ppxscal/embedding_network huggingface dataset:
A device for stent designing in emodynamic surgery room
Authors: Mario Cannataro, Ciro Indolfi, Giuseppe Tradigo, Pierangelo Veltri
Venue: Proceedings of the 2009 IEEE International Workshop on Medical Measurements and Applications (2009)

Quantitative angiography has becoming largely used in interventional cardiology mainly because of its positive impact in terms of patients survival indexes and life quality. Such a tecnique is performed with a laparoscopic procedure and cures coronary stenoses with the installation of a medical stent. Benefits from the treatment are immediately perceived by patients. Furthermore laparoscopy avoids the potential problems related to the complexity of an open-heart surgery procedure. Stent positioning is guided by using contrast liquid and angiographic X-Rays images. The operator looks at angiographic images to estimate the dimensions of the stent to be installed. With the described procedure physicians may have difficulties in optimally estimating the stenosis size in order to choose the most appropriate stent because they have no absolute reference on the angiographer screens. In this paper we present an innovative device able to assist the physicians pre-implant analysis and thus supporting him for an optimal stent choice.
XMG: an expressive formalism for describing tree-based grammars
Authors: Yannick Parmentier, Joseph Le Roux, Benoît Crabbé
Venue: Proceedings of the Eleventh Conference of the European Chapter of the Association for Computational Linguistics: Posters & Demonstrations (2006)

In this paper we introduce eXtensible MetaGrammar, a system that facilitates the development of tree based grammars. This system includes both (1) a formal language adapted to the description of linguistic information and (2) a compiler for this language. It applies techniques of logic programming (e.g. Warren's Abstract Machine), thus providing an efficient and theoretically motivated framework for the processing of linguistic meta-descriptions.
Development of an Emotional Robot as a Teaching Assistant
Authors: Jwu-E Chen, Lu-Tsou Yeh, Hua-Hsiang Tseng, G -W Wu, In-Hang Chung
Venue: Proceedings of the 4th International Conference on E-Learning and Games: Learning by Playing. Game-based Education System Design and Development (2009)

Robot as a teaching assistant is a popular topic in recent years. A development for the robot assistant is presented, which includes five interactive operation modes and a progressive scheduling scheme to facilitate the use by a teacher and parent. In storytelling, this robot assistant can play a role assigned in advance and cooperate with the teacher and parent to react to some events. Or replacing the sound of teacher and parent, the robot can talk to the students or children. Or the robot can just be a faithful audience within the conversation of teacher-and-students or parent-and children.
A Unified Out-of-Sequence Measurements Fusion Algorithm for WSN
Authors: Yuepeng Shi, Yuqing Wan, Quanbo Ge
Venue: Proceedings of the 2009 First International Workshop on Database Technology and Applications (2009)

Influenced by multi-hop transmission module of wireless sensor networks (WSN) and high sensor's data rate etc.., the late measurement for the same target may arrive in the fusion center ahead of schedule than the early measurement in the system with ordered sampling, namely "Out-of-Sequence" Measurements (OOSM) phenomenon. Accordingly, the traditional filtering methods based on ordered measurement can’t be used. Aiming at the problem that most of current OOSM update algorithms only adapt to the OOSM system where the fusion center only gets one OOSM in the fusion period, a unified OOSM fusion method for the single sensor system with arbitrarily random mixed OOSMs system is proposed by use of the pseudo-measurement technology and Kalman filtering with correlated noise in this paper. Synchronously, the centralized and recursive forms of this proposed OOSM method are presented. The theoretic analysis and computer simulation both show the validity and superiority of the proposed OOSM method.
A Fault Detection System for Large Scale Sensor Networks Considering Reliability of Sensor Data
Authors: Masato Yamanouchi, Satoshi Matsuura, Hideki Sunahara
Venue: Proceedings of the 2009 Ninth Annual International Symposium on Applications and the Internet (2009)

In recent years, sensors have become smaller, more affordable, and widely used. Also, Internet spreads all over the globe, and made possible transfer large data instantly. Thereby, large scale weather sensor networks have been constructible. In this kind of sensor network, we need to consider load balancing, network redundancy, and reliability of sensor data. Using P2P technology is one of the solutions for load balancing and network redundancy. Fault detection is a method for calculating reliability of sensor data. We propose a system that can calculate reliability of sensor data. This system can install method of fault detection by plug-in. It can install and update not only existing method but also new method. In other words, this system is a sustainable fault detection system. In these days, pinpoint heavy rain is occurring frequently. In this paper, we validate a fault detection system at a pinpoint heavy rain. We consider a validation, and improve a plug-in that can be useful at a pinpoint heavy rain. We install the improved plug-in to system, and experiment it using real pinpoint heavy rain data. The result shows that our system can detect 100% of data fault at pinpoint heavy rain which occurred in August 29th, 2008.
A Modified Particle Swarm Optimization and Radial Basis Function Neural Network Hybrid Algorithm Model and Its Application
Authors: Biao Shi, Li Yu-xia, Yu Xin-hua, Yan Wang, Li Peng, Meng Xin
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 01 (2009)

