Scalable discovery of networked data : Algorithms, Infrastructure, Applications

Harmelen, F.A.H. van [Promotor]Siebes, R.M. [Copromotor

Design and evaluation of parallel hashing over large-scale data

High-performance analytical data processing systems often run on servers with large amounts of memory. A common data structure used in such environment is the hash tables. This paper focuses on investigating efficient parallel hash algorithms for processing large-scale data. Currently, hash tables on distributed architectures are accessed one key at a time by local or remote threads while shared-memory approaches focus on accessing a single table with multiple threads. A relatively straightforward “bulk-operation” approach seems to have been neglected by researchers. In this work, using such a method, we propose a high-level parallel hashing framework, Structured Parallel Hashing, targeting efficiently processing massive data on distributed memory. We present a theoretical analysis of the proposed method and describe the design of our hashing implementations. The evaluation reveals a very interesting result - the proposed straightforward method can vastly outperform distributed hashing methods and can even offer performance comparable with approaches based on shared memory supercomputers which use specialized hardware predicates. Moreover, we characterize the performance of our hash implementations through extensive experiments, thereby allowing system developers to make a more informed choice for their high-performance applications

Efficiently Handling Skew in Outer Joins on Distributed Systems

Outer joins are ubiquitous in databases and big data systems. The question of how best to execute outer joins in large parallel systems is particularly challenging as real world datasets are characterized by data skew leading to performance issues. Although skew handling techniques have been extensively studied for inner joins, there is little published work solving the corresponding problem for parallel outer joins. Conventional approaches to this problem such as ones based on hash redistribution often lead to load balancing problems while duplication-based approaches incurs significant overhead in terms of network communication. In this paper, we propose a new algorithm, query with counters (QC), for directly handling skew in outer joins on distributed architectures. We present an efficient implementation of our approach based on the asynchronous partitioned global address space (APGAS) parallel programming model. We evaluate the performance of our approach on a cluster of 192 cores (16 nodes) and datasets of 1 billion tuples with different skew. Experimental results show that our method is scalable and, in cases of high skew, faster than the state-of-the-art

Mobile Cloud Support for Semantic-Enriched Speech Recognition in Social Care

Nowadays, most users carry high computing power mobile devices where speech recognition is certainly one of the main technologies available in every modern smartphone, although battery draining and application performance (resource shortage) have a big impact on the experienced quality. Shifting applications and services to the cloud may help to improve mobile user satisfaction as demonstrated by several ongoing efforts in the mobile cloud area. However, the quality of speech recognition is still not sufficient in many complex cases to replace the common hand written text, especially when prompt reaction to short-term provisioning requests is required. To address the new scenario, this paper proposes a mobile cloud infrastructure to support the extraction of semantics information from speech recognition in the Social Care domain, where carers have to speak about their patients conditions in order to have reliable notes used afterward to plan the best support. We present not only an architecture proposal, but also a real prototype that we have deployed and thoroughly assessed with different queries, accents, and in presence of load peaks, in our experimental mobile cloud Platform as a Service (PaaS) testbed based on Cloud Foundry

Asymptomatic fatal post-lobectomy hemopericardium

We report a case of an asymptomatic post-lobectomy hemopericardium in a female who died suddenly at day two post surgery. Autopsy revealed no pathologic findings, but 250 ml of blood and clots in the pericardium and a non-significant injury to the epicardial fat overlying the circumflex artery territory

Genetic vs community diversity patterns of macrobenthic species: preliminary results from the lagoonal ecosystem

1 - The use of molecular data derived from multispecies assemblages in order to test ecological theory has only recently been introduced in the scientific literature.2 - As a first step, we compared patterns of abiotic environment, polychaeta distribution and their genetic diversity in five lagoon ecosystems in Greece. Our results confirm the hypothesis that higher genetic diversity is expected in the populations of the species occurring in the transitional waters rather than of those occurring in the marine environment.3 - Patterns derived from the polychaete community level and from the mitochondrial DNA (16S rRNA) obtained from Nephtys hombergii and Hediste diversicolor showed convergence, indicating the potential use of molecular matrices as surrogates in community analysis.4 - Finally, the high correlation between the genetic diversity pattern of H. diversicolor and the phosphorus concentration in the sediments may imply the broadening of the hierarchic-response-tostress hypothesis towards lower than species level

The OpenKnowledge System: An Interaction-Centered Approach to Knowledge Sharing

Abstract. The information that is made available through the semantic web will be accessed through complex programs (web-services, sensors, etc.)thatmayinteract in sophisticated ways. Composition guided simply by the specifications of programs ’ inputs and outputs is insufficient to obtain reliable aggregate performance- hence the recognised need for process models to specify the interactions required between programs. These interaction models, however, are traditionally viewed as a consequence of service composition rather than as the focal point for facilitating composition. We describe an operational system that uses models of interaction as the focus for knowledge exchange. Our implementation adopts a peer to peer architecture, thus making minimal assumptions about centralisation of knowledge sources, discovery and interaction control.

Preoperative diagnosis of obscure gastrointestinal bleeding due to a GIST of the jejunum: a case report

Gastrointestinal stromal tumours (GISTs) are rare mesenchymal neoplasms affecting the digestive tract or nearby structures within the abdomen. We present a case of a 66-year-old female patient who presented with obscure anemia due to gastrointestinal bleeding and underwent exploratory laparotomy during which a large GIST of the small intestine was discovered. Examining the preoperative results of video capsule endoscopy, computed tomography, and angiography and comparing them with the operative findings we discuss which of these investigations plays the most important role in the detection and localization of GIST. A sort review of the literature is also conducted on these rare mesenchymal tumours

The dosimetric effects of limited elective nodal irradiation in volumetric modulated arc therapy treatment planning for locally advanced non-small cell lung cancer

Objective—Contemporary radiotherapy guidelines for locally advanced non-small cell lung carcinoma (LA-NSCLC) recommend omitting elective nodal irradiation, despite the fact that evidence supporting this came primarily from older reports assessing comprehensive nodal coverage using 3D conformal techniques. Herein, we evaluated the dosimetric implications of the addition of limited elective nodal irradiation (LENI) to standard involved field irradiation (IFI) using volumetric modulated arc therapy (VMAT) planning. Method—Target volumes and organs-at-risk (OARs) were delineated on CT simulation images of 20 patients with LA-NSCLC. Two VMAT plans (IFI and LENI) were generated for each patient. Involved sites were treated to 60 Gy in 30 fractions for both IFI and LENI plans. Adjacent uninvolved nodal regions, considered high risk based on the primary tumor site and extent of nodal involvement, were treated to 51 Gy in 30 fractions in LENI plans using a simultaneous integrated boost approach. Results—All planning objectives for PTVs and OARs were achieved for both IFI and LENI plans. LENI resulted in significantly higher esophagus Dmean (15.3 vs. 22.5 Gy, p \u3c 0.01), spinal cord Dmax (34.9 vs. 42.4 Gy, p = 0.02) and lung Dmean (13.5 vs. 15.9 Gy, p = 0.02), V20 (23.0 vs. 27.9%, p = 0.03), and V5 (52.6 vs. 59.4%, p = 0.02). No differences were observed in heart parameters. On average, only 32.2% of the high-risk nodal volume received an incidental dose of 51 Gy when untargeted in IFI plans. Conclusion—The addition of LENI to VMAT plans for LA-NSCLC is feasible, with only modestly increased doses to OARs and marginal expected increase in associated toxicity