Search results for: football analytics

Authors: Mani Venkatesh, Catarina Delgado, Purvishkumar Patel

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The sustainable supply chain is gaining popularity among practitioners because of increased environmental degradation and stakeholder awareness. On the other hand supply chain, risk management is very crucial for the practitioners as it potentially disrupts supply chain operations. Prediction and addressing the risk caused by social issues in the supply chain is paramount importance to the sustainable enterprise. More recently, the usage of Big data analytics for forecasting business trends has been gaining momentum among professionals. The aim of the research is to explore the application of big data, predictive analytics in successfully mitigating supply chain social risk and demonstrate how such mitigation can help in achieving sustainability (environmental, economic & social). The method involves the identification and validation of social issues in the supply chain by an expert panel and survey. Later, we used a case study to illustrate the application of big data in the successful identification and mitigation of social issues in the supply chain. Our result shows that the company can predict various social issues through big data, predictive analytics and mitigate the social risk. We also discuss the implication of this research to the body of knowledge and practice.

Keywords: big data, sustainability, supply chain social sustainability, social risk, case study

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Authors: Vikram Singh

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The objective of the study was to study the effectiveness of common yoga protocol on reaction time (simple visual reaction time-SVRT measured in milliseconds/seconds) of male football players in the age group of 15 to 21 years. The 40 boys were randomly assigned into two groups i.e. control and experimental. SVRT for both the groups were measured on day-1 and post intervention (common yoga protocol here) was measured after 45 days of training to the experimental group only. One way ANOVA (Univariate analysis) and Independent t-test using SPSS 23 statistical package was applied to get and analyze the results. There was a significant difference after 45 days of yoga protocol in simple visual reaction time of experimental group (p = .032), t (33.05) = 3.881, p = .000 (two-tailed). Null hypothesis (that there would be no post measurement differences in reaction times of control and experimental groups) was rejected. Where p<.05. Therefore alternate hypothesis was accepted.

Keywords: footballers, t-test, yoga protocol, reaction time

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Authors: Thuan Nguyen

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In the present time, data to a data-driven knowledge-based economy is the same as oil to the industrial age hundreds of years ago. Data is everywhere in vast volumes! Big data analytics is expected to help firms not only efficiently improve performance but also completely transform how they should run their business. However, employing the emergent technology successfully is not easy, and assessing the roles of big data in improving firm performance is even much harder. There was a lack of studies that have examined the impacts of big data analytics on organizational performance. This study aimed to fill the gap. The present study suggested using firms’ intellectual capital as a proxy for big data in evaluating its impact on organizational performance. The present study employed the Value Added Intellectual Coefficient method to measure firm intellectual capital, via its three main components: human capital efficiency, structural capital efficiency, and capital employed efficiency, and then used the structural equation modeling technique to model the data and test the models. The financial fundamental and market data of 100 randomly selected publicly listed firms were collected. The results of the tests showed that only human capital efficiency had a significant positive impact on firm profitability, which highlighted the prominent human role in the impact of big data technology.

Keywords: big data, big data analytics, intellectual capital, organizational performance, value added intellectual coefficient

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Authors: Gianluca Del Rossi

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Sub-concussive impacts occur frequently in collision sports such as American tackle football. Sub-concussive level impacts are defined as hits to the head that do not result in the clinical manifestation of concussion injury. Presently, there is limited information known about the short-term effects of repeated sub-concussive blows to the head. Therefore, the purpose of this investigation was to determine if standard clinical measures could detect acute impairments in neurologic function resulting from the accumulation of sub-concussive impacts throughout a season of high school American tackle football. Simple reaction time using the ruler-drop test, and oculomotor performance using the King-Devick (KD) test, were assessed in 15 athletes prior to the start of the athletic season, then repeated each week of the season, and once following its completion. The mean reaction times and fastest KD scores that were recorded or calculated from each study participant and from each test session were analyzed to assess for change in reaction time and oculomotor performance over the course of the American tackle football season. Analyses of KD data revealed improvements in oculomotor performance from baseline measurements (i.e., decreased time), with most weekly comparisons to baseline being significantly different. Statistical tests performed on the mean reaction times obtained via the ruler-drop test throughout the season revealed statistically significant declines (i.e., increased time) between baseline and weeks 3, 4, 10, and 12 of the athletic season. The inconsistent and contrasting findings between KD data and reaction time demonstrate the need to identify more robust clinical measures to definitively assess if repeated sub-concussive impacts to the head are acutely detrimental to patients.

Keywords: head injury, mTBI and sport, subclinical head trauma, sub-concussive impacts

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Authors: Ho-Won Jung, Donghun Lee, Hyung-Jin Kim

