ppxscal/embedding_network huggingface dataset:
Robust and Adaptive Fuzzy Feedback Linearization Regulator Design
Authors: Chang-Woo Park, Young-Ouk Kim, Chong Ho Yi
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence (2008)

In this paper, we have proposed a new adaptive fuzzy control algorithm and the regulation problem based on Takagi-Sugeno fuzzy model. The regulation problem for the uncertain SISO nonlinear system is solved by the proposed algorithm. Using the advanced stability theory, the stability of the state, the control gain and the parameter choosing considering the approximation error due to the fuzzy modeling is proved. Some numerical examples are presented to verify the effectiveness of the proposed methods.
Development of PT Secondary Circuit's Drop Test Instrument Based on dsPIC30F6010 Singlechip
Authors: Haiquan Li, Shuguang Zhang, Dening Zhang, Hongjuan Kou, Shan Zhang
Venue: Proceedings of the 2008 ISECS International Colloquium on Computing, Communication, Control, and Management - Volume 02 (2008)

In the comprehensive error of energy metering device, only metering error of voltage drop of TV secondary circuit can be reduced by some technical improvement measures. This paper introduces a portable intellectual instrument used to measure PT secondary drop of voltage transformer based on metering, while relying on dsPIC30F6010 single chip, as well as the form of hardware and procedure of software.
A Rough-Apriori Technique in Mining Linguistic Association Rules
Authors: Yun-Huoy Choo, Azuraliza Abu Bakar, Abdul Razak Hamdan
Venue: Proceedings of the 4th international conference on Advanced Data Mining and Applications (2008)

This paper has proposed a rough-Apriori based mining technique in mining linguistic association rules focusing on the problem of capturing the numerical interval with linguistic terms in quantitative association rules mining. It uses the rough membership function to capture the linguistic interval before implementing the Apriori algorithm to mine interesting association rules. The performance of conventional quantitative association rules mining algorithm with Boolean reasoning as the discretization method was compared to the proposed technique and the fuzzy-based technique. Five UCI datasets were tested in the 10-fold cross validation experiment settings. The frequent itemsets discovery in the Apriori algorithm was constrained to five iterations comparing to maximum iterations. Results show that the proposed technique has performed comparatively well by generating more specific rules as compared to the other techniques.
Three and two-valued Łukasiewicz theories in the formal deductive system L* (NM-logic)
Authors: Hongjun Zhou, Guojun Wang
Venue: Fuzzy Sets and Systems (2008)

In order to offer a logic foundation for fuzzy reasoning and to reduce the gap between fuzzy reasoning and artificial intelligence, a new formal deductive system L^* was introduced in 1996. It was proved that the prominent nilpotent minimum logic is a logic system equivalent to L^*. As is well known, in classical propositional logic, there is a one-to-one correspondence between deductively closed theories and topologically closed subsets of the Stone space of all maximally consistent theories. Recently, by means of the strong completeness of L^*, we obtained the structural and topological characterizations of maximally consistent theories in this logic. It was proved that the set of all maximally consistent theories over L^* with an induced topology is a Cantor space. In order to establish a similar connection between theories over L^* and closed subsets of this topological space to the classical case, we introduce in this paper the notion of three-valued Lukasiewicz theory and the notion of two-valued Lukasiewicz (Boolean) theory. We prove that there is also a one-to-one correspondence between deductively closed three-valued Lukasiewicz theories and closed subsets of the space, and Boolean theories correspond to the closed subsets of the subspace of all maximally consistent Boolean theories. Lastly, we give an alternative proof for the structural characterization of the maximality of consistent theories over L^* by induction on the complexity of formulas, which is independent of the strong completeness of L^* and also independent of the perfectness of the standard R"0-algebra.
A class density approximation neural network for improving the generalization of Fisherface
Authors: Jiayan Jiang, Liming Zhang, Tetsuo Furukawa
Venue: Neurocomputing (2008)

Fisherface is a popular dimensionality reduction technique in face recognition. The obtained discriminative subspace, however, may not generalize well to unseen classes, as in the case of enrollment of new identities. In this paper, a class density approximation network based on SOM^2 is introduced to derive ''prototype classes'' for training, which improves the generalization of Fisherface and reduces its performance variance resulting from random selections of training classes. We also propose a splitting method to estimate the number of prototype classes needed in approximation. Experiments on synthesized data and real face databases validate the effectiveness of our method.
Hybrid Multi-step Disfluency Detection
Authors: Sebastian Germesin, Tilman Becker, Peter Poller
Venue: Proceedings of the 5th international workshop on Machine Learning for Multimodal Interaction (2008)

