ppxscal/embedding_network huggingface dataset:
Optimality analysis of sensor-target localization geometries
Authors: Adrian N. Bishop, Barış Fidan, Brian D. O. Anderson, Kutluyıl Doğançay, Pubudu N. Pathirana
Venue: Automatica (Journal of IFAC) (2010)

The problem of target localization involves estimating the position of a target from multiple noisy sensor measurements. It is well known that the relative sensor-target geometry can significantly affect the performance of any particular localization algorithm. The localization performance can be explicitly characterized by certain measures, for example, by the Cramer-Rao lower bound (which is equal to the inverse Fisher information matrix) on the estimator variance. In addition, the Cramer-Rao lower bound is commonly used to generate a so-called uncertainty ellipse which characterizes the spatial variance distribution of an efficient estimate, i.e. an estimate which achieves the lower bound. The aim of this work is to identify those relative sensor-target geometries which result in a measure of the uncertainty ellipse being minimized. Deeming such sensor-target geometries to be optimal with respect to the chosen measure, the optimal sensor-target geometries for range-only, time-of-arrival-based and bearing-only localization are identified and studied in this work. The optimal geometries for an arbitrary number of sensors are identified and it is shown that an optimal sensor-target configuration is not, in general, unique. The importance of understanding the influence of the sensor-target geometry on the potential localization performance is highlighted via formal analytical results and a number of illustrative examples.
A simple, least-time, and energy-efficient routing protocol with one-level data aggregation for wireless sensor networks
Authors: Sudip Misra, P. Dias Thomasinous
Venue: Journal of Systems and Software (2010)

The area of wireless sensor networks (WSN) is currently attractive in the research community area due to its applications in diverse fields such as defense security, civilian applications and medical research. Routing is a serious issue in WSN due to the use of computationally-constrained and resource-constrained micro-sensors. These constraints prohibit the deployment of traditional routing protocols designed for other ad hoc wireless networks. Any routing protocol designed for use in WSN should be reliable, energy-efficient and should increase the lifetime of the network. We propose a simple, least-time, energy-efficient routing protocol with one-level data aggregation that ensures increased life time for the network. The proposed protocol was compared with popular ad hoc and sensor network routing protocols, viz., AODV (Royer and Perkins, 1999; Das et al., 2003), DSR (Johnson et al., 2001), DSDV (Perkins and Bhagwat, 1994), DD (Intanagonwiwat et al., 2000) and MCF (Ye et al., 2001). It was observed that the proposed protocol outperformed them in throughput, latency, average energy consumption and average network lifetime. The proposed protocol uses absolute time and node energy as the criteria for routing, this ensures reliability and congestion avoidance.
Morphid academy: a virtual laboratory for evolution of form and function
Authors: Marcin L. Pilat
Venue:  (2009)

Physical forms are a vital part of our daily lives and can be seen all around us. Some forms are static, others move around, but all have a certain desired function. Forms and their associated functions are normally created by human hands or using various human-made machinery and manufacturing processes. Some complex forms, such as living organisms, have been created through complex evolutionary forces. It is those forces that are of interest in improving the human-made forms. This thesis tackles the problem of evolution of physically simulated forms and their associated functions. In order to harness the power of natural evolution, the forces behind it have to be understood and controlled. Evolution is not very practical to study in nature due to its very long time scale. It can, however, be studied in computer simulations using models of form and function. We have created Morphid Academy (MA) - a virtual laboratory for the study of evolution for physical forms and their functions. This evolutionary framework allows for the generation, simulation, evolution, and visualization of various models of forms. The aspect of form and its function is encapsulated into a physically simulated agent called a Morphid. The MA studies Morphid evolution through an experimental framework composed of structured simulation entities called Training Grounds. A special Morphocosm Training Ground is an ecosystem of interacting Morphids. To demonstrate the Morphid Academy on a concrete example, we have implemented a virtual creature model of a Morphid. The virtual creature Morphid model, composed of a morphology and neural controller, allowed us to use MA in order to evolve virtual creatures in the training tasks of locomotion and light following. To showcase MA functionality, complex experimental topologies were designed to study incremental evolution, neural network evolution, and adaptation to environmental perturbations. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
A framework for superimposed applications: techniques to represent, access, transform, and interchange bi-level information
Authors: Sudarshan Srinivasa Murthy
Venue:  (2009)

