ppxscal/embedding_network huggingface dataset:
Hybrid genetic algorithms and line search method for industrial production planning with non-linear fitness function
Authors: Pandian Vasant, Nader Barsoum
Venue: Engineering Applications of Artificial Intelligence (2009)

Many engineering, science, information technology and management optimization problems can be considered as non-linear programming real-world problems where all or some of the parameters and variables involved are uncertain in nature. These can only be quantified using intelligent computational techniques such as evolutionary computation and fuzzy logic. The main objective of this research paper is to solve non-linear fuzzy optimization problem where the technological coefficient in the constraints involved are fuzzy numbers, which was represented by logistic membership functions using the hybrid evolutionary optimization approach. To explore the applicability of the present study, a numerical example is considered to determine the production planning for the decision variables and profit of the company.
Dynamic Analysis of Delayed Fuzzy Cellular Neural Networks with Time-Varying Coefficients
Authors: Manchun Tan
Venue: Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks (2009)

Some new sufficient conditions are obtained guaranteeing the exponential convergence behavior of each solution of fuzzy cellular neural networks (FCNNs) with variable delays and time-varying coefficients. Compared with some earlier works, the new criteria do not require the Lipschitz continuous condition on activation functions and the differentiability of variable delays.
Research Article: Hybrid stochastic simulations of intracellular reaction-diffusion systems
Authors: Georgios Kalantzis
Venue: Computational Biology and Chemistry (2009)

With the observation that stochasticity is important in biological systems, chemical kinetics have begun to receive wider interest. While the use of Monte Carlo discrete event simulations most accurately capture the variability of molecular species, they become computationally costly for complex reaction-diffusion systems with large populations of molecules. On the other hand, continuous time models are computationally efficient but they fail to capture any variability in the molecular species. In this study a hybrid stochastic approach is introduced for simulating reaction-diffusion systems. We developed an adaptive partitioning strategy in which processes with high frequency are simulated with deterministic rate-based equations, and those with low frequency using the exact stochastic algorithm of Gillespie. Therefore the stochastic behavior of cellular pathways is preserved while being able to apply it to large populations of molecules. We describe our method and demonstrate its accuracy and efficiency compared with the Gillespie algorithm for two different systems. First, a model of intracellular viral kinetics with two steady states and second, a compartmental model of the postsynaptic spine head for studying the dynamics of Ca+2 and NMDA receptors.
Challenges and Research Directions for Adaptive Biometric Recognition Systems
Authors: Norman Poh, Rita Wong, Josef Kittler, Fabio Roli
Venue: Proceedings of the Third International Conference on Advances in Biometrics (2009)

Biometric authentication using mobile devices is becoming a convenient and important means to secure access to remote services such as telebanking and electronic transactions. Such an application poses a very challenging pattern recognition problem: the training samples are often sparse and they cannot represent the biometrics of a person. The query features are easily affected by the acquisition environment, the user's accessories, occlusions and aging. Semi-supervised learning --- learning from the query/test data --- can be a means to tap the vast unlabeled training data. While there is evidence that semi-supervised learning can work in text categorization and biometrics, its application on mobile devices remains a great challenge. As a preliminary, yet, indispensable study towards the goal of semi-supervised learning, we analyze the following sub-problems: model adaptation, update criteria, inference with several models and user-specific time-dependent performance assessment, and explore possible solutions and research directions.
Evaluation of the academic effectiveness of the read 180 program: educational software intervention in reading for at risk high school students in riverside county, california
Authors: Matthew Ashley Robby
Venue:  (2008)

A formative and summative program evaluation was conducted to determine the academic effectiveness of the READ 180 software in 2006 and 2007 as an intervention for experimental participants (n = 260) versus a teacher provided intervention for randomly selected control participants (n = 280). Both groups consisted of freshman high school students reading significantly below grade level and experiencing difficulties making grade level progress in the required curriculum. The evaluation used a rigorous quasi-experimental design with mixed methods and appropriate statistical controls, including archival data and multiple measures to triangulate and interpret results. The study performed replication activities involving two program years (2006 and 2007), two experimental and control group cohorts, and two different baseline and posttest periods. Academic outcomes were compared with ANCOVA and Heges's G procedures between each experimental and control group cohort. Analysis occurred between years and by subgroups, including English learners, disadvantaged students, special education students, and Hispanic students. Additionally, correlations were examined between READ 180 software usage and performance variables and academic outcomes. Findings revealed the null hypothesis was retained for the READ 180 software because of inconsistent cohort 1 and 2 results on the CST in Reading Comprehension and Word Analysis, Fluency, and Systematic Vocabulary Development for English learners, special education students, and Hispanic students; and based on outcomes on the CST in ELA for disadvantaged students, special education students, and Hispanic students. Nevertheless, the null hypothesis was rejected by 2006 and 2007 findings revealing statistically significant and &ldquo;small to moderate&rdquo; effects greater than control conditions for English learners on the CST in ELA, and &ldquo;small&rdquo; effects for disadvantaged students on the CST in Reading Comprehension. Practical analysis revealed subgroups remained below grade level in English language arts and reading comprehension respectively; and that the achievement gap in reading was only slightly reduced. It is unclear if the initial positive effects will show &ldquo;sustained effects&rdquo; during follow-up years. Implications yielded suggestions for improving leadership practices, academic interventions, and the conditions for effective use of educational software in reading. Recommendations were offered for conducting follow-up research on the effects of the READ 180 software. 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
Leader-follower strategies for robotic patrolling in environments with arbitrary topologies
Authors: Nicola Basilico, Nicola Gatti, Francesco Amigoni
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1 (2009)

