984 resultados para Computer Forensics, Profiling
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This thesis investigates profiling and differentiating customers through the use of statistical data mining techniques. The business application of our work centres on examining individuals’ seldomly studied yet critical consumption behaviour over an extensive time period within the context of the wireless telecommunication industry; consumption behaviour (as oppose to purchasing behaviour) is behaviour that has been performed so frequently that it become habitual and involves minimal intentions or decision making. Key variables investigated are the activity initialised timestamp and cell tower location as well as the activity type and usage quantity (e.g., voice call with duration in seconds); and the research focuses are on customers’ spatial and temporal usage behaviour. The main methodological emphasis is on the development of clustering models based on Gaussian mixture models (GMMs) which are fitted with the use of the recently developed variational Bayesian (VB) method. VB is an efficient deterministic alternative to the popular but computationally demandingMarkov chainMonte Carlo (MCMC) methods. The standard VBGMMalgorithm is extended by allowing component splitting such that it is robust to initial parameter choices and can automatically and efficiently determine the number of components. The new algorithm we propose allows more effective modelling of individuals’ highly heterogeneous and spiky spatial usage behaviour, or more generally human mobility patterns; the term spiky describes data patterns with large areas of low probability mixed with small areas of high probability. Customers are then characterised and segmented based on the fitted GMM which corresponds to how each of them uses the products/services spatially in their daily lives; this is essentially their likely lifestyle and occupational traits. Other significant research contributions include fitting GMMs using VB to circular data i.e., the temporal usage behaviour, and developing clustering algorithms suitable for high dimensional data based on the use of VB-GMM.
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This study investigated whether conceptual development is greater if students learning senior chemistry hear teacher explanations and other traditional teaching approaches first then see computer based visualizations or vice versa. Five Canadian chemistry classes, taught by three different teachers, studied the topics of Le Chatelier’s Principle and dynamic chemical equilibria using scientific visualizations with the explanation and visualizations in different orders. Conceptual development was measured using a 12 item test based on the Chemistry Concepts Inventory. Data was obtained about the students’ abilities, learning styles (auditory, visual or kinesthetic) and sex, and the relationships between these factors and conceptual development due to the teaching sequences were investigated. It was found that teaching sequence is not important in terms of students’ conceptual learning gains, across the whole cohort or for any of the three subgroups.
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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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Visual modes of representation have always been very important in science and science education. Interactive computer-based animations and simulations offer new visual resources for chemistry education. Many studies have shown that students enjoy learning with visualisations but few have explored how learning outcomes compare when teaching with or without visualisations. This study employs a quasi-experimental crossover research design and quantitative methods to measure the educational effectiveness - defined as level of conceptual development on the part of students - of using computer-based scientific visualisations versus teaching without visualisations in teaching chemistry. In addition to finding that teaching with visualisations offered outcomes that were not significantly different from teaching without visualisations, the study also explored differences in outcomes for male and female students, students with different learning styles (visual, aural, kinesthetic) and students of differing levels of academic ability.
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Discovering proper search intents is a vi- tal process to return desired results. It is constantly a hot research topic regarding information retrieval in recent years. Existing methods are mainly limited by utilizing context-based mining, query expansion, and user profiling techniques, which are still suffering from the issue of ambiguity in search queries. In this pa- per, we introduce a novel ontology-based approach in terms of a world knowledge base in order to construct personalized ontologies for identifying adequate con- cept levels for matching user search intents. An iter- ative mining algorithm is designed for evaluating po- tential intents level by level until meeting the best re- sult. The propose-to-attempt approach is evaluated in a large volume RCV1 data set, and experimental results indicate a distinct improvement on top precision after compared with baseline models.
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Internet and computer addiction has been a popular research area since the 90s. Studies on Internet and computer addiction have usually been conducted in the US, and the investigation of computer and Internet addiction at different countries is an interesting area of research. This study investigates computer and Internet addiction among teenagers and Internet cafe visitors in Turkey. We applied a survey to 983 visitors in the Internet cafes. The results show that the Internet cafe visitors are usually teenagers, mostly middle and high-school students and usually are busy with computer and Internet applications like chat, e-mail, browsing and games. The teenagers come to the Internet cafe to spend time with friends and the computers. In addition, about 30% of cafe visitors admit to having an Internet addiction, and about 20% specifically mention the problems that they are having with the Internet. It is rather alarming to consider the types of activities that the teenagers are performing in an Internet cafe, their reasons for being there, the percentage of self-awareness about Internet addiction, and the lack of control of applications in the cafe.
