ppxscal/embedding_network huggingface dataset:
Trellis-coded residual vector quantization: its geometrical advantages and application to image coding
Authors: M. A. U. Khan
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 05 (2000)

Residual vector quantization (RVQ), also known as multistage vector quantization, is investigated in the context of quantization cell shapes and is found to produce oblong cell shapes and suboptimal point densities. The oblong cell shapes are partially responsible for the performance degradation of RVQ compared with vector quantization (VQ). In an attempt to realize better cell shapes, a trellis-coded RVQ (TCRVQ) is suggested and is shown to provide optimal point densities and square cell shapes. In order to improve the performance of TCRVQ, an entropy-constrained TCRVQ (EC-TCRVQ) is designed and implemented for non-uniformly distributed sources. The simulation results indicate a performance improvement of 1.5 dB for EC-TCRVQ over entropy-constrained trellis-coded VQ. For an image coding application, we have developed conditional EC-TCRVQ, by employing adjacent vector conditioning in addition to residual vector conditioning. The simulation tests show that the 8/spl times/8 CEC-TCRVQ outperforms other predictive and trellis-based VQ schemes.
Microphone-array speech recognition via incremental map training
Authors: J. E. Adcock
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 02 (1996)

For a hidden Markov model (HMM) based speech recognition system it is desirable to combine enhancement of the acoustical signal and statistical representation of model parameters, ensuring both a high quality speech signal and an appropriately trained HMM. In this paper the incremental variant of maximum a posteriori (MAP) estimation is used to adjust the parameters of a talker-independent HMM-based speech recognition system to accurately recognize speech data acquired with a microphone-array. The approach is novel for a microphone-array speech recognition task in that a robust talker-independent model is derived from a baseline system using a relatively small amount of data for training. The results show that (1) ILIAP training significantly improves recognition performance compared to the baseline, and (2) beamforming signal enhancement outperforms single-channel enhancement before and after the adaptive MAP training.
Effects of rain attenuation on wireless transmission of frame relay traffic
Authors: B. Fong, P. B. Rapajic, G. Y. Hong
Venue: Proceedings of the The 8th International Conference on Communication Systems - Volume 02 (2002)

The link availability of outdoor radio systems is often affected by atmospheric conditions such as rain and snow. The effects of rainfall on wireless transmission are particularly noticeable at data rate in the magnitude of megabits per second. As the rate of rainfall increases, more disruption is caused to the outdoor link. This paper presents a statistical analysis and discusses modeling of the effects of rain attenuation on wideband radio channels used by local multipoint distribution service (LMDS) systems. Our results provide an insight into the effects of rainfall on coverage area. The possible implications for optimum data throughput are outlined.
Solving Dynamic and Irregular Problems on SIMD Architectures with Runtime Support
Authors: WEI SHU, MIN-YOU WU
Venue: Proceedings of the 1993 International Conference on Parallel Processing - Volume 02 (1993)

One of the essential problems in parallel computing is: can STMD machines handle asynchronous problems? Thas is a dificult, unsolved problem because of the mismatch between asynchronous problems and SIMD archtiectures. We propose a soluiaon to let SIMD machines handle general asynchronous problems. Our approach is to implement a runtime support system which can run MIMD-like software on SIMD hardware. Substantial performance has been obtained on CM-2 and CM-5.
Using self-directed work group concepts for successful classroom group experiences
Authors: J. Smith David
Venue: Proceedings of the 28th Annual Frontiers in Education - Volume 01 (1998)

Global markets and sophisticated information technology have increased the pace of competition. To succeed in this new environment, firms are evolving their organizational structure from purely hierarchical to more team-oriented groups. As a result, university recruiters want engineering and business graduates to perform well in groups. Unfortunately, there is some evidence that universities have not been able to meet this goal (Davis et al. 1997 and Siegel and Sorensen 1994). To provide their students with productive group experiences, the authors studied the characteristics of successful group environments and now create similar situations in their classrooms. Patterning their groups after self-directed work groups (SDWGs), they have developed and refined a structure that allows students to control long-term group activities, including task organization, compensation and problem resolution (Zuidema and Kleiner 1994). They have used these forms in a range of computer science classes and upper-division accounting and CIS classes. They present the structure they impose and anecdotal results from these experiences.
Performance of non-data aided carrier offset estimation for non-circular transmissions through frequency-selective channels
Authors: P. Ciblat
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 05 (2000)

