ppxscal/embedding_network huggingface dataset:
Improving Blind Equalization Algorithm for Wireless Communication Systems
Authors: Lijun Sun, Ying He
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 02 (2007)

Blind equalization technique is an effective approach for canceling the intersymbol interference (ISI) induced by multipath effect in digital wireless communications. The convergence behavior as well as the residual mean square error (MSE) of a blind equalizer is an interesting issue in its design. Perhaps the main drawback of the traditional constant modulus algorithm (CMA) is its relatively slow convergence, especially in the time varying multipath wireless channels. In order to overcome this difficulty, a novel combined blind equalization algorithm based on a normalized iterative method is proposed in this paper. At the beginning of the iteration process, the normalized super-exponential iterative algorithm is utilized to perform an initial equalization, and then the iteration process switches to a decision-directed (DD) algorithm at appropriate values of the mean square error. This switch method can obtain a great improvement in both convergence behavior and residual MSE. The performance of the proposed algorithm is verified through computer simulations.
Efficient indexing methods for probabilistic threshold queries over uncertain data
Authors: Reynold Cheng, Yuni Xia, Sunil Prabhakar, Rahul Shah, Jeffrey Scott Vitter
Venue: Proceedings of the Thirtieth international conference on Very large data bases - Volume 30 (2004)

It is infeasible for a sensor database to contain the exact value of each sensor at all points in time. This uncertainty is inherent in these systems due to measurement and sampling errors, and resource limitations. In order to avoid drawing erroneous conclusions based upon stale data, the use of uncertainty intervals that model each data item as a range and associated probability density function (pdf) rather than a single value has recently been proposed. Querying these uncertain data introduces imprecision into answers, in the form of probability values that specify the likeliness the answer satisfies the query. These queries are more expensive to evaluate than their traditional counterparts but are guaranteed to be correct and more informative due to the probabilities accompanying the answers. Although the answer probabilities are useful, for many applications, it is only necessary to know whether the probability exceeds a given threshold - we term these Probabilistic Threshold Queries (PTQ). In this paper we address the efficient computation of these types of queries. In particular, we develop two index structures and associated algorithms to efficiently answer PTQs. The first index scheme is based on the idea of augmenting uncertainty information to an R-tree. We establish the difficulty of this problem by mapping one-dimensional intervals to a two-dimensional space, and show that the problem of interval indexing with probabilities is significantly harder than interval indexing which is considered a well-studied problem. To overcome the limitations of this R-tree based structure, we apply a technique we call variance-based clustering, where data points with similar degrees of uncertainty are clustered together. Our extensive index structure can answer the queries for various kinds of uncertainty pdfs, in an almost optimal sense. We conduct experiments to validate the superior performance of both indexing schemes.
A Microprocessor-Based Pulse-Height Analyzer
Authors: R. Hariharan, Vallabha Kulkarni
Venue: IEEE Micro (1982)

Need to analyze particles in a flow? This system takes electrical pulses from acoustical or optical sensors and groups them into bands representing ranges of particle sizes.
Scalable DTN distribution over uni-directional links
Authors: Dirk Kutscher, Janico Greifenberg, Kevin Loos
Venue: Proceedings of the 2007 workshop on Networked systems for developing regions (2007)

We present an architecture for scalable DTN communication in sparsely populated areas. Our approach is based on Uni-DTN, a unidirectional DTN convergence layer that we have developed for unicast and multicast distribution of DTN bundles. In this paper, we discuss possible application scenarios, present a suitable distribution architecture and the Uni-DTN convergence layer and describe, how specific features of the DTN bundle specification and DTN communication scenarios can be implemented using Uni-DTN.
Automatic correspondence of tags and genes (ACTG)
Authors: Pedro A. F. Galante, Jeff Trimarchi, Constance L. Cepko, Sandro J. de Souza, Lucila Ohno-Machado, Winston P. Kuo
Venue: Bioinformatics (2007)

