ppxscal/embedding_network huggingface dataset:
Edge-Enhanced Image Reconstruction Using (TV) Total Variation and Bregman Refinement
Authors: Shantanu H. Joshi, Antonio Marquina, Stanley J. Osher, Ivo Dinov, John D. Horn, Arthur W. Toga
Venue: Proceedings of the Second International Conference on Scale Space and Variational Methods in Computer Vision (2009)

We propose a novel image resolution enhancement method for multidimensional images based on a variational approach. Given an appropriate down-sampling operator, the reconstruction problem is posed using a deconvolution model under the assumption of Gaussian noise. In order to preserve edges in the image, we regularize the optimization problem by the norm of the total variation of the image. Additionally, we propose a new edge-preserving operator that emphasizes and even enhances edges during the up-sampling and decimation of the image. Furthermore, we also propose the use of the Bregman iterative refinement procedure for the recovery of higher order information from the image. This is coarse to fine approach for recovering finer scales in the image first, followed by the noise. This method is demonstrated on a variety of low-resolution, natural images as well as 3D anisotropic brain MRI images. The edge enhanced reconstruction is shown to yield significant improvement in resolution, especially preserving important edges containing anatomical information.
Algorithm of Neural Network Ensembles and Robust Learning
Authors: Hai Qian, Youping Fan
Venue: Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks (2009)

Neural networks ensemble (NNE) has recently attracted great interests because of their advantages over single neural networks (SNN) as the ability of universal approximate and generalization. However, the design of neural network ensembles is a complex task. In this paper, we propose a general framework for designing neural network ensembles by means of cooperative co-evolution. The proposed model has two main objectives: first, the improvement of the combination of the trained individual networks; second, the cooperative evolution of such networks, encouraging collaboration among them, instead of a separate training of each network. In order to favor the cooperation of the networks, each network is evaluated throughout the evolutionary process using a PSO algorithm based on bootstrap technology (BPSO). A simulation example of the 3-D Mexican Hat is given to validate the method. The result proved its effectiveness.
Determining loading dock requirements in production-distribution facilities under uncertainty
Authors: Avninder Gill
Venue: Computers and Industrial Engineering (2009)

Product handling activities play an important role in the operational aspects of a supply chain network. These activities apart from representing a major portion of the logistic costs, impede the product velocity and affect the lead time it takes to deliver the product to customers. A well designed shipping or receiving facility can significantly reduce the operational costs associated with these activities. Dock design in general and the problem of assessing the dock bay requirements in particular, has a major impact on these costs. The present paper uses a fuzzy set theoretic approach to address the dock bay requirements of a loading facility when the throughput, truck capacity, dock availability and loading times have a certain degree of imprecision or vagueness involved. A dock performance index has been introduced to check the adequacy of dock bays to support a certain level of loading activity. A simulation experiment has been designed and the model was simulated for several days to test the validity of results. Finally, concluding remarks and some direction for further research have been provided.
SLIDE: A Useful Special Case of the CARDPATH Constraint
Authors: Christian Bessiere, Emmanuel Hebrard, Brahim Hnich, Zeynep Kiziltan, Toby Walsh
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

We study the CARDPATH constraint. This ensures a given constraint holds a number of times down a sequence of variables. We show that SLIDE, a special case of CARDPATH where the slid constraint must hold always, can be used to encode a wide range of sliding sequence constraints including CARDPATH itself. We consider how to propagate SLIDE and provide a complete propagator for CARDPATH. Since propagation is NP-hard in general, we identify special cases where propagation takes polynomial time. Our experiments demonstrate that using SLIDE to encode global constraints can be as efficient and effective as specialised propagators.
Decision dependability and its application to identity management
Authors: Nathan D. Kalka, Nick Bartlow, Bojan Cukic
Venue: Proceedings of the 5th Annual Workshop on Cyber Security and Information Intelligence Research: Cyber Security and Information Intelligence Challenges and Strategies (2009)

In this paper we describe decision dependability theory for binary classification problems. Each classification decision is subjected to an informal evaluation of confidence that can be attributed to it. The confidence measure emanates from the strength of evidence which supports the decision. We utilize decision dependability theory in the context of multimodal biometric identity verification systems. The confidence measure is estimated from quality and match scores of biometric samples using subjective Bayesian methodology. We demonstrate how fusion algorithms, such as Bayesian belief networks and likelihood ratio, can be complemented with decision dependability in order to predict classification errors. Furthermore, we illustrate how decision dependability can be used to rectify incorrect decisions.
Reference Signal Impact on EEG Energy
Authors: Sanqing Hu, Matt Stead, Hualou Liang, Gregory A. Worrell
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III (2009)

