ppxscal/embedding_network huggingface dataset:
NMR signal enhancement via a new time-frequency transform
Authors: O. A. Ahmed
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 06 (2000)

A reliable method to reduce the noise from nuclear magnetic resonance (NMR) signals using a previously developed linear critically-sampled time-frequency transform is proposed. In addition to its low computational requirements, this transform has many theoretical advantages that make it a good candidate for NMR signal enhancement. NMR signals, in the transform domain, are concentrated in a very few number of coefficients while the noise is fairly distributed among the coefficients. Therefore, performing a thresholding technique in the transform domain significantly enhances the signal. Comparison with other noise reduction techniques used for the same purpose showed that this technique has superior performance thus confirming the theoretical expectations.
A deterministic blind identification technique for SIMO systems of unknown model order
Authors: G. T. Venkatesan
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 04 (1999)

In this paper we present a method for the deterministic blind identification of single-input multiple-output systems with unknown model order. The technique, that is applicable to both the FIR and IIR cases, requires only an upper bound of the model order. It is based on the special kernel structure of block Toeplitz matrices. When the model order is overestimated, this special structure entails the true solution to be embedded in the overestimated solution in a unique shift-chain form. This special shift-chain structure is then utilized to extract the true solution.
Implementing TQM in the classroom: removing fear
Authors: J. William Ray,  Jr., D. W. Yates
Venue: Proceedings of the Frontiers in Education Conference on 1995. Proceedings., 1995 vol 1. - Volume 01 (1995)

This paper recounts the continuing efforts of the Louisiana Tech University's EET program to implement Deming's (1986) 14 points in the classroom. In an effort "to remove fear from the workplace", the faculty has implemented a policy called "A, B or retry" to remove the fear of failure from the student. The paper discusses the policy and its implementation, how it is presented to the students, measures of effectiveness, and the various drawbacks of the policy. The policy also has a supplemental effect of improving student accountability toward the actual learning of the material. This new level of accountability, along with the effect it has on "adopting a new philosophy" is discussed. Finally, the paper considers how an electronic engineering department can be restructured to better remove the fear from the process of education.
Using accessory functions to generalize dynamic dispatch in single-dispatch object-oriented languages
Authors: David Wonnacott
Venue: Proceedings of the 6th conference on USENIX Conference on Object-Oriented Technologies and Systems - Volume 6 (2001)

Object oriented languages generally include some form of dynamic dispatch; that is, in the absence of precise compile-time type information, they perform a run-time selection of the appropriate function body (or method) from a set of candidates. Existing single-dispatch languages restrict dynamic dispatch to the object receiving the message. Such languages exhibit a conflict between the goals of providing an extensible a set of types and providing an extensible the set of operations that can be performed on these types. We show that this conflict is a consequence of the restriction of dynamic dispatch to the receiver object. We also demonstrate that this conflict can be resolved by introducing a generalized form of single dispatch (thus avoiding the complexity of multiple dispatch). On this evidence, we argue that dispatch technique should be decoupled from membership in a class and access to its representation.
Optimal Estimation of Descriptor Scales for Multimedia Retrieval
Authors: Nikolaos Doulamis
Venue: Proceedings of the Eight International Workshop on Image Analysis for Multimedia Interactive Services (2007)

Relevance feedback schemes use a given set of descriptors and at each feedback iteration they just modify the importance of each descriptor to the retrieval performance. This implies that the same type of descriptors is used for all feedback iterations. Therefore, such approaches cannot improve the retrieval performance beyond the efficiency of the descriptors used to represent the multimedia content. In this paper, an alternative concept is to adopt a progressive descriptor organization and to allow dynamic modification of the type of descriptors (expansion or shrink) at each retrieval iteration by exploiting the current user's information needs. In other words, descriptors that best fit the current user's preferences are expanded into more details, in constant to the descriptors that are far way from the user's needs which are shrinking. In this case, instead of using a large set of descriptors, most of them inappropriate with respect to the current user's information needs, a small number of dominant descriptors is selected for the retrieval process. Thus, the proposed approach significantly increases the precision performance by discarding descriptors that yield noise in the retrieval.
A hidden Markov model based visual speech synthesizer
Authors: J. J. Williams
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 04 (2000)

This paper describes a hidden Markov model (HMM) based visual synthesizer designed to assist persons with impaired hearing. This synthesizer builds on results in the area of audio-visual speech recognition. We describe how a correlation HMM can be used to integrate independent acoustic and visual HMMs for speech-to-visual synthesis. Our results show that an HMM correlating model can significantly improve synchronization errors versus techniques which compensate for rate differences through scaling.
Fine-grained localization in sensor and ad-hoc networks
Authors: Y. Richard Yang
Venue:  (2006)

