ppxscal/embedding_network huggingface dataset:
Fuzzy Expert System to Estimate Ignition Timing for Hydrogen Car
Authors: Tien Ho, Vishy Karri
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks, Part II (2008)

This paper presents the application of fuzzy expert system technique as a basis to estimate ignition timing for subsequent tuning of a Toyota Corolla 4 cylinder, 1.8l hydrogen powered car. Ignition timing prediction is a typical problem to which decision support fuzzy system can be used. Based on extensive experiments, the basic fuzzy rules on ignition timing have been constructed, in which the engine speed, throttle position, manifold air pressure, fuel pulse width, engine power, lambda value were chosen as fuzzy sets of the linguistic input variables, and ignition advance is selected as performance output of the fuzzy system. The constructed fuzzy system initially mapped 136 basic rules based on physical theories and extensive experimentation. For all the input parameters various triangular, trapezoidal and generalized bell-shaped membership functions were successfully applied to best represent the ignition timing output from the expert system. The results have shown that the minimum ignition advance for maximum torque without detonation was achieved. The estimation of ignition advance achieved from fuzzy expert system was ± 5% root mean square error.
Dynamic Data-Driven Systems Approach for Simulation Based Optimizations
Authors: Tahsin Kurc, Xi Zhang, Manish Parashar, Hector Klie, Mary F. Wheeler, Umit Catalyurek, Joel Saltz
Venue: Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007 (2007)

This paper reviews recent developments in our project that are focused on dynamic data-driven methods for efficient and reliable simulation based optimization, which may be suitable for a wide range of different application problems. The emphasis in this paper is on the coupling of parallel multiblock predictive models with optimization, the development of autonomic execution engines for distributing the associated computations, and deployment of systems capable of handling large datasets. The integration of these components results in a powerful framework for developing large-scale and complex decision-making systems for dynamic data-driven applications.
Instruction Decoder Module Design of 32-bit RISC CPU Based on MIPS
Authors: YunZhu Xiang, YueHua Ding
Venue: Proceedings of the 2008 Second International Conference on Genetic and Evolutionary Computing (2008)

This paper introduces architecture and feature of 32-bit micro-processor, and describes internal data path in processor. Through analysis of function and theory of RISC CPU instruction decoder module, we design instruction decoder (ID) module of 32-bit CPU by pipeline theory. The instruction decoder includes register file, write back data to register file, sign bit extend, relativity check, and it is simulated on QuartusII successfully. Static time sequence shows the instruction decode module completing required function.
A Novel Feature for Emotion Recognition in Voice Based Applications
Authors: Hari Krishna Maganti, Stefan Scherer, Günther Palm
Venue: Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction (2007)

In the context of affective computing, a significant trend in multi modal human-computer interaction is focused to determine emotional status of the users. For a constructive and natural human-computer interaction, the computers should be able to adapt to the user's emotional state and respond appropriately. This work proposes few simple and robust features in the framework of determining emotions from speech. Our approach is suitable for voice based applications, such as call centers or interactive voice systems, which are dependent on telephone conversations. For a typical call center application, it is crucial to recognize and classify agitation (anger, happiness, fear, and disgust) and calm (neutral, sadness, and boredom) callers, for the systems to respond appropriately. For instance, in a typical voice based application, the system should be able to either apologize or appreciate the problem of the caller suitably, if necessary by directing the call to the supervisor concerned.
Automatic On-Line Color Calibration Using Class-Relative Color Spaces
Authors: Pablo Guerrero, Javier Ruiz-Del-Solar, Josué Fredes, Rodrigo Palma-Amestoy
Venue: RoboCup 2007: Robot Soccer World Cup XI (2008)

In this article we present an automatic on-line color calibration system that makes extensive use of the spatial relationships between color classes in the color space. First, we introduce the definition of class-relative color spaces, where classes are represented in terms of their spatial relation to a base color class. Then, using class-relative color spaces, the system is able to remap classes from the already trained ones, which gives a starting point for training the remaining classes. The color-calibrating system also uses a feedback from the detected objects using the remapped (or partially trained) classes. As a result, the system is able to generate a complete color look-up table from scratch, and to adapt quickly to severe lighting condition changes. A particularity of our system is that it does not need to solve the natural ambiguity in color classes' intersections, but it is able to keep and use it during color segmentation using the concept of soft-colors.
A Priority Based Distributed Deadlock Detection Algorithm
Authors: M. K. Sinha
Venue: IEEE Transactions on Software Engineering (1985)

