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991.
Acceptance, utility, and usability of system designs have become a focal interest in human–computer interaction (HCI) research, yet at present there is a lack detailed understandings of which system design features influence them. The purpose of the study is to examine the effects of five product design features; customization, adaptive behavior, memory load, content density, and speed on user preference through an experimental study by using conjoint analysis. In experimental study, instead of classical conjoint cards, prototypes were generated for products. Besides, desirability and market segments of product prototypes were identified. In line with the results, among the five product design features, speed is the most and customization is the least important features that affect user preference. Contrary to the expectations, customization has a relatively small importance value in this research. Subsequent design features that influence user preference after speed are minimal memory load, adaptive behavior, and content density, respectively. According to findings, interfaces that have high-speed, minimal memory load, adaptive behavior, low content density, and customization features are more preferable than those that do not. 相似文献
992.
Maria-Jose Escobar Guillaume S. Masson Thierry Vieville Pierre Kornprobst 《International Journal of Computer Vision》2009,82(3):284-301
We propose a bio-inspired feedforward spiking network modeling two brain areas dedicated to motion (V1 and MT), and we show
how the spiking output can be exploited in a computer vision application: action recognition. In order to analyze spike trains,
we consider two characteristics of the neural code: mean firing rate of each neuron and synchrony between neurons. Interestingly,
we show that they carry some relevant information for the action recognition application. We compare our results to Jhuang
et al. (Proceedings of the 11th international conference on computer vision, pp. 1–8, 2007) on the Weizmann database. As a conclusion, we are convinced that spiking networks represent a powerful alternative framework
for real vision applications that will benefit from recent advances in computational neuroscience. 相似文献
993.
The feasibility of general task systems with precedence constraints on multiprocessor platforms 总被引:1,自引:1,他引:0
Feasibility analysis determines (prior to system execution-time) whether a specified collection of hard-real-time jobs executed
on a processing platform can meet all deadlines. In this paper, we derive near-optimal sufficient tests for determining whether
a given collection of jobs can feasibly meet all deadlines upon a specified multiprocessor platform assuming job migration
is permitted. The collection of jobs may contain precedence constraints upon the order of execution of these jobs. The derived
tests are general enough to be applied even when the collection of jobs is incompletely specified. We discuss the applicability
of these tests to the scheduling of collections of jobs that are generated by systems of recurrent real-time tasks. We also
show that our feasibility conditions may be used to obtain global-EDF schedulability conditions.
相似文献
Sanjoy BaruahEmail: |
994.
This paper provides an analysis of the collaborative work conducted at a multidisciplinary medical team meeting, where a patient’s
definitive diagnosis is agreed, by consensus. The features that distinguish this process of diagnostic work by consensus are
examined in depth. The current use of technology to support this collaborative activity is described, and experienced deficiencies
are identified. Emphasis is placed on the visual and perceptual difficulty for individual specialities in making interpretations,
and on how, through collaboration in discussion, definitive diagnosis is actually achieved. The challenge for providing adequate
support for the multidisciplinary team at their meeting is outlined, given the multifaceted nature of the setting, i.e. patient
management, educational, organizational and social functions, that need to be satisfied.
相似文献
Saturnino LuzEmail: |
995.
Per Bjesse 《Formal Methods in System Design》2009,35(1):56-72
In this paper we present a word-level model checking method that attempts to speed up safety property checking of industrial
netlists. Our aim is to construct an algorithm that allows us to check both bounded and unbounded properties using standard
bit-level model checking methods as back-end decision procedures, while incurring minimum runtime penalties for designs that
are unsuited to our analysis. We do this by combining modifications of several previously known techniques into a static abstraction
algorithm which is guaranteed to produce bit-level netlists that are as small or smaller than the original bitblasted designs.
We evaluate our algorithm on several challenging hardware components. 相似文献
996.
This work proposes a method to decompose the kernel within-class eigenspace into two subspaces: a reliable subspace spanned
mainly by the facial variation and an unreliable subspace due to limited number of training samples. A weighting function
is proposed to circumvent undue scaling of eigenvectors corresponding to the unreliable small and zero eigenvalues. Eigenfeatures
are then extracted by the discriminant evaluation in the whole kernel space. These efforts facilitate a discriminative and
stable low-dimensional feature representation of the face image. Experimental results on FERET, ORL and GT databases show
that our approach consistently outperforms other kernel based face recognition methods.
相似文献
Alex KotEmail: |
997.
