ppxscal/embedding_network huggingface dataset:
An integrated view of Grid services, Agents and Human Learning
Authors: Stefano A. Cerri
Venue: Proceeding of the 2005 conference on Towards the Learning Grid: Advances in Human Learning Services (2005)

The contribution reports on three aspects of our research activities on Grid services, Agents and Human learning: an integrated vision, a statement of intentions concerning a relatively new life cycle for Service Engineering and a review of achieved results, presented by embedding remarks and quotations in the relevant points. The essence of the contribution lies in the concept of service that is considered to be intrinsically conversational both during its dynamic definition and during its delivery. It is shown that Agents are the most promising abstractions (and technologies) offering a concrete approximation for future conversational Grid services and that Human learning is a quite suitable context for including the Human in the loop of the higher level services to be developed for mixed Virtual Organizations on future Grid networks.
The academic enhancement program: encouraging students to learn about learning as part of their computing science courses
Authors: Diana Cukierman, Donna McGee Thompson
Venue: Proceedings of the 14th annual ACM SIGCSE conference on Innovation and technology in computer science education (2009)

The Academic Enhancement Program (AEP) at Simon Fraser University has been created to support student learning by integrating activities that introduce students to basic learning theory and strategies into core first-year Computing Science (CS) courses. Program activities include two required workshops run specifically for the CS courses, tailored to course topics. The AEP also includes a third "Elective" component that encourages students to learn about a topic of their choice related to student success and wellness. Students receive course marks for these activities. In this paper we describe how we have developed the program over the past three years and present results about the perceived usefulness of these activities both from student survey responses and from interviews with academic advisors. We also discuss lessons learned. Our findings indicate that such practices are of general benefit to our student population and are promising to address students' academic challenges, possibly having a positive impact on retention.
Utilizing Information Technology Systems Across Disciplines: Advancements in the Application of Computer Science, 1st edition
Authors: Evon Abu-taieh, Jeihan Abu-Tayeh, Asim A. El-Sheikh
Venue:  (2009)

With continual computer advances in the information technology age, information systems have become an integral part of many disciplines. Business, medicine, geography, aviation, forensics, agriculture, even traffic lights all have one thing in common - computers. Utilizing Information Technology Systems Across Disciplines: Advancements in the Application of Computer Science provides original material concerned with all aspects of information resources management, managerial and organizational applications, as well as implications of information technology. An advanced reference work in its field, this book is instrumental in the improvement and development of the theory and practice of information resources management, appealing to both practicing managers and academicians.
Applicability of the willow architecture for cloud management
Authors: Zach Hill, Marty Humphrey
Venue: Proceedings of the 1st workshop on Automated control for datacenters and clouds (2009)

The differences between Grids and Clouds arguably include objectives, organization, scale, and workload. By examining these characteristics and requirements in detail, we assess the degree to which a generic management infrastructure for Grid computing can be applied to Cloud infrastructures. Our analysis is further refined by considering a specific management system, Willow, which we have recently successfully applied to Grid management. Three distinct architectures are evaluated: wholly within the datacenter transparent to users; completely within the user software stack and transparent to the Cloud provider; and, a hybrid in which the system is known to both the provider and the users.
Mining Data and Modelling Social Capital in Virtual Learning Communities
Authors: Ben K. Daniel, Gordon I. McCalla, Richard A. Schwier
Venue: Proceeding of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology (2005)

This paper describes the use of content analysis and Bayesian Belief Network (BBN) techniques aimed at modelling social capital (SC) in virtual learning communities (VLCs). An initial BBN model of online SC based on previous work is presented. Transcripts drawn from two VLCs were analysed and inferences were drawn to build scenarios to train and update the model. The paper presents three main contributions. First, it extends the understanding of SC to VLCs. Second; it offers a methodology for studying SC in VLCs. Third the paper presents a computational model of SC that can be used in the future to understand various social issues critical to effective interactions in VLCs.
More on "Connected (n, m)-graphs with minimum and maximum zeroth-order general Randić index"
Authors: Ljiljana Pavlović, Mirjana Lazić, Tatjana Aleksić
Venue: Discrete Applied Mathematics (2009)

Let G be a graph and d(u) denote the degree of a vertex u in G. The zeroth-order general Randic index ^0R"@a(G) of the graph G is defined as @?"u"@?"V"("G")d(u)^@a, where the summation goes over all vertices of G and @a is an arbitrary real number. In this paper we correct the proof of the main Theorem 3.5 of the paper by Hu et al. [Y. Hu, X. Li, Y. Shi, T. Xu, Connected (n,m)-graphs with minimum and maximum zeroth-order general Randic index, Discrete Appl. Math. 155 (8) (2007) 1044-1054] and give a more general Theorem. We finally characterize for @a
Grooming of Dynamic Traffic in WDM Tree Networks Using Genetic Algorithms
Authors: Shutong Xie, Yinbiao Guo, Yong Xu, Kunhong Liu
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II (2009)

