ppxscal/embedding_network huggingface dataset:
MetaCDN: Harnessing 'Storage Clouds' for high performance content delivery
Authors: James Broberg, Rajkumar Buyya, Zahir Tari
Venue: Journal of Network and Computer Applications (2009)

Content delivery networks (CDNs) such as Akamai and Mirror Image place web server clusters in numerous geographical locations to improve the responsiveness and locality of the content it hosts for end-users. However, their services are priced out of reach for all but the largest enterprise customers. An alternative approach to content delivery could be achieved by leveraging existing infrastructure provided by 'Storage Cloud' providers, who offer internet accessible data storage and delivery at a fraction of the cost. In this paper, we introduce MetaCDN, a system that exploits 'Storage Cloud' resources, creating an integrated overlay network that provides a low cost, high performance CDN for content creators. MetaCDN removes the complexity of dealing with multiple storage providers, by intelligently matching and placing users' content onto one or many storage providers based on their quality of service, coverage and budget preferences. MetaCDN makes it trivial for content creators and consumers to harness the performance and coverage of numerous 'Storage Clouds' by providing a single unified namespace that makes it easy to integrate into origin websites, and is transparent for end-users. We then demonstrate the utility of this new approach to content delivery by showing that the participating 'Storage Clouds' used by MetaCDN provide high performance (in terms of throughput and response time) and reliable content delivery for content consumers, whilst the MetaCDN system itself introduces minimal overhead compared to using these 'Storage Clouds' directly.
k-Clustering Minimum Biclique Completion via a Hybrid CP and SDP Approach
Authors: Stefano Gualandi
Venue: Proceedings of the 6th International Conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems (2009)

This paper presents a hybrid Constraint Programming (CP) and Semidefinite Programming (SDP) approach to the k-clustering minimum biclique completion problem on bipartite graphs. The problem consists in partitioning a bipartite undirected graph into k clusters such that the sum of the edges that complete each cluster into a biclique, i.e., a complete bipartite subgraph, is minimum. The problem arises in telecommunications, in particular in bundling channels in multicast transmissions. In literature, the problem has been tackled with an Integer Bilinear Programming approach. We introduce two quasi-biclique constraints and we propose a SDP relaxation of the problem that provides much stronger lower bounds than the Bilinear Programming relaxation. The quasi-biclique constraints and the SDP relaxation are integrated into a hybrid CP and SDP approach. Computational results on a set of random instances provide further evidence about the potential of CP and SDP hybridizations. 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
Data Access in a Cyber World: Making Use of Cyberinfrastructure
Authors: Julia Lane, Pascal Heus, Tim Mulcahy
Venue: Transactions on Data Privacy (2008)

The vast amount of data now collected on human beings and organizations as a result of cyberinfrastructure advances has created similarly vast opportunities for social scientists to study and understand human behavior. It has also made traditional ways of protecting social science data obsolete. The challenge to social scientists is to exploit advances in cyberinfrastructure to develop new access modalities that not only provide access but preserve data and create scientific communities. This paper outlines an approach that draws on both advances in the social science and the computer science literatures.
Feature-Level Fusion of Iris and Face for Personal Identification
Authors: Zhifang Wang, Qi Han, Xiamu Niu, Christoph Busch
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III (2009)

Feature-level fusion remains a challenging problem for multimodal biometrics. However, existing fusion schemes such as sum rule and weighted sum rule are inefficient in complicated condition. In this paper, we propose an efficient feature-level fusion algorithm for iris and face in parallel. The algorithm first normalizes the original features of iris and face using z-score model, and then take complex FDA as the classifier of unitary space. The proposed algorithm is tested using CASIA iris database and two face databases (ORL database and Yale database). Experimental results show the effectiveness of the proposed algorithm.
The Development of an Epistemic Platform for Nanoscience and Nanotechnology with a Computer Game for High School Students
Authors: Chanunan Skonchai, Boonprakob Manat
Venue: Proceeding of the 2007 conference on Supporting Learning Flow through Integrative Technologies (2007)

