ppxscal/embedding_network huggingface dataset:
Resource estimation and control in wireless networks
Authors: Elizabeth M. Belding
Venue:  (2008)

The capacity of wireless networks is fundamentally limited due to a fixed frequency spectrum and the shared nature of the resources. The increased usage of IEEE 802.11 based wireless mesh networks as metro backhauls as well as for indoor connectivity and the growing popularity of real time applications, such as VoIP and video, presents a challenging resource management problem due to the limited capacity of wireless networks. IEEE 802.11 networks fail to support high traffic volumes [42]. Hence an unrestrained increase of user traffic can lead to degraded network performance and at times can cause complete network breakdown [42]. This can severely restrict the usefulness of mesh networks as last mile infrastructure for ubiquitous wireless connectivity. In this PhD dissertation, we address the problem of resource management in wireless networks to enable the support of media-rich applications with constrained QoS requirements. We believe that resource management is a critical component towards enabling ubiquitous multimedia support on wireless networks in cities, homes, offices, schools and university campuses. Our contributions can be broadly categorized into three main areas as follows. First, to assess the capability of wireless mesh networks, we perform experimental evaluations on deployed networks [75, 87]. We show that VoIP and video support on current 802.11 multihop networks is severely constrained. Additionally, we demonstrate the drawbacks associated with the current design of routing in mesh networks.Next, to predict and control the usage of available wireless resources, we provide a measurement driven framework for admission control on multihop wireless networks [82, 81]. Our work provides a decision making framework to predict the feasibility of admitting new voice calls on a network. Further, we improve upon the measurement based prediction framework to predict link interference on an indoor wireless testbed. This enables selection and control of link sets for packet scheduling on a TDM wireless network.Finally, to efficiently utilize the available resources in multihop wireless networks, we build an indoor multi-radio wireless network, the UCSB MeshNet, and propose channel assignment and multipath selection schemes that can significantly increase the network utilization to enable the support of multimedia applications [76, 83].In addition to providing a framework to manage the restricted wireless resources, our work shows the feasibility of a distributed framework to make global predictions based on local inferences about the wireless conditions. This makes a strong case for measurement-based protocol design for future wireless networks.
Exploiting context for biomedical entity recognition: from syntax to the web
Authors: Jenny Finkel, Shipra Dingare, Huy Nguyen, Malvina Nissim, Christopher Manning, Gail Sinclair
Venue: Proceedings of the International Joint Workshop on Natural Language Processing in Biomedicine and its Applications (2004)

We describe a machine learning system for the recognition of names in biomedical texts. The system makes extensive use of local and syntactic features within the text, as well as external resources including the web and gazetteers. It achieves an F-score of 70% on the Coling 2004 NLPBA/BioNLP shared task of identifying five biomedical named entities in the GENIA corpus.
On the Sulina precipitation data analysis using the ARMA models and a neural network technique
Authors: Alina Barbulescu, Elena Pelican
Venue: Proceedings of the 10th WSEAS international conference on Mathematical and computational methods in science and engineering (2008)

Weather modification is a topic of substantial worldwide interest for all countries. Only a small number of studies is devoted to model the precipitation evolution in different regions of Romania, including the Black Sea coast [4]. This study concerns the data analysis of Sulina series, using an ARMA model, and a neural networks technique.
Combining Decision Procedures by (Model-)Equality Propagation
Authors: Diego Caminha B. de Oliveira, David Déharbe, Pascal Fontaine
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2009)

SMT (Satisfiability Modulo Theories) solvers are automatic verification engines suitable to discharge important classes of proof obligations generated in applying formal construction of software and hardware designs. In this paper, we present a new approach to combine decision procedures and propositional solvers into an SMT-solver. This approach is based on the generation of model equalities by decision procedures. We show the soundness and completeness of the proposed approach using an original abstract framework to represent and reason about SMT-solvers. We then present an algorithmic version of the new SMT-solving approach and discuss practical aspects of our implementation.
An ant colony optimization approach to the traveling tournament problem
Authors: David C. Uthus, Patricia J. Riddle, Hans W. Guesgen
Venue: Proceedings of the 11th Annual conference on Genetic and evolutionary computation (2009)

The traveling tournament problem has proven to be a difficult problem for the ant colony optimization metaheuristic, with past approaches showing poor results. This is due to the unusual problem structure and feasibility constraints. We present a new ant colony optimization approach to this problem, hybridizing it with a forward checking and conflict-directed backjumping algorithm while using pattern matching and other constraint satisfaction strategies. The approach improves on the performance of past ant colony optimization approaches, finding better quality solutions in shorter time, and exhibits results comparable to other state-of-the-art approaches.
Detecting Defects in Object Oriented Designs Using Design Metrics
Authors: Munkhnasan Choinzon, Yoshikazu Ueda
Venue: Proceeding of the 2006 conference on Knowledge-Based Software Engineering: Proceedings of the Seventh Joint Conference on Knowledge-Based Software Engineering (2006)

