distribution in northern hemisphere. It can provide a good background to improve better management on this important ecosystem. Landsat has provided valuable images to earth changes detection to researchers. This research has used MSS, TM, +ETM, OLI sensors from 1975, 1990, 2000, 2003-2013. Changes had been studied after essential corrections such as fix errors, bands combination, georeferencing on 2012 images as basic image, by maximum likelihood and IPVI Index. It was done by supervised classification. 2004 google earth image and ground points by GPS (2010-2012) was used to compare satellite images obtained changes. Results showed mangrove area in bidkhoon was 1119072 m2 by GPS and 1231200 m2 by maximum likelihood supervised classification and 1317600 m2 by IPVI in 2012. Basatin areas is respectively: 466644 m2, 88200 m2, 63000 m2. Final results show forests have been declined naturally. It is due to human activities in Basatin. The defect was offset by planting in many years. Although the trend has been declining in recent years again. So, it mentioned satellite images have high ability to estimation all environmental processes. This research showed high correlation between images and indexes such as IPVI and NDVI with ground control points.Keywords: IPVI index, Landsat sensor, maximum likelihood supervised classification, Nayband National Park
Procedia PDF Downloads 2931668 Detecting Tomato Flowers in Greenhouses Using Computer Vision
Authors: Dor Oppenheim, Yael Edan, Guy Shani
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This paper presents an image analysis algorithm to detect and count yellow tomato flowers in a greenhouse with uneven illumination conditions, complex growth conditions and different flower sizes. The algorithm is designed to be employed on a drone that flies in greenhouses to accomplish several tasks such as pollination and yield estimation. Detecting the flowers can provide useful information for the farmer, such as the number of flowers in a row, and the number of flowers that were pollinated since the last visit to the row. The developed algorithm is designed to handle the real world difficulties in a greenhouse which include varying lighting conditions, shadowing, and occlusion, while considering the computational limitations of the simple processor in the drone. The algorithm identifies flowers using an adaptive global threshold, segmentation over the HSV color space, and morphological cues. The adaptive threshold divides the images into darker and lighter images. Then, segmentation on the hue, saturation and volume is performed accordingly, and classification is done according to size and location of the flowers. 1069 images of greenhouse tomato flowers were acquired in a commercial greenhouse in Israel, using two different RGB Cameras – an LG G4 smartphone and a Canon PowerShot A590. The images were acquired from multiple angles and distances and were sampled manually at various periods along the day to obtain varying lighting conditions. Ground truth was created by manually tagging approximately 25,000 individual flowers in the images. Sensitivity analyses on the acquisition angle of the images, periods throughout the day, different cameras and thresholding types were performed. Precision, recall and their derived F1 score were calculated. Results indicate better performance for the view angle facing the flowers than any other angle. Acquiring images in the afternoon resulted with the best precision and recall results. Applying a global adaptive threshold improved the median F1 score by 3%. Results showed no difference between the two cameras used. Using hue values of 0.12-0.18 in the segmentation process provided the best results in precision and recall, and the best F1 score. The precision and recall average for all the images when using these values was 74% and 75% respectively with an F1 score of 0.73. Further analysis showed a 5% increase in precision and recall when analyzing images acquired in the afternoon and from the front viewpoint.Keywords: agricultural engineering, image processing, computer vision, flower detection
Procedia PDF Downloads 3291667 Machine Learning Approach for Automating Electronic Component Error Classification and Detection
Authors: Monica Racha, Siva Chandrasekaran, Alex Stojcevski
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The engineering programs focus on promoting students' personal and professional development by ensuring that students acquire technical and professional competencies during four-year studies. The traditional engineering laboratory provides an opportunity for students to "practice by doing," and laboratory facilities aid them in obtaining insight and understanding of their discipline. Due to rapid technological advancements and the current COVID-19 outbreak, the traditional labs were transforming into virtual learning environments. Aim: To better understand the limitations of the physical laboratory, this research study aims to use a Machine Learning (ML) algorithm that interfaces with the Augmented Reality HoloLens and predicts the image behavior to classify and detect the electronic components. The automated electronic components error classification and detection automatically detect and classify the position of all components on a breadboard by using the ML algorithm. This research will assist first-year undergraduate engineering students in conducting laboratory practices without any supervision. With the help of HoloLens, and ML algorithm, students will reduce component placement