Should energy efficiency be traded off for other product attributes? : an analysis of air-conditioner regulation in Japan

This paper examines the functioning of energy efficiency standards and labeling policies for air conditioners in Japan. The results of our empirical analysis suggest that consumers respond more to label information, which benchmarks the energy efficiency performance of each product to a pre-specified target, than to direct performance measures. This finding provides justification for the setting, and regular updating, of target standards as well as their use in calculating relative performance measures. We also find, through graphical analysis, that air conditioner manufacturers face a tradeoff between energy efficiency and product compactness when they develop their products. This tradeoff, combined with the semi-regular upward revision of minimum energy efficiency standards, has led to the growth in indoor unit size of air conditioners in recent years. In the face of this phenomenon, regulatory rules were revised so that manufacturers could adhere to less stringent standards if the indoor unit size of their product remains below a certain size. Our demand estimates provide no evidence that larger indoor unit size causes disutility to consumers. It is therefore possible that the regulatory change was not warranted from a consumer welfare point of view.

Consumers knowledge about dietary fibre : Results of a survey questionnaire in Hungary and Romania

Dietary fi bres (DFs) are essential components of the balanced diet. Even though the adequate level of their consumption can be ensured from several natural (e.g. fruit, vegetables, legumes) and ‘artifi cial’ sources (e.g. functional foods), the consumed levels are below the recommendations. To analyse the Hungarian and Romanian consumers’ knowledge level, their perceptions of the health benefi ts associated with fi bre, as well as the recognition of the potential information sources, a survey questionnaire was conducted with the total of 713 consumers. Results showed that the level of knowledge about DFs was not adequate. Internet was found to be widely used and identifi ed as one of the most appropriate information sources to encourage the consumption of DF. It was a favourable result that three-quarter of the respondents was interested in the topic of healthy food consumption; however, just less than half of them took into consideration the label information during their shopping decisions. To increase the consumption of DF and to support the responsibility and conscious consumer decisions steps must to be done (e.g. education of children, pointing out of the sources). For this purpose, modern information technology and communication channels fi tting to the consumers’ cultural and personal particularities can be utilized.

Evaluation of information extraction techniques to label extracted data from e-commerce web page

Automatically determining and assigning shared and meaningful text labels to data extracted from an e-Commerce web page is a challenging problem. An e-Commerce web page can display a list of data records, each of which can contain a combination of data items (e.g. product name and price) and explicit labels, which describe some of these data items. Recent advances in extraction techniques have made it much easier to precisely extract individual data items and labels from a web page, however, there are two open problems: 1. assigning an explicit label to a data item, and 2. determining labels for the remaining data items. Furthermore, improvements in the availability and coverage of vocabularies, especially in the context of e-Commerce web sites, means that we now have access to a bank of relevant, meaningful and shared labels which can be assigned to extracted data items. However, there is a need for a technique which will take as input a set of extracted data items and assign automatically to them the most relevant and meaningful labels from a shared vocabulary. We observe that the Information Extraction (IE) community has developed a great number of techniques which solve problems similar to our own. In this work-in-progress paper we propose our intention to theoretically and experimentally evaluate different IE techniques to ascertain which is most suitable to solve this problem.

GEO Label – quality information interrogation tool for geospatial datasets:towards effective visualization of quality metadata

Although the importance of dataset fitness-for-use evaluation and intercomparison is widely recognised within the GIS community, no practical tools have yet been developed to support such interrogation. GeoViQua aims to develop a GEO label which will visually summarise and allow interrogation of key informational aspects of geospatial datasets upon which users rely when selecting datasets for use. The proposed GEO label will be integrated in the Global Earth Observation System of Systems (GEOSS) and will be used as a value and trust indicator for datasets accessible through the GEO Portal. As envisioned, the GEO label will act as a decision support mechanism for dataset selection and thereby hopefully improve user recognition of the quality of datasets. To date we have conducted 3 user studies to (1) identify the informational aspects of geospatial datasets upon which users rely when assessing dataset quality and trustworthiness, (2) elicit initial user views on a GEO label and its potential role and (3), evaluate prototype label visualisations. Our first study revealed that, when evaluating quality of data, users consider 8 facets: dataset producer information; producer comments on dataset quality; dataset compliance with international standards; community advice; dataset ratings; links to dataset citations; expert value judgements; and quantitative quality information. Our second study confirmed the relevance of these facets in terms of the community-perceived function that a GEO label should fulfil: users and producers of geospatial data supported the concept of a GEO label that provides a drill-down interrogation facility covering all 8 informational aspects. Consequently, we developed three prototype label visualisations and evaluated their comparative effectiveness and user preference via a third user study to arrive at a final graphical GEO label representation. When integrated in the GEOSS, an individual GEO label will be provided for each dataset in the GEOSS clearinghouse (or other data portals and clearinghouses) based on its available quality information. Producer and feedback metadata documents are being used to dynamically assess information availability and generate the GEO labels. The producer metadata document can either be a standard ISO compliant metadata record supplied with the dataset, or an extended version of a GeoViQua-derived metadata record, and is used to assess the availability of a producer profile, producer comments, compliance with standards, citations and quantitative quality information. GeoViQua is also currently developing a feedback server to collect and encode (as metadata records) user and producer feedback on datasets; these metadata records will be used to assess the availability of user comments, ratings, expert reviews and user-supplied citations for a dataset. The GEO label will provide drill-down functionality which will allow a user to navigate to a GEO label page offering detailed quality information for its associated dataset. At this stage, we are developing the GEO label service that will be used to provide GEO labels on demand based on supplied metadata records. In this presentation, we will provide a comprehensive overview of the GEO label development process, with specific emphasis on the GEO label implementation and integration into the GEOSS.

