ppxscal/embedding_network huggingface dataset:
Two-stage vector quantization-pyramidal lattice vector quantization and application to speech LSP coding
Authors: Jianping Pan
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 02 (1996)

Motivated by two-stage vector quantization-(spherical) lattice vector quantization introduced by Pan and Fischer (1995), two-stage vector quantization-pyramidal lattice vector quantization (VQ-PLVQ) is proposed that has a lower computational requirement and a slightly superior encoding performance. The complexity of VQ-PLVQ is further reduced by introducing tree-structures into the first-stage VQ. It is found that the efficiency of tree-searching depends on source distributions. Tree-structured VQ-PLVQ provides a performance very close to VQ-PLVQ for sources with memory. Then, these two quantisation schemes are applied to encoding of speech line spectrum pair parameters. Tree-structured VQ-PLVQ is an attractive approach that achieves an outstanding performance for the spectral distortion of 1 dB as well as a significant reduction of the implementation complexity. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Segmentation of news videos based on audio-video information
Authors: Massimo De Santo, Gennaro Percannella, Carlo Sansone, Mario Vento
Venue: Pattern Analysis Applications (2007)

In this paper, we propose an innovative architecture to segment a news video into the so-called &#x201c;stories&#x201d; by both using the included video and audio information. Segmentation of news into stories is one of the key issues for achieving efficient treatment of news-based digital libraries. While the relevance of this research problem is widely recognized in the scientific community, we are in presence of a few established solutions in the field. In our approach, the segmentation is performed in two steps: first, shots are classified by combining three different anchor shot detection algorithms using video information only. Then, the shot classification is improved by using a novel anchor shot detection method based on features extracted from the audio track. Tests on a large database confirm that the proposed system outperforms each single video-based method as well as their combination.
A note on large-buffer asymptotics for generalized processor sharing with Gaussian inputs
Authors: Krzysztof Dębicki, Michel Mandjes
Venue: Queueing Systems: Theory and Applications (2007)

In a previous study by D¿bicki and van Uitert (Queueing Syst. 54, 111---120, 2006) logarithmic large-buffer asymptotics were derived for a two-class generalized processor sharing system with Gaussian inputs, for three of the four possible scenarios. In this note we show how the large-buffer asymptotics for the remaining fourth regime follow from a recently derived result for tandem systems. We also provide a heuristic interpretation of the result.
CU FOREX: a bilingual spoken dialog system for foreign exchange enquiries
Authors: H. M. Meng
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 02 (2000)

This paper reports on the design, development and evaluation of a bilingual telephone-based spoken language system for foreign exchange inquiries-the CU FOREX system. The telephone-based system supports Cantonese and English in a single spoken language interface to access real-time foreign exchange information. The specific domain covers information on the exchange rates between foreign currencies, as well as deposit interest rates of various time durations for a specified currency. Overall our system achieves a performance of 0.95 (kappa-statistic), with a typical transaction duration of 2 minutes on average.
Discriminative mixture weight estimation for large Gaussian mixture models
Authors: F. Beaufays
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 01 (1999)

This paper describes a new approach to acoustic modeling for large vocabulary continuous speech recognition (LVCSR) systems. Each phone is modeled with a large Gaussian mixture model (GMM) whose context-dependent mixture weights are estimated with a sentence-level discriminative training criterion. The estimation problem is cast in a neural network framework, which enables the incorporation of the appropriate constraints on the mixture weight vectors, and allows a straight-forward training procedure, based on steepest descent. Experiments conducted on the Callhome-English and Switchboard databases show a significant improvement of the acoustic model performance, and a somewhat lesser improvement with the combined acoustic and language models.
Improving the Performance of Online Auctions Through Server-side Activity-based Caching
Authors: Daniel A. Menascé, Vasudeva Akula
Venue: World Wide Web (2007)