error on a breadboard and increase the efficiency of simple laboratory practices virtually. Method: The images of breadboards, resistors, capacitors, transistors, and other electrical components will be collected using HoloLens 2 and stored in a database. The collected image dataset will then be used for training a machine learning model. The raw images will be cleaned, processed, and labeled to facilitate further analysis of components error classification and detection. For instance, when students conduct laboratory experiments, the HoloLens captures images of students placing different components on a breadboard. The images are forwarded to the server for detection in the background. A hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm will be used to train the dataset for object recognition and classification. The convolution layer extracts image features, which are then classified using Support Vector Machine (SVM). By adequately labeling the training data and classifying, the model will predict, categorize, and assess students in placing components correctly. As a result, the data acquired through HoloLens includes images of students assembling electronic components. It constantly checks to see if students appropriately position components in the breadboard and connect the components to function. When students misplace any components, the HoloLens predicts the error before the user places the components in the incorrect proportion and fosters students to correct their mistakes. This hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm automating electronic component error classification and detection approach eliminates component connection problems and minimizes the risk of component damage. Conclusion: These augmented reality smart glasses powered by machine learning provide a wide range of benefits to supervisors, professionals, and students. It helps customize the learning experience, which is particularly beneficial in large classes with limited time. It determines the accuracy with which machine learning algorithms can forecast whether students are making the correct decisions and completing their laboratory tasks.Keywords: augmented reality, machine learning, object recognition, virtual laboratories
Procedia PDF Downloads 1341666 Celebrity Culture and Social Role of Celebrities in Türkiye during the 1990s: The Case of Türkiye, Newspaper, Radio, Televison (TGRT) Channel
Authors: Yelda Yenel, Orkut Acele
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In a media-saturated world, celebrities have become ubiquitous figures, encountered both in public spaces and within the privacy of our homes, seamlessly integrating into daily life. From Alexander the Great to contemporary media personalities, the image of celebrity has persisted throughout history, manifesting in various forms and contexts. Over time, as the relationship between society and the market evolved, so too did the roles and behaviors of celebrities. These transformations offer insights into the cultural climate, revealing shifts in habits and worldviews. In Türkiye, the emergence of private television channels brought an influx of celebrities into everyday life, making them a pervasive part of daily routines. To understand modern celebrity culture, it is essential to examine the ideological functions of media within political, economic, and social contexts. Within this framework, celebrities serve as both reflections and creators of cultural values and, at times, act as intermediaries, offering insights into the society of their era. Starting its broadcasting life in 1992 with religious films and religious conversation, Türkiye Newspaper, Radio, Television channel (TGRT) later changed its appearance, slogan, and the celebrities it featured in response to the political atmosphere. Celebrities played a critical role in transforming from the existing slogan 'Peace has come to the screen' to 'Watch and see what will happen”. Celebrities hold significant roles in society, and their images are produced and circulated by various actors, including media organizations and public relations teams. Understanding these dynamics is crucial for analyzing their influence and impact. This study aims to explore Turkish society in the 1990s, focusing on TGRT and its visual and discursive characteristics regarding celebrity figures such as Seda Sayan. The first section examines the historical development of celebrity culture and its transformations, guided by the conceptual framework of celebrity studies. The complex and interconnected image of celebrity, as introduced by post-structuralist approaches, plays a fundamental role in making sense of existing relationships. This section traces the existence and functions of celebrities from antiquity to the present day. The second section explores the economic, social, and cultural contexts of 1990s Türkiye, focusing on the media landscape and visibility that became prominent in the neoliberal era following the 1980s. This section also discusses the political factors underlying TGRT's transformation, such as the 1997 military memorandum. The third section analyzes TGRT as a case study, focusing on its significance as an Islamic television channel and the shifts in its public image, categorized into two distinct periods. The channel’s programming, which aligned with Islamic teachings, and the celebrities who featured prominently during these periods became the public face of both TGRT and the broader society. In particular, the transition to a more 'secular' format during TGRT's second phase is analyzed, focusing on changes in celebrity attire and program formats. This study reveals that celebrities are used as indicators of ideology, benefiting from this instrumentalization by enhancing their own fame and reflecting the prevailing cultural hegemony in society.Keywords: celebrity culture, media, neoliberalism, TGRT
