ppxscal/embedding_network huggingface dataset:
A new characteristic property of rich words
Authors: Michelangelo Bucci, Alessandro De Luca, Amy Glen, Luca Q. Zamboni
Venue: Theoretical Computer Science (2009)

Originally introduced and studied by the third and fourth authors together with J. Justin and S. Widmer (2008), rich words constitute a new class of finite and infinite words characterized by containing the maximal number of distinct palindromes. Several characterizations of rich words have already been established. A particularly nice characteristic property is that all 'complete returns' to palindromes are palindromes. In this note, we prove that rich words are also characterized by the property that each factor is uniquely determined by its longest palindromic prefix and its longest palindromic suffix.
Analysis of a collaborative workflow process with distributed actors
Authors: Hajo A. Reijers, Minseok Song, Byungduk Jeong
Venue: Information Systems Frontiers (2009)

Current workflow management technology offers rich support for process-oriented coordination of distributed teamwork. In this paper, we evaluate the performance of an industrial workflow process where similar tasks can be performed by various actors at many different locations. We analyzed a large workflow process log with state-of-the-art mining tools associated with the ProM framework. Our analysis leads to the conclusion that there is a positive effect on process performance when workflow actors are geographically close to each other. Our case study shows that the use of workflow technology in itself is not sufficient to level geographical barriers between team members and that additional measures are required for a desirable performance.
Impact of Prior Channel Information for Speaker Identification
Authors: C. Vaquero, N. Scheffer, S. Karajekar
Venue: Proceedings of the Third International Conference on Advances in Biometrics (2009)

Joint factor analysis (JFA) has been very successful in speaker recognition but its success depends on the choice of development data. In this work, we apply JFA to a very diverse set of recording conditions and conversation modes in NIST 2008 SRE, showing that having channel matched development data will give improvements of about 50% in terms of Equal Error Rate against a Maximum a Posteriori (MAP) system, while not having it will not give significant improvement. To provide robustness to the system, we estimate eigenchannels in two ways. First, we estimate the eigenchannels separately for each condition and stack them. Second, we pool all the relevant development data and obtain a single estimate. Both techniques show good performance, but the former leads to lower performance when working with low-dimension channel subspaces, due to the correlation between those subspaces.
Optimality Theory and Vector Semirings
Authors: Wolfgang Seeker, Daniel Quernheim
Venue: Proceeding of the 2009 conference on Finite-State Methods and Natural Language Processing: Post-proceedings of the 7th International Workshop FSMNLP 2008 (2009)

As [1] and [2] have shown, some applications of Optimality Theory can be modelled using finite state algebra provided that the constraints are regular. However, their approaches suffered from an upper bound on the number of constraint violations. We present a method to construct finite state transducers which can handle an arbitrary number of constraint violations using a variant of the tropical semiring as its weighting structure. In general, any Optimality Theory system whose constraints can be represented by regular relations, can be modelled this way. Unlike [3], who used roughly the same idea, we can show, that this can be achieved by using only the standard (weighted) automaton algebra.
On the design and alphabet size of Roth-Skachek nearly MDS expander codes
Authors: Marc A. Armand
Venue: Proceedings of the 13th WSEAS international conference on Applied mathematics (2008)

Recently, Roth and Skachek presented an expander-based code construction which, by an appropriate choice of constituent code parameters, yields linear-time encodable and decodable codes that lie within an Ε away from the Singleton bound and have an alphabet of size 2O((log 1/Ε)/Ε3) where Ε > 0 is sufficiently small. We (i) show that the set of constituent code parameters chosen by Roth and Skachek is not completely correct, (ii) resolve the discrepancies in their work, and (iii) show that an asymptotic reduction in the alphabet size may be obtained for their linear-time decodable codes for rates nearly 1.
Fuzzy system modelling of drinking water consumption prediction
Authors: Zekíi Şen, Abdüsselam Altunkaynak
Venue: Expert Systems with Applications: An International Journal (2009)

It is important to determine the amount of daily drinking water requirement for a person not only for the health of people but also for the planning and management of the water resources. Physical activity, body weight and temperature play significant role in drinking water consumption rates. Human activity variables are most often given in crisp numerical interval classifications for water consumption calculations. The aim of this paper is to establish a fuzzy model for predicting the water consumption rates based on data at the hand. The fuzzy sets such as low, medium, high can be used to quantify vague, imprecise or incomplete descriptions which are collectively referred to as fuzzy data in the literature. Fuzzy model inputs are considered as the physical activity, body weight and temperature, whereas the output is the water consumption levels. The fuzzy sets are chosen in an appropriate manner and the prediction model of water consumption is compared with the actual consumption amounts. It is not possible to treat such linguistic fuzzy data by statistical methods. It is observed that the model predictions have less than 5% relative error. The model is tested with an independent data set for its successful prediction capability.
Model Management Based on a Visual Transformation Language
Authors: Michał Śmiałek, Andrzej Kardas
Venue: Proceeding of the 2005 conference on Software Engineering: Evolution and Emerging Technologies (2005)