Superimposed applications (SAs) superimpose (that is, overlay) new information and structures (such as annotations) on parts (such as sub-documents) of existing base information (BI). In this setting, SA developers and users work with bi-level information, a combination of the superimposed information and the referenced BI parts. We have designed a framework to assist SAs in the following bi-level-information-management activities: representation, access, transformation, and interchange. This framework defines the abstraction context agent to activate any BI part and to retrieve information from the context of the part. It includes means to represent and access bi-level information in a conceptual model (the Entity-Relationship model augmented with relationship patterns), the relational model, the XML model, and an object model. It defines a mechanism to transform bi-level information to alternative forms using queries expressed in existing query languages and executed by existing query processors. It also includes a formal model to improve the expression and execution of certain classes of queries. Finally, the framework employs the notion of SI dependency graphs to facilitate interchanging of bi-level information among SA users. Specifically for the XML model, the framework defines Sixml, an XML markup language to represent bi-level information; Sixml DOM, an extension of the XML Document Object Model (DOM) to efficiently manipulate Sixml documents at run time; and Sixml Navigator, an alternative path navigator that improves both query expression and execution. Using our framework, an SA can reference heterogeneous BI parts in situ, allowing multiple simultaneous organizations of the same BI parts, while preserving their original context. Also, the SA developer may employ the data model and schema that is appropriate for each SA. We have evaluated each framework component using a method appropriate for the component. For example, we have implemented the context-agent abstraction to reference BI parts of the following types: Microsoft Word, Excel, and PowerPoint; XML, HTML, PDF, audio, and video. We have built six SAs that employ distinct schemas (in different data models). We have implemented the design of Sixml DOM and Sixml Navigator, used them with existing query processors, and experimentally evaluated the implementations' performance. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
An image analysis pipeline for the semi-automated analysis of clinical fMRI images based on freely available software
Authors: Christof Karmonik, Michele York, Robert Grossman, Ekta Kakkar, Krutina Patel, Hani Haykal, David King
Venue: Computers in Biology and Medicine (2010)

The technique of functional Magnetic Resonance Imaging (fMRI) has evolved in the last 15 years from a research concept into a clinically relevant medical procedure. In this study, an efficient, semi-automated and cost-effective solution for the analysis of fMRI images acquired in a clinical setting is presented relying heavily on open source software. The core of the pipeline is the software Analysis of Functional NeuroImages (AFNI, National Institute of Mental Health (NIMH)) combined with K-PACS and ImageJ. Its application is illustrated with clinical fMRI exams and with a research study involving comparing subjects diagnosed with Parkinson's disease and age-matched controls.
A nice attempt
Authors: Katherine Heit
Venue: ACM SIGCAS Computers and Society (2010)

Throughout history, one focus of society has been expanding and educating its less fortunate or less advanced. This has not change in the twenty-first century. It seems to be a topic in every political election: what are you going to do to help the poor? What are you going to do to help the poor in other countries? The mistreatment of others is all over the media. It fills the home and the head. The squalor of poorer countries is featured on the nightly news. People typically say, send food. Send medicine. One man had a different idea. Send education in the form of inexpensive laptops.
Differently implicational universal triple I method of (1, 2, 2) type
Authors: Yi-Ming Tang, Xiao-Ping Liu
Venue: Computers Mathematics with Applications (2010)

As a generalization of the triple I method, differently implicational universal triple I method of (1, 2, 2) type (universal triple I method for short) is investigated. First, the concepts of residual operators and strongly residual operators are given, and then related conclusions of residual pairs are provided. Second, the related universal triple I solutions (including FMP-solutions, FMT-solutions and so on) are strictly defined by the infimum, where such solutions are divided into two parts respectively corresponding to the minimum and infimum. Then, we put emphasis on the FMP-solutions, in which the unified forms of FMP-solutions w.r.t. strongly residual operators and a new idea for getting FMP-solutions w.r.t. infimum are achieved. Third, as a result of analyzing the logic basis of a sort of CRI (Compositional Rule of Inference) method, it is found that their CRI solutions can be regarded as special cases of FMP-solutions. Lastly, the response functions of fuzzy systems via universal triple I method are discussed, which demonstrates that the universal triple I method can provide bigger choosing space and get better fuzzy controllers by contrast with the triple I method and CRI method.
A new adaptive layered multicast protocol
Authors: K. Papazis, N. K. Chilamkurti, B. Soh
Venue: International Journal of Computers and Applications (2008)

