Thesis (Ph. D.)--State University of New York at Binghamton, Department of Computer Science, 2006. / Includes bibliographical references (leaves 89-93).

The rising popularity of wireless services resulting in spectrum shortage has motivated dynamic spectrum sharing to facilitate e cient usage of the underutilized spectrum. Wideband spectrum sensing is a critical functionality to enable dynamic spectrum access by enhancing the opportunities of exploring spectral holes, but entails a major implemen- tation challenge in compact commodity radios that have limited energy and computation capabilities. The sampling rates speci ed by the Shannon-Nyquist theorem impose great challenges both on the acquisition hardware and the subsequent storage and digital sig- nal processors. Sub-Nyquist sampling was thus motivated to sample wideband signals at rates far lower than the Nyquist rate, while still retaining the essential information in the underlying signals. This thesis proposes several algorithms for invoking sub-Nyquist sampling in wideband spectrum sensing. Speci cally, a sub-Nyquist wideband spectrum sensing algorithm is proposed that achieves wideband sensing independent of signal sparsity without sampling at full bandwidth by using the low-speed analog-to-digital converters based on sparse Fast Fourier Transform. To lower signal spectrum sparsity while maintaining the channel state information, the received signal is pre-processed through a proposed permutation and ltering algorithm. Additionally, a low-complexity sub-Nyquist wideband spectrum sensing scheme is proposed that locates occupied channels blindly by recovering the sig- nal support, based on the jointly sparse nature of multiband signals. Exploiting the common signal support shared among multiple secondary users, an e cient coopera- tive spectrum sensing scheme is developed, in which the energy consumption on signal acquisition, processing, and transmission is reduced with the detection performance guar- antee. To further reduce the computation complexity of wideband spectrum sensing, a hybrid framework of sub-Nyquist wideband spectrum sensing with geolocation database is explored. Prior channel information from geolocation database is utilized in the sens- ing process to reduce the processing requirements on the sensor nodes. The models of the proposed algorithms are derived and veri ed by numerical analyses and tested on both real-world and simulated TV white space signals.

This study seeks to undertake an analysis of the topic of 'science and the media' as it has been constituted in academic discourse since the end of the Second World War. It finds that concern has polarized in two distinct camps: The larger, participant in the traditional project of North American media studies, blames the press for what it perceives as a widespread and deleterious "scientific illiteracy" on the part of the laity. The more recent, indebted to critical developments in social theory, philosophy of science, and the study of mass communication, works to expose the assumptions on which press coverage of science has been based and the interests which have benefited. / The thesis argues that the adequacy of the dominant concern to its object of analysis is at best suspect, but that nevertheless its agitations have been chiefly responsible for the form which popular science has predominantly assumed.

Thesis (M.S.)--University of Florida, 2005. / Title from title page of source document. Document formatted into pages; contains 96 pages. Includes vita. Includes bibliographical references.

Services Science is a new research discipline that has received, over the last years, a growing attention from academia and practice. It combines research from various fields which have evolved more or less independently and is concerned with the development and management of service products. Whereas theories from organizational and marketing science usually capture the nature of these products, engineering disciplines focus on shaping and developing these information goods, and the information systems field on integrating services as encapsulated application functionalities by using standardized (XML) interfaces. All these research streams converge in the new interdisciplinary area of Services Science which integrates the principles, design, and management of economic and technical services. For the fourth time, the \\\\\\\'International Symposium on Services Science (ISSS)\\\\\\\' offered an outstanding platform for the advancement and discussion of research in Service Science. In 2012, the ISSS focused on knowledge-intensive business services, also known as Smart Services, and their application in theory and practice. The ISSS was part of the Multi-Conference SABRE (Software, Agents and Services for Business, Research and E-Sciences, 24th-25th September 2012) and was held in Leipzig, Germany as a one-day event on the 25th September, 2012. The symposium was organized by the Information Systems Institute and the Department of Computer Science at the University of Leipzig as well as the Institute for Applied Informatics (InfAI), Fraunhofer MOEZ and the Leipziger Informatik-Verbund (LIV). As reflected in the conference proceedings, the sessions included in the agenda dealt with Smart Services from different perspectives: Smart Services in Theory and Practice, Smart Services in Management and Application, and Smart Services in High-Tech-Sectors. Although the official language of the conference is English, the authors had the opportunity to write their research contributions in English or German.

Recommender systems such as Amazon, offer uses recommendations, or suggestions of items to try or buy. We propose a novel classification of reasons for including explanations in recommender systems. Our focus is on the aim of effectiveness, or decision support, and we contrast it with other metrics such as satisfaction and persuasion. In user studies, we found that people varied in the features they found important, and composed a short list of features in two domains (movies and cameras). We then built a natural language explanation testbed system, considering these features as well as the limitations of using commercial data. This testbed was used in a series of experiments to test whether personalization of explanations affects effectiveness, persuasion and satisfaction. We chose a simple form of personalization which considers likely constraints of a recommender system (e.g. limited meta-data related to the user) as well as brevity. In these experiments we found that: 1. Explanations help participants to make decisions compared to recommendations without explanations, we saw as a significant decrease in opt-outs in item ratings – participants were more likely to be able to give an initial rating for an item if they were given an explanation, and the likelihood of receiving a rating increased for feature-based explanations compared to a baseline. 2. Contrary to our initial hypothesis, our method of personalization could damage effectiveness for both movies and cameras which are domains that differ with regard to two dimensions which we found affected perceived effectiveness: cost (low vs. high), and valuation type (subjective vs. objective). 3. Participants were more satisfied with feature-based than baseline explanations. If the personalization is perceived as relevant to them, then personalized feature-based explanations were preferred over non-personalized. 4. Satisfaction with explanation was also reflected in the proportion of opt-outs. The opt-out rate for the explanations was highest in the baseline for all experiments. This was the case despite the different types of explanation baselines used in the two domains.

