ppxscal/embedding_network huggingface dataset:
A Fast Retrieval Algorithm for Large-Scale XML Data
Authors: Hiroki Tanioka
Venue: Focused Access to XML Documents: 6th International Workshop of the Initiative for the Evaluation of XML Retrieval, INEX 2007 Dagstuhl Castle, Germany, December 17-19, 2007. Selected Papers (2008)

This paper proposes a novel approach for retrieving large-scale XML data using the vector space model. The vector space model is commonly used in the information retrieval community. Last year, for the Evaluation of XML Retrieval (INEX) 2006 Adhoc Track, we developed a system using fragment elements. The system made it possible to search over XML elements for queries with varying constraints on XML elements to be included in the search, without the need for reindexing the collection, supporting more flexible queries. However the system took significant time to unitize the fragment elements. To solve the problem, our new system is composed of an inverted-file list and a relative inverted-path list on the INEX 2007 Adhoc Track corpus. 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
CBR for CBR: A Case-Based Template Recommender System for Building Case-Based Systems
Authors: Juan A. Recio-García, Derek Bridge, Belén Díaz-Agudo, Pedro A. González-Calero
Venue: Proceedings of the 9th European conference on Advances in Case-Based Reasoning (2008)

Our goal is to support system developers in rapid prototyping of Case-Based Reasoning (CBR) systems through component reuse. In this paper, we propose the idea of templates that can be readily adapted when building a CBR system. We define a case base of templates for case-based recommender systems. We devise a novel case-based template recommender, based on recommender systems research, but using a new idea that we call Retrieval-by-Trying. Our experiments with the system show that similarity based on semantic features is more effective than similarity based on behavioural features, which is in turn more effective than similarity based on structural features.
Open Community Authoring of Targeted Worked Example Problems
Authors: Turadg Aleahmad, Vincent Aleven, Robert Kraut
Venue: Proceedings of the 9th international conference on Intelligent Tutoring Systems (2008)

Open collaborative authoring systems such as Wikipedia are growing in use and impact. How well does this model work for the development of educational resources? In particular, can volunteers contribute materials of sufficient quality? Could they create resources that meet students' specific learning needs and engage their personal characteristics? Our experiment explored these questions using a novel web-based tool for authoring worked examples. Participants were professional teachers (math and non-math) and amateurs. Participants were randomly assigned to the basic tool, or to an enhanced version that prompted authors to create materials for a specific (fictitious) student. We find that while there are differences by teaching status, all three groups make contributions of worth and that targeting a specific student leads contributors to author materials with greater potential to engage students. The experiment suggests that community authoring of educational resources is a feasible model of development and can enable new levels of personalization.
General AFIPS History of Computing Activities
Venue: IEEE Annals of the History of Computing (1979)

It certainly seems appropriate that in the first issue of this new journal involving computing history, which AFIPS is launching, there should be a description of what is also AFIPS' first major venture into a broad based spectrum of activities in the area of computing history. It is the purpose of this article to describe these AFIPS activities and plans, and simultaneously to encourage all readers to participate, either actively or supportively. 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
Restoring the Patient Control over Her Medical History
Authors: Nicolas Anciaux, Mehdi Benzine, Luc Bouganim, Kévin Jacquemin, Philippe Pucheral, Shaoyi Yin
Venue: Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems (2008)

Paper-based folders have been widely used to coordinate cares in medical-social networks, but they introduce some burning issues (e.g. privacy protection, remote access to the folder). Replacing the paper-based folder system by a traditional Electronic Healthcare Record (EHR) introduces new drawbacks: forcing of the patient consent, unbounded data retention, no security guarantee outside the server domain and no disconnected access to the folder. To solve these problems, this paper proposes an experimental platform which combines an EHR system with medical-social folders embedded in a new hardware portable device. The objectives pursued are (1) to re-establish a natural and powerful way of protecting and sharing highly sensitive information among trusted parties and (2)to build a shared medical-social folder providing the highest degree of availability, whatever the mode of operation (disconnected or not).
On the Limits of Payload-Oblivious Network Attack Detection
Authors: M. Patrick Collins, Michael K. Reiter
Venue: Proceedings of the 11th international symposium on Recent Advances in Intrusion Detection (2008)

We introduce a methodology for evaluating network intrusion detection systems using an observable attack space, which is a parameterized representation of a type of attack that can be observed in a particular type of log data. Using the observable attack space for log data that does not include payload (e.g., NetFlow data), we evaluate the effectiveness of five proposed detectors for bot harvesting and scanning attacks, in terms of their ability (even when used in conjunction) to deter the attacker from reaching his goals. We demonstrate the ranges of attack parameter values that would avoid detection, or rather that would require an inordinately high number of false alarms in order to detect them consistently.
Proceedings of the Second ACM-IEEE international symposium on Empirical software engineering and measurement
Venue: Empirical Software Engineering and Measurement (2008)

