ppxscal/embedding_network huggingface dataset:
Website Credibility, Active Trust and Behavioural Intent
Authors: Brian Cugelman, Mike Thelwall, Phil Dawes
Venue: Proceedings of the 3rd international conference on Persuasive Technology (2008)

This paper evaluates data from an international anti-poverty campaign to assess if common principles from e-marketing and persuasive technology apply to online social marketing. It focuses on the relationships between website credibility, users' active trust attitudes and behavioural intent. Using structural equation modelling, the evaluation found a significant relationship between these variables and suggests strategies for online behavioural change interventions.
Multi-level Coupling of Dynamic Data-Driven Experimentation with Material Identification
Authors: John G. Michopoulos, Tomonari Furukawa
Venue: Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007 (2007)

We describe a dynamic data-driven methodology that is capable of simultaneously determining both the parameters of a constitutive model associated with the response of a composite material, and the optimum experimental design that leads to the corresponding material characterization. The optimum design of experiments may contain two parts. One involving the identification of the parameters that are tunable prior to performing the experiment such as specimen characteristics and a priori loading path. The other is involving the parameters characterizing the experiment during the experiment itself such as the directionality of the loading path for the case of multi-axial loading machine. A multi-level coupled design optimization methodology is developed and applied to demonstrate the concept. Essential to the process is the development of objective functions that express the quality of the experimental procedure in terms of the uniqueness and distinguishability associated with the inverse solution of the constitutive model determination. The examples provided are based on the determination of the linear constitutive response of a laminate composite material.
A mean-field approach for the determination of the polarizabilities for the water molecule in liquid state
Authors: A. V. Gubskaya, P. G. Kusalik
Venue: Journal of Computational Methods in Sciences and Engineering (2004)

A mean-field method is presented describing the electrostatic environment experienced by water molecule in liquid state, which is used to extract the corresponding hyper- and high-order polarizabilities. Within this approach, MD computer simulations of liquid water samples for two standard water potentials at several different temperatures are performed to characterize the distributions (specifically average values) of local fields and field gradients. The electric response properties (including non-linear contributions up to fourth-order) are then calculated using ab initio techniques in conjunction with a charge perturbation variant of a finite field method. Sets of fixed charges are used to generate the desired electric fields and electric field gradients. Calculations of dipole polarizability, hyper- and principal components of high-order polarizabilities of the water molecule in gas and liquid phase conditions are carried out at MP2 and MP4 levels of theory; the values obtained for three different liquid phase models are compared with those for gas phase. For a liquid phase water molecule the first hyperpolarizability (&beta;) and first higher polarizability (A) increase markedly, actually changing sign. The second hyperpolarizability &gamma;) also increases but much less dramatically, and components of the second high-order polarizability tensor (B) demonstrate a rearrangement of contributions. We observe that a less symmetrical gradient model gives the most accurate representation of liquid-phase conditions. The excellent agreement of our gas-phase values with experimental results and the most accurate previous theoretical predictions is evident of the quality of our higher order polarizabilities and theoretical models.
STyLE-OLM: Interactive Open Learner Modelling
Authors: Vania Dimitrova
Venue: International Journal of Artificial Intelligence in Education (2003)

There is a strong argument in Artificial Intelligence in Education which advocates that computer-based learning systems need to adapt to the needs of learners if they are to provide for effective personalised instruction (Self, 1999a). Diagnosing a learner's cognitive capacity is a crucial issue in building adaptive systems. We have explored an interactive open learner modelling (IOLM) approach which conceives diagnosis as an interactive process involving both a computer system and a learner that discuss and together construct the learner model. This paper outlines the architecture of an interactive open learner modelling system and illustrates the method in a terminological domain. We discuss an evaluative study of an IOLM demonstrator - a system called STyLE-OLM. The results from the study demonstrate potential benefits of the method for improving the quality of the learner model and providing a means for fostering reflective thinking. We argue that IOLM is a fruitful approach which may be employed in intelligent learning environments both for obtaining a better model of a learner's cognitive state and engaging learners in reflective activities.
Many holes in hindley-milner
Authors: Sam Lindley
Venue: Proceedings of the 2008 ACM SIGPLAN workshop on ML (2008)

We implement statically-typed multi-holed contexts in OCaml using an underlying algebraic datatype augmented with phantom types. Existing approaches require dynamic checks or more complex type systems. In order to support concatenation we use two type parameters to represent the number of holes in a context as the difference between two Peano numbers. In order to support plugging a context with contexts of different arity we introduce a datatype of lists of contexts of length n with a total of m holes. Further, we extend our representation to allow holes to be marked with additional type information. As an example, we use these marks to implement statically-typed multi-holed XHTML contexts. We take advantage of Garrigue's relaxed value restriction.
A Faster Algorithm for RNA Co-folding
Authors: Michal Ziv-Ukelson, Irit Gat-Viks, Ydo Wexler, Ron Shamir
Venue: Proceedings of the 8th international workshop on Algorithms in Bioinformatics (2008)