Previous research has shown that speech disfluencies - speech errors that occur in spoken language - affect NLP systems and hence need to be repaired or at least marked. This study presents a hybrid approach that uses different detection techniques for this task where each of these techniques is specialized within its own disfluency domain. A thorough investigation of the used disfluency scheme, which was developed by [1], led us to a detection design where basic rule-matching techniques are combined with machine learning approaches. The aim was both to reduce computational overhead and processing time and also to increase the detection performance. In fact, our system works with an accuracy of 92.9% and an F-Score of 90.6% while working faster than real-time.
A Pseudo-Boolean Optimization for Multiple Criteria Decision Making in Complex Systems
Authors: Bahram Alidaee, Haibo Wang, Yaquan Xu
Venue: Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007 (2007)

In complex system problems, a Decision Maker (DM) is often faced with choosing a subset of alternatives from a bigger set. This process is known as multiple criteria decision making (MCDM). Examples of MCDM include decision making in human resource management, water resource management, environmental management and site selection, energy policy issues, portfolio selection, transportation and routing selection, student admission. In general, there are several criteria that need to be satisfied; however, they are usually at least partly conflicting. In this study, we propose a pseudo-boolean approach for multiple criteria decision making on complex system problems. The computational results illustrate both robustness and attractiveness of this solution approach.
The MultiMatch Prototype: Multilingual/Multimedia Search for Cultural Heritage Objects
Authors: Giuseppe Amato, Franca Debole, Carol Peters, Pasquale Savino
Venue: Proceedings of the 12th European conference on Research and Advanced Technology for Digital Libraries (2008)

MultiMatch is a 30 month targeted research project under the Sixth Framework Programme, supported by the unit for Content, Learning and Cultural Heritage (Digicult) of the Information Society DG. MultiMatch is developing a multimedia/multilingual search engine designed specifically for the access, organization and personalized presentation of cultural heritage information. The demonstration will present the MultiMatch system prototype.
Affective Video Data Collection Using an Automobile Simulator
Authors: Tevfik Metin Sezgin, Peter Robinson
Venue: Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction (2007)

The correlation between driver status and safety has increased interest in automated systems that can infer the physical and mental state of drivers [2,3]. So far, most research on automated recognition of driver state has focused on physical state. More recently, researchers have proposed inferring the mental states of drivers by extracting drivers' facial expressions from video data. Although systems that infer physical state have been evaluated in simulators or in real driving conditions, this has not been the case for systems inferring mental states which rely primarily on video data. Consequently, issues regarding the design of an experimental setup to collect such affective data have not been explored. Here, we describe our experimental setup for collecting video data from drivers.
Solving Medium-Density Subset Sum Problems in Expected Polynomial Time: An Enumeration Approach
Authors: Changlin Wan, Zhongzhi Shi
Venue: Proceedings of the 2nd annual international workshop on Frontiers in Algorithmics (2008)

The subset sum problem (SSP) can be briefly stated as: given a target integer E and a set A containing n positive integer a j , find a subset of A summing to E. The density d of an SSP instance is defined by the ratio of n to m, where m is the logarithm of the largest integer within A. Based on the structural and statistical properties of subset sums, we present an improved enumeration scheme for SSP, and implement it as a complete and exact algorithm (EnumPlus). The algorithm always equivalently reduces an instance to be low-density, and then solve it by enumeration. Through this approach, we show the possibility to design a sole algorithm that can efficiently solve arbitrary density instance in a uniform way. Furthermore, our algorithm has considerable performance advantage over previous algorithms. Firstly, it extends the density scope, in which SSP can be solved in expected polynomial time. Specifically, It solves SSP in expected O(nlogn) time when density $d \geq c\cdot \sqrt{n}/\log{n}$, while the previously best density scope is d ¿ c·n/(logn)2. In addition, the overall expected time and space requirement in the average case are proven to be O(n 5logn) and O(n 5) respectively. Secondly, in the worst case, it slightly improves the previously best time complexity of exact algorithms for SSP. The worst-case time complexity of our algorithm is proved to be O(n·2 n/2 ¿ c·2 n/2 + n), while the previously best result is O(n·2 n/2).
Two algorithms for automatic document page layout
Authors: João Batista S. de Oliveira
Venue: Proceeding of the eighth ACM symposium on Document engineering (2008)

This paper describes two approaches to the problem of automatically placing document items on pages of some output device. Both solutions partition the page into regions where each item is to be placed, but work on different input data according to the application: One approach assumes that previously defined rectangular items are to be placed freely on the page (as in a sales brochure), whereas the second approach places free-form items on pages divided into columns (as in a newspaper). Moreover, both approaches try to preserve the reading order provided by the input and use all available area on the page. The algorithms implementing those approaches and based on recursive page division are presented, as well as test results, possible changes and research directions.
Ugo Montanari and Software Verification
Authors: Gian-Luigi Ferrari
Venue: Concurrency, Graphs and Models: Essays Dedicated to Ugo Montanari on the Occasion of His 65th Birthday (2008)

