860 resultados para Military art and science.
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Despite over three decades of legislation and initiatives designed to tackle the traditional gender divide in the science, technology and design fields, only a quarter of the registered architects in Australia are women. There are no statistics available for other design disciplines, with little known about why women choose design as a career path and who or what influences this decision. This qualitative research addresses this knowledge gap, through semi-structured in-depth interviews conducted with 19 Australian women who completed an industrial (product) design degree. Thematic analysis revealed three key themes: childhood aptitude and exposure; significant experiences and people; and design as a serendipitous choice. The findings emphasise the importance of early exposure to design as a potential career choice, highlighting the critical role played by parents, teachers, professionals and social networks.
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Long term exposure to organic pollutants, both inside and outside school buildings may affect children’s health and influence their learning performance. Since children spend significant amount of time in school, air quality, especially in classrooms plays a key role in determining the health risks associated with exposure at schools. Within this context, the present study investigated the ambient concentrations of Volatile Organic Compounds (VOCs) in 25 primary schools in Brisbane with the aim to quantify the indoor and outdoor VOCs concentrations, identify VOCs sources and their contribution, and based on these; propose mitigation measures to reduce VOCs exposure in schools. One of the most important findings is the occurrence of indoor sources, indicated by the I/O ratio >1 in 19 schools. Principal Component Analysis with Varimax rotation was used to identify common sources of VOCs and source contribution was calculated using an Absolute Principal Component Scores technique. The result showed that outdoor 47% of VOCs were contributed by petrol vehicle exhaust but the overall cleaning products had the highest contribution of 41% indoors followed by air fresheners and art and craft activities. These findings point to the need for a range of basic precautions during the selection, use and storage of cleaning products and materials to reduce the risk from these sources.
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We propose a novel technique for conducting robust voice activity detection (VAD) in high-noise recordings. We use Gaussian mixture modeling (GMM) to train two generic models; speech and non-speech. We then score smaller segments of a given (unseen) recording against each of these GMMs to obtain two respective likelihood scores for each segment. These scores are used to compute a dissimilarity measure between pairs of segments and to carry out complete-linkage clustering of the segments into speech and non-speech clusters. We compare the accuracy of our method against state-of-the-art and standardised VAD techniques to demonstrate an absolute improvement of 15% in half-total error rate (HTER) over the best performing baseline system and across the QUT-NOISE-TIMIT database. We then apply our approach to the Audio-Visual Database of American English (AVDBAE) to demonstrate the performance of our algorithm in using visual, audio-visual or a proposed fusion of these features.
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It is well known that different arguments appeal to different people. We all process information in ways that are adapted to be consistent with our underlying ideologies. These ideologies can sometimes be framed in terms of particular axes or dimensions, which makes it possible to represent some aspects of an ideology as a region in the kind of vector space that is typical of many generalised quantum models. Such models can then be used to explain and predict, in broad strokes, whether a particular argument or proposal is likely to appeal to an individual with a particular ideology. The choice of suitable arguments to bring about desired actions is traditionally part of the art or science of rhetoric, and today's highly polarised society means that this skill is becoming more important than ever. This paper presents a basic model for understanding how different goals will appeal to people with different ideologies, and thus how different rhetorical positions can be adopted to promote the same desired outcome. As an example, we consider different narratives and hence actions with respect to the environment and climate change, an important but currently highly controversial topic.
