ppxscal/embedding_network huggingface dataset:
Solving Large-Scale and Sparse-Reward DEC-POMDPs with Correlation-MDPs
Authors: Feng Wu, Xiaoping Chen
Venue: RoboCup 2007: Robot Soccer World Cup XI (2008)

Within a group of cooperating agents the decision making of an individual agent depends on the actions of the other agents. A lot of effort has been made to solve this problem with additional assumptions on the communication abilities of agents. However, in some realworld applications, communication is limited and the assumptions are rarely satisfied. An alternative approach newly developed is to employ a correlation device to correlate the agents' behavior without exchanging information during execution. In this paper, we apply correlation device to large-scale and spare-reward domains. As a basis we use the framework of infinite-horizon DEC-POMDPs which represent policies as joint stochastic finite-state controllers. To solve any problem of this kind, a correlation device is firstly calculated by solving Correlation Markov Decision Processes (Correlation-MDPs) and then used to improve the local controller for each agent. By using this method, we are able to achieve a tradeoff between computational complexity and the quality of the approximation. In addition, we demonstrate that, adversarial problems can be solved by encoding the information of opponents' behavior in the correlation device. We have successfully implemented the proposed method into our 2D simulated robot soccer team and the performance in RoboCup-2006 was encouraging.
Parameterization of Quadrilateral Meshes
Authors: Li Liu, Caiming Zhang, Frank Cheng
Venue: Proceedings of the 7th international conference on Computational Science, Part II (2007)

Low-distortion parameterization of 3D meshes is a fundamental problem in computer graphics. Several widely used approaches have been presented for triangular meshes. But no direct parameterization techniques are available for quadrilateral meshes yet. In this paper, we present a parameterization technique for non-closed quadrilateral meshes based on mesh simplification. The parameterization is done through a simplify-project-embed process, and minimizes both the local and global distortion of the quadrilateral meshes. The new algorithm is very suitable for computer graphics applications that require parameterization with low geometric distortion.
One genetic algorithm for hierarchical covering location problem
Authors: Miroslav Maric, Milan Tuba, Jozef Kratica
Venue: Proceedings of the 9th WSEAS International Conference on Evolutionary Computing (2008)

In this paper we present a new heuristic approach to solve the Hierarchical Covering Location Problem - HCLP. The binary encoding with the new genetic operators that keep the feasibility of individuals is proposed. The caching GA technique was used, in order to improve computational performance. Results were obtained for test problems available in the literature with 100 and 150 vertices. GA results were compared with exact results obtained using CPLEX. In all cases the computing times were reasonable.
Towards a Cooperative Visual Authoring Environment for Storytelling
Authors: Ivan Blecic, Arnaldo Cecchini, Giuseppe A. Trunfio
Venue: Proceedings of the 5th international conference on Cooperative Design, Visualization, and Engineering (2008)

In this paper we present a methodological approach and a client-server software authoring environment for cooperative visual creation of story-outlines. The methodological approach adopted for story outlining facilitates the representation and visualisation of relevant aspects of stories in a way that is easy to use and understand, and enough general to admit a large number of types and genres of stories. Additional design objectives were set in order to support effective cooperative work and rapid story prototyping.
Lease-based consistency schemes in the web environment
Authors: Byoung-Hoon Lee, Sung-Hwa Lim, Jai-Hoon Kim, Geoffrey C. Fox
Venue: Future Generation Computer Systems (2009)

There are many methods to maintain consistency in the distributed computing environment. Ideally, efficient schemes for maintaining consistency should take into account the following factors: lease duration of replicated data, data access pattern and system parameters. One method used to supply strong consistency in the web environment is the lease method. During the proxy's lease time from a web server, the web server can notify the modification to the proxy by invalidation or update. In this paper, we analyze lease protocol performance by the varying update/invalidation scheme, lease duration and read rates. By using these analyses, we can choose the adaptive lease time and proper protocol (invalidation or update scheme of the modification for each proxy in the web environment). As the number of proxies for web caching increases exponentially, a more efficient method for maintaining consistency needs to be designed. We also present three-tier hierarchies on which each group and node independently and adaptively choose the proper lease time and protocol for each proxy cache. These classifications of the scheme make proxy caching adaptive to client access pattern and system parameters.
Integration of a Complex Learning Object in a Web-Based Interactive Learning System
Authors: Françoise Calvez, Hélène Giroire
Venue: Proceedings of the 9th international conference on Intelligent Tutoring Systems (2008)