Procedia PDF Downloads 301665 Application of Low-order Modeling Techniques and Neural-Network Based Models for System Identification
Authors: Venkatesh Pulletikurthi, Karthik B. Ariyur, Luciano Castillo
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The system identification from the turbulence wakes will lead to the tactical advantage to prepare and also, to predict the trajectory of the opponents’ movements. A low-order modeling technique, POD, is used to predict the object based on the wake pattern and compared with pre-trained image recognition neural network (NN) to classify the wake patterns into objects. It is demonstrated that low-order modeling, POD, is able to predict the objects better compared to pretrained NN by ~30%.Keywords: the bluff body wakes, low-order modeling, neural network, system identification
Procedia PDF Downloads 1801664 Immersive and Interactive Storytelling: Exploring Narratives and Online Multisensory Experience for Cultural Memory and Collective Awareness through Graphic Novel
Authors: Cristina Greco
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The spread of the digital and we-based technologies has led to a transformation process, which has coincided with an increase in the number of cases who are beyond the mainstream storytelling and its codes on the interaction with the user. On the base of a previous research on i-docs and virtual museums, this study analyses interactive and immersive online Graphic Novel – one-page, animated, illustrated, and hybrid – to reflect on the transformational implications of this expressive form on the user perception, remembrance, and awareness. The way in which the user experiences a certain level of interaction with the story and immersion in the semantic and figurative universe would bring user’s attention, activating introspection and self-reflection processes, perception, imagination, and creativity. This would have to do with the involvement of different senses – visual, proprioceptive, tactile, auditory, and vestibular – and the activation of a phenomenon of synaesthesia (involuntary cross-modal sensory association) – where, for example, the aural reconnect the user to another sense, providing a multisensory experience. The case studies show specific forms of interactive and immersive graphic novel and reflect on application that has sought to engage innovative ways to communicate different messages and stimulate cultural memory and collective awareness. The visual semiotic and narrative analysis of the distinctive traits of such a complex textuality, along with a study of the user’s experience through observation in naturalistic settings and interviews, allows us to question the functioning of these configurations, with regard to the relationships between the figurative dimension, the perceptive activity, and their impact on the user’s engagement.Keywords: collective awareness, cultural memory, graphic novel, interactive and immersive storytelling
Procedia PDF Downloads 1491663 Bridging the Internalist-Externalist Divide: A Catholic-Reformed Epistemological Synthesis of the Justification of Christian Beliefs
Authors: Linto Francis Kallukulangara
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Although the Catholic and Reformed traditions share a common baptismal heritage, they differe considerably in their epistemic stance on whether a believer can legitimatly subscribe to a proposition of Christian Revelation without any evidence. Catholic tradition, which is essentially rooted in the internalist epistemology, posits that a theistic belief must be substantiated by a rational ground that is cognitively accessible to the believer. In contrast, Reformed thinkers have historically maintained a non-evidentialist stance, which has received strong criticism, including allegations of irrationality. However, recent developments in analytic philosophy, particularly the rise of externalist epistemology, have revitalized the non-evidentialist position within the Reformed tradition. The intellectual allure of this movement has led many contemporary thinkers to argue that the Catholic internalist/evidentialist position has not only been significantly challenged but has also been largely silenced by this externalism-based Reformed epistemological stance. Consequently, they argue that the non-cogntive Reformed currect has established itself as the dominant, or perhaps the only, epistemological position in the philosophy of religion. This paper counters the prevailing narrative, arguing that despite the ostensible challenge posed by Reformed non-evidentialism, a synthesis is possible. By analyzing various Reformed epistemological movements within the contemporary anaytic tradtion, we demonstrate that externalist-based Reformed epistemology does not fundamentally undermine Catholic evidentialism. Instead, it offers a new and more promising framework for a Christian epistemology that sythesizes elements from both traditions, offering a more comprehensive and nuanced understing of the justification of religion belief, incoperating both internalist and externalist perspective.Keywords: reformed and catholic epistemology, evidentialism, non-evidentialism, internalism, externalism
