Search results for: market segmentation of sports fans

Authors: Hana Janáčková

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Housing can be sorted as basic needs of households. Purchase of acceptable ownership housing is important investments for most them. For rental housing households must consider the part of rent expenditure paid in the total household income. For this reason, financial considerations of households in this area depend on the government innervations (public administration) in housing - on housing policy. Market system of housing allocation, whether ownership or tenancy, is based on the fact that housing is a scarce good. The allocation of housing is based on demand and supply. The market system of housing can sometimes have a negative impact on some households, the market is unable to satisfy certain groups of the population that are not able or willing to accept market price. For these reasons, there is a more or less regulation of the market. Regulation is both on the demand and supply side, and the state determines the rules of behaviour for all economic entities of the housing market. This article submits results of analysis of selected regulatory interference of the state in the housing market and assesses their implications deforming the market in the selected region of the Czech Republic. The first part describes tools of supports and the second part discusses deformations and analyses their consequences on the demand side of housing market and on supply side.

Keywords: housing, housing market, microeconomic consequences, deformation

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Authors: Gunnar Oskarsson, Irena Georgsdottir

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Tourism has been growing incredibly fast during the past years, including the cruise industry, which is gaining increasing popularity among various groups of travelers. It is a challenging task for companies serving cruise ship passengers with local products and services at the point of destination to reach them in due time with information about their offerings, as well learning how to adapt their offerings and messages to the type of customers arriving on each particular occasion. Although some research has been conducted in this sphere, there is still limited knowledge about many specifics within this sector of the tourist industry. The objective of this research is to examine one of these, with the main goal of studying the segmentation of cruise passengers and to learn about marketing practices directed towards them. A qualitative research method, based on in-depth interviews, was used, as this provides an opportunity to gain insight into the participants’ perspectives. Interviews were conducted with 10 respondents from different companies in the tourist industry in Iceland, who interact with cruise passengers on a regular basis in their work environment. The main objective was to gain an understanding of what distinguishes different customer groups, or segments, in this industry, and of the marketing approaches directed towards them. The main findings reveal that participants note the strongest difference between cruise passengers of different nationalities, passengers coming on different ships (size and type), and passengers arriving at different times of the year. A drastic difference was noticed between nationalities in four main segments, American, British, Other European, and Asian customers, although some of these segments could be divided into even further sub-segments. Other important differencing factors were size and type of ships, quality or number of stars on the ship, and travelling time of the year. Companies serving cruise ship passengers, as well as the customers themselves, could benefit if the offerings of services were designed specifically for particular segments within the industry. Concerning marketing towards cruise passengers, the results indicate that it is carried out almost exclusively through the Internet using; a reliable website and, search engine optimization. Marketing is also by word-of-mouth. This research can assist practitioners by offering a deeper understanding of the approaches that may be effective in marketing local products and services to cruise ship passengers, based on their segmentation and by identifying effective ways to reach them. The research, furthermore, provides a valuable contribution to marketing knowledge for the benefit of an increasingly important market segment in a fast growing tourist industry.

Keywords: capabilities, global integration, internationalisation, SMEs

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Authors: Anas Ali

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The British administration at Malabar, the southern coastal commercial outpost in the Indian Subcontinent, faced with a series of perpetual revolts from the Mappila Muslim peasants during the last decades of the 19th and early decades of the 20th century. The control of Malabar region was a concern for the British administrators as the region was a prime centre of spice trade and plantation products. The Madras government set up a special police battalion called the Malabar Special Police in 1884 and summoned different army battalions to Malabar to crush the revolts. The setting up of army camps in the rural Malabar led to the diffusion of modern sports as the army men played different games in the garrisons and with the local people. For the imperial army men deployed in Malabar, sports acted as a viable medium to strengthen solidarity with other European settlers. They actively participated in the ‘Canterbury Week’, an annual sporting event organized by the European planters and organized tournaments among themselves. This paper would argue that, sports enabled the imperial army men, European planters and British administrators to build camaraderie that enabled them to manifest their imperial solidarity during the time of these constant revolts. Based on newspaper reports and colonial memoirs, this paper would look at how modern sports enabled the imperial army men to be ‘good in health’ and create a feeling of ‘being at home’ during this period.

Keywords: imperial army, Malabar, modern sports, mutiny

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Authors: Harold Mauricio Díaz-Vargas, Cristian Alfonso Jimenez-Castaño, David Augusto Cárdenas-Peña, Guillermo Alberto Ortiz-Gómez, Alvaro Angel Orozco-Gutierrez

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Precise identification of the nerves is a crucial task performed by anesthesiologists for an effective Peripheral Nerve Blocking (PNB). Now, anesthesiologists use ultrasound imaging equipment to guide the PNB and detect nervous structures. However, visual identification of the nerves from ultrasound images is difficult, even for trained specialists, due to artifacts and low contrast. The recent advances in deep learning make neural networks a potential tool for accurate nerve segmentation systems, so addressing the above issues from raw data. The most widely spread U-Net network yields pixel-by-pixel segmentation by encoding the input image and decoding the attained feature vector into a semantic image. This work proposes a conditioning approach and encoder pre-training to enhance the nerve segmentation of traditional U-Nets. Conditioning is achieved by the one-hot encoding of the kind of target nerve a the network input, while the pre-training considers five well-known deep networks for image classification. The proposed approach is tested in a collection of 619 US images, where the best C-UNet architecture yields an 81% Dice coefficient, outperforming the 74% of the best traditional U-Net. Results prove that pre-trained models with the conditional approach outperform their equivalent baseline by supporting learning new features and enriching the discriminant capability of the tested networks.

