ppxscal/embedding_network huggingface dataset:
Loss and gain functions for CBR retrieval
Authors: J. L. Castro, M. Navarro, J. M. Sánchez, J. M. Zurita
Venue: Information Sciences: an International Journal (2009)

The method described in this article evaluates case similarity in the retrieval stage of case-based reasoning (CBR). It thus plays a key role in deciding which case to select, and therefore, in deciding which solution will be eventually applied. In CBR, there are many retrieval techniques. One feature shared by most is that case retrieval is based on attribute similarity and importance. However, there are other crucial factors that should be considered, such as the possible consequences of a given solution, in other words its potential loss and gain. As their name clearly implies, these concepts are defined as functions measuring loss and gain when a given retrieval case solution is applied. Moreover, these functions help the user to choose the best solution so that when a mistake is made the resulting loss is minimal. In this way, the highest benefit is always obtained.
Broadcasting in dynamic radio networks
Authors: Andrea E. F. Clementi, Angelo Monti, Francesco Pasquale, Riccardo Silvestri
Venue: Journal of Computer and System Sciences (2009)

It is reasonable to claim that almost all major questions related to radio broadcasting can be considered closed as far as static networks are considered: the network never changes during the entire protocol's execution. On the other hand, theoretical results on communication protocols in any scenario where the network topology may change during protocol's execution (i.e. a dynamic radio network) are very few. In this paper, we present a theoretical study of broadcasting in radio networks having dynamic unknown topology. The dynamic network is modeled by means of adversaries: we consider two of them. We first analyze an oblivious, memoryless random adversary that can be seen as the dynamic version of the average-case study presented by Elsasser and Gasieniec in JCSS, 2006. We then consider the deterministic worst-case adversary that, at each time slot, can make any network change (thus the strongest adversary). This is the dynamic version of the worst-case study provided by Bar-Yehuda, Goldreich and Itai in JCSS, 1992. In both cases we provide tight bounds on the completion time of randomized broadcast protocols.
Fast Object Segmentation by Growing Minimal Paths from a Single Point on 2D or 3D Images
Authors: Fethallah Benmansour, Laurent D. Cohen
Venue: Journal of Mathematical Imaging and Vision (2009)

In this paper, we present a new method for segmenting closed contours and surfaces. Our work builds on a variant of the minimal path approach. First, an initial point on the desired contour is chosen by the user. Next, new keypoints are detected automatically using a front propagation approach. We assume that the desired object has a closed boundary. This a-priori knowledge on the topology is used to devise a relevant criterion for stopping the keypoint detection and front propagation. The final domain visited by the front will yield a band surrounding the object of interest. Linking pairs of neighboring keypoints with minimal paths allows us to extract a closed contour from a 2D image. This approach can also be used for finding an open curve giving extra information as stopping criteria. Detection of a variety of objects on real images is demonstrated. Using a similar idea, we can extract networks of minimal paths from a 3D image called Geodesic Meshing. The proposed method is applied to 3D data with promising results.
Energy-efficient capture of stochastic events by global- and local-periodic network coverage
Authors: Shibo He, Jiming Chen, David K.Y. Yau, Huanyu Shao, Youxian Sun
Venue: Proceedings of the tenth ACM international symposium on Mobile ad hoc networking and computing (2009)

We consider a high density of sensors randomly placed in a geographical area for event monitoring. The monitoring regions of the sensors may have significant overlap, and a subset of the sensors can be turned off to conserve energy, thereby increasing the lifetime of the monitoring network. Prior work in this area does not consider the event dynamics. In this paper, we show that knowledge about the event dynamics can be exploited for significant energy savings, by putting the sensors on a periodic on/off schedule. We discuss energy-aware optimization of the periodic schedule for both cases of a synchronous and an asynchronous network. Under the periodic scheduling, coordinated sleep by the sensors can be applied orthogonally to minimize the redundancy of coverage and further improve the energy efficiency. We consider four points in the design space: synchronous periodic scheduling with and without coordinated sleep, and asynchronous periodic scheduling with and without coordinated sleep. We show that the asynchronous network exceeds the synchronous network in the coverage intensity, thereby increasing the effectiveness of the event capture, though it may also reduce the opportunities for coordinated sleep. When the sensor density is high, the asynchronous network with coordinated sleep can achieve extremely good event capture performance while being highly energy-efficient.
Feedback Error Learning with Insufficient Excitation
Authors: Basel Alali, Kentaro Hirata, Kenji Sugimoto
Venue: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences (2008)