Modeling becomes the most prominent method of dealing with software complexity. Models for software systems can be created on different levels of abstraction and in different phases of the software development process. In order to manage these various models effectively we need to apply methods for keeping them coherent and traceable. The current paper proposes a method for defining and executing transformations between models written in the currently most popular modeling language (UML). We propose a general purpose transformation language that allows for specifying transformation mappings between different models. This language has a visual (MOF-based) notation and allows for defining transformation templates and rules. With this language, the software developers are capable of determining traceability links between individual model elements. Moreover, the transformations can be executed automatically to high extent, with the use of a dedicated tool that extends a standard UML CASE tool.
Robust performance characterization of PID controllers in the frequency domain
Authors: Tooran Emami, John M. Watkins
Venue: WSEAS Transactions on Systems and Control (2009)

In this paper a method is introduced for finding all proportional integral derivative (PID) controllers that satisfy a robust performance constraint for a given single-input-single-output transfer function of any order with time-delay. This problem can be solved by finding all achievable PID controllers that simultaneously stabilize the closed-loop characteristic polynomial and satisfy constraints defined by a set of related complex polynomials. A key advantage of this procedure is that it only depends on the frequency response of the system and does not require the plant transfer function coefficients. If the plant transfer function is given, the procedure is still appropriate. The ability to include the time-delay in the nominal model of the system will often allow for designs with reduced conservativeness in the plant uncertainty and an increase in size of the set of all PID controllers that robustly meet the performance requirements.
Structure segmentation and recognition in images guided by structural constraint propagation
Authors: Olivier Nempont, Jamal Atif, Elsa Angelini, Isabelle Bloch
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

In some application domains, such as medical imaging, the objects that compose the scene are known as well as some of their properties and their spatial arrangement. We can take advantage of this knowledge to perform the segmentation and recognition of structures in medical images. We propose here to formalize this problem as a constraint network and we perform the segmentation and recognition by iterative domain reductions, the domains being sets of regions. For computational purposes we represent the domains by their upper and lower bounds and we iteratively reduce the domains by updating their bounds. We show some preliminary results on normal and pathological brain images.
In-world data services in virtual environments
Authors: John Fisher, Sebastien Goasguen
Venue: Proceedings of the 47th Annual Southeast Regional Conference (2009)

This paper presents a set of data services that allow access to real life digital information within virtual environments. Since the emergence of virtual environments, technology has continued to evolve offering more powerful and more sophisticated virtual worlds. No longer just a tool for researchers, these environments have since become a presence in people's lives. Some of these may include video games while others are more social, like Second Life&trade; and Microsoft's New Xbox Experience. Data services provide real life synchronicity making the virtual environment a better interface for researchers and educators. In this paper we investigate how to make data sources available in virtual environments, monitor and virtually represent information, we also study the limitations of these data services and the ability to transfer data in parallel between real and virtual life. The implementation presented is based on Second Life (SL) a successful virtual environment created by Linden Labs. Among its features, SL gives its users the ability to create virtual programmable objects and to use basic http based data transfers. To illustrate our study, we use three different objects: a weather object that calls the NOAA's web service, a sensor object that virtually represents an array of sensors deployed throughout South Carolina, and finally a parallel data transfer object that demonstrates some intrinsic limitations of Second Life.
Analysis of call scenario in NGN network
Authors: Skënder Rugova, Arianit Maraj
Venue: Proceedings of the 8th WSEAS international conference on Electronics, hardware, wireless and optical communication (2009)

Next Generation Network (NGN) is a safe technology for future. Market demands always change. Subscribers require different services with high quality. NGN network technology supports those services. In its efforts to keep the leading position in Kosova's competitive telecommunication market, TK (Telecom of Kosova) is implementing its technological development strategy and migration to full IP NGN network. Scope of this paper is to describe the network connectivity in TK NGN. At the beginning is described the architecture of TK (Telecom of Kosova) NGN network with its corresponding elements and functionality. Such standard-based, open architecture core network enables the integration of Voice and Multimedia services on a single network infrastructure. Later, are described two call scenarios in NGN network in telecom of Kosova: NGN to NGN and NGN to PSTN (Public Switched Telephone Network) call scenario.
Hybrid Game Theory and D-S Evidence Approach to Multiple UCAVs Cooperative Air Combat Decision
Authors: Xingxing Wei, Haibin Duan, Yanran Wang
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III (2009)

