ppxscal/embedding_network huggingface dataset:
Numerical simulation of stochastic replicator models in catalyzed RNA-like polymers
Authors: Andreas Röíler, Mohammed Seaïd, Mostafa Zahri
Venue: Mathematics and Computers in Simulation (2009)

A stochastic model for replicators in catalyzed RNA-like polymers is presented and numerically solved. The model consists of a system of reaction-diffusion equations describing the evolution of a population formed by RNA-like molecules with catalytic capabilities in a prebiotic process. The diffusion effects and the catalytic reactions are deterministic. A stochastic excitation with additive noise is introduced as a force term. To numerically solve the governing equations we apply the stochastic method of lines. A finite-difference reaction-diffusion system is constructed by discretizing the space and the associated stochastic differential system is numerically solved using a class of stochastic Runge-Kutta methods. Numerical experiments are carried out on a prototype of four catalyzed selfreplicator species along with an activated and an inactivated residues. Results are given in two space dimensions.
A New Adaptive Linear Interpolation Algorithm Using Pattern Weight Based on Inverse Gradient
Authors: Joohyeok Kim, Jechang Jeong
Venue: Proceedings of the 2009 First International Conference on Advances in Multimedia (2009)

Most of conventional interpolation methods do not consider the sufficient pattern of neighbor pixels, which cause quality degradation. Kim et al. proposed New Adaptive Linear (NAL) algorithm to consider patterns near the interpolated value [8]. However, they have a critical defect which does not reflect whether each neighbor pixels influence the interpolated pixel. To remove this defect, we propose a new image interpolation method using adaptive weight based on inverse gradient. Experimental results show that the proposed algorithm exhibits a better performance than conventional algorithms in both objective and subjective criteria with a variety of images. In addition, the proposed method just needs a little computational burden compared with other algorithms.
Conservative dual consistency
Authors: Christophe Lecoutre, Stéphane Cardon, Julien Vion
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 1 (2007)

Consistencies are properties of Constraint Networks (CNs) that can be exploited in order to make inferences. When a significant amount of such inferences can be performed, CNs are much easier to solve. In this paper, we interest ourselves in relation filtering consistencies for binary constraints, i.e. consistencies that allow to identify inconsistent pairs of values. We propose a new consistency called Dual Consistency (DC) and relate it to Path Consistency (PC). We show that Conservative DC (CDC, i.e. DC with only relations associated with the constraints of the network considered) is more powerful, in terms of filtering, than Conservative PC (CPC). Following the approach of Mac Gregor, we introduce an algorithm to establish (strong) CDC with a very low worst-case space complexity. Even if the relative efficiency of the algorithm introduced to establish (strong) CDC partly depends on the density of the constraint graph, the experiments we have conducted show that, on many series of CSP instances, CDC is largely faster than CPC (up to more than one order of magnitude). Besides, we have observed that enforcing CDC in a preprocessing stage can significantly speed up the resolution of hard structured instances.
Axiomatizing causal reasoning
Authors: Joseph Y. Halpern
Venue: Journal of Artificial Intelligence Research (2000)

Causal models defined in terms of a collection of equations, as defined by Pearl, are axiomatized here. Axiomatizations are provided for three successively more general classes of causal models: (1) the class of recursive theories (those without feedback), (2) the class of theories where the solutions to the equations are unique, (3) arbitrary theories (where the equations may not have solutions and, if they do, they are not necessarily unique). It is shown that to reason about causality in the most general third class, we must extend the language used by Galles and Pearl (1997, 1998). In addition, the complexity of the decision procedures is characterized for all the languages and classes of models considered.
Learning measures of progress for planning domains
Authors: SungWook Yoon, Alan Fern, Robert Givan
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 3 (2005)

We study an approach to learning heuristics for planning domains from example solutions. There has been little work on learning heuristics for the types of domains used in deterministic and stochastic planning competitions. Perhaps one reason for this is the challenge of providing a compact heuristic language that facilitates learning. Here we introduce a new representation for heuristics based on lists of set expressions described using taxonomic syntax. Next, we review the idea of a measure of progress (parmar 2002), which is any heuristic that is guaranteed to be improvable at every state. We take finding a measure of progress as our learning goal, and describe a simple learning algorithm for this purpose. We evaluate our approach across a range of deterministic and stochastic planning-competition domains. The results show that often greedily following the learned heuristic is highly effective. We also show our heuristic can be combined with learned rule-based policies, producing still stronger results.
The Filtering Performance of a Kind Antenna Model
Authors: Pang Xiaoyan, DingJun, Guo Chenjiang
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 03 (2009)