This letter studies the tracking error in Multi-input Multi-output Feedback Error Learning (MIMO-FEL) system having insufficient excitation. It is shown that the error converges to zero exponentially even if the reference signal lacks the persistently excitation (PE) condition. Furthermore, by making full use of this fast convergence, we estimate the plant parameter while in operation based on frequency response. Simulation results show the effectiveness of the proposed method compared to a conventional approach.
Wireless Channel Tracking Based on Optimum Predictive LMS
Authors: Qassim Nasir
Venue: Wireless Personal Communications: An International Journal (2009)

A frequency domain analysis is presented to optimize the Predictive Least Mean Square (PLMS) algorithm used for wireless channel tracking. Simulation results show that the PLMS offers significant improvement in tracking performance compared to that of the conventional LMS based method. The algorithm parameters should be carefully selected in order to gain such improvements. The objective of this paper is to use frequency domain analysis to determine an expression for the Mean Square Tracking Error (MSTE) and use it to obtain the optimum PLMS algorithm parameters such as step size (&mu;) and smoothing constant (&theta;) with numerical optimization methods.
A multilevel algorithm for solving the trust-region subproblem
Authors: Philippe L. Toint, D. Tomanos, M. Weber-Mendonca
Venue: Optimization Methods Software (2009)

We present a multilevel numerical algorithm for the exact solution of the Euclidean trust-region subproblem. This particular subproblem typically arises when optimizing a nonlinear (possibly non-convex) objective function whose variables are discretized continuous functions, in which case the different levels of discretization provide a natural multilevel context. The trust-region problem is considered at the highest level (corresponding to the finest discretization), but information on the problem curvature at lower levels is exploited for improved efficiency. The algorithm is inspired by the method described in [J.J. More and D.C. Sorensen, On the use of directions of negative curvature in a modified Newton method, Math. Program. 16(1) (1979), pp. 1-20], for which two different multilevel variants will be analysed. Some preliminary numerical comparisons are also presented.
Performance analysis of loss-based high-speed TCP congestion control algorithms
Authors: Habibullah Jamal, Kiran Sultan
Venue: Proceedings of the 3rd WSEAS international conference on Computer engineering and applications (2009)

The demands for fast transfer of large volumes of data, and the deployment of the network infrastructures to support the demand are ever increasing. However, the dominant transport protocol of today, TCP, does not meet this demand because it favors reliability over timeliness and fails to fully utilize the network capacity due to limitations of its conservative congestion control algorithm. The slow response of TCP in fast long distance networks leaves sizeable unused bandwidth in such networks. Some works have been proposed to improve the connection's throughput by adopting more aggressive TCP congestion control algorithms. The existing loss-based, high-speed TCP congestion control algorithms are highly aggressive to satisfy the efficiency requirement, however this aggressiveness causes severe TCP unfairness. A comparative analysis of TCP Reno with three loss-based, high-speed TCP congestion control algorithms namely, HSTCP, STCP, and CUBIC-TCP is presented in this paper using default parameters of these algorithms for different network topologies.
What classroom role should the PLATO computer system play?
Authors: Robert B. Davis
Venue: Proceedings of the May 6-10, 1974, national computer conference and exposition (1974)

Inserting computers into the ecology of an elementary school classroom involves a combination of promise and uncertainty that parallels similar technological innovations in other areas, whether heart pacers, artificial kidneys, tranquilizers, atomic power plants, transportation, food production or virtually any other area one can think of. In each instance we lack a complete description of the original ecology, and we cannot be, a priori, fully aware of new possibilities.
Automatic metadata extraction from museum specimen labels
Authors: P. Bryan Heidorn, Qin Wei
Venue: Proceedings of the 2008 International Conference on Dublin Core and Metadata Applications (2008)

This paper describes the information properties of museum specimen labels and machine learning tools to automatically extract Darwin Core (DwC) and other metadata from these labels processed through Optical Character Recognition (OCR). The DwC is a metadata profile describing the core set of access points for search and retrieval of natural history collections and observation databases. Using the HERBIS Learning System (HLS) we extract 74 independent elements from these labels. The automated text extraction tools are provided as a web service so that users can reference digital images of specimens and receive back an extended Darwin Core XML representation of the content of the label. This automated extraction task is made more difficult by the high variability of museum label formats, OCR errors and the open class nature of some elements. In this paper we introduce our overall system architecture, and variability robust solutions including, the application of Hidden Markov and Na&iuml;ve Bayes machine learning models, data cleaning, use of field element identifiers, and specialist learning models. The techniques developed here could be adapted to any metadata extraction situation with noisy text and weakly ordered elements.
Horn Query Learning with Multiple Refinement
Authors: Josefina Sierra, Josefina Santibáñez
Venue: Proceedings of the 7th International Conference on Simulated Evolution and Learning (2008)

