KEMNAD:a knowledge engineering methodology for negotiating agent development

Automated negotiation is widely applied in various domains. However, the development of such systems is a complex knowledge and software engineering task. So, a methodology there will be helpful. Unfortunately, none of existing methodologies can offer sufficient, detailed support for such system development. To remove this limitation, this paper develops a new methodology made up of: (1) a generic framework (architectural pattern) for the main task, and (2) a library of modular and reusable design pattern (templates) of subtasks. Thus, it is much easier to build a negotiating agent by assembling these standardised components rather than reinventing the wheel each time. Moreover, since these patterns are identified from a wide variety of existing negotiating agents (especially high impact ones), they can also improve the quality of the final systems developed. In addition, our methodology reveals what types of domain knowledge need to be input into the negotiating agents. This in turn provides a basis for developing techniques to acquire the domain knowledge from human users. This is important because negotiation agents act faithfully on the behalf of their human users and thus the relevant domain knowledge must be acquired from the human users. Finally, our methodology is validated with one high impact system.

A design and implementation methodology for high variety electronics assembly systems

Small indigenous manufacturers of electronic equipment are coming under increasingly severe pressure to adopt a strong defensive position against large multinational and Far Eastern companies. A common response to this threat has been for these firms to adopt a 'market driven' business strategy based on quality and customer service, rather than a 'technology led' strategy which uses technical specification and price to compete. To successfully implement this type of strategy there is a need for production systems to be redesigned to suit the new demands of marketing. Increased range and fast response require economy of scope rather t ban economy or scale while the organisation's culture must promote quality and process consciousness. This paper describes the 'Modular Assembly Cascade' concept which addresses these needs by applying the principles of flexible manufacturing (FMS) and just in time (,JlT) to electronics assembly. A methodology for executing the concept is also outlined. This is called DRAMA (Design Houtirw !'or· Adopting Modular Assembly).

Complexity of classical dynamics of molecular systems. I. Methodology

Methods for the calculation of complexity have been investigated as a possible alternative for the analysis of the dynamics of molecular systems. “Computational mechanics” is the approach chosen to describe emergent behavior in molecular systems that evolve in time. A novel algorithm has been developed for symbolization of a continuous physical trajectory of a dynamic system. A method for calculating statistical complexity has been implemented and tested on representative systems. It is shown that the computational mechanics approach is suitable for analyzing the dynamic complexity of molecular systems and offers new insight into the process.

Intelligence Algorithms for Increasing Navigation Systems Accuracy

Application of neural network algorithm for increasing the accuracy of navigation systems are showing. Various navigation systems, where a couple of sensors are used in the same device in different positions and the disturbances act equally on both sensors, the trained neural network can be advantageous for increasing the accuracy of system. The neural algorithm had used for determination the interconnection between the sensors errors in two channels to avoid the unobservation of navigation system. Representation of thermal error of two- component navigation sensors by time model, which coefficients depend only on parameters of the device, its orientations relative to disturbance vector allows to predict thermal errors change, measuring the current temperature and having identified preliminary parameters of the model for the set position. These properties of thermal model are used for training the neural network and compensation the errors of navigation system in non- stationary thermal fields.

A methodology for formally modeling and analyzing software architecture of mobile agent systems

A methodology for formally modeling and analyzing software architecture of mobile agent systems provides a solid basis to develop high quality mobile agent systems, and the methodology is helpful to study other distributed and concurrent systems as well. However, it is a challenge to provide the methodology because of the agent mobility in mobile agent systems.^ The methodology was defined from two essential parts of software architecture: a formalism to define the architectural models and an analysis method to formally verify system properties. The formalism is two-layer Predicate/Transition (PrT) nets extended with dynamic channels, and the analysis method is a hierarchical approach to verify models on different levels. The two-layer modeling formalism smoothly transforms physical models of mobile agent systems into their architectural models. Dynamic channels facilitate the synchronous communication between nets, and they naturally capture the dynamic architecture configuration and agent mobility of mobile agent systems. Component properties are verified based on transformed individual components, system properties are checked in a simplified system model, and interaction properties are analyzed on models composing from involved nets. Based on the formalism and the analysis method, this researcher formally modeled and analyzed a software architecture of mobile agent systems, and designed an architectural model of a medical information processing system based on mobile agents. The model checking tool SPIN was used to verify system properties such as reachability, concurrency and safety of the medical information processing system. ^ From successful modeling and analyzing the software architecture of mobile agent systems, the conclusion is that PrT nets extended with channels are a powerful tool to model mobile agent systems, and the hierarchical analysis method provides a rigorous foundation for the modeling tool. The hierarchical analysis method not only reduces the complexity of the analysis, but also expands the application scope of model checking techniques. The results of formally modeling and analyzing the software architecture of the medical information processing system show that model checking is an effective and an efficient way to verify software architecture. Moreover, this system shows a high level of flexibility, efficiency and low cost of mobile agent technologies. ^

