ppxscal/embedding_network huggingface dataset:
Applying fixed-priority preemptive scheduling with preemption threshold to asynchronous event handling in the RTSJ
Authors: MinSeong Kim, Andy Wellings
Venue: Proceedings of the 7th International Workshop on Java Technologies for Real-Time and Embedded Systems (2009)

The primary goal for asynchronous event handlers in the Real-Time Specification for Java (RTSJ) is to have a lightweight concurrency mechanism. The emphasis here is on 'lightweightness' which should be achieved by having fewer servers to execute more handlers. Some implementation will, however, simply map a handler to a real-time thread and this results in undermining the original motivations and introduces performance penalties. Furthermore it is generally unclear how to map handlers to real-time threads efficiently with respect to the lightweightness requirement. In this paper we therefore first define the worst case scenario that demands the maximum number of real-time threads for blocking and non-blocking handlers. Based on the worst case scenarios, it is also proved that the number of real-time threads required to execute a given number of non-blocking handlers depends on the number of priority levels, not on the number of handlers. It is also shown that each blocking handler is required to have its own real-time thread to prevent unbounded priority inversion. Based on these results we also propose to adapt the notion of preemption threshold to minimise the number of priority levels in the system, which enables AEH to feasibly schedule a given handler set with the least number of real-time threads. We have extended the non-blocking AEH implementation [8] to support the fixed-priority scheduling with preemption threshold on an existing RTSJ implementation, jRate, to show that the number of real-time threads can be further decreased while feasibly scheduling a set of non-blocking handlers, regardless of the number of them in the system.
Knowledge extraction and recurrent neural networks: an analysis of an Elman network trained on a natural language learning task
Authors: Ingo Schellhammer, Joachim Diederich, Michael Towsey, Claudia Brugman
Venue: Proceedings of the Joint Conferences on New Methods in Language Processing and Computational Natural Language Learning (1998)

We present results of experiments with Elman recurrent neural networks (Elman, 1990) trained on a natural language processing task. The task was to learn sequences of word categories in a text derived from a primary school reader. The grammar induced by the network was made explicit by cluster analysis which revealed both the representations formed during learning and enabled the construction of state-transition diagrams representing the grammar. A network initialised with weights based on a prior knowledge of the text's statistics, learned slightly faster than the original network.
Distributed Knowledge Acquisition Based on Semantic Grid
Authors: Huimin Wang, Guihua Nie, Kui Fu
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 01 (2009)

Today, many public organizations, industries, and scientific labs produce and manage large amounts of complex data and information that are distributed and semantically heterogeneous. Knowledge acquisition from distributed data resources to support decision making is receiving an increasing attention. The paper proposes a distributed knowledge acquisition architecture and puts forward any new solve algorithms for knowledge acquisition from large-scale distributed and heterogeneous data resources. Semantic web technology is used to explicitly define data semantics. By the semantic mapping between data resources and ontology, the query and acquisition of user-demanded knowledge can be realized by distributed data mining and semantic reasoning.
A Recursive Descent Algorithm for Finding the Optimal Minimax Piecewise Linear Approximation of Convex Functions
Authors: Alyson Imamoto, Benjamim Tang
Venue: Proceedings of the Advances in Electrical and Electronics Engineering - IAENG Special Edition of the World Congress on Engineering and Computer Science 2008 (2008)

The optimal minimax solution to the N segment piecewise linear approximation of arbitrary convex differentiable functions over a finite range is described. The optimal solution is uniquely described by the derivatives at N distinct points. The optimality of the solution is proven and a recursive descent algorithm is proposed. The efficacy of the algorithm and optimality of the solution are demonstrated in example solutions for commonly used functions.
Using sound to understand software architecture
Authors: Lewis I. Berman, Keith B. Gallagher
Venue: Proceedings of the 27th ACM international conference on Design of communication (2009)

Use of non-speech sound can facilitate the understanding of a software program. Non-speech sound has been shown to be useful in dynamic program comprehension, that is, understanding the dynamic behavior of a program. We have developed a sonification scheme to describe static software entities in Java programs, and we show that it is useful in static program comprehension, notably concerning low-level architecture. The scheme is implemented via a tool in which an Eclipse IDE is integrated with a CSound synthesis engine. The tool is intended for use by sighted software developers in a static browsing/editing environment. A validation study of the concept has been performed via one-on-one sessions with experienced software developers. Preliminary results indicate that software developers are easily able to learn and recognize sonified characteristics of software entities and their relationships by listening to sequences of mapped sound constructs. Identification of specific entities is more problematic. Developers have indicated that they would find the tool useful during both exploration and more focused programming activities. Their additional perceptions have been collected using grounded qualitative means.
New Image Denoising Method Based Wavelet and Curvelet Transform
Authors: Hong-qiao Li, Sheng-qian Wang, Cheng-zhi Deng
Venue: Proceedings of the 2009 WASE International Conference on Information Engineering - Volume 01 (2009)

