ppxscal/embedding_network huggingface dataset:
The Approximation and Computation of a Basis of the Trace Space H1/2
Authors: Petr Klouček, Danny C. Sorensen, Jennifer L. Wightman
Venue: Journal of Scientific Computing (2007)

We present a method for construction of an approximate basis of the trace space H 1/2 based on a combination of the Steklov spectral method and a finite element approximation. Specifically, we approximate the Steklov eigenfunctions with respect to a particular finite element basis. Then solutions of elliptic boundary value problems with Dirichlet boundary conditions can be efficiently and accurately expanded in the discrete Steklov basis. We provide a reformulation of the discrete Steklov eigenproblem as a generalized eigenproblem that we solve by the implicitly restarted Arnoldi method of ARPACK. We include examples highlighting the computational properties of the proposed method for the solution of elliptic problems on bounded domains using both a conforming bilinear finite element and a non-conforming harmonic finite element. In addition, we document the efficiency of the proposed method by solving a Dirichlet problem for the Laplace equation on a densely perforated domain.
Automatic Seal Information Reader
Authors: Farshad Nourbakhsh, Peeta Basa Pati, A. G. Ramakrishnan
Venue: Proceedings of the International Conference on Computing: Theory and Applications (2007)

Seals contain a lot of vital information about the document. Seal detection is a necessary step to gain access to that information. In the present paper, we present a correlation based technique which exploits the existence of some constant character strings and their topology for detection of seals. We also present a technique which separates the false positives from the actual seals. We achieved an accuracy of about 98% for extraction of such kind of seals. Once the seal is extracted from a page image, an OCR has been employed to read the contextual information present in the seal. A knowledge based post-processing step is employed to enhance the accuracy of the recognized text strings.
Low Complexity Multiple Description Coding for H.264/AVC
Authors: Kenneth Vermeirsch, Yves Dhondt, Stefaan Mys, Rik Van de Walle
Venue: Proceedings of the Eight International Workshop on Image Analysis for Multimedia Interactive Services (2007)

Today's wireless networks suffer from high error rates in real-life conditions. Moreover errors tend to occur in large bursts. Multiple Description Coding (MDC) of digital video is a promising technique to overcome these problems in wireless environments by taking advantage of frequency or channel diversity. This papers proposes two low complexity MDC techniques for H.264/AVC at the Network Abstraction Layer level, aiming at conversational (video teleconferencing) and sports Video on Demand (VoD) application scenarios, respectively. For conversational applications, an MDC scheme based on H.264/AVC data partitioning is used, offering low additional delay and good performance for video with static backgrounds. For the sports VoD application, a scheme based on redundant slices is proposed. The latter scheme performs better for high-motion sequences than the former, but also introduces more delay.
Service Supplier Infrastructure for Location-based M-Commerce
Authors: PD Mzila, MO Adigun, SS Xulu
Venue: Proceedings of the Second International Conference on Internet Monitoring and Protection (2007)

Dynamic development and improvement of mobile devices enforces more attention to the manner in which information is handled (storage and management) among participating components in mobile commerce environment. There are many instances when tourists become strangers in foreign countries and become worried about available services in each and every place they visit. These services which are known as location based services are normally available to only subscribers of those services. This research proposes a dynamic service discovery mechanism whereby every mobile user is capable of service discovery irrespective of being a subscriber or not. The research focuses on the structure of location based service supplier's database and the infrastructure, in which participating components interact to enable mobile users in a given coverage area to easily access available services that are provided by suppliers in an advertising form. Through network operators using Mobile Network Coverage Area (MNCA), mobile device's current location is automatically detected. This mechanism occurs when a user with mobile device registers with local network transmitter through which network operators identify its location and inform Location Based Application Server (LBAS) about the current location of the user.
The O3-Vet project: A veterinary electronic patient record based on the web technology and the ADT-IHE actor for veterinary hospitals
Authors: M. Zaninelli, F. M. Tangorra, S. Castano, A. Ferrara, E. Ferro, P. G. Brambilla, S. Faverzani, S. Chinosi, P. Scarpa, M. Di Giancamillo, D. Zani, A. Zepponi, C. Saccavini
Venue: Computer Methods and Programs in Biomedicine (2007)