In order to decrease the cost, it is recommended to detect defects in the phase they occur. This paper presents a metrics-based approach to detect defects in OO designs. We first identify a list of OO design defects which have a significant impact on the design quality based on the violations of many design guidelines and best practices expressed by experts. Then, we define the metrics for automatically detecting each of these defects. Several number of well-known metrics are used. For some defects, however, there are no suitable design metrics. Therefore, we define new design metrics to detect these defects. Moreover, thresholds to judge whether a metrics value indicates a critical situation, or not are defined for each of the metrics. By defining metrics on each design defect, many design rules and heuristics, and flaws which are described qualitatively can be evaluated quantitatively. On the other hand, we will show that intended application of metrics becomes clear.
Intelligent adaptive monitoring for cardiac surveillance
Authors: Lucie Callens, Guy Carrault, Marie-Odile Cordier, Elisa Fromont, François Portet, René Quiniou
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

Monitoring patients in intensive care units is a critical task. Simple condition detection is generally insufficient to diagnose a patient and may generate many false alarms to the clinician operator. Deeper knowledge is needed to discriminate among alarms those that necessitate urgent therapeutic action. We propose an intelligent monitoring system that makes use of many artificial intelligence techniques: artificial neural networks for temporal abstraction, temporal reasoning, model based diagnosis, decision rule based system for adaptivity and machine learning for knowledge acquisition. To tackle the difficulty of taking context change into account, we introduce a pilot aiming at adapting the system behavior by reconfiguring or tuning the parameters of the system modules. A prototype has been implemented and is currently experimented and evaluated. Some results, showing the benefits of the approach, are given.
Multi-Media Retrieval with Semantic Web: A Case Study in Airport Security Inspection Applications
Authors: Kai Zhang, Le-jian Liao, Yuanda Cao, Liehuang Zhu
Venue: Proceeding of the 2006 conference on Advances in Intelligent IT: Active Media Technology 2006 (2006)

Multi-media retrieval based on content meaning is an important issue. It has significant applications in the tracing of terrorists based on airport security inspection information. In this paper, we review the defects of traditional image retrieval technology. A semantic Web based image retrieval method is proposed, which is deployed into an airport security inspection information retrieval system. We present the techniques of domain ontology construction and semantic-Web annotation for the media. An image retrieval technique based on semantic annotation is suggested, and the design of a semantic information retrieval prototype system for airport security inspection application is described.
Confidence interval estimation for lognormal data with application to health economics
Authors: Guang Yong Zou, Julia Taleban, Cindy Y. Huo
Venue: Computational Statistics Data Analysis (2009)

There has accumulated a large amount of literature on confidence interval construction involving lognormal data owing to the fact that many data in scientific inquiries may be approximated by this distribution. Procedures have usually been developed in a piecemeal fashion for a single mean, a single mean with excessive zeros, a difference between two means, and a difference between two differences (net health benefit). As an alternative, we present a general approach for all these cases that requires only confidence limits available in introductory texts. Simulation results confirm the validity of this approach. Examples arising from health economics are used to exemplify the methodology.
Non-monotonic feature selection
Authors: Zenglin Xu, Rong Jin, Jieping Ye, Michael R. Lyu, Irwin King
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

We consider the problem of selecting a subset of m most informative features where m is the number of required features. This feature selection problem is essentially a combinatorial optimization problem, and is usually solved by an approximation. Conventional feature selection methods address the computational challenge in two steps: (a) ranking all the features by certain scores that are usually computed independently from the number of specified features m, and (b) selecting the top m ranked features. One major shortcoming of these approaches is that if a feature f is chosen when the number of specified features is m, it will always be chosen when the number of specified features is larger than m. We refer to this property as the "monotonic" property of feature selection. In this work, we argue that it is important to develop efficient algorithms for non-monotonic feature selection. To this end, we develop an algorithm for non-monotonic feature selection that approximates the related combinatorial optimization problem by a Multiple Kernel Learning (MKL) problem. We also present a strategy that derives a discrete solution from the approximate solution of MKL, and show the performance guarantee for the derived discrete solution when compared to the global optimal solution for the related combinatorial optimization problem. An empirical study with a number of benchmark data sets indicates the promising performance of the proposed framework compared with several state-of-the-art approaches for feature selection.
Fault-tree analysis for liquefied natural gas terminal emergency shutdown system
Authors: Shuen-Ren Cheng, Binshan Lin, Bi-Min Hsu, Ming-Hung Shu
Venue: Expert Systems with Applications: An International Journal (2009)