A reference is required to record electroencephalography (EEG) signals, and therefore the reference signal can effect any quantitative EEG analysis. In this study, we investigate the impact of reference signal amplitude on a commonly used quantitative measure of the EEG, the signal energy. We show that: (i) when the reference signal and the non-referential signal have negative correlation, the energy of the referential signal will monotonically increase as the amplitude of the reference signal increases from 0 to ¿. (ii) When the reference signal and the non-referential signal have positive correlation, energy of the referential signal first decreases to some nonnegative value and then increases as the amplitude of the reference signal increases from 0 to ¿. In general, the reference signal may decrease or increase energy values. But a reference signal with higher relative amplitude will surely increase energy values. In [1], we developed a method to identify and extract the reference signal contribution to EEG recordings. Here we apply this approach to referential EEG recorded from human subjects and directly investigate the contribution of recording reference on energy and show that the reference signal may have a significant effect on energy values.
Survey of indexing schemes for information retrieval on flash memory based wireless sensor networks
Authors: Hassen Redwan, Md. Aminul Haque Chowdhury, Muhammad Ikram, Ki-Hyung Kim
Venue: Proceedings of the 2009 conference on Information Science, Technology and Applications (2009)

The advancement in wireless technologies is playing greatest role in providing information services to users anywhere and any time by using various devices in a ubiquitous environment. Research works concerning the techniques used to effectively store and retrieve information from wireless sensor networks (WSNs) is immature. In this paper, we survey and describe mechanisms for rendering effective information retrieval services in a ubiquitous sensor network environment as efficient information storage and retrieval mechanisms are needed for the resource constrained wireless sensor network. This paper describes flash memory based indexing scheme implementations for information storage and retrieval in WSNs. Finally, we recommend future research direction on indexing scheme for information storage and retrieval in flash memory based WSNs.
Meta-Typicalness Approach to Reliable Classification
Authors: E. N. Smirnov, S. Vanderlooy, I. G. Sprinkhuizen-Kuyper
Venue: Proceeding of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy (2006)

We propose a meta-typicalness approach to apply the typicalness framework for any type of classifiers. The approach can be used to construct classifiers with specified classification performance. Experiments show that the approach results in classifiers that can outperform an existing typicalness-based classifier.
Specifying what to search for
Authors: Steven P. Reiss
Venue: Proceedings of the 2009 ICSE Workshop on Search-Driven Development-Users, Infrastructure, Tools and Evaluation (2009)

In this position paper we look at the problem of letting the programmer specify what they want to search for. We discuss current approaches and their problems. We propose a semantics-based approach and describe the steps we have taken and the many open questions remaining
Non-constrained Blood Pressure Monitoring Using ECG and PPG for Personal Healthcare
Authors: Youngzoon Yoon, Jung H. Cho, Gilwon Yoon
Venue: Journal of Medical Systems (2009)

Blood pressure (BP) is one of the important vital signs that need to be monitored for personal healthcare. Arterial blood pressure (BP) was estimated from pulse transit time (PTT) and PPG waveform. PTT is a time interval between an R-wave of electrocardiography (ECG) and a photoplethysmography (PPG) signal. This method does not require an aircuff and only a minimal inconvenience of attaching electrodes and LED/photo detector sensors on a subject. PTT computed between the ECG R-wave and the maximum first derivative PPG was strongly correlated with systolic blood pressure (SBP) (R¿=¿¿0.712) compared with other PTT values, and the diastolic time proved to be appropriate for estimation diastolic blood pressure (DBP) (R¿=¿¿0.764). The percent errors of SBP using the individual regression line (4---11%) were lower than those using the regression line obtained from all five subjects (9---14%). On the other hand, the DBP estimation did not show much difference between the individual regression (4---10%) and total regression line (6---10%). Our developed device had a total size of 7¿×¿13.5 cm and was operated by single 3-V battery. Biosignals can be measured for 72 h continuously without external interruptions. Through a serial network communication, an external personal computer can monitor measured waveforms in real time. Our proposed method can be used for non-constrained, thus continuous BP monitoring for the purpose of personal healthcare.
Models of Greedy Algorithms for Graph Problems
Authors: Sashka Davis, Russell Impagliazzo
Venue: Algorithmica (2009)

