878 resultados para ALGOL (Computer program language)


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Students struggle with learning to program. In recent years, not only has there been a dramatic drop in the number of students enrolling in IT and Computer Science courses, but attrition from these courses continues to be significant. Introductory programming subjects traditionally have high failure rates and as they tend to be core to IT and Computer Science courses can be a road block for many students to their university studies. Is programming really that difficult — or are there other barriers to learning that have a serious and detrimental effect on student progression? In-class experiments were conducted in introductory programming units to confirm our hypothesis that that pair-programming would benefit students' learning to program. We investigated the social and cultural barriers to learning programming by questioning students' perceptions of confidence, difficulty and enjoyment of programming. The results of paired and non-paired students were compared to determine the effect of pair-programming on learning outcomes. Both the empirical and anecdotal results of our experiments strongly supported our hypothesis.

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Health education in Western Countries has grown considerably in the last decade and this has occurred for a number of reasons. Specifically Universities actively recruit International students as the health workforce becomes global; also it is much easier for students to move and study globally. Internationally there is a health workforce shortage and if students gain a degree in a reputable university their ability to work globally is improved significantly. However, when studying to practice in the health care field the student must undertake clinical practice in an acute or aged care setting. This can be a significant problem for students who are culturally and linguistically diverse in an English speaking country such as Australia. The issues that can arise stem from the language differences where communication, interpretation understanding and reading the cultural norms of the health care setting are major challenges for International students. To assist international students to be successful in their clinical education, an extra curriculum workshop program was developed to provide additional support. The program which runs twice each year includes on-campus interactive workshops that are complemented by targeted support provided for students and clinical staff who are supervising students’ practice experience in the workplace. As this is an English speaking country the workshop is based on practicing reading, writing, listening and speaking, as well as exploring basic health care concepts and cultural differences. This enables students to gain knowledge of and practice interpretation of cultural norms and expectations in a safe environment. This innovative series of interactive workshops in a highly student-centred learning environment combine education with role play and discussion with peers who are supported by culturally aware and competent Educators. Over the years it has been running, the program has been undertaken by an increasing number of students. In 2011, more than 100 students are expected to participate. Student evaluation of the program has confirmed that it has assisted the majority of them to be successful in their clinical studies. Effectiveness of the project is measured throughout the program and in follow up sessions. This ongoing information allows for continuous development of the program that serves to meet individual needs of the International student, the University and Service providers such as the hospitals. This feedback from students regarding their increased comprehension of the Australian colloquial Language, healthcare terminology, critical thinking and clinical skill development and a cultural awareness also enables them to maintain their feelings of self confidence and self esteem.

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Intuitively, any ‘bag of words’ approach in IR should benefit from taking term dependencies into account. Unfortunately, for years the results of exploiting such dependencies have been mixed or inconclusive. To improve the situation, this paper shows how the natural language properties of the target documents can be used to transform and enrich the term dependencies to more useful statistics. This is done in three steps. The term co-occurrence statistics of queries and documents are each represented by a Markov chain. The paper proves that such a chain is ergodic, and therefore its asymptotic behavior is unique, stationary, and independent of the initial state. Next, the stationary distribution is taken to model queries and documents, rather than their initial distributions. Finally, ranking is achieved following the customary language modeling paradigm. The main contribution of this paper is to argue why the asymptotic behavior of the document model is a better representation then just the document’s initial distribution. A secondary contribution is to investigate the practical application of this representation in case the queries become increasingly verbose. In the experiments (based on Lemur’s search engine substrate) the default query model was replaced by the stable distribution of the query. Just modeling the query this way already resulted in significant improvements over a standard language model baseline. The results were on a par or better than more sophisticated algorithms that use fine-tuned parameters or extensive training. Moreover, the more verbose the query, the more effective the approach seems to become.

