ppxscal/embedding_network huggingface dataset:
Designing a Personalized Semantic Web Browser
Authors: Melike Şah, Wendy Hall, David C. Roure
Venue: Proceedings of the 5th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems (2008)

Web browsing is a complex activity and in general, users are not guided during browsing. Our hypothesis is that by using Semantic Web technologies and personalization methods, browsing can be supported better. However, existing personalization mechanisms on the Web are obstructive; users need to log in to multiple websites and enter their personal information and preferences, and the profiles are different for each site. There is a need for generic user profiles, which can also support the user's browsing. In this paper, we propose a novel Semantic Web browser using an ontology-driven user modeling architecture to enable semantic and adaptive links. We also introduce a new behavior-based user model. With our approach, users need to log in to their Web browser only and personalization is achieved on different websites.
Statistic characteristics of M-ary FSK signal in the presence of Gaussian noise, intersymbol interference and Rayleigh fading
Authors: Mihajlo Stefanovic, Dragana Krstic, Nataša Kapacinovic, Srdjan Jovkovic
Venue: Proceedings of the 7th WSEAS International Conference on Electronics, Hardware, Wireless and Optical Communications (2008)

In this paper the receiver for the demodulation of M-FSK signals in the presence of Gaussian noise, intersymbol interference and Rayleigh fading is considered. The influence of the Gaussian noise, intersymbol iterference and Rayleigh fading to the communication systems can seriously degrade their performance.
Multi-label Text Categorization Using VG-RAM Weightless Neural Networks
Authors: Claudine Badue, Felipe Pedroni, Alberto F. De Souza
Venue: Proceedings of the 2008 10th Brazilian Symposium on Neural Networks (2008)

In automated multi-label text categorization, an automatic categorization system should output a category set, whose size is unknown a priori, for each document under analysis. Many machine learning techniques have been used for building such automatic text categorization systems. In this paper, we examine Virtual Generalizing Random Access Memory Weightless Neural Networks (VG-RAM WNN), an effective machine learning technique which offers simple implementation and fast training and test, as a tool for building automatic multi-label text categorization systems. We evaluate the performance of VG-RAM WNN on the categorization of Web pages, and compare our results with that of the multi-label lazy learning approach ML-KNN, the boosting-style algorithm BOOSTEXTER, the multi-label decision tree ADTBOOST.MH, and the multi-label kernel method Rank-SVM. Our experimental comparative analysis shows that, on average, VG-RAM WNN either outperforms the other mentioned techniques or show similar categorization performance.
A Tree Kernel-Based Shallow Semantic Parser for Thematic Role Extraction
Authors: Daniele Pighin, Alessandro Moschitti
Venue: Proceedings of the 10th Congress of the Italian Association for Artificial Intelligence on AI*IA 2007: Artificial Intelligence and Human-Oriented Computing (2007)

We present a simple, two-steps supervised strategy for the identification and classification of thematic roles in natural language texts. We employ no external source of information but automatic parse trees of the input sentences. We use a few attribute-value features and tree kernel functions applied to specialized structured features. Different configurations of our thematic role labeling system took part in 2 tasks of the SemEval 2007 evaluation campaign, namely the closed tasks on semantic role labeling for the English and the Arabic languages. In this paper we present and discuss the system configuration that participated in the English semantic role labeling task and present new results obtained after the end of the evaluation campaign.
Highly Efficient Structure of 64-Bit Exponential Function Implemented in FPGAs
Authors: Maciej Wielgosz, Ernest Jamro, Kazimierz Wiatr
Venue: Proceedings of the 4th international workshop on Reconfigurable Computing: Architectures, Tools and Applications (2008)

