ppxscal/embedding_network huggingface dataset:
Virtualization Technologies in the Undergraduate IT Curriculum
Authors: Alessio Gaspar, Sarah Langevin, William D. Armitage
Venue: IT Professional (2007)

A Linux-based virtualization solution for IT courses leverages an open source approach for a low-cost, scalable cluster. The tool is suited for student home use for OS and networking lab assignments
Object fusion in geographic information systems
Authors: Catriel Beeri, Yaron Kanza, Eliyahu Safra, Yehoshua Sagiv
Venue: Proceedings of the Thirtieth international conference on Very large data bases - Volume 30 (2004)

Given two geographic databases, a fusion algorithm should produce all pairs of corresponding objects (i.e., objects that represent the same real-world entity). Four fusion algorithms, which only use locations of objects, are described and their performance is measured in terms of recall and precision. These algorithms are designed to work even when locations are imprecise and each database represents only some of the real-world entities. Results of extensive experimentation are presented and discussed. The tests show that the performance depends on the density of the data sources and the degree of overlap among them. All four algorithms are much better than the current state of the art (i.e., the one-sided nearest-neighbor join). One of these four algorithms is best in all cases, at a cost of a small increase in the running time compared to the other algorithms.
Analysis of Variable Reordering on the QMDD Representation of Quantum Circuits
Authors: Sharon Van Schaick, Kenneth B. Kent
Venue: Proceedings of the 10th Euromicro Conference on Digital System Design Architectures, Methods and Tools (2007)

In previous research, a novel structure was discussed for representing the matrices that can be built from an n-variable rvalued reversible/quantum circuit. This structure, called a QMDD, takes on a form similar to that of a reduced-orderedbinary- decision-diagram (ROBDD). It is known that the order of variables used for developing an ROBDD from a binary logic circuit is relevant to the size and structure of that ROBDD. This paper determines what effect, if any, variable order has on the QMDD structure and proposes a simple heuristic for choosing a "good' variable order.
The Design of a New Non-linear Predictive Filter
Authors: Xiaoqin Wu, Yanqin Wang, Yaohong Kang
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 03 (2007)

The paper presents a new method to design a predictive filter which suits to analyze non-stationary data. The processed data are approximated by polynomial. The approximating function in the paper is cubic spline. The predictive filter is constructed with the true value and the observation value of each observation point. The designed filter can perform adaptive analysis to the observation data, and is able to implement multi-resolution analysis as wavelet transform. The paper discusses the derivation of the filter in detail and analyzes its amplitude- frequency characteristics, and then presents the decomposition and composition structure when using the filter to analyze data.
Integrating corpus work into secondary education: From data-driven learning to needs-driven corpora
Authors: Sabine Braun
Venue: ReCALL (2007)

This paper reports on an empirical case study conducted to investigate the overall conditions and challenges of integrating corpus materials and corpus-based learning activities into English-language classes at a secondary school in Germany. Starting from the observation that in spite of the large amount of research into corpus-based language learning, hands-on work with corpora has remained an exception in secondary schools, the paper starts by outlining a set of pedagogical requirements for corpus integration and the approach which has formed the basis for designing the case study. Then the findings of the study are reported and discussed. As a result of the methodological challenges identified in the study, the author argues for a move from ‘data-driven learning’ to needs-driven corpora, corpus activities and corpus methodologies.
Estimating Similarity over Data Streams Based on Dynamic Time Warping
Authors: Jian-Kui Guo, Qing Wang, Zhenhua Huang, Shengli Sun, Yang-Yong Zhu
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 03 (2007)

Estimating similarity over data streams has many applications in the data streams environment, such as intrusion detection in the network, data analysis in the sensor net, cluster, k-nearest neighbor queries and so on. However, there has only a few research related to similarity evaluation under data stream contexts. The main reason is because of the native feature of data streams, namely, large, continuous, and only one pass scan. It is hard to find an efficient method to evaluate similarity over data streams. In this paper, we propose a new algorithm ESDS(Estimating Similarity over Data Streams), which not only can estimate similarity efficiently over data streams under the time warping distance but is the first time to use DTW(Dynamic Time Warping) distance based on the sliding window to deal with similarity evaluation over data streams. To the best of our knowledge, this paper is the first paper to address this problem. In order to evaluate the efficiency of our algorithm, we present a simple but efficiently method to denote the original stream data. In computing the distance of DTW between data streams by using dynamic programming, we also introduce a new distance of DTW which can compute the similarity over data streams efficiently. The experiments of many real and synthetic data sets show that our algorithm can evaluate the similarity over data streams efficiently and not be studied in the previous research.
The Build Group of Solid Modelers
Authors: R. Hillyard
Venue: IEEE Computer Graphics and Applications (1982)

