ppxscal/embedding_network huggingface dataset:
Support Vector Machines for color adjustment in automotive basecoat
Authors: Francisco Ruiz, Cecilio Angulo, Núria Agell
Venue: Proceeding of the 2006 conference on Artificial Intelligence Research and Development (2006)

Traditionally, Computer Colorant Formulation has been implemented using a theory of radiation transfer known as the Kubelka-Munk (K-M) theory. In recent studies, Artificial Neural Networks (ANNs) has been put forward for dealing with color formulation problems. This paper investigates the ability of Support Vector Machines (SVMs), a particular machine learning technique, to help color adjustment processing in the automotive industry. Imitating 'color matcher' employees, SVMs based on a standard Gaussian kernel are used in an iterative color matching procedure. Two experiments were carried out to validate our proposal, the first considering objective color measurements as output in the training set, and a second where expert criterion was used to assign the output. The comparison of the two experiments reveals some insights about the complexity of the color adjustment analysis and suggests the viability of the method presented.
Evaluating Learning Style Personalization in Adaptive Systems: Quantitative Methods and Approaches
Authors: Elizabeth J. Brown, Timothy J. Brailsford, Tony Fisher, Adam Moore
Venue: IEEE Transactions on Learning Technologies (2009)

It is a widely held assumption that learning style is a useful model for quantifying user characteristics for effective personalized learning. We set out to challenge this assumption by discussing the current state of the art, in relation to quantitative evaluations of such systems and also the methodologies that should be employed in such evaluations. We present two case studies that provide rigorous and quantitative evaluations of learning-style-adapted e-learning environments. We believe that the null results of both these studies indicate a limited usefulness in terms of learning styles for user modeling and suggest that alternative characteristics or techniques might provide a more beneficial experience to users.
Highbrow Films Gather Dust: Time-Inconsistent Preferences and Online DVD Rentals
Authors: Katherine L. Milkman, Todd Rogers, Max H. Bazerman
Venue: Management Science (2009)

We report on a field study demonstrating systematic differences between the preferences people anticipate they will have over a series of options in the future and their subsequent revealed preferences over those options. Using a novel panel data set, we analyze the film rental and return patterns of a sample of online DVD rental customers over a period of four months. We predict and find that should DVDs (e.g., documentaries) are held significantly longer than want DVDs (e.g., action films) within customer. Similarly, we also predict and find that people are more likely to rent DVDs in one order and return them in the reverse order when should DVDs are rented before want DVDs. Specifically, a 1.3% increase in the probability of a reversal in preferences (from a baseline rate of 12%) ensues if the first of two sequentially rented movies has more should and fewer want characteristics than the second film. Finally, we find that as the same customers gain more experience with online DVD rentals, the extent to which they hold should films longer than want films decreases. Our results suggest that present bias has a meaningful impact on choice in the field, and that people may learn about their present bias with experience and, as a result, gain the capacity to curb its influence.
An eye-tracking study of how color coding affects multimedia learning
Authors: Erol Ozcelik, Turkan Karakus, Engin Kursun, Kursat Cagiltay
Venue: Computers Education (2009)

Color coding has been proposed to promote more effective learning. However, insufficient evidence currently exists to show how color coding leads to better learning. The goal of this study was to investigate the underlying cause of the color coding effect by utilizing eye movement data. Fifty-two participants studied either a color-coded or conventional format of multimedia instruction. Eye movement data were collected during the study. The results indicate that color coding increased retention and transfer performance. Enhancement of learning by color coding was due to efficiency of locating corresponding information between illustration and text. Color coding also attracted attention of learners to perceptually salient information.
An exact almost optimal algorithm for target set selection in social networks
Authors: Oren Ben-Zwi, Danny Hermelin, Daniel Lokshtanov, Ilan Newman
Venue: Proceedings of the tenth ACM conference on Electronic commerce (2009)

