Campus & alumni news

Boston University Medicine was published by the Boston University Medical Campus, and presented stories on events and topics of interest to members of the BU Medical Campus community. It followed the discontinued publication Centerscope as Boston University Medicine from 1991-2005, then continued as Campus & Alumni News from 2006-2013 before returning to the title Boston University Medicine from 2014-present

Shaping Online Dialogue: Examining How Community Rules Affect Discussion Structures on Reddit

Community rules play a key part in enabling or constraining the behaviors of members in online communities. However, little is unknown regarding whether and to what degree changing rules actually affects community dynamics. In this paper, we seek to understand how these behavior-governing rules shape the interactions between users, as well as the structure of their discussion. Using the top communities on Reddit (i.e. subreddits), we first contribute a taxonomy of behavior-based rule categories across Reddit. Then, we use a network analysis perspective to discover how changing implementation of different rule categories affects subreddits' user interaction and discussion networks over a 1.5 year period. Our study find several significant effects, including greater clustering among users when subreddits increase rules focused on structural regulation and how restricting allowable content surprisingly leads to more interactions between users. Our findings contribute to research in proactive moderation through rule setting, as well as lend valuable insights for online community designers and moderators to achieve desired community dynamics

固有値分解とテンソル分解を用いた大規模グラフデータ分析に関する研究

筑波大学 (University of Tsukuba)201

Pengelolaan Waktu Endap dan Tingkat Kepadatan Lapangan Penumpukan Peti Kemas di PT Jakarta International Container Terminal

Abstrak. Waktu menunggu rata-rata petikemas untuk pemeriksaan dan pengurusan dokumen-dokumen yang dibutuhkan di lapangan penumpukan terminal terutama untuk barang import yang juga disebut dwell time (DT) di Jakarta Indonesia akhir-akhir ini menjadi isu nasional. Hal ini disebabkan masih tingginya waktu endap yang secara rata-rata masih berkisar 6 hari atau lebih, berakibat meningkatnya biaya pengiriman barang dan juga akan mempengaruhi tingkat kepadatan lapangan penumpukan petikemas/Yard Occupancy Ratio (YOR) dan menimbulkan kongesti sehingga kinerja operasional pelabuhan akan menurun. Tujuan penelitian ini adalah untuk : 1. menjelaskan kondisi eksisting hubungan DT dan YOR di PT. Jakarta International Container Terminal sebagai terminal petikemas terbesar di Indonesia dengan menggunakan data sekunder dari tahun 2011 sampai dengan tahun 2015; 2. menyusun prakiraan perkembangan kinerja DT dan YOR yang akan datang dengan menggunakan analisis forecasting data time series dengan error paling kecil dan 3. memperoleh alternatif strategi dan solusi untuk mengatasi DT dengan teknik Analytical Hierarchy Process (AHP) yang menggunakan pendapat 7 pakar (expert) yang mewakili para pemangku kepentingan. Hasil korelasi antara DT dan YOR menunjukkan bahwa terdapat hubungan positif yang signifikan, sedangkan prakiraan menunjukkan bahwa dwell time cenderung turun dan YOR juga akan cenderung turun. Hasil analisis AHP menunjukkan bahwa strategi yang menjadi prioritas utama adalah perancangan model early warning system (EWS)/sistem peringatan dini lingkup antar lembaga yang dimaksudkan untuk mengantisipasi apabila terjadi lonjakan YOR para pihak dapat melakukan secara bersama-sama dengan cepat dan terkoordinasi dan alternatif solusi mengatasi DT dikarenakan aktifitas di terminal petikemas didominasi variabel waktu dalam pengurusan dokumen maka dapat dilakukan dengan memperbanyak barang yang lewat tanpa pemerikasaan dilihat dari rekam jejak para pemiliknya yaitu dapat dipercaya.Kata Kunci: waktu endap, tingkat kepadatan lapangan penumpukan, prakiraan, AHP, sistem peringatan diniAbstract. The average waiting time of containers for inspecting and handling documents required in the container yards of terminals, especially for imported goods, known as DT (dwell time), in Jakarta, Indonesia, lately becomes a national issue. This is due to the high settling time, which on average is still around 6 days or more, resulting in increased shipping cost and affecting the density of container yards/YOR (Yard Occupancy Ratio) and causing congestions that decrease the port operational performance. The purposes of this study were to: 1. Explain the existing condition of the relation between DT and YOR in PT. Jakarta International Container Terminal which is the largest container terminal in Indonesia, by using secondary data from 2011 to 2015; 2. Predict the growth of the future performances of DT and YOR using time series with the smallest error and to obtain alternative strategies and solutions to handle DT using AHP (Analytical Hierarchy Process) which uses opinions of 7 experts who represent stakeholders. The correlation between DT and YOR showed that there was a significant positive relation, while estimation indicated that the dwell time tended to decline and so did YOR. The results of AHP analysis showed that the prioritized strategy was designing EWS (Early Warning System) model between agencies to anticipate surge of YOR so that the parties could work together rapidly and in a coordinated manner. Alternative solutions to solve DT because activities in the container terminal are dominated by the time variable in terms of documents handling was multiplying goods which passed through without examination based on track records of trustworthy owners.Keywords: dwell time, yard occupancy ratio, predict, analytical hierarchy process, early warning syste

