766 resultados para Data Mining, Big Data, Consumi energetici, Weka Data Cleaning
Resumo:
A survey of a number of schools in a number of different climates was carried out to determine the condition of building components of interest in the project. Schools in Melbourne, the Victorian Surf Coast, Brisbane, Townsville and the Sunshine Coast were inspected. A rating system was devised to categorise the components and the results collated in tables. Analysis of the data (where sufficient examples permitted) resulted in formulae to predict the service of the components and a database was derived.
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This project report presents the results of a study on wireless communication data transfer rates for a mobile device running a custombuilt construction defect reporting application. The study measured the time taken to transmit data about a construction defect, which included digital imagery and text, in order to assess the feasibility of transferring various types and sizes of data and the ICT-supported construction management applications that could be developed as a consequence. Data transfer rates over GPRS through the Telstra network and WiFi over a private network were compared. Based on the data size and data transfer time, the rate of transfer was calculated to determine the actual data transmission speeds at which the information was being sent using the wireless mobile communication protocols. The report finds that the transmission speeds vary considerably when using GPRS and can be significantly slower than what is advertised by mobile network providers. While WiFi is much faster than GPRS, the limited range of WiFi limits the protocol to residential-scale construction sites.
Resumo:
Reliable budget/cost estimates for road maintenance and rehabilitation are subjected to uncertainties and variability in road asset condition and characteristics of road users. The CRC CI research project 2003-029-C ‘Maintenance Cost Prediction for Road’ developed a method for assessing variation and reliability in budget/cost estimates for road maintenance and rehabilitation. The method is based on probability-based reliable theory and statistical method. The next stage of the current project is to apply the developed method to predict maintenance/rehabilitation budgets/costs of large networks for strategic investment. The first task is to assess the variability of road data. This report presents initial results of the analysis in assessing the variability of road data. A case study of the analysis for dry non reactive soil is presented to demonstrate the concept in analysing the variability of road data for large road networks. In assessing the variability of road data, large road networks were categorised into categories with common characteristics according to soil and climatic conditions, pavement conditions, pavement types, surface types and annual average daily traffic. The probability distributions, statistical means, and standard deviation values of asset conditions and annual average daily traffic for each type were quantified. The probability distributions and the statistical information obtained in this analysis will be used to asset the variation and reliability in budget/cost estimates in later stage. Generally, we usually used mean values of asset data of each category as input values for investment analysis. The variability of asset data in each category is not taken into account. This analysis method demonstrated that it can be used for practical application taking into account the variability of road data in analysing large road networks for maintenance/rehabilitation investment analysis.
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In the past decade, the utilization of ambulance data to inform the prevalence of nonfatal heroin overdose has increased. These data can assist public health policymakers, law enforcement agencies, and health providers in planning and allocating resources. This study examined the 672 ambulance attendances at nonfatal heroin overdoses in Queensland, Australia, in 2000. Gender distribution showed a typical 70/30 male-to-female ratio. An equal number of persons with nonfatal heroin overdose were between 15 and 24 years of age and 25 and 34 years of age. Police were present in only 1 of 6 cases, and 28.1% of patients reported using drugs alone. Ambulance data are proving to be a valuable population-based resource for describing the incidence and characteristics of nonfatal heroin overdose episodes. Future studies could focus on the differences between nonfatal heroin overdose and fatal heroin overdose samples.
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In recent years considerable effort has gone into quantifying the reuse and recycling potential of waste generated by residential construction. Unfortunately less information is available for the commercial refurbishment sector. It is hypothesised that significant economic and environmental benefit can be derived from closer monitoring of the commercial construction waste stream. With the aim of assessing these benefits, the authors are involved in ongoing case studies to record both current standard practice and the most effective means of improving the eco-efficiency of materials use in office building refurbishments. This paper focuses on the issues involved in developing methods for obtaining the necessary information on better waste management practices and establishing benchmark indicators. The need to create databases to establish benchmarks of waste minimisation best practice in commercial construction is stressed. Further research will monitor the delivery of case study projects and the levels of reuse and recycling achieved in directly quantifiable ways
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The over represented number of novice drivers involved in crashes is alarming. Driver training is one of the interventions aimed at mitigating the number of crashes that involve young drivers. To our knowledge, Advanced Driver Assistance Systems (ADAS) have never been comprehensively used in designing an intelligent driver training system. Currently, there is a need to develop and evaluate ADAS that could assess driving competencies. The aim is to develop an unsupervised system called Intelligent Driver Training System (IDTS) that analyzes crash risks in a given driving situation. In order to design a comprehensive IDTS, data is collected from the Driver, Vehicle and Environment (DVE), synchronized and analyzed. The first implementation phase of this intelligent driver training system deals with synchronizing multiple variables acquired from DVE. RTMaps is used to collect and synchronize data like GPS, vehicle dynamics and driver head movement. After the data synchronization, maneuvers are segmented out as right turn, left turn and overtake. Each maneuver is composed of several individual tasks that are necessary to be performed in a sequential manner. This paper focuses on turn maneuvers. Some of the tasks required in the analysis of ‘turn’ maneuver are: detect the start and end of the turn, detect the indicator status change, check if the indicator was turned on within a safe distance and check the lane keeping during the turn maneuver. This paper proposes a fusion and analysis of heterogeneous data, mainly involved in driving, to determine the risk factor of particular maneuvers within the drive. It also explains the segmentation and risk analysis of the turn maneuver in a drive.
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Forensic analysis requires the acquisition and management of many different types of evidence, including individual disk drives, RAID sets, network packets, memory images, and extracted files. Often the same evidence is reviewed by several different tools or examiners in different locations. We propose a backwards-compatible redesign of the Advanced Forensic Formatdan open, extensible file format for storing and sharing of evidence, arbitrary case related information and analysis results among different tools. The new specification, termed AFF4, is designed to be simple to implement, built upon the well supported ZIP file format specification. Furthermore, the AFF4 implementation has downward comparability with existing AFF files.
