ppxscal/embedding_network huggingface dataset:
Minimising Loss-Induced Errors in Real Time Wireless Sensing by Avoiding Data Dependency
Authors: A. D. Young, M. J. Ling
Venue: Proceedings of the 2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks (2009)

The use of local processing to reduce data transmission rates, and thereby power and bandwidth requirements, is common in wireless sensor networks. Achieving the minimum possible data rate, however, is not always the optimal choice when the effects of packet loss on overall measurement error are considered. This paper presents a case study from the area of wireless inertial motion capture, in which the best distributed processing strategy is shown to be that which minimises inter-packet data dependency, rather than overall data rate. Drawing on this result and further analysis, we identify questions that should be raised during the design process in order to understand the effects of packet loss on distributed signal processing tasks, decide whether the errors are acceptable for an application, and choose appropriate techniques to mitigate them if necessary.
Feature-aligned shape texturing
Authors: Kai Xu, Daniel Cohen-Or, Tao Ju, Ligang Liu, Hao Zhang, Shizhe Zhou, Yueshan Xiong
Venue: ACM Transactions on Graphics (TOG) (2009)

The essence of a 3D shape can often be well captured by its salient feature curves. In this paper, we explore the use of salient curves in synthesizing intuitive, shape-revealing textures on surfaces. Our texture synthesis is guided by two principles: matching the direction of the texture patterns to those of the salient curves, and aligning the prominent feature lines in the texture to the salient curves exactly. We have observed that textures synthesized by these principles not only fit naturally to the surface geometry, but also visually reveal, even reinforce, the shape's essential characteristics. We call these feature-aligned shape texturing. Our technique is fully automatic, and introduces two novel technical components in vector-field-guided texture synthesis: an algorithm that orients the salient curves on a surface for constrained vector field generation, and a feature-to-feature texture optimization.
From Data Integration towards Knowledge Mediation
Authors: Gerhard Brewka, Thomas Eiter
Venue: Proceedings of the 10th International Conference on Logic Programming and Nonmonotonic Reasoning (2009)

A major goal of AI are powerful reasoning capabilities which empower the development of advanced knowledge processing systems. To this end, current research is focused on information and knowledge integration, addressing the needs that emerge in the realm of the World Wide Web and future information systems. Following Wiederhold's mediator concept, powerful knowledge mediation is envisioned that fruitfully exploits LPNMR technology, as already done in the data integration context. Realizing this vision raises in turn challenging issues for research.
Abstraction in predictive state representations
Authors: Vishal Soni, Satinder Singh
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 1 (2007)

Most work on Predictive Representations of State (PSRs) focuses on learning a complete model of the system that can be used to answer any question about the future. However, we may be interested only in answering certain kinds of abstract questions. For instance, we may only care about the presence of objects in an image rather than pixel level details. In such cases, we may be able to learn substantially smaller models that answer only such abstract questions. We present the framework of PSR homomorphisms for model abstraction in PSRs. A homomorphism transforms a given PSR into a smaller PSR that provides exact answers to abstract questions in the original PSR. As we shall show, this transformation captures structural and temporal abstractions in the original PSR.
Redefining Architectural Elements by Digital Media
Authors: Kai-Hsiang Liang
Venue: Proceedings of the 1st International Conference on Human Centered Design: Held as Part of HCI International 2009 (2009)

An architectural element is a unit of a construction. Architects and researchers can understand how to design by defining architectural elements. Design media act as helping roles between the designers' abstract concept and the concrete composition. Today, architectures designed by different media have different outcomes. This study discusses the relationship between architectural elements and design media, and treats whether digital media impact the existing architectural elements. In conclusion, digital media can not only use architectural elements from non-digital media, but also create three digital architectural elements, which are "curvy-surface", "multiple-functions" and "slit-opening."
Creating novel goal-directed actions using chaotic dynamics
Authors: Hiroaki Arie, Tetsuro Endo, Takafumi Arakaki, Shigeki Sugano, Jun Tani
Venue: Proceedings of the 2009 IEEE 8th International Conference on Development and Learning (2009)

The present study examines the possible roles of cortical chaos in generating novel actions for achieving specified goals. The proposed neural network model consists of a sensory-forward model responsible for parietal lobe functions, a chaotic network model for premotor functions and prefrontal cortex model responsible for manipulating the initial state of the chaotic network. Experiments using humanoid robot were performed with the model and showed that the action plans for satisfying specific novel goals can be generated by diversely modulating and combining prior-learned behavioral patterns at critical dynamical states. Although this criticality resulted in fragile goal achievements in the physical environment of the robot, the reinforcement of the successful trials was able to provide a substantial gain with respect to the robustness. The discussion leads to the hypothesis that the consolidation of numerous sensory-motor experiences into the memory, meditating diverse imagery in the memory by cortical chaos, and repeated enaction and reinforcement of newly generated effective trials are indispensable for realizing an open-ended development of cognitive behaviors.
One More Decidable Class of Finitely Ground Programs
Authors: Yuliya Lierler, Vladimir Lifschitz
Venue: Proceedings of the 25th International Conference on Logic Programming (2009)

