ppxscal/embedding_network huggingface dataset:
On the Power of Power Analysis in the Real World: A Complete Break of the KeeLoq Code Hopping Scheme
Authors: Thomas Eisenbarth, Timo Kasper, Amir Moradi, Christof Paar, Mahmoud Salmasizadeh, Mohammad T. Shalmani
Venue: Proceedings of the 28th Annual conference on Cryptology: Advances in Cryptology (2008)

KeeLoq remote keyless entry systems are widely used for access control purposes such as garage openers or car door systems. We present the first successful differential power analysis attacks on numerous commercially available products employing KeeLoq code hopping. Our new techniques combine side-channel cryptanalysis with specific properties of the KeeLoq algorithm. They allow for efficiently revealing both the secret key of a remote transmitter and the manufacturer key stored in a receiver. As a result, a remote control can be cloned from only ten power traces, allowing for a practical key recovery in few minutes. After extracting the manufacturer key once, with similar techniques, we demonstrate how to recover the secret key of a remote control and replicate it from a distance, just by eavesdropping on at most two messages. This key-cloning without physical access to the device has serious real-world security implications, as the technically challenging part can be outsourced to specialists. Finally, we mount a denial of service attack on a KeeLoq access control system. All proposed attacks have been verified on several commercial KeeLoq products.
Biometric Image Integrity Authentication Based on SVD and Fragile Watermarking
Authors: De-song Wang, Jian-ping Li, Xiao-yang Wen
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 5 - Volume 05 (2008)

According to the fragile watermarking theory and insecure computer network, the integrity authentication scheme of biometric image based on singular value decomposition (SVD) is proposed for remote users via insecure computer network. We make good use of singular values of singular value decomposition (SVD) of biometric image to check the integrity of biometric image. To make authentication data, the singular values are changed to the binary bits using modular arithmetic. The binary bits of authentication data are embedded into the least significant bit (LSB) of the original biometric image. The pixels to be changed are randomly selected in the original biometric image. The advantages of this scheme are that 1) we can detect any modification of watermarked biometric image; 2) the quality of watermarked biometric image is very high because only a few bits of authentication data are embedded. Experimental results show that the proposed fragile watermarking scheme can be applied to the integrity authentication systems based on biometric image.
Logfile Player and Analyzer for RoboCup 3D Simulation
Authors: Steffen Planthaber, Ubbo Visser
Venue: RoboCup 2006: Robot Soccer World Cup X (2006)

In multi agent environments or systems equipped with artificial intelligence it is often difficult to obtain the function or method which led to a particular behavior that is noticeable from outside. However, this information is crucial if not necessary to optimize the agents behavior. In the RoboCup 3D simulation league this dilemma becomes obvious when replaying logfiles of a game that was simulated before. The 3D soccer simulation league monitor (rcssmonitor-lite) is restricted with regards to replaying logfiles.This paper describes the concept and the implementation of improvements for the logplaying and analyzing abilities of the monitor. The idea is to provide a tool that is able to assist developers to detect problems of their agents both in single and cooperation mode.
Texture Image Retrieval Based on Contourlet Transform and Active Perceptual Similarity Learning
Authors: Huaijing Qu, Yuhua Peng, Honglin Wan, Min Han
Venue: Proceedings of the 4th international conference on Advanced Data Mining and Applications (2008)

This paper proposes a new texture image retrieval scheme based on contourlet transform and support vector machines (SVMs). In the scheme, the energies and the generalized Gaussian distribution (GGD) parameters are used to represent the contourlet subband features. Using the representations, a two-run SVM retrieval algorithm which employs an one-class SVM followed by a two-class SVM is proposed to carry out the perceptual similarity measurement. For the query image, the one-class SVM is used to obtain the effective initial training set with positive and negative samples. Using these initial samples, the two-class SVM is applied to refine on the image classification subject to the user's relevance feedback. Compared with existing texture image retrieval methods, the proposed retrieval scheme is demonstrated respectively to be effective on the VisTex database of 640 texture images and the Brodatz database of 1760 texture images. Experimental results have shown that the proposed retrieval scheme can attain 99.38% and 98.07% of the average rates respectively for the two databases.
Fractal analysis for mobile objectives navigation
Authors: Dan Popescu, Radu Dobrescu, Nicoleta Angelescu
Venue: Proceedings of the 9th WSEAS International Conference on International Conference on Automation and Information (2008)