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Predictive analytics (data analysis) uses a subset of measurements (the features, predictor, or independent variable) to predict another measurement (the outcome, target, or dependent variable) on a single person or unit. It applies empirical methods in statistics, operations research, and machine learning to predict the future, or otherwise unknown events or outcome on a single or person or unit, based on patterns in data. Most analyses of metabolic syndrome are not predictive analytics but statistical explanatory studies that build a proposed model (theory building) and then validate metabolic syndrome predictors hypothesized (theory testing). A proposed theoretical model forms with causal hypotheses that specify how and why certain empirical phenomena occur. Predictive analytics and explanatory modeling have their own territories in analysis. However, predictive analytics can perform vital roles in explanatory studies, i.e., scientific activities such as theory building, theory testing, and relevance assessment. In the context, this study is to demonstrate how to use our predictive analytics to support theory building (i.e., hypothesis generation). For the purpose, this study utilized a big data predictive analytics platform TM based on a co-occurrence graph. The co-occurrence graph is depicted with nodes (e.g., items in a basket) and arcs (direct connections between two nodes), where items in a basket are fully connected. A cluster is a collection of fully connected items, where the specific group of items has co-occurred in several rows in a data set. Clusters can be ranked using importance metrics, such as node size (number of items), frequency, surprise (observed frequency vs. expected), among others. The size of a graph can be represented by the numbers of nodes and arcs. Since the size of a co-occurrence graph does not depend directly on the number of observations (transactions), huge amounts of transactions can be represented and processed efficiently. For a demonstration, a total of 13,254 metabolic syndrome training data is plugged into the analytics platform to generate rules (potential hypotheses). Each observation includes 31 predictors, for example, associated with sociodemographic, habits, and activities. Some are intentionally included to get predictive analytics insights on variable selection such as cancer examination, house type, and vaccination. The platform automatically generates plausible hypotheses (rules) without statistical modeling. Then the rules are validated with an external testing dataset including 4,090 observations. Results as a kind of inductive reasoning show potential hypotheses extracted as a set of association rules. Most statistical models generate just one estimated equation. On the other hand, a set of rules (many estimated equations from a statistical perspective) in this study may imply heterogeneity in a population (i.e., different subpopulations with unique features are aggregated). Next step of theory development, i.e., theory testing, statistically tests whether a proposed theoretical model is a plausible explanation of a phenomenon interested in. If hypotheses generated are tested statistically with several thousand observations, most of the variables will become significant as the p-values approach zero. Thus, theory validation needs statistical methods utilizing a part of observations such as bootstrap resampling with an appropriate sample size.

Keywords: explanatory modeling, metabolic syndrome, predictive analytics, theory building

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Authors: A. Giani

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The current pedagogical culture recognizes an educational scope within the sports practices. It is widely accepted, in the pedagogical culture, that thanks to the acquisition and development of motor skills, it is also possible to exercise abilities that concern the way of facing and managing the difficulties of everyday life. Sport is a peculiar educational environment: the children have the opportunity to discover the possibilities of their body, to correlate with their peers, and to learn how to manage the rules and the relationship with authorities, such as coaches. Educational aspects of the sport concern both non-formal and formal educational environments. Coaches play a critical role in an agonistic sphere: exactly like the competencies developed by the children, coaches have to work on their skills to properly set up the educational scene. Facing these new educational tasks - which are not new per se, but new because they are brought back to awareness - a few questions arise: does the coach have adequate preparation? Is the training of the coach in this specific area appropriate? This contribution aims to explore the issue in depth by focusing on the reality of the Football School. Starting from a possible sense of pedagogical inadequacy detected during a series of meetings with several football clubs in Piedmont (Italy), there have been highlighted some important educational needs within the professional training of sports coaches. It is indeed necessary for the coach to know the processes underlying the educational relationship in order to better understand the centrality of the assessment during the educational intervention and to be able to manage the asymmetry in the coach-athlete relationship. In order to provide a response to these pedagogical needs, a formative plan has been designed to allow both an in-depth study of educational issues and a correct self-evaluation of certain pedagogical skills’ control levels, led by the coach. This plan has been based on particular practices, the Educational Practices of Pre-test (EPP), a specific version of community practices designed for the extracurricular activities. The above-mentioned practices realized through the use of texts meant as pre-tests, promoted a reflection within the group of coaches: they set up real and plausible sports experiences - in particular football, triggering a reflection about the relationship’s object, spaces, and methods. The characteristic aspect of pre-tests is that it is impossible to anticipate the reflection as it is necessarily connected to the personal experience and sensitivity, requiring a strong interest and involvement by participants: situations must be considered by the coaches as possible settings in which they could be found on the field.

Keywords: relational needs, values, responsibility, self-evaluation

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Authors: A. D. Tayal

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The energy industry is undergoing significant disruption. This research outlines that, whilst challenging; this disruption is also an emerging opportunity for electricity utilities. One such opportunity is leveraging the developments in data analytics and machine learning. As the uptake of renewable energy technologies and complimentary control systems increases, electricity grids will likely transform towards dense microgrids with high penetration of renewable generation sources, rich in network and customer data, and linked through intelligent, wireless communications. Data digitisation and analytics have already impacted numerous industries, and its influence on the energy sector is growing, as computational capabilities increase to manage big data, and as machines develop algorithms to solve the energy challenges of the future. The objective of this paper is to address how far the uptake of renewable technologies can go given the constraints of existing grid infrastructure and provides a qualitative assessment of how higher levels of renewable energy penetration can be facilitated by incorporating even broader technological advances in the fields of data analytics and machine learning. Western Australia is used as a contextualised case study, given its abundance and diverse renewable resources (solar, wind, biomass, and wave) and isolated networks, making a high penetration of renewables a feasible target for policy makers over coming decades.

