ppxscal/embedding_network huggingface dataset:
A constrained adaptive diversity combiner for interference suppression in CDMA systems
Authors: J. B. Schodorf
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 05 (1996)

A multisensor interference cancellation scheme for CDMA communication systems is presented. The algorithm consists of constrained output power minimization at each sensor followed by optimal combining of the sensor outputs. Knowledge of the desired user's code is used to specify the constraint for minimizing the output power at each sensor of the array. If the codes (and timing) of other users (i.e., interferers) are known, they may be incorporated as additional constraints to improve receiver performance. Optimal combining of the individual sensor outputs is achieved by employing the LMS algorithm in tracking mode for the adaptation. The receiver is blind in the sense that only knowledge of the desired user's code (not the actual transmitted bit sequence) and associated timing is necessary. Algorithm performance results for Rayleigh fading channels are presented in the form of signal to interference-plus-noise ratios and bit error rate curves.
Localization of multiple sound sources based on a CSP analysis with a microphone array
Authors: T. Nishiura
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 02 (2000)

Accurate localization of multiple sound sources is indispensable for the microphone array-based high quality sound capture. For single sound source localization, the CSP (cross-power spectrum phase analysis) method has been proposed. The CSP method localizes a sound source as a crossing point of sound directions estimated using different microphone pairs. However, when localizing multiple sound sources, the CSP method has a problem that the localization accuracy is degraded due to cross-correlation among different sound sources. To solve this problem, this paper proposes a new method which suppresses the undesired cross-correlation by synchronous addition of CSP coefficients derived from multiple microphone pairs. Experiment results in a real room showed that the proposed method improves the localization accuracy when increasing the number of the synchronous addition.
E-ITRC Protocol with Long & Adjustable Range on Underwater Acoustic Sensor Network
Authors: Donghoon Kim, Yong-Man Cho, Changhwa Kim, Sangkyung Kim, Soo-Hyun Park, Tae-Won Kang
Venue: Proceedings of the 21st International Conference on Advanced Information Networking and Applications Workshops - Volume 02 (2007)

The underwater sensor network environment differs substantially from a terrestrial sensor network in the aspect of the communication medium so Acoustic communication is alternative, which is relatively very slow and narrow bandwidth compared with Radio Frequency. In this paper, we propose an underwater sensor network architecture and then present the essential routing algorithm focused on minimum response time as well as energy efficiency. The characteristic of our proposed underwater sensor network is that there are a long-range communication node on the surface of the water and adjustable transmission range on underwater nodes. The surface station equipped with solar panels may request queries to underwater sensor nodes with long-range transmission. In order to gather messages from underwater sensor node, we use underwater relay nodes in the midst of water using Energy efficiency & Innovative Time Reduction Communication (E-ITRC) protocol. Our proposed E-ITRC protocol can find the optimal path to save energy and minimize response time. The simulation results clearly show that our protocol is a fast, energy efficient and fault-tolerant method in an underwater environment.
K12 and the World Wide Web
Authors: S. A. Mengel
Venue: Proceedings of the Frontiers in Education Conference,1997. on 27th Annual Conference. Teaching and Learning in an Era of Change. - Volume 01 (1997)

K12 students who are the college students of tomorrow are growing in their sophistication with computers. As an example, K12 web pages show complex designs by the students that rival or surpass university web pages. The students are also very adept at searching the web for information. Since students are becoming more sophisticated with computers, higher education institutions will be able to take advantage of that sophistication and should track the progress of K12 web usage to understand how this increased sophistication will impact and improve college courses. They might also be able to exploit the web better to attract students to their institution or even particular subject areas. This paper can serve as a starting point to discover what is happening at the K12 level on the World Wide Web (WWW). It shows numerous resources for K12 including those for putting up school web pages, finding out about science experiments, going through museums, and communicating with students in other countries. It gives examples where K12 students along with their teachers are designing sophisticated web pages for others to learn about their school. In these examples, students put up original artwork, produce movies, or write about their school, and educators make their students' work a showcase or show their own creativity in projects they have their students do.
Dictionary-based English text compression using word endings
Authors: Jeehong Yang, Serap A. Savari
Venue: Proceedings of the 2007 Data Compression Conference (2007)

