ppxscal/embedding_network huggingface dataset:
Wavelets for Improving Spectral Efficiency in a Digital Communication System
Authors: J. Oliver, R. Shantha Selva Kumari, V. Sadasivam
Venue: Proceedings of the Sixth International Conference on Computational Intelligence and Multimedia Applications (2005)

In this paper, two types of wavelet based schemes to improve the Spectral Efficiency (SE) of a digital communication system are presented. First one is wavelet based pulse shaping and the other is Wavelet based digital modulation called Wavelet Shift Keying (WSK). In pulse shaping scheme, orthonormal wavelets and their translates are used as base band shaping pulses. To improve spectral efficiency and coding gain, dyadic expansions and their translates are used for signaling. Since wavelets have zero average value, they can be transmitted using Single Side-Band (SSB) transmission. By comparing with Raised-Cosine (RC) signaling, this wavelet approach offers more data rate at the same bandwidth. RC system offers only 0.83 b/S/Hz for low pass transmission where as transmission using the first two dyadics offers 1.12 b/S/Hz. More over, it is shown that wavelets obey Nyquist pulse shaping conditions. Using a dyadic expansion to support a channel code there is a coding gain over the RC system, with essentially no bandwidth penalty. In Modulation scheme, the user data stream is transformed into sequence of scaled mother wavelets to indicate which version of the mother wavelet is transmitted. This modulation offers more Spectral Efficiency as number of users increases keeping the power efficiency as constant.
Intelligent Feature Extraction and Tracking for Visualizing Large-Scale 4D Flow Simulations
Authors: Fan-Yin Tzeng, Kwan-Liu Ma
Venue: Proceedings of the 2005 ACM/IEEE conference on Supercomputing (2005)

Terascale simulations produce data that is vast in spatial, temporal, and variable domains, creating a formidable challenge for subsequent analysis. Feature extraction as a data reduction method offers a viable solution to this large data problem. This paper presents a new approach to the problem of extracting and visualizing 4D features within large volume data. Conventional methods requires either an analytical description of the feature of interest or tedious manual intervention throughout the feature extraction and tracking process. We show that it is possible for a visualization system to "learn" to extract and track features in complex 4D flow field according to their "visual" properties, location, shape, and size. The basic approach is to employ machine learning in the process of visualization. Such an intelligent system approach is powerful because it allows us to extract and track an feature of interest in a high-dimensional space without explicitly specifying the relations between those dimensions, resulting in a greatly simplified and intuitive visualization interface.
Modeling of the single- and dual-gate microwave field effect transistors for computer aided design
Authors: Mohammad Abdeen
Venue:  (2004)

The increasing need for advanced communication technologies in the 21 st century is leading to continuous development of new and more complex active devices and systems. Transistors such as BJTs, HBTs, FETs, and HEMTs are fundamental components in today's personal, corporate and global communication systems. The single- and dual-gate MESFETs are widely used devices with wide areas of RF/Microwave applications. Due to their superior performance, MESFETs have been extensively used in high frequency, high-gain, and low-noise amplifiers, oscillator, mixers, and many other applications. In this thesis, conventional and intelligent modeling methodologies are investigated for the applicability to today's computer-aided design methodologies and tools. Novel approaches of this work are applied to the area of small- and large-signal modeling of the GaAs MESFET (the single- and dual-gate.) Optimal models for the single-gate MESFET are obtained using conventional techniques. A CAD tool called, TopFinder, is developed for optimal small and large-signal model generation. The tool has been successfully tested on a commercial single-gate MESFET and HEMT transistors. Neural network modeling technique is applied to the modeling of the dual-gate MESFET. More specifically, neural network large-signal models for the dual-gate MESFET are developed. These models present the RF device performance behavior including temperature dependence. The neural network technique is successfully applied to two dual-gate MESFET devices; a discrete chip and an on-wafer chip. First, the drain current is modeled while presenting both isothermal (using pulsed measurements) and temperature dependent neural network model for the dual-gate MESFET. A comprehensive large-signal neural network model is also developed. This model includes the nonlinearity of conductances as well as those of the junction capacitances. The nonlinear dual-gate MESFET model is successfully incorporated into ADS. The model is verified by comparing the measurements of a nonlinear single-stage amplifier application based on the dual-gate MESFET to harmonic balance simulations in ADS showing satisfactory results.
Using a DSM application to locally align DNA sequences
Authors: R. B. Batista, D. N. Silva, A. C. M. A. de Melo, L. Weigang
Venue: Proceedings of the 2004 IEEE International Symposium on Cluster Computing and the Grid (2004)