Keywords: data, innovation, renewable, solar

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Authors: Siti Azrina B. A. Aziz, Siti Hafizah A. Hamid

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New approaches to analyze and visualize data stream in real-time basis is important in making a prompt decision by the decision maker. Financial market trading and surveillance, large-scale emergency response and crowd control are some example scenarios that require real-time analytic and data visualization. This situation has led to the development of techniques and tools that support humans in analyzing the source data. With the emergence of Big Data and social media, new techniques and tools are required in order to process the streaming data. Today, ranges of tools which implement some of these functionalities are available. In this paper, we present chronological evolution evaluation of technologies for supporting of real-time analytic and visualization of the data stream. Based on the past research papers published from 2002 to 2014, we gathered the general information, main techniques, challenges and open issues. The techniques for streaming text visualization are identified based on Text Visualization Browser in chronological order. This paper aims to review the evolution of streaming text visualization techniques and tools, as well as to discuss the problems and challenges for each of identified tools.

Keywords: information visualization, visual analytics, text mining, visual text analytics tools, big data visualization

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Authors: M. Graus, K. Westhoff, X. Xu

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The climate change causes a change in all aspects of society. While the expansion of renewable energies proceeds, industry could not be convinced based on general studies about the potential of demand side management to reinforce smart grid considerations in their operational business. In this article, a procedure model for a case-specific data-driven decision support for industrial energy management based on a holistic data analytics approach is presented. The model is executed on the example of the strategic decision problem, to integrate the aspect of renewable energies into industrial energy management. This question is induced due to considerations of changing the electricity contract model from a standard rate to volatile energy prices corresponding to the energy spot market which is increasingly more affected by renewable energies. The procedure model corresponds to a data analytics process consisting on a data model, analysis, simulation and optimization step. This procedure will help to quantify the potentials of sustainable production concepts based on the data from a factory. The model is validated with data from a printer in analogy to a simple production machine. The overall goal is to establish smart grid principles for industry via the transformation from knowledge-driven to data-driven decisions within manufacturing companies.

Keywords: data analytics, green production, industrial energy management, optimization, renewable energies, simulation

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Authors: Haritha Saranga

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Service quality has become an important driver of competition in manufacturing industries of late, as many products are being sold in conjunction with service offerings. With increase in computational power and data capture capabilities, it has become possible to analyze and estimate various aspects of service quality at the granular level and determine their impact on business performance. In the current study context, dealer level, model-wise warranty data from one of the top two-wheeler manufacturers in India is used to estimate service quality of individual dealers and its impact on warranty related costs and sales performance. We collected primary data on warranty costs, number of complaints, monthly sales, type of quality upgrades, etc. from the two-wheeler automaker. In addition, we gathered secondary data on various regions in India, such as petrol and diesel prices, geographic and climatic conditions of various regions where the dealers are located, to control for customer usage patterns. We analyze this primary and secondary data with the help of a variety of analytics tools such as Auto-Regressive Integrated Moving Average (ARIMA), Seasonal ARIMA and ARIMAX. Study results, after controlling for a variety of factors, such as size, age, region of the dealership, and customer usage pattern, show that service quality does influence sales of the products in a significant manner. A more nuanced analysis reveals the dynamics between product quality and service quality, and how their interaction affects sales performance in the Indian two-wheeler industry context. We also provide various managerial insights using descriptive analytics and build a model that can provide sales projections using a variety of forecasting techniques.

Keywords: service quality, product quality, automobile industry, business analytics, auto-regressive integrated moving average

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Authors: Zineb Jibraili, Said Ouhadi, Jorge Arana

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Introduction: Organizational performance is recognized by some theorists as one-dimensional concept, and by others as multidimensional. This concept, which is already difficult to apply in traditional companies, is even harder to identify, to measure and to manage when voluntary organizations are concerned, essentially because of the complexity of that form of organizations such as sport clubs who are characterized by the multiple goals and multiple constituencies. Indeed, the new culture of professionalization and modernization around organizational performance emerges new pressures from the state, sponsors, members and other stakeholders which have required these sport organizations to become more performance oriented, or to build their capacity in order to better manage their organizational performance. The evaluation of performance can be made by evaluating the input (e.g. available resources), throughput (e.g. processing of the input) and output (e.g. goals achieved) of the organization. In non-profit organizations (NPOs), questions of performance have become increasingly important in the world of practice. To our knowledge, most of studies used the same methods to evaluate the performance in NPSOs, but no recent study has proposed a club-specific model. Based on a review of the studies that specifically addressed the organizational performance (and effectiveness) of NPSOs at operational level, the present paper aims to provide a multidimensional framework in order to understand, analyse and measure organizational performance of sport clubs. This paper combines all dimensions founded in literature and chooses the most suited of them to our model that we will develop in Moroccan sport clubs case. Method: We propose to implicate our unified model of evaluating organizational performance that takes into account all the limitations found in the literature. On a sample of Moroccan sport clubs ‘Football, Basketball, Handball and Volleyball’, for this purpose we use a qualitative study. The sample of our study comprises data from sport clubs (football, basketball, handball, volleyball) participating on the first division of the professional football league over the period from 2011 to 2016. Each football club had to meet some specific criteria in order to be included in the sample: 1. Each club must have full financial data published in their annual financial statements, audited by an independent chartered accountant. 2. Each club must have sufficient data. Regarding their sport and financial performance. 3. Each club must have participated at least once in the 1st division of the professional football league. Result: The study showed that the dimensions that constitute the model exist in the field with some small modifications. The correlations between the different dimensions are positive. Discussion: The aim of this study is to test the unified model emerged from earlier and narrower approaches for Moroccan case. Using the input-throughput-output model for the sketch of efficiency, it was possible to identify and define five dimensions of organizational effectiveness applied to this field of study.