Build 2, Design, and Romulus are solid modelers with evolutionary links. Consideration of their characteristics and histories yields some general insights into solid modeling.
Context-Sensitive Error Correction: Using Topic Models to Improve OCR
Authors: M. Wick, M. Ross, E. Learned-Miller
Venue: Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 02 (2007)

Modern optical character recognition software relies on human interaction to correct misrecognized charac- ters. Even though the software often reliably identifies low-confidence output, the simple language and vocabu- lary models employed are insufficient to automatically cor- rect mistakes. This paper demonstrates that topic models, which automatically detect and represent an article's se- mantic context, reduces error by 7% over a global word distribution in a simulated OCR correction task. Detecting and leveraging context in this manner is an important step towards improving OCR.
The Kowledge-Based Simulation System
Authors: Y. V. Ramana Reddy
Venue: IEEE Software (1986)

To answer what-if questions, KBS uses artificial intelligence techniques to model complex organizations, recognize cause-and-effect relations, and generates scenarios automatically.
An improved handover algorithm based on signal strength plus distance for interoperability in mobile cellular networks
Authors: Brahmjit Singh
Venue: Wireless Personal Communications: An International Journal (2007)

In future generation mobile cellular systems, position location of mobile terminal is expected to be available. In this paper, we propose an initiation algorithm for intersystem handover based on the combination of position location of mobile terminal and the absolute signal strength thresholds. Global System for Mobile communication (GSM) and Universal Mobile Telecommunication Systems (UMTS) networks are considered for interworking. The proposed algorithm reduces the handover rate by around 50% and thus improves the network resource efficiency as compared to that based on signal strength thresholds only.
Exploring a Stack Architecture
Authors: R. P. Blake
Venue: Computer (1977)

Computer architects design a high-performance system out of the same components that the rest of us would use to build a common one. They do it through an understanding of how the system will actually be programmed. Such was the insight which led to the development of stack-based computers.
Tidier Drawings of Trees
Authors: E. M. Reingold
Venue: IEEE Transactions on Software Engineering (1981)

Various algorithms have been proposed for producing tidy drawings of trees-drawings that are aesthetically pleasing and use minimum drawing space. We show that these algorithms contain some difficulties that lead to aesthetically unpleasing, wider than necessary drawings. We then present a new algorithm with comparable time and storage requirements that produces tidier drawings. Generalizations to forests and m-ary trees are discussed, as are some problems in discretization when alphanumeric output devices are used.
Runtime leakage power estimation technique for combinational circuits
Authors: Yu-Shiang Lin, D. Sylvester
Venue: Proceedings of the 2007 Asia and South Pacific Design Automation Conference (2007)

This paper carefully examines subthreshold leakage during circuit operation (runtime) and develops a novel analysis technique to capture this important effect, which is currently ignored in traditional steady-state leakage calculation approaches. We implement novel dynamic and static estimation methods that provide significant speed improvements over full SPICE simulations and yield estimation errors of approximately 12% on average compared to more than 2times errors in steady-state based subthreshold leakage analysis.
Product Life-Cycle Metadata Modeling and Its Application with RDF
Authors: Hong-Bae Jun, Dimitris Kiritsis, Paul Xirouchakis
Venue: IEEE Transactions on Knowledge and Data Engineering (2007)

The whole product lifecycle consists of three phases: Beginning Of Life (BOL), Middle Of Life (MOL), and End Of Life (EOL). Although large amounts of product lifecycle data are generated over the whole product lifecycle, data flows are rather vague after BOL. Over the last decade, however, emerging Internet, wireless mobile telecommunications, and product identification technologies have created the potential to make the whole product lifecycle visible. As a result, the scope of data to be managed has expanded over the whole product lifecycle. Hence, it becomes important to describe product lifecycle meta data in a systematic manner. Although much attention has been paid to data modeling over several objects such as products and processes, modeling methodology for product lifecycle meta data is not well developed. To cope with this limitation, we develop a modeling method for product lifecycle meta data using the resource description framework (RDF). We define an RDF data model and its schema for describing and managing product lifecycle meta data. In addition, we describe how the proposed RDF model can be usefully applied to track, trace, and infer product lifecycle data with an RDF query language.
Towards content trust of web resources
Authors: Yolanda Gil, Donovan Artz
Venue: Web Semantics: Science, Services and Agents on the World Wide Web (2007)

Trust is an integral part of the Semantic Web architecture. Most prior work on trusts focuses on entity-centered issues such as authentication and reputation and does not take into account the content, i.e., the nature and use of the information being exchanged. This paper defines content trust and discusses it in the context of other trust measures that have been previously studied. We introduce several factors that users consider in deciding whether to trust the content provided by a Web resource. Our goal is to discern which of these factors could be captured in practice with minimal user interaction in order to maximize the quality of the system's trust estimates. We present results on a study to determine which factors were more important to capture, and describe a simulation environment that we have designed to study alternative models of content trust.
Anthropometric Modeling Programs-A Survey
Venue: IEEE Computer Graphics and Applications (1982)

