ppxscal/embedding_network huggingface dataset:
Improving the Behavior of Creatures by Time-Shuffling
Authors: Patrick Ediger, Rolf Hoffmann
Venue: Proceedings of the 8th international conference on Cellular Automata for Reseach and Industry (2008)

The goal is to optimize the behavior of moving creatures by using "time-shuffling" techniques. The "creatures' exploration problem" is used as an example for a multi-agent problem modeled by cellular automata. The task of the creatures is to visit all empty cells in an environment with a minimum number of steps. The behavior of a creature is modeled by an automaton taking care of the collisions. Time-shuffling means that two behaviors (algorithms X and Y) are sequentially alternated with a certain time period. Ten different "uniform" (non-time-shuffled) algorithms with good performance from former investigations were used. We defined three time-shuffling modes differing in the way how the algorithms are interchanged. New metrics are used for such multi-agent systems, especially the success rate (number of successful explored environments) and the mean normalized work (cost). Time-shuffled systems with a time period of around 100 have resulted in much better success rates and lower cost compared to the uniform systems.
Research-pyramid based search tools for online digital libraries
Authors: Gultekin Ozsoyoglu
Venue:  (2008)

In any online literature digital library, findability precedes usability: users cannot use what they cannot find. Four research directions that support better findability in digital libraries are (a) Accurate scoring functions to assign importance/prestige scores to publications, (b) Accurate similarity measures for publications to locate publications similar to a given publication, (c) Accurate ranking measures to order search results based on their importance and relevance to users&rsquo; interests, and (d) Helping users develop search keywords that lead to successful searches.The contributions of this thesis are as follows. (1) Propose and comparatively evaluate score functions for publications, authors, and publication venues, as well as similarity measures for publications, towards research direction items a and b. (2) Validate a new model for the evolution of research and citation behavior, namely, the Research Pyramid Model. Then, propose and evaluate two algorithms for identifying research pyramid structures in publication citation graphs, and for research-pyramid-based publication score generation, towards research direction item a. (3) Propose and evaluate a citation-based publication popularity growth and decay model, towards research direction item c. (4) Using the Research Pyramid Model and the identified research pyramid structures, develop two literature digital library searching and ranking tools: (a) A Research-Pyramid-based ranking tool that assigns accurate scores for publications, and (b) A scalable content-driven Search-Keyword Suggester that helps users to put together query search terms effectively.
Distributed Relay Protocol for Probabilistic Information-Theoretic Security in a Randomly-Compromised Network
Authors: Travis R. Beals, Barry C. Sanders
Venue: Proceedings of the 3rd international conference on Information Theoretic Security (2008)

We introduce a simple, practical approach with probabilistic information-theoretic security to mitigate one of quantum key distribution's major limitations: the short maximum transmission distance (~200 km) possible with present day technology. Our scheme uses classical secret sharing techniques to allow secure transmission over long distances through a network containing randomly-distributed compromised nodes. The protocol provides arbitrarily high confidence in the security of the protocol, and modest scaling of resource costs with improvement of the security parameter. Although some types of failure are undetectable, users can take preemptive measures to make the probability of such failures arbitrarily small.
Bookmark Category Web Page Classification Using Four Indexing and Clustering Approaches
Authors: Chris Staff
Venue: Proceedings of the 5th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems (2008)

Web browser bookmark files store records of web pages that the user would like to revisit. We use four methods to index and automatically classify documents referred to in 80 bookmark files, based on document title-only and full-text indexing and two clustering approaches. We evaluate the approaches by selecting a bookmark entry to classify from a bookmark file, re-creating a snapshot of the bookmark file to contain only entries created before the selected bookmark entry. The baseline algorithm is 39% accurate at rank 1 when the target category contains 7 entries. By fusing the recommendations of the 4 approaches, we reach 78.7% accuracy on average, recommending at most 3 categories.
A Theory of Similarity Functions for Learning and Clustering
Authors: Avrim Blum
Venue: Proceedings of the 18th international conference on Algorithmic Learning Theory (2007)

