97,684 research outputs found
Joshua Davis: Author of Spare Parts
No full textCitation: K-State First (2016). Joshua Davis: Author of Spare Parts [Flier]. Manhattan, Kansas: K-State First.Flyer advertising Joshua Davis's author talk at Kansas State University
Steven Johnson Author Talk Poster
No full textK-State Book NetworkA poster advertising an author talk by Steven Johnson at Kansas State University on September 3, 2014. Steven Johnson's book "The Ghost Map" was the 2014-2015 common book
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Appropriate Similarity Measures for Author Cocitation Analysis
No full textWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Expanding “Communities and Collections” in the K-State Research Exchange (K-REx) to benefit the K-State Community and Beyond
No full textKansas State University has used its institutional repository, the K-State Research Exchange (K-REx), to store and share its first year experience program, K-State First, and notably its common reading program, K-State First Book. We have done so with the aim that the accessibility and preservation of these documents ensures program stability, promotes engagement with first year programming, and provides the ability to foster growth,educational opportunities, and community building outside of K-State. Moving away from research concentrated repositories and taking a more holistic approach to scholarship, especially when realizing the pedagogical significance of collaborative campus programming, institutions can showcase, discover, preserve, and grow programs that shape campus communities and engagement.
This session will provide an overview of K-REx and spotlight the digital archive of the university’s first year experience program and common reading program, K-State First Book. We will discuss the benefits and challenges to expanding the purview of your repositories. We talkthrough the types of materials we decide to host in our repository and why we share what we do. We will also provide recommendations on new ways to evaluate what belongs in institutional repositories and how this diversity can benefit your program, your institution, the community, and others
Ready Player One Program Event Poster
No full textK-State Book NetworkA poster advertising an author talk by Ernest Cline at Kansas State University on October 10, 2013. Ernest Cline's book "Ready Player One" was selected as the 2013-2014 common book
Depolarization and decreased surface expression of K+ channels contribute to NSAID-inhibition of intestinal restitution
No full textNon-steroidal anti-inflammatory drugs (NSAIDs) contribute to gastrointestinal ulcer formation by inhibiting epithelial cell migration and mucosal restitution; however, the drug-affected signaling pathways are poorly defined. We investigated whether NSAID inhibition of intestinal epithelial migration is associated with depletion of intracellular polyamines, depolarization of membrane potential (Em) and altered surface expression of K+ channels. Epithelial cell migration in response to the wounding of confluent IEC-6 and IEC-Cdx2 monolayers was reduced by indomethacin (100μM), phenylbutazone (100μM) and NS-398 (100μM) but not by SC-560 (1μM). NSAID-inhibition of intestinal cell migration was not associated with depletion of intracellular polyamines. Treatment of IEC-6 and IEC-Cdx2 cells with indomethacin, phenylbutazone and NS-398 induced significant depolarization of Em, whereas treatment with SC-560 had no effect on Em. The Em of IEC-Cdx2 cells was: −38.5±1.8mV under control conditions; −35.9±1.6mV after treatment with SC-560; −18.8±1.2mV after treatment with indomethacin; and −23.7±1.4mV after treatment with NS-398. Whereas SC-560 had no significant effects on the total cellular expression of Kv1.4 channel protein, indomethacin and NS-398 decreased not only the total cellular expression of Kv1.4, but also the cell surface expression of both Kv1.4 and Kv1.6 channel subunits in IEC-Cdx2. Both Kv1.4 and Kv1.6 channel proteins were immunoprecipitated by Kv1.4 antibody from IEC-Cdx2 lysates, indicating that these subunits co-assemble to form heteromeric Kv channels. These results suggest that NSAID inhibition of epithelial cell migration is independent of polyamine-depletion, and is associated with depolarization of Em and decreased surface expression of heteromeric Kv1 channels.ID: S0006295207001931; M3: Article; Accession Number: S0006295207001931; Author: L.C. Freeman (b); Author: D.F. Narvaez (a); Author: A. McCoy (a); Author: F.B. von Stein (c); Author: S. Young (b); Author: K. Silver (a); Author: S. Ganta (b); Author: D. Koch (b); Author: R. Hunter (b); Author: R.F. Gilmour (c); Author: J.D. Lillich (a, ⁎); Affiliation: Department of Clinical Sciences, Kansas State University, Manhattan, KS 66506, United States; Affiliation: Department of Anatomy and Physiology, Kansas State University, Manhattan, KS 66506, United States; Affiliation: Department of Biomedical Sciences, Cornell University, Ithaca, NY 14853, United States; Keyword: Non-steroidal anti-inflammatory drugs; Keyword: Intestinal epithelial cells; Keyword: Membrane potential; Keyword: Potassium channels; Number of Pages: 12; Language: English;Source type: Electronic(1)http://search.ebscohost.com/login.aspx?direct=true&db=edselp&AN=S0006295207001931&site=eds-live&scope=sit
Fragmenting Very Large XML Data Warehouses via K-means Clustering Algorithm
No full textXML data sources are gaining popularity in the context of Business Intelligence and On-Line Analytical Processing (OLAP) applications, due to the amenities of XML in representing and managing complex and heterogeneous data. However, XML-native database systems currently suffer from limited performance, both in terms of volumes of manageable data and query response time. Therefore, recent research efforts are focusing on horizontal fragmentation techniques, which are able to overcome the above limitations. However, classical fragmentation algorithms are not suitable to control the number of originated fragments, which instead plays a critical role in data warehouses. In this paper, we propose the use of the K-means clustering algorithm for effectively and efficiently supporting the fragmentation of very large XML data warehouses. We complement our analytical contribution with a comprehensive experimental assessment where we compare the efficiency of our proposal against existing fragmentation algorithms
