924 resultados para distributed amorphous human intelligence genesis robust communication network
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The control of the right application of medical protocols is a key issue in hospital environments. For the automated monitoring of medical protocols, we need a domain-independent language for their representation and a fully, or semi, autonomous system that understands the protocols and supervises their application. In this paper we describe a specification language and a multi-agent system architecture for monitoring medical protocols. We model medical services in hospital environments as specialized domain agents and interpret a medical protocol as a negotiation process between agents. A medical service can be involved in multiple medical protocols, and so specialized domain agents are independent of negotiation processes and autonomous system agents perform monitoring tasks. We present the detailed architecture of the system agents and of an important domain agent, the database broker agent, that is responsible of obtaining relevant information about the clinical history of patients. We also describe how we tackle the problems of privacy, integrity and authentication during the process of exchanging information between agents.
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Graph theory has provided a key mathematical framework to analyse the architecture of human brain networks. This architecture embodies an inherently complex relationship between connection topology, the spatial arrangement of network elements, and the resulting network cost and functional performance. An exploration of these interacting factors and driving forces may reveal salient network features that are critically important for shaping and constraining the brain's topological organization and its evolvability. Several studies have pointed to an economic balance between network cost and network efficiency with networks organized in an 'economical' small-world favouring high communication efficiency at a low wiring cost. In this study, we define and explore a network morphospace in order to characterize different aspects of communication efficiency in human brain networks. Using a multi-objective evolutionary approach that approximates a Pareto-optimal set within the morphospace, we investigate the capacity of anatomical brain networks to evolve towards topologies that exhibit optimal information processing features while preserving network cost. This approach allows us to investigate network topologies that emerge under specific selection pressures, thus providing some insight into the selectional forces that may have shaped the network architecture of existing human brains.
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Activity decreases, or deactivations, of midline and parietal cortical brain regions are routinely observed in human functional neuroimaging studies that compare periods of task-based cognitive performance with passive states, such as rest. It is now widely held that such task-induced deactivations index a highly organized"default-mode network" (DMN): a large-scale brain system whose discovery has had broad implications in the study of human brain function and behavior. In this work, we show that common task-induced deactivations from rest also occur outside of the DMN as a function of increased task demand. Fifty healthy adult subjects performed two distinct functional magnetic resonance imaging tasks that were designed to reliably map deactivations from a resting baseline. As primary findings, increases in task demand consistently modulated the regional anatomy of DMN deactivation. At high levels of task demand, robust deactivation was observed in non-DMN regions, most notably, the posterior insular cortex. Deactivation of this region was directly implicated in a performance-based analysis of experienced task difficulty. Together, these findings suggest that task-induced deactivations from rest are not limited to the DMN and extend to brain regions typically associated with integrative sensory and interoceptive processes.
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Tutkimuksen päätavoitteena on ollut selvittää miten kansallinen ja organisaatiokulttuuri, niihin liittyvät normit ja arvot edesauttavat tai vaikeuttavat luottamuksen kehittymistä monikulttuurisissa tiimeissä maailmanlaajuisessa organisaatiossa. Tutkimuksen avulla haluttiin myös selvittää miten luottamus kehittyy hajautetuissa monikansallisissa tiimeissä WorldCom Internationalissa. Empiirinen tutkimusmenetelmä perustuu kvalitatiivisiin teemahaastatteluihin, jotka tehtiin WorldComin työntekijöille. Tutkimuksessa havaittiin, ettei yhteisten sosiaalisten normien merkitys luottamuksen syntymiselle ole niin merkittävä, koska WorldComin yhtenäiset toimintatavat sekä hallitseva amerikkalaisen emoyhtiön "kotikulttuuri" muodostavat yhtenäiset toimintalinjat tiimeissä. Tietokonevälitteisen kommunikoinnin jatkuva käyttö on edesauttanut työntekijöiden ns. sosiaalisen älyn kehittymistä, sillä henkilökohtaisen tapaamisen puuttuminen kehittää vastaavasti taitoja aistia ja tulkita sähköpostien tai puhelinneuvotteluiden aikana välittyviä vastapuolen "näkymättömiä" vihjeitä.