Vocabulary Evolution on the Semantic Web: From Changes to Evolution of Vocabularies and its Impact on the Data

The main objective of the Semantic Web is to provide data on the web well-defined meaning. Vocabularies are used for modeling data in the web, provide a shared understanding of a domain and consist of a collection of types and properties. These types and properties are so-called terms. A vocabulary can import terms from other vocabularies, and data publishers use vocabulary terms for modeling data. Importing terms via vocabularies results in a Network of Linked vOcabularies (NeLO). Vocabularies are subject to change during their lifetime. When vocabularies change, the published data become a problem if they are not updated based on these changes. So far, there has been no study that analyzes vocabulary changes over time. Furthermore, it is unknown how data publishers reflect on such vocabulary changes. Ontology engineers and data publishers may not be aware of the changes in the vocabulary terms that have already happened since they occur rather rarely. This work addresses the problem of vocabulary changes and their impact on other vocabularies and the published data. We analyzed the changes of vocabularies and their reuse. We selected the most dominant vocabularies, based on their use by data publishers. Additionally, we analyzed the changes of 994 vocabularies. Furthermore, we analyzed various vocabularies to better understand by whom and how they are used in the modeled data, and how these changes are adopted in the Linked Open Data cloud. We computed the state of the NeLO from the available versions of vocabularies for over 17 years. We analyzed the static parameters of the NeLO such as its size, density, average degree, and the most important vocabularies at certain points in time. We further investigated how NeLO changes over time, specifically measuring the impact of a change in one vocabulary on others, how the reuse of terms changes, and the importance of vocabulary changes. Our results show that the vocabularies are highly static, and many of the changes occurred in annotation properties. Additionally, 16% of the existing terms are reused by other vocabularies, and some of the deprecated and deleted terms are still reused. Furthermore, most of the newly coined terms are adopted immediately. Our results show that even if the change frequency of terms is rather low, it can have a high impact on the data due to a large amount of data on the web. Moreover, due to a large number of vocabularies in the NeLO, and therefore the increase of available terms, the percentage of imported terms compared with the available ones has decreased over time. Additionally, based on the scores of the average number of exports for the vocabularies in the NeLO, some vocabularies have become more popular over time. Overall, understanding the evolution of vocabulary terms is important for ontology engineers and data publishers to avoid wrong assumptions about the data published on the web. Furthermore, it may foster a better understanding of the impact of the changes in vocabularies and how they are adopted to possibly learn from previous experience. Our results provide for the first time in-depth insights into the structure and evolution of the NeLO. Supported by proper tools exploiting the analysis of this thesis, it may help ontology engineers to identify data modeling shortcomings and assess the dependencies implied by the reusing of a specific vocabulary.Das Hauptziel des Semantic Web ist es, den Daten im Web eine klar definierte Bedeutung zu geben. Vokabulare werden zum Modellieren von Daten im Web verwendet. Vokabulare vermitteln ein gemeinsames Verständnis einer Domäne und bestehen aus einer