ppxscal/embedding_network huggingface dataset:
Reconstruction of Dysphonic Speech by MELP
Authors: H. Irem Türkmen, M. Elif Karsligil
Venue: Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications (2008)

The chronical dysphony is the result of neural, structural or pathological effects on the vocal cords or larynx and it causes undesirable changes in the quality of speech. This paper presents a Mixed Excitation Linear Prediction (MELP) based system that reconstructs normally phonated speech from dysphonic speech, while preserving the individuality of the patient. The proposed system can be used as speech prosthesis for the patients who have lost the ability to produce voice. To reconstruct normally phonated speech from dysphonic speech, pitch generation using the perceived pitch relationship with formant frequencies, formant and voicing modification steps were performed for phonemes. The principle novelty of this study is to modify voiced phonemes' acoustic features while preserving unvoiced ones. Therefore voiced-unvoiced detection is performed for each phoneme.The proposed system is composed of three main parts. In the analysis phase the acoustic differences observed between normal and dysphonic speech are determined. Acoustic parameters of the dysphonic speech's voiced phonemes are modified in order to obtain a synthetic speech that is closer to normal speech. Finally, enhanced speech is synthesized by MELP.
Mining Edge-Weighted Call Graphs to Localise Software Bugs
Authors: Frank Eichinger, Klemens Böhm, Matthias Huber
Venue: Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I (2008)

An important problem in software engineering is the automated discovery of noncrashing occasional bugs. In this work we address this problem and show that mining of weighted call graphs of program executions is a promising technique. We mine weighted graphs with a combination of structural and numerical techniques. More specifically, we propose a novel reduction technique for call graphs which introduces edge weights. Then we present an analysis technique for such weighted call graphs based on graph mining and on traditional feature selection schemes. The technique generalises previous graph mining approaches as it allows for an analysis of weights. Our evaluation shows that our approach finds bugs which previous approaches cannot detect so far. Our technique also doubles the precision of finding bugs which existing techniques can already localise in principle.
Dialog Support for Deafblind Persons by Conveying Backchannels through Vibration
Authors: Misako Nambu, Akira Okamoto, Shigeki Miyoshi, Masatsugu Sakajiri
Venue: Proceedings of the 11th international conference on Computers Helping People with Special Needs (2008)

We conducted an experiment using vibration system, by which a deafblind participant, communicating through an interpreter, could directly receive back-channel feedback from a conversational partner. Statistical analysis of the interaction structure showed that the back-channel vibration increased his turn-taking and interactivity of communication. And, from a qualitative analysis of video data, we found that the experience of receiving back-channel feedback caused a change in his haptic behavior in usual communication. Our results indicate that low mental workload and learnability of this vibration system allow deaf-blind persons to improve their communication.
The MICKEY Stream Ciphers
Authors: Steve Babbage, Matthew Dodd
Venue: New Stream Cipher Designs: The eSTREAM Finalists (2008)

The family of stream ciphers MICKEY (which stands for Mutual Irregular Clocking KEYstream generator) is aimed at resource-constrained hardware platforms. It is intended to have low complexity in hardware, while providing a high level of security. It uses irregular clocking of shift registers, with some novel techniques to balance the need for guarantees on period and pseudorandomness against the need to avoid certain cryptanalytic attacks.
Updating Reduced Implicate Tries
Authors: Neil V. Murray, Erik Rosenthal
Venue: Proceedings of the 16th international conference on Automated Reasoning with Analytic Tableaux and Related Methods (2007)

The reduced implicate trie, introduced in [11], is a data structure that may be used as a target language for knowledge compilation. It has the property that, even when large, it guarantees fast response to queries. Specifically, a query can be processed in time linear in the size of the query regardless of the size of the compiled knowledge base.The knowledge compilation paradigm typically assumes that the "intractable part" of the processing be done once, during compilation. This assumption could render updating the knowledge base infeasible if recompilation is required. The ability to install updates without recompilation may therefore considerably widen applicability.In this paper, several update operations not requiring recompilation are developed. These include disjunction, substitution of truth constants, conjunction with unit clauses, reordering of variables, and conjunction with clauses.
Local Maps: New Insights into Mobile Agent Algorithms
Authors: Bilel Derbel
Venue: Proceedings of the 22nd international symposium on Distributed Computing (2008)

