35666646
A Linguistics-Based Approach for Use Case Driven Analysis Using Goal and Scenario Authoring
Although Use Case driven analysis has been widely used in requirements analysis, it does not facilitate effective requirements elicitation or provide rationale for the various artifacts that get generated. On the other hand, goal and scenario based approach is considered to be effective for elicitation but it does not lead to use cases. This paper discusses how to combine goal and scenario based requirements elicitation technique with use case driven analysis using natural language concepts. In our proposed approach, four levels of goals, scenario authoring rules, and linguistic techniques have been developed to identify use cases from text based goal and scenario descriptions. The artifacts resulting from our approach could be used as input to a use case diagramming tool to automate the process of use case diagram generation.
16878992
Improving use case driven analysis using goal and scenario authoring: A linguistics-based approach
Use case driven analysis does not facilitate effective requirements elicitation or provide rationale for the various artifacts that get generated during the requirements analysis phase. On the other hand, goal and scenario based approach is considered to be effective for elicitation but it does not lead to use cases. This paper discusses how to combine goal and scenario based requirements elicitation technique with use case driven analysis using natural language concepts. In our proposed approach, four levels of goals, scenario authoring rules, and linguistic techniques have been developed to identify use cases from text based goal and scenario descriptions. The artifacts resulting from our approach could be used as input to a use case diagramming tool to automate the process of use case diagram generation.
6065142
On effective data clustering in bitemporal databases
Temporal databases provide built-in supports for efficient recording and querying of time-evolving data. In this paper, data clustering issues in temporal database environment are addressed. Data clustering is one of the most effective techniques that can improve performance of a database system. However, data clustering methods for conventional databases do not perform well in temporal databases because there exist crucial differences between their query patterns. We propose a data clustering measure, called Temporal Affinity, that can be used for the clustering of temporal data. The temporal affinity, which is based on the analysis of query patterns in temporal databases, reflects the closeness of temporal data objects in viewpoints of temporal query processing. We perform experiments to evaluate the proposed measure. The experimental results show that a data clustering method with the temporal affinity works better than other methods.
9856169
CARA: Collision-Aware Rate Adaptation for IEEE 802.11 WLANs
Today’s IEEE 802.11 WLANs (Wireless LANs) provide multiple transmission rates so that different rates can be exploited in an adaptive manner depending on the underlying channel condition in order to maximize the system performance. Many rate adaptation schemes have been proposed so far while most (if not all) of the commercial devices implement a simple open-loop rate adaptation scheme (i.e., without feedback from the receiver), called ARF (Automatic Rate Fallback) due to its simplicity. A key problem with such open-loop rate adaptation schemes is that they do not consider the collision effect, and hence, malfunction severely when many transmission failures are due to collisions. In this paper, we propose a novel rate-adaptation scheme, called CARA (Collision-Aware Rate Adaptation). The key idea of CARA is that the transmitter station combines adaptively the Request-to-Send/Clear-to-Send (RTS/CTS) exchange with the Clear Channel Assessment (CCA) functionality to differentiate frame collisions from frame transmission failures caused by channel errors. Therefore, compared with other open-loop rateadaptation schemes, CARA is more likely to make the correct rate adaptation decisions. Through extensive simulation runs, we evaluate our proposed scheme to show that our scheme yields significantly higher throughput performance than the existing schemes
3979458
Video-based document tracking: unifying your physical and electronic desktops
This paper presents an approach for tracking paper documents on the desk over time and automatically linking them to the corresponding electronic documents using an overhead video camera. We demonstrate our system in the context of two scenarios, <i>paper tracking</i> and <i>photo sorting</i>. In the paper tracking scenario, the system tracks changes in the stacks of printed documents and books on the desk and builds a complete representation of the spatial structure of the desktop. When users want to find a printed document buried in the stacks, they can query the system based on appearance, keywords, or access time. The system also provides a <i>remote desktop</i> interface for directly browsing the physical desktop from a remote location. In the photo sorting scenario, users sort printed photographs into physical stacks on the desk. The systemautomatically recognizes the photographs and organizes the corresponding digital photographs into separate folders according to the physical arrangement. Our framework provides a way to unify the physical and electronic desktops without the need for a specialized physical infrastructure except for a video camera.
2642560
Forward-secure commercial key escrow systems
Key escrow system has been studied widely in recent years to reduce the gap between the needs for individual privacy and the needs for public security. In this paper, we survey three popular key escrow products of Netscape's, VeriSign's and Entrust's. And we also propose forward-secure KESs (Key Escrow Systems) and analyze their security.
2551048
Computers Are from Mars, Organisms Are from Venus
Biology and computer science share a natural affinity. Physicist Erwin Schrodinger envisioned life as an aperiodic crystal, observing that the organizing structure of life is neither completely regular, like a pure crystal, nor completely chaotic and without structure, like dust in the wind. Perhaps this is why biological information has never satisfactorily yielded to classical mathematical analysis. Machine computations combine elegant algorithms with brute-force calculations, which seems a reasonable approach to this aperiodic structure. Likewise, computing seeks to create a machine that can flexibly solve diverse problems. In nature, such plastic problem solving resides uniquely in the domain of organic matter. Thus, examining how organisms solve problems can lead to new computation and algorithm development approaches that devour the problems that are so easy to approach using a computer, yet so difficult to tackle in the laboratory. The paper discusses the two most successful uses of computers in biology, comparative sequence analysis and in silico cloning. It considers DNA computing and genetic algorithms.