993 resultados para Feature construction
Resumo:
Identifying the correct sense of a word in context is crucial for many tasks in natural language processing (machine translation is an example). State-of-the art methods for Word Sense Disambiguation (WSD) build models using hand-crafted features that usually capturing shallow linguistic information. Complex background knowledge, such as semantic relationships, are typically either not used, or used in specialised manner, due to the limitations of the feature-based modelling techniques used. On the other hand, empirical results from the use of Inductive Logic Programming (ILP) systems have repeatedly shown that they can use diverse sources of background knowledge when constructing models. In this paper, we investigate whether this ability of ILP systems could be used to improve the predictive accuracy of models for WSD. Specifically, we examine the use of a general-purpose ILP system as a method to construct a set of features using semantic, syntactic and lexical information. This feature-set is then used by a common modelling technique in the field (a support vector machine) to construct a classifier for predicting the sense of a word. In our investigation we examine one-shot and incremental approaches to feature-set construction applied to monolingual and bilingual WSD tasks. The monolingual tasks use 32 verbs and 85 verbs and nouns (in English) from the SENSEVAL-3 and SemEval-2007 benchmarks; while the bilingual WSD task consists of 7 highly ambiguous verbs in translating from English to Portuguese. The results are encouraging: the ILP-assisted models show substantial improvements over those that simply use shallow features. In addition, incremental feature-set construction appears to identify smaller and better sets of features. Taken together, the results suggest that the use of ILP with diverse sources of background knowledge provide a way for making substantial progress in the field of WSD.
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Data preprocessing is widely recognized as an important stage in anomaly detection. This paper reviews the data preprocessing techniques used by anomaly-based network intrusion detection systems (NIDS), concentrating on which aspects of the network traffic are analyzed, and what feature construction and selection methods have been used. Motivation for the paper comes from the large impact data preprocessing has on the accuracy and capability of anomaly-based NIDS. The review finds that many NIDS limit their view of network traffic to the TCP/IP packet headers. Time-based statistics can be derived from these headers to detect network scans, network worm behavior, and denial of service attacks. A number of other NIDS perform deeper inspection of request packets to detect attacks against network services and network applications. More recent approaches analyze full service responses to detect attacks targeting clients. The review covers a wide range of NIDS, highlighting which classes of attack are detectable by each of these approaches. Data preprocessing is found to predominantly rely on expert domain knowledge for identifying the most relevant parts of network traffic and for constructing the initial candidate set of traffic features. On the other hand, automated methods have been widely used for feature extraction to reduce data dimensionality, and feature selection to find the most relevant subset of features from this candidate set. The review shows a trend toward deeper packet inspection to construct more relevant features through targeted content parsing. These context sensitive features are required to detect current attacks.
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This study aims to explore the perceptions of principals and teacher leaders regarding their roles and the interaction between these roles in Chinese urban primary schools at the time of unprecedented curriculum reform. This involves a complexity of factors such as the influence of globalisation, the impact of traditional Chinese cultural attitudes towards education through Confucianism, and the implementation requirements of the current education reforms. All of these wider contextual factors help to shape the leadership practices that are described in the study. A qualitative exploratory case study approach has been utilised to undertake this investigation. The conceptual framework for this study draws upon scholars‘ work from Western countries but has been adapted in order to address three research questions for the study‘s focus on the context in Shandong province, Mainland China. Three research questions were addressed: First, what are principals‘ perceptions of their leadership roles in Mainland China under current educational reform? Second, what are teacher leaders‘ perceptions of their leadership roles in Mainland China under current educational reform? And finally, what are principals‘ and teacher leaders‘ perceptions of how their roles interact? With reference to the principals in the study, the findings confirm Gurr‘s (2008) comprehensive leadership model relating to four roles, specifically, learning and teaching, symbolic and cultural awareness, future orientation, and accountability. Significantly, some sub-roles that emerge from the data are uniquely Chinese. For example, school culture construction is a very deliberate process in which principals and their staff talked openly about and were involved in creating a positive school climate comprising spiritual, material, and system dimensions. Another finding relates to school feature construction. This refers to the process that principals and staff used to make their schools distinctive and different from other schools and included such features as the school‘s philosophy and the school-based curriculum. In seeking to understand the nature of teacher leadership in Chinese primary schools, this research confirms some findings identified in Western literature. For instance, teacher leaders in Shandong province were involved in decision-making, working with parents and community members, undertaking and planning professional development for staff, and mediating between colleagues (Day & Harris, 2002; Harrison & Killion, 2007; Leithwood, Jantzi, & Steinbach, 1999; Muijs & Harris, 2006; Smylie, 1992). However, some new aspects, such as a heightened awareness of the importance of accountability, emerge from this study. The study‘s conceptual framework also draws upon some significant insights from micropolitics and, in particular, two core constructs, namely cooperation and conflict (Blase, 1991), to explore the interactions between principals and teacher leaders. In this study, principals and teacher leaders employed exchange and facilitation as two strategies in cooperative processes; and they adopted enforcement and compromise in conflictive processes. Finally, the study‘s findings indicate that principals and teacher leaders were developing new ways of interacting in response to the requirements of significant education reform. Most principals were exercising their power through (Blase, 1991) their teacher leaders who in turn, were working in alignment with their principals to achieve the desired outcomes in schools. It was significant that this form of 'parallel leadership' (Crowther, Ferguson, & Ham, 2009) characterised the teacher leadership roles at this period of change to the curriculum in Mainland China.