Game theoretic approaches to patrolling have become a topic of increasing interest in the very last years. They mainly refer to a patrolling mobile robot that preserves an environment from intrusions. These approaches allow for the development of patrolling strategies that consider the possible actions of the intruder in deciding where the robot should move. Usually, it is supposed that the intruder can hide and observe the actions of the patroller before intervening. This leads to the adoption of a leader-follower solution concept. In this paper, mostly theoretical in its nature, we propose an approach to determine optimal leader-follower strategies for a mobile robot patrolling an environment. Differently from previous works in literature, our approach can be applied to environments with arbitrary topologies.
Grid-aware approach to data statistics, data understanding and data preprocessing
Authors: Alexander Wohrer, Lenka Novakova, Peter Brezany, A. Min Tjoa
Venue: International Journal of High Performance Computing and Networking (2009)

In recent years the focus of grid computing shifted towards more data intensive applications, increasingly needing access to various public and private databases. Relocating the code for Data Preprocessing (DPP) closer towards the data source is the overall task of the D&#179;Gframework. This paper presents the data service side architecture to gather Data Statistics (DS) on-the-fly, use them in remote DPP methods on query results and gather exact continuous DS for whole tables inside a database. The performance results are showing low running costs for the continuous DS and the feasibility of the service side DPP functionality.
Joint range assignment and routing to conserve energy in wireless ad hoc networks
Authors: Sajjad Zarifzadeh, Amir Nayyeri, Nasser Yazdani, Ahmad Khonsari, Hamid Hajabdolali Bazzaz
Venue: Computer Networks: The International Journal of Computer and Telecommunications Networking (2009)

In wireless ad hoc networks, energy utilization is perhaps the most important issue, since it corresponds directly to the operational network lifetime. Topology Control (TC) is a well-known energy saving technique which tries to assign transmission ranges of nodes to optimize their energy utilization while keeping the network connected. In current TC schemes, the transmission range of each node is mostly accounted as the exclusive estimator for its energy consumption, while ignoring the amount of data it forwards. Especially when such schemes are coupled with the popular shortest path routing, they usually create a highly-loaded area at the center of the network in which nodes deplete their battery very quickly. In this paper, we introduce efficient strategies that take both load and range into account to handle this problem. We first consider the simple strategy in which a proper transmission range is computed for all nodes of the network to optimize their energy utilization under the presence of the shortest path routing. Inspiring from the results of this strategy, we then propose our combined strategy and argue that a combination of circular paths and shortest paths could result in a much better solution. We also provide detailed analytical models to measure the forwarding load and interference of nodes and then corroborate them with simulation results. Using the combined strategy, the achieved improvement in terms of traffic load, interference, and maximum energy consumption is about 50%, as compared with the simple strategy.
The mixtures of Student's t-distributions as a robust framework for rigid registration
Authors: Demetrios Gerogiannis, Christophoros Nikou, Aristidis Likas
Venue: Image and Vision Computing (2009)

The problem of registering images or point sets is addressed. At first, a pixel similarity-based algorithm for the rigid registration between single and multimodal images is presented. The images may present dissimilarities due to noise, missing data or outlying measures. The method relies on the partitioning of a reference image by a Student's t-mixture model (SMM). This partition is then projected onto the image to be registered. The main idea is that a t-component in the reference image corresponds to a t-component in the image to be registered. If the images are correctly registered the distances between the corresponding components is minimized. Moreover, the extension of the method to the registration of point clouds is also proposed. The use of SMM components is justified by the property that they have heavier tails than standard Gaussians, thus providing robustness to outliers. Experimental results indicate that, even in the case of low SNR or important amount of dissimilarities due to temporal changes, the proposed algorithm compares favorably to the mutual information method for image registration and to the Iterative Closest Points (ICP) algorithm for the alignment of point sets.
Variational Transform Invariant Mixture of Probabilistic PCA
Authors: Jilin Tu, Yun Fu, Alexandar Ivanovic, Thomas S. Huang, Li Fei-Fei
Venue: Proceedings of the 2008 IEEE Workshop on Applications of Computer Vision (2008)