Teaching and learning the emerging fields of nanoscience and nanotechnology at high school level is not simply bringing concepts to students but also providing them with authentic learning experiences that can lead to deeper understandings, including both conceptual and procedural knowledge. Computer game technologies are considered multiple-representation systems and it is believed that using computer games as a framework to develop an epistemic platform, a novel science learning experience, is promising for science education. This dissertation is to develop an epistemic platform for science learning with a computer game and to investigate the impact of the epistemic platform on high school students. The integrated science-learning units of nanoscience and nanotechnology are developed using computer game technologies. Nine high school science students will be set in pilot study state to perform learning unit activities. After improving the learning units, forty other high school science students will be set in the implementation state. The data of the study will be collected using questionnaire, achievement assessment and focus group discussion technique for students. The teacher researcher will be interviewed before and after implementing the learning units.
Invariant 2D object recognition using KRA and GRA
Authors: Te-Hsiu Sun, Horng-Chyi Horng, Chi-Shuan Liu, Fang-Chin Tien
Venue: Expert Systems with Applications: An International Journal (2009)

Computer vision has been extensively adopted in industry for the last two decades. It enhances productivity and quality management, and is flexibility, efficient, fast, inexpensive, reliable and robust. This study presents a new translation, rotation and scaling-free object recognition method for 2D objects. The proposed method comprises two parts: KRA feature extractor and GRA classifier. The KRA feature extractor employs K-curvature, re-sampling, and autocorrelation transformation to extract unique features of objects, and then gray relational analysis (GRA) classifies the extracted invariant features. The boundary of the digital object was first represented as the form of the K-curvature over a given region of support, and was then re-sampled and transformed with autocorrelation function. After that, the extracted features own the unique property that is invariant to translation, rotation and scaling. To verify and validate the proposed method, 50 synthetic and 50 real objects were digitized as standard patterns, and 10 extra images of each object (test images) which were taken at different positions, orientations and scales, were acquired and compared with the standard patterns. The experimental results reveal that the proposed method with either GRA or MD methods is effective and reliable for part recognition.
The quest for scalable support of data-intensive workloads in distributed systems
Authors: Ioan Raicu, Ian T. Foster, Yong Zhao, Philip Little, Christopher M. Moretti, Amitabh Chaudhary, Douglas Thain
Venue: Proceedings of the 18th ACM international symposium on High performance distributed computing (2009)

Data-intensive applications involving the analysis of large datasets often require large amounts of compute and storage resources, for which data locality can be crucial to high throughput and performance. We propose a "data diffusion" approach that acquires compute and storage resources dynamically, replicates data in response to demand, and schedules computations close to data. As demand increases, more resources are acquired, thus allowing faster response to subsequent requests that refer to the same data; when demand drops, resources are released. This approach can provide the benefits of dedicated hardware without the associated high costs, depending on workload and resource characteristics. To explore the feasibility of data diffusion, we offer both a theoretical and an empirical analysis. We define an abstract model for data diffusion, introduce new scheduling policies with heuristics to optimize real-world performance, and develop a competitive online cache eviction policy. We also offer many empirical experiments to explore the benefits of dynamically expanding and contracting resources based on load, to improve system responsiveness while keeping wasted resources small. We show performance improvements of one to two orders of magnitude across three diverse workloads when compared to the performance of parallel file systems with throughputs approaching 80 Gb/s on a modest cluster of 200 processors. We also compare data diffusion with a best model for active storage, contrasting the difference between a pull-model found in data diffusion and a push-model found in active storage.
Template Update Methods in Adaptive Biometric Systems: A Critical Review
Authors: Ajita Rattani, Biagio Freni, Gian Luca Marcialis, Fabio Roli
Venue: Proceedings of the Third International Conference on Advances in Biometrics (2009)