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Data flow analysis techniques can be used to help assess threats to data confidentiality and integrity in security critical program code. However, a fundamental weakness of static analysis techniques is that they overestimate the ways in which data may propagate at run time. Discounting large numbers of these false-positive data flow paths wastes an information security evaluator's time and effort. Here we show how to automatically eliminate some false-positive data flow paths by precisely modelling how classified data is blocked by certain expressions in embedded C code. We present a library of detailed data flow models of individual expression elements and an algorithm for introducing these components into conventional data flow graphs. The resulting models can be used to accurately trace byte-level or even bit-level data flow through expressions that are normally treated as atomic. This allows us to identify expressions that safely downgrade their classified inputs and thereby eliminate false-positive data flow paths from the security evaluation process. To validate the approach we have implemented and tested it in an existing data flow analysis toolkit.

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The Lingodroids are a pair of mobile robots that evolve a language for places and relationships between places (based on distance and direction). Each robot in these studies has its own understanding of the layout of the world, based on its unique experiences and exploration of the environment. Despite having different internal representations of the world, the robots are able to develop a common lexicon for places, and then use simple sentences to explain and understand relationships between places even places that they could not physically experience, such as areas behind closed doors. By learning the language, the robots are able to develop representations for places that are inaccessible to them, and later, when the doors are opened, use those representations to perform goal-directed behavior.

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Service-oriented Architectures (SOA) and Web services leverage the technical value of solutions in the areas of distributed systems and cross-enterprise integration. The emergence of Internet marketplaces for business services is driving the need to describe services, not only from a technical level, but also from a business and operational perspective. While, SOA and Web services reside in an IT layer, organizations owing Internet marketplaces are requiring advertising and trading business services which reside in a business layer. As a result, the gap between business and IT needs to be closed. This paper presents USDL (Unified Service Description Language), a specification language to describe services from a business, operational and technical perspective. USDL plays a major role in the Internet of Services to describe tradable services which are advertised in electronic marketplaces. The language has been tested using two service marketplaces as use cases.

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In the era of Web 2.0, huge volumes of consumer reviews are posted to the Internet every day. Manual approaches to detecting and analyzing fake reviews (i.e., spam) are not practical due to the problem of information overload. However, the design and development of automated methods of detecting fake reviews is a challenging research problem. The main reason is that fake reviews are specifically composed to mislead readers, so they may appear the same as legitimate reviews (i.e., ham). As a result, discriminatory features that would enable individual reviews to be classified as spam or ham may not be available. Guided by the design science research methodology, the main contribution of this study is the design and instantiation of novel computational models for detecting fake reviews. In particular, a novel text mining model is developed and integrated into a semantic language model for the detection of untruthful reviews. The models are then evaluated based on a real-world dataset collected from amazon.com. The results of our experiments confirm that the proposed models outperform other well-known baseline models in detecting fake reviews. To the best of our knowledge, the work discussed in this article represents the first successful attempt to apply text mining methods and semantic language models to the detection of fake consumer reviews. A managerial implication of our research is that firms can apply our design artifacts to monitor online consumer reviews to develop effective marketing or product design strategies based on genuine consumer feedback posted to the Internet.

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Cities accumulate and distribute vast sets of digital information. Many decision-making and planning processes in councils, local governments and organisations are based on both real-time and historical data. Until recently, only a small, carefully selected subset of this information has been released to the public – usually for specific purposes (e.g. train timetables, release of planning application through websites to name just a few). This situation is however changing rapidly. Regulatory frameworks, such as the Freedom of Information Legislation in the US, the UK, the European Union and many other countries guarantee public access to data held by the state. One of the results of this legislation and changing attitudes towards open data has been the widespread release of public information as part of recent Government 2.0 initiatives. This includes the creation of public data catalogues such as data.gov.au (U.S.), data.gov.uk (U.K.), data.gov.au (Australia) at federal government levels, and datasf.org (San Francisco) and data.london.gov.uk (London) at municipal levels. The release of this data has opened up the possibility of a wide range of future applications and services which are now the subject of intensified research efforts. Previous research endeavours have explored the creation of specialised tools to aid decision-making by urban citizens, councils and other stakeholders (Calabrese, Kloeckl & Ratti, 2008; Paulos, Honicky & Hooker, 2009). While these initiatives represent an important step towards open data, they too often result in mere collections of data repositories. Proprietary database formats and the lack of an open application programming interface (API) limit the full potential achievable by allowing these data sets to be cross-queried. Our research, presented in this paper, looks beyond the pure release of data. It is concerned with three essential questions: First, how can data from different sources be integrated into a consistent framework and made accessible? Second, how can ordinary citizens be supported in easily composing data from different sources in order to address their specific problems? Third, what are interfaces that make it easy for citizens to interact with data in an urban environment? How can data be accessed and collected?

