1,634 research outputs found
LIPIcs, Volume 251, ITCS 2023, Complete Volume
LIPIcs, Volume 251, ITCS 2023, Complete Volum
Making of Wars: Analysis of the Franchise Management of \u3ci\u3eGod\u3c/i\u3e \u3ci\u3eof\u3c/i\u3e \u3ci\u3eWar\u3c/i\u3e and \u3ci\u3eGears\u3c/i\u3e \u3ci\u3eof\u3ci\u3e \u3ci\u3eWar\u3c/i\u3e
Two of the most prominent franchises in the video game industry are God of War and Gears of War. These franchises, produced by Sony Interactive Entertainment (SIE) and Xbox Game Studios (XGS), respectively, and their presentation through company blogs offer insight into the franchise management strategies and franchise conceptualizations that their parent companies have. Understanding these franchising aspects furthers knowledge on how these companies, two of the three largest video game producers, engage in franchising behaviors through discourse. Utilizing a framework of the discourse of franchise paratexts, this thesis examines those franchising tactics and discursive frames that the companies use as well as how they compare to each other, due to their market position as competitors. Through a discourse analysis of 49 blog posts (27 from SIE; 22 from XGS) over the last two development cycles (2018-2022), this thesis discovered that while both companies use the blogs as a marketing tool, SIE engages in more artistic and community framing while XGS focuses on product marketing and direct consumer outcomes. As such, their differing frames provide insight into how the franchises are conceptualized: an artistic achievement for SIE and a part of a product line for XGS
Japanese Expert Teachers' Understanding of the Application of Rhythm in Judo: a New Pedagogy
Aim
The aim of this research is to understand the application of rhythm in judo through the experience of expert Japanese coaches.
Background
Scientists and experienced coaches agree rhythm is an important skill in peopleâs everyday life. There is currently no research that investigates the importance of rhythm in judo. People with a highly developed sense of rhythm, move properly, breathe properly, or begin and finish work at the right time. Where sport is concerned, motion and dance can play an important role not only in the improvement of performance, but also in the reduction, or even prevention of, injuries. Those who are naturally musically inclined (have a musical ear) may find they can improve their technique faster than others, and this is something that, by investigating the way expert coaches understand the application of rhythm in judo, this research seeks to understand.
As Lange, (1970) stated, factors of movement are âweight, space, time, and flow on the background of the general flux of movement in proportional arrangementsâ (Bradley, 2008; Selioni, 2013; Youngerman, 1976), therefore, this research will investigate the interaction of body and mind. Dance training as well as judo are somatic experiences that have as their ultimate goal the attainment of a skilled body. With quality training an athlete gains an increased awareness of their body which leads to better control of movement and is very important for judo athletes. This training is found in Japanese kabuki dance (Hahn, 2007), the Greek syrtaki dance (Zografou & Pateraki, 2007), and in walking techniques used in the traditional and Olympic sports of Japanese judo and Greek wrestling.
Methods
Interpretative phenomenological analysis (IPA) was the most suitable data analysis approach for this study for a number of reasons, mainly because it was considered to most closely reflect the author's realist epistemological view. The idiographic approach and framework, particularly on IPA, was regarded as a useful framework in which the current topic could meaningfully be explored.
As this study is one of the first to explore this new thematic area, IPA was the preferred approach to address the goal of providing a detailed account of the expertâs experience. Therefore, semi-structured interviews were used as a data source. This is the most conventional form of data collection using IPA and most closely reflects the researcher-participant relationship. Semi-structured interviews provide considerable flexibility by allowing the researcher to be guided by the phenomena of interest to the participant.
In this study, purposive sampling was achieved using inclusion criteria pertaining to the research question.
Using the ranking system criteria based on the belt in combination with age employed by the International Judo Federation (IJF) and Kodokan Judo Institute, six expert coaches of forty years old and over with a minimum belt rank of 6th dan were selected as a sample.
Results
Both interviews and the codification process contributed to new findings regarding the application of rhythm to judo, and judo itself as a pedagogical tool.
The diagrammatic model can be considered a 'guideline' to the phenomena deemed most significant. The personal significance of rhythm in judo was evidenced by the frequency with which the interviewees naturally referred to it during the interviews. A number of interviewees said that it was important for rhythm to be second nature. Rhythm was also described as an integrated and representative
element in the context of training. This framework was seen as essential in providing the reader with a contextualised understanding of the phenomena considered most important for the current research. Interviewees reported various motives for employing training in rhythm such as faster technical development, better attack/defence, fitness, speed, skills acquisition, personal and spiritual growth, competition results.
