ppxscal/embedding_network huggingface dataset:
A Compact Genetic Algorithm with Elitism and Mutation Applied to Image Recognition
Authors: Rafael R. Silva, Heitor S. Lopes, Carlos R. Erig Lima
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence (2008)

The problem of object recognition in images is a hard problem frequently found in industrial and academic application. This work presents the application of an extension of the Compact Genetic Algorithm (emCGA) to three problems of object recognition in real images. Results are compared with an exhaustive search algorithm and another CGA. Results suggested the efficiency of emCGA for this problem and encourages future developments.
Emotion Recognition through Multiple Modalities: Face, Body Gesture, Speech
Authors: Ginevra Castellano, Loic Kessous, George Caridakis
Venue: Affect and Emotion in Human-Computer Interaction: From Theory to Applications (2008)

In this paper we present a multimodal approach for the recognition of eight emotions. Our approach integrates information from facial expressions, body movement and gestures and speech. We trained and tested a model with a Bayesian classifier, using a multimodal corpus with eight emotions and ten subjects. Firstly, individual classifiers were trained for each modality. Next, data were fused at the feature level and the decision level. Fusing the multimodal data resulted in a large increase in the recognition rates in comparison with the unimodal systems: the multimodal approach gave an improvement of more than 10% when compared to the most successful unimodal system. Further, the fusion performed at the feature level provided better results than the one performed at the decision level.
Memetic Algorithm-Based Image Watermarking Scheme
Authors: Qingzhou Zhang, Ziqiang Wang, Dexian Zhang
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks (2008)

Watermarking technology is the most efficient way to protect the ownership of multimedia data. In this paper, a novel image watermarking scheme using the Discrete Wavelet Transform (DWT) and memetic algorithm (MA) is introduced. The watermark is embedded to subband coefficients of subimage which is extracted from the original image by using DWT, and watermark extraction is efficiently performed via memetic algorithm. Experimental results show that the proposed watermarking scheme makes an almost invisible difference between the watermarked image and the original image, and is robust to common image processing operations.
Implementing Spi Calculus Using Nominal Techniques
Authors: Temesghen Kahsai, Marino Miculan
Venue: Proceedings of the 4th conference on Computability in Europe: Logic and Theory of Algorithms (2008)

The aim of this work is to obtain an interactive proof environment based on Isabelle/HOL for reasoning formally about cryptographic protocols, expressed as processes of the spi calculus (a ¿-calculus with cryptographic primitives). To this end, we formalise syntax, semantics, and hedged bisimulation, an environment-sensitive bisimulation which can be used for proving security properties of protocols. In order to deal smoothly with binding operators and reason up-to ¿-equivalence of bound names, we adopt the new Nominal datatype package. This simplifies both the encoding, and the formal proofs, which turn out to correspond closely to "manual proofs".
Hybrid Support Vector Machine and General Model Approach for Audio Classification
Authors: Xin He, Ling Guo, Xianzhong Zhou, Wen Luo
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

In recent years, the searching and indexing techniques for multimedia data are getting more attention in the area of multimedia databases. As many research works were done on the content-based retrieval of image and video data, less attention was received to the content-based retrieval of audio data. Audio is one of important multimedia information and there is a growing need for automatic audio indexing and retrieval techniques in recent years. Audio data contain abundant semantics and the audio signal processing can reduce computational complexity, so effective and efficient indexing and retrieval techniques for audio data are getting more attention. In this paper, problems of audio retrieval are discussed firstly. Then, main audio characteristics and features are introduced. Finally the combination of Support Vector Machine and General Model is described and the hybrid model is used in audio retrieval. Experiments show that the hybrid model is effective for audio classification.
Decomposing Verification Around End-User Features
Authors: Kathi Fisler, Shriram Krishnamurthi
Venue: Verified Software: Theories, Tools, Experiments: First IFIP TC 2/WG 2.3 Conference, VSTTE 2005, Zurich, Switzerland, October 10-13, 2005, Revised Selected Papers and Discussions (2005)

Practical program verification techniques must align with the software development methodologies that produce the programs. Numerous researchers have independently proposed models of program development in which modules encapsulate units of end-user functionality known as features. Such encapsulation reflects user concerns into a program's modular structure, which in turn promises to simplify program maintenance in the face of requirements evolution. The interplay between feature-oriented modules and verification raises some interesting challenges and opportunities. Such modules ameliorate some difficulties with conventional modular verification, such as property decomposition, while creating others, by contradicting assumptions that underlie most modular program verification techniques. This paper motivates the decomposition of systems by features and provides an overview of the promises and challenges it poses to verification.
Comparing the Performance of Digital Mammography Systems
Authors: Kenneth C. Young, Jennifer M. Oduko, Ozcan Gundogdu, Abdulaziz Alsager
Venue: Proceedings of the 9th international workshop on Digital Mammography (2008)