The popularity of real-time audio and video streaming applications on the Internet has burdened the congestion control mechanisms and highlighted the fairness concerns with misbehaving flows. Packet Pair Layered Multicast (PLM) protocol is based on cumulative layered multicasting that enables the bottleneck bandwidth to be inferred by the use of a packet pair mechanism. Increased complexity in PLM might hinder the deployment of the protocol in the wider network. This is due to the increased state stored in network routers and the propagation of dual packets in the network. In this paper, we discuss the development of the Adaptive Layered Multicast protocol to regulate and distribute available bandwidth to heterogeneous receivers without the complexities associated with PLM.
Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental analysis of power
Authors: Salvador García, Alberto Fernández, Julián Luengo, Francisco Herrera
Venue: Information Sciences: an International Journal (2010)

Experimental analysis of the performance of a proposed method is a crucial and necessary task in an investigation. In this paper, we focus on the use of nonparametric statistical inference for analyzing the results obtained in an experiment design in the field of computational intelligence. We present a case study which involves a set of techniques in classification tasks and we study a set of nonparametric procedures useful to analyze the behavior of a method with respect to a set of algorithms, such as the framework in which a new proposal is developed. Particularly, we discuss some basic and advanced nonparametric approaches which improve the results offered by the Friedman test in some circumstances. A set of post hoc procedures for multiple comparisons is presented together with the computation of adjusted p-values. We also perform an experimental analysis for comparing their power, with the objective of detecting the advantages and disadvantages of the statistical tests described. We found that some aspects such as the number of algorithms, number of data sets and differences in performance offered by the control method are very influential in the statistical tests studied. Our final goal is to offer a complete guideline for the use of nonparametric statistical procedures for performing multiple comparisons in experimental studies.
Brief paper: Interval observer design for consistency checks of nonlinear continuous-time systems
Authors: Tarek Raïssi, Gaétan Videau, Ali Zolghadri
Venue: Automatica (Journal of IFAC) (2010)

This paper deals with fault detection for nonlinear continuous-time systems. A procedure based on interval analysis is proposed to build a guaranteed qLPV (quasi-Linear Parameter-Varying) approximation of the nonlinear model. The interval qLPV approximation makes it possible to derive two point observers which estimate respectively the lower and the upper bound of the state vector using cooperativity theory. A set guaranteed to contain the actual value of the residual is then designed. The modelling uncertainties and measurement errors are taken into account at the design stage. The proposed methodology is illustrated through numerical simulations.
Technical communique: A note on the differential regulator equation for non-minimum phase linear systems with time-varying exosystems
Authors: Hyungbo Shim, Jung-Su Kim, Hongkeun Kim, Juhoon Back
Venue: Automatica (Journal of IFAC) (2010)

Some control problems in practice are often formulated as a linear output regulation problem with time-varying exosystems. Although this problem has been studied recently, an explicit and constructive solution has been given only for minimum phase systems. This paper presents a solution for non-minimum phase systems whose zero dynamics is hyperbolic (or has an exponentially dichotomic split in the case of time-varying zero dynamics). The idea is inspired by the non-causal stable inversion.
Simultaneous and proportional bandwidth, delay, and loss differentiation
Authors: M. Selvaraj, G. Y. Lazarou, R. Hu
Venue: International Journal of Computers and Applications (2008)

A robust adaptive scheduler for proportional delay differentiation services is presented. Proportional services are further policed by a class-based packet dropper. Our proposed combination of the adaptive scheduler and the packet dropper treats the traffic classes proportionally in terms of three quality of service (QoS) metrics: bandwidth, delay, and packet loss, simultaneously. Traffic types used to study the performance of the scheme ranges from ordinary FTP data to bursty Pareto traffic. Numerical results validate our claim that regardless of the network traffic characteristics, especially burstiness, the adaptive delay scheduler combined with the packet dropper can effectively differentiate services in terms of delay, bandwidth, and loss simultaneously. In addition, our proposed scheme showed on an average 11% improvement in performance when compared to the scheme proposed in C. Dovrolis, D. Stiliadis, & P. Ramanathan, Proportional differentiated services: Delay differentiation and packet scheduling, IEEE/ACM Transactions on Networking, 10(1), 2002, 12--26.
Structural and semantic aspects of similarity of Document Type Definitions and XML schemas
Authors: Aleš Wojnar, Irena Mlýnková, Jiří Dokulil
Venue: Information Sciences: an International Journal (2010)