Abstract—The study is to improve the power short-term forecast accuracy and speed, and the modified particle swarm optimization algorithm was brought up. The forecast model is set up by using the modified particle swarm optimization and radial basis function neural network combined to form MPSO-RBF algorithm, and then training the neural network by using the MPSO-RBF algorithm. It can automatically determine the structure and parameters of the neural network from the sample data. Form the power short-term forecast model based on the modified particle swarm optimization and radial basis function neural network, considering weather, date and other factors. The result shows the convergence of method is faster and forecast accuracy is more accurate than that of the traditional radial basis function neural network, the particle swarm optimization and radial basis function neural networks algorithm. The method improved forecast accuracy, and improves the radial basis function neural network generalization capacity, and overcomes the RBF neural networks that exist in some of the shortcomings. The model can be used to forecast the short-term load forecast of the power system.
Preserving Relay Connectivity and Coverage in Heterogeneous Wireless Sensor Networks
Authors: Jun Wen, Jie Jiang, Guofu Wu, Dongsong Ban, Wenhua Dou
Venue: Proceedings of the 2009 IEEE International Conference on Networking, Architecture, and Storage (2009)

To achieve scalability, a few resource-rich heterogeneous nodes are scattered in a wireless sensor network consisting of a large number of energy-constrained sensor nodes. Heterogeneous nodes are equipped with powerful radio transceiver and their main task is to organize a backbone communication network and to relay data to the sink. For the scenario, this paper proposes a coverage problem which maintaining relay connectivity at the same time in heterogeneous wireless sensor networks. The goal is to find a minimum relay connected set cover (MRCSC) which satisfies (1) active nodes in set cover fully sense the whole task area. Motivated by triangular lattice with asymptotic optimality, we address a rule for restricting irregularity spread to form an approximate nice triangular lattice, (2) active nodes are relay connected which means any active node connects to at least one heterogeneous node with a given success data forwarding rate. Simulations show that the coverage of MRCSC nearly reaches that of OGCD, but relay connectivity of active nodes is strongly reinforced with limited count of additional nodes.
Multiple levels of preference in interactive strategic decisions
Authors: Haiyan Xu, Keith W. Hipel, D. Marc Kilgour
Venue: Discrete Applied Mathematics (2009)

A multiple-level preference ranking structure is developed within the paradigm of the Graph Model for Conflict Resolution to study multi-objective decision making in conflict situations more realistically. In this structure, a decision maker may have multiple levels of preference for one state or scenario over another; for example, if state A is preferred to state B, it may be mildly preferred at level 1, more strongly preferred at level 2, ..., or maximally preferred at level r, where r>0 is a fixed parameter. The number of levels, r, is unrestricted in this system, thereby extending earlier two-level (r=1) and three-level (r=2) structures. Multilevel versions of four stability definitions, Nash stability, general metarationality, symmetric metarationality, and sequential stability, are defined for the graph model with this extended preference structure, and the relationships among them are investigated. A specific case study, including multiple decision makers and multiple levels of preference, is carried out to illustrate how the new solution concepts can be applied in practice.
Incorporating mental simulation for a more effective robotic teammate
Authors: William G. Kennedy, Magdalena D. Bugajska, William Adams, Alan C. Schultz, J. Gregory Trafton
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 3 (2008)

How can we facilitate human-robot teamwork? The teamwork literature has identified the need to know the capabilities of teammates. How can we integrate the knowledge of another agent's capabilities for a justifiably intelligent teammate? This paper describes extensions to the cognitive architecture, ACT-R, and the use of artificial intelligence (AI) and cognitive science approaches to produce a more cognitively-plausible, autonomous robotic system that "mentally" simulates the decision-making of its teammate. The extensions to ACT-R added capabilities to interact with the real world through the robot's sensors and effectors and simulate the decision-making of its teammate. The AI applications provided visual sensor capabilities by methods clearly different than those used by humans. The integration of these approaches into intelligent team-based behavior is demonstrated on a mobile robot. Our "TeamBot" matches the descriptive work and theories on human teamwork. We illustrate our approach in a spatial, team-oriented task of a guard force responding appropriately to an alarm condition that requires the human and robot team to "man" two guard stations as soon as possible after the alarm.
Research on Maritime Search and Rescue Decision-Making Ontology Model
Authors: Yu Weihong
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 02 (2009)

