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Search Results: 1 - 10 of 17430 matches for " Adaptive Systems "
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The complexity of prognosis communication in heart failure: Patient and cardiologists’ preferences in the outpatient clinical setting  [PDF]
Patricia H. Strachan, Heather M. Arthur, Catherine Demers, Robert J. Robson
World Journal of Cardiovascular Diseases (WJCD) , 2013, DOI: 10.4236/wjcd.2013.31A017

Background: The determination of prognosis in heart failure (HF) has focused primarily on the identification of potential biological and physiological markers and not on communication. High morbidity and mortality rates suggest that patients require prognostic information to assist in life planning. This study examined the preferences of both patients with HF and cardiologists for prognosis communication in the outpatient clinical setting, with the aim of guiding practitioners in undertaking prognosis conversations. Methods: Using qualitative descriptive techniques informed by a grounded theory approach, 32 patients with HF and 9 cardiologists from outpatient settings in Ontario, Canada were interviewed to identify convergent preferences for prognosis communication. Strategies to enhance methodological rigor were employed. Results: Individualized, context-specific prognosis communication between patients and cardiologists was preferred. Two main themes and ten related attributes were identified to describe convergent preferences; 1) Set the Stage for Prognosis Communication, and 2) Map the HF route. Attributes reflected the complex, dynamic, interactive and iterative nature of prognosis communication preferences. Conclusions: Prognosis communication occurs within a complex, adaptive healthcare system. While specific preferences exist, changing contextual elements within and outside of the system create conditions that require cardiologists to adjust their approach to individual patients. Patients with HF and cardiologists each have preferences that affect their willingness and ability to engage in dyadic HF-specific prognosis communication. Findings have relevance for the implementation of any efforts, including HF guidelines, aimed at improving prognosis communication. Our findings, informed by a complexity science approach, offer an innovative and robust alternative to traditional linear approaches to prognosis communication.

