ppxscal/embedding_network huggingface dataset:
Perform Energy-Aware Resource Discovery over Ad Hoc Networks
Authors: Yao Yu, Yu Zhou, Sidan Du
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 02 (2009)

Due to the imitated power supply in MANETs, the power consumption must be taken into account for a design of the resource discovery approach. In this paper, we proposed a distributed energy-aware resource discover approach, named EaDiscovery, to perform energy-efficient resource discovery. The motivation of the proposed approach is to minimize the total power consumption to request a service or subscribe a content after discovery, and maximize the lifetime of the resource provider with a low lever of power supply remained. We modeled the problem of energy-aware discovery based on the motivation mentioned above, and proposed a power Consumption Based Decay Bloom Filter (cbdBF) based upon the traditional bloom filters to achieve an optimal discovery for MANETs. We also illustrated the proof to verify the correctness of the EaDiscovery. Simulation results suggest that EaDiscovery achieves almost 95% of the theoretical results derived from the global information.
Evolutionary and case-based approaches to REG: NIL-UCM-EvoTAP, NIL-UCM-ValuesCBR and NIL-UCM-EvoCBR
Authors: Raquel Hervás, Pablo Gervás
Venue: Proceedings of the 12th European Workshop on Natural Language Generation (2009)

We propose the use of evolutionary algorithms (EAs) (Holland, 1992) to deal with the attribute selection task of referring expression generation. Evolutionary algorithms operate over a population of individuals (possible solutions for a problem) that evolve according to selection rules and genetic operators. The fitness function is a metric that evaluates each of the possible solutions, ensuring that the average adaptation of the population increases each generation. Repeating this process hundreds or thousands of times leads to very good solutions for the problem.
Computing optimal subsets
Authors: Maxim Binshtok, Ronen I. Brafman, Solomon E. Shimony, Ajay Martin, Craig Boutilier
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 (2007)

Various tasks in decision making and decision support require selecting a preferred subset of items from a given set of feasible items. Recent work in this area considered methods for specifying such preferences based on the attribute values of individual elements within the set. Of these, the approach of (Brafman et al. 2006) appears to be the most general. In this paper, we consider the problem of computing an optimal subset given such a specification. The problem is shown to be NP-hard in the general case, necessitating heuristic search methods. We consider two algorithm classes for this problem: direct set construction, and implicit enumeration as solutions to appropriate CSPs. New algorithms are presented in each class and compared empirically against previous results.
Safety Requirements Parameter Derivation for Maglev Train Propulsion and Protection Systems Based on Stochastic Petri Nets
Authors: Wei Zheng, Hongze Xu
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

This paper presents a formal approach to model thetraffic operational processes on a Maglev train example basedon Stochastic Petri nets. The Maglev train is modeled withrespect to process, function and dependability. Process modeldescribes the normal running status and abnormal protectedstatus of the Maglev train from departure to stopping andfunction model shows the working principle of propulsion andprotection function. Dependability model describes the failureand recover rate of this two functions. The relationshipbetween process, function and dependability is also describedin this model based on the propulsion and protection principle.The relationship between individual risk and accident rates isbuilt up and then simulations based on the model show that thedependability parameters of the propulsion and protectionfunctions can be derived based on the safety requirements ofthe CENELEC standards. Finally the availability of thepropulsion and protection systems is analyzed.
Dynamics Characteristics of Air Propeller-Gear Reducer Propulsion Device Based on Virtual Prototype
Authors: Rui-guang Geng, Wan-you Li, Hong-tian Zhang
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

To study characteristics of a air propeller-gear reducer propulsion device, a scale virtual prototype of the device was established using ADAMS and Pro/E software based on virtual prototyping and parametric modeling. Kinematics and dynamics characteristics were gained through computer simulation in rated-load and in no-load. The influence of elastic coupling for propeller movement and gear meshing force was obtained. Study result shows propeller movement and gear meshing force are influenced by change of device velocity and acceleration, elastic coupling torsion stiffness, propeller’s movement of inertia and working load.
A Methodological Specification of a Guideline for Diagnosis and Management of PreEclampsia
Authors: Avner Hatsek, Yuval Shahar, Meirav Taieb-Maimon, Erez Shalom, Adit Dubi-Sobol, Guy Bar, Arie Koyfman, Eitan Lunenfeld
Venue: Knowledge Management for Health Care Procedures: ECAI 2008 Workshop, K4HelP 2008, Patras, Greece, July 21, 2008, Revised Selected Papers (2009)