This paper presents implementation of the double precision exponential function. A novel table-based architecture, together with short Taylor expansion, provides low latency (30 clock cycles) which is comparable to 32-bit implementations. Low area consumption of a single exp() module (roughtly 4% of XC4LX200) allows implementation of several parallel modules on a single FPGAs. The exp() function was implemented on the SGI RASC platform, thus external memory interface limitation allowed only a twin module parallelism. Each module is capable of processing at speed of 200 MHz with max. error of 1 ulp, RMSE equals 0,62. This implementation aims primarily to meet quantum chemistry's huge and strict requirements of precision and speed.
Plugin-Agents as Conceptual Basis for Flexible Software Structures
Authors: Lawrence Cabac, Michael Duvigneau, Daniel Moldt, Benjamin Schleinzer
Venue: Proceedings of the 5th international Central and Eastern European conference on Multi-Agent Systems and Applications V (2007)

To allow for flexibility in software structures (architectures) especially plugins and agents are proposed solutions. While plugins are used to support the conceptual and practical issues within component oriented software environments, agents are used in software areas where social metaphors like (self-)adaptability, flexibility, mobility, interactivity etc. are of interest. Common to both approaches is a strong relation to a service-oriented view on exporting functionality. This contribution illustrates the idea of the integration of both concepts on the formal basis of high-level Petri nets.
A Key Distribution Scheme Based on Public Key Cryptography for Sensor Networks
Authors: Xiaolong Li, Yaping Lin, Siqing Yang, Yeqing Yi, Jianping Yu, Xinguo Lu
Venue: Computational Intelligence and Security: International Conference, CIS 2006, Guangzhou, China, November 3-6, 2006, Revised Selected Papers (2007)

This paper takes advantages of symmetrical key and asymmetrical key technologies, and proposes a key distribution scheme based on public key cryptography. This scheme does not need to pre-distribute pair-wise keys. Pair-wise key is established between two nodes after deployment according to a specific route algorithm. The scheme can guarantee there is a direct pair-wise key between two nodes that need communication frequently. As a result, it will decrease communication overhead. Both analytical results and simulation results demonstrate that the scheme can save memory usage, and in the scenario of large and dense deployment, the scheme achieves a higher level of connectivity and robustness.
A Queuing Theory Based Model for Studying Intrusion Evolution and Elimination in Computer Networks
Authors: Pantelis Kammas, Thodoros Komninos, Yannis C. Stamatiou
Venue: Proceedings of the 2008 The Fourth International Conference on Information Assurance and Security (2008)

In this paper we present a virus propagation and elimination model that takes into account the traffic and server characteristics of the network computers. This model partitions the network nodesinto perimeter and non-perimeter nodes. Incoming/outgoing trafficof the network passes through the perimeter of the network, where the perimeter is defined as the set of the servers which are connected directly to the internet. The non-perimeter network nodes, i.e. the computers with no direct internet connection, form a kind of isolated internet connected to the outside world through the perimeter nodes. All network nodes are assumed to process tasks based on the M/M/1 queuing model. Thus, the model behaves as an open network of M/M/1 queues. We study burst intrusions (e.g.Denial of Service Attacks) at the network perimeter and how the intrusion evolves given that, in parallel with the intrusion, anti-virus tasks also propagate in the network and kill intruder tasks. We propose a realistic kind of interactions between these agents that results in a product form steady state distribution ofthe agent numbers for each network node, much like the product form solution for the distribution of network tasks for Jackson open networks of queues.
A system to understand incorrect programs
Authors: Harald Wertz
Venue: Issue 2 (July 1978) (1978)

This paper presents a systems (PHENARETE) which understands and improves incompletely defined LISP programs, such as those written by students beginning to program in LISP. This system takes, as input, the program without any additional information. In order to understand the program, the system meta-evaluates it, using a library of "pragmatic rules", describing the construction and correction of general program constructs, and a set of "specialists", describing the syntax and semantics of the standard LISP functions. The system can use its understanding of the program to detect errors in it, to debug them and, eventually, to justify its proposed modification. This paper gives a brief survey of the working of the system, emphasizing on some commented examples.
Inductive Synthesis of Recursive Functional Programs
Authors: Martin Hofmann, Andreas Hirschberger, Emanuel Kitzelmannn, Ute Schmid
Venue: Proceedings of the 30th annual German conference on Advances in Artificial Intelligence (2007)