Natural gas, one of the cleanest, most efficient and useful of all energy sources, is a vital component of the world's supply of energy. To make natural gas more convenient for storage and transportation, it is refined and condensed into a liquid called liquefied natural gas (LNG). In a LNG site, safety is a long-team and critical issue. The emergency shutdown (ESD) system in the LNG receiving terminal is used to automatically stop the pumps and isolate the leakage section. Fault-tree analysis (FTA) has been widely used for providing logical functional relationships among subsystems and components of a system and identifying the root causes of the undesired failures in a system. In the conventional FTA for the ESD system, we usually assume that exact failure probabilities of events are collected. However, in most real applications, first, the FTA for the ESD system needs to be made at a early design or manufacturing stage, certain new components normally used without failure data; secondly, sometimes the environmental change in the system during the operation periods. This makes more difficult to gather past exact failures data for the FTA. To complete the FTA of the ESD system under these uncertain situations, we apply the intuitionistic fuzzy sets (IFS) theory to the FTA. We generate the intuitionistic fuzzy fault-tree interval, and the intuitionistic fuzzy reliability interval for the ESD system. We also present an algorithm to find the critical components in the system based on IFS-FTA and determine weak paths in the ESD system, where the key improvement must be made.
iDYNamicTV: a social adaptive television experience
Authors: Francesca Carmagnola, Federica Cena, Luca Console, Pierluigi Grillo, Fabiana Vernero, Rossana Simeoni, Monica Perrero
Venue: Proceedings of the 20th ACM conference on Hypertext and hypermedia (2009)

The paper presents an approach to merge Web 2.0 and adaptation with TV contents in order to enrich the user experience. We present iDYNamicTV, a social Web-based recommender system dealing with multimedia contents. iDYNamicTV is part of a larger project by Telecom Italia (DynamicTV) for enhancing user experience in TV fruition. The goal of iDynamicTV is to provide facilities to entertain when exploring and discovering media contents on the Web using a computer interface.
Modelling the characteristics of virtual teams' structure
Authors: Daphna Shwarts-Asher, Niv Ahituv, Dalia Etzion
Venue: International Journal of Business Intelligence and Data Mining (2009)

The main research question is whether output of virtual teams is affected by the teams' structure. A model, suggesting that the team structure can be manipulated in order to increase the team's output will be presented. The study used an experiment, in which subjects, who were grouped into teams, had to share information in order to complete an intellective task. The findings indicated that virtual teams output were inferior to face-to-face teams output, and that structure did overcome two negative impacts of the virtuality &ndash; less effectiveness and less satisfaction; yet it did not raise the virtual team efficiency.
An introduction to the hydrological modelling system PREVAH and its pre- and post-processing-tools
Authors: D. Viviroli, M. Zappa, J. Gurtz, R. Weingartner
Venue: Environmental Modelling Software (2009)

Spatially distributed modelling is an important instrument for studying the hydrological cycle, both concerning its present state as well as possible future changes in climate and land use. Results of such simulations are particularly relevant for the fields of water resources, natural hazards and hydropower. The semi-distributed hydrological modelling system PREVAH (PREecipitation-Runoff-EVApotranspiration HRU Model) implements a conceptual process-oriented approach and has been developed especially to suit conditions in mountainous environments with their highly variable environmental and climatic conditions. This article presents an overview of the actual model core of PREVAH and introduces the various tools which have been developed for obtaining a comprehensive, user-friendly modelling system: DATAWIZARD for importing and managing hydrometeorological data, WINMET for pre-processing meteorological data, GRIDMATH for carrying out elementary raster data operations, FAOSOIL for processing FAO World Soil Map information, WINHRU for pre-processing spatial data and aggregating hydrological response units (HRU), WINPREVAH for operating the model, HYDROGRAPH for visualising hydrograph data and VIEWOPTIM for visualising the calibration procedure. The PREVAH components introduced here support a modelling task from pre-processing the data over the actual model calibration and validation to visualising and interpreting the results (post-processing). A brief overview of current PREVAH applications demonstrates the flexibility of the modelling system with examples that range from water balance modelling over flood estimation and flood forecasting to drought analysis in Switzerland, Austria, China, Russia and Sweden.
A data collection protocol for real-time sensor applications
Authors: Lilia Paradis, Qi Han
Venue: Pervasive and Mobile Computing (2009)

