A multi-agent system for pervasive healthcare

Wireless technology based pervasive healthcare has been proposed in many applications such as disease management and accident prevention for cost saving and promoting citizen’s wellbeing. However, the emphasis so far is on the artefacts with limited attentions to guiding the development of an effective and efficient solution for pervasive healthcare. Therefore, this paper aims to propose a framework of multi-agent systems design for pervasive healthcare by adopting the concept of pervasive informatics and using the methods of organisational semiotics. The proposed multi-agent system for pervasive healthcare utilises sensory information to support healthcare professionals for providing appropriate care. The key contributions contain theoretical aspect and practical aspect. In theory, this paper articulates the information interactions between the pervasive healthcare environment and stakeholders by using the methods of organisational semiotics; in practice, the proposed framework improves the healthcare quality by providing appropriate medical attentions when and as needed. In this paper, both systems and functional architecture of the multi-agent system are elaborated with the use of wireless technologies such as RFID and wireless sensor networks. The future study will focus on the implementation of the proposed framework.

A multi-agent system with a percolation approach to simulate the driving pattern of Plug-In ELectric Vehicles

A multi-agent system with a percolation approach to simulate the driving pattern of Plug-In Electric Vehicle (PEV), especially suited to simulate the PEVs behavior on any distribution systems, is presented. This tool intends to complement information about the driving patterns database on systems where that kind of information is not available. So, this paper aims to provide a framework that is able to work with any kind of technology and load generated of PEVs. The service zone is divided into several sub-zones, each subzone is considered as an independent agent identified with corresponding load level, and their relationships with the neighboring zones are represented as network probabilities. A percolation approach is used to characterize the autonomy of the battery of the PVEs to move through the city. The methodology is tested with data from a mid-size city real distribution system. The result shows the sub-area where the battery of PEVs will need to be recharge and gives the planners of distribution systems the necessary input for a medium to long term network planning in a smart grid environment. © 2012 IEEE.

Meiotic pairing of B chromosomes, multiple sexual system, and Robertsonian fusion in the red brocket deer Mazama americana (Mammalia, Cervidae)

Deer species of the genus Mazama show significant inter and intraspecific chromosomal variation due to the occurrence of rearrangements and B chromosomes. Given that carriers of aneuploidies and structural rearrangements often show anomalous chromosome pairings, we here performed a synaptonemal complex analysis to study chromosome pairing behavior in a red brocket deer (Mazama americana) individual that is heterozygous for a Robertsonian translocation, is a B chromosome carrier, and has a multiple sex chromosome system (XY1Y2). The synaptonemal complex in spermatocytes showed normal chromosome pairings for all chromosomes, including the autosomal and sex trivalents. The electromicrographs showed homology among B chromosomes since they formed bivalents, but they also appeared as univalents, indicating their anomalous behavior and non-Mendelian segregation. Thus, synaptonemal complex analysis is a useful tool to evaluate the role of B chromosomes and rearrangements during meiosis on the intraspecific chromosomal variation that is observed in the majority of Mazama species. © FUNPEC-RP.