The performance of a wide range of digital mammography systems has been compared in terms of the dose required to achieve the image quality standards in the European guidelines at different detail sizes. This paper considers how these results relate to measurements of detector performance on these systems. The dose to meet the minimum requirements in European Guidelines was found to be strongly related to the DQE of the detector systems. Thus where a system has a relatively low DQE at high spatial frequencies (e.g. 5 cycles per mm) a relatively large dose is required to meet the minimum image quality level in European Guidelines for the smallest detail size (i.e. 0.1 mm). The systems showed a very wide range in performance.
Monitoring and Reputation Mechanisms for Service Level Agreements
Authors: Omer Rana, Martijn Warnier, Thomas B. Quillinan, Frances Brazier
Venue: Proceedings of the 5th international workshop on Grid Economics and Business Models (2008)

A Service Level Agreement (SLA) is an electronic contract between a service user and a provider, and specifies the service to be provided, Quality of Service (QoS) properties that must be maintained by a provider during service provision (generally defined as a set of Service Level Objectives (SLOs)), and a set of penalty clauses specifying what happens when service providers fail to deliver the QoS agreed. Although significant work exists on how SLOs may be specified and monitored, not much work has focused on actually identifying how SLOs may be impacted by the choice of specific penalty clauses. A trusted mediator may be used to resolve conflicts between the parties involved. The objectives of this work are to: (i) identify classes of penalty clauses that can be associated with an SLA; (ii) define how to specify penalties in an extension of WS-Agreement; and (iii) specify to what extent penalty clauses can be enforced based on monitoring of an SLA.
Modelling and Performance Measure of a Perinatal Network Centre in the United Kingdom
Authors: Md Asaduzzaman, Thierry J. Chaussalet
Venue: Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems (2008)

The main aim of this paper is to model the neonatal unit of a perinatal network centre using the general framework of a loss network model and to estimate some performance measures. A special case of the class of model has been applied for capacity planning to the perinatal network centre of a neonatal network in the United Kingdom. Using the data supplied from the perinatal network centre about admission process, length of stay (LoS) and discharge pattern of the babies, the loss network model is applied to estimate the admission refusal probability in the system under steady-state conditions. Results are derived for different arrival patterns and different combinations of cots at all levels of care of the neonatal unit. This approach can be useful to select the optimal combination of cots for any given acceptance rate of arrival to the neonatal unit.
Gem #15: timers
Authors: Anh Vo
Venue: ACM SIGAda Ada Letters (2008)

Ada Gem #15 -- Timers are essential software elements of embedded and real-time systems. Thus, making an intuitive and easy way to create timers helps in the software design process.
Local Firm's Strategic Upgrading in Global Manufacturing Network: Evidence from Chinese Firms
Authors: Xuefeng Liu
Venue: Proceedings of the 2008 International Symposiums on Information Processing (2008)

The Global Manufacturing Network (GMN) is a new manufacturing system that has super manufacturing and servicing capabilities, and it is challenging traditional manufacturing conceptions. In this paper, after literature reviews of the GMN, our exploratory work suggests that there are four stages through which manufacturing firms embed themselves into the GMN and upgrade their strategies, which involve penetration based on low-cost manufacturing, network embedding and evolving, accumulating knowledge and capabilities, and strategic upgrading.
Internet governance: A personal perspective
Authors: Houlin Zhao
Venue: Information Polity (2007)

Internet governance is one of the hot issues that emerged during the World Summit on the Information Society (WSIS) in Tunis November 2005. The discussions did not start then but much earlier. This article gives an overview of the International Telecommunciation Union's contribution to the debate as well as author's personal views on possible paths for Internet governance development. In this author's view the debates in WSIS and IGF preparatory processes reflected the reality that Internet governance is not limited to technical, nor to policy issues only. It increasingly includes important social, economic, national security and, to some extent, sovereignty issues.
combinFormation: Mixed-initiative composition of image and text surrogates promotes information discovery
Authors: Andruid Kerne, Eunyee Koh, Steven M. Smith, Andrew Webb, Blake Dworaczyk
Venue: ACM Transactions on Information Systems (TOIS) (2008)