Conclusions
This study offers first-hand accounts from professional coaches of a previously unknown phenomena, namely the use of rhythm in judo, and sheds insight on how judo experts understand rhythm in terms of training, competition, and personal growth. These findings suggest that outside of training, coaches play an important role in teaching, mentoring, and leading students. In conclusion, the research revealed four important points which form the basis of a new method of teaching judo: pedagogy, skills, rhythm and movement
The European Experience: A Multi-Perspective History of Modern Europe, 1500â2000
The European Experience brings together the expertise of nearly a hundred historians from eight European universities to internationalise and diversify the study of modern European history, exploring a grand sweep of time from 1500 to 2000. Offering a valuable corrective to the Anglocentric narratives of previous English-language textbooks, scholars from all over Europe have pooled their knowledge on comparative themes such as identities, cultural encounters, power and citizenship, and economic development to reflect the complexity and heterogeneous nature of the European experience. Rather than another grand narrative, the international author teams offer a multifaceted and rich perspective on the history of the continent of the past 500 years. Each major theme is dissected through three chronological sub-chapters, revealing how major social, political and historical trends manifested themselves in different European settings during the early modern (1500â1800), modern (1800â1900) and contemporary period (1900â2000). This resource is of utmost relevance to todayâs history students in the light of ongoing internationalisation strategies for higher education curricula, as it delivers one of the first multi-perspective and truly âEuropeanâ analyses of the continentâs past. Beyond the provision of historical content, this textbook equips students with the intellectual tools to interrogate prevailing accounts of European history, and enables them to seek out additional perspectives in a bid to further enrich the discipline
Scalable Learning of Bayesian Networks Using Feedback Arc Set-Based Heuristics
Bayesianske nettverk er en viktig klasse av probabilistiske grafiske modeller. De bestÄr av en struktur (en rettet asyklisk graf) som beskriver betingede uavhengighet mellom stokastiske variabler og deres parametere (lokale sannsynlighetsfordelinger). Med andre ord er Bayesianske nettverk generative modeller som beskriver simultanfordelingene pÄ en kompakt form.
Den stÞrste utfordringen med Ä lÊre et Bayesiansk nettverk skyldes selve strukturen, og pÄ grunn av den kombinatoriske karakteren til asyklisitetsegenskapen er det ingen overraskelse at strukturlÊringsproblemet generelt er NP-hardt. Det eksisterer algoritmer som lÞser dette problemet eksakt: dynamisk programmering og heltalls lineÊr programmering er de viktigste kandidatene nÄr man Þnsker Ä finne strukturen til smÄ til mellomstore Bayesianske nettverk fra data. PÄ den annen side er heuristikk som bakkeklatringsvarianter ofte brukt nÄr man forsÞker Ä lÊre strukturen til stÞrre nettverk med tusenvis av variabler, selv om disse heuristikkene vanligvis ikke har teoretiske garantier og ytelsen i praksis kan bli uforutsigbar nÄr man arbeider med storskala lÊring.
Denne oppgaven tar for seg utvikling av skalerbare metoder som takler det strukturlÊringsproblemet av Bayesianske nettverk, samtidig som det forsÞkes Ä opprettholde et nivÄ av teoretisk kontroll. Dette ble oppnÄdd ved bruk av relaterte kombinatoriske problemer, nemlig det maksimale asykliske subgrafproblemet (maximum acyclic subgraph) og det duale problemet (feedback arc set). Selv om disse problemene er NP-harde i seg selv, er de betydelig mer hÄndterbare i praksis. Denne oppgaven utforsker mÄter Ä kartlegge Bayesiansk nettverksstrukturlÊring til maksimale asykliske subgrafforekomster og trekke ut omtrentlige lÞsninger for det fÞrste problemet, basert pÄ lÞsninger oppnÄdd for det andre.
VÄr forskning tyder pÄ at selv om Þkt skalerbarhet kan oppnÄs pÄ denne mÄten, er det adskillig mer utfordrende Ä opprettholde den teoretisk forstÄelsen med denne tilnÊrmingen. Videre fant vi ut at Ä lÊre strukturen til Bayesianske nettverk basert pÄ maksimal asyklisk subgraf kanskje ikke er den beste metoden generelt, men vi identifiserte en kontekst - lineÊre strukturelle ligningsmodeller - der vi eksperimentelt kunne validere fordelene med denne tilnÊrmingen, som fÞrer til rask og skalerbar identifisering av strukturen og med mulighet til Ä lÊre komplekse strukturer pÄ en mÄte som er konkurransedyktig med moderne metoder.Bayesian networks form an important class of probabilistic graphical models. They consist of a structure (a directed acyclic graph) expressing conditional independencies among random variables, as well as parameters (local probability distributions). As such, Bayesian networks are generative models encoding joint probability distributions in a compact form.
The main difficulty in learning a Bayesian network comes from the structure itself, owing to the combinatorial nature of the acyclicity property; it is well known and does not come as a surprise that the structure learning problem is NP-hard in general. Exact algorithms solving this problem exist: dynamic programming and integer linear programming are prime contenders when one seeks to recover the structure of small-to-medium sized Bayesian networks from data. On the other hand, heuristics such as hill climbing variants are commonly used when attempting to approximately learn the structure of larger networks with thousands of variables, although these heuristics typically lack theoretical guarantees and their performance in practice may become unreliable when dealing with large scale learning.