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Existing secure software development principles tend to focus on coding vulnerabilities, such as buffer or integer overflows, that apply to individual program statements, or issues associated with the run-time environment, such as component isolation. Here we instead consider software security from the perspective of potential information flow through a program’s object-oriented module structure. In particular, we define a set of quantifiable "security metrics" which allow programmers to quickly and easily assess the overall security of a given source code program or object-oriented design. Although measuring quality attributes of object-oriented programs for properties such as maintainability and performance has been well-covered in the literature, metrics which measure the quality of information security have received little attention. Moreover, existing securityrelevant metrics assess a system either at a very high level, i.e., the whole system, or at a fine level of granularity, i.e., with respect to individual statements. These approaches make it hard and expensive to recognise a secure system from an early stage of development. Instead, our security metrics are based on well-established compositional properties of object-oriented programs (i.e., data encapsulation, cohesion, coupling, composition, extensibility, inheritance and design size), combined with data flow analysis principles that trace potential information flow between high- and low-security system variables. We first define a set of metrics to assess the security quality of a given object-oriented system based on its design artifacts, allowing defects to be detected at an early stage of development. We then extend these metrics to produce a second set applicable to object-oriented program source code. The resulting metrics make it easy to compare the relative security of functionallyequivalent system designs or source code programs so that, for instance, the security of two different revisions of the same system can be compared directly. This capability is further used to study the impact of specific refactoring rules on system security more generally, at both the design and code levels. By measuring the relative security of various programs refactored using different rules, we thus provide guidelines for the safe application of refactoring steps to security-critical programs. Finally, to make it easy and efficient to measure a system design or program’s security, we have also developed a stand-alone software tool which automatically analyses and measures the security of UML designs and Java program code. The tool’s capabilities are demonstrated by applying it to a number of security-critical system designs and Java programs. Notably, the validity of the metrics is demonstrated empirically through measurements that confirm our expectation that program security typically improves as bugs are fixed, but worsens as new functionality is added.

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Teacher education programs bridge the interests of two worlds - the world of educational theory and the world of teaching practice. Despite teacher educators’ best attempts to convince pre-service teachers that theory and practice are linked, it is often during their practicum placements when pre-service teachers claim that their ‘real’ learning takes place. It is also on practicum when students teachers face (and are surprised by) the ‘extensive decision-making role of the teacher, the emotional aspects of teaching, and the sheer volume of work’ (p.4). Kosnick and Beck’s new book Teaching in a Nutshell utilises the authors’ extensive research with beginning teachers to help students ‘navigate’ their way through their programs. Identifying what they have found in their research to be the seven key priorities for teachers, each chapter follows a helpful structure beginning with an overview of current thinking in the priority area, followed by a case study of a beginning teacher showing how s/he implements the strategy...

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Programming is a subject that many beginning students find difficult. This paper describes a knowledge base designed for the purpose of analyzing programs written in the PHP web development language. The aim is to use this knowledge base in an Intelligent Tutoring System that will provide effective feedback to students. The main focus of this research is that a programming exercise can have many correct solutions. This paper presents an overview of how the proposed knowledge base can be utilized to accept different solutions to a given exercise

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Programming is a subject that many beginning students students find difficult. This paper descibes a knowledge base designed for the purpose of analyzing programs written in the PHP web development language. The aim is to use this knowledge base in an Intelligent Tutoring System. The main emphasis is on accepting alternative solutions to a given problem.