Keywords: nerve segmentation, U-Net, deep learning, ultrasound imaging, peripheral nerve blocking

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Authors: Kamel Malik Bensafta, Gervasio Bensafta

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The purpose of this paper is to investigate the relationship between oil prices and socks markets. The empirical analysis in this paper is conducted within the context of Multivariate GARCH models, using a transform version of the so-called BEKK parameterization. We show that mean and uncertainty of US market are transmitted to oil market and European market. We also identify an important transmission from WTI prices to Brent Prices.

Keywords: oil volatility, stock markets, MGARCH, transmission, structural break

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Authors: Ali Hamza

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Accurate segmentation of breast ultrasound images is of paramount importance in enhancing the diagnostic capabilities of breast cancer detection. This study presents an approach utilizing the U-Net architecture for segmenting breast ultrasound images aimed at improving the accuracy and reliability of mass identification within the breast tissue. The proposed method encompasses a multi-stage process. Initially, preprocessing techniques are employed to refine image quality and diminish noise interference. Subsequently, the U-Net architecture, a deep learning convolutional neural network (CNN), is employed for pixel-wise segmentation of regions of interest corresponding to potential breast masses. The U-Net's distinctive architecture, characterized by a contracting and expansive pathway, enables accurate boundary delineation and detailed feature extraction. To evaluate the effectiveness of the proposed approach, an extensive dataset of breast ultrasound images is employed, encompassing diverse cases. Quantitative performance metrics such as the Dice coefficient, Jaccard index, sensitivity, specificity, and Hausdorff distance are employed to comprehensively assess the segmentation accuracy. Comparative analyses against traditional segmentation methods showcase the superiority of the U-Net architecture in capturing intricate details and accurately segmenting breast masses. The outcomes of this study emphasize the potential of the U-Net-based segmentation approach in bolstering breast ultrasound image analysis. The method's ability to reliably pinpoint mass boundaries holds promise for aiding radiologists in precise diagnosis and treatment planning. However, further validation and integration within clinical workflows are necessary to ascertain their practical clinical utility and facilitate seamless adoption by healthcare professionals. In conclusion, leveraging the U-Net architecture for breast ultrasound image segmentation showcases a robust framework that can significantly enhance diagnostic accuracy and advance the field of breast cancer detection. This approach represents a pivotal step towards empowering medical professionals with a more potent tool for early and accurate breast cancer diagnosis.

Keywords: mage segmentation, U-Net, deep learning, breast cancer detection, diagnostic accuracy, mass identification, convolutional neural network

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Authors: Sandhya Manjunath

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The World Association for Sport Management (WASM) was established in 2012, and its mission is "to facilitate sport management research, teaching, and learning excellence and professional practice worldwide". As the field of sport management evolves, it have seen increasing globalization of not only the sport product but many educators have also internationalized courses and curriculums. Curricula should reflect globally recognized issues and disseminate specific intercultural knowledge, skills, and practices, but regional disparities still exist. For example, while India has some of the most ardent sports fans and events in the world, sport management education programs and the development of a proper curriculum in India are still in their nascent stages, especially in comparison to the United States and Europe. Using the extant literature on professionalization and institutional theory, this study aims to investigate the source of knowledge and professionalism of sports managers in India with limited sport management education programs and to subsequently develop a conceptual framework that addresses any gaps or disparities across regions. This study will contribute to WASM's (2022) mission statement of research practice worldwide, specifically to fill the existing disparities between regions. Additionally, this study may emphasize the value of higher education among professionals entering the workforce in the sport industry. Most importantly, this will be a pioneer study highlighting the social issue of limited sport management higher education programs in India and improving professional research practices. Sport management became a field of study in the 1980s, and scholars have studied its professionalization since this time. Dowling, Edwards, & Washington (2013) suggest that professionalization can be categorized into three broad categories of organizational, systemic, and occupational professionalization. However, scant research has integrated the concept of professionalization with institutional theory. A comprehensive review of the literature reveals that sports industry research is progressing in every country worldwide at its own pace. However, there is very little research evidence about the Indian sports industry and the country's limited higher education sport management programs. A growing need exists for sports scholars to pursue research in developing countries like India to develop theoretical frameworks and academic instruments to evaluate the current standards of qualified professionals in sport management, sport marketing, venue and facilities management, sport governance, and development-related activities. This study may postulate a model highlighting the value of higher education in sports management. Education stakeholders include governments, sports organizations and their representatives, educational institutions, and accrediting bodies. As these stakeholders work collaboratively in developed countries like the United States and Europe and developing countries like India, they simultaneously influence the professionalization (i.e., organizational, systemic, and occupational) of sport management education globally. The results of this quantitative study will investigate the current standards of education in India and the source of knowledge among industry professionals. Sports industry professionals will be randomly selected to complete the COSM survey on PsychData and rate their perceived knowledge and professionalism on a Likert scale. Additionally, they will answer questions involving their competencies, experience, or challenges in contributing to Indian sports management research. Multivariate regression will be used to measure the degree to which the various independent variables impact the current knowledge, contribution to research, and professionalism of India's sports industry professionals. This quantitative study will contribute to the limited academic literature available to Indian sports practitioners. Additionally, it shall synthesize knowledge from previous work on professionalism and institutional knowledge, providing a springboard for new research that will fill the existing knowledge gaps. While a further empirical investigation is warranted, our conceptualization contributes to and highlights India's burgeoning sport management industry.

