ppxscal/embedding_network huggingface dataset:
FEW-PNets - A framework for emulation of wireless personal networks
Authors: R. Venkatesha Prasad, Yonghua Li, Martin Jacobsson, Anthony Lo, Ignas Niemegeers
Venue: Proceedings of the 2008 International Symposium on a World of Wireless, Mobile and Multimedia Networks (2008)

With the advent of miniaturization and higher computing capabilities of wireless devices, there is an exponential rise in the number of devices such as personal digital assistants, etc. Application development for these devices is the main focus for many device manufacturers and software developers. The applications developed need to be tested and tried before releasing it to the market. There are cross-compilers to produce the binary files of the software applications that can run on these devices. However, it is rather difficult for developers to test it on the actual devices every time a change is made in the program. Further, a wireless network infrastructure should also be in place for testing. To expedite application development FEW-PNets — a Framework for Emulation of Wireless Personal Networks is proposed. It is a networked application to emulate a Personal Network (PN) owned by a person. It supports emulation of the most functions of PNs. We explain our model by emulating simple PN devices. In this article we elucidate the concepts, advantages, application domains and limitations of FEW-PNets.
On Bernstein-Markov-type inequalities for multivariate polynomials in Lq-norm
Authors: András Kroó
Venue: Journal of Approximation Theory (2009)

Bernstein-Markov-type inequalities provide estimates for the norms of derivatives of algebraic and trigonometric polynomials. They play an important role in Approximation Theory since they are widely used for verifying inverse theorems of approximation. In the past decades these inequalities were extended to the multivariate setting, but the main emphasis so far was on the uniform norm. It is considerably harder to derive Bernstein-Markov-type inequalities in the L"q-norm, and it requires introduction of new methods. In this paper we verify certain Bernstein-Markov-type inequalities in L"q-norm on convex and star-like domains. Special attention is given to the question of how the geometry of the domain affects the corresponding estimates.
Multi-objective evolutionary optimization of polynomial neural networks for modelling and prediction of explosive cutting process
Authors: A. Jamali, N. Nariman-zadeh, A. Darvizeh, A. Masoumi, S. Hamrang
Venue: Engineering Applications of Artificial Intelligence (2009)

In this paper, evolutionary algorithms (EAs) are deployed for multi-objective Pareto optimal design of group method of data handling (GMDH)-type neural networks which have been used for modelling an explosive cutting process using some input-output experimental data. In this way, multi-objective EAs (non-dominated sorting genetic algorithm, NSGA-II) with a new diversity-preserving mechanism are used for Pareto optimization of such GMDH-type neural networks. The important conflicting objectives of GMDH-type neural networks that are considered in this work are, namely, training error (TE), prediction error (PE), and number of neurons (N) of such neural networks. Different pairs of theses objective functions are selected for 2-objective optimization processes. Therefore, optimal Pareto fronts of such models are obtained in each case which exhibit the trade-off between the corresponding pair of conflicting objectives and, thus, provide different non-dominated optimal choices of GMDH-type neural networks models for explosive cutting process. Moreover, all the three objectives are considered in a 3-objective optimization process, which consequently leads to some more non-dominated choices of GMDH-type models representing the trade-offs among the training error, prediction error, and number of neurons (complexity of network), simultaneously. The overlay graphs of these Pareto fronts also reveal that the 3-objective results include those of the 2-objective results and, thus, provide more optimal choices for the multi-objective design of GMDH-type neural networks in terms of minimum training error, minimum prediction error, and minimum complexity.
iCAAS: interoperable and configurable architecture for accessing sensor networks
Authors: Marcello Cinque, Catello Di Martino, Alessandro Testa
Venue: Proceedings of the 3rd international workshop on Adaptive and dependable mobile ubiquitous systems (2009)

The increasing use of wireless sensor networks (WSNs) calls for solutions for mastering the complexity due to WSN heterogeneity and differentiated user needs. This paper presents an architecture, named iCAAS, designed to collect, to store, to manage and to make available to users data received from heterogeneous WSNs. The aim of the architecture is to adaptively deliver data to users depending on their specific interests and irrespective of adopted terminals (e.g., mobile device, workstation, ...) and of sensor networks details. The contribution of the paper is twofold. First we detail the requirements that these types of architectures should meet to fill the gap between sensors details and users needs. Second, we describe the structural organization of the proposed architecture, designed by taking into account the defined requirements. Implementation details and case studies are also provided, showing the effectiveness of the architecture when used in real world application scenarios.
6-dof parallel manipulators with better dexterity, rotatability, or singularity-free workspace
Authors: K. y. Tsai, T. k. Lee
Venue: Robotica (2009)