Some anhtropometric modeling programs focus on analytical and numerical data, but others provide mainly visual output for researchers to analyze.
Rehabilitation and the Handicapped Programmer
Authors: R. J. Leneway
Venue: Computer (1981)

The lives of many handicapped persons have been vastly improved by computer technology, both in adaptive devices and job opportunity but millions wait to be served.
Regularized Large Margin Classifier
Authors: Caikou Chen, Jingyu Yang
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 02 (2007)

In this paper, a novel linear projection classification technique, termed regularized large margin classifier (RLMC), is developed in this paper. Through adding a regularized term (within-class scatter) to the margin criterion of the classical large margin classifier, the margin between two classes of the resulting projection feature vectors achieves maximized while the within-class scatter can achieve minimum. Finally, the proposed classifier is tested on ORL face database and AR face database. The experimental results verify the effectiveness of the proposed method.
Efficient Exact Algorithms through Enumerating Maximal Independent Sets and Other Techniques
Authors: Venkatesh Raman, Saket Saurabh, Somnath Sikdar
Venue: Theory of Computing Systems (2007)

We give substantially improved exact exponential-time algorithms for a number of NP-hard problems. These algorithms are obtained using a variety of techniques. These techniques include: obtaining exact algorithms by enumerating maximal independent sets in a graph, obtaining exact algorithms from parameterized algorithms and a variant of the usual branch-and-bound technique which we call the "colored" branch-and-bound technique. These techniques are simple in that they avoid detailed case analyses and yield algorithms that can be easily implemented. We show the power of these techniques by applying them to several NP-hard problems and obtaining new improved upper bounds on the running time. The specific problems that we tackle are: (1) the Odd Cycle Transversal problem in general undirected graphs, (2) the Feedback Vertex Set problem in directed graphs of maximum degree 4, (3) Feedback Arc Set problem in tournaments, (4) the 4-Hitting Set problem and (5) the Minimum Maximal Matching and the Edge Dominating Set problems. The algorithms that we present for these problems are the best known and are a substantial improvement over previous best results. For example, for the Minimum Maximal Matching we give an O*(1.4425n) algorithm improving the previous best result of O*(1.4422m) [35]. For the Odd Cycle Transversal problem, we give an O*(1.62n) algorithm which improves the previous time bound of O*(1.7724n) [3].
Experience with Path Analysis and Testing of Programs
Authors: M. R. Woodward
Venue: IEEE Transactions on Software Engineering (1980)

There are a number of practical difficulties in performing a path testing strategy for computer programs. One problem is in deciding which paths, out of a possible infinity, to use as test cases. A hierarchy of structural test metrics is suggested to direct the choide and to monitor the coverge of test paths. Another problem is that many of the chosen paths may be infeasible in the sense that no test data can ever execute them. Experience with the use of "allegations" to circumvent this problem and prevent the static generation of many infeasible paths is reported.
Value Regularization and Fenchel Duality
Authors: Ryan M. Rifkin, Ross A. Lippert
Venue: The Journal of Machine Learning Research (2007)

Regularization is an approach to function learning that balances fit and smoothness. In practice, we search for a function f with a finite representation f = Σi ci φi(·). In most treatments, the ci are the primary objects of study. We consider value regularization, constructing optimization problems in which the predicted values at the training points are the primary variables, and therefore the central objects of study. Although this is a simple change, it has profound consequences. From convex conjugacy and the theory of Fenchel duality, we derive separate optimality conditions for the regularization and loss portions of the learning problem; this technique yields clean and short derivations of standard algorithms. This framework is ideally suited to studying many other phenomena at the intersection of learning theory and optimization. We obtain a value-based variant of the representer theorem, which underscores the transductive nature of regularization in reproducing kernel Hilbert spaces. We unify and extend previous results on learning kernel functions, with very simple proofs. We analyze the use of unregularized bias terms in optimization problems, and low-rank approximations to kernel matrices, obtaining new results in these areas. In summary, the combination of value regularization and Fenchel duality are valuable tools for studying the optimization problems in machine learning.
The Motorola MC68020
Authors: Doug MacGregor, Dave Mothersole, Bill Moyer
Venue: IEEE Micro (1984)

This new 32-bit microprocessor provides high performance, instruction set extensibility, and compatibility with existing M68000 family software.
Exploration of Network Security Information Hid in Web Pages Based on Immunology
Authors: Caiming Liu, Tao Li, Hui Zhao, Lingxi Peng, Jinquan Zeng, Yan Zhang
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 01 (2007)