This thesis is concerned with the development of scalable methods tackling the Bayesian network structure learning problem, while attempting to maintain a level of theoretical control. This was achieved via the use of related combinatorial problems, namely the maximum acyclic subgraph problem and its dual problem the minimum feedback arc set problem. Although these problems are NP-hard themselves, they exhibit significantly better tractability in practice. This thesis explores ways to map Bayesian network structure learning into maximum acyclic subgraph instances and extract approximate solutions for the first problem, based on the solutions obtained for the second.
Our research suggests that although increased scalability can be achieved this way, maintaining theoretical understanding based on this approach is much more challenging. Furthermore, we found that learning the structure of Bayesian networks based on maximum acyclic subgraph/minimum feedback arc set may not be the go-to method in general, but we identified a setting - linear structural equation models - in which we could experimentally validate the benefits of this approach, leading to fast and scalable structure recovery with the ability to learn complex structures in a competitive way compared to state-of-the-art baselines.Doktorgradsavhandlin
LIPIcs, Volume 261, ICALP 2023, Complete Volume
LIPIcs, Volume 261, ICALP 2023, Complete Volum
The separated accelerated : A study of the perspectives of gifted primary students attending withdrawal acceleration options in schools
This study investigated perspectives on Withdrawal Acceleration Options (WAOs), a form of teaching intervention provided by some primary schools to cater to children displaying exceptional academic abilities. The notion of schools supporting intellectually advantaged students brings a unique range of strategic considerations for teachers, parents, researchers, and the gifted students central to this investigation.
Case study research and Grounded Theory explaining these considerations is not keeping pace with strategies such as WAOs, leading to a gap in the field of giftedness research. Acknowledging the dominance of US literature in this field, this study sought to generate knowledge of perspectives on this teaching strategy from an Australian context for the first time, with international implications. The importance of this study is seen to add literature that primary schools can access when considering or reinforcing WAOs for gifted students.
To raise awareness of WAO experiences, this thesis examined the perspectives of gifted children selected to this teaching option via the research question, what are the perspectives of gifted primary students attending acceleration options in schools? The aim of this research project was to explore observations, reactions, and predictions by gifted primary children of withdrawal accelerations and generated theories and recommendations to inform educational policies, practices, and further research in the field of giftedness.
Twenty-one primary school children attending WAOs in six schools provided almost 700 responses to an electronic questionnaire and semi-structured interviews between July 2019 and April 2020. Schools providing the participants in this study augment the efforts of their class teachers by funding personnel to withdraw gifted primary children from classes, who then deliver tasks targeting the advanced range and speed of those students.
Analysis of the data revealed indications of participantsâ confusion, their observation of othersâ ambivalence and wanting involvement in the planning, resourcing, and provision of their withdrawal acceleration options. These findings had not previously been interconnected in the literature when investigating accelerations for gifted students and validate the importance of this study. When seeking to contextualise the gifted studentsâ perspectives, an examination of contemporary theoretical frameworks revealed one model, the Education Situation/Quality model (Domenech-Betoret, Gomez-Artiga and Abellan-Rosello, 2019) informed the design of a unique, unifying conceptual model proposed by this thesis, which will be introduced as the Doorway model.
This research project advocates the Doorway model as a significant contribution to knowledge of gifted primary school experiences in withdrawal accelerations. The Doorway model depicts a 6-stage system mapping when influences on the perspectives of gifted children in WAOs occurred. Each stage impacts a subsequent stage and respondents indicated the perspectives were influenced before and after WAO lessons, a significant difference with other theoretical frameworks, further validating the importance of this investigation and the findings.
Analysis of the data and subsequent discussion resulted in a set of recommendations for primary schools developing WAOs. Wider policy and research implications are discussed addressing professional policies and research to widen this field further. Implications for the practices of class teachers selecting gifted students for accelerations and the WAO teachers providing these programs are discussed. The thesis advocates that an awareness of the perspectives of gifted children on Withdrawal Acceleration Options, mapped by the stages of the Doorway model makes is plausible for schools to reinforce professional policy, practices, and knowledge of interventions for the gifted to influence improved academic, affective, and creative outcomes
2010 GREAT Day Program
SUNY Geneseoâs Fourth Annual GREAT Day.
This file has a supplement of three additional pages, linked in this record.https://knightscholar.geneseo.edu/program-2007/1004/thumbnail.jp
The PACE 2022 Parameterized Algorithms and Computational Experiments Challenge: Directed Feedback Vertex Set
The Parameterized Algorithms and Computational Experiments challenge (PACE) 2022 was devoted to engineer algorithms solving the NP-hard Directed Feedback Vertex Set (DFVS) problem. The DFVS problem is to find a minimum subset in a given directed graph such that, when all vertices of and their adjacent edges are deleted from , the remainder is acyclic.
Overall, the challenge had 90 participants from 26 teams, 12 countries, and 3 continents that submitted their implementations to this yearâs competition. In this report, we briefly describe the setup of the challenge, the selection of benchmark instances, as well as the ranking of the participating teams. We also briefly outline the approaches used in the submitted solvers
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