In this paper, we propose an dictionary-based English text compression algorithm; we name it Star Word Ending (StarWE) because of certain similarities to the StarNT algorithm. Furthermore, StarWE borrows techniques that are used in WRT such as EOL coding, punctuation mark modeling, and n-gram matching. The main difference between StarWE and StarNT is in the division of the external dictionary; StarWE divides it by word endings so that the compressor would be able to obtain some of the tag information.
Analytic problem solving methodology
Authors: D. Reamon
Venue: Proceedings of the 26th Annual Frontiers in Education - Volume 01 (1996)

This paper examines the largely ignored process of analytic problem solving. By applying learning theory to different problem-solving situations, we determine what factors contribute to a positive learning environment. An ideal environment includes facilities to observe the problem states simply and easily, and guidance in abstracting the observations into symbolic expressions.
Rethinking hardware support for network analysis and intrusion prevention
Authors: V. Paxson, K. Asanović, S. Dharmapurikar, J. Lockwood, R. Pang, R. Sommer, N. Weaver
Venue: Proceedings of the 1st USENIX Workshop on Hot Topics in Security (2006)

The performance pressures on implementing effective network security monitoring are growing fiercely due to rising traffic rates, the need to perform much more sophisticated forms of analysis, the requirement for inline processing, and the collapse of Moore's law for sequential processing. Given these growing pressures, we argue that it is time to fundamentally rethink the nature of using hardware to support network security analysis. Clearly, to do so we must leverage massively parallel computing elements, as only these can provide the necessary performance. The key, however, is to devise an abstraction of parallel processing that will allow us to expose the parallelism latent in semantically rich, stateful analysis algorithms; and that we can then further compile to hardware platforms with different capabilities.
Image-driven re-targeting and relighting of facial expressions
Authors: L. Zhang, Y. Wang, S. Wang, D. Samaras
Venue: Proceedings of the Computer Graphics International 2005 (2005)

Synthesis and re-targeting of facial expressions is central to facial animation and often involves significant manual work in order to achieve realistic expressions, due to the difficulty of capturing high quality expression data. Recent progress in dynamic 3-D scanning allows very accurate acquisition of dense point clouds of facial geometry and texture moving at video speeds. Often the new facial expressions need to be rendered in different environments where the illumination is different from the original capture conditions. In this paper we examine the problem of re-targeting captured facial motion under different illumination conditions when the information we have about the face we want to animate is minimal, a single input image. Given an input image of a face, a set of illumination example images (of other faces captured under different illumination) and a facial expression motion sequence, we aim to generate novel expression sequences of the input face under the lighting conditions in the illumination example images. The input image and illumination example images can be taken under arbitrary unknown lighting. In this paper, we propose two methods in which a 3D spherical harmonic morphable model (SHBMM) can generate images under new lighting conditions with remarkable quality even if only one single image under unknown lighting is available, not only for static poses but for dynamic sequences as well where the face is undergoing subtle high-detail motion.
Intelligent techniques for optimization and estimation
Authors: Mohamed A. El-Sharkawi, Deirdre R. Meldrum
Venue:  (2006)

Environmentally adaptive design of multistatic sonar systems in coastal environments is important because of the propagation medium impact on system performance. Complex underwater acoustic models allowing computation of sonar performance prediction have been developed. In this work, we develop intelligent optimization algorithms for solving the placement problems. The objective functions, derived from the sonar performance prediction model, are not analytically tractable. Therefore, standard mathematical programming techniques can not be applied without simplifying assumptions. Instead, we resort to stochastic approximate methods, especially a novel population-based metaheuristic algorithm, the particle swarm optimization (PSO). Population-based techniques are adept at finding near-optimal solutions for combinatorial optimization problems. Thanks to advances in computational power, they have been successfully applied to some challenging real-world optimization problems. Their wide acceptance is limited however because most real-world optimization problems present objective functions that are computationally intensive. In addition, the thousands of function evaluations required by this class of optimizers render their application impractical. Surrogate models and parallelization are commonly used to address that problem, but even the evaluation of these models can be time-consuming. Another limitation is the lack of guarantee in finding the optimal solution. The problem at hand, sonar sensor placement, is in the category of real-world optimization problems with expensive objective functions. Here we propose and develop computationally frugal methods based on PSO for solving coverage maximization problem. We then apply it to multi-objective placement problems. In the second part of our work, we present important contributions to the area of genomic signal processing and analysis. Specifically, we looked at the problem of quantitation, or estimation of initial concentration, using real-time Polymerase Chain Reaction (PCR). Quantitative estimation of genetic material is an important problem with applications in multiple fields from homeland security to clinical diagnostic or genomic research. Real-time PCR is one of the tools for solving this problem. Because of its simple basic principles, there has been a huge development of instrumentation to perform this reaction. On the analytical side, there exist multiple models to explain the reaction but none are accurate enough to completely model it. Using data generated by a high-throughput real-time PCR instrument we developed; the first of its kind to operate on single-digit microliter capillaries, we modeled reaction using artificial neural networks.
A New Method for Reducing the Revocation Delay in the Attribute Authentication
Authors: Yoshio KAKIZAKI, Hidekazu TSUJI
Venue: Proceedings of the The Second International Conference on Availability, Reliability and Security (2007)