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Increasingly detailed data on the network topology of neural circuits create a need for theoretical principles that explain how these networks shape neural communication. Here we use a model of cascade spreading to reveal architectural features of human brain networks that facilitate spreading. Using an anatomical brain network derived from high-resolution diffusion spectrum imaging (DSI), we investigate scenarios where perturbations initiated at seed nodes result in global cascades that interact either cooperatively or competitively. We find that hub regions and a backbone of pathways facilitate early spreading, while the shortest path structure of the connectome enables cooperative effects, accelerating the spread of cascades. Finally, competing cascades become integrated by converging on polysensory associative areas. These findings show that the organizational principles of brain networks shape global communication and facilitate integrative function.
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Peer-reviewed
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Simulation has traditionally been used for analyzing the behavior of complex real world problems. Even though only some features of the problems are considered, simulation time tends to become quite high even for common simulation problems. Parallel and distributed simulation is a viable technique for accelerating the simulations. The success of parallel simulation depends heavily on the combination of the simulation application, algorithm and message population in the simulation is sufficient, no additional delay is caused by this environment. In this thesis a conservative, parallel simulation algorithm is applied to the simulation of a cellular network application in a distributed workstation environment. This thesis presents a distributed simulation environment, Diworse, which is based on the use of networked workstations. The distributed environment is considered especially hard for conservative simulation algorithms due to the high cost of communication. In this thesis, however, the distributed environment is shown to be a viable alternative if the amount of communication is kept reasonable. Novel ideas of multiple message simulation and channel reduction enable efficient use of this environment for the simulation of a cellular network application. The distribution of the simulation is based on a modification of the well known Chandy-Misra deadlock avoidance algorithm with null messages. The basic Chandy Misra algorithm is modified by using the null message cancellation and multiple message simulation techniques. The modifications reduce the amount of null messages and the time required for their execution, thus reducing the simulation time required. The null message cancellation technique reduces the processing time of null messages as the arriving null message cancels other non processed null messages. The multiple message simulation forms groups of messages as it simulates several messages before it releases the new created messages. If the message population in the simulation is suffiecient, no additional delay is caused by this operation A new technique for considering the simulation application is also presented. The performance is improved by establishing a neighborhood for the simulation elements. The neighborhood concept is based on a channel reduction technique, where the properties of the application exclusively determine which connections are necessary when a certain accuracy for simulation results is required. Distributed simulation is also analyzed in order to find out the effect of the different elements in the implemented simulation environment. This analysis is performed by using critical path analysis. Critical path analysis allows determination of a lower bound for the simulation time. In this thesis critical times are computed for sequential and parallel traces. The analysis based on sequential traces reveals the parallel properties of the application whereas the analysis based on parallel traces reveals the properties of the environment and the distribution.
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An LC-MS/MS method has been developed for the determination of efavirenz (EFZ) in human plasma using hydrochlorothiazide as internal standard (I.S.). An ESI negative mode with multiple reaction-monitoring was used monitoring the transitions m/z 313.88→69.24 (EFZ) and 296.02→204.76 (I.S.). Samples were extracted using liquid-liquid extraction. The total run time was 2.0 min. The separation was achieved with HPLC-RP using a monolithic column. The assay was linear in the concentration range of 100 - 5000 ng mL-1. The mean recovery was 83%. Intra- and inter-day precision were < 9.5% and < 8.9%, respectively and accuracy was in the range ± 8.33%. The method was successfully applied to a bioequivalence study.