Template representativeness is a fundamental problem in a biometric recognition system. The performance of the system degrades if the enrolled templates are un-representative of the substantial intra-class variations encountered in the input biometric samples. Recently, several template updates methods based on supervised and semi-supervised learning have been proposed in the literature with an aim to update the enrolled templates to the intra-class variations of the input data. However, the state of art related to template update is still in its infancy. This paper presents a critical review of the current approaches to template updating in order to analyze the state of the art in terms of advancement reached and open issues remain.
Formatting & Document Processing Essentials, Lessons 61-120, 2nd edition
Authors: Susie VanHuss, Connie Forde, Donna Woo, Linda Hefferin
Venue:  (2007)

KEYBOARDING ESSENTIALS 2nd Edition: FORMATTING & DOCUMENT PROCESSING, LESSONS 61-120, focuses on mastery of formatting letters, memos, reports, and business documents using the functions of Microsoft Word 2007! Additional skill building is included to increase your keyboarding speed and accuracy. Word processing skills are isolated and introduced prior to document formatting lessons, while proofreading skills are reinforced within the documents. The document formatting lessons are devoted solely to documents and teach no additional word processing so you can focus on formatting mastery.
XPath query evaluation based on the stack encoding
Authors: Yangjun Chen, Donovan Cooke
Venue: Proceedings of the 2nd Canadian Conference on Computer Science and Software Engineering (2009)

The twig join, which is used to find all occurrences of a twig pattern in an XML database, is a core operation for XML query processing. A great many strategies for handling this problem have been proposed and can be roughly classified into two groups. The first group decomposes a twig pattern (a small tree) into a set of binary relationships between pairs of nodes, such as parent-child and ancestor-descendant relations; and transforms a tree matching problem into a series of simple relation look-ups. The second group decomposes a twig pattern into a set of paths. Among all this kind of methods, the approach based on the so-called stack encoding by Bruno et. al. [2] is very interesting, which can represent in linear space a potentially exponential (in the number of query nodes) number of matching paths. However, the available processes for generating such compressed paths suffer some redundancy and can be significantly improved. In this paper, we analyze this method and show that the time complexities of path generation in its two main procedures: PathStack and TwigStack can be reduced from O(m2 &middot;n) to O(m &middot;n), where m and n are the sizes of the query tree and document tree, respectively. Experiments have been done to compare ours and some existing startegies, which shows that using our method much less time is needed to generate matching paths.
A framework of energy efficient mobile sensing for automatic user state recognition
Authors: Yi Wang, Jialiu Lin, Murali Annavaram, Quinn A. Jacobson, Jason Hong, Bhaskar Krishnamachari, Norman Sadeh
Venue: Proceedings of the 7th international conference on Mobile systems, applications, and services (2009)

Urban sensing, participatory sensing, and user activity recognition can provide rich contextual information for mobile applications such as social networking and location-based services. However, continuously capturing this contextual information on mobile devices consumes huge amount of energy. In this paper, we present a novel design framework for an Energy Efficient Mobile Sensing System (EEMSS). EEMSS uses hierarchical sensor management strategy to recognize user states as well as to detect state transitions. By powering only a minimum set of sensors and using appropriate sensor duty cycles EEMSS significantly improves device battery life. We present the design, implementation, and evaluation of EEMSS that automatically recognizes a set of users' daily activities in real time using sensors on an off-the-shelf high-end smart phone. Evaluation of EEMSS with 10 users over one week shows that our approach increases the device battery life by more than 75% while maintaining both high accuracy and low latency in identifying transitions between end-user activities.
The context of the game
Authors: Amanda Friedenberg, Martin Meier
Venue: Proceedings of the 12th Conference on Theoretical Aspects of Rationality and Knowledge (2009)