A novel methodology for analysis of large scale interconnected power and gas systems

The European Union continues to exert a large influence on the direction of member states energy policy. The 2020 targets for renewable energy integration have had significant impact on the operation of current power systems, forcing a rapid change from fossil fuel dominated systems to those with high levels of renewable power. Additionally, the overarching aim of an internal energy market throughout Europe has and will continue to place importance on multi-jurisdictional co-operation regarding energy supply. Combining these renewable energy and multi-jurisdictional supply goals results in a complicated multi-vector energy system, where the understanding of interactions between fossil fuels, renewable energy, interconnection and economic power system operation is increasingly important. This paper provides a novel and systematic methodology to fully understand the changing dynamics of interconnected energy systems from a gas and power perspective. A fully realistic unit commitment and economic dispatch model of the 2030 power systems in Great Britain and Ireland, combined with a representative gas transmission energy flow model is developed. The importance of multi-jurisdictional integrated energy system operation in one of the most strategically important renewable energy regions is demonstrated.

'Artificial Immune Systems Tutorial'

The biological immune system is a robust, complex, adaptive system that defends the body from foreign pathogens. It is able to categorize all cells (or molecules) within the body as self-cells or non-self cells. It does this with the help of a distributed task force that has the intelligence to take action from a local and also a global perspective using its network of chemical messengers for communication. There are two major branches of the immune system. The innate immune system is an unchanging mechanism that detects and destroys certain invading organisms, whilst the adaptive immune system responds to previously unknown foreign cells and builds a response to them that can remain in the body over a long period of time. This remarkable information processing biological system has caught the attention of computer science in recent years. A novel computational intelligence technique, inspired by immunology, has emerged, called Artificial Immune Systems. Several concepts from the immune have been extracted and applied for solution to real world science and engineering problems. In this tutorial, we briefly describe the immune system metaphors that are relevant to existing Artificial Immune Systems methods. We will then show illustrative real-world problems suitable for Artificial Immune Systems and give a step-by-step algorithm walkthrough for one such problem. A comparison of the Artificial Immune Systems to other well-known algorithms, areas for future work, tips & tricks and a list of resources will round this tutorial off. It should be noted that as Artificial Immune Systems is still a young and evolving field, there is not yet a fixed algorithm template and hence actual implementations might differ somewhat from time to time and from those examples given here.

'Artificial Immune Systems Tutorial'

The biological immune system is a robust, complex, adaptive system that defends the body from foreign pathogens. It is able to categorize all cells (or molecules) within the body as self-cells or non-self cells. It does this with the help of a distributed task force that has the intelligence to take action from a local and also a global perspective using its network of chemical messengers for communication. There are two major branches of the immune system. The innate immune system is an unchanging mechanism that detects and destroys certain invading organisms, whilst the adaptive immune system responds to previously unknown foreign cells and builds a response to them that can remain in the body over a long period of time. This remarkable information processing biological system has caught the attention of computer science in recent years. A novel computational intelligence technique, inspired by immunology, has emerged, called Artificial Immune Systems. Several concepts from the immune have been extracted and applied for solution to real world science and engineering problems. In this tutorial, we briefly describe the immune system metaphors that are relevant to existing Artificial Immune Systems methods. We will then show illustrative real-world problems suitable for Artificial Immune Systems and give a step-by-step algorithm walkthrough for one such problem. A comparison of the Artificial Immune Systems to other well-known algorithms, areas for future work, tips & tricks and a list of resources will round this tutorial off. It should be noted that as Artificial Immune Systems is still a young and evolving field, there is not yet a fixed algorithm template and hence actual implementations might differ somewhat from time to time and from those examples given here.

An ecosystem of products and systems for ambient intelligence – the AAL4ALL users perspective

Texto completo em atas de encontros científicos internacionais com arbitragem

Intelligence-led policing : O papel dos sistemas de informação no planeamento e orientação do esforço de policiamento