Summary: A critical step in any SAGE, MPSS and SBS data analysis is tag-to-gene assignment. Current available tools are limited by a tag-by-tag annotation process and/or do not provide the dataset that is used to produce a complete tag-to-gene mapping. We developed ACTG, a web-based application that allows a large-scale tag-to-gene mapping using several reference datasets. ACTG can annotate SAGE (14 or 21 bp), MPSS (17 or 20 bp) and SBS (16 bp) data for both human and mouse organisms. Availability: http://retina.med.harvard.edu/ACTG/ Contact: pgalante@ludwig.org.br Supplementary information: Supplementary data are available at Bioinformatics online.
SVM-UBM Based Automatic Language Identification Using a Vowel-guided Segmentation
Authors: Tianqiang Peng, Wenlin Zhang, Bicheng Li
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 01 (2007)

As powerful theoretical and computational tools, support vector machines (SVMs) have been widely used in pattern classification of many areas. A key issue of applying SVMs to language identification of speech signals is to find a SVM kernel that compares a sequence of feature vectors with others efficiently. In this paper, we introduce a sequence kernel used in language identification, and develop a Gaussian Mixture Model to do the sequence mapping task, which maps a variable length sequence of vectors to a fixed dimensional space. Experiment results demonstrate that the new system not only yields performance superior to those of a GMM classifier but also outperforms the system using Generalized Linear Discriminant Sequence (GLDS) Kernel.
An Interval Ranking Method of Multimedia Presentation based on Relative Query Keyword Position
Authors: Daisuke Kitayama, Youko Kitahata, Ryoko Hiramoto, Kazutoshi Sumiya
Venue: Proceedings of the 18th International Conference on Database and Expert Systems Applications (2007)

Presentation content can consist of heterogeneous media, such as videos and slides, which have been recorded and used. A variety of retrieval methods have been proposed for each kind of stored media. This paper proposes an extraction method using the features of each type of media. The proposed method specifically uses presentation video and slides. A user inputs query keywords, which are used to extract the most appropriate interval for the query according to appearance positions in the media. This enables the user to extract intervals that can be viewed more efficiently than when the interval depends only on the presence of query keywords.
Optimization of Chaos Control by Means of Evolutionary Algorithms
Authors: Ivan Zelinka, Roman Senkerik, Eduard Navratil
Venue: Proceedings of the 18th International Conference on Database and Expert Systems Applications (2007)

This work deals with an evolutionary data processing, concretely optimization of control of chaos based on using EA. The main aim of this work is to show that evolutionary algorithms are capable of optimization of chaos control. As models of deterministic chaotic system one dimensional Logistic equation and two dimensional Henon map were used. The evolutionary algorithm Self-Organizing Migrating Algorithm (SOMA) was used in four versions. For each version, simulations were repeated several times to show and check robustness of used method.
Semantic Retrieval of Text Documents
Authors: Vitaly Klyuev, Vladimir Oleshchuk
Venue: Proceedings of the 7th IEEE International Conference on Computer and Information Technology (2007)

Nowadays, the Internet is the major source of information for millions of people. There are many search tools available on the net but finding appropriate text information is still difficult. The retrieval efficiency of the presently used systems cannot be significantly improved: "Bag of words" interpretation causes loosing semantics of texts. We applied the functional approach to present English text documents in the memory of computers. It allowed to keep semantic relations between words when indexing documents and use ordinary English sentences as queries to submit to a search engine. The proposed retrieval algorithm returns highly relevant documents. The presented example illustrates the advantage of the discussed approach compared to the traditional key word search.
Improving Selection Methods for Evolutionary Algorithms by Clustering
Authors: Kaikuo Xu, Changjie Tang, Yintian Liu, Chuan Li, Jiang Wu, Jun Zhu, Li Dai
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 03 (2007)

This study applies clustering in population selection to improve the efficiency of evolutionary algorithms. The main contributions include: (a) Proposes a novel selection framework that uses the number of clusters for a population as the measurement the population diversity. (b) Proposes clustering-ranking selection, an instance of this framework, and discusses its mathematical principle by PD-SP equation. (c) Gives experiments over CLPSO (Comprehensive Learning Particle Swarm Optimization). Experiment result shows that the proposed selection method outperforms canonical exponential ranking on all the sixteen-benchmark functions for both 10-D and 30-D problems except a function for 30-D problem.
An Overview of Anna, a Specification Language for Ada
Authors: D. C. Luckham
Venue: IEEE Software (1985)

