ppxscal/embedding_network huggingface dataset:
What ELSE? Regulation and Compliance in Medical Imaging and Medical Informatics
Authors: Penny Duquenoy, Carlisle George, Anthony Solomonides
Venue: Medical Imaging and Informatics: 2nd International Conference, MIMI 2007, Beijing, China, August 14-16, 2007 Revised Selected Papers (2008)

The focus on the use of existing and new technologies to facilitate advances in Medical Imaging and Medical Informatics (MIMI), is often directed to the technical capabilities and possibilities that these technologies bring. In addition to discussing new methodologies, techniques and applications, there is need for a discussion of ethical, legal and socio-economic (ELSE) issues surrounding the use and application of technologies in MIMI. Such discussions are important because scientists need to be aware of the legal/regulatory framework which govern various new advances in MIMI research (especially to safeguard patients' interests), the ethical questions raised by such advances and the impact of these advances on society. This paper aims to discuss important ethical, legal and socio-economic issues related to MIMI and calls for an interdisciplinary approach to better address the increasing use of Information and Communication Technologies (ICT) in healthcare.
Decomposable Families of Itemsets
Authors: Nikolaj Tatti, Hannes Heikinheimo
Venue: Proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases - Part II (2008)

The problem of selecting a small, yet high quality subset of patterns from a larger collection of itemsets has recently attracted a lot of research. Here we discuss an approach to this problem using the notion of decomposable families of itemsets. Such itemset families define a probabilistic model for the data from which the original collection of itemsets was derived. Furthermore, they induce a special tree structure, called a junction tree, familiar from the theory of Markov Random Fields. The method has several advantages. The junction trees provide an intuitive representation of the mining results. From the computational point of view, the model provides leverage for problems that could be intractable using the entire collection of itemsets. We provide an efficient algorithm to build decomposable itemset families, and give an application example with frequency bound querying using the model. An empirical study show that our algorithm yields high quality results.
Fine-Scale Genetic Mapping Using Independent Component Analysis
Authors: Zaher Dawy, Michel Sarkis, Joachim Hagenauer, Jakob C. Mueller
Venue: IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) (2008)

The aim of genetic mapping is to locate the loci responsible for specific traits such as complex diseases. These traits are normally caused by mutations at multiple loci of unknown locations and interactions. In this work, we model the biological system that relates DNA polymorphisms with complex traits as a linear mixing process. Given this model, we propose a new fine-scale genetic mapping method based on independent component analysis. The proposed method outputs both independent associated groups of SNPs in addition to specific associated SNPs with the phenotype. It is applied to a clinical data set for the Schizophrenia disease with 368 individuals and 42 SNPs. It is also applied to a simulation study to investigate in more depth its performance. The obtained results demonstrate the novel characteristics of the proposed method compared to other genetic mapping methods. Finally, we study the robustness of the proposed method with missing genotype values and limited sample sizes.
A Tabular Pruning Rule in Tree-Based Fast Nearest Neighbor Search Algorithms
Authors: Jose Oncina, Franck Thollard, Eva Gómez-Ballester, Luisa Micó, Francisco Moreno-Seco
Venue: Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II (2007)

Some fast nearest neighbor search (NNS) algorithms using metric properties have appeared in the last years for reducing computational cost. Depending on the structure used to store the training set, different strategies to speed up the search have been defined. For instance, pruning rules avoid the search of some branches of a tree in a tree-based search algorithm. In this paper, we propose a new and simple pruning rule that can be used in most of the tree-based search algorithms. All the information needed by the rule can be stored in a table (at preprocessing time). Moreover, the rule can be computed in constant time. This approach is evaluated through real and artificial data experiments. In order to test its performance, the rule is compared to and combined with other previously defined rules.
A Comparison of Centralized and Distributed Information Retrieval Approaches
Authors: Georgios Paltoglou, Michail Salampasis, Maria Satratzemi
Venue: Proceedings of the 2008 Panhellenic Conference on Informatics (2008)

Distributed Information Retrieval (DIR) has been suggested to offer a prospective solution to a number of issues concerning information retrieval in the WWW. On the other hand, previous studies have indicated that centralized approaches offer the best solution for optimal quality of result (i.e. effectiveness). In this paper, we revisit those claims and investigate if and under which conditions can DIR offer a new paradigm for both efﬁcient and effective information retrieval.
On the Computational Complexity of Spiking Neural P Systems
Authors: Turlough Neary
Venue: Proceedings of the 7th international conference on Unconventional Computing (2008)

