ppxscal/embedding_network huggingface dataset:
Inference of locus-specific ancestry in closely related populations
Authors: Bogdan Paşaniuc, Sriram Sankararaman, Gad Kimmel, Eran Halperin
Venue: Bioinformatics (2009)

A characterization of the genetic variation of recently admixed populations may reveal historical population events, and is useful for the detection of single nucleotide polymorphisms (SNPs) associated with diseases through association studies and admixture mapping. Inference of locus-specific ancestry is key to our understanding of the genetic variation of such populations. While a number of methods for the inference of locus-specific ancestry are accurate when the ancestral populations are quite distant (e.g. African–Americans), current methods incur a large error rate when inferring the locus-specific ancestry in admixed populations where the ancestral populations are closely related (e.g. Americans of European descent). Results: In this work, we extend previous methods for the inference of locus-specific ancestry by the incorporation of a refined model of recombination events. We present an efficient dynamic programming algorithm to infer the locus-specific ancestries in this model, resulting in a method that attains improved accuracies; the improvement is most significant when the ancestral populations are closely related. An evaluation on a wide range of scenarios, including admixtures of the 52 population groups from the Human Genome Diversity Project demonstrates that locus-specific ancestry can indeed be accurately inferred in these admixtures using our method. Finally, we demonstrate that imputation methods can be improved by the incorporation of locus-specific ancestry, when applied to admixed populations. Availability: The implementation of the WINPOP model is available as part of the LAMP package at http://lamp.icsi.berkeley.edu/lamp Contact: heran@icsi.berkeley.edu
Group lasso with overlap and graph lasso
Authors: Laurent Jacob, Guillaume Obozinski, Jean-Philippe Vert
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

We propose a new penalty function which, when used as regularization for empirical risk minimization procedures, leads to sparse estimators. The support of the sparse vector is typically a union of potentially overlapping groups of co-variates defined a priori, or a set of covariates which tend to be connected to each other when a graph of covariates is given. We study theoretical properties of the estimator, and illustrate its behavior on simulated and breast cancer gene expression data.
RadSem: Semantic Annotation and Retrieval for Medical Images
Authors: Manuel Möller, Sven Regel, Michael Sintek
Venue: Proceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications (2009)

We present a tool for semantic medical image annotation and retrieval. It leverages the MEDICO ontology which covers formal background information from various biomedical ontologies such as the Foundational Model of Anatomy (FMA), terminologies like ICD-10 and RadLex and covers various aspects of clinical procedures. This ontology is used during several steps of annotation and retrieval: (1) We developed an ontology-driven metadata extractor for the medical image format DICOM. Its output contains, e. g., person name, age, image acquisition parameters, body region, etc. (2) The output from (1) is used to simplify the manual annotation by providing intuitive visualizations and to provide a preselected subset of annotation concepts. Furthermore, the extracted metadata is linked together with anatomical annotations and clinical findings to generate a unified view of a patient's medical history. (3) On the search side we perform query expansion based on the structure of the medical ontologies. (4) Our ontology for clinical data management allows us to link and combine patients, medical images and annotations together in a comprehensive result list. (5) The medical annotations are further extended by links to external sources like Wikipedia to provide additional information.
Determination of optimum allocation and pricing of distributed generation using genetic algorithm methodology
Authors: Arun Sekar
Venue:  (2008)

Electric power distribution systems play a significant role in providing continuous and "quality" electrical energy to different classes of customers. In the context of the present restrictions on transmission system expansions and the new paradigm of "open and shared" infrastructure, new approaches to distribution system analyses, economic and operational decision-making need investigation. This dissertation includes three layers of distribution system investigations. In the basic level, improved linear models are shown to offer significant advantages over previous models for advanced analysis. In the intermediate level, the improved model is applied to solve the traditional problem of operating cost minimization using capacitors and voltage regulators. In the advanced level, an artificial intelligence technique is applied to minimize cost under Distributed Generation injection from private vendors. Soft computing techniques are finding increasing applications in solving optimization problems in large and complex practical systems. The dissertation focuses on Genetic Algorithm for investigating the economic aspects of distributed generation penetration without compromising the operational security of the distribution system. The work presents a methodology for determining the optimal pricing of distributed generation that would help utilities make a decision on how to operate their system economically. This would enable modular and flexible investments that have real benefits to the electric distribution system. Improved reliability for both customers and the distribution system in general, reduced environmental impacts, increased efficiency of energy use, and reduced costs of energy services are some advantages.
Software for computerized thermal image processing
Authors: Anna Andonova, Andrew Andreev
Venue: Proceedings of the 10th WSEAS international conference on evolutionary computing (2009)