When a logic program is processed by an answer set solver, the first task is to generate its instantiation. In a recent paper, Calimeri et el. made the idea of efficient instantiation precise for the case of disjunctive programs with function symbols, and introduced the class of "finitely ground" programs that can be efficiently instantiated. Since that class is undecidable, it is important to find its large decidable subsets. In this paper, we introduce such a subset--the class of argument-restricted programs. It includes, in particular, all finite domain programs, ¿-restricted programs, and ¿-restricted programs.
Mobility increases the connectivity of K-hop clustered wireless networks
Authors: Qingsi Wang, Xinbing Wang, Xiaojun Lin
Venue: Proceedings of the 15th annual international conference on Mobile computing and networking (2009)

In this paper we investigate the connectivity for large-scale clustered wireless sensor and ad hoc networks. We study the effect of mobility on the critical transmission range for asymptotic connectivity in k-hop clustered networks, and compare to existing results on non-clustered stationary networks. By introducing k-hop clustering, any packet from a cluster member can reach a cluster head within k hops, and thus the transmission delay is bounded as Θ(1) for any finite k. We first characterize the critical transmission range for connectivity in mobile k-hop clustered networks where all nodes move under either the random walk mobility model with non-trivial velocity or the i.i.d. mobility model. By the term non-trivial velocity, we mean that the velocity of nodes v is Θ(1). We then compare with the critical transmission range for stationary k-hop clustered networks. We also study the transmission power versus delay trade-off and the average energy consumption per flow among different types of networks. We show that random walk mobility with non-trivial velocity increases connectivity in k-hop clustered networks, and thus significantly decreases the energy consumption and improves the power-delay trade-off. The decrease of energy consumption per flow is shown to be Θ(logn/nd}) in clustered networks. These results provide insights on network design and fundamental guidelines on building a large-scale wireless network.
Service Discovery in Mobile Ad Hoc Networks Using Mobility-Aware Attenuated Bloom Filters
Authors: Yao Yu, Yu Zhou, Sidan Du
Venue: Proceedings of the 2009 IITA International Conference on Services Science, Management and Engineering (2009)

Due to high mobility, highly dynamic topology and unreliable communication medium of Mobile Ad Hoc Networks (MANETs), nodes mobility must be taken into account in design of a service discovery protocol for such environment. A novel approach, Mobility-aware Attenuated Bloom Filters (maBF), to perform effective and efficient service discovery in MANETs is proposed in this paper. In order to guarantee both of the efficiency and performance in terms of low cost for advertisement, reasonable searching speed and high probability of finding a effective service, maBF employs a simple but efficient on demand advertisement algorithm to adapt nodes mobility. Such approach can significantly reduce the cost of service discovery but never enroll in performance degradation comparing with attenuated bloom filters. The Simulation results show that service discovery base on the use of maBF can well save traffic load even in the high mobility speed scenario.
Summarization with a joint model for sentence extraction and compression
Authors: André F. T. Martins, Noah A. Smith
Venue: Proceedings of the Workshop on Integer Linear Programming for Natural Langauge Processing (2009)

Text summarization is one of the oldest problems in natural language processing. Popular approaches rely on extracting relevant sentences from the original documents. As a side effect, sentences that are too long but partly relevant are doomed to either not appear in the final summary, or prevent inclusion of other relevant sentences. Sentence compression is a recent framework that aims to select the shortest subsequence of words that yields an informative and grammatical sentence. This work proposes a one-step approach for document summarization that jointly performs sentence extraction and compression by solving an integer linear program. We report favorable experimental results on newswire data.
Automatic Method for Measuring Eye Blinks Using Split-Interlaced Images
Authors: Kiyohiko Abe, Shoichi Ohi, Minoru Ohyama
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part I: New Trends (2009)

We propose a new eye blink detection method that uses NTSC video cameras. This method utilizes split-interlaced images of the eye. These split images are odd- and even-field images in the NTSC format and are generated from NTSC frames (interlaced images). The proposed method yields a time resolution that is double that in the NTSC format; that is, the detailed temporal change that occurs during the process of eye blinking can be measured. To verify the accuracy of the proposed method, experiments are performed using a high-speed digital video camera. Furthermore, results obtained using the NTSC camera were compared with those obtained using the high-speed digital video camera. We also report experimental results for comparing measurements made by the NTSC camera and the high-speed digital video camera.
On the approximation of instance level update and erasure in description logics
Authors: Giuseppe De Giacomo, Maurizio Lenzerini, Antonella Poggi, Riccardo Rosati
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 1 (2007)