Despite the importance of knowledge transfer for firms involved in foreign direct investment activities, this area has not
received appropriate attention from the perspectives of both the knowledge transferor (i.e., MNC parent) and the knowledge
recipient. To fill in the gap in the current literature we propose a model to understand the links between criteria complicating
the transfer of knowledge and preferences that the company has to focus. This model is based on both the existing literature
as well as views of company representatives and provides a useful methodology for identifying decision making problems on
the transfer of knowledge. In this paper, we investigate the fuzzy linear programming technique (FLP) to analyze these links
and for multiple attribute group decision making (MAGDM) problems with preference information on criteria. To reflect the
decision maker’s subjective preference information and to determine the weight vector of attributes, the technique for order
preference by similarity to ideal solution (TOPSIS) developed by Hwang and Yoon (1995) and the linear programming technique
for multidimensional analysis of preference (LINMAP) developed by Sirinivasan and Shocker (Psychometrica 38:337–369, 1973)
are used. 相似文献
998.
Multi-criteria decision making for assembly line balancing 总被引:1,自引:0,他引:1
Assembly line balancing often has significant impact on performance of manufacturing systems, and is usually a multiple-objective
problem. Neither an algorithmic nor a procedural assembly line balancing methodology is usually effective in solving these
problems. This article proposes a data envelopment analysis (DEA) approach to solve an assembly line balancing problem. A
computer-aided assembly line balancing tool as Flexible Line Balancing software is used to generate a considerable number
of solutions alternatives as well as to generate quantitative decision-making unit outputs. The quantitative performance measures
were considered in this article. Then DEA was used to solve the multiple-objective assembly line balancing problem. An illustrative
example shows the effectiveness of the proposed methodology. 相似文献
999.
This study proposes a technique based upon Fuzzy C-Means (FCM) classification theory and related fuzzy theories for choosing an appropriate value of the Variable Precision Rough Set (VPRS) threshold parameter (β) when applied to the classification of continuous information systems. The VPRS model is then combined with a moving Average Autoregressive Exogenous (ARX) prediction model and Grey Systems theory to create an automatic stock market forecasting and portfolio selection mechanism. In the proposed mechanism, financial data are collected automatically every quarter and are input to an ARX prediction model to forecast the future trends of the collected data over the next quarter or half-year period. The forecast data are then reduced using a GM(1, N) model, classified using a FCM clustering algorithm, and then supplied to a VPRS classification module which selects appropriate investment stocks in accordance with a pre-determined set of decision-making rules. Finally, a grey relational analysis technique is employed to weight the selected stocks in such a way as to maximize the rate of return of the stock portfolio. The validity of the proposed approach is demonstrated using electronic stock data extracted from the financial database maintained by the Taiwan Economic Journal (TEJ). The portfolio results obtained using the proposed hybrid model are compared with those obtained using a Rough Set (RS) selection model. The effects of the number of attributes of the RS lower approximation set and VPRS β-lower approximation set on the classification are systematically examined and compared. Overall, the results show that the proposed stock forecasting and stock selection mechanism not only yields a greater number of selected stocks in the β-lower approximation set than in the RS approximation set, but also yields a greater rate of return. 相似文献
1000.
This paper reports a work that was intended to reveal the connection between topics investigated by conference papers and journal papers. This work selected hundreds of papers in data mining and information retrieval from well-known databases and showed that the topics covered by conference papers in a year often leads to similar topics covered by journal papers in the subsequent year and vice versa. This study used some existing algorithms and combination of these algorithms to proposed a new detective procedure for the researchers to detect the new trend and get the academic intelligence from conferences and journals.The goal of this research is fourfold: First, the research investigates if the conference papers’ themes lead the journal papers’. Second, the research examines how the new research themes can be identified from the conference papers. Third, the research looks at a specific area such as information retrieval and data mining as an illustration. Fourth, the research studies any inconsistencies of the correlation between the conference papers and the journal papers.This study explores the connections between the academic publications. The methodologies of information retrieval and data mining can be exploited to discover the relationships between published papers among all topics. By discovering the connections between conference papers and journal papers, researchers can improve the effectiveness of their research by identifying academic intelligence.This study discusses how conference papers and journal papers are related. The topics of conference papers are identified to determine whether they represent new trend discussed in journal papers. An automatic examination procedure based on information retrieval and data mining is also proposed to minimize the time and human resources required to predict further research developments. This study develops a new procedure and collects a dataset to verify those problems. Analytical results demonstrate that the conference papers submitted to journals papers are similar each year. Conference papers certainly affect the journal papers published over three years. About 87.23% of data points from papers published in 1991–2007 support our assumption. The research is intended to help researchers identify new trend in their research fields, and focus on the urgent topics. This is particularly valuable for new researchers in their field, or those who wish to perform cross-domain studies. 相似文献