It is my great pleasure to welcome you to the Second International Symposium on Empirical Software Engineering and Measurement (ESEM 2008) in Kaiserslautern, Germany. Empirical software engineering and measurement are important sub-disciplines aimed at advancing software engineering towards an engineering discipline. They focus on measurement in order to better understand, control, and improve software development processes, and on empirical studies to better model products and processes and understand process products. The 1st ESEM was held in Madrid in September 2007. Although this is only the second ESEM symposium, this series continues the long tradition of two high-quality conference series. ESEM resulted from the merger of the IEEE/ACM International Symposium on Empirical Software Engineering (ISESE) and the IEEE International Software Metrics Symposium (METRICS). ISESE was held five times, first in Japan in 2002 and last in Brazil in 2006. As its name suggests, ISESE's primary goal was to disseminate knowledge on and from experimental research on software engineering. METRICS is a long-standing conference series, which was held first in the United States in 1999 and last in Italy in 2005. METRICS' foremost objective was to disseminate knowledge on and from research on software metrics. ESEM 2008 is part of the week-long Experimental Software Engineering International Week (ESEIW) in Kaiserslautern, Germany. It is an honor to welcome this conference to Kaiserslautern. Kaiserslautern has evolved into one of the premier centers for software & systems research in Europe. About 800 scientists and engineers -- spread across 3 departments of the University of Kaiserslautern and several institutes -- are working on advancing the state of the art in our field. The institutes include a Max-Planck Institute on Software Systems, two Fraunhofer Institutes -- for Industrial Mathematics (ITWM) and Experimental Software Engineering (IESE) -- and the German Research Institute for Artificial Intelligence (DFKI). I invite you to learn more about any of these institutes during your stay. We have a full two-day program of three parallel tracks on each day including two keynotes, technical papers, short papers, and a panel (please see the message from the Program Chairs for details).
Content-Based Retrieval of Medical Images by Continuous Feature Selection
Authors: Pedro Henrique Bugatti, Marcela Xavier Ribeiro, Agma Juci Machado Traina, Caetano Traina Junior
Venue: Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems (2008)

Feature selection can significantly improve the precision of content-based queries in image databases by removing noisy features or by bursting the most relevant ones. Continuous feature selection techniques assign continuous weights to each feature according to their relevance. In this paper, we propose a supervised method for continuous feature selection. The proposed method applies statistical association rules to find patterns relating low-level image features to high-level knowledge about the images, and it uses the patterns mined to determine the weight of the features. The feature weighting through the statistical association rules reduces the semantic gap that exists between low-level features and the high-level user interpretation of images, improving the precision of the content-based queries. Moreover, the proposed method performs dimensionality reduction of image features avoiding the "dimensionality curse" problem. Experiments show that the proposed method improves the precision of the query results up to 38%, indicating that statistical association rules can be successfully employed to perform continuous feature selection in medical image databases.
Virtual Workspace Based Job Execution Methods and Dynamic Makespan Optimized Scheduling Algorithms
Authors: Zhili Cheng, Zhihui Du, Yinong Chen, Xiaoying Wang
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems Workshops (2008)

The virtualization technology is helpful to support grid QoS. A manual configuration method and an automatic configuration method are designed to build the virtual workspace environment based on virtualization technology. Both the MetaServices and the automatic configuration software are employed to establish the virtual workspace environment. For dynamic jobs, the corresponding Dynamic Makespan Optimized (DMO) scheduling algorithms are developed. Results of the simulation experiments demonstrate that, compared to models without virtualization support, the job execution methods and DMO scheduling algorithms proposed in this paper can achieve higher throughput, optimize job makespan, and improve the QoS of grid systems.
Vision-Based 3D Articulated Pose Tracking Using Particle Filtering and Model Constraints
Authors: Fawang Liu, Gangyi Ding, Xiao Deng, Yihua Xu
Venue: Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System (2007)

We describe a probabilistic approach for 3D upper body pose tracking by fusing depth, color and underlying body constraints. Existing tracking algorithms can be roughly divided into model-free and model-based methods. Probabilistic assembly of parts falls into model-free category. An important advantage of this technique is that pose can be estimated independently at each frame, allowing estimation for rapid movements, but most such approaches only get 2D tracking results. The use of an explicit model is the most widely investigated methodology, but often suffers from high computational costs. In this paper, we employ particle filtering to get candidate body parts with salient features, integrate probabilistic assembly of parts with model constraints to get the best pose configuration. Experimental results show that our approach can robustly track human motion even when hands move rapidly or self-occlusion exists, and can also automatically initialize and recover from tracking failure.
Optimizing distributed systems using swarm intelligence
Authors: Calin Ciufudean
Venue: Proceedings of the 10th WSEAS International Conference on Mathematical Methods and Computational Techniques in Electrical Engineering (2008)