In many video-based object recognition applications, the object appearances are acquired by visual tracking or detection and are inconsistent due to misalignments. We believe the misalignments can be removed if we can reduce the inconsistency in the object appearances caused by misalignments through clustering the objects in appearance, space and time domain simultaneously. We therefore propose to learn Transform Invariant Mixtures of Probabilistic PCA (TIMPPCA) model from the data while at the same time eliminating the misalignments. The model is formulated in a generative framework, and the misalignments are considered as hidden variables in the model. Variational EM update rules are then derived based on Variational Message Passing (VMP) techniques. The proposed TIMP-PCA is applied to improve head pose estimation performance and to detect the change of attention focus in meeting room video for meeting room video indexing/retrieval and achieves promising performance.
Combined structure and motion extraction from visual data using evolutionary active learning
Authors: Krishnanand N. Kaipa, Josh C. Bongard, Andrew N. Meltzoff
Venue: Proceedings of the 11th Annual conference on Genetic and evolutionary computation (2009)

We present a novel stereo vision modeling framework that generates approximate, yet physically-plausible representations of objects rather than creating accurate models that are computationally expensive to generate. Our approach to the modeling of target scenes is based on carefully selecting a small subset of the total pixels available for visual processing. To achieve this, we use the estimation-exploration algorithm (EEA) to create the visual models: a population of three-dimensional models is optimized against a growing set of training pixels, and periodically a new pixel that causes disagreement among the models is selected from the observed stereo images of the scene and added to the training set. We show here that using only 5 % of the available pixels, the algorithm can generate approximate models of compound objects in a scene. Our algorithm serves the dual goals of extracting the 3D structure and relative motion of objects of interest by modeling the target objects in terms of their physical parameters (e.g., position, orientation, shape, etc.), and tracking how these parameters vary with time. We support our claims with results from simulation as well from a real robot lifting a compound object.
Cross-Cultural Evaluation of Politeness in Tactics for Pedagogical Agents
Authors: W. Lewis Johnson, Richard E. Mayer, Elisabeth André, Matthias Rehm
Venue: Proceeding of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology (2005)

Politeness may play a role in tutorial interaction, including promoting learner motivation and avoiding negative affect. Politeness theory can account for this as a means of mitigating the face threats arising in tutorial situations. It further provides a way of accounting for differences in politeness in different cultures. Research in social aspects of human-computer interaction predict that similar phenomena will arise when a computer tutor interacts with learners, i.e., they should exhibit politeness, and the degree of politeness may be culturally dependent. To test this hypothesis, a series of experiments was conducted. First, American students were asked to rate the politeness of possible messages delivered by a computer tutor. The ratings were consistent with the conversational politeness hypothesis, although they depended upon the level of computer literacy of the subjects. Then, the materials were translated into German, in two versions: a polite version, using the formal pronoun Sie, and a familiar version, using the informal pronoun Du. German students were asked to rate these messages. Ratings of the German students were highly consistent with the ratings given by the American subjects, and the same pattern was found across both pronoun forms.
Total cost of security: a method for managing risks and incentives across the extended enterprise
Authors: Russell Cameron Thomas
Venue: Proceedings of the 5th Annual Workshop on Cyber Security and Information Intelligence Research: Cyber Security and Information Intelligence Challenges and Strategies (2009)

This is an extended abstract of the presentation of the same title for the Cyber Security and Information Intelligence Research Workshop, 2009.
End-user programming in the wild: A field study of CoScripter scripts
Authors: Christopher Bogart, Margaret Burnett, Allen Cypher, Christopher Scaffidi
Venue: Proceedings of the 2008 IEEE Symposium on Visual Languages and Human-Centric Computing (2008)

