ppxscal/embedding_network huggingface dataset:
Leveraging Relational Autocorrelation with Latent Group Models
Authors: Jennifer Neville, David Jensen
Venue: Proceedings of the Fifth IEEE International Conference on Data Mining (2005)

The presence of autocorrelation provides a strong motivation for using relational learning and inference techniques. Autocorrelation is a statistical dependence between the values of the same variable on related entities and is a nearly ubiquitous characteristic of relational data sets. Recent research has explored the use of collective inference techniques to exploit this phenomenon. These techniques achieve significant performance gains by modeling observed correlations among class labels of related instances, but the models fail to capture a frequent cause of autocorrelation — the presence of underlying groups thatinfluence the attributes on a set of entities. We propose a latent group model (LGM) for relational data, which discovers and exploits the hidden structures responsible for the observed autocorrelation among class labels. Modeling the latent group structure improves model performance, increases inference efficiency, and enhances our understanding of the datasets. We evaluate performance on three relational classification tasks and show that LGM outperforms models that ignore latent group structure, particularly when there is little information with which to seed inference.
Spatial data structures and algorithms for large scale applications
Authors: Sathish Govindarajan
Venue:  (2004)

In this thesis, we develop spatial data structures and algorithms for two broad classes of applications&mdash;forest growth models and range searching. Forest growth model. We have developed an individual-based, spatially-explicit forest growth model. Our model is highly realistic and is quite complex compared to most forest models. Our forest model allows for many sources of variability and uncertainty that characterize processes and data. To perform efficient simulation, we balance accuracy against the stochasticity inherent in data and process. Based on this approach, we have developed efficient data structures and algorithms for calculating dispersal and light. We have developed a quad-tree based data structure to represent the trees in the forest. Based on this data structure, we have developed a monopole-based approximation algorithm to compute dispersal. This yields an efficiency-accuracy tradeoff scheme. Experimental results show a speedup of about an order of magnitude for reasonable error. We have performed experiments to evaluate the stochasticity in the dispersal model. Results show that the stochasticity is at least an order of magnitude greater than computational error, thus justifying approximation. We also provide experimental results that provide guidelines for choosing the monopole constant. We have performed ecological experiments using model simulations to evaluate various mechanisms that affect biodiversity. Range searching. We have developed data structures for answering two types of orthogonal range queries&mdash;range aggregate query and colored range query. We have developed an efficient indexing scheme, Compressed Range Tree (CRB-tree) for answering range aggregate queries. For count queries in 2D, the CRB-tree is linear in size and can answer queries using logarithmic I/Os. Our index can be extended to handle SUM aggregate as well. We also show how to dynamize our index and extend it to higher dimensions. We demonstrate the efficacy of our data structure by comparing its performance with kdB-tree. We develop efficient indices to answer colored range searching queries on a grid. (Abstract shortened by UMI.)
Configuring and managing a large-scale monitoring network solving real world challenges for ultra low powered and long-range wireless mesh networks
Authors: Laurent Maleysson, Christophe Dugas
Venue: Proceedings of the 2005 joint conference on Smart objects and ambient intelligence: innovative context-aware services: usages and technologies (2005)

In creating wireless networking solutions suitable for deployment in harsh, unpredictable, and widespread environments, we were confronted with a series of problems as-yet unsolved by commercially available technologies. The purpose of this article is to describe how we addressed mission-critical customer requirements by developing a wireless technology explicitly for devices in Ultra Low Power (ULP) and Long-Range wireless mesh networks. The key end-points in our target implementation are battery-operated devices located in hard-to-reach places, but which are nonetheless expected to offer a lifespan of several years without human intervention.We provide an overview of the technical requirements for building ULP networks, with a focus on configuration and management (including patent pending self-configuration and dynamic-routing features).This is followed by a case study of an existing 25,000 node wireless network deployed for an automatic meter reading (AMR) solution, and examples of provisioning individual nodes in complex real-world networks. We also describe how transmitting information about existing network hierarchy to new nodes not only preserves overall battery life in other network nodes, but also simplifies installation efforts significantly. The technology described here is particularly applicable to metering, telemetry, remote monitoring, and large-scale data collection solutions, while straightforwardly suited for personal and property security, medical surveillance, access control, lighting systems, as well as numerous industrial sectors.With a strong background in utility metering systems, Coronis Systems provides ready-to-use wireless solutions for manufacturers, VARs, and integrators in the automatic remote metering and wireless sensor network industries.
Interactive simulation with GASP IV on a minicomputer
Authors: Mark A. Fox, A. Alan B. Pritsker
Venue: ACM SIGSIM Simulation Digest (1975)

