Detection and prevention of distributed denial of services attacks by collaborative effort of software agents, first prototype implementation

Distributed Denial of Services DDoS, attacks has become one of the biggest threats for resources over Internet. Purpose of these attacks is to make servers deny from providing services to legitimate users. These attacks are also used for occupying media bandwidth. Currently intrusion detection systems can just detect the attacks but cannot prevent / track the location of intruders. Some schemes also prevent the attacks by simply discarding attack packets, which saves victim from attack, but still network bandwidth is wasted. In our opinion, DDoS requires a distributed solution to save wastage of resources. The paper, presents a system that helps us not only in detecting such attacks but also helps in tracing and blocking (to save the bandwidth as well) the multiple intruders using Intelligent Software Agents. The system gives dynamic response and can be integrated with the existing network defense systems without disturbing existing Internet model. We have implemented an agent based networking monitoring system in this regard.

DDX : A distributed software architecture for robotic systems

The Dynamic Data eXchange (DDX) is our third generation platform for building distributed robot controllers. DDX allows a coalition of programs to share data at run-time through an efficient shared memory mechanism managed by a store. Further, stores on multiple machines can be linked by means of a global catalog and data is moved between the stores on an as needed basis by multi-casting. Heterogeneous computer systems are handled. We describe the architecture of DDX and the standard clients we have developed that let us rapidly build complex control systems with minimal coding.

Impacts of vessel capacity reduction programs on the efficiency in fisheries. The case of Australia's multispecies in northern prawn fishery

Capacity reduction programs in the form of buybacks or decommissioning programs have had relatively widespread application in fisheries in the US, Europe and Australia. A common criticism of such programs is that they remove the least efficient vessels first, resulting in an increase in average efficiency of the remaining fleet. The effective fishing power of the fleet, therefore, does not decrease in proportion to the number of vessels removed. Further, reduced crowding may increase efficiency of the remaining vessels. In this paper, the effects of a buyback program on average technical efficiency in Australia’s Northern Prawn Fishery are examined using a multi-output distance function approach with an explicit inefficiency model. The results indicate that average efficiency of the remaining vessels was greater than that of the removed vessels, and that average efficiency of remaining vessels also increased as a result of reduced crowding.

Constructing the hallucinations of psychosis in Virtual Reality

Schizophrenia is a mental disorder affecting 1-2% of the population and it is estimated 12-16% of hospital beds in Australia are occupied by patients with psychosis. The suicide rate for patients with this diagnosis is higher than that of the general population. Any technique which enhances training and treatment of this disorder will have a significant societal and economic impact. A significant research project using Virtual Reality (VR), in which both visual and auditory hallucinations are simulated, is currently being undertaken at the University of Queensland. The virtual environments created by the new software are expected to enhance the experiential learning outcomes of medical students by enabling them to experience the inner world of a patient with psychosis. In addition the Virtual Environment has the potential to provide a technologically advanced therapeutic setting where behavioral, exposure therapies can be conducted with exactly controlled exposure stimuli with an expected reduction in risk of harm. This paper reports on the current work of the project, previous stages of software development and future educational and clinical applications of the Virtual Environments. (C) 2004 Elsevier Ltd. All rights reserved.

Voltage unbalance reduction in low voltage distribution networks with rooftop PVs

Voltage Unbalance (VU) is a power quality issue arising within the low voltage residential distribution networks due to the random location and rating of single-phase rooftop photovoltaic cells (PVs). In this paper, an analysis has been carried out to investigate how PV installations, their random location and power generation capacity can cause an increase in VU. Several efficient practical methods are discussed for VU reduction. Based on this analysis, it has been shown that the installation of a DSTATCOM can reduce VU. In this paper, the best possible location for DSTATCOM and its efficient control method to reduce VU will be presented. The results are verified through PSCAD/EMTDC and Monte Carlo simulations.

A programming language for software components

Component software has many benefits, most notably increased software re-use; however, the component software process places heavy burdens on programming language technology, which modern object-oriented programming languages do not address. In particular, software components require specifications that are both sufficiently expressive and sufficiently abstract, and, where possible, these specifications should be checked formally by the programming language. This dissertation presents a programming language called Mentok that provides two novel programming language features enabling improved specification of stateful component roles. Negotiable interfaces are interface types extended with protocols, and allow specification of changing method availability, including some patterns of out-calls and re-entrance. Type layers are extensions to module signatures that allow specification of abstract control flow constraints through the interfaces of a component-based application. Development of Mentok's unique language features included creation of MentokC, the Mentok compiler, and formalization of key properties of Mentok in mini-languages called MentokP and MentokL.

Nitrogen fertilizer rate management as a nitrous oxide mitigation strategy: Development of a nitrous oxide emission reduction protocol (NERP)

Nitrous oxide (N2O) is a potent agricultural greenhouse gas (GHG). More than 50% of the global anthropogenic N2O flux is attributable to emissions from soil, primarily due to large fertilizer nitrogen (N) applications to corn and other non-leguminous crops. Quantification of the trade–offs between N2O emissions, fertilizer N rate, and crop yield is an essential requirement for informing management strategies aiming to reduce the agricultural sector GHG burden, without compromising productivity and producer livelihood. There is currently great interest in developing and implementing agricultural GHG reduction offset projects for inclusion within carbon offset markets. Nitrous oxide, with a global warming potential (GWP) of 298, is a major target for these endeavours due to the high payback associated with its emission prevention. In this paper we use robust quantitative relationships between fertilizer N rate and N2O emissions, along with a recently developed approach for determining economically profitable N rates for optimized crop yield, to propose a simple, transparent, and robust N2O emission reduction protocol (NERP) for generating agricultural GHG emission reduction credits. This NERP has the advantage of providing an economic and environmental incentive for producers and other stakeholders, necessary requirements in the implementation of agricultural offset projects.