Although a new class of languages has emerged to enable end users to create their own web applications, little is known about how end-user programmers actually use such languages in the real world. In this paper, we report a field study on over 1400 scripts collected from the internet which were created by early adopters of CoScripter, a web macro programming-by-demonstration language. We contrast these internet scripts with those written by users inside IBM, and describe script usage and re-usage patterns, features used, and users’ clever workarounds for features not present in the language. The results show how users grapple with such programming notions as repetition, generalization, and reuse, sometimes inventing their own devices for these. Finally, we discuss the many scripts we found with social implications, whose purposes were to circumvent intended rules, regulations, and usage norm assumptions of a number of web sites.
SOSBP: An Efficient Bargaining Protocol for E-Market
Authors: Liu Hong, Haigang Song, Xueguang Chen, Qihua Zhang
Venue: Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks (2009)

Alternating-Offer Protocol (AOP) is the most predominant way for one-to one bargaining. In this paper, we provide an alternative protocol, Sealed-Offer Synchronous Bargaining Protocol (SOSBP), which can be useful for the automated bargaining between self-interested agents for Open E-Marketplaces. SOSBP introduces an intermediary agent who monitors the bargaining process and hides buyer's offers from seller, and vice versa. Using SOSBP, agents could free submit their offers for evaluating because the intermediary agent has no preference on both buyer and seller. We design some mechanisms to facilitate the success of bargaining, such as Minimum Concession, Concession Reward, Surplus Quote and etc, and present the basic framework of SOSBP. From the result of strategy analysis and experimental study, we concluded that SOSBP has better performance than AOP when agents negotiate under specified situation.
Web Mining for Malaysia's Political Social Networks Using Artificial Immune System
Authors: Ahmad Nadzri Muhammad Nasir, Ali Selamat, Md. Hafiz Selamat
Venue: Knowledge Acquisition: Approaches, Algorithms and Applications: Pacific Rim Knowledge Acquisition Workshop, PKAW 2008, Hanoi, Vietnam, December 15-16, 2008, Revised Selected Papers (2009)

Currently, politic is one of the critical and hot issues in Malaysia. There are many aspects that are related with politics. These politic aspects are mainly about spreading rumors and information through cyberspace that created positive and negative effects to the political situations in Malaysia. There are many branches of cyberspace that can be used by the Internet users to channel their opinions such as websites, forums and blogs which contain the political issues in Malaysia. In this paper, we have analyzed an adaptive model of web mining using Artificial Immune System (AIS) to retrieve the list of URLs that have relevant information on political issues in Malaysia. In addition, we have also used a concept of social network analysis in order to understand the relationships among the websites and web pages related to the political issues in Malaysia. The results from this model have been used to analyze the social networks and the impact of online community which contribute to the outcome of Malaysia's 12th general election.
CFDC: a flash-aware replacement policy for database buffer management
Authors: Yi Ou, Theo Härder, Peiquan Jin
Venue: Proceedings of the Fifth International Workshop on Data Management on New Hardware (2009)

Flash disks are becoming an important alternative to conventional magnetic disks. Although accessed through the same interface by applications, flash disks have some distinguished characteristics that make it necessary to reconsider the design of the software to leverage their performance potential. This paper addresses this problem at the buffer management layer of database systems and proposes a flash-aware replacement policy that significantly improves and outperforms one of the previous proposals in this area.
Unobtrusive data acquisition for spreadsheet research
Authors: Brian Bishop, Kevin McDaid
Venue: Proceedings of the 2008 IEEE Symposium on Visual Languages and Human-Centric Computing (2008)

Spreadsheets are one of the most common end-user programming environments in use today, and their importance in the business world continues to grow. Although considered critical software tools in many industries, particularly the financial sector, it is now widely accepted that the reliability of end-user developed spreadsheets is very poor. In order to address this problem, recent research has focused on the design and development of tools to aid end-users in the testing and debugging of spreadsheets. But to design tools that complement end-users natural behaviour, a knowledge of their behaviour within the most common commercial spreadsheet environment (Excel) is required. This paper details the design and application of a novel, custom built, data acquisition tool, which can be used for the unobtrusive recording of end-users mouse, keyboard and Excel specific actions during the debugging of Excel spreadsheets. The data acquisition tool was utilised in experiments to investigate debugging behaviour, and consequently formed the basis for the development and evaluation of a cell-coverage based debugging tool.
Learning from measurements in exponential families
Authors: Percy Liang, Michael I. Jordan, Dan Klein
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

Given a model family and a set of unlabeled examples, one could either label specific examples or state general constraints---both provide information about the desired model. In general, what is the most cost-effective way to learn? To address this question, we introduce measurements, a general class of mechanisms for providing information about a target model. We present a Bayesian decision-theoretic framework, which allows us to both integrate diverse measurements and choose new measurements to make. We use a variational inference algorithm, which exploits exponential family duality. The merits of our approach are demonstrated on two sequence labeling tasks.