Procedia PDF Downloads 251662 Post 2014 Afghanistan and Its Implications on Pakistan
Authors: Naad-E-Ali Sulehria
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This paper unfolds the facts and findings of Afghan scenario particularly its implications on Pakistan. At present, the Post 2014 withdrawal of US and ISAF combat forces from Afghan land is one of the up-to-the-minute issues among analysts of international relations. Deliberating from the current situation of Afghanistan towards its future prospects and the elements vibrating Afghanistan's internal dynamics, as well as exploitation of its resources by other states and non-state actors, are discussed accordingly. Moreover, the reasons behind such a paradigm shift in US foreign policy are tried to be contemplated with first hand knowledge. It is investigated that 'what is the current image of Afghanistan in today's world?', 'what will be its future aspects?', and 'what sort of Afghanistan does Pakistan foresees' as the concerned area of discussion.Keywords: Afghanistan, Pakistan, new great game, taliban
Procedia PDF Downloads 3001661 Clustering the Wheat Seeds Using SOM Artificial Neural Networks
Authors: Salah Ghamari
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In this study, the ability of self organizing map artificial (SOM) neural networks in clustering the wheat seeds varieties according to morphological properties of them was considered. The SOM is one type of unsupervised competitive learning. Experimentally, five morphological features of 300 seeds (including three varieties: gaskozhen, Md and sardari) were obtained using image processing technique. The results show that the artificial neural network has a good performance (90.33% accuracy) in classification of the wheat varieties despite of high similarity in them. The highest classification accuracy (100%) was achieved for sardari.Keywords: artificial neural networks, clustering, self organizing map, wheat variety
Procedia PDF Downloads 6561660 Reviving Sustainable Architecture in Non-Wester Culture
Authors: Khaled Asfour
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Going for LEED certification is the latest concern in Egyptian practice that only materialized during the last 4 years. Egyptian Consultant Group (ECG) together with Credit Agricole had the vision to design a headquarters (Cairo) that delivers a serious sustainable design. The bank is a strong advocator of “green banking” and supports renewable energy and energy saving projects. Their HQ in Cairo has passed all the hurdles to become the first platinum LEED certificate holder in Egypt. With this design Egyptian practice has finally re-engaged in a serious way with its long-standing traditions in sustainable architecture. Perhaps the closest to our memory is the medieval houses of Cairo. Few centuries later these qualities disappeared with the advent of Modern Movement that focused more on standard modernist image making than real localized quality of living environments. The first person to note this disappearance was Hassan Fathy half a century ago. Despite international applaud for his efforts he had no effect on prevailing local practice that continued senselessly adopting recycled modernist templates. The Egyptian society was not ready to accept any reference to historic architecture. Disciples of Hassan Fathy, few decades later sought, of tackling the lack of interest in green architecture in a different way. Mohamed Awad introduced in his design sustainable ideals inspired from traditional architecture rather than recycling directly historic forms and images. Despite success, this approach did not go far enough to influence the prevailing practice. Since year 2000 Egyptian economy was ebbing and flowing dramatically. This staggering fluctuation coupled by energy crisis has disillusioned architects and clients on the issue of modern image making. No more shining architecture under the sun with high running cost of fossil fuel. They sought of adopting contemporary green measures that offer pleasant living while saving on energy. A revival is on its way but is very slow and timid. The paper will present this problem of reviving sustainable architecture. How this process can be accelerated in order to give stronger impact on current practice will be addressed through the works of Mario Cucinella and Norman Foster.Keywords: LEED certification, Hasan Fathy, Medieval architecture, Mario Cucinella, Norman Foster
Procedia PDF Downloads 4911659 Implementation of a Method of Crater Detection Using Principal Component Analysis in FPGA
Authors: Izuru Nomura, Tatsuya Takino, Yuji Kageyama, Shin Nagata, Hiroyuki Kamata
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We propose a method of crater detection from the image of the lunar surface captured by the small space probe. We use the principal component analysis (PCA) to detect craters. Nevertheless, considering severe environment of the space, it is impossible to use generic computer in practice. Accordingly, we have to implement the method in FPGA. This paper compares FPGA and generic computer by the processing time of a method of crater detection using principal component analysis.Keywords: crater, PCA, eigenvector, strength value, FPGA, processing time
Procedia PDF Downloads 5551658 The Mashishing Marking Memories Project: A Culture-Centered Approach to Participation
Authors: Nongcebo Ngcobo