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O trabalho aborda o estudo e o desenvolvimento de um interferômetro sensor de alta tensão, baseado em célula Pockels (modulador eletro-óptico) na topologia reflexiva (\"double pass\") e que é parte integrante de um Transformador de Potencial Óptico (TPO), que utiliza sistema interferométrico de luz branca (WLI-White Light Interferometry), que está sendo desenvolvido pelo grupo do Laboratório de Sensores Ópticos (LSO) do PEA-EPUSP, e é capaz de medir diretamente tensões presentes em sistema elétrico de potência (SEP) classe 69kVRMS. Para desenvolver o tema proposto foi feita uma revisão da literatura baseada em livros, artigos e teses para identificar topologias em moduladores eletro-ópticos transmissiva (\"single pass\") e reflexiva (\"double pass\") para definir o tipo de modulador mais adequado para a aplicação em questão. A partir dos estudos e implementações realizadas, verificou-se um enorme potencial para o desenvolvimento e aplicação da topologia \"double pass\" no sensor interferométrico da célula de alta tensão do TPO. A topologia mostrou-se vantajosa em relação aos protótipos dos TPOs desenvolvidos anteriormente, a partir de características tais como: a facilidade de recurso de alinhamento do feixe de luz, construção e reprodução relacionados ao cristal eletro-óptico, diminuição do número de componentes ópticos volumétricos e aumento da rigidez dielétrica da célula sensora. Simulações computacionais foram realizadas mediante a aplicação do método dos elementos finitos (MEF) que contribuíram para o auxílio do projeto da célula sensora, particularmente, para estimativa do valor da voltagem de meia onda, V?, parâmetro importante para o projeto do TPO. Um protótipo do TPO com célula sensora de alta tensão reflexiva foi implementado e testado no laboratório de alta tensão do IEEUSP a partir de ensaios com tensões nominais de 69kVrms a 60Hz e máxima de 140kVrms a 60 Hz. Como resultado deste trabalho, amplia-se o conhecimento e domínio das técnicas de construção de interferômetros sensores de alta tensão na topologia reflexiva aplicadas a TPOs.
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A building information model (BIM) provides a rich representation of a building's design. However, there are many challenges in getting construction-specific information from a BIM, limiting the usability of BIM for construction and other downstream processes. This paper describes a novel approach that utilizes ontology-based feature modeling, automatic feature extraction based on ifcXML, and query processing to extract information relevant to construction practitioners from a given BIM. The feature ontology generically represents construction-specific information that is useful for a broad range of construction management functions. The software prototype uses the ontology to transform the designer-focused BIM into a construction-specific feature-based model (FBM). The formal query methods operate on the FBM to further help construction users to quickly extract the necessary information from a BIM. Our tests demonstrate that this approach provides a richer representation of construction-specific information compared to existing BIM tools.
