ppxscal/embedding_network huggingface dataset:
User Care Preference-Based Semantic Service Discovery in a Ubiquitous Environment
Authors: Dongpil Kwak, Joongsoo Lee, Dohyun Kim, Younghee Lee
Venue: Proceedings of the 35th Conference on Current Trends in Theory and Practice of Computer Science (2009)

Each service that the event like "alarming" needs for noticing a user is respectively differenly accepted to a user. This paper introduces a user care preference model for describing the user's condition. This model is used to discover the best service based on the current user's condition and the kind of functionality available services support.The entire process of service discovery is explained on the specific case of monitoring the user's current health via sensors and selecting appropriate service according to the health condition.(e.g. radio should be used instead of TV, if the user has problems with sight). And a systematic matching design to measure the relativity between user's condition and service is proposed. Our approach helps service discovery using the context incorporating user condition to represent user's intention and sensitivity richer.
Reconfiguration of Vibro-tactile Feedback Based on Drivers' Sitting Attitude
Authors: Andreas Riener, Alois Ferscha
Venue: Proceedings of the 2009 Second International Conferences on Advances in Computer-Human Interactions (2009)

The today mainly incorporated sensory modalities vision and hearing are most often highly charged due to an increasing number, as well as a rising complexity of diversified assistance systems in vehicles. These systems, originally developed for "supporting" the driver in its tasks, increasingly directs to operation errors caused by cognitive overload. The sense of touch – as additional interaction channel – should have the ability to release cognitive load from visual and auditory channels by adapting in a natural, intuitive and non-distracting manner. A drawback of haptics is that feedback is reliant to both driver and environmental conditions. For instance, different sizes and weights of drivers' result in a changed haptic perceptivity, and vibro-tactile feedback potentially is interpreted erroneous due to personal sitting attitudes. A vibro-tactile seat, endowed with a set of unobtrusive embedded sensors and actuators, is proposed to counter action these issues. The input channel is used for determining the occupied seating surface and, in addition, is also responsible for observing disruptive vibrations, originating in the environment. These information is employed in order to reconfigure vibro-tactile output dynamically with the aim to guarantee consistent haptic perception for any person.
Rethinking Commonsense Psychology: A Critique of Folk Psychology, Theory of Mind and Simulation (New Directions in Philosophy and Cognitive Science), Reprint edition
Authors: Matthew Ratcliffe
Venue:  (2008)

This book offers arguments against the view that interpersonal understanding involves a "folk" or "commonsense" psychology, a view which Ratcliffe suggests is a theoretically motivated abstraction. His alternative account draws on phenomenology, neuroscience and developmental psychology, exploring patterned interactions in shared social situations.
Contory: a middleware for the provisioning of context information on smart phones
Authors: Oriana Riva
Venue: Proceedings of the ACM/IFIP/USENIX 2006 International Conference on Middleware (2006)

Context-awareness can serve to make ubiquitous applications deployed for mobile devices adaptive, personalized, and accessible in dynamically changing environments. Unfortunately, existing approaches for the provisioning of context information in ubiquitous computing environments rarely take into consideration the resource constraints of mobile devices and the uncertain availability of sensors and service infrastructures. This paper presents the design, prototype implementation, and experimental evaluation of Contory, a middleware specifically designed to accomplish efficient context provisioning on mobile devices. To make context provisioning flexible and adaptive based on dynamic operating conditions, Contory integrates multiple context provisioning strategies, namely internal sensors-based, external infrastructure-based, and distributed provisioning in ad hoc networks. Applications can request context information provided by Contory using a declarative query language which features on-demand, periodic, and event-based context queries. Experimental results obtained in a testbed of smart phones demonstrate the feasibility of our approach and quantify the cost of supporting context provisioning in terms of energy consumption.
Implementation Technique of Unrestricted LL Action Grammar
Authors: Jing Zhang, Ying Jin
Venue: Proceedings of the 2009 International Conference on Computer Engineering and Technology - Volume 01 (2009)

