950 resultados para Automated Hazard Analysis


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Malware detection is a growing problem particularly on the Android mobile platform due to its increasing popularity and accessibility to numerous third party app markets. This has also been made worse by the increasingly sophisticated detection avoidance techniques employed by emerging malware families. This calls for more effective techniques for detection and classification of Android malware. Hence, in this paper we present an n-opcode analysis based approach that utilizes machine learning to classify and categorize Android malware. This approach enables automated feature discovery that eliminates the need for applying expert or domain knowledge to define the needed features. Our experiments on 2520 samples that were performed using up to 10-gram opcode features showed that an f-measure of 98% is achievable using this approach.

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Safety on public transport is a major concern for the relevant authorities. We
address this issue by proposing an automated surveillance platform which combines data from video, infrared and pressure sensors. Data homogenisation and integration is achieved by a distributed architecture based on communication middleware that resolves interconnection issues, thereby enabling data modelling. A common-sense knowledge base models and encodes knowledge about public-transport platforms and the actions and activities of passengers. Trajectory data from passengers is modelled as a time-series of human activities. Common-sense knowledge and rules are then applied to detect inconsistencies or errors in the data interpretation. Lastly, the rationality that characterises human behaviour is also captured here through a bottom-up Hierarchical Task Network planner that, along with common-sense, corrects misinterpretations to explain passenger behaviour. The system is validated using a simulated bus saloon scenario as a case-study. Eighteen video sequences were recorded with up to six passengers. Four metrics were used to evaluate performance. The system, with an accuracy greater than 90% for each of the four metrics, was found to outperform a rule-base system and a system containing planning alone.

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BACKGROUND: The aim of this study was to investigate the association between statin use and survival in a population-based colorectal cancer (CRC) cohort and perform an updated meta-analysis to quantify the magnitude of any association.

METHODS: A cohort of 8391 patients with newly diagnosed Dukes' A-C CRC (2009-2012) was identified from the Scottish Cancer Registry. This cohort was linked to the Prescribing Information System and the National Records of Scotland Death Records (until January 2015) to identify 1064 colorectal cancer-specific deaths. Adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for cancer-specific mortality by statin use were calculated using time dependent Cox regression models. The systematic review included relevant studies published before January 2016. Meta-analysis techniques were used to derive combined HRs for associations between statin use and cancer-specific and overall mortality.

RESULTS: In the Scottish cohort, statin use before diagnosis (HR=0.84, 95% CI 0.75-0.94), but not after (HR=0.90, 95% CI 0.77-1.05), was associated with significantly improved cancer-specific mortality. The systematic review identified 15 relevant studies. In the meta-analysis, there was consistent (I(2)=0%,heterogeneity P=0.57) evidence of a reduction in cancer-specific mortality with statin use before diagnosis in 6 studies (n=86,622, pooled HR=0.82, 95% CI 0.79-0.86) but this association was less apparent and more heterogeneous (I(2)=67%,heterogeneity P=0.03) with statin use after diagnosis in 4 studies (n=19,152, pooled HR=0.84, 95% CI 0.68-1.04).

CONCLUSION: In a Scottish CRC cohort and updated meta-analysis there was some evidence that statin use was associated with improved survival. However, these associations were weak in magnitude and, particularly for post-diagnosis use, varied markedly between studies.

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Companies face new challenges almost every day. In order to stay competitive, it is important that companies strive for continuous development and improvement. By describing companies through their processes it is possible to get a clear overview of the entire operation, which can contribute, to a well-established overall understanding of the company. This is a case study based on Stort AB which is a small logistics company specialized in international transportation and logistics solutions. The purpose of this study is to perform value stream mapping in order to create a more efficient production process and propose possible improvements in order to reduce processing time. After performing value stream mapping, data envelopment analysis is used to calculate how lean Stort AB is today and how lean the company can become by implementing the proposed improvements. The results show that the production process can improve efficiency by minimizing waste produced by a bad workplace layout and over-processing. The authors suggested solution is to introduce standardized processes and invest in technical instruments in order to automate the process to reduce process time. According to data envelopment analysis the business is 41 percent lean at present and may soon become 55 percent lean and finally reach an optimum 100 percent lean mode if the process is automated.

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Performance improvements subsequent to the implementation of a pay-for-performance plan can result because more productive employees self-select into the firm (selection effect) and/or because employees allocate effort to become more effective (effort effect). We analyze individual performance data for 3,776 sales employees of a retail firm to evaluate these alternative sources of continuing performance improvement. The incentive plan helps the firm attract and retain more productive sales employees, and motivates these employees to further improve their productivity. In contrast, the less productive sales employees’ performance declines before they leave the firm.