Resumo:
The study was conducted in collaboration with the ECFC project of the FAO (BGD/97/017) in Cox's Bazar to develop a low cost solar tunnel dryer for the production of high quality marine dried fish. The study areas were Kutubdiapara, Maheshkhali and Shahparirdip under Cox's Bazar district. Three different models of low cost solar dryer were constructed with locally available materials such as bamboo, wood, bamboo mat, hemp, canvas, wire, nails, rope, tin, polythene and net. Size of the dryers were: 20x4x3 ft ; 30x3x3 ft and 65x3x3 ft with the costs of Tk. 3060, 3530, 9600 for dryer 1, 2 and 3, respectively having different models. The drying capacities were 50, 150, 500 kg for dryer 1, 2 and 3 respectively. The average temperature range inside the dryers were 29-43°C, 34-51°C and 37-57°C for dryer 1, 2 and 3 respectively as recorded at 8:30h to 16:30h. The relative humidity were in the ranges of 22-42%, 27-39% and 24-41 % in dryer 1, 2 and 3 respectively. The fish samples used were Bombay duck, Silver Jew fish and Ribbon fish. The total drying time was in the range of 30-42, 28-38 and 24-34 hours to reach the moisture content of 12.3-14.5, 11.8-14.3, and 11.6-14.1% in dryer 1, 2 and 3 respectively. Among these three fish samples the drying was faster in Silver Jew fish followed by Bombay duck and Ribbon fish in all the three dryer.
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An important characteristic of virtual assembly is interaction. Traditional di-rect manipulation in virtual assembly relies on dynamic collision detection, which is very time-consuming and even impossible in desktop virtual assembly environment. Feature-matching isa critical process in harmonious virtual assembly, and is the premise of assembly constraint sens-ing. This paper puts forward an active object-based feature-matching perception mechanism and afeature-matching interactive computing process, both of which make the direct manipulation in vir-tual assembly break away from collision detection. They also help to enhance virtual environmentunderstandability of user intention and promote interaction performance. Experimental resultsshow that this perception mechanism can ensure that users achieve real-time direct manipulationin desktop virtual environment.
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On obstacle-cluttered construction sites where heavy equipment is in use, safety issues are of major concern. The main objective of this paper is to develop a framework with algorithms for obstacle avoidance and path planning based on real-time three-dimensional job site models to improve safety during equipment operation. These algorithms have the potential to prevent collisions between heavy equipment vehicles and other on-site objects. In this study, algorithms were developed for image data acquisition, real-time 3D spatial modeling, obstacle avoidance, and shortest path finding and were all integrated to construct a comprehensive collision-free path. Preliminary research results show that the proposed approach is feasible and has the potential to be used as an active safety feature for heavy equipment.
Resumo:
Automated feature extraction and correspondence determination is an extremely important problem in the face recognition community as it often forms the foundation of the normalisation and database construction phases of many recognition and verification systems. This paper presents a completely automatic feature extraction system based upon a modified volume descriptor. These features form a stable descriptor for faces and are utilised in a reversible jump Markov chain Monte Carlo correspondence algorithm to automatically determine correspondences which exist between faces. The developed system is invariant to changes in pose and occlusion and results indicate that it is also robust to minor face deformations which may be present with variations in expression.
Resumo:
Discussion of Attention-Deficit/Hyperactivity Disorder (ADHD) in the media, and thus much popular discourse, typically revolves around the possible causes of disruptive behaviour and the “behaviourally disordered” child. The usual suspects - too much television and video games, food additives, bad parenting, lack of discipline and single mothers – feature prominently as potential contributors to the spiralling rate of ADHD diagnosis in Western industrialised nations, especially the United States and Australia. Conspicuously absent from the field of investigation, however, is the scene of schooling and the influence that the discourses and practices of schooling might bring to bear upon the constitution of “disorderly behaviour” and subsequent recognition of particular children as a particular kind of “disorderly”. This paper reviews a sample of the literature surrounding ADHD, in order to question the function of this absence and, ultimately, make an argument for an interrogation of the school as a site for the production of disorderly objects.
Resumo:
Building information modeling (BIM) is an emerging technology and process that provides rich and intelligent design information models of a facility, enabling enhanced communication, coordination, analysis, and quality control throughout all phases of a building project. Although there are many documented benefits of BIM for construction, identifying essential construction-specific information out of a BIM in an efficient and meaningful way is still a challenging task. This paper presents a framework that combines feature-based modeling and query processing to leverage BIM for construction. The feature-based modeling representation implemented enriches a BIM by representing construction-specific design features relevant to different construction management (CM) functions. The query processing implemented allows for increased flexibility to specify queries and rapidly generate the desired view from a given BIM according to the varied requirements of a specific practitioner or domain. Central to the framework is the formalization of construction domain knowledge in the form of a feature ontology and query specifications. The implementation of our framework enables the automatic extraction and querying of a wide-range of design conditions that are relevant to construction practitioners. The validation studies conducted demonstrate that our approach is significantly more effective than existing solutions. The research described in this paper has the potential to improve the efficiency and effectiveness of decision-making processes in different CM functions.