Keywords: organisational performance, model multidimensional, evaluation organizational performance, sport clubs

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Authors: Alok Kumar, Raviraj Patil

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The ability to respond to an incident of a disastrous event in a vulnerable area is very crucial an aspect of emergency management. The ability to constantly predict the likelihood of an event along with its severity in an area and react to those significant events which are likely to have a high impact allows the authorities to respond by allocating resources optimally in a timely manner. It provides for measuring, monitoring, and modeling facilities that integrate underlying systems into one solution to improve operational efficiency, planning, and coordination. We were particularly involved in this innovative incubation work on the current state of research and development in collaboration. technologies & systems for a disaster.

Keywords: predictive analytics, advanced analytics, area flood likelihood model, area flood severity model, level of impact model, mortality score, economic loss score, resource allocation, crew allocation

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Authors: Donna Woodhouse, Beth Fielding-Lloyd, Ruth Sequerra

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This paper explores the structure and culture of the English Football Association (FA) the governing body of soccer in England, in relation to the development of the FA Women’s Super League (WSL). In doing so, it examines the organisation’s journey from banning the sport in 1921 to establishing the country’s first semi professional female soccer league in 2011. As the FA has a virtual monopoly on defining the structures of the elite game, we attempted to understand its behaviour in the context of broader issues of power, control and resistance by giving voice to the experiences of those affected by its decisions. Observations were carried out at 39 matches over three years. Semi structured interviews with 17 people involved in the women’s game, identified via snowball sampling, were also carried out. Transcripts accompanied detailed field notes and were inductively coded to identify themes. What emerged was the governing body’s desire to create a new product, jettisoning the long history of the women’s game in order to shape and control the sport in a way it is no longer able to, with the elite male club game. The League created was also shaped by traditional conceptualisations of gender, in terms of the portrayal of its style of play and target audience, setting increased participation and spectatorship targets as measures of ‘success’. The national governing body has demonstrated pseudo inclusion and a lack of enthusiasm for the implementation of equity reforms, driven by a belief that the organisation is already representative, fair and accessible. Despite a consistent external pressure, the Football Association is still dominated at its most senior levels by males. Via claiming to hold a monopoly on expertise around the sport, maintaining complex committee structures and procedures, and with membership rules rooted in the amateur game, it remains a deeply gendered organisation, resistant to structural and cultural change. In WSL, the FA's structure and culture have created a franchise over which it retains almost complete control, dictating the terms of conditions of entry and marginalising alternative voices. The organisation presents a feminised version of both play and spectatorship, portraying the sport as a distinct, and lesser, version of soccer.

Keywords: football association, organisational culture, soccer, women’s super league

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Authors: Joel Rookwood

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Sports mega events have become increasingly significant in sporting, political and economic terms, with analysis often focusing on issues including resource expenditure, development, legacy and sustainability. Transnational tournaments can inspire interest from a variety of demographics, and the operational management of such events can involve contributions from a range of personnel. In addition to television audiences events also attract attending spectators, and in football contexts the temporary migration of fans from potentially rival nations and teams can present event organising committees and security personnel with various challenges in relation to crowd management. The behaviour, interaction and control of supporters has previously led to incidents of disorder and hooliganism, with damage to property as well as injuries and deaths proving significant consequences. The Heysel tragedy at the 1985 European Cup final in Brussels is a notable example, where 39 fans died following crowd disorder and mismanagement. Football disasters and disorder, particularly in the context of international competition, have inspired responses from police, law makers, event organisers, clubs and associations, including stadium improvements, legislative developments and crowd management practice to improve the effectiveness of spectator safety. The growth and internationalisation of fandom and developments in event management and tourism have seen various responses to the evolving challenges associated with hosting large numbers of visiting spectators at mega events. In football contexts ‘fan parks’ are a notable example. Since the first widespread introduction in European football competitions at the 2006 World Cup finals in Germany, these facilities have become a staple element of such mega events. This qualitative, longitudinal, multi-continent research draws on extensive semi-structured interview and observation data. As a frame of reference, this work considers football events staged before and after the development of fan parks. Research was undertaken at four World Cup finals (Japan 2002, Germany 2006, South Africa 2010 and Brazil 2014), four European Championships (Portugal 2004, Switzerland/Austria 2008, Poland/Ukraine 2012 and France 2016), four other confederation tournaments (Ghana 2008, Qatar 2011, USA 2011 and Chile 2015), and four European club finals (Istanbul 2005, Athens 2007, Rome 2009 and Basle 2016). This work found that these parks are typically temporarily erected, specifically located zones where supporters congregate together irrespective of allegiances to watch matches on large screens, and partake in other forms of organised on-site entertainment. Such facilities can also allow organisers to control the behaviour, confine the movement and monitor the alcohol consumption of supporters. This represents a notable shift in policy from previous football tournaments, when the widely assumed causal link between alcohol and hooliganism which frequently shaped legislative and police responses to disorder, also dissuaded some authorities from permitting fans to consume alcohol in and around stadia. It also reflects changing attitudes towards modern football fans. The work also found that in certain contexts supporters have increasingly engaged with such provision which impacts fan behaviour, but that this is relative to factors including location, facilities, management and security.