To discover information endangering network security, an exploration method of network security information based on immunology is proposed. Antibody and antigen in Biological Immune System are used to denote keywords hid in HTML pages. Proposed method generates new antibodies to recognize unknown keywords through immune rules. By mechanisms of self-learning and evolution, antibody families form to represent distribution of different network security information. All antibodies in the same family are totalized to evaluate the information distribution degree. Simulation experiments show that the proposed method is able to find useful information threatening network and improve the intelligent degree of evaluating security of web information.
Enabling DVD-like features in P2P video-on-demand systems
Authors: Nevena Vratonjić, Priya Gupta, Nikola Knežević, Dejan Kostić, Antony Rowstron
Venue: Proceedings of the 2007 workshop on Peer-to-peer streaming and IP-TV (2007)

Peer-to-peer (p2p) video-on-demand (VoD) is increasingly popular with Internet users. Currently deployed pure p2p VoD systems provide poor general performance and they lack advanced features such as fast forward and seeking to arbitrary points. Peer-assisted VoD systems can provide such services, but they require very well provisioned source servers (or server farms). We propose BulletMedia, a system that uses proactive caching to attempt to provide advanced features without requiring a well provisioned server. In BulletMedia, blocks are altruistically replicated by peers not to aid immediate playback but to simply increase the number of replicas of each block. This helps ensure that blocks are available in-overlay and reduces dependence on the source. BulletMedia combines a traditional overlay mesh approach with a structured overlay. The overlay mesh is used to fetch blocks at a high rate, while the structured overlay is used to enable efficient block discovery and to control block replication. Initial experimental results from a prototype BulletMedia implementation demonstrate that it can both effectively control in-overlay block replication and can efficiently use these replicas to perform forward seeks.
Dynamic EMCUD for knowledge acquisition
Authors: Shun-Chieh Lin, Shian-Shyong Tseng, Chia-Wen Teng
Venue: Expert Systems with Applications: An International Journal (2008)

Due to the knowledge explosion, the new objects will be evolved in a dynamic environment. Hence, the knowledge can be classified into static knowledge and dynamic knowledge. Although many knowledge acquisition methodologies, based upon the Repertory Grid technique, have been proposed to systematically elicit useful rules from static grid from domain experts, they lack the ability of grid evolution to incrementally acquire the dynamic knowledge of new evolved objects. In this paper, we propose dynamic EMCUD, a new Repertory Grid-based knowledge acquisition methodology to elicit the embedded meanings of knowledge (embedded rules bearing on m objects and k object attributes), to enhance the ability of original EMCUD to iteratively integrate new evolved objects and new added attributes into the original Acquisition Table (AT) and original Attribute Ordering Table (AOT). The AOT records the relative importance of all attribute to each object in EMCUD to capture the embedded meanings with acceptable certainty factor value by relaxing or ignoring some minor attributes. In order to discover the new evolved objects, a collaborative framework including local knowledge based systems (KBSs) and a collaborative KBS is proposed to analyze the correlations of inference behaviors of embedded rules between multiple KBSs in a dynamic environment. Each KBS monitors the frequent inference behaviors of interesting embedded rules to construct a small AT increment to facilitate the acquisition of dynamic knowledge after experts confirming the new evolved objects. Moreover, the significance of knowledge may change after a period of time, a trend of all attributes to each evolved object is used to construct a new AOT increment to help experts automatically adjust the relative importance of each attribute to each object using time series analysis approach. Besides, three cases are considered to assist experts in adjusting the certainty factor values of the dynamic knowledge of the new evolved objects from the collection of inference logs in the collaborative KBS. To evaluate the performance of dynamic EMCUD in incrementally integrating new knowledge into the knowledge base, a worm detection prototype system is implemented.
Energy-Efficient Hybrid Key Management Protocol for Wireless Sensor Networks
Authors: Tim Landstra, Maciej Zawodniok, S. Jagannathan
Venue: Proceedings of the 32nd IEEE Conference on Local Computer Networks (2007)

In this paper, we propose a subnetwork key management strategy in which the heterogeneous security requirements of a wireless sensor network are considered to provide differing levels of security with minimum communication overhead. Additionally, it allows the dynamic creation of high security subnetworks within the wireless sensor network and provides subnetworks with a mechanism for dynamically creating a secure key using a novel and dynamic group key management protocol. The proposed energy-efficient protocol utilizes a combination of pre-deployed group keys and initial trustworthiness of nodes to create a level of trust between neighbors in the network. This trust is later used to allow secure communication between neighbors when creating a dynamic, high security subnetwork within the sensor network. Results of simulations of the protocol in Ns2 are presented and the complexity of the protocol is analyzed. The proposed protocol reduces delay by 50% and energy consumption by 70% over the existing dynamic group key management (DGKM) scheme.