ppxscal/embedding_network huggingface dataset:
An extended MD-tree with internal leaf for efficient management of moving objects
Authors: Hiroyuki Dekihara, Yasuaki Nakamura
Venue: Journal of Computational Methods in Sciences and Engineering (2009)

Management systems for moving objects such as automobiles, airplanes, ships, and humans, must not only manage the moving objects efficiently but also quickly provide information about their surroundings on demand, because a moving object must know its environment to determine optimal solutions, e.g., the best path to a destination. In this paper, an efficient method for managing moving objects is proposed. This method is developed by extending the spatial data structure, MD-tree, through the introduction of two novel concepts, internal leaf and improvements in bottom-up search. The internal leaf that is managed by corresponding internal node in a tree has pointers to moving objects and helps reduce the update cost of the tree. The improved bottom-up search of the tree reduces the retrieval costs by managing the non-overlapped areas of split data space. Moreover, the usual spatial searches and updates of the tree can be executed as efficient as the MD-tree.
Design and performance of wireless data gathering networks based on unicast random walk routing
Authors: Gwillerm Froc, Issam Mabrouki, Xavier Lagrange
Venue: IEEE/ACM Transactions on Networking (TON) (2009)

Wireless environment monitoring applications with significantly relaxed quality-of-service constraints are emerging. Hence, the possibility to use rough low knowledge routing in sensor networks to reduce hardware resource and software complexity is questionable. Moreover, low knowledge handling allows better genericity, which is of interest, for instance, for basic operation enabling system set-up. In this framework, this paper revisits stateless unicast random walk routing in wireless sensor networks. Based on random walk theory, original closed-form expressions of the delay, the power consumption and related spatial behaviors are provided according to the scale of the system. Basic properties of such a random routing are discussed. Exploiting its properties, data gathering schemes that fulfill the requirements of the application with rather good energy efficiency are then identified.
The Optimization of Monascus Fermentation Process for Pigments Increment and Citrinin Reduction
Authors: Chao-Chin Chung, Tzou-Chi Huang, Ho-Hsien Chen
Venue: Proceedings of the 2009 Ninth IEEE International Conference on Bioinformatics and Bioengineering (2009)

The species of the fungus (Monascus purpureus, NPUST, Taiwan) used to produce the high pigment was isolated from rice waste. Its genomic DNA was confirmed by examining the NCBI database to check this species is M. purpureus strain ATCC 36114 (Identity 100%, Gap 0%). In this study, Taguchi Method was applied to find the optimal conditions of medium composition to enhance the production of pigments synthesis, and to reduce the yield of citrinin, metabolites in the M. purpureus fermentation process. In the production of the yellow pigment (OD400) and the red pigment (OD500), the result showed that their optimal conditions were A2B3C3D4E4 (1% Japonica-type rice, 1% peptone, 0.01% glycerol, 0.01% potassium phosphate and pH 9). In the production of the orange pigment (OD460), the result showed that the optimal conditions were A2B3C3D1E4 (1% Japonica-type rice, 1% peptone, 0.01% glycerol, 0.01% magnesium sulfate and pH 9). Under the optimal conditions for the best yield of pigment synthesis, the result showed that yellow pigment was 4.132 ppm, red pigment was 8.480 ppm and the orange pigment was 4.573 ppm. In the reduction of the citrinin yield, the result showed that A4B1C1D3E1 (1% whole wheat flour, 1% gelatin, 0.01% olive oil, 0.01% sodium choride and pH 3) were optimal conditions inhibit citrinin metabolism. Citrinin was reduced to 0.055 ppb. The optimal combination obtained from this study could be a reference for production line Monascus fermentation processing.
High Performance Participatory GIS - Application in Emergency Evacuation
Authors: Jiasong Zhu, Qinghua Qiao, Tong Zhang
Venue: Proceedings of the 2009 First International Workshop on Database Technology and Applications (2009)

This article discusses how Participatory GIS (PGIS) can be improved by applying current start-of-the-art computing technologies, in particular high performance computing technology. The discussion covers the methods and tools for the four types of space-time collaboration situations (different place/time). While the four types are all addressed, the focus is directed to the same time, different place collaboration which is prone to pose more challenges for time-critical services. A design of a high performance Grid-enabled PGIS for this scenario is presented along with pilot implementations for an emergency evacuation problem.
Structure-Preserving Regularisation Constraints for Shape-from-Shading
Authors: Rui Huang, William A. Smith
Venue: Proceedings of the 13th International Conference on Computer Analysis of Images and Patterns (2009)