The work of maritime search and rescue is involved with many areas. Accordingly, search and rescue decision-making systems need to deal with a wide range of information, which results in a large number of heterogeneous data. One common problem is the semantic heterogeneous. This paper applies ontology into solving these problems and realizes knowledge acquisition, sharing and reuse. Maritime search and rescue decision-making ontology reference model is proposed. To discuss the procedure of ontology construction based on Protégé, an ontology for Classification on maritime perils is constructed as an example. As a conclusion, further research work is proposed.
A new e-learning paradigm through annotating operations
Authors: Hiroaki Saito, Kyoko Ohara, Kengo Sato, Kazunari Ito, Shinsuke Hizuka, Masaya Soga, Tomoya Nishino, Yuji Nomura, Hideaki Shirakawa, Hiroyuki Okamoto
Venue: Proceedings of the Workshop on eLearning for Computational Linguistics and Computational Linguistics for eLearning (2004)

This paper proposes a new e-learning paradigm which enables the user to type in arbitrary sentences. The current NLP technologies, however, are not matured enough to perform full-automatic semantic or discourse analysis. Thus, we take a different approach; an instructor corrects the contents and its correction is embedded into the contents in an XML format called KeML. The key/mouse operations of the user are also embedded as annotations. Thus, the contents can be incomplete at the initial stage and become solid gradually as being utilized. We have implemented an e-learning system of group discussion for a foreign language class, which is demonstrated at the workshop.
Rank-Balanced Trees
Authors: Bernhard Haeupler, Siddhartha Sen, Robert E. Tarjan
Venue: Proceedings of the 11th International Symposium on Algorithms and Data Structures (2009)

Since the invention of AVL trees in 1962, a wide variety of ways to balance binary search trees have been proposed. Notable are red-black trees, in which bottom-up rebalancing after an insertion or deletion takes O(1) amortized time and O(1) rotations worst-case. But the design space of balanced trees has not been fully explored. We introduce the rank-balanced tree, a relaxation of AVL trees. Rank-balanced trees can be rebalanced bottom-up after an insertion or deletion in O(1) amortized time and at most two rotations worst-case, in contrast to red-black trees, which need up to three rotations per deletion. Rebalancing can also be done top-down with fixed lookahead in O(1) amortized time. Using a novel analysis that relies on an exponential potential function, we show that both bottom-up and top-down rebalancing modify nodes exponentially infrequently in their heights.
Development, Implementation, and Evaluation of Sonification Tools for Point-and-Surface-Based Data Exploration
Authors: Wagner José Franchin, Lionis de Souza Watanabe, Haim Levkowitz, Rosane Minghim
Venue: Proceedings of the 2009 Second International Conference in Visualisation (2009)

Most existing visualization tools utilize only the visual channel to represent information. Several studies have demonstrated that sonification,the use of sound as an alternative or additional channel for data representation, can help increase the dimensionality of the visual representation and aid in the interpretation of information. We introduce a new sonification module for a visual data exploration system, the Super Spider. It extends a previously developed interactive visualization tool \cite{minghim05spider} to support data exploration using sound. We also introduce a new data sonification technique and system, 2D Sonar. We have integrated it into Super Spider. Finally, we present user studies conducted to evaluate and validate the efficacy of visual and auditory mappings devised for these tools, and their results.
Mining Databases to Mine Queries Faster
Authors: Arno Siebes, Diyah Puspitaningrum
Venue: Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II (2009)

Inductive databases are databases in which models and patterns are first class citizens. Having models and patterns in the database raises the question: do the models and patterns that are stored help in computing new models and patterns? For example, let C be a classifier on database DB and let Q be a query. Does knowing C speed up the induction of a new classifier on the result of Q?In this paper we answer this problem positively for the code tables induced by our Krimp algorithm. More in particular, assume we have the code tables for all tables in the database. Then we can approximate the code table induced by Krimp on the result of a query, using only these global code tables as candidates. That is, we do not have to mine for frequent item sets on the query result.
A QoS-oriented Optimization Model for Web Service Group
Authors: Xiaopeng Deng, Chunxiao Xing
Venue: Proceedings of the 2009 Eigth IEEE/ACIS International Conference on Computer and Information Science (2009)

With the ever increasing of Web services in a Web service group, in which Web services offer the same functionality with different QoS parameters, Web service selection in a Web service group is an ongoing research topic. In this paper, we propose a QoS-oriented optimization model for Web service selection from a Web service group. The proposed model builds up a lightweight QoS model firstly, which defines functionality satisfaction degree, performance satisfaction degree, cost satisfaction degree and trust satisfaction degree as the QoS parameters of a Web service. Secondly, the Web service optimization model is described formally. Based on the described optimization model, the QoS vectors are clustered by hierarchical merging clustering approach. The clustering process is determined by the maximum similar degree parameter. QoS predication and QoS parameter predications are produced after the clustering is finished. Finally, the optimization is carried out by two searching modes: the clusters are optimized and the optimized Web services are selected from the optimized clusters by using of decision tree, QoS predication and QoS parameter predications. It is proved by our simulation cases that the proposed model is effective and can be used for Web service selection from its group.
Blind Digital Watermarking of Low Bit-Rate Advanced H.264/AVC Compressed Video
Authors: Dawen Xu, Rangding Wang, Jicheng Wang
Venue: Proceedings of the 8th International Workshop on Digital Watermarking (2009)