Action Grammar is a grammar with action symbols appearing in the right part of production rules, which can be used to implement semantic analyzer automatically. An action symbol represents the name of a semantic routine. Implementation of action grammar relies on specific parsing methods, such as LL(K), recursive-descent or LR, and so on. However, these parsing methods have their own restrictions on grammars, therefore, in order to accomplish these parsing methods certain equivalent transformations have been done to make the grammars meet the restrictions. This paper has proposed an implementation technique of LL action grammar, which requires no transformation to the original grammar. Our approach includes following steps: parsing the input string with back-tracking and producing the parsing paths for each non-terminal symbol, then constructing LL parsing table with the parsing paths obtained, finally conducting semantic analysis with LL parsing table. The main contribution of this paper is that non-backtracking semantic analyzer has been achieved without making any transformations to the grammar.
Creating operation method patterns for automating information system operations
Authors: Matsuki Yoshino, Norihisa Komoda, Michiko Oba
Venue: Proceedings of the 8th conference on Applied computer scince (2008)

The authors propose operation patterns based upon analysis of operations conducted in data centers for system management. The feasibility of the automated operations is analyzed for each pattern. The correlations between operation patterns and the objectives of operations are also analyzed.
Capture Properties of the Generalized CMA in Alpha-Stable Noise Environment
Authors: Hong Tang, Tianshuang Qiu, Ting Li
Venue: Wireless Personal Communications: An International Journal (2009)

Constant modulus algorithm (CMA) is an adaptive technique for correcting multipath and interference-induced degradations in constant envelope waveforms. The algorithm exploits the fact that both multipath and additive interference can disrupt the constant envelope of the received signal. By detecting the received envelope variations, the adaptive algorithm has the ability to reset the coefficients vector so as to remove the variations, and in the process, reject the various interference components from the desired signal. If both the interferer and the signal of interest have constant envelope and are spectrally non-overlapped, it is possible to find two different solutions for the coefficient vector, in which one suppresses the interferer and the other "captures" the interferer. The problem of how "capture" can occur and how it may be prevented in Gaussian noise environment has been perfectly developed in the previous work (Treichler, Larimore, IEEE Trans Acoust Speech Signal Process, 33:946---958, 1985). However, recent investigation on the physical channels in wireless communication shows that there is aggregate noise component exhibiting high amplitudes for small duration time interval. This paper proposes a GCMA (Generalized CMA) which generalizes the CMA by introducing the &alpha;-stable distribution as the noise model. Here the original CMA is only a special case of the GCMA. In order to describe the average behavior of the GCMA, a simple model consisting of only two sinusoids is presented. As assuming slow adaptation, the adaptive weight recursion is shown to compress into a two-by-two recursion in the tone output amplitudes. The simplified recursion is analyzed to determine what combination of signals power and initialization on coefficient vectors leads to "lock" and what leads to the capture of the interferer. The method to determine lock and capture zone boundaries is analyzed. These convergence properties of the GCMA are studied by computer simulations.
Adaptive moment-of-fluid method
Authors: Hyung Taek Ahn, Mikhail Shashkov
Venue: Journal of Computational Physics (2009)

A novel adaptive mesh refinement (AMR) strategy based on the moment-of-fluid (MOF) method for volume-tracking of evolving interfaces is presented. Moment-of-fluid method is a new interface reconstruction and volume advection method using volume fractions as well as material centroids. The mesh refinement criterion is based on the deviation of the actual centroid obtained by interface reconstruction from the reference centroid given by moment advection process. The centroid error indicator detects not only high curvature regions but also regions with complicated subcell structures like filaments. A new Lagrange+remap scheme is presented for advecting moments, which includes Lagrangian backtracking, polygon intersection-based remapping and forward tracking to define the material centroid. The effectiveness and efficiency of AMR-MOF method is demonstrated with classical test problems, such as Zalesak's disk and reversible vortex problem. The comparison with previously published results for these problems shows the superior accuracy of the AMR-MOF method over other methods. In addition, two new test cases with severe deformation rates are introduced, namely droplet deformation and S-shape deformation problems, for further demonstration of the capabilities of the AMR-MOF method.
Sundial: Using Sunlight to Reconstruct Global Timestamps
Authors: Jayant Gupchup, Răzvan Musăloiu-E., Alex Szalay, Andreas Terzis
Venue: Proceedings of the 6th European Conference on Wireless Sensor Networks (2009)