A veterinary electronic patient record, compliant with the IT standards (HL7, DICOM and IHE), was developed at the School of Veterinary Medicine, University of Milan (Italy) in order to improve the veterinary hospital workflows, making the stored clinical data more homogenous and sharable, thereby increasing the integration with current and future software applications. The system was developed by open-source software in order to reduce the implementation and maintenance costs and to make the system sharable with other veterinary hospitals or research centers without additional costs. The system was tested from May to October 2006. Results show that the majority of the veterinarians involved in the test agreed on the advantages obtained by the use of application software concerning the availability of all the useful clinical data [71.4%], the quality of the diagnostic procedures [78.58%] and the efficiency [85.58%] of hospital activities.
Processor-Level Selective Replication
Authors: Nithin Nakka, Karthik Pattabiraman, Ravishankar Iyer
Venue: Proceedings of the 37th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (2007)

We propose a processor-level technique called Selective Replication, by which the application can choose where in its application stream and to what degree it requires replication. Recent work on static analysis and fault-injection-based experiments on applications reveals that certain variables in the application are critical to its crash- and hang-free execution. If it can be ensured that only the computation of these variables is error-free, then a high degree of crash/hang coverage can be achieved at a low performance overhead to the application. The Selective Replication technique provides an ideal platform for validating this claim. The technique is compared against complete duplication as provided in current architecture-level techniques. The results show that with about 59% less overhead than full duplication, selective replication detects 97% of the data errors and 87% of the instruction errors that were covered by full duplication. It also reduces the detection of errors benign to the final outcome of the application by 17.8% as compared to full duplication.
Generation of optimal finite test suites for timed systems
Authors: Mercedes G. Merayo, Manuel Nunez, Ismael Rodriguez
Venue: Proceedings of the First Joint IEEE/IFIP Symposium on Theoretical Aspects of Software Engineering (2007)

One of the main problems to test timed systems is that the tester has to decide when to apply the next input to the system under test. Even though the tester could determine good sequences of inputs to find a big variety of errors, the quality of the test suite usually depends on the time when the different parts of the sequences are applied. In this paper we give a formal methodology to provide good time values to test timed systems. These values are computed by taking into account the time stability of the system, that is, if the system is more likely to remain in its current internal state during a given time interval then no input will be applied during that period. In other words, our method will (probabilistically) find those time values that are closer to a change of state in the system, being these values more suitable to apply the appropriate input to the system.
Multi-robot Exploration Based on Market Approach and Immune Optimizing Strategy
Authors: Guangming Xiong, Jianwei Gong, Huiyan Chen, Zhibao Su
Venue: Proceedings of the Third International Conference on Autonomic and Autonomous Systems (2007)

A multi-robot system is used to explore an environment and create a map based on market approach. Data fusion is performed using Bayes theorem and then the local maps are updated. A diffusivity concept is defined to describe the robots' extent apart from one another. The immune optimizing strategy is introduced to select goal points since it is a problem of optimized combination. In order to minimize repeated coverage and improve the exploration efficiency, the evaluation function considers the cost, revenue and diffusivity. Simulation examples show that the proposed method is effective for the stated problem and the immune optimizing strategy is more efficient than other strategies.
Agreeing to disagree: search engines and their public interfaces
Authors: Frank McCown, Michael L. Nelson
Venue: Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries (2007)

Google, Yahoo and MSN all provide both web user interfaces (WUIs) and application programming interfaces (APIs) to their collections. Whether building collections of resources or studying the search engines themselves, the search engines request that researchers use their APIs and not "scrape" the WUIs. However, anecdotal evidence suggests the interfaces produce different results. We provide the first in depth quantitative analysis of the results produced by the Google, MSN and Yahoo API and WUI interfaces. We have queried both interfaces for five months and found significant discrepancies between the interfaces in several categories. In general, we found MSN to produce the most consistent results between their two interfaces. Our findings suggest that the API indexes are not older, but they are probably smaller for Google and Yahoo. We also examined how search results decay over time and built predictive models based on the observed decay rates. Based on our findings, it can take over a year for half of the top 10 results to a popular query to be replaced in Google and Yahoo; for MSN it may take only 2-3 months.
Image analysis: a group assignment in programming with breadth
Authors: R. E. Montgomery
Venue: Proceedings of the Frontiers in Education Conference, on 1995. Proceedings., 1995 - Volume 02 (1995)

