Search results for: market segmentation of sports fans

Authors: Belgherbi Aicha, Bessaid Abdelhafid

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In the recent years a great deal of research work has been devoted to the development of semi-automatic and automatic techniques for the analysis of abdominal CT images. The first and fundamental step in all these studies is the semi-automatic liver and spleen segmentation that is still an open problem. In this paper, a semi-automatic liver and spleen segmentation method by the mathematical morphology based on watershed algorithm has been proposed. Our algorithm is currency in two parts. In the first, we seek to determine the region of interest by applying the morphological to extract the liver and spleen. The second step consists to improve the quality of the image gradient. In this step, we propose a method for improving the image gradient to reduce the over-segmentation problem by applying the spatial filters followed by the morphological filters. Thereafter we proceed to the segmentation of the liver, spleen. The aim of this work is to develop a method for semi-automatic segmentation liver and spleen based on watershed algorithm, improve the accuracy and the robustness of the liver and spleen segmentation and evaluate a new semi-automatic approach with the manual for liver segmentation. To validate the segmentation technique proposed, we have tested it on several images. Our segmentation approach is evaluated by comparing our results with the manual segmentation performed by an expert. The experimental results are described in the last part of this work. The system has been evaluated by computing the sensitivity and specificity between the semi-automatically segmented (liver and spleen) contour and the manually contour traced by radiological experts. Liver segmentation has achieved the sensitivity and specificity; sens Liver=96% and specif Liver=99% respectively. Spleen segmentation achieves similar, promising results sens Spleen=95% and specif Spleen=99%.

Keywords: CT images, liver and spleen segmentation, anisotropic diffusion filter, morphological filters, watershed algorithm

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Authors: Khalid Salhi, El Miloud Jaara, Mohammed Talibi Alaoui

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In this paper, we present a neural approach for unsupervised natural color-texture image segmentation, which is based on both Kohonen maps and mathematical morphology, using a combination of the texture and the image color information of the image, namely, the fractal features based on fractal dimension are selected to present the information texture, and the color features presented in RGB color space. These features are then used to train the network Kohonen, which will be represented by the underlying probability density function, the segmentation of this map is made by morphological watershed transformation. The performance of our color-texture segmentation approach is compared first, to color-based methods or texture-based methods only, and then to k-means method.

Keywords: segmentation, color-texture, neural networks, fractal, watershed

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Authors: Gaokai Liu

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Automatic defect detection for nanomaterial images is widely required in industrial scenarios. Deep learning approaches are considered as the most effective solutions for the great majority of image-based tasks. In this paper, an edge guidance network for defect segmentation is proposed. First, the encoder path with multiple convolution and downsampling operations is applied to the acquisition of shared features. Then two decoder paths both are connected to the last convolution layer of the encoder and supervised by the edge and segmentation labels, respectively, to guide the whole training process. Meanwhile, the edge and encoder outputs from the same stage are concatenated to the segmentation corresponding part to further tune the segmentation result. Finally, the effectiveness of the proposed method is verified via the experiments on open nanofibrous datasets.

Keywords: deep learning, defect detection, image segmentation, nanomaterials

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Authors: Poopak Dehshahri

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The applicability of intellectual property rights in the sports industry from the present paper’s perspective includes athletic skills, which are comprised of two parts: athletic movements and athletic methods. Also, the applicability pertaining to the athletes᾽ personality, such as the Name, the Image, the Voice, the Signature and their Shirt Number, are deemed as related to the sports natural persons. Radio and TV broadcasting rights of the sports events, the signs and symbols of the athletic institutions including the sign and symbol, trademark (brand name), the name and the place of residence of the sports clubs, the Sports events and the special sports, special slogan of the sports clubs or sports competitions and the sports clothing design are Included under the athletic institutions᾽ applicability of intellectual property rights.