We consider blind estimation of the carrier frequency offset of a linearly modulated non-circular transmission through an unknown frequency selective channel. A frequency estimator is developed based on the unique conjugate cyclic frequency of the received signal that equals twice the frequency offset. We establish consistency and asymptotic normality of the frequency estimator, and calculate its asymptotic variance in closed form. This expression enables performance analysis of the proposed frequency offset estimator as a function of the number of estimated cyclic correlation coefficients used. Numerical simulations show that estimation and compensation of the carrier frequency offset in the presence of an unknown frequency selective channel can be performed with no loss in performance relative to methods where the channel is pre-equalized first and the frequency offset is compensated afterwards.
Optimal capacity planning in stochastic loss networks with time-varying workloads
Authors: Sandeep Bhadra, Yingdong Lu, Mark S. Squillante
Venue: Proceedings of the 2007 ACM SIGMETRICS international conference on Measurement and modeling of computer systems (2007)

We consider a capacity planning optimization problem in a general theoretical framework that extends the classical Erlang loss modeland related stochastic loss networks to support time-varying workloads. The time horizon consists of a sequence of coarse time intervals, each of which involves a stochastic loss network under a fixed multi-class workload that can change in a general manner from one interval to the next. The optimization problem consists of determining the capacities for each time interval that maximize a utility function over the entire time horizon, finite or infinite, where rewards gained from servicing customers are offset by penalties associated with deploying capacities in an interval and with changing capacities among intervals. We derive a state-dependent optimal policy within the context of a particular limiting regime of the optimization problem, and we prove this solution to be a symptotically optimal. Then, under fairly mild conditions, we prove that a similar structural property holds for the optimal solution of the original stochastic optimization problem, and we show how the optimal capacities comprising this solution can be efficiently computed.
Localized delimited release: combining the what and where dimensions of information release
Authors: Aslan Askarov, Andrei Sabelfeld
Venue: Proceedings of the 2007 workshop on Programming languages and analysis for security (2007)

Information release (or declassification) policies are the key challenge for language-based information security. Although much progress has been made, different approaches to information release tend to address different aspects of information release. In a recent classification, these aspects are referred to as what, who, where, and when dimensions of declassification. In order to avoid information laundering, it is important to combine defense along the different dimensions. As a step in this direction, this paper presents a combination of what and where information release policies. Moreover, we show that a minor modification of a security type system from the literature (which was designed for treating the what dimension) in fact enforces the combination of what and where policies
Collaboration and the importance for novices in learning java computer programming
Authors: Carole A. Bagley, C. Candace Chou
Venue: Proceedings of the 12th annual SIGCSE conference on Innovation and technology in computer science education (2007)

The authors propose that a correlation exists between collaboration and success by novices when learning computer programming. Research in an introductory course was conducted that focused on answering several questions: At what time in their learning java programming and algorithmic problem solving, would a student benefit best by collaboration? At what time during the problem solving process would the learner benefit greatest by collaboration? Would the student benefit greater by collaborating with 1 student in the class, a group, or an expert mentor/coach? What cognitive and affective strategies are used during various types of collaboration? Does collaboration increase problem solving performance by females. This research will advance fundamental knowledge of teaching and learning of computer science. It will further the understanding of problem solving and strategies used in learning computer programming and whether collaboration is important.
Improved speech recognition via speaker stress directed classification
Authors: B. D. Womak
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 01 (1996)

Speech production variations due to perceptually induced stress contribute significantly to reduced speech processing performance. This study proposes an algorithm for estimation of the degree of perceptually induced stress. It is suggested that the resulting stress score could be integrated into speech processing algorithms to improve robustness in adverse conditions. First, results from a previous study motivate selection of a targeted set of speech features across phoneme and stress groups to improve stress classification performance. Analysis of articulatory, excitation, and cepstral based features is conducted using a previously established stressed speech database (SUSAS). Targeted feature sets are selected across ten stress conditions (including Apache helicopter, angry, clear, Lombard effect, loud, etc.). Next, an improved targeted feature stress classification system is developed and evaluated achieving rates of 91.01%. Finally, application of stress classification is incorporated into a stress directed speech recognition system. An improvement of +10.14% and +15.43% over conventionally trained neutral and multi-style trained recognizers is demonstrated using the new stress directed recognition system.
An adaptive microphone array with good sound quality using auxiliary fixed beamformers and its DSP implementation
Authors: O. Hoshuyama
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 02 (1999)

