ppxscal/embedding_network huggingface dataset:
The WEB Collection Revealed Premium Edition: Adobe Dreamweaver CS4, Adobe Flash CS4, and Adobe Photoshop CS4, 1st edition
Authors: Sherry Bishop, James E. Shuman, Elizabeth Eisner Reding
Venue: Revealed Series Vision (2009)

With the release of Adobe's Creative Suite 4, the integration that Web developers and graphic designers had only dreamed about is now becoming a reality. The Web Collection Revealed Premium Edition is the first book on the market to feature Adobe Dreamweaver, Adobe Flash, and Adobe Photoshop all together in the same text. Readers gain practical experience with the software as they work through end-of-chapter learning projects and step-by-step tutorials. An integration chapter demonstrates how to move from one application to the other while creating a Dreamweaver Web site that incorporates both Flash and Photoshop files. Full-color illustrations and a user-friendly design combine to create a solid learning experience that reveals how to master the latest features of these popular applications.
A Two-Step Execution Mechanism for Thin Secure Hypervisors
Authors: Manabu Hirano, Takahiro Shinagawa, Hideki Eiraku, Shoichi Hasegawa, Kazumasa Omote, Koichi Tanimoto, Takashi Horie, Seiji Mune, Kazuhiko Kato, Takeshi Okuda, Eiji Kawai, Suguru Yamaguchi
Venue: Proceedings of the 2009 Third International Conference on Emerging Security Information, Systems and Technologies (2009)

Virtual Machine Monitors (VMMs), also called hypervisors, can be used to construct a trusted computing base (TCB) enhancing the security of existing operating systems. The complexity of a VMM-based TCB causes the high risk of security vulnerabilities. Therefore, this paper proposes a two-step execution mechanism to reduce the complexity of a VMM-based TCB. We propose a method to separate a conventional VMM-based TCB into the following two parts: (1) A thin hypervisor with security services and (2) A special guest OS for security preprocessing. A special guest OS performing security tasks can be executed in advance. After shutting down the special guest OS, a hypervisor obtains preprocessing security data and next boots a target guest OS to be protected. Thus, the proposed two-step execution mechanism can reduce run-time codes of a hypervisor. This paper shows a design, a prototype implementation and measurement results of lines of code using BitVisor, a VMM-based TCB we have developed.
ADROIT: automatic discourse relation organizer of internet-based text
Authors: A. S. M. Mahbub Morshed, Mitsuru Ishizuka
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 3 (2008)

The ADROIT system that we are developing allows automatic discourse analysis of information rich natural language texts extracted directly from the web. We use guidelines and relations of Rhetorical Structure Theory (RST) to decompose texts into elementary segments and to perform the discourse parsing between them. In this paper, we present version 1.0 of ADROIT and focus on the noble technique of cue-phrase disambiguation and machine learning for identification and organization of discourse relations.
Predicting success in machine translation
Authors: Alexandra Birch, Miles Osborne, Philipp Koehn
Venue: Proceedings of the Conference on Empirical Methods in Natural Language Processing (2008)

The performance of machine translation systems varies greatly depending on the source and target languages involved. Determining the contribution of different characteristics of language pairs on system performance is key to knowing what aspects of machine translation to improve and which are irrelevant. This paper investigates the effect of different explanatory variables on the performance of a phrase-based system for 110 European language pairs. We show that three factors are strong predictors of performance in isolation: the amount of reordering, the morphological complexity of the target language and the historical relatedness of the two languages. Together, these factors contribute 75% to the variability of the performance of the system.
Biometrics in Practice: What Does HCI Have to Say?
Authors: Lynne Coventry, Graham I. Johnson, Tom Mcewan, Chris Riley
Venue: Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction: Part II (2009)

This panel discusses biometric technologies from different perspectives in HCI in order to arrive at a coherent response that the community can give in this area. The challenges of doing this will also be of interest in terms of HCI's general influence on topical issues.
Approximation Algorithms for Key Management in Secure Multicast
Authors: Agnes Chan, Rajmohan Rajaraman, Zhifeng Sun, Feng Zhu
Venue: Proceedings of the 15th Annual International Conference on Computing and Combinatorics (2009)

Many data dissemination and publish-subscribe systems that guarantee the privacy and authenticity of the participants rely on symmetric key cryptography. An important problem in such a system is to maintain the shared group key as the group membership changes. We consider the problem of determining a key hierarchy that minimizes the average communication cost of an update, given update frequencies of the group members and an edge-weighted undirected graph that captures routing costs. We first present a polynomial-time approximation scheme for minimizing the average number of multicast messages needed for an update. We next show that when routing costs are considered, the problem is NP-hard even when the underlying routing network is a tree network or even when every group member has the same update frequency. Our main result is a polynomial time constant-factor approximation algorithm for the general case where the routing network is an arbitrary weighted graph and group members have nonuniform update frequencies.
The Role of Social Networking Services in eParticipation
Authors: Øystein Sæbø, Jeremy Rose, Tom Nyvang
Venue: Proceedings of the 1st International Conference on Electronic Participation (2009)

