miRBase Tracker : keeping track of microRNA annotation changes

Since 2002, information on individual microRNAs (miRNAs), such as reference names and sequences, has been stored in miRBase, the reference database for miRNA annota- tion. As a result of progressive insights into the miRNome and its complexity, miRBase underwent addition and deletion of miRNA records, changes in annotated miRNA se- quences and adoption of more complex naming schemes over time. Unfortunately, miRBase does not allow straightforward assessment of these ongoing miRNA annota- tion changes, which has resulted in substantial ambiguity regarding miRNA identity and sequence in public literature, in target prediction databases and in content on various commercially available analytical platforms. As a result, correct interpretation, compari- son and integration of miRNA study results are compromised, which we demonstrate here by assessing the impact of ignoring sequence annotation changes. To address this problem, we developed miRBase Tracker (www.mirbasetracker.org), an easy-to-use on- line database that keeps track of all historical and current miRNA annotation present in the miRBase database. Three basic functionalities allow researchers to keep their miRNA annotation up-to-date, reannotate analytical miRNA platforms and link published results with outdated annotation to the latest miRBase release. We expect miRBase Tracker to increase the transparency and annotation accuracy in the field of miRNA research. Database URL: www.mirbasetracker.or

Computer-Aided System for Wind Turbine Data Analysis

Context: The current work on wind turbine failure detection focuses on researching suitable signal processing algorithms and developing efficient diagnosis algorithms. The laboratory research would involve large and complex data, and it can be a daunting task. Aims: To develop a Computer-Aided system for assisting experts to conduct an efficient laboratory research on wind turbine data analysis. System is expected to provide data visualization, data manipulation, massive data processing and wind turbine failure detection. Method: 50G off-line SCADA data and 4 confident diagnosis algorithms were used in this project. Apart from the instructions from supervisor, this project also gained help from two experts from Engineering Department. Java and Microsoft SQL database were used to develop the system. Results: Data visualization provided 6 different charting solutions and together with robust user interactions. 4 failure diagnosis solutions and data manipulations were provided in the system. In addition, dedicated database server and Matlab API with Java RMI were used to resolve the massive data processing problem. Conclusions: Almost all of the deliverables were completed. Friendly GUI and useful functionalities make user feel more comfortable. The final product does enable experts to conduct an efficient laboratory research. The end of this project also gave some potential extensions of the system

A real-time active routing approach via a database for airport surface movement

Airports face challenges due to the increasing volume of air traffic and tighter environmental restrictions which result in a need to actively integrate speed profiles into conventional routing and scheduling procedure. However, only until very recently, the research on airport ground movement has started to take into account such a speed profile optimisation problem actively so that not only time efficiency but also fuel saving and decrease in airport emissions can be achieved at the same time. It is envisioned that the realism of planning could also be improved through speed profiles. However, due to the multi-objective nature of the problem and complexity of the investigated models (objective functions), the existing speed profile optimisation approach features high computational demand and is not suitable for an on-line application. In order to make this approach more competitive for real-world application and to meet limits imposed by International Civil Aviation Organization for on-line decision time, this paper introduces a pre-computed database acting as a middleware to effectively separate the planning (routing and scheduling) module and the speed profile generation module. Employing a database not only circumvents duplicative optimisation for the same taxiway segments, but also completely avoids the computation of speed profiles during the on-line decision support owing a great deal to newly proposed database initialization procedures. Moreover, the added layer of database facilitates, in the future, more complex and realistic models to be considered in the speed profile generation module, without sacrificing on-line decision time. The experimental results carried out using data from a major European hub show that the proposed approach is promising in speeding up the search process

Application of Dynamic Interface Technology in Scientific Research Management System

Abstractthis paper tries to develop an Internet-based evaluation system for declaration of scientific research projects. The system, employing the integrating mode of C/S and B/S, accomplishes three functions: on-line declaration of scientific research projects, project management and on-line evaluation. The problem of dovetailing word text with database is properly solved. Furthermore, the efficiency of designation of the system is highly raised thanks to the adoption of XML store profile, DOM interface and dynamic interface technology

Ground-based studies of emission-line variability: Recent results for NGC 5548 and future plans

Ever since emission-line variability was first detected in AGNs, it has been clearly understood that light-travel time effects in the broadline region (BLR) afford a tool for studying the structure of these spatially unresolved regions. However, only within the last few years has the observational problem become well defined in terms of the sampling rates and quality of data necessary to address the problem correctly. The amount of data required to extract structural information about the BLR from the continuum and emission-line light curves is so considerable that the most promising approach seemed to be to combine the observational efforts. The goal was to work together to produce a large, high-quality database which would then be released to individual investigators for more complete analysis. The cornerstone of this effort, was a joint NASA/ESA/SERC program to monitor the spectrum of NGC 5548 every four days with IUE from December 1988 through August 1988. A concurrent ground-based program was organized in an effort to enhance the scientific return on the project by extending the wavelength coverage and providing higher spectral resolution and signal to noise ratios than would be possible with IUE. It also turned out that the temporal resolution of the ground-based program was somewhat better than the temporal resolution of the IUE program, and the temporal baseline is longer and continues to grow. The database and initial results are presented by Peterson et al., (1991). The important results of the ground-based program are summarized, some additional applications of the existing data are described, and a few comments are made on what can be done in the future to expand on this work

Interest of Syntactic Knowledge for On-line Flowchart Recognition

International audienceIn this paper, we address the problem of segmentation and recognition of on-line flowcharts. Flowcharts are bi-dimensional documents, in the sense that the order of writing is not defined. Some statistical approaches have been proposed in the literature to label and segment the flowcharts. However, as they are very well structured documents, we propose to introduce some structural and syntactic knowledge on flowcharts to improve their recognition. For this purpose, we have used an existing grammatical off-line method with on-line a posteriori signal. We apply this work on a freely available database. The results demonstrate the interest of structural knowledge on the context to improve the recognition

On-line sampling methods for discovering association rules

Association rule discovery is one of the prototypical problems in data mining. In this problem, the input database is assumed to be very large and most of the algorithms are designed to minimize the number of scans of the database. Enumerating association rules is usually an expensive task due to the size of the input database. A proposed approach for reducing the running time of this process is random sampling. Of course, any implementation of an algorithm that uses sampling must solve the problem of determining which sample size is appropriate. Previous research of sampling for association rule mining has approached this problem concluding that, in general, the theoretically obtained sample size bounds are far from what is observed in practice. In this paper, we try to reduce this gap between theory and practice. We propose two on-line sampling algorithms for association rule mining. Our algorithms maintain the same theoretical guarantees of previous approaches while using a much smaller number of transactions in most of the cases. In the experiments we report, this improvement is often by an order of magnitude.Postprint (published version