ppxscal/embedding_network huggingface dataset:
NDX-100: An Electronic Filing Machine for the Office of the Future
Authors: J. Slonim
Venue: Computer (1981)

This distributed microprocessor-based filing system will not only replace those familiar grey cabinets it will be part of the advanced communications system of the office of the future.
Nested Named Entity Recognition in Historical Archive Text
Authors: Kate Byrne
Venue: Proceedings of the International Conference on Semantic Computing (2007)

This paper describes work on Named Entity Recognition (NER), in preparation for Relation Extraction (RE), on data from a historical archive organisation. As is often the case in the cultural heritage domain, the source text includes a high percentage of specialist terminology, and is of very variable quality in terms of grammaticality and completeness. The NER and RE tasks were carried out using a specially annotated corpus, and are themselves preliminary steps in a larger project whose aim is to transform discovered relations into a graph structure that can be queried using standard tools. Experimental results from the NER task are described, with emphasis on dealing with nested entities using a multi-word token method. The overall objective is to improve access by non-specialist users to a valuable cultural resource.
Workshop Report: A Computer Element Technology Update
Authors: M. F. Slana
Venue: Computer (1977)

The IEEE Computer Society's Technical Committee on Computer Elements held its annual workshop last June in Vail, Colorado. Below, Matt Slana of Bell Labs summarizes the highlights. As is traditional practice with most Computer Society workshops, a candid exchange of points of view was encouraged by guaranteeing anonymity for all speakers...which explains why no speakers are identified or quoted in the report.
Ultrasound Image-Based Visual Servoing of a Surgical Instrument Through Nonlinear Model Predictive Control
Authors: Mickaël Sauvée, Philippe Poignet, Etienne Dombre
Venue: International Journal of Robotics Research (2008)

Ultrasound image-guided interventions are widespread in surgery because of the non-invasive character of the procedures. However, hand/eye synchronization is relatively difficult for a surgeon. Ultrasound image-based visual servoing is one way to perform this kind of surgery. In this work, the control of instrument motion based on ultrasound images through nonlinear model predictive control is investigated. This new scheme ensures the convergence of the instrument to the desired position and also offers the possibility of satisfying constraints such as joint limits, actuator saturation and visibility preserving. This paper describes the proposed controller. The efficiency and the robustness of the proposed solution to control a six degree-of-freedom mechanical system is first illustrated by simulation. Experiments on a Mitsubishi PA10 robot highlight the efficiency of the vision control scheme to handle constraints of ultrasound image-based visual servoing.
Detecting faults in heterogeneous and dynamic systems using DSP and an agent-based architecture
Authors: Osama Zaki, Keith Brown, John Fletcher, David Lane
Venue: Engineering Applications of Artificial Intelligence (2007)

This paper demonstrates the use of multi-agent systems (MAS), firstly as a modelling technique for dynamic physical systems and secondly as the basis for a generic and powerful diagnostic system, which can support heterogeneous distributed systems. First an overview of the diagnostic techniques including those offered by the two communities fault detection and isolation (FDI ) and DX (based on intelligent techniques) is given. The use of digital signal processing (DSP) as a significant technique for improved fault diagnosis is illustrated. A rule-based engine is used to control the behaviours of the agents and also as a tool for diagnosis. Finally, the integration of DSP agents and the rule-based engine into MAS is demonstrated using a real-life application, a class-AB amplifier (a power electronic circuit). It is shown that the integration of DSP agents and rules into MAS provides a powerful tool for prognosis and for detection of abrupt (short and open circuit) and incipient faults.
Constructing Role-Based Access Control and Delegation Based on Hierarchical IBS
Authors: Jin Wang, Daxing Li, Qiang Li, Bai Xi
Venue: Proceedings of the 2007 IFIP International Conference on Network and Parallel Computing Workshops (2007)

Authentication and authorization are crucial for information and system security. Role-based delegation based on role-based access control (RBAC) can act as an efficient means of authorization management in distributed collaborative environment. In this paper, we present a scheme that integrates hierarchical identity-based signature (Hierarchical IBS) technique to perform role-based access control and role-based delegation. In our suggestion, original user-role assignment relation can be regarded as a particular form of one-depth delegation. We eliminate the use of digital certificates, and handle the multidepth role-based delegation based on hierarchical identity-based signature scheme [8]. Our access control process can provide both aspects of user authentication and role-based authorization simultaneously, so the independent authentication procedure is eliminated. We also prove the security of our scheme in the random oracle model.
Problems encountered by novice pair programmers
Authors: Brian Hanks
Venue: Journal on Educational Resources in Computing (JERIC) (2008)

