ppxscal/embedding_network huggingface dataset:
Speeding up the convergence of value iteration in partially observable Markov decision processes
Authors: Nevin L. Zhang, Weihong Zhang
Venue: Journal of Artificial Intelligence Research (2001)

Partially observable Markov decision processes (POMDPs) have recently become popular among many AI researchers because they serve as a natural model for planning under uncertainty. Value iteration is a well-known algorithm for finding optimal policies for POMDPs. It typically takes a large number of iterations to converge. This paper proposes a method for accelerating the convergence of value iteration. The method has been evaluated on an array of benchmark problems and was found to be very effective: It enabled value iteration to converge after only a few iterations on all the test problems.
Inversion/Non-inversion Implementation for an 11,424 Gate-Count Dynamic Optically Reconfigurable Gate Array VLSI
Authors: Shinichi Kato, Minoru Watanabe
Venue: Proceedings of the 9th International Workshop on Embedded Computer Systems: Architectures, Modeling, and Simulation (2009)

To date, various optically reconfigurable gate arrays (ORGAs) have been developed to realize both fast reconfiguration and numerous reconfiguration contexts. Optically differential reconfigurable gate arrays (ODRGAs) present the advantageous capabilities compared with ORGAs: they have increased reconfiguration frequency per unit of laser power and reduced optical power consumption. Dynamic optically reconfigurable gate arrays (DORGA) can realize the highest gate density, but an important disadvantage of DORGAs is that their reconfiguration frequency is lower than that of ODRGAs and their optical power consumption is greater than that of ODRGAs. Therefore, a novel inversion/non-inversion dynamic optically reconfigurable gate array that adopts only the good factors from both architectures has been developed. This paper presents an inversion/non-inversion implementation for a fabricated 11,424 gate-count dynamic optically reconfigurable gate array VLSI. Based on that implementation, three factors are discussed: gate density, reconfiguration frequency per unit of laser power, and optical power consumption.
Fast load balancing with the most to least loaded policy in dynamic networks
Authors: Abderrahmane Sider, Raphaël Couturier
Venue: The Journal of Supercomputing (2009)

Load balancing a distributed/parallel system consists in allocating work (load) to its processors so that they have to process approximately the same amount of work or amounts in relation with their computation power. In this paper, we present a new distributed algorithm that implements the Most to Least Loaded (M2LL) policy. This policy aims at indicating pairs of processors, that will exchange loads, taking into account actually broken edges as well as the current load distribution in the system. The M2LL policy fixes the pairs of neighboring processors by selecting in priority the most loaded and the least loaded processor of each neighborhood. Our first and main result is that the M2LL distributed implementation terminates after at most (n/2)¿d t iterations where n and d t are respectively the number of nodes and the degree of the system at time t. We then present a performance comparison between Generalized Adaptive Exchange (GAE) that uses M2LL and Relaxed First Order Scheme (RFOS), two load balancing algorithms for dynamic networks in which only link failures are considered. The comparison is carried out on a dedicated test bed that we have designed and implemented to this end. Our second important result is that although generating more communications, the GAE algorithm with the M2LL policy is faster than RFOS in balancing the system load. In addition, GAE M2LL is able to achieve a more stable balanced state than RFOS and scales well.
Preliminary Study on Remote Assistance for People with Dementia at Home by Using Multi-media Contents
Authors: Toshimi Hamada, Noriaki Kuwahara, Kazunari Morimoto, Kiyoshi Yasuda, Utsumi Akira, Shinji Abe
Venue: Proceedings of the 5th International Conference on Universal Access in Human-Computer Interaction. Addressing Diversity. Part I: Held as Part of HCI International 2009 (2009)

We are developing the system that remotely support the daily living of people with dementia at home by using multi-media contents for bringing their peace of mind, for preventing their behavioural disturbances, and for guiding actions of their daily living, because a major problem in providing good care at home to people with dementia is that it must be constantly provided without interruption, which puts a great burden on family caregivers. At first, our developed system can provide dementia people with multi-media contents such as reminiscence photos and videos for instilling a sense of peacefulness in their minds. These contents are used in remote reminiscence therapy by using simultaneous photo and video sharing. Also, we developed video instruction system for guiding their actions in a toilet to help them. We evaluated the effectiveness of our system from viewpoints of relieving the stress of their family caregivers, and of the extent of their independence in daily living. According to the evaluation results, we discuss on essential problems to be overcome for supporting people with dementia remotely, and present our approach towards realizing the system that effectively guides and navigates people with dementia for living independently.
Neurophysiological correlates of comprehending emotional meaning in context
Authors: Daphne J. Holt, Spencer K. Lynn, Gina R. Kuperberg
Venue: Journal of Cognitive Neuroscience (2009)