Sammlung von Typen und Eigenschaften. Diese Typen und Eigenschaften sind sogenannte Begriffe. Ein Vokabular kann Begriffe aus anderen Vokabularen importieren, und Datenverleger verwenden die Begriffe der Vokabulare zum Modellieren von Daten. Durch das Importieren von Begriffen entsteht ein Netzwerk verknüpfter Vokabulare (NeLO). Vokabulare können sich im Laufe der Zeit ändern. Wenn sich Vokabulare ändern, kann dies zu Problemen mit bereits veröffentlichten Daten führen, falls diese nicht entsprechend angepasst werden. Bisher gibt es keine Studie, die die Veränderung der Vokabulare im Laufe der Zeit analysiert. Darüber hinaus ist nicht bekannt, inwiefern bereits veröffentlichte Daten an diese Veränderungen angepasst werden. Verantwortliche für Ontologien und Daten sind sich möglicherweise der Änderungen in den Vokabularen nicht bewusst, da solche Änderungen eher selten vorkommen. Diese Arbeit befasst sich mit dem Problem der Änderung von Vokabularen und deren Auswirkung auf andere Vokabulare sowie die Daten. Wir analysieren die Änderung von Vokabularen und deren Wiederverwendung. Für unsere Analyse haben wir diejenigen Vokabulare ausgewählt, die am häufigsten verwendet werden. Zusätzlich analysieren wir die Änderungen von 994 Vokabularen aus dem Verzeichnis "Linked Open Vocabulary". Wir analysieren die Vokabulare, um zu verstehen, von wem und wie sie in den modellierten Daten verwendet werden und inwiefern Änderungen in die Linked Open Data Cloud übernommen werden. Wir beobachten den Status von NeLO aus den verfügbaren Versionen der Vokabulare über einen Zeitraum von 17 Jahren. Wir analysieren statische Parameter von NeLO wie Größe, Dichte, Durchschnittsgrad und die wichtigsten Vokabulare zu bestimmten Zeitpunkten. Wir untersuchen weiter, wie sich NeLO mit der Zeit ändert. Insbesondere messen wir die Auswirkung einer Änderung in einem Vokabular auf andere, wie sich die Wiederverwendung von Begriffen ändert und wie wichtig Änderungen im Vokabular sind. Unsere Ergebnisse zeigen, dass die Vokabulare sehr statisch sind und viele Änderungen an sogenannten Annotations-Properties vorgenommen wurden. Darüber hinaus werden 16% der vorhandenen Begriffen von anderen Vokabularen wiederverwendet, und einige der veralteten und gelöschten Begriffe werden weiterhin wiederverwendet. Darüber hinaus werden die meisten neu erstellten Begriffe unmittelbar verwendet. Unsere Ergebnisse zeigen, dass selbst wenn die Häufigkeit von Änderungen an Vokabularen eher gering ist, so kann dies aufgrund der großen Datenmenge im Web erhebliche Auswirkungen haben. Darüber hinaus hat sich aufgrund einer großen Anzahl von Vokabularen in NeLO und damit der Zunahme der verfügbaren Begriffe der Prozentsatz der importierten Begriffe im Vergleich zu den verfügbaren Begriffen im Laufe der Zeit verringert. Basierend auf den Ergebnissen der durchschnittlichen Anzahl von Exporten für die Vokabulare in NeLO sind einige Vokabulare im Laufe der Zeit immer beliebter geworden. Insgesamt ist es für Verantwortliche für Ontologien und Daten wichtig, die Entwicklung der Vokabulare zu verstehen, um falsche Annahmen über die im Web veröffentlichten Daten zu vermeiden. Darüber hinaus ermöglichen unsere Ergebnisse ein besseres Verständnis der Auswirkungen von Änderungen in Vokabularen, sowie deren Nachnutzung, um möglicherweise aus früheren Erfahrungen zu lernen. Unsere Ergebnisse bieten erstmals detaillierte Einblicke in die Struktur und Entwicklung des Netzwerks der verknüpften Vokabularen. Unterstützt von geeigneten Tools für die Analyse in dieser Arbeit, kann es Verantwortlichen für Ontologien helfen, Mängel in der Datenmodellierung zu identifizieren und Abhängigkeiten zu bewerten, die durch die Wiederverwendung eines bestimmten Vokabulars entstehenden