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This research explores the importance of including a multitude of voices in the cultural heritage narrative, particularly in South Africa. The Mashishing project is an extension of and builds on the existing ‘Biesje Poort project’ which is a rock art project that was funded by the National Heritage Council in 2010 - 2013. Hence, the Mashishing marking memories project applies comparable Biesje Poort project objectives, though in a different geographical area. The wider project objectives are to transfer skills, promote social cohesion and empowerment, and lastly to add to the knowledge base of the Mashishing region and the repository of the local museum in the Lydenburg museum. This study is located in the Mashishing area, in Mpumalanga, South Africa. In this area, there were no present multi-vocal heritage projects. This research assesses the Mashishing marking memories project through the culture-centered approach for communication for social change, which examines the impact that the diverse participants have on the operations of the Mashishing project and also investigates whether the culturally diverse participants facilitates or hinders effective participation within the project. Key findings of this research uncovered the significance of participation and diverse voices in the cultural heritage field. Furthermore, this study highlights how unequal power relations affect effective participation. As a result, this study encourages the importance of bringing the researcher and the participant in a safe space to facilitate mutual learning. It also encourages an exchange of roles, where the researcher shifts from being an authoritarian figure to being in the role of a listener.Keywords: culture, heritage, participation, social change
Procedia PDF Downloads 1211657 Comparative Literature, Postcolonialism and the “African World” in Wole Soyinka’s Myth, Literature and the African World
Authors: Karen de Andrade
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Literature is generally understood as an aesthetic creation, an artistic object that relates to the history and sociocultural paradigms of a given era. Moreover, through it, we can dwell on the deepest reflections on the human condition. It can also be used to propagate projects of domination, as Edward Said points out in his book Culture and Imperialism, connecting narrative, history and land conquest. Having said that, the aim of this paper is to analyse how Wole Soyinka elaborated his main theoretical work, Myth, Literature and African World, a collection of essays published in 1976, by comparing the philosophical, ideological and aesthetic practices of African, diasporic and European writers from the point of view of the Yoruba tradition, to which he belongs. Moreover, Soyinka believes that (literary) art has an important function in the formation of a people, in the construction of its political identity and in cultural regeneration, especially after the independence. The author's critical endeavour is that of attempting to construct a past. For him, the "African World" is not a mere allegory of the continent, and to understand it in this way would be to perpetuate a colonialist vision that would deny the subjectivities that cross black cultures, history and bodies. For him, comparative literature can be used not to "equate" local African texts with the European canon; but rather to recognise that they have aesthetic value and socio-cultural importance. Looking at the local, the particular and specific to each culture is, according to Soyinka, appropriate for dealing with African cultures, as opposed to abstractions of dialectical materialism or capitalist nationalism. In view of this, in his essays, the author creates a possibility for artistic and social reflection beyond the logic of Western politics.Keywords: comparative literature, African Literature, Literary Theory, Yoruba Mythology, Wole Soyinka, Afrodiaspora
Procedia PDF Downloads 691656 A Survey and Analysis on Inflammatory Pain Detection and Standard Protocol Selection Using Medical Infrared Thermography from Image Processing View Point
Authors: Mrinal Kanti Bhowmik, Shawli Bardhan Jr., Debotosh Bhattacharjee
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Human skin containing temperature value more than absolute zero, discharges infrared radiation related to the frequency of the body temperature. The difference in infrared radiation from the skin surface reflects the abnormality present in human body. Considering the difference, detection and forecasting the temperature variation of the skin surface is the main objective of using Medical Infrared Thermography(MIT) as a diagnostic tool for pain detection. Medical Infrared Thermography(MIT) is a non-invasive imaging technique that records and monitors the temperature flow in the body by receiving the infrared radiated from the skin and represent it through thermogram. The intensity of the thermogram measures the inflammation from the skin surface related to pain in human body. Analysis of thermograms provides automated anomaly detection associated with suspicious pain regions by following several image processing steps. The paper represents a rigorous study based survey related to the processing and analysis of thermograms based on the previous works published in the area of infrared thermal imaging for detecting inflammatory pain diseases like arthritis, spondylosis, shoulder impingement, etc. The study also explores the performance analysis of thermogram processing accompanied by thermogram acquisition protocols, thermography camera specification and the types of pain detected by thermography in summarized tabular format. The tabular format provides a clear structural vision of the past works. The major contribution of the paper introduces a new thermogram acquisition standard associated with inflammatory pain detection in human body to enhance the performance rate. The FLIR T650sc infrared camera with high sensitivity and resolution is adopted to increase the accuracy of thermogram acquisition and analysis. The survey of previous research work highlights that intensity distribution based comparison of comparable and symmetric region of interest and their statistical analysis assigns adequate result in case of identifying and detecting physiological disorder related to inflammatory diseases.Keywords: acquisition protocol, inflammatory pain detection, medical infrared thermography (MIT), statistical analysis