Isotropic manipulators are generally considered as designs with optimum dexterity. Currently, many 6-DOF (degrees-of-freedom) isotropic parallel manipulators can be developed by numerical or analytical methods. At an isotropic configuration, a manipulator is equidistant from its neighboring singular points. The distance, however, can be very small, so an isotropic design might have relatively smaller singularity-free workspace. This paper presents methods to develop traditional 6-DOF parallel manipulators with better dexterity and larger singularity-free workspace. Some fully symmetric nontraditional designs are then proposed. The evaluation of kinematic properties shows that the fully symmetric designs have very good global dexterity, better rotatability, and relatively larger singularity-free workspace. The manipulators are suitable for some special tasks requiring higher precision, better rotatability, or larger workspace.
Abductive Logic Programming in the Clinical Management of HIV/AIDS
Authors: Oliver Ray, Athos Antoniades, Antonis Kakas, Ioannis Demetriades
Venue: Proceeding of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy (2006)

This paper presents a new Abductive Logic Programming (ALP) approach for assisting clinicians in the selection of antiretroviral drugs for patients infected with Human Immunodeficiency Virus (HIV). The approach is comparable to laboratory genotypic resistance testing in that it aims to determine which viral mutations a patient is carrying and predict which drugs they are most likely resistant to. But, instead of genetically analysing samples of the virus taken from patients --which is not always practicable --our approach infers likely mutations using the patient's full clinical history and a model of drug resistance maintained by a leading HIV research agency. Unlike previous applications of abduction, our approach does not attempt to find the “best” explanations, as we can never be absolutely sure which mutations a patient is carrying. Rather, the intrinsic uncertainty of this domain means that multiple alternative explanations are inevitable and we must seek ways to extract useful information from them. The computational and pragmatic issues raised by this approach have led us to develop a new ALP methodology for handling numerous explanations and for drawing predictions with associated levels of confidence. We present our in-Silico Sequencing System (iS3) for reasoning about HIV drug resistance as a concrete example of this approach.
Exploring Java software vocabulary: A search and mining perspective
Authors: Erik Linstead, Lindsey Hughes, Cristina Lopes, Pierre Baldi
Venue: Proceedings of the 2009 ICSE Workshop on Search-Driven Development-Users, Infrastructure, Tools and Evaluation (2009)

We conduct a large-scale analysis of Java source code vocabulary for 12,151 open source projects from Source-Forge and Apache, a corpus substantially larger than considered previously. Simple statistical analysis demonstrates robust power-law behavior for word count distributions across multiple program entities. We then identify salient vocabulary trends for classes, interfaces, methods, and fields. Our results provide low-level insight into the vocabulary space governing Java software development, with direct application to program comprehension and software search. Supplementary material may be found at: http://sourcerer.ics.uci.edu/suite2009/suite.html.
Linking the Gene Ontology with Social Ontology: A Prolegomena to the Ontology of Personhood
Authors: David R. Koepsell
Venue: Proceeding of the 2006 conference on Formal Ontology in Information Systems: Proceedings of the Fourth International Conference (FOIS 2006) (2006)

The Gene Ontology captures information at a very small scale, namely: molecular function, biological process, and cellular components. At this level, the Gene Ontology project should be capable of developing a semantics for every relation of genomic data to protein synthesis to the biological processes that result. In essence, the Gene Ontology should be able to describe the complete biomechanical functioning of an organism. But what of the social ontological statuses of organisms, and the relations of individuals to their higher level functions? Can the Gene Ontology account for higher level activities of an organism (such as intentionality, rights, property relations, etc)? Without leaping to conclusions about whether higher level functions are in fact naturalistically based, we should develop a semantics to serve as a hypothetical bridge should genomics lead us in that direction.
GLM and SVM analyses of neural response to tonal and atonal stimuli: new techniques and a comparison
Authors: Simon Durrant, David R. Hardoon, Andre Brechmann, John Shawe-Taylor, Eduardo R. Miranda, Henning Scheich
Venue: Connection Science (2009)

This paper gives both general linear model (GLM) and support vector machine (SVM) analyses of an experiment concerned with tonality in music. The two forms of analysis are both contrasted and used to complement each other, and a new technique employing the GLM as a pre-processing step for the SVM is presented. The SVM is given the task of classifying the stimulus conditions (tonal or atonal) on the basis of the blood oxygen level-dependent signal of novel data, and the prediction performance is evaluated. In addition, a more detailed assessment of the SVM performance is given in a comparison of the similarity in the identification of voxels relevant to the classification of the SVM and a GLM. A high level of similarity between SVM weight and GLM t-maps demonstrate that the SVM is successfully identifying relevant voxels, and it is this that allows it to perform well in the classification task in spite of very noisy data and stimuli that involve higher-order cognitive functions and considerably inter-subject variation in neural response.
Improving adjustable autonomy strategies for time-critical domains
Authors: Nathan Schurr, Janusz Marecki, Milind Tambe
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1 (2009)