Wavelet multi-resolution analysis is widely used and achieves good results in image denoising fields. Wavelet transform has unique advantages in dealing with singular point, but has some disadvantages in dealing with the borders and the line features of the image. But curvelet transform has the finest approximation of the singular curve in the image. In this paper, we combine the wavelet transform and curvelet transform to deal with the noisy image. The results show that the proposed method is better than only using wavelet transform or curvelet transform to deal with noisy image, that is to say this method can get better visual effects and higher PSNR.
Boosting Active Learning to Optimality: A Tractable Monte-Carlo, Billiard-Based Algorithm
Authors: Philippe Rolet, Michèle Sebag, Olivier Teytaud
Venue: Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II (2009)

This paper focuses on Active Learning with a limited number of queries; in application domains such as Numerical Engineering, the size of the training set might be limited to a few dozen or hundred examples due to computational constraints. Active Learning under bounded resources is formalized as a finite horizon Reinforcement Learning problem, where the sampling strategy aims at minimizing the expectation of the generalization error. A tractable approximation of the optimal (intractable) policy is presented, the Bandit-based Active Learner (BAAL) algorithm. Viewing Active Learning as a single-player game, BAAL combines UCT, the tree structured multi-armed bandit algorithm proposed by Kocsis and Szepesvári (2006), and billiard algorithms. A proof of principle of the approach demonstrates its good empirical convergence toward an optimal policy and its ability to incorporate prior AL criteria. Its hybridization with the Query-by-Committee approach is found to improve on both stand-alone BAAL and stand-alone QbC.
Shape Detection from Line Drawings by Hierarchical Matching
Authors: Rujie Liu, Yuehong Wang, Takayuki Baba, Daiki Masumoto
Venue: Proceedings of the 13th International Conference on Computer Analysis of Images and Patterns (2009)

An object detection method from line drawing images is presented. In this method, the content of line drawing images are hierarchically represented, where a local neighborhood structure is formed for each primitive by grouping its nearest neighbors. The detection process is a hypothesis verification scheme. Firstly, the top k most similar local structures in the object drawing are obtained for each local structure of the model, and the corresponding transformation parameters are estimated. By treating each estimation result as a point in the parameter space, a dense region around the ground truth is then formed provided that there exists a model in the object drawing. At last, the mode detection method is used to find this dense region, and the significant modes are accepted as the occurrence of object instances. 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
Intelligent Tutoring Games with Agent Modeling
Authors: D. W. Krevelen
Venue: Proceedings of the 9th International Conference on Intelligent Virtual Agents (2009)

Business strategy educators increasingly rely on simulation games to provide students with experience in strategic decision making. Business games however often limit interaction to operational decision making so discovering the value of alternative strategies in different situations may take a lot of time. Furthermore, to ensure students can grasp the system complexity at this operational level, game scenarios remain relatively simple. We hypothesize that business game effectiveness for strategy education can increase if players instead create teams of delegate agents to appropriately handle operations in more complex settings. To test this we are working on an intelligent learning environment that will help players create successful teams of agents to handle operations. 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
A solution method for a car fleet management problem with maintenance constraints
Authors: Alain Hertz, David Schindl, Nicolas Zufferey
Venue: Journal of Heuristics (2009)

The problem retained for the ROADEF'99 international challenge was an inventory management problem for a car rental company. It consists in managing a given fleet of cars in order to satisfy requests from customers asking for some type of cars for a given time period. When requests exceed the stock of available cars, the company can either offer better cars than those requested, subcontract some requests to other providers, or buy new cars to enlarge the available stock. Moreover, the cars have to go through a maintenance process at a regular basis, and there is a limited number of workers that are available to perform these maintenances.The problem of satisfying all customer requests at minimum cost is known to be NP-hard. We propose a solution technique that combines two tabu search procedures with algorithms for the shortest path, the graph coloring and the maximum weighted independent set problems. Tests on benchmark instances used for the ROADEF'99 challenge give evidence that the proposed algorithm outperforms all other existing methods (thirteen competitors took part to this contest).
Non-location-based Mobile Sensor Relocation in a Hybrid Static-Mobile Wireless Sensor Network
Authors: Fang-Jing Wu, Hsiu-Chi Hsu, Yu-Chee Tseng, Chi-Fu Huang
Venue: Proceedings of the 2009 Third International Conference on Sensor Technologies and Applications (2009)