Keywords: sport management, professionalism, source of knowledge, higher education, India

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Authors: Herjuno Bagus Wicaksono, Emma Almira Fauni, Salma Amelia Dina

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The Efficient Market Hypothesis (EMH) states that, in an efficient capital market, price fully reflects the information available in the market. This theory has influenced many investors behavior in trading in the stock market. Advanced researches have been conducted to test the efficiency of the stock market in particular countries. Indonesia, as one of the emerging countries, has performed substantial growth in the past years. Hence, this paper aims to examine the efficiency of Islamic stock market in Indonesia in its weak form. The daily stock price data from Indonesia Sharia Stock Index (ISSI) for the period October 2015 to October 2016 were used to do the statistical tests: Run Test and Serial Correlation Test. The results show that there is no serial correlation between the current price with the past prices and the market follows the random walk. This research concludes that Indonesia Islamic stock market is weak form efficient.

Keywords: efficient market hypothesis, Indonesia sharia stock index, random walk, weak form efficiency

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Authors: Quang Dong Dang

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This paper examines the possible effects of stock market developments by channels on income and wealth inequality. We use the Bayesian Multilevel Model with the explanatory variables of the market’s channels, such as accessibility, efficiency, and market health in six selected countries: the US, UK, Japan, Vietnam, Thailand, and Malaysia. We found that generally, the improvements in the stock market alleviate income inequality. However, stock market expansions in higher-income countries are likely to trigger income inequality. We also found that while enhancing the quality of channels of the stock market has counter-effects on wealth equality distributions, open accessibilities help reduce wealth inequality distributions within the scope of the study. In addition, the inverted U-shaped hypothesis seems not to be valid in six selected countries between the period from 2006 to 2020.

Keywords: Bayesian multilevel model, income inequality, inverted u-shaped hypothesis, stock market development, wealth inequality

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Authors: Rosa Alin Cristian

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As in any other sports branch, there is also a relationship of dependence between the motor qualities and the technical skills in the sports dance, in the sense that superior performances from a technical, artistic point of view can be obtained only on the basis of a certain level of motor qualities and of the morphological and functional indices of the organism. Starting from the premise that physical training is a basic component of the dancers' training process, determining the efficacy and efficiency of the athletes in training and competitions, its main objectives are to obtain an optimal functional capacity of the body, which is reached through a superior level of development and manifestation of the basic and specific motor qualities, through appropriate values of the morph-functional indices, all against the background of a perfect state of health. We propose in this paper to create an inventory of the motor qualities specific to the sports dance, of their forms of manifestation, to establish some methodical priorities for their development, in order to support the specialists in their attempt to approach the physical training in the most rigorous and efficient way, according to the characteristics of each age category.

Keywords: physical training, motor skills, sports dance, performance

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Authors: Sonam Kelzang

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Background: Penetrating injuries as a result of traditional sports (Archery and Khuru) are commonly seen in Bhutan. To our knowledge, there is no study carried out looking into the data of penetrating injuries due to traditional sports. Aim: This is a retrospective analysis of cases of penetrating injuries as a result of traditional sports admitted to JDWNRH over the last 3 years to draw an inference on the pattern of injury and associated morbidity and mortality. Method: Data on penetrating injuries related to traditional sports (Archery and Khuru) were collected and reviewed over the period of 3 years. Assault cases were excluded. For each year we analysed age, sex, parts of the body affected, agent of injury and whether admission was required or not. Results: Out of the total 44 victims of penetrating injury by traditional sports (Archery and Khuru) between 2013 and 2015 (average of 15 cases of penetrating injuries per year). Eighty-five percent were male and 15% were female. Their age ranged from 4 yrs to 62 years. Sixty-one percent of the victims were in the working age group of 19-58 years; 30% of the victims were referred from various district hospitals; 38% of the victims needed admission; 42 % of the victims suffered injury to the head; and 54% of the injuries were caused by Khuru. Conclusion: Penetrating injuries due to traditional sports admitted to JDWNRH, Thimphu, remained same over the three years period despite safety regulations in place. Although there were no deaths during the last three years, morbidity still remains high.