Mission decision-making is one of the most important techniques for cooperative combat of multiple unmanned combat aerial vehicles (UCAVs), while game theory is an efficient method in solving mission decision-making. In this paper, the game theory is applied to the air combat decision of multiple UCAVs. Then a weapon model for UCAVs' air-to-air missiles is proposed to obtain the basic probability value of the D-S evidence theory. In order to obtain the Nash equilibrium point, the bimatrix problem is transferred into an optimization problem. In this way, the function "linprog" in MATLAB can be used to obtain the optimal solution, which can greatly simplify the steps of solving the bimatrix problem. Finally, the optimal strategy is obtained by optimizing calculation. Series of experimental results demonstrate the feasibility and effectiveness of the proposed approach in solving the multiple UCAVs cooperative air combat decision problem.
Preventing Cheating in Computational Visual Cryptography
Authors: Chin-Chen Chang, Tzung-Her Chen, Li-Jen Liu
Venue: Fundamenta Informaticae (2009)

Visual Cryptography (VC) has drawn much attention for providing the service of secret communication. Basically, VC is the process of encoding a secret into several meaningless shares and later decoding the secret by superimposing all or some of the shares without any computation involved. VC has been adopted to support some practical applications, such as image authentication, visual authentication, image hiding, and digital watermarking. Unfortunately, in many applications, VC has been shown to suffer from the "cheating problem" in which the disclosed secret image may be altered by malicious insiders who are called "cheaters." While ubiquitous computing has been well developed, it has recently occurred to people in both academia and industry that research could benefit more from computational VC by introducing light-weight computation costs in the decoding phase. In this paper, a simple scheme is proposed to conquer the cheating problem by facilitating the capability of share authentication. It is worthwhile to note that the proposed scheme can identify for certain whether cheating attacks have occurred or not, while other schemes that have the same objective frequently provide a vague answer. In addition, the proposed scheme effectively addresses the two main problems of VC, i.e., the inconvenience of meaningless share management and the challenge of achieving difficult alignment.
Many-Valued Concept Lattices for Conceptual Clustering and Information Retrieval
Authors: Nizar Messai, Marie-Dominique Devignes, Amedeo Napoli, Malika Smail-Tabbone
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

In this paper we present an extension of the Galois connection to deal with many-valued formal contexts. We define a many-valued Galois connection with respect to similarity between attribute values in a many-valued context. Then, we define many-valued formal concepts and many-valued concept lattices. Depending on a similarity threshold, many-valued concept lattices may have different levels of precision. This feature makes them very useful for multilevel conceptual clustering. Many-valued concept lattices are also used in a new lattice-based information retrieval approach for efficiently answering complex queries.
A Danish phonetically annotated spontaneous speech corpus (DanPASS)
Authors: Nina Grønnum
Venue: Speech Communication (2009)

A corpus is described consisting of non-scripted monologues and dialogues, recorded by 27 speakers, comprising a total of 73,227 running words, corresponding to 9h and 46min of speech. The monologues were recorded as one-way communication with an unseen partner where the speaker performed three different tasks: (s)he described a network consisting of various geometrical shapes in various colours, (s)he guided the listener through four different routes in a virtual city map, and (s)he instructed the listener how to build a house from its individual pieces. The dialogues are replicas of the HCRC map tasks. Annotation is performed in Praat. The sound files are segmented into prosodic phrases, words, and syllables. The files are supplied, in separate interval tiers, with an orthographical representation, detailed part-of-speech tags, simplified part-of-speech tags, a phonemic notation, a semi-narrow phonetic notation, a symbolic representation of the pitch relation between each stressed and post-tonic syllable, and a symbolic representation of the phrasal intonation.
Facilitating Knowledge Construction by Providing Individualized Services
Authors: Weidong Pan, Igor Hawryszkiewycz
Venue: Proceeding of the 2006 conference on Learning by Effective Utilization of Technologies: Facilitating Intercultural Understanding (2006)

In this paper, we propose an agent-based approach to facilitating individual learner's knowledge construction through individualized services. The services go beyond simply presenting course materials, but supply a wider range of technological facilities, tools and services to support the learning process. A learning process specification language is used to describe rules related to what supportive services should provide for which learners at what moment in a learning process. According to the rules, agents provide individualized services for online learners.
A conceptual graph feature model for use in developing software product-lines
Authors: Harry Delugach
Venue:  (2008)

