Data mining on prices of highway project main material based on WEB

The management of main material prices of provincial highway project quota has problems of lag and blindness. Framework of provincial highway project quota data MIS and main material price data warehouse were established based on WEB firstly. Then concrete processes of provincial highway project main material prices were brought forward based on BP neural network algorithmic. After that standard BP algorithmic, additional momentum modify BP network algorithmic, self-adaptive study speed improved BP network algorithmic were compared in predicting highway project main prices. The result indicated that it is feasible to predict highway main material prices using BP NN, and using self-adaptive study speed improved BP network algorithmic is the relatively best one.

Work engagement and its antecedents in high-risk occupations : a police service case study

Introduction: Work engagement is a recent application of positive psychology and refers to a positive, fulfilling, work-related state of mind characterized by vigor, dedication and absorption. Despite theoretical assumptions, there is little published research on work engagement, due primarily to its recent emergence as a psychological construct. Furthermore, examining work engagement among high-stress occupations, such as police, is useful because police officers are generally characterized as having a high level of work engagement. Previous research has identified job resources (e.g. social support) as antecedents of work engagement. However detailed evaluation of job demands as an antecedent of work engagement within high-stress occupations has been scarce. Thus our second aim was to test job demands (i.e. monitoring demands and problem-solving demands) and job resources (i.e. time control, method control, supervisory support, colleague support, and friend and family support) as antecedents of work engagement among police officers. Method: Data were collected via a self-report online survey from one Australian state police service (n = 1,419). Due to the high number of hypothesized antecedent variables, hierarchical multiple regression analysis was employed rather than structural equation modelling. Results: Work engagement reported by police officers was high. Female officers had significantly higher levels of work engagement than male officers, while officers at mid-level ranks (sergeant) reported the lowest levels of work engagement. Job resources (method control, supervisor support and colleague support) were significant antecedents of three dimensions of work engagement. Only monitoring demands were significant antecedent of the absorption. Conclusion: Having healthy and engaged police officers is important for community security and economic growth. This study identified some common factors which influence work engagement experienced by police officers. However, we also note that excessive work engagement can yield negative outcomes such as psychological distress.

The reliability of information on work-related injuries available from hospitalisation data in Australia

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.

The Children's Depression Scale : assessment of factor structure with data from a normal population

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.

Interoperable Standards Development : Final Report

Since 1995 the buildingSMART International Alliance for Interoperability (buildingSMART)has developed a robust standard called the Industry Foundation Classes (IFC). IFC is an object oriented data model with related file format that has facilitated the efficient exchange of data in the development of building information models (BIM). The Cooperative Research Centre for Construction Innovation has contributed to the international effort in the development of the IFC standard and specifically the reinforced concrete part of the latest IFC 2x3 release. Industry Foundation Classes have been endorsed by the International Standards Organisation as a Publicly Available Specification (PAS) under the ISO label ISO/PAS 16739. For more details, go to http://www.tc184- sc4.org/About_TC184-SC4/About_SC4_Standards/ The current IFC model covers the building itself to a useful level of detail. The next stage of development for the IFC standard is where the building meets the ground (terrain) and with civil and external works like pavements, retaining walls, bridges, tunnels etc. With the current focus in Australia on infrastructure projects over the next 20 years a logical extension to this standard was in the area of site and civil works. This proposal recognises that there is an existing body of work on the specification of road representation data. In particular, LandXML is recognised as also is TransXML in the broader context of transportation and CityGML in the common interfacing of city maps, buildings and roads. Examination of interfaces between IFC and these specifications is therefore within the scope of this project. That such interfaces can be developed has already been demonstrated in principle within the IFC for Geographic Information Systems (GIS) project. National road standards that are already in use should be carefully analysed and contacts established in order to gain from this knowledge. The Object Catalogue for the Road Transport Sector (OKSTRA) should be noted as an example. It is also noted that buildingSMART Norway has submitted a proposal

Privacy and security in open and trusted health information systems

The Open and Trusted Health Information Systems (OTHIS) Research Group has formed in response to the health sector’s privacy and security requirements for contemporary Health Information Systems (HIS). Due to recent research developments in trusted computing concepts, it is now both timely and desirable to move electronic HIS towards privacy-aware and security-aware applications. We introduce the OTHIS architecture in this paper. This scheme proposes a feasible and sustainable solution to meeting real-world application security demands using commercial off-the-shelf systems and commodity hardware and software products.

Open and trusted information systems/health informatics access control (OTHIS/HIAC)

Information and Communications Technologies globally are moving towards Service Oriented Architectures and Web Services. The healthcare environment is rapidly moving to the use of Service Oriented Architecture/Web Services systems interconnected via this global open Internet. Such moves present major challenges where these structures are not based on highly trusted operating systems. This paper argues the need of a radical re-think of access control in the contemporary healthcare environment in light of modern information system structures, legislative and regulatory requirements, and security operation demands in Health Information Systems. This paper proposes the Open and Trusted Health Information Systems (OTHIS), a viable solution including override capability to the provision of appropriate levels of secure access control for the protection of sensitive health data.