Procedia PDF Downloads 3421655 Sensory Ethnography and Interaction Design in Immersive Higher Education
Authors: Anna-Kaisa Sjolund
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The doctoral thesis examines interaction design and sensory ethnography as tools to create immersive education environments. In recent years, there has been increasing interest and discussions among researchers and educators on immersive education like augmented reality tools, virtual glasses and the possibilities to utilize them in education at all levels. Using virtual devices as learning environments it is possible to create multisensory learning environments. Sensory ethnography in this study refers to the way of the senses consider the impact on the information dynamics in immersive learning environments. The past decade has seen the rapid development of virtual world research and virtual ethnography. Christine Hine's Virtual Ethnography offers an anthropological explanation of net behavior and communication change. Despite her groundbreaking work, time has changed the users’ communication style and brought new solutions to do ethnographical research. The virtual reality with all its new potential has come to the fore and considering all the senses. Movie and image have played an important role in cultural research for centuries, only the focus has changed in different times and in a different field of research. According to Karin Becker, the role of image in our society is information flow and she found two meanings what the research of visual culture is. The images and pictures are the artifacts of visual culture. Images can be viewed as a symbolic language that allows digital storytelling. Combining the sense of sight, but also the other senses, such as hear, touch, taste, smell, balance, the use of a virtual learning environment offers students a way to more easily absorb large amounts of information. It offers also for teachers’ different ways to produce study material. In this article using sensory ethnography as research tool approaches the core question. Sensory ethnography is used to describe information dynamics in immersive environment through interaction design. Immersive education environment is understood as three-dimensional, interactive learning environment, where the audiovisual aspects are central, but all senses can be taken into consideration. When designing learning environments or any digital service, interaction design is always needed. The question what is interaction design is justified, because there is no simple or consistent idea of what is the interaction design or how it can be used as a research method or whether it is only a description of practical actions. When discussing immersive learning environments or their construction, consideration should be given to interaction design and sensory ethnography.Keywords: immersive education, sensory ethnography, interaction design, information dynamics
Procedia PDF Downloads 1371654 Evaluation of Virtual Reality for the Rehabilitation of Athlete Lower Limb Musculoskeletal Injury: A Method for Obtaining Practitioner’s Viewpoints through Observation and Interview
Authors: Hannah K. M. Tang, Muhammad Ateeq, Mark J. Lake, Badr Abdullah, Frederic A. Bezombes
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Based on a theoretical assessment of current literature, virtual reality (VR) could help to treat sporting injuries in a number of ways. However, it is important to obtain rehabilitation specialists’ perspectives in order to design, develop and validate suitable content for a VR application focused on treatment. Subsequently, a one-day observation and interview study focused on the use of VR for the treatment of lower limb musculoskeletal conditions in athletes was conducted at St George’s Park England National Football Centre with rehabilitation specialists. The current paper established the methods suitable for obtaining practitioner’s viewpoints through observation and interview in this context. Particular detail was provided regarding the method of qualitatively processing interview results using the qualitative data analysis software tool NVivo, in order to produce a narrative of overarching themes. The observations and overarching themes identified could be used as a framework and success criteria of a VR application developed in future research. In conclusion, this work explained the methods deemed suitable for obtaining practitioner’s viewpoints through observation and interview. This was required in order to highlight characteristics and features of a VR application designed to treat lower limb musculoskeletal injury of athletes and could be built upon to direct future work.Keywords: athletes, lower-limb musculoskeletal injury, rehabilitation, return-to-sport, virtual reality