The Anna approach to specification language design strengthens the existing explanatory constructs in Ada and adds new ones where there is an obvious need.
Vertex suppression in 3-connected graphs
Authors: Matthias Kriesell
Venue: Journal of Graph Theory (2008)

To suppress a vertex $v$ in a finite graph G means to delete it and add an edge from a to b if a, b are distinct nonadjacent vertices which formed the neighborhood of $v$. Let $G--x$ be the graph obtained from $G-x$ by suppressing vertices of degree at most 2 as long as it is possible; this is proven to be well defined. Our main result states that every 3-connected graph G has a vertex x such that $G -- x$ is 3-connected unless G is isomorphic to $K_{3,3}$, $K_2 \times K_3$, or to a wheel $K_{1}*C_{\ell}$ for some $\ell \geq 3$. This leads to a generator theorem for 3-connected graphs in terms of series parallel extensions. &copy; 2007 Wiley Periodicals, Inc. J Graph Theory 57: 41&ndash;54, 2008
Back-End Technology Trends
Authors: G. A. Champine
Venue: Computer (1980)

Rapid decreases in hardware costs, increases in economy of scale, and improvements in functionality are accelerating the move to back-end systems.
A periodical replacement model based on cumulative repair-cost limit
Authors: Min-Tsai Lai
Venue: Applied Stochastic Models in Business and Industry (2007)

This paper considers a periodical replacement model based on a cumulative repair-cost limit, whose concept uses the information of all repair costs to decide whether the system is repaired or replaced. The failures of the system can be divided into two types. One is minor failure that is assumed to be corrected by minimal repair, while the other is serious failure where the system is damaged completely. When a minor failure occurs, the corresponding repair cost is evaluated and minimal repair is then executed if this accumulated repair cost is less than a pre-determined limit L, otherwise, the system is replaced by a new one. The system is also replaced at scheduled time T or at serious failure. Long-run expected cost per unit time is formulated and the optimal period T* minimizing that cost is also verified to be finite and unique under some specific conditions. Copyright &copy; 2007 John Wiley Sons, Ltd.
Game Theoretic Stochastic Routing for Fault Tolerance and Security in Computer Networks
Authors: Stephan Bohacek, Joao Hespanha, Junsoo Lee, Chansook Lim, Katia Obraczka
Venue: IEEE Transactions on Parallel and Distributed Systems (2007)

We introduce the Game-Theoretic Stochastic Routing (GTSR) framework, a proactive alternative to today's reactive approaches to route repair. GTSR minimizes the impact of link and router failure by (1) computing multiple paths between source and destination and (2) selecting among these paths randomly to forward packets. Besides improving fault-tolerance, the fact that GTSR makes packets take random paths from source to destination also improves security. In particular, it makes connection eavesdropping attacks maximally difficult as the attacker would have to listen on all possible routes. The approaches developed are suitable for network layer routing as well as for application layer overlay routing and multi-path transport protocols such as SCTP.Through simulations, we validate our theoretical results and show how the resulting routing algorithms perform in terms of the security/fault-tolerance/delay/throughput trade-off. We also show that a beneficial side-effect of these algorithms is an increase in throughput, as they make use of multiple paths.
LogTM-SE: Decoupling Hardware Transactional Memory from Caches
Authors: Luke Yen, Jayaram Bobba, Michael R. Marty, Kevin E. Moore, Haris Volos, Mark D. Hill, Michael M. Swift, David A. Wood
Venue: Proceedings of the 2007 IEEE 13th International Symposium on High Performance Computer Architecture (2007)