In this paper we try to understand the heuristics that underlie the decisions made by the Horn query learning algorithm proposed in [1]. We take advantage of our explicit representation of such heuristics in order to present an alternative termination proof for the algorithm, as well as to justify its decisions by showing that they always guarantee that the negative examples in the sequence maintained by the algorithm violate different clauses in the target formula. Finally, we propose a new algorithm that allows multiple refinement when we can prove that such a refinement does not affect the independence of the negative examples in the sequence maintained by the algorithm.
Two Level Question Classification Based on SVM and Question Semantic Similarity
Authors: Jibin Fu, Youli Qu, Zhifei Wang
Venue: Proceedings of the 2009 International Conference on Electronic Computer Technology (2009)

Question classification is very important in question answering system. This paper presents our research about question classification in a real-world on-line interactive question answering system in computer service & support domain. In the domain, questions are divided into 15 cursory categories and 220 sub-categories. The difference of this system is that standard question sentences represent the subcategories rather than only classification criterion. For the special situation, the two level question classification method is present in the paper. Support Vector Machine method is adopted to train a classifier on coarse categories; question semantic similarity model is used to classify the question into sub-categories. The lexical feature and domain ontology concept hierarchy is constructed and exploited to enhance the expression capacity of the feature characteristic for both feature selection for SVM and question semantic similarity computing. When trained and tested on the 11000 question instances in the domain, our approach reaches an accuracy up to 91.5%, which outperforms the result of the baseline.
User-oriented document summarization through vision-based eye-tracking
Authors: Songhua Xu, Hao Jiang, Francis C.M. Lau
Venue: Proceedings of the 13th international conference on Intelligent user interfaces (2009)

We propose a new document summarization algorithm which is personalized. The key idea is to rely on the attention (reading) time of individual users spent on single words in a document as the essential clue. The prediction of user attention over every word in a document is based on the user's attention during his previous reads, which is acquired via a vision-based commodity eye-tracking mechanism. Once the user's attentions over a small collection of words are known, our algorithm can predict the user's attention over every word in the document through word semantics analysis. Our algorithm then summarizes the document according to user attention on every individual word in the document. With our algorithm, we have developed a document summarization prototype system. Experiment results produced by our algorithm are compared with the ones manually summarized by users as well as by commercial summarization software, which clearly demonstrates the advantages of our new algorithm for user-oriented document summarization.
Variable selection for ad prediction
Authors: Suma Bhat, Kenneth Church
Venue: Proceedings of the 2nd International Workshop on Data Mining and Audience Intelligence for Advertising (2008)

We consider the problem of predicting the probability of a click for an advertisement when the outcome of a click or no-click is expressed by means of a set of a large number of variables. Many, if not most, of these variables are very weakly related to the clicking of the ad. Thus, a traditional approach to address this problem that treats each variable on an equal and blind footing takes away the interpretability in explaining the underlying process of the outcome. Such an approach would be computationally expensive and, further, may suffer from poor generalization. We investigate the forward selection method for variable subset selection in the domain of advertisement click-through-rate prediction. The forward selection method proceeds sequentially in a way that rewards a set of variables by how much information it provides regarding the outcome, but penalizes the set based on the number of variables in it. Concretely, we propose a logistic regression model for estimating the conditional expectation between the outcome and the ensemble of variables. The model obtained compares favorably with that obtained via an exhaustive search through the model space. We also observe that the set of variables selected by the forward selection procedure has better predictive power than that selected by considering their individual statistical significance. Thus we show that the forward-selection method for subset selection serves to produce a good model for predicting ad click-through-rates.
Methanol Synthesis Process Control and Simulation
Authors: Tie-jun Chen, Dan-dan Cui, Yan-he Shen, Ke-hong Bi
Venue: Proceedings of the 2009 International Conference on Advanced Computer Control (2009)

In order to obtain the greatest economic benefit of synthetic circuit with the minimum energy consumption of the unit methanol, this paper analyzes the mechanism of the methanol synthesis, brings forward a control algorithm based on chain system, finds out two major factors which affect the energy consumption and output, builds a chain system model made up of two related chains and designs the prediction algorithm and the chain control system for the methanol synthesis process. The simulation indicates that the chain system model has high stability, anti-interference ability and fault-tolerance, so the process can be controlled effectively.
Rescuing IT Outsourcing: Strategic Use of Service-Level Agreements
Authors: C. Derrick Huang, Jahyun Goo
Venue: IT Professional (2009)

