Parallel disk systems consume a significant amount of energy due to the large number of disks. To design economically attractive and environmentally friendly parallel disk systems, in this paper we design and evaluate...
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Parallel disk systems consume a significant amount of energy due to the large number of disks. To design economically attractive and environmentally friendly parallel disk systems, in this paper we design and evaluate an energy-aware prefetching strategy for parallel disk systems consisting of a small number of buffer disks and large number of data disks. Using buffer disks to temporarily handle requests for data disks, we can keep data disks in the low-power mode as long as possible. Our prefetching algorithm aims to group many small idle periods in data disks to form large idle periods, which in turn allow data disks to remain in the standby state to save energy. To achieve this goal, we utilize buffer disks to aggressively fetch popular data from regular data disks into buffer disks, thereby putting data disks into the standby state for longer time intervals. A centrepiece in the prefetching mechanism is an energy-saving prediction model, based on which we implement the energy-saving calculation module that is invoked in the prefetching algorithm. We quantitatively compare our energy-aware prefetching mechanism against existing solutions, including the dynamic power management strategy. Experimental results confirm that the buffer-disk-based prefetching can significantly reduce energy consumption in parallel disk systems by up to 50 percent. In addition, we systematically investigate the energy efficiency impact that varying disk power parameters has on our prefetching algorithm.
The paper focuses on a novel system iFeel_IM! that integrates 3D virtual world Second Life, intelligent component for automatic emotion recognition from text messages, and innovative affective haptic interfaces provid...
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The paper focuses on a novel system iFeel_IM! that integrates 3D virtual world Second Life, intelligent component for automatic emotion recognition from text messages, and innovative affective haptic interfaces providing additional nonverbal communication channels through simulation of emotional feedback and social touch (physical co-presence). The motivation behind our work is to enrich social interaction and emotional involvement of online interpersonal communication. iFeel_IM! users can not only exchange messages but also emotionally and physically feel the presence of the communication partner (e.g., family member, friend, or beloved person).
This paper fits into the topic of eco-design education and explores questions related to the modern student's perspective on design education and how we should consider the curricula from a future perspective. Thi...
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This paper fits into the topic of eco-design education and explores questions related to the modern student's perspective on design education and how we should consider the curricula from a future perspective. This paper first confirms the state of the art by reviewing the literature on the socio-centric dimension of sustainable design. This will determine the component sections required of a learning and teaching resource which focuses on the implications of human expectations and aspirations for the development of solutions to sustainable design problems. The paper then presents an evaluation of the existing learning and teaching resources, including well regarded resources such as the 'Toolbox for Sustainable design', part of the larger Information Inspiration Ecodesign web based resource at ***. The paper also considers the outputs of groups such as the Product Life Spans Network, based at Sheffield Hallam University and the Sustainable design Network, based at Loughborough University. The paper concludes with some suggestions for a new learning and teaching resource which is specifically aimed at assisting with the socio-centric aspects of sustainable product design.
Data-mining algorithms are used in many applications to help extract meaningful data from very large datasets. For example, the NetFlix [12] Web site uses hundreds of thousands of past movie ratings stored in an Oracl...
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Recently there has been some spurt of interests to use photoelastic materials for sensing applications. This has been successfully applied for designing a number of signal-based sensors, however, there have been limit...
Recently there has been some spurt of interests to use photoelastic materials for sensing applications. This has been successfully applied for designing a number of signal-based sensors, however, there have been limited efforts to design image-based sensors on photoelasticity which can have wider applications in term of actual loading and visualisation. The main difficulty in achieving this is the infinite loading conditions that may generate same image on the material surface. This, however, can be useful for known loading situations as this can provide dynamic and actual conditions of loading in real time. This is particularly useful for separating components of forces in and out of the loading plane. One such application is the separation of normal and shear forces acting on the plantar surface of foot of diabetic patients for predicting ulceration. In our earlier work we have used neural networks to extract normal force information from the fringe patterns using image intensity. This paper considers geometric and various other statistical parameters in addition to the image intensity to extract normal as well as shear force information from the fringe pattern in a controlled experimental environment. The results of neural network output with the above parameters and their combinations are compared and discussed. The aim is to generalise the technique for a range of loading conditions that can be exploited for whole-field load visualisation and sensing applications in biomedical field.
Remote patient monitoring (RPM) of physiological measurements can provide an efficient method and high quality care to patients. The physiological signals measurement is the initial and the most important factor in RP...
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ISBN:
(纸本)9780889867215
Remote patient monitoring (RPM) of physiological measurements can provide an efficient method and high quality care to patients. The physiological signals measurement is the initial and the most important factor in RPM. This paper discusses the characteristics of the most popular sensors, which are used to obtain vital clinical signals in prevalent RPM systems. The sensors discussed in this paper are used to measure ECG, heart sound, pulse rate, oxygen saturation, blood pressure and respiration rate, which are treated as the most important vital data in patient monitoring and medical examination.
Until recently the guiding tenet in human-computer interaction was that any interface must be easy to learn and use. However, it has been increasingly recognized that the appeal of the interface to the user and their ...
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ISBN:
(纸本)9781605606859
Until recently the guiding tenet in human-computer interaction was that any interface must be easy to learn and use. However, it has been increasingly recognized that the appeal of the interface to the user and their enjoyment of it is also important. The aim of the current study was to examine the nature of the relationships between icon characteristics, user performance, and aesthetic appeal. When participants were asked to rate the appeal of a corpus of icons, it was found that the same icon characteristics predicted appeal as those predicting user performance. The theoretical and practical implications of the remarkable similarity in the factors determining appeal and usability are discussed.
Over the last decade there has been a shift in emphasis from interface usability to interface appeal. Very few studies, however, have examined the link between the two. The current study examined the possibility that ...
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ISBN:
(纸本)9781605606859
Over the last decade there has been a shift in emphasis from interface usability to interface appeal. Very few studies, however, have examined the link between the two. The current study examined the possibility that aesthetic appeal may affect user performance. In a visual search task designed to mimic user searches of interface displays, participants were asked to search for a target icon in an array of distractors. Target icons were varied orthogonally along two dimensions, complexity (which is known to affect visual search for icons in displays) and aesthetic appeal. The results showed that visually simple icons were found faster than visually complex icons, replicating previous findings. More importantly, aesthetic appeal interacted with icon complexity, significantly reducing search times for complex but not simple icons. These findings provide empirical evidence to support the idea that aesthetic appeal can influence performance.
In this paper we investigate potential benefits that an adaptive delayed channel access algorithm can attain for the next-generation wireless LANs, the IEEE 802.11n. We show that the performance of frame aggregation i...
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