Sensor networks are seen as one of the most promising emerging technologies. In many cases, sensed information is useless without knowing the sensor location. In addition, many of the networking protocols currently being developed for sensor networks assume the availability of node positions. In the first part of this dissertation, we provide a theoretical foundation for the internode distance-based localization problem (fine-grained localization). We construct "grounded graphs" to model network localization and apply graph rigidity theory to develop conditions for the unique localizability of networks as well as to construct and characterize classes of uniquely localizable networks. In addition, we study the computational complexity of network localization and prove that the problem is NP-complete, even for uniquely localizable networks where a distance measurement exists between every two nodes within a certain distance r of one other. We then describe subclasses of uniquely localizable grounded graphs for which localization can be efficiently computed. In the remainder of our work, we study localizability and localization in sensor networks of randomly-placed nodes and present new algorithms for controlled mobility, deployment and localization. Our localization algorithm succeeds in unambiguously localizing a much wider class of networks than was previous possible. In random networks, almost all localizable nodes are localized using our approach, even at node densities close to the minimum required for localizability. We close with an example application of localization in a novel controlled mobility algorithm for the optimization of power usage in sensor networks.
Quadratic programming with transaction costs
Authors: Michael J. Best, Jaroslava Hlouskova
Venue: Computers and Operations Research (2008)

We consider the problem of maximizing the mean-variance utility function of n assets. Associated with a change in an asset's holdings from its current or target value is a transaction cost. These must be accounted for in practical problems. A straightforward way of doing so results in a 3n-dimensional optimization problem with 3n additional constraints. This higher dimensional problem is computationally expensive to solve. We present an algorithm for solving the 3n-dimensional problem by modifying an active set quadratic programming (QP) algorithm to solve the 3n-dimensional problem as an n-dimensional problem accounting for the transaction costs implicitly rather than explicitly. The method is based on deriving the optimality conditions for the higher dimensional problem solely in terms of lower dimensional quantities and requires substantially less computational effort than any active set QP algorithm applied directly on a 3n-dimensional problem.
Explicit Ziv-Zakai lower bound for bearing estimation
Authors: K. L. Bell
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 05 (1996)

The extended Ziv-Zakai bound for vector parameters is used to develop a lower bound on the mean square error (MSE) in estimating the two-dimensional bearing of a narrowband planewave signal using planar arrays of arbitrary geometry. The bound has a simple closed form expression which is a function of the signal wavelength, the signal-to-noise ratio (SNR), the number of data snapshots, the number of sensors in the array, and the array configuration. Analysis of the bound suggests that there are several regions of operation, and expressions for the thresholds separating the regions are provided. In the asymptotic region where the number of snapshots and/or SNR are large, the bound approaches the inverse Fisher information. In the a priori performance region where the number of snapshots or SNR is small, the bound approaches the a priori covariance. In the transition region, the bound varies smoothly between the two extremes. Results from simulation of the maximum likelihood estimator (MLE) demonstrate that the bound closely predicts the performance of the MLE in all regions.
System Dynamics Modeling for SOA Project Management
Authors: JJ Jeng, Lianjun An
Venue: Proceedings of the IEEE International Conference on Service-Oriented Computing and Applications (2007)

Service-Oriented Architecture (SOA) has the potential to vastly improve IT's efficiency. But to implement one at an organization, enterprises need more than just technical know-how: the leadership team has to be skilled in management as well. Especially, SOA implies different emphasis of project management. This paper describes in brief the use of system dynamics models for managing large scale SOA projects. System dynamics is a methodology for studying and managing complex feedback systems, such as one finds in business and other social systems. In fact it has been used to address practically every sort of feedback system including project management. In this paper, we will present a framework of managing SOA projects and show how system dynamics model can be used to enhance the effectiveness and agility of SOA project management. A general SOA project lifecycle is presented and two examples are used to illustrate the needs and effectiveness of adopting quantified simulation method such as system dynamics into large-scale SOA projects.
Using audience accommodation for effective and ethical communication
Authors: J. M. Williams
Venue: Proceedings of the 30th Annual Frontiers in Education - Volume 02 (2000)