Borodin et al. (Algorithmica 37(4):295&#x2013;326, 2003) gave a model of greedy-like algorithms for scheduling problems and Angelopoulos and Borodin (Algorithmica 40(4):271&#x2013;291, 2004) extended their work to facility location and set cover problems. We generalize their model to include other optimization problems, and apply the generalized framework to graph problems. Our goal is to define an abstract model that captures the intrinsic power and limitations of greedy algorithms for various graph optimization problems, as Borodin et al. (Algorithmica 37(4):295&#x2013;326, 2003) did for scheduling. We prove bounds on the approximation ratio achievable by such algorithms for basic graph problems such as shortest path, weighted vertex cover, Steiner tree, and independent set. For example, we show that, for the shortest path problem, no algorithm in the FIXED priority model can achieve any approximation ratio (even one dependent on the graph size), but the well-known Dijkstra&#x2019;s algorithm is an optimal ADAPTIVE priority algorithm. We also prove that the approximation ratio for weighted vertex cover achievable by ADAPTIVE priority algorithms is exactly&#x00a0;2. Here, a new lower bound matches the known upper bounds (Johnson in J. Comput. Syst. Sci. 9(3):256&#x2013;278, 1974). We give a number of other lower bounds for priority algorithms, as well as a new approximation algorithm for minimum Steiner tree problem with weights in the interval [1,2].
The Effectiveness of a Study Support System Based on Mobile Phones and Web-based Information Sharing: Reporting Activities in a Class for the First Grade of an Elementary School
Authors: Makiko Takenaka, Shigenori Inagaki, Hideko Kuroda, Masahiko Ohkubo, Akiko Deguchi
Venue: Proceeding of the 2005 conference on Towards Sustainable and Scalable Educational Innovations Informed by the Learning Sciences: Sharing Good Practices of Research, Experimentation and Innovation (2005)

The aim of this study was to examine the effectiveness of a study support system introduced into a class of the first grade (7 years old) of a Japanese elementary school to support children in reporting activities to be conducted at home. In this system, children used camera-equipped mobile phones to take pictures and then sent them as e-mail attachments to a website, which enabled easy sharing of information such as images and text. As a result of the study, it was revealed that the children enthusiastically worked on the reporting activities using mobile phones while being able to find interests in the contents of their activities. Meanwhile, it is assumed that their parents have generally approved the educational use of mobile phones, accepting them as indispensable tools in today's society and as an additional means of expressing ourselves.
Maximizing anonymity of a vehicle through pseudonym updation
Authors: Brijesh Kumar Chaurasia, Shekhar Verma
Venue: Proceedings of the 4th Annual International Conference on Wireless Internet (2008)

A vehicle can be tracked through its locatable transmission. The broadcast by a source contains its current identity and also allows estimation of its location by receivers of this transmission. This possibility of mapping between the physical entity and the estimated location through the communication broadcast is a threat to privacy. The changes in the location due to motion and the alteration in the temporal identifiers diminish the correlation between location and physical entity. However, such a mapping can still be recognized when an actively communicating node in relative isolation is observed for a sufficient interval of time. This paper addresses the challenges in providing anonymity to a moving vehicle that continually switches identifiers. As a vehicle moves on a road, its neighbors change in accordance to its relative speed with neighboring vehicles. This change in the nature and size of the neighborhood, i.e. the anonymity set, reduces the anonymity of a vehicle. It is shown that the effective size of anonymity set reduces drastically due to change in the neighbors and transmissions by vehicles. The work studies the possibility that a node may retain its anonymity by switching identities in the vicinity of other vehicles to decorrelate its location and identity relation. A heuristic that allows a vehicle to switch its identity at a time and place where the potential of anonymity preservation can be maximized by increasing the anonymity set is proposed. The performance of the proposed heuristic is evaluated in a highway environment with vehicle mobility and dynamic vehicle population. Results indicate that updating pseudonyms in accordance to the heuristic maximizes the size of the anonymity set and through it, the anonymity of a vehicle.
Group belief dynamics under iterated revision: fixed points and cycles of joint upgrades
Authors: Alexandru Baltag, Sonja Smets
Venue: Proceedings of the 12th Conference on Theoretical Aspects of Rationality and Knowledge (2009)

What happens if in the Muddy Children story [22] we drop the assumption that the public announcements (made by the father and by the children) are commonly known to be always true, and instead we simply assume that they are true and commonly believed to be true? More generally, what happens in the long term with a group's beliefs, knowledge and "epistemic states" (fully describable in fact by conditional beliefs), when receiving (or exchanging) a sequence of public announcements of truthful but uncertain information? Do the agents' beliefs (or knowledge, or conditional beliefs, or other doxastic attitudes such as "strong beliefs") reach a fixed point? Or do they exhibit instead a cyclic behavior, oscillating forever?
Evaluating the utility of content delivery networks
Authors: Konstantinos Stamos, George Pallis, Athena Vakali, Marios D. Dikaiakos
Venue: Proceedings of the 4th edition of the UPGRADE-CN workshop on Use of P2P, GRID and agents for the development of content networks (2009)