This paper presents an adaptive microphone array using two auxiliary fixed beamformers for good sound quality. One auxiliary fixed beamformer is introduced in the target signal path to avoid suppression of high-frequency components in the total output. The other auxiliary fixed beamformer is used for adaptation-mode control to eliminate the hysteresis in the relationship between the signal direction and sensitivity. Both auxiliary fixed beamformers bring about good sound quality, which improve intelligibility in speech communications and speech recognition rate. The proposed microphone array is implemented on a DSP system, which demonstrates flat frequency response and less hysteresis in its directivity pattern.
Modelling magnetic material images with simultaneous autoregressions
Authors: Changjing Shang
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 06 (1999)

This paper presents a novel application of simultaneous autoregressive models to the synthesis of magnetic material images. The effects of using either symmetric or non-symmetric neighbour sets upon the visual and statistical properties of the resulting synthesised images are investigated. The use of a neighbour set whose shape corresponds to the orientations and coarseness of the texture allows the generation of synthetic images of good quality. Also, the size of such a neighbour set is usually smaller than that of the symmetric set required to reach similar modelling accuracy, thereby minimising the computational effort.
JIT instrumentation: a novel approach to dynamically instrument operating systems
Authors: Marek Olszewski, Keir Mierle, Adam Czajkowski, Angela Demke Brown
Venue: ACM SIGOPS Operating Systems Review (2007)

As modern operating systems become more complex, understanding their inner workings is increasingly difficult. Dynamic kernel instrumentation is a well established method of obtaining insight into the workings of an OS, with applications including debugging, profiling and monitoring, and security auditing. To date, all dynamic instrumentation systems for operating systems follow the probe-based instrumentation paradigm. While efficient on fixed-length instruction set architectures, probes are extremely expensive on variable-length ISAs such as the popular Intel x86 and AMD x86-64. We propose using just-in-time (JIT) instrumentation to overcome this problem. While common in user space, JIT instrumentation has not until now been attempted in kernel space. In this work, we show the feasibility and desirability of kernel-based JIT instrumentation for operating systems with our novel prototype, implemented as a Linux kernel module. The prototype is fully SMP capable. We evaluate our prototype against the popular Kprobes Linux instrumentation tool. Our prototype outperforms Kprobes, at both micro and macro levels, by orders of magnitude when applying medium- and fine-grained instrumentation.
Unsupervised minor prototype detection using an adaptive population partitioning algorithm
Authors: Jung-Hsien Chiang, Zong-Xian Yin
Venue: Pattern Recognition (2007)

This paper presents a new partitioning algorithm, designated as the Adaptive C-Populations (ACP) clustering algorithm, capable of identifying natural subgroups and influential minor prototypes in an unlabeled dataset. In contrast to traditional Fuzzy C-Means clustering algorithms, which partition the whole dataset equally, adaptive clustering algorithms, such as that presented in this study, identify the natural subgroups in unlabeled datasets. In this paper, data points within a small, dense region located at a relatively large distance from any of the major cluster centers are considered to form a minor prototype. The aim of ACP is to adaptively separate these isolated minor clusters from the major clusters in the dataset. The study commences by introducing the mathematical model of the proposed ACP algorithm and demonstrates its convergence to a stable solution. The ability of ACP to detect minor prototypes is confirmed via its application to the clustering of three different datasets with different sizes and characteristics.
Interrupt and low-level programming support for expanding the application domain of statically-scheduled horizontal-microcoded architectures in embedded systems
Authors: Mehrdad Reshadi, Daniel Gajski
Venue: Proceedings of the conference on Design, automation and test in Europe (2007)

The increasing role of software in the embedded systems has made processor an important component in these systems. However, to meet the tight constraints of embedded application, it is often required to customize the processor for the application. Customizing instruction-based processors is difficult and very challenging. Design approaches based on statically-scheduled horizontal-microcoded architectures have been proposed to simplify the architecture customization. In these approaches, first the datapath is specified by the designer, and then the operations of the datapath are extracted automatically. Since the operations are statically scheduled in these architectures (i) low-level programming using assembly is impossible or very tedious; and (ii) execution of programs cannot be interrupted arbitrarily. In this paper, we address the above problems. We show how to efficiently handle interrupts in such architectures and also propose an elegant way of controlling low-level hardware resources in a general way in C language. We also show that after adding interrupt and low-level programming we could use the above architectural style in a multi-core system to implement a complete MP3 decoder that can process 122 frames per second while the standard requirement is 38 frames per seconds.
A generalized adaptive code acquisition scheme using backpropagation network in DS/SS systems
Authors: Takki Yu, Sangchul Han, Daesik Hong, Changeon Kang
Venue: Proceedings of the The 8th International Conference on Communication Systems - Volume 01 (2002)