Online auction sites have very specific workloads and user behavior characteristics. Previous studies on workload characterization conducted by the authors showed that (1) bidding activity on auctions increases considerably after 90% of an auction's life time has elapsed, (2) a very large percentage of auctions have a relatively low number of bids and bidders and a very small percentage of auctions have a high number of bids and bidders, (3) prices rise very fast after an auction has lasted more than 90% of its life time. Thus, if bidders are not able to successfully bid at the very last moments of an auction because of site overload, the final price may not be as high as it could be and sellers, and consequently the auction site, may lose revenue. In this paper, we propose server-side caching strategies in which cache placement and replacement policies are based on auction-related parameters such as number of bids placed or percent remaining time till closing time. A main-memory auction cache at the application server can be used to reduce accesses to the back-end database server. Trace-based simulations were used to evaluate these caching strategies in terms of cache hit ratio and cache efficiency. The performance characteristics of the best policies were then evaluated through experiments conducted on a benchmark online auction system.
POST: a secure, resilient, cooperative messaging system
Authors: Alan Mislove, Ansley Post, Charles Reis, Paul Willmann, Peter Druschel, Dan S. Wallach, Xavier Bonnaire, Pierre Sens, Jean-Michel Busca, Luciana Arantes-Bezerra
Venue: Proceedings of the 9th conference on Hot Topics in Operating Systems - Volume 9 (2003)

POST is a decentralized messaging infrastructure that supports a wide range of collaborative applications, including electronic mail, instant messaging, chat, news, shared calendars and whiteboards. POST is highly resilient, secure, scalable and does not rely on dedicated servers. Instead, POST is built upon a peer-to-peer (p2p) overlay network, consisting of participants' desktop computers. POST offers three simple and general services: (i) secure, single-copy message storage, (ii) metadata based on single-writer logs, and (iii) event notification. We sketch POST's basic messaging infrastructure and show how POST can be used to construct a co-operative, secure email service called ePOST.
Extension and complexity reduction of TwinVQ audio coder
Authors: T. Moriya
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 02 (1996)

This paper proposes two novel techniques for twinVQ (transform domain weighted interleave VQ) high-quality audio coding scheme for rates lower than 64 kbit/s. One is an extension of the weighted interleave technique to the time and input channel domains as well as the frequency domain. The other is an efficient representation scheme of the spectral envelope by means of a interpolated square root LPC (linear predictive coding) spectrum.
Relationship of homework complexity to quiz scores
Authors: E. W. Thomas
Venue: Proceedings of the Frontiers in Education Conference,1997. on 27th Annual Conference. Teaching and Learning in an Era of Change. - Volume 01 (1997)

We demonstrate that the performance of students in an Introductory Physics course, a major stumbling block for engineers, may be improved by a homework regime involving complex, multiple step problems. In introductory courses the work done out of class, or "homework" represents the principal method of training students in the manipulation of class material. In a standard Introductory Physics course for Engineers the homework problems are typically short, and involve a single application of a single concept; we have demonstrated that this encourages memorization of formulae. We have examined whether the use of complex multiple step homework problems might improve student performance. A group of "complex" homework problems were devised for an Introductory Physics course. Student performance was measured on standard tests where a number of the problems had an extensive past history with which we could compare. We also assess changes in performance by using the technique of discriminant analysis which predicts student performance on the basis of historical records. Training with the "complex" problems raised student performance of the whole class by about half a letter grade and reduced the proportion of unsatisfactory grades by one-half. The use of "complex" problems for training purposes enhances the long term performance of students who we would normally expect to attain lower levels of grades.
Continuous Mandarin speech recognition using hierarchical recurrent neural networks
Authors: Yuan-Fu Liao
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 06 (1996)

An ANN-based continuous Mandarin base-syllable recognition system is proposed. It adopts a hybrid approach to combine an HRNN with a Viterbi search. The HRNN is taken at a front-end processor and responsible for calculating discrimination scores for all 411 base-syllables. The Viterbi search is then followed to find out the best base-syllable sequence with highest score as the recognized output. Experimental results showed that the proposed system outperforms the conventional HMM method on both the recognition accuracy and the computational complexity. The system can also be further modified to reduce the computational complexity while retaining the recognition accuracy almost be ungraded.
An engineering skills and design course for sophomores with seniors as mentors
Authors: J. C. Sutton
Venue: Proceedings of the Frontiers in Education Conference, on 1995. Proceedings., 1995 - Volume 02 (1995)