Information literacy programs and research: reflections on 'Information literacy programs and research: An international review' by Christine Bruce. 2000. The Australian Library Journal 49, 3: 209-218

Although in the late 1990s there was much discussion as to whether the idea of information literacy was necessary or had longevity, global interest in the phenomenon has increased rather than diminished. In the midst of all this activity, what has happened to the way in which we interpret the idea of information literacy in the last decade or more? The label of information literacy has certainly become widely applied, especially to library based programs and remains more popular in formal learning environments.Ultimately information literacy is about peoples’ experience of using information wherever they happen to be. Information literacy is about people interacting, engaging, working with information in many contexts, either individually or in community. Emerging technologies may transform the kinds of information available and how it is engaged with. Nevertheless, we continue to need to understand the experience of information use in order to support people in their information environments. We continue to need to develop programs which reflect and enhance peoples’ experiences of using information to learn in ever widening and more complex settings (Bruce, 2008; Bruce & Hughes, 2010).

Unsupervised multi-label text classification using a world knowledge ontology

The development of text classification techniques has been largely promoted in the past decade due to the increasing availability and widespread use of digital documents. Usually, the performance of text classification relies on the quality of categories and the accuracy of classifiers learned from samples. When training samples are unavailable or categories are unqualified, text classification performance would be degraded. In this paper, we propose an unsupervised multi-label text classification method to classify documents using a large set of categories stored in a world ontology. The approach has been promisingly evaluated by compared with typical text classification methods, using a real-world document collection and based on the ground truth encoded by human experts.

Automatic population HARDI white matter tract clustering by label fusion of multiple tract atlases

Automatic labeling of white matter fibres in diffusion-weighted brain MRI is vital for comparing brain integrity and connectivity across populations, but is challenging. Whole brain tractography generates a vast set of fibres throughout the brain, but it is hard to cluster them into anatomically meaningful tracts, due to wide individual variations in the trajectory and shape of white matter pathways. We propose a novel automatic tract labeling algorithm that fuses information from tractography and multiple hand-labeled fibre tract atlases. As streamline tractography can generate a large number of false positive fibres, we developed a top-down approach to extract tracts consistent with known anatomy, based on a distance metric to multiple hand-labeled atlases. Clustering results from different atlases were fused, using a multi-stage fusion scheme. Our "label fusion" method reliably extracted the major tracts from 105-gradient HARDI scans of 100 young normal adults. © 2012 Springer-Verlag.

Label-free isolation of a prostate cancer cell among blood cells and the single-cell measurement of drug accumulation using an integrated microfluidic chip

Circulating tumor cells (CTCs) are found in the blood of patients with cancer. Although these cells are rare, they can provide useful information for chemotherapy. However, isolation of these rare cells from blood is technically challenging because they are small in numbers. An integrated microfluidic chip, dubbed as CTC chip, was designed and fabricated for conducting tumor cell isolation. As CTCs usually show multidrug resistance (MDR), the effect of MDR inhibitors on chemotherapeutic drug accumulation in the isolated single tumor cell is measured. As a model of CTC isolation, human prostate tumor cells were mixed with mouse blood cells and the labelfree isolation of the tumor cells was conducted based on cell size difference. The major advantages of the CTC chip are the ability for fast cell isolation, followed by multiple rounds of single-cell measurements, suggesting a potential assay for detecting the drug responses based on the liquid biopsy of cancer patients.

