ppxscal/embedding_network huggingface dataset:
A lattice-based approach to query-by-example spoken document retrieval
Authors: Tee Kiah Chia, Khe Chai Sim, Haizhou Li, Hwee Tou Ng
Venue: Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval (2008)

Recent efforts on the task of spoken document retrieval (SDR) have made use of speech lattices: speech lattices contain information about alternative speech transcription hypotheses other than the 1-best transcripts, and this information can improve retrieval accuracy by overcoming recognition errors present in the 1-best transcription. In this paper, we look at using lattices for the query-by-example spoken document retrieval task - retrieving documents from a speech corpus, where the queries are themselves in the form of complete spoken documents (query exemplars). We extend a previously proposed method for SDR with short queries to the query-by-example task. Specifically, we use a retrieval method based on statistical modeling: we compute expected word counts from document and query lattices, estimate statistical models from these counts, and compute relevance scores as divergences between these models. Experimental results on a speech corpus of conversational English show that the use of statistics from lattices for both documents and query exemplars results in better retrieval accuracy than using only 1-best transcripts for either documents, or queries, or both. In addition, we investigate the effect of stop word removal which further improves retrieval accuracy. To our knowledge, our work is the first to have used a lattice-based approach to query-by-example spoken document retrieval.
Microsoft Word 2007 Advanced Quick Reference Guide
Authors: Beezix Inc
Venue:  (2007)

Laminated quick reference guide showing step-by-step instructions and shortcuts for how to use advanced features of Microsoft Office Word 2007. The following topics are covered: Using Styles and Formatting; Character, Paragraph, and Linked Styles; Applying a Style; Creating a Style; Displaying the Styles Pane; Modifying Styles; Deleting a Style or Formatting; Selecting All Text with Same Style, Turning Off/On Showing Formatting as Styles; Importing Styles; Adding Styles to the Default Style List; Heading Numbering, Creating Index & Table of Contents; Marking Index Entries Manually and with a Word List; Footnotes and Endnotes; Embedding Excel Objects; Section Breaks; Changing Page Setup in a Section; Changing Starting Page Number; Changing Headers & Footers within a Document, Outlining; Comparing Documents Side by Side; Creating and Using Bookmarks; Referring to the Page a Bookmark is On; Templates; Restricting Formatting. This guide is suitable as a training handout, or simply an easy to use reference guide, for any type of user.
Characterization of polycrystalline 3C-SiC thin film diodes for extreme environment applications
Authors: Gwiy-Sang Chung, Jeong-Hak Ahn
Venue: Microelectronic Engineering (2008)

This paper describes the fabrication and characteristics of polycrystalline (poly) 3C-SiC thin film diodes for extreme environment applications, in which the poly 3C-SiC thin film was deposited onto oxidized Si wafers by APCVD using HMDS as a precursor. In this work, the optimized growth temperature and HMDS flow rate were 1100^oC and 8sccm, respectively. A Schottky diode with a Au, Al/poly 3C-SiC/SiO"2/Si(n-type) structure was fabricated and its threshold voltage (V"d), breakdown voltage, thickness of depletion layer, and doping concentration (N"D) values were measured as 0.84V, over 140V, 61nm, and 2.7x10^1^9cm^3, respectively. To produce good ohmic contact, Al/3C-SiC were annealed at 300, 400, and 500^oC for 30min under a vacuum of 5.0x10^-^6Torr. The obtained p-n junction diode fabricated by poly 3C-SiC had similar characteristics to a single 3C-SiC p-n junction diode.
A neuro-fuzzy based forecasting approach for rush order control applications
Authors: Wen-Pai Wang, Ze Chen
Venue: Expert Systems with Applications: An International Journal (2008)