Keywords: sport industry, intellectual property, sport skills, right to fame, radio and television broadcasting right, sport sign

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Authors: Enver Kucukkulahli, Pakize Erdogmus, Kemal Polat

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The 2D image segmentation is a significant process in finding a suitable region in medical images such as MRI, PET, CT etc. In this study, we have focused on 2D MRI images for image segmentation process. We have designed a GUI (graphical user interface) written in MATLABTM for 2D MRI images. In this program, there are two different interfaces including data pre-processing and image clustering or segmentation. In the data pre-processing section, there are median filter, average filter, unsharp mask filter, Wiener filter, and custom filter (a filter that is designed by user in MATLAB). As for the image clustering, there are seven different image segmentations for 2D MR images. These image segmentation algorithms are as follows: PSO (particle swarm optimization), GA (genetic algorithm), Lloyds algorithm, k-means, the combination of Lloyds and k-means, mean shift clustering, and finally BBO (Biogeography Based Optimization). To find the suitable cluster number in 2D MRI, we have designed the histogram based cluster estimation method and then applied to these numbers to image segmentation algorithms to cluster an image automatically. Also, we have selected the best hybrid method for each 2D MR images thanks to this GUI software.

Keywords: image segmentation, clustering, GUI, 2D MRI

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Authors: Jiangbo Shi, Zeyu Gao, Chen Li

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Nuclei segmentation is a fundamental task in digital pathology analysis and can be automated by deep learning-based methods. However, the development of such an automated method requires a large amount of data with precisely annotated masks which is hard to obtain. Training with weakly labeled data is a popular solution for reducing the workload of annotation. In this paper, we propose a novel meta-learning-based nuclei segmentation method which follows the label correction paradigm to leverage data with noisy masks. Specifically, we design a fully conventional meta-model that can correct noisy masks by using a small amount of clean meta-data. Then the corrected masks are used to supervise the training of the segmentation model. Meanwhile, a bi-level optimization method is adopted to alternately update the parameters of the main segmentation model and the meta-model. Extensive experimental results on two nuclear segmentation datasets show that our method achieves the state-of-the-art result. In particular, in some noise scenarios, it even exceeds the performance of training on supervised data.

Keywords: deep learning, histopathological image, meta-learning, nuclei segmentation, weak annotations

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Authors: Belgherbi Aicha, Hadjidj Ismahen, Bessaid Abdelhafid

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The phase of segmentation is an important step in the processing and interpretation of medical images. In this paper, we focus on the segmentation of liver and spleen from the abdomen computed tomography (CT) images. The importance of our study comes from the fact that the segmentation of ROI from CT images is usually a difficult task. This difficulty is the gray’s level of which is similar to the other organ also the ROI are connected to the ribs, heart, kidneys, etc. Our proposed method is based on the anatomical information and mathematical morphology tools used in the image processing field. At first, we try to remove the surrounding and connected organs and tissues by applying morphological filters. This first step makes the extraction of interest regions easier. The second step consists of improving the quality of the image gradient. In this step, we propose a method for improving the image gradient to reduce these deficiencies by applying the spatial filters followed by the morphological filters. Thereafter we proceed to the segmentation of the liver, spleen. To validate the segmentation technique proposed, we have tested it on several images. Our segmentation approach is evaluated by comparing our results with the manual segmentation performed by an expert. The experimental results are described in the last part of this work.The system has been evaluated by computing the sensitivity and specificity between the semi-automatically segmented (liver and spleen) contour and the manually contour traced by radiological experts.

Keywords: CT images, liver and spleen segmentation, anisotropic diffusion filter, morphological filters, watershed algorithm

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Authors: Yakubu Nkom Bityong, A. I. Kabido, K. Venkateswarlu

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The influence of branding and consultancy services on sports development and marketing mix has been a matter of interest among coaches athletes and sports managers in Nigeria. Marketers use sports as a promotional vehicle towards attracting customers to their products and services. The use of images, names, and photographs of sports personalities to advertise beverages, cars, and a whole range of other products and services as it is clearly noticed all over the television, radio and print media has generated a lot of argument among consumers who have vested interest and are more drawn to their favorite teams and sports personalities than they are to many company products This paper examines the influence of branding and consultancy services on sports Performance of coaches, athletes and sports managers in Nigeria. From a population of 7,441 made up of coaches, athletes and sports managers, 372 respondents were sampled for the study. A self developed and standardized questionnaire was the instrument used for data collection. One-tailed t-test was used to test the hypothesis. Results revealed that branding and consultancy services influence the performances of coaches, athletes and sports managers in Nigeria. It was concluded that the establishment of the National Institute of Sports (NIS) in Lagos with affiliated sports training programmes in Nigerian Universities is responsible for boosting the performance of sports personalities in Nigeria. It was recommended that National Policy on Sports should be reviewed in order to inculcate new methods and strategies towards enhancing sports development initiatives in the country while stakeholders should intensify regular training and retraining programmes for coaches, athletes and sports managers to update their knowledge and skills.