Resumo:
Identifying the design features that impact construction is essential to developing cost effective and constructible designs. The similarity of building components is a critical design feature that affects method selection, productivity, and ultimately construction cost and schedule performance. However, there is limited understanding of what constitutes similarity in the design of building components and limited computer-based support to identify this feature in a building product model. This paper contributes a feature-based framework for representing and reasoning about component similarity that builds on ontological modelling, model-based reasoning and cluster analysis techniques. It describes the ontology we developed to characterize component similarity in terms of the component attributes, the direction, and the degree of variation. It also describes the generic reasoning process we formalized to identify component similarity in a standard product model based on practitioners' varied preferences. The generic reasoning process evaluates the geometric, topological, and symbolic similarities between components, creates groupings of similar components, and quantifies the degree of similarity. We implemented this reasoning process in a prototype cost estimating application, which creates and maintains cost estimates based on a building product model. Validation studies of the prototype system provide evidence that the framework is general and enables a more accurate and efficient cost estimating process.
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This paper investigates the teaching and learning of fractions to Indigenous adult learners in a Civil Construction Certificate Course. More specifically it explores why the use of materials is critical to building knowledge and understanding. This focus is important for two reasons. First, it allows for considerations of a trainer’s approach for teaching fractions and, second it provides insights into how adult learners can be supported with representing their practical experiences of fractions to make generalisation thus building on their knowledge and learning experiences. The paper draws on teaching episodes from an Australian Research Council funded Linkage project that investigates how mathematics is taught and learned in Certificate Courses, here, Certificate 11 in Civil Construction. Action research and decolonising methods (Smith, 1999) were used to conduct the research. Video excerpts which feature one trainer and three students are analysed and described. Findings from the data indicate that adult learners need to be supported with materials to assist with building their capacity to know and apply understandings of fractions in a range of contexts, besides construction. Without materials and where fractions are taught via pen and paper tasks, students are less likely to retain and apply fraction ideas to their Certificate Course. Further they are less likely to understand decimals because of limited understanding of fractions.
Resumo:
A recurring feature of modern practice is the stress placed on project professionals, with both debilitating effects on the people concerned and indirectly affecting project success. Cost estimation, for example, is an essential task for successful project management involving a high level of uncertainty. It is not surprising, therefore, that young cost estimators especially can become stressful at work due to a lack of experience and the heavy responsibilities involved. However, the concept of work stress and the associated underlying dimensions has not been clearly defined in extant studies in the construction management field. To redress this situation, an updated psychology perceived stress questionnaire (PSQ) , first developed by Levenstein et al (1993) and revised by Fliege et al (2005), is used to explore the dimensions of work stress with empirical evidence from the construction industry in China. With 145 reliable responses from young (less than 5 years’ experience) Chinese cost estimators, this study explores the internal dimensions of work stress, identifying four dimensions of tension, demands, lack of joy and worries. It is suggested that this four-dimensional structure may also be applicable in a more general context.
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We present a systematic, practical approach to developing risk prediction systems, suitable for use with large databases of medical information. An important part of this approach is a novel feature selection algorithm which uses the area under the receiver operating characteristic (ROC) curve to measure the expected discriminative power of different sets of predictor variables. We describe this algorithm and use it to select variables to predict risk of a specific adverse pregnancy outcome: failure to progress in labour. Neural network, logistic regression and hierarchical Bayesian risk prediction models are constructed, all of which achieve close to the limit of performance attainable on this prediction task. We show that better prediction performance requires more discriminative clinical information rather than improved modelling techniques. It is also shown that better diagnostic criteria in clinical records would greatly assist the development of systems to predict risk in pregnancy. We present a systematic, practical approach to developing risk prediction systems, suitable for use with large databases of medical information. An important part of this approach is a novel feature selection algorithm which uses the area under the receiver operating characteristic (ROC) curve to measure the expected discriminative power of different sets of predictor variables. We describe this algorithm and use it to select variables to predict risk of a specific adverse pregnancy outcome: failure to progress in labour. Neural network, logistic regression and hierarchical Bayesian risk prediction models are constructed, all of which achieve close to the limit of performance attainable on this prediction task. We show that better prediction performance requires more discriminative clinical information rather than improved modelling techniques. It is also shown that better diagnostic criteria in clinical records would greatly assist the development of systems to predict risk in pregnancy.