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There is currently a strong focus worldwide on the potential of large-scale Electronic Health Record (EHR) systems to cut costs and improve patient outcomes through increased efficiency. This is accomplished by aggregating medical data from isolated Electronic Medical Record databases maintained by different healthcare providers. Concerns about the privacy and reliability of Electronic Health Records are crucial to healthcare service consumers. Traditional security mechanisms are designed to satisfy confidentiality, integrity, and availability requirements, but they fail to provide a measurement tool for data reliability from a data entry perspective. In this paper, we introduce a Medical Data Reliability Assessment (MDRA) service model to assess the reliability of medical data by evaluating the trustworthiness of its sources, usually the healthcare provider which created the data and the medical practitioner who diagnosed the patient and authorised entry of this data into the patient’s medical record. The result is then expressed by manipulating health record metadata to alert medical practitioners relying on the information to possible reliability problems.
Resumo:
Electronic Health Record (EHR) systems are being introduced to overcome the limitations associated with paper-based and isolated Electronic Medical Record (EMR) systems. This is accomplished by aggregating medical data and consolidating them in one digital repository. Though an EHR system provides obvious functional benefits, there is a growing concern about the privacy and reliability (trustworthiness) of Electronic Health Records. Security requirements such as confidentiality, integrity, and availability can be satisfied by traditional hard security mechanisms. However, measuring data trustworthiness from the perspective of data entry is an issue that cannot be solved with traditional mechanisms, especially since degrees of trust change over time. In this paper, we introduce a Time-variant Medical Data Trustworthiness (TMDT) assessment model to evaluate the trustworthiness of medical data by evaluating the trustworthiness of its sources, namely the healthcare organisation where the data was created and the medical practitioner who diagnosed the patient and authorised entry of this data into the patient’s medical record, with respect to a certain period of time. The result can then be used by the EHR system to manipulate health record metadata to alert medical practitioners relying on the information to possible reliability problems.
Resumo:
Objective: To examine the reliability of work-related activity coding for injury-related hospitalisations in Australia. Method: A random sample of 4373 injury-related hospital separations from 1 July 2002 to 30 June 2004 were obtained from a stratified random sample of 50 hospitals across 4 states in Australia. From this sample, cases were identified as work-related if they contained an ICD-10-AM work-related activity code (U73) allocated by either: (i) the original coder; (ii) an independent auditor, blinded to the original code; or (iii) a research assistant, blinded to both the original and auditor codes, who reviewed narrative text extracted from the medical record. The concordance of activity coding and number of cases identified as work-related using each method were compared. Results: Of the 4373 cases sampled, 318 cases were identified as being work-related using any of the three methods for identification. The original coder identified 217 and the auditor identified 266 work-related cases (68.2% and 83.6% of the total cases identified, respectively). Around 10% of cases were only identified through the text description review. The original coder and auditor agreed on the assignment of work-relatedness for 68.9% of cases. Conclusions and Implications: The current best estimates of the frequency of hospital admissions for occupational injury underestimate the burden by around 32%. This is a substantial underestimate that has major implications for public policy, and highlights the need for further work on improving the quality and completeness of routine, administrative data sources for a more complete identification of work-related injuries.
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A study investigated the reliability and construct validity of the Children's Depression Scale. The revised subscales were shown to have strong construct and face validity and high reliability.
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Over the last few years more stringent environmental laws (e.g. the German “Energie¬ein-sparverordnung ENEV” - Energy Performance of Buildings Directive) and soaring energy prices has increased the need for the real estate industry to react and participate in overall energy reduction through efficient house construction and design, as well as upgrading the existing housing stock to be more energy efficient. Therefore the Property Economics Group at Queensland University of Technology in Australia and Nuertingen-Geislingen University in Germany are carrying out research in relation to sustainable housing construction and public awareness of “green” residential property. Part of this research is to gain an understanding of the level of knowledge and importance of these issues to the house buyer and to determine the importance of sustainable housing to the general public. The paper compares data from two different empirical studies; one of studies analyzes the situation in New Zealand, the other is focused on Germany.
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Advances in information and communications technologies during the last two decades have allowed organisations to capture and utilise data on a vast scale, thus heightening the importance of adequate measures for protecting unauthorised disclosure of personal information. In this respect, data breach notification has emerged as an issue of increasing importance throughout the world. It has been the subject of law reform in the United States and in other international jurisdictions. Following the Australian Law Reform Commission’s review of privacy, data breach notification will soon be addressed in Australia. This article provides a review of US and Australian legal initiatives regarding the notification of data breaches. The authors highlight areas of concern based on the extant US literature that require specific consideration in Australia regarding the development of an Australian legal framework for the notification of data breaches.
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Ecological dynamics characterizes adaptive behavior as an emergent, self-organizing property of interpersonal interactions in complex social systems. The authors conceptualize and investigate constraints on dynamics of decisions and actions in the multiagent system of team sports. They studied coadaptive interpersonal dynamics in rugby union to model potential control parameter and collective variable relations in attacker–defender dyads. A videogrammetry analysis revealed how some agents generated fluctuations by adapting displacement velocity to create phase transitions and destabilize dyadic subsystems near the try line. Agent interpersonal dynamics exhibited characteristics of chaotic attractors and informational constraints of rugby union boxed dyadic systems into a low dimensional attractor. Data suggests that decisions and actions of agents in sports teams may be characterized as emergent, self-organizing properties, governed by laws of dynamical systems at the ecological scale. Further research needs to generalize this conceptual model of adaptive behavior in performance to other multiagent populations.