Dans cette recherche, nous abordons le problème de le recherche de services qui répondent à des besoins des utilisateurs exprimés sous forme de requête en texte libre. Notre objectif est de résoudre les problèmes qui affectent l'efficacité des modèles de recherche d'information existant lorsqu'ils sont appliqués à la recherche de services dans un corpus rassemblant des descriptions standard de ces services. Ces problèmes sont issus du fait que les descriptions des services sont brèves. En effet, les fournisseurs de services n'utilisent que quelques termes pour décrire les services souhaités. Ainsi, lorsque ces descriptions sont différentes des phrases dans les requêtes ce qui diminue l'efficacité des modèles classiques qui dépendent de traits observables au lieu de traits sémantiques latents du texte. Nous avons adapté une famille de modèles de recherche d'information (IR) dans le but de contribuer à accroître l'efficacité acquise avec les modèles existant concernant la découverte de services. En outre, nous avons mené des expériences systématiques afin de comparer notre famille de modèles IR avec ceux de l'état de l'art portant sur la découverte de service. Des résultats des expériences, nous concluons que notre modèle basé sur l'extension des requêtes via un thésaurus co-occurrence est plus efficace en terme des mesures classiques utilisées en IR que tous les modèles étudiés dans cette recherche. Par conséquent, nous avons mis en place ce modèle dans S3niffer, qui est un moteur de recherche de service basé sur leur description standard. / In this research, we address the problem of retrieving services which fulfil users' need expressed in query in free text. Our goal is to cope the term mismatch problems which affect the effectiveness of service retrieval models applied in prior re- search on text descriptions-based service retrieval models. These problems are caused due to service descriptions are brief. Service providers use few terms to describe desired services, thereby, when these descriptions are different to the sentences in queries, term mismatch problems decrease the effectiveness in classical models which depend on the observable text features instead of the latent semantic features of the text. We have applied a family of Information Retrieval (IR) models for the purpose of contributing to increase the effectiveness acquired with the models applied in prior research on service retrieval. Besides, we have conducted systematic experiments to compare our family of IR models with those used in the state-of-the-art in service discovery. From the outcomes of the experiments, we conclude that our model based on query expansion via a co-occurrence thesaurus outperforms the effectiveness of all the models studied in this research. Therefore, we have implemented this model in S3niffer, which is a text description-based service search engine.

Thesis (Ph.D.)--Aberdeen University, 2009. / Title from web page (viewed on Feb. 23, 2010). Includes bibliographical references.

Dans cette recherche, nous abordons le problème de le recherche de services qui répondent à des besoins des utilisateurs exprimés sous forme de requête en texte libre. Notre objectif est de résoudre les problèmes qui affectent l'efficacité des modèles de recherche d'information existant lorsqu'ils sont appliqués à la recherche de services dans un corpus rassemblant des descriptions standard de ces services. Ces problèmes sont issus du fait que les descriptions des services sont brèves. En effet, les fournisseurs de services n'utilisent que quelques termes pour décrire les services souhaités. Ainsi, lorsque ces descriptions sont différentes des phrases dans les requêtes ce qui diminue l'efficacité des modèles classiques qui dépendent de traits observables au lieu de traits sémantiques latents du texte. Nous avons adapté une famille de modèles de recherche d'information (IR) dans le but de contribuer à accroître l'efficacité acquise avec les modèles existant concernant la découverte de services. En outre, nous avons mené des expériences systématiques afin de comparer notre famille de modèles IR avec ceux de l'état de l'art portant sur la découverte de service. Des résultats des expériences, nous concluons que notre modèle basé sur l'extension des requêtes via un thésaurus co-occurrence est plus efficace en terme des mesures classiques utilisées en IR que tous les modèles étudiés dans cette recherche. Par conséquent, nous avons mis en place ce modèle dans S3niffer, qui est un moteur de recherche de service basé sur leur description standard. / In this research, we address the problem of retrieving services which fulfil users' need expressed in query in free text. Our goal is to cope the term mismatch problems which affect the effectiveness of service retrieval models applied in prior re- search on text descriptions-based service retrieval models. These problems are caused due to service descriptions are brief. Service providers use few terms to describe desired services, thereby, when these descriptions are different to the sentences in queries, term mismatch problems decrease the effectiveness in classical models which depend on the observable text features instead of the latent semantic features of the text. We have applied a family of Information Retrieval (IR) models for the purpose of contributing to increase the effectiveness acquired with the models applied in prior research on service retrieval. Besides, we have conducted systematic experiments to compare our family of IR models with those used in the state-of-the-art in service discovery. From the outcomes of the experiments, we conclude that our model based on query expansion via a co-occurrence thesaurus outperforms the effectiveness of all the models studied in this research. Therefore, we have implemented this model in S3niffer, which is a text description-based service search engine.