Efficient grooming of traffic can greatly reduce the cost of the network. To deal with the changing traffic in SONET/WDM tree networks, two heuristic algorithms are developed by combining genetic algorithm with traffic-splitting heuristics. To evaluate the algorithms, the bound is also derived. Computer simulations show that the proposed algorithms can achieve good results in reducing the blocking rate of new traffic.
Secondary-storage confidence computation for conjunctive queries with inequalities
Authors: Dan Olteanu, Jiewen Huang
Venue: Proceedings of the 35th SIGMOD international conference on Management of data (2009)

This paper investigates the problem of efficiently computing the confidences of distinct tuples in the answers to conjunctive queries with inequalities ( Our contributions are of both theoretical and practical importance. We define a class of tractable queries with inequalities, and generalize existing results on #P-hardness of query evaluation, now in the presence of inequalities. For the tractable queries, we introduce a confidence computation technique based on efficient compilation of the lineage of the query answer into Ordered Binary Decision Diagrams (OBDDs), whose sizes are linear in the number of variables of the lineage. We implemented a secondary-storage variant of our technique in PostgreSQL. This variant does not need to materialize the OBDD, but computes, in one scan over the lineage, the probabilities of OBDD fragments and combines them on the fly. Experiments with probabilistic TPC-H data show up to two orders of magnitude improvements when compared with state-of-the-art approaches.
GIMIAS: An Open Source Framework for Efficient Development of Research Tools and Clinical Prototypes
Authors: Ignacio Larrabide, Pedro Omedas, Yves Martelli, Xavier Planes, Maarten Nieber, Juan A. Moya, Constantine Butakoff, Rafael Sebastián, Oscar Camara, Mathieu Craene, Bart H. Bijnens, Alejandro F. Frangi
Venue: Proceedings of the 5th International Conference on Functional Imaging and Modeling of the Heart (2009)

GIMIAS is a workflow-oriented environment for addressing advanced biomedical image computing and build personalized computational models, which is extensible through the development of application-specific plug-ins. In addition, GIMIAS provides an open source framework for efficient development of research and clinical software prototypes integrating contributions from the Virtual Physiological Human community while allowing business-friendly technology transfer and commercial product development. This framework has been fully developed in ANSI-C++ on top of well known open source libraries like VTK, ITK and wxWidgets among others. Based on GIMIAS, in this paper is presented a workflow for medical image analysis and simulation of the heart.
Language communities in enterprise architecture research
Authors: Joachim Schelp, Robert Winter
Venue: Proceedings of the 4th International Conference on Design Science Research in Information Systems and Technology (2009)

As a result of the rigor vs. relevance debate, researchers who focus on design research on organizational problems are beginning to focus on their research methodology's rigor. One of the means to lever the standards is the explicit establishment of defined language communities. This paper investigates to what extent current design research focusing on organizational problems is satisfying the requirements to establish such language communities. As research on organizational problems in IS research is still a very broad field, this paper focuses on research on enterprise architecture (EA). It contributes a state of the art overview on EA research regarding the research methodology employed and their language community state. Results show that local language communities in EA research do exist, but still have to lever their standards---both regarding the quality of the language communities and the quality of the design research.
A framework for designing fisheye views to support multiple semantic contexts
Authors: Paul Janecek, Pearl Pu
Venue: Proceedings of the working conference on Advanced visual interfaces (2002)

In this paper we discuss the design and use of fisheye view techniques to explore semantic relationships in information. Traditional fisheye and "focus + context" techniques dynamically modify the visual rendering of data in response to the changing interest of the user. "Interesting" information is shown in more detail or visually emphasized, while less relevant information is shown in less detail, de-emphasized, or filtered. These techniques are effective for navigating through large sets of information in a constrained display, and for discovering hidden relationships in a particular representation. An open area of research with these techniques, however, is how to redefine interest as a user's tasks and information needs change. We are developing a framework for implementing fisheye views to support multiple semantic contexts. The framework is based on two components: Degree Of Interest functions, and visual emphasis algorithms to change the representation of information with respect to interest. The framework supports different contexts through the aggregation of multiple weighted distance metrics in the calculation of interest. Using this framework, we have developed a user-configurable interface for browsing tabular data that visually emphasizes objects with respect to different semantic contexts.
Improving Batch Reinforcement Learning Performance through Transfer of Samples
Authors: Alessandro Lazaric, Marcello Restelli, Andrea Bonarini
Venue: Proceeding of the 2008 conference on STAIRS 2008: Proceedings of the Fourth Starting AI Researchers' Symposium (2008)