In games of incomplete information, the analyst must specify the players' choices, payoff functions, and hierarchies of beliefs (about the payoffs of the game). The importance of correctly specifying players' choices or actual payoff functions is well understood. (See, Kreps-Wilson [8, 1982] and Milgrom-Roberts [10, 1982], amongst many others.)
Automatic Classification of Sentences in Dutch Laws
Authors: Emile de Maat, Radboud Winkels
Venue: Proceeding of the 2008 conference on Legal Knowledge and Information Systems: JURIX 2008: The Twenty-First Annual Conference (2008)

The work described here builds on [1], where we presented a categorisation of norms or provisions in legislation. We claimed that the categories are characterized by the use of typical sentence structures and that this would enable automatic detection and classification. In this paper we present the results of experiments in such automatic classification of provisions. We have defined fourteen different categories of provisions, and compiled a list of 81 sentence structures for those categories from twenty Dutch laws. Based on these structures, a parser was used to classify the sentences in fifteen different Dutch laws, classifying 94% of 476 sentences correctly. It compares well with other, statistical approaches. An important improvement of our classifier will be the distinction of principal and auxiliary sentences.
Synthesis of timed behavior from scenarios in the Fujaba Real-Time Tool Suite
Authors: Stefan Henkler, Joel Greenyer, Martin Hirsch, Wilhelm Schafer, Kahtan Alhawash, Tobias Eckardt, Christian Heinzemann, Renate Loffler, Andreas Seibel, Holger Giese
Venue: Proceedings of the 2009 IEEE 31st International Conference on Software Engineering (2009)

Based on a well-defined component architecture the tool supports the synthesis of so-called real-time statecharts from timed sequence diagrams. The two step synthesis process addresses the existing scalability problems by a proper decomposition and allows the user to define particular restrictions on the resulting statecharts.
Reconstruction method of foam structures from MRI imaging
Authors: I. Zsoldos
Venue: Proceedings of the 7th WSEAS international conference on System science and simulation in engineering (2008)

In the case of the liquid foams the MRI imaging method has a problem: only the edges can be seen and the surfaces of the bubbles are not visible in the images. The problem is solved by a special reconstruction algorithm of the Potts model in 2-D case where the vertexes are known from an MRI image and the edges of the cells have to be reconstructed. We have shown that the similar special algorithm of the Potts model has an applicability limit in general 3-D froths because of the existence of the so called unfavourable growth directions. However the algorithm has to work well in the case of real liquid foams where the Plateau law is valid for the angles at meeting surfaces and edges in the cell system.
Autonomic Workflow Management in Agent-based Structural Health Monitoring Systems Using Graph Theory
Authors: Kay Smarsly, Karlheinz Lehner, Dietrich Hartmann
Venue: Proceeding of the 2006 conference on Leading the Web in Concurrent Engineering: Next Generation Concurrent Engineering (2006)

This paper presents an approach towards autonomic workflow management within a distributed, agent-based structural health monitoring system. This monitoring system is currently being developed at the Institute of Computational Engineering. Its global aim is to support the involved human experts in monitoring safety-relevant civil infrastructures by an artificial organization of several cooperating software agents. For the purpose of managing the workflow, Graph Theory --suitable to mathematically represent discrete distributed systems --is utilized by self-controlling software agents. To this end, software agents are regarded as distributed, self-contained entities and capable of making independent decisions. However, by applying the Graph Theory, and in particular Petri Nets, for controlling software agents, the agents just carry out instructions of a “centralized planning capability” that provides workflow specifications but cannot act independently. Thus, a layered approach is outlined allowing benefits from both the independent agent nature and the advantages of centralized planning.
Goal generation from beliefs based on trust and distrust
Authors: Célia da Costa Pereira, Andrea G. B. Tettamanzi
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