Keywords: archery, Bhutan, Khuru, darts

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Authors: B. O. Diyaolu

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The web created by sport in academics has made it difficult for it to be separated from adolescent educational development. The enthusiasm expressed towards sport by students in higher institutions is quite enormous. Primarily, academic performance should be the pride of all students but whether sports affect the academic performance of student-athletes remain an unknown fact. This study investigated the influence of sports participation on academic performance among Afe Babalola University student-athletes. Ex post facto research design was used. Two groups of students were used for the study; Student-athlete (SA) and Regular Students (RS). Purposive sampling technique was used to select 224 student-athletes, only those that are regular in the university sports team training were considered and their records (i.e. name, department, level, matriculation number, and phone number) were collected through the assistance of their coaches. For the regular students, purposive sampling technique was used to select 224 participants, only those that have no interest in sports were considered and their records were retrieved from the college registration officer. The first and second semester examination results of the two groups were compared in 10 general study courses without their knowledge, using descriptive statistics of frequency counts, mean, and standard deviation. Out of the 10 compared courses, 7 courses result showed no significant difference between students-athlete and regular students while student-athletes perform better in 3 practically oriented courses. Sports role in academics is quite significant. Exposure to sports can help build the confidence that athletes need especially when it comes to practical courses. Student-athletes can perform better in academics if the environment is friendly and not intimidating. Lecturers and coaches need to work together in order to build a well cultured and intelligent graduate.

Keywords: academic performance, regular students, sports participation, student-athlete, university sports team

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Authors: R. R. Ramsheeja, R. Sreeraj

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For view the internal structures of the human body such as liver, brain, kidney etc have a wide range of different modalities for medical images are provided nowadays. Computer Tomography is one of the most significant medical image modalities. In this paper use CT liver images for study the use of automatic computer aided techniques to calculate the volume of the liver tumor. Segmentation method is used for the detection of tumor from the CT scan is proposed. Gaussian filter is used for denoising the liver image and Adaptive Thresholding algorithm is used for segmentation. Multiple Region Of Interest(ROI) based method that may help to characteristic the feature different. It provides a significant impact on classification performance. Due to the characteristic of liver tumor lesion, inherent difficulties appear selective. For a better performance, a novel proposed system is introduced. Multiple ROI based feature selection and classification are performed. In order to obtain of relevant features for Support Vector Machine(SVM) classifier is important for better generalization performance. The proposed system helps to improve the better classification performance, reason in which we can see a significant reduction of features is used. The diagnosis of liver cancer from the computer tomography images is very difficult in nature. Early detection of liver tumor is very helpful to save the human life.

Keywords: computed tomography (CT), multiple region of interest(ROI), feature values, segmentation, SVM classification

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Authors: Pavel Chmelar, Martin Dobrovolny

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Laser projection or laser footprint detection is today widely used in many fields of robotics, measurement, or electronics. The system accuracy strictly depends on precise laser footprint detection on target objects. This article deals with the laser line detection based on the RGB segmentation and the component labeling. As a measurement device was used the developed optical rangefinder. The optical rangefinder is equipped with vertical sweeping of the laser beam and high quality camera. This system was developed mainly for automatic exploration and mapping of unknown spaces. In the first section is presented a new detection algorithm. In the second section are presented measurements results. The measurements were performed in variable light conditions in interiors. The last part of the article present achieved results and their differences between day and night measurements.

Keywords: color segmentation, component labelling, laser line detection, automatic mapping, distance measurement, vector map

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Authors: Donghee Noh, Seonhyeong Kim, Junhwan Choi, Heegon Kim, Sooho Jung, Keunho Park

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In this paper, we describe an image post-processing method to enhance the performance of the parcel segmentation method using deep learning-based aerial images conducted in previous studies. The study results were evaluated using a confusion matrix, IoU, Precision, Recall, and F1-Score. In the case of the confusion matrix, it was observed that the false positive value, which is the result of misclassification, was greatly reduced as a result of image post-processing. The average IoU was 0.9688 in the image post-processing, which is higher than the deep learning result of 0.8362, and the F1-Score was also 0.9822 in the image post-processing, which was higher than the deep learning result of 0.8850. As a result of the experiment, it was found that the proposed technique positively complements the deep learning results in segmenting the parcel of interest.

Keywords: aerial image, image process, machine vision, open field smart farm, segmentation

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Authors: Aniket Alam, Sravya Gurram

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This paper proposes a categorization of sport that is based on the system of rules that a sport must adhere to. We focus on these systems of rules to examine how a winner is produced in different sports. The rules of a sport dictate the game play and the direction it takes. We propose to break down the game play into events. At this junction, we observe two kinds of events that constitute the game play of a sport –ones that follow sequential logic and ones that do not. Our focus is pertained to sports that are comprised of sequential events. To examine these events further, to understand how a winner emerges, we take the help of finite-state automaton from the theory of computation (Automata theory). We showcase how sequential sports are eligible to be represented as finite state machines. We depict these finite state machines as state diagrams. We examine these state diagrams to observe how a team/player reaches the final states of the sport, with a special focus on one final state –the final state which determines the winner. This exercise has been carried out for the following sports: Hurdles, Track, Shot Put, Long Jump, Bowling, Badminton, Pacman and Weightlifting (Snatch). Based on our observations of how this final state of winning is achieved, we propose a categorization of sports.