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Growing recognition of the electricity grid modernization to enable new electricity generation and consumption schemes has found articulation in the vision of the Smart Grid platform. The essence of this vision is an autonomous network with two-way electricity power flows and extensive real-time information between the generation nodes, various electricity-dependent appliances and all points in-between. Three major components of the Smart Grids are distributed intelligence, communication technologies, and automated control systems. The aim of this thesis is to recognize the challenges that Smart Grids are facing, while extinguishing the main driving factors for their introduction. The scope of the thesis also covers possible place of electricity Aggregator Company in the current and future electricity markets. Basic functions of an aggregator and possible revenue sources along with demand response feasibility calculations are reviewed within this thesis.
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Operating in business-to-business markets requires an in-depth understanding on business networks. Actions and reactions made to compete in markets are fundamentally based on managers‘ subjective perceptions of the network. However, an amalgamation of these individual perceptions, termed a network picture, to a common company level shared understanding on that network, known as network insight, is found to be a substantial challenge for companies. A company‘s capability to enhance common network insight is even argued to lead competitive advantage. Especially companies with value creating logics that require wide comprehension of and collaborating in networks, such as solution business, are necessitated to develop advanced network insight. According to the extant literature, dispersed pieces of atomized network pictures can be unified to a common network insight through a process of amalgamation that comprises barriers/drivers of multilateral exchange, manifold rationality, and recursive time. However, the extant body of literature appears to lack an understanding on the role of internal communication in the development of network insight. Nonetheless, the extant understanding on the amalgamation process indicates that internal communication plays a substantial role in the development of company level network insight. The purpose of the present thesis is to enhance understanding on internal communication in the amalgamation of network pictures to develop network insight in the solution business setting, which was chosen to represent business-to-business value creating logic that emphasizes the capability to understand and utilize networks. Thus, in solution business the role of succeeding in the amalgamation process is expected to emphasize. The study combines qualitative and quantitative research by means of various analytical methods including multiple case analysis, simulation, and social network analysis. Approaching the nascent research topic with differing perspectives and means provides a broader insight on the phenomenon. The study provides empirical evidence from Finnish business-to-business companies which operate globally. The empirical data comprise interviews (n=28) with managers of three case companies. In addition the data includes a questionnaire (n=23) collected mainly for the purpose of social network analysis. In addition, the thesis includes a simulation study more specifically achieved by means of agent based modeling. The findings of the thesis shed light on the role of internal communication in the amalgamation process, contributing to the emergent discussion of network insights and thus to the industrial marketing research. In addition, the thesis increases understanding on internal communication in the change process to solution business, a supplier‘s internal communication in its matrix organization structure during a project sales process, key barriers and drivers that influence internal communication in project sales networks, perceived power within industrial project sales, and the revisioning of network pictures. According to the findings, internal communication is found to play a substantial role in the amalgamation process. First, it is suggested that internal communication is a base of multilateral exchange. Second, it is suggested that internal communication intensifies and maintains manifold rationality. Third, internal communication is needed to explicate the usually differing time perspectives of others and thus it is suggested that internal communication has role as the explicator of recursive time. Furthermore, the role of an efficient amalgamation process is found to be emphasized in solutions business as it requires a more advanced network insight for cross-functional collaboration. Finally, the thesis offers several managerial implications for industrial suppliers to enhance the amalgamation process when operating in solution business.
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Production and generation of electrical power is evolving to more environmental friendly technologies and schemes. Pushed by the increasing cost of fossil fuels, the operational costs of producing electrical power with fossil fuels and the effect in the environment, like pollution and global warming, renewable energy sources gain con-stant impulse into the global energy economy. In consequence, the introduction of distributed energy sources has brought a new complexity to the electrical networks. In the new concept of smart grids and decen-tralized power generation; control, protection and measurement are also distributed and requiring, among other things, a new scheme of communication to operate with each other in balance and improve performance. In this research, an analysis of different communication technologies (power line communication, Ethernet over unshielded twisted pair (UTP), optic fiber, Wi-Fi, Wi-MAX, and Long Term Evolution) and their respective characteristics will be carried out. With the objective of pointing out strengths and weaknesses from different points of view (technical, economical, deployment, etc.) to establish a richer context on which a decision for communication approach can be done depending on the specific application scenario of a new smart grid deployment. As a result, a description of possible optimal deployment solutions for communication will be shown considering different options for technologies, and a mention of different important considerations to be taken into account will be made for some of the possible network implementation scenarios.