combinFormation is a mixed-initiative creativity support tool for searching, browsing, organizing, and integrating information. Images and text are connected to represent surrogates (enhanced bookmarks), optimizing the use of human cognitive facilities. Composition, an alternative to lists and spatial hypertext, is used to represent a collection of surrogates as a connected whole, using principles from art and design. This facilitates the creative process of information discovery, in which humans develop new ideas while finding and collecting information. To provoke the user to think about the large space of potentially relevant information resources, a generative agent proactively engages in collecting information resources, forming image and text surrogates, and composing them visually. The agent develops the collection and its visual representation over time, enabling the user to see ideas and relationships. To keep the human in control, we develop interactive mechanisms for authoring the composition and directing the agent. In a field study in an interdisciplinary course on The Design Process, over a hundred students alternated using combinFormation and Google+Word to collect prior work on information discovery invention assignments. The students that used combinFormation's mixed-initiative composition of image and text surrogates performed better.
Steganography in Textiles
Authors: Sajad Shirali-Shahreza, Mohammad Shirali-Shahreza
Venue: Proceedings of the 2008 The Fourth International Conference on Information Assurance and Security (2008)

Covert exchange of information has been long a significant and highlighted affair. Numerous methods have been devised for the matter of which steganography is a popular one. Already applied in the past, the method has been massive used following the invention of computer. This paper discusses a new application of steganography in textiles in which information is hidden in the images on the clothes. In this way, information is first hidden by computer in images by a special method. Then the provided images are printed on clothes. The related information is extracted after scanning the images by relevant programs.
Fair Traceable Multi-Group Signatures
Authors: Vicente Benjumea, Seung Geol Choi, Javier Lopez, Moti Yung
Venue: Financial Cryptography and Data Security: 12th International Conference, FC 2008, Cozumel, Mexico, January 28-31, 2008. Revised Selected Papers (2008)

This paper presents fair traceable multi-group signatures (FTMGS), which have enhanced capabilities, compared to group and traceable signatures, that are important in real world scenarios combining accountability and anonymity. The main goal of the primitive is to allow multiple groups that are managed separately (managers are not even aware of the other ones), yet allowing users (in the spirit of the Identity 2.0 initiative) to manage what they reveal about their identity with respect to these groups by themselves. This new primitive incorporates the following additional features. While considering multiple groups it discourages users from sharing their private membership keys through two orthogonal and complementary approaches. In fact, it merges functionality similar to credential systems with anonymous type of signing with revocation. The group manager now mainly manages joining procedures, and new entities (called fairness authorities and consisting of various representatives, possibly) are involved in opening and revealing procedures. In many systems scenario assuring fairness in anonymity revocation is required. We specify the notion and implement it in the random oracle model.
Real-Time Expression Recognition System Using Active Appearance Model and EFM
Authors: Kyoung-Sic Cho, Yong-Guk Kim, Yang-Bok Lee
Venue: Computational Intelligence and Security: International Conference, CIS 2006, Guangzhou, China, November 3-6, 2006, Revised Selected Papers (2007)

We present a continuous facial expression recognition system based on Active Appearance Model (AAM) and Enhanced Fisher-Discriminant Model (EFM). AAM has been widely used in face tracking, face recognition, and object recognition tasks. In this study, we have implemented an independent AAM using Inverse Compositional Image Alignment method, which is a useful for the real-time system, because of its fast performance. The evaluation of this system carried out with the standard Cohn-Kanade facial expression database.
On the Collision-Propagation and Gather-Update Formulations of a Cellular Automata Rule
Authors: Bastien Chopard, Jean-Luc Falcone, Ranaivo Razakanirina, Alfons Hoekstra, Alfonso Caiazzo
Venue: Proceedings of the 8th international conference on Cellular Automata for Reseach and Industry (2008)

We consider two formulations of a cellular automata: the first one uses a gather-update paradigm and the second one a collision-propagation paradigm. We show the equivalence of both descriptions and, using the latter paradigm, we propose a simple way to define a Cellular Automata on a graph with arbitrary topology. Finally, we exploit the duality of formulation to reconsider the problem of characterizing invertible cellular automata.
On Regularization Parameters Estimation in Edge---Preserving Image Reconstruction
Authors: Ivan Gerace, Francesca Martinelli
Venue: Proceedings of the international conference on Computational Science and Its Applications, Part II (2008)