Keywords: event, facility, fan, management, park

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Authors: D. Pogliana, A. Maso, N. Milani, D. Panzin, S. Rivaroli, J. Konin

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This case aims to identify the role of movement quality during the final stage of return to sport (RTS) in a male amateur football player 13 years old after passing the acute phase of the bilateral Osgood-Schlatter disease (OSD). The patient, after a year from passing the acute phase of OSD with the abstention of physical activity, reports bilateral anterior knee pain at the beginning of the football sport activity. Interventions: After the orthopedist check, who recommended physiotherapy sessions for the correction of motor patterns and the isometric reinforcement of the muscles of the quadriceps, the rehabilitation intervention was developed in 7 weeks through 14 sessions of neuro-motor training (NMT) with a frequency of two weekly sessions and six sessions of muscle-strengthening with a frequency of one weekly session. The sessions of NMT were carried out through free body exercises (or with overloads) with visual bio-feedback with the help of two cameras (one with anterior vision and one with lateral vision of the subject) and a big touch screen. The aim of these sessions of NMT was to modify the dysfunctional motor patterns evaluated by the 2D motion analysis test. The test was carried out at the beginning and at the end of the rehabilitation course and included five movements: single-leg squat (SLS), drop jump (DJ), single-leg hop (SLH), lateral shuffle (LS), and change of direction (COD). Each of these movements was evaluated through the video analysis of dynamic valgus knee, pelvic tilt, trunk control, shock absorption, and motor strategy. A free image analysis software (Kinovea) was then used to calculate scores. Results: Baseline assessment of the subject showed a total score of 59% on the right limb and 64% on the left limb (considering an optimal score above 85%) with large deficits in shock absorption capabilities, the presence of dynamic valgus knee, and dysfunctional motor strategies defined “quadriceps dominant.” After six weeks of training, the subject achieved a total score of 80% on the right limb and 86% on the left limb, with significant improvements in shock absorption capabilities, the presence of dynamic knee valgus, and the employment of more hip-oriented motor strategies on both lower limbs. The improvements shown in dynamic knee valgus, greater hip-oriented motor strategies, and improved shock absorption identified through six weeks of the NMT program can help a teenager amateur football player to manage the anterior knee pain during sports activity. In conclusion, NMT was a good choice to help a 13 years old male amateur football player to return to performance without pain after OSD and can also be used with all this type of athletes of the other teams' sports.

Keywords: movement analysis, neuro-motor training, knee pain, movement strategies

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Authors: Seyed Hossein Alavi, Farshad Ghazalian, Soghra Jamshidi

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Nowadays, athletic aggression discussion is considered as an important issue in sports psychology and sports effects have been noted by researchers from a long time ago. In this research, the amount of aggression among athletic students of different sport courses will be surveyed and compared. Statistics society in this research consists of all of boy athletic students in wrestling, taekwondo, football, and basketball of Mahmoudabad City that are 200 persons and the limitation of their ages are between 12-15 years old. Among all athletic students of different sport courses, 40 persons were chosen randomly for the sample. The method of research is a descriptive-comparative type that has been done according to field study and for measurement of examinations aggression amount, we have used Ayzank exam. In analysis step of foundations, for comparison of aggression of examined group, we have used Varian’s analysis exam. Research results show that among aggression amounts of athletic students of wrestling, taekwondo, football and basketball, there is no fundamental difference (p < 0.05). Stimulation of guest team with the host team fans, referees performance, exhaustion, physical confrontations, team position in the tournament table, and so on. There is no significant difference among aggression amount of selected sport athletic students.

Keywords: aggression, athletic, student, sports

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Authors: Balamurugan L.

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Artificial intelligence (AI) and its applications in Intellectual Property Rights (IPR) has been significantly growing in recent years. In last couple of years, AI tools for Patent Research and Patent Analytics have been well-stabilized in terms of accuracy of references and representation of identified patent insights. However, AI tools for Patent Prosecution and Patent Litigation are still in the nascent stage and there may be a significant potential if such market is explored further. Our research is primarily focused on identifying potential whitespaces and schematic algorithms to automate the Patent Prosecution and Patent Litigation Process of the Intellectual Property. The schematic algorithms may assist leading AI tool developers, to explore such opportunities in the field of Intellectual Property. Our research is also focused on identification of pitfalls of the AI. For example, Information Security and its impact in IPR, and Potential remediations to sustain the IPR in the digital environment.

Keywords: artificial intelligence, patent analytics, patent drafting, patent litigation, patent prosecution, patent research

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Authors: K. Hardy, A. Maurushat

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Policy makers are increasingly looking to make evidence-based decisions. Evidence-based decisions have historically used rigorous methodologies of empirical studies by research institutes, as well as less reliable immediate survey/polls often with limited sample sizes. As we move into the era of Big Data analytics, policy makers are looking to different methodologies to deliver reliable empirics in real-time. The question is not why did these people do this for the last 10 years, but why are these people doing this now, and if the this is undesirable, and how can we have an impact to promote change immediately. Big data analytics rely heavily on government data that has been released in to the public domain. The open data movement promises greater productivity and more efficient delivery of services; however, Australian government agencies remain reluctant to release their data to the general public. This paper considers the barriers to releasing government data as open data, and how these barriers might be overcome.