Deadlock handling is an important component of transaction management in a database system. In this paper, we contribute to the development of techniques for transaction management by presenting an algorithm for detecting deadlocks in a distributed database system. The algorithm uses priorities for transactions to minimize the number of messages initiated for detecting deadlocks. It does not construct any wait-for graph but detects cycles by an edge-chasing method. It does not detect any phantom deadlock (in the absence of failures), and for the resolution of deadlocks it does not need any extra computation. The algorithm also incorporates a post-resolution computation that leaves information characterizing dependence relations of remaining transactions of the deadlock cycle in the system, and this will help in detecting and resolving deadlocks which may arise in the future. An interesting aspect of this algorithm is that it is possible to compute the exact number of messages generated for a given deadlock configuration. The complexity is comparable to the best algorithm reported. We first present a basic algorithm and then extend it to take into account shared and exclusive lock modes, simultaneous acquisition of multiple locks, and nested transactions.
Local Link Protection Scheme in IP Networks
Authors: Hui-Kai Su, Cheng-Shong Wu
Venue: Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007 (2007)

In this paper, we proposed an IP Local Link-Protection (IPLLP) scheme based on the characteristic of shortest-path routing in IP networks. Our scheme working in an intra-area routing domain provides a simple and efficient solution to improve IP network survivability without extra control protocols and enhanced routing protocols. Because the backup next hops are predetermined in advance, the service interrupted time can be limited to a few milliseconds. In the simulation results, we observe that IP Local Link-Protection scheme can efficiently improve network survivability in a small-scale and high-degree network.
Haar image compression using a neural network
Authors: Adnan Khashman, Kamil Dimililer
Venue: Proceedings of the WSEAS International Conference on Applied Computing Conference (2008)

Wavelet Transform is one of the most popular methods applied in image compression. Wavelet-based image compression provides substantial improvements in picture quality at higher compression ratios. Haar wavelet transform based compression is one of the methods that can be applied to images. An ideal image compression system must yield good quality compressed images with good compression ratio, while maintaining minimum time cost. A neural network will be trained to establish the non-linear relationship between the image intensity and its compression ratios in search for an optimum ratio. This paper suggests that a neural network could be trained to recognize an optimum ratio for Haar wavelet compression of an image upon presenting the image to the network. Experimental results suggest that a trained neural network can simulate such non-linear relationship and thus can be successfully used to provide an intelligent optimum image compression system.
Simulator for production modeling: virtual experiments
Authors: Monica Dascalu, Eduard Franti, Lucian Milea, Marius Stoian, Gabriel Sebe
Venue: Proceedings of the 7th WSEAS International Conference on Artificial intelligence, knowledge engineering and data bases (2008)

This paper presents a new experiment undertaken in the artificial society introduced by Epstein and Axtell [1]. The artificial society basically consists of a "cellular" landscape that contains resources and a population of agents that move around in this landscape, searching for the resources that they need to consume in order to survive. The new experiment introduces production and trade in this model in a very simple manner: the richest agents can produce a new commodity, named vitamin, that the other agents can buy and consume. The effect of the vitamins is to improve the agent's skills for a certain period of time, proportional to the quantity consumed. Running the artificial societies program with this new scenario, one can notice the improvement of population dynamics, explained by the fact that the agents have better survival skills. The most important effect is that the dynamics of agents' wealth shows a very clear clustering of agents after the level of their accumulated resources, phenomenon that we have called emergence of social classes.
Need to Know: Questions and the Paradox of Epistemic Obligation
Authors: Joris Hulstijn
Venue: Proceedings of the 9th international conference on Deontic Logic in Computer Science (2008)

Åqvist's paradox of epistemic obligation can be solved, if we use knowledge-wh instead of knowledge-that in specifications of the `need to know': the knowledge which an agent in a certain organisational role is required to have. Knowledge-wh is knowledge of an answer to a question, which depends on the context. We show how knowledge-wh can be formalised in a logic of questions, which is combined with standard deontic logic to represent epistemic obligations. We demonstrate that under the new interpretation, the paradox can no longer be derived. The resulting logic is useful for representation of access control policies.
The emptiness problem for automata on infinite trees
Authors: R. Hossley, C. Rackoff
Venue: Proceedings of the 13th Annual Symposium on Switching and Automata Theory (swat 1972) (1972)

The purpose of this paper is to give an alternative proof to the decidability of the emptiness problem for tree automata, as shown in Rabin4. The proof reduces the emptiness problem for automata on infinite trees to that for automata on finite trees, by showing that any automata definable set of infinite trees must contain a finitely-generable tree.
Applying Rough Sets to Information Tables Containing Probabilistic Values
Authors: Michinori Nakata, Hiroshi Sakai
Venue: Proceedings of the 4th international conference on Modeling Decisions for Artificial Intelligence (2007)