The main objective of transfer in reinforcement learning is to reduce the complexity of learning the solution of a target task by effectively reusing the knowledge retained from solving a set of source tasks. One of the main problems is to avoid negative transfer, that is the transfer of knowledge across tasks that are significantly different that may worsen the learning performance. In this paper, we introduce a novel algorithm that selectively transfers samples (i.e., tuples <s,a,s',r>) from source to target tasks and that uses them as input for batch reinforcement-learning algorithms. By transferring samples from source tasks that are mostly similar to the target task, we reduce the number of samples actually collected from the target task to learn its solution. We show that the proposed approach is effective in reducing the learning complexity, even when some source tasks are significantly different from the target task.
Delay-Dependent Exponential Stability of Discrete-Time BAM Neural Networks with Time Varying Delays
Authors: Rui Zhang, Zhanshan Wang, Jian Feng, Yuanwei Jing
Venue: Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks (2009)

In this paper, the global exponential stability is discussed for discrete-time bidirectional associative memory (BAM) neural networks with time varying delays. By the linear matrix inequality (LMI) technique and discrete Lyapunov functional combined with inequality techniques, a new global exponential stability criterion of the equilibrium points is obtained for this system. The proposed result is less restrictive than those given in the earlier literatures, and easier to check in practice. Remarks are made with other previous works to show the superiority of the obtained results, and the simulation example is used to demonstrate the effectiveness of our result.
The bee colony-inspired algorithm (BCiA): a two-stage approach for solving the vehicle routing problem with time windows
Authors: Sascha Häckel, Patrick Dippold
Venue: Proceedings of the 11th Annual conference on Genetic and evolutionary computation (2009)

The paper presents a new optimization algorithm, which adapts the behavior of honey bees during their search for nectar. In addition to the established ant algorithms, bee-inspired algorithms represent a relatively young form of solution procedures, whose applicability to the solution of complex optimization problems has already been shown. The herein presented two-stage approach belongs to the class of metaheuristics to control a construction heuristic and has been applied successfully to the NP-hard Vehicle Routing Problem with Time Windows (VRPTW). Within the paper, evaluation results are presented, which compare the developed algorithm to some of the most successful procedures for the solution of benchmark problems. The pursued approach gives the best results so far for a metaheuristic to control a construction heuristic.
Vision-based detection, tracking and classification of vehicles using stable features with automatic camera calibration
Authors: Stanley Birchfield
Venue:  (2008)

A method is presented for segmenting and tracking vehicles on highways using a camera that is relatively low to the ground. At such low angles, 3D perspective effects cause significant appearance changes over time, as well as severe occlusions by vehicles in neighboring lanes. Traditional approaches to occlusion reasoning assume that the vehicles initially appear well-separated in the image, but in our sequences it is not uncommon for vehicles to enter the scene partially occluded and remain so throughout. By utilizing a 3D perspective mapping from the scene to the image, along with a plumb line projection, a subset of features is identified whose 3D coordinates can be accurately estimated. These features are then grouped to yield the number and locations of the vehicles, and standard feature tracking is used to maintain the locations of the vehicles over time. Additional features are then assigned to these groups and used to classify vehicles as cars or trucks. The technique uses a single grayscale camera beside the road, processes image frames incrementally, works in real time, and produces vehicle counts with over 90% accuracy on challenging sequences. Adverse weather conditions are handled by augmenting feature tracking with a boosted cascade vehicle detector (BCVD). To overcome the need of manual camera calibration, an algorithm is presented which uses BCVD to calibrate the camera automatically without relying on any scene-specific image features such as road lane markings.
Energy-efficient design of adhoc and sensor networks
Authors: Sameh Gobriel
Venue:  (2008)

Adhoc and sensor networks (ASNs) are emerging wireless networks that are expected to have significant impact on the efficiency of many military and civil applications. However, building ASNs efficiently poses a considerable technical challenge because of the many constraints imposed by the environment, or by the ASN nodes capabilities themselves. One of the main challenges is the finite supply energy. Since the network hosts are battery operated, they need to be energy conserving so that the nodes and hence the network itself does not expire. In this thesis different techniques for an energy-efficient design for ASNs are presented. My work spans two layers of the network protocol stack; these are the Medium Access Layer (MAC) and the Routing Layer. This thesis first identifies and highlights the different sources of energy inefficiency in ASNs, and then it describes how each of these inefficiencies is handled. Toward this goal, I first focus on the Medium Access (MAC) Layer and present my work that handles the wasted energy in transmission and describe how the transmission distance is optimized to extend the network lifetime. I then describe BLAM, an energy-efficient extension for the IEEE 802.11, that handles the wasted energy in collisions. Next, TDMA-ASAP, a new MAC protocol for sensor networks, is introduced. TDMA-ASAP targets the wasted energy in idle listening. I also investigate energy-efficiency at the routing layer level. First, the &ldquo;Flooding-Waves&rdquo; problem is identified. This is a problem in any cost-based energy-efficient routing protocol for adhoc networks, different ways of solving this problem are presented. For sensor networks routing trees are usually used, I introduce a new routing scheme called RideSharing which is energy-efficient and fault-tolerant. RideSharing will deliver a better aggregate result to the end user while masking network link failures. Next, I present how to extend the RideSharing scheme to handle different link quality models. Finally, I introduce GroupBeat, a new health detection system for sensor networks, which when combined with RideSharing can deliver the information to the end user even in case of node failures.
Ontology-based Management of Pervasive Systems
Authors: Nikolaos Dimakis, John Soldatos, Lazaros Polymenakos
Venue: Proceeding of the 2007 conference on Emerging Artificial Intelligence Applications in Computer Engineering: Real Word AI Systems with Applications in eHealth, HCI, Information Retrieval and Pervasive Technologies (2007)