In this paper we focus our discussion on techniques for the prediction and optimization of scheduling tasks of distributed systems. In order to perform this, considering that modern production systems are complex ones and involve a large amount of equipments, we use the swarm intelligence formalism, and for modeling clearly the necessary synchronization of these systems a Petri net model is used. We focus our research area on the performance optimization of an event graph with random firing times. We have an upper bound and a lower bound for the average cycle time of event graphs knowing the initial marking. We propose an algorithm to evaluate the bounds used to calculate an average cycle time. An application of the results to the evaluation of a Kanban system is proposed.
Detection of Masses in Digital Breast Tomosynthesis Mammography: Effects of the Number of Projection Views and Dose
Authors: Heang-Ping Chan, Jun Wei, Yiheng Zhang, Berkman Sahiner, Lubomir Hadjiiski, Mark A. Helvie
Venue: Proceedings of the 9th international workshop on Digital Mammography (2008)

We are developing a computer-aided detection (CAD) system for masses on digital breast tomosynthesis mammograms (DBT). A data set of DBT from patients was collected with informed consent using a GE prototype DBT system. The system has an Rh/Rh x-ray source and a CsI/a:Si detector, and acquires 21 projection view (PV) images over a 60º arc in 3º increments. The total dose of the 21 PVs is set to be about 1.5 times of the dose of a single screen-film mammogram. In this preliminary study, the DBTs from 50 patients are reconstructed with a simultaneous algebraic reconstruction technique (SART) in two conditions: one using all 21 PVs in 3º increments and the other 11 PVs in 6º increments. The latter therefore uses a subset of the PVs and about half the dose of the former. We compared the mass detection accuracy in these two sets of DBTs using the same CAD system. The system first identifies locations of mass candidates in the DBT volume using 3D gradient field analysis. The mass candidates are then segmented by 3D region growing. Morphological, gray level, and texture features are extracted from the segmented objects. A linear discriminant analysis (LDA) classifier with stepwise feature selection is designed by leave-one-out resampling. The output of the LDA is a mass likelihood score to which a decision threshold is applied and a free-response receiver operating characteristic (FROC) curve is generated. For the DBT set reconstructed with 21 PVs, the system achieved an 80% sensitivity at an average false positive (FP) rate of 1.52 per DBT volume. For the DBT set reconstructed with 11 PVs, the FP rate was 2.38 per breast at the same sensitivity. The difference in the FROC curves for the two conditions was statistically significant (p=0.03) by alternative FROC analysis. When the subset of 14 malignant cases was analyzed, the average FP rates were 0.87 and 1.11 per DBT volume at a sensitivity of 80% for the 21-PV and 11-PV conditions, respectively. The difference in the FROC curves for this smaller subset did not achieve statistical significance.
Proxy data transfer system with a stable control channel and dynamically changing data channels
Authors: Akira Nagata, Shinya Yamamura, Masato Uchida, Masato Tsuru
Venue: Proceedings of the third ACM workshop on Challenged networks (2008)

The present paper introduces the Proxy Data Transfer system, which enables file transfer applications to work over long delays and leaky or frequently disconnecting networks (referred to hereinafter as a "challenged environment"), in which traditional end-to-end communication does not work well. An important feature is that the satellite link is applied to the control channel with a low data rate in order to achieve sustainability over a very large area. We developed a prototype and conducted an experiment using the Japanese engineering testing satellite "KIKU no.8" in May of 2008. An experiment using KIKU no.8 will be described and a live demonstration in an emulated network environment will be given at CHANTS2008.
An Introduction to iTasks: Defining Interactive Work Flows for the Web
Authors: Rinus Plasmeijer, Peter Achten, Pieter Koopman
Venue: Central European Functional Programming School: Second Summer School, CEFP 2007, Cluj-Napoca, Romania, June 23-30, 2007, Revised Selected Lectures (2008)