We address the problem of computing with mobile agents having small local maps. Several trade-offs concerning the radius of the local maps, the number of agents, the time complexity and the number of agent moves are proven. Our results are based on a generic simulation scheme allowing to transform any message passing algorithm into a mobile agent one. For instance, we show that using a near linear (resp. sublinear) number of agents having local maps of polylogarithmic (resp. sublinear) radius allows us to obtain a polylogarithmic (resp. sublinear) ratio between the time complexity of a message passing algorithm and its mobile agent counterpart. As a fundamental application, we show that there exists a universal algorithm that computes, from scratch, any global labeling function of any graph using n mobile agents knowing their o(n ¿ )-neighborhood (resp. without any neighborhood knowledge) in $\widetilde{O}(D)$ time (resp. $\widetilde{O}(\Delta+ D)$ expected time), where n,D,Δ are respectively the size, the diameter, the maximum degree of the graph and ¿ is an arbitrary small constant. For the leader election problem (resp. BFS tree construction), we obtain $\widetilde{O}(D)$ time algorithms under the additional restriction of using mobile agents having only log O(1) n (resp. $\widetilde{O}(n)$) memory bits.To the extent of our knowledge, the impact of local maps on mobile agent algorithms has not been studied in previous works. Our results prove that small local maps can have a strong global impact on the power of computing with mobile agents. Thus, we believe that the local map concept is likely to play an important role to a better understanding of the locality nature of mobile agent algorithms.
A Method for Multi-relational Classification Using Single and Multi-feature Aggregation Functions
Authors: Richard Frank, Flavia Moser, Martin Ester
Venue: Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases (2007)

This paper presents a novel method for multi-relational classification via an aggregation-based Inductive Logic Programming (ILP) approach. We extend the classical ILP representation by aggregation of multiple-features which aid the classification process by allowing for the analysis of relationships and dependencies between different features. In order to efficiently learn rules of this rich format, we present a novel algorithm capable of performing aggregation with the use of virtual joins of the data. By using more expressive aggregation predicates than the existential quantifier used in standard ILP methods, we improve the accuracy of multi-relational classification. This claim is supported by experimental evaluation on three different real world datasets.
Large Simple Binary Equality Words
Authors: Jana Hadravová, Štěpán Holub
Venue: Proceedings of the 12th international conference on Developments in Language Theory (2008)

Let w be an equality word of two nonperiodic binary morphisms g,h:{a,b}*¿Δ *. Suppose that no overflow occurs twice in w and that w contains at least 9 occurrences of a and at least 9 occurrences of b.Then either w = (ab) i a, or w = a i b j with $\gcd(i,j)=1$, up to the exchange of letters a and b.
Development of Contents Improving the Effectiveness of Self Learning, for the C Program Language
Authors: Saeron Han, Ilhyun Moon, Kwansun Choi, Dongsik Kim, Changwan Jeon, Min Hong, Sangyeon Woo, Heunggu Jeon
Venue: Proceedings of the 7th international conference on Advances in Web Based Learning (2008)

The web affords unique opportunities to assist students in learning. Due to the rapid proliferation of the web in recent years, many educators seek to improve the effectiveness of their instruction by providing innovative web-based course material to their students. In particular, many web-based educational contents are being developed. It helps to teach and train students. It is spreading widely due to repeated learning any time, any where. In this paper we implemented C functions and quizzes for checking comprehension of statements in a C programming lecture, developing scenario related concepts and algorithm comprehension. We used visual representation. The web-based contents were implemented as FLASH animations or Java applets.
A New Framework on Measuring Customer Perceived Value in Service Interface Design
Authors: Chang K. Cho, Minjoo Jung, Chai-Woo Lee, Sangwoo Bahn, Myung Hwan Yun
Venue: Proceedings of the 8th Asia-Pacific conference on Computer-Human Interaction (2008)