Understanding and supporting occupational therapists clinical decision-making for the management of upper limb post stoke sensory impairment

Background Stroke survivors form the largest client group seen by occupational therapists and a large proportion of these stroke survivors experience upper limb post-stroke sensory impairments (ULPSSI) which impact upper limb function and participation. This thesis addresses the clinical decision-making (CDM) of occupational therapists when managing ULPSSI. No appraised and synthesised summary of the research evidence related to the effectiveness of interventions for ULPSSI is available to support therapists’ CDM. Information on occupational therapists’ practice choices and decisions about managing ULPSSI and the survivors’ perspective on ULPSSI is scant. This information could support occupational therapists CDM when addressing ULPSSI and potentially improve stroke survivors’ outcomes. Thesis Aims This thesis aims to: 1. Synthesise the effectiveness of interventions for ULPSSI; 2. Explore how occupational therapists make and manage decisions regarding ULPSSI management; 3. Describe practice choices occupational therapists commonly make when managing ULPSSI and the sources of information they use to make these decisions; 4. Compare current assessment choices and intervention practices with recommendations from the research evidence and clinical practice guidelines; 5. Describe the stroke survivors’ perspective with regard to ULPSSI; and 6. Design and pilot an evidence-based, theory-driven educational intervention to support occupational therapists’ CDM when addressing ULPSSI. Thesis Methods Five distinct studies addressed the above aims. A Cochrane systematic review evaluated the evidence for the effectiveness of ULPSSI interventions. Twelve occupational therapists participated in a qualitative descriptive study exploring therapists’ practice choices and CDM related to ULPSSI. • Based on the qualitative study, a survey of 187 occupational therapists described therapists’ current practice choices regarding ULPSSI management and factors impacting CDM. A qualitative descriptive study using semi-structured interviews with 15 stroke survivors explored their experience of ULPSSI and the associated rehabilitation encounter. Finally, based on the need for training expressed by the survey participants, a one group pre- and post-test design, feasibility study evaluated the effect of a one day, theory-based educational intervention on 19 occupational therapists’ knowledge, perceived behavioural control, attitudes and intended behaviour regarding ULPSSI management, research utilisation, and shared decision-making. Workshop content incorporated information from the prior research studies forming this thesis. Results A Cochrane systematic review located 13 randomised controlled trials (RCTs) addressing ULPSSI interventions, with benefit shown from individual RCTs evaluating mirror therapy, a graded thermal stimulation, and intermittent pneumatic compression. Other single RCTs reporting statistically significant results for repetitive peripheral magnetic stimulation, early intensive task-orientated training and graded sensory rehabilitation were found but lacked sufficient data to determine effects sizes. Therapists in the qualitative study expressed considerable uncertainty when managing ULPSSI and focused on searching for knowledge especially from peers, reasoning by analogy, and trialling interventions to manage this uncertainty. Therapists described clinical and contextual factors influencing their CDM. The majority of survey respondents reported frequently assessing sensation but failed to use standardised measures. Just over half of the respondents frequently provided ULPSSI interventions, primarily providing non-specific sensory stimulation followed by compensatory strategies differing from those in recent research. Most therapists provided patient/caregiver safety education. Therapists cited lack of knowledge and skills, patients’ short length of stay, and lack of time as barriers to utilising ULPSSI interventions. Most therapists reported not being up-to-date with current research requesting continuing education to support practice. Survey respondents’ lack of awareness of interventions, believing that interventions for motor impairments addressed ULPSSI, and lack of time most commonly led to the decision not to use ULPSSI interventions. Clients’ cognitive status, ULPSSI severity, and time since stroke impacted therapists’ choice between compensatory or remedial approaches. Prior personal experience, trialling interventions, and consulting other therapists most commonly influenced specific intervention choice. Stroke survivors clearly articulated how ULPSSI impacted upper limb functional use. Survivors saw the recovery process extending years beyond current rehabilitation time frames and necessitating considerable work, though many survivors felt they were left on their own to address upper limb impairments. They reported little involvement in decision-making regarding their rehabilitation. A feasibility study of a theory-driven educational intervention demonstrated potential to significantly change therapists knowledge, attitudes and perceived behavioural control, and changes from current behaviour to intended behaviour regarding ULPSSI management, using research, and shared decision-making

