984 resultados para Computational-Linguistic resource
Resumo:
Immigrant Entrepreneurs (IE) are often portrayed as pushed into self-employment due to employment barriers in their adopted countries. But IE have human resources, like international experience, which can help them form international new ventures (INV). We question the role of IE in INV. We use randomly selected data from 561 young firms from the Comprehensive Australian Study of Entrepreneurial Emergence (CAUSEE) project. We find that IE are over-represented in INV and have many characteristics known to facilitate INV success including more founders, university degree, international connections and technical capability. These findings are relevant to policy makers, and nascent IE.
Resumo:
The interoperable and loosely-coupled web services architecture, while beneficial, can be resource-intensive, and is thus susceptible to denial of service (DoS) attacks in which an attacker can use a relatively insignificant amount of resources to exhaust the computational resources of a web service. We investigate the effectiveness of defending web services from DoS attacks using client puzzles, a cryptographic countermeasure which provides a form of gradual authentication by requiring the client to solve some computationally difficult problems before access is granted. In particular, we describe a mechanism for integrating a hash-based puzzle into existing web services frameworks and analyze the effectiveness of the countermeasure using a variety of scenarios on a network testbed. Client puzzles are an effective defence against flooding attacks. They can also mitigate certain types of semantic-based attacks, although they may not be the optimal solution.
Resumo:
Evidence suggests that both start-up and young firms (henceforth: new firms) – despite typically being resource-constrained – are sometimes able to innovate (Katila & Shane 2005). Such firms are seldom able to invest in expensive innovation processes, which suggests that they may rely on other pathways to innovation. In this paper, we test arguments that “bricolage,” defined as making do by applying combinations of the resources at hand to new problems and opportunities, provides a pathway to innovation for new firms. Our results suggest that variations in bricolage behaviors can provide an explanation of innovation under resource constraints by new firms.
Resumo:
Computational journalism involves the application of software and technologies to the activities of journalism, and it draws from the fields of computer science, the social sciences, and media and communications. New technologies may enhance the traditional aims of journalism, or may initiate greater interaction between journalists and information and communication technology (ICT) specialists. The enhanced use of computing in news production is related in particular to three factors: larger government data sets becoming more widely available; the increasingly sophisticated and ubiquitous nature of software; and the developing digital economy. Drawing upon international examples, this paper argues that computational journalism techniques may provide new foundations for original investigative journalism and increase the scope for new forms of interaction with readers. Computer journalism provides a major opportunity to enhance the delivery of original investigative journalism, and to attract and retain readers online.
Resumo:
This chapter focuses on the interactions and roles between delays and intrinsic noise effects within cellular pathways and regulatory networks. We address these aspects by focusing on genetic regulatory networks that share a common network motif, namely the negative feedback loop, leading to oscillatory gene expression and protein levels. In this context, we discuss computational simulation algorithms for addressing the interplay of delays and noise within the signaling pathways based on biological data. We address implementational issues associated with efficiency and robustness. In a molecular biology setting we present two case studies of temporal models for the Hes1 gene (Monk, 2003; Hirata et al., 2002), known to act as a molecular clock, and the Her1/Her7 regulatory system controlling the periodic somite segmentation in vertebrate embryos (Giudicelli and Lewis, 2004; Horikawa et al., 2006).
Resumo:
Concerns raised in educational reports about school science in terms of students. outcomes and attitudes, as well as science teaching practices prompted investigation into science learning and teaching practices at the foundational level of school science. Without science content and process knowledge, understanding issues of modern society and active participation in decision-making is difficult. This study contended that a focus on the development of the language of science could enable learners to engage more effectively in learning science and enhance their interest and attitudes towards science. Furthermore, it argued that explicit teaching practices where science language is modelled and scaffolded would facilitate the learning of science by young children at the beginning of their formal schooling. This study aimed to investigate science language development at the foundational level of school science learning in the preparatory-school with students aged five and six years. It focussed on the language of science and science teaching practices in early childhood. In particular, the study focussed on the capacity for young students to engage with and understand science language. Previous research suggests that students have difficulty with the language of science most likely because of the complexities and ambiguities of science language. Furthermore, literature indicates that tensions transpire between traditional science teaching practices and accepted early childhood teaching practices. This contention prompted investigation into means and models of pedagogy for learning foundational science language, knowledge and processes in early childhood. This study was positioned within qualitative assumptions of research and reported via descriptive case study. It was located in a preparatory-school classroom with the class teacher, teacher-aide, and nineteen students aged four and five years who participated with the researcher in the study. Basil Bernstein.s pedagogical theory coupled with Halliday.s Systemic Functional Linguistics (SFL) framed an examination of science pedagogical practices for early childhood science learning. Students. science learning outcomes were gauged by focussing a Hallydayan lens on their oral and reflective language during 12 science-focussed episodes of teaching. Data were collected throughout the 12 episodes. Data included video and audio-taped science activities, student artefacts, journal and anecdotal records, semi-structured interviews and photographs. Data were analysed according to Bernstein.s visible and invisible pedagogies and performance and competence models. Additionally, Halliday.s SFL