This paper explored the possible ways to apply various principles of NPD, NSP and UCD, and combined them appropriately in context of mobile internet service development in order to provide a high customer value via useful and usable service design. We investigated the characteristics of mobile internet and usability problems, and identified the benefits and limitations of previous UCD principles applied to mobile internet service development. Then applicability of CPV in mobile service design has been investigated in phases of divergent and convergent thinking. During the scenario-based ideation, potential customer values can be used as ideation stimuli in the process of structured brainstorming. In divergent thinking, CPV can be applied as evaluation criteria in comparing new ideas with alternative services. For the efficient implementation, work templates for accelerated front-end UCD are developed in co-operation with mobile service staffs in Korean mobile operator. This paper could be helpful for mobile industry and practitioners to develop and evaluate new mobile internet service which reflects users' implicit needs and CPV concept in the efficient and effective way.
A General Framework for Encoding and Evolving Neural Networks
Authors: Yohannes Kassahun, Jan Hendrik Metzen, Jose Gea, Mark Edgington, Frank Kirchner
Venue: Proceedings of the 30th annual German conference on Advances in Artificial Intelligence (2007)

In this paper we present a novel general framework for encoding and evolving networks called Common Genetic Encoding (CGE) that can be applied to both direct and indirect encoding methods. The encoding has important properties that makes it suitable for evolving neural networks: (1) It is complete in that it is able to represent all types of valid phenotype networks. (2) It is closed, i. e. every valid genotype represents a valid phenotype. Similarly, the encoding is closed under genetic operators such as structural mutation and crossover that act upon the genotype. Moreover, the encoding's genotype can be seen as a composition of several subgenomes, which makes it to inherently support the evolution of modular networks in both direct and indirect encoding cases. To demonstrate our encoding, we present an experiment where direct encoding is used to learn the dynamic model of a two-link arm robot. We also provide an illustration of how the indirect-encoding features of CGE can be used in the area of artificial embryogeny.
Dealing with Spoken Requests in a Multimodal Question Answering System
Authors: Roberto Gretter, Milen Kouylekov, Matteo Negri
Venue: Proceedings of the 13th international conference on Artificial Intelligence: Methodology, Systems, and Applications (2008)

This paper reports on experiments performed in the development of the QALL-ME system, a multilingual QA infrastructure capable of handling input requests both in written and spoken form. Our objective is to estimate the impact of dealing with automatically transcribed (i.e. noisy) requests on a specific question interpretation task, namely the extraction of relations from natural language questions. A number of experiments are presented, featuring different combinations of manually and automatically transcribed questions datasets to train and evaluate the system. Results (ranging from 0.624 to 0.634 F-measure in the recogniton of the relations expressed by a question) demonstrate that the impact of noisy data on question interpretation is negligible with all the combinations of training/test data. This shows that the benefits of enabling speech access capabilities, allowing for a more natural human-machine interaction, outweight the minimal loss in terms of performance.
Advanced Concurrency Control for Transactional Memory Using Transaction Commit Rate
Authors: Mohammad Ansari, Christos Kotselidis, Kim Jarvis, Mikel Luján, Chris Kirkham, Ian Watson
Venue: Proceedings of the 14th international Euro-Par conference on Parallel Processing (2008)

Concurrency control for Transactional Memory (TM) is investigated as a means for improving resource usage by adjusting dynamically the number of concurrently executing transactions. The proposed control system takes as feedback the measured Transaction Commit Rate to adjust the concurrency. Through an extensive evaluation, a new Concurrency Control Algorithm (CCA), called P-only Concurrency Control (PoCC), is shown to perform better than our other four proposed CCAs for a synthetic benchmark, and the STAMP and Lee-TM benchmarks.
Want a Better Software Development Process? Complement It
Authors: Granville Miller
Venue: IT Professional (2003)