Sequence comparison is a basic operation in DNA sequencing projects, and most sequence comparison methods used are based on heuristics, that are faster but do not produce optimal alignments. Recently, many organisms have had their DNA entirely sequenced, and this reality presents the need for comparing long DNA sequences, which is a challenging task due to its high demands for computational power and memory. Although DSM is presented as a feasible parallel programming paradigm, much of the work in DSM is validated by benchmarks and there are only a few examples of real parallel applications running on DSM systems. In this article, we present and evaluate a parallelization strategy for implementing a local DNA sequence alignment algorithm. This strategy was implemented in JIAJIA, a scope consistent software DSM system. Our results on an eight-machine cluster presented very good speedups, which are comparable with the ones obtained with MPI, showing that our parallelization strategy and programming support were appropriate.
A software methodology for applied research: eXtreme Researching: Research Articles
Authors: Olivier Chirouze, David Cleary, George G. Mitchell
Venue: Software&mdash;Practice Experience (2005)

Applied research is, by necessity, a distributed, collaborative process. To be useful, research methodologies must not only be applicable in such an environment, but must also be adaptive to the needs of human resources and specific research area requirements. This paper introduces eXtreme Researching (XR), an adaptation of eXtreme Programming (XP) by Ericsson, to support distributed telecommunications research and development. XR builds on XP and tailors it to meet the needs of applied industrial research. It adopts and extends the most useful elements of XP: collective ownership, planning game, continuous integration and metaphor and shows how they are applicable in multi-site, research projects. XPWeb is developed as a tool to facilitate XR in a distributed research environment. XPWeb and XR are actively used by Ericsson Applied Research and have been shown to significantly increase output and efficiencies in multi disciplinary research projects. Copyright &copy; 2005 John Wiley & Sons, Ltd.
Interfacing compilers, proof checkers, and proofs for foundational proof-carrying code
Authors: Andrew W. Appel
Venue:  (2005)

Proof-Carrying Code (PCC) is a general framework for the mechanical verification of safety properties of machine-language programs. It allows a code producer to provide an executable program to a code consumer, along with a machine-checkable proof of safety such that the code consumer can check the proof before running the program. PCC has the advantage of a small Trusted Computing Base (TCB), since the proof checking can be a simple mechanical procedure. A weakness of previous PCC systems is that the proof-checking infrastructure is based on some complicated logic or type system that is not necessarily sound. Foundational Proof-Carrying Code (FPCC) aims to further reduce the TCB size by an order of magnitude by building the safety proof based on the simple and trustworthy foundations of mathematical logic. There are three major components in an FPCC system: a compiler, a proof checker, and the safety proof of an input machine-language program. The compiler should produce machine code accompanied by a proof of safety. The proof checker verifies, sometimes also reconstructs, the safety proof before the program gets executed. We have built a prototype system. Our prototype is the first end-to-end FPCC system, including a type-preserving compiler from core ML to SPARC (based on SML/NJ), a low-level typed assembly language LTAL, a foundational proof-checker Flit, and a nearly complete machine-checkable soundness proof. The system compiles Core ML programs to SPARC code, accompanied with programs in a low-level typed assembly language; these typed assembly programs serve as the proof witnesses of safety of the corresponding SPARC machine code. Our Flit proof checker includes a simple logic programming engine enabling efficient proof-checking. In this thesis, I'll explain the design of interfaces between these components and show how to build an end-to-end FPCC system. We have come to the following conclusion: a type system (a low-level typed assembly language) should be designed to check machine code; and the proof-checking should be factored into two stages, namely typechecking of the input machine code and verification of soundness of the type system. Since a type checker can be efficiently interpreted as a logic program, Flit's logic programming engine enables efficient proof-checking.
The reverse pamphlet document scheme
Authors: Diana Patterson
Venue: ACM SIGDOC Asterisk Journal of Computer Documentation (1977)

All documentation must be readable. Much of it isn't. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Automatic video annotation using ontologies extended with visual information
Authors: Marco Bertini, Alberto Del Bimbo, Carlo Torniai
Venue: Proceedings of the 13th annual ACM international conference on Multimedia (2005)

Classifying video elements according to some pre-defined ontology of the video content domain is a typical way to perform video annotation. Ontologies are defined by establishing relationships between linguistic terms that specify domain concepts at different abstraction levels. However, although linguistic terms are appropriate to distinguish event and object categories, they are inadequate when they must describe specific patterns of events or video entities. Instead, in these cases, pattern specifications can be better expressed through visual prototypes that capture the essence of the event or entity. Therefore pictorially enriched ontologies, that include both visual and linguistic concepts, can be useful to support video annotation up to the level of detail of pattern specification.This paper presents pictorially enriched ontologies and discusses a solution for their implementation for the soccer video domain. An unsupervised clustering method is proposed in order to create the enriched ontologies by defining visual prototypes representing specific patterns of highlights and adding them as visual concepts to the ontology.An algorithm that uses pictorially enriched ontologies to perform automatic soccer video annotation is proposed and results for typical highlights are presented. Annotation is performed associating occurrences of events, or entities, to higher level concepts by checking their proximity to visual concepts that are hierarchically linked to higher level semantics.
High-Performance and Area-Efficient Reduction Circuits on FPGAs
Authors: Ling Zhuo, Viktor K. Prasanna
Venue: Proceedings of the 17th International Symposium on Computer Architecture on High Performance Computing (2005)