Keywords: big data, open data, productivity, data governance

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Authors: Beng Yew Low, Cher Liang Cha, Cheng Yong Teoh

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Due to a lack of continual assessment or grade related data, identifying first-year engineering students in a polytechnic education at risk of failing is challenging. Our experience over the years tells us that there is no strong correlation between having good entry grades in Mathematics and the Sciences and excelling in hardcore engineering subjects. Hence, identifying students at risk of failure cannot be on the basis of entry grades in Mathematics and the Sciences alone. These factors compound the difficulty of early identification and intervention. This paper describes the development of a predictive analytics model in the early detection of students at risk of failing and evaluates its effectiveness. Data from continual assessments conducted in term one, supplemented by data of student psychological profiles such as interests and study habits, were used. Three classification techniques, namely Logistic Regression, K Nearest Neighbour, and Random Forest, were used in our predictive model. Based on our findings, Random Forest was determined to be the strongest predictor with an Area Under the Curve (AUC) value of 0.994. Correspondingly, the Accuracy, Precision, Recall, and F-Score were also highest among these three classifiers. Using this Random Forest Classification technique, students at risk of failure could be identified at the end of term one. They could then be assigned to a Learning Support Programme at the beginning of term two. This paper gathers the results of our findings. It also proposes further improvements that can be made to the model.

Keywords: continual assessment, predictive analytics, random forest, student psychological profile

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Authors: Douglas A. Menezes, Isabel D. Nunes, Ulrich Schiel

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Most Virtual Learning Environments do not provide support mechanisms for the integrated planning, construction and follow-up of Instructional Design supported by Learning Analytic results. The present work aims to present an authoring tool that will be responsible for constructing the structure of an Instructional Design (ID), without the data being altered during the execution of the course. The visual interface aims to present the critical situations present in this ID, serving as a support tool for the course follow-up and possible improvements, which can be made during its execution or in the planning of a new edition of this course. The model for the ID is based on High-Level Petri Nets and the visualization forms are determined by the specific kind of the data generated by an e-course, a population of students generating sequentially dependent data.

Keywords: educational data visualization, high-level petri nets, instructional design, learning analytics

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Authors: Mahdi Motahari, Mojtaba Farzaneh, Ebrahim Sepidbar

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Tracking of moving and flying targets is one of the most important issues in image processing topic. Estimating of trajectory of desired object in short-term and long-term scale is more important than tracking of moving and flying targets. In this paper, a new way of identifying and estimating of future trajectory of a moving ball in long-term scale is estimated by using synthesis and interaction of image processing algorithms including noise removal and image segmentation, Kalman filter algorithm in order to estimating of trajectory of ball in football game in short-term scale and intelligent adaptive neuro-fuzzy algorithm based on time series of traverse distance. The proposed system attain more than 96% identify accuracy by using aforesaid methods and relaying on aforesaid algorithms and data base video in format of synthesis and interaction. Although the present method has high precision, it is time consuming. By comparing this method with other methods we realize the accuracy and efficiency of that.

Keywords: tracking, signal processing, moving targets and flying, artificial intelligent systems, estimating of trajectory, Kalman filter

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Authors: Geumchan Hwang

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Professional sport leagues in Europe and North America are shut down due to novel coronavirus disease (COVID-19) outbreak. Football leagues in Europe (e.g., La Liga, English Premier League, Bundesliga, Serie A, and Ligue 1) and big four professional sport leagues in North America (e.g., National Football League, Major League Baseball, National Basketball Association, and National Hockey League) are indefinitely suspended or delayed. COVID-19 outbreak has a growing negative impact on economics of sport leagues. For example, loss of revenue in Europe’s top five leagues due to the COVID-19 pandemic was estimated at € 4 billion and loss of revenue in the NBA was estimated at $650 million as of March 2020. In the unprecedented difficult situation, sport teams and leagues try to communicate with sport fans through diverse media platforms. In sport, however, very few studies have been done regarding how sport organizations effectively communicate with sport fans during pandemics, such as COVID-19 outbreak. Understanding sport organizations’ crisis communication is important to develop effective crisis management strategies for sport organizations. Therefore, the purpose of the study is to examine how sport organizations communicate with sport fans via online platforms in COVID-19 outbreak and how sport fans evaluate their communication strategies. 9 official sport league sites (i.e., five major football leagues in Europe and four major sport leagues in North America) and COVID-19 news articles published between January and June in 2020 will be analyzed in terms of coronavirus information, teams and players’ live update, fan interaction, fan support, and community engagement. In addition, comments posted on social media sites (i.e., Facebook and Twitter) of major sport leagues will be also analyzed to examine how sport fans perceive online messages provided by sport leagues as an effective communication strategy. To measure the effectiveness of crisis communication performance, five components (i.e., prompt, compassionate, honest, informative, and interactive) of crisis communication will be collected from leagues’ official websites information and social media posts. Upon completing data collection, content analysis method will be used to evaluate effectiveness of crisis communication among 9 professional sport leagues. The results of the study will provide athletic directors, administrators, and public relations managers in sport organizations with practical information regarding how athlete celebrities and sport organizations should interact with their fans in pandemic situations. In particular, this study will contribute to developing specific crisis management plan for sport organizations. For instance, football teams and leagues in Europe will be able to create standard manuals to minimize damages caused by disease outbreak, such as COVID-19 outbreak.

Keywords: COVID-19, communication, sport leagues, fans

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Authors: David Ming Liu, Benjamin Hirsch, Bashir Aden

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Syndromic surveillance is to detect or predict disease outbreaks through the analysis of medical sources of data. Using social media data like tweets to do syndromic surveillance becomes more and more popular with the aid of open platform to collect data and the advantage of microblogging text and mobile geographic location features. In this paper, a Syndromic Surveillance Framework is presented with machine learning kernel using tweets data analytics. Influenza and the three cities Abu Dhabi, Al Ain and Dubai of United Arabic Emirates are used as the test disease and trial areas. Hospital cases data provided by the Health Authority of Abu Dhabi (HAAD) are used for the correlation purpose. In our model, Latent Dirichlet allocation (LDA) engine is adapted to do supervised learning classification and N-Fold cross validation confusion matrix are given as the simulation results with overall system recall 85.595% performance achieved.