The Target Set Selection problem proposed by Kempe, Kleinberg, and Tardos, gives a nice clean combinatorial formulation for many problems arising in economy, sociology, and medicine. Its input is a graph with vertex thresholds, the social network, and the goal is to find a subset of vertices, the target set, that "activates" a prespecified number of vertices in the graph. Activation of a vertex is defined via a so-called activation process as follows: Initially, all vertices in the target set become active. Then at each step i of the process, each vertex gets activated if the number of its active neighbors at iteration i -- 1 exceeds its threshold. The activation process is "monotone" in the sense that once a vertex is activated, it remains active for the entire process. Unsurprisingly perhaps, Target Set Selection is NPC. More surprising is the fact that both of its maximization and minimization variants turn out to be extremely hard to approximate, even for very restrictive special cases. The only known case for which the problem is known to have some sort of acceptable worst-case solution is the case where the given social network is a tree and the problem becomes polynomial-time solvable. In this paper, we attempt at extending this sparse landscape of tractable instances by considering the treewidth parameter of graphs. This parameter roughly measures the degree of tree-likeness of a given graph, e.g. the treewidth of a tree is 1, and has previously been used to tackle many classical NPhard problems in the literature. Our contribution is twofold: First, we present an algorithm for Target Set Selection running in nO(w) time, for graphs with n vertices and treewidth bounded by w. The algorithm utilizes various combinatorial properties of the problem; drifting somewhat from standard dynamic-programming algorithms for small treewidth graphs. Also, it can be adopted to much more general settings, including the case of directed graphs, weighted edges, and weighted vertices. On the other hand, we also show that it is highly unlikely to find an nO(√w) time algorithm for Target Set Selection, as this would imply a sub-exponential algorithm for all problems in SNPclass. Together with our upper bound result, this shows that the treewidth parameter determines the complexity of Target Set Selection to a large extent, and should be taken into consideration when tackling this problem in any scenario.
Computer science student transformations: changes and causes
Authors: Jan Erik Moström, Jonas Boustedt, Anna Eckerdal, Robert McCartney, Kate Sanders, Lynda Thomas, Carol Zander
Venue: Proceedings of the 14th annual ACM SIGCSE conference on Innovation and technology in computer science education (2009)

We examine the transformations experienced by students during their study of computing. These transformations led to changes in the students' perceptions of computer science, in their sense of identity as computer scientists, their behavior and their confidence. The changes are caused by learning or using particular concepts, and often associated with writing computer programs, learning new programming languages, or interacting with peers.
Plenary lecture 3: multi-time dynamic programming for multiple integral actions
Authors: Constantin Udriste
Venue: Proceedings of the 2nd WSEAS international conference on Multivariate analysis and its application in science and engineering (2009)

This paper introduces a new type of dynamic programming PDE for optimal control problems with performance criteria involving multiple integrals. The main novel feature of the multitime dynamic programming PDE, relative to the standard Hamilton-Jacobi-Bellman PDE, is that it is connected to the multitime maximum principle. In other words, we present an interesting and useful connection between the multitime maximum principle and the multitime dynamic programming, characterizing the optimal control by means of a multitime Hamilton-Jacobi-Bellman PDE system that may be viewed as a feedback law. In the case of performance criteria involving multiple integrals with quadratic integrands, the new equations lead to multitime variant of the Riccati equation. Section 1 introduces the multitime Hamilton-Jacobi PDE from geometrical point of view. Section 2 shows how a multitime control dynamics determines the multitime Hamilton-Jacobi-Bellman PDE via the value functions. Section 3 describes the connection between multitime dynamic programming and the multitime maximum principle.
Left to Right Atrial Electrophysiological Differences: Substrate for a Dominant Reentrant Source during Atrial Fibrillation
Authors: Oleg V. Aslanidi, Mark R. Boyett, Henggui Zhang
Venue: Proceedings of the 5th International Conference on Functional Imaging and Modeling of the Heart (2009)

Experimentally observed differences in the action potential (AP) properties --- primarily, refractoriness --- between the left (LA) and right (RA) atria are believed to be important in maintaining atrial fibrillation. We incorporate AP models for single LA and RA cells into 2D atrial tissue models and study the role of tissue heterogeneity in global interaction between reentrant spiral waves in the LA and RA. Our simulations show that shorter refractoriness in the LA translates into a shorter period of spiral rotation, and as a result, reentry in the LA dominates the overall excitation patterns in the atria.
Fast Self-stabilization for Gradients
Authors: Jacob Beal, Jonathan Bachrach, Dan Vickery, Mark Tobenkin
Venue: Proceedings of the 5th IEEE International Conference on Distributed Computing in Sensor Systems (2009)