Keywords: sport classification, sport modelling, ontology, automata theory

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Authors: Saba Rahimi, Ozan Oktay, Javier Alvarez-Valle, Sujeeth Bharadwaj

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Successful application of deep learning in medical image analysis necessitates unprecedented amounts of labeled training data. Unlike conventional 2D applications, radiological images can be three-dimensional (e.g., CT, MRI), consisting of many instances within each image. The problem is exacerbated when expert annotations are required for effective pixel-wise labeling, which incurs exorbitant labeling effort and cost. Active learning is an established research domain that aims to reduce labeling workload by prioritizing a subset of informative unlabeled examples to annotate. Our contribution is a cost-effective approach for U-Net 3D models that uses Monte Carlo sampling to analyze pixel-wise uncertainty. Experiments on the AAPM 2017 lung CT segmentation challenge dataset show that our proposed framework can achieve promising segmentation results by using only 42% of the training data.

Keywords: image segmentation, active learning, convolutional neural network, 3D U-Net

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Authors: Jay Raval

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Sports and physical fitness have been a vital component of our civilization. It is such a power which, motivates and inspires every individual, communities and even countries to be aware of the physical and mental health. All though, sports play vital role in the overall development of the nation, but in the developing countries such as India, this culture of sports is yet to be motivated. However, in India lack of sporting culture has held back the growth of a similar industry in the past, despite the growing awareness and interest in various different sports besides cricket. Hence, due to a lack of sporting culture, corporate investments in India’s sports have traditionally been limited to only non-profit corporate social responsibility activities and initiatives. From past couple of years, India has come up with new initiatives such as Indian Premier League (Cricket), Hockey India League, Indian Badminton League, Pro Kabaddi League, and Indian Super League (Football) which help to boost Indian sports culture and thereby increase economy of the country. Out of 29 states of India, among all of those competitive states, Gujarat is showing very rapid increase in sports participation. Khel Mahakumbh, the competition conducted for the last six years has been a giant step in this direction and covers rural and urban areas of Gujarat. The objective of the research is to address the overall development of the sports system. Sports system includes infrastructure, coaches, resources, and participants. The current existing system is not disabled friendly. This research paper highlights adequate steps in order to improve and sort out pressing issues in the sports system. Education system is highly academic-centric with a definite trend towards reducing school sports and extra-curricular sports in the Gujarat state. Constituents of this research work make an attempt to evaluate the framework of the Olympic Charter, the Sports Authority of India, the Indian Olympics Association and the National Sports Federations. It explores the areas that need to be revamped, rejuvenated and reoriented to function in an open, democratic, equitable, transparent and accountable manner. Research is based on mixed method approach. It is used for the data collection which includes the personal interviews, document analysis and the use of news article. Quality assurance is also tested by conducting the trustworthiness of the paper. Mixed method helps to strengthen the analysis part and give strong base for the discussion during the analysis.

Keywords: physical development, sports authority of India, sports policy, women empowerment

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Authors: Ahmedou Moulaye Idriss, Tfeil Yahya, Tamas Ungi, Gabor Fichtinger

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Image-guided therapy (IGT) plays a crucial role in minimally invasive procedures for liver interventions. Accurate segmentation of the liver and precise needle placement is essential for successful interventions such as needle aspiration. In this study, we propose a deep learning-based liver 3D slicer designed to enhance segmentation accuracy and facilitate needle aspiration procedures. The developed 3D slicer leverages state-of-the-art convolutional neural networks (CNNs) for automatic liver segmentation in medical images. The CNN model is trained on a diverse dataset of liver images obtained from various imaging modalities, including computed tomography (CT) and magnetic resonance imaging (MRI). The trained model demonstrates robust performance in accurately delineating liver boundaries, even in cases with anatomical variations and pathological conditions. Furthermore, the 3D slicer integrates advanced image registration techniques to ensure accurate alignment of preoperative images with real-time interventional imaging. This alignment enhances the precision of needle placement during aspiration procedures, minimizing the risk of complications and improving overall intervention outcomes. To validate the efficacy of the proposed deep learning-based 3D slicer, a comprehensive evaluation is conducted using a dataset of clinical cases. Quantitative metrics, including the Dice similarity coefficient and Hausdorff distance, are employed to assess the accuracy of liver segmentation. Additionally, the performance of the 3D slicer in guiding needle aspiration procedures is evaluated through simulated and clinical interventions. Preliminary results demonstrate the effectiveness of the developed 3D slicer in achieving accurate liver segmentation and guiding needle aspiration procedures with high precision. The integration of deep learning techniques into the IGT workflow shows great promise for enhancing the efficiency and safety of liver interventions, ultimately contributing to improved patient outcomes.