One of the most challenging subfields, and a still little researched niche of machine learning, is the inductive synthesis of recursive programs from incomplete specifications, such as examples for the desired input/output behavior [1,2,3,4].
Interview with Jim Thatcher, winner of the 2008 SIGCAS Making a Difference Award
Authors: Matt North
Venue: ACM SIGCAS Computers and Society (2008)

On March 28, 2008, the Association for Computer Machinery's Special Interest Group for Computers and Society (ACM SIGCAS) conferred the 2008 Making a Difference Award on Dr. Jim Thatcher. Dr. Thatcher's work in the area of assistive technologies has spanned four decades, and has enabled many blind and visually impaired individuals throughout the world to expand their use of computers in their daily lives. This summer, I had the opportunity to talk with Dr. Thatcher about his extraordinary career and this acknowledgement he has received from the ACM. --- MN
The Analysis of Windows Vista Disk Encryption Algorithm
Authors: Mohamed Abo El-Fotouh, Klaus Diepold
Venue: Proceeedings of the 22nd annual IFIP WG 11.3 working conference on Data and Applications Security (2008)

Windows Vista Enterprise and Ultimate editions use Bitlocker Drive Encryption as its disk encryption algorithm, and at its heart is the AES-CBC + Elephant diffuser encryption algorithm (ELEPHANT). In this paper we present our analysis of ELEPHANT using statistical tests. Our analysis has explored some weaknesses in its diffusers, thus we propose new diffusers to replace them. The new diffusers overcome the weaknesses of the original ones, and offer better and faster diffusion properties. We used the new diffusers to build variants of ELEPHANT, that possess better diffusion properties.
Multi-agency working in British social policy: Risk, information sharing and privacy
Authors: Christine Bellamy, Charles Raab, Charles Raab
Venue: Information Polity (2005)

Tensions between goals of integrated, seamless public services and of client confidentiality are increasingly important, as trends in public services require more extensive sharing of information about users of those services. This article identifies reasons why these tensions have become more salient under the Labour Government in the UK and the types of policy initiative that now give rise to them, before considering the development of the policy frameworks intended to strike settlements between these goals. In conclusion, the sustainability of these settlements is considered in the context of the trade-off between the risks of different types of judgment errors likely to be made by professionals providing public services in decisions on whether, when and how much to share client information.
A cooperation-based approach for evolution of service ontologies
Authors: Murat Şensoy, Pinar Yolum
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2 (2008)

Communication among agents requires a common vocabulary to facilitate successful information exchange. One way to achieve this is to assume the existence of a common ontology among communicating agents. However, this is a strong assumption, because agents may experience situations that result in independent evolution of their ontologies. When this is the case, agents need to form common grounds to enable communication. Accordingly, this paper proposes an approach in which agents can add new service concepts into their service ontologies and teach others services from their ontologies by exchanging service descriptions. This leads to a society of agents with different but overlapping ontologies where mutually accepted services emerge based on agents' exchange of service descriptions. Our simulations of societies show that allowing cooperative evolution of local service ontologies facilitates better representation of agents' needs. Further, through cooperation, not only more useful services emerge over time, but also ontologies of agents having similar service needs become aligned gradually.
Bosco: One-Step Byzantine Asynchronous Consensus
Authors: Yee Jiun Song, Robbert Renesse
Venue: Proceedings of the 22nd international symposium on Distributed Computing (2008)

Asynchronous Byzantine consensus algorithms are an important primitive for building Byzantine fault-tolerant systems. Algorithms for Byzantine consensus typically require at least two communication steps for decision; in many systems, this imposes a significant performance overhead. In this paper, we show that it is possible to design Byzantine fault-tolerant consensus algorithms that decide in one message latency under contention-free scenarios and still provide strong consistency guarantees when contention occurs. We define two variants of one-step asynchronous Byzantine consensus and show a lower bound on the number of processors needed for each. We present a Byzantine consensus algorithm, Bosco, for asynchronous networks that meets these bounds, even in the face of a strong network adversary.
Application of BP Nerual Network into Prediction of Nitrobenzene Compound in Toxicity
Authors: HuiYu Jiang, Min Dong, Feng Yang
Venue: Proceedings of the 2008 Second International Conference on Genetic and Evolutionary Computing (2008)