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PURPOSE: To quantitatively analyze and compare the fundoscopic features between fellow eyes of retinal angiomatous proliferation and typical exudative age-related macular degeneration and to identify possible predictors of neovascularization. METHODS: Retrospective case-control study. Seventy-nine fellow eyes of unilateral retinal angiomatous proliferation (n = 40) and typical exudative age-related macular degeneration (n = 39) were included. Fundoscopic features of the fellow eyes were assessed using digital color fundus photographs taken at the time of diagnosis of neovascularization in the first affected eye. Grading was performed by two independent graders using RetmarkerAMD, a computer-assisted grading software based on the International Classification and Grading System for age-related macular degeneration. RESULTS: Baseline total number and area (square micrometers) of drusen in the central 1,000, 3,000, and 6,000 μm were considerably inferior in the fellow eyes of retinal angiomatous proliferation, with statistically significant differences (P < 0.05) observed in virtually every location (1,000, 3,000, and 6,000 μm). A soft drusen (≥125 μm) area >510,196 μm2 in the central 6,000 μm was associated with an increased risk of neovascularization (hazard ratio, 4.35; 95% confidence interval [1.56-12.15]; P = 0.005). CONCLUSION: Baseline fundoscopic features of the fellow eye differ significantly between retinal angiomatous proliferation and typical exudative age-related macular degeneration. A large area (>510,196 μm2) of soft drusen in the central 6,000 μm confers a significantly higher risk of neovascularization and should be considered as a phenotypic risk factor.

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Background: The role of temporary ovarian suppression with luteinizing hormone-releasing hormone agonists (LHRHa) in the prevention of chemotherapy-induced premature ovarian failure (POF) is still controversial. Our meta-analysis of randomized, controlled trials (RCTs) investigates whether the use of LHRHa during chemotherapy in premenopausal breast cancer patients reduces treatment-related POF rate, increases pregnancy rate, and impacts disease-free survival (DFS). Methods: A literature search using PubMed, Embase, and the Cochrane Library, and the proceedings of major conferences, was conducted up to 30 April 2015. Odds ratios (ORs) and 95% confidence intervals (CIs) for POF (i.e. POF by study definition, and POF defined as amenorrhea 1 year after chemotherapy completion) and for patients with pregnancy, as well hazard ratios (HRs) and 95% CI for DFS, were calculated for each trial. Pooled analysis was carried out using the fixed- and random-effects models. Results: A total of 12 RCTs were eligible including 1231 breast cancer patients. The use of LHRHa was associated with a significant reduced risk of POF (OR 0.36, 95% CI 0.23-0.57; P < 0.001), yet with significant heterogeneity (I2 = 47.1%, Pheterogeneity = 0.026). In eight studies reporting amenorrhea rates 1 year after chemotherapy completion, the addition of LHRHa reduced the risk of POF (OR 0.55, 95% CI 0.41-0.73, P < 0.001) without heterogeneity (I2 = 0.0%, Pheterogeneity = 0.936). In five studies reporting pregnancies, more patients treated with LHRHa achieved pregnancy (33 versus 19 women; OR 1.83, 95% CI 1.02-3.28, P = 0.041; I2 = 0.0%, Pheterogeneity = 0.629). In three studies reporting DFS, no difference was observed (HR 1.00, 95% CI 0.49-2.04, P = 0.939; I2 = 68.0%, Pheterogeneity = 0.044). Conclusion: Temporary ovarian suppression with LHRHa in young breast cancer patients is associated with a reduced risk of chemotherapy-induced POF and seems to increase the pregnancy rate, without an apparent negative consequence on prognosis.

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Carbonic anhydrases are enzymes that are ubiquitously found in all organisms that are engaged in catalyzing the hydration of carbon dioxide to form bicarbonate and proton and vice versa. They are crucial in the process of respiration, bone resorption, pH regulation, ion transport, and photosynthesis in plants. Out of the five classes of carbonic anhydrase α, β, γ, δ, ζ this study focused in the α carbonic anhydrases. This class of CAs constitute of 16 subfamilies in mammals that include 3 non-active enzymes known as Carbonic Anhydrase Related Proteins. The inactiveness of these enzymes is due to the loss of one or more Histidine residues in the active site. This thesis was conducted based on the aim of studying evolutionary analysis of carbonic anhydrase sequences from organisms spanning from the Cambrian age. It was carried out in two phases. The first phase was the sequence collection, which involved many biological sequence databases as a source. The scope of this segment included sequence alignments and analysis of the sequence manually and in an automated form incorporating few analysis tools. The second Phase was phylogenetic analysis and exploring the subcellular location of the proteins, which was key for the evolutionary analysis. Through the medium of the methods conducted with respect to the phases mentioned above, it was possible to accomplish the desired result. Certain thought-provoking sequences were come across and analyzed thoroughly. Whereas, Phylogenetics showed interesting results to bolster previous findings and new findings as well which lay bedrock for future intensified studies.