Kernel methods have proven to be powerful tools in machine learning. They perform well in many applications, and there is also a well-developed theory of sufficient conditions for a kernel to be useful for a given learning problem. However, while a kernel can be thought of as just a pairwise similarity function that satisfies additional mathematical properties, this theory requires viewing kernels as implicit (and often difficult to characterize) maps into high-dimensional spaces. In this talk I will describe work on developing a theory that applies to more general similarity functions (not just legal kernels) and furthermore describes the usefulness of a given similarity function in terms of more intuitive, direct properties, without need to refer to any implicit spaces.An interesting feature of the proposed framework is that it can also be applied to learning from purely unlabeled data, i.e., clustering. In particular, one can ask how much stronger the properties of a similarity function should be (in terms of its relation to the unknown desired clustering) so that it can be used to cluster well: to learn well without any label information at all. We find that if we are willing to relax the objective a bit (for example, allow the algorithm to produce a hierarchical clustering that we will call successful if some pruning is close to the correct answer), then this question leads to a number of interesting graph-theoretic and game-theoretic properties that are sufficient to cluster well. This work can be viewed as an approach to defining a PAC model for clustering.This talk is based on work joint with Maria-Florina Balcan and Santosh Vempala.
Machine Learning in Ecosystem Informatics
Authors: Thomas G. Dietterich
Venue: Proceedings of the 18th international conference on Algorithmic Learning Theory (2007)

The emerging field of Ecosystem Informatics applies methods from computer science and mathematics to address fundamental and applied problems in the ecosystem sciences. The ecosystem sciences are in the midst of a revolution driven by a combination of emerging technologies for improved sensing and the critical need for better science to help manage global climate change. This paper describes several initiatives at Oregon State University in ecosystem informatics.
The Descriptive Complexity of Parity Games
Authors: Anuj Dawar, Erich Grädel
Venue: Proceedings of the 22nd international workshop on Computer Science Logic (2008)

We study the logical definablity of the winning regions of parity games. For games with a bounded number of priorities, it is well-known that the winning regions are definable in the modal μ-calculus. Here we investigate the case of an unbounded number of priorities, both for finite game graphs and for arbitrary ones. In the general case, winning regions are definable in guarded second-order logic (GSO), but not in least-fixed point logic (LFP). On finite game graphs, winning regions are LFP-definable if, and only if, they are computable in polynomial time, and this result extends to any class of finite games that is closed under taking bisimulation quotients.
WHFPMiner: Efficient Mining of Weighted Highly-Correlated Frequent Patterns Based on Weighted FP-Tree Approach
Authors: Runian Geng, Xiangjun Dong, Jing Zhao, Wenbo Xu
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks, Part II (2008)

Most algorithms for frequent pattern mining use a support-based pruning strategy to prune a combinatorial search space. However, they are not effective for finding correlated patterns with similar levels of support. In additional, traditional patterns mining algorithms rarely consider weighted pattern mining. In this paper, we present a new algorithm, WHFPMiner (Weighted Highly-correlated Frequent Patterns Miner) in which a new objective measure, called weighted h-confidence, is developed to mine weighted highly-correlated frequent patterns with similar levels of weighted support. Adopting an improved weighted FP-tree structure, this algorithm exploits both cross-weighted support and anti-monotone properties of the weighted h-confidence measure for the efficient discovery of weighted hyperclique patterns. A comprehensive performance study shows that WHFPMiner is efficient and fast for finding weighted highly-correlated frequent patterns. Moreover, it generates fewer but more valuable patterns with the high correlation.
A Sequential Hybrid Forecasting System for Demand Prediction
Authors: Luis Aburto, Richard Weber
Venue: Proceedings of the 5th international conference on Machine Learning and Data Mining in Pattern Recognition (2007)

Demand prediction plays a crucial role in advanced systems for supply chain management. Having a reliable estimation for a product's future demand is the basis for the respective systems. Various forecasting techniques have been developed, each one with its particular advantages and disadvantages compared to other approaches. This motivated the development of hybrid systems combining different techniques and their respective advantages. Based on a comparison of ARIMA models and neural networks we propose to combine these approaches to a sequential hybrid forecasting system. In our system the output from an ARIMA-type model is used as input for a neural network which tries to reproduce the original time series. The applications on time series representing daily product sales in a supermarket underline the excellent performance of the proposed system.
Predictive Modeling of Large-Scale Sequential Curves Based on Clustering
Authors: Wen Long, Huiwen Wang
Venue: Proceedings of the 8th international conference on Computational Science, Part II (2008)

Traditional approach to predict large-scale sequential curves is to build model separately according to every curve, which causes heavy and complicated modeling workload inevitably. A new method is proposed in this paper to solve this problem. By reducing model types of curves, clustering curves and modeling by clusters, the new method simplifies modeling work to a large extent and reserves original information as possible in the meantime. This paper specifies the theory and algorithm, and applies it to predict GDP curves of multi-region, which confirms practicability and validity of the presented approach.
Bi-criteria Pipeline Mappings for Parallel Image Processing
Authors: Anne Benoit, Harald Kosch, Veronika Rehn-Sonigo, Yves Robert
Venue: Proceedings of the 8th international conference on Computational Science, Part I (2008)