Gradients are distributed distance estimates used as a building block in many sensor network applications. In large or long-lived deployments, it is important for the estimate to self-stabilize in response to changes in the network or ongoing computations, but existing algorithms may repair very slowly, produce distorted estimates, or suffer large transients. The CRF-Gradient algorithm[1] addresses these shortcomings, and in this paper we prove that it self-stabilizes in O(diameter) time--more specifically, in 4 ·diameter/c + k seconds, where k is a small constant and c is the minimum speed of multi-hop message propagation.
Greedy Local Search and Vertex Cover in Sparse Random Graphs
Authors: Carsten Witt
Venue: Proceedings of the 6th Annual Conference on Theory and Applications of Models of Computation (2009)

Recently, various randomized search heuristics have been studied for the solution of the minimum vertex cover problem, in particular for sparse random instances according to the G(n,c/n) model, where c > 0 is a constant. Methods from statistical physics suggest that the problem is easy if c < e. This work starts with a rigorous explanation for this claim based on the refined analysis of the Karp-Sipser algorithm by Aronson et al. Subsequently, theoretical supplements are given to experimental studies of search heuristics on random graphs. For c < 1, a greedy and randomized local-search heuristic finds an optimal cover in polynomial time with a probability arbitrarily close to 1. This behavior relies on the absence of a giant component. As an additional insight into the randomized search, it is shown that the heuristic fails badly also on graphs consisting of a single tree component of maximum degree 3.
Part-of-speech tagging of Northern Sotho: disambiguating polysemous function words
Authors: Gertrud Faaß, Ulrich Heid, Elsabé Taljard, Danie Prinsloo
Venue: Proceedings of the First Workshop on Language Technologies for African Languages (2009)

A major obstacle to part-of-speech (=POS) tagging of Northern Sotho (Bantu, S 32) are ambiguous function words. Many are highly polysemous and very frequent in texts, and their local context is not always distinctive. With certain taggers, this issue leads to comparatively poor results (between 88 and 92% accuracy), especially when sizeable tagsets (over 100 tags) are used. We use the RF-tagger (Schmid and Laws, 2008), which is particularly designed for the annotation of fine-grained tagsets (e.g. including agreement information), and we restructure the 141 tags of the tagset proposed by Taljard et al. (2008) in a way to fit the RF tagger. This leads to over 94% accuracy. Error analysis in addition shows which types of phenomena cause trouble in the POS-tagging of Northern Sotho.
Remote Estimation with Sensor Scheduling
Authors: Li Xiao, Zigang Sun, Desen Zhu, Mianyun Chen
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III (2009)

A time-varying Kalman filter is proposed to solve the problem of remote estimation with sensor scheduling and measurement loss. The statistical properties of the estimation error are studied. The expectation of the estimation error covariance is proved to have upper and lower bounds. Convergence conditions and methods to calculate these bounds are also presented. The optimal sensor selection probability is found by using gradient search method. When the remote estimator schedules the transmission of sensors using optimal probability, the best estimation performance can be obtained. The validity of the proposed results are demonstrated by numerical examples.
Monitoring MLP's free parameters for generalization
Authors: Hung Han Chen
Venue: Proceedings of the 8th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases (2009)

Generalization is one of major concerns for neural network training. In common practice, the number of weights in a MLP network is assumed to be the number of free parameters. This assumption leads to a conclusion: large MLP networks will generalize poorly if their sizes exceed the necessary capacity. However, individual weight in MLP network may not stay as a free parameter since operational condition for hidden neurons alters during the course of training. There have been studies showing that larger networks appear to generalize as well as smaller networks, sometimes even better. Therefore this paper constructs a new perspective on MLP's free parameters to address the issue of generalization.
Challenges of integration of high-κ dielectric with III-V materials (Invited Paper)
Authors: W. Tsai, N. Goel, S. Koveshnikov, P. Majhi, W. Wang
Venue: Microelectronic Engineering (2009)

This paper gives a brief overview of some of the challenges and approaches of integration of high dielectric constant (high-@k) dielectrics with compound semiconductor materials for future high performance low power logic applications. Reviewed themes include interface passivation layer, atomic layer deposition self-cleaning effects and characterization of dielectric/III-V interfaces.
The best of two worlds: cooperation of statistical and rule-based taggers for Czech
Authors: Drahomíra "johanka" Spoustová, Jan Hajič, Jan Votrubec, Pavel Krbec, Pavel Květoň
Venue: Proceedings of the Workshop on Balto-Slavonic Natural Language Processing: Information Extraction and Enabling Technologies (2007)