In this paper we present a new framework for shape-from-shading which relies on a novel regularisation term which preserves surface structure. The resulting algorithm is both robust and accurate. We show that it can recover stable surface estimates from both synthetic and real world images of complex objects, even under extreme illumination. 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
Method for Movement and Gesture Assessment (MMGA) in Ergonomics
Authors: Giuseppe Andreoni, Marco Mazzola, Oriana Ciani, Marta Zambetti, Maximiliano Romero, Fiammetta Costa, Ezio Preatoni
Venue: Proceedings of the 2nd International Conference on Digital Human Modeling: Held as Part of HCI International 2009 (2009)

We present a technique for the ergonomic assessment of motor tasks and postures. It is based on movement analysis and it integrates the perceived discomfort scores for joints motions and the time involvement of the different body districts. It was tested on 8 subjects performing reaching movements. The experimental protocol was designed to have an a priori expected comfort ranking, namely, higher values in presence of more uncomfortable tasks. The validation of the Method for Movement and Gesture Assessment (MMGA) in the ergonomic evaluation of a reaching task gave promising results and showed the effectiveness of the index. Possible applications of the method might be the integration into CAD tools and human motion simulation to provide an early comparative evaluation of the ergonomics of the prototyping process and workplace redesign in industry.
Extraction of definitions using grammar-enhanced machine learning
Authors: Eline Westerhout
Venue: Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop (2009)

In this paper we compare different approaches to extract definitions of four types using a combination of a rule-based grammar and machine learning. We collected a Dutch text corpus containing 549 definitions and applied a grammar on it. Machine learning was then applied to improve the results obtained with the grammar. Two machine learning experiments were carried out. In the first experiment, a standard classifier and a classifier designed specifically to deal with im-balanced datasets are compared. The algorithm designed specifically to deal with imbalanced datasets for most types outperforms the standard classifier. In the second experiment we show that classification results improve when information on definition structure is included.
Dynamics Simulation on Installation Angle of Mast Link Frame System of Rotary Drilling Rig
Authors: Huimei Kang, Qinghua He, Jianxin Zhu
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

In order to improve the mechanical behavior of mast link frame system of rotary drilling rig, studying on the impact of installation angle of mast link frame system is necessary. Based on Newton-Euler method, the kinematic and dynamic constraint equations of mast link frame system were derived. The dynamic simulation model based on MATLAB was built in Simulink, and a series of simulation were run. The simulation results indicate that when installation angle belongs to [46°, 49°], three of the averages of driving force supplied by hydraulic cylinder of lift-arm, restraining force of the pin joint connecting lift-arm and swing platform, and the sum of restraining forces born by swing platform achieve or very close to the minima.
Is sentence compression an NLG task?
Authors: Erwin Marsi, Emiel Krahmer, Iris Hendrickx, Walter Daelemans
Venue: Proceedings of the 12th European Workshop on Natural Language Generation (2009)

Data-driven approaches to sentence compression define the task as dropping any subset of words from the input sentence while retaining important information and grammaticality. We show that only 16% of the observed compressed sentences in the domain of subtitling can be accounted for in this way. We argue that part of this is due to evaluation issues and estimate that a deletion model is in fact compatible with approximately 55% of the observed data. We analyse the remaining problems and conclude that in those cases word order changes and paraphrasing are crucial, and argue for more elaborate sentence compression models which build on NLG work.
Learning from data with uncertain labels by boosting credal classifiers
Authors: Benjamin Quost, Thierry Denœux
Venue: Proceedings of the 1st ACM SIGKDD Workshop on Knowledge Discovery from Uncertain Data (2009)

In this article, we investigate supervised learning when training data are associated with uncertain labels. We tackle this problem within the theory of belief functions. Each training pattern xi is thus associated with a basic belief assignment, representing partial knowledge of its actual class. Here, we propose to use the approach known as boosting to solve the classification problem. We propose a variant of the AdaBoost algorithm where the outputs of the classifiers are interpreted as belief functions. During training, our algorithm estimates the reliability of each classifier to identify patterns from the various classes. During test phase, the outputs of the classifiers are first discounted according to these reliabilities, and then combined using a suitable rule. Experiments conducted on classical datasets show that our algorithm is comparable to AdaBoost in accuracy. Processing EEG data with imperfect labels clearly demonstrates the interest of taking into account the reliability of the labelling, and thus the relevance of our approach.
Cost-algebraic heuristic search
Authors: Stefan Edelkamp, Shahid Jabbar, Alberto Lluch Lafuente
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 3 (2005)

Heuristic search is used to efficiently solve the single-node shortest path problem in weighted graphs. In practice, however, one is not only interested in finding a short path, but an optimal path, according to a certain cost notion. We propose an algebraic formalism that captures many cost notions, like typical Quality of Service attributes. We thus generalize A*, the popular heuristic search algorithm. for solving optimal-path problem. The paper provides an answer to a fundamental question for AI search, namely to which general notion of cost, heuristic search algorithms can be applied. We proof correctness of the algorithms and provide experimental results that validate the feasibility of the approach.
Variable Dimension Space Audio Scrambling Algorithm Against MP3 Compression
Authors: Huan Li, Zheng Qin, Liping Shao, Shanjun Zhang, Bin Wang
Venue: Proceedings of the 9th International Conference on Algorithms and Architectures for Parallel Processing (2009)