In this paper, we investigate how the fractal dimension is used for textured image classifications. In order to measure the similarity of a textured region pair, the fractal dimensions of both regions are computed by the box-counting algorithm utilizing. The analysis of textural images was made on a set of ten image regions and the results prove that the mean fractal dimension can be used to classify the textural images. To validate the algorithm, a MATLAB program was implemented. The results are the classification of the tested texture and also the localization of the road from the divided regions. Our experimental results indicate the fact that the selected features have a good discriminating power.
The development and evaluation of novel algorithms for contrast enhancement in grayscale images
Authors: Hao Ying
Venue:  (2008)

Image contrast enhancement is an imperative step in almost every image processing application. The absence of a general theory for image enhancement pioneered the development of numerous enhancement algorithms to cope with the considerable diversity of images and enhancement objectives. Many of these algorithms have been developed for grayscale images that are still used in many important fields such as medical imaging and electron microscopy. One important fact is that dealing with grayscale images is easier than color images. However, grayscale-based algorithms can be extended and modified to work with color images as long as they do not produce color distortions. In this dissertation, I introduce the development and experimentation of four general image contrast enhancement algorithms in the spatial domain and applied them to grayscale images. Three of these algorithms are developed based on the understanding of the mechanism and problems of the popular histogram equalization (HE) algorithm. However, each algorithm approaches these problems from different angle. The Multilevel Component-Based Histogram Equalization (MCBHE) algorithm utilizes subimage processing, multiple graylevel thresholding, and connected components labeling. The Constrained Variational Histogram Equalization (CVHE) algorithm and its local variants build on the variational definition of the HE algorithm to define a new transformation function that reduces the change in the image brightness. Similarly, the Brightness Constrained Automatic Histogram Specification (BCAHS) algorithm enhances the image contrast by preserving its mean brightness, however it achieves that by automatically specifying the output histogram that is the closest to a uniform distribution and has the same mean value. Generally, these three algorithms showed better performance than the HE algorithm and its variants in terms of the quality of the perceived contrast and less production of enhancement artifacts in the processed images, but at the expense of relative increase in processing time. The last algorithm is the Adaptive Local Graylevel Transformation (ALGT) algorithm that is introduced for contrast sharpening. It is based on stretching local graylevel values adaptively using an optimal transformation function. It was shown through experimentation that the ALGT algorithm allows for contrast sharpening better than some algorithms and with less noise amplification in smooth regions.
ViP: A User-Centric View-Based Annotation Framework for Scientific Data
Authors: Qinglan Li, Alexandros Labrinidis, Panos K. Chrysanthis
Venue: Proceedings of the 20th international conference on Scientific and Statistical Database Management (2008)

Annotations play an increasingly crucial role in scientific exploration and discovery, as the amount of data and the level of collaboration among scientists increase. In this paper, we introduce ViP, a user-centric, view-based annotation framework that promotes annotations as first-class citizens. ViP introduces novel ways of propagating annotations, empowering users to express their preferences over the time and network semantics of annotations. To efficiently support such novel functionality, ViP utilizes database views and introduces new caching techniques. Through an extensive experimental study on a real system, we show that ViP can seamlessly introduce new annotation propagation semantics while significantly improving the performance over the current state of the art.
u-Teacher: Ubiquitous Learning Approach
Authors: Zacarías F. Fernando, Cuapa C. Rosalba, Lozano T. Francisco, Vazquez F. Andres, Zacarías F. Dionicio
Venue: Proceedings of the 3rd international conference on Technologies for E-Learning and Digital Entertainment (2008)

The Learning of the century XXI demand ubiquitous characteristics that allow to learner not only to have information available in any place, in any time and in any way. But rather, to have the information in right time, in the right place and in right way [3]. An ubiquitous learning environment should allow the learner to have these three characteristics at your disposal in all moment. Considering that a lot of people have access to cell phone technology and it would be fantastic to use this technology as a learning tool. We have developed an ubiquitous learning system (on cellular phones) that also it combines web technologies and cell phone. Our system shows that this novel form of learning is completely accepted and it increases the learning level significantly.
On Faster Integer Calculations Using Non-arithmetic Primitives
Authors: Katharina Lürwer-Brüggemeier, Martin Ziegler
Venue: Proceedings of the 7th international conference on Unconventional Computing (2008)

The unit cost model is both convenient and largely realistic for describing integer decision algorithms over + ,×. Additional operations like division with remainder or bitwise conjunction, although equally supported by computing hardware, may lead to a considerable drop in complexity. We show a variety of concrete problems to benefit from such non-arithmetic primitives by presenting and analyzing corresponding fast algorithms.
Experimenting with formal languages using forlan
Authors: Alley Stoughton
Venue: Proceedings of the 2008 international workshop on Functional and declarative programming in education (2008)