In a study of the types of problems encountered by students that led them to seek assistance, Robins et al. [2006] found that the most common problems were related to trivial mechanics. The students in this study worked by themselves on their programming exercises. This article discusses a replication of the Robins et al. study in which the subjects pair programmed. The types of problems encountered by the pairing students were similar to those of the solo students. The number of problems requiring assistance was much smaller for the pairing students, which suggests that they were able to resolve more problems on their own.
The State of the Art in Grid Scheduling Systems
Authors: Yi Jian, Yanbing Liu
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 04 (2007)

The overall increase in traffic on the Internet is augmenting scheduling performance from the traditional network, especially in conjunction with heterogeneous, scattered and geographically distributed resources spreading in multiple administrative domains. This article will focus on grid scheduling system architectures that consist of multiple resources distributed on various management areas, with one especial mechanism to assign adequate resource and schedule user's jobs among administrative domains. Moreover, it classifies and describes main mechanisms to allocate grid resources dynamically and execute job scheduling across different areas, discussing both the alternative architectures and the resource sharing policies. It also identifies some of open research issues associated with the use of current grid scheduling system.
Using Interactive Video Technology for the Development of Game-Based Learning
Authors: Han-Bin Chang, Hui-Huang Hsu, Timothy K. Shih
Venue: Proceedings of the 2007 International Conference on Parallel Processing Workshops (2007)

Interactive video technologies are developed for providing interactions for users to get better interactivity in watching TV programs. Since receiving TV programs is a common affair for general users, many systems with interactive TV technologies are implemented for educational or commercial purposes. Learning by playing game is a hot topic in current distance learning systems. Most of game-based learning systems designed by computer programmers and domain experts. Generating interactive game courses is hard for content providers since they are not computer experts. The interactive game authoring tool proposed in this paper provides a friendly interface to help the users to create their educational games easily. The students will be attracted in such learning platform with entertaining elements.
Efficient Identity-based Signature Scheme with Partial Message Recovery
Authors: Yong Li, Huiyan Chen
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 01 (2007)

Signature schemes with message recovery have been investigated a decade ago in the literature, but the first identity-based signature with message recovery was put forth until 2005. In this paper, we present a new identity-based signature scheme with message recovery (IBSMR) based on bilinear map, which is more efficient than the previous scheme. This new scheme shortens the total length of the original message and the appended signature. Furthermore, the IBSMR scheme can deal with any message with arbitrary length. Our scheme is proved secure against existential forgery on adaptive chosen message and ID attack in the random oracle model.
People in DP: the 1980s
Authors: Ann Work
Venue: ACM SIGCPR Computer Personnel (1980)

Twenty years ago, applications were run one at a time in batch processing mode. To generate a report, a card deck was submitted. The results might not come back until the next day. Data was grouped by organizational component: there were accounting files, purchasing files, marketing files production files - each department had a different set of files. The same data might be represented in several files in different formats. 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
Facial Expression Recognition using AAM and Local Facial Features
Authors: Fangqi Tang, Benzai Deng
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 02 (2007)

A new technique for facial expression recognition is proposed, which uses Active Appearance Model (AAM) to extract facial feature points and combines useful local shape features to form a classifier. To enhance performance of AAM, we use Adaboost to locate eye position to initialize AAM. After extraction of facial feature points, we analyze local facial changes and use some simple features to form an effective classifier. At last, we demonstrate our approach by experiments.
Risk Mitigation Tactics for Planning and Monitoring Global Software Development Projects
Authors: Mathew Bass, Michael Smith, Raghvinder S. Sangwan
Venue: Proceedings of the International Conference on Global Software Engineering (2007)

This tutorial describes a structured approach for determining the GSD related risks specific to a given project, selecting appropriate tactics for addressing these risks, and suggesting ways in which the level of risk can be monitored during the execution of the project.
Survivability evaluation of SIGMA and mobile IP
Authors: Shaojian Fu, Mohammed Atiquzzaman
Venue: Wireless Personal Communications: An International Journal (2007)