A Description Logics knowledge base is constituted by two components, called TBox and ABox, where the former expresses general knowledge about the concepts and their relationships, and the latter describes the properties of instances of concepts. We address the problem of how to deal with changes to a Description Logic knowledge base, when these changes affect only its ABox. We consider two types of changes namely update and erasure, and we characterize the semantics of these operations on the basis of the approaches proposed by Winslett and by Katsuno and Mendelzon. It is well known that, in general, Description Logics are not closed with respect to updates, in the sense that the set of models corresponding to an update applied to a knowledge base in a Description Logic L may not be expressible by ABoxes in L. We show that this is true also for erasure. To deal with this problem, we introduce the notion of best approximation of an update (erasure) in a DL L, with the goal of characterizing the L ABoxes that capture the update (erasure) at best. We then focus on DL-LiteF, a tractable Description Logic, and present polynomial algorithms for computing the best approximation of updates and erasures in this logic, which shows that the nice computational properties of DL-LiteF are retained in dealing with the evolution of the ABox.
Estimating the market impact of security breach announcements on firm values
Authors: Sanjay Goel, Hany A. Shawky
Venue: Information and Management (2009)

Security breaches can have a significant economic impact on a firm. With public disclosure laws passed, security breaches involving disclosure of private client information can both damage the firms' reputation and lead to fines by US government agencies. We examined the impact of security breaches of US firms, as measured by their impact on the firm's market value. Data on security breaches were collected over the period 2004-2008. Reports and news articles corresponding to these breaches were obtained from public sources. Using event-study methodology, we estimate the impact of security breaches on the market value of publicly traded firms. Daily stock returns for firms impacted were obtained. Our results indicated that, on average, the announcement of a corporate security breach had a negative impact of about 1% of the market value of the firm during the days surrounding the event.
Incremental integer linear programming for non-projective dependency parsing
Authors: Sebastian Riedel, James Clarke
Venue: Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing (2006)

Integer Linear Programming has recently been used for decoding in a number of probabilistic models in order to enforce global constraints. However, in certain applications, such as non-projective dependency parsing and machine translation, the complete formulation of the decoding problem as an integer linear program renders solving intractable. We present an approach which solves the problem incrementally, thus we avoid creating intractable integer linear programs. This approach is applied to Dutch dependency parsing and we show how the addition of linguistically motivated constraints can yield a significant improvement over state-of-the-art.
Can one language bootstrap the other: a case study on event extraction
Authors: Zheng Chen, Heng Ji
Venue: Proceedings of the NAACL HLT 2009 Workshop on Semi-Supervised Learning for Natural Language Processing (2009)

This paper proposes a new bootstrapping framework using cross-lingual information projection. We demonstrate that this framework is particularly effective for a challenging NLP task which is situated at the end of a pipeline and thus suffers from the errors propagated from upstream processing and has low-performance baseline. Using Chinese event extraction as a case study and bitexts as a new source of information, we present three bootstrapping techniques. We first conclude that the standard mono-lingual bootstrapping approach is not so effective. Then we exploit a second approach that potentially benefits from the extra information captured by an English event extraction system and projected into Chinese. Such a cross-lingual scheme produces significant performance gain. Finally we show that the combination of mono-lingual and cross-lingual information in bootstrapping can further enhance the performance. Ultimately this new framework obtained 10.1% relative improvement in trigger labeling (F-measure) and 9.5% relative improvement in argument-labeling.
Non-monotonic temporal logics that facilitate elaboration tolerant revision of goals
Authors: Chitta Baral, Jicheng Zhao
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 1 (2008)

Temporal logics are widely used in specifying goals of agents. We noticed that when directing agents, humans often revise their requirements for the agent, especially as they gather more knowledge about the domain. However, all existing temporal logics, except one, do not focus on the revision of goals in an elaboration tolerant manner. Thus formal temporal logics that can allow elaboration tolerant revision of goals are needed. As non-monotonic languages are often used for elaboration tolerant specification, we propose to explore non-monotonic temporal logics for goal specification. Recently, a non-monotonic temporal logic, N-LTL, was proposed with similar aims. In N-LTL, goal specifications could be changed via strong and weak exceptions. However, in NLTL, one had to a-priori declare whether exceptions will be weak or strong exceptions. We propose a new nonmonotonic temporal logic, that not only overcomes this, but is also able to express exception to exceptions, strengthen and weaken preconditions, and revise and replace consequents; all in an elaboration tolerant manner.
Secure-TWS: Authenticating node to multi-user communication in shared sensor networks
Authors: Leonardo B. Oliveira, Aman Kansal, Bodhi Priyantha, Michel Goraczko, Feng Zhao
Venue: Proceedings of the 2009 International Conference on Information Processing in Sensor Networks (2009)