Rough sets are applied to information tables containing imprecise values that are expressed in a probability distribution. A family of weighted equivalence classes is obtained where each equivalence class is accompanied by the probability to which it is an actual one. By using the family of weighted equivalence classes, we derive lower and upper approximations. The lower and upper approximations coincide with ones obtained from methods of possible worlds. Therefore, the method of weighted equivalence classes is justified. In addition, this method is applied to missing values interpreted probabilistically. Using weighted equivalence classes correctly derives a lower approximation, even in the case where the method of Kryszkiewicz does not derive any lower approximation.
System Design from Instrument Level Down to ASIC Transistors with Speed and Low Power as Driving Parameters
Authors: A. Emrich
Venue: Proceedings of the 17th international workshop on Integrated Circuit and System Design. Power and Timing Modeling, Optimization and Simulation (2007)

For wide bandwidth spectrometers there are several competing technologies to consider, digital, optical and various analog schemes. For applications demanding wide bandwidth and low power consumption in combination, autocorrelation based digital designs take advantage of Moores law and will take a dominating position in the coming years. 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
On Developing Open Mobile Fault Tolerant Agent Systems
Authors: Budi Arief, Alexei Iliasov, Alexander Romanovsky
Venue: Software Engineering for Multi-Agent Systems V: Research Issues and Practical Applications (2007)

The paper introduces the Cama (Context-Aware Mobile Agents) framework intended for developing large-scale mobile applications using the agent paradigm. Cama provides a powerful set of abstractions, a supporting middleware and an adaptation layer allowing developers to address the main characteristics of the mobile applications: openness, asynchronous and anonymous communication, fault tolerance, and device mobility. It ensures recursive system structuring using location, scope, agent, and role abstractions. Cama supports system fault tolerance through exception handling and structured agent coordination within nested scopes. The applicability of the framework is demonstrated using an ambient lecture scenario --- the first part of an ongoing work on a series of ambient campus applications. This scenario is developed starting from a thorough definition of the traceable requirements including the fault tolerance requirements. This is followed by the design phase at which the Cama abstractions are applied. At the implementation phase, the Cama middleware services are used through a provided API. This work is part of the FP6 IST RODIN project on Rigorous Open Development Environment for Complex Systems.
Public Key Authentication Schemes for Local Area Networks
Authors: Tzung-Her Chen, Gwoboa Horng, Chuan-Sheng Yang
Venue: Informatica (2008)

The invention of public-key cryptography makes many new network applications, such as electronic commerce (CE), possible. However, the widely used Internet is open and unprotected. Therefore, verifying the legitimacy of an individual's public key is very important. Most of the key authentication schemes require one or more trustworthy authorities to authenticate the key of a user. Consequently, the system security is mainly dependent on the honesty of these third parties. Unfortunately, a security solution in wide area networks (for example, the Internet) often cannot be applied to local area networks directly without any modification. Sometimes, a complete rebuild is necessary, especially for performance criteria consideration. In this paper, we propose two simple key authentication schemes that require no certification authorities for computer systems in local area networks, in which a host is responsible for user authentication and it uses a designated password authentication mechanism.
User controlled filtering in WEB usage mining
Authors: I. (Corresponding author. E-mail: ilias@co.umist.ac.uk) Petrounias, A. Tseng, V. Kodogiannis
Venue: Journal of Computational Methods in Sciences and Engineering (2005)

Web log analysis can provide valuable information about user behaviour when visiting a web site. Analysing users' traversal patterns and frequency or repetition of visits can provide very valuable information. However, the amount of information contained in web logs is huge. Primarily based on the Web servers' log files, the main objective of traversal pattern mining is to discover the frequent patterns in users' browsing paths and behaviours. Constraints have not been considered extensively as part of pre-mining tasks in web mining. This paper presents a complete framework for web usage mining, allowing users to pre-define constraints when analysing complex traversal patterns in order to improve the efficiency of algorithms and offer flexibility in producing results.
Dynamic Service Substitution in Service-Oriented Architectures
Authors: Manel Fredj, Nikolaos Georgantas, Valerie Issarny, Apostolos Zarras
Venue: Proceedings of the 2008 IEEE Congress on Services - Part I (2008)

The problem we deal with in this paper is the dynamic substitution of stateful services that become unavailable during the execution of service orchestrations. Previous research efforts focusing on the reconfiguration of conventional distributed systems enable the substitution of system entities with other prefabricated passive entities that serve as a backup. Nevertheless, the problem of service substitution is far more complex. In SOA, we can assume the possible existence of several semantically compatible services capable of performing the same or similar tasks. However, each one of them constantly serves requests and cannot be considered as a passive backup for other services. Therefore, we propose the SIROCO middleware platform, enabling the runtime, semantic-based service substitution. The basic concepts of SIROCO are discussed along with an experimental evaluation of our first prototype. Our findings show that SIROCO provides the necessary means for achieving dynamic service substitution with a reasonable expense on the execution of service orchestrations.
Rough Set Theory from a Math-Assistant Perspective
Authors: Adam Grabowski, Magdalena Jastrzebska
Venue: Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms (2007)

