Laboratory information management software for genotyping workflows: Applications in high throughput crop genotyping

Background: With the advances in DNA sequencer-based technologies, it has become possible to automate several steps of the genotyping process leading to increased throughput. To efficiently handle the large amounts of genotypic data generated and help with quality control, there is a strong need for a software system that can help with the tracking of samples and capture and management of data at different steps of the process. Such systems, while serving to manage the workflow precisely, also encourage good laboratory practice by standardizing protocols, recording and annotating data from every step of the workflow Results: A laboratory information management system (LIMS) has been designed and implemented at the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) that meets the requirements of a moderately high throughput molecular genotyping facility. The application is designed as modules and is simple to learn and use. The application leads the user through each step of the process from starting an experiment to the storing of output data from the genotype detection step with auto-binning of alleles; thus ensuring that every DNA sample is handled in an identical manner and all the necessary data are captured. The application keeps track of DNA samples and generated data. Data entry into the system is through the use of forms for file uploads. The LIMS provides functions to trace back to the electrophoresis gel files or sample source for any genotypic data and for repeating experiments. The LIMS is being presently used for the capture of high throughput SSR (simple-sequence repeat) genotyping data from the legume (chickpea, groundnut and pigeonpea) and cereal (sorghum and millets) crops of importance in the semi-arid tropics. Conclusions: A laboratory information management system is available that has been found useful in the management of microsatellite genotype data in a moderately high throughput genotyping laboratory. The application with source code is freely available for academic users and can be downloaded from http://www.icrisat.org/bt-software-d-lims.htm

Semanttisen webin ontologisen tekstiilikäsitteistön kehittäminen ja liittäminen museoiden luettelointitietoihin

DEVELOPING A TEXTILE ONTOLOGY FOR THE SEMANTIC WEB AND CONNECTING IT TO MUSEUM CATALOGING DATA The goal of the Semantic Web is to share concept-based information in a versatile way on the Internet. This is achievable using formal data structures called ontologies. The goal of this re-search is to increase the usability of museum cataloging data in information retrieval. The work is interdisciplinary, involving craft science, terminology science, computer science, and museology. In the first part of the dissertation an ontology of concepts of textiles, garments, and accessories is developed for museum cataloging work. The ontology work was done with the help of thesauri, vocabularies, research reports, and standards. The basis of the ontology development was the Museoalan asiasanasto MASA, a thesaurus for museum cataloging work which has been enriched by other vocabularies. Concepts and terms concerning the research object, as well as the material names of textiles, costumes, and accessories, were focused on. The research method was terminological concept analysis complemented by an ontological view of the Semantic Web. The concept structure was based on the hierarchical generic relation. Attention was also paid to other relations between terms and concepts, and between concepts themselves. Altogether 977 concept classes were created. Issues including how to choose and name concepts for the ontology hierarchy and how deep and broad the hierarchy could be are discussed from the viewpoint of the ontology developer and museum cataloger. The second part of the dissertation analyzes why some of the cataloged terms did not match with the developed textile ontology. This problem is significant because it prevents automatic ontological content integration of the cataloged data on the Semantic Web. The research datasets, i.e. the cataloged museum data on textile collections, came from three museums: Espoo City Museum, Lahti City Museum and The National Museum of Finland. The data included 1803 textile, costume, and accessory objects. Unmatched object and textile material names were analyzed. In the case of the object names six categories (475 cases), and of the material names eight categories (423 cases), were found where automatic annotation was not possible. The most common explanation was that the cataloged field was filled with a long sentence comprised of many terms. Sometimes in the compound term, the object name and material, or the name and the way of usage, were combined. As well, numeric values in the material name cataloging field prevented annotation and so did the absence of a corresponding concept in the ontology. Ready-made drop-down lists of materials used in one cataloging system facilitated the annotation. In the case of naming objects and materials, one should use terms in basic form without attributes. The developed textile ontology has been applied in two cultural portals, MuseumFinland and Culturesampo, where one can search for and browse information based on cataloged data using integrated ontologies in an interoperable way. The textile ontology is also part of the national FinnONTO ontology infrastructure. Keywords: annotation, concept, concept analysis, cataloging, museum collection, ontology, Semantic Web, textile collection, textile material