A serious problem in eParticipation projects is citizen engagement --- citizens do not necessarily become more willing to participate simply because net-services are provided for them. Most forms of eParticipation in democratic contexts are, however, dependent on citizen engagement, interaction and social networking because democratic systems favour the interests of larger groups of citizens --- the more voices behind a political proposition, the greater its chances of success. In this context of challenges the study of social networking on the internet and social network theory offers valuable insights into the practices and theories of citizen engagement. Social network theory focuses on the chains of relationships that social actors communicate and act within. Some social networking services on the internet attract large numbers of users, and apparently sustain a great deal of interaction, content-generation and the development of loosely-coupled communities. They provide the forum for much discussion and interaction. In this respect social networking could contribute to solve some of the problems of engaging their users that eParticipation services often struggle with. This paper investigates the potential of Social Networking Services for the eParticipation area by defining social networking services, introducing the driving forces behind their advance, and discusses the potential use of social networking software in the eParticipation context.
Demo abstract: Signal reconstruction with subnyquist sampling using wireless sensor networks
Authors: Andria Pazarloglou, Stephen George, Radu Stoleru, Ricardo Gutierrez-Osuna
Venue: Proceedings of the 2009 International Conference on Information Processing in Sensor Networks (2009)

Data streaming for sensor networks is an emerging class of application that can offer significant safety and utility enhancements in a number of critical environments. In one such application, disaster response, a wireless sensor network may assist in the detection of living victims trapped in collapsed buildings. As a step towards this goal, this paper addresses the very high bandwidth and processing requirements posed by streaming applications, and demonstrates a sub-Nyquist sampling procedure for reconstructing higher-resolution speech signals.
A Web 2.0 Personal Learning Environment for Classical Chinese Poetry
Authors: Yiwei Cao, Ralf Klamma, Yan Gao, Rynson W. Lau, Matthias Jarke
Venue: Proceedings of the 8th International Conference on Advances in Web Based Learning (2009)

Classical Chinese Poetry (CCP) is a valuable but almost locked treasure chest of human wisdom and civilization since 2000 years. With the advent of the Web 2.0 a renaissance of CCP is possible even outside Chinese-speaking communities world-wide. With mobile technologies and educational games we can address new learning communities for CCP and open the chest again. In this paper, we introduce a Web 2.0 personal learning environment for CCP. We have developed a generic and interoperable data model for CCP we utilize not only for mobile learning scenarios but also for educational gaming with different levels of difficulty. Learners are empowered to learn Chinese poetry, language, history, and culture. This research work shows how modern information technologies assist users to diffuse knowledge across the borderlines of communities and societies.
Relationality Design toward Enriched Communications
Authors: Yukiko Nakano, Masao Morizane, Ivan Tanev, Katsunori Shimohara
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part III: Ubiquitous and Intelligent Interaction (2009)

We have been conducting research on how to design relationality in complex systems composed of intelligent tangible or intangible, artificial artifacts, by using evolutionary computation and network science as methodologies. This paper describes the research concept, methodologies, and issues of relationality design. As one of research on relationality, we investigate here significance of linkage between a real world and a virtual world in a learning system.
Feature Selection Method Combined Optimized Document Frequency with Improved RBF Network
Authors: Hao-Dong Zhu, Xiang-Hui Zhao, Yong Zhong
Venue: Proceedings of the 5th International Conference on Advanced Data Mining and Applications (2009)

Feature selection is the core research topic in text categorization. Firstly, it combined word frequency with document frequency and presented an optimized document frequency (ODF) method. Then it proposed an adaptive quantum-behaved particle swarm optimization (AQPSO) algorithm in order to train the central position and width of the basis function adopted in the RBF neural network. Next the weight of the RBF network was computed by means of least-square method (LSM). Finally, a combined feature selection method was provided. The combined feature selection method firstly uses the optimal document frequency method to filter out some terms to reduce the sparsity of feature spaces, and then employs the improved RBF neural network to select more outstanding feature subsets. The experimental results show that the combined method is effective.
Structure and complexity in planning with unary operators
Authors: Ronen I. Brafman, Carmel Domshlak
Venue: Journal of Artificial Intelligence Research (2003)