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As a way to gain greater insights into the operation of online communities, this dissertation applies automated text mining techniques to text-based communication to identify, describe and evaluate underlying social networks among online community members. The main thrust of the study is to automate the discovery of social ties that form between community members, using only the digital footprints left behind in their online forum postings. Currently, one of the most common but time consuming methods for discovering social ties between people is to ask questions about their perceived social ties. However, such a survey is difficult to collect due to the high investment in time associated with data collection and the sensitive nature of the types of questions that may be asked. To overcome these limitations, the dissertation presents a new, content-based method for automated discovery of social networks from threaded discussions, referred to as ‘name network’. As a case study, the proposed automated method is evaluated in the context of online learning communities. The results suggest that the proposed ‘name network’ method for collecting social network data is a viable alternative to costly and time-consuming collection of users’ data using surveys. The study also demonstrates how social networks produced by the ‘name network’ method can be used to study online classes and to look for evidence of collaborative learning in online learning communities. For example, educators can use name networks as a real time diagnostic tool to identify students who might need additional help or students who may provide such help to others. Future research will evaluate the usefulness of the ‘name network’ method in other types of online communities.

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The aim of this thesis was threefold, firstly, to compare current player tracking technology in a single game of soccer. Secondly, to investigate the running requirements of elite women’s soccer, in particular the use and application of athlete tracking devices. Finally, how can game style be quantified and defined. Study One compared four different match analysis systems commonly used in both research and applied settings: video-based time-motion analysis, a semi-automated multiple camera based system, and two commercially available Global Positioning System (GPS) based player tracking systems at 1 Hertz (Hz) and 5 Hz respectively. A comparison was made between each of the systems when recording the same game. Total distance covered during the match for the four systems ranged from 10 830 ± 770 m (semi-automated multiple camera based system) to 9 510 ± 740m (video-based time-motion analysis). At running speeds categorised as high-intensity running (>15 km⋅h-1), the semi-automated multiple camera based system reported the highest distance of 2 650 ± 530 m with video-based time-motion analysis reporting the least amount of distance covered with 1 610 ± 370 m. At speeds considered to be sprinting (>20 km⋅h-1), the video-based time-motion analysis reported the highest value (420 ± 170 m) and 1 Hz GPS units the lowest value (230 ± 160 m). These results demonstrate there are differences in the determination of the absolute distances, and that comparison of results between match analysis systems should be made with caution. Currently, there is no criterion measure for these match analysis methods and as such it was not possible to determine if one system was more accurate than another. Study Two provided an opportunity to apply player-tracking technology (GPS) to measure activity profiles and determine the physical demands of Australian international level women soccer players. In four international women’s soccer games, data was collected on a total of 15 Australian women soccer players using a 5 Hz GPS based athlete tracking device. Results indicated that Australian women soccer players covered 9 140 ± 1 030 m during 90 min of play. The total distance covered by Australian women was less than the 10 300 m reportedly covered by female soccer players in the Danish First Division. However, there was no apparent difference in the estimated "#$%&', as measured by multi-stage shuttle tests, between these studies. This study suggests that contextual information, including the “game style” of both the team and opposition may influence physical performance in games. Study Three examined the effect the level of the opposition had on the physical output of Australian women soccer players. In total, 58 game files from 5 Hz athlete-tracking devices from 13 international matches were collected. These files were analysed to examine relationships between physical demands, represented by total distance covered, high intensity running (HIR) and distances covered sprinting, and the level of the opposition, as represented by the Fédération Internationale de Football Association (FIFA) ranking at the time of the match. Higher-ranking opponents elicited less high-speed running and greater low-speed activity compared to playing teams of similar or lower ranking. The results are important to coaches and practitioners in the preparation of players for international competition, and showed that the differing physical demands required were dependent on the level of the opponents. The results also highlighted the need for continued research in the area of integrating contextual information in team sports and demonstrated that soccer can be described as having dynamic and interactive systems. The influence of playing strategy, tactics and subsequently the overall game style was highlighted as playing a significant part in the physical demands of the players. Study Four explored the concept of game style in field sports such as soccer. The aim of this study was to provide an applied framework with suggested metrics for use by coaches, media, practitioners and sports scientists. Based on the findings of Studies 1- 3 and a systematic review of the relevant literature, a theoretical framework was developed to better understand how a team’s game style could be quantified. Soccer games can be broken into key moments of play, and for each of these moments we categorised metrics that provide insight to success or otherwise, to help quantify and measure different methods of playing styles. This study highlights that to date, there had been no clear definition of game style in team sports and as such a novel definition of game style is proposed that can be used by coaches, sport scientists, performance analysts, media and general public. Studies 1-3 outline four common methods of measuring the physical demands in soccer: video based time motion analysis, GPS at 1 Hz and at 5 Hz and semiautomated multiple camera based systems. As there are no semi-automated multiple camera based systems available in Australia, primarily due to cost and logistical reasons, GPS is widely accepted for use in team sports in tracking player movements in training and competition environments. This research identified that, although there are some limitations, GPS player-tracking technology may be a valuable tool in assessing running demands in soccer players and subsequently contribute to our understanding of game style. The results of the research undertaken also reinforce the differences between methods used to analyse player movement patterns in field sports such as soccer and demonstrate that the results from different systems such as GPS based athlete tracking devices and semi-automated multiple camera based systems cannot be used interchangeably. Indeed, the magnitude of measurement differences between methods suggests that significant measurement error is evident. This was apparent even when the same technologies are used which measure at different sampling rates, such as GPS systems using either 1 Hz or 5 Hz frequencies of measurement. It was also recognised that other factors influence how team sport athletes behave within an interactive system. These factors included the strength of the opposition and their style of play. In turn, these can impact the physical demands of players that change from game to game, and even within games depending on these contextual features. Finally, the concept of what is game style and how it might be measured was examined. Game style was defined as "the characteristic playing pattern demonstrated by a team during games. It will be regularly repeated in specific situational contexts such that measurement of variables reflecting game style will be relatively stable. Variables of importance are player and ball movements, interaction of players, and will generally involve elements of speed, time and space (location)".