The nature of many sensor applications as well as continuously changing sensor data often imposes real-time requirements on wireless sensor network protocols. Due to numerous design constraints, such as limited bandwidth, memory and energy of sensor platforms, and packet collisions that can potentially lead to an unbounded number of retransmissions, timeliness techniques designed for real-time systems and real-time databases cannot be applied directly to wireless sensor networks. Our objective is to design a protocol for sensor applications that require periodic collection of raw data reports from the entire network in a timely manner. We formulate the problem as a graph coloring problem. We then present TIGRA (Timely Sensor Data Collection using Distributed Graph Coloring) - a distributed heuristic for graph coloring that takes into account application semantics and special characteristics of sensor networks. TIGRA ensures that no interference occurs and spatial channel reuse is maximized by assigning a specific time slot for each node. Although the end-to-end delay incurred by sensor data collection largely depends on a specific topology, platform, and application, TIGRA provides a transmission schedule that guarantees a deterministic delay on sensor data collection.
The essence of the iterator pattern
Authors: Jeremy Gibbons, Bruno c. d. s. Oliveira
Venue: Journal of Functional Programming (2009)

The Iterator pattern gives a clean interface for element-by-element access to a collection, independent of the collection's shape. Imperative iterations using the pattern have two simultaneous aspects: mapping and accumulating. Various existing functional models of iteration capture one or other of these aspects, but not both simultaneously. We argue that C. McBride and R. Paterson's applicative functors (Applicative programming with effects, J. Funct. Program., 18 (1): 1–13, 2008), and in particular the corresponding traverse operator, do exactly this, and therefore capture the essence of the Iterator pattern. Moreover, they do so in a way that nicely supports modular programming. We present some axioms for traversal, discuss modularity concerns and illustrate with a simple example, the wordcount problem.
A new approach for image processing in foreign fiber detection
Authors: Wenzhu Yang, Daoliang Li, Liang Zhu, Yuguo Kang, Futang Li
Venue: Computers and Electronics in Agriculture (2009)

In the textile industry, different types of foreign fibers may be mixed in cotton that need to be sorted out to ensure the quality of the final cotton textile products. Automated visual inspection (AVI) system is a popular tool at present for real time foreign fibers detection in lint. The image processing is one of the key techniques in the AVI system. This paper presents a new approach for processing images of foreign fibers. This approach includes four main steps, namely, image transformation, image enhancement, image segmentation and segmentation post-processing. In the first step, color images were captured and then transformed into gray-scale images. In the second step, the histograms of the gray-scale images were analyzed, and a piecewise nonlinear transform model was proposed to enhance the image based on the analysis results. Thirdly, an improved Otsu's method was employed for segmenting the gray images of foreign fibers. Finally, post-processing of segmentation was performed, and a modified closing operation in mathematics morphology was proposed to fill up the image gaps of the wirelike foreign fibers caused by segmentation, and an area threshold method was suggested to remove the small objects generated by pseudo-foreign-fibers. The results indicate that the contrast between objects and background can be remarkably improved by the proposed enhancement model. The Otsu's method can effectively subdivide the enhanced images into objects and background. The gaps can be filled up by the modified closing operation, and the small objects can be removed effectively using the Area Threshold algorithm.
A method for minimizing unnecessary handovers in heterogeneous wireless networks
Authors: Xiaohuan Yan, Y. Ahmet Sekercioglu, Nallasamy Mani
Venue: Proceedings of the 2008 International Symposium on a World of Wireless, Mobile and Multimedia Networks (2008)

In near future, various wireless access technologies will be used together to provide seamless and cost effective connectivity to mobile users. Multiple wireless access systems with overlapping coverage fields will be accessible to a mobile terminal with multiple interfaces. One problem arising from the availability of alternatives is the unnecessary occurrences of handovers (especially vertical ones) that lead to excessive resource consumption. To avoid this, a suite of algorithms need to be deployed to limit the number of handovers. In this paper, we present an algorithm which is run in the mobile terminal and minimizes the number of handovers when the device detects the presence of wireless local area network (WLAN) signals. Conventionally, a mobile terminal should switch from cellular to WLAN whenever WLAN connectivity is available, to make use of the WLAN’s high speed and low cost as much as possible. However, a considerable proportion of these handovers will be detrimental to the call quality due to potential failures. Our algorithm reduces the number of handovers whenever the predicted traveling distance inside the WLAN cell is smaller than a threshold value. Through performance analysis we show that our algorithm successfully minimizes the probability of unnecessary handovers, and through simulation we discuss about the accuracy of the distance prediction based on the received signal strength measurements.
Temporal dependence networks for the design of convivial multiagent systems
Authors: Patrice Caire, Leendert van der Torre
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

We show how to use TROPOS as a design methodology for convivial multi-agent systems. We introduce temporal dependence networks to measure the evolution of conviviality over time, and we compare them to dynamic dependence networks introduced for conviviality masks and internal dynamics.