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Intelligent embedded agents for biological data acquisition in an environment of a distributed e-laboratory
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An approach of interpreting some bioinformatics data using Self-Organizing Map (SOM) type neural networks is described. The ways are proposed constructing intelligent program tools of embedded agents to collect ECG and EEG data for academic usage in a virtual e-laboratory. A SOM-based diagnostic algorithm is proposed interpreting data from Medical...
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... software for an adap- tive control and Delphi programming environment for real- izing IRC communication between remote objects. Physi- cal communications with remote objects are designed via TCP/IP sockets. An implementation of a remote adaptive bio-robot control within an e-laboratory is based on AT- mega8 microcontrollers as embedded agents (Fig. 1). The embedded agents are supported by remotely communicable hardware implementing In System Programming (ISP) fea-ture of each microcontroller. Every Bio-Robot i=1,m in an e- laboratory is controlled by its own JADEX-based bio-robot control agent JBRCA i=1,m . Multi-robot control strategy by Multi-user is being permanently realized by ...
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... MRCA.. Each Bio- Robot i=1,m is controlled directly by its IRC Client i=1,m via serial RS232 port using HyperTerminal software. Adaptive control strategy of Bio-Robot i=1,m can be implemented only having its online reprogramming capabilities by perma- nently using In System Programming (ISP) feature of each microcontroller. In the e-laboratory of Fig. 1, this is real- ized by arranging for each Bio-Robot i=1,m both the Commu- tative Hardware i=1,m and ISP Programmer i=1,m . These ad- ditional elements allow communication with each remote ATmega8-based embedded agent either for its control or reprogramming purposes implementing adaptive properties of Bio-Robot i=1,m . A learner -a ...
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Citations
... The control subsystem is working as on-line diagnostic systems of complex mechanisms with the cooperation of multi-agent's activities in recognizing human affect sensing. Being able both to provide an intelligent accident preventive robot-based support for people with moving disabilities and to include affect sensing in Human Computer Interaction (HCI, in providing e-health care for people with moving disabilities), Human-Robot Interaction (HRI, for assisting tele-healthcare patients remaining autonomous), and Computer Mediated Communication (CMC, in providing adaptive user-robot friendly collaboration), such system should depend upon the possibility of extracting emotions without interrupting the user during HCI, HRI, or CMC (Mandryk, Atkins 2007;Bielskis et al. 2007;Pentland 2004). Emotion is a mind-body phenomenon that is accessible at different levels of observation (social, psychological, cerebral and physiological). ...
The aims of this research are focused on the construction of intellectualized equipments for people with moving disabilities to help them in sustainable integration into environment. The problem is to reveal main components of diagnosis of disabled persons, as well as to develop decision making models which are integrated into the control mechanisms of the special equipments, that are assigned to the class of bio‐robots. This paper analyses the approach of the construction of such type of bio‐robots with possibilities to integrate different knowledge representation techniques for the development of the reinforcement framework with multiple cooperative agents for the recognition of the diagnosis of emotional situation of disabled persons. Large‐scale of multidimensional recognitions of emotional diagnosis of disabled persons often generate a large amount of multi‐dimensional data with complex recognition mechanisms, based on the integration of different knowledge representation techniques and complex inference models. Sensors can easily record primary data; however, the recognition of abnormal situations, cauterisation of emotional stages and resolution for certain type of diagnosis is an oncoming issue for bio‐robot constructors. The research results present the development of multi‐layered model of this framework with the integration of the evaluation of fuzzy neural control of speed of two wheelchair type robots working in real time by providing moving support for disabled individuals. An approach for representation of reasoning processes, using fuzzy logical Petri nets for evaluation of physiological state of individuals is presented. The reasoning is based on recognition of emotions of persons during their activities.