Federated Query Processing over Heterogeneous Data Sources in a Semantic Data Lake

Data provides the basis for emerging scientific and interdisciplinary data-centric applications with the potential of improving the quality of life for citizens. Big Data plays an important role in promoting both manufacturing and scientific development through industrial digitization and emerging interdisciplinary research. Open data initiatives have encouraged the publication of Big Data by exploiting the decentralized nature of the Web, allowing for the availability of heterogeneous data generated and maintained by autonomous data providers. Consequently, the growing volume of data consumed by different applications raise the need for effective data integration approaches able to process a large volume of data that is represented in different format, schema and model, which may also include sensitive data, e.g., financial transactions, medical procedures, or personal data. Data Lakes are composed of heterogeneous data sources in their original format, that reduce the overhead of materialized data integration. Query processing over Data Lakes require the semantic description of data collected from heterogeneous data sources. A Data Lake with such semantic annotations is referred to as a Semantic Data Lake. Transforming Big Data into actionable knowledge demands novel and scalable techniques for enabling not only Big Data ingestion and curation to the Semantic Data Lake, but also for efficient large-scale semantic data integration, exploration, and discovery. Federated query processing techniques utilize source descriptions to find relevant data sources and find efficient execution plan that minimize the total execution time and maximize the completeness of answers. Existing federated query processing engines employ a coarse-grained description model where the semantics encoded in data sources are ignored. Such descriptions may lead to the erroneous selection of data sources for a query and unnecessary retrieval of data, affecting thus the performance of query processing engine. In this thesis, we address the problem of federated query processing against heterogeneous data sources in a Semantic Data Lake. First, we tackle the challenge of knowledge representation and propose a novel source description model, RDF Molecule Templates, that describe knowledge available in a Semantic Data Lake. RDF Molecule Templates (RDF-MTs) describes data sources in terms of an abstract description of entities belonging to the same semantic concept. Then, we propose a technique for data source selection and query decomposition, the MULDER approach, and query planning and optimization techniques, Ontario, that exploit the characteristics of heterogeneous data sources described using RDF-MTs and provide a uniform access to heterogeneous data sources. We then address the challenge of enforcing privacy and access control requirements imposed by data providers. We introduce a privacy-aware federated query technique, BOUNCER, able to enforce privacy and access control regulations during query processing over data sources in a Semantic Data Lake. In particular, BOUNCER exploits RDF-MTs based source descriptions in order to express privacy and access control policies as well as their automatic enforcement during source selection, query decomposition, and planning. Furthermore, BOUNCER implements query decomposition and optimization techniques able to identify query plans over data sources that not only contain the relevant entities to answer a query, but also are regulated by policies that allow for accessing these relevant entities. Finally, we tackle the problem of interest based update propagation and co-evolution of data sources. We present a novel approach for interest-based RDF update propagation that consistently maintains a full or partial replication of large datasets and deal with co-evolution