As agents begin to perform complex tasks alongside humans as collaborative teammates, it becomes crucial that the resulting human-multiagent teams adapt to time-critical domains. In such domains, adjustable autonomy has proven useful by allowing for a dynamic transfer of control of decision making between human and agents. However, existing adjustable autonomy algorithms commonly discretize time, which not only results in high algorithm runtimes but also translates into inaccurate transfer of control policies. In addition, existing techniques fail to address decision making inconsistencies often encountered in human multiagent decision making. To address these limitations, we present novel approach for Resolving Inconsistencies in Adjustable Autonomy in Continuous Time (RIAACT) that makes three contributions: First, we apply continuous time planning paradigm to adjustable autonomy, resulting in high-accuracy transfer of control policies. Second, our new adjustable autonomy framework both models and plans for the resolving of inconsistencies between human and agent decisions. Third, we introduce a new model, Interruptible Action Time-dependent Markov Decision Problem (IA-TMDP), which allows for actions to be interrupted at any point in continuous time. We show how to solve IA-TMDPs efficiently and leverage them to plan for the resolving of inconsistencies in RIAACT. Furthermore, these contributions have been realized and evaluated in a complex disaster response simulation system.
Emission load estimation and modeling in relation to the real input traffic data
Authors: Pavel Hrubeš, Přemysl Derbek
Venue: Proceedings of the 2009 Euro American Conference on Telematics and Information Systems: New Opportunities to increase Digital Citizenship (2009)

The paper presents a model of the emission load in the vicinity of a monitored road in relation to the real traffic input data. It describes a simple method of the emission load estimating. In Addition to the modeling method itself, the paper describes particular methodologies of the real data conversion and processing. Discussed are traffic intensities of the heavy trucks over 12 tons of weight. The model uses as its input real traffic data files from intelligent traffic systems (ITS) localized by the monitored roads. More specifically, data from selected highway toll gates were used in this work. At the end, particular and final, results are presented in graphs as examples.
PKI Challenges: An Industry Analysis
Authors: Geraint Price
Venue: Proceeding of the 2005 conference on Applied Public Key Infrastructure: 4th International Workshop: IWAP 2005 (2005)

In this paper we categorise some of the challenges facing those building, deploying and using Public Key Infrastructures (PKIs). Our work is based upon a series of in-depth interviews and analysis. The aim of the work in this paper is twofold: to present the conclusions drawn from work that is based on years of practical experience of those in the field; to analyse those conclusions in order to highlight research avenues that will answer the challenges raised by those in industry.
Current Issues in Knowledge Management
Authors: Murray E. Jennex
Venue:  (2007)

As global enterprise grows increasingly reliant on electronic data, processes, and procedures, studies of the management of organizational knowledge are emergin at the forefront of critical research. Current Issues in Knowledge Management combines cutting-edge research on the cultural, technical, organizational, and human issues surrounding the creation, capture, transfer, and use of knowledge in todays organizations. Providing foremost information on topics such as organizational memory, knowledge management in enterprises, enablers and inhibitors of knowledge sharing and transfer, and emerging technologies of knowledge management, this estimable reference offers vital research information to practitioners and scholars in a variety of settings.
Concurrent Engineering and the Dynaxity Approach. How to Benefit from Multidisciplinarity
Authors: Tom Tiltmann, Uschi Rick, Klaus Henning
Venue: Proceeding of the 2006 conference on Leading the Web in Concurrent Engineering: Next Generation Concurrent Engineering (2006)

Some authors (i.e. [1]) claim for an appropriate organisational realisation of concurrent engineering. As the pressure to realise and maintain competitiveness in turbulent environments grows, organisations need processes and methods to deal with this challenging situation. This paper will examine the complexity in today's software development processes and present ways to cope with it. For that purpose, approaches of different disciplines are presented: concurrent engineering, multidisciplinarity and the dynaxity approach that categorises the behaviour of organisations into four zones. An approach will then be proposed that combines these three elements. It will be revealed by the example of a network project KONVOI in order to prove that this approach succeeds in turbulent environments.
Complex systems modelling by rule based networks
Authors: Alexander Gegov
Venue: Proceedings of the 8th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases (2009)