Bio-inspired Self-Adaptive Agents in Distributed Systems
Ichiro SATOH
ADCAIJ : Advances in Distributed Computing and Artificial Intelligence Journal , 2013,
Abstract: This paper proposes a bio-inspired middleware for selfadaptive software agents on distributed systems. It is unique to other existing approaches for software adaptation because it introduces the notions of differentiation, dedifferentiation, and cellular division in cellular slime molds, e.g., dictyostelium discoideum, into real distributed systems. When an agent delegates a function to another agent coordinating with it, if the former has the function, this function becomes lessdeveloped and the latter’s function becomes welldeveloped.
Optimizing nonlinear adaptive control allocation
Johannes Tj?nn?s,Tor A. Johansen
Modeling, Identification and Control , 2006, DOI: 10.4173/mic.2006.1.3
Abstract: A control-Lyapunov approach is used to develop an adaptive optimizing control allocation algorithm for over-actuated mechanical systems where the actuator model is affine in the uncertain parameters. Uniform global (asymptotic) stability is guaranteed by the control allocation defined by the dynamic update laws in combination with an exponentially stable controller.
Nonlinear Steam Valve Adaptive Controller Design for the Power Systems  [PDF]
Nan Jiang, Xiangyong Chen, Ting Liu, Bin Liu, Yuanwei Jing
Intelligent Control and Automation (ICA) , 2011, DOI: 10.4236/ica.2011.21004
Abstract: Considering generator rotor and valve by external disturbances for turbine regulating system, the nonlinear large disturbance attenuation controller and parameter updating law of turbine speed governor system are designed using backstepping method. The controller not only considers transmission line parameter uncer-tainty, and has attenuated the influences of large external disturbances on system output. The nonlinear con-troller does not have the sensitivity to the influences of external disturbances, but also has strong robustness for system parameters variation, which is because of the transmission line uncertainty being considered in internal disturbances. The simulation results show that the control effect of the large disturbance attenuation controller more advantages by comparing with the control performance of conventional nonlinear robust controller.
Adaptive Processing Gain Data Services in Cellular CDMA in Presence of Soft Handoff with Truncated ARQ  [PDF]
Dipta DAS, Sumit KUNDU
Int'l J. of Communications, Network and System Sciences (IJCNS) , 2009, DOI: 10.4236/ijcns.2009.22017
Abstract: An adaptive data transmission scheme based on variable spreading gain (VSG) is studied in cellular CDMA network in presence of soft handoff (HO). The processing gain is varied according to traffic intensity meet-ing a requirement on data bit error rate (BER). The overall performance improvement due to processing gain adaptation and soft HO is evaluated and compared with a fixed rate system. The influence of soft HO pa-rameters on rate adaptation and throughput and delay performance of data is indicated. Further truncated automatic repeat request (T-ARQ) is used in link layer to improve the performance of delay sensitive ser-vices. The joint impact of VSG based transmission in presence of soft handoff at physical layer and T-ARQ at link layer is evaluated. A variable packet size scheme is also studied to meet a constraint on packet loss.
Adaptive Tracking Control of an Uncertain Nonholonomic Robot  [PDF]
Nan Hu, Chaoli Wang
Intelligent Control and Automation (ICA) , 2011, DOI: 10.4236/ica.2011.24045
Abstract: In this paper, a new controller is proposed by using backstepping method for the trajectory tracking problem of nonholonomic dynamic mobile robots with nonholonomic constraints under the condition that there is a distance between the mass center and the geometrical center and the distance is unknown. And an adaptive feedback controller is also proposed for the case that some kinematic parameters and dynamic parameters are uncertain. The asymptotical stability of the control system is proved with Lyapunov stability theory. The simulation results show the effectiveness of the proposed controller. The comparison with the previous methods is made to show the effectiveness of the method in this article.
A New Adaptive Technique for Enhancement of Zone-2 Settings of Distance Relay  [PDF]
Avinash N. Sarwade, Pradeep K. Katti, Jayant G. Ghodekar
Energy and Power Engineering (EPE) , 2012, DOI: 10.4236/epe.2012.41001
Abstract: This paper presents a technique that increases the second-zone coverage of distance relays without causing overreach problems. The technique is based on the impedance seen by distance relays when faults are simulated on the reach of zone-1 relays. The approach checks the relay operation for the maximum as well as the minimum generation outputs of the power system. The proposed technique can be used for different reach setting for zone-1. Results show that it is possible to increase the coverage provided by zone-2 distance relays without causing coordination problems with the primary relays that protect the lines emanating from the remote bus. The proposed method is modified for use in an adaptive protection system. It is shown that further improvements can be achieved when settings are calculated using the proposed method and the prevailing system conditions. The proposed method and its adaptive version were applied to a part of the Power system. The simulation of the system is done by using PSCAD-EMTDC software. The simulated results are observed and compared with the conventional and proposed technique.
Lyapunov-Based Dynamic Neural Network for Adaptive Control of Complex Systems  [PDF]
Farouk Zouari, Kamel Ben Saad, Mohamed Benrejeb
Journal of Software Engineering and Applications (JSEA) , 2012, DOI: 10.4236/jsea.2012.54028
Abstract: In this paper, an adaptive neuro-control structure for complex dynamic system is proposed. A recurrent Neural Network is trained-off-line to learn the inverse dynamics of the system from the observation of the input-output data. The direct adaptive approach is performed after the training process is achieved. A lyapunov-Base training algorithm is proposed and used to adjust on-line the network weights so that the neural model output follows the desired one. The simulation results obtained verify the effectiveness of the proposed control method.
CAS-Based Approach for Automatic Data Integration  [PDF]
Eli Rohn
American Journal of Operations Research (AJOR) , 2013, DOI: 10.4236/ajor.2013.31A017

Research of automatic integration of structured and semi-structured data has not resulted in success over the past fifty years. No theory of data integration exists. It is unknown what the theoretical necessary requirements are, to fully support automatic data integration from autonomous heterogeneous data sources. Therefore, it is not possible to objectively evaluate if and how much new algorithms, techniques, and specifically Data Definition Languages, move towards meeting such theoretical requirements. To overcome the serious reverse salient the field and industry are in, it will be helpful if a data integration theory would be developed. This article proposes a new look at data integration by using complex adaptive systems principles to analyze current shortcomings and propose a direction that may lead to a data integration theory.

Moving towards Personalized Geospatial Queries  [PDF]
Giorgos Mountrakis, Anthony Stefanidis
Journal of Geographic Information System (JGIS) , 2011, DOI: 10.4236/jgis.2011.34031
Abstract: Geospatial datasets are typically available as distributed collections contributed by various government or commercial providers. Supporting the diverse needs of various users that may be accessing the same dataset for different applications remains a challenging issue. In order to overcome this challenge there is a clear need to develop the capabilities to take into account complicated patterns of preference describing user and/or application particularities, and use these patterns to rank query results in terms of suitability. This paper offers a demonstration on how intelligent systems can assist geospatial queries to improve retrieval accuracy by customizing results based on preference patterns. We outline the particularities of the geospatial domain and present our method and its application.
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