In this paper, the implementation of an interactive version of GASP IV, a FORTRAN-based discrete/continuous simulation language (1,2,3) is described. Interactive GASP IV was implemented on a General Automation SPC 16/65 mini-computer configured with 16K words of core memory and operating under the control of a disk based operating system (4). All features of GASP IV are included in the interactive version. A list of the subprograms of GASP IV is presented in Figure 1 (5). In addition, four forms of real-time man-computer interaction have been designed into Interactive GASP IV:1) online presentation of simulated system status on requests through the use of clearly formatted reports and plots;2) free formatted online data input of GASP variables and model parameters;3) programmed decision events requiring online responses as part of the discrete event structure; and4) user intervention in an executing program through keyboard interrupts.
Multi-way distributional clustering via pairwise interactions
Authors: Ron Bekkerman, Ran El-Yaniv, Andrew McCallum
Venue: Proceedings of the 22nd international conference on Machine learning (2005)

We present a novel unsupervised learning scheme that simultaneously clusters variables of several types (e.g., documents, words and authors) based on pairwise interactions between the types, as observed in co-occurrence data. In this scheme, multiple clustering systems are generated aiming at maximizing an objective function that measures multiple pairwise mutual information between cluster variables. To implement this idea, we propose an algorithm that interleaves top-down clustering of some variables and bottom-up clustering of the other variables, with a local optimization correction routine. Focusing on document clustering we present an extensive empirical study of two-way, three-way and four-way applications of our scheme using six real-world datasets including the 20 News-groups (20NG) and the Enron email collection. Our multi-way distributional clustering (MDC) algorithms consistently and significantly outperform previous state-of-the-art information theoretic clustering algorithms.
Comprehensive Evaluation of E-commerce Website Based on Concordance Analysis
Authors: Chang Jinling, Xia Guoping
Venue: Proceedings of the IEEE International Conference on e-Business Engineering (2005)

As the e-commerce is playing a more and more important role in our life, the appropriate methods and metrics are needed to evaluate the e-commerce websites. The websites evaluation belongs to multicriteria decision problems. The main processes used including survey and technical measure did not establish a mathematic model, nor unite the object's satisfaction and dissatisfaction. In this paper, the concordance analysis approach is introduced to evaluate the e-commerce websites, and the comprehensive evaluation model is established. The concordance priority index and the discordance priority index are adopted to display aspects of the website. The project that has both the maximal concordance priority index and the minimal discordance priority index is the best. One instance including 4 websites is analyzed to show the application of this model. The advantages of the model are discussed in the end.
Essays on software systems design, release, and early promotion
Authors: Zhengrui Jiang
Venue:  (2005)

In today's volatile software market, both quality and time to market are critical to a new software product's success. However, can a firm accelerate the delivery and adoption of its software products without trading off software quality, or improve the qualify of its software without delaying release and market adoption? To answer this question, my dissertation study focuses on the (1) design, (2) testing and release, as well as (3) early promotion phases of the software development and marketing process. I propose three strategies that a firm could consider: (1) usage-based optimal design, (2) patching, and (3) free software offer. The three strategies are addressed in three separate essays. In the first essay, I study an important usage-based design issue, the attribute-value conflict problem that is often encountered when merging data from multiple sources. I propose a framework for making the cost-minimizing decision based on the distribution of possible values and costs of errors associated with decision problems of interest. Analyses show that the cost-optimal solution provides a substantial amount of cost saving as compared to a solution that always pick the most likely value. The second essay studies the software release policy with patching considered. I show that when patching is available and not very costly, a firm can release its software early and continue to test even after release. This policy has several advantages over the policy without considering patching. First, the total expected cost is reduced by a significant amount. Second, the reliability of the software product is higher after testing stops. Third, the expected number of software failures in the field is lower. The third essay addresses the free software offer strategy. In this essay, I answer the following questions: what kind of products can benefit from free offer, and when and how should the free software be distributed to maximize a firm's own benefit? I conclude that a software firm can benefit from free offer because the word-of-mouth effect of the free adopters can accelerate the whole diffusion process.
On the feasibility of utilizing correlations between user populations for traffic inference
Authors: Kun-chan Lan, John Heidema
Venue: Proceedings of the The IEEE Conference on Local Computer Networks 30th Anniversary (2005)