Problems based on material already familiar to students have some advantage in allowing depth of coverage of computer programming topics. However it is sometimes necessary to force students to cover a wide variety of topics in programming, and it may be necessary or expedient to introduce a problem topic that is unfamiliar to the students to accomplish this. To that end, a problem was utilized in a freshman engineering honors course at Purdue University with applications to printing and robot vision, with a title designed to grab the attention of the students in the classes-"Image Analysis: Halftoning by Grayscale Histogram Thresholding and Edge Detection by Laplacian Convolution". Students were expected to learn a great deal of material, all of which was needed for timely project completion, with coverage provided through regular lectures or supplemental class meetings. The problem to be solved was sufficiently complex that the four-person teams reported little difficulty in splitting up the work so that every team member had sufficient work to do. In spite of the complexity of the assignment, the overwhelming voice heard from the students at semester's end was that they developed incredible amounts of programming skill from the project, and that it definitely should be kept in the course in the future. However, the project may be just a bit ambitious.
The Asymmetry of Image Registration and Its Application to Face Tracking
Authors: Goksel Dedeoglu, Takeo Kanade, Simon Baker
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2007)

Most image registration problems are formulated in an asymmetric fashion. Given a pair of images, one is implicitly or explicitly regarded as a template and warped onto the other to match as well as possible. In this paper, we focus on this seemingly arbitrary choice of the roles and reveal how it may lead to biased warp estimates in the presence of relative scaling. We present a principled way of selecting the template and explain why only the correct asymmetric form, with the potential inclusion of a blurring step, can yield an unbiased estimator. We validate our analysis in the domain of model-based face tracking. We show how the usual Active Appearance Model (AAM) formulation overlooks the asymmetry issue, causing the fitting accuracy to degrade quickly when the observed objects are smaller than their model. We formulate a novel, "resolution-aware fitting” (RAF) algorithm that respects the asymmetry and incorporates an explicit model of the blur caused by the camera's sensing elements into the fitting formulation. We compare the RAF algorithm against a state-of-the-art tracker across a variety of resolutions and AAM complexity levels. Experimental results show that RAF significantly improves the estimation accuracy of both shape and appearance parameters when fitting to low-resolution data. Recognizing and accounting for the asymmetry of image registration leads to tangible accuracy improvements in analyzing low-resolution imagery.
An Efficient Algorithm for Mining Coherent Patterns from Heterogeneous Microarrays
Authors: Xiang Zhang, Wei Wang
Venue: Proceedings of the 19th International Conference on Scientific and Statistical Database Management (2007)

DNA microarray techniques present a novel way for geneticists to monitor interactions among tens of thousands of genes simultaneously, and have become standard lab routines in gene discovery, disease diagnosis, and drug design. There has been extensive research on coherent subspace clustering of gene expressions measured under consistent experimental settings. This implies that all experiments are run using the same batch of microarray chips with similar characteristics of noise. Algorithms developed under this assumption may not be applicable for analyzing data collected from heterogeneous settings, where the set of genes being monitored may be different and expression levels may be not directly comparable even for the same gene. In this paper, we propose a model, F-cluster, for mining subspace coherent patterns from heterogeneous gene expression data, which is shown effective for revealing truthful patterns and reducing spurious ones. We also develop an efficient and scalable hybrid approach that combines gene-pair based and sample-pair based pruning to generate F-clusters from multiple gene expression matrices simultaneously. The experimental results demonstrate that our model can discover significant clusters that may not be identified by previous models.
A New Algorithm for Mining Fuzzy Association Rules in the Large Databases Based on Ontology
Authors: Zahra Farzanyar, Mohammadreza kangavari, Sattar Hashemi
Venue: Proceedings of the Sixth IEEE International Conference on Data Mining - Workshops (2006)

Association rule mining is an active data mining research area. Recent years have witnessed many efforts on discovering fuzzy associations. The key strength of fuzzy association rule mining is its completeness. This strength, however, comes with a major drawback to handle large datasets. It open produces a huge number of candidate itemsets. The huge number of candidate itemsets makes it ineffective for a data mining system to analyze them. To overcome this problem in this study, fuzzy association rule mining system is driven by domain ontology. It describes the use of a concept hierarchy for improving the results of fuzzy association rule mining. Our ontology-based data mining algorithm makes the rules more visual, more interesting and more understandable. At last the paper, the efficiency and advantages of this algorithm has been approved by experimental results.
Integrating interactive digital video techniques in an introductory physics course for non-science majors
Authors: T. L. Hein
Venue: Proceedings of the Frontiers in Education Conference,1997. on 27th Annual Conference. Teaching and Learning in an Era of Change. - Volume 01 (1997)