There are a variety of certificates to prove the identity and the attribute on network. Public key certificate is used to prove the identity of the user. And attribute certificate is used to prove the attributes of the user. It is necessary to bind attribute certificate to public key certificate to prove the owner of the attributes because attribute certificate does not contain the identity information. Some attributes have the derivation relationship between attributes. Therefore, branch attributes should be revoked when origin attributes are revoked. It is necessary to do it at once. The naive method cannot show the relationship with derivation attributes directly. Therefore, the naive methods have the following problems. First, the relationship between attributes is not written into attribute certificate. Second, branch attribute certificate cannot be revoked at once when origin attributes are revoked. In this paper, we propose the method to shorten the revocation delay of attribute certificate with the relationship by using an attribute authentication method that can show the relationship between attributes. Our method makes it possible to invalidate branch attribute certificate at once when origin attribute certificate is revoked, and protects against illegal use of attribute certificate that use the time difference of revocation processing.
Linux-HA heartbeat system design
Authors: Alan Robertson
Venue: Proceedings of the 4th annual Linux Showcase & Conference - Volume 4 (2000)

One of the most commonly identified features which is felt to be necessary for LinuxTM to be considered "enterprise-ready" is High-Availability. High-Availability (HA) systems provide increased service availability through clustering techniques. HA clusters minimize availability interruptions by quickly switching services over from failed systems to working systems, providing the customer with an illusion of continuous availability. As such, high-availability features, are vital to mission-critical systems. Although there are many components to a high-availability system, two of the key components are heartbeat services and cluster communication services. Heartbeat services provide notification of when nodes are working, and when they fail. In the Linux-HA project, the heartbeat program provides these services and intracluster communication services. This paper describes the design of the heartbeat program which is part of the High-Availability Linux Project with particular emphasis on the rationales behind key design choices, and the results obtained.
Transparent Rendering of Tool Contact with Compliant Environments
Authors: Miguel A. Otaduy, Markus Gross
Venue: Proceedings of the Second Joint EuroHaptics Conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems (2007)

Transparent haptic rendering of the contact between a tool and its environment requires very frequent update of the contact forces acting on the tool. Given a rigid tool and a deformable environment, we define contact constraints by solving a constrained dynamic simulation problem, typ- ically at a low update rate. A generalized contact Jaco- bian defines velocities at the constraints given the velocity of the rigid tool. We define an inverse of the contact Jaco- bian that is dynamically consistent with the constraints and, once we know other forces acting on the rigid tool, it allows a fast update of the accumulated contact forces, and thereby highly transparent rendering.
A blind identification algorithm robust to order over estimation
Authors: H. Gazzah
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 05 (2000)

Active research in blind identification of single input multiple output (SIMO) channels has led to a variety of second order statistics based algorithms, mainly the subspace and the linear prediction approaches. The subspace algorithm shows good performance, although it requires exact knowledge of the channel order, which is not guaranteed by current order detection algorithms. The linear prediction algorithm is sensitive to observation noise while its robustness to channel order over estimation is only theoretical. We propose a new second order statistics based blind channel identification algorithm using a shifted version of the channel output covariance matrix. It proves to be truly robust to channel order over estimation i.e., able to estimate the channel impulse response when the assumed channel order is greater than the exact order and when channel output is corrupted by additive noise and observed over finite time duration. Moreover, the proposed algorithm shows clearly better performance than the linear prediction algorithm.
IDNs: Straightforward Technical Problem or Machiavellian Nightmare?
Authors: Greg Goth
Venue: IEEE Internet Computing (2007)

Internationalized domain names' arcane technical requirements have long served as a wedge issue for governments, organizations, and individuals dissatisfied with the Internet's governance structure.
Minimum risk annealing for training log-linear models
Authors: David A. Smith, Jason Eisner
Venue: Proceedings of the COLING/ACL on Main conference poster sessions (2006)