There is a broad agreement regarding the necessity of building usable and functional tools for specification of machine-interpretable clinical guidelines, to provide guideline-based medical care. There is much less of a consensus of how to go about it and whether the whole process is feasible in a real clinical domain. In this study, we have applied a new architecture, the Gesher graphical tool, to the specification of an important Obstetric guideline (diagnosis and management of PreEclampsia / Eclampsia toxemia). We have assessed the feasibility (functionality and usability) of (1) representing a clinical consensus customized for a particular medical center and (2) structuring the full content of the guideline. In addition, we have assessed in a preliminary fashion, the potential of using a less experienced clinician as a markup editor, by asking both a senior Obstetrics and Gynecology clinician, and a general intern, to represent the same guideline using the Gesher system. The results demonstrated the functionality and usability of the Gesher system, at least for these two editors; the intern's performance was at least as good as that of the senior physician with respect to the specific task of structuring the guideline according to the Hybrid Asbru ontology, using our tools.
Proceedings of the 4th ACM workshop on Challenged networks
Venue: International Conference on Mobile Computing and Networking (2009)

We welcome you to the 4th ACM Workshop on Challenged Networks (CHANTS), the fifth workshop in its series after WDTN 2005 and CHANTS 2006, 2007, and 2008 focusing on communication in challenged networking environments in general and delay-tolerant networking in particular. Challenged and delay-tolerant communications are receiving increasingly more attention. The disruption-prone or opportunistic nature of networking peered with potentially non-existing end-to- end paths are becoming commonly accepted for research in many areas, including (but not limited to) mobile ad-hoc and sensor networks as can be witnessed from many recent publications addressing these issues. Particularly ad-hoc communication among mobile human users with their specific mobility patterns and application demands--for daily life and in extreme situations such as disaster management--has attracted many researchers' interest. We observe how research efforts expand their scope in many ways highly relevant to the future of challenged communication: from synthetic mobility models to realistic ones (e.g., based on human mobility traces), from routing protocols and optimizations to real applications, from isolated views of individual problems to system and integration aspects, and from simulations to implementations. At the same time, fundamental research on understanding and categorizing algorithms and protocols for challenged networks are pursued to provide a more solid foundation where our current understanding is still in the early stages. The focus of this year's workshop is on experiences with challenged networks, such as experimental results, measurements, implementations, full-system and large-scale simulations, operational experiences, deployment problems, and applications for challenged networks. A keynote will set the stage giving perspectives on the future research questions at hand. In our sessions, we will cover basic concepts on routing in opportunistic networks, protocols and incentives, as well as applications for challenged networks. From the 9 papers included in the workshop, 8 were selected out of 22 submissions, and we added one invited paper to the program. Each paper received at least three independent single-blind reviews by the TPC. In support of the trend towards implementation, this year's workshop provides a venue for primarily practical and otherwise hard-to-publish results and therefore includes a demonstration session. We hope that you will find the program interesting and thought-provoking and that the symposium will provide you with a valuable opportunity to share ideas with other researchers and practitioners from institutions around the world.
Theories without Heart
Authors: Leopoldina Fortunati
Venue: Cross-Modal Analysis of Speech, Gestures, Gaze and Facial Expressions: COST Action 2102 International Conference Prague, Czech Republic, October 15-18, 2008 Revised Selected and Invited Papers (2009)

In general, sociological theories are, or at least seem, to be without heart. However many fundamental sociological notions such as solidarity, social cohesion and identity are highly emotional. In the field of information and communication technologies studies there is a specific theory, that of domestication (Silverstone and Hirsch [58], Silverstone and Haddon [59], Haddon and Silverstone [31]), inside which several research studies on the emotional relationship with ICTs have flourished (Fortunati [19], [20]; Vincent [63]). In this paper I will focus on this theory, which is one of the frameworks most commonly applied to understand the integration of ICTs into everyday life. I argue that emotion empowers sociological theories when its analysis is integrated into them. To conclude, I will discuss the seminal idea proposed by Star and Bowker [62] to consider emotion as an infrastructure of body-to-body communication.
Boundaries as Contours of Optimal Appearance and Area of Support
Authors: Christina Pavlopoulou, Stella X. Yu
Venue: Proceedings of the 7th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition (2009)

Bayesian boundary models often assume that the evidence for each contour is derived from the entire image. Consequently, the normalization term in the Bayes rule is the same for every contour and becomes irrelevant when seeking the optimal. However, in practice these models only use the vicinity of a contour, making the normalization term contour-specific. We propose a formulation that acknowledges the normalization term and includes it in the optimization. We show that it can be interpreted as a confidence measure promoting contours which are far better than other nearby candidate contours. We validate our approach in an interactive boundary delineation setting and demonstrate that complex boundaries can be extracted with significantly smaller amount of user input than when traditional Bayesian models are employed.
Robust path integration in the entorhinal grid cell system with hippocampal feed-back
Authors: D&#x00e1;vid Samu, P&#x00e9;ter Er&#x0151;s, Bal&#x00e1;zs Ujfalussy, Tam&#x00e1;s Kiss
Venue: Biological Cybernetics (2009)