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This paper details a workshop aimed at exploring opportunities for experience design through wearable art and design concepts. Specifically it explores the structure of the workshop with respect to facilitating learning through technology in the development of experiential wearable art and design. A case study titled Cloud Workshop: Wearables and Wellbeing; Enriching connections between citizens in the Asia-Pacific region was initiated through a cooperative partnership between Hong Kong Baptist University (HKBU), Queensland University of Technology (QUT) and Griffith University (GU). Digital technologies facilitated collaboration through an inter-disciplinary, inter-national and inter- cultural approach (Facer & Sandford, 2010) between Australia and Hong Kong. Students cooperated throughout a two-week period to develop innovative wearable concepts blending art, design and technology. An unpacking of the approach, pedagogical underpinning and final outcomes revealed distinct educational benefits as well as certain learning and technological challenges of the program. Qualitative feedback uncovered additional successes with respect to student engagement and enthusiasm, while uncovering shortcomings in the delivery and management of information and difficulties with cultural interactions. Potential future versions of the program aim to take advantage of the positives and overcome the limitations of the current pedagogical approach. It is hoped the case study will become a catalyst for future workshops that blur the boundaries of art, design and technology to uncover further benefits and potentials for new outcomes in experience design.
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Gentlemen, Lads and the Art of War The Construction of Citizen Soldier- and Professional Soldier Armies into the Miracle of the Winter War During the 1920s and 1930s The Miracle of the Winter War was not a myth - at least according to them, who were making that miracle to happen. This study is not just about the Armed Forces and society, but moreover a study about civil society inside the organization of armed forces. Conscription kept Finnish military organization (and is still keeping) very closely connected with civil society and therefore there is no need to locate the possible critical misunderstandings brought by two different identity-based approaches. The great performance of the Armed Forces during the Second World War was not made of superior art of war. It was not the high level of discipline either. Art of war is basically a (deep level) cultural level equation that has more to do with culturally absorbed schemes of meaning making than rational decision-making. Naturally attrition based approach to effect-making directed the organizational methods in attrition based organisational practices, where there were only minor possibilities to practice any manoeuvre-based organisational behaviour. The practice and method of leadership lent similarly to the attrition-based thinking, which directed the organisational cultural thoughts towards composition that confirmed antagonism between gentlemen and lads . This setting has been absorbed and learned through cultural socialisation and was therefore not a product of the military organisation itself. The Finnish Armed Forces included two different communities (gentlemen and lads) within the same organisation as there were both the official and the unofficial organisations presented. This caused problems as they both made meaning-making processes simultaneously. These organisations had their own overlapping and in most cases also contradictory social meanings. The unofficial organisation has been overshadowed by the vast number of studies concerning the official organisation. The main reason for this systematic neglect is based on the reality of the attitudes and living conditions of the micro-level organisation which produced (perhaps) too realistic and repulsive viewpoints that are presenting a picture of a national level identity process in a way that is separating it from the ideals made to verify the ethos of national values. Complaining, griping, grumbling and moaning are usually situated in a category of abnormal and unwanted behaviour. However, within the context of a citizen soldier army community this was more of a characteristic feature of that organisation (in Finland) and therefore it was crucially important to locate the context of that abnormal behaviour. According to this study, it was not a malicious act but moreover seriously formed efforts in trying to use common sense in the chaos citizen soldiers faced when they were uniformed and placed in an unfamiliar process of disciplinary measures and frictions and competition between different ranks. There is much evidence that reinforces the argument that what seemed to be the most unconventional behaviour was finally the most efficient in a sense of military performance.
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In the last thirty years, ethnic museums have mushroomed in American cities. Although this is certainly a national phenomenon, it has been particularly evident in Los Angeles. In this paper we examine the genesis and evolution of these emerging institutions. We survey the mission, scope, and role of ethnic museums in Los Angeles, and we contrast them with the stated mission and scope of “mainstream” museums in the city. We further present case studies of three Los Angeles ethnic museums. The museums vary considerably in the ways they perceive their role in the community, the city, and the nation and in the preservation and display of ethnic culture. At their best, ethnic museums serve to make new art and histories more accessible and visible and provide a forum in which to debate contemporary issues of politics and identity. The paper highlights some of the tensions faced by ethnic museums as they seek to define their audience and role(s) in multi-ethnic, twenty-first century Los Angeles.