Usually, learning objects are described and indexed in repositories using metadata so that users can select them to create new on line courses. What must the granularity level of these metadata be to make them fit the learners' needs? We describe here the problems encountered in integrating a complex learning object to train learners in solving problems in a web-based interactive learning system based on a learner model, and we give a possible solution.
Database Prebuffering as a Way to Create a Mobile Control and Information System with Better Response Time
Authors: Ondrej Krejcar, Jindrich Cernohorsky
Venue: Proceedings of the 8th international conference on Computational Science, Part I (2008)

Location-aware services can benefit from indoor location tracking. The widespread adoption of Wi-Fi as the network infrastructure creates the opportunity of deploying WiFi-based location services with no additional hardware costs. Additionally, the ability to let a mobile device determine its location in an indoor environment supports the creation of a new range of mobile control system applications. Main area of interest is in a model of a radio-frequency based system enhancement for locating and tracking users of our control system inside the buildings. The developed framework as it is described here joins the concepts of location and user tracking as an extension for a new control system. The experimental framework prototype uses a WiFi network infrastructure to let a mobile device determine its indoor position. User location is used for data pre-buffering and pushing information from server to user's PDA. All server data is saved as artifacts (together) with its position information in building.
Techniques for Efficient Software Checking
Authors: Jing Yu, María Jesús Garzarán, Marc Snir
Venue: Languages and Compilers for Parallel Computing: 20th International Workshop, LCPC 2007, Urbana, IL, USA, October 11-13, 2007, Revised Selected Papers (2007)

Dramatic increases in the number of transistors that can be integrated on a chip make processors more susceptible to radiation-induced transient errors. For commodity chips which are cost- and energy-constrained, we need a flexible and inexpensive technology for fault detection. Software approaches can play a major role for this sector of the market because they need little hardware modifications and can be tailored to fit different requirements of reliability and performance. However, software approaches add a significant overhead.In this paper we propose two novel techniques that reduce the overhead of software error checking approaches. The first technique uses boolean logic to identify code patterns that correspond to outcome tolerant branches. We develop a compiler algorithm that finds those patterns and removes the unnecessary replicas. In the second technique we evaluate the performance benefit obtained by removing address checks before load and stores. In addition, we evaluate the overheads that can be removed when the register file is protected in hardware.Our experimental results show that the first technique improves performance by an average 7% for three of the SPEC benchmarks. The second technique can reduce overhead by up-to 50% when the most aggressive optimization is applied.
Locally Discriminant Projection with Kernels for Feature Extraction
Authors: Jun-Bao Li, Shu-Chuan Chu, Jeng-Shyang Pan
Venue: Proceedings of the 3rd international conference on Advanced Data Mining and Applications (2007)

Local Preserving Projection (LPP) is an unsupervised feature extraction method which considers the nearest neighbor information and has little to do with the class information, and it fails to perform well for the nonlinear problems due to its limitation of linearity. In this paper, we extend LPP to propose a novel feature extraction namely Kernel Locally Discriminant Projection (KLDP) by considering class label information and the nonlinear problems. The main work lies in: 1) the class label information is considered to create the similarity measure for the local structure graph; 2) the class-wise cosine similarity measure is applied to solve the selection of the free parameter of the similarity measure; 3) kernel method is applied to solve limitation of linearity of LPP. Besides some theory derivation, the experiments are implemented on ORL and Yale face database to evaluate the feasibility of the proposed algorithm.
Fast Parallel Exponentiation Algorithm for RSA Public-Key Cryptosystem
Authors: Chia-Long Wu, Der-Chyuan Lou, Jui-Chang Lai, Te-Jen Chang
Venue: Informatica (2006)

We know the necessity for information security becomes more widespread in these days, especially for hardware-based implementations such as smart cards chips for wireless applications and cryptographic accelerators. Fast modular exponentiation algorithms are often considered of practical significance in public-key cryptosystems. The RSA cryptosystem is one of the most widely used technologies for achieving information security. The main task of the encryption and decryption engine of RSA cryptosystem is to compute M E mod&thinsp;N. Because the bit-length of the numbers M, E, and N would be about 512 to 1024 bits now, the computations for RSA cryptosystem are time-consuming. In this paper, an efficient technique for parallel computation of the modular exponentiation is proposed and our algorithm can reduce time complexity. We can have the speedup ratio as 1.06 or even 2.75 if the proposed technique is used. In Savas-Tenca-Koc algorithm, they design a multiplier with an insignificant increase in chip area (about 2.8&percnt;) and no increase in time delay. Our proposed technique is faster than Savas-Tenca-Koc algorithm in time complexity and improves efficiency for RSA cryptosystem.
A novel stochastic search method for polygonal approximation problem
Authors: Bin Wang, Huazhong Shu, Chaojian Shi, Limin Luo
Venue: Neurocomputing (2008)