Keywords: Syndromic surveillance, Tweets, Machine Learning, data mining, Latent Dirichlet allocation (LDA), Influenza

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Authors: Suvarna Kumar Gogula, Sandhya Devi Gogula, P. Chanakya

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Augmented reality is defined as the collection of the digital (or) computer generated information like images, audio, video, 3d models, etc. and overlay them over the real time environment. Augmented reality can be thought as a blend between completely synthetic and completely real. Augmented reality provides scope in a wide range of industries like manufacturing, retail, gaming, advertisement, tourism, etc. and brings out new dimensions in the modern digital world. As it overlays the content, it makes the users enhance the knowledge by providing the content blended with real world. In this application, we integrated augmented reality with data analytics and integrated with cloud so the virtual content will be generated on the basis of the data present in the database and we used marker based augmented reality where every marker will be stored in the database with corresponding unique ID. This application can be used in wide range of industries for different business processes, but in this paper, we mainly focus on the marketing industry which helps the customer in gaining the knowledge about the products in the market which mainly focus on their prices, customer feedback, quality, and other benefits. This application also focuses on providing better market strategy information for marketing managers who obtain the data about the stocks, sales, customer response about the product, etc. In this paper, we also included the reports from the feedback got from different people after the demonstration, and finally, we presented the future scope of Augmented Reality in different business processes by integrating with new technologies like cloud, big data, artificial intelligence, etc.

Keywords: augmented reality, data analytics, catch room, marketing and sales

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Authors: Judith Enriquez-Gibson

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This paper meddles with the notion of phatic communion introduced 90 years ago by Malinowski, who was a Polish-born British anthropologist. It explores the phatic in Twitter within the contents of tweets related to moocs (massive online open courses) as a topic or trend. It is not about moocs though. It is about practices that could easily be hidden or neglected if we let big or massive topics take the lead or if we simply follow the computational or secret codes behind Twitter itself and third party software analytics. It draws from media and cultural studies. Though at first it appears data-driven as I submitted data collection and analytics into the hands of a third party software, Twitonomy, the aim is to follow how phatic communion might be practised in a social media site, such as Twitter. Lurking becomes its research method to analyse mooc-related tweets. A total of 3,000 tweets were collected on 11 October 2013 (UK timezone). The emphasis of lurking is to engage with Twitter as a system of connectivity. One interesting finding is that a click is in fact a phatic practice. A click breaks the silence. A click in one of the mooc website is actually a tweet. A tweet was posted on behalf of a user who simply chose to click without formulating the text and perhaps without knowing that it contains #mooc. Surely, this mechanism is not about reciprocity. To break the silence, users did not use words. They just clicked the ‘tweet button’ on a mooc website. A click performs and maintains connectivity – and Twitter as the medium in attendance in our everyday, available when needed to be of service. In conclusion, the phatic culture of breaking silence in Twitter does not have to submit to the power of code and analytics. It is a matter of human code.

Keywords: click, Twitter, phatic communion, social media data, mooc

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Authors: Rajender Lal, Seema Kaushik

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The FIFA World Cup, often simply called the World Cup, is an international association football competition contested by the senior men's national teams of the members of Fédération Internationale de Football Association (FIFA), the sport's global governing body. The championship has been awarded every four years since the inaugural tournament in 1930, except in 1942 and 1946 when it was not held because of the Second World War. Its 20th edition took place in Brazil from 12 June to 13 July 2014, which was won by Germany. The World Cup is the most widely viewed and followed sporting event in the world, exceeding even the Olympic Games; the cumulative audience of all matches of the 2006 FIFA World Cup was estimated to be 26.29 billion with an estimated 715.1 million people watching the final match, a ninth of the entire population of the planet. General-interest newspapers typically publish news articles and feature articles on national and international news as well as local news. The news includes political events and personalities, business and finance, crime, severe weather, and natural disasters; health and medicine, science, and technology; sports; and entertainment, society, food and cooking, clothing and home fashion, and the arts. It became curiosity to investigate that how much coverage is given to this most widely viewed international event as compared to other sports in India. Hence, the present study was conducted with the aim of examining the comparative coverage of FIFA World Cup 2014 and other sports in the four leading Newspapers of India including Hindustan Times, The Hindu, The Times of India, and The Tribune. Specific objectives were to measure the source of news, type of news items and the placement of news related to FIFA World Cup and other sports. Representative sample of ten editions each of the four English dailies was chosen for the purpose of the study. The analysis was based on the actual scanning of data from the representative sample of the dailies for the period of the competition. It can be concluded from the analysis that this event was given maximum coverage by the Hindustan Times while other sports were equally covered by The Hindu.