Unary operator domains - i.e., domains in which operators have a single effect - arise naturally in many control problems. In its most general form, the problem of STRIPS planning in unary operator domains is known to be as hard as the general STRIPS planning problem - both are PSPACE-complete. However, unary operator domains induce a natural structure, called the domain's causal graph. This graph relates between the preconditions and effect of each domain operator. Causal graphs were exploited by Williams and Nayak in order to analyze plan generation for one of the controllers in NASA's Deep-Space One spacecraft. There, they utilized the fact that when this graph is acyclic, a serialization ordering over any subgoal can be obtained quickly. In this paper we conduct a comprehensive study of the relationship between the structure of a domain's causal graph and the complexity of planning in this domain. On the positive side, we show that a non-trivial polynomial time plan generation algorithm exists for domains whose causal graph induces a polytree with a constant bound on its node indegree. On the negative side, we show that even plan existence is hard when the graph is a directed-path singly connected DAG. More generally, we show that the number of paths in the causal graph is closely related to the complexity of planning in the associated domain. Finally we relate our results to the question of complexity of planning with serializable subgoals.
On User Modelling for Personalised News Video Recommendation
Authors: Frank Hopfgartner, Joemon M. Jose
Venue: Proceedings of the 17th International Conference on User Modeling, Adaptation, and Personalization: formerly UM and AH (2009)

In this paper, we introduce a novel approach for modelling user interests. Our approach captures users' evolving information needs, identifies aspects of their need and recommends relevant news items to the users. We introduce our approach within the context of personalised news video retrieval. A news video data set is used for experimentation. We employ a simulated user evaluation.
Mining Multi-Level Multi-Relational Frequent Patterns Based on Conjunctive Query Containment
Authors: Wei Zhang
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 02 (2009)

While there is much scope for improving understandability, accessibility, efficiency and scalability of the state-of-the-art of multi-relational frequent pattern discovery approaches based on the ILP techniques, we propose a novel and general algorithm MMRFP for multi-level multi-relational frequent pattern discovery based on concepts and techniques of relational database. Specially, we define the search space based on conjunctive query containment, a well understood concept in relational database theory, which effectively and efficiently discovery multi-level multi-relational frequent pattern and reduce the semantically redundant patterns with regard to the concept hierarchies background knowledge. Theoretical analyses and experimental results demonstrate the high understandability, accessibility, efficiency and scalability of the presented algorithms.
Cryptographic Protocol Synthesis and Verification for Multiparty Sessions
Authors: Karthikeyan Bhargavan, Ricardo Corin, Pierre-Malo Deniélou, Cédric Fournet, James J. Leifer
Venue: Proceedings of the 2009 22nd IEEE Computer Security Foundations Symposium (2009)

We present the design and implementation of a compiler that, given high-level multiparty session descriptions, generates custom cryptographic protocols. Our sessions specify pre-arranged patterns of message exchanges and data accesses between distributed participants. They provide each participant with strong security guarantees for all their messages. Our compiler generates code for sending and receiving these messages, with cryptographic operations and checks, in order to enforce these guarantees against any adversary that may control both the network and some session participants. We verify that the generated code is secure by relying on a recent type system for cryptography. Most of the proof is performed by mechanized type checking and does not rely on the correctness of our compiler.We obtain the strongest session security guarantees to date in a model that captures the executable details of protocol code. We illustrate and evaluate our approach on a series of protocols inspired by web services.
Study on the Risk Detection about Network Security Based on Grey Theory
Authors: Kuang Yin, Tang Nianqing
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 01 (2009)

Risk detection about network security can discover anomaly traffic in time and decrease the harm and losing caused by network attacks. By means of NetFlow, packets were collected from Internet. Analyzing these data, four addresses (source IP/port and destination IP/port) were abstracted to form information entropy, which was extended from thermodynamic. Based on information entropy, risk coefficient was defined to describe the whole condition of network security. To forecast the change of risk coefficient, a model was set up according to grey theory. Using a few data, the model can forecast risk coefficient accurately. Simulation and experiments were completed by MATLAB and in LAN. The experiments in LAN prove that information entropy can reflect anomaly traffic caused by DDoS attacks and Internet worms in time and effectively. The simulation by MATLAB shows that by GM(1,1) information entropy and risk coefficient can be forecasted accurately. Now the system has been applied for two years and provides good performance.
A Dynamic Simulated Annealing Algorithm with Self-adaptive Technique for Grid Scheduling
Authors: Xiaohong Kong, Xiqu Chen, Wei Zhang, Guanjun Liu, Hongju Ji
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 01 (2009)

Due to the availability of the excess computation power, the heterogeneous grid systems have significant predominance in higher performance and low cost. In this paper, a self-adaptive algorithm is proposed based on Simulated Annealing (SA) for grid scheduling to minimize the make span, in response to the grid dynamic characteristic. During the process of scheduling, partial scheduling information is exploited to decide the next partial scheduling parameters set, which is self-adaptive to the stochastic job arrival time. We simulated the algorithm in GridSim environment, and the simulation results demonstrated that the proposed algorithm improved performance compared to existing scheduling techniques.
Redundant Instruments Placement Using ACO
Authors: Kechang Fu
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 02 (2009)