The great honour of introducing the Chapter on Software Verification for the Festschrift dedicated to Ugo Montanari brings to mind a very personal memory. I was a young Ph.D. student and I was discussing something with Ugo, or better I was learning something from Ugo about how one could apply the abstract notions of category theory in order to understand better the problems raised from concurrency and synchronization. At a certain point Ugo wanted to interrupt our talk because a seminar by Jaco de Bakker on the denotational semantics of concurrency by metric spaces was about to begin. I was very familiar with the works of de Bakker having studied them for my Laurea thesis under Ugo's supervision. Following my request to continue our discussion, Ugo replied, "Let's go to the seminar. We can always learn something listening to de Bakker".
Parametric Language Analysis of the Class of Stop-and-Wait Protocols
Authors: Guy Edward Gallasch, Jonathan Billington
Venue: Proceedings of the 29th international conference on Applications and Theory of Petri Nets (2008)

Model checking a parametric system when one or more of its parameters is unbounded requires considering an infinite family of models. The Stop-and-Wait Protocol (SWP) has two (unbounded) parameters: the maximum sequence number and the maximum number of retransmissions. Previously, we presented a novel method for the parametric analysis of the SWP by developing algebraic formulas in the two parameters that symbolically represent the corresponding infinite class of reachability graphs. Properties were then verified directly from these expressions. This paper extends this analysis to the verification of the SWP using language equivalence. From the algebraic expressions developed previously, a parametric Finite State Automaton (FSA) representing all sequences of user-observable events (i.e. the protocol language) is derived. We then perform determinisation and minimisation directly on the parametric FSA. The result is a simple, non-parametric FSA that is isomorphic to the service language of alternating send and receive events. This result is significant as it verifies conformance of the SWP to its service for all values of the two unbounded parameters.
The permanence of paradigms: The integration of the Dutch police's information domains and its (non)effects
Authors: Pieter Wagenaar, Stefan Soeparman
Venue: Information Polity (2003)

At the moment the Dutch police is busily integrating its information domains. What effect will this have on the Dutch police system? Will it cause the stark centralisation Bellamy and Taylor feared in 1997? Due to the peculiarities of its institutional arrangements, simply posing the centralisation/decentralisation question about the Dutch police system leads to little. As we will show in our article, if we want to assess anything at all about the direction the system is heading in, we also need to pay attention to two other oppositions determining its organisation: the administrative versus the judicial police duty, and administrative police management versus authority over the police. It is these three oppositions that form the Dutch police system's 'institutional paradigm': the norms, values, cognitions, rules and regulations that determine its organisation.
Chaotic Search for Traveling Salesman Problems by Using 2-opt and Or-opt Algorithms
Authors: Takafumi Matsuura, Tohru Ikeguchi
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part II (2008)

The traveling salesman problem (TSP) is one of the widely studied combinatorial optimization problems. Because, the TSP belongs to a class of $\mathcal{NP}$-hard, it is almost impossible to obtain an optimal solution in a reasonable time frame. To find the near optimum solutions of TSPs, a method with chaotic neurodynamics has already been proposed. In this paper, we propose a new method to solve TSP introducing chaotic neurodynamics, which uses not only the 2-opt algorithm but also the Or-opt algorithm, which is one of the powerful local searches. Namely, in the proposed method, the 2-opt and the Or-opt algorithms are adaptively driven by the chaotic neurodynamics. Thus, the local minimum problem in these algorithms is resolved by controlling executions of these local searches. As a result, the proposed method shows higher performance than the previous chaotic search methods.
Optimum Resource Allocation for Amplify-and-Forward Cooperative Networks with Differential Modulation
Authors: Mohammadreza Rahmatpour, Vahid Tabataba Vakili
Venue: Proceedings of the 8th international conference, NEW2AN and 1st Russian Conference on Smart Spaces, ruSMART on Next Generation Teletraffic and Wired/Wireless Advanced Networking (2008)

The optimum resource allocation in relay networks is used to improve the error performance and increase the energy efficiency. In this paper, a two-dimensional resource allocation, i.e., the energy optimization and location optimization, is carried out based on the average symbol error rate (SER) for the system with and without a direct link. Differential modulation which bypasses the channel estimation at the transceiver is investigated using amplify-and-forward protocol for the system with multiple relays. We also show that the minimum error rate can be achieved via the joint energy-location optimization.
Optimisation of Asymmetric Mutational Pressure and Selection Pressure Around the Universal Genetic Code
Authors: Paweł Mackiewicz, Przemysław Biecek, Dorota Mackiewicz, Joanna Kiraga, Krystian Baczkowski, Maciej Sobczynski, Stanisław Cebrat
Venue: Proceedings of the 8th international conference on Computational Science, Part III (2008)