This paper investigates postmortem timestamp reconstruction in environmental monitoring networks. In the absence of a time-synchronization protocol, these networks use multiple pairs of (local, global) timestamps to retroactively estimate the motes' clock drift and offset and thus reconstruct the measurement time series. We present Sundial, a novel offline algorithm for reconstructing global timestamps that is robust to unreliable global clock sources. Sundial reconstructs timestamps by correlating annual solar patterns with measurements provided by the motes' inexpensive light sensors. The surprising ability to accurately estimate the length of day using light intensity measurements enables Sundial to be robust to arbitrary mote clock restarts. Experimental results, based on multiple environmental network deployments spanning a period of over 2.5 years, show that Sundial achieves accuracy as high as 10 parts per million (ppm), using solar radiation readings recorded at 20 minute intervals.
Coordinating Agents Plans in Multi-Agent Systems Using Colored Petri Nets
Authors: Maryam Nooraee Abadeh, Kamran Zaminifar, Mohammad-Reza Khayyambashi
Venue: Proceedings of the 11th Pacific Rim International Conference on Multi-Agents: Intelligent Agents and Multi-Agent Systems (2008)

Applying coordination mechanisms to handle interdependencies that exist between agents in multi-agent systems (MASs), is an important issue. In this paper, two levels MAS modeling scheme and a language to describe a MAS plan based on interdependencies between agents' plans are proposed. Initially a generic study of possible interdependencies between agents in MASs is presented, followed by the formal modeling (using Colored Petri Nets) of coordination mechanisms for those dependencies. These mechanisms control the dependencies between agents to avoid unsafe interactions where individual agents' plans are merged into a global multi-agent plan. This separation, managed by the coordination mechanisms, offers more powerful modularity in MASs modeling.
Using sonification for mining time series data
Authors: Mark Last, Anna Gorelik
Venue: Proceedings of the 9th International Workshop on Multimedia Data Mining: held in conjunction with the ACM SIGKDD 2008 (2008)

In recent years, there is a growing interest in mining time series databases by both automated and interactive tools. In this paper, we present an interactive methodology for mining of time series data using a novel sonification technique which uses some important properties of time series and tonal music to achieve effective (accurate) and efficient (fast) results. We have created an experimental website, where participants were asked to perform some basic data exploration and mining tasks by listening to a musical display of several time series. The initial results indicate that the proposed methodology for musical representation of data allows, on one hand, to efficiently perform some decision-making tasks "on the fly" - by only listening to some short music examples, and on the other hand, it provides an alternative data representation for blind or visually impaired users or users who are due to their professional or personal activities (e.g., driving) cannot use their sense of vision for watching a visual display of data, but still need to get some important time-based information by using their other senses.
A Web Services Gateway for the H2O Lightweight Grid Computing Framework
Authors: Mauro Migliardi
Venue: Proceedings of the 1st European Conference on Towards a Service-Based Internet (2008)