This paper proposes an adaptive neuro-fuzzy inference system (ANFIS) and a KERNEL System to solve the problem of predicting rush orders for regulating the capacity reservation mechanism in advance. The adopted approaches generalize the association rules among rush orders, as well as to forecast product items, quantities and the occasion of the contingent rush orders via learning from the sales data of an actual electronic manufacturing firm. Especially, we compare results with the traditional regression analysis and obtain preferable forecasts. In sum the overall forecasting correctness is 83% by ANFIS which is superior to regression manner with 63%. Preliminary results on the application of the proposed methods are also reported. It is expected to offer managers to refer to arrange the reserved capacity and to construct a robust schedule in anticipation.
Reduction of Complexity via Operatorial Parametric Formulations for Some Nonlinear Dynamic Problems of Biology
Authors: Emmanuel Montseny, Andrei Doncescu
Venue: Proceedings of the 22nd International Conference on Advanced Information Networking and Applications - Workshops (2008)

Dynamic models most of the time involve differential equations, which are "time-local". Such models can also be considered "globally", that is in the sense of "trajectories" in the "space-time" state. Up to adapted concepts, such a different interpretation reveals itself more flexible, namely because it allows to use Various operatorial transformations whose time-local equivalent in general cannot exist and from which can result some remarkable properties. Namely, we introduce a principle of parametrizing for dynamic equations by means of such transformations. We then consider an example of bioreactor model for which we highlight how suitable time-nonlocal transformations can sometimes be used to efficiently solve some nonlinear control problems.
Design patterns for monitoring adaptive ULS systems
Authors: Andres J. Ramirez, Betty H.C. Cheng
Venue: Proceedings of the 2nd international workshop on Ultra-large-scale software-intensive systems (2008)

As applications grow in size and complexity, and computing infrastructure continues to evolve, it is increasingly difficult to build a system that satisfies all requirements and constraints that might arise during its lifetime. As a result, there is increasing need for the software to adapt to new requirements and environmental conditions after the software has been deployed. Autonomic computing refers to a system that monitors itself based on high-level objectives and achieves, with minimal human guidance, self-management, and self-conguration. While progress has been made recently in applying rigorous development techniques to autonomic software, self-monitoring has received little attention. This paper describes a preliminary investigation into identifying design patterns associated with the self-monitoring aspects of autonomic computing systems.
Application MTTFE vs. Platform MTBF: A Fresh Perspective on System Reliability and Application Throughput for Computations at Scale
Authors: J. T. Daly, L. A. Pritchett-Sheats, S. E. Michalak
Venue: Proceedings of the 2008 Eighth IEEE International Symposium on Cluster Computing and the Grid (2008)

When running on HPC systems characterized by component failure rates high enough to impact productivity, it becomes important to consider the impact of those failures on individual applications. Typically, this is done by assuming that the mean time between failures (MTBF) for hardware and software components on the system is equivalent to the mean time to fatal error (MTTFE) for an application running on that system. In addition, one commonly applies the rule of thumb estimate that application MTTFE scales as the inverse of the number of nodes used to run the application, so that running on half as many nodes increases MTTFE by a factor of two. However, this estimate does not take into account the fact that a non-trivial fraction of failures affect multiple compute nodes, so a single component failure has the potential to cause multiple application fatal errors. In the work that follows, a new model for application MTTFE is derived based on the impact of multi-component failures and their potential to terminate multiple applications.
Losses due to quantum size effects in thermionic currents in III-V MQW solar cells
Authors: Argyrios C. Varonides, Robert A. Spalletta
Venue: Proceedings of the 9th International Conference on Circuits (2005)