This paper investigates the filtering performance of a new kind of compact antenna model, the cube antenna model. At first, the explicit expressionfor the signal to interference-plus-noise ratio (SINR) is obtained in terms of the parameters of the signal, interference, and noise. Then the filtering performance is simulated with Matlab simulation software. The results show that this antenna model has an excellent filtering performance in Polarization Domain, which makes up the limitation of the traditional Adaptive Array Antenna (AAA). Comparison with the polarization-sensitive-array (PSA) presents that the cube antenna model does not only performs well in Space Domain but also more even in different directions. Moreover, this compact structurecan be used in a much smaller volume. All these results demonstrate that the cube antenna model has an outstanding performance both in Space and Polarization Domains. as illustrated by the portions given in this document.
WVALI: temporal relation identification by syntactico-semantic analysis
Authors: Georgiana Puşcaşu
Venue: Proceedings of the 4th International Workshop on Semantic Evaluations (2007)

This paper reports on the participation of University of Wolverhampton and University of Alicante at the SemEval-2007 TempEval evaluation exercise. TempEval consisted of three tasks involving the identification of event-time and event-event temporal relations. We participated in all three tasks with TICTAC (Syntactico-Semantic Temporal Annotation Cluster), a system comprising both knowledge based and statistical techniques. Our system achieved the highest strict and relaxed scores for tasks A and B, and the highest relaxed score for task C.
Glancing at personal navigation devices can affect driving: experimental results and design implications
Authors: Andrew L. Kun, Tim Paek, Željko Medenica, Nemanja Memarović, Oskar Palinko
Venue: Proceedings of the 1st International Conference on Automotive User Interfaces and Interactive Vehicular Applications (2009)

Nowadays, personal navigation devices (PNDs) that provide GPS-based directions are widespread in vehicles. These devices typically display the real-time location of the vehicle on a map and play spoken prompts when drivers need to turn. While such devices are less distracting than paper directions, their graphical display may distract users from their primary task of driving. In experiments conducted with a high fidelity driving simulator, we found that drivers using a navigation system with a graphical display indeed spent less time looking at the road compared to those using a navigation system with spoken directions only. Furthermore, glancing at the display was correlated with higher variance in driving performance measures. We discuss the implications of these findings on PND design for vehicles.
Research of Optimizing Device Description Technology Based on XML in EPA
Authors: Shu Yuanzhong, Tao Chenggong, Li Quan, Peng Xiaohong
Venue: Proceedings of the 2009 Second International Symposium on Electronic Commerce and Security - Volume 01 (2009)

In order to enhance the interoperability of device in EPA industry network control system, the characteristics of XDDL, the application flow and functions of EPA device description were discussed. The latest methods of XML parsing and the utilization efficiency of the device description data after being parsed were analyzed. A kind of parsing method and a double buffers technology used for device description data application were proposed. To evaluate the optimizing solution, the parsing methods were tested and compared. The test results indicated that the processing efficiency of EPA data parsing and application was improved. On the basis, the applying prospect of the optimizing solutions in CIMS and field device system was discussed.
Running Time Analysis of ACO Systems for Shortest Path Problems
Authors: Christian Horoba, Dirk Sudholt
Venue: Proceedings of the Second International Workshop on Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics (2009)

Ant Colony Optimization (ACO) is inspired by the ability of ant colonies to find shortest paths between their nest and a food source. We analyze the running time of different ACO systems for shortest path problems. First, we improve running time bounds by Attiratanasunthron and Fakcharoenphol [Information Processing Letters, 105(3):88---92, 2008] for single-destination shortest paths and extend their results for acyclic graphs to arbitrary graphs. Our upper bound is asymptotically tight for large evaporation factors, holds with high probability, and transfers to the all-pairs shortest paths problem. There, a simple mechanism for exchanging information between ants with different destinations yields a significant improvement. Our results indicate that ACO is the best known metaheuristic for the all-pairs shortest paths problem.
RTLS For Dummies
Authors: Ajay Malik
Venue: For Dummies (2009)