We give an introduction to the Forlan formal language theory toolset, which was designed to facilitate sophisticated experimentation with formal languages. Forlan is embedded in the functional programming language Standard ML, a language whose notation and concepts are similar to those of mathematics. It is strongly typed and interactive, properties that help make experimentation robust, simple and enjoyable. We give an extended example of the kind of experimentation that Forlan makes possible. It involves the use of closure properties/algorithms for regular languages/finite automata and a "difference" function on strings of zeros and ones.
Ontology-Based Integration and Management of Distributed Design Data
Authors: J. Morbach, W. Marquardt
Venue: Collaborative and Distributed Chemical Engineering. From Understanding to Substantial Design Process Support: Results of the IMPROVE Project (2008)

During the design phase of a chemical plant, information is created by various software tools and stored in different documents and databases. These distributed design data are a potential source of valuable knowledge, which could be exploited by novel software applications. However, before further processing, the scattered information has to be merged and consolidated. For this task, semantic technologies are a promising alternative to conventional database technology. This contribution gives an outline of the transfer project T1, which aims at the development of an ontology-based software prototype for the integration and reconciliation of design data. Both ontology and software development will be performed in close cooperation with partners from the chemical and software industries to ensure their compliance with the requirements of industrial practice. The advantages of semantic technologies will be demonstrated by comparing the prototype against a conventional integration solution.
Appearance of woven cloth
Authors: Stephen R. Marschner
Venue:  (2008)

The appearance of a particular fabric is produced by variations in both large-scale reflectance and small-scale texture as the viewing and illumination angles change across the surface. This thesis presents a study of the reflectance and texture of woven cloth that aims to identify and model the most important optical features of cloth appearance. New measurements are reported for a range of fabrics including natural and synthetic fibers as well as staple and filament yarns. A new scattering model for woven cloth is introduced that describes the reflectance and the texture based on all analysis of specular reflection from the fibers. Unlike data-based models, our procedural model requires no image data. It can handle a wide range of fabrics using a small set of physically meaningful parameters that describe the characteristics of the fibers, the geometry of the yarns, and the pattern of the weave. The model is validated against the measurements and by comparisons to high-resolution video of the real fabrics.
Modular Termination of Basic Narrowing
Authors: María Alpuente, Santiago Escobar, José Iborra
Venue: Proceedings of the 19th international conference on Rewriting Techniques and Applications (2008)

Basic narrowing is a restricted form of narrowing which constrains narrowing steps to a set of non-blocked (or basic) positions. Basic narrowing has a number of important applications including equational unification in canonical theories. Another application is analyzing termination of narrowing by checking the termination of basic narrowing, as done in pioneering work by Hullot. In this work, we study the modularity of termination of basic narrowing in hierarchical combinations of TRSs, including a generalization of proper extensions with shared subsystem. This provides new algorithmic criteria to prove termination of basic narrowing.
Deterministic Encryption: Definitional Equivalences and Constructions without Random Oracles
Authors: Mihir Bellare, Marc Fischlin, Adam O'Neill, Thomas Ristenpart
Venue: Proceedings of the 28th Annual conference on Cryptology: Advances in Cryptology (2008)

We strengthen the foundations of deterministic public-key encryption via definitional equivalences and standard-model constructs based on general assumptions. Specifically we consider seven notions of privacy for deterministic encryption, including six forms of semantic security and an indistinguishability notion, and show them all equivalent. We then present a deterministic scheme for the secure encryption of uniformly and independently distributed messages based solely on the existence of trapdoor one-way permutations. We show a generalization of the construction that allows secure deterministic encryption of independent high-entropy messages. Finally we show relations between deterministic and standard (randomized) encryption.
Batch Support Vector Training Based on Exact Incremental Training
Authors: Shigeo Abe
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part I (2008)

In this paper we discuss training support vector machines (SVMs) repetitively solving a set of linear equations, which is an extension of accurate incremental training proposed by Cauwenberghs and Poggio. First, we select two data in different classes and determine the optimal separating hyperplane. Then, we divide the training data set into several chunk data sets and set the two data to the active set, which includes current and previous support vectors. For the combined set of the active set and a chunk data set, we detect the datum that maximally violates the Karush-Kuhn-Tacker (KKT) conditions, and modify the optimal hyperplane by solving a set of equations that constrain the margins of unbounded support vectors and the optimality of the bias term. We iterate this procedure until there are no violating data in any combined set. By the computer experiment using several benchmark data sets, we show that the training speed of the proposed method is comparable with the primal-dual interior-point method combined with the decomposition technique, usually with a smaller number of support vectors.
Alpha-Beta Weightless Neural Networks
Authors: Amadeo José Arguelles-Cruz, Itzamá López-Yáñez, Mario Aldape-Pérez, Napoleón Conde-Gaxiola
Venue: Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications (2008)

