Web services based state of the environment reporting

The Environmental Sciences Division within Queensland Environmental Protection Agency works to monitor, assess and model the condition of the environment. The Division has as a legislative responsibility to produce a whole-of-government report every four years dealing environmental conditions and trends in a ”State of the Environment report” (SoE)[1][2][3]. State of Environment Web Service Reporting System is a supplementary web service based SoE reporting tool, which aims to deliver accurate, timely and accessible information on the condition of the environment through web services via Internet [4][5]. This prototype provides a scientific assessment of environmental conditions for a set of environmental indicators. It contains text descriptions and tables, charts and maps with spatiotemporal dimensions to show the impact of certain environmental indicators on our environment. This prototype is a template based indicator system, to which the administrator may add new sql queries for new indicator services without changing the architecture and codes of this template. The benefits are brought through a service-oriented architecture which provides an online query service with seamless integration. In addition, since it uses web service architecture, each individual component within the application can be implemented by using different programming languages and in different operating systems. Although the services showed in this demo are built upon two datasets of regional ecosystem and protection area of Queensland, it will be possible to report on the condition of water, air, land, coastal zones, energy resources, biodiversity, human settlements and natural culture heritage on the fly as well. Figure 1 shows the architecture of the prototype. In the next section, I will discuss the research tasks in the prototype.

Increased availability and scalability for clustered services via the wait time calculation, trust based filtering and redirection of TCP connection requests

The paper describes two new transport layer (TCP) options and an expanded transport layer queuing strategy that facilitate three functions that are fundamental to the dispatching-based clustered service. A transport layer option has been developed to facilitate. the use of client wait time data within the service request processing of the cluster. A second transport layer option has been developed to facilitate the redirection of service requests by the cluster dispatcher to the cluster processing member. An expanded transport layer service request queuing strategy facilitates the trust based filtering of incoming service requests so that a graceful degradation of service delivery may be achieved during periods of overload - most dramatically evidenced by distributed denial of service attacks against the clustered service. We describe how these new options and queues have been implemented and successfully tested within the transport layer of the Linux kernel.

UMA NOVA CARTOGRAFIA COGNITIVA PARA O ENSINO DA COMUNICAÇÃO

O trabalho proposto é a montar um projeto exploratório funcional que parta da cartografia cognitiva, que é definida como a arte, teoria e técnica de construir mapas do conhecimento, visando com esta cartografia a sua aplicabilidade na estruturação de um conjunto de cursos/saberes da área da Comunicação. Assemelhado ao conceito de mapas conceituais, ou cognitivos, representam o conhecimento organizado e são compostos por conceitos. Este mapas foram desenvolvido a partir da década de setenta por vários pesquisadores. A tese experimento foi montada tendo como base os softwares de relacionamento por temas e interesses dentro de um ambiente de interatividade tridimensional , montado no conceito de arvore do conhecimento relacional. Esta experiência é construída em ambiente tridimensional com uso de softwares 3D que rodam como aplicativos de engines de vídeo games, que são motores gráficos. A base de dados e a interatividade de textos e tarefas é realizada sob a plataforma do MediaWiki, que é o software aberto que roda a Wikipédia. A plataforma de mapas roda dentro de um software MindJet MindManager e do CMAPS. As vídeo conferências são administradas pelo FlashMeeting, de Web conferência. A maioria deles são softwares abertos. Todos operando em sistemas presenciais ou de modulação EAD. A base conceitual está estruturada dentro de uma visão de educação disruptiva, que lança um novo modelo educacional baseado em mapas, visto dentro de uma abordagem de um mundo de múltiplas telas, um mundo da era hiper, um mundo hipermoderno, que tem como base uma cultura da era tecnológica, numa renovação dos conceitos de Cultura, agora revigorados à luz das novas tecnologias e da nova sociedade interligada em rede.

An improved tool for automated compiler construction

Since the advent of High Level Programming languages (HLPLs) in the early 1950s researchers have sought ways to automate the construction of HLPL compilers. To this end a variety of Translator Writing Tools (TWTs) have been developed in the last three decades. However, only a very few of these tools have gained significant commercial acceptance. This thesis re-examines traditional compiler construction techniques, along with a number of previous TWTs, and proposes a new improved tool for automated compiler construction called the Aston Compiler Constructor (ACC). This new tool allows the specification of complete compilation systems using a high level compiler oriented specification notation called the Compiler Construction Language (CCL). This specification notation is based on a modern variant of Backus Naur Form (BNF) and an extended variant of Attribute Grammars (AGs). The implementation and processing of the CCL is discussed along with an extensive CCL example. The CCL is shown to have an extensive expressive power, to be convenient in use, and highly readable, and thus a superior alternative to earlier TWTs, and to traditional compiler construction techniques. The execution performance of CCL specifications is evaluated and shown to be acceptable. A number of related areas are also addressed, including tools for the rapid construction of individual compiler components, and tools for the construction of compilation systems for multiprocessor operating systems and hardware. This latter area is expected to become of particular interest in future years due to the anticipated increased use of multiprocessor architectures.