In the paper, we draw a perspective of the computer-assisted theory exploration within rough set theory. We examine two well-known approaches to the topic, drawing some paradigms for a machine math-assistant to be feasible tool any researcher can use to verify his own results. Some features of a Mizar language chosen for the verification task are also presented.
CoCoME in Fractal
Authors: Lubomír Bulej, Tomáš Bureš, Thierry Coupaye, Martin Děcký, Pavel Ježek, Pavel Parízek, František Plášil, Tomáš Poch, Nicolas Rivierre, Ondřej Šerý, Petr Tůma
Venue: The Common Component Modeling Example: Comparing Software Component Models (2007)

This chapter presents our solution to the CoCoME assignment that is based on the Fractal component model. The solution involves (i) modeling architecture in Fractal ADL, (ii) specification of component behavior via behavior protocols, (iii) checking compatibility of components, (iv) verification of correspondence between component code and behavior specification, and (v) run-time monitoring of non-functional properties. Among the issues we have faced was the need to modify the architecture - the component hierarchy was reorganized in order to improve clarity of the design and the hierarchical bus was split into two independent buses. These were modeled by primitive components, since Fractal does not support message bus as a first-class entity. Since the CoCoME assignment does not include a complete UML behavior specification (e.g. via activity diagrams and state charts), behavior protocols for all the components are based on the provided plain-English use cases, the UML sequence diagrams, and the reference Java implementation.
Continuous Top-k Dominating Queries in Subspaces
Authors: Maria Kontaki, Apostolos N. Papadopoulos, Yannis Manolopoulos
Venue: Proceedings of the 2008 Panhellenic Conference on Informatics (2008)

Dominating queries are significant tools for preference-based query processing in databases and decision support applications. An important preference-based query is the top-$k$ dominating query, which reports the $k$ most important objects according to their domination capabilities (score). In this paper, we address the following issues to tackle two limitations of previously proposed approaches: (i) we allow dominating queries to be expressed in a subset of the available dimensions and (ii) we provide the necessary techniques to enable continuous processing of multiple queries. We use a grid-based indexing scheme to facilitate efficient search and update operations, avoiding expensive reorganization costs. In addition, several optimizations are proposed to enhance efficiency. Performance evaluation results, based on real-life and synthetic data sets, show the efficiency and scalability of the proposed scheme.
An integration scheme for electromagnetic scattering using plane wave edge elements
Authors: M. E. Honnor, J. Trevelyan, P. Bettess, M. El-hachemi, O. Hassan, K. Morgan, J. J. Shirron
Venue: Advances in Engineering Software (2009)

Finite element techniques for the simulation of electromagnetic wave propagation are, like all conventional element based approaches for wave problems, limited by the ability of the polynomial basis to capture the sinusoidal nature of the solution. The Partition of Unity Method (PUM) has recently been applied successfully, in finite and boundary element algorithms, to wave propagation. In this paper, we apply the PUM approach to the edge finite elements in the solution of Maxwell's equations. The electric field is expanded in a set of plane waves, the amplitudes of which become the unknowns, allowing each element to span a region containing multiple wavelengths. However, it is well known that, with PUM enrichment, the burden of computation shifts from the solver to the evaluation of oscillatory integrals during matrix assembly. A full electromagnetic scattering problem is not simulated or solved in this paper. This paper is an addition to the work of Ledger and concentrates on efficient methods of evaluating the oscillatory integrals that arise. A semi-analytical scheme of the Filon character is presented.
On-line Algorithm for Extraction of Specific Signals with Temporal Structure
Authors: Ewaldo Santana, André B. Cavalcante, Marcio O. Santos, Allan Barros, R. C. Freire
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part II (2008)

Blind source separation techniques based on statistical independence criteria require a large number of data samples to estimate higher-order statistics. Thus, those techniques are not suitable to either on-line adaptive modeling. In this work we developed both an online and a batch algorithms for semi-blind extraction of a desired source signal with temporal structure from linear mixtures . Here, we do not assume that sources are statistically independent but we use an a priori information about the autocorrelation function of primary sources to extract the desired signal. Also, we develop an analytical framework to guarantee convergence of the online algorithm based on second-order statistics. Extensive computer simulations and real data applications confirm the validity and high performance of the proposed algorithms.