When training the parameters for a natural language system, one would prefer to minimize 1-best loss (error) on an evaluation set. Since the error surface for many natural language problems is piecewise constant and riddled with local minima, many systems instead optimize log-likelihood, which is conveniently differentiable and convex. We propose training instead to minimize the expected loss, or risk. We define this expectation using a probability distribution over hypotheses that we gradually sharpen (anneal) to focus on the 1-best hypothesis. Besides the linear loss functions used in previous work, we also describe techniques for optimizing nonlinear functions such as precision or the BLEU metric. We present experiments training log-linear combinations of models for dependency parsing and for machine translation. In machine translation, annealed minimum risk training achieves significant improvements in BLEU over standard minimum error training. We also show improvements in labeled dependency parsing.
Feedback-directed thread scheduling with memory considerations
Authors: Fengguang Song, Shirley Moore, Jack Dongarra
Venue: Proceedings of the 16th international symposium on High performance distributed computing (2007)

This paper describes a novel approach to generate an optimized schedule to run threads on distributed shared memory (DSM) systems. The approach relies upon a binary instrumentation tool to automatically acquire the memory sharingrelationship between user-level threads by analyzing their memory trace. We introduce the concept of Affinity Graph to model the relationship. Expensive I/O for large trace files is completely eliminated by using an online graph creation scheme. We apply the technique of hierarchical graph partitioning and thread reordering to the affinity graph to determine an optimal thread schedule. We have performed experiments on an SGI Altix system. The experimental results show that our approach is able to reduce the totalexecution time by 10% to 38% for a variety of applications through the maximization of the data reuse within a single processor, minimization of the data sharing between processors, and a good load balance.
Tutorial IND2A: Embedded Systems Design with Xilinx Virtex-5 Series FPGA
Authors: Parimal Patel
Venue: Proceedings of the 20th International Conference on VLSI Design held jointly with 6th International Conference: Embedded Systems (2007)

Embedded systems design is a hot application field which merges logic design and processor-based hardware development in a single or few chips solution. In recent years, embedded applications have emerged at a faster rate and used in every field of one can think of ranging from household products such as microwaves, to automotive products such as air bags sensing and control, to industrial robots which employ distributed processing and coordination. Various technologies have been used in the development of embedded systems; microcontroller, DSP processor, ASIC, and now FPGA. Embedded systems development involves hardware and software components development as they co-exist in such systems. The software is unique to a system and varies in complexity from system to system and application to application. This peculiar characteristic makes the system development unique and challenging. Typically, such system development involves another system on which design and development takes place. Field Programmable Gate Arrays (FPGA) from Xilinx, through generations of development, have enlarged applications area envelope. With the introduction of Virtex-II Pro, Xilinx entered embedded processing area. Through the rigorous development of supporting tools and introduction of Virtex-4, Xilinx positioned itself as a major player in the embedded applications area. In order to gain higher performance, Virtex-4 architecture was radically improved and Virtex-5, introduced in mid-April, pushed the envelope further. The trend is to improve silicon efficiency by porting widely used functions in hard core. Xilinx FPGA families carry hard core and soft core processors. The development kits provide hardware/software tools which facilitate implementation of functions, which are not yet realized, by embedding them as soft intellectual property in the FPGA fabric.
Adjoint LMS: an efficient alternative to the filtered-x LMS and multiple error LMS algorithms
Authors: E. A. Wan
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 03 (1996)

The Filtered-x LMS algorithm is currently the most popular method for adapting a filter when there exists a transfer function in the error path. Such instances arise, for example, in active control of sound and vibration. For multiple-input-multiple-output systems the Multiple Error LMS Algorithm is a generalization of Filtered-x LMS. The derivation of both algorithms rely on several assumptions, including linearity of the adaptive filter and error channel. Furthermore, in the Multiple Error LMS Algorithm the desirable order N computational complexity of LMS is lost, resulting in a prohibitive cost in certain DSP implementations. In this paper, we describe a new algorithm termed adjoint LMS which provides a simple alternative to the previously mentioned algorithms. In adjoint LMS, the error (rather than the input) is filtered through an adjoint filter of the error channel. Performance regarding convergence and misadjustment are equivalent. However, linearity is not assumed in the derivation of the algorithm. Furthermore, equations for single-input-single-output (SISO) and multiple-input-multiple-output (MIMO) are identical and both remain order N.