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In the wake of an almost decade long economic downturn and increasing competition from developing economies, a new agenda in the Australian Government for science, technology, engineering, and mathematics (STEM) education and research has emerged as a national priority. However, to art and design educators, the pervasiveness and apparent exclusivity of STEM can be viewed as another instance of art and design education being relegated to the margins of curriculum (Greene, 1995). In the spirit of interdisciplinarity, there have been some recent calls to expand STEM education to include the arts and design, transforming STEM into STEAM in education (Maeda, 2013). As with STEM, STEAM education emphasises the connections between previously disparate disciplines, meaning that education has been conceptualised in different ways, such as focusing on the creative design thinking process that is fundamental to engineering and art (Bequette & Bequette, 2012). In this article, we discuss divergent creative design thinking process and metacognitive skills, how, and why they may enhance learning in STEM and STEAM.
Desenvolvimento do clube de história da matemática: um diálogo das ciências humanas com a matemática
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Este trabalho apresenta uma pesquisa sobre a utilização da História da Matemática no ensino básico do Colégio Militar do Rio de Janeiro CMRJ através de manifestações artísticas, fazendo uso, principalmente, do teatro,para que alunos percebam a matemática como uma ciência temporal, humana e sujeita a interferências políticas e sociais e, dessa forma, desenvolver a criticidade, aumentar a sensibilidade e o senso de solidariedade. A partir de um tema da história envolvendo fatos matemáticos os alunos pesquisam, escrevem uma peça teatral e encenam para um público formado por pessoas da comunidade escolar. Como a intenção é tornar essa prática efetiva, a pesquisa culmina na fundação do Clube de História da Matemática, espaço onde, espera-se, atividades recorrentes sejamdesenvolvidas, atraindo alunos afetos tanto às ciências humanas e sociais como às ciências exatas. Realiza-se um estudo de caso com observação participante, por ser o autor também professor do CMRJ. Este estudo busca referência teórica principalmente em autores relacionados à História da Matemática, Arte na Educação, gestão democrática, relações de poder e na legislação vigente. A pesquisa aponta a importância do trabalho com a história e com a arte e nos leva a concluir que, para formar cidadãos participativos e críticos, o primeiro passo é a sociedade tornar-se participativa e crítica, sendo a escola o principal locuspara tal formação.
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Lee M.H., Many-Valued Logic and Qualitative Modelling of Electrical Circuits, in Proc. QR?2000, 14th Int. Workshop on Qualitative Reasoning, Morelia, Mexico June 3rd - 7th 2000.
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Q. Shen and R. Jensen, 'Rough sets, their extensions and applications,' International Journal of Automation and Computing (IJAC), vol. 4, no. 3, pp. 217-218, 2007.
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A new neural network architecture is introduced for the recognition of pattern classes after supervised and unsupervised learning. Applications include spatio-temporal image understanding and prediction and 3-D object recognition from a series of ambiguous 2-D views. The architecture, called ART-EMAP, achieves a synthesis of adaptive resonance theory (ART) and spatial and temporal evidence integration for dynamic predictive mapping (EMAP). ART-EMAP extends the capabilities of fuzzy ARTMAP in four incremental stages. Stage 1 introduces distributed pattern representation at a view category field. Stage 2 adds a decision criterion to the mapping between view and object categories, delaying identification of ambiguous objects when faced with a low confidence prediction. Stage 3 augments the system with a field where evidence accumulates in medium-term memory (MTM). Stage 4 adds an unsupervised learning process to fine-tune performance after the limited initial period of supervised network training. Each ART-EMAP stage is illustrated with a benchmark simulation example, using both noisy and noise-free data. A concluding set of simulations demonstrate ART-EMAP performance on a difficult 3-D object recognition problem.
