| 1. |
- Abrahamsson, Henrik, et al.
(författare)
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Simulation of IPTV caching strategies
- 2010. - 6
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Ingår i: Proceedings of the 2010 International Symposium on Performance Evaluation of Computer and Telecommunication Systems. ; , s. 187-193
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Konferensbidrag (refereegranskat)abstract
- IPTV, where television is distributed over the Internet Protocol in a single operator network, has become popular and widespread. Many telecom and broadband companies have become TV providers and distribute TV channels using multicast over their backbone networks. IPTV also means an evolution to time-shifted television where viewers now often can choose to watch the programs at any time. However, distributing individual TV streams to each viewer requires a lot of bandwidth and is a big challenge for TV operators. In this paper we present an empirical IPTV workload model, simulate IPTV distribution with time-shift, and show that local caching can limit the bandwidth requirements significantly.
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| 2. |
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| 3. |
- Adolfsson, Margareta, 1950-, et al.
(författare)
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Exploring changes over time in habilitation professionals' perceptions and applications of the International Classification of Functioning, Disability and Health, version for Children and Youth (ICF-CY).
- 2010
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Ingår i: Journal of Rehabilitation Medicine. - : Medical Journals Sweden AB. - 1650-1977 .- 1651-2081. ; 42:7, s. 670-678
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE This study explored how professionals in inter-disciplinary teams perceived the implementation of the World Health Organization's International Classification of Functioning, Disability and Health, version for Children and Youth (ICF-CY) in Swedish habilitation services. DESIGN Descriptive longitudinal mixed-methods design. METHODS Following participation in a 2-day in-service training on the ICF-CY, 113 professionals from 14 interdisciplinary teams described their perceptions of the implementation of the ICF-CY at 3 consecutive time-points: during in-service training, after 1 year, and after 2.5 years. RESULTS Implementation of the ICF-CY in daily work focused on assessment and habilitation planning and required adaptations of routines and materials. The ICF-CY was perceived as useful in supporting analyses and in communication about children's needs. Professionals also perceived it as contributing to new perspectives on problems and a sharpened focus on participation. CONCLUSION Professionals indicated that the ICF-CY enhanced their awareness of families' views of child participation, which corresponded to organizational goals for habilitation services. An implementation finding was a lack of tools fitting the comprehensive ICF-CY perspective. The study points to the need for ICF-CY-based assessment and intervention methods focusing on child participation
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| 4. |
- Afzal, Wasif, et al.
(författare)
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Genetic programming for cross-release fault count predictions in large and complex software projects
- 2010
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Ingår i: Evolutionary Computation and Optimization Algorithms in Software Engineering. - : IGI Global, Hershey, USA. - 9781615208098
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Bokkapitel (refereegranskat)abstract
- Software fault prediction can play an important role in ensuring software quality through efficient resource allocation. This could, in turn, reduce the potentially high consequential costs due to faults. Predicting faults might be even more important with the emergence of short-timed and multiple software releases aimed at quick delivery of functionality. Previous research in software fault prediction has indicated that there is a need i) to improve the validity of results by having comparisons among number of data sets from a variety of software, ii) to use appropriate model evaluation measures and iii) to use statistical testing procedures. Moreover, cross-release prediction of faults has not yet achieved sufficient attention in the literature. In an attempt to address these concerns, this paper compares the quantitative and qualitative attributes of 7 traditional and machine-learning techniques for modeling the cross-release prediction of fault count data. The comparison is done using extensive data sets gathered from a total of 7 multi-release open-source and industrial software projects. These software projects together have several years of development and are from diverse application areas, ranging from a web browser to a robotic controller software. Our quantitative analysis suggests that genetic programming (GP) tends to have better consistency in terms of goodness of fit and accuracy across majority of data sets. It also has comparatively less model bias. Qualitatively, ease of configuration and complexity are less strong points for GP even though it shows generality and gives transparent models. Artificial neural networks did not perform as well as expected while linear regression gave average predictions in terms of goodness of fit and accuracy. Support vector machine regression and traditional software reliability growth models performed below average on most of the quantitative evaluation criteria while remained on average for most of the qualitative measures.