A novel Variable Dimension Space Audio Scrambling Algorithm Against MP3 Compression is proposed. The algorithm is implemented in audio position space, which changes the dimension of coordinates and uses arbitrary matrices to scramble audio. The scrambled audio was segmented and a sequence number is embedded in the front of each segment to discriminate different segments. The proposed method can increase the combination of encrypting parameters, which increases the difficulty being attacked; random generated high dimensional transform matrix has no fixed period and has no special restriction on the audio length; a sequence number can be used to determine the each segment audio positions, so the scrambled audio compressed by MP3 can be recovered. Experiments show the proposed algorithm is validity in audio scrambling, low cost in recovering the scrambled audio and still has a wonderful one time scrambling performance. The proposed algorithm is robust in enduring MP3 attacks.
An Adaptive Combination of Matchers: Application to the Mapping of Biological Ontologies for Genome Annotation
Authors: Bastien Rance, Jean-François Gibrat, Christine Froidevaux
Venue: Proceedings of the 6th International Workshop on Data Integration in the Life Sciences (2009)

Biological ontologies are widely used for genome annotation. Identifying correspondences between concepts of two ontologies (mapping) allows the reuse and sharing of annotations. Accordingly, biological ontology mapping has attracted a lot of interest. In this paper, we introduce O'Browser, a semi-automatic method for mapping two functional hierarchies using two sets of carefully annotated proteins. While being based on a classical ontology mapping architecture, O'Browser computes correspondences using a combination of different kinds of matchers. A key feature of O'Browser is that it places the expert at the center of the mapping process at two stages: (i) both to validate the very strong correspondences discovered by the system and to identify functional groups of concepts and (ii) to validate the correspondences given by the combination of results found by the matchers. These matchers have been designed in O'Browser to fit best with functional hierarchy features. For instance, we have introduced a new instance-based matcher which uses homology relationships between proteins. The combination of the different matchers is based on an original notion of adaptive weighting. Here, we show the ability of O'Browser to map concepts of Subtilist to concepts of FunCat, two functional hierarchies. First results appear to be very promising.
Efficiently exploiting dependencies in local search for SAT
Authors: Duc Nghia Pham, John Thornton, Abdul Sattar
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 3 (2008)

We propose a new local search platform that splits a CNF formula into three sub-components: i) a minimal dependency lattice (representing the core connections between logic gates), ii) a conjunction of equivalence clauses, and iii) the remaining clauses. We also adopt a new hierarchical cost function that focuses on solving the core components of the problem first. We then show experimentally that our platform not only significantly outperforms existing local search approaches but is also competitive with modern systematic solvers on highly structured problems.
Dependability Analysis of a Fault-Tolerant Network Reconfiguring Strategy
Authors: Vicente Chirivella, Rosa Alcover, José Flich, José Duato
Venue: Proceedings of the 15th International Euro-Par Conference on Parallel Processing (2009)

Fault tolerance mechanisms become indispensable as the number of processors increases in large systems. Measuring the effectiveness of such mechanisms before its implementation becomes mandatory. Research toward understanding the effects of different network parameters on the dependability parameters, like mean time to network failure or availability, becomes necessary. In this paper we analyse in detail such effects with a methodology proposed previously by us. This methodology is based on Markov chains and Analysis of Variance techniques. As a case study we analyse the effects of network size, mean time to node failure, mean time to node repair, mean time to network repair and coverage of the failure when using a 2D mesh network with a fault-tolerant mechanism (similar to the one used in the BlueGene/L system), that is able to remove rows and/or columns in the presence of failures.
Natural language generation as planning under uncertainty for spoken dialogue systems
Authors: Verena Rieser, Oliver Lemon
Venue: Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics (2009)

We present and evaluate a new model for Natural Language Generation (NLG) in Spoken Dialogue Systems, based on statistical planning, given noisy feedback from the current generation context (e.g. a user and a surface realiser). We study its use in a standard NLG problem: how to present information (in this case a set of search results) to users, given the complex tradeoffs between utterance length, amount of information conveyed, and cognitive load. We set these trade-offs by analysing existing match data. We then train a NLG policy using Reinforcement Learning (RL), which adapts its behaviour to noisy feedback from the current generation context. This policy is compared to several baselines derived from previous work in this area. The learned policy significantly outperforms all the prior approaches.
User eXperience: Tools for Developers
Authors: Anssi Jääskeläinen
Venue: Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction: Part II (2009)