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Adaptive Resonance Theory (ART) models are real-time neural networks for category learning, pattern recognition, and prediction. Unsupervised fuzzy ART and supervised fuzzy ARTMAP synthesize fuzzy logic and ART networks by exploiting the formal similarity between the computations of fuzzy subsethood and the dynamics of ART category choice, search, and learning. Fuzzy ART self-organizes stable recognition categories in response to arbitrary sequences of analog or binary input patterns. It generalizes the binary ART 1 model, replacing the set-theoretic: intersection (∩) with the fuzzy intersection (∧), or component-wise minimum. A normalization procedure called complement coding leads to a symmetric: theory in which the fuzzy inter:>ec:tion and the fuzzy union (∨), or component-wise maximum, play complementary roles. Complement coding preserves individual feature amplitudes while normalizing the input vector, and prevents a potential category proliferation problem. Adaptive weights :otart equal to one and can only decrease in time. A geometric interpretation of fuzzy AHT represents each category as a box that increases in size as weights decrease. A matching criterion controls search, determining how close an input and a learned representation must be for a category to accept the input as a new exemplar. A vigilance parameter (p) sets the matching criterion and determines how finely or coarsely an ART system will partition inputs. High vigilance creates fine categories, represented by small boxes. Learning stops when boxes cover the input space. With fast learning, fixed vigilance, and an arbitrary input set, learning stabilizes after just one presentation of each input. A fast-commit slow-recode option allows rapid learning of rare events yet buffers memories against recoding by noisy inputs. Fuzzy ARTMAP unites two fuzzy ART networks to solve supervised learning and prediction problems. A Minimax Learning Rule controls ARTMAP category structure, conjointly minimizing predictive error and maximizing code compression. Low vigilance maximizes compression but may therefore cause very different inputs to make the same prediction. When this coarse grouping strategy causes a predictive error, an internal match tracking control process increases vigilance just enough to correct the error. ARTMAP automatically constructs a minimal number of recognition categories, or "hidden units," to meet accuracy criteria. An ARTMAP voting strategy improves prediction by training the system several times using different orderings of the input set. Voting assigns confidence estimates to competing predictions given small, noisy, or incomplete training sets. ARPA benchmark simulations illustrate fuzzy ARTMAP dynamics. The chapter also compares fuzzy ARTMAP to Salzberg's Nested Generalized Exemplar (NGE) and to Simpson's Fuzzy Min-Max Classifier (FMMC); and concludes with a summary of ART and ARTMAP applications.
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Adaptive Resonance Theory (ART) models are real-time neural networks for category learning, pattern recognition, and prediction. Unsupervised fuzzy ART and supervised fuzzy ARTMAP networks synthesize fuzzy logic and ART by exploiting the formal similarity between tile computations of fuzzy subsethood and the dynamics of ART category choice, search, and learning. Fuzzy ART self-organizes stable recognition categories in response to arbitrary sequences of analog or binary input patterns. It generalizes the binary ART 1 model, replacing the set-theoretic intersection (∩) with the fuzzy intersection(∧), or component-wise minimum. A normalization procedure called complement coding leads to a symmetric theory in which the fuzzy intersection and the fuzzy union (∨), or component-wise maximum, play complementary roles. A geometric interpretation of fuzzy ART represents each category as a box that increases in size as weights decrease. This paper analyzes fuzzy ART models that employ various choice functions for category selection. One such function minimizes total weight change during learning. Benchmark simulations compare peformance of fuzzy ARTMAP systems that use different choice functions.
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The processes by which humans and other primates learn to recognize objects have been the subject of many models. Processes such as learning, categorization, attention, memory search, expectation, and novelty detection work together at different stages to realize object recognition. In this article, Gail Carpenter and Stephen Grossberg describe one such model class (Adaptive Resonance Theory, ART) and discuss how its structure and function might relate to known neurological learning and memory processes, such as how inferotemporal cortex can recognize both specialized and abstract information, and how medial temporal amnesia may be caused by lesions in the hippocampal formation. The model also suggests how hippocampal and inferotemporal processing may be linked during recognition learning.