Although the neurocognitive mechanisms of nonaffective language comprehension have been studied extensively, relatively less is known about how the emotional meaning of language is processed. In this study, electrophysiological responses to affectively positive, negative, and neutral words, presented within nonconstraining, neutral contexts, were evaluated under conditions of explicit evaluation of emotional content (Experiment 1) and passive reading (Experiment 2). In both experiments, a widely distributed Late Positivity was found to be larger to negative than to positive words (a "negativity bias"). In addition, in Experiment 2, a small, posterior N400 effect to negative and positive (relative to neutral) words was detected, with no differences found between N400 magnitudes to negative and positive words. Taken together, these results suggest that comprehending the emotional meaning of words following a neutral context requires an initial semantic analysis that is relatively more engaged for emotional than for nonemotional words, whereas a later, more extended, attention-modulated process distinguishes the specific emotional valence (positive vs. negative) of words. Thus, emotional processing networks within the brain appear to exert a continuous influence, evident at several stages, on the construction of the emotional meaning of language.
A unigram orientation model for statistical machine translation
Authors: Christoph Tillmann
Venue: Proceedings of HLT-NAACL 2004: Short Papers on XX (2004)

In this paper, we present a unigram segmentation model for statistical machine translation where the segmentation units are blocks: pairs of phrases without internal structure. The segmentation model uses a novel orientation component to handle swapping of neighbor blocks. During training, we collect block unigram counts with orientation: we count how often a block occurs to the left or to the right of some predecessor block. The orientation model is shown to improve translation performance over two models: 1) no block re-ordering is used, and 2) the block swapping is controlled only by a language model. We show experimental results on a standard Arabic-English translation task.
Contextual phrase-level polarity analysis using lexical affect scoring and syntactic N-grams
Authors: Apoorv Agarwal, Fadi Biadsy, Kathleen R. Mckeown
Venue: Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics (2009)

We present a classifier to predict contextual polarity of subjective phrases in a sentence. Our approach features lexical scoring derived from the Dictionary of Affect in Language (DAL) and extended through WordNet, allowing us to automatically score the vast majority of words in our input avoiding the need for manual labeling. We augment lexical scoring with n-gram analysis to capture the effect of context. We combine DAL scores with syntactic constituents and then extract n-grams of constituents from all sentences. We also use the polarity of all syntactic constituents within the sentence as features. Our results show significant improvement over a majority class baseline as well as a more difficult baseline consisting of lexical n-grams.
A Temporal Description Logic Based Access Control Model for Expressing History Constrained Policies in Semantic Web
Authors: Fathieh Faghih, Morteza Amini, Rasool Jalili
Venue: Proceedings of the 2009 IEEE International Symposium on Policies for Distributed Systems and Networks (2009)

An access control model for Semantic Web should be compatible with the corresponding semantic model. The access control procedure(s) should also take the semantic relationships between the entities (specified as ontologies) into account. Considering the benefits of logic-based models and the description logic foundation of Semantic Web, in this paper, we propose an access control model based on a temporal variant of description logics (TL-ALCF). This logical schema enables us to express history constrained policies to enrich the policy-base with dynamic properties based on previous accesses.The specification of each component of the model as well as the approach to define history constrained policies along with some clarifying examples are presented. The access control procedure of the model is proposed over the inference services of TL-ALCF.
Fish inspection system using a parallel neural network chip and image knowledge builder application
Authors: Anne Menendez, Guy Paillet
Venue: Proceedings of the 19th national conference on Innovative applications of artificial intelligence - Volume 2 (2007)

A generic image learning system, CogniSight®, is being used for the inspection of fishes before filleting off-shore. More than thirty systems have been deployed on seven fishing vessels in Norway and Iceland over the past three years. Each CogniSight uses four neural network chips (a total of 312 neurons) based on a natively parallel hardwired architecture perfonning real time learning and non-linear classification (RBF). These systems are trained by the ship crew using Image Knowledge Builder, a "show and tell" interface for easy training and validation. Fishermen can reinforce the learning at anytime when needed. The use of CogniSight has reduced significantly the number of crewmembers on the boats (by up to six persons) and the time at sea has shortened by 15%. The prompt and strong return of the investment to the fishing fleet has increased significantly the market shares of Pisces Industries, the company integrating CogniSight systems to its filleting machines.
Automatic Chat Generation of Emotional Entertainment Characters Using News Information
Authors: Jun'Ichi Hoshino, Tetsuya Saito, Kenichi Hirota
Venue: Proceedings of the 8th International Conference on Entertainment Computing (2009)