Semantic Classes in Topic Detection and Tracking

Topic detection and tracking (TDT) is an area of information retrieval research the focus of which revolves around news events. The problems TDT deals with relate to segmenting news text into cohesive stories, detecting something new, previously unreported, tracking the development of a previously reported event, and grouping together news that discuss the same event. The performance of the traditional information retrieval techniques based on full-text similarity has remained inadequate for online production systems. It has been difficult to make the distinction between same and similar events. In this work, we explore ways of representing and comparing news documents in order to detect new events and track their development. First, however, we put forward a conceptual analysis of the notions of topic and event. The purpose is to clarify the terminology and align it with the process of news-making and the tradition of story-telling. Second, we present a framework for document similarity that is based on semantic classes, i.e., groups of words with similar meaning. We adopt people, organizations, and locations as semantic classes in addition to general terms. As each semantic class can be assigned its own similarity measure, document similarity can make use of ontologies, e.g., geographical taxonomies. The documents are compared class-wise, and the outcome is a weighted combination of class-wise similarities. Third, we incorporate temporal information into document similarity. We formalize the natural language temporal expressions occurring in the text, and use them to anchor the rest of the terms onto the time-line. Upon comparing documents for event-based similarity, we look not only at matching terms, but also how near their anchors are on the time-line. Fourth, we experiment with an adaptive variant of the semantic class similarity system. The news reflect changes in the real world, and in order to keep up, the system has to change its behavior based on the contents of the news stream. We put forward two strategies for rebuilding the topic representations and report experiment results. We run experiments with three annotated TDT corpora. The use of semantic classes increased the effectiveness of topic tracking by 10-30\% depending on the experimental setup. The gain in spotting new events remained lower, around 3-4\%. The anchoring the text to a time-line based on the temporal expressions gave a further 10\% increase the effectiveness of topic tracking. The gains in detecting new events, again, remained smaller. The adaptive systems did not improve the tracking results.

Dessy : desktop search and synchronization

Current smartphones have a storage capacity of several gigabytes. More and more information is stored on mobile devices. To meet the challenge of information organization, we turn to desktop search. Users often possess multiple devices, and synchronize (subsets of) information between them. This makes file synchronization more important. This thesis presents Dessy, a desktop search and synchronization framework for mobile devices. Dessy uses desktop search techniques, such as indexing, query and index term stemming, and search relevance ranking. Dessy finds files by their content, metadata, and context information. For example, PDF files may be found by their author, subject, title, or text. EXIF data of JPEG files may be used in finding them. User–defined tags can be added to files to organize and retrieve them later. Retrieved files are ranked according to their relevance to the search query. The Dessy prototype uses the BM25 ranking function, used widely in information retrieval. Dessy provides an interface for locating files for both users and applications. Dessy is closely integrated with the Syxaw file synchronizer, which provides efficient file and metadata synchronization, optimizing network usage. Dessy supports synchronization of search results, individual files, and directory trees. It allows finding and synchronizing files that reside on remote computers, or the Internet. Dessy is designed to solve the problem of efficient mobile desktop search and synchronization, also supporting remote and Internet search. Remote searches may be carried out offline using a downloaded index, or while connected to the remote machine on a weak network. To secure user data, transmissions between the Dessy client and server are encrypted using symmetric encryption. Symmetric encryption keys are exchanged with RSA key exchange. Dessy emphasizes extensibility. Also the cryptography can be extended. Users may tag their files with context tags and control custom file metadata. Adding new indexed file types, metadata fields, ranking methods, and index types is easy. Finding files is done with virtual directories, which are views into the user’s files, browseable by regular file managers. On mobile devices, the Dessy GUI provides easy access to the search and synchronization system. This thesis includes results of Dessy synchronization and search experiments, including power usage measurements. Finally, Dessy has been designed with mobility and device constraints in mind. It requires only MIDP 2.0 Mobile Java with FileConnection support, and Java 1.5 on desktop machines.