IT outsourcing has become increasingly difficult to manage due to its growing complexity and multitude of objectives. To mitigate the management risks, most outsourcing arrangements include service-level agreements (SLAs); but, without proper designs, they tend to be either too limited to be useful or too expansive to be manageable. Our study, based on theoretic conceptualization and analysis of survey data, offers practical guidelines for companies to effectively structure SLAs to warrant the success of IT outsourcing. Specifically, we find that foundation accords of SLAs are important to operationally oriented outsourcing, while change accords should be the focus of those relationships intended to achieve strategic benefits. In addition, firms engaging in "alliance" type of outsourcing relationships should structure their SLAs by carefully selecting SLA elements best for their specific case to provide a mechanism for the practice of interorganizational trust.
On the dynamics of some Newton's type iterative functions
Authors: S. Amat, C. Bermudez, S. Busquier, P. Leauthier, S. Plaza
Venue: International Journal of Computer Mathematics (2009)

The dynamics of a family of Newton's type iterative methods for second-and third-degree complex polynomials is studied. The conjugacy classes of these methods are presented. Classical properties of rational maps are used.
Reusability assessment for software components
Authors: Arun Sharma, P. S. Grover, Rajesh Kumar
Venue: ACM SIGSOFT Software Engineering Notes (2009)

Software reuse has been used as a tool to reduce the development cost and time of the software. Nowadays, in fact, majority of software systems are being developed from an assembly of existing reusable components. In order to assess the reuse of components effectively, it is necessary to measure the reusability of these components. Paper proposes Artificial Neural Network based approach to assess the reusability of software component. This work will help developers to select the best component in terms of its reusability, which will improve the maintainability of the overall system.
Existentially restricted quantified constraint satisfaction
Authors: Hubie Chen
Venue: Information and Computation (2009)

The quantified constraint satisfaction problem (QCSP) is a framework for modelling PSPACE computational problems. The general intractability of the QCSP has motivated the pursuit of restricted cases that avoid its maximal complexity. In this paper, we introduce and study a new model for investigating QCSP complexity in which the types of constraints given by the existentially quantified variables, is restricted. Our primary technical contribution is the development and application of a general technology for proving positive results on parameterizations of the model, of inclusion in the complexity class coNP.
Representation of women in CS: how do we measure a program's success?
Authors: Brad Richards
Venue: Proceedings of the 40th ACM technical symposium on Computer science education (2009)

This paper presents an analysis of the data on representation of women in US liberal arts computer science departments, using 10 years' worth of IPEDS data. What began as a search for departments with exemplary representation ended with the conclusion that the representation data is too unstable to be a useful measure of success: The correlation between average representation values in consecutive five-year periods is small, only r=0.156, and not significantly different from zero (p=0.143, t=1.477) for this set of institutions. Other metrics and sample populations are considered with similar results. This result has important implications for studies assessing the impact of departmental interventions on the representation of women, as well as research on the factors that influence representation.
Solving an integrated employee timetabling and job-shop scheduling problem via hybrid branch-and-bound
Authors: Christian Artigues, Michel Gendreau, Louis-Martin Rousseau, Adrien Vergnaud
Venue: Computers and Operations Research (2009)

We propose exact hybrid methods based on integer linear programming (ILP) and constraint programming (CP) for an integrated employee timetabling and job-shop scheduling problem. Each method we investigate uses a CP formulation associated with an LP relaxation. Under a CP framework, the LP relaxation is integrated into a global constraint using in addition reduced cost-based filtering techniques. We propose two CP formulations of the problem yielding two different LP relaxations. The first formulation is based on a direct representation of the problem. The second formulation is based on a decomposition in intervals of the possible operation starting times. We show the theoretical interest of the decomposition-based representation compared to the direct representation through the analysis of dominant schedules. Computational experiments on a set of randomly generated instances confirm the superiority of the decomposition-based representation. In both cases, the hybrid methods outperform pure CP for employee cost minimization while it is not the case for makespan minimization. The experiments also investigate the interest of the proposed integrated method compared to a sequential approach and show its potential for multiobjective optimization.
Simulated augmented reality windshield display as a cognitive mapping aid for elder driver navigation
Authors: SeungJun Kim, Anind K. Dey
Venue: Proceedings of the 27th international conference on Human factors in computing systems (2009)

A common effect of aging is decline in spatial cognition. This is an issue for all elders, but particularly for elder drivers. To address this driving issue, we propose a novel concept of an in-vehicle navigation display system that displays navigation information directly onto the vehicle's windshield, superimposing it on the driver's view of the actual road. An evaluation of our simulated version of this display shows that it results in a significant reduction in navigation errors and distraction-related measures compared to a typical in-car navigation display for elder drivers. These results help us understand how context-sensitive information and a simulated augmented reality representation can be combined to minimize the cognitive load in translating between virtual/information spaces and the real world.
Upcoming Events
Venue: IEEE MultiMedia (2009)

This department presents publishing opportunities to multimedia researchers, as well as announcing pertinent upcoming conferences.