This study was conducted to incorporate interactive digital video techniques (IDV) into the laboratory portion of an introductory course for nonscience majors at American University in Washington, DC. A total of 68 students in four sections of laboratory participated in the study. Two kinematics experiments were designed. Students in two lab sections performed the experiments using IDV techniques. One aspect of the study involved the assessment of student learning styles in an attempt to determine if students with particular learning preferences had higher learning gains when instruction involved IDV techniques versus when it involved more traditional techniques. Student learning gains were assessed, in part, using the Test of Understanding Graphs-Kinematics (TUG-K). The IDV techniques developed for use in the laboratory are discussed. Quantitative and qualitative results from this study are summarized. Finally, implications for integration of these techniques into the undergraduate curriculum are presented.
Exploiting the Self-Organizing Map for Medical Image Segmentation
Authors: Ping-Lin Chang, Wei-Guang Teng
Venue: Proceedings of the Twentieth IEEE International Symposium on Computer-Based Medical Systems (2007)

As the computer technology advances, data acquisition, processing and visualization techniques have a tremendous impact on medical imaging. On the other hand, however, the interpretation of medical images is still almost performed by radiologists nowadays. Developments in artificial intelligence and image processing show that computer-aided diagnosis emerges with increasingly high potential. In this paper, we develop an intelligent approach to perform image segmentation and thus to discover region of interest (ROI) for diagnosis purposes through the use of self-organizing map (SOM) techniques. Specifically, we propose a two-stage SOM approach which can precisely identify dominant color components and thus segment a medical image into several smaller pieces. In addition, with a proper merging step conducted iteratively, one or more ROIs in a medical image can usually be identified. Empirical studies show that our approach is effective at processing various types of medical images. Moreover, the feasibility of our approach is also evaluated by the illustration of image semantics.
Enhancing the recruitment and retention of first-year students with improved career selection opportunities
Authors: D. McDonald
Venue: Proceedings of the Frontiers in Education Conference on 1995. Proceedings., 1995 vol 1. - Volume 01 (1995)

The paper describes an on going project to improve the persistence of first year engineering technology majors. This project involves a pilot course that uses an experiential learning approach to provide students with an improved understanding of engineering and technology. The team taught course also helps to develop the students' academic support system, including interaction with upper class technology students. Initial evaluations indicate that the students found the attitude of the faculty, the active learning instructional method, and content material helpful in their career selection and persistence in the technical area. 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
Service oriented architectures: approaches, technologies and research issues
Authors: Mike P. Papazoglou, Willem-Jan Heuvel
Venue: The VLDB Journal &mdash; The International Journal on Very Large Data Bases (2007)

Service-oriented architectures (SOA) is an emerging approach that addresses the requirements of loosely coupled, standards-based, and protocol- independent distributed computing. Typically business operations running in an SOA comprise a number of invocations of these different components, often in an event-driven or asynchronous fashion that reflects the underlying business process needs. To build an SOA a highly distributable communications and integration backbone is required. This functionality is provided by the Enterprise Service Bus (ESB) that is an integration platform that utilizes Web services standards to support a wide variety of communications patterns over multiple transport protocols and deliver value-added capabilities for SOA applications. This paper reviews technologies and approaches that unify the principles and concepts of SOA with those of event-based programing. The paper also focuses on the ESB and describes a range of functions that are designed to offer a manageable, standards-based SOA backbone that extends middleware functionality throughout by connecting heterogeneous components and systems and offers integration services. Finally, the paper proposes an approach to extend the conventional SOA to cater for essential ESB requirements that include capabilities such as service orchestration, "intelligent" routing, provisioning, integrity and security of message as well as service management. The layers in this extended SOA, in short xSOA, are used to classify research issues and current research activities.
Intelligent Reconfiguration of Dynamic Distributed Components
Authors: George R. Ribeiro-Justo, Ahmed Saleh, Tereska Karran
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2007)

Naming service and the reconfiguration management systems usually work in a client-server manner where both the selection of components and the reconfiguration are a result of a request. Developing intelligent systems that are capable of monitoring and learning about themselves, and thereby rapidly react to changes in their environment, has become essential to most systems. This paper proposes an extension to FRODICA (Framework for Distributed Configurable Applications), a framework that supports the development of non-functional oriented reconfiguration of distributed systems, using the Complex Organic Distributed Architecture (CODA). CODA applies cybernetic concepts such as self-organisation, self-regulation and viability to derive an intelligent architecture, which can react to failures in achieving its objectives and proactively search for successful patterns of behaviour. The result is a configuration management system, which can use the knowledge of itself to proactively and dynamically drive both the search and the reconfiguration of its components.