This paper proposes a hardware transactional memory (HTM) system called LogTM Signature Edition (LogTM-SE). LogTM-SE uses signatures to summarize a transaction's read-and write-sets and detects conflicts on coherence requests (eager conflict detection). Transactions update memory "in place" after saving the old value in a per-thread memory log (eager version management). Finally, a transaction commits locally by clearing its signature, resetting the log pointer, etc., while aborts must undo the log. LogTM-SE achieves two key benefits. First, signatures and logs can be implemented without changes to highly-optimized cache arrays because LogTM-SE never moves cached data, changes a block's cache state, or flash clears bits in the cache. Second, transactions are more easily virtualized because signatures and logs are software accessible, allowing the operating system and runtime to save and restore this state. In particular, LogTM-SE allows cache victimization, unbounded nesting (both open and closed), thread context switching and migration, and paging.
Flush: a reliable bulk transport protocol for multihop wireless networks
Authors: Sukun Kim, Rodrigo Fonseca, Prabal Dutta, Arsalan Tavakoli, David Culler, Philip Levis, Scott Shenker, Ion Stoica
Venue: Proceedings of the 5th international conference on Embedded networked sensor systems (2007)

We present Flush, a reliable, high goodput bulk data transport protocol for wireless sensor networks. Flush provides end-to-end reliability, reduces transfer time, and adapts to time-varying network conditions. It achieves these properties using end-to-end acknowledgments, implicit snooping of control information, and a rate-control algorithm that operates at each hop along a flow. Using several real network topologies, we show that Flush closely tracks or exceeds the maximum goodput achievable by a hand-tuned but fixed rate for each hop over a wide range of path lengths and varying network conditions. Flush is scalable; its effective bandwidth over a 48-hop wireless network is approximately one-third of the rate achievable over one hop. The design of Flush is simplified by assuming that different flows do not interfere with each other, a reasonable restriction for many sensornet applications that collect bulk data in a coordinated fashion, like structural health monitoring, volcanic activity monitoring, or protocol evaluation. We collected all of the performance data presented in this paper using Flush itself.
A quantitative foundation for defining and manipulating deals to facilitate automated e-commerce
Authors: Boaz Golany, Oded Shmueli
Venue: Electronic Commerce Research (2007)

We propose a goal programming framework that aims at automating e-commerce transactions. This framework consists of three basic layers: deal definition--defining the deal's parameters and associated constraints (e.g., item, price, delivery dates); deal manipulation--a collection of procedures for shaping deals to attain desired goals (e.g., earliest delivery and minimum price) and an applications layer that employs these procedures within some negotiations settings (e.g., an auction-related application presents a "better offer" while bidding on a contract). Our proposed foundation is rich enough to support a wide array of applications ranging from 1-1 and 1-n negotiations (auctions) to deal valuation and deal splitting. Whereas the techniques are appropriate to a multitude of settings, we shall mainly present them in the context of business-to-business (B2B) commerce where we see the greatest short term benefits.
Pictorial Data-Base Systems
Authors: Shi-Kuo Chang
Venue: Computer (1981)

New applications in digital picture processing notably in handling geographic data and in computer-aided design have prompted development of a variety of pictorial data-base systems.
The Sage System Architecture: A System for the Rapid Development of Graphics Interfaces for Decision Support
Authors: Eric Clemons, Arnold Greenfield
Venue: IEEE Computer Graphics and Applications (1985)

Easily defined and modified icons are the building blocks of a flexible system designed to support sensitivity analysis.
Virtual Rheoscopic Fluids for Flow Visualization
Authors: William Barth
Venue: IEEE Transactions on Visualization and Computer Graphics (2007)