An inherent concern for a wireless sensor network (WSN) is the unbalanced energy consumption problem, where sensors closer to the sink are more likely to exhaust their energy faster than other nodes. To mitigate this problem, this paper considers including some resource-rich mobile nodes, called mobile data-pumps, to conduct data relaying from static sensors to the sink. The network thus becomes a two-tier network, with the original static sensors at the low tier and data-pumps at both low and high tiers. We propose a novel distributed navigation protocol that does not rely on any location information of sensor nodes to relocate data-pumps to meet both goals of connectivity and load balance. The main idea is a concept called virtual Voronoi cells, which can help data-pumps to locally balance their loads using the underlaying low-tier topology and thus significantly balance energy consumption of sensors. Simulation results are presented to verify the effectiveness of our result.
A theory of architecture for spatial abstraction
Authors: Juyang Weng
Venue: Proceedings of the 2009 IEEE 8th International Conference on Development and Learning (2009)

A great mystery is how the brain abstracts during the process of development. It is also unclear how motor actions alter cortical representation. The architecture theory introduced here indicates that for each cortical area, the bottom-up space and top-down space are two sources of its representation — bridge representation which embeds manifolds of both spaces into a single space. A bridge representation has the following properties (a) responses from developed neurons are relatively less sensitive to irrelevant sensory information (i.e., invariants) but are relatively more sensitive to relevant sensory information for classification (i.e., discriminants), (b) neurons form topographic cortical areas according to abstract classes. Both properties transform meaningless (iconic, pixel like) raw sensory inputs into an internal representation with abstract meanings. The most abstract area can be considered as frontal cortex (or motor area if each firing pattern of the motor represents a unique abstract class). Such a cortical representation system is neither a purely symbolic system nor a monolithic meaning system, but is iconic-abstract two-way: bottom-up attention, top-down attention and recognition are all tightly integrated and highly distributed throughout the developmental network.
Compressing configuration data for memory limited devices
Authors: Esben Rune Hansen, Peter Tiedemann
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 1 (2007)

The paper introduces a new type of compression for decision diagram data structures, such as BDDs, MDDs and AOMDDs. The compression takes advantage of repeated substructures within the decision diagram in order to lessen redundancy beyond what is possible using simple subfunction sharing. The resulting compressed data structure allows traversal of the original decision diagram with no significant overhead. Specifically it allows the efficient computation of valid domains, that is, the assignments for each encoded variable that can participate in a solution, which is critical when the decision diagram is used to support an interactive configurator. We relate these results to applications for interactively configurable memory limited devices and give empirical results on the amount of saved space for a wide variety of instances.
Express Virtual Channels with Capacitively Driven Global Links
Authors: Tushar Krishna, Amit Kumar, Li-Shiuan Peh, Jacob Postman, Patrick Chiang, Mattan Erez
Venue: IEEE Micro (2009)

Networks on chip must deliver high bandwidth at low latencies while keeping within a tight power envelope. Using express virtual channels for flow control improves energy-delay throughput by letting packets bypass intermediate routers, but EVCs have key limitations. Nochi (NoC with hybrid interconnect) overcomes these limitations by transporting data payloads and control information on separate planes, optimized for bandwidth and latency respectively.
Delay-efficient bus encoding techniques
Authors: N. Satyanarayana, A. Vinaya Babu, Madhu Mutyam
Venue: Microprocessors Microsystems (2009)

On-chip buses in deep-submicron designs have large propagation delay due to dominant coupling capacitance. As delay impacts system performance, several techniques have been proposed in the literature to minimize it. A common point in most of the existing techniques is to consider uniformly distributed random data, but propagation delay is data dependent and data is application dependent. Different applications may have different data behaviors. The existing techniques which consider uniformly distributed random data may not exploit the exact data behavior of an application and hence can give inferior performance results. By exploiting similarity in the data transmitted on on-chip buses, we propose three delay minimization techniques, namely, data packing (DPack), data permutation (DPerm), and data replication with shielding and two-phase transmission (RESTP). We show that for a 5-mm 32-bit on-chip bus in 90nm CMOS technology, the DPack, DPerm, and RESTP techniques achieve more than 25%, 32%, and 51% delay savings, respectively, in both address and data buses. For a 32-bit bus, the DPack, DPerm, and RESTP techniques require 38, 34, and 48 wires, respectively.
Fast Shape-Simplifying Image Abstraction Using Graphics Hardware
Authors: Hanli Zhao, Xiaogang Jin, Jianbing Shen, Li Shen, Ruifang Pan
Venue: Proceedings of the 4th International Conference on E-Learning and Games: Learning by Playing. Game-based Education System Design and Development (2009)