At present, the multivariate linear regression analysis was adopted in the biological toxicity forecast through establishment equation of the QSAR mostly, but the error forecasted was big in many situations because of the complexity and nonlinearity of structure-activity relationship, and it has a high request to the sample selection,In this paper forecast model of the nitrobenzene compound biological toxicity has been established based on the Levenberg_Marquardt BP neural network in this paper ,The studies suggest that the BP network has the strong misalignment to approach ability, the fitting precision is good between the output and the sample,the result is better using the BP network to forecast, the correlation coefficient has achieved 0.999, the prediction error in the permission scope, the biggest absolute value of error is 0.04 in this parper.So it is a good forecast mode of the nitrobenzene compound biological activity.
Instance-Based Action Models for Fast Action Planning
Authors: Mazda Ahmadi, Peter Stone
Venue: RoboCup 2007: Robot Soccer World Cup XI (2008)

Two main challenges of robot action planning in real domains are uncertain action effects and dynamic environments. In this paper, an instance-based action model is learned empirically by robots trying actions in the environment. Modeling the action planning problem as a Markov decision process, the action model is used to build the transition function. In static environments, standard value iteration techniques are used for computing the optimal policy. In dynamic environments, an algorithm is proposed for fast replanning, which updates a subset of state-action values computed for the static environment. As a test-bed, the goal scoring task in the RoboCup 4-legged scenario is used. The algorithms are validated in the problem of planning kicks for scoring goals in the presence of opponent robots. The experimental results both in simulation and on real robots show that the instance-based action model boosts performance over using parametric models as done previously, and also incremental replanning significantly improves over original off-line planning.
THF0 --- The Core of the TPTP Language for Higher-Order Logic
Authors: Christoph Benzmüller, Florian Rabe, Geoff Sutcliffe
Venue: Proceedings of the 4th international joint conference on Automated Reasoning (2008)

One of the keys to the success of the Thousands of Problems for Theorem Provers (TPTP) problem library and related infrastructure is the consistent use of the TPTP language. This paper introduces the core of the TPTP language for higher-order logic --- THF0, based on Church's simple type theory. THF0 is a syntactically conservative extension of the untyped first-order TPTP language.
StonyCam: A Formal Framework for Modeling, Analyzing and Regulating Cardiac Myocytes
Authors: Ezio Bartocci, Flavio Corradini, Radu Grosu, Emanuela Merelli, Oliviero Riganelli, Scott A. Smolka
Venue: Concurrency, Graphs and Models: Essays Dedicated to Ugo Montanari on the Occasion of His 65th Birthday (2008)

This paper presents a formal framework, experimental infrastructure, and computational environment for modeling, analyzing and regulating the behavior of cardiac tissues. Based on the theory of hybrid automata, we aim at providing suitable tools to be used in devising strategies for the pharmacological or other forms of treatment of cardiac electrical disturbances.
A General Framework for Increasing the Robustness of PCA-Based Correlation Clustering Algorithms
Authors: Hans-Peter Kriegel, Peer Kröger, Erich Schubert, Arthur Zimek
Venue: Proceedings of the 20th international conference on Scientific and Statistical Database Management (2008)