Physics-based flow visualization techniques seek to mimic laboratory flow visualization methods with virtual analogues. In this work we describe the rendering of a virtual rheoscopic fluid to produce images with results strikingly similar to laboratory experiments with real-world rheoscopic fluids using products such as Kalliroscope. These fluid additives consist of microscopic, anisotropic particles which, when suspended in the flow, align with both the flow velocity and the local shear to produce high-quality depictions of complex flow structures. Our virtual rheoscopic fluid is produced by defining a closed-form formula for the orientation of shear layers in the flow and using this orientation to volume render the flow as a material with anisotropic reflectance and transparency. Examples are presented for natural convection, thermocapillary convection, and Taylor-Couette flow simulations. The latter agree well with photographs of experimental results of Taylor-Couette flows from the literature.
DR-Chord-FAn Efficient Double-Ring Chord Protocol
Authors: Yu Shao-Shan, Yu Jiong, Kamil Kamil, Sun Qi-Gang
Venue: Proceedings of the Sixth International Conference on Grid and Cooperative Computing (2007)

The DHT-based Chord protocol for P2P networks is one of the research hotspots recently. Considering the low efficiency problem on the resource lookup, we have developed a more efficient double-ring Chord protocol for P2P networks. We analyze theoretically the expectation of hops and present the simulation results.
International Market Selection for Agricultural Product Using Fuzzy Neural Networks
Authors: Meimei Zhang, Chuanli Zhuang, Bo Gao
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 02 (2007)

International market selection is non-linear, multi- criteria decision-making problems characterized by overwhelm complexity. To solve this problem, we proposed a multigroup classification model based on a hybrid fuzzy neural network (FNN) model. The model is combined by the straightforward fuzzy inference system with the back-propagation neural network. Due to the representative ability of fuzzy inference system and the learning or intelligent ability of neural network, the results of the application of the methodology on real data indicate that the proposed method performed remarkable well in the international market selection.
Mobile multi-agent based, distributed information platform (MADIP) for wide-area e-health monitoring
Authors: Chuan Jun Su
Venue: Computers in Industry (2008)

e-Health care is characterized by high degree of distributed, labor-intensive works, mobility, and information access from various types of devices. Current and emerging developments in mobile computing integrated with developments in pervasive agent technologies such as mobile agent will have a radical impact on future health-care delivery systems. In this paper we present the design and architecture of a mobile multi-agent based information platform - MADIP - to support the intensive and distributed nature of wide-area (e.g., national or metropolitan) monitoring environment. To exemplify the proposed methodology, an e-health monitoring environment was built on top of MADIP as an illustration. Aglets Software Development Kit (ASDK) was adopted for prototyping, concept-proofing, and evaluation. By integrating the proposed platform with light-weight, portable monitoring devices (e.g., portable vital sign monitor), continuous long-term health monitoring can be performed without interfering with the patients' everyday activities and without restricting their mobility. The optimal utilization of medical resources can be also achieved.
Analysis of three multilevel security architectures
Authors: Timothy E. Levin, Cynthia E. Irvine, Clark Weissman, Thuy D. Nguyen
Venue: Proceedings of the 2007 ACM workshop on Computer security architecture (2007)

Various system architectures have been proposed for high assurance enforcement of multilevel security. This paper provides an analysis of the relative merits of three architectural types -- one based on a security kernel, another based on a traditional separation kernel, and a third based on a least-privilege separation kernel. We introduce the Least Privilege architecture, which incorporates security features from the recent "Separation Kernel Protection Profile," and show how it can provide several unique aspects of security and assurance, although each architecture has advantages.
Social networks of author-coauthor relationships
Authors: Yasmin H. Said, Edward J. Wegman, Walid K. Sharabati, John T. Rigsby
Venue: Computational Statistics Data Analysis (2008)

Social network analysis has proven to be a useful tool in analysis of many situations. We begin by giving an overview of social network analysis. We then illustrate the concepts by examining the social networks of co-authors of scholarly publications. Scholarly publication is in many ways the lifeblood of academic institutions and there are strong incentives, both in terms of prestige and financial compensation, for faculty members to publish. Different disciplines and individuals have evolved distinguishable mechanisms for coping with the publication pressures. We examine the co-authorship networks of a number of prominent scholars. Based on the clustering within the co-author social network, we distinguish several styles of co-authorship including solo models (no co-authors), mentor models, entrepreneurial models, and team models. We conjecture that certain styles of co-authorship lead to the possibility of group-think, reduced creativity, and the possibility of less rigorous reviewing processes.