The radical in arts education research

Arts education research, as an interdisciplinary field, has developed in the shadows of a number of research traditions. However amid all the methodological innovation, I believe there is one particular, distinctive and radical research strategy which arts educators have created to research the practice of arts education: namely arts-based research. For many, and Elliot Eisner from Stanford University was among the first, arts education needed a research approach which could deal with the complex dynamics of arts education in the classroom. What was needed was ‘an approach to the conduct of educational research that was rooted in the arts and that used aesthetically crafted forms to reveal aspects of practice that mattered educationally’ (Eisner 2006: 11). While arts education researchers were crafting the principles and practices of arts-based research, fellow artist/researchers in the creative arts were addressing similar needs and fashioning their own exacting research strategies. This chapter aligns arts-based research with the complementary research practices established in creative arts studios and identifies the shared and truly radical nature of these moves. Finally, and in a contemporary turn many will find surprising, I will discuss how the radical aspects of these methodologies are now being held up as core elements of what is being called the fourth paradigm of scientific research, known as eScience. Could it be that the radical dynamics of arts-based research pre-figured the needs of eScience researchers who are currently struggling to manage the ‘deluge of Big Data’ which is disrupting their well-established scientific methods?

Wear Next: An Exploration into the Future of Wearable Technology

Technology is increasingly infiltrating all aspects of our lives and the rapid uptake of devices that live near, on or in our bodies are facilitating radical new ways of working, relating and socialising. This distribution of technology into the very fabric of our everyday life creates new possibilities, but also raises questions regarding our future relationship with data and the quantified self. By embedding technology into the fabric of our clothes and accessories, it becomes ‘wearable’. Such ‘wearables’ enable the acquisition of and the connection to vast amounts of data about people and environments in order to provide life-augmenting levels of interactivity. Wearable sensors for example, offer the potential for significant benefits in the future management of our wellbeing. Fitness trackers such as ‘Fitbit’ and ‘Garmen’ provide wearers with the ability to monitor their personal fitness indicators while other wearables provide healthcare professionals with information that improves diagnosis. While the rapid uptake of wearables may offer unique and innovative opportunities, there are also concerns surrounding the high levels of data sharing that come as a consequence of these technologies. As more ‘smart’ devices connect to the Internet, and as technology becomes increasingly available (e.g. via Wi-Fi, Bluetooth), more products, artefacts and things are becoming interconnected. This digital connection of devices is called The ‘Internet of Things’ (IoT). IoT is spreading rapidly, with many traditionally non-online devices becoming increasingly connected; products such as mobile phones, fridges, pedometers, coffee machines, video cameras, cars and clothing. The IoT is growing at a rapid rate with estimates indicating that by 2020 there will be over 25 billion connected things globally. As the number of devices connected to the Internet increases, so too does the amount of data collected and type of information that is stored and potentially shared. The ability to collect massive amounts of data - known as ‘big data’ - can be used to better understand and predict behaviours across all areas of research from societal and economic to environmental and biological. With this kind of information at our disposal, we have a more powerful lens with which to perceive the world, and the resulting insights can be used to design more appropriate products, services and systems. It can however, also be used as a method of surveillance, suppression and coercion by governments or large organisations. This is becoming particularly apparent in advertising that targets audiences based on the individual preferences revealed by the data collected from social media and online devices such as GPS systems or pedometers. This type of technology also provides fertile ground for public debates around future fashion, identity and broader social issues such as culture, politics and the environment. The potential implications of these type of technological interactions via wearables, through and with the IoT, have never been more real or more accessible. But, as highlighted, this interconnectedness also brings with it complex technical, ethical and moral challenges. Data security and the protection of privacy and personal information will become ever more present in current and future ethical and moral debates of the 21st century. This type of technology is also a stepping-stone to a future that includes implantable technology, biotechnologies, interspecies communication and augmented humans (cyborgs). Technologies that live symbiotically and perpetually in our bodies, the built environment and the natural environment are no longer the stuff of science fiction; it is in fact a reality. So, where next?... The works exhibited in Wear Next_ provide a snapshot into the broad spectrum of wearables in design and in development internationally. This exhibition has been curated to serve as a platform for enhanced broader debate around future technology, our mediated future-selves and the evolution of human interactions. As you explore the exhibition, may we ask that you pause and think to yourself, what might we... Wear Next_? WEARNEXT ONLINE LISTINGS AND MEDIA COVERAGE: http://indulgemagazine.net/wear-next/ http://www.weekendnotes.com/wear-next-exhibition-gallery-artisan/ http://concreteplayground.com/brisbane/event/wear-next_/ http://www.nationalcraftinitiative.com.au/news_and_events/event/48/wear-next http://bneart.com/whats-on/wear-next_/ http://creativelysould.tumblr.com/post/124899079611/creative-weekend-art-edition http://www.abc.net.au/radionational/programs/breakfast/smartly-dressed-the-future-of-wearable-technology/6744374 http://couriermail.newspaperdirect.com/epaper/viewer.aspx RADIO COVERAGE http://www.abc.net.au/radionational/programs/breakfast/wear-next-exhibition-whats-next-for-wearable-technology/6745986 TELEVISION COVERAGE http://www.abc.net.au/radionational/programs/breakfast/wear-next-exhibition-whats-next-for-wearable-technology/6745986 https://au.news.yahoo.com/video/watch/29439742/how-you-could-soon-be-wearing-smart-clothes/#page1

