Google Earth Engine: Planetary-scale geospatial analysis for everyone

We present YAGO, a light-weight and extensible ontology with high coverage and quality. YAGO builds on entities and relations and currently contains more than 1 million entities and 5 million facts. This includes the Is-A hierarchy as well as non-taxonomic relations between entities (such as HASONEPRIZE). The facts have been automatically extracted from Wikipedia and unified with WordNet, using a carefully designed combination of rule-based and heuristic methods described in this paper. The resulting knowledge base is a major step beyond WordNet: in quality by adding knowledge about individuals like persons, organizations, products, etc. with their semantic relationships - and in quantity by increasing the number of facts by more than an order of magnitude. Our empirical evaluation of fact correctness shows an accuracy of about 95%. YAGO is based on a logically clean model, which is decidable, extensible, and compatible with RDFS. Finally, we show how YAGO can be further extended by state-of-the-art information extraction techniques.

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Yago: a core of semantic knowledge

Social Network Analysis

The objective of this paper is to give a comprehensive introduction to applied cryptography with an engineer or computer scientist in mind. The emphasis is on the knowledge needed to create practical systems which supports integrity, confidentiality, or authenticity. Topics covered includes an introduction to the concepts in cryptography, attacks against cryptographic systems, key use and handling, random bit generation, encryption modes, and message authentication codes. Recommendations on algorithms and further reading is given in the end of the paper. This paper should make the reader able to build, understand and evaluate system descriptions and designs based on the cryptographic components described in the paper.

[서평]「Applied Cryptography」

The present report is submitted in response to General Assembly resolution 61/106, by which the Assembly adopted the Convention on the Rights of Persons with Disabilities and the Optional Protocol thereto. As requested by the Assembly, a brief overview of the status of the Convention as at 3 August 2007 is presented. The report also contains a brief description of technical arrangements on staff and facilities made necessary for the effective performance of the functions of the Conference of States Parties and the Committee under the Convention and the Optional Protocol, and a description on the progressive implementation of standards and guidelines for the accessibility of facilities and services of the United Nations system. Recent efforts of the United Nations and agencies to disseminate information on the Convention and the Optional Protocol are also described.

わかりやすい障害者の権利条約 : 知的障害のある人の権利のために = Convention on the rights of persons with disabilities

Modern processors consist of multiple cores that each support parallel processing by multiple physical threads, and they offer ample main-memory storage. This paper studies the use of such processors for the processing of update-intensive moving-object workloads that contain very frequent updates as well as contain queries.

The non-trivial challenge addressed is that of avoiding contention between long-running queries and frequent updates. Specifically, the paper proposes a grid-based indexing technique. A static grid indexes a near up-to-date snapshot of the data to support queries, while a live grid supports updates. An efficient cloning technique that exploits the memcpy system call is used to maintain the static grid.

An empirical study conducted with three modern processors finds that very frequent cloning, on the order of tens of milliseconds, is feasible, that the proposal scales linearly with the number of hardware threads, and that it significantly outperforms the previous state-of-the-art approach in terms of update throughput and query freshness.

Thread-level parallel indexing of update intensive moving-object workloads

With the widespread deployment of mobile devices with positioning capabilities, increasingly massive volumes of trajectory data are being collected that capture the movements of people and vehicles. This data enables co-movement pattern detection, which is important in applications such as trajectory compression and future-movement prediction. Existing co-movement pattern detection studies generally consider historical data and thus propose offline algorithms. However, applications such as future movement prediction need real-time processing over streaming trajectories. Thus, we investigate real-time distributed co-movement pattern detection over streaming trajectories.Existing off-line methods assume that all data is available when the processing starts. Nevertheless, in a streaming setting, unbounded data arrives in real time, making pattern detection challenging. To this end, we propose a framework based on Apache Flink, which is designed for efficient distributed streaming data processing. The framework encompasses two phases: clustering and pattern enumeration. To accelerate the clustering, we use a range join based on two-layer indexing, and provide techniques that eliminate unnecessary verifications. To perform pattern enumeration efficiently, we present two methods FBA and VBA that utilize id-based partitioning. When coupled with bit compression and candidate-based enumeration techniques, we reduce the enumeration cost from exponential to linear. Extensive experiments offer insight into the efficiency of the proposed framework and its constituent techniques compared with existing methods.