Field-Programmable Gate Arrays (FPGAs) have become an attractive option for scientific applications. However, due to the pipelining in the FPGA-based floating-point units, data hazards may occur during reduction of series of values. A typical example of reduction is the accumulation of sets of floating-point values, which is needed in many scientific operations such as dot product and matrix-vector multiplication. Reduction circuits can significantly impact the overall performance, impose unrealistic buffer requirements, or occupy large area on the FPGA. In this paper, we introduce a high-performance and area-efficient FPGAbased reduction circuit. It can reduce multiple sets of sequentially delivered floating-point values without stalling the pipeline. In contrast with previous works, the proposed circuit uses one floating-point adder, and can handle input sets of arbitrary size. The buffer size needed by the circuit is independent of the size of the individual sets and the number of input sets. Using a Xilinx Virtex-II Pro FPGA as the target device, we implement the proposed reduction circuit and present performance and area results.
ACE: An Aggressive Classifier Ensemble with Error Detection, Correction, and Cleansing
Authors: Yan Zhang, Xingquan Zhu, Xindong Wu, Jeffrey P. Bond
Venue: Proceedings of the 17th IEEE International Conference on Tools with Artificial Intelligence (2005)

Learning from noisy data is a challenging and reality issue for real-world data mining applications. Common practices include data cleansing, error detection and classifier ensembling. The essential goal is to reduce noise impacts and enhance the learners built from the noise corrupted data, so as to benefit further data mining procedures. In this paper, we present a novel framework that unifies error detection, correction and data cleansing to build an aggressive classifier ensemble for effective learning from noisy data. Being aggressive, the classifier ensemble is built from the data that has been preprocessed by the data cleansing and correcting techniques. Experimental comparisons will demonstrate that such an aggressive classifier ensemble is superior to the model built from the original noisy data, and is more reliable in enhancing the learning theory extracted from noisy data sources, in comparison with simple data correction or cleansing efforts.
Some Experiments with the Performance of LAMP Architecture
Authors: UV Ramana
Venue: Proceedings of the The Fifth International Conference on Computer and Information Technology (2005)

Measurements are very useful to gauge the actual performance of various architectures and their components. In this paper we investigate the performance of the LAMP(Linux, Apache, MySQL, PHP) architecture and MySQL and PHP components. We build a web-site using LAMP and measure the application level performance. We use "measurements as a means" to improve the performance of the website. We then investigate the performance of the application when ported to Windows with running IIS and Apache with MySQL and PHP.
Elimination of Duplicate Labels in Petri-Net-Based System Specification
Authors: K. S. Cheung, K. O. Chow
Venue: Proceedings of the The Fifth International Conference on Computer and Information Technology (2005)

Labelled Petri nets are commonly used for system specification where the locations of conditions are denoted as places with condition labels and the locations of events as transitions with event labels. It is often in a Petri-net-based specification that the same condition label or event label appears in multiple locations. As every condition is finally implemented as a unique state and every event as a unique operation, in order for the system specification to become useful for implementation, all duplicate condition labels and event labels must be eliminated. In this paper, we propose a method for eliminating the duplicate labels. Firing sequences are preserved so that the intended system behaviours will not be altered.
Model-based self-monitoring embedded programs with temporal logic specifications
Authors: Li Tan
Venue: Proceedings of the 20th IEEE/ACM international Conference on Automated software engineering (2005)

We propose a model-based framework for developing self-monitoring embedded programs with temporal logic specifications. In our framework the requirement specification of an embedded program is encoded in the temporal logic MEDL. We propose an algorithm that synthesizes a model-based monitor from a MEDL script. We also introduce a technique that instruments a system model to emit events defined in the model-based primitive event definition language mPEDL. The synthesized model-based monitor may be composed with the instrumented model to form a self-monitoring model, which can be simulated for design-level verification; the composed self-monitoring model can also be used to generate a self-monitoring embedded program, which can monitor its own execution on the target platform in addition to its normal functions. Our approach combines the rigidness of temporal logic specifications with the easy use of a toolkit M2IST that we developed to automate the process of building a self-monitoring embedded program from a system model and its requirement specification.
Nonnegative time-frequency distributions for parametric time-frequency representations using semi-affine transformation group
Authors: Hongxing Zou, Dianjun Wang, Xianda Zhang, Yanda Li
Venue: Signal Processing (2005)