Keywords: deep learning, liver segmentation, 3D slicer, image guided therapy, needle aspiration

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Authors: Iorwase Derek Kaka’an, Peter Smolianov, Steven Dion, Christopher Schoen, Jaclyn Norberg, Charles Gabriel Iortimah

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This study examines the current state of football in Nigeria to identify the country's practices, which could be useful internationally, and to determine areas for improvement. Over 200 sources of literature on sport delivery systems in successful sports nations were analyzed to construct a globally applicable model of elite football integrated with mass participation, comprising of the following three levels: macro (socio-economic, cultural, legislative, and organizational), meso (infrastructures, personnel, and services enabling sports programs) and micro level (operations, processes, and methodologies for the development of individual athletes). The model has received scholarly validation and has shown to be a framework for program analysis that is not culturally bound. It has recently been utilized for further understanding such sports systems as US rugby, tennis, soccer, swimming, and volleyball, as well as Dutch and Russian swimming. A questionnaire was developed using the above-mentioned model. Survey questions were validated by 12 experts including academicians, executives from sports governing bodies, football coaches, and administrators. To identify best practices and determine areas for improvement of football in Nigeria, 116 coaches completed the questionnaire. Useful exemplars and possible improvements were further identified through semi-structured discussions with 10 Nigerian football administrators and experts. Finally, a content analysis of the Nigeria Football Federation's website and organizational documentation was conducted. This paper focuses on the micro level of Nigerian football delivery, particularly talent search and development as well as advanced athlete preparation and support. Results suggested that Nigeria could share such progressive practices as the provision of football programs in all schools and full-time coaches paid by governments based on the level of coach education. Nigerian football administrators and coaches could provide better football services affordable for all, where success in mass and elite sports is guided by science focused on athletes' needs. Better implemented could be international best practices such as lifelong guidelines for health and excellence of everyone and integration of fitness tests into player development and ranking as done in best Dutch, English, French, Russian, Spanish, and other European clubs; integration of educational and competitive events for elite and developing athletes as well as fans as done at the 2018 World Cup Russia; and academies with multi-stage athlete nurturing as done by Ajax in Africa as well as Barcelona FC and other top clubs expanding across the world. The methodical integration of these practices into the balanced development of mass and elite football will help contribute to international sports success as well as national health, education, crime control, and social harmony in Nigeria.

Keywords: football, high performance, mass participation, Nigeria, sport development

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Authors: Arunas Burinskas, Manuela Tvaronavičienė

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Although the new trade theories, unlike the theories of an industrial organisation, see the structure of the market and competition between enterprises through their heterogeneity according to various parameters, they do not pay any particular attention to the analysis of the market structure and its development. In this article, although we relied mainly on models developed by the scholars of new trade theory, we proposed a different approach. In our simulation model, we model market demand according to normal distribution function, while on the supply side (as it is in the new trade theory models), productivity is modeled with the Pareto distribution function. The results of the simulation show that companies with higher productivity (lower marginal costs) do not pass on all the benefits of such economies to buyers. However, even with higher marginal costs, firms can choose to offer higher value-added goods to stay in the market. In general, the structure of the market is formed quickly enough and depends on the skills available to firms.

Keywords: market, structure, simulation, heterogenous firms

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Authors: Jose Ramon Sanabria Navarro, Yahilina Silveira Perez, Valentin Molina Moreno, Digna Dionisia Perez Bravo

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The general objective of this research is to conceive a model of strategic direction for Latin American high-performance sports centers for the improvement of their results. The sample is 62 managers, 187 trainers, 2930 athletes and 62 expert researchers from centers in Cuba, Venezuela, Ecuador, Colombia and Argentina, for 3241. The measurement instrument includes 12 key variables in the process of management strategies which are consolidated with the factorial analysis and the ANOVA of a factor through the SPSS 24.0. The reliability of the scale obtained an alpha higher than 0.7 in each sample. In this sense, a model is obtained that taxes the deficiencies detected in the diagnosis, based on the needs of the members of these organizations, considering criteria and theories of the strategic direction in the improvement of the organizational results. The validation of the model for high performance sports centers of the countries analyzed aims to develop joint strategies to generate synergies in their operational mode, which leads to enhance the sports organization.

Keywords: sports organization, information management, decision making, control

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Authors: Zachary Smith, Riette Bloomfield, Taylor Dukate, Joshua Halterman, Noah Phillips

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College students have stressful lives, classes, work, and home life; it all adds up to anxiety and stress. Most students can manage the stress, but some can’t and need help. Mental health issues are on the rise among college-age students, which could lead to other health issues, depression, or even suicidal thoughts. There needs to be an outlet for these students, and one suggestion is participating in sports or exercise/recreation activities. “Strong body, strong mind” is a concept that has been researched for many decades now. While that has been preached, depression and anxiety have still been at an all-time high in college students within the last five years. College students are expected to stay on top of their academic coursework, obtain and keep relationships, adjust to living independently, and economic strain. As p oor mental health becomes inherent, struggles academically, dropping out of school, becoming involved in immoral situations, or as far as committing suicide, can be seen shortly after. This research proposal examines the positive impact of sports on students' mental health in post-secondary education programs. The study aims to investigate how participation in college sports can alleviate stress, anxiety, and depression, improve mood and focus, and contribute to better academic performance. With the increasing prevalence of mental health issues among college students and the growing emphasis on mental health awareness, this research is significant for understanding and managing collegiate sports programs. Overall, sports help with mental and physical health for all ages.