Select, invest in, and deploy a Real Time Location System Is your business ready for an RTLS? This friendly, hands-on guide shows you how to understand and implement this cutting-edge technology, explaining RTLS methodologies in plain English. From the initial deployment to monitoring to determining Return on Investment, you'll see how to successfully meet your needs, ensure data accuracy, and sustain your system. Get your bearings understand what RTLS does and its various methodologies, determine your needs, and select the right system Prepare for installation outline your goals, plan your applications, assess your site, select the right tag technology, and conduct a pilot test Implement RTLS in your world know how to train your staff, set expectations, set up monitoring, and assess whether the RTLS is working as desired Deal with design issues learn the most common pitfalls of RTLS implementation and how to handle them Take the technology tour use RTLS to locate at choke points, room level, presence, by association, and precisely Monitor and secure your RTLS verify and fine-tune your system, establish performance metrics, and manage security issues and vulnerabilities such as network attacks Open the book and find: An overview of RTLS and its uses Explanations of underlying technologies How to integrate RTLS into your other business applications Comparative detail on technologies that enable different types of locating Tips for evaluating RTLS vendors Essential RTLS resources and references Tips for getting the most out of the batteries used in tags Privacy issues related to RTLS 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
Generation of repeated references to discourse entities
Authors: Anja Belz, Sebastian Varges
Venue: Proceedings of the Eleventh European Workshop on Natural Language Generation (2007)

Generation of Referring Expressions is a thriving subfield of Natural Language Generation which has traditionally focused on the task of selecting a set of attributes that unambiguously identify a given referent. In this paper, we address the complementary problem of generating repeated, potentially different referential expressions that refer to the same entity in the context of a piece of discourse longer than a sentence. We describe a corpus of short encyclopaedic texts we have compiled and annotated for reference to the main subject of the text, and report results for our experiments in which we set human subjects and automatic methods the task of selecting a referential expression from a wide range of choices in a full-text context. We find that our human subjects agree on choice of expression to a considerable degree, with three identical expressions selected in 50% of cases. We tested automatic selection strategies based on most frequent choice heuristics, involving different combinations of information about syntactic MSR type and domain type. We find that more information generally produces better results, achieving a best overall test set accuracy of 53.9% when both syntactic MSR type and domain type are known.
One Improved SAGA-ML Method for Parameters Estimation of Hydrologic Frequency Models
Authors: Sang Yanfang, Wang Dong, Wu Jichun
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 01 (2009)

For solving the difficult problems of parameters estimation (influenced by model type, parameters number, complex computation process, etc) in the process of hydrologic frequency analysis by traditional methods, one improved method named SAGA-ML has been proposed as follows: firstly establishing one parameter optimization program, whose object function is the expression of minimal likelihood function about hydrologic frequency model, and the constraint equations are gotten by MOM, then SAGA is used to optimize parameters. This improved SAGA-ML method can overcome the disadvantages of conventional ML method because of using SAGA for parameter optimization. By Monte-Carlo tests, it has been concluded that the improved SAGA-ML method is effective and convenient when being used, and suitable for any hydrologic models, any numbers of parameters and any constraint conditions. So SAGA-ML becomes useful and effective both in theory and in practice.
Automatic acquisition of grammatical types for nouns
Authors: Núria Bel, Sergio Espeja, Montserrat Marimon
Venue: Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers on XX (2007)

The work we present here is concerned with the acquisition of deep grammatical information for nouns in Spanish. The aim is to build a learner that can handle noise, but, more interestingly, that is able to overcome the problem of sparse data, especially important in the case of nouns. We have based our work on two main points. Firstly, we have used distributional evidences as features. Secondly, we made the learner deal with all occurrences of a word as a single complex unit. The obtained results show that grammatical features of nouns is a level of generalization that can be successfully approached with a Decision Tree learner.
Collaborative learning in virtual seminars: analyzing learning processes and learning outcomes
Authors: Birgitta Kopp, Katharina Schnurer, Heinz Mandl
Venue: Proceedings of the 9th international conference on Computer supported collaborative learning - Volume 1 (2009)

This paper focuses on the analysis of a virtual seminar in respect to learning processes and learning outcomes of its participants who collaborated over a four month period. To investigate the learning processes in this field study, we analyzed the learners' contributions according to four main learning processes: epistemic activities, construction of a conceptual space, dissemination of shared knowledge, and conflict-orientation. To investigate the learning outcome, we analyzed the joint task solutions with respect to knowledge acquisition and knowledge application. Learners were assigned to three groups who had to solve four tasks relating to the main topics on knowledge management. Results show that learning processes varied depending on the tasks and groups, but no general trend was found. Furthermore, the four task solutions also differed in their quality. The fact that learning processes were related to group products confirms the relevance of learning processes for acquiring and applying knowledge.
Adapting Language Modeling Methods for Expert Search to Rank Wikipedia Entities
Authors: Jiepu Jiang, Wei Lu, Xianqian Rong, Yangyan Gao
Venue: Advances in Focused Retrieval: 7th International Workshop of the Initiative for the Evaluation of XML Retrieval, INEX 2008, Dagstuhl Castle, Germany, December 15-18, 2008. Revised and Selected Papers (2009)