It is shown that there is no standard spiking neural P system that simulates Turing machines with less than exponential time and space overheads. The spiking neural P systems considered here have a constant number of neurons that is independent of the input length. Following this we construct a universal spiking neural P system with exhaustive use of rules that simulates Turing machines in polynomial time and has only 18 neurons.
CASD: Management of a context-aware service directory
Authors: Christos Doulkeridis, Michalis Vazirgiannis
Venue: Pervasive and Mobile Computing (2008)

Traditional web service discovery is strongly related to the use of service directories. Especially in the case of mobile web services, where both service requestors and providers are mobile, the dynamics impose the need for directory-based discovery. Context plays an eminent role with mobility, as a filtering mechanism that enhances service discovery through the selection of the most appropriate service. However, current service directory specifications do not focus on mobility of services or context-awareness. In this paper, we propose CASD, a context-aware service directory, envisioned as a context-based index for services on top of any traditional service directory, and design algorithms for construction, search, update and merge of such directories. Furthermore, we describe the architecture of our system for context-aware service discovery, we present a prototype implementation and discuss the experimental results as well as the overall evaluation. The contribution of this work is the proposal for a novel, enhanced representation model for a context-aware service directory.
Distributed os for sensor networks
Authors: Jan Rabaey
Venue:  (2007)

Sensor networks are an exciting new technology that promise to revolutionize the environment we live in by creating ambient intelligent spaces. In the current software model, applications are statically loaded onto the network at compile time. This means applications cannot read to changes in the underlying network and code reuse is rare because applications are so tightly coupled with hardware. Sensor network deployments suffer from a lack of standard software APIs that allows applications to interact with the network. This dissertation presents SNSP, a distributed service-based operating system for sensor networks. SNSP presents an integrated interface to applications, which abstracts the distributed nature of the underlying network. It enables dynamic application and content management in the sensor network. SNSP's core consists of seven OS-level services that manage content, discover network resources, monitor resource utilization, dynamically map network applications, provide fault detection and recovery, migrate applications and implement security for the sensor network. Programmers can write services that become a reusable library of SNSP code. The dissertation outlines a programming language and integrated development environment for programmers. Further, the mechanisms for content management and replication and task allocation (mapping) are studied in more detail. Three replication schemes are compared via simulation. Results indicate that the probabilistic scheme has the best performance in terms of cost per data access and increased data availability. Moreover, three task allocation schemes are also compared. The third algorithm, a hybrid genetic search and market bidding protocol, outperforms the other two algorithms. However, due to its twelve times higher computation and 51% higher communication cost the greedy algorithm is preferred. As a proof-of-concept, SNSP is demonstrated on a TelosB and Mica2 (with TinyOS) testbed implementation. The testbed allows applications on different hardware platforms (Mica2 and TelosB) to coexist. Measurements from the testbed indicate that the content management algorithm lowers data access cost and also the time to map a process onto the network.
Architecting Solvers for SAT Modulo Theories: Nelson-Oppen with DPLL
Authors: Sava Krstić, Amit Goel
Venue: Proceedings of the 6th international symposium on Frontiers of Combining Systems (2007)

We offer a transition system representing a high-level but detailed architecture for SMT solvers that combine a propositional SAT engine with solvers for multiple disjoint theories. The system captures succintly and accurately all the major aspects of the solver's global operation: boolean search with across-the-board backjumping, communication of theory-specific facts and equalities between shared variables, and cooperative conflict analysis. Provably correct and prudently underspecified, our system is a usable ground for high-quality implementations of comprehensive SMT solvers.
Uncertainty Management for the Retrieval of Economic Information from Distributed Markets
Authors: René Brunner, Felix Freitag, Leandro Navarro
Venue: Proceedings of the 2nd international conference on Scalable Uncertainty Management (2008)

The provision of real-time and highly accurate information in large-scale distributed systems is technically difficult and approximations imply uncertainty. In economic science, however, reliable information about markets, its specifications, and the behavior of its participants is essential for sophisticated and efficient negotiation strategies. There is the need for a system that provides and allows consulting an overall knowledge of economic information in distributed markets, while managing the accuracy of information for the user. This paper evaluates the influences of uncertainties for information retrieval within distributed Grid markets. It proposes an uncertainty management component for a Decentralized Market Information System (DMIS), which regulates the accuracy of information and the number of messages for the retrieval of economic data from a scalable market. First, we analyze the properties and the completeness of information in Grid markets. Therefore, we simulate Grid market specific scenarios under complete and incomplete information provision by varying the information accessibility. The results confirm the influence of the accuracy on the stability of the market. Based on these results, an optimization mechanism, which uses approximations is introduced for the retrieval of information. The approximations are controlled by the uncertainty management to find a trade-off between the amount of messages and the accuracy of information.
Towards an Ontology-Based Approach for Dealing with Web Guidelines
Authors: Joseph Xiong, Christelle Farenc, Marco Winckler
Venue: Proceedings of the 2008 international workshops on Web Information Systems Engineering (2008)