Mobile IP has been developed by IETF to handle mobility of Internet hosts at the network layer. Mobile IP suffers from a number of drawbacks, including low survivability due to single-point failure of Home Agents. Recently, Seamless IP diversity based Generalized Mobility Architecture (SIGMA) was proposed to support low latency, low packet loss mobility of IP hosts. In this paper, we show that the location management scheme used in SIGMA enhances the survivability of the SIGMA-based mobile network. We develop an analytical model to evaluate and compare the survivability of SIGMA with that of Mobile IP. Numerical results show the improvement in system response time and service blocking probability of SIGMA over Mobile IP in the presence of hardware failures and Distributed Denial of Service (DDoS) attacks.
A Real-time Vision-based Vehicle Tracking and Traffic Surveillance
Authors: Zhi-fang Liu, Zhisheng You
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 01 (2007)

A vision-based detecting and tracking vehicle in video streams is an important research in computer vision, and it plays an important role in ITS. The aim of motion detection is to get the changed region from the background image in video sequences, and it is also very important for targets classification and tracking motion objects. In this paper, a self-adaptive background subtraction method for vehicle segmentation was proposed. To indicate motion mask regions in a scene, instead of determining the threshold value manually, we use an adaptive thresholding method to automatically choose the threshold value. In order to accurately locate vehicle, we combined the projection of the difference image and the projection of the edge map from coarse to refine accurately locate vehicles. This proposed method could locate vehicle well. We formed an association graph between the regions from the previous frame and the regions from the current frame, so we modeled the vehicle tracking problem as a problem of finding maximal weight association graph. Very promising experimental results are provided using real-time video sequences, Experimental results demonstrate the validity of the approach in term of robustness, accuracy and time responses.
Collaborative Workflow Management for eGovernment
Authors: Christian Wolter, Henrik Plate, Cedric Hebert
Venue: Proceedings of the 18th International Conference on Database and Expert Systems Applications (2007)

eGovernment has become reality: Most governmental organisations offer electronic services to citizens through the Internet. However, inter-organizational collaboration, especially by means of workflows, is not as widespread. To foster transparency and control in collaborative workflows according to global policies, such as European law regulations, collaborative partners have to partially provide insight into local events and workflows to comply to the global regulations. An example collaboration between Eurojust and Europol emphasises the shortage of existing collaboration architectures lacking the desired control and transparency capabilities needed for the application domain of human-centric eGovernment workflows. To address this, we propose an architecture of a modular runtime infrastructure for decentralized, collaborative eGovernment workflows, hereby respecting the heterogeneity of the system and application landscapes in place.
A Graph Reduction Approach to Symbolic Circuit Analysis
Authors: Guoyong Shi, Weiwei Chen
Venue: Proceedings of the 2007 Asia and South Pacific Design Automation Conference (2007)

A new graph reduction approach to symbolic circuit analysis is developed in this paper. A Binary Decision Diagram (BDD) mechanism is formulated, together with a specially designed graph reduction process and a recursive sign determination algorithm. A symbolic analog circuit simulator is developed using a combination of these techniques. The simulator is able to analyze large analog circuits in the frequency domain. Experimental results are reported.
Performance Criteria in Inter-Organizational Global Software Development Projects
Authors: Timo Poikolainen, Juha Paananen
Venue: Proceedings of the International Conference on Global Software Engineering (2007)

Clear and well aligned performance criteria are fundamentally important in global software development projects. We found significant diversity in performance criteria between different projects done by a single company. The performance criteria were clear and aligned in simpler projects, whereas there was a lot of ambiguity in performance criteria in complex projects. The clarity of the performance criteria seems to have a positive effect on the project performance. Meeting the end-user needs was identified as a key performance criterion, and was often not properly covered in the project requirements or in explicit performance criteria. Long term view to project performance and management of expectations between the teams has an effect to project performance. Our research is based on a study of 18 inter-organizational software development projects in Nokia Corporation during 2006.
DEUCE: Separating Concerns in User Interfaces
Authors: Sofie Goderis, Dirk Deridder, Ellen Van Paesschen
Venue: Proceedings of the International Conference on Software Engineering Advances (2007)

As current software systems evolve continuously, both the application and its user interface (UI) have to be adapted. However, UI code is often scattered through and entangled with the application code. In large and complex UIs, this tangling renders the implementation complex and hard to maintain. The Deuce framework (Declarative User Interface Concerns Extrication) intends to reduce the complexity of UI implementations by applying separation of concerns on three UI concerns: presentation logic, business and data logic, and connection logic. It does so by using a declarative meta-language (SOUL) on top of an object oriented language (Smalltalk) such that an adequate language is provided to describe the entire structure and behavior of the UI, as well as linking it with the application.
A hybrid entropic proximal decomposition method with self-adaptive strategy for solving variational inequality problems
Authors: Deren Han
Venue: Computers Mathematics with Applications (2008)