Network models today are often derived from two different methods. On one hand, detailed traffic models are generated based on traces from a single tap into the network. Alternatively, one can collect higher-level traffic-matrix data with SNMP from many routers. However, inferring flow-level details from such data is still an open research issue. Today it is infeasible to collect a fine-grained, packet-level representation of a complete, multi-router network. Even if it were economically feasible to synchronize and monitor every router in a large network, the amount of data generated would tax storage and computation resources. In this work, we propose a methodology to infer flow-level traffic across a network by exploiting the correlations between user populations across different networks. The contribution of this paper is twofold. First, based on traces of web traffic collected from two different sources, we observe that the user-behavior parameters of the traffic (such as user "think" time in web traffic) are correlated across time, while the application-specific parameters of the traffic (such as object size) are correlated across "similar" networks. Second, by utilizing the correlations between similar networks, we propose a methodology for inferring traffic at places where continuously taking measurements is infeasible. We evaluate the effectiveness of our methodology via simulation.
On the Tractability of Rule Discovery from Distributed Data
Authors: Martin Scholz
Venue: Proceedings of the Fifth IEEE International Conference on Data Mining (2005)

This paper analyses the tractability of rule selection for supervised learning in distributed scenarios. The selection of rules is usually guided by a utility measure such as predictive accuracy or weighted relative accuracy. A common strategy to tackle rule selection from distributed data is to evaluate rules locally on each dataset. While this works well for homogeneously distributed data, this work proves limitations of this strategy if distributions are allowed to deviate. The identification of those subsets for which local and global distributions deviate, poses a learning task of its own, which is shown to be at least as complex as discovering the globally best rules from local data.
The Birth, Evolution and Future of the Microprocessor
Authors: Masatoshi Shima
Venue: Proceedings of the The Fifth International Conference on Computer and Information Technology (2005)

The world's first microprocessor, the 4004, was co-developed by Busicom, a Japanese manufacturer of calculators, and Intel, a U.S. manufacturer of semiconductors. During the development of a general-purpose LSI for not only desktop calculators but also other business machines, originally based on a decimal computer with a stored program method, a basic architecture of 4004 was developed in August 1969; a concrete plan for the 4004 system was finalized in December 1969; and the first microprocessor was successfully developed in March 1971. Microprocessors, which became the "technology to open up a new era," brought two outstanding impacts, "power of intelligence" and "power of computing". First, microprocessors opened up a new "era of programming" through replacing with software, the hardwired logic based on IC's of the former "era of logic". At the same time, microprocessors allowed young engineers access to "power of computing" for the creative development of personal computers and computer games, which in turn led to growth in the software industry, and paved the way to the development of high-performance microprocessors. Development engineers involved in creative development can be likened to explorers who go into unmapped territory without a compass, having hope for success and fear of failure. Also, an engineer must be armed with the firm belief that his mission is nothing but development, and must be determined to go his own way, never following another's tracks. In this talk, the birth, evolution and future of Microprocessor will be described. 4004 performance was only 0.06MIPS with 2,238 transistors and 750 KHz operating frequency. Microprocessors evolved from 4 bit to 64 bit microprocessors, introducing computer technologies such as pipeline, super-pipeline, super-scalar, VLIW, cache memory, and virtual memory system. Now, it is possible to integrate 16 sets of microprocessor with 64GB of memory on the board. In 20th century, microprocessors were used for increasing "power of intelligence". In 21st century, microprocessors will evolve into "tool to bring forth wisdom" for all mankind.
Whipping Up Some Gourmet Software
Authors: Phillip A. Laplante
Venue: IT Professional (2005)

As it turns out, software engineering and cooking have more in common than you may think. By studying the practices of great chefs, a software engineer can learn a great deal about the best way to develop a piece of software. Often the qualities inherent to masterful food preparation can also be applied to software engineering.
Extended Link Analysis for Extracting Spatial Information Hubs
Authors: Jianwei Zhang, Yoshiharu Ishikawa, Hiroyuki Kitagawa
Venue: Proceedings of the International Workshop on Challenges in Web Information Retrieval and Integration (2005)

Recently, web mining that tries to find useful knowledge from the vast amount of web pages has attracted a lot of research interests. Besides, it is becoming an essential task to provide web pages related to a user-specified geographic area. In this paper, we propose an approach to extract spatial information hubs from the web. A spatial information hub is a web page which is related to a specified geographic area and has much local information and/or many hyperlinks to local web pages. In the traditional approach of web link analysis, the importance and quality of pages are judged only by their contents and hyperlink structures. However, we take their geographic localities into consideration. In our approach, we first extract geographic information from web pages to create spatial nodes and spatial links, then conduct a link analysis based on the extended link structures. We also show our approach works well based on the experiments.
On the Intersection of XPath Expressions
Authors: Beda Christoph Hammerschmidt, Martin Kempa, Volker Linnemann
Venue: Proceedings of the 9th International Database Engineering & Application Symposium (2005)