Learning with symmetric label noise: The importance of being unhinged

Convex potential minimisation is the de facto approach to binary classification. However, Long and Servedio [2008] proved that under symmetric label noise (SLN), minimisation of any convex potential over a linear function class can result in classification performance equivalent to random guessing. This ostensibly shows that convex losses are not SLN-robust. In this paper, we propose a convex, classification-calibrated loss and prove that it is SLN-robust. The loss avoids the Long and Servedio [2008] result by virtue of being negatively unbounded. The loss is a modification of the hinge loss, where one does not clamp at zero; hence, we call it the unhinged loss. We show that the optimal unhinged solution is equivalent to that of a strongly regularised SVM, and is the limiting solution for any convex potential; this implies that strong l2 regularisation makes most standard learners SLN-robust. Experiments confirm the unhinged loss’ SLN-robustness.

Using multi-label classification for acoustic pattern detection and assisting bird species surveys

Acoustics is a rich source of environmental information that can reflect the ecological dynamics. To deal with the escalating acoustic data, a variety of automated classification techniques have been used for acoustic patterns or scene recognition, including urban soundscapes such as streets and restaurants; and natural soundscapes such as raining and thundering. It is common to classify acoustic patterns under the assumption that a single type of soundscapes present in an audio clip. This assumption is reasonable for some carefully selected audios. However, only few experiments have been focused on classifying simultaneous acoustic patterns in long-duration recordings. This paper proposes a binary relevance based multi-label classification approach to recognise simultaneous acoustic patterns in one-minute audio clips. By utilising acoustic indices as global features and multilayer perceptron as a base classifier, we achieve good classification performance on in-the-field data. Compared with single-label classification, multi-label classification approach provides more detailed information about the distributions of various acoustic patterns in long-duration recordings. These results will merit further biodiversity investigations, such as bird species surveys.

Multitask learning without label correspondences

We propose an algorithm to perform multitask learning where each task has potentially distinct label sets and label correspondences are not readily available. This is in contrast with existing methods which either assume that the label sets shared by different tasks are the same or that there exists a label mapping oracle. Our method directly maximizes the mutual information among the labels, and we show that the resulting objective function can be efficiently optimized using existing algorithms. Our proposed approach has a direct application for data integration with different label spaces, such as integrating Yahoo! and DMOZ web directories.

A matter of life and death: sociomateriality, information systems and critical care

Sociomateriality has been attracting growing attention in the Organization Studies and Information Systems literatures since 2007, with more than 140 journal articles now referring to the concept. Over 80 percent of these articles have been published since January 2011 and almost all cite the work of Orlikowski (2007, 2010; Orlikowski and Scott 2008) as the source of the concept. Only a few, however, address all of the notions that Orlikowski suggests are entailed in sociomateriality, namely materiality, inseparability, relationality, performativity, and practices, with many employing the concept quite selectively. The contribution of sociomateriality to these literatures is, therefore, still unclear. Drawing on evidence from an ongoing study of the adoption of a computer-based clinical information system in a hospital critical care unit, this paper explores whether the notions, individually and collectively, offer a distinctive and coherent account of the relationship between the social and the material that may be useful in Information Systems research. It is argued that if sociomateriality is to be more than simply a label for research employing a number of loosely related existing theoretical approaches, then studies employing the concept need to pay greater attention to the notions entailed in it and to differences in their interpretation.

Label-free Analysis of Conformational Dynamics and Molecular Interaction of Biomolecules by Vis-NIR Metasensor

Analysis of binding recognition and conformation of biomolecules is of paramount important in understanding of their vital functions in complex biological systems. By enabling sub-wavelength light localization and strong local field enhancement, plasmonic biosensors have become dominant tools used for such analysis owing to their label-free and real-time attributes1,2. However, the plasmonic biosensors are not well-suited to provide information regarding conformation or chemical fingerprint of biomolecules. Here, we show that plasmonic metamaterials, consisting of periodic arrays of artificial split-ring resonators (SRRs)3, can enable capabilities of both sensing and fingerprinting of biomolecules. We demonstrate that by engineering geometry of individual SRRs, localized surface plasmon resonance (LSPR) frequency of the metamaterials could be tuned to visible-near infrared regimes (Vis-NIR) such that they possess high local field enhancement for surface-enhanced Raman scattering spectroscopy (SERS). This will provide the basis for the development of a dual mode label-free conformational-resolving and quantitative detection platform. We present here the ability of each sensing mode to independently detect binding adsorption and to identify different conformational states of Guanine (G)-rich DNA monolayers in different environment milieu. Also shown is the use of the nanosensor for fingerprinting and detection of Arginine-Glycine-Glycine (RGG) peptide binding to the G-quadruplex aptamer. The dual-mode nanosensor will significantly contribute to unraveling the complexes of the conformational dynamics of biomolecules as well as to improving specificity of biodetection assays that the conventional, population-averaged plasmonic biosensors cannot achieve.