Keywords: branding, consultancy, sports performance, sports development

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Authors: Tian Zhang

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Unsupervised object segmentation aims at segmenting objects in sequential images and obtaining the mask of each object without any manual intervention. Unsupervised segmentation remains a challenging task due to the lack of prior knowledge about these objects. Previous methods often require manually specifying the action of each object, which is often difficult to obtain. Instead, this paper does not need action information of objects and automatically learns the actions and relations among objects from the structured environment. To obtain the object segmentation of sequential images, the relationships between objects and images are extracted to infer the action and interaction of objects based on the multi-head attention mechanism. Three types of objects’ relationships in the object segmentation task are proposed: the relationship between objects in the same frame, the relationship between objects in two frames, and the relationship between objects and historical information. Based on these relationships, the proposed model (1) is effective in multiple objects segmentation tasks, (2) just needs images as input, and (3) produces better segmentation results as more relationships are considered. The experimental results on multiple datasets show that this paper’s method achieves state-of-art performance. The quantitative and qualitative analyses of the result are conducted. The proposed method could be easily extended to other similar applications.

Keywords: unsupervised object segmentation, attention mechanism, contrastive learning, structured environment

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Authors: Pengchao Wei, Xiangzhong Fang

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Noise is ubiquitous in this world. Denoising is an essential technology, especially in image semantic segmentation, where noises are generally categorized into two main types i.e. feature noise and label noise. The main focus of this paper is aiming at modeling label noise, investigating the behaviors of different types of label noise on image semantic segmentation tasks using K-Nearest-Neighbor and Convolutional Neural Network classifier. The performance without label noise and with is evaluated and illustrated in this paper. In addition to that, the influence of feature noise on the image semantic segmentation task is researched as well and a feature noise reduction method is applied to mitigate its influence in the learning procedure.

Keywords: convolutional neural network, denoising, feature noise, image semantic segmentation, k-nearest-neighbor, label noise

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Authors: Min Pan, An-Hsu Chen

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Burnout has been proved to be one of the factors that hinder the development and sport performances of athletes while moral disengagement is the psychological mechanism used by athletes to elevate the guilt caused by conducting the anti-social behaviors to gain competitive advantages and in sports which have both been discussed extensively. The sports devaluation in burnout may undermine the sportsmanship of athletes therefore may serve as one of factors of moral disengagement in sports. Nonetheless, the connection between athlete burnout and moral disengagement in sports is yet established. Hence, the study aims to investigate whether there is the correlation between athlete burnout and moral disengagement in sports. Participants of this study are 120 collegiate athletes who specialize in seven different sports (e.g., fence, boxing, taekwondo, and etc.) with average training hours of 3.7 per day and 4.5 days per week. Athlete Burnout Questionnaire and Moral Disengagement in Sports – Short were administrated as the research instruments. Data collected were analyzed with descriptive statistics, t-test, one-way ANOVA, and step-wise regression. The results show, participants demonstrate mild to moderate burnout and moral disengagement in their perspective sports disciplines. Moreover, athletes specialize in different sports experience distinct burnout situations while there is no significant variation of moral disengagement in different sports. It is also found, moral disengagement in sports has significant and positive correlations with emotional and physical exhaustion as well as sports devaluation in athlete burnout. Furthermore, athlete burnout can positively predict moral disengagement in sports while sports devaluation plays an important role within. It can be concluded that, athlete burnout may contribute to their tendency of moral disengagement in sport. By relieving the burnout level may help improve their moral disengagement inclination in sports. The finding may contribute to the current literature regarding athlete burnout and moral disengagement in sports.

Keywords: athlete burnout, dehumanization, moral disengagement, reduced sense of accomplishment

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Authors: Sheema Shuja Khattak, Gule Saman, Imran Khan, Abdus Salam

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Image segmentation plays an important role in medical imaging applications. Therefore, accurate methods are needed for the successful segmentation of medical images for diagnosis and detection of various diseases. In this paper, we have used maximum entropy to achieve image segmentation. Maximum entropy has been calculated using Shannon, Renyi, and Tsallis entropies. This work has novelty based on the detection of skin lesion caused by the bite of a parasite called Sand Fly causing the disease is called Cutaneous Leishmaniasis.