Detecting and resolving redundancies in EP3P policies

Current regulatory requirements on data privacy make it increasingly important for enterprises to be able to verify and audit their compliance with their privacy policies. Traditionally, a privacy policy is written in a natural language. Such policies inherit the potential ambiguity, inconsistency and mis-interpretation of natural text. Hence, formal languages are emerging to allow a precise specification of enforceable privacy policies that can be verified. The EP3P language is one such formal language. An EP3P privacy policy of an enterprise consists of many rules. Given the semantics of the language, there may exist some rules in the ruleset which can never be used, these rules are referred to as redundant rules. Redundancies adversely affect privacy policies in several ways. Firstly, redundant rules reduce the efficiency of operations on privacy policies. Secondly, they may misdirect the policy auditor when determining the outcome of a policy. Therefore, in order to address these deficiencies it is important to identify and resolve redundancies. This thesis introduces the concept of minimal privacy policy - a policy that is free of redundancy. The essential component for maintaining the minimality of privacy policies is to determine the effects of the rules on each other. Hence, redundancy detection and resolution frameworks are proposed. Pair-wise redundancy detection is the central concept in these frameworks and it suggests a pair-wise comparison of the rules in order to detect redundancies. In addition, the thesis introduces a policy management tool that assists policy auditors in performing several operations on an EP3P privacy policy while maintaining its minimality. Formal results comparing alternative notions of redundancy, and how this would affect the tool, are also presented.

Enforcing P3P policies using a digital rights management system

The protection of privacy has gained considerable attention recently. In response to this, new privacy protection systems are being introduced. SITDRM is one such system that protects private data through the enforcement of licenses provided by consumers. Prior to supplying data, data owners are expected to construct a detailed license for the potential data users. A license specifies whom, under what conditions, may have what type of access to the protected data. The specification of a license by a data owner binds the enterprise data handling to the consumer’s privacy preferences. However, licenses are very detailed, may reveal the internal structure of the enterprise and need to be kept synchronous with the enterprise privacy policy. To deal with this, we employ the Platform for Privacy Preferences Language (P3P) to communicate enterprise privacy policies to consumers and enable them to easily construct data licenses. A P3P policy is more abstract than a license, allows data owners to specify the purposes for which data are being collected and directly reflects the privacy policy of an enterprise.

Location constraints in digital rights management

Digital rights management allows information owners to control the use and dissemination of electronic documents via a machine-readable licence. This paper describes the design and implementation of a system for creating and enforcing licences containing location constraints that can be used to restrict access to sensitive documents to a defined area. Documents can be loaded onto a portable device and used in the approved areas, but cannot be used if the device moves to another area. Our contribution includes a taxonomy for access control in the presence of requests to perform non-instantaneous controlled actions.

Adaptive unsupervised learning of human actions

Automatic detection of suspicious activities in CCTV camera feeds is crucial to the success of video surveillance systems. Such a capability can help transform the dumb CCTV cameras into smart surveillance tools for fighting crime and terror. Learning and classification of basic human actions is a precursor to detecting suspicious activities. Most of the current approaches rely on a non-realistic assumption that a complete dataset of normal human actions is available. This paper presents a different approach to deal with the problem of understanding human actions in video when no prior information is available. This is achieved by working with an incomplete dataset of basic actions which are continuously updated. Initially, all video segments are represented by Bags-Of-Words (BOW) method using only Term Frequency-Inverse Document Frequency (TF-IDF) features. Then, a data-stream clustering algorithm is applied for updating the system's knowledge from the incoming video feeds. Finally, all the actions are classified into different sets. Experiments and comparisons are conducted on the well known Weizmann and KTH datasets to show the efficacy of the proposed approach.

Characterising anomalous events using change point correlation on unsolicited network traffic

Monitoring unused or dark IP addresses offers opportunities to extract useful information about both on-going and new attack patterns. In recent years, different techniques have been used to analyze such traffic including sequential analysis where a change in traffic behavior, for example change in mean, is used as an indication of malicious activity. Change points themselves say little about detected change; further data processing is necessary for the extraction of useful information and to identify the exact cause of the detected change which is limited due to the size and nature of observed traffic. In this paper, we address the problem of analyzing a large volume of such traffic by correlating change points identified in different traffic parameters. The significance of the proposed technique is two-fold. Firstly, automatic extraction of information related to change points by correlating change points detected across multiple traffic parameters. Secondly, validation of the detected change point by the simultaneous presence of another change point in a different parameter. Using a real network trace collected from unused IP addresses, we demonstrate that the proposed technique enables us to not only validate the change point but also extract useful information about the causes of change points.

Ageing, learning, technology, and health management

The world’s population is ageing rapidly. Ageing has an impact on all aspects of human life, including social, economic, cultural, and political. Understanding ageing is therefore an important issue for the 21st century. This chapter will consider the active ageing model. This model is based on optimising opportunities for health, participation, and security in order to enhance quality of life. There is a range of exciting options developing for personal health management, for and by the ageing population, that make use of computer technology, and these should support active ageing. Their use depends however on older people learning to use computer technology effectively. The ability to use such technology will allow them to access relevant health information, advice, and support independently from wherever they live. Such support should increase rapidly in the future. This chapter is a consideration of ageing and learning, ageing and use of computer technology, and personal health management using computers.

Crowd Counting Using Multiple Local Features

In public venues, crowd size is a key indicator of crowd safety and stability. Crowding levels can be detected using holistic image features, however this requires a large amount of training data to capture the wide variations in crowd distribution. If a crowd counting algorithm is to be deployed across a large number of cameras, such a large and burdensome training requirement is far from ideal. In this paper we propose an approach that uses local features to count the number of people in each foreground blob segment, so that the total crowd estimate is the sum of the group sizes. This results in an approach that is scalable to crowd volumes not seen in the training data, and can be trained on a very small data set. As a local approach is used, the proposed algorithm can easily be used to estimate crowd density throughout different regions of the scene and be used in a multi-camera environment. A unique localised approach to ground truth annotation reduces the required training data is also presented, as a localised approach to crowd counting has different training requirements to a holistic one. Testing on a large pedestrian database compares the proposed technique to existing holistic techniques and demonstrates improved accuracy, and superior performance when test conditions are unseen in the training set, or a minimal training set is used.