In these lecture notes we present the iTasks system: a set of combinators to specify work flows in a pure functional language at a very high level of abstraction. Work flow systems are automated systems in which tasks are coordinated that have to be executed by either humans or computers. The combinators that we propose support work flow patterns commonly found in commercial work flow systems. In addition, we introduce novel work flow patterns that capture real world requirements, but that can not be dealt with by current systems. Compared with most of these commercial systems, the iTasks system offers several further advantages: tasks are statically typed, tasks can be higher order, the combinators are fully compositional, dynamic and recursive work flows can be specified, and last but not least, the specification is used to generate an executable web-based multi-user work flow application. With the iTasks system, useful work flows can be defined which cannot be expressed in other systems: a work can be interrupted and subsequently directed to other workers for further processing. The iTasks system has been constructed in the programming language Clean, making use of its generic programming facilities, and its iData toolkit with which interactive, thin-client, form-based web applications can be created. In all, iTasks are an excellent case of the expressive power of functional and generic programming.
The effect of new product development acceleration approaches on development speed: A case study
Authors: Fred Langerak, Erik Jan Hultink
Venue: Journal of Engineering and Technology Management (2008)

This study investigates the impact of nine new product development (NPD) acceleration approaches on development speed. Our findings from 233 manufacturing firms show that 5 approaches (supplier involvement, lead user involvement, speeding up activities and tasks, training and rewarding of employees, and simplification of organizational structure) increase development speed, whereas 2 approaches (implementing support systems and techniques and stimulating inter-functional coordination) decrease development speed. Two approaches (i.e., reduction of parts and components and emphasizing the customer) have no effect on development speed. Our results further show that firms developing different types of new products should use different NPD acceleration approaches, as the speed impact of six out of nine approaches is dependent upon the degree of product innovativeness.
Goal Generation with Ordered Beliefs
Authors: Célia Costa Pereira, Andrea G. Tettamanzi
Venue: Proceedings of the 10th Congress of the Italian Association for Artificial Intelligence on AI*IA 2007: Artificial Intelligence and Human-Oriented Computing (2007)

A rational agent adopts (or changes) its desires/goals when new information becomes available or its "desires" (e.g., tasks it is supposed to carry out) change. In conventional approaches on goal generation a desire is adopted if and only if all conditions leading to its generation are satisfied. The fact that certain beliefs might be differently relevant in the process of desire/goal generation is not considered. As a matter of fact, a belief could be crucial for adopting a given goal but less crucial for adopting another goal. Besides, a belief could be more influent than another in the generation of a particular goal.We propose an approach which takes into account the relevance of beliefs (more or less useful and more or less prejudicial) in the desire/goal generation process. More precisely, we propose a logical framework to represent changes in the mental state of an agent depending on the acquisition of new information and/or on the arising of new desires, by taking into account the fact that some beliefs may help the generation of a goal while others may prevent it.We compare this logical framework with one where relevance of beliefs is not accounted for, and we show that the novel framework favors the adoption of a broader set of goals, exhibiting a behavior which imitates more faithfully how goals are generated/adopted in real life.
Design of the Intelligent Real-Time Hypertensive Diagnosis Expert System Based on Web
Authors: Dai Sheng-hui, Gui Ying, Zhu Xue-qin
Venue: Proceedings of the 2008 International Symposiums on Information Processing (2008)

Hypertension is a serious disease, which can affect the life of persons. However, access to medical care is sometimes very difficult for people living in rural and underserved areas. They have to trek long distances for a medical diagnosis. We propose a medical network based on state-of-the-art medical kiosk that addresses the problems of providing preventive and diagnostic health care. The patients can directly enter and can be screened for hypertensive with all the necessary tests that are intelligent. The intelligent real-time hypertensive diagnosis expert system runs on a Tele health server and is connected to the kiosk through the internet. Based on the symptoms, tests taken and previous history of the patient, a prescription is generated by the expert system that is also sent to a hospital where the doctor is online. Any changes required can be made by the physician in the diagnosis and prescription generated by the expert system and sent to the patient at the kiosk end as a printout. This paper presents the structure of a web-based telehealth system employing expert system rules to detect for a fully automatic hypertension screening system.
Sensor network localization, euclidean distance matrix completions, and graph realization
Authors: Yichuan Ding, Nathan Krislock, Jiawei Qian, Henry Wolkowicz
Venue: Proceedings of the first ACM international workshop on Mobile entity localization and tracking in GPS-less environments (2008)

We study Semidefinite Programming, SDP, relaxations for Sensor Network Localization, SNL, with anchors and with noisy distance information. The main point of the paper is to view SNL as a (nearest) Euclidean Distance Matrix, EDM, completion problem and to show the advantages for using this latter, well studied model. We first show that the current popular SDP relaxation is equivalent to known relaxations in the literature for EDM completions. The existence of anchors in the problem is not special. The set of anchors simply corresponds to a given fixed clique for the graph of the EDM problem. We next propose a method of projection when a large clique or a dense subgraph is identified in the underlying graph. This projection reduces the size, and improves the stability, of the relaxation. In addition, the projection/reduction procedure can be repeated for other given cliques of sensors or for sets of sensors, where many distances are known. Thus, further size reduction can be obtained.