One of hypotheses explaining the origin of the genetic code assumes that its evolution has minimised the deleterious effects of mutations in coded proteins. To estimate the level of such optimization, we calculated optimal codes for genes located on differently replicating DNA strands separately assuming the rate of amino acid substitutions in proteins as a measure of code's susceptibility to errors. The optimal code for genes located on one DNA strand was simultaneously worse than the universal code for the genes located on the other strand. Furthermore, we generated 20 million random codes of which only 23 were better than the universal one for genes located on both strands simultaneously while about two orders of magnitude more codes were better for each of the two strands separately. The result indicates that the existing universal code, the mutational pressure, the codon and amino acid compositions are highly optimised for the both differently replicating DNA strands.
A Practical Activity Capture Framework for Personal, Lifetime User Modeling
Authors: Max Kleek, Howard E. Shrobe
Venue: Proceedings of the 11th international conference on User Modeling (2007)

This paper addresses the problem of capturing rich, long-term personal activity logs of users' interactions with their workstations, for the purpose of deriving predictive, personal user models. Our architecture addresses a number of practical problems with activity capture, including incorporating heterogeneous information from different applications, measuring phenomena with different rates of change, efficiently scheduling knowledge sources, incrementally evolving knowledge representations, and incorporating prior knowledge to combine low-level observations into interpretations better suited for user modeling tasks. We demonstrate that the computational and memory demands of general activity capture are well within reasonable limits even on today's hardware and software platforms.
Role Based Access Control in Distributed Object Systems
Authors: Tomoya Enokido, Makoto Takizawa
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems Workshops (2008)

The role-based access control (RBAC) model is widely used to make information systems secure. Even if every access request is authorized, illegal information flow might occur as the well known confinement problem. In this paper, we discuss how prevent illegal information flow to occur by synchronizing onflicting transactions in the RBAC model. We first define types of information flow relations, legal (LIF), illegal (IIF), and possibly illegal (PIF) ones R1 ⇒ R2, R1 ↪ R2, and R1 → R2 among a pair of role families R1 and R2, respectively. Here, let T1 and T2 be a pair of transactions with role families R1 and R2, respectively. Suppose T1 precedes T2 in a schedule, i.e. for every pair of conflicting methods op1 and op2 from T1 and T2, respectively, op1 is performed prior to op2. Here, if the LIF relation R1 ⇒ R2 holds, no illegal information flow occur. If R1 ↪ R2, illegal information flow necessarily occur. R1 → R2 implies that illegal information flow might occur depending on in which order the transactions perform what methods.
Software learning tool to calculate isotope pattern for chemistry area of study
Authors: K. Massila, H. C. Soong, A. A. Azlianor, S. M. Suhaizan
Venue: Proceedings of the WSEAS International Conference on Applied Computing Conference (2008)

This article describes the anticipated software learning tool to calculate the isotope pattern for educational purposes. Despite the availability of the mass spectrometer to classify the existence of the isotopes from the particular elements, the projected software is indeed practical, beneficial and constructive for the academic learners as well for the intellectual researchers for rapidly defining the numbers of the possibility isotope patterns obtainable from a substance(chemical compound) for example methane (CH2). Hence, with the mathematical application (Cartesian Products) and the fundamental knowledge of chemistry that facilitate the calculations are feasible to obtain the isotope patterns without the aid of the mass spectrometer. For instance, the intended calculator called as Theoretical Isotope Generator (TIG) is fairly to be a calculation engine as well that is proficient to retrieve the information of the mass (atomic/molecular weight) from the substance specified based from the isotope patterns available. In conjunction of the patterns attained, the current mass spectrometer defines the acknowledged atomic isotopes of each identified elements which will be predefined for the software learning tools in order to regain the calculation for the molecular isotope patterns.
A New Self-adjusting Immune Genetic Algorithm
Authors: Shaojie Qiao, Changjie Tang, Shucheng Dai, Mingfang Zhu, Binglun Zheng
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks, Part II (2008)

The genetic algorithm based on immunity has recently been an appealing research methodology in evolutionary computation. Aiming to cope with the problems of genetic algorithms, i.e., the solution is apt to trap into a local optimum and the convergence speed is slow, this paper proposes a new self-adjusting immune genetic algorithm, called SaiGa (Self-adjusted immune Genetic algorithm), which seeks for an optimal solution with regard to complex problems such as the optimization of multidimensional functions by automatically tuning the crossover and the mutation probabilities, which can help avoid prematurity phenomena and maintain individual diversity. In particular, SaiGa introduces a variable optimization approach to improve the precision in terms of solving complex problems. The empirical results demonstrate that SaiGa can greatly accelerate convergence for finding an optimal solution compared with genetic algorithms and immune algorithms, achieve a better precision in function optimization, and avoid prematurity convergence.