provided the resource to examine teacher and student language to determine teacher/student interpersonal relationships as well as specialised science and everyday language used in teacher and student science talk. Their analysis established the socio-linguistic characteristics that promoted science competencies in young children. An analysis of the data identified those teaching practices that facilitate young children.s acquisition of science meanings. Positive indications for modelling science language and science text types to young children have emerged. Teaching within the studied setting diverged from perceived notions of common early childhood practices and the benefits of dynamic shifting pedagogies were validated. Significantly, young students demonstrated use of particular specialised components of school-science language in terms of science language features and vocabulary. As well, their use of language demonstrated the students. knowledge of science concepts, processes and text types. The young students made sense of science phenomena through their incorporation of a variety of science language and text-types in explanations during both teacher-directed and independent situations. The study informs early childhood science practices as well as practices for foundational school science teaching and learning. It has exposed implications for science education policy, curriculum and practices. It supports other findings in relation to the capabilities of young students. The study contributes to Systemic Functional Linguistic theory through the development of a specific resource to determine the technicality of teacher language used in teaching young students. Furthermore, the study contributes to methodology practices relating to Bernsteinian theoretical perspectives and has demonstrated new ways of depicting and reporting teaching practices. It provides an analytical tool which couples Bernsteinian and Hallidayan theoretical perspectives. Ultimately, it defines directions for further research in terms of foundation science language learning, ongoing learning of the language of science and learning science, science teaching and learning practices, specifically in foundational school science, and relationships between home and school science language experiences.
Resumo:
Abstract—Computational Intelligence Systems (CIS) is one of advanced softwares. CIS has been important position for solving single-objective / reverse / inverse and multi-objective design problems in engineering. The paper hybridise a CIS for optimisation with the concept of Nash-Equilibrium as an optimisation pre-conditioner to accelerate the optimisation process. The hybridised CIS (Hybrid Intelligence System) coupled to the Finite Element Analysis (FEA) tool and one type of Computer Aided Design(CAD) system; GiD is applied to solve an inverse engineering design problem; reconstruction of High Lift Systems (HLS). Numerical results obtained by the hybridised CIS are compared to the results obtained by the original CIS. The benefits of using the concept of Nash-Equilibrium are clearly demonstrated in terms of solution accuracy and optimisation efficiency.
Resumo:
Web service technology is increasingly being used to build various e-Applications, in domains such as e-Business and e-Science. Characteristic benefits of web service technology are its inter-operability, decoupling and just-in-time integration. Using web service technology, an e-Application can be implemented by web service composition — by composing existing individual web services in accordance with the business process of the application. This means the application is provided to customers in the form of a value-added composite web service. An important and challenging issue of web service composition, is how to meet Quality-of-Service (QoS) requirements. This includes customer focused elements such as response time, price, throughput and reliability as well as how to best provide QoS results for the composites. This in turn best fulfils customers’ expectations and achieves their satisfaction. Fulfilling these QoS requirements or addressing the QoS-aware web service composition problem is the focus of this project. From a computational point of view, QoS-aware web service composition can be transformed into diverse optimisation problems. These problems are characterised as complex, large-scale, highly constrained and multi-objective problems. We therefore use genetic algorithms (GAs) to address QoS-based service composition problems. More precisely, this study addresses three important subproblems of QoS-aware web service composition; QoS-based web service selection for a composite web service accommodating constraints on inter-service dependence and conflict, QoS-based resource allocation and scheduling for multiple composite services on hybrid clouds, and performance-driven composite service partitioning for decentralised execution. Based on operations research theory, we model the three problems as a constrained optimisation problem, a resource allocation and scheduling problem, and a graph partitioning problem, respectively. Then, we present novel GAs to address these problems. We also conduct experiments to evaluate the performance of the new GAs. Finally, verification experiments are performed to show the correctness of the GAs. The major outcomes from the first problem are three novel GAs: a penaltybased GA, a min-conflict hill-climbing repairing GA, and a hybrid GA. These GAs adopt different constraint handling strategies to handle constraints on interservice dependence and conflict. This is an important factor that has been largely ignored by existing algorithms that might lead to the generation of infeasible composite services. Experimental results demonstrate the effectiveness of our GAs for handling the QoS-based web service selection problem with constraints on inter-service dependence and conflict, as well as their better scalability than the existing integer programming-based method for large scale web service selection problems. The major outcomes from the second problem has resulted in two GAs; a random-key GA and a cooperative coevolutionary GA (CCGA). Experiments demonstrate the good scalability of the two algorithms. In particular, the CCGA scales well as the number of composite services involved in a problem increases, while no other algorithms demonstrate this ability. The findings from the third problem result in a novel GA for composite service partitioning for decentralised execution. Compared with existing heuristic algorithms, the new GA is more suitable for a large-scale composite web service program partitioning problems. In addition, the GA outperforms existing heuristic algorithms, generating a better deployment topology for a composite web service for decentralised execution. These effective and scalable GAs can be integrated into QoS-based management tools to facilitate the delivery of feasible, reliable and high quality composite web services.