Quantum wells in solar cells are important probes for the study of free carrier behavior. Photogenerated carriers in quantum wells contribute to transport and hence current only via thermionic escape, and once they are in the conduction band continuum, they can be treated as propagated plane waves subject to constraints of the crystal lattice. It is pointed out that neighboring quantum wells act as scattering centers causing back-scattering and trapping (standing waves). On the other hand, thermionically escaping electrons comprise traveling quantum mechanical waves liable to trapping and backscattering due to nearest neighbor quantum wells in a multi-layer photovoltaic device. Such losses due to scattering and trapping are taken into consideration in this communication, where transmitted waves are calculated after scattering and trapping take place. In such lossy multiquantum well "lines", computations show that only 16 to 25% of thermionically escaping carriers get through, and the rest remain trapped in quantum wells and/or reflect back to neighboring unit cells. For 6nm-width (GaAs-AlGaAs) undoped quantum wells, illuminated at room temperature, current densities are expected to drop from 0.4 mA/cm2/qu. well (with recombination losses but with no scattering) down to a range between 0.064 to 0.100 mA/cm2/qu. well (with both recombination losses and overall scattering included in this study).
Construction of speculative optimization algorithms
Authors: A. A. Belevantsev, S. S. Gaisaryan, V. P. Ivannikov
Venue: Programming and Computing Software (2008)

In modern processors, instructions to perform operations are often produced before it becomes known that this is required. Such an expedient, which is called speculative execution, helps to reveal parallelism at the instruction level. In the EPIC architectures, the speculative execution is completely controlled by the compiler, which makes it possible to avoid using complex hardware mechanisms for supporting speculative instruction production. Moreover, the idea of the speculative execution can be used by the compiler in machine-independent optimizations. The paper describes a scheme of construction of the speculative optimization that is based on the selection of properties of the control flow and data flow that are important from the optimization standpoint and on the estimation of the probabilities of their fulfillment. The probabilities found are used for searching and constructing advantageous speculative and bookkeeping transformations. For optimizations that include only speculative movements of instructions upwards along the control flow graph, on the basis of the suggested scheme, a method has been developed that includes algorithms for finding probabilities of data and control dependences, for estimating benefit of speculative movements, and for constructing a recovery code. On the basis of this method, an algorithm for the speculative scheduling of instructions for the Intel Itanium architecture has been developed and implemented. Specific features of its implementation and experimental results are described.
Revised Loss Bounds for the Set Covering Machine and Sample-Compression Loss Bounds for Imbalanced Data
Authors: Zakria Hussain, François Laviolette, Mario Marchand, John Shawe-Taylor, Spencer Charles Brubaker, Matthew D. Mullin
Venue: The Journal of Machine Learning Research (2007)

Marchand and Shawe-Taylor (2002) have proposed a loss bound for the set covering machine that has the property to depend on the observed fraction of positive examples and on what the classifier achieves on the positive training examples. We show that this loss bound is incorrect. We then propose a loss bound, valid for any sample-compression learning algorithm (including the set covering machine), that depends on the observed fraction of positive examples and on what the classifier achieves on them. We also compare numerically the loss bound proposed in this paper with the incorrect bound, the original SCM bound and a recently proposed loss bound of Marchand and Sokolova (2005) (which does not depend on the observed fraction of positive examples) and show that the latter loss bounds can be substantially larger than the new bound in the presence of imbalanced misclassifications.
Exploring the performance impact of stripe size on network attached storage systems
Authors: Yuhui Deng, Frank Wang
Venue: Journal of Systems Architecture: the EUROMICRO Journal (2008)

Network attached storage (NAS) integrates redundant array of independent disks (RAID) subsystem that consists of multiple disk drives to aggregate storage capacity, I/O performance and reliability based on data striping and distribution. Traditionally, the stripe size is an important parameter that has a great influence on the RAID subsystem performance, whereas the performance impact has been changed due to the development of disk drive technologies and some I/O optimization methods. Based on disk drive access time, this paper constructs a performance analysis model to exploit the impact of some I/O optimization approaches including sub-commands combination, storage interface augment, and I/O scatter/gather on the stripe size of NAS. The analysis results and experimental validation indicate that due to the evolution of hardware and software, the stripe size has a negligible performance impact on NAS when the disk drives involved are organized in a RAID0 pattern.
The commonality of vector generation techniques
Authors: Scott Davidson
Venue: IEEE Design Test (2008)