Recent changes in engineering education have focused on improving students' communication skills and increasing their understanding of ethical dimensions of engineering practices. Unfortunately the interrelations between ethics and communication are often overlooked, and these connections can actually improve development of both skills sets. As engineering educators, we can play an important role in ensuring that our engineering graduates are able to address a wide range of audiences clearly with correct and complete information. By working to ensure our students have-and value-the ability to address a variety of audiences, we can help raise public knowledge on technical issues and thereby impact the ethical content of the decisions made on them. This paper introduces the fundamentals of audience analysis and demonstrates how these principles can be applied in engineering courses.
An analysis of process and memory models to support high-speed networking in a UNIX environment
Authors: B. J. Murphy, S. Zeadally, C. J. Adams
Venue: Proceedings of the 1996 annual conference on USENIX Annual Technical Conference (1996)

In order to reap the benefits of high-speed networks, the performance of the host operating system must at least match that of the underlying network. A barrier to achieving high throughput is the cost of copying data within current host architectures. We present a performance comparison of three styles of network device driver designed for a conventional monolithic UNIX kernel. Each driver performs a different number of copies. The zero-copy driver works by allowing the memory on the network adapter to be mapped directly into user address space. This maximises performance at the cost of: 1) breaking the semantics of existing network APIs such as BSD sockets and SVR4 TLI; 2) pushing responsibility for network buffer management up from the kernel into the application layer. The single-copy driver works by copying data directly between user space and adapter memory obviating the need for an intermediate copy into kernel buffers in main memory. This approach can be made transparent to existing application code but, like the zero-copy case, relies on an adapter with a generous quantity of on-board memory for buffering network data. The two-copy driver is a conventional STREAMS driver. The two-copy approach sacrifices performance for generality. We observe that the STREAMS overhead for small packets is significant. We report on the benefit of the hardware cache in ameliorating the effect of the second copy, although we note that streaming network data through the cache reduces the level of cache residency seen by the rest of the system. A barrier to achieving low jitter is the non-deterministic nature of many operating system schedulers. We describe the implementation and report on the performance of a kernel streaming driver that allows data to be copied between a network adapter and another I/O device without involving the process scheduler. This provides performance benefits in terms of increased throughput, increased CPU availability and reduced jitter.
MS2DB: A Mass-Based Hashing Algorithm for the Identification of Disulfide Linkage Patterns in Protein Utilizing Mass Spectrometric Data
Authors: Timothy Lee, Rahul Singh, Ten-Yang Yen, Bruce Macher
Venue: Proceedings of the Twentieth IEEE International Symposium on Computer-Based Medical Systems (2007)

The tertiary structure and biological function of a protein can be better understood given knowledge of the number and location of its disulfide bonds. By utilizing mass spectrometric (MS) experimental procedures that produce spectra of the protein's peptides joined by a disulfide bond, we can make initial identifications of these bonded cysteine pairings. The algorithmic problem then becomes how to match a theoretical mass space of all possible bonded peptides against the MS data. Our solution, MSHashID, utilizes the Expected Amino Acid Mass in combination with a hash structure to improve the time complexity of making an identification from worse than O(n2) to approximately O(n), where n is the size of the mass space. We have developed a software package, MS2DB, which includes an implementation of this algorithm. Experiments using published data show that the MSHashID algorithm efficiently makes the correct initial identifications, which can then be confirmed using tandem mass spectrometry (MS/MS).
A Geo-Routing Algorithm in Planar Graph for Ad Hoc Wireless Networks
Authors: Rashid Bin Muhammad
Venue: Proceedings of the 21st International Conference on Advanced Information Networking and Applications Workshops - Volume 02 (2007)

This paper presented a fully distributed algorithm to compute a planar subgraph for geo-routing in ad hoc wireless networks. We considered the idealized unit disk graph model in which nodes are assumed to be connected if, and only if, nodes are within their transmission range. The main contribution of this work is a fully distributed algorithm to extract the connected, planar graph for routing in the wireless networks. The communication cost of the proposed algorithm is O(d log d) bits, where d is the degree of a node.
Policy Verification and Validation Framework Based on Model Checking Approach
Authors: Shinji Kikuchi, Satoshi Tsuchiya, Motomitsu Adachi, Tsuneo Katsuyama
Venue: Proceedings of the Fourth International Conference on Autonomic Computing (2007)

Policy-based management is drawing attention as a solution to managing today's complex information systems. To be dependable, a policy-based system must be able to check the validity of a policy written by administrators. However, common test methods such as operations tests in a test scenario and simulations cannot check whether systems with given policies will work properly in every possible situation. To solve this problem, we propose a policy verification and validation framework based on model checking that exhaustively verifies a policy's validity by considering the relations between system characteristics and policies. We first define the validity of policies and the information needed to verify them from the viewpoint of model checking. We then construct our policy verification framework based on the definition and, finally, present a case study applying this framework to an on-demand data center scenario and show the effectiveness of our approach.
Word alignment for languages with scarce resources using bilingual corpora of other language pairs
Authors: Haifeng Wang, Hua Wu, Zhanyi Liu
Venue: Proceedings of the COLING/ACL on Main conference poster sessions (2006)