A novel stochastic search method (NSSM) is proposed for the polygonal approximation problem. NSSM incorporates the ranking selection scheme, which is initially developed for solving the premature convergence of genetic algorithms (GAs), into the traditional split-and-merge technique. For avoiding getting trapped in a local optimum, NSSM randomly selects the splitting points and the merging points and determines the selection probability using the ranking selection scheme. Three groups of digital curves, including the synthesized benchmark curves and the real image curves, are used to test the performance of NSSM. The experimental results show the higher performance over the other methods including the GA-based methods and the local search methods.
Path Algorithms for One-Class SVM
Authors: Liang Zhou, Fuxin Li, Yanwu Yang
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks (2008)

The One-Class Support Vector Machine (OC-SVM) is an unsupervised learning algorithm, identifying unusual or outlying points (outliers) from a given dataset. In OC-SVM, it is required to set the regularization hyperparameter and kernel hyperparameter in order to obtain a good estimate. Generally, cross-validation is often used which requires multiple runs with different hyperparameters, making it very slow. Recently, the solution path algorithm becomes popular. It can obtain every solution for all hyperparameters in a single run rather than re-solve the optimization problem multiple times. Generalizing from previous algorithms for solution path in SVMs, this paper proposes a complete set of solution path algorithms for OC-SVM, including a ¿-path algorithm and a kernel-path algorithm. In the kernel-path algorithm, a new method is proposed to avoid the failure of algorithm due to indefinite matrix . Using those algorithms, we can obtain the optimum hyperparameters by computing an entire path solution with the computational cost O(n 2 + cnm 3) on ¿-path algorithm or O(cn 3 + cnm 3) on kernel-path algorithm (c: constant, n: the number of sample, m: the number of sample which on the margin).
Effects of Optimizations for Software Implementations of Small Binary Field Arithmetic
Authors: Roberto Avanzi, Nicolas Thériault
Venue: Proceedings of the 1st international workshop on Arithmetic of Finite Fields (2007)

We describe an implementation of binary field arithmetic written in the C programming language. Even though the implementation targets 32-bit CPUs, the results can be applied also to CPUs with different granularity.We begin with separate routines for each operand size in words to minimize performance penalties that have a bigger relative impact for shorter operands --- such as those used to implement modern curve based cryptography. We then proceed to use techniques specific to operand size in bits for several field sizes.This results in an implementation of field arithmetic where the curve representing field multiplication performance closely resembles the theoretical quadratic bit-complexity that can be expected for small inputs.This has important practical consequences: For instance, it will allow us to compare the performance of the arithmetic on curves of different genera and defined over fields of different sizes without worrying about penalties introduced by field arithmetic and concentrating on the curve arithmetic itself. Moreover, the cost of field inversion is very low, making the use of affine coordinates in curve arithmetic more interesting. These applications will be mentioned.
Multi-level Classification of Emphysema in HRCT Lung Images Using Delegated Classifiers
Authors: Mithun Prasad, Arcot Sowmya
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

Emphysema is a common chronic respiratory disorder characterized by the destruction of lung tissue. It is a progressive disease where the early stages are characterized by diffuse appearance of small air spaces and later stages exhibit large air spaces called bullae. A bullous region is a sharply demarcated region of emphysema. In this paper, we show that an automated texture-based system based on delegated classifiers is capable of achieving multiple levels of emphysema extraction in High Resolution Computed Tomography (HRCT) images. The key idea of delegation is that a cautious classifier makes predictions that meet a minimum level of confidence, and delegates the difficult or uncertain predictions to a more specialized classifier. In this paper, we design a two-step scenario where a first classifier chooses the examples to classify on and delegates the more difficult examples to a second classifier. We compare this technique to well known emphysema classification techniques and ensemble methods such as bagging and boosting. Comparison of the results shows that the techniques presented here are more accurate. From a medical standpoint, the classifiers built at different iterations appear to show an interesting correlation with different levels of emphysema.
Caching Dynamic Skyline Queries
Authors: Dimitris Sacharidis, Panagiotis Bouros, Timos Sellis
Venue: Proceedings of the 20th international conference on Scientific and Statistical Database Management (2008)

Given a query tuple q, the dynamic skyline query retrieves the tuples that are not dynamically dominated by any other in the data set with respect to q. A tuple dynamically dominates another, w.r.t. q, if it has closer to q's values in all attributes, and has strictly closer to q's value in at least one. The dynamic skyline query can be treated as a standard skyline query, subject to the transformation of all tuples' values. In this work, we make the observation that results to past dynamic skyline queries can help reduce the computation cost for future queries. To this end, we propose a caching mechanism for dynamic skyline queries and devise a cache-aware algorithm. Our extensive experimental evaluation demonstrates the efficiency of this mechanism compared to standard techniques without caching.
Designing for long-term human-robot interaction and application to weight loss
Authors: Cynthia Breazeal
Venue:  (2008)