In the Electrical and Computer Engineering (ECE) Department at North Carolina State University, an experimental, elective course was offered to sophomores entering the department in the fall semester of 1994. The course was designed to provide these students with resources that would help them be better prepared for the demands of the ECE curriculum, to give them a better understanding of engineering practice, and to afford an opportunity for fun and excitement in their engineering education. The course responsibilities were shared by ECE faculty and senior students. The seniors taught time management, team building, and communication skills to the sophomores. The faculty and seniors shared responsibility for teaching simple circuit design, circuit building, creativity, and documentation. The faculty presented engineering career options, conceptual design, and prototyping. The participating sophomores gave the course very high ratings. The students' progress will be evaluated against a control group throughout their academic careers at NC State. The senior instructors were excellent peer role models and provided the sophomores with a perspective beyond that offered by the faculty. The senior mentors also gained a great deal from their teaching experience and used this experience to advantage in job interviews. The course is being taught again in the fall semester of 1995. After that semester we anticipate proposing the course to the curriculum committee for adoption as a required course.
The role of pre-mrna secondary structure in gene splicing in saccharomyces cerevisiae
Authors: Sanja Rogic
Venue:  (2006)

The process of gene splicing, which involves the excision of introns from a pre-mRNA and joining of exons into mature mRNA is one of the essential steps in protein production. Although this process has been extensively studied, it is still not clear how the splice sites are accurately identified and correctly paired across the intron. It is currently believed that identification is accomplished through base-pairing interactions between the splice sites and the spliceosomal snRNAs. However, the relatively conserved sequences at the splice sites are often indistinguishable from similar sequences that are not involved in splicing. This suggests that not only sequence but other features of pre-mRNA may play a role in splicing. A number of authors have studied the effects of pre-mRNA secondary structure on splicing, but these studies are usually limited to one or a small number of genes, and therefore the conclusions are usually gene-specific. This thesis aims to complement previous studies of the role of pre-mRNA secondary structure in splicing by performing a comprehensive computational study of structural characteristics of Saccharomyces cerevisiae introns and their possible role in pre-mRNA splicing. We identify long-range interactions in the secondary structures of all long introns that effectively shorten the distance between the donor site and the branchpoint sequence. The shortened distances are distributed similarly to the branchpoint distances in short yeast introns, which are presumed to be optimal for splicing, and very different from the corresponding distances in random and exonic sequences. We show that in the majority of cases, these stems are conserved among closely related yeast species. Furthermore, we formulate a model of structural requirements for efficient splicing of yeast introns that explains previous splicing studies of the RP51B intron. We also test our model by laboratory experiments, which verify our computational predictions. Finally, we use different computational approaches to identify any structural context at the boundaries or within yeast introns. Our study reveals statistically significant biases, which we use to train machine learning classifiers to distinguish between real and pseudo splice sites.
Reuse in system-level stimuli-generation
Authors: Y. Katz, I. Jaeger, R. Emek, Y. Lichtenstein
Venue: Proceedings of the High-Level Design Validation and Test Workshop, 2005. on Tenth IEEE International (2005)

This paper reports on the verification models of twelve systems including servers and advanced processors. We focus on system-level stimuli generation and study reuse in subsequent system models. The paper describes our modeling framework, where systems are modeled mainly by declarative constructs with some procedural code. Separate test specifications are used to direct stimuli generation, but are not studied in this paper. We find that a high level of white-box reuse reduces costs and allows starting the verification process early. This result reflects gradual evolution of the systems we study and the effectiveness of the declarative modeling scheme. We discuss the possible influence of libraries of system-level constructs on reuse in languages such 'e' Vera, and SystemVerilog.
Ontology-based Management Systems for the Next Generation Services: State-of-the-Art
Authors: Imen Grida Ben Yahia, Emmanuel Bertin, Noel Crespi
Venue: Proceedings of the Third International Conference on Networking and Services (2007)

Next Generation Networks (NGN) introduces a great emphasis on creating innovative telecommunications services that are rapidly deployed and tied to users need. Telecom operators and Service Providers are therefore facing important challenges to manage the overloaded data of the user preferences, the customized services and the whole service delivery chain. This is mainly due to the lack of standardization and common vocabulary, which strongly hinder information exchange and communication between information systems. Ontologies, which capture the semantics of information from various sources and giving them a concise, uniform and declarative description, have gained significant interests in research activities and industry. This paper is an analysis of ontologies usefulness to answer the NGN management challenges. Hence how ontologies may be used to improve Telecom Operators information systems in the NGN context. Keywords: ontology, Enterprise Information System, Next Generation Networks, Next Generation Services (NGS), service delivery.
Metadata update performance in file systems
Authors: Gregory R. Ganger, Yale N. Patt
Venue: Proceedings of the 1st USENIX conference on Operating Systems Design and Implementation (1994)