Mapping workflow applications onto parallel platforms is a challenging problem, even for simple application patterns such as pipeline graphs. Several antagonistic criteria should be optimized, such as throughput/period and latency (or a combination). Typical applications include digital image processing, where images are processed in steady-state mode. In this paper, we study the bi-criteria mapping (minimizing period and latency) of the JPEG encoding on a cluster of workstations. We present an integer linear programming formulation for this NP-hard problem, and we present an in-depth performance evaluation of several polynomial heuristics.
Elongation method for linear scaling SCF calculations of polymers
Authors: Jacek Korchowiec, Feng Long Gu, Yuriko Aoki
Venue: Journal of Computational Methods in Sciences and Engineering (2006)

The elongation method utilizes the locality or nearsightedness approximation in the electronic structure calculations. In analogy to polymerization/copolymerization mechanism, the elongation method extends the polymer chain by stepwise adding a monomer unit to a starting oligomer. In the same time it preserves as much chemical information as possible by freezing the shape of selected localized molecular orbitals (LMOs). As a consequence the dimension of variational space is effectively reduced and is almost constant along the whole elongation process. Besides diminishing the variational space, LMO basis can also reduce the physical dimension of the Fock matrix in a so called cutoff procedure. In such a way, the computation of large number of two-electron integrals is avoided in the SCF process. In this paper we describe the elongation method implemented with the cutoff technique at the Hartree-Fock level of theory. As an illustrative example, we have chosen C5 conformer of polyglycine to demonstrate that the elongation method is a powerful tool in electronic structure calculations.
Optimization for MASK Scheme in Privacy Preserving Data Mining for Association Rules
Authors: Piotr Andruszkiewicz
Venue: Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms (2007)

As a result of advances in technology, large amounts of data can be collected and stored automatically. Significant development of the Internet and easier access to it have contributed to collecting large amounts of information about users' characteristics. Along with these changes, concerns about privacy of data have emerged. Several methods of preserving privacy for association rules mining have been proposed in literature: MASK scheme and its optimizations. This paper provides new solutions concerning efficiency for this scheme and considers different methods of distorting data using randomization techniques. Effectiveness of these solutions has been tested and presented in this paper. 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
Duals of Simple and Subdirectly Irreducible Distributive Modal Algebras
Authors: Be Birchall
Venue: Logic, Language, and Computation: 6th International Tbilisi Symposium on Logic, Language, and Computation,TbiLLC 2005 Batumi, Georgia, September 12-16, 2005. Revised Selected Papers (2007)

Simplicity and subdirect irreducibility of complex algebra duals of Kripke frames can be readily characterized in terms of roots of the corresponding Kripke frames.Here these characterizations are generalized to the case of distributive modal algebras $(A, \vee , \wedge , 0 , 1, \Diamond , \Box , \rhd , \lhd)$, and their duals. Such an algebra consists of a distributive bounded lattice (A, ¿ , ¿ , 0, 1) together with a join preserving operator $\Diamond$, a meet preserving operator $\Box$, a join reversing operator ¿, and a meet reversing operator ¿. 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
Genetic Based Distribution Service Restoration with Minimum Average Energy Not Supplied
Authors: Thitipong Charuwat, Thanatchai Kulworawanichpong
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I (2007)

This paper presents optimal planning of tie-switch operation in an electric power distribution system under an emergency feed condition, i.e. operation during a post-fault condition. A heuristic fault isolation algorithm and a genetic-based service restoration algorithm are proposed and compared. With the proposed restoration algorithm, high reliable service of electric distribution systems is expected. To ensure a small number of customer interruption, average energy not supplied (AENS) is used as the objective function to be minimized. 25-node and 118-node distribution test feeders were employed for test. Satisfactory results show that the genetic approach is appropriate to a kind of tie-switch operation planning in order to minimize effects of a permanent fault on customer service interruption.
A Distributed Computing Environment for Embedded Control Systems with Time-Triggered and Event-Triggered Processing
Authors: Yuichi Itami, Tasuku Ishigooka, Takanori Yokoyama
Venue: Proceedings of the 2008 14th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (2008)