Animals are able to update their knowledge about their current position solely by integrating the speed and the direction of their movement, which is known as path integration. Recent discoveries suggest that grid cells in the medial entorhinal cortex might perform some of the essential underlying computations of path integration. However, a major concern over path integration is that as the measurement of speed and direction is inaccurate, the representation of the position will become increasingly unreliable. In this paper, we study how allothetic inputs can be used to continually correct the accumulating error in the path integrator system. We set up the model of a mobile agent equipped with the entorhinal representation of idiothetic (grid cell) and allothetic (visual cells) information and simulated its place learning in a virtual environment. Due to competitive learning, a robust hippocampal place code emerges rapidly in the model. At the same time, the hippocampo-entorhinal feed-back connections are modified via Hebbian learning in order to allow hippocampal place cells to influence the attractor dynamics in the entorhinal cortex. We show that the continuous feed-back from the integrated hippocampal place representation is able to stabilize the grid cell code.
Narrowband Interference Suppression for IEEE UWB Channels
Authors: Miglen Ovtcharov, Vladimir Poulkov, Georgi Iliev, Zlatka Nikolova
Venue: Proceedings of the 2009 Fourth International Conference on Digital Telecommunications (2009)

In this paper we put forward a scheme for suppressing narrowband interference by the use of adaptive narrowband filtering. We compare this method with other schemes for the suppression of complex narrowband interference in OFDM UWB systems, such as the frequency excision method and complex narrowband interference identification and cancelation algorithms. The study shows that the three schemes give slightly different performance depending on the type of IEEE UWB channel, but the optimal solution is to apply a complex adaptive narrowband filter that offers a trade-off between narrowband interference suppression efficiency and computational complexity.
Reflections on Optimal and Nearly Optimal Binary Search Trees
Authors: J. Ian Munro
Venue: Efficient Algorithms: Essays Dedicated to Kurt Mehlhorn on the Occasion of His 60th Birthday (2009)

We take a rather informal look at the development of techniques for finding optimal and near optimal binary search trees. The point of view is both that of the "early" development of the field and as a set of wonderful examples for teaching algorithms.
Projecting POS tags and syntactic dependencies from English and French to Polish in aligned corpora
Authors: Sylwia Ozdowska
Venue: Proceedings of the International Workshop on Cross-Language Knowledge Induction (2006)

This paper presents the first step to project POS tags and dependencies from English and French to Polish in aligned corpora. Both the English and French parts of the corpus are analysed with a POS tagger and a robust parser. The English/Polish bi-text and the French/Polish bi-text are then aligned at the word level with the Giza++ package. The intersection of IBM-4 Viterbi alignments for both translation directions is used to project the annotations from English and French to Polish. The results show that the precision of direct projection vary according to the type of induced annotations as well as the source language. Moreover, the performances are likely to be improved by defining regular conversion rules among POS tags and dependencies.
On Software Parallel Implementation of Cryptographic Pairings
Authors: Philipp Grabher, Johann Großschädl, Dan Page
Venue: Selected Areas in Cryptography: 15th International Workshop, SAC 2008, Sackville, New Brunswick, Canada, August 14-15, Revised Selected Papers (2009)

A significant amount of research has focused on methods to improve the efficiency of cryptographic pairings; in part this work is motivated by the wide range of applications for such primitives. Although numerous hardware accelerators for pairing evaluation have used parallelism within extension field arithmetic to improve efficiency, thus far less emphasis has been placed on software exploitation of similar. In this paper we focus on parallelism within one pairing evaluation (intra-pairing), and parallelism between different pairing evaluations (inter-pairing). We identify several methods for exploiting such parallelism (extending previous results in the context of ECC) and show that it is possible to accelerate pairing evaluation by a significant factor in comparison to a naive approach.
Syntactic reordering for English-Arabic phrase-based machine translation
Authors: Jakob Elming, Nizar Habash
Venue: Proceedings of the EACL 2009 Workshop on Computational Approaches to Semitic Languages (2009)

We investigate syntactic reordering within an English to Arabic translation task. We extend a pre-translation syntactic reordering approach developed on a close language pair (English-Danish) to the distant language pair, English-Arabic. We achieve significant improvements in translation quality over related approaches, measured by manual as well as automatic evaluations. These results prove the viability of this approach for distant languages.
Transferring multi-device localization models using latent multi-task learning
Authors: Vincent Wenchen Zheng, Sinno Jialin Pan, Qiang Yang, Jeffrey Junfeng Pan
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 3 (2008)