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| 5. |
- Afzal, Wasif, et al.
(författare)
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Search-based prediction of fault-slip-through in large software projects
- 2010
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Ingår i: Proceedings - 2nd International Symposium on Search Based Software Engineering, SSBSE 2010. - : IEEE. - 9780769541952 ; , s. 79-88
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Konferensbidrag (refereegranskat)abstract
- A large percentage of the cost of rework can be avoided by finding more faults earlier in a software testing process. Therefore, determination of which software testing phases to focus improvements work on, has considerable industrial interest. This paper evaluates the use of five different techniques, namely particle swarm optimization based artificial neural networks (PSO-ANN), artificial immune recognition systems (AIRS), gene expression programming (GEP), genetic programming (GP) and multiple regression (MR), for predicting the number of faults slipping through unit, function, integration and system testing phases. The objective is to quantify improvement potential in different testing phases by striving towards finding the right faults in the right phase. We have conducted an empirical study of two large projects from a telecommunication company developing mobile platforms and wireless semiconductors. The results are compared using simple residuals, goodness of fit and absolute relative error measures. They indicate that the four search-based techniques (PSO-ANN, AIRS, GEP, GP) perform better than multiple regression for predicting the fault-slip-through for each of the four testing phases. At the unit and function testing phases, AIRS and PSO-ANN performed better while GP performed better at integration and system testing phases. The study concludes that a variety of search-based techniques are applicable for predicting the improvement potential in different testing phases with GP showing more consistent performance across two of the four test phases.
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| 6. |
- Afzal, Wasif
(författare)
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Using faults-slip-through metric as a predictor of fault-proneness
- 2010
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Ingår i: Proceedings - Asia-Pacific Software Engineering Conference, APSEC. - : IEEE. - 9780769542669
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Konferensbidrag (refereegranskat)abstract
- The majority of software faults are present in small number of modules, therefore accurate prediction of fault-prone modules helps improve software quality by focusing testing efforts on a subset of modules. This paper evaluates the use of the faults-slip-through (FST) metric as a potential predictor of fault-prone modules. Rather than predicting the fault-prone modules for the complete test phase, the prediction is done at the specific test levels of integration and system test. We applied eight classification techniques to the task of identifying fault-prone modules, representing a variety of approaches, including a standard statistical technique for classification (logistic regression), tree-structured classifiers (C4.5 and random forests), a Bayesian technique (Na\"{i}ve Bayes), machine-learning techniques (support vector machines and back-propagation artificial neural networks) and search-based techniques (genetic programming and artificial immune recognition systems) on FST data collected from two large industrial projects from the telecommunication domain. \emph{Results:} Using area under the receiver operating characteristic (ROC) curve and the location of (PF, PD) pairs in the ROC space, GP showed impressive results in comparison with other techniques for predicting fault-prone modules at both integration and system test levels. The use of faults-slip-through metric in general provided good prediction results at the two test levels. The accuracy of GP is statistically significant in comparison with majority of the techniques for predicting fault-prone modules at integration and system test levels. (ii) Faults-slip-through metric has the potential to be a generally useful predictor of fault-proneness at integration and system test levels.
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| 7. |
- Agervi, Pia, et al.
(författare)
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Foveal function in children treated for amblyopia.