Santrauka
Šio mokslinio tyrimo tikslai yra nukreipti į intektualizuotų įrenginių, skirtų žmonėms su judėjimo
negalia ir užtikrinančių jų būklės stebėseną ir darnaus judėjimo valdymo aplinkoje galimybes, kūrimą. Sprendžiami uždaviniai skirti neįgaliųjų diagnozės pagrindinių komponenčių tyrimams, sudarant lanksčius sprendimų priėmimo modelius, integruojamus į specialių įrenginių valdymo mechanizmus, kurie priskiriami biorobotų klasei. Straipsnyje pateikiami metodai, kaip konstruoti tokio tipo biorobotų sistemas, leidžiant skirtingų žinių vaizdavimo priemones integruoti į sistemą, kad būtų sukurta daugelio agentų bendradarbiavimo aplinka, skirta neįgaliųjų emocinės būklės diagnuozei analizuoti. Neįgaliųjų diagnozės procesams formalizuoti reikia kelių metodų, kurie grindžiami skirtingais žinių vaizdavimo formalizmais, skirtingų matų parametrų atpažinimo algoritmais. Sensorinės sistemos fiksuoja pirminius stebėsenos duomenis, tačiau nenormalioms situacijos būklėms atpažinti reikia sudėtingų išvedimo metodų, taikant lanksčias neuroninių tinklų valdymo priemones. Tyrimo rezultatai pateikiami per daugelio lygmenų darbo infrastruktūrą, kuri integruoja miglota logika grindžiamų neuroninių tinklų valdymo būdus, taikant juos neįgaliojo vežimėlio valdymo konstrukcijoms, kurios leidžia valdyti vežimėlio judėjimą automatiškai valdoma trajektorija. Miglota logika grindžiamų Petri tinklų taikymas leido pademonstruoti galimybes atpažinti neįgaliojo psichologinės būsenos pokyčius ir vertinti juos laike stebint pacientus skirtingą laiką.
First published online: 21 Oct 2010
Reikšminiai žodžiai: daugiaagentis sistemos valdymas, biorobotai, išskirstytosios informacinės sistemos, žinių vaizdavimo priemonės, miglota logika, neuroniniai tinklai, Petri tinklai.
... index.php? int_pageId=37, and [5]). In the proposed model of Fig. 1, two adaptive moving wheelchair-type robots are remotely communicating with two wearable human's affect sensing bio-robots. ...
An approach is proposed in creating of an intelligent e-health care environment by modelling of an adaptive multi-agent-based e-health and e-social care system for people with movement disabilities. Human's Arousal Recognition Module (HARM) described based on online recognition of human's ECG, EDA and body temperature signals by using embedded Atmega32 type microcontrollers. Multi-agent based online motion control of multiple wheelchair-type robots is realized based on integration of an adaptive Fuzzy Neural Network Control algorithm into ATmega32 microcontroller. Human Computer Interaction in the system is realized in providing of necessary e-health care support actions for users with some movement disabilities by using Java-based JACK agent oriented environment. The dynamic multi-agent system is proposed to permanently realizing e-social care support actions for disabled by gathering data such as current position of robot and user's state information; finding decisions for given situation; sending signals to performing appropriate actions of the objects in the system. Ill. 6, bibl. 5 (in English; summaries in English, Russian and Lithuanian).
This paper presents an original strategy of teaching IT curricula subjects seeking a goal of making Artificial Intelligence (AI) friendlier for the students. The strategy is based on applying learning by doing principle by in-tegration of permanent remote experimentation capabilities into adaptive e-tu-toring system. The ways of realizing of remote e-laboratory experiments are discussed based on introduction of an ambient intelligence perception within an e-laboratory. Methods of implementation of an embedded agent-based re-mote multiple object control within an e-laboratory are analyzed and some practical realization aspects are described in this paper.
Considerable achievements in computing and telecommunication area make possible in a new way solve a wide spectrum of transportation problems, affected in the concept of intelligent transportation systems (ITS). In a technical aspect such sort systems represent a set of interacting computational nodes, equipped with various sensors, and can be treated as distributed computer systems. The distributed structure of ITS supposes parallelization of solvable transportation tasks and their distributed realization. The concept of efficiency of parallelized calculations presupposes a few aspects. Three such aspects are picked out in the work: calculation speed, efficiency of system scaling, and efficiency of parallel computations as compared to sequential ones. Proper metrics for each group are offered, allowing numerical characterization of certain aspect of parallelized computations. As such metrics the index of parallelism and speedup (PI and S), efficiency and utilization (E and U), redundancy and compression (R and C) are examined. The peculiarity of intelligent transportation systems is in, that a large volume of communications is typical for them, substantially telling on the indexes of the system. Influence of communication overheads on the total efficiency of the system is analysed in the work. The question of private indexes integration into a single integral index, characterizing the quality of ITS realization, is examined. Applicability of the suggested metrics and their evidence is illustrated by examples.
This paper presents further development of intelligent multi-agent based e-health care system for people with movement disabilities.
The research results present further development of multi-layered model of this system with integration of fuzzy neural control
of speed of two wheelchair type robots working in real time by providing movement support for disabled individuals. An approach
of filtering of skin conductance (SC) signals using Nadaraya-Watson kernel regression smoothing for emotion recognition of
disabled individuals is described and implemented in the system by R software tool. The unsupervised clustering by self organizing
maps (SOM) of data sample of physiological parameters extracted from SC signals was proposed in order to reduce teacher noise
as well as to increase of speed and accuracy of learning process of multi-layer perceptron (MLP) training.