In this paper, Ant Colony Optimization (ACO) Algorithm is introduced to redundant instruments placement for optimum process variable estimation accuracy. It is proved that additional redundancy measurement will enhance estimation accuracy if the measurements relate the process variables in a different way, whereas the quantity of accuracy improvement is determined by the measurements structure. To find the optimal redundant instruments placement is substantially combinatorial optimization problem, Ant Colony System (ACS) can perform this perfectly. In this paper, ACO based redundant instruments placement algorithm is proposed. Simulation shows the proposed outperform the GA algorithm, which is a prevailing algorithm to combinatorial problem.
Use of collaborative technologies and knowledge sharing in co-located and distributed teams: Towards the 24-h knowledge factory
Authors: Amar Gupta, Elisa Mattarelli, Satwik Seshasai, Joseph Broschak
Venue: The Journal of Strategic Information Systems (2009)

The relocation of knowledge work to emerging countries is leading to an increasing use of globally distributed teams (GDT) engaged in complex tasks. In the present study, we investigate a particular type of GDT working 'around the clock': the 24-h knowledge factory (Gupta, 2008). Adopting the productivity perspective on knowledge sharing (Haas and Hansen, 2005, 2007), we hypothesize how a 24-h knowledge factory and a co-located team will differ in technology use, knowledge sharing processes, and performance. We conducted a quasi-experiment in IBM, collecting both quantitative and qualitative data, over a period of 12months, on a GDT and a co-located team. Both teams were composed of the same number of professionals, provided with the same technologies, engaged in similar tasks, and given similar deadlines. We found significant differences in their use of technologies and in knowledge sharing processes, but not in efficiency and quality of outcomes. We show how the co-located team and the GDT enacted a knowledge codification strategy and a personalization strategy, respectively; in each case grafting elements of the other strategy in order to attain both knowledge re-use and creativity. We conclude by discussing theoretical contributions to knowledge sharing and GDT literatures, and by highlighting managerial implications to those organizations interested in developing a fully functional 24-h knowledge factory.
Fingerprinting Blank Paper Using Commodity Scanners
Authors: William Clarkson, Tim Weyrich, Adam Finkelstein, Nadia Heninger, J. Alex Halderman, Edward W. Felten
Venue: Proceedings of the 2009 30th IEEE Symposium on Security and Privacy (2009)

We develop a novel technique for authenticating physical documentsby using random, naturally occurring imperfections in paper texture.To this end, we devised a new method for measuring thethree-dimensional surface of a paper without modifying the documentin any way, using only a commodity scanner.From this physicalfeature, we generate a concise fingerprint that uniquely identifiesthe document.Our method is secure against counterfeiting, robustto harsh handling, and applicable even before any content is printedon a page.It has a wide range of applications, including detectingforged currency and tickets, authenticating passports, and haltingcounterfeit goods.On a more sinister note, document identificationcould be used to de-anonymize printed surveys and to compromise thesecrecy of paper ballots.
Latent Dirichlet Bayesian Co-Clustering
Authors: Pu Wang, Carlotta Domeniconi, Kathryn Blackmond Laskey
Venue: Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II (2009)

Co-clustering has emerged as an important technique for mining contingency data matrices. However, almost all existing co-clustering algorithms are hard partitioning, assigning each row and column of the data matrix to one cluster. Recently a Bayesian co-clustering approach has been proposed which allows a probability distribution membership in row and column clusters. The approach uses variational inference for parameter estimation. In this work, we modify the Bayesian co-clustering model, and use collapsed Gibbs sampling and collapsed variational inference for parameter estimation. Our empirical evaluation on real data sets shows that both collapsed Gibbs sampling and collapsed variational inference are able to find more accurate likelihood estimates than the standard variational Bayesian co-clustering approach.
The Genetic Diversity and Differentiation of Haliotis Ovina by AFLP
Authors: Zhongbao Li
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 01 (2009)

Amplified fragment length polymorphism technique has been applied to detect the genetic diversity and differentiation of three wild Haliotis ovina populations in Hainan province, China. High level of genetic diversity was detected among the populations. The mean effective number of alleles per locus was from 1.2027+0.3090 to 1.3530+0.3404, with an average of 1.2969+0.3338. The percentage of polymorphic loci ranged from 66.54% to 60.36%, with an average of 76.18%. The mean of Shannon's Information index was 0.2870+0.2422, ranging from 0.2026+0.2403 to 0.3397+0.2440. And the average of gene diversity index was 0.1981+0.1767, ranging from 0.1306+0.1686 to 0.2276+0.1791. In general, the genetic differentiation among the three populations was insignificant, the average genetic distance among the three populations was 0.0201, ranging from 0.0087 to 0.0462. The UPGMA dendrogram showed that Yinzhou and Yalongwan first clustered into a group and then grouped with Anyou.