The value of test compression is that it has allowed us to move along a continuum between the extremes of ATPG and logic BIST, and has enabled us to find the right combination of test size, test coverage, and test time for a given situation. The basic similarity among different DFT techniques should make us feel confident that we are on the right track in our drive for efficient test compression.
Stochastic vector mapping-based feature enhancement using prior-models and model adaptation for noisy speech recognition
Authors: Chia-Hsin Hsieh, Chung-Hsien Wu
Venue: Speech Communication (2008)

This paper presents an approach to feature enhancement for noisy speech recognition. Three prior-models are introduced to characterize clean speech, noise and noisy speech, respectively. Sequential noise estimation is employed for prior-model construction based on noise-normalized stochastic vector mapping. Therefore, feature enhancement can work without stereo training data and manual tagging of background noise type based on the auto-clustering on the estimated noise data. Environment model adaptation is also adopted to reduce the mismatch between training data and test data. For the evaluation on the AURORA2 database, the experimental results indicate that a 9.6% relative reduction in digit error rate for multi-condition training and a 3.5% relative reduction in digit error rate for clean speech training were achieved without stereo training data compared to the SPLICE-based approach. For MATBN Mandarin broadcast news database with multi-condition training, a 13% relative reduction in syllable error rate for anchor speech, a 12% relative reduction in syllable error rate for field reporter speech and a 7% relative reduction in syllable error rate for interviewee speech were obtained compared to the MCE-based approach.
On the Feasibility of Obtaining a Globally Optimal Floorplanning for an L-shaped Layout Problem
Authors: Tsu-Shuan Chang, Manish Kumar, Teng S. Moh, Chung-Li Tseng
Venue: Proceedings of the 9th international symposium on Quality Electronic Design (2008)

The floorplanning for an L-shaped layout problem can be formulated as a global optimization problem. In this paper, we will explore the feasibility of finding a globally optimal solution for such a problem by using an approximation technique. The problem formulation is first explained through a simple example with two L-shaped cells. Then, it is illustrated that the solution obtained by such an approximation can be indeed in the neighborhood of a global optimal solution. Numerical examples are used to demonstrate the possibility of using such an approach to obtain a global optimal solution.
A really temporal logic
Authors: R. Alur, T. A. Henzinger
Venue: Proceedings of the 30th Annual Symposium on Foundations of Computer Science (1989)

A real-time temporal logic for the specification of reactive systems is introduced. The novel feature of the logic, TPTL, is the adoption of temporal operators as quantifiers over time variables; every modality binds a variable to the time(s) it refers to. TPTL is demonstrated to be both a natural specification language and a suitable formalism for verification and synthesis. A tableau-based decision procedure and model-checking algorithm for TPTL are presented. Several generalizations of TPTL are shown to be highly undecidable.
Semantic text similarity using corpus-based word similarity and string similarity
Authors: Aminul Islam, Diana Inkpen
Venue: ACM Transactions on Knowledge Discovery from Data (TKDD) (2008)

We present a method for measuring the semantic similarity of texts using a corpus-based measure of semantic word similarity and a normalized and modified version of the Longest Common Subsequence (LCS) string matching algorithm. Existing methods for computing text similarity have focused mainly on either large documents or individual words. We focus on computing the similarity between two sentences or two short paragraphs. The proposed method can be exploited in a variety of applications involving textual knowledge representation and knowledge discovery. Evaluation results on two different data sets show that our method outperforms several competing methods.
Term clouds as surrogates for user generated speech
Authors: Manos Tsagkias, Martha Larson, Maarten de Rijke
Venue: Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval (2008)

User generated spoken audio remains a challenge for Automatic Speech Recognition (ASR) technology and content-based audio surrogates derived from ASR-transcripts must be error robust. An investigation of the use of term clouds as surrogates for podcasts demonstrates that ASR term clouds closely approximate term clouds derived from human-generated transcripts across a range of cloud sizes. A user study confirms the conclusion that ASR-clouds are viable surrogates for depicting the content of podcasts.
Describing function analysis of second-order sliding mode observers
Authors: I. BoIko, M. I. Castellanos, L. Fridman
Venue: International Journal of Systems Science (2007)