The modern thermograph cameras are providing great opportunity to observe consequently surfaces. The generated image result can be processed for additional analytical purposes. The current research and development demonstrates how an independent digital image processing can identify the object temperature directly from the source without having specialized hardware. It shows also different techniques for image enhancements, three-dimensional representations and effective batch processing of operations for compression analyses.
Mining discrete patterns via binary matrix factorization
Authors: Bao-Hong Shen, Shuiwang Ji, Jieping Ye
Venue: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining (2009)

Mining discrete patterns in binary data is important for subsampling, compression, and clustering. We consider rank-one binary matrix approximations that identify the dominant patterns of the data, while preserving its discrete property. A best approximation on such data has a minimum set of inconsistent entries, i.e., mismatches between the given binary data and the approximate matrix. Due to the hardness of the problem, previous accounts of such problems employ heuristics and the resulting approximation may be far away from the optimal one. In this paper, we show that the rank-one binary matrix approximation can be reformulated as a 0-1 integer linear program (ILP). However, the ILP formulation is computationally expensive even for small-size matrices. We propose a linear program (LP) relaxation, which is shown to achieve a guaranteed approximation error bound. We further extend the proposed formulations using the regularization technique, which is commonly employed to address overfitting. The LP formulation is restricted to medium-size matrices, due to the large number of variables involved for large matrices. Interestingly, we show that the proposed approximate formulation can be transformed into an instance of the minimum s-t cut problem, which can be solved efficiently by finding maximum flows. Our empirical study shows the efficiency of the proposed algorithm based on the maximum flow. Results also confirm the established theoretical bounds.
Decomposition property for markov-modulated queues with applications to warranty management
Authors: Nan Liu, Vidyadhar g. Kulkarni
Venue: Probability in the Engineering and Informational Sciences (2009)

In this article we study Markov-modulated queues with and without jumps. These queuing models arise naturally in production-inventory systems with and without an external supplier. We show an interesting decomposition property that relates the equilibrium state distributions in these two systems and present an integrated warranty-inventory management model as an application.
FlashLogging: exploiting flash devices for synchronous logging performance
Authors: Shimin Chen
Venue: Proceedings of the 35th SIGMOD international conference on Management of data (2009)

Synchronous transactional logging is the central mechanism for ensuring data persistency and recoverability in database systems. Unfortunately, magnetic disks are ill-suited for the small sequential write pattern of synchronous logging. Alternative solutions (e.g., backup servers or sophisticated battery-backed write caches in high-end disk arrays) are either expensive or complicated. In this paper, we exploit flash devices for synchronous logging based on the observation that flash devices support small sequential writes well. Comparing a wide variety of flash devices, we find that USB flash drives are a good match for this task because of its unique characteristics: widely available USB ports, hot-plug capability useful for coping with flash wear, and low price so that multiple drives are affordable. We propose FlashLogging, a logging solution that exploits multiple (USB) flash drives for synchronous logging. We identify and address four challenges: (i) efficiently exploiting multiple flash drives for logging; (ii) coping with the large variance of write latencies because of device erasure operations; (iii) efficient recovery processing; and (iv) combining flash drives and disks for better logging and recovery performance. We implemented our solution within MySQL-InnoDB. Our real machine experiments running online transaction processing workloads (TPCC) show that FlashLogging achieves up to 5.7X improvements over magnetic-disk-based logging, and obtains up to 98.6% of the ideal performance. We further compare our design with one that uses Solid-State Drives (SSDs), and find that although SSDs improve logging performance, multiple USB flash drives can achieve comparable or better performance with much lower price.
System Engineering in the Energy and Maritime Sectors: Towards a Solution Based on Model-Centric Processes
Authors: Lionel Briand
Venue: Proceedings of the International Conference on Software Process: Trustworthy Software Development Processes (2009)

The Maritime and Energy industry is facing rapid change with an increasing reliance on software embedded systems and integrated control and monitoring systems. From a practical stand point, challenges are related to increased system complexity, increasingly integrated sub-systems relying on Commercial-Of-The-Shelf software, longer supply chains for equipment and components delivered by different suppliers, and short duration for construction and commissioning of ships and offshore platforms. As a result, there is a lack of visibility into the architecture of systems, their design rationale, how subsystems/components were verified and integrated, and finally how systems were validated and certified with a particular focus on safety. In turn, this has hindered effective collaboration among stakeholders, including suppliers and system integrators.This talk will present a recent initiative, led by Simula Research Laboratory and Det Norske Veritas (DNV), Norway, to address the above problems. The general approach relies on model-centric processes, where models of the system specifications, architecture, and design properties, are used to support the documentation of architecture and design rationale, traceability among development artifacts, and guide safety analysis and testing, among other things. The project is focused on devising novel but scalable approaches to the long-standing model-driven development challenges.
On probabilistic results for the discrepancy of a hybrid-Monte Carlo sequence
Authors: Michael Gnewuch
Venue: Journal of Complexity (2009)