Ubiquitous and pervasive systems rely on a highly dynamic and heterogeneous software / hardware infrastructure. A key factor in dealing with this diverse and sophisticated environment is the ability to 'map' all entities into a robust, scalable and flexible directory mechanism, able to maintain and manage a large number of heterogeneous components while acting not only as an information repository but also to be able to associate individual and component-specific information. This mechanism should enable the ubiquitous service designer to use a global directory service which can answer queries in an intelligent manner and relieve both the user and developer from tedious procedures of querying databases. In this paper we elaborate on the benefits gained by incorporating semantic technologies in the area of ubiquitous and pervasive computing as a means of meetings these needs. We base our experience on a case study of software component exchange among 3 different vendors which demonstrated the flexibility of adopting such a mechanism of ontology registry.
(α,β)-fuzzy ideals of hemirings
Authors: W. A. Dudek, M. Shabir, M. Irfan Ali
Venue: Computers Mathematics with Applications (2009)

We give a characterization of different types of (@a,@b)-fuzzy ideals of hemirings, where @a,@b@?{@?,q,@?@?q,@?@?q} and @a
Bzier and Splines in Image Processing and Machine Vision, 1st edition
Authors: Sambhunath Biswas, Brian C. Lovell
Venue:  (2007)

Digital image processing and machine vision have grown considerably during the last few decades. Of the various techniques, developed so far, splines play a significant role in many of them. This book deals with various image processing and machine vision problems efficiently with splines and includes: the significance of Bernstein Polynomial in splines, detailed coverage of Beta-splines applications which are relatively new, Splines in motion tracking, various deformative models and their uses. Finally the book covers wavelet splines which are efficient and effective in different image applications.
Digital anastylosis of the Octagon in Ephesos
Authors: Barbara Thuswaldner, Simon Flöry, Robert Kalasek, Michael Hofer, Qi-Xing Huang, Hilke Thür
Venue: Journal on Computing and Cultural Heritage (JOCCH) (2009)

Anastylosis is the archaeological and architectural reconstruction of a ruined monument at the historic site after careful study of the remaining original elements. We present research results concerning 3D technologies that are used in the digital anastylosis of cultural heritage monuments. Based on current state-of-the-art research, we present 3D data collection, digital artifacts reconstruction, and digital reassembly of existing fragments illustrated by means of the Octagon monument in Ephesos, Turkey. Our focus is on methods that belong to geometry processing.
Staff and graphical primitive segmentation in old handwritten music scores
Authors: Alicia Fornés, Josep Lladós, Gemma Sánchez
Venue: Proceeding of the 2005 conference on Artificial Intelligence Research and Development (2005)

In document analysis field, Optical Musical Recognition is a mature area in printed scores, whereas few research works have been done in handwritten ones. The difficulties in handwritten scores are increased if we work in old documents, because of paper degradation and the lack of a standard in musical notation. In this paper we propose a method to segment staff and graphical primitives in old handwritten scores. The extraction of staff lines has been performed using Hough Transform, skeletization, median filters and a contour tracking process. The segmentation of lines and head notes has been done using morphological operations and median filters. Our method has been tested with several scores of XIX century with high performance rates.
Qualitative Induction Trees applied to the study of the financial rating
Authors: Llorenç Roselló, Núria Agell, Mónica Sánchez, Francesc Prats
Venue: Proceeding of the 2006 conference on Artificial Intelligence Research and Development (2006)

In this work the Qualitative Induction Trees and the algorithm QUIN are described to construct them. It is justified its suitability for the prediction of the rating of the companies. Predicting the rating of a company requires a thorough knowledge of the ratios and values that indicate the company's situation and, also, a deep understanding of the relationships between them and the main factors that can modify these values. In this paper are given concrete examples of application in the prediction of the variation of the rating, analyzing on one hand which is this variation and on the other hand explaining which are the more influent variables in this change.