Procedia PDF Downloads 2571653 Detection and Classification Strabismus Using Convolutional Neural Network and Spatial Image Processing
Authors: Anoop T. R., Otman Basir, Robert F. Hess, Eileen E. Birch, Brooke A. Koritala, Reed M. Jost, Becky Luu, David Stager, Ben Thompson
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Strabismus refers to a misalignment of the eyes. Early detection and treatment of strabismus in childhood can prevent the development of permanent vision loss due to abnormal development of visual brain areas. We developed a two-stage method for strabismus detection and classification based on photographs of the face. The first stage detects the presence or absence of strabismus, and the second stage classifies the type of strabismus. The first stage comprises face detection using Haar cascade, facial landmark estimation, face alignment, aligned face landmark detection, segmentation of the eye region, and detection of strabismus using VGG 16 convolution neural networks. Face alignment transforms the face to a canonical pose to ensure consistency in subsequent analysis. Using facial landmarks, the eye region is segmented from the aligned face and fed into a VGG 16 CNN model, which has been trained to classify strabismus. The CNN determines whether strabismus is present and classifies the type of strabismus (exotropia, esotropia, and vertical deviation). If stage 1 detects strabismus, the eye region image is fed into stage 2, which starts with the estimation of pupil center coordinates using mask R-CNN deep neural networks. Then, the distance between the pupil coordinates and eye landmarks is calculated along with the angle that the pupil coordinates make with the horizontal and vertical axis. The distance and angle information is used to characterize the degree and direction of the strabismic eye misalignment. This model was tested on 100 clinically labeled images of children with (n = 50) and without (n = 50) strabismus. The True Positive Rate (TPR) and False Positive Rate (FPR) of the first stage were 94% and 6% respectively. The classification stage has produced a TPR of 94.73%, 94.44%, and 100% for esotropia, exotropia, and vertical deviations, respectively. This method also had an FPR of 5.26%, 5.55%, and 0% for esotropia, exotropia, and vertical deviation, respectively. The addition of one more feature related to the location of corneal light reflections may reduce the FPR, which was primarily due to children with pseudo-strabismus (the appearance of strabismus due to a wide nasal bridge or skin folds on the nasal side of the eyes).Keywords: strabismus, deep neural networks, face detection, facial landmarks, face alignment, segmentation, VGG 16, mask R-CNN, pupil coordinates, angle deviation, horizontal and vertical deviation
Procedia PDF Downloads 931652 The Intersection of Artificial Intelligence and Mathematics
Authors: Mitat Uysal, Aynur Uysal
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Artificial Intelligence (AI) is fundamentally driven by mathematics, with many of its core algorithms rooted in mathematical principles such as linear algebra, probability theory, calculus, and optimization techniques. This paper explores the deep connection between AI and mathematics, highlighting the role of mathematical concepts in key AI techniques like machine learning, neural networks, and optimization. To demonstrate this connection, a case study involving the implementation of a neural network using Python is presented. This practical example illustrates the essential role that mathematics plays in training a model and solving real-world problems.Keywords: AI, mathematics, machine learning, optimization techniques, image processing
Procedia PDF Downloads 141651 Relational Attention Shift on Images Using Bu-Td Architecture and Sequential Structure Revealing
Authors: Alona Faktor
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In this work, we present a NN-based computational model that can perform attention shifts according to high-level instruction. The instruction specifies the type of attentional shift using explicit geometrical relation. The instruction also can be of cognitive nature, specifying more complex human-human interaction or human-object interaction, or object-object interaction. Applying this approach sequentially allows obtaining a structural description of an image. A novel data-set of interacting humans and objects is constructed using a computer graphics engine. Using this data, we perform systematic research of relational segmentation shifts.Keywords: cognitive science, attentin, deep learning, generalization
Procedia PDF Downloads 1981650 Congenital Sublingual Dermoid Cyst with Cutaneous Fistula
Authors: Rafael Ricieri, Rogerio Barros, Francisco Clovis
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Objective– The Objective of this is study is to report a rare case of dermoid cyst, with a sublingual location and cutaneous fistula in a 4 year-old child.Methods: This study is a case report. The main study instrument was the medical record and the radiological and intraoperative image bank. Results: Infants with congenital cervical lesions eventually need tomography for diagnostic elucidation, and health services should be structured to perform sedation and thin tomographic sections in order to reduce morbidity.Keywords: congenital, sublingual dermoid cyst, fistula, pediatric surgery, head and kneck surgery
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