Currently interactive entertainment characters have their conversation topics prepared beforehand by the creator. In this paper, we propose the automatic chat generation engine for emotional entertainment characters using real-time news information. The character emotionally reacts to the news contents based on their interest and feelings so that the users can have intimate feeling. The character also incrementally learns user's interest from their response.
Application of H-Fuzzy Evaluation Model in Traffic Congestion Degree of City Road-Network
Authors: Qi-liang Ren, Qi-yuan Peng
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

There is no one standard to evaluate traffic congestion degree of city road-network in the world, in this paper, degree of city road-network traffic congestion is divided into three classes: Jam ,congestion, crowd, fluency. The indexes to evaluate the degree of city road network traffic congestion are selected, and the hierarchy evaluation index system are built with analytic hierarchy process and hierarchy -fuzzy comprehensive evaluation model. In the end, the H-Fuzzy evaluation model was used to evaluate the traffic states of one typical city road network.
MMR-based feature selection for text categorization
Authors: Changki Lee, Gary Geunbae Lee
Venue: Proceedings of HLT-NAACL 2004: Short Papers on XX (2004)

We introduce a new method of feature selection for text categorization. Our MMR-based feature selection method strives to reduce redundancy between features while maintaining information gain in selecting appropriate features for text categorization. Empirical results show that MMR-based feature selection is more effective than Koller & Sahami's method, which is one of greedy feature selection methods, and conventional information gain which is commonly used in feature selection for text categorization. Moreover, MMR-based feature selection sometimes produces some improvements of conventional machine learning algorithms over SVM which is known to give the best classification accuracy.
Document Classification Algorithm Using Kernel LPP
Authors: Ziqiang Wang, Xu Qian
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 02 (2009)

With the explosive increase in document data on the Internet, classifying documents from document database has become one of the hottest research fields.To efficiently deal with this problem, an efficient document classification algorithm based on kernel locality preserving projection (Kernel LPP) is presented in this paper. Experimental results show that the proposed algorithm outperforms other related document classification algorithms.
Maximum likelihood estimation in vector long memory processes via EM algorithm
Authors: Jeffrey Pai, Nalini Ravishanker
Venue: Computational Statistics Data Analysis (2009)

We present an approach for exact maximum likelihood estimation of parameters from univariate and multivariate autoregressive fractionally integrated moving average models with Gaussian errors using the Expectation Maximization (EM) algorithm. The method takes advantage of the relation between the VARFIMA(0,d,0) process and the corresponding VARFIMA(p,d,q) process in the computation of the likelihood.
Depth first algorithms and inferencing for AFD mining
Authors: Jeremy T. Engle, Edward L. Robertson
Venue: Proceedings of the 2009 International Database Engineering & Applications Symposium (2009)

The task of searching a powerset lattice is part of many problem domains. In Approximate Functional Dependencies (AFDs) mining the algorithm used for searching lattices has been bottom-up breadth first search (BU-BFS). This paper introduces as part of the MoLS framework a method for managing and using inferred information about the status of rules in the lattice. BU-BFS however has limited ability to use inferred information. This paper instead explores the ability of depth first search (DFS) algorithms to use inferred information. The focus on algorithms is motivated by the idea that improved performance from an algorithm is more likely to persist as users make customizations or use different approximation measures. Algorithms are experimentally evaluated and performance is judged based on the portion of the search space for which the approximation measure has been calculated. This presents a machine independent evaluation where differences in performance can be directly attributed to the algorithm.
Recommending Multidimensional Queries
Authors: Arnaud Giacometti, Patrick Marcel, Elsa Negre
Venue: Proceedings of the 11th International Conference on Data Warehousing and Knowledge Discovery (2009)

Interactive analysis of datacube, in which a user navigates a cube by launching a sequence of queries is often tedious since the user may have no idea of what the forthcoming query should be in his current analysis. To better support this process we propose in this paper to apply a Collaborative Work approach that leverages former explorations of the cube to recommend OLAP queries. The system that we have developed adapts Approximate String Matching, a technique popular in Information Retrieval, to match the current analysis with the former explorations and help suggesting a query to the user. Our approach has been implemented with the open source Mondrian OLAP server to recommend MDX queries and we have carried out some preliminary experiments that show its efficiency for generating effective query recommendations.
Role Assignment, Non-communicative Multi-agent Coordination in Dynamic Environments Based on the Situation Calculus
Authors: Desheng Xu, Kejian Xia
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 01 (2009)

Coordination in multi-robot systems is a very active research field in Artificial Intelligence and Robotics, since through coordination one can achieve a more effective execution of the robots’ tasks. We achieve collaboration between agents through introducing roles into the situation calculus. Homogeneous agents can flexibly switch roles according to pre-defined triggers to be evaluated at run-time. A role in our framework defines the set of actions and the policy of an agent. Moreover, we demonstrate that, with common knowledge assumptions, an agent can predict the actions of the other agents, rendering communication unnecessary. Experimental results showing the effectiveness of our approach, the method has been successfully implemented in the domain of simulated robotic soccer based on the situation calculus.
Gesture improves coreference resolution
Authors: Jacob Eisenstein, Randall Davis
Venue: Proceedings of the Human Language Technology Conference of the NAACL, Companion Volume: Short Papers on XX (2006)