This paper proposes an approach to improve word alignment for languages with scarce resources using bilingual corpora of other language pairs. To perform word alignment between languages L1 and L2, we introduce a third language L3. Although only small amounts of bilingual data are available for the desired language pair L1-L2, large-scale bilingual corpora in L1-L3 and L2-L3 are available. Based on these two additional corpora and with L3 as the pivot language, we build a word alignment model for L1 and L2. This approach can build a word alignment model for two languages even if no bilingual corpus is available in this language pair. In addition, we build another word alignment model for L1 and L2 using the small L1-L2 bilingual corpus. Then we interpolate the above two models to further improve word alignment between L1 and L2. Experimental results indicate a relative error rate reduction of 21.30% as compared with the method only using the small bilingual corpus in L1 and L2.
Forming consensus in the networks of knowledge
Authors: Witold Pedrycz, Kaoru Hirota
Venue: Engineering Applications of Artificial Intelligence (2007)

Information granules, such as e.g., fuzzy sets, capture essential knowledge about data and the key dependencies between them. Quite commonly, we may envision that information granules (fuzzy sets) have become a result of fuzzy clustering and therefore could be succinctly represented in the form of some fuzzy partition matrices. Interestingly, the same data set could be represented from various standpoints and this multifaceted view yields a collection of different partition matrices being reflective of the higher-order granular knowledge about the data. The levels of specificity of the clusters the data are organized into could be quite different-the larger the number of clusters, the more detailed insight into the structure of data becomes available. Given the granularity of the resulting constructs (rather than plain data themselves), one could view a collection of partition matrices as a certain type of a network of knowledge. Considering a variety of sources of knowledge encountered across the network, we are interested in forming consensus between them. In a nutshell, this leads to the construction of certain fuzzy partition matrices which ''reconcile'' the knowledge captured by the individual partition matrices. Given that the granularity of the sources of knowledge under consideration could vary quite substantially, we develop a unified optimization perspective by introducing fuzzy proximity matrices that are induced by the corresponding partition matrices. In the sequel, the optimization is realized on a basis of these proximity matrices. We offer a detailed algorithm and illustrate its performance using a series of numeric experiments.
Test volume reduction via flip-flop compatibility analysis for balanced parallel scan
Authors: M. Ashouei, A. Chatterjee, A. Singh
Venue: Proceedings of the 2004 IEEE International Workshop on Defect Based Testing (2004)

Test generation for scan-based test of sequential circuits is typically performed by generating tests for the embedded combinational logic (ECL) and translating these into scan test vectors. However, the serial nature of scan-based test incurs significant overhead in terms of test application time. To reduce the test data volume, in this paper we propose a new algorithm for compatibility analysis of the circuit flip flops. This algorithm, when applied to parallel-scan methods such as the Illinois Scan Architecture (ILS), results in shorter and more balanced scan chains. It also eliminates the need to apply test vectors in serial mode. As a result, an average reduction of 1.4/spl times/ and a maximum reduction of 1.7/spl times/ in test data volume was obtained for the ISCAS89 benchmarks, over current versions of ILS.
Fundamental equivalences between set-theoretic and maximum-entropy methods in multiple-domain image restoration
Authors: P. Ishwar
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 01 (2000)

Several powerful, but heuristic techniques in the image denoising literature have used overcomplete image representations. A general framework for incorporating information from multiple representations based on fundamental statistical estimation principles was presented in Ishwar and Moulin (1999) where, information about image attributes from multiple wavelet transforms was incorporated as moment constraints on the underlying image prior. In this paper we explore the fundamental equivalence between the stochastic setting of multiple-domain restoration in Ishwar and Moulin and its deterministic set-theoretic counterpart. The main technical tool is the Lagrange multiplier theory of constrained optimization. The insights gained by this analysis allow us to derive a state-of-the-art denoising algorithm.
Problem solving: learning and assessment model
Authors: M. L. de la Barra
Venue: Proceedings of the 30th Annual Frontiers in Education - Volume 01 (2000)

A significant number of freshman students entering Universidad Tecnica Federico Santa Maria (UTFSM), Valparaiso, Chile, lack the necessary cognitive skills to solve problems. Since 1999, a didactic approach in mathematics is being applied to first year maths. This new teaching scheme involves the systematic use of routine steps that constitute the whole problem solving process. Several evaluation charts to provide the instructors with the necessary assessment and evaluation tools are also being developed and tested at this time.