This paper presents an Ontology-based approach for dealing with guidelines concerning the usability and the accessibility of Web applications. We report an ontology which provides a formal description of concepts used to express ergonomic knowledge related to Web design. This paper demonstrates how to employ such Ontology for organizing ergonomic knowledge by the means of guidelines and, in particular how to employ such guidelines during the inspection of Web-based user interfaces.
Design and validate of a scale anchoring based test items library
Authors: Yi-Hsing Chang, Shih-Feng Hsu, Rong-Jyue Fang
Venue: Proceedings of the 8th WSEAS International Conference on Multimedia systems and signal processing (2008)

The traditional process of scale anchoring only set several specific scores as anchoring points. It only causes ambiguous grading results. Furthermore, the skills and abilities used in solving tests, the applied indicators are abstract and obscure. Thus, in this paper, a smoothing method of arbitrary anchoring revised from scale anchoring is proposed to make tests more accurate in distinguishing test levels. It reflects the difficultness of test scores by the sum and hence easily shows the test levels. In addition, a library containing test items is set up to be shared and reused for users. The paper comes out with two conclusions: smoothing method of arbitrary anchoring can represent the levels of test items by all possible score points. Its scale anchoring could indicate exam's difficultness as well as the tester's ability of passing the test; the test items library could provide references for teachers doing proposition and give students a better adaptive learning environment.
Learning decision trees with taxonomy of propositionalized attributes
Authors: Dae-Ki Kang, Kiwook Sohn
Venue: Pattern Recognition (2009)

We consider the problem of exploiting a taxonomy of propositionalized attributes in order to learn compact and robust classifiers. We introduce propositionalized attribute taxonomy guided decision tree learner (PAT-DTL), an inductive learning algorithm that exploits a taxonomy of propositionalized attributes as prior knowledge to generate compact decision trees. Since taxonomies are unavailable in most domains, we also introduce propositionalized attribute taxonomy learner (PAT-Learner) that automatically constructs taxonomy from data. PAT-DTL uses top-down and bottom-up search to find a locally optimal cut that corresponds to the literals of decision rules from data and propositionalized attribute taxonomy. PAT-Learner propositionalizes attributes and hierarchically clusters the propositionalized attributes based on the distribution of class labels that co-occur with them to generate a taxonomy. Our experimental results on UCI repository data sets show that the proposed algorithms can generate a decision tree that is generally more compact than and is sometimes comparably accurate to those produced by standard decision tree learners.
Direct Adaptive Fuzzy-Neural Control for MIMO Nonlinear Systems Via Backstepping
Authors: Shaocheng Tong, Yongming Li
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

In this paper, an adaptive fuzzy-neural network control problem is discussed for some uncertain MIMO nonlinear systemswith the block-triangular structure. The fuzzy-neural networks are utilized to approximate the virtual controllers, and by using backstepping technique, the direct adaptive FNN control scheme is developed. The proposed control method guarantees the closed-loop signals to be semiglobally uniformly ultimately bounded.
Image registration and statistical analysis for quantitative in vivo spin-lock magnetic resonance imaging of the intervertebral disc response to compression
Authors: Thomas Budinger
Venue:  (2007)

Low back pain decreases the quality of life and affects almost 50% of the population. Quantitative spin-lock magnetic resonance imaging of the T 1&rho;, relaxation parameter is a promising marker of early degeneration in intervertebral discs. However, T1&rho; measurements may be affected by disc compression, and understanding this effect is necessary for studying abnormal dynamics of disc response to compression or correlations between degeneration and T1&rho; values. We developed an algorithm to register images of intervertebral discs in different compression states and to calculate the statistical significance of local changes in T1&rho;. Our procedure includes automatic registration during image acquisition to view the some location across exams, segmentation of intervertebral discs with minimal user intervention, automatic registration of discs using a non-rigid transformation guided by rigid transformations of vertebrae, and a method of investigating the statistical significance of changes in local neighborhoods using resampling hypothesis testing with variable confidence levels. Validation tests on phantoms and volunteer data indicate sub-pixel registration accuracy and precision. Registration results agree with a manual gold standard. Hypothesis testing is sensitive to registration accuracy, indicating the need for registration even with patient movements of less than a millimeter. Tests confirm expected trade-offs between type I and type II statistical significance errors depending on neighborhood size, significance level, and confidence level. We demonstrate the algorithm on varying compression states caused by lying down after 30 minutes of standing with a 20 lb backpack or by supporting 55 pounds while lying using a leg-press-like device. T1&rho; varies locally depending on the distribution of compression within the discs. The coefficient of variation was 7.6% while relaxing and 13.9% when applying and releasing the compression device, indicating an effect of the device. Variation was 48% less in degenerated versus healthy discs (p < 0.04). T1&rho; in the lower discs increased by 20% (p < 0.05) when the compression device pressure was released. Local comparisons showed that T1&rho; tended to decrease under compression and increase after compression was released. Changes were not significant during an hour of supine resting, suggesting that variable pre-scan compression from normal daily activities does not considerably complicate T1&rho; measurements.
Procedural Graphics Model and Behavior Generation
Authors: J. L. Hidalgo, E. Camahort, F. Abad, M. J. Vicent
Venue: Proceedings of the 8th international conference on Computational Science, Part II (2008)