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Privacy preserving top-k query processing over outsourced data
No full textL’externalisation de données d’entreprise ou individuelles chez un fournisseur de cloud, par exemple avec l’approche Database-as-a-Service, est pratique et rentable. Mais elle introduit un problème majeur: comment préserver la confidentialité des données externalisées, tout en prenant en charge les requêtes expressives des utilisateurs. Une solution simple consiste à crypter les données avant leur externalisation. Ensuite, pour répondre à une requête, le client utilisateur peut récupérer les données cryptées du cloud, les décrypter et évaluer la requête sur des données en texte clair (non cryptées). Cette solution n’est pas pratique, car elle ne tire pas parti de la puissance de calcul fournie par le cloud pour évaluer les requêtes.Dans cette thèse, nous considérons un type important de requêtes, les requêtes top-k, et le problème du traitement des requêtes top-k sur des données cryptées dans le cloud, tout en préservant la vie privée. Une requête top-k permet à l’utilisateur de spécifier un nombre k de tuples les plus pertinents pour répondre à la requête. Le degré de pertinence des tuples par rapport à la requête est déterminé par une fonction de notation.Nous proposons d’abord un système complet, appelé BuckTop, qui est capable d’évaluer efficacement les requêtes top-k sur des données cryptées, sans avoir à les décrypter dans le cloud. BuckTop inclut un algorithme de traitement des requêtes top-k qui fonctionne sur les données cryptées, stockées dans un nœud du cloud, et retourne un ensemble qui contient les données cryptées correspondant aux résultats top-k. Il est aidé par un algorithme de filtrage efficace qui est exécuté dans le cloud sur les données chiffrées et supprime la plupart des faux positifs inclus dans l’ensemble renvoyé. Lorsque les données externalisées sont volumineuses, elles sont généralement partitionnées sur plusieurs nœuds dans un système distribué. Pour ce cas, nous proposons deux nouveaux systèmes, appelés SDB-TOPK et SD-TOPK, qui permettent d’évaluer les requêtes top-k sur des données distribuées cryptées sans avoir à les décrypter sur les nœuds où elles sont stockées. De plus, SDB-TOPK et SD-TOPK ont un puissant algorithme de filtrage qui filtre les faux positifs autant que possible dans les nœuds et renvoie un petit ensemble de données cryptées qui seront décryptées du côté utilisateur. Nous analysons la sécurité de notre système et proposons des stratégies efficaces pour la mettre en œuvre.Nous avons validé nos solutions par l’implémentation de BuckTop, SDB-TOPK et SD-TOPK, et les avons comparé à des approches de base par rapport à des données synthétiques et réelles. Les résultats montrent un excellent temps de réponse par rapport aux approches de base. Ils montrent également l’efficacité de notre algorithme de filtrage qui élimine presque tous les faux positifs. De plus, nos systèmes permettent d’obtenir une réduction significative des coûts de communication entre les nœuds du système distribué lors du calcul du résultat de la requête.Outsourcing corporate or individual data at a cloud provider, e.g. using Database-as-a-Service, is practical and cost-effective. But it introduces a major problem: how to preserve the privacy of the outsourced data, while supporting powerful user queries. A simple solution is to encrypt the data before it is outsourced. Then, to answer a query, the user client can retrieve the encrypted data from the cloud, decrypt it, and evaluate the query over plaintext (non encrypted) data. This solution is not practical, as it does not take advantage of the computing power provided by the cloud for evaluating queries.In this thesis, we consider an important kind of queries, top-k queries,and address the problem of privacy-preserving top-k query processing over encrypted data in the cloud.A top-k query allows the user to specify a number k, and the system returns the k tuples which are most relevant to the query. The relevance degree of tuples to the query is determined by a scoring function.We first propose a complete system, called BuckTop, that is able to efficiently evaluate top-k queries over encrypted data, without having to decrypt it in the cloud. BuckTop includes a top-k query processing algorithm that works on the encrypted data, stored at one cloud node,and returns a set that is proved to contain the encrypted data corresponding to the top-k results. It also comes with an efficient filtering algorithm that is executed in the cloud on encypted data and removes most of the false positives included in the set returned.When the outsourced data is big, it is typically partitioned over multiple nodes in a distributed system. For this case, we propose two new systems, called SDB-TOPK and SD-TOPK, that can evaluate top-k queries over encrypted distributed data without having to decrypt at the nodes where they are stored. In addition, SDB-TOPK and SD-TOPK have a powerful filtering algorithm that filters the false positives as much as possible in the nodes, and returns a small set of encrypted data that will be decrypted in the user side. We analyze the security of our system, and propose efficient strategies to enforce it.We validated our solutions through implementation of BuckTop , SDB-TOPK and SD-TOPK, and compared them to baseline approaches over synthetic and real databases. The results show excellent response time compared to baseline approaches. They also show the efficiency of our filtering algorithm that eliminates almost all false positives. Furthermore, our systems yieldsignificant reduction in communication cost between the distributed system nodes when computing the query result
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