The paper presents a distributed computing environment for embedded control systems with time-triggered and event-triggered distributed processing. We have already presented a time-triggered distributed object model and a time-triggered distributed computing environment for embedded control systems. However, there are many embedded control systems with time-triggered and event-triggered processing. In this paper, we present two kinds of event-triggered distributed object models, a pure event-triggered distributed object model and a data-triggered distributed object model, in addition to the time-triggered distributed object model. We also present a distributed object computing environment based on a time-division scheduling for the mixed architecture with time-triggered and event-triggered distributed processing. The time division scheduling divides an execution cycle into a time-triggered processing segment and a non-time-triggered processing segment. The time-triggered distributed processing is executed in the former segment, and the event-triggered distributed processing is executed in the latter segment. The distributed object computing environment consists of a real-time operating system with the time division scheduling and distributed computing middleware to support the three kinds of distributed object models. We provide a development environment that generates stubs and configuration data to build distributed control systems.
Time-Shrinking and the Design of Tactons
Authors: Jan B. Erp, Michiel M. Spapé
Venue: Proceedings of the 6th international conference on Haptics: Perception, Devices and Scenarios (2008)

When three pulses mark two open intervals, the length of the second interval is underestimated when it is longer than the first. This phenomenon is called time-shrinking and found in audition and vision. In the present experiment, we investigated time-shrinking for the tactile modality. Eighteen observers adjusted the length of a comparison interval to match a test interval that was presented alone or with a preceding interval. In the range of test intervals (260 --- 580 ms), we found a time-shrinking effect of 30 ms that was not dependent on the difference between the test interval and the preceding interval. This result is relevant for the design of tactons that use rhythm or the interval length between pulses to code information.
An exploratory mapping strategy for web-driven magazines
Authors: Fabio Giannetti
Venue: Proceeding of the eighth ACM symposium on Document engineering (2008)

"There will always (I hope) be print books, but just as the advent of photography changed the role of painting or film changed the role of theater in our culture, electronic publishing is changing the world of print media. To look for a one-to-one transposition to the new medium is to miss the future until it has passed you by." - Tim O'Reilly [1]. It is not hard to envisage that publishers will leverage subscribers' information, interest groups' shared knowledge and others sources to enhance their publications. While this enhances the value of the publication through more accurate and personalized content, it also brings a new set of challenges to the publisher. Content is now driven by web and in a truly automated system no designer "re-touch" intervention can be envisaged. The paper introduces an exploratory mapping strategy to allocate web driven content in a highly graphical publication like a traditional magazine. Two major aspects of the mapping are covered, which enables different level of flexibility and addresses different content flowing strategies. The last contribution is an evaluation of existing standards, which potentially can leverage this work to incorporate more flexible mapping, and subsequently, composition capabilities.
Distributed Timed Automata with Independently Evolving Clocks
Authors: S. Akshay, Benedikt Bollig, Paul Gastin, Madhavan Mukund, K. Narayan Kumar
Venue: Proceedings of the 19th international conference on Concurrency Theory (2008)

We propose a model of distributed timed systems where each component is a timed automaton with a set of local clocks that evolve at a rate independent of the clocks of the other components. A clock can be read by any component in the system, but it can only be reset by the automaton it belongs to.There are two natural semantics for such systems. The universal semantics captures behaviors that hold under any choice of clock rates for the individual components. This is a natural choice when checking that a system always satisfies a positive specification. However, to check if a system avoids a negative specification, it is better to use the existential semantics--the set of behaviors that the system can possibly exhibit under some choice of clock rates.We show that the existential semantics always describes a regular set of behaviors. However, in the case of universal semantics, checking emptiness turns out to be undecidable. As an alternative to the universal semantics, we propose a reactive semantics that allows us to check positive specifications and yet describes a regular set of behaviors.
Does Body Movement Engage You More in Digital Game Play? and Why?
Authors: Nadia Bianchi-Berthouze, Whan Woong Kim, Darshak Patel
Venue: Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction (2007)

In past years, computer game designers have tried to increase player engagement by improving the believability of characters and environment. Today, the focus is shifting toward improving the game controller. This study seeks to understand engagement on the basis of the body movements of the player. Initial results from two case-studies suggest that an increase in body movement imposed, or allowed, by the game controller results in an increase in the player's engagement level. Furthermore, they lead us to hypothesize that an increased involvement of the body can afford the player a stronger affective experience. We propose that the contribution of full-body experience is three-fold: (a) it facilitates the feeling of presence in the digital environment (fantasy); (b) it enables the affective aspects of human-human interaction (communication); and (c) it unleashes the regulatory properties of emotion (affect).