In many applications it has been observed that hybrid-Monte Carlo sequences perform better than Monte Carlo and quasi-Monte Carlo sequences, especially in difficult problems. For a mixed s-dimensional sequence m, whose elements are vectors obtained by concatenating d-dimensional vectors from a low-discrepancy sequence q with (s-d)-dimensional random vectors, probabilistic upper bounds for its star discrepancy have been provided. In a paper of G. Okten, B. Tuffin and V. Burago [G. Okten, B. Tuffin, V. Burago, J. Complexity 22 (2006), 435-458] it was shown that for arbitrary @e>0 the difference of the star discrepancies of the first N points of m and q is bounded by @e with probability at least 1-2exp(-@e^2N/2) for N sufficiently large. The authors did not study how large N actually has to be and if and how this actually depends on the parameters s and @e. In this note we derive a lower bound for N, which significantly depends on s and @e. Furthermore, we provide a probabilistic bound for the difference of the star discrepancies of the first N points of m and q, which holds without any restrictions on N. In this sense it improves on the bound of Okten, Tuffin and Burago and is more helpful in practice, especially for small sample sizes N. We compare this bound to other known bounds.
Geostatistical Computing in PSInSAR Data Analysis
Authors: Andrzej Lesniak, Stanislawa Porzycka
Venue: Proceedings of the 9th International Conference on Computational Science: Part I (2009)

The presented paper describes the geostatistical analysis of PSInSAR data. This analysis was preceded by short description of PSInSAR technique. The geostatistical computations showed in this article were performed with the R open-source software containing the gstat package. The analysis contains variograms computing (directional variograms) and ordinary kriging interpolation. The computationally costly problems in geostatistical analysis of PSInSAR data were discussed.
Adaptive call admission control based on reward-penalty model in wireless/mobile network
Authors: Jian-Hui Huang, De-Pei Qian, Sheng-Ling Wang
Venue: Journal of Computer Science and Technology (2007)

A dynamic threshold-based Call Admission Control (CAC) scheme used in wireless/mobile network for multi-class services is proposed. In the scheme, each class's CAC thresholds are solved through establishing a reward-penalty model which strives to maximize network's revenue. In order to lower Handoff Dropping Probability (HDP), the scheme joints packet and connection levels Quality of Service constraints, designing a bandwidth degradation algorithm to accept handoff calls by degrading existing calls' bandwidth during network congestion. Analyses show that the CAC thresholds change adaptively with the average call arrival rate. The performance comparison shows that the proposed scheme outperforms the Mobile IP Reservation scheme.
SceDer and COML: Toolsets for Learning Design and Facilitation in One-to-One Technology Classroom
Authors: Jitti Niramitranon, Mike Sharples, Chris Greenhalgh, Chiu-Pin Lin
Venue: Proceeding of the 2007 conference on Supporting Learning Flow through Integrative Technologies (2007)

In a one-to-one collaborative learning classroom supported by ubiquitous computing and a distributed system runtime environment, teachers require tools that allow them to design learning scenarios, and to manage and monitor the activities happening in the classroom. We propose an architecture for a classroom management system and a scenarios designer tool (SceDer), both based on a Classroom Orchestration Modelling Language (COML), to support these requirements. We have developed and tested this with the GroupScribbles software based on a set of learning scenarios for classrooms equipped with pen tablet computers.
Model for estimating Venezuelan population with working age using artificial neural networks
Authors: Samaria Muñoz-Bravo, Anna Pérez-Méndez, Francklin Rivas-Echeverría
Venue: Proceedings of the 10th WSEAS international conference on Neural networks (2009)

This work presents the development of an Artificial Neural Networks model for estimating the female and male population with working age in Venezuela. For the creation of the model it is used the previous year values related to the employed, unemployed and inactive population (out of the labor force). This model will predict future values of the Venezuelan population with working age, which will help in decision making at governmental, firms and institutions responsible for Venezuelan social security, in order to improve the functioning of the labor market both female and male.
Hierarchical PCA Using Tree-SOM for the Identification of Bacteria
Authors: Stephan Simmuteit, Frank-Michael Schleif, Thomas Villmann, Markus Kostrzewa
Venue: Proceedings of the 7th International Workshop on Advances in Self-Organizing Maps (2009)