Most correlation clustering algorithms rely on principal component analysis (PCA) as a correlation analysis tool. The correlation of each cluster is learned by applying PCA to a set of sample points. Since PCA is rather sensitive to outliers, if a small fraction of these points does not correspond to the correct correlation of the cluster, the algorithms are usually misled or even fail to detect the correct results. In this paper, we evaluate the influence of outliers on PCA and propose a general framework for increasing the robustness of PCA in order to determine the correct correlation of each cluster. We further show how our framework can be applied to PCA-based correlation clustering algorithms. A thorough experimental evaluation shows the benefit of our framework on several synthetic and real-world data sets.
The Complexity of Algorithms Computing Game Trees on Random Assignments
Authors: Chenguang Liu, Kazuyuki Tanaka
Venue: Proceedings of the 3rd international conference on Algorithmic Aspects in Information and Management (2007)

The complexity of algorithms for computing game trees on random assignments has been given substantial attention in the literature. In this line, we investigate the complexity of algorithms that compute a special class of game trees $T_{2}^{k}$ from a new perspective -- eigen-distribution. This particular distribution is defined as the worst distribution on assignments to variables of $T_{2}^{k}$ regarding a best algorithm. In this paper, we show the eigen-distribution on assignments for $T_{2}^{k}$ in two separate cases, where the assignments to leaves are independently distributed (ID) and correlated distributed(CD). Then we use eigen-distribution to derive the tight bound of the complexity of algorithms for $T_{2}^{k}$.
Alternative Display of Friction Represented by Tactile Stimulation without Tangential Force
Authors: Masashi Konyo, Hiroshi Yamada, Shogo Okamoto, Satoshi Tadokoro
Venue: Proceedings of the 6th international conference on Haptics: Perception, Devices and Scenarios (2008)

A new display method of friction sensation based on tactile stimulation is proposed. In this method, no tangential force on the fingertip is required to represent friction sensation. We focus on the activities of tactile receptors in response to stick-slip contact phenomena with the fingertip. The proposed method controls the activities of FA II type receptors using very high frequency vibrations (at 600 Hz) in corresponding to the phase of stick-slip transition. The stick-slip transition was expressed by a single DOF model with Coulomb's friction, which represents the effects of coefficients of dynamic/static friction and hand movements. The sensory magnitudes of the perceived friction by the proposed method were evaluated in contrast with a force display. The experimental results showed that the perceived friction proposed had high correlation with that of the force display in regard to the increase tendency toward static friction coefficients. The sensory magnitudes of the tactile perceived friction were about one-seventh smaller than that of the force display.
Cyclostationary Neural Networks for Air Pollutant Concentration Prediction
Authors: Monica Bianchini, Ernesto Iorio, Marco Maggini, Augusto Pucci
Venue: Proceedings of the 3rd IAPR workshop on Artificial Neural Networks in Pattern Recognition (2008)

There are many substances in the air which may impair the health of plants and animals, including humans, that arise both from natural processes and human activity. Nitrogen dioxide NO2 and particulate matter (PM10, PM2.5) emissions constitute a major concern in urban areas pollution. The state of the air is, in fact, an important factor in the quality of life in the cities, since it affects the health of the community and directly influences the sustainability of our lifestyles and production methods. In this paper we propose a cyclostationary neural network (CNN) model for the prediction of the NO2 and PM10 concentrations. The cyclostationary nature of the problem guides the construction of the CNN architecture, which is composed by a number of MLP blocks equal to the cyclostationary period in the analyzed phenomenon, and is independent from exogenous inputs. Some experiments are also reported in order to show how the CNN model significantly outperforms standard statistical tools and linear regressors usually employed in these tasks.
Agent-based simulation of the spatial dynamics of crime: on the interplay between criminal hot spots and reputation
Authors: Tibor Bosse, Charlotte Gerritsen
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2 (2008)

An important challenge within the field of Criminology is to investigate the spatio-temporal dynamics of crime. Typical questions in this area are how the behaviour of offenders, targets, and guardians, and the emergence and displacement of criminal hot spots can be predicted. This paper presents an agent-based simulation model that can be used as an experimental tool to address such questions. The simulation model particularly focuses on the interplay between hot spots and reputation. Using the model, a number of simulation experiments have been performed, of which results have been analysed using formal techniques. The results indicate that the presented approach is able to adequately reproduce displacement patterns as described in the literature.