Structural changes, such as file creation and block allocation, have consistently been identified as file system performance problems in many user environments. We compare several implementations that maintain metadata integrity in the event of a system failure but do not require changes to the on-disk structures. In one set of schemes, the file system uses asynchronous writes and passes ordering requirements to the disk scheduler. These scheduler-enforced ordering schemes outperform the conventional approach (synchronous writes) by more than 30 percent for metadata update intensive benchmarks, but are suboptimal mainly due to their inability to safely use delayed writes when ordering is required. We therefore introduce soft updates, an implementation that asymptotically approaches memory-based file system performance (within 5 percent) while providing stronger integrity and security guarantees than most UNIX file systems. For metadata update in-tensive benchmarks, this improves performance by more than a factor of two when compared to the conventional approach.
Identification and Localization of Data Types within Large-Scale File Systems
Authors: Robert F. Erbacher, John Mulholland
Venue: Proceedings of the Second International Workshop on Systematic Approaches to Digital Forensic Engineering (2007)

This research examines the application of statistical analysis techniques for the identification of data types embedded within a file to assist analysts with the location of data, potentially relevant to criminal activity. The results show that the statistical analysis can effectively aid identification of the types of data embedded in a file and the approximate location of these data types. This analysis identifies component data types, irrespective of the type of file being analyzed. When applied, this technique will allow analysts to more effectively and efficiently locate relevant data on a hard drive, especially on today's particularly large hard drives.
An end-to-end process for cancer identification from images of lung tissue
Authors: Zhongfei (Mark) Zhang
Venue:  (2006)

The purpose of this study was to develop a prototype for a non-interactive, computer-based second opinion diagnostic tool that could read microscope images of lung tissue and classify the tissue sample as normal or cancerous. This problem can be broken down into three areas: segmentation, feature extraction and measurement, and classification. This study introduces a kernel-based extension of fuzzy c-means to provide a coarse initial segmentation, with heuristically-based mechanisms to improve the accuracy of the segmentation. The segmented image is then processed to extract and quantify features. Finally, the measured features are used by a Support Vector Machine (SVM) to classify the tissue sample. The performance of this approach was tested using a training data set of 83 images, and an independent validation data set of 79 images, all collected at the Moffitt Cancer Center and Research Institute. These images represent a wide variety of normal lung tissue samples, as well as multiple types of lung cancer. The process developed was able to correctly classify 67% of the images in the validation set with a Receiver Operating Characteristic (ROC) curve area (AZ) of up to 0.704. When using only the images of normal tissue and a single type of cancer, the process was able to achieve up to 81% accuracy with a ROC AZ of 0.806.
Engineering a BPEL orchestration engine as a multi-agent system
Authors: Mirko Viroli, Enrico Denti, Alessandro Ricci
Venue: Science of Computer Programming (2007)

The BPEL language is currently the primary candidate for standardising Web Services orchestration. BPEL specifications are meant to be run by BPEL orchestration engines, which are therefore crucial components of today's business-to-business infrastructures, carrying the burden of dynamically composing existing services. In this paper, we present the design of a BPEL orchestration engine based on a multi-agent system: while the basic BPEL activities are autonomously executed by agents, workflow aspects are realised by the mediation of ReSpecT tuple centres, a coordination model extending Linda with the ability of declaratively programming the tuple space behaviour. Our architecture separates the interaction, correlation, and workflow concerns into clearly identified tiers. In particular, we identify the workflow tier as the one encapsulating the core and most critical behaviour of the engine: due to its intrinsic complexity, we tackle its design formally. We introduce a core algebraic language of BPEL dealing with its workflow-related aspects, and provide it with a semantics based on a mapping into a net specification, modelling the dependencies between the activities to be executed by the engine. This mapping plays the role of a formal design, since it directly leads to an implementation of the workflow tier in the orchestration engine.
Combining Meta-Heuristics to Solve the Rook Problem
Authors: Camelia-M. Pintea, Camelia Chira, D. Dumitrescu
Venue: Proceedings of the Eighth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (2006)

The combination of various meta-heuristics to solve NP-hard problems has great potential to produce good results. Ant algorithms and Multi-Agent System are proposed to solve a chess problem. The problem is about how to place n rooks on a chessboard so that they are all mutually non-attacking. The introduced algorithms produce reasonable results and have several advantages. A combination between the two meta-heuristics is presented and some possible crossover improvements of the proposed algorithms are suggested.