In this paper we present an extended version of Evolving Trees using Oja's rule. Evolving Trees are extensions of Self-Organizing Maps developed for hierarchical classification systems. Therefore they are well suited for taxonomic problems like the identification of bacteria. The paper focus on clustering and visualization of bacteria measurements. A modified variant of the Evolving Tree is developed and applied to obtain a hierarchical clustering. The method provides an inherent PCA analysis which is analyzed in combination with the tree based visualization. The obtained loadings support insights in the classification decision and can be used to identify features which are relevant for the cluster separation.
Ethics in Cyberspace: How Cyberspace May Influence Interpersonal Interaction, 1st edition
Authors: Thomas Ploug
Venue:  (2009)

Over the last few decades information and communication technology has come to play an increasingly prominent role in our dealings with other people. Computers, in particular, have made available a host of new ways of interacting, which we have increasingly made use of. In the wake of this development a number of ethical questions have been raised and debated. Ethics in Cyberspace focuses on the consequences for ethical agency of mediating interaction by means of computers, seeking to clarify how the conditions of certain kinds of interaction in cyberspace (for example, in chat-rooms and virtual worlds) differ from the conditions of interaction face-to-face and how these differences may come to affect the behaviour of interacting agents in terms of ethics.
VLSI-SoC: Research Trends in VLSI and Systems on Chip Fourteenth International Conference on Very Large Scale Integration of System on Chip VLSI-SoC2006, 1st edition
Authors: Giovanni De Micheli, Giovanni De Micheli, Salvador Mir, Ricardo Reis
Venue: Federation For Information Processing (2007)

International Federation for Information Processing The IFIP series publishes state-of-the-art results in the sciences and technologies of information and communication. The scope of the series includes: foundations of computer science; software theory and practice; education; computer applications in technology; communication systems; systems modeling and optimization; information systems; computers and society; computer systems technology; security and protection in information processing systems; artificial intelligence; and human-computer interaction. Proceedings and post-proceedings of referred international conferences in computer science and interdisciplinary fields are featured. These results often precede journal publication and represent the most current research. The principal aim of the IFIP series is to encourage education and the dissemination and exchange of information about all aspects of computing.
An embedded platform for reliable applications over heterogeneous wireless networks
Authors: Omneya Issa, Jean-Charles Gregoire, Yacine Belala, James Wong
Venue: Proceedings of the 2008 International Symposium on a World of Wireless, Mobile and Multimedia Networks (2008)

A variety of wireless access technologies provides today’s users with pervasive access to critical content and applications. Guaranteeing a satisfactory quality of service requires reliable and ubiquitous delivery schemes that optimally use the available access technologies. This paper presents a novel architecture to support adaptive real-time data and multimedia applications over different wireless technologies. It addresses several issues associated with the satisfactory operation of applications running over heterogeneous networks. The system is validated using a real-life healthcare application capable of transmitting voice, video and medical data simultaneously. Experimental results are reported that demonstrate the viability of the approach.
Strategic and collaborative approach in information literacy applied in engineering teaching
Authors: Angela Repanovici
Venue: WSEAS Transactions on Information Science and Applications (2009)

This paper provides an overview of an information skills program integrated into the first year engineering subject "Documentation techniques". This is a problem based learning subject, which requires the students to work through and report on an engineering project. Over the past four years the program has transformed radically as a result of applying an action research framework which is primarily concerned with continual improvement and change in practice. Currently the information skills program consists of a student-led orientation tour, an integrated subject web page (developed using SEARCH AND WRITE tutorial).
Oscillation of solutions for first order neutral differential equations with distributed deviating arguments
Authors: Jiu-Gang Dong
Venue: Computers Mathematics with Applications (2009)

Some new sufficient conditions for oscillation and nonoscillation are obtained for first order neutral differential equations with distributed deviating arguments. Our conditions are sharp in the sense that when the coefficients are constants the conditions are also necessary.
Analysing the behavioural intention of using telehomecare from a management viewpoint &ndash; an application of artificial neural network
Authors: Jui-Chen Huang
Venue: International Journal of Computer Applications in Technology (2009)

This study applies the Artificial Neural Network (ANN) based on health belief model to explore the key factors affecting the Behavioural Intention (BI) of using telehomecare. This study interviewed 369 samples in Taiwan. The results suggest that the most effective method to enhance the BI of using telehomecare is to improve the perceived benefits for potential users. The application of ANN is also proven to be feasible in analysing the BI of using telehomecare. The contributions of this study include modelling and identifying the key factors for both practical and management aspects. These findings may serve as a reference to future studies.