This paper presents a new GPU-based method for creating abstracted representations of photographs. Based on the constrained mean curvature flow and the Shock filter, our approach simplifies both shapes and colors simultaneously while preserving and conveying the directionality of important features and shape boundaries. The level of abstraction can be intuitively controlled by iteratively and incrementally applying the algorithm. Note that the whole pipeline design is highly parallel, enabling a GPU-based implementation. Our GPU-based method outperforms the CPU-based one with two magnitudes of speedup. Several experimental examples are shown to demonstrate both the effectiveness and efficiency of the proposed method.
Knowledge forgetting: Properties and applications
Authors: Yan Zhang, Yi Zhou
Venue: Artificial Intelligence (2009)

In this paper we study a formal notion of knowledge forgetting in S5 modal logic. We propose four postulates and prove that these postulates precisely characterize both semantic and logical properties of knowledge forgetting. We then investigate possible applications of knowledge forgetting in various epistemic reasoning scenarios. In particular, we show that different forms of knowledge updates may be represented via knowledge forgetting. We also demonstrate how knowledge forgetting can be used in formalizing and reasoning about knowledge games with bounded memory.
Probabilistic Coordination Language for Component Dynamic Composition
Authors: Dehui Du, Ling Yin
Venue: Proceedings of the 2009 Third IEEE International Symposium on Theoretical Aspects of Software Engineering (2009)

Coordination model facilitates the composition of components by separating the coordination aspects of an application from its computation aspects. In this paper we present a probabilistic coordination language based on the Linda model to describe the dynamic composition of components. In the language, sequence composition, parallel composition, conditional choice and probabilistic choice are defined. Operational semantics of the language is given. Finally, we demonstrate the language with an example.
A Novel Query Preprocessing Technique for Efficient Access to XML-Relational Databases
Authors: Pei-Lun Suei, Jun Wu, Yung-Feng Lu, Der-Nien Lee, Shih-Chun Chou, Chuo-Yen Lin
Venue: Proceedings of the 2009 First International Workshop on Database Technology and Applications (2009)

In recent years, many researchers and vendors have proposed their XML storage approaches based on relational databases (RDB), which are called XML-relational databases (XRDB). To manipulate XML data in XRDB, many excellent model-mapping schemas were proposed to provide schema definitions to translate various XML documents with different structures into relational tables. Such an approach can support any sophisticated applications and well-formed XML documents. When XML data stored in an XRDB, the user query must be translated into the corresponding SQL commands, then executed in the relational database. However, most model-mapping-schema-based approaches have a potential performance problem for retrieving XML data from an XRDB, because a large number of join operations are needed. In this paper, a novel query preprocessing technique will be proposed to reduce the number of join operations from the corresponding SQL commands. The rationale behind our approach is to replace join operations by predefined constant-mapping selection operations. By reducing the number of join operations, the performance of query processing can be greatly improved. The capability of our proposed approach was verified by experiments, for which we have some encouraging results.
Peculiarities of equilibria in the forbidden-situation games
Authors: V. V. Tokarev
Venue: Automation and Remote Control (2009)

Continued was a previous study of the peculiarities of the forbidden-situation games that analyzed the guaranteed results for various sequences of the participants' actions. Consideration now was given to the deformations of the Nash and Pareto equilibria by the mutual actions of the game participants on the set of permissible controls. The general constructions are illustrated by the analytical solutions for the Cournot model of competitive interaction of two manufacturing companies complemented by a constraint on the total raw-material resource.
Caller Interaction Classification: A Comparison of Real and Binary Coded GA-MLP Techniques
Authors: Pretesh B. Patel, Tshilidzi Marwala
Venue: Advances in Neuro-Information Processing: 15th International Conference, ICONIP 2008, Auckland, New Zealand, November 25-28, 2008, Revised Selected Papers, Part II (2009)

This paper employs pattern classification methods for assisting contact centers in determining caller interaction at a 'Say account' field within an Interactive Voice Response application. Binary and real coded genetic algorithms (GAs) that employed normalized geometric ranking as well as tournament selection functions were utilized to optimize the Multi-Layer Perceptron neural network architecture. The binary coded genetic algorithm (GA) that used tournament selection function yielded the most optimal solution. However, this algorithm was not the most computationally efficient. This algorithm demonstrated acceptable repeatability abilities. The binary coded GA that used normalized geometric selection function yielded poor repeatability capabilities. GAs that employed normalized geometric ranking selection function were computationally efficient, but yielded solutions that were approximately equal. The real coded tournament selection function GA produced classifiers that were approximately 3% less accurate than the binary coded tournament selection function GA.