Creating software development processes with complementary activities is the key to doing things the right way from the beginning. 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
AGENTFLY: a multi-agent airspace test-bed
Authors: David Šišlák, Přemysl Volf, Štěpán Kopřiva, Michal Pěchouček
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems: demo papers (2008)

The contribution presents a multi-agent technology in the domain of the air-traffic control of several autonomous aerial vehicles (manned as well as unmanned). The system has been validated mainly by the collision avoidance (CA) tasks. Several cooperative and non-cooperative CA methods have been integrated in the system to validate and compare their properties in the scalable experiments. The AGENTFLY system is suitable also for the developing and testing of algorithms for the collective flight control. The operation of the underlying multi-agent system has been integrated with freely available geographical and tactical data sources. The system provides real time 2D/3D visualization and also the web-access component.
Rule Calculus: Semantics, Axioms and Applications
Authors: Yi Zhou, Yan Zhang
Venue: Proceedings of the 11th European conference on Logics in Artificial Intelligence (2008)

We consider the problem of how a default rule can be deduced from a default theory. For this purpose, we propose an axiom system which precisely captures the deductive reasoning about default rules. We show that our axiomatic system is sound and complete under the semantics of the logic of here-and-there. We also study other important properties such as substitution and monotonicity of our system and prove the essential decision problem complexity. Finally, we discuss applications of our default rule calculus to various problems.
Improving Support of Appropriate Executive Decisions by Combining Artificial Immune Systems and Fuzzy Logic
Authors: Bernardo J. B. Caldas, Flávio R. S. Oliveira, Fernando B. de Lima Neto
Venue: Proceedings of the 2008 10th Brazilian Symposium on Neural Networks (2008)

This paper presents a novel approach to support appropriateness of executive decisions by using combined principles of Artificial Immune System (AIS) and Fuzzy Logic (FL). The main goal is to show that more Appropriate Executive Decisions (AED) may be obtained if strategic decision makers are equipped with supportive tools based on AIS and FL (Fuzzy-AED). In addition, this work aims at improving the quality of the system response by adding new features to the original version of the AED model. A proof of concept for Fuzzy-AED is also included here along with experiments carried out within a real business environment. Experimental results suggest that this hybrid approach to executive decision making could be used to assemble helpful executive decision systems that may be easily deployed to reduce some of the risks inherent in strategic decision making.
Asymptotic Improvement of Computations over Free Monads
Authors: Janis Voigtländer
Venue: Proceedings of the 9th international conference on Mathematics of Program Construction (2008)

We present a low-effort program transformation to improve the efficiency of computations over free monads in Haskell. The development is calculational and carried out in a generic setting, thus applying to a variety of datatypes. An important aspect of our approach is the utilisation of type class mechanisms to make the transformation as transparent as possible, requiring no restructuring of code at all. There is also no extra support necessary from the compiler (apart from an up-to-date type checker). Despite this simplicity of use, our technique is able to achieve true asymptotic runtime improvements. We demonstrate this by examples for which the complexity is reduced from quadratic to linear.
Constructing Strong KEM from Weak KEM (or How to Revive the KEM/DEM Framework)
Authors: Joonsang Baek, David Galindo, Willy Susilo, Jianying Zhou
Venue: Proceedings of the 6th international conference on Security and Cryptography for Networks (2008)

We propose a generic method that transforms a weakly secure KEM, i.e. a KEM which is secure against constrained chosen ciphertext attack (CCCA), to a strongly secure KEM, i.e. a KEM which is secure against full chosen ciphertext attack (CCA). The proposed method does not depend on the random oracle nor any other non- standard assumptions. Using this method, we obtain new efficient hybrid encryption schemes based on Kurosawa Desmedt and Hofheinz Kiltz weakly secure KEMs. These are the first hybrid encryption schemes which are as efficient as Kurosawa Desmedt and Hofheinz Kiltz encryption schemes, but whose security can be explained in the original KEM/DEM framework.
Inferences in shape spaces with applications to image analysis and computer vision
Authors: Shantanu H. Joshi
Venue:  (2007)