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Nowadays, Workflow Management Systems (WfMSs) and, more generally, Process Management Systems (PMPs) are process-aware Information Systems (PAISs), are widely used to support many human organizational activities, ranging from well-understood, relatively stable and structures processes (supply chain management, postal delivery tracking, etc.) to processes that are more complicated, less structured and may exhibit a high degree of variation (health-care, emergency management, etc.). Every aspect of a business process involves a certain amount of knowledge which may be complex depending on the domain of interest. The adequate representation of this knowledge is determined by the modeling language used. Some processes behave in a way that is well understood, predictable and repeatable: the tasks are clearly delineated and the control flow is straightforward. Recent discussions, however, illustrate the increasing demand for solutions for knowledge-intensive processes, where these characteristics are less applicable. The actors involved in the conduct of a knowledge-intensive process have to deal with a high degree of uncertainty. Tasks may be hard to perform and the order in which they need to be performed may be highly variable. Modeling knowledge-intensive processes can be complex as it may be hard to capture at design-time what knowledge is available at run-time. In realistic environments, for example, actors lack important knowledge at execution time or this knowledge can become obsolete as the process progresses. Even if each actor (at some point) has perfect knowledge of the world, it may not be certain of its beliefs at later points in time, since tasks by other actors may change the world without those changes being perceived. Typically, a knowledge-intensive process cannot be adequately modeled by classical, state of the art process/workflow modeling approaches. In some respect there is a lack of maturity when it comes to capturing the semantic aspects involved, both in terms of reasoning about them. The main focus of the 1st International Workshop on Knowledge-intensive Business processes (KiBP 2012) was investigating how techniques from different fields, such as Artificial Intelligence (AI), Knowledge Representation (KR), Business Process Management (BPM), Service Oriented Computing (SOC), etc., can be combined with the aim of improving the modeling and the enactment phases of a knowledge-intensive process. The 1st International Workshop on Knowledge-intensive Business process (KiBP 2012) was held as part of the program of the 2012 Knowledge Representation & Reasoning International Conference (KR 2012) in Rome, Italy, in June 2012. The workshop was hosted by the Dipartimento di Ingegneria Informatica, Automatica e Gestionale Antonio Ruberti of Sapienza Universita di Roma, with financial support of the University, through grant 2010-C26A107CN9 TESTMED, and the EU Commission through the projects FP7-25888 Greener Buildings and FP7-257899 Smart Vortex. This volume contains the 5 papers accepted and presented at the workshop. Each paper was reviewed by three members of the internationally renowned Program Committee. In addition, a further paper was invted for inclusion in the workshop proceedings and for presentation at the workshop. There were two keynote talks, one by Marlon Dumas (Institute of Computer Science, University of Tartu, Estonia) on "Integrated Data and Process Management: Finally?" and the other by Yves Lesperance (Department of Computer Science and Engineering, York University, Canada) on "A Logic-Based Approach to Business Processes Customization" completed the scientific program. We would like to thank all the Program Committee members for the valuable work in selecting the papers, Andrea Marrella for his valuable work as publication and publicity chair of the workshop, and Carola Aiello and the consulting agency Consulta Umbria for the organization of this successful event.