Keywords: shannon, maximum entropy, Renyi, Tsallis entropy

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Authors: Jie Huo, Jonathan Wu

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Segmentation of anatomical structures in medical images is essential for scientific inquiry into the complex relationships between biological structure and clinical diagnosis, treatment and assessment. As a method of incorporating the prior knowledge and the anatomical structure similarity between a target image and atlases, multi-atlas segmentation has been successfully applied in segmenting a variety of medical images, including the brain, cardiac, and abdominal images. The basic idea of multi-atlas segmentation is to transfer the labels in atlases to the coordinate of the target image by matching the target patch to the atlas patch in the neighborhood. However, this technique is limited by the pairwise registration between target image and atlases. In this paper, a novel multi-atlas segmentation approach is proposed by introducing a dynamic energy model. First, the target is mapped to each atlas image by minimizing the dynamic energy function, then the segmentation of target image is generated by weighted fusion based on the energy. The method is tested on MICCAI 2012 Multi-Atlas Labeling Challenge dataset which includes 20 target images and 15 atlases images. The paper also analyzes the influence of different parameters of the dynamic energy model on the segmentation accuracy and measures the dice coefficient by using different feature terms with the energy model. The highest mean dice coefficient obtained with the proposed method is 0.861, which is competitive compared with the recently published method.

Keywords: brain MRI segmentation, dynamic energy model, multi-atlas segmentation, energy minimization

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Authors: Silvio Ricardo Rodrigues Sanches, Bianca Cogo Barbosa, Beatriz Regina Brum, Cléber Gimenez Corrêa

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To evaluate the quality of a segmentation algorithm, the authors use subjective or objective metrics. Although subjective metrics are more accurate than objective ones, objective metrics do not require user feedback to test an algorithm. Objective metrics require subjective experiments only during their development. Subjective experiments typically display to users some videos (generated from frames with segmentation errors) that simulate the environment of an application domain. This user feedback is crucial information for metric definition. In the subjective experiments applied to develop some state-of-the-art metrics used to test segmentation algorithms, the videos displayed during the experiments did not contain audio. Audio is an essential component in applications such as videoconference and augmented reality. If the audio influences the user’s perception, using only videos without audio in subjective experiments can compromise the efficiency of an objective metric generated using data from these experiments. This work aims to identify if the audio influences the user’s perception of segmentation quality in background substitution applications with audio. The proposed approach used a subjective method based on formal video quality assessment methods. The results showed that audio influences the quality of segmentation perceived by a user.

Keywords: background substitution, influence of audio, segmentation evaluation, segmentation quality

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Authors: Mohadese Motahari

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In general, we consider the phenomenon of "fandism" or extreme fandom to be an aspect of fandom for a person, a group, or a collection, which leads to extreme support for them. So, for example, we consider a fan or a "fanatic" (which literally means a "fanatical person") to be a person who is extremely interested in a certain topic or topics and has a special passion and fascination for that issue. It may also be beyond the scope of logic and normal behavior of the society. With the expansion of the media and the advancement of technology, the phenomenon of fandom also underwent many changes and not only became more intense, but a large economy was also formed alongside it, and it is becoming more and more important every day. This economy, which emerged from the past with the formation of the first media, has now taken a different form with the development of media and social networks, as well as the change in the interaction between celebrities and audiences. Earning huge amounts of money with special methods in every social network and every media is achieved through fans and fandoms. In this article, we have studied the relationship between fans and famous people with reference to the economic debates surrounding it.