Shapes of boundaries can play an important role in characterizing objects in images. Shape analysis involves choosing mathematical representations of shapes, deriving tools for quantifying shape differences, and characterizing imaged objects according to the shapes of their boundaries. We describe an approach for statistical analysis of shapes of closed curves using ideas from differential geometry. In this thesis, we initially focus on characterizing shapes of continuous curves, both open and closed, in R2 and then propose extensions to more general elastic curves in Rn . Under appropriate constraints that remove shape-preserving transformations, these curves form infinite-dimensional, non-linear spaces, called shape spaces. We impose a Riemannian structure on the shape space and construct geodesic paths under different metrics. Geodesic paths are used to accomplish a variety of tasks, including the definition of a metric to compare shapes, the computation of intrinsic statistics for a set of shapes, and the definition of intrinsic probability models on shape spaces. Riemannian metrics allow for the development of a set of tools for computing intrinsic statistics for a set of shapes and clustering them hierarchically for efficient retrieval. Pursuing this idea, we also present algorithms to compute simple shape statistics&mdash;means and covariances&mdash;and derive probability models on shape spaces using local principal component analysis (PCA), called tangent PCA (TPCA). These concepts are demonstrated using a number of applications: (i) unsupervised clustering of imaged objects according to their shapes, (ii) developing statistical shape models of human silhouettes in infrared surveillance images, (iii) interpolation of endo- and epicardial boundaries in echocardiographic image sequences, and (iv) using shape statistics to test phylogenetic hypotheses. Finally, we present a framework for incorporating prior information about high-probability shapes in the process of contour extraction and object recognition in images. Here one studies shapes as elements of an infinite-dimensional, non-linear quotient space, and statistics of shapes are defined and computed intrinsically using differential geometry of this shape space. Prior models on shapes are constructed using probability distributions on tangent bundles of shape spaces. Similar to the past work on active contours, where curves are driven by vector fields based on image gradients and roughness penalties, we incorporate prior shape knowledge also in form of gradient fields on curves. Through experimental results, we demonstrate the use of prior shape models in estimation of object boundaries, and their success in handling partial obscuration and missing data. Furthermore, we describe the use of this framework in shape-based object recognition or classification. This Bayesian shape extraction approach is found to yield a significant improvement in detection of objects in presence of occlusions or obscurations.
A Concept Mapping Tool for Nursing Education
Authors: Norio Ishii, Saori Sakuma
Venue: Proceedings of the 5th international conference on Diagrammatic Representation and Inference (2008)

We have developed a concept mapping tool for nursing education. We first conducted a student attitude survey on concept mapping to identify points that the students felt were difficult. The three main problem areas were 1) thinking about correlations, 2) drawing maps, and 3) collecting reference materials. We therefore designed a tool that would help students overcome these difficulties. The tool, which makes use of Microsoft Excel VBA, enables students to easily draw, review, and revise concept maps.
A Fragile Watermarking Scheme for Audio Detection and Recovery
Authors: Fan Chen, HongJie He, HongXia Wang
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 5 - Volume 05 (2008)

In this paper, we propose a method for self-embedding an audio signal into itself as a means for protecting the content of audio signal. In the proposed algorithm, the host audio signal is divided into 4 segments, and the feature of every segment is embedded in the less significant bits (LSBs) of another segment that is randomly assigned based on the secret key. And the tamper detection can be performed by checking the surrounding segments of the tested segment and the segment that is carrying its feature. Experimental results show that the modified audio signal not only can be effectively detected, but also can be successfully recovered with acceptable quality.