A novel weightless neural network model is presented, based on the known operations Alpha and Beta, and three original operations proposed. The new model of weightless neural network has been called CAINN --- Computing Artificial Intelligent Neural Network. The experimental aspect is presented by applying the CAINN model to several known databases. Also, comparative studies about the performance of the CAINN model concerning ADAM weightless neural network and other models are reported. Results exhibit the superiority of the CAINN model over the ADAM model, its counterpart as a weightless neural network; and over other models immersed in the state of the art of neural networks; taking into account the No Free Lunch theorem.
MEM&LCW 2008 Workshop PC Chairs' Message
Authors: Marek Kowalkiewicz, Dominik Flejter, Tomasz Kaczmarek
Venue: Proceedings of the 2008 international workshops on Web Information Systems Engineering (2008)

Today's business world relies on a range of sophisticated IT solutions. Due to the sophistication, business and IT have separated in many organizations. That separation has left a gap between the two and has led to frequent IT project failures or escalations. While the gap between business and IT does not pose a difficulty for highly structured business problems and processes that are stable in time, it is a major obstacle for all other problems and processes.
On relay node placement and assignment for two-tiered wireless networks
Authors: Wenxuan Guo, Xinming Huang, Wenjing Lou, Cao Liang
Venue: Mobile Networks and Applications (2008)

Wireless networks that operate on batteries are imposed with energy constraints and long distance communications between nodes are not desirable. Implementing Relay Nodes (RNs) can improve network capacity and save communication energy. A two-hop relay routing scheme is considered, in which the RNs are temporarily placed and have energy constraints. This paper investigates a joint optimization problem on Relay Node Placement (RNP) and route assignment for two-tiered wireless networks. A recursive Weighted Clustering Binary Integer Programming (WCBIP) algorithm is proposed to maximize the total number of information packets received at the Base Station (BS) during the network lifetime. We first present an optimization algorithm based on Binary Integer Programming (BIP) for Relay Node Assignment (RNA) with the current node locations. Subsequently, a weighted clustering algorithm is applied to move the RNs to the best locations to best serve their respectively associated Edge Nodes (ENs). The algorithm has the complexity of O(2n). The simulation results show that the proposed algorithm has significantly better performance than the other two relay placement schemes. Both theoretical analysis and practical design procedures are also presented with details.
The Lixto Systems Applications in Business Intelligence and Semantic Web
Authors: Robert Baumgartner, Oliver Frölich, Georg Gottlob
Venue: Proceedings of the 4th European conference on The Semantic Web: Research and Applications (2007)

This paper shows how technologies for Web data extraction, syndication and integration allow for new applications and services in the Business Intelligence and the Semantic Web domain. First, we demonstrate how knowledge about market developments and competitor activities on the market can be extracted dynamically and automatically from semi-structured information sources on the Web. Then, we show how the data can be integrated in Business Intelligence Systems and how data can be classified, re-assigned and transformed with the aid of Semantic Web ontological domain knowledge. Existing Semantic Web and Business Intelligence applications and scenarios using our technology illustrate the whole process.
Toasters, Seat Belts, and Inferring Program Properties
Authors: David Evans
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)

Today's software does not come with meaningful guarantees. This position paper explores why this is the case, suggests societal and technical impediments to more dependable software, and considers what realistic, meaningful guarantees for software would be like and how to achieve them.
Lee-TM: A Non-trivial Benchmark Suite for Transactional Memory
Authors: Mohammad Ansari, Christos Kotselidis, Ian Watson, Chris Kirkham, Mikel Luján, Kim Jarvis
Venue: Proceedings of the 8th international conference on Algorithms and Architectures for Parallel Processing (2008)

Transactional Memory (TM) is a concurrent programming paradigm that aims to make concurrent programming easier than fine-grain locking, whilst providing similar performance and scalability. Several TM systems have been made available for research purposes. However, there is a lack of a wide range of non-trivial benchmarks with which to thoroughly evaluate these TM systems.This paper introduces Lee-TM, a non-trivial and realistic TM benchmark suite based on Lee's routing algorithm. The benchmark suite provides sequential, lock-based, and transactional implementations to enable direct performance comparison. Lee's routing algorithm has several of the desirable properties of a non-trivial TM benchmark, such as large amounts of parallelism, complex contention characteristics, and a wide range of transaction durations and lengths. A sample evaluation shows unfavourable transactional performance and scalability compared to lock-based execution, in contrast to much of the published TM evaluations, and highlights the need for non-trivial TM benchmarks.