XPath is a common language for selecting nodes in an XML document. XPath uses so called path expressions which describe a navigation path through semistructured data. In the last years some of the characteristics of XPath have been discussed. Examples include the containment of two XPath expressions p and p' (p ¿ p'). To the best of our knowledge the intersection of two XPath expressions (p ¿ p') has not been treated yet. The intersection of p and p' is the set that contains all XML nodes that are selected both by p and p'. In the context of indexes in XML databases the emptiness of the intersection of p and p' is a major issue when updating the index. In order to keep the index consistent to the indexed data, it has to be detected if an index that is defined upon p is affected by a modifying database operation with the path expression p'. In this paper we introduce the intersection problem for XPath and give a motivation for its relevance. We present an efficient intersection algorithm for XPath expressions without the NOT operator that is based on finite automata. For expressions that contain the NOT operator the intersection problem becomes NP-complete leading to exponential computations in general. With an average case simulation we show that the NPcompleteness is no significant limitation for most real-world database operations.
Mosaicing-by-recognition: a technique for video-based text recognition
Authors: Hiromitsu Miyazaki, Seiichi Uchida, Hiroaki Sakoe
Venue: Proceedings of the Eighth International Conference on Document Analysis and Recognition (2005)

In this paper, a mosaicing-by-recognition technique is proposed where video mosaicing and text recognition are simultaneously and collaboratively optimized in a one-step manner. Specifically, multiple frames capturing a long text line are optimally concatenated with a guide of the text recognition framework. In this optimization process, rotation, scaling, vertical shift, and speed fluctuation, which often appear in video frames captured by hand-held cameras, are compensated. The optimization is performed by a DPbased algorithm. The results of experiments to evaluate not only the accuracy of text recognition but also that of video mosaicing indicates that the proposed technique is practical and can provide reasonable results in most cases.
A Distributed Algorithm for Path Restoration in Circuit Switched Communication Networks
Authors: S. Venkatesan, Maulin Patel, Neeraj Mittal
Venue: Proceedings of the 24th IEEE Symposium on Reliable Distributed Systems (2005)

Path restoration is an important approach for building survivable telecommunication backbone networks. Path restoration is known for high restoration efficiency and its ability to protect against single link, multiple link and node failures. Path restoration can be formulated as the wellknown multi-commodity network flow (MCNF) problem. While many centralized algorithms have been proposed for solving the MCNF problem, distributed algorithms have received very little attention. This paper presents an online distributed multi-commodity flow approximation algorithm specifically tailored for path restoration. Our algorithm uses O(|E|diam^2) messages and O(diam^2) time in the worst case, and substantially fewer messages and less time in practical networks. When simulated on a sample real-life backbone network similar to those used by the telecommunication service providers, our algorithm finds a solution significantly faster than many published algorithms.
Using Continuous Biometric Verification to Protect Interactive Login Sessions
Authors: Sandeep Kumar, Terence Sim, Rajkumar Janakiraman, Sheng Zhang
Venue: Proceedings of the 21st Annual Computer Security Applications Conference (2005)

In this paper we describe the theory, architecture, implementation, and performance of a multi-modal passive biometric verification system that continually verifies the presence/ participation of a logged-in user. We assume that the user logged in using strong authentication prior to the starting of the continuous verification process. While the implementation described in the paper combines a digital camera-based face verification with a mouse-based fingerprint reader, the architecture is generic enough to accommodate additional biometric devices with different accuracy of classifying a given user from an imposter. The main thrust of our work is to build a multi-modal biometric feedback mechanism into the operating system so that verification failure can automatically lock up the computer within some estimate of the time it takes to subvert the computer. This must be done with low false positives in order to realize a usable system. We show through experimental results that combining multiple suitably chosen modalities in our theoretical framework can effectively do that with currently available off-the-shelf components.
A rewriting-based inference system for the NRL protocol analyzer: grammar generation
Authors: Santiago Escobar, Catherine Meadows, José Meseguer
Venue: Proceedings of the 2005 ACM workshop on Formal methods in security engineering (2005)

The NRL Protocol Analyzer (NPA) is a tool for the formal specification and analysis of cryptographic protocols that has been used with great effect on a number of complex real-life protocols. It probably outranks any of the existing tools in the sheer range of the types of attacks it is able to model and discover. However, the techniques in NPA lack an independent formal specification and model, and instead are closely intertwined with other NPA features. The main contribution of this paper is to rectify this problem by giving for the first time a precise formal specification of one of the main features of the NPA inference system: its grammar-based techniques for invariant generation, as well as a backwards reachability analysis method that captures some of the key features of the NPA. This formal specification is given within the well-known rewriting framework so that the inference system is specified as a set of rewrite rules modulo an equational theory describing the behavior of the cryptographic algorithms involved.