This dissertation aims to narrow the user experience gap between the design and test phases in software development by offering UX tools for the developers.Research area: Tools for Design, Modeling, Evaluation.
Fast CRCs
Authors: Gam D. Nguyen
Venue: IEEE Transactions on Computers (2009)

CRCs have desirable properties for effective error detection. But their software implementation, which relies on many steps of the polynomial division, is typically slower than other codes such as weaker checksums. A relevant question is whether there are some particular CRCs that have fast implementation. In this paper, we introduce such fast CRCs as well as an effective technique to implement them. For these fast CRCs, even without using table lookup, it is possible either to eliminate or to greatly reduce many steps of the polynomial division during their computation.
The Distribution Reliability Assessment Based on the Arithmetic of Simulating Reasoning
Authors: Huang Lihua, Hu Jie, Zhang Lina, Xie Yunfang, Huo Limin
Venue: Proceedings of the 2009 First International Workshop on Database Technology and Applications (2009)

It mentions a new method of distribution reliability assessment based on Bayesian Network timing simulation. It uses node model "causal" to change the gotten or lost duration of load points combined with the characteristics of bayesian diagnostic reasoning and causal reasoning. it can simply effectively obtain the index of distribution system reliability and find out the weakest link of the power net; The value of the elements reliability are converged faster and enhance the index convergence rate by the method Flag Constringency mentioned as followed. The result of operation calculated realistically proves the method here mentioned is effectively.
What's there to talk about?: a multi-modal model of referring behavior in the presence of shared visual information
Authors: Darren Gergle
Venue: Proceedings of the Eleventh Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop (2006)

This paper describes the development of a rule-based computational model that describes how a feature-based representation of shared visual information combines with linguistic cues to enable effective reference resolution. This work explores a language-only model, a visual-only model, and an integrated model of reference resolution and applies them to a corpus of transcribed task-oriented spoken dialogues. Preliminary results from a corpus-based analysis suggest that integrating information from a shared visual environment can improve the performance and quality of existing discourse-based models of reference resolution.
A Human DNA Methylation Site Predictor Based on SVM
Authors: Yi-Ming Sun, Wei-Li Liao, Hsien-Da Huang, Baw-Jhiune Liu, Cheng-Wei Chang, Jorng-Tzong Horng, Li-Ching Wu
Venue: Proceedings of the 2009 Ninth IEEE International Conference on Bioinformatics and Bioengineering (2009)

During gene expression, transcription factors are unable to bind to a transcription binding site (TFBS) involved in regulation if DNA methylation has occurred at the TFBS. Methyl-CpG-binding proteins may also occupy the TFBS and prevent the functioning of a transcription factor. Thus, the methylation status of CpG sites is an important issue when trying to understand gene regulation and shows strong correlation with the TFBS involved. In addition, CpG islands would seem to undergo cell-specific and tissue-specific me-thylation. Such differential methylation is presented at numerous genetic loci that are essential for development. Current DNA methylation site prediction tools need to be improved so that they include TFBS features and have greater accuracy in terms of the DNA region that is involved in methylation. We developed models that compare the differences across these regions and tissues. The TFBSs, DNA properties and DNA distribution were used as features for this classification. From the results, we found some TFBSs that were able to discriminate whether a sequence was methylated or not. The sensitivity, specificity and accuracy estimated using 10-fold cross validation were 90.8%, 80.54%, and 86.07%, respectively. Thus, for these four regions and twelve tissues, the performance levels (ACC) were all greater than 80%. We propose that the differential features or methylations vary between the different regions because the features common to each DNA region made up only 50% of the top 70 features. An online predictor based on EpiMeP is available at http://140.115.51.41/EpiMeP/. Supplementary file is available at http://140.115.51.41/EpiMeP/supplementary.doc.
Probabilistic QoS Guarantees, Downlink and Uplink Scheduling Studies in a Bluetooth Piconet
Authors: Karima Maalaoui, Leila Saidane
Venue: Proceedings of the 2009 IEEE International Conference on Networking, Architecture, and Storage (2009)

We address analytic performance evaluation of a bluetooth piconet by considering the M/G/1 queue with batch arrivals and vacation times. We present a probabilistic approach to support diverse traffics with QoS guarantees. We consider mainly two constraints: the packet deadline and its priority. We focus on two new scheduling techniques that we have proposed in our previous works. The first technique combines FIFO and the class based priority queuing (PQ) while the second combines EDF (Earliest deadline First) and PQ. We focus our interest to providing Quality of Service (QoS) guarantees to various classes of soft real-time applications by using a probabilistic approach. Here, we compute the end-to-end delay distribution composed by the uplink and downlink waiting times. The end-to-end delay is used to obtain the probability that the response time doesn't exceed a given deadline. Then, we propose a probabilistic admission control procedure for real time flows. We validated the obtained theoretical results through simulations using an extension of the network simulator NS2 called Bluehoc.