Keywords: fandism, famous people, social media, new media

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Authors: Belgherbi Aicha, Hadjidj Ismahen, Bessaid Abdelhafid

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Interpretation of medical images benefits from anatomical and physiological priors to optimize computer-aided diagnosis applications. Segmentation of liver, spleen and kidneys is regarded as a major primary step in the computer-aided diagnosis of abdominal organ diseases. In this paper, a semi-automated method for medical image data is presented for the abdominal organ segmentation data using mathematical morphology. Our proposed method is based on hierarchical segmentation and watershed algorithm. In our approach, a powerful technique has been designed to suppress over-segmentation based on mosaic image and on the computation of the watershed transform. Our algorithm is currency in two parts. In the first, we seek to improve the quality of the gradient-mosaic image. In this step, we propose a method for improving the gradient-mosaic image by applying the anisotropic diffusion filter followed by the morphological filters. Thereafter, we proceed to the hierarchical segmentation of the liver, spleen and kidney. To validate the segmentation technique proposed, we have tested it on several images. Our segmentation approach is evaluated by comparing our results with the manual segmentation performed by an expert. The experimental results are described in the last part of this work.

Keywords: anisotropic diffusion filter, CT images, morphological filter, mosaic image, simultaneous organ segmentation, the watershed algorithm

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Authors: Daoudi Abdelaziz, Mahmoudi Saïd, Chikh Mohamed Amine

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This paper presents a fully automatic segmentation method of the left ventricle at End Systolic (ES) and End Diastolic (ED) in the ultrasound images by means of an implicit deformable model (level set) based on Geodesic Active Contour model. A pre-processing Gaussian smoothing stage is applied to the image, which is essential for a good segmentation. Before the segmentation phase, we locate automatically the area of the left ventricle by using a detection approach based on the Hough Transform method. Consequently, the result obtained is used to automate the initialization of the level set model. This initial curve (zero level set) deforms to search the Endocardial border in the image. On the other hand, quantitative evaluation was performed on a data set composed of 15 subjects with a comparison to ground truth (manual segmentation).

Keywords: level set method, transform Hough, Gaussian smoothing, left ventricle, ultrasound images.

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Authors: Helen Zhang

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Accurate segmentation of the airways from CT scans is crucial for early diagnosis of lung cancer. However, the existing airway segmentation algorithms often rely on thin-slice CT scans, which can be inconvenient and costly. This paper presents a set of machine learning-based 3D super-resolution algorithms along heterogeneous dimensions to improve the resolution of thicker CT scans to reduce the reliance on thin-slice scans. To evaluate the efficacy of the super-resolution algorithms, quantitative assessments using PSNR (Peak Signal to Noise Ratio) and SSIM (Structural SIMilarity index) were performed. The impact of super-resolution on airway segmentation accuracy is also studied. The proposed approach has the potential to make airway segmentation more accessible and affordable, thereby facilitating early diagnosis and treatment of lung cancer.

Keywords: 3D super-resolution, airway segmentation, thin-slice CT scans, machine learning

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Authors: L. A. Jennings

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Traditional sports media marginalizes or ignores female athletes in their coverage despite increasing numbers of female participation in professional sports. However, in venues in which women and men compete in the same event, such as fighting sports, media coverage of female athletes increases dramatically. Focusing on fighting sports, including boxing, submission wrestling, kickboxing, and Mixed Martial Arts, this paper demonstrates that inclusive venues provide an avenue for female athletes to receive equitable promotion, media coverage, and sponsorship opportunities using data from ESPN, Neilson, the Fan Report, and other emerging sources. This paper further argues that transgendered and nonbinary athletes could thrive in these environments in future sporting activities.

Keywords: sports, media, athletes, sports media, women in sports

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Authors: Ouazoul Abdelouahd, Jemjami Nadia

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The concept of well-being at work is one of today's significant challenges in maintaining quality of life and managing psycho-social risks at work. Indeed, work in the sports sector has evolved, and this exponential evolution, marked by increasing demands and psychological, physical, and social challenges, which sometimes exceed the resources of sports actors, influences their sense of well-being at work. Well-being and burnout as antagonists provide information on the quality of working life in sports. The Basic aim of this literature review is to analyze the scientific corpus dealing with the subject of well-being at work in the sports sector while exploring the link between sports burnout and well-being. The results reveal the richness of the conceptual approaches and the difficulties of implementing them. Prospects for future research have, therefore, been put forward.