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The importance of after-sales service or service in general can be seen and experienced by customers every day with industrial as well as other non-industrial services or products. This dissertation, drawing on theory and experience, focuses on practical engineering implications, specifically the management of customer issues in the after-sales phase in the mobile phone arena. The main objective of this doctoral dissertation is to investigate customer after-sales issue management, specifically regarding mobile phones. The case studies focus on issue resolution time and the issue of corrective actions. This dissertation consists of a main body and four peer-reviewed journal articles and one manuscript currently under review by a peer-reviewed journal. The main body of this dissertation examines the elements of customer satisfaction, loyalty, and retention with respect to corrective actions to address customer issues and issue resolution time through literature and empirical studies. The five independent works are case studies supporting the thesis research questions. This study examines four questions: 1) What are the factors affecting corrective actions for customers? 2) How can customer issue resolution time be controlled? 3) What are the factors affecting processes in the service chain? and 4) How can communication be measured in a service chain? In this work, both quantitative and qualitative analysis methods are used. The main body of the thesis reviews the literature regarding the elements that bridge the five case studies. The case studies of the articles and surveys lean more toward the methodology of critical positivism and then apply the interpretive approach in interpreting the results. The case study articles employ various statistical methods to analyze and to interpret the empirical and survey data. The statistical methods were used to create a model that is useful for significantly optimizing issue resolution time. Moreover, it was found that samples for verifying issues provided by the customer neither improve the perceived quality of corrective actions nor the perceived quality of issue resolution time. The term “service” in this work is limited to the technical services that are provided by product manufacturers and after-sales authorized service vendors. On the basis of this research work, it has been observed that corrective actions and issue resolution time are associated with customer satisfaction and hence, according to induction theory, to customer loyalty and retention. This thesis utilizes knowledge of marketing and customer relationships to contribute to the existing body of knowledge concerning information and communication technology for after-sales service recovery of mobile terminals. The established models in the thesis contribute to the existing knowledge of the after-sales process of dealing with customer issues in the field of mobile phones. The findings suggest that process managers could focus more on communication and training provided to the staff as new technology evolves rapidly. The study also suggest the managers formulate strategies for how customers can be kept informed on a regular basis of the status of issues that have been escalated for corrective action. The findings also lay the foundation for the comprehensive objective to control the entire product development process, starting with conceptualization. This implies that robust design should be applied to the new products so that problems affecting customer service quality are not repeated. The objective will be achieved when the entire service chain from product development to the final user can be modeled and this model can be used to support the organization at all levels.
