857 research outputs found
Research on the Improvement of Cargo Service Quality of XM Airlines
No full textThis study takes XM Airlines' baggage check-in service as the object, and based on the SERVQUAL model and analytic hierarchy process, constructs a service quality evaluation system to systematically evaluate its service status. The main content includes the following: Firstly, based on the theoretical framework, a basic overview and analysis of the operational status of XM Airlines are conducted to understand the main problems currently existing, and a targeted evaluation system is constructed for the existing problems. Secondly, based on the completed evaluation system, the Analytic Hierarchy Process is used to establish a corresponding mathematical model. The systematic problem of evaluating the quality of freight services is decomposed into various factors for quantitative analysis, and the importance weights of each factor are calculated and ranked. Thirdly, analyze and summarize the analysis data of the second stage, design and distribute survey questionnaires, establish relevant evaluation criteria, construct a matrix to calculate weights, obtain the final evaluation results, and based on this, provide targeted suggestions for XM Airlines to improve service quality, further discuss and prospect.
Research has found that the overall quality of XM Airlines baggage check-in is at a satisfactory level, but there is still room for improvement in terms of reliability, security, and tangibility. Specific issues include damaged or lost luggage, cumbersome compensation processes, and delayed updates to luggage status. In response to the above issues, it is recommended that XMAirlines enhance its existing intelligent technology, optimize service processes, strengthen resource and facility management to effectively improve luggage check-in efficiency and accuracy, enhance passenger satisfaction and trust, and thus enhance the airline's market competitiveness
Sequential Path Entanglement for Quantum Metrology
No full textPath entanglement is a key resource for quantum metrology. Using path-entangled states, the standard quantum limit can be beaten, and the Heisenberg limit can be achieved. However, the preparation and detection of such states scales unfavourably with the number of photons. Here we introduce sequential path entanglement, in which photons are distributed across distinct time bins with arbitrary separation, as a resource for quantum metrology. We demonstrate a scheme for converting polarization Greenberger-Horne-Zeilinger entanglement into sequential path entanglement. We observe the same enhanced phase resolution expected for conventional path entanglement, independent of the delay between consecutive photons. Sequential path entanglement can be prepared comparably easily from polarization entanglement, can be detected without using photon-number-resolving detectors, and enables novel applications
Biodegradable polymer blends of poly(3-hydroxybutyrate) and hydroxyethyl cellulose acetate
No full textPolymer38246001-6007POLM
Biodegradable polymer blends of poly(3-hydroxybutyrate) and poly(DL-lactide)-co-poly(ethylene glycol)
No full textJournal of Applied Polymer Science65101849-1856JAPN
CANONICAL ABERRATION THEORY IN ELECTROMAGNETIC MULTIPOLES
No full textIn a 2N-pole electromagnetic system, defining the electron optical Hamiltonian function, we have derived both general algebraic expressions (arbitrary N) and special numerical formulas (N = 3,4,5,6,7) for different aberrations from lower to higher order (i.e., the order of N - 1, N + 1, 2N - 3, 2N - 1, 3N - 5). The so-called canonical aberration theory in electromagnetic multipoles has thus been developed, which allows us to deduce angular dependencies of different aberrations and to examine the possibility for spherical correction of a round lens by using multipoles.Physics, AppliedSCI(E)0ARTICLE125968-59756
Combining multiple precision-boosted classifiers for indoor-outdoor scene classification
No full textAlong with the progress of the content-based image retrieval research and the development of the MPEG-7 XM feature descriptors, there has been an increasing research interest on object recognition and semantics extraction from images and videos. In this paper, we revisit an old problem of indoor versus outdoor scene classification. By introducing a precision-boosted combination scheme of multiple classifiers trained on several global and regional feature descriptors, our experiment has led to better results compared with conventional approaches.UnpublishedA.W.M. Smeulders, M. Worring, and S. Santini and A. Gupta, “Content-based Image Retrieval of the end of the early years”. IEEE Trans on PAMI, Vol. 22, No. 12, 2000, pp. 1349-1380.
J.M. Corridoni, A.D. Bimbo, and P. Pala, “Image Retrieval by Colour Semantics”, Multimedia System, Vol. 7, No. 3, 1999, pp.175-183.
B.S. Manjunath, J. Ohm and V. Vinod, “Colour and Texture Descriptors”, IEEE Trans on Circuits and Systems for Video Technology, Vol. 11, No. 6, 2001, pp.703-715.
M. Bober, “MPEG-7 Visual Shape Descriptors”, IEEE Trans. on Circuits and Systems for Video Technology, Vol. 11, 2001, pp.716-719.
M. Szummer and R.W. Picard,“Indoor-Outdoor Image Classification,” in Proc. IEEE International Workshop on Content-based Access of Image and Video Databases, 1998, pp.42-51.
M. Soysal and A.A. Alatan, “Combining MPEG-7 Based Visual Experts For Reaching Semantics”, in Proc. of VLBV03, Madrid, 2003.
J. Li and J.Z. Wang, “Automatic Linguistic Indexing of Pictures by A Statistical Modelling Approach”, IEEE Trans. on PAMI, vol. 25, No. 9, 2003, pp.1075-1088.
MPEG-7 eXperimentation Model (XM), Institute for Integrated Systems, Munich University of Technology, Germany. URL http://www.lis.ei.tum.de/research/bv/topics/mmdb/e mpeg7.html.
Y. Deng and B.S. Manjunath, “Unsupervised segmentation of colour-texture regions in images and video”, IEEE Trans. on PAMI, Vol. 23, 2001, pp.800-810.