Keywords: Well-being, quality of life, Burnout, ; psycho-social risk, Sports sector

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Authors: Samuel J. Ahmad, Michael Zhu, Andrew J. Kobets

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Segmentation tools continue to advance, evolving from manual methods to automated contouring technologies utilizing convolutional neural networks. These techniques have evaluated ventricular and hemorrhagic volumes in the past but may be applied in novel ways to assess posterior fossa-associated pathologies such as Chiari malformations. Herein, we summarize literature pertaining to segmentation in the context of this and other posterior fossa-based diseases such as trigeminal neuralgia, hemifacial spasm, and posterior fossa syndrome. A literature search for volumetric analysis of the posterior fossa identified 27 papers where semi-automated, automated, manual segmentation, linear measurement-based formulas, and the Cavalieri estimator were utilized. These studies produced superior data than older methods utilizing formulas for rough volumetric estimations. The most commonly used segmentation technique was semi-automated segmentation (12 studies). Manual segmentation was the second most common technique (7 studies). Automated segmentation techniques (4 studies) and the Cavalieri estimator (3 studies), a point-counting method that uses a grid of points to estimate the volume of a region, were the next most commonly used techniques. The least commonly utilized segmentation technique was linear measurement-based formulas (1 study). Semi-automated segmentation produced accurate, reproducible results. However, it is apparent that there does not exist a single semi-automated software, open source or otherwise, that has been widely applied to the posterior fossa. Fully-automated segmentation via such open source software as FSL and Freesurfer produced highly accurate posterior fossa segmentations. Various forms of segmentation have been used to assess posterior fossa pathologies and each has its advantages and disadvantages. According to our results, semi-automated segmentation is the predominant method. However, atlas-based automated segmentation is an extremely promising method that produces accurate results. Future evolution of segmentation technologies will undoubtedly yield superior results, which may be applied to posterior fossa related pathologies. Medical professionals will save time and effort analyzing large sets of data due to these advances.

Keywords: chiari, posterior fossa, segmentation, volumetric

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Authors: Ciaran Conway, Nick Jeffers, Jeff Punch

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With the current trend of miniaturisation of electronic devices, piezoelectric fans have attracted increasing interest as an alternative means of forced convection over traditional rotary solutions. Whilst there exists an abundance of research on various piezo-actuated flapping fans in the literature, the geometries of these fans all consist of a smooth rectangular cross section with thicknesses typically of the order of 100 um. The focus of these studies is primarily on variables such as frequency, amplitude, and in some cases resonance mode. As a result, the induced flow dynamics are a direct consequence of the pressure differential at the fan tip as well as the pressure-driven ‘over the top’ vortices generated at the upper and lower edges of the fan. Rough surfaces such as golf ball dimples or vortex generators on an aircraft wing have proven to be beneficial by tripping the boundary layer and energising the adjacent air flow. This paper aims to examine the influence of surface roughness on the airflow generation of a flapping fan and determine whether the induced wake can be manipulated or enhanced by energising the airflow around the fan tip. Particle Image Velocimetry (PIV) is carried out on mechanically oscillated rigid fans with various surfaces consisting of pillars, perforations and cell-like grids derived from the wing topology of natural fliers. The results of this paper may be used to inform the design of piezoelectric fans and possibly aid in understanding the complex aerodynamics inherent in flapping wing flight.

Keywords: aerodynamics, oscillating cantilevers, PIV, vortices

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Authors: Ouazoul Abdeloauhd, Jemjami Nadia

Abstract:

The concept of well-being at work is one of today's significant challenges in maintaining quality of life and managing psycho-social risks at work. Indeed, work in the sports sector has evolved, and this exponential evolution, marked by increasing demands and psychological, physical, and social challenges, which sometimes exceed the resources of sports actors, influences their sense of well-being at work. Well-being and burnout as antagonists provide information on the quality of working life in sports. The Basic aim of this literature review is to analyze the scientific corpus dealing with the subject of well-being at work in the sports sector while exploring the link between sports burnout and well-being. The results reveal the richness of the conceptual approaches and the difficulties of implementing them. Prospects for future research have, therefore, been put forward.

Keywords: well-being, burnout, quality of life, psycho-social risk, work on sports sector

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Authors: Abdolvahab Ehsani Rad, Mohd Shafry Mohd Rahim, Alireza Norouzi

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Medical image analysis is one of the great effects of computer image processing. There are several processes to analysis the medical images which the segmentation process is one of the challenging and most important step. In this paper the segmentation method proposed in order to segment the dental radiograph images. Thresholding method has been applied to simplify the images and to morphologically open binary image technique performed to eliminate the unnecessary regions on images. Furthermore, horizontal and vertical integral projection techniques used to extract the each individual tooth from radiograph images. Segmentation process has been done by applying the level set method on each extracted images. Nevertheless, the experiments results by 90% accuracy demonstrate that proposed method achieves high accuracy and promising result.