In this paper, we propose a latent multi-task learning algorithm to solve the multi-device indoor localization problem. Traditional indoor localization systems often assume that the collected signal data distributions are fixed, and thus the localization model learned on one device can be used on other devices without adaptation. However, by empirically studying the signal variation over different devices, we found this assumption to be invalid in practice. To solve this problem, we treat multiple devices as multiple learning tasks, and propose a multi-task learning algorithm. Different from algorithms assuming that the hypotheses learned from the original data space for related tasks can be similar, we only require the hypotheses learned in a latent feature space are similar. To establish our algorithm, we employ an alternating optimization approach to iteratively learn feature mappings and multi-task regression models for the devices. We apply our latent multi-task learning algorithm to real-world indoor localization data and demonstrate its effectiveness.
Design of a Central Pattern Generator Using Reservoir Computing for Learning Human Motion
Authors: Francis Wyffels, Benjamin Schrauwen
Venue: Proceedings of the 2009 Advanced Technologies for Enhanced Quality of Life (2009)

To generate coordinated periodic movements, robot locomotion demands mechanisms which are able to learn and produce stable rhythmic motion in a controllable way. Because systems based on biological central pattern generators (CPGs) can cope with these demands, these kind of systems are gaining in success. In this work we introduce a novel methodology that uses the dynamics of a randomly connected recurrent neural network for the design of CPGs. When a randomly connected recurrent neural network is excited with one or more useful signals, an output can be trained by learning an instantaneous linear mapping of the neuron states. This technique is known as reservoir computing (RC). We will show that RC has the necessary capabilities to be fruitful in designing a CPG that is able to learn human motion which is applicable for imitation learning in humanoid robots.
Capturing expression using linguistic information
Authors: Özlem Uzuner, Boris Katz
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 3 (2005)

Recognizing similarities between literary works for copyright infringement detection requires evaluating similarity in the expression of content. Copyright law protects expression of content; similarities in content alone are not enough to indicate infringement. Expression refers to the way people convey particular information; it captures both the information and the manner of its presentation. In this paper, we present a novel set of linguistically informed features that provide a computational definition of expression and that enable accurate recognition of individual titles and their paraphrases more than 80% of the time. In comparison, baseline features, e.g., tfidf-weighted keywords, function words, etc., give an accuracy of at most 53%. Our computational definition of expression uses linguistic features that are extracted from POS-tagged text using context-free grammars, without incurring the computational cost of full parsers. The results indicate that informative linguistic features do not have to be computationally prohibitively expensive to extract.
Maintaining Ideally Distributed Random Search Trees without Extra Space
Authors: Raimund Seidel
Venue: Efficient Algorithms: Essays Dedicated to Kurt Mehlhorn on the Occasion of His 60th Birthday (2009)

We consider the problem of maintaing a random binary search tree under insertions and deletions under the conditions that (i) no extra permanent storage space be used besides the tree itself, and (ii) that at any point in time the tree be perfectly random, meaning that it is drawn from the ideal binary search tree distribution. We present a simple solution to this problem with an expected deletion time of O(logn) and expected insertion time of O(log2 n) time.
An Urban Study of Crime and Health Using an Exploratory Spatial Data Analysis Approach
Authors: Su-Yin Tan, Robert Haining
Venue: Proceedings of the International Conference on Computational Science and Its Applications: Part I (2009)

Research into the impacts of crime on health is relevant to adopting effective social policy and encouraging partnerships between local health and crime prevention agencies. Although it is not difficult to support the notion of crime as a threat to public health, the difficulty lies in quantifying the impact. Confounding effects of other influential variables (i.e. income, employment, housing) further complicate any analysis into the causal relationships between crime and health. An exploratory spatial data analysis approach was adopted in this study to examine the spatial relationships between crime, health, and quality of life indicators in Super Output Areas (SOAs) in Sheffield (UK). Quantitative methods of spatial data exploration and visualisation, and spatial autocorrelation analysis were used, based on aggregated secondary data drawn from census and crime databases. Statistical models of crime and health were specified, while taking into account the presence of spatial effects by applying spatial regression techniques.
An unsupervised clustering approach for leukaemia classification based on DNA micro-arrays data
Authors: Simone Garatti, Sergio Bittanti, Diego Liberati, Andrea Maffezzoli
Venue: Intelligent Data Analysis (2007)

DNA micro-arrays provide thousands of genomic expressions on the same subject. A main issue is then to find the subset of genes whose degeneration is responsible of a certain type of cancer. In this paper, starting from a paradigmatic classification problem of two kinds of Leukaemia, we discuss the use of data-mining techniques in such a context. Particular attention is devoted not only to the classification method but also to all the data analysis steps including data pre-processing and information retrieval.