H.264/AVC is becoming a popular video codec for its better compression ratio, lower distortion and applicability to portable electronic devices. Thus, issues of copyright protection and authentication that are appropriate for this standard become very important. In this paper, a blind video watermarking algorithm for H.264/AVC is proposed. The watermark information is embedded directly into H.264/AVC video at the encoder by modifying the quantized DC coefficients in luminance residual blocks slightly. The watermark embedded in the residuals can avoid decompressing the video and to decrease the complexity of the watermarking algorithm. To reduce visual quality degradation caused by DC coefficients modifying, block selection mechanism is introduced to control the modification strength. Experimental results reveal that the proposed scheme can achieve enough robustness while preserving the perceptual quality.
Increasing Information Worker Productivity through Information Work Infrastructure
Authors: Udo-Ernst Haner, Jörg Kelter, Wilhelm Bauer, Stefan Rief
Venue: Proceedings of the International Conference on Ergonomics and Health Aspects of Work with Computers: Held as Part of HCI International 2009 (2009)

Deploying high-quality information work infrastructure leads to higher productivity levels of information workers, findings from empirical research show. Different types of information workers use different sets of technologies and devices. Knowledge workers with a high degree of autonomy depend on mobile and flexible work infrastructure. The OFFICE21® Information Worker's Workplace supports productive information work.
DoIT Right: Measuring Effectiveness of Different eConsultation Designs
Authors: Åke Grönlund, Joachim Åström
Venue: Proceedings of the 1st International Conference on Electronic Participation (2009)

eConsultations have been used in many countries over many years, yet most research in the field is case descriptions and there is so far little systematic evidence as to the effectiveness of consultations as a tool for enhancing democracy. Using a case survey method we investigate what factors make a consultation succeed or fail based on data from 57 cases reported in the literature. Success is measured as high participation, deliberative mode of discussion, and impact on policy. We test three hypotheses from the literature claiming, respectively, that institutional design, democratic intent, and quality of research are the most important factors behind the reported success. We find support for all hypotheses. Using consultation at the analysis/decision making stage, mixing online and offline methods and active strategic recruiting are institutional factors positively contributing. Democratic intent and content analysis research both have positive influence.
Compressing and indexing labeled trees, with applications
Authors: Paolo Ferragina, Fabrizio Luccio, Giovanni Manzini, S. Muthukrishnan
Venue: Journal of the ACM (JACM) (2009)

Consider an ordered, static tree T where each node has a label from alphabet &Sigma;. Tree T may be of arbitrary degree and shape. Our goal is designing a compressed storage scheme of T that supports basic navigational operations among the immediate neighbors of a node (i.e. parent, ith child, or any child with some label,&hellip;) as well as more sophisticated path-based search operations over its labeled structure. We present a novel approach to this problem by designing what we call the XBW-transform of the tree in the spirit of the well-known Burrows-Wheeler transform for strings [1994]. The XBW-transform uses path-sorting to linearize the labeled tree T into two coordinated arrays, one capturing the structure and the other the labels. For the first time, by using the properties of the XBW-transform, our compressed indexes go beyond the information-theoretic lower bound, and support navigational and path-search operations over labeled trees within (near-)optimal time bounds and entropy-bounded space. Our XBW-transform is simple and likely to spur new results in the theory of tree compression and indexing, as well as interesting application contexts. As an example, we use the XBW-transform to design and implement a compressed index for XML documents whose compression ratio is significantly better than the one achievable by state-of-the-art tools, and its query time performance is order of magnitudes faster.
The degree of word-expansion of lexicalized RRWW-automata - A new measure for the degree of nondeterminism of (context-free) languages
Authors: F. Mráz, F. Otto, M. Plátek
Venue: Theoretical Computer Science (2009)

Restarting automata can be seen as analytical variants of classical automata as well as of regulated rewriting systems. We study a measure for the degree of nondeterminism of (context-free) languages in terms of deterministic restarting automata that are (strongly) lexicalized. This measure is based on the number of occurrences of auxiliary symbols (categories) used for recognizing a language as the projection of its characteristic language onto its input alphabet. This type of recognition is typical for analysis by reduction, a method used in linguistics for the creation and verification of formal descriptions of natural languages. Our main results establish a hierarchy of classes of context-free languages and two hierarchies of classes of non-context-free languages that are based on the expansion factor of a language.