Several hybrid disambiguation methods are described which combine the strength of hand-written disambiguation rules and statistical taggers. Three different statistical (HMM, Maximum-Entropy and Averaged Perceptron) taggers are used in a tagging experiment using Prague Dependency Tree-bank. The results of the hybrid systems are better than any other method tried for Czech tagging so far.
Modeling and control of die-sinking EDM
Authors: Chingyei Chung, Shou-Yen Chao M. F. Lu, J. S. Deng
Venue: Proceedings of the 9th WSEAS international conference on Robotics, control and manufacturing technology (2009)

This paper explores the mathematical model of the control systems for electrically discharged machining (EDM) machine. Conventionally, it is known that the machining efficiency of EDM is closed related to the so-called ignition delay time. Here, it can be observed that the ignition delay time is the RC time-constant of the circuit model of EDM. Then, it can be shown that ignition delay time is closed related to the gap resistance. According to electromagnetic theory, it can be shown that if the electrode and work-piece is a perfect parallel plate, the resistance is a linear function of the gap distance. Then, the overall control system becomes a simple linear system. For the general case, the gap resistance is a nonlinear function of the gap distance. Then, the overall control system becomes a nonlinear Lur'e problem. For this special Lur'e problem, we applied the SPR (Strict Positive Real) condition for the motor control of EDM to ensure the overall system is globally asymptotically stable. For the requirement of SPR condition, a differential-PID controller is proposed to satisfy SPR condition. Experimental results will be verified. Especially, the machining efficiency can be enhanced up to 33% compared to the conventional optimal PID controller.
Evaluating Legal Argument Instruction with Graphical Representations Using LARGO
Authors: Niels Pinkwart, Vincent Aleven, Kevin Ashley, Collin Lynch
Venue: Proceeding of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work (2007)

Previous research has highlighted the advantages of graphical argument representations. A number of tutoring systems have been built that support students in rendering arguments graphically, as they learn argumentation skills. The relative tutoring benefits of graphical argument representations have not been reliably shown, however. In this paper we present an evaluation of the LARGO system which enables law students graphically to represent examples of legal interpretation with hypotheticals they observe while reading texts of U.S. Supreme Court oral arguments. We hypothesized that LARGO's graphical representations and advice would help students to identify important elements of the arguments (i.e., proposed hypotheses, hypothetical challenges, and responses) and to reflect on their significance to the argument's merits better than a purely text-based alternative. In an experiment, we found some empirical support for this hypothesis.
Trust-Aided Acquisition Of Unverifiable Information
Authors: Eugen Staab, Volker Fusenig, Thomas Engel
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

We propose a mechanism for the acquisition of information from potentially unreliable sources. Our mechanism addresses the case where the acquired information cannot be verified. The idea is to intersperse questions (“challenges”) for which the correct answers are known. By evaluating the answers to these challenges, probabilistic conclusions about the correctness of the unverifiable information can be drawn. Less challenges need to be used if an information provider has shown to be trustworthy. Our approach can resist collusion and shows great promise for various application scenarios such as grid-computing or peer-to-peer networks.
Key Factors Affecting Continuous Usage Intention in Web Analytics Service
Authors: Jaesung Park, Jaejon Kim, Joon Koh
Venue: Proceedings of the Third KES International Symposium on Agent and Multi-Agent Systems: Technologies and Applications (2009)

Web Analytics Service (WAS) has become a rapidly growing business in the internet transactions between firms. It is, from the client firm's perspective, considered to be a form of IT outsourcing. In this paper, we identify factors which can influence the continuous usage intention of a firm that has utilized WAS, and empirically validate the relationships between the identified factors. In the research model developed and described herein, only information quality among the several quality factors was found to be significantly associated with the satisfaction of the client firm. Relative value, switching cost, service usage period, and satisfaction were all significantly associated with dependence.
Accelerated sampling for the Indian Buffet Process
Authors: Finale Doshi-Velez, Zoubin Ghahramani
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

We often seek to identify co-occurring hidden features in a set of observations. The Indian Buffet Process (IBP) provides a non-parametric prior on the features present in each observation, but current inference techniques for the IBP often scale poorly. The collapsed Gibbs sampler for the IBP has a running time cubic in the number of observations, and the uncollapsed Gibbs sampler, while linear, is often slow to mix. We present a new linear-time collapsed Gibbs sampler for conjugate likelihood models and demonstrate its efficacy on large real-world datasets.