The current pairwise RNA (secondary) structural alignment algorithms are based on Sankoff's dynamic programming algorithm from 1985. Sankoff's algorithm requires O(N 6) time and O(N 4) space, where N denotes the length of the compared sequences, and thus its applicability is very limited. The current literature offers many heuristics for speeding up Sankoff's alignment process, some making restrictive assumptions on the length or the shape of the RNA substructures. We show how to speed up Sankoff's algorithm in practice via non-heuristic methods, without compromising optimality. Our analysis shows that the expected time complexity of the new algorithm is O(N 4 ¿(N)), where ¿(N) converges to O(N), assuming a standard polymer folding model which was supported by experimental analysis. Hence our algorithm speeds up Sankoff's algorithm by a linear factor on average. In simulations, our algorithm speeds up computation by a factor of 3-12 for sequences of length 25-250.Availability: Code and data sets are available, upon request.
Natural or internal selection? the case of canalization in complex evolutionary systems
Authors: Alexander Riegler
Venue: Artificial Life (2008)

Using biological examples and theoretical arguments, the case is presented for extending the notion of natural selection to include internal selection in order to account for the evolution of complex systems. It is suggested that we take into consideration internal factors that arise from the hierarchical dynamics of complex systems. In addition to environmental selection, it is argued, decisive constraints are created by the system itself. Canalization is shown to be an indispensable ingredient for evolutionary processes in both biological and artificial complex systems. In artificial life systems canalization is not only an instrument for controlling complexity, it also increases the speed and stability of evolutionary processes.
Aspect-Based Personalized Text Summarization
Authors: Shlomo Berkovsky, Timothy Baldwin, Ingrid Zukerman
Venue: Proceedings of the 5th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems (2008)

This work investigates user attitudes towards personalized summaries generated from a coarse-grained user model based on document aspects. We explore user preferences for summaries at differing degrees of fit with their stated interests, the impact of length on user ratings, and the faithfulness of personalized and general summaries.
Finding Text Boundaries and Finding Topic Boundaries: Two Different Tasks?
Authors: Alexandre Labadié, Violaine Prince
Venue: Proceedings of the 6th international conference on Advances in Natural Language Processing (2008)

The goal of this paper is to demonstrate that usual evaluation methods for text segmentation are not adapted for every task linked to text segmentation. To do so we differentiated the task of finding text boundaries in a corpus of concatenated texts from the task of finding transitions between topics inside the same text. We worked on a corpus of twenty two French political discourses trying to find boundaries between them when they are concatenated, and to find topic boundaries inside them when they are not. We compared the results of our distance based method to the well known c99 algorithm.
Robust watermarking of audio with blind self-authentication
Authors: O. Farooq, S. Datta, J. Blackledge
Venue: Proceedings of the 7th WSEAS International Conference on Electronics, Hardware, Wireless and Optical Communications (2008)

In this paper robust audio watermarking based on chirp signal is proposed which also includes capability of blind self-authentication. Watermark sequence is extracted from the original audio signal based on sub-bands energy obtained by using wavelet decomposition. The watermarking scheme is such that the watermark sequence remains unchanged for the original and watermarked audio. This enables two independent extraction processes for this sequence. A total match in the sequence extracted by the two procedures ensures the authenticity of audio data and any mismatch indicates tampering. Different simulated attacks were carried out on the watermarked audio and in all the cases tampering was detected by the proposed technique. The test audio signals were selected from the Speech Quality Assessment Material (SQAM) for embedding watermark. The scheme was found to be robust for attacks such as up-sampling, down-sampling, scaling, filtering and additive noise.
Recognizing Humor Without Recognizing Meaning
Authors: Jonas Sjöbergh, Kenji Araki
Venue: Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory (2007)

We present a machine learning approach for classifying sentences as one-liner jokes or normal sentences. We use no deep analysis of the meaning to try to see if it is humorous, instead we rely on a combination of simple features to see if these are enough to detect humor. Features such as word overlap with other jokes, presence of words common in jokes, ambiguity and word overlap with common idioms turn out to be useful. When training and testing on equal amounts of jokes and sentences from the British National Corpus, a classification accuracy of 85% is achieved.
Using Social Networks to Organize Researcher Community
Authors: Xian-Ming Xu, Justin Zhan, Hai-Tao Zhu
Venue: Proceedings of the IEEE ISI 2008 PAISI, PACCF, and SOCO international workshops on Intelligence and Security Informatics (2008)