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A breaker restrike is an abnormal arcing phenomenon, leading to a possible breaker failure. Eventually, this failure leads to interruption of the transmission and distribution of the electricity supply system until the breaker is replaced. Before 2008, there was little evidence in the literature of monitoring techniques based on restrike measurement and interpretation produced during switching of capacitor banks and shunt reactor banks in power systems. In 2008 a non-intrusive radiometric restrike measurement method and a restrike hardware detection algorithm were developed by M.S. Ramli and B. Kasztenny. However, the limitations of the radiometric measurement method are a band limited frequency response as well as limitations in amplitude determination. Current restrike detection methods and algorithms require the use of wide bandwidth current transformers and high voltage dividers. A restrike switch model using Alternative Transient Program (ATP) and Wavelet Transforms which support diagnostics are proposed. Restrike phenomena become a new diagnostic process using measurements, ATP and Wavelet Transforms for online interrupter monitoring. This research project investigates the restrike switch model Parameter „A. dielectric voltage gradient related to a normal and slowed case of the contact opening velocity and the escalation voltages, which can be used as a diagnostic tool for a vacuum circuit-breaker (CB) at service voltages between 11 kV and 63 kV. During current interruption of an inductive load at current quenching or chopping, a transient voltage is developed across the contact gap. The dielectric strength of the gap should rise to a point to withstand this transient voltage. If it does not, the gap will flash over, resulting in a restrike. A straight line is fitted through the voltage points at flashover of the contact gap. This is the point at which the gap voltage has reached a value that exceeds the dielectric strength of the gap. This research shows that a change in opening contact velocity of the vacuum CB produces a corresponding change in the slope of the gap escalation voltage envelope. To investigate the diagnostic process, an ATP restrike switch model was modified with contact opening velocity computation for restrike waveform signature analyses along with experimental investigations. This also enhanced a mathematical CB model with the empirical dielectric model for SF6 (sulphur hexa-fluoride) CBs at service voltages above 63 kV and a generalised dielectric curve model for 12 kV CBs. A CB restrike can be predicted if there is a similar type of restrike waveform signatures for measured and simulated waveforms. The restrike switch model applications are used for: computer simulations as virtual experiments, including predicting breaker restrikes; estimating the interrupter remaining life of SF6 puffer CBs; checking system stresses; assessing point-on-wave (POW) operations; and for a restrike detection algorithm development using Wavelet Transforms. A simulated high frequency nozzle current magnitude was applied to an Equation (derived from the literature) which can calculate the life extension of the interrupter of a SF6 high voltage CB. The restrike waveform signatures for a medium and high voltage CB identify its possible failure mechanism such as delayed opening, degraded dielectric strength and improper contact travel. The simulated and measured restrike waveform signatures are analysed using Matlab software for automatic detection. Experimental investigation of a 12 kV vacuum CB diagnostic was carried out for the parameter determination and a passive antenna calibration was also successfully developed with applications for field implementation. The degradation features were also evaluated with a predictive interpretation technique from the experiments, and the subsequent simulation indicates that the drop in voltage related to the slow opening velocity mechanism measurement to give a degree of contact degradation. A predictive interpretation technique is a computer modeling for assessing switching device performance, which allows one to vary a single parameter at a time; this is often difficult to do experimentally because of the variable contact opening velocity. The significance of this thesis outcome is that it is a non-intrusive method developed using measurements, ATP and Wavelet Transforms to predict and interpret a breaker restrike risk. The measurements on high voltage circuit-breakers can identify degradation that can interrupt the distribution and transmission of an electricity supply system. It is hoped that the techniques for the monitoring of restrike phenomena developed by this research will form part of a diagnostic process that will be valuable for detecting breaker stresses relating to the interrupter lifetime. Suggestions for future research, including a field implementation proposal to validate the restrike switch model for ATP system studies and the hot dielectric strength curve model for SF6 CBs, are given in Appendix A.

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The University of Newcastle (UoN) offers various access and support programs for a range of students through the English Language and Foundation Studies Centre and a University orientation for students. At UoN, students are required to engage in a learning experience, meet program outcomes and demonstrate the core attributes of the University at each graduation point. For a University with a strong focus on access is there a missing facet to the access programs where students are required to study within a teaching delivery style which may be vastly different to their previous educational experience? This paper will describe a pedagogical orientation program currently delivered at UoN School of Architecture and Built Environment in 2005 to assist in the transition of students from different cultural and pedagogical backgrounds into “Problem Based Learning” as delivered by this School. Furthermore the paper will analyse how this program has enabled students from diverse backgrounds to understand and successfully embrace the new learning opportunities.