Keywords: mental health, sports, college students, recreation programs

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Authors: Ana Londral, Burcu Demiray, Marcus Cheetham

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Speech recording is a methodology used in many different studies related to cognitive and behaviour research. Modern advances in digital equipment brought the possibility of continuously recording hours of speech in naturalistic environments and building rich sets of sound files. Speech analysis can then extract from these files multiple features for different scopes of research in Language and Communication. However, tools for analysing a large set of sound files and automatically extract relevant features from these files are often inaccessible to researchers that are not familiar with programming languages. Manual analysis is a common alternative, with a high time and efficiency cost. In the analysis of long sound files, the first step is the voice segmentation, i.e. to detect and label segments containing speech. We present a comprehensive methodology aiming to support researchers on voice segmentation, as the first step for data analysis of a big set of sound files. Praat, an open source software, is suggested as a tool to run a voice detection algorithm, label segments and files and extract other quantitative features on a structure of folders containing a large number of sound files. We present the validation of our methodology with a set of 5000 sound files that were collected in the daily life of a group of voluntary participants with age over 65. A smartphone device was used to collect sound using the Electronically Activated Recorder (EAR): an app programmed to record 30-second sound samples that were randomly distributed throughout the day. Results demonstrated that automatic segmentation and labelling of files containing speech segments was 74% faster when compared to a manual analysis performed with two independent coders. Furthermore, the methodology presented allows manual adjustments of voiced segments with visualisation of the sound signal and the automatic extraction of quantitative information on speech. In conclusion, we propose a comprehensive methodology for voice segmentation, to be used by researchers that have to work with large sets of sound files and are not familiar with programming tools.

Keywords: automatic speech analysis, behavior analysis, naturalistic environments, voice segmentation

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Authors: Cem Ozatalay, Senem Ornek

Abstract:

The Artprice Contemporary Art Market Annual Report 2014 notices that Istanbul, with its art market volume of $3.6 million has become the first city of the Middle East and North Africa region and the 14th city of the World. Indeed, the period 2004–2014 has been significant in terms of the growth of the art market, during which the majority of contemporary art galleries and museums in Istanbul was inaugurated. This boom means that with the joining of new agents, the structure of the art market has dramatically changed. To use Nathalie Heinich’s terminology, in the current art field, three art genres – namely classical art, modern art and contemporary art – coexist, but in the case of Istanbul, such as many art cities in the world, the latter genre has become increasingly dominant. This presentation aims to show how the power shifts away from the classical art agents to contemporary art agents, and the effects produced by the conflicts between the old and new agents of current art field. Based on the data obtained from an ongoing field research in Istanbul among the art market agents such as art dealers, curators, art critics and artists, it will be shown that even if the agents of different art genres are in conflict with each other, there is, at the same time, a continuum between the three art worlds.

Keywords: contemporary art market, economic sociology of art, Istanbul art market, structure of the art field in Istanbul

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Authors: Patrik Jangl, Milan Mikuláštík

Abstract:

The objective of the paper is to measure and compare market orientation of Swiss and Czech banks, as well as examine statistically the degree of influence it has on competitiveness of the institutions. The analysis of market orientation is based on the collecting, analysis and correct interpretation of the data. Descriptive analysis of market orientation describe current situation. Research of relation of competitiveness and market orientation in the sector of big international banks is suggested with the expectation of existence of a strong relationship. Partially, the work served as reconfirmation of suitability of classic methodologies to measurement of banks’ market orientation. Two types of data were gathered. Firstly, by measuring subjectively perceived market orientation of a company and secondly, by quantifying its competitiveness. All data were collected from a sample of small, mid-sized and large banks. We used numerical secondary character data from the international statistical financial Bureau Van Dijk’s BANKSCOPE database. Statistical analysis led to the following results. Assuming classical market orientation measures to be scientifically justified, Czech banks are statistically less market-oriented than Swiss banks. Secondly, among small Swiss banks, which are not broadly internationally active, small relationship exist between market orientation measures and market share based competitiveness measures. Thirdly, among all Swiss banks, a strong relationship exists between market orientation measures and market share based competitiveness measures. Above results imply existence of a strong relation of this measure in sector of big international banks. A strong statistical relationship has been proven to exist between market orientation measures and equity/total assets ratio in Switzerland.

Keywords: market orientation, competitiveness, marketing strategy, measurement of market orientation, relation between market orientation and competitiveness, banking sector

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Authors: Nkwanyang L. Takem, Christopher M. Agyingi

Abstract:

Background and aim: An integrated interpretation of wireline logs and lithology of two selected wells (KF-1 and KF-2) of Kribi oil field within the southeastern offshore Douala/Kribi Campo Basin was carried out for sequence stratigraphic analysis of sediments penetrated by the wells. Methods: The stratigraphic units within the wells were subdivided into depositional sequences using characteristic well log patterns that were deposited between Tertiary Miocene to lower Cretaceous. Results: Nine (9) and eight (8) depositional sequences were identified respectively for KF-1 and KF-2. The sequences comprise LST (progradational packages), TSTs (retrogradational packages) and HSTs (aggradational packages), which reflect depositional systems deposited during different phases of base-level changes. The (LST) consists of Basin Floor Fans (BFF), Slope Fans and Channel Sands deposited when sea level was low and accommodation space lower than rate of sediment influx. TST consists of retrogradational marine shales deposited during high relative sea levels and when accommodation space was higher than rate of sediment influx. HST consisted of shoreface sands displaying mostly aggradational to progradational stacking patterns. Conclusion: The rapid facies changes between successive systems tracts provide potential stratigraphic traps. Reservoir stratification and continuity vary greatly between systems tracts and this enhanced development of stratigraphic traps in the area. Basin floor fans comprise sandstone of good reservoir quality, thus huge accumulation of HC can be trapped in this reservoirs.