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Human activity recognition in everyday environments is a critical, but challenging task in Ambient Intelligence applications to achieve proper Ambient Assisted Living, and key challenges still remain to be dealt with to realize robust methods. One of the major limitations of the Ambient Intelligence systems today is the lack of semantic models of those activities on the environment, so that the system can recognize the speci c activity being performed by the user(s) and act accordingly. In this context, this thesis addresses the general problem of knowledge representation in Smart Spaces. The main objective is to develop knowledge-based models, equipped with semantics to learn, infer and monitor human behaviours in Smart Spaces. Moreover, it is easy to recognize that some aspects of this problem have a high degree of uncertainty, and therefore, the developed models must be equipped with mechanisms to manage this type of information. A fuzzy ontology and a semantic hybrid system are presented to allow modelling and recognition of a set of complex real-life scenarios where vagueness and uncertainty are inherent to the human nature of the users that perform it. The handling of uncertain, incomplete and vague data (i.e., missing sensor readings and activity execution variations, since human behaviour is non-deterministic) is approached for the rst time through a fuzzy ontology validated on real-time settings within a hybrid data-driven and knowledgebased architecture. The semantics of activities, sub-activities and real-time object interaction are taken into consideration. The proposed framework consists of two main modules: the low-level sub-activity recognizer and the high-level activity recognizer. The rst module detects sub-activities (i.e., actions or basic activities) that take input data directly from a depth sensor (Kinect). The main contribution of this thesis tackles the second component of the hybrid system, which lays on top of the previous one, in a superior level of abstraction, and acquires the input data from the rst module's output, and executes ontological inference to provide users, activities and their in uence in the environment, with semantics. This component is thus knowledge-based, and a fuzzy ontology was designed to model the high-level activities. Since activity recognition requires context-awareness and the ability to discriminate among activities in di erent environments, the semantic framework allows for modelling common-sense knowledge in the form of a rule-based system that supports expressions close to natural language in the form of fuzzy linguistic labels. The framework advantages have been evaluated with a challenging and new public dataset, CAD-120, achieving an accuracy of 90.1% and 91.1% respectively for low and high-level activities. This entails an improvement over both, entirely data-driven approaches, and merely ontology-based approaches. As an added value, for the system to be su ciently simple and exible to be managed by non-expert users, and thus, facilitate the transfer of research to industry, a development framework composed by a programming toolbox, a hybrid crisp and fuzzy architecture, and graphical models to represent and con gure human behaviour in Smart Spaces, were developed in order to provide the framework with more usability in the nal application. As a result, human behaviour recognition can help assisting people with special needs such as in healthcare, independent elderly living, in remote rehabilitation monitoring, industrial process guideline control, and many other cases. This thesis shows use cases in these areas.
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Bone homeostasis seems to be controlled by delicate and subtle “cross talk” between the nervous system and “osteo-neuromediators” that control bone remodeling. The purpose of this study was to evaluate the effect of interactions between neuropeptides and human bone morphogenetic protein 2 (hBMP2) on human osteoblasts. We also investigated the effects of neuropeptides and hBMP2 on gap junction intercellular communication (GJIC). Osteoblasts were treated with neuropeptide Y (NPY), substance P (SP), or hBMP2 at three concentrations. At various intervals after treatment, cell viability was measured by the MTT assay. In addition, cellular alkaline phosphatase (ALP) activity and osteocalcin were determined by colorimetric assay and radioimmunoassay, respectively. The effects of NPY, SP and hBMP on GJIC were determined by laser scanning confocal microscopy. The viability of cells treated with neuropeptides and hBMP2 increased significantly in a time-dependent manner, but was inversely associated with the concentration of the treatments. ALP activity and osteocalcin were both reduced in osteoblasts exposed to the combination of neuropeptides and hBMP2. The GJIC of osteoblasts was significantly increased by the neuropeptides and hBMP2. These results suggest that osteoblast activity is increased by neuropeptides and hBMP2 through increased GJIC. Identification of the GJIC-mediated signal transduction capable of modulating the cellular activities of bone cells represents a novel approach to studying the biology of skeletal innervation.
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Persons with intellectual disabilities (ID) are far more likely to be abused than the general population, but there is little research on teaching people with ID about their rights. The goal of this study was to teach four participants with ID and limited communication abilities about their human rights by training them on specific rights topics. The training program included icebreaker activities, instruction on rights concepts, watching and answering questions about videotaped scenarios of rights restrictions, watching and answering questions about role pl ay scenarios of rights restrictions, and responding to brief, low risk in situ rights restrictions imposed by the researchers. Participant performance did not improve significantly or consistently from baseline to training on the questions asked about the videotaped or the role play scenarios, but two of three participants demonstrated defmite improvements in responding to in situ rights restrictions.