J. Kittler, Mohamad Hatef et al., “On Combination Classifiers”, IEEE Trans on PAMI, Vol. 20, No. 3, 1998, pp.226-238
Combining multiple precision-boosted classifiers for indoor-outdoor scene classification
No full textAlong with the progress of the content-based image retrieval research and the development of the MPEG-7 XM feature descriptors, there has been an increasing research interest on object recognition and semantics extraction from images and videos. In this paper, we revisit an old problem of indoor versus outdoor scene classification. By introducing a precision-boosted combination scheme of multiple classifiers trained on several global and regional feature descriptors, our experiment has led to better results compared with conventional approaches.UnpublishedA.W.M. Smeulders, M. Worring, and S. Santini and A. Gupta, “Content-based Image Retrieval of the end of the early years”. IEEE Trans on PAMI, Vol. 22, No. 12, 2000, pp. 1349-1380.
J.M. Corridoni, A.D. Bimbo, and P. Pala, “Image Retrieval by Colour Semantics”, Multimedia System, Vol. 7, No. 3, 1999, pp.175-183.
B.S. Manjunath, J. Ohm and V. Vinod, “Colour and Texture Descriptors”, IEEE Trans on Circuits and Systems for Video Technology, Vol. 11, No. 6, 2001, pp.703-715.
M. Bober, “MPEG-7 Visual Shape Descriptors”, IEEE Trans. on Circuits and Systems for Video Technology, Vol. 11, 2001, pp.716-719.
M. Szummer and R.W. Picard,“Indoor-Outdoor Image Classification,” in Proc. IEEE International Workshop on Content-based Access of Image and Video Databases, 1998, pp.42-51.
M. Soysal and A.A. Alatan, “Combining MPEG-7 Based Visual Experts For Reaching Semantics”, in Proc. of VLBV03, Madrid, 2003.
J. Li and J.Z. Wang, “Automatic Linguistic Indexing of Pictures by A Statistical Modelling Approach”, IEEE Trans. on PAMI, vol. 25, No. 9, 2003, pp.1075-1088.
MPEG-7 eXperimentation Model (XM), Institute for Integrated Systems, Munich University of Technology, Germany. URL http://www.lis.ei.tum.de/research/bv/topics/mmdb/e mpeg7.html.
Y. Deng and B.S. Manjunath, “Unsupervised segmentation of colour-texture regions in images and video”, IEEE Trans. on PAMI, Vol. 23, 2001, pp.800-810.
J. Kittler, Mohamad Hatef et al., “On Combination Classifiers”, IEEE Trans on PAMI, Vol. 20, No. 3, 1998, pp.226-238
Tunable visual color filter using microfluidic grating
No full textAuthor name used in this publication: X. M. Zhang2010-2011 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishedVoR allowe
Combining textual and visual information processing for interactive video retrieval: SCHEMA's participation in TRECVID 2004
No full textIn this paper, the two different applications based on the Schema Reference System that were developed by the SCHEMA NoE for participation to the search task of TRECVID 2004 are illustrated. The first application, named ”Schema-Text”, is an interactive retrieval application that employs only textual information while the second one, named ”Schema-XM”, is an extension of the former, employing algorithms and
methods for combining textual, visual and higher level information. Two runs for each application were submitted, I A 2 SCHEMA-Text 3, I A 2 SCHEMA-Text 4 for Schema-Text and I A 2 SCHEMA-XM 1, I A 2 SCHEMA-XM 2 for Schema-XM. The comparison of these two applications in terms of retrieval efficiency revealed that the combination of information from different data sources can provide higher efficiency for retrieval systems. Experimental testing additionally revealed that initially performing a text-based query and subsequently proceeding with visual similarity search using one of the returned relevant keyframes as an example image is a good scheme for combining visual and textual information
An approach for intelligent image collection navigation and semantic analysis
No full textWith the growing use of multimedia such as images and videos in industries as well as in our daily life, image retrieval has become a vital technology for users to consume the valuable multimedia resources effectively and efficiently. For example it is not easy to browse or search a large image collection. Content-based image retrieval has achieved limited success in multimedia asset management and rapid information retrieval based on low-level visual features. However, humans normally access multimedia assets by semantic concepts. There is a significant semantic gap existing between low-level visual features processed by machines and semantic concepts interpreted by humans. It is generally understood that the problem of image retrieval is still far from being solved. As indicated by literatures, image semantic analysis and visualisation are well known research areas to overcome this gap and to enhance the capability of content-based image retrieval systems.
This thesis proposes an approach for intelligent image collection navigation and semantic analysis to bridge the gap between visual features and semantics. Some of MPEG-7 colour and texture descriptors based on global and local visual features are selected as multiple representations of images, as they have been intensively and successfully evaluated in many of image retrieval experiments. Taking a pattern classification approach for image semantic analysis, two types of classifiers are designed according to the different characteristics of global and local visual features to classify images into the predefined classes. Combination classifications are investigated in this study. Leave-one-out cross-validation is employed to evaluate their performances using different visual features and combination schemes. In order to increase the impact of the classifiers with high precisions in the final classification decision, the precision-based combination rule that weights each classifier based on its precision in the combination of the results is proposed. For the visualisation of image collections, an intelligent image collection navigation system is developed by joining the SOM-based image visualisation based on visual feature spaces together with semantic concepts extracted from semantic analysis.
Experiments show that the proposed approach is successful in improving the accuracy of indoor and outdoor scenes classification and revealing image collection structure both in the visual feature spaces and on the semantics level. With further works on this study the system is able to assist users to develop automatic interpretations to the image collection and navigate and access images of interests much more easily.UnpublishedA.Vailaya, M, A, T. Figueiredo, et al. (2001). "Image classification for content-based
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