Today's virtual worlds challenge the capacity of human creation. Trying to reproduce natural scenes, with large and complex models, involves reproducing their inherent complexity and detail. Procedural generation helps by allowing artists to create and generalize objects for highly detailed scenes. But existing procedural algorithms can not always be applied to existing applications without major changes. We introduce a new system that helps include procedural generation into existing modeling and rendering applications. Due to its design, extensibility and comprehensive interface, our system can handle user's objects to create and improve applications with procedural generation of content. We demonstrate this and show how our system can generate both models and behaviours for a typical graphics application.
Sensor Placement for 3-Coverage with Minimum Separation Requirements
Authors: Jung-Eun Kim, Man-Ki Yoon, Junghee Han, Chang-Gun Lee
Venue: Proceedings of the 4th IEEE international conference on Distributed Computing in Sensor Systems (2008)

Sensors have been increasingly used for many ubiquitous computing applications such as asset location monitoring, visual surveillance, and human motion tracking. In such applications, it is important to place sensors such that every point of the target area can be sensed by more than one sensor. Especially, many practical applications require 3-coverage for triangulation, 3D hull building, and etc. Also, in order to extract meaningful information from the data sensed by multiple sensors, those sensors need to be placed not too close to each other--minimum separation requirement. To address the 3-coverage problem with the minimum separation requirement, this paper proposes two methods, so called, overlaying method and TRE-based method, which complement each other depending on the minimum separation requirement. For these two methods, we also provide mathematical analysis that can clearly guide us when to use the TRE-based method and when to use the overlaying method and also how many sensors are required. To the best of our knowledge, this is the first work that systematically addresses the 3-coverage problem with the minimum separation requirement.
A knowledge-based approach to manage information systems interoperability
Authors: Jolita Ralyté, Manfred A. Jeusfeld, Per Backlund, Harald Kühn, Nicolas Arni-Bloch
Venue: Information Systems (2008)

Interoperability is a key property of enterprise applications, which is hard to achieve due to the large number of interoperating components and semantic heterogeneity. The inherent complexity of interoperability problems implies that there exists no silver bullet to solve them. Rather, the knowledge about how to solve wicked interoperability problems is hidden in the application cases that expose those problems. The paper addresses the question of how to organise and use method knowledge to resolve interoperability problems. We propose the structure of a knowledge-based system that can deliver situation-specific solutions, called method chunks. Situational Method Engineering promotes modularisation and formalisation of method knowledge in the form of reusable method chunks, which can be combined to compose a situation-specific method. The method chunks are stored in a method chunk repository. In order to cater for management and retrieval, we introduce an Interoperability Classification Framework, which is used to classify and tag method chunks and to assess the project situation in which they are to be used. The classification framework incorporates technical as well as business and organisational aspects of interoperability. This is an important feature as interoperability problems typically are multifaceted spanning multiple aspects. We have applied the approach to analyse an industry case from the insurance sector to identify and classify a set of method chunks.
Data mining to cluster human performance by using online self regulating clustering method
Authors: Adem Karahoca, Dilek Karahoca, Osman Kaya
Venue: Proceedings of the 1st WSEAS International Conference on Multivariate Analysis and its Application in Science and Engineering (2008)

Human capital is critical and vital factor for banking sector. High technology usage and procedural job descriptions have been forced the staff to develop themselves. In this study, staff performance measurements and evaluations gathered by Human Resource department. For cluster evaluation, x-mean algorithm is used to find optimum clusters. Findings show that the usefulness of an innovative technique when applied to research so far conducted through traditional methodologies, and brings to the surface questions about the universal applicability of the widely accepted relationship between superior HRM and superior business performance.