We propose three alternative belief change operators to be used in a goal generation and adoption framework. The originality of these operators is that the trustworthiness of a source depends not only on the degree of trust but also on an independent degree of distrust. Explicitly taking distrust into account allows us to mark a clear difference between the distinct notions of negative trust and insufficient trust. More precisely, it is possible, unlike in approaches where only trust is accounted for, to "weigh" differently information from helpful, malicious, unknown, or neutral sources.
Testing Behavioral Models with an Online Game
Authors: Michael Zyda, Marc Spraragen, Balakrishnan Ranganathan
Venue: Computer (2009)

The WarPipe massively multiplayer online game engine promises to enhance games and more serious applications.
Real World Camera Raw with Adobe Photoshop CS3, 1st edition
Authors: Bruce Fraser, Jeff Schewe
Venue:  (2007)

The raw revolution that began in 2003 with the Adobe Camera Raw plug-in for Adobe Photoshop has changed the way photographers work with images. Shooting in the raw format gives digital photographers complete control over every aspect of image quality. Adobe Camera Raw makes the process of using raw files easier by providing a standardized way of accessing and working with these uncompressed digital negatives. Today serious photographers shoot raw images only. Real World Camera Raw with Adobe Photoshop was the first book devoted exclusively to the topic, explaining the advantages and challenges of using Adobe Camera Raw to produce magnificent images. Real World Adobe Camera Raw in Photoshop CS3 keeps pace with new directions in digital photography and raw image processing. Jeff Schewe, a contributor to the development of Adobe Camera Raw from its beginnings, updates Bruce Frasers best-selling book with inside knowledge of how new features let photographers optimize and convert images for the best results in Adobe Photoshop CS3. Hands-on techniques show readers how to expose and shoot for raw image capture as well as use new features such as Spot Healing. Readers will also learn how to use the latest version of Adobe Bridge to manage the thousands of imagesand gigabytes of datathat result from raw shooting. Finally, Schewe discusses how Adobes latest revolutionary imaging software Photoshop Lightroom adds to the raw equation.
Expressing combinatorial problems by systems of polynomial equations and hilbert's nullstellensatz
Authors: J. a. Loera, J. Lee, S. Margulies, S. Onn
Venue: Combinatorics, Probability and Computing (2009)

Systems of polynomial equations over the complex or real numbers can be used to model combinatorial problems. In this way, a combinatorial problem is feasible (e.g., a graph is 3-colourable, Hamiltonian, etc.) if and only if a related system of polynomial equations has a solution. For an infeasible polynomial system, the (complex) Hilbert Nullstellensatz gives a certificate that the associated combinatorial problem is infeasible. Thus, unless P = NP, there must exist an infinite sequence of infeasible instances of each hard combinatorial problem for which the minimum degree of a Hilbert Nullstellensatz certificate of the associated polynomial system grows. In the first part of the paper, we show that the minimum degree of a Nullstellensatz certificate for the non-existence of a stable set of size greater than the stability number of the graph is the stability number of the graph. Moreover, such a certificate contains at least one term per stable set of G. In contrast, for non-3-colourability, we proved that the minimum degree of a Nullstellensatz certificate is at least four. Our efforts so far have only yielded graphs with Nullstellensatz certificates of precisely that degree. In the second part of this paper, for the purpose of computation, we construct new polynomial encodings for the problems of finding in a graph its longest cycle, the largest planar subgraph, the edge-chromatic number, or the largest k-colourable subgraph. We include some applications to graph theory.
Teaching software architectures and aspect-oriented software development using open-source projects
Authors: Cristóbal Costa-Soria, Jennifer Pérez
Venue: ACM SIGCSE Bulletin (2009)

The complexity and the big size of current software systems are challenges to be faced in software development. In the last few years, these challenges have increased the effort required to develop such large software systems. As a result, students must be able to develop these systems using approaches that reduce their development costs. Two of these approaches are Software Architectures and the Aspect-Oriented Software Development. However, in order to acquire skills in these approaches, students must put them into practice in realistic software projects. For this reason, we propose a reverse engineering method to learn these approaches by using open-source projects.