Efficient content-based image retrieval based on multi-feature fusion

The increased availability of image capturing devices has enabled collections of digital images to rapidly expand in both size and diversity. This has created a constantly growing need for efficient and effective image browsing, searching, and retrieval tools. Pseudo-relevance feedback (PRF) has proven to be an effective mechanism for improving retrieval accuracy. An original, simple yet effective rank-based PRF mechanism (RB-PRF) that takes into account the initial rank order of each image to improve retrieval accuracy is proposed. This RB-PRF mechanism innovates by making use of binary image signatures to improve retrieval precision by promoting images similar to highly ranked images and demoting images similar to lower ranked images. Empirical evaluations based on standard benchmarks, namely Wang, Oliva & Torralba, and Corel datasets demonstrate the effectiveness of the proposed RB-PRF mechanism in image retrieval.

Scheduling tools to reduce the cost of cane railway transport

Cane railway systems provide empty bins for harvesters to fill and full bins of cane for the factory to process. These operations need to be conducted in a timely fashion to minimise delays to harvesters and the factory and to minimise the cut-to-crush delay, while also minimising the cost of providing this service. A range of tools has been provided over the years to assist in this process. This paper reviews the objectives of the cane transport system and the tools available to achieve those objectives. The facilities within these tools to assist in the control of costs are highlighted.

Scalable multi-dimensional user intent identification using tree structured distributions

The problem of identifying user intent has received considerable attention in recent years, particularly in the context of improving the search experience via query contextualization. Intent can be characterized by multiple dimensions, which are often not observed from query words alone. Accurate identification of Intent from query words remains a challenging problem primarily because it is extremely difficult to discover these dimensions. The problem is often significantly compounded due to lack of representative training sample. We present a generic, extensible framework for learning the multi-dimensional representation of user intent from the query words. The approach models the latent relationships between facets using tree structured distribution which leads to an efficient and convergent algorithm, FastQ, for identifying the multi-faceted intent of users based on just the query words. We also incorporated WordNet to extend the system capabilities to queries which contain words that do not appear in the training data. Empirical results show that FastQ yields accurate identification of intent when compared to a gold standard.

A semantic middleware to enhance current multimedia retrieval systems with content-based functionalities

210 p. : graf.

Authority files: Breaking out of the library silo to become signposts for research information

Authority files serve to uniquely identify real world ‘things’ or entities like documents, persons, organisations, and their properties, like relations and features. Already important in the classical library world, authority files are indispensable for adequate information retrieval and analysis in the computer age. This is because, even more than humans, computers are poor at handling ambiguity. Through authority files, people tell computers which terms, names or numbers refer to the same thing or have the same meaning by giving equivalent notions the same identifier. Thus, authority files signpost the internet where these identifiers are interlinked on the basis of relevance. When executing a query, computers are able to navigate from identifier to identifier by following these links and collect the queried information on these so-called ‘crosswalks’. In this context, identifiers also go under the name controlled access points. Identifiers become even more crucial now massive data collections like library catalogues or research datasets are releasing their till-now contained data directly to the internet. This development is coined Open Linked Data. The concatenating name for the internet is Web of Data instead of the classical Web of Documents.