Software product-line methods have proven to be an effective approach to developing software product families. At the core of these methods is a feature model that describes the product-line. One of the more popular models is the FODA feature model proposed by the Feature Oriented Design and Analysis (FODA) method. A significant attraction of this model is its simplicity; however, this simplicity has also led to many proposed extensions that seek to expand the expressivity of the model. Unfortunately, these extensions are often incompatible with each other or with the goals of the original FODA feature model designers. This dissertation proposes a new feature model that is by its nature more flexible and more expressive than the FODA model and one that can embrace new feature model requirements in a consistent manner. This dissertation proposes a conceptual graph-based feature model. Conceptual graphs share a close relationship with natural languages and, as a result, they are very easy to read. This makes them an excellent knowledge-based representation that is easily mastered by software engineers responsible for building and maintaining feature models. Conceptual graphs are also based on first-order logic and therefore have clear and unambiguous semantics&mdash;a requirement for developing product specifications. The resulting conceptual graph feature model (CGFM) proposed by this dissertation supports the consolidated list of feature model requirements derived from the original FODA model plus many of the proposed extensions to that model. An extensible conceptual graph modeling language (CGML) was also developed to describe the domain vocabulary, constraints, and rules which make up the CGFM. In order to demonstrate the modeling capabilities of the CGFM, a prototype of a conceptual graph feature modeling system was developed. An example camera product-line was modeled using this modeling system. The example demonstrated the flexibility of the language and directly showed that the language satisfied the majority of the requirements of the FODA model and the proposed extensions to that model.
Unsupervised Real-Time Unusual Behavior Detection for Biometric-Assisted Visual Surveillance
Authors: Tsz-Ho Yu, Yiu-Sang Moon
Venue: Proceedings of the Third International Conference on Advances in Biometrics (2009)

This paper presents a novel unusual behaviors detection algorithm to acquire biometric data for intelligent surveillance in real-time. Our work aims to design a completely unsupervised method for detecting unusual behaviors without using any explicit training dataset. To this end, the proposed approach learns from the behaviors recorded in the history; such that the definition of unusual behavior is modeled according to previous observations, but not a manually labeled dataset. To implement this, pyramidal Lucas-Kanade algorithm is employed to estimate the optical flow between consecutive frames, the results are encoded into flow histograms. Leveraging the correlations between the flow histograms, unusual actions can be detected by applying principal component analysis (PCA). This approach is evaluated under both indoor and outdoor surveillance scenarios. It shows promising results that our detection algorithm is able to discover unusual behaviors and adapt to changes in behavioral pattern automatically.
Double barrier option under regime-switching exponential mean-reverting process
Authors: P. Eloe, R. H. Liu, J. Y. Sun
Venue: International Journal of Computer Mathematics (2009)

In this paper, we study a double barrier option when the underlying asset price follows a regime-switching exponential mean-reverting process. Our method is a combination of analysis of a deterministic boundary value problem with a probabilistic approach. In this setting, the double barrier option prices satisfy a system of m linear second-order differential equations with variable coefficients and with Dirichlet boundary conditions, where m is the number of regimes considered for the economy. We prove the existence of a smooth solution of the boundary value system by the method of upper and lower solutions; we proceed to construct monotonic sequences of upper and lower solutions that converge to true solutions, respectively. The uniqueness of the solution is established by applying Dynkin's formula. This proof by construction also provides a numerical procedure to compute approximate option values. An important feature of the proposed numerical method is that the true option values are bracketed by the upper and the lower solutions. Examples are provided to illustrate the method.
Iterated discriminants
Authors: Daniel Lazard, Scott McCallum
Venue: Journal of Symbolic Computation (2009)

It is shown that the discriminant of the discriminant of a multivariate polynomial has the same irreducible factors as the product of seven polynomials each of which is defined as the GCD of the generators of an elimination ideal. Under relatively mild conditions of genericity, three of these polynomials are irreducible and generate the corresponding elimination ideals, while the other four are equal to one. Moreover the irreducible factors of two of these polynomials have multiplicity at least two in the iterated discriminant and the irreducible factors of two others of the seven polynomials have multiplicity at least three. The proof involves an extended use of the notion of generic point of an algebraic variety and a careful study of the singularities of the hypersurface defined by a discriminant, which may be interesting by themselves.
Genetic algorithm-based boundary extraction of plaque in intravascular ultrasound image
Authors: Ryosuke Kubota, Eiji Uchino, Noriaki Suetake, Genta Hashimoto, Takafumi Hiro, Masunori Matsuzaki
Venue: Proceedings of the 7th WSEAS international conference on System science and simulation in engineering (2008)

A novel method for plaque boundary extraction in an intravascular ultrasound image is proposed. The present method is based on a genetic algorithm with a fitness function of a statistical discriminant measure. Fine extraction results are obtained without any medical doctor's expert knowledge.