The image restoration problem is a well known ill-posed inverse problem. Thus, to solve it some regularization techniques are necessary. By these techniques the solution of the problem is defined as the minimum of an energy function. This function is given by the sum of two terms: the first one is due to the data consistency condition, the second one is related to the a priori smoothness condition on the solution. A regularization parameter regulate the degree of strength of the two terms. A right estimation of this parameter is very important to obtain a correct image reconstruction.Dealing with an edge---preserving image reconstruction, another free parameter is introduced. This parameter controls the number of discontinuities presenting in the restored image. In this paper we deal with joint estimation of these two parameters, proposing a novel technique for a correct second order reconstruction.
Virtual Reality: How Much Immersion Is Enough?
Authors: Doug A. Bowman, Ryan P. McMahan
Venue: Computer (2007)

Solid evidence of virtual reality's benefits has graduated from impressive visual demonstrations to producing results in practical applications. Further, a realistic experience is no longer immersion's sole asset. Empirical studies show that various components of immersion provide other benefits--full immersion is not always necessary.
Graph theoretic modeling: case studies in redundant arrays of independent disks and network defense
Authors: Narsingh Deo
Venue:  (2007)

Graph theoretic modeling has served as an invaluable tool for solving a variety of problems since its introduction in Euler&rsquo;s paper on the Bridges of K&ouml;nigsberg in 1736 [1]. Two amongst them of contemporary interest are the modeling of Redundant Arrays of Inexpensive Disks (RAID), and the identification of network attacks. While the former is vital to the protection and uninterrupted availability of data, the latter is crucial to the integrity of systems comprising networks. Both are of practical importance due to the continuing growth of data and its demand at increasing numbers of geographically distributed locations through the use of networks such as the Internet. The popularity of RAID has soared because of the enhanced I/O bandwidths and large capacities they offer at low cost. However, the demand for bigger capacities has led to the use of larger arrays with increased probability of random disk failures. This has motivated the need for RAID systems to tolerate two or more disk failures, without sacrificing performance or storage space. To this end, we shall first perform a comparative study of the existing techniques that achieve this objective. Next, we shall devise novel graph-theoretic algorithms for placing data and parity in arrays of n disks ( n &ge; 3) that can recover from two random disk failures, for n = p &ndash; 1, n = p and n = 2p &ndash; 2, where p is a prime number. Each shall be shown to utilize an optimal ratio of space for storing parity. We shall also show how to extend the algorithms to arrays with an arbitrary number of disks, albeit with non-optimal values for the aforementioned ratio. The growth of the Internet has led to the increased proliferation of malignant applications seeking to breach the security of networked systems. Hence, considerable effort has been focused on detecting and predicting the attacks they perpetrate. However, the enormity of the Internet poses a challenge to representing and analyzing them by using scalable models. Furthermore, forecasting the systems that they are likely to exploit in the future is difficult due to the unavailability of complete information on network vulnerabilities. We shall present a technique that identifies attacks on large networks using a scalable model, while filtering for false positives and negatives. Furthermore, it also forecasts the propagation of security failures proliferated by attacks over time and their likely targets in the future.
Interactive Decision Tree Construction for Interval and Taxonomical Data
Authors: François Poulet, Thanh-Nghi Do
Venue: Visual Data Mining: Theory, Techniques and Tools for Visual Analytics (2008)

Visual data-mining strategy lies in tightly coupling the visualizations and analytical processes into one data-mining tool that takes advantage of the assets from multiple sources. This paper presents two graphical interactive decision tree construction algorithms able to deal either with (usual) continuous data or with interval and taxonomical data. They are the extensions of two existing algorithms: CIAD [17] and PBC [3]. Both CIAD and PBC algorithms can be used in an interactive or cooperative mode (with an automatic algorithm to find the best split of the current tree node). We have modified the corresponding help mechanisms to allow them to deal with interval-valued attributes. Some of the results obtained on interval-valued and taxonomical data sets are presented with the methods we have used to create these data sets.
An Empirical Investigation of the Applicability of a Component-Based Performance Prediction Method
Authors: Anne Martens, Steffen Becker, Heiko Koziolek, Ralf Reussner
Venue: Proceedings of the 5th European Performance Engineering Workshop on Computer Performance Engineering (2008)

Component-based software performance engineering (CBSPE) methods shall enable software architects to assess the expected response times, throughputs, and resource utilization of their systems already during design. This avoids the violation of performance requirements. Existing approaches for CBSPE either lack tool support or rely on prototypical tools, who have only been applied by their authors. Therefore, industrial applicability of these methods is unknown. On this behalf, we have conducted a controlled experiment involving 19 computer science students, who analysed the performance of two component-based designs using our Palladio performance prediction approach, as an example for a CBSPE method. Our study is the first of its type in this area and shall help to mature CBSPE to industrial applicability. In this paper, we report on results concerning the prediction accuracy achieved by the students and list several lessons learned, which are also relevant for other methods than Palladio.