Human-robot interaction is now well enough understood to allow us to build useful systems that can function outside of the laboratory. This thesis defines sociable robot system in the context of long-term interaction, proposes guidelines for creating and evaluating such systems, and describes the implementation of a robot that has been designed to help individuals effect behavior change while dieting. The implemented system is a robotic weight loss coach, which is compared to a standalone computer and to a traditional paper log in a controlled study. A current challenge in weight loss is in getting individuals to keep off weight that is lost. The results of our study show that participants track their calorie consumption and exercise for nearly twice as long when using the robot than with the other methods and develop a closer relationship with the robot. Both of these are indicators of longer-term success at weight loss and maintenance. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)
Searching for approximate equilibria in empirical games
Authors: Patrick R. Jordan, Yevgeniy Vorobeychik, Michael P. Wellman
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2 (2008)

When exploring a game over a large strategy space, it may not be feasible or cost-effective to evaluate the payoff of every relevant strategy profile. For example, determining a profile payoff for a procedurally defined game may require Monte Carlo simulation or other costly computation. Analyzing such games poses a search problem, with the goal of identifying equilibrium profiles by evaluating payoffs of candidate solutions and potential deviations from those candidates. We propose two algorithms, applicable to distinct models of the search process. In the revealed-payoff model, each search step determines the exact payoff for a designated pure-strategy profile. In the noisy-payoff model, a step draws a stochastic sample corresponding to such a payoff. We compare our algorithms to previous proposals from the literature for these two models, and demonstrate performance advantages.
Multilevel Conditional Fuzzy C-Means Clustering of XML Documents
Authors: Michal Kozielski
Venue: Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases (2007)

XML documents are the special kind of data having hierarchical structure. Typical clustering algorithms do not meet requirements which may be stated for analysis of such data. A novel, dedicated for XML documents clustering method called Multilevel clustering of XML documents (ML) is presented in the paper. The method clusters feature vectors encoding XML documents on the different structure levels. Application of Conditional Fuzzy C-Means algorithm to ML method is proposed in the paper and the advantage of this fuzzy method over hard approach to ML algorithm is discussed and proved. An application of ML method to accelerating query execution on XML documents is discussed in the paper. The experimental results performed on two data sets having different characteristics show that the proposed method of multilevel conditional fuzzy clustering of XML documents outperforms hard multilevel clustering.
Security Analysis of Public-Key Encryption Scheme Based on Neural Networks and Its Implementing
Authors: Niansheng Liu, Donghui Guo
Venue: Computational Intelligence and Security: International Conference, CIS 2006, Guangzhou, China, November 3-6, 2006, Revised Selected Papers (2007)

A Diffie-Hellman public-key cryptography based on chaotic attractors of neural networks is described in the paper. There is a one-way function between chaotic attractors and initial states in an Overstoraged Hopfield Neural Networks (OHNN). If the synaptic matrix of OHNN is changed, each attractor and its corresponding domain of initial state attraction will be changed. Then, we regard the neural synaptic matrix as a trap door, and change it with commutative random permutation matrix. A new Diffie-Hellman public-key cryptosystem can be implemented, namely keeping the random permutation operation of the neural synaptic matrix as the secret key, and the neural synaptic matrix after permutation as public-key. In order to explain the practicability of the encryption scheme, Security and encryption efficient of the scheme are discussed. The scheme of application for Internet secure communications is implemented by using Java program. The experimental results show that the proposed cryptography is feasible, and has a good performance of encryption and decryption speed to ensure the real time of IPng secure communications.
A TCP Based Performance Test Method and Its Application
Authors: Lei Chen, Lu Lu
Venue: Proceedings of the 2008 Second International Conference on Genetic and Evolutionary Computing (2008)

With the increasing scale of software and the exploding amount of data, software performance problem has become more and more serious, drawing more and more people to study the way of testing software’s performance. Although there are many performance test methods focusing on B/S structured system, other systems are ignored. In this paper, the common performance test procedure is given first, and then a method is presented to show how to perform such a procedure on an application based on the TCP. This method, which involves three main phases including “Capture and filter out useless packages”, “Parameterization”, and “Testing and monitoring”, provides an adaptive approach to test a system built upon the TCP. At last, the method’s validation is proved in an experiment, in which the target application is based on a typical C/S structure.