Coreference resolution, like many problems in natural language processing, has most often been explored using datasets of written text. While spontaneous spoken language poses well-known challenges, it also offers additional modalities that may help disambiguate some of the inherent disfluency. We explore features of hand gesture that are correlated with coreference. Combining these features with a traditional textual model yields a statistically significant improvement in overall performance.
Domain-independent construction of pattern database heuristics for cost-optimal planning
Authors: Patrik Haslum, Adi Botea, Malte Helmert, Blai Bonet, Sven Koenig
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 (2007)

Heuristic search is a leading approach to domain-independent planning. For cost-optimal planning, however, existing admissible heuristics are generally too weak to effectively guide the search. Pattern database heuristics (PDBs), which are based on abstractions of the search space, are currently one of the most promising approaches to developing better admissible heuristics. The informedness of PDB heuristics depends crucially on the selection of appropriate abstractions (patterns). Although PDBs have been applied to many search problems, including planning, there are not many insights into how to select good patterns, even manually. What constitutes a good pattern depends on the problem domain, making the task even more difficult for domain-independent planning, where the process needs to be completely automatic and generaL We present a novel way of constructing good patterns automatically from the specification of planning problem instances. We demonstrate that this allows a domain-independent planner to solve planning problems optimally in some very challenging domains, including a STRIPS formulation of the Sokoban puzzle.
Dominance and equivalence for sensor-based agents
Authors: Jason M. O'Kane, Steven M. LaValle
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 (2007)

This paper describes recent results from the robotics community that develop a theory, similar in spirit to the theory of computation, for analyzing sensor-based agent systems. The central element to this work is a notion of dominance of one such system over another. This relation is formally based on the agents' progression through a derived information space, but may informally be understood as describing one agent's ability to "simulate" another. We present some basic properties of this dominance relation and demonstrate its usefulness by applying it to a basic problem in robotics. We argue that this work is of interest to a broad audience of artificial intelligence researchers for two main reasons. First, it calls attention to the possibility of studying belief spaces in way that generalizes both probabilistic and nondeterministic uncertainty models. Second, it provides a means for evaluating the information that an agent is able to acquire (via its sensors and via conformant actions), independent of any optimality criterion and of the task to be completed.
Food Wholesales Prediction: What Is Your Baseline?
Authors: Jorn Bakker, Mykola Pechenizkiy
Venue: Proceedings of the 18th International Symposium on Foundations of Intelligent Systems (2009)

Sales prediction is an important problem for different companies involved in manufacturing, logistics, marketing, wholesaling and retailing. Different approaches have been suggested for food sales forecasting. Several researchers, including the authors of this paper, reported on the advantage of one type of technique over the others for a particular set of products. In this paper we demonstrate that besides an already recognized challenge of building accurate predictive models, the evaluation procedures themselves should be considered more carefully. We give illustrative examples to show that e.g. popular MAE and MSE estimates can be intuitive with one type of product and rather misleading with the others. Furthermore, averaging errors across differently behaving products can be also counter intuitive. We introduce new ways to evaluate the performance of wholesales prediction and discuss their biases with respect to different error types.
The Adaptability Study of Bursa Model
Authors: Yu Caixia, Cui Gaosong, Zheng Yidong, Chen Huirong, Nie Qun
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 03 (2009)

In Burs, compared to 3-parameter model, 7-parameter is more tight, but it has the problems that the parameters in part are instability and hard to ensure the transformation accuracy in the area outside control points. In the paper, the accuracy, stability and the relation with the control point range of 3-parameter and 7-parameter models are verified by simulation test, and then the method of choosing model is obtained.
Engineering Optics, 3rd edition
Authors: Keigo Iizuka
Venue:  (2009)

Engineering Optics is a book for students who want to apply their knowledge of optics to engineering problems, as well as for engineering students who want to acquire the basic principles of optics. It covers such important topics as optical signal processing, holography, tomography, holographic radars, fiber optical communication, electro- and acousto-optic devices, and integrated optics (including optical bistability). As a basis for understanding these topics, the first few chapters give easy-to-follow explanations of diffraction theory, Fourier transforms, and geometrical optics. Practical examples, such as the video disk, the Fresnel zone plate, and many more, appear throughout the text, together with numerous solved exercises. There is an entirely new section in this updated edition on 3-D imaging. 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