Fast access to clinical data is necessary when performing real-time predictions of medical events. A clinical data repository (CDR) therefore requires an efficient format for storing data so it can meet the access dem...
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Human interaction is highly intuitive: we infer reactions of our opponents mainly from what we have learned in years of experience and often assume that other people have the same knowledge about certain situations, a...
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Human interaction is highly intuitive: we infer reactions of our opponents mainly from what we have learned in years of experience and often assume that other people have the same knowledge about certain situations, abilities, and expectations as we do. In human-robot interaction (HRI) we cannot take for granted that this is equally true since HRI is asymmetrical. In other words, robots have different abilities, knowledge, and expectations than humans. They need to react appropriately to human expectations and behaviour. With this respect, scientific advances have been made to date for applications in entertainment and service robotics that largely depend on intuitive interaction. However, HRI today is often still unnatural, slow, and unsatisfactory for the human interlocutor. Both the sensorimotor interaction with environment and interlocutor, and the social aspects of the interaction still need to be researched and improved. Therefore, this full-day workshop aims to bring together researchers from different scientific fields to discuss these crosscutting issues and to exchange views on what are the preconditions and principles of intuitive interaction.
Nowadays, almost all the enterprises in the world fall in Small Medium Enterprises (SMEs) category even though SMEs has different definitions in different countries. At the same time, there is no exemplar standard and...
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Nowadays, almost all the enterprises in the world fall in Small Medium Enterprises (SMEs) category even though SMEs has different definitions in different countries. At the same time, there is no exemplar standard and /or framework for information technology (IT) governance for SMEs. This paper presents the main issues in implementing IT governance in SMEs. Firstly, it explains the definition of SMEs and their characteristics, secondly it discusses IT governance definition and its framework. Finally, some issues and approaches for ITG implementation in SMEs are described, and end with conclusion and future work.
Communities in social networks emerge from interactions among individuals and can be analyzed through a combination of clustering and graph layout algorithms. These approaches result in 2D or 3D visualizations of clus...
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Communities in social networks emerge from interactions among individuals and can be analyzed through a combination of clustering and graph layout algorithms. These approaches result in 2D or 3D visualizations of clustered graphs, with groups of vertices representing individuals that form a community. However, in many instances the vertices have attributes that divide individuals into distinct categories such as gender, profession, geographic location, and similar. It is often important to investigate what categories of individuals comprise each community and vice-versa, how the community structures associate the individuals from the same category. Currently, there are no effective methods for analyzing both the community structure and the category-based partitions of social graphs. We propose Group-In-a-Box (GIB), a meta-layout for clustered graphs that enables multi-faceted analysis of networks. It uses the tree map space filling technique to display each graph cluster or category group within its own box, sized according to the number of vertices therein. GIB optimizes visualization of the network sub-graphs, providing a semantic substrate for category-based and cluster-based partitions of social graphs. We illustrate the application of GIB to multi-faceted analysis of real social networks and discuss desirable properties of GIB using synthetic datasets.
Current neonatal illness scoring systems are not designed to predict outcomes for individual patients, but rather can provide an overview of a population of patients for objective comparison when reporting outcomes. H...
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Current neonatal illness scoring systems are not designed to predict outcomes for individual patients, but rather can provide an overview of a population of patients for objective comparison when reporting outcomes. Having more patient-specific predictions may help physicians make better treatment decisions in a Neonatal Intensive Care Unit (NICU) environment. We developed neonatal mortality prediction models using C5.0 decision tree software that met criteria for clinically useful results (>;50-60% sensitivity, >;90% specificity) for individual patients using data from real-time medical measurement devices. The models were evaluated to identify: (1) the model with the best performance based on minimizing false positives, and (2) the attributes used most often in the best clinically useful models. Performance results showed that the mortality model using summary data during the first 48 hours after NICU admission provided, on average, the highest sensitivity and specificity with the least number of false positives (sensitivity=63%, specificity=94%, positive predictive value=38%), exceeding the performance criteria requested by our clinical partners. The attributes used most often in the best models for predicting mortality with our data were: mean blood pressure, serum pH, immature/total neutrophil ratio, serum sodium, serum glucose, respiratory rate, heart rate, and pO 2 blood oxygen level.
This paper deals with the approximate string-matching problem with Hamming distance and a single gap for sequence alignment. We consider an extension of the approximate string-matching problem with Hamming distance, b...
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Scheduling in traditional distributed systems has been mainly studied for system performance parameters without data transmission requirements. With the emergence of Data Grids (DGs) and Data Centers, data-aware sched...
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Scheduling in traditional distributed systems has been mainly studied for system performance parameters without data transmission requirements. With the emergence of Data Grids (DGs) and Data Centers, data-aware scheduling has become a major research issue. DGs arise quite naturally to support needs of scientific communities to share, access, process, and manage large data collections geographically distributed. In fact, DGs can be seen as precursors of Data Centers of Cloud Computing platforms, which serve as basis for collaboration at large scale. In such computational infrastructures, the large amount of data to be efficiently processed is a real challenge. One of the key issues contributing to the efficiency of massive processing is the scheduling with data transmission requirements. Data-aware scheduling, although similar in nature with Grid scheduling, is giving rise to the definition of a new family of optimization problems. New requirements such as data transmission, decoupling of data from processing, data replication, data access and security are the basis for the definition of a whole taxonomy of data scheduling problems from an optimization perspective. In this work we present the modelling of such requirements and define data scheduling problems. We exemplify the methodology for the case of data-ware independent batch task scheduling and present several heuristic resolution methods for the problem.
Quality assurance center in Mansoura University has been developing new strategic plans and activities. These plans and activities need to be automated as a part of the whole automation objectives of quality assurance...
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ISBN:
(纸本)9789774033964
Quality assurance center in Mansoura University has been developing new strategic plans and activities. These plans and activities need to be automated as a part of the whole automation objectives of quality assurance. Process management is the most suitable approach to automate the quality assurance procedures. The system integrates with the University data management systems using a set of web services. In this paper we introduce a service oriented process management system to manage the quality assurance procedures in University. We've modeled the quality assurance procedures from a process management perspective. Then introduced the service oriented architecture and services composition of the system. The system provides a suitable tool for executing, monitoring, and enhancing the quality assurance procedures.
The MADNESS project aims at the definition of innovative system-level design methodologies for embedded MP-SoCs, extending the classic concept of design space exploration in multi-application domains to cope with high...
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The MADNESS project aims at the definition of innovative system-level design methodologies for embedded MP-SoCs, extending the classic concept of design space exploration in multi-application domains to cope with high heterogeneity, technology scaling and system reliability. The main goal of the project is to provide a framework able to guide designers and researchers to the optimal composition of embedded MPSoC architectures, according to the requirements and the features of a given target application field. The proposed approach will tackle the new challenges, related to both architecture and design methodologies, arising with the technology scaling, the system reliability and the ever-growing computational needs of modern applications. The methodologies proposed with this project act at different levels of the design flow, enhancing the state-of-the art with novel features in system-level synthesis, architectural evaluation and prototyping. Support for fault resilience and efficient adaptive runtime management is introduced at hardware and middleware level, and considered by the system-level synthesis as one of the optimization factors to be taken into account. This paper presents the first stable results obtained in the MADNESS project, already demonstrating the effectiveness of the proposed methods.
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