다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

Data Mining Practical Machine Learning Tools and Techniques

物件導向軟體之架構(Object-Oriented Software Construction)探討

http://homepage.cs.latrobe.edu.au/sloke/papers/1-s2.0-S0167739X12001318-main.pdf

Mobile cloud computing

Differential Evolution (DE) is arguably one of the most powerful and versatile evolutionary optimizers for the continuous parameter spaces in recent times. Almost 5 years have passed since the first comprehensive survey article was published on DE by Das and Suganthan in 2011. Several developments have been reported on various aspects of the algorithm in these 5 years and the research on and with DE have now reached an impressive state. Considering the huge progress of research with DE and its applications in diverse domains of science and technology, we find that it is a high time to provide a critical review of the latest literatures published and also to point out some important future avenues of research. The purpose of this paper is to summarize and organize the information on these current developments on DE. Beginning with a comprehensive foundation of the basic DE family of algorithms, we proceed through the recent proposals on parameter adaptation of DE, DE-based single-objective global optimizers, DE adopted for various optimization scenarios including constrained, large-scale, multi-objective, multi-modal and dynamic optimization, hybridization of DE with other optimizers, and also the multi-faceted literature on applications of DE. The paper also presents a dozen of interesting open problems and future research issues on DE.

Recent advances in differential evolution – An updated survey

Pervasive and Smart Technologies for Healthcare: Ubiquitous Methodologies and Tools provides insight from members of prestigious universities and research institutes around the world into possible solutions for the aforementioned pressures within today's healthcare systems. Pervasive healthcare technologies are creating a new market for higher quality and less expensive healthcare applications, making this book ideal for ICT community members willing to design and develop advanced pervasive healthcare applications, and healthcare practitioners wanting to reorganize business processes within a healthcare system so that patients are diagnosed and treated more quickly and effectively.

Pervasive and Smart Technologies for Healthcare: Ubiquitous Methodologies and Tools

http://www.inf.ufsc.br/%7Efrank/INE6514/Artigos2012/MiPeG%20-%20A%20middleware%20infrastructure%20for%20pervasive%20grids.pdf

MiPeG: A middleware infrastructure for pervasive grids

This paper presents semantic models, mechanisms and a service to locate mobile entities in Smart and Intelligent Environments. The key feature of the service is the semantic integration of different positioning systems that not only enables the environment to handle transparently such physical positioning systems, but also to reason on location information coming from different systems and to combine it to obtain higher context information. Indeed, the service relies on the use of ontologies and rules to define a uniform, unambiguous and well-defined model for the location information, independently of the particular positioning system. Moreover, the location service performs logic and reasoning mechanisms to provide both physical and semantic locations of mobile objects and to infer the finest granularity in the case when a mobile object is located by more than one positioning system. Finally, we present an application of the proposed approach to the case of a Smart Hospital.

A multimodal semantic location service for intelligent environments: an application for Smart Hospitals

Falls represent one of the most common causes of injury-related morbidity and mortality in later life. Subjects with cardiovascular disorders (e.g., related to autonomic dysfunctions and postural hypotension) are at higher risk of falling. Autonomic dysfunctions increasing the risk of falling in the short and mid-term could be assessed by Heart Rate Variability (HRV) extracted by electrocardiograph (ECG). We developed three trials for assessing the usefulness of ECG monitoring using wearable devices for: risk assessment of falling in the next few weeks; prevention of imminent falls due to standing hypotension; and fall detection. Statistical and data-mining methods are adopted to develop classification and regression models, validated with the cross-validation approach. The first classifier based on HRV features enabled to identify future fallers among hypertensive patients with an accuracy of 72% (sensitivity: 51.1%, specificity: 80.2%). The regression model to predict falls due to orthostatic dropdown from HRV recorded before standing achieved an overall accuracy of 80% (sensitivity: 92%, specificity: 90%). Finally, the classifier to detect simulated falls using ECG achieved an accuracy of 77.3% (sensitivity: 81.8%, specificity: 72.7%). The evidence from these three studies showed that ECG monitoring and processing could achieve satisfactory performances compared to other system for risk assessment, fall prevention and detection. This is interesting as differently from other technologies actually employed to prevent falls, ECG is recommended for many other pathologies of later life and is more accepted by senior citizens.

Wearable technology and ECG processing for fall risk assessment, prevention and detection

This article presents a methodology to formally express requirements in safety-critical ubiquitous and pervasive applications in order to achieve a higher degree of dependability. In particular, it will be shown how it is possible to formalize and constrict mobility characteristics by combining and extending several formal methods. The article also discusses some issues concerning both static and dynamic verification.

Giuseppe De Pietro

Papers

Pervasive and Smart Technologies for Healthcare: Ubiquitous Methodologies and Tools

MiPeG: A middleware infrastructure for pervasive grids

A multimodal semantic location service for intelligent environments: an application for Smart Hospitals

Wearable technology and ECG processing for fall risk assessment, prevention and detection

Formal Specification and Verification of Ubiquitous and Pervasive Systems