Status epilepticus and multiple organ system dysfunction

Recent reports have suggested the possible association of status epilepticus and multiple organ system failure. The purpose of this case control study was to investigate this association and to identify factors that predispose individuals with status epilepticus (SE) or aborted status epilepticus (ASE) to develop multiple organ system failure (MOSF) or multiple organ system dysfunction (MODS).^ For the purpose of the study, definitions of SE, ASE, MOSF, and MODS were operationalized as follows: SE was defined as any seizure lasting for a duration of $\ge$30 minutes or intermittent seizures lasting for $\ge$30 minutes from which the patient does not regain consciousness. ASE was defined as any seizure lasting for a duration of $\ge$10 minutes but $<$30 minutes and which was aborted as a result of a medical intervention. MOSF was defined as the failure of $\ge$2 organ systems in the same patient; organ system failure was said to be present whenever standard MOSF criteria were met. MODS was defined as the dysfunction of $\ge$2 organ systems in the same patient; organ system dysfunction was said to be present, whenever the monitor(s) of that organ's function exceeded the normal range for the physiological or laboratory parameters.^ Medical records of 686 individuals between the age of 5 and 44 years, with history of seizures needing hospitalization at the Texas Children's Hospital or Methodist Hospital, Houston, Texas, between 1991-95 were reviewed and 100 individuals with SE/ASE were identified. Of these 100 individuals with SE/ASE, 45 developed MOSF/MODS during their hospitalization and 9 of these individuals died. Using multivariate analyses, it was found that adult individuals who had an "acute" etiology of their seizure disorder (OR = 5.23; 95%CI: 0.41, 66.24) and children who had a "remote" etiology of their seizure disorder (OR = 3.92; 95%CI: 0.53, 29.22), were more likely to develop MOSF/MODS compared with those who had other etiologies of the seizure disorder. Individuals with SE lasting more than one hour were more likely to develop MOSF/MODS compared with individuals with SE lasting less than 1 hour (OR = 6.51; 95%CI: 1.63, 25.92). Individuals who presented with the SE/ASE episode as their first seizure episode were more likely to develop MOSF/MODS compared to those with a previous history of seizure episodes (OR = 1.78; 95%CI: 0.36, 8.82).^ The major limitations of this study includes the relatively small sample size and the study being performed in only two institutions. However, this is the first study of this kind and should therefore be viewed as largely exploratory in nature. Future studies should investigate the relationship of the risk factors identified in this study using a larger number of institutions and patients. ^

A Multi-Agent System for the Solution of Fuzzy Incidents in Telecommunications

This article presents a multi-agent expert system (SMAF) , that allows the input of incidents which occur in different elements of the telecommunications area. SMAF interacts with experts and general users, and each agent with all the agents? community, recording the incidents and their solutions in a knowledge base, without the analysis of their causes. The incidents are expressed using keywords taken from natural language (originally Spanish) and their main concepts are recorded with their severities as the users express them. Then, there is a search of the best solution for each incident, being helped by a human operator using a distancenotions between them.

A multi-agent system with distributed bayesian reasoning for network fault diagnosis

In this paper, an innovative approach to perform distributed Bayesian inference using a multi-agent architecture is presented. The final goal is dealing with uncertainty in network diagnosis, but the solution can be of applied in other fields. The validation testbed has been a P2P streaming video service. An assessment of the work is presented, in order to show its advantages when it is compared with traditional manual processes and other previous systems.

Multi-agent system for control of robots inspired on the distributed activity and hormonal regulation of humans

Robotics is an emerging field with great activity. Robotics is a field that presents several problems because it depends on a large number of disciplines, technologies, devices and tasks. Its expansion from perfectly controlled industrial environments toward open and dynamic environment presents a many new challenges. New uses are, for example, household robots or professional robots. To facilitate the low cost, rapid development of robotic systems, reusability of code, its medium and long term maintainability and robustness are required novel approaches to provide generic models and software systems who develop paradigms capable of solving these problems. For this purpose, in this paper we propose a model based on multi-agent systems inspired by the human nervous system able to transfer the control characteristics of the biological system and able to take advantage of the best properties of distributed software systems. Specifically, we model the decentralized activity and hormonal variation.

Proposal for a multiple console system for Illiac II /

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A multi-agent system using iterative bidding mechanism to enhance manufacturing agility

The global market has become increasingly dynamic, unpredictable and customer-driven. This has led to rising rates of new product introduction and turbulent demand patterns across product mixes. As a result, manufacturing enterprises were facing mounting challenges to be agile and responsive to cope with market changes, so as to achieve the competitiveness of producing and delivering products to the market timely and cost-effectively. This paper introduces a currency-based iterative agent bidding mechanism to effectively and cost-efficiently integrate the activities associated with production planning and control, so as to achieve an optimised process plan and schedule. The aim is to enhance the agility of manufacturing systems to accommodate dynamic changes in the market and production. The iterative bidding mechanism is executed based on currency-like metrics; each operation to be performed is assigned with a virtual currency value and agents bid for the operation if they make a virtual profit based on this value. These currency values are optimised iteratively and so does the bidding process based on new sets of values. This is aimed at obtaining better and better production plans, leading to near-optimality. A genetic algorithm is proposed to optimise the currency values at each iteration. In this paper, the implementation of the mechanism and the test case simulation results are also discussed. © 2012 Elsevier Ltd. All rights reserved.