O presente trabalho de investigação aplicada está subordinado ao tema “Intelligence-led policing: o papel dos sistemas de informação no planeamento e orientação do esforço de policiamento”. Começámos por fazer um enquadramento teórico e abordar conceitos importantes para o desenvolvimento de todo o trabalho. Assumindo um método dedutivo, desenvolvemos um estudo com base na seguinte questão de partida: “Qual o impacto dos sistemas de informação no planeamento e orientação do esforço de policiamento?”. Posto isto, este trabalho tem como objetivo perceber qual a influência que os sistemas de informação têm na tomada de decisão do comandante, neste caso de Destacamento Territorial, mais precisamente no planeamento e orientação do esforço de policiamento. Quanto à metodologia, incidiu numa análise documental sobre as variáveis em estudo e também na análise de respostas aos inquéritos por questionário efetuados aos Comandantes de Destacamento Territorial. Com este trabalho concluímos que, do ponto de vista de uma grande parte dos inquiridos, os sistemas de informação que a Guarda Nacional Republicana dispõe não são adequados às necessidades operacionais desta. Outra conclusão a que chegámos foi ao facto de, apesar da informação analisada ter reconhecidamente valor acrescentado, as ferramentas de análise que a Guarda dispõe também não são suficientes para suprir as necessidades sentidas.

Irish state infrastructural investment: an analysis of past patterns, and an outline of a future integrated systems of systems evaluation methodology

The literature clearly links the quality and capacity of a country’s infrastructure to its economic growth and competitiveness. This thesis analyses the historic national and spatial distribution of investment by the Irish state in its physical networks (water, wastewater and roads) across the 34 local authorities and examines how Ireland is perceived internationally relative to its economic counterparts. An appraisal of the current status and shortcomings of Ireland’s infrastructure is undertaken using key stakeholders from foreign direct investment companies and national policymakers to identify Ireland's infrastructural gaps, along with current challenges in how the country is delivering infrastructure. The output of these interviews identified many issues with how infrastructure decision-making is currently undertaken. This led to an evaluation of how other countries are informing decision-making, and thus this thesis presents a framework of how and why Ireland should embrace a Systems of Systems (SoS) methodology approach to infrastructure decision-making going forward. In undertaking this study a number of other infrastructure challenges were identified: significant political interference in infrastructure decision-making and delivery the need for a national agency to remove the existing ‘silo’ type of mentality to infrastructure delivery how tax incentives can interfere with the market; and their significance. The two key infrastructure gaps identified during the interview process were: the need for government intervention in the rollout of sufficient communication capacity and at a competitive cost outside of Dublin; and the urgent need to address water quality and capacity with approximately 25% of the population currently being served by water of unacceptable quality. Despite considerable investment in its national infrastructure, Ireland’s infrastructure performance continues to trail behind its economic partners in the Eurozone and OECD. Ireland is projected to have the highest growth rate in the euro zone region in 2015 and 2016, albeit that it required a bailout in 2010, and, at the time of writing, is beginning to invest in its infrastructure networks again. This thesis proposes the development and implementation of a SoS approach for infrastructure decision-making which would be based on: existing spatial and capacity data of each of the constituent infrastructure networks; and scenario computation and analysis of alternative drivers eg. Demographic change, economic variability and demand/capacity constraints. The output from such an analysis would provide valuable evidence upon which policy makers and decision makers alike could rely, which has been lacking in historic investment decisions.

A Case Based Methodology for Problem Solving aiming at Knee Osteoarthritis Detection

Knee osteoarthritis is the most common type of arthritis and a major cause of impaired mobility and disability for the ageing populations. Therefore, due to the increasing prevalence of the malady, it is expected that clinical and scientific practices had to be set in order to detect the problem in its early stages. Thus, this work will be focused on the improvement of methodologies for problem solving aiming at the development of Artificial Intelligence based decision support system to detect knee osteoarthritis. The framework is built on top of a Logic Programming approach to Knowledge Representation and Reasoning, complemented with a Case Based approach to computing that caters for the handling of incomplete, unknown, or even self-contradictory information.

Integration of heterogeneous data sources and automated reasoning in healthcare and domotic IoT systems

In recent years, IoT technology has radically transformed many crucial industrial and service sectors such as healthcare. The multi-facets heterogeneity of the devices and the collected information provides important opportunities to develop innovative systems and services. However, the ubiquitous presence of data silos and the poor semantic interoperability in the IoT landscape constitute a significant obstacle in the pursuit of this goal. Moreover, achieving actionable knowledge from the collected data requires IoT information sources to be analysed using appropriate artificial intelligence techniques such as automated reasoning. In this thesis work, Semantic Web technologies have been investigated as an approach to address both the data integration and reasoning aspect in modern IoT systems. In particular, the contributions presented in this thesis are the following: (1) the IoT Fitness Ontology, an OWL ontology that has been developed in order to overcome the issue of data silos and enable semantic interoperability in the IoT fitness domain; (2) a Linked Open Data web portal for collecting and sharing IoT health datasets with the research community; (3) a novel methodology for embedding knowledge in rule-defined IoT smart home scenarios; and (4) a knowledge-based IoT home automation system that supports a seamless integration of heterogeneous devices and data sources.