A rule based system is a 'black box' model in the form of a single large rule base which does not take into account any interconnections in a complex process. As opposed to this, a rule based network is a 'white box' model in the form of multiple smaller rule bases which takes into account all interconnections. This paper introduces briefly the foundations of rule based networks including formal models, basic operations, structural properties and advanced operations. It also highlights feedforward and feedback rule based networks. Finally, a comparative evaluation of rule based networks in relation to rule based systems is presented.
Research on SSVEP-Based Controlling System of Multi-DoF Manipulator
Authors: Hui Shen, Li Zhao, Yan Bian, Longteng Xiao
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III (2009)

Steady State Visual Evoked Potential (SSVEP) rapidly becomes a practical signal of brain-computer interface system due to the advantage of high transmission rate and short training time. A SSVEP-Based controlling system of multi-dof manipulator is presented in this paper on the basis of virtual instruments. In this system, the ssvep-based electroencephalogram(EEG) was derived from scalp and then translated to several controlling commands of manipulator. In order to improve the performance of the system, the wavelet transform and Short-time Fourier Transform were used in signal processing. The experiment results have proved the effectiveness of the proposed method. The realization of the system can provide a new way to the using of robot-assisted in space based on BCI.
Discrimination of myocardial infarction stages by subjective feature extraction
Authors: Dingfei Ge, Lihui Sun, Jiayin Zhou, Yuquan Shao
Venue: Computer Methods and Programs in Biomedicine (2009)

Lots of studies on myocardial infarction (MI) computer assisted diagnosis are based on certain important ECG components which only account for local information. 12-Lead ECG signals which were regarded as hyper-dimensional time-series data were utilized to extract features from global information in this study. Existing feature extraction techniques for classification attempt to classify all the classes included. However sometimes it is more important to better recognize certain specific classes rather than to discriminate all the classes. A feature extraction method based on subjective-classification was proposed to discriminate the specific classes, which the classification priority was given subjectively, and each of the other classes was separated at the same time. The method includes data reduction by principal component analysis (PCA), data normalization by whitening transformation and derivation of projecting vectors for subjective-classification, etc. The data in the analysis were collected from PTB diagnostic ECG database. The results show that the proposed method can obtain a small number of effective features from 12-lead ECGs to better classify classes with priority, and the other classes can be classified at the same time.
Reversible Data Hiding Based on Three-Circular-Pixel Difference Expansion
Authors: Ching-Chiuan Lin, Shun-Ping Yang, Nien-Lin Hsueh
Venue: Fundamenta Informaticae (2009)

This paper proposes a reversible data hiding scheme based on three-circular-pixel (TCP) difference expansion. To embed a message in an image, the image is divided into three-pixel blocks, each of which is, then, transformed into a TCP block with two differences. When the pixel value of the largest pixel in the TCP block is increased, two differences are increased - one is between the largest and the smallest, and the other is between the largest and the middle. Expanding the two differences in the block by increasing the largest pixel value may make the image less modified. In addition, the number of pixel pairs is increased to two thirds of the number of pixels in the image. Compared to Tian's study, both the visual quality and the embedding capacity of the image are significantly improved.
Feature set selection in data mining techniques for unknown virus detection: a comparison study
Authors: Jianyong Dai, Ratan Guha, Joohan Lee
Venue: Proceedings of the 5th Annual Workshop on Cyber Security and Information Intelligence Research: Cyber Security and Information Intelligence Challenges and Strategies (2009)

Detecting unknown viruses is a challenging research topic. Data mining approaches have been used to detect unknown viruses. The key to data mining lies on the feature set to be used. There are several different approaches have been tried before, simple heuristics, static features and dynamic features. In this paper, we present several different data mining approaches and compare the result of these approaches.
Towards Software Development Methodology for Web Services
Authors: George Feuerlicht, Sooksathit Meesathit
Venue: Proceeding of the 2005 conference on New Trends in Software Methodologies, Tools and Techniques: Proceedings of the fourth SoMeT_W05 (2005)

The emergence of Web services represents a shift from component-based architectures that have proved successful in the context of enterprise computing to service-oriented architectures that are more suited to the highly distributed Internet-based applications. This trend towards service-oriented computing necessitates the re-evaluation of software development methodologies that are used in the construction of distributed applications. With growing acceptance of service-oriented computing and increasing number of large-scale Web Services projects there is some evidence that practitioners involved in implementing these solutions are paying only limited attention to how such applications should be designed. Frequently, the design of Web Services applications is driven by performance and scalability considerations, rather than any sound software engineering principles. A comprehensive methodological framework is required to guide designers and developers of service-oriented applications through the various phases of software development life cycle with specific emphasis on producing stable, reusable and extendable services. In this paper we discuss design of service-oriented applications from a software engineering perspective, and propose a software development framework for Web Services based on identification of elementary business function using business function decomposition and mapping these functions to service operations. We apply interface design principles adapted from object-oriented design as guidelines for the design of services.