Social Network is being a popular word in WEB 2.0 era. Various social network websites connect us and our friends together. A buzzword which describes the idea is "communicate with anyone anywhere". By using social network websites like Facebook or blog, we can find out the communities which share the same interests with us. In the academic area, people sharing the similar research interest can also form community which is one type of social network. In this paper, we are trying to identify the people with similar research interest and help them build up such kind of social network. The information sources mainly come from the research papers and articles which can be searched freely from some research organizations' websites, such as ACM web Portal and IEEE web Portal. In addition, we would like to find out more personal information about experts in particular research field by using common search tools such as Google and Live Search.
Evolutionary Induction of Decision Trees for Misclassification Cost Minimization
Authors: Marek Kretowski, Marek Grześ
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I (2007)

In the paper, a new method of decision tree learning for cost-sensitive classification is presented. In contrast to the traditional greedy top-down inducer in the proposed approach optimal trees are searched in a global manner by using an evolutionary algorithm (EA). Specialized genetic operators are applied to modify both the tree structure and tests in non-terminal nodes. A suitably defined fitness function enables the algorithm to minimize the misclassification cost instead of the number of classification errors. The performance of the EA-based method is compared to three well-recognized algorithms on real-life problems with known and randomly generated cost-matrices. Obtained results show that the proposed approach is competitive both in terms of misclassification cost and compactness of the classifier at least for some datasets.
Teaching a Pet Robot through Virtual Games
Authors: Anja Austermann, Seiji Yamada
Venue: Proceedings of the 8th international conference on Intelligent Virtual Agents (2008)

In this paper, we present a human-robot teaching framework that uses "virtual" games as a means for adapting a robot to its user through natural interaction in a controlled environment. We present an experimental study in which participants instruct an AIBO pet robot while playing different games together on a computer generated playfield. By playing the games in cooperation with its user, the robot learns to understand the user's natural way of giving multimodal positive and negative feedback. The games are designed in a way that the robot can reliably anticipate positive or negative feedback based on the game state and freely explore its user's reward behavior by making good or bad moves. We implemented a two-staged learning method combining Hidden Markov Models and a mathematical model of classical conditioning to learn how to discriminate between positive and negative feedback. After finishing the training the system was able to recognize positive and negative reward based on speech and touch with an average accuracy of 90.33%.
Implementation Challenges: Competing Structures When New Public Management Meets eGovernment
Authors: Andreas Ask, Åke Grönlund
Venue: Proceedings of the 7th international conference on Electronic Government (2008)

This article discusses practices, opportunities and challenges in local eGovernment project management; the development towards eGovern ment and "the 24/7 agency". Analyzing a case against eGovernment success factors we find seven "critical issues"; political timing, resource allocation, political mandate, distinction between administrative and political responsibilities, coordination of departments, dependence on providers, and use of standards. These are issues where development is open for local choice, influences of strong stakeholders, and chance. This situation is a consequence of the prevailing strategic model for the public sector, New Public Manage ment. This model by design leaves these issues in a void which has to be filled by negotiations among many actors with different roles, goals, and action space. The general lesson is that the void needs to be filled strategically; to reduce the risk level and increase the ability to implement policy or it will be open for unexpected turns of events.
Addition and Deletion of Agent Memories to Realize Autonomous Decentralized Manufacturing Systems
Authors: Yamamoto Hidehiko
Venue: Proceedings of the 21st international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: New Frontiers in Applied Artificial Intelligence (2008)

This paper describes a method to control Autonomous decentralized Flexible Manufacturing System (AD-FMS) by using a memory to determine a priority ranking for competing hypotheses. The aim is to increase the reasoning efficiency of a system the author calls reasoning to anticipate the future (RAF) which controls automatic guided vehicles (AGVs) in AD-FMSs. The system includes memory data of past production conditions and AGV actions. Using these memory data, the system reorders hypotheses by giving the highest priority ranking to the hypothesis that is most likely to be true. The system was applied to an AD-FMS that was constructed on a computer. The results showed that, compared with conventional reasoning, this reasoning system reduced the number of hypothesis replacements until a true hypothesis was reached.
Sequence disambiguation and pattern completion by cooperation between autoassociative and heteroassociative memories of functionally divided hippocampal CA3
Authors: Toshikazu Samura, Motonobu Hattori, Shun Ishizaki
Venue: Neurocomputing (2008)