H2O is a lightweight distributed component framework for the dynamic aggregation of software components, services and computational resources into Grid Computing Systems. H2O provides a powerful separation of roles clearly distinguishing providers of software components from provides of computational services, this model allows developers to easily design layered applications and to deploy them on top of dynamically aggregated computational nodes. The ease of use does not exact a weak security system, in fact, by combining the native Java sandbox model and the use of JAAS, H2O provides a robust security layer. Although H2O supports an extended version of Java RMI (RMIX) as its native inter-component communication language, the software components deployed inside an H2O virtual machine are exposed only as Java Objects. In this paper we present the H2O Web Services Gateway, a set of H2O software component capable of dynamically capturing the deployment of new software components into an H2O virtual machine and automatically generating and publishing the WSDL description of these components. This feature, combined with the use of the Web Services Invocation Framework, enables the automated export of software components deployed into an H2O virtual machine as Web Services and facilitates the integration of lightweight Grid application into Service Oriented Architectures.
Recognizability of multi-inkdot finite automata on four-dimensional input tapes
Authors: Yasuo Uchida, Takao Ito, Hidenobu Okabe, Makoto Sakamoto, Hiroshi Furutani, Michio Kono
Venue: Proceedings of the 12th WSEAS international conference on Computers (2008)

During the past about thirty-five years, many automata on a two- or three-dimensional input tape have been proposed and a lot of properties of such automata have been obtained. On the other hand, we think that recently, due to the advances in computer animation, motion image processing, and so forth, it is very useful for analyzing computational complexity of multi-dimensional information processing to explicate the properties of four-dimensional automata, i.e., three-dimensional automata with the time axis. In this paper, we propose a four-dimensional multi-inkdot finite automaton and mainly investigate its recognizability of four-dimensional connected pictures.
An introduction to computed chaining
Authors: Kuo-Chung Tai, Alan L. Tharp
Venue: Proceedings of the May 19-22, 1980, national computer conference (1980)

A hashing function, H(x), is a transformation from a key value x to an address. Since such transformations may produce the same address for distinct keys, hashing functions lead to collisions in the address space. Many methods for resolving hashing collisions have been reported [1, 2]. Direct chaining and open addressing are the two basic collision-resolution methods. This paper presents a form of hybrid hashing, computed chaining, which is better than a previously described hybrid hashing procedure called pseudochaining [3]. In certain situations it is also better than other collision procedures.
Research of Coal-Gas Outburst Forecasting Based on Artificial Immune Network Clustering Model
Authors: Yu Zhu, Hong Zhang, Ling-dong Kong
Venue: Proceedings of the 2009 Second International Workshop on Knowledge Discovery and Data Mining (2009)

Based on the basic theory of the representative artificial immune network model, a hierarchical clustering algorithm aiNHCA was presented. Firstly, aiNHCA generates the memory matrix and the similarity matrix of the antibodies in the aiNet method. So it can divide the data set into several sub-clusters. Then it combines the sub-clusters with higher similarities in the hierarchical clustering method and gets the final clustering result. The algorithm can be used in clustering the arbitrary shapes of data sets, and it has the advantages of fast discovering speed and high efficiency, which inherit the advantages of the immune algorithms. Using aiNHCA, the basic courses of researching on coal-gas outburst clustering of experimental samples, are analyzed based on artificial immune network model by using 5 indexes. At last, the coal-gas outburst clustering based on artificial immune network model by using synthetic index system including level, initial velocity of gas, crustal stress, comprehensive index, coal-seam thickness and tectonic complexity modulus is researched. The results of the experiment show that the prediction achieves an actuality level.
Modelling decision making in fund raising management by a fuzzy knowledge system
Authors: Luca Barzanti, Mauro Gaspari, Davide Saletti
Venue: Expert Systems with Applications: An International Journal (2009)

In fund raising management the employment of a decision support system is crucial for optimising the results of fund raising campaigns. However, the current tools based on database technology are not able to suggest suitable fund raising strategies and the support to the fund raiser is limited to giving general indications in relation to specific claims. In this paper, we present a fuzzy knowledge based decision support system, which is able to individuate promising fund raising strategies for a given campaign. The system uses a knowledge based description of the campaign features and of the donors profiles and integrates these data with two models for strategies and historical information evaluation, rules of thumb suggested by experts in the field, and recent econometric studies. The system provides a ranking of suitable strategies using fuzzy evaluations. Experimental results confirm the applicability of the proposed approach in real contexts, providing significant insight into the improvement of campaigns performances.
Discovery of hierarchical thematic structure in text collections with adaptive resonance theory
Authors: Louis Massey
Venue: Neural Computing and Applications (2009)