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Chronic kidney disease (CKD) and atrial fibrillation (AF) frequently coexist. However, the extent to which CKD increases the risk of thromboembolism in patients with nonvalvular AF and the benefits of anticoagulation in this group remain unclear. We addressed the role of CKD in the prediction of thromboembolic events and the impact of anticoagulation using a meta-analysis method. Data sources included MEDLINE, EMBASE, and Cochrane (from inception to January 2014). Three independent reviewers selected studies. Descriptive and quantitative information was extracted from each selected study and a random-effects meta-analysis was performed. After screening 962 search results, 19 studies were considered eligible. Among patients with AF, the presence of CKD resulted in an increased risk of thromboembolism (hazard ratio [HR] 1.46, 95% confidence interval [CI] 1.20 to 1.76, p = 0.0001), particularly in case of end-stage CKD (HR 1.83, 95% CI 1.56 to 2.14, p <0.00001). Warfarin decreased the incidence of thromboembolic events in patients with non-end-stage CKD (HR 0.39, 95% CI 0.18 to 0.86, p <0.00001). Recent data on novel oral anticoagulants suggested a higher efficacy of these agents compared with warfarin (HR 0.80, 95% CI 0.66 to 0.96, p = 0.02) and aspirin (HR 0.32, 95% CI 0.19 to 0.55, p <0.0001) in treating non-end-stage CKD. In conclusion, the presence of CKD in patients with AF is associated with an almost 50% increased thromboembolic risk, which can be effectively decreased with appropriate antithrombotic therapy. Further prospective studies are needed to better evaluate the interest of anticoagulation in patients with severe CKD.