Predicting and diagnosing faults in wastewater treatment process by Bayesian Belief Networks

Diagnosing faults in wastewater treatment, like diagnosis of most problems, requires bi-directional plausible reasoning. This means that both predictive (from causes to symptoms) and diagnostic (from symptoms to causes) inferences have to be made, depending on the evidence available, in reasoning for the final diagnosis. The use of computer technology for the purpose of diagnosing faults in the wastewater process has been explored, and a rule-based expert system was initiated. It was found that such an approach has serious limitations in its ability to reason bi-directionally, which makes it unsuitable for diagnosing tasks under the conditions of uncertainty. The probabilistic approach known as Bayesian Belief Networks (BBNS) was then critically reviewed, and was found to be well-suited for diagnosis under uncertainty. The theory and application of BBNs are outlined. A full-scale BBN for the diagnosis of faults in a wastewater treatment plant based on the activated sludge system has been developed in this research. Results from the BBN show good agreement with the predictions of wastewater experts. It can be concluded that the BBNs are far superior to rule-based systems based on certainty factors in their ability to diagnose faults and predict systems in complex operating systems having inherently uncertain behaviour.

CamSim:a distributed smart camera network simulator

Smart cameras allow pre-processing of video data on the camera instead of sending it to a remote server for further analysis. Having a network of smart cameras allows various vision tasks to be processed in a distributed fashion. While cameras may have different tasks, we concentrate on distributed tracking in smart camera networks. This application introduces various highly interesting problems. Firstly, how can conflicting goals be satisfied such as cameras in the network try to track objects while also trying to keep communication overhead low? Secondly, how can cameras in the network self adapt in response to the behavior of objects and changes in scenarios, to ensure continued efficient performance? Thirdly, how can cameras organise themselves to improve the overall network's performance and efficiency? This paper presents a simulation environment, called CamSim, allowing distributed self-adaptation and self-organisation algorithms to be tested, without setting up a physical smart camera network. The simulation tool is written in Java and hence allows high portability between different operating systems. Relaxing various problems of computer vision and network communication enables a focus on implementing and testing new self-adaptation and self-organisation algorithms for cameras to use.

Integration Principles of Russian and Japanese Databases on Inorganic Materials

The methods and software for integration of databases (DBs) on inorganic material and substance properties have been developed. The information systems integration is based on known approaches combination: EII (Enterprise Information Integration) and EAI (Enterprise Application Integration). The metabase - special database that stores data on integrated DBs contents is an integrated system kernel. Proposed methods have been applied for DBs integrated system creation in the field of inorganic chemistry and materials science. Important developed integrated system feature is ability to include DBs that have been created by means of different DBMS using essentially various computer platforms: Sun (DB "Diagram") and Intel (other DBs) and diverse operating systems: Sun Solaris (DB "Diagram") and Microsoft Windows Server (other DBs).

Detecting and monitoring the symptoms of Parkinson's disease using smartphones:a pilot study

Background: Remote, non-invasive and objective tests that can be used to support expert diagnosis for Parkinson's disease (PD) are lacking. Methods: Participants underwent baseline in-clinic assessments, including the Unified Parkinson's Disease Rating Scale (UPDRS), and were provided smartphones with an Android operating system that contained a smartphone application that assessed voice, posture, gait, finger tapping, and response time. Participants then took the smart phones home to perform the five tasks four times a day for a month. Once a week participants had a remote (telemedicine) visit with a Parkinson disease specialist in which a modified (excluding assessments of rigidity and balance) UPDRS performed. Using statistical analyses of the five tasks recorded using the smartphone from 10 individuals with PD and 10 controls, we sought to: (1) discriminate whether the participant had PD and (2) predict the modified motor portion of the UPDRS. Results: Twenty participants performed an average of 2.7 tests per day (68.9% adherence) for the study duration (average of 34.4 days) in a home and community setting. The analyses of the five tasks differed between those with Parkinson disease and those without. In discriminating participants with PD from controls, the mean sensitivity was 96.2% (SD 2%) and mean specificity was 96.9% (SD 1.9%). The mean error in predicting the modified motor component of the UPDRS (range 11-34) was 1.26 UPDRS points (SD 0.16). Conclusion: Measuring PD symptoms via a smartphone is feasible and has potential value as a diagnostic support tool.

Mobile Access to Cultural and Historical Heritage Web Pages

The main focus of attention in this paper is the access to websites of leading regional, national and world museums. Their accessibility from desktop and mobile devices is hereby evaluated. The paper covers a detailed analysis of the mobile operating systems, their market share in Bulgaria and the opportunities they offer to the users. The need for contemporary cultural and historical heritage websites which maintain lighter but fully-functioning mobile versions, facilitating and making their access from portable devices easier, is also well-grounded here.