This paper investigates the abilities of adaptive resonance theory (ART) neural networks as miners of hierarchical thematic structure in text collections. We present experimental results with binary ART1 on the benchmark Reuter-21578 corpus. Using both quantitative evaluation with the standard F 1 measure and qualitative visualization of the hierarchy obtained with ART, we discuss how useful ART built hierarchies would be to a user intending to use it as a means to find and access textual information. Our F 1 results show that ART1 produces hierarchical clustering that exhibit a quality exceeding k-means and a hierarchical clustering algorithm. However, we identify several critical problem areas that would make it rather impractical to actually use such a hierarchy in a real-life environment. These predicaments point to the importance of semantic feature selection. Our main contribution is to test in details the applicability of ART to the important domain of hierarchical document clustering, an application of Adaptive Resonance that had received little attention until now.
Etopia
Authors: William Sims Bainbridge
Venue: netWorker (2009)

The larger the number of participants in broadband-enabled society, the more likely traditional mass culture will fragment into smaller subcultures online.
Constraint based role based access control (CRBAC) for restricted administrative delegation constraints in the SECTET
Authors: Muhammad Alam
Venue: Proceedings of the 2006 International Conference on Privacy, Security and Trust: Bridge the Gap Between PST Technologies and Business Services (2006)

To guarantee the consistency and integrity of dynamic constraints, this paper extends our Constraint based Role Based Access Control (CRBAC) [1] model for the concept of Administrative RBAC (ARBAC) [14] with the specification of dynamic administrative constraints at a higher level of abstraction. The CRBAC uses SECTET-PL, a predicative language for the specification of access rights based on the concepts of RBAC. SECTET-PL is part of the SECTET-framework for model-driven security for B2B workflows.
Arc reversals in hybrid Bayesian networks with deterministic variables
Authors: Esma Nur Cinicioglu, Prakash P. Shenoy
Venue: International Journal of Approximate Reasoning (2009)

This article discusses arc reversals in hybrid Bayesian networks with deterministic variables. Hybrid Bayesian networks contain a mix of discrete and continuous chance variables. In a Bayesian network representation, a continuous chance variable is said to be deterministic if its conditional distributions have zero variances. Arc reversals are used in making inferences in hybrid Bayesian networks and influence diagrams. We describe a framework consisting of potentials and some operations on potentials that allows us to describe arc reversals between all possible kinds of pairs of variables. We describe a new type of conditional distribution function, called partially deterministic, if some of the conditional distributions have zero variances and some have positive variances, and show how it can arise from arc reversals.
High-performance global routing with fast overflow reduction
Authors: Huang-Yu Chen, Chin-Hsiung Hsu, Yao-Wen Chang
Venue: Proceedings of the 2009 Asia and South Pacific Design Automation Conference (2009)

Global routing is an important step for physical design. In this paper, we develop a new global router, NTUgr, that contains three major steps: prerouting, initial routing, and enhanced iterative negotiation-based rip-up/rerouting (INR). The prerouting employs a two-stage technique of congestion-hotspot historical cost pre-increment followed by small bounding-box area routing. The initial routing is based on efficient iterative monotonic routing. For traditional INR, it has evolved as the main stream for the state-of-the-art global routers, which reveals its great ability to reduce the congestion and overflow. As pointed out by recent works, however, traditional INR may get stuck at local optima as the number of iterations increases. To remedy this deficiency, we replace INR by enhanced iterative forbidden-region rip-up/rerouting (IFR) which features three new techniques of (1) multiple forbidden regions expansion, (2) critical subnet rerouting selection, and (3) look-ahead historical cost increment. Experimental results show that NTUgr achieves high-quality results for the ISPD'07 and ISPD'08 benchmarks for both overflow and runtime.