Resumo:
Increasing global competitiveness worldwide has forced manufacturing organizations to produce high-quality products more quickly and at a competitive cost. In order to reach these goals, they need good quality components from suppliers at optimum price and lead time. This actually forced all the companies to adapt different improvement practices such as lean manufacturing, Just in Time (JIT) and effective supply chain management. Applying new improvement techniques and tools cause higher establishment costs and more Information Delay (ID). On the contrary, these new techniques may reduce the risk of stock outs and affect supply chain flexibility to give a better overall performance. But industry people are unable to measure the overall affects of those improvement techniques with a standard evaluation model .So an effective overall supply chain performance evaluation model is essential for suppliers as well as manufacturers to assess their companies under different supply chain strategies. However, literature on lean supply chain performance evaluation is comparatively limited. Moreover, most of the models assumed random values for performance variables. The purpose of this paper is to propose an effective supply chain performance evaluation model using triangular linguistic fuzzy numbers and to recommend optimum ranges for performance variables for lean implementation. The model initially considers all the supply chain performance criteria (input, output and flexibility), converts the values to triangular linguistic fuzzy numbers and evaluates overall supply chain performance under different situations. Results show that with the proposed performance measurement model, improvement area for each variable can be accurately identified.
Is the public sector ready to collaborate? Human resource implications of collaborative Arrangements
Resumo:
Relational governance arrangements across agencies and sectors have become prevalent as a means for government to become more responsive and effective in addressing complex, large scale or ‘wicked’ problems. The primary characteristic of such ‘collaborative’ arrangements is the utilisation of the joint capacities of multiple organisations to achieve collaborative advantage, which Huxham (1993) defines as the attainment of creative outcomes that are beyond the ability of single agencies to achieve. Attaining collaborative advantage requires organisations to develop collaborative capabilities that prepare organisations for collaborative practice (Huxham, 1993b). Further, collaborations require considerable investment of staff effort that could potentially be used beneficially elsewhere by both the government and non-government organisations involved in collaboration (Keast and Mandell, 2010). Collaborative arrangements to deliver services therefore requires a reconsideration of the way in which resources, including human resources, are conceptualised and deployed as well as changes to both the structure of public service agencies and the systems and processes by which they operate (Keast, forthcoming). A main aim of academic research and theorising has been to explore and define the requisite characteristics to achieve collaborative advantage. Such research has tended to focus on definitional, structural (Turrini, Cristofoli, Frosini, & Nasi, 2009) and organisational (Huxham, 1993) aspects and less on the roles government plays within cross-organisational or cross-sectoral arrangements. Ferlie and Steane (2002) note that there has been a general trend towards management led reforms of public agencies including the HRM practices utilised. Such trends have been significantly influenced by New Public Management (NPM) ideology with limited consideration to the implications for HRM practice in collaborative, rather than market contexts. Utilising case study data of a suite of collaborative efforts in Queensland, Australia, collected over a decade, this paper presents an examination of the network roles government agencies undertake. Implications for HRM in public sector agencies working within networked arrangements are drawn and implications for job design, recruitment, deployment and staff development are presented. The paper also makes theoretical advances in our understanding of Strategic Human Resource Management (SHRM) in network settings. While networks form part of the strategic armoury of government, networks operate to achieve collaborative advantage. SHRM with its focus on competitive advantage is argued to be appropriate in market situations, however is not an ideal conceptualisation in network situations. Commencing with an overview of literature on networks and network effectiveness, the paper presents the case studies and methodology; provides findings from the case studies in regard to the roles of government to achieve collaborative advantage and implications for HRM practice are presented. Implications for SHRM are considered.
An experimental and computational investigation of performance of Green Gully for reusing stormwater
Resumo:
A new stormwater quality improvement device (SQID) called ‘Green Gully’ has been designed and developed in this study with an aim to re-using stormwater for irrigating plants and trees. The main purpose of the Green Gully is to collect road runoff/stormwater, make it suitable for irrigation and provide an automated network system for watering roadside plants and irrigational areas. This paper presents the design and development of Green Gully along with experimental and computational investigations of the performance of Green Gully. Performance (in the form of efficiency, i.e. the percentage of water flow through the gully grate) was experimentally determined using a gully model in the laboratory first, then a three dimensional numerical model was developed and simulated to predict the efficiency of Green Gully as a function of flow rate. Computational Fluid Dynamics (CFD) code FLUENT was used for the simulation. GAMBIT was used for geometry creation and mesh generation. Experimental and simulation results are discussed and compared in this paper. The predicted efficiency was compared with the laboratory measured efficiency. It was found that the simulated results are in good agreement with the experimental results.