Keywords: integral production, level set method, morphological operation, segmentation

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Authors: Ernest Boateng Nuako

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This research is to find the effects of sports hooliganism on Ashanti school sports and find out some possible ways of amending or controlling them if we are to still experience them in our sporting fraternity. The researcher limited himself to the Ashanti region. The sample population was made up of officials, performances, and spectators drawn from four major second-cycle institutions and four basic schools in Ashanti. In all, 150 respondents were used, and all of them fell into the set of population, that is, performers, officials, and spectators. A structured questionnaire consisting of 29 statements where used to solicit views and opinions from the respondents on the effects of sports hooliganism in Ashanti school sports. Microsoft Office Excel tool (MS Excel) was used to analyze the response of the respondents, and the results were expressed in percentages. The study is aimed at finding out the effect sports hooliganism has on school sports festivals in Ghana with the Ashanti region as a case study and identify possible controlling measures to curb down the fast-pace effect of hooliganism on Ashanti regional schools. The research seeks to assist sports officials to identify some effects of sports hooliganism in Ashanti regional schools. It is also there to help officials to identify the influence hooliganism has on sports. This research also serves as a guide to other researchers who want to go into researching sports in the region. This research revealed that sports hooliganism has, in diverse ways, affected school sports in the region. It was also evident from the research study that sanctions, the presence of security, and other employable remedies could be used in controlling this unfortunate incident during our school sports competitions.

Keywords: officiating officials, school sports, hooliganism, spectators, performer

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Authors: Mohd Akram Shair Mohamad

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The relation to the infinite variety issues sprouting in sports or lex sportiva, like lex mercatoria in the early centuries, has now come of age and even begun a maturing process in the past thirty-five years or so. Lex sportiva now straddles sports management, sports medicine, tort, criminal law, employment contract, competition law and a host of multifarious activities related to sports. This has catapulted a host of legal issue and problems, demanding urgent legal solutions to actual or potential disputes. This paper discusses the nature and development of lex sportiva, and how it is able to resolve sports disputes. Resolving sports dispute via the tiresome, dilatory and expensive process of litigation is most unsuitable. Arbitration may not be equally a satisfactory solution. The paper strongly advocates the far the most effective and resolution friendly mode of settling sports disputes namely, mediation. In support it highlights numerous advantages mediation has to offer and with reference to many significant sports disputes which had been successfully resolved via mediation.

Keywords: alternative dispute resolution, mediation, arbitration, litigation

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Authors: Ashaawari Datta Chaudhuri

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India is a country that worships sports, especially cricket and football. This paper investigates the different intellectual property law issues that arise for sports. The paper will be a study of the legal precedents and landmark judgements in India for sports law. Some of the issues, such as brand abuse, misbranding, and infringement of IP, are very common and will be studied through case-based analysis. As a developing country, India is coping with new issues for theft of IP in different sectors. It has sportspersons of various kinds representing the country in many international events. This invites various problems in terms of recognition, credit, brand promotions, sponsorships, endorsements, and merchandising. Intellectual property is vital in many such endeavors for both brands and sportspersons. One of the major values associated with sport is ethics. Fairness, equality, and basic concern for credit are crucial in this industry. This paper will focus mostly on issues pertaining to design, trademarks, and copyrights. The contribution of this paper would be to study different problems and identify the gaps that require legislative intervention and policymaking. This is important to help boost businesses and brands associated with this industry to help occupy spaces in the market.