Recent works have shown the usefulness of network and application layer protocols that connect low power sensor nodes directly to multiple applications and users on the Internet. We propose a security solution for this scenario. While previous works have provided security support for various communication patterns in sensor networks, such as among nodes, from nodes to a base station, and from users to nodes, the security of communication from sensor nodes to multiple users has not been sufficiently addressed. Specifically, we explore this design space and develop a security solution, named Secure-TWS, for efficient authentication of data sent by a resource constrained sensor node to multiple users, using digital signatures. We investigate the resource overheads in communication and computation for two most suitable signature schemes - the Elliptic Curve Digital Algorithm (ECDSA) and the Boneh-Lynn-Shacham (BLS) short signature schemes. We implement these schemes on two popular sensor node architectures (based onMSP430 and ARM processors with 802.15.4 radios) and experimentally characterize relevant trade-offs.
The DEFACTO system: training tool for incident commanders
Authors: Nathan Schurr, Janusz Marecki, J. P. Lewis, Milind Tambe, Paul Scerri
Venue: Proceedings of the 17th conference on Innovative applications of artificial intelligence - Volume 3 (2005)

Techniques for augmenting the automation of routine coordination are rapidly reaching a level of effectiveness where they can simulate realistic coordination on the ground for large numbers of emergency response entities (e.g. fire engines. police cars) for the sake of training. Furthermore, it seems inevitable that future disaster response systems will utilize such technology. We have constructed a new system, DE-FACTO (Demonstrating Effective Flexible Agent Coordination of Teams through Omnipresence), that integrates state-of-the-art agent reasoning capabilities and 3D visualization into a unique high fidelity system for training incident commanders. The DEFACTO system achieves this goal via three main components: (i) Omnipresent Viewer - intuitive interface, (ii) Proxy Framework - for team coordination, and (iii) Flexible Interaction - between the incident commander and the team. We have performed detailed preliminary experiments with DEFACTO in the fire-fighting domain. In addition, DEFACTO has been repeatedly demonstrated to key police and fire department personnel in Los Angeles area, with very positive feedback.
Learning quantity insensitive stress systems via local inference
Authors: Jeffrey Heinz
Venue: Proceedings of the Eighth Meeting of the ACL Special Interest Group on Computational Phonology and Morphology (2006)

This paper presents an unsupervised batch learner for the quantity-insensitive stress systems described in Gordon (2002). Unlike previous stress learning models, the learner presented here is neither cue based (Dresher and Kaye, 1990), nor reliant on a priori Optimality-theoretic constraints (Tesar, 1998). Instead our learner exploits a property called neighborhood-distinctness, which is shared by all of the target patterns. Some consequences of this approach include a natural explanation for the occurrence of binary and ternary rhythmic patterns, the lack of higher n-ary rhythms, and the fact that, in these systems, stress always falls within a certain window of word edges.
Outstanding teachers and ICT
Authors: Aristidis Protopsaltis, Andy Goodwyn, Carol L. Fuller
Venue: Proceedings of the 27th ACM international conference on Design of communication (2009)

This paper presents evidence about expertise in teaching and the use of ICT (Information Communication Technology) to communicate information. Fifty four (54) expert teachers and teaching assistants from infant, primary and secondary schools participated in the study. Participants were nominated by their peers as 'outstanding' in their practice. Semi- structured interviews were conducted, exploring what technology experts have adapted to produce highly effective practice. The current study discusses the results of the demographic data, the technologies expert practitioners use in their teaching and their reasons for using these technologies.
Personalized Human Emotion Classification Using Genetic Algorithm
Authors: M. Rizon, D. Hazry, M. Karthigayan, R. Nagarajan, N. Alajlan, Y. Sazali
Venue: Proceedings of the 2009 Second International Conference in Visualisation (2009)

In this paper, lip and eye features are applied to classify the human emotion through a set of irregular and regular ellipse fitting equations using Genetic algorithm (GA). South East Asian face is considered in this study. All six universally accepted emotions and one neutral are considered for classifications. The method which is fastest in extracting lip features is adopted in this study. Observation of various emotions of the subject lead to an unique characteristic of lips and eye. GA is adopted to optimize irregular ellipse and regular ellipse characteristics of the lip and eye features in each emotion respectively. That is, the top portion of lip configuration is a part of one ellipse and the bottom of different ellipse. Two ellipse based fitness equations are proposed for the lip configuration and relevant parameters that define the emotion are listed. One ellipse based fitness function is proposed for eye. The GA method approach has achieved reasonably successful classification of emotion. While performing classification, optimized values can mess or overlap with other emotions range. In order to overcome the overlapping problem between the emotions and at the same time to improve the classification, a neural network (NN) approach is implemented. The GA-NN based process exhibits a range of 83% - 90% classification of the emotion from the optimized feature of top lip, bottom lip and eye.