Content Delivery Networks (CDNs) balance costs and quality in services related to content delivery. This has urged many Web entrepreneurs to make contracts with CDNs. In the literature, a wide range of techniques has been developed, implemented and standardized for improving the performance of CDNs. The ultimate goal of all the approaches is to improve the utility of CDN surrogate servers. In this paper we define a metric which measures the utility of CDN surrogate servers, called CDN utility. This metric captures the traffic activity in a CDN, expressing the usefulness of surrogate servers in terms of data circulation in the network. Through an extensive simulation testbed, we identify the parameters that affect the CDN utility in such infrastructures. We evaluate the utility of surrogate servers under various parameters and provide insightful comments.
Applying syntactic similarity algorithms for enterprise information management
Authors: Ludmila Cherkasova, Kave Eshghi, Charles B. Morrey, Joseph Tucek, Alistair Veitch
Venue: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining (2009)

For implementing content management solutions and enabling new applications associated with data retention, regulatory compliance, and litigation issues, enterprises need to develop advanced analytics to uncover relationships among the documents, e.g., content similarity, provenance, and clustering. In this paper, we evaluate the performance of four syntactic similarity algorithms. Three algorithms are based on Broder's "shingling" technique while the fourth algorithm employs a more recent approach, "content-based chunking". For our experiments, we use a specially designed corpus of documents that includes a set of "similar" documents with a controlled number of modifications. Our performance study reveals that the similarity metric of all four algorithms is highly sensitive to settings of the algorithms' parameters: sliding window size and fingerprint sampling frequency. We identify a useful range of these parameters for achieving good practical results, and compare the performance of the four algorithms in a controlled environment. We validate our results by applying these algorithms to finding near-duplicates in two large collections of HP technical support documents.
Proceedings of the 7th international workshop on Challenges of large applications in distributed environments
Venue: High Performance Distributed Computing (2009)

Welcome to the 7th International Workshop on Challenges of Large Applications in Distributed Environments (CLADE'09) held on June 10, 2009 in Munich, Germany, in conjunction with the 18th International Symposium on High Performance Distributed Computing (HPDC-18). A new era of large scale, distributed applications are exploiting advances in networking, high-end computers, large data stores and middleware capabilities to address challenging problems. This workshop focuses on the complex issues that arise in large-scale applications of distributed computation, and promotes the development of innovative applications that effectively use distributed resources, e.g., to adapt to heterogeneity and dynamics in space and time. This includes recent results on the development, deployment, management and evaluations of large scale applications in science, engineering, medicine, business, economics, education, and other disciplines, on Grids and other distributed heterogeneous and dynamic computing environments. Topics of the CLADE workshop series include large-scale distributed applications, application-specific portals in distributed environments, distributed problem-solving environments, distributed, collaborative science applications, large, distributed data analysis, applications with heterogeneous spatial and temporal characteristics, distributed, multidimensional, dynamically adaptive applications, applications of new theories and tools for constructing adaptive software systems, enterprise/data-center applications, and applications on Emerging Distributed Environments such as Clouds. Examples of applications benefitting from these advantages include workflow tools in distributed environments, application hosting frameworks for distributed environments, runtime support for intelligent, adaptive systems, programming models for heterogeneous and dynamic computation, portability, quality of service, or fault-tolerance in cluster and Grid computation, resource management, and dynamic scheduling or load balancing in heterogeneous environments.
Plenary lecture I: the software agent paradigm as a powerful simulation tools to support modelling of complex systems. the cases of consumer markets and telecom architectures
Authors: Filippo Neri
Venue: Proceedings of the 7th WSEAS international conference on System science and simulation in engineering (2008)

In the talk we will describe how the software agent paradigm can be a powerful and versatile simulation tool to model and study complex systems, allowing to fast prototype approximate solutions to difficult problems and to easily select which ones to take forward at the deployment stage. To support our position, we will introduce two different domains: consumer decisions in fast moving consumers goods and mobile telecom network management applications. Then we will shows two interesting research problems faced today the expert in those fields. And we will show how a software agent modeling approach could be used to increase the understanding of the problems, their modelization, and the proposal of alternative solutions. In particular, in the talk, we will show how an agent based tool for analysing markets behaviour under several rate of information diffusion can be developed. This methodology has allowed for the study of tradeoffs among several variables of information like product advertisement efforts, consumers' memory span, and passing word among friends in determining market shares. Concerning the mobile telecom domain, we will propose how to study the impact of moving from a centralized network management architecture toward a distributed one, where each network management application consists of a controller part and a set of distributed parts running on the individual network elements.