Keywords: coverage analysis, FIFA World Cup 2014, Hindustan Times, the Hindu, The Times of India, The Tribune

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Authors: Alicia Regodon Puyalto, Alfonso Garcia-Santos

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This article presents a method to analyze the use of indoor spaces based on data analytics obtained from inbuilt digital devices. The study uses the data generated by the in-place devices, such as smart locks, Wi-Fi routers, and electrical sensors, to gain additional insights on space occupancy, user behaviour, and comfort. Those devices, originally installed to facilitate remote operations, report data through the internet that the research uses to analyze information on human real-time use of spaces. Using an in-place Internet of Things (IoT) network enables a faster, more affordable, seamless, and scalable solution to analyze building interior spaces without incorporating external data collection systems such as sensors. The methodology is applied to a real case study of coliving, a residential building of 3000m², 7 floors, and 80 users in the centre of Madrid. The case study applies the method to classify IoT devices, assess, clean, and analyze collected data based on the analysis framework. The information is collected remotely, through the different platforms devices' platforms; the first step is to curate the data, understand what insights can be provided from each device according to the objectives of the study, this generates an analysis framework to be escalated for future building assessment even beyond the residential sector. The method will adjust the parameters to be analyzed tailored to the dataset available in the IoT of each building. The research demonstrates how human-centered data analytics can improve the future spatial design of indoor spaces.

Keywords: in-place devices, IoT, human-centred data-analytics, spatial design

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Authors: Jinan Fiaidhi, Sabah Mohammed

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Cross-domain learning in the medical field is a research challenge as many conditions, like in oncology imaging, use different imaging modalities. Moreover, in most of the medical learning applications, the sample training size is relatively small. Although few-shot learning (FSL) through the use of a Siamese neural network was able to be trained on a small sample with remarkable accuracy, FSL fails to be effective for use in multiple domains as their convolution weights are set for task-specific applications. In this paper, we are addressing this problem by enabling FSL to possess the ability to shift across domains by designing a two-layer FSL network that can learn individually from each domain and produce a shared features map with extra modulation to be used at the second layer that can recognize important targets from mix domains. Our initial experimentations based on mixed medical datasets like the Medical-MNIST reveal promising results. We aim to continue this research to perform full-scale analytics for testing our cross-domain FSL learning.

Keywords: Siamese neural network, few-shot learning, meta-learning, metric-based learning, thick data transformation and analytics

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Authors: Francis Alterado, Jennifer Enriquez

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Semantic Based Analysis in Complaint Management System with Analytics is an enhanced tool of providing complaints by the clients as well as a mechanism for Palawan Polytechnic College to gather, process, and monitor status of these complaints. The study has a mobile application that serves as a remote facility of communication between the students and the school management on the issues encountered by the student and the solution of every complaint received. In processing the complaints, text mining and clustering algorithms were utilized. Every module of the systems was tested and based on the results; these are 100% free from error before integration was done. A system testing was also done by checking the expected functionality of the system which was 100% functional. The system was tested by 10 students by forwarding complaints to 10 departments. Based on results, the students were able to submit complaints, the system was able to process accordingly by identifying to which department the complaints are intended, and the concerned department was able to give feedback on the complaint received to the student. With this, the system gained 4.7 rating which means Excellent.

Keywords: technology adoption, emerging technology, issues challenges, algorithm, text mining, mobile technology

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Authors: Nicola Milani, Carla Bellissimo, Davide Pogliana, Davide Panzin, Luca Garlaschelli, Giulia Facchinetti, Claudia Casson, Luca Marazzina, Andrea Sartori, Simone Rivaroli, Jeff Konin

Abstract:

The patient is a 26 year-old male amateur football player from Milan, Italy; (81kg; 185cm; BMI 23.6 kg/m²). He sustained a non-contact anterior cruciate ligament tear to his right knee in June 2021. In September 2021, his right knee ligament was reconstructed using a semitendinosus graft. The injury occurred during a football match on natural grass with typical shoes on a warm day (32 degrees celsius). Playing as a defender he sustained the injury during a change of direction, where the foot was fixated on the grass. He felt pain and was unable to continue playing the match. The surgeon approved his rehabilitation to begin two weeks post-operative. The initial physiotherapist assessment determined performing two training sessions per day within the first three months. In the first three weeks, the pain was 4/10 on Numerical Rating Scale (NRS), no swelling, a range of motion was 0-110°, with difficulty fully extending his knee and minimal quadriceps activation. Crutches were discontinued at four weeks with improved walking. Active exercise, electrostimulator, physical therapy, massages, osteopathy, and passive motion were initiated. At week 6, he completed his first functional movement screen; the score was 16/21 with no pain and no swelling. At week 8, the isokinetic test showed a 23% differential deficit between the two legs in maximum strength (at 90°/s). At week 10, he improved to 15% of injury-induced deficit which suggested he was ready to start running. At week 12, the athlete sustained his first threshold test. At week 16, he performed his first return to sports movement assessment, which revealed a 10% stronger difference between the legs. At week 16, he had his second threshold test. At week 17, his first on-field test revealed a 5% differential deficit between the two legs in the hop test. At week 18, isokinetic test demonstrates that the uninjured leg was 7% stronger than the recovering leg in maximum strength (at 90°/s). At week 20, his second on-field test revealed a 2% difference in hop test; at week 21, his third isokinetic test demonstrated a difference of 5% in maximum strength (at 90°/s). At week 21, he performed his second return to sports movement assessment which revealed a 2% difference between the limbs. Since it was the end of the championship, the team asked him to partake in the playoffs; moreover the player was very motivated to participate in the playoffs also because he was the captain of the team. Together with the player and the team, we decided to let him play even though we were aware of a heightened risk of injury than what is reported in the literature because of two factors: biological recovery times and the results of the tests we performed. In the decision making process about the athlete’s recovery time, it is important to balance the information available from the literature with the desires of the patient to avoid frustration.

Keywords: ACL, football, rehabilitation, return to play

Procedia PDF Downloads 93