/pdf/real-time-distributed-co-movement-pattern-detection-on-4vwzj4saih.pdf

Real-time distributed co-movement pattern detection on streaming trajectories

Many databases contain temporal, or time-referenced, data and use intervals to capture the temporal aspect While SQL-based database management systems (DBMSs) are capable of supporting the management of interval data, the support they offer can be improved considerably A range of proposed temporal data models and query languages offer ample evidence to this effect Natural queries that are very difficult to formulate in SQL are easy to formulate in these temporal query languages The increased focus on analytics over historical data where queries are generally more complex exacerbates the difficulties and thus the potential benefits of a temporal query language Commercial DBMSs have recently started to offer limited temporal functionality in a step-by-step manner, focusing on the representation of intervals and neglecting the implementation of the query evaluation engineThis article demonstrates how it is possible to extend the relational database engine to achieve a full-fledged, industrial-strength implementation of sequenced temporal queries, which intuitively are queries that are evaluated at each time point Our approach reduces temporal queries to nontemporal queries over data with adjusted intervals, and it leaves the processing of nontemporal queries unaffected Specifically, the approach hinges on three concepts: interval adjustment, timestamp propagation, and attribute scaling Interval adjustment is enabled by introducing two new relational operators, a temporal normalizer and a temporal aligner, and the latter two concepts are enabled by the replication of timestamp attributes and the use of so-called scaling functions By providing a set of reduction rules, we can transform any temporal query, expressed in terms of temporal relational operators, to a query expressed in terms of relational operators and the two new operators We prove that the size of a transformed query is linear in the number of temporal operators in the original query An integration of the new operators and the transformation rules, along with query optimization rules, into the kernel of PostgreSQL is reported Empirical studies with the resulting temporal DBMS are covered that offer insights into pertinent design properties of the article's proposal The new system is available as open-source software

/pdf/extending-the-kernel-of-a-relational-dbms-with-comprehensive-3k4f1qq9s2.pdf

Extending the Kernel of a Relational DBMS with Comprehensive Support for Sequenced Temporal Queries

Previous approaches to implementing temporal DBMSs have assumed that a temporal DBMS must be built from scratch, employing an integrated architecture and using new temporal implementation techniques such as temporal indexes and join algorithms. However, this is a very large and time-consuming task. The paper explores approaches to implementing a temporal DBMS as a stratum on top of an existing non-temporal DBMS, rendering implementation more feasible by reusing much of the functionality of the underlying conventional DBMS. More specifically, the paper introduces three stratum meta-architectures, each with several specific architectures. Based on a new set of evaluation criteria, advantages and disadvantages of the specific architectures are identified. The paper also classifies all existing temporal DBMS implementations according to the specific architectures they, employ. It is concluded that a stratum architecture is the best short, medium, and perhaps even long-term, approach to implementing a temporal DBMS.

/pdf/stratum-approaches-to-temporal-dbms-implementation-1kxyyqt8nl.pdf

Stratum approaches to temporal DBMS implementation

The availability of Global Navigation Satellite Systems (GNSS) enables sophisticated vehicle guidance and advisory systems such as intelligent speed adaptation (ISA) systems. In ISA systems, it is essential to be able to position vehicles within a road network. Because digital road networks as well as GNSS positioning are often inaccurate, a technique known as map matching is needed that aims to use this inaccurate data for determining a vehicle's real road-network position. Then, knowing this position, an ISA system can compare speed with the speed limit in effect and take measures against speeding. An on-line map-matching algorithm is presented with an extensive number of weighting parameters that allow better determination of a vehicle's road network position. The algorithm uses certainty value to express its belief in the correctness of its results. The algorithm was designed and implemented to be used in the large scale ISA project 'Spar pa' farten'. Using test data and data collected from project participants, the algorithm's performance is evaluated. It is shown that the algorithm performs correctly 95% of the time and is capable of handling GNSS positioning errors in a conservative manner.

/pdf/map-matching-for-intelligent-speed-adaptation-4efhz485hw.pdf

Christian S. Jensen

Papers

Thread-level parallel indexing of update intensive moving-object workloads

Real-time distributed co-movement pattern detection on streaming trajectories

Extending the Kernel of a Relational DBMS with Comprehensive Support for Sequenced Temporal Queries

Stratum approaches to temporal DBMS implementation

Map matching for intelligent speed adaptation