A generalized adaptive code acquisition scheme is proposed by using a multi-layer structure. The backpropagation network (BPN) is used in modeling the multilayer system. The timing offset of the received code can be detected by combining the hidden layer weights after an adaptation period. The characteristics of mean squared error (MSE) and weight distribution for the generalized system are analyzed, and the effects of input and hidden nodes are investigated. The generalized system provides a high detection probability and flexibility in acquisition system design.
A Hermite spectral method for the computation of homoclinic orbits and associated functionals
Authors: Valeriy R. Korostyshevskiy, Thomas Wanner
Venue: Journal of Computational and Applied Mathematics (2007)

We present a spectral method for the computation of homoclinic orbits in ordinary differential equations. The method is based on Hermite-Fourier expansions of the complete homoclinic solution and exhibits exponential convergence. In addition, our method can be used to approximate nonlinear functionals which depend on the complete homoclinic solution. This is demonstrated using examples from phase separation dynamics and metastability.
Utility-Based Bandwidth Allocation for Triple-Play Services
Authors: Changbin Liu, Lei Shi, Bin Liu
Venue: Proceedings of the Fourth European Conference on Universal Multiservice Networks (2007)

It is expected that, in near future, the multi-class traffic previously in Public Switched Telephone network (PSTN), cable television network and IP network will be multiplexed at backbone and carried by the converged Next-Generation Network (NGN). A pragmatic challenge in facilitating NGN is how to schedule traffic and allocate bandwidth among the triple-play services, namely voice (VoIP), video (IPTV) and data. Different from traditional strict-priority based scheduling intensively used in industry, in this paper, we try to discuss this issue from the objective of Network Utility Maximization (NUM). We first investigate the characteristics of most existing traffic classes and explicitly formulate their utilities to be the function of occupied bandwidth. After that, a novel scheduling scheme to achieve NUM is derived using Lagrange method with KKT conditions. Numerical results under two network scenarios are calculated. Both of them reveal the unique nature of this scheduling, compared with strict-priority scheduling, still highest priority is provided for VoIP traffic, however, no strict priority should be given to IPTV traffic since it will conflict with NUM objective. We hope our results will shed lights on the evolvement towards the converged network.
An optimization algorithm based on chaotic behavior and fractal nature
Authors: Mohammad Saleh Tavazoei, Mohammad Haeri
Venue: Journal of Computational and Applied Mathematics (2007)

In this paper, we propose a new optimization technique by modifying a chaos optimization algorithm (COA) based on the fractal theory. We first implement the weighted gradient direction-based chaos optimization in which the chaotic property is used to determine the initial choice of the optimization parameters both in the starting step and in the mutations applied when a convergence to local minima occurred. The algorithm is then improved by introducing a method to determine the optimal step size. This method is based on the fact that the sensitive dependence on the initial condition of a root finding technique (such as the Newton-Raphson search technique) has a fractal nature. From all roots (step sizes) found by the implemented technique, the one that most minimizes the cost function is employed in each iteration. Numerical simulation results are presented to evaluate the performance of the proposed algorithm.
On the application of the global matched filter to DOA estimation with uniform circular arrays
Authors: J.-J. Fuchs
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 05 (2000)

The problem of estimating the direction of arrivals (azimuths) of narrow-band sources impinging on a uniform circular array is considered. We present a method that uses as input the values of a small number of uniformly spaced beams and apply a model-fitting approach taking into account the statistical properties of the beams. The approach called the "global matched filter" fits simultaneously to the observations all the elements needed to explain them. It chooses among all the potential representations the one with minimal energy. The method drastically improves upon the conventional beamformer and has a performance comparable to the best high resolution techniques. It further applies when the number of sources exceeds the number of sensors, a situation that cannot be handled by standard high resolution techniques.
Adaptive filter banks for lossless image compression
Authors: R. Oktem
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 03 (2001)

A subband decomposition based lossless image compression algorithm based on adaptive methods is described. The decomposition is achieved by a two-channel adaptive filter bank. The resulting coefficients are lossy coded first, and then the residual error between the lossy and error free coefficients are compressed. The locations and the magnitudes of the nonzero coefficients are encoded separately by a hierarchical enumerative coding method. The locations of the nonzero coefficients in child bands are predicted from those in the parent band. The proposed compression algorithm, on the average, provides higher compression ratios than the state-of-the-art methods.