Beyond Short Snippets: Deep Networks for Video Classification

Convolutional neural networks (CNNs) have been extensively applied for image recognition problems giving state-of-the-art results on recognition, detection, segmentation and retrieval. In this work we propose and evaluate several deep neural network architectures to combine image information across a video over longer time periods than previously attempted. We propose two methods capable of handling full length videos. The first method explores various convolutional temporal feature pooling architectures, examining the various design choices which need to be made when adapting a CNN for this task. The second proposed method explicitly models the video as an ordered sequence of frames. For this purpose we employ a recurrent neural network that uses Long Short-Term Memory (LSTM) cells which are connected to the output of the underlying CNN. Our best networks exhibit significant performance improvements over previously published results on the Sports 1 million dataset (73.1% vs. 60.9%) and the UCF-101 datasets with (88.6% vs. 88.0%) and without additional optical flow information (82.6% vs. 72.8%)

Design Ltd.: Renovated Myths for the Development of Socially Embedded Technologies

This paper argues that traditional and mainstream mythologies, which have been continually told within the Information Technology domain among designers and advocators of conceptual modelling since the 1960s in different fields of computing sciences, could now be renovated or substituted in the mould of more recent discourses about performativity, complexity and end-user creativity that have been constructed across different fields in the meanwhile. In the paper, it is submitted that these discourses could motivate IT professionals in undertaking alternative approaches toward the co-construction of socio-technical systems, i.e., social settings where humans cooperate to reach common goals by means of mediating computational tools. The authors advocate further discussion about and consolidation of some concepts in design research, design practice and more generally Information Technology (IT) development, like those of: task-artifact entanglement, universatility (sic) of End-User Development (EUD) environments, bricolant/bricoleur end-user, logic of bricolage, maieuta-designers (sic), and laissez-faire method to socio-technical construction. Points backing these and similar concepts are made to promote further discussion on the need to rethink the main assumptions underlying IT design and development some fifty years later the coming of age of software and modern IT in the organizational domain.Comment: This is the peer-unreviewed of a manuscript that is to appear in D. Randall, K. Schmidt, & V. Wulf (Eds.), Designing Socially Embedded Technologies: A European Challenge (2013, forthcoming) with the title "Building Socially Embedded Technologies: Implications on Design" within an EUSSET editorial initiative (www.eusset.eu/

Alignment of human competencies with mobile technology and business strategy in women-led SMEs

Includes bibliographical references.Studies show that women entrepreneurs are constrained and faced with challenges that inhibit the growth and performance of their businesses. Such challenges include race and gender differences, inadequate education, family responsibilities, lack of access to capital and other socio-cultural factors. However, with their human competencies, mobile technology and the appropriate business strategy, women-led small and medium-sized Enterprises (SMEs) can steer their businesses to better performance. While the need for SMEs to align these three elements (human competencies, mobile technology and business strategy) has been suggested, there is limited knowledge on how SMEs can achieve this; no studies, to the author’s knowledge, have examined this in women-led SMEs. This study therefore sought to fill this gap by investigating how women-led SMEs can best align these three elements to enhance their business performance. In light of this, extensive literature review and theoretical work on the phenomenon was conducted. Given the existence of the interplay between these three elements (human competencies, mobile technology and business strategy), the study adopted the perspective of alignment as Gestalts as the most appropriate method in determining the best way women-led SMEs may align these three aspects

Turnaround of Indian Railways: A Critical Appraisal of Strategies and Processes

Indian Railways (IR), which was declared to be heading towards bankruptcy as per the Expert Group on Indian Railways in 2001, is today the second largest profit making Public Sector Undertaking after ONGC. The fund balance crossed Rs.12,000 crores in 2005-06, which had reached a low of just Rs.149 crores in 1990-2000. The total investment being planning for the eight-year time frame (2007-2015) is tentatively in the order of Rs.350,000 crores. This confidence is not only due to the rising trend of performance, but also due to the significant growth in the past two years. These two years coincided with Mr. Lalu Prasad being at the helm of affairs of the IR, having moved into his position on 23rd May, 2004. Railway officials called this as the ‘turnaround’ of IR. This paper attempts a diagnosis of the ‘turnaround,’ beginning with the question as to whether it really was a ‘turnaround’. This paper then carried out an analysis of the various determinants of the ‘turnaround’ related to goods, passenger and other operations. This is followed by a critical assessment of the strategies and key processes being the ‘turnaround’. Finally the sustainability of the ‘turnaround’ is explored.

Intent-aware search result diversification

Search result diversification has gained momentum as a way to tackle ambiguous queries. An effective approach to this problem is to explicitly model the possible aspects underlying a query, in order to maximise the estimated relevance of the retrieved documents with respect to the different aspects. However, such aspects themselves may represent information needs with rather distinct intents (e.g., informational or navigational). Hence, a diverse ranking could benefit from applying intent-aware retrieval models when estimating the relevance of documents to different aspects. In this paper, we propose to diversify the results retrieved for a given query, by learning the appropriateness of different retrieval models for each of the aspects underlying this query. Thorough experiments within the evaluation framework provided by the diversity task of the TREC 2009 and 2010 Web tracks show that the proposed approach can significantly improve state-of-the-art diversification approaches