Keywords: copyright, design, intellectual property, Indian landscape for sports law, patents, trademark, licensing, infringement

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Authors: Joshua Doe, George Amoako

Abstract:

Purpose: In an increasingly digital world, the realm of sports fandom has extended its borders, creating a vibrant ecosystem of online communities centered around football clubs. This study ventures into the intricate interplay of motivations that drive football fans to respond to brand activism and its profound implications for brand antagonism and engagement among two of Ghana's most revered premier football clubs. Methods: A sample of 459 fervent fans from these two rival clubs were engaged through self-administered questionnaires expertly distributed via social media and online platforms. Data was analysed, using PLS-SEM. Findings: The tapestry of motivations that weave through these online football communities is as diverse as the fans themselves. It becomes apparent that fans are propelled by a spectrum of incentives. They seek education, yearn for information, revel in entertainment, embrace socialization, and fortify their self-esteem through their interactions within these digital spaces. Yet, it is the nuanced distinction in these motivations that shapes the trajectory of brand antagonism and engagement. Surprisingly, the study reveals a remarkable pattern. Football fans, despite their fierce rivalries, do not engage in brand antagonism based on educational pursuits, information-seeking endeavors, or socialization. Instead, it is motivations rooted in entertainment and self-esteem that serve as the fertile grounds for brand antagonism. Paradoxically, it is these very motivations coupled with the desire for socialization that nurture brand engagement, manifesting as active support and advocacy for their chosen club brand. Originality: Our research charters new waters by extending the boundaries of existing theories in the field. The Technology Acceptance Uses and Gratifications Theory, and Social Identity Theory all find new dimensions within the context of online brand community engagement. This not only deepens our understanding of the multifaceted world of online football fandom but also invites us to explore the implications these insights carry within the digital realm. Contribution to Practice: For marketers, our findings offer a treasure trove of actionable insights. They beckon the development of targeted content strategies that resonate with fan motivations. The implementation of brand advocacy programs, fostering opportunities for socialization, and the effective management of brand antagonism emerge as pivotal strategies. Furthermore, the utilization of data-driven insights is poised to refine consumer engagement strategies and strengthen brand affinity. Future Studies: For future studies, we advocate for longitudinal, cross-cultural, and qualitative studies that could shed further light on this topic. Comparative analyses across different types of online brand communities, an exploration of the role of brand community leaders, and inquiries into the factors that contribute to brand community dissolution all beckon the research community. Furthermore, understanding motivation-specific antagonistic behaviors and the intricate relationship between information-seeking and engagement present exciting avenues for further exploration. This study unfurls a vibrant tapestry of fan motivations, brand activism, and rivalry within online football communities. It extends a hand to scholars and marketers alike, inviting them to embark on a journey through this captivating digital realm, where passion, rivalry, and engagement harmonize to shape the world of sports fandom as we know it.

Keywords: online brand engagement, football fans, brand antagonism, motivations

Procedia PDF Downloads 48

Authors: Khalil Khan, Ikram Syed, Muhammad Ehsan Mazhar, Iran Uddin, Nasir Ahmad

Abstract:

Face parts labeling is the process of assigning class labels to each face part. A face parts labeling method (FPL) which divides a given image into its constitutes parts is proposed in this paper. A database FaceD consisting of 564 images is labeled with hand and make publically available. A supervised learning model is built through extraction of features from the training data. The testing phase is performed with two semantic segmentation methods, i.e., pixel and super-pixel based segmentation. In pixel-based segmentation class label is provided to each pixel individually. In super-pixel based method class label is assigned to super-pixel only – as a result, the same class label is given to all pixels inside a super-pixel. Pixel labeling accuracy reported with pixel and super-pixel based methods is 97.68 % and 93.45% respectively.

Keywords: face labeling, semantic segmentation, classification, face segmentation

Procedia PDF Downloads 238

Authors: Shiu-Wan Hung, Che-Wei Chang, Han-Yu Lin

Abstract:

Internet celebrities possess high visibility and a great number of fans on the Internet and are the targets that various companies are keen to collaborate with. This study investigated the para-social interaction and its antecedents among internet celebrities and their fans. The effects of Internet celebrity advertising from the perspectives of source credibility and endorser suitability were studied. This study gathered 283 valid questionnaires from people who regularly follow internet celebrities for analysis. The experimental results suggest that expertise has the most significant and direct influence on advertising. Additionally, Internet celebrities with high attractiveness can better influence the thinking of their fans and enhance homophily. However, when considering the construction of source credibility, the direct influence of attractiveness is the least significant, suggesting that the attractiveness of internet celebrities can only promote advertising via the mediating effect of homophily.

Keywords: celebrity, para-social interaction, homophily, source credibility

Procedia PDF Downloads 63