In this paper, we propose two methods to adapt language modeling methods for expert search to the INEX entity ranking task. In our experiments, we notice that language modeling methods for expert search, if directly applied to the INEX entity ranking task, cannot effectively distinguish entity types. Thus, our proposed methods aim at resolving this problem. First, we propose a method to take into account the INEX category query field. Second, we use an interpolation of two language models to rank entities, which can solely work on the text query. Our experiments indicate that both methods can effectively adapt language modeling methods for expert search to the INEX entity ranking task.
Spatial prepositions in context: the semantics of near in the presence of distractor objects
Authors: Fintan J. Costello, John D. Kelleher
Venue: Proceedings of the Third ACL-SIGSEM Workshop on Prepositions (2006)

The paper examines how people's judgements of proximity between two objects are influenced by the presence of a third object. In an experiment participants were presented with images containing three shapes in different relative positions, and asked to rate the acceptability of a locative expression such as 'the circle is near the triangle' as descriptions of those images. The results showed an interaction between the relative positions of objects and the linguistic roles that those objects play in the locative expression: proximity was a decreasing function of the distance between the head object in the expression and the prepositional clause object, and an increasing function the distance between the head and the third, distractor object. This finding leads us to a new account for the semantics of spatial prepositions such as near.
Research on Position Detection of PSD Based on Light Intensity Modulation and Digital Fit
Authors: He Xiaorui, Zhong Yuning, Wang Xuanze, Zheng Huili
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 03 (2009)

Position sensitive detector (PSD) is influenced by the background light source when the weak light falls on its photo sensitive face. This paper applies the technique of sine light intensity modulation and band-pass filter which can overcome the background light to enhance the signal to noise ratio(S/N) of this position detection system greatly. The sum-intensity signal and the difference-intensity signal extracted from PSD are modulation frequency signals and the amplitude ratio and phase discrepancy are decided by the position of the light spot. Based on these characteristics, the approach of using simultaneous A/D and elliptical fitting algorithm to locate the light spot is adopted, and the related theoretical formulas are also carried out. This approach can conquer the defects of traditional signal processing methods. The experiment results show that: when the range of measured position is 9mm, the measurement accuracy is up to 0.01mm.
On the interaction between inverse features and path-functional dependencies in description logics
Authors: David Toman, Grant Weddell
Venue: Proceedings of the 19th international joint conference on Artificial intelligence (2005)

We investigate how inverse features can be added to a boolean complete description logic with path-functional dependencies in ways that avoid undecidability of the associated logical implication problem. In particular, we present two conditions that ensure the problem remains EXPTIME-complete. The first is syntactic in nature and limits the form that dependencies may have in argument terminologies. The second is a coherence condition on terminologies that is sufficiently weak to allow the transfer of relational and emerging object-oriented normalization techniques.
Qualified Computations in Functional Logic Programming
Authors: Rafael Caballero, Mario Rodríguez-Artalejo, Carlos A. Romero-Díaz
Venue: Proceedings of the 25th International Conference on Logic Programming (2009)

Qualification has been recently introduced as a generalization of uncertainty in the field of Logic Programming. In this paper we investigate a more expressive language for First-Order Functional Logic Programming with Constraints and Qualification. We present a Rewriting Logic which characterizes the intended semantics of programs, and a prototype implementation based on a semantically correct program transformation. Potential applications of the resulting language include flexible information retrieval. As a concrete illustration, we show how to write program rules to compute qualified answers for user queries concerning the books available in a given library.
Relative Span Weighted Localization of Uncooperative Nodes in Wireless Networks
Authors: Christine Laurendeau, Michel Barbeau
Venue: Proceedings of the 4th International Conference on Wireless Algorithms, Systems, and Applications (2009)

Increasingly ubiquitous wireless technologies require novel localization techniques to pinpoint the position of an uncooperative node, whether the target be a malicious device engaging in a security exploit or a low-battery handset in the middle of a critical emergency. Such scenarios necessitate that a radio signal source be localized by other network nodes efficiently, using minimal information. We propose two new algorithms for estimating the position of an uncooperative transmitter, based on the received signal strength (RSS) of a single target message at a set of receivers whose coordinates are known. As an extension to the concept of centroid localization, our mechanisms weigh each receiver's coordinates based on the message's relative RSS at that receiver, with respect to the span of RSS values over all receivers. The weights may decrease from the highest RSS receiver either linearly or exponentially. Our simulation results demonstrate that for all but the most sparsely populated wireless networks, our exponentially weighted mechanism localizes a target node within the regulations stipulated for emergency services location accuracy.