In this paper, we propose a hybrid nonlinear decomposition-projection method for solving a class of monotone variational inequality problems. The algorithm utilizes the problems' structure conductive to decomposition and a projection step to get the next iterate. To make the method more practical, we allow solving of the subproblems approximately and adopt the constructive accuracy criterion developed recently by Solodov and Svaiter for classical proximal point algorithm and by the author for generalized proximal point algorithm. The Fejer monotonicity to the solution set of the problem is obtained by only assuming the underlying mapping is monotone and the solution set is nonempty. The parameter is allowed to vary in a larger interval than that of Auslender and Teboulle, and we also propose some improved self-adaptive strategies to choose the sequence of parameters, which makes the algorithm more flexible.
Birds-of-a-feather: where would you like to see GNAT go?
Authors: Robert Dewar
Venue: Proceedings of the 2007 ACM international conference on SIGAda annual international conference (2007)

This BOF will discuss future directions for the GNAT technology, including both the GAP and Pro versions. We at AdaCore will give some of our thoughts on interesting future possibilities, but mostly we would like to hear from the user community, so we see this session as an open discussion of interesting ideas for the future. This is a chance for you to say what you want, and have your ideas discussed!
Combining neural networks, fuzzy sets, and the evidence theory based techniques for detecting colour specks
Authors: A. Verikas, K. Malmqvist, M. Bacauskiene
Venue: Journal of Intelligent Fuzzy Systems: Applications in Engineering and Technology (2001)

An approach to detecting colour specks in an image taken from a pulp sample of recycled paper is presented. The task is solved through pixel-wise colour classification by an artificial neural network and post-processing based on the evidence theory. The network is trained using possibilistic target values, which are determined through a self-organising process in a 2D and 1D map of chromaticity and lightness, respectively. The problem of post-processing of a pixelwise-classified image is addressed from the point of view of the Dempster-Shafer theory of evidence. Each neighbour of a pixel being analysed is considered as an item of evidence supporting particular hypotheses regarding the class label of that pixel. The strength of support is defined as a function of the degree of uncertainty in class label of the neighbour, and the distance between the neighbour and the pixel being considered. The experiments performed have shown that the colour classification results correspond well with the human perception of colours of the specks.
Speaker Identification Based on Multi-reduced SVM
Authors: Ming Li, Xueyan Liu, Fuwen Wu
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 03 (2007)

SVM is a novel type of statistical learning methods that has been successfully used in speaker recognition. However, Training SVM consumes long computing time and large memory with all training data. This paper proposes a speaker identification method based on Multi- Reduced support vector machine (MRSVM). MRSVM has two reduction steps. Firstly, speech feature dimensions are reduced by using KL transform, the noise is removed from speech simultaneity. Secondly, speech feature data are selected at boundary of each cluster as SVs by using Kernel-based fuzzy clustering technique. Experiment results show that not only the training data, training time and storage can be reduced remarkably, but also the identification accuracy can be improved by the proposed MRSVM compared with other reduced algorithms and the system has better robustness.
Analysis of Chordal Ring Network
Authors: B. W. Arden
Venue: IEEE Transactions on Computers (1981)

A family of regular graphs of degree 3, called Chordal Rings, is presented as a possible candidate for the implementation of a local network of message-connected (micro) computers. For a properly constructed graph in this family having n nodes the diameter, or maximum length message path, is shown to be of 0(n 1/2). The symmetry of the graphs makes it possible to determine message routing by using a simple distributed algorithm. The given algorithm is also potentially useful for the determination of alternate paths in the event of node or link failure.
Learning Repetitive Patterns for Classifying Non-Rigidly Deforming Texture Surfaces
Authors: Roman Filipovych, Eraldo Ribeiro
Venue: Proceedings of the 14th International Conference on Image Analysis and Processing (2007)

In this paper, we address the relatively unexplored problem of classifying texture surfaces undergoing significant levels of non-rigid deformation. State-of-the-art texture classification methods have demonstrated to be very effective for classifying fronto-parallel texture fields. Recently, affine-invariant descriptors have been proposed as an effective way to model local perspective distortion in textures. However, if the effects of local surface curvature distortion are large, affine-invariant descriptors become unreliable. Our contribution in this paper is twofold. First, we propose a method for learning representative basic elements of non-fronto-parallel texture fields undergoing non-rigid deformations. Secondly, we demonstrate the effectiveness of our texture learning method for the classification of nonrigid deforming texture surfaces. We test our method on a set of images obtained from man-made texture surfaces.