A behavior based approach to virus detection

Fast spreading unknown viruses have caused major damage on computer systems upon their initial release. Current detection methods have lacked capabilities to detect unknown viruses quickly enough to avoid mass spreading and damage. This dissertation has presented a behavior based approach to detecting known and unknown viruses based on their attempt to replicate. Replication is the qualifying fundamental characteristic of a virus and is consistently present in all viruses making this approach applicable to viruses belonging to many classes and executing under several conditions. A form of replication called self-reference replication, (SR-replication), has been formalized as one main type of replication which specifically replicates by modifying or creating other files on a system to include the virus itself. This replication type was used to detect viruses attempting replication by referencing themselves which is a necessary step to successfully replicate files. The approach does not require a priori knowledge about known viruses. Detection was accomplished at runtime by monitoring currently executing processes attempting to replicate. Two implementation prototypes of the detection approach called SRRAT were created and tested on the Microsoft Windows operating systems focusing on the tracking of user mode Win32 API system calls and Kernel mode system services. The research results showed SR-replication capable of distinguishing between file infecting viruses and benign processes with little or no false positives and false negatives. ^

A Behavior Based Approach to Virus Detection

Fast spreading unknown viruses have caused major damage on computer systems upon their initial release. Current detection methods have lacked capabilities to detect unknown virus quickly enough to avoid mass spreading and damage. This dissertation has presented a behavior based approach to detecting known and unknown viruses based on their attempt to replicate. Replication is the qualifying fundamental characteristic of a virus and is consistently present in all viruses making this approach applicable to viruses belonging to many classes and executing under several conditions. A form of replication called self-reference replication, (SR-replication), has been formalized as one main type of replication which specifically replicates by modifying or creating other files on a system to include the virus itself. This replication type was used to detect viruses attempting replication by referencing themselves which is a necessary step to successfully replicate files. The approach does not require a priori knowledge about known viruses. Detection was accomplished at runtime by monitoring currently executing processes attempting to replicate. Two implementation prototypes of the detection approach called SRRAT were created and tested on the Microsoft Windows operating systems focusing on the tracking of user mode Win32 API system calls and Kernel mode system services. The research results showed SR-replication capable of distinguishing between file infecting viruses and benign processes with little or no false positives and false negatives.

Integrity-based kernel malware detection

Kernel-level malware is one of the most dangerous threats to the security of users on the Internet, so there is an urgent need for its detection. The most popular detection approach is misuse-based detection. However, it cannot catch up with today's advanced malware that increasingly apply polymorphism and obfuscation. In this thesis, we present our integrity-based detection for kernel-level malware, which does not rely on the specific features of malware. ^ We have developed an integrity analysis system that can derive and monitor integrity properties for commodity operating systems kernels. In our system, we focus on two classes of integrity properties: data invariants and integrity of Kernel Queue (KQ) requests. ^ We adopt static analysis for data invariant detection and overcome several technical challenges: field-sensitivity, array-sensitivity, and pointer analysis. We identify data invariants that are critical to system runtime integrity from Linux kernel 2.4.32 and Windows Research Kernel (WRK) with very low false positive rate and very low false negative rate. We then develop an Invariant Monitor to guard these data invariants against real-world malware. In our experiment, we are able to use Invariant Monitor to detect ten real-world Linux rootkits and nine real-world Windows malware and one synthetic Windows malware. ^ We leverage static and dynamic analysis of kernel and device drivers to learn the legitimate KQ requests. Based on the learned KQ requests, we build KQguard to protect KQs. At runtime, KQguard rejects all the unknown KQ requests that cannot be validated. We apply KQguard on WRK and Linux kernel, and extensive experimental evaluation shows that KQguard is efficient (up to 5.6% overhead) and effective (capable of achieving zero false positives against representative benign workloads after appropriate training and very low false negatives against 125 real-world malware and nine synthetic attacks). ^ In our system, Invariant Monitor and KQguard cooperate together to protect data invariants and KQs in the target kernel. By monitoring these integrity properties, we can detect malware by its violation of these integrity properties during execution.^

Performance analysis of disk mirroring techniques

Unequaled improvements in processor and I/O speeds make many applications such as databases and operating systems to be increasingly I/O bound. Many schemes such as disk caching and disk mirroring have been proposed to address the problem. In this thesis we focus only on disk mirroring. In disk mirroring, a logical disk image is maintained on two physical disks allowing a single disk failure to be transparent to application programs. Although disk mirroring improves data availability and reliability, it has two major drawbacks. First, writes are expensive because both disks must be updated. Second, load balancing during failure mode operation is poor because all requests are serviced by the surviving disk. Distorted mirrors was proposed to address the write problem and interleaved declustering to address the load balancing problem. In this thesis we perform a comparative study of these two schemes under various operating modes. In addition we also study traditional mirroring to provide a common basis for comparison.

PanTool - software for data harmonization and conversion, Version 1

The program PanTool was developed as a tool box like a Swiss Army Knife for data conversion and recalculation, written to harmonize individual data collections to standard import format used by PANGAEA. The format of input files the program PanTool needs is a tabular saved in plain ASCII. The user can create this files with a spread sheet program like MS-Excel or with the system text editor. PanTool is distributed as freeware for the operating systems Microsoft Windows, Apple OS X and Linux.