The hippocampus memorizes event sequences and some events are shared by a few sequences. When a sequence is retrieved from the linked sequences, ambiguity of sequences becomes a serious problem because the shared events have some possible ways to retrieve other events. We have focused on location dependency elucidated from the hippocampus and suggested that CA3 is functionally divided into autoassociative and heteroassociative memories. Computer simulation results show that the functionally divided CA3 concurrently enables both sequence disambiguation and pattern completion. Consequently, it demonstrates that cooperation between both memories of CA3 brings out the abilities of sequence disambiguation and pattern completion in the hippocampus.
Middleware Support for Pluggable Non-Functional Properties in Wireless Sensor Networks
Authors: Pruet Boonma, Junichi Suzuki
Venue: Proceedings of the 2008 IEEE Congress on Services - Part I (2008)

Wireless sensor networks (WSN) imposes stringent constraints on efficiency, memory footprint and power consumption. Since the need to satisfy these constraints often results in tightly coupled designs, WSN applications tend to be inflexible; it is hard to flexibly reuse, introduce, customize and replace various non-functional properties (e.g., data routing, concurrency, data aggregation and event filtering) for developing and maintaining WSN applications. In order to address this issue, this paper proposes the TinyDDS middleware, which decouples various non-functional properties from WSN applications and allows those applications to flexibly reuse and transparently configure non-functional properties according to their own requirements. Without breaking the generic architecture of TinyDDS, the proposed pluggable framework allows WSN applications to have fine-grained control over non-functional properties and specialize in their own requirements. Currently, TinyDDS supports two types of non-functional properties: application-level and middleware-level non-functional properties.
Geometric scale-space framework for the analysis of hyperspectral imagery
Authors: Miguel Velez-Reyes
Venue:  (2008)

This work introduces a framework for a fast and algorithmically scalable multiscale representation and segmentation of hyperspectral imagery. The framework is based on the scale-space representation generated by geometric partial differential equations (PDEs) and state of the art numerical methods such as semi-implicit discretization methods, preconditioned conjugated gradient, and multigrid solvers. Multi-scale segmentation of hyperspectral imagery exploits the fact that different image structures exists only at different image scales or resolutions, enabling a better exploitation of the high spatial-spectral information content in hyperspectral imagery. Higher level processes in hyperspectral imagery such as classification, registration, target detection, restoration, and change detection can improve significatively; by working on the regions (objects) identified by the segmentation process, rather than with the image pixels, as it is traditionally done. The main contribution of this work is the introduction of a framework, where vector-valued geometric scale-spaces are seamlessly integrated with an algorithm for multiscale segmentation of hyperspectral imagery, in a fast and scalable way that makes feasible an object-oriented approach for higher level processes in hyperspectral image processing.
Simplified Submission of Inputs to Protocols
Authors: Douglas Wikström
Venue: Proceedings of the 6th international conference on Security and Cryptography for Networks (2008)

Consider an electronic election scheme implemented using a mix-net; a large number of voters submit their votes and then a smaller number of servers compute the result. The mix-net accepts an encrypted vote from each voter and outputs the set of votes in sorted order without revealing the permutation used. To ensure a fair election, the votes of corrupt voters should be independent of the votes of honest voters, i.e., some type of non-malleability or plaintext awareness is needed. However, for efficiency reasons the servers typically expect inputs from some homomorphic cryptosystem, which is inherently malleable.In this paper we consider the problem of how non-malleability can be guaranteed in the submission phase and still allow the servers to start their computation with ciphertexts of the homomorphic cryptosystem. This can clearly be achieved using general techniques, but we would like a solution which is: (i) provably secure under standard assumptions, (ii) non-interactive for submittors (iii) very efficient for all parties in terms of computation and communication.We give the first solution to this problem which has all these properties. Our solution is surprisingly simple and can be based on various Cramer-Shoup cryptosystems. To capture its security properties we introduce a variation of CCA2-security.
Fingerprint Matching Using Global Minutiae and Invariant Moments
Authors: JuCheng Yang, JinWook Shin, ByoungJun Min, JoonWhoan Lee, DongSun Park, Sook Yoon
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

In this paper, a fingerprint matching algorithm based on global minutiae and invariant moments is proposed. Although minutiae features based method is popular in most case of fingerprint matching, minutiae are difficult to be extracted robustly in low quality image and easy to deduce false recognition. Combination of other discriminatory features can effectively strengthen the performance of the matching. A fingerprint image is first preprocessed for minutiae and reference point determination. Then, the reference point is used to align the template fingerprint and input fingerprint. Based on the aligned fingerprints, combined features are constructed from all the minutiae and their invariant moments, and a global matching algorithm is proposed to match the template and input fingerprint. The experimental results show higher performance comparing with a public algorithm over FVC2004 databases.