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SQL Injection Attack (SQLIA) remains a technique used by a computer network intruder to pilfer an organisation’s confidential data. This is done by an intruder re-crafting web form’s input and query strings used in web requests with malicious intent to compromise the security of an organisation’s confidential data stored at the back-end database. The database is the most valuable data source, and thus, intruders are unrelenting in constantly evolving new techniques to bypass the signature’s solutions currently provided in Web Application Firewalls (WAF) to mitigate SQLIA. There is therefore a need for an automated scalable methodology in the pre-processing of SQLIA features fit for a supervised learning model. However, obtaining a ready-made scalable dataset that is feature engineered with numerical attributes dataset items to train Artificial Neural Network (ANN) and Machine Leaning (ML) models is a known issue in applying artificial intelligence to effectively address ever evolving novel SQLIA signatures. This proposed approach applies numerical attributes encoding ontology to encode features (both legitimate web requests and SQLIA) to numerical data items as to extract scalable dataset for input to a supervised learning model in moving towards a ML SQLIA detection and prevention model. In numerical attributes encoding of features, the proposed model explores a hybrid of static and dynamic pattern matching by implementing a Non-Deterministic Finite Automaton (NFA). This combined with proxy and SQL parser Application Programming Interface (API) to intercept and parse web requests in transition to the back-end database. In developing a solution to address SQLIA, this model allows processed web requests at the proxy deemed to contain injected query string to be excluded from reaching the target back-end database. This paper is intended for evaluating the performance metrics of a dataset obtained by numerical encoding of features ontology in Microsoft Azure Machine Learning (MAML) studio using Two-Class Support Vector Machines (TCSVM) binary classifier. This methodology then forms the subject of the empirical evaluation.

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PURPOSE: To quantitatively analyze and compare the fundoscopic features between fellow eyes of retinal angiomatous proliferation and typical exudative age-related macular degeneration and to identify possible predictors of neovascularization. METHODS: Retrospective case-control study. Seventy-nine fellow eyes of unilateral retinal angiomatous proliferation (n = 40) and typical exudative age-related macular degeneration (n = 39) were included. Fundoscopic features of the fellow eyes were assessed using digital color fundus photographs taken at the time of diagnosis of neovascularization in the first affected eye. Grading was performed by two independent graders using RetmarkerAMD, a computer-assisted grading software based on the International Classification and Grading System for age-related macular degeneration. RESULTS: Baseline total number and area (square micrometers) of drusen in the central 1,000, 3,000, and 6,000 μm were considerably inferior in the fellow eyes of retinal angiomatous proliferation, with statistically significant differences (P < 0.05) observed in virtually every location (1,000, 3,000, and 6,000 μm). A soft drusen (≥125 μm) area >510,196 μm2 in the central 6,000 μm was associated with an increased risk of neovascularization (hazard ratio, 4.35; 95% confidence interval [1.56-12.15]; P = 0.005). CONCLUSION: Baseline fundoscopic features of the fellow eye differ significantly between retinal angiomatous proliferation and typical exudative age-related macular degeneration. A large area (>510,196 μm2) of soft drusen in the central 6,000 μm confers a significantly higher risk of neovascularization and should be considered as a phenotypic risk factor.

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Still a big gap exists between clinical and genetic diagnosis of dyslipidemic disorders. Almost the 60% of the patients with a clinical diagnosis of Familial hypercholesterolemia (FH) still lack of a genetic diagnosis. Here we present the preliminary results of an integrative approach intended to identify new candidate genes and to dissect pathways that can be dysregulated in the disease. Interesting hits will be subsequently knocked down in vitro in order to evaluate their functional role in the uptake of fluorescently-labeled LDL and free cell cholesterol using automated microscopy.

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Objectives: Our aim was to study the effect of combination therapy with aspirin and dipyridamole (A+D) over aspirin alone (ASA) in secondary prevention after transient ischemic attack or minor stroke of presumed arterial origin and to perform subgroup analyses to identify patients that might benefit most from secondary prevention with A+D. Data sources: The previously published meta-analysis of individual patient data was updated with data from ESPRIT (N=2,739); trials without data on the comparison of A+D versus ASA were excluded. Review methods: A meta-analysis was performed using Cox regression, including several subgroup analyses and following baseline risk stratification. Results: A total of 7,612 patients (5 trials) were included in the analyses, 3,800 allocated to A+D and 3,812 to ASA alone. The trial-adjusted hazard ratio for the composite event of vascular death, non-fatal myocardial infarction and non-fatal stroke was 0.82 (95% confidence interval 0.72-0.92). Hazard ratios did not differ in subgroup analyses based on age, sex, qualifying event, hypertension, diabetes, previous stroke, ischemic heart disease, aspirin dose, type of vessel disease and dipyridamole formulation, nor across baseline risk strata as assessed with two different risk scores. A+D were also more effective than ASA alone in preventing recurrent stroke, HR 0.78 (95% CI 0.68 – 0.90). Conclusion: The combination of aspirin and dipyridamole is more effective than aspirin alone in patients with TIA or ischemic stroke of presumed arterial origin in the secondary prevention of stroke and other vascular events. This superiority was found in all subgroups and was independent of baseline risk. ---------------------------7dc3521430776 Content-Disposition: form-data; name="c14_creators_1_name_family" Halkes