The natural optimization strategy for XML-to-relational mapping methods is exploitation of similarity of XML data. However, none of the current similarity evaluation approaches is suitable for this purpose. While the key emphasis is currently put on semantic similarity of XML data, the main aspect of XML-to-relational mapping methods is analysis of their structure. In this paper we propose an approach that utilizes a verified strategy for structural similarity evaluation - tree edit distance - to DTD constructs. This approach is able to cope with the fact that DTDs involve several types of nodes and can form general graphs. In addition, it is optimized for the specific features of XML data and, if required, it enables one to exploit the semantics of element/attribute names. Using a set of experiments we show the impact of these extensions on similarity evaluation. And, finally, we discuss how this approach can be extended for XSDs, which involve plenty of ''syntactic sugar'', i.e. constructs that are structurally or semantically equivalent.
Scenario analysis using Bayesian networks: A case study in energy sector
Authors: Didem Cinar, Gulgun Kayakutlu
Venue: Knowledge-Based Systems (2010)

This paper provides a general overview of creating scenarios for energy policies using Bayesian Network (BN) models. BN is a useful tool to analyze the complex structures, which allows observation of the current structure and basic consequences of any strategic change. This research will propose a decision model that will support the researchers in forecasting and scenario analysis fields. The proposed model will be implemented in a case study for Turkey. The choice of the case is based on complexities of a renewable energy resource rich country. Turkey is a heavy energy importer discussing new investments. Domestic resources could be evaluated under different scenarios aiming the sustainability. Achievements of this study will open a new vision for the decision makers in energy sector.
A multilingual ontology framework for R&D project management systems
Authors: Ou Liu, Jian Ma
Venue: Expert Systems with Applications: An International Journal (2010)

R&D project management systems are developed to facilitate the efficient management of R&D projects in government-funding agencies and universities. They should support R&D information sharing among researchers and research administrators from different nationalities using different languages. This paper presents an ontology-based methodology to the development of R&D project management systems with multilingual supports. In particular, a multilingual ontology is proposed, which consists of domain model, application model, user model and linguistic model. The methodology is used in the development of an R&D project management system for the Innovation and Technology Commission of the Hong Kong SAR Government. The system supports three languages and facilitates R&D information sharing among users with different culture backgrounds and usage preferences.
Electricity market analysis with co-evolutionary computation
Authors: Kit Po Wong
Venue:  (2009)

Many techniques, such as empirical analysis, agents-based simulation, iterative Nash Equilibrium (NE) search algorithms and complementarity program methods, have been utilized to determine the power market equilibrium. Despite of the previous efforts, no method is widely recognized as being an effective method for market equilibrium determination. Hence there is an urgent need to develop an effective and powerful approach for power market analysis and equilibrium determination. Co-evolutionary computation has been used as a new methodology to market simulation and determine market equilibrium recently. The thesis applies co-evolutionary genetic algorithms (CGA) to solve the power market equilibrium and to study several important issues in power market analysis. The first issue is using the CGA to determine the market equilibrium with transmission constraints and generation capacity constraints. The existence or non-existence of the NE due to the transmission and generation capacity constraints are illustrated using a 2-bus test system and the IEEE 30-bus system. The effects of different parameters settings of the LSFE model on the equilibria are also studied and compared with those found based on the Cournot model. The second issue is to study a multiple pricing periods market with inter-temporal constraints and to make the simulation results comparable to actual market settings. The market outcome of a GenCo using a constant supply function across multiple pricing periods is contrasted and discussed with the case that GenCos using a specified supply function in each pricing period. The third issue of whether GenCos would voluntarily enter forward markets or not is examined and the factors which could affect the bidding behavior are studied. The LSFE model and Cournot model are used to model strategic bidding for the spot market, while the forward market is modeled by the Cournot model. GenCos' bidding behaviors are analyzed by CGA and two numerical examples are used to verify the theoretical analysis. From the works undertaken in this thesis, it is found that the CGA method is robust and flexible and has the potential to be used to solve the complicated equilibrium problems in real-world electricity markets. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Near-optimal solutions for the generalized max-controlled set problem
Authors: Ivairton M. Santos, Carlos A. Martinhon, Luiz S. Ochi
Venue: Computers and Operations Research (2010)

In this work we deal with sandwich graphs G=(V,E) and present the notion of vertices f-controlled by a subset M@?V. We introduce the generalized max-controlled set problem (GMCSP), where minimum gaps (defined by function f) and positive weights are associated to each vertex of V. In this case, the objective is to find a sandwich graph G in order to maximize the sum of the weights associated to all vertices f-controlled by M. We present a 12-approximation algorithm for the GMCSP and a new procedure for finding feasible solutions based on a linear relaxation. These solutions are then used as starting point in a local search procedure (Tabu Search with Path Relinking) looking for solutions of better quality. Finally, we present some computational results and compare our heuristics with the optimum solution value obtained for some instances of the problem.