Keywords: Douala-Kribi-Campo Basin, reservoirs, sequence strastigraphyy, system tracks

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Authors: Jiameng Wang, Yunfei Yin, Xiyu Deng

Abstract:

Parallel optimization is one of the important research topics of data mining at this stage. Taking Classification and Regression Tree (CART) parallelization as an example, this paper proposes a parallel data mining algorithm based on SSP-OGini-PCCP. Aiming at the problem of choosing the best CART segmentation point, this paper designs an S-SP model without data association; and in order to calculate the Gini index efficiently, a parallel OGini calculation method is designed. In addition, in order to improve the efficiency of the pruning algorithm, a synchronous PCCP pruning strategy is proposed in this paper. In this paper, the optimal segmentation calculation, Gini index calculation, and pruning algorithm are studied in depth. These are important components of parallel data mining. By constructing a distributed cluster simulation system based on SPARK, data mining methods based on SSP-OGini-PCCP are tested. Experimental results show that this method can increase the search efficiency of the best segmentation point by an average of 89%, increase the search efficiency of the Gini segmentation index by 3853%, and increase the pruning efficiency by 146% on average; and as the size of the data set increases, the performance of the algorithm remains stable, which meets the requirements of contemporary massive data processing.

Keywords: classification, Gini index, parallel data mining, pruning ahead

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Authors: Plessen Mogens Graf

Abstract:

Within the context of multivariate time series segmentation, this paper proposes a method inspired by a posteriori optimal trading. After a normalization step, time series are treated channelwise as surrogate stock prices that can be traded optimally a posteriori in a virtual portfolio holding either stock or cash. Linear transaction costs are interpreted as hyperparameters for noise filtering. Trading signals, as well as trading signals obtained on the reversed time series, are used for unsupervised channelwise labeling before a consensus over all channels is reached that determines the final segmentation time instants. The method is model-free such that no model prescriptions for segments are made. Benefits of proposed approach include simplicity, computational efficiency, and adaptability to a wide range of different shapes of time series. Performance is demonstrated on synthetic and real-world data, including a large-scale dataset comprising a multivariate time series of dimension 1000 and length 2709. Proposed method is compared to a popular model-based bottom-up approach fitting piecewise affine models and to a recent model-based top-down approach fitting Gaussian models and found to be consistently faster while producing more intuitive results in the sense of segmenting time series at peaks and valleys.

Keywords: time series segmentation, model-free, trading-inspired, multivariate data

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Authors: Alastair Hales, Xi Jiang, Siming Zhang

Abstract:

Numerical methods are used to generate vortices in a domain. Through considered design, two counter-rotating vortices may interact and effectively drive one another downstream. This phenomenon is comparable to the vortex interaction that occurs in a region immediately downstream from two counter-oscillating piezoelectric (PE) fan blades. PE fans are small blades clamped at one end and driven to oscillate at their first natural frequency by an extremely low powered actuator. In operation, the high oscillation amplitude and frequency generate sufficient blade tip speed through the surrounding air to create downstream air flow. PE fans are considered an ideal solution for low power hot spot cooling in a range of small electronic devices, but a single blade does not typically induce enough air flow to be considered a direct alternative to conventional air movers, such as axial fans. The development of face-to-face PE fan arrays containing multiple blades oscillating in counter-phase to one another is essential for expanding the range of potential PE fan applications regarding the cooling of power electronics. Even in an unoptimised state, these arrays are capable of moving air volumes comparable to axial fans with less than 50% of the power demand. Replicating the airflow generated by face-to-face PE fan arrays without including the actual blades in the model reduces the process’s computational demands and enhances the rate of innovation and development in the field. Vortices are generated at a defined inlet using a time-dependent velocity profile function, which pulsates the inlet air velocity magnitude. This induces vortex generation in the considered domain, and these vortices are shown to separate and propagate downstream in a regular manner. The generation and propagation of a single vortex are compared to an equivalent vortex generated from a PE fan blade in a previous experimental investigation. Vortex separation is found to be accurately replicated in the present numerical model. Additionally, the downstream trajectory of the vortices’ centres vary by just 10.5%, and size and strength of the vortices differ by a maximum of 10.6%. Through non-dimensionalisation, the numerical method is shown to be valid for PE fan blades with differing parameters to the specific case investigated. The thorough validation methods presented verify that the numerical model may be used to replicate vortex formation from an oscillating PE fans blade. An investigation is carried out to evaluate the effects of varying the distance between two PE fan blade, pitch. At small pitch, the vorticity in the domain is maximised, along with turbulence in the near vicinity of the inlet zones. It is proposed that face-to-face PE fan arrays, oscillating in counter-phase, should have a minimal pitch to optimally cool nearby heat sources. On the other hand, downstream airflow is maximised at a larger pitch, where the vortices can fully form and effectively drive one another downstream. As such, this should be implemented when bulk airflow generation is the desired result.

Keywords: piezoelectric fans, low energy cooling, vortex formation, computational fluid dynamics

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