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The purpose of this paper is to study the profiling of property, plant and equipment (PPE) contributions in Australia and Malaysia construction companies. A company’s worth is usually based on the listed share price on the stock exchange. In arriving at the net profit, the contribution of PPE in the company’s assets is somehow being neglected. This paper will investigate the followings; firstly the level of PPE contribution in the construction firms by comparing the PPE contributions to the company’s asset as a whole which includes fixed (non-current) assets and current assets. This will determine the true strength of the companies, rather than relying on the share prices alone. Secondly, the paper will determine the trend of company’s asset ownership to show the company’s performance of the PPE ownership during the period of study. The data is based on the selected construction companies listed on the Australian Stock Exchange (ASX) and Malaysian Stock Exchange, known as Bursa Malaysia. The profiling will help to determine the strength of the construction firms based on the PPE holding, and the level of PPE ownerships in the two countries construction firms during the period of study.
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A time-resolved inverse spatially offset Raman spectrometer was constructed for depth profiling of Raman-active substances under both the lab and the field environments. The system operating principles and performance are discussed along with its advantages relative to traditional continuous wave spatially offset Raman spectrometer. The developed spectrometer uses a combination of space- and time-resolved detection in order to obtain high-quality Raman spectra from substances hidden behind coloured opaque surface layers, such as plastic and garments, with a single measurement. The time-gated spatially offset Raman spectrometer was successfully used to detect concealed explosives and drug precursors under incandescent and fluorescent background light as well as under daylight. The average screening time was 50 s per measurement. The excitation energy requirements were relatively low (20 mW) which makes the probe safe for screening hazardous substances. The unit has been designed with nanosecond laser excitation and gated detection, making it of lower cost and complexity than previous picosecond-based systems, to provide a functional platform for in-line or in-field sensing of chemical substances.
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It is a big challenge to acquire correct user profiles for personalized text classification since users may be unsure in providing their interests. Traditional approaches to user profiling adopt machine learning (ML) to automatically discover classification knowledge from explicit user feedback in describing personal interests. However, the accuracy of ML-based methods cannot be significantly improved in many cases due to the term independence assumption and uncertainties associated with them. This paper presents a novel relevance feedback approach for personalized text classification. It basically applies data mining to discover knowledge from relevant and non-relevant text and constraints specific knowledge by reasoning rules to eliminate some conflicting information. We also developed a Dempster-Shafer (DS) approach as the means to utilise the specific knowledge to build high-quality data models for classification. The experimental results conducted on Reuters Corpus Volume 1 and TREC topics support that the proposed technique achieves encouraging performance in comparing with the state-of-the-art relevance feedback models.
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Local climate is a critical element in the design of buildings. In this paper, ten years of historical weather data in Australia's all eight capital cities are analyzed to characterize the variation profiles of climatic variables. The method of descriptive statistics is employed. Either the pattern of cumulative distribution and/or the profile of percentage distribution are used to graphically illustrate the similarity and difference between different study locations. It is found that although the weather variables vary with different locations, except for the extreme parts, there is often a good, nearly linear relation between weather variable and its cumulative percentage for the majority of middle part. The implication of these extreme parts and the slopes of the middle parts on building design is also discussed.
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The purpose of this study is to understand the constructs of work motivation in project-based organizations. We first juxtapose work motivation in traditional and project-based organizations to put forward an operational definition of work motivation for our study. We then present the research methodology where we profile work motivation as perceived by project workers using principal component analysis. We obtain a five factor structure of work motivation. Finally, we discuss these results by putting them within the project management perspective and suggest managerial implications.
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The purpose of this study is to understand the constructs of work motivation in project—based organizations. We first juxtapose work motivation in traditional and project—based organizations to put forward an operational definition of work motivation for our study. We then present the research methodology where we profile work motivation as perceived by project workers using principal component analysis. We obtain a five factor structure of work motivation. Finally, we discuss these results by putting them within the project management perspective and suggest managerial implications.
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Early-stage treatments for osteoarthritis are attracting considerable interest as a means to delay, or avoid altogether, the pain and lack of mobility associated with late-stage disease, and the considerable burden that it places on the community. With the development of these treatments comes a need to assess the tissue to which they are applied, both in trialling of new treatments and as an aid to clinical decision making. Here, we measure a range of mechanical indentation, ultrasound and near-infrared spectroscopy parameters in normal and osteoarthritic bovine joints in vitro to describe the role of different physical phenomena in disease progression, using this as a basis to investigate the potential value of the techniques as clinical tools. Based on 72 samples we found that mechanical and ultrasound parameters showed differences between fibrillated tissue, macroscopically normal tissue in osteoarthritic joints, and normal tissue, yet did were unable to differentiate degradation beyond that which was visible to the naked eye. Near-infrared spectroscopy showed a clear progression of degradation across the visibly normal osteoarthritic joint surface and as such, was the only technique considered useful for clinical application.