- 2010
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Ingår i: Acta ophthalmologica. - : Wiley. - 1755-3768 .- 1755-375X. ; 88:2, s. 222-226
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Tidskriftsartikel (refereegranskat)abstract
- PURPOSE: This study aimed to evaluate foveal function, using three different methods, in children treated for monocular amblyopia. METHODS: A sample of 24 otherwise healthy children with treated amblyopia and an age-matched control group of 25 healthy children were examined for best corrected visual acuity (BCVA) using a standard decimal (KM) chart and the computerized TriVA method at 50% and 10% contrasts. Foveal function was also measured with the rarebit fovea test (RFT), which is included in the rarebit perimetry program package. This test uses very small and bright dots against a dark background. The result is expressed as mean hit rate (MHR). RESULTS: Amblyopic eyes showed significantly lower BCVA when evaluated with the KM chart and with the TriVA test at different contrast levels, compared with both fellow eyes and control eyes. No statistically significant difference between amblyopic and fellow eyes was found when foveal function was evaluated with the RFT (median MHRs 91.5% and 94.5%, respectively), although results for both amblyopic and fellow eyes were statistically lower than those of the control group (median MHR 97%) (p = 0.001 and p = 0.046, respectively). This might indicate that the RFT provides different information about foveal function than conventional VA tests. CONCLUSIONS: The findings in the current study accord with those of other studies reporting abnormalities in the fellow eyes of previously treated amblyopic patients. These findings may reflect a general disturbance in the visual system rather than a monocular adaptation to refractive error or ocular motor disturbance.
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| 9. |
- Ahmed, Mobyen Uddin
(författare)
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A case-based multi-modal clinical system for stress management
- 2010
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- A difficult issue in stress management is to use biomedical sensor signal in the diagnosis and treatment of stress. Clinicians often make their diagnosis and decision based on manual inspection of physiological signals such as, ECG, heart rate, finger temperature etc. However, the complexity associated with manual analysis and interpretation of the signals makes it difficult even for experienced clinicians. Today the diagnosis and decision is largely dependent on how experienced the clinician is interpreting the measurements. A computer-aided decision support system for diagnosis and treatment of stress would enable a more objective and consistent diagnosis and decisions. A challenge in the field of medicine is the accuracy of the system, it is essential that the clinician is able to judge the accuracy of the suggested solutions. Case-based reasoning systems for medical applications are increasingly multi-purpose and multi-modal, using a variety of different methods and techniques to meet the challenges of the medical domain. This research work covers the development of an intelligent clinical decision support system for diagnosis, classification and treatment in stress management. The system uses a finger temperature sensor and the variation in the finger temperature is one of the key features in the system. Several artificial intelligence techniques have been investigated to enable a more reliable and efficient diagnosis and treatment of stress such as case-based reasoning, textual information retrieval, rule-based reasoning, and fuzzy logic. Functionalities and the performance of the system have been validated by implementing a research prototype based on close collaboration with an expert in stress. The case base of the implemented system has been initiated with 53 reference cases classified by an experienced clinician. A case study also shows that the system provides results close to a human expert. The experimental results suggest that such a system is valuable both for less experienced clinicians and for experts where the system may function as a second option.
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| 10. |
- Ahmed, Mobyen Uddin, et al.
(författare)
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Case-Based Reasoning for Medical and Industrial Decision Support Systems
- 2010
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Ingår i: Successful Case-based Reasoning Applications. - Berlin, Heidelberg : Springer. - 9783642140778 ; , s. 7-52
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- The amount of medical and industrial experience and knowledge is rapidly growing and it is almost impossible to be up to date with everything. The demand of decision support system (DSS) is especially important in domains where experience and knowledge grow rapidly. However, traditional approaches to DSS are not always easy to adapt to a flow of new experience and knowledge and may also show a limitation in areas with a weak domain theory. This chapter explores the functionalities of Case-Based Reasoning (CBR) to facilitate experience reuse both in clinical and in industrial decision making tasks. Examples from the field of stress medicine and condition monitoring in industrial robots are presented here to demonstrate that the same approach assists both for clinical applications as well as for decision support for engineers. In the both domains, DSS deals with sensor signal data and integrate other artificial intelligence techniques into the CBR system to enhance the performance in a number of different aspects. Textual information retrieval, Rule-based Reasoning (RBR), and fuzzy logic are combined together with CBR to offer decision support to clinicians for a more reliable and efficient management of stress. Agent technology and wavelet transformations are applied with CBR to diagnose audible faults on industrial robots and to package such a system. The performance of the CBR systems have been validated and have shown to be useful in solving such problems in both of these domains.
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