Contemporary apparel design practice is such that the functional and ergonomic aspects can be readily rationalized and thus computerized, but this is not true for the aspects of affect or emotion. Design for emotion or affect remains an ad hoc exercise. In the apparel industry, affects or emotions of both wearers and audiences are very important. This paper presents a work with an overall objective to rationalize the affective property of apparel. To achieve this overall objective, the first step is to have a language (a set of words in this case) to describe the customer’s need in the affective attribute or property of apparel into a technical specification. In the work reported in this paper, this language (simply, a set of words) has been developed by the application of a proposed data mining procedure with a proprietary tool. A preliminary experiment was performed to validate this language – how to accurately capture the voice of customer in the aspect of affects in this case. There are two contributions out of this work: (1) finding a set of words that describe the affective property of apparel to capture the voice of customer in the aspect of affect, which is a foundation for the computer-based affective design of apparel; and (2) formulation of a new data mining process for searching affective words from the internet, which has a generalized implication to affective design in other domains of products, such as furniture.
Increase in the number of audiences interested in watching live events through the internet has become a challenge for traditional client-server approaches. In fact, supporting manifold audiences requires that broadcasters allocate more bandwidth. P2P networks for live streaming allow the users to support video dissemination by contributing their resources. Consequently, P2P networks are effective and scalable alternative for video streaming in the network. Since the performance of a P2P streaming system is dependent on the contribution of the group members, free riding is one of the main challenges of such systems. Free riders are some selfish peers that do not upload any data to other peers while downloading from the network. Therefore, designing incentive mechanisms for P2P streaming systems is essential. In this paper we designed and proposed an incentive mechanism for mesh based P2P video streaming. The proposed approach includes two parts. In the first part, the contribution of the peers in the network is measured and maintained in a distributed fashion, and in the second part, differentiated service is provided for the peers based on their contribution. We simulated the proposed approach and the results show the efficiency of the proposed mechanism in improving the overall quality of the perceived video in the group.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.