The second-order sliding mode observer dynamics are analyzed in the frequency domain. The so-called super-twisting algorithm is utilized for generating the second-order sliding mode in the observer dynamical system. The frequency response of the observer dynamics is obtained and used as a characteristic of the observer. The analysis proposed is based on the describing function method and the concept of the equivalent gains of nonlinear functions of the super-twisting algorithm.
Parallel FFT Algorithms on Network-on-Chips
Authors: Jun Ho Bahn, Jungsook Yang, Nader Bagherzadeh
Venue: Proceedings of the Fifth International Conference on Information Technology: New Generations (2008)

This paper presents several parallel FFT algorithms with different degree of communication overhead for multiprocessors in Network-on-Chip (NoC) environment. Three different methods of parallel FFT are presented. One is the reference parallel FFT for comparison, and the other two with well-distributed computation as well as reduced communication overhead. By evenly distributing parallel computation tasks which uses data locality, the execution time for completing each stage of FFT can be reduced. Moreover, by optimizing data exchanges we minimize the communication overhead. Depending on the communication regularity, one can select appropriate parallel FFT algorithm. By using the simulation results of our cycle-accurate SystemC NoC model with a parameterizable 2-D mesh architecture, and the performance analysis in time as well as complexity, our proposed algorithms are shown to outperform other parallel FFT algorithm or high-speed DSP implementations.
Sampling cube: a framework for statistical olap over sampling data
Authors: Xiaolei Li, Jiawei Han, Zhijun Yin, Jae-Gil Lee, Yizhou Sun
Venue: Proceedings of the 2008 ACM SIGMOD international conference on Management of data (2008)

Sampling is a popular method of data collection when it is impossible or too costly to reach the entire population. For example, television show ratings in the United States are gathered from a sample of roughly 5,000 households. To use the results effectively, the samples are further partitioned in a multidimensional space based on multiple attribute values. This naturally leads to the desirability of OLAP (Online Analytical Processing) over sampling data. However, unlike traditional data, sampling data is inherently uncertain, i.e., not representing the full data in the population. Thus, it is desirable to return not only query results but also the confidence intervals indicating the reliability of the results. Moreover, a certain segment in a multidimensional space may contain none or too few samples. This requires some additional analysis to return trustable results. In this paper we propose a Sampling Cube framework, which efficiently calculates confidence intervals for any multidimensional query and uses the OLAP structure to group similar segments to increase sampling size when needed. Further, to handle high dimensional data, a Sampling Cube Shell method is proposed to effectively reduce the storage requirement while still preserving query result quality.
Reflections on the Teaching of Programming: Methods and Implementations, 1 edition
Authors: Jens Bennedsen, Michael E. Caspersen, Michael Klling
Venue: Lecture Notes In Computer Science (2008)

This state-of-the-art survey, reflecting on the teaching of programming, has been written by a group of primarily Scandinavian researchers and educators with special interest and experience in the subject of programming. The 14 chapters - contributed by 24 authors - present practical experience gathered in the process of teaching programming and associated with computing education research work. Special emphasis is placed on practical advice and concrete suggestions. The authors are all members of the Scandinavian Pedagogy of Programming Network (SPoP), and bring together a diverse body of experiences from the Nordic countries. The 14 chapters of the book have been carefully written and edited to present 4 coherent units on issues in introductory programming courses, object-oriented programming, teaching software engineering issues, and assessment. Each of these individual parts has its own detailed introduction. The topics addressed span a wide range of problems and solutions associated with the teaching of programming such as introductory programming courses, exposition of the programming process, apprentice-based learning, functional programming first, problem-based learning, the use of on-line tutorials, object-oriented programming and Java, the BlueJ environment to introduce programming, model-driven programming as opposed to the prevailing language-driven approach, teaching software engineering, testing, extreme programming, frameworks, feedback and assessment, active learning, technology-based individual feedback, and mini project programming exams.