This paper proposes a method for calculating a nonnegative time-frequency distribution (TFD) whose concentration is identical to that of Wigner-Ville distribution (WVD) when instantaneous frequencies (IFs) of the best-matched elementary functions of the signal under analysis are pre-estimated. This method is based on a special class of transformation group, referred to as semi-affine transformation (SAT) group. The essence of this method is to create a joint distribution by translating the values of WVDs of Morlet wavelet to the positions around IFs of the best-matched elementary functions. Theoretical predictions and numerical results indicate that the proposed strategy can result in the most visually appealing TFDs for highly nonstationary signals.
Text/Graphic labelling of Ancient Printed Documents
Authors: N. Journet, V. Eglin, J. Y. Ramel, R. Mullot
Venue: Proceedings of the Eighth International Conference on Document Analysis and Recognition (2005)

This paper presents a text/graphic labelling for ancient printed documents. Our approach is based on the extraction and the quantification of the various orientations that are present in ancient printed document images. The documents are initially cut into normalized square windows in which we analyze significant orientations with a directional rose. Each kind of information (textual or graphical) is typically identified and marked by its orientation distribution. This choice of characterization allows us to separate textual regions from graphics by minimizing the a priori knowledge. The evaluation of our proposition lies on a page classification using layout extraction criteria. The system has been tested over several ancient printed books of the Renaissance.
Enabling live internet broadcasting using an application endpoint architecture
Authors: Yang-Hua Chu
Venue:  (2004)

It has been a long standing challenge to make Internet audio/video broadcasting a commodity service. This means that anyone with commodity Internet connection and computer equipments can broadcast high quality video to a large group of receivers in real time. The key challenge is the bandwidth cost in distributing the video streams. To distribute 300Kbps video stream to 100 receivers directly, a publisher must provision 30Mbps bandwidth to the Internet. This is too expensive for most individuals to afford. The conventional wisdom is to add functionality in the underlying network infrastructure, i.e. at the IP layer. With IP Multicast, the publisher sends just one copy of the video stream to the IP network, and the network intelligently replicates the video streams to all the receivers. By shifting the task of data replication to the IP routers, IP Multicast greatly reduces the bandwidth requirements for the publishers and receivers. However, 15 years after its initial proposal, IP Multicast is still plagued with concerns pertaining to scalability, network management, deployment, and support for higher level functionality. This dissertation takes a different architecture approach to meet the challenge in broadcasting high quality video over the Internet. Our thesis is that &ldquo;it is feasible today to provide video broadcasting as a commodity service, without changing the underlying IP infrastructure .&rdquo; We propose a new architecture called End System Multicast. In End System Multicast, data replication is performed not by the routers, but by the receivers in the broadcast, which are end systems on the Internet. Thus, the publisher only needs to send the video stream to a few receivers, and these receivers iteratively forward the video streams to other receivers. This avoids costly bandwidth provisioning for the publisher and requires no changes to the IP infrastructure. We demonstrate the feasibility of End System Multicast not only in simulators and Internet testbeds, but also in live broadcast scenarios. In the past two years, we have built an operational video broadcasting system based on this architecture. The system has been successful in broadcasting 20 events, benefiting 4000 users. This dissertation describes a complete solution in building a video broadcast system based on End System Multicast. This includes protocol-level designs to handle group dynamics and network heterogeneity, and system-level designs to integrate with media codecs and players. In addition, we address the issue of incentive for publishers and receivers to participate in this system.
A Half-Eye Wavelet Based Method for Iris Recognition
Authors: A. Poursaberi, B. N. Araabi
Venue: Proceedings of the 5th International Conference on Intelligent Systems Design and Applications (2005)

Iris detection is a crucial part of an iris recognition system. One of the main issues in iris segmentation is coping with occlusions that happen due to eyelids and eyelashes. In this paper, only the lower part of the iris is utilized for recognition. Wavelet based texture features along with a mixed Hamming; harmonic mean distance classifier is used for identification. It is observed that relying in a smaller but more reliable part of the iris, though reducing the net amount of information, improves the overall performance. Experimental results on CASIA database show that the method has a promising performance with an accuracy of more than 99%.
When Ants Attack: Ant Algorithms for Constraint Satisfaction Problems
Authors: Finbarr Tarrant, Derek Bridge
Venue: Artificial Intelligence Review (2005)

We describe an ant algorithm for solving constraint problems (Solnon 2002, IEEE Transactions on Evolutionary Computation 6(4): 347---357). We devise a number of variants and carry out experiments. Our preliminary results suggest that the best way to deposit pheromone and the best heuristics for state transitions may differ from current practice