ppxscal/embedding_network huggingface dataset:
The Design and Verification of RFID Authentication Protocol for Ubiquitous Computing
Authors: Hyun-Seok Kim, Jin-Young Choi
Venue: Proceedings of the 18th International Conference on Database and Expert Systems Applications (2007)

The growing use of Radio Frequency Identification (RFID) technology to enhance ubiquitous computing environments has only begun to be realized. It allows for the identification of objects and/or subjects remotely using attached RFID tags via a radio frequency channel, hence identification is achieved in a contactless manner. This paper presents issues concerning security and privacy of RFID Systems which are heavily discussed in public and introduces Authentication Protocol for a RFID security protocol which serves as a proof of concept for authentication an RFID tag to a reader device using the vernam and standard encryption as a cryptographic primitive. To verify our protocol, we use model checking methodology, that is, Casper(A Compiler for Security Protocol), CSP(Communicating Sequential Processes) and then verify security properties such as secrecy and authentication using FDR(Failure Divergence Refinement) tool.
Protecting Networks by Controlling Access
Authors: Sixto Ortiz Jr.
Venue: Computer (2007)

To meet the security challenge of keeping infected or otherwise unsecure laptops, PCs, PDAs, and other devices from accessing their networks, a growing number of companies are turning to network-access-control technology.
Semi-supervised learning by search of optimal target vector
Authors: Leonardo Angelini, Daniele Marinazzo, Mario Pellicoro, Sebastiano Stramaglia
Venue: Pattern Recognition Letters (2008)

We introduce a semi-supervised learning estimator which tends to the first kernel principal component as the number of labeled points vanishes. We show application of the proposed method for dimensionality reduction and develop a semi-supervised regression and classification algorithm for transductive inference.
Test Generation and Diagnostic Test Generation for Open Faults with Considering Adjacent Lines
Authors: Hiroshi Takahashi, Yoshinobu Higami, Toru Kikkawa, Takashi Aikyo, Yuzo Takamatsu, Koji Yamazaki, Toshiyuki Tsutsumi, Hiroyuki Yotsuyanagi, Masaki Hashizume
Venue: Proceedings of the 22nd IEEE International Symposium on Defect and Fault-Tolerance in VLSI Systems (2007)

In order to ensure high quality of DSM circuits, testing for the open defect in the circuits is necessary. However, the modeling and techniques for test generation for open faults have not been established yet. In this paper, we propose a method for generating tests and diagnostic tests based on a new open fault model. Firstly, we show a new open fault model with considering adjacent lines [9]. Under the open fault model, we reveal more about the conditions to excite the open fault. Next we propose a method for generating tests for open faults by using a stuck-at fault test with don't cares. We also propose a method for generating a diagnostic test that can distinguish the pair of open faults. Finally, experimental results show that 1) the proposed method is able to achieve 100% fault coverages for almost all benchmark circuits and 2) the proposed method is able to reduce the number of indistinguished open fault pairs.
Program Graphs and Execution Behavior
Authors: R. R. Oldehoeft
Venue: IEEE Transactions on Software Engineering (1983)

This paper describes a technique for predicting the execution behavior of a source program or a software design specification. As a by-product of syntactic analysis, a program graph is constructed which can subsequently be treated as the graph of a finite automaton. The expression for execution behavior is the regular expression of the graph. Several simplification techniques for these expressions are discussed and exemplified. In particular, the substitution of known values for program segments followed by constant folding cannot be done indiscriminately; the allowable situations are characterized. Applications include the prediction of execution time for a program or a software design, other forms of language analysis, and program restructuring.
Exploiting redundancy in natural language to penetrate Bayesian spam filters
Authors: Christoph Karlberger, Günther Bayler, Christopher Kruegel, Engin Kirda
Venue: Proceedings of the first USENIX workshop on Offensive Technologies (2007)

Today's attacks against Bayesian spam filters attempt to keep the content of spam mails visible to humans, but obscured to filters. A common technique is to fool filters by appending additional words to a spam mail. Because these words appear very rarely in spam mails, filters are inclined to classify the mail as legitimate. The idea we present in this paper leverages the fact that natural language typically contains synonyms. Synonyms are different words that describe similar terms and concepts. Such words often have significantly different spam probabilities. Thus, an attacker might be able to penetrate Bayesian filters by replacing suspicious words by innocuous terms with the same meaning. A precondition for the success of such an attack is that Bayesian spam filters of different users assign similar spam probabilities to similar tokens. We first examine whether this precondition is met; afterwards, we measure the effectivity of an automated substitution attack by creating a test set of spam messages that are tested against SpamAssassin, DSPAM, and Gmail.
Efficient Fast Fourier Transform Programs for Arbitary Factors with One Step Loop Unscrambling
Authors: R. J. Polge
Venue: IEEE Transactions on Computers (1976)

This correspondence develops efficient fast Fourier transform (FFT) programs to transform arrays of dimension N, where N can be written as a power of two possibly multiplied by arbitrary factors. Two programs were developed which use radix-2 and radix-4 transformations for the binary factors. These programs call another subprogram to transform with respect to the arbitrary factors, if any. Since the sequential transformation is well known, the emphasis is on developing an efficient unscrambling procedure to follow the transformation.
Interactive wormhole detection and evaluation
Authors: Weichao Wang, Aidong Lu
Venue: Information Visualization (2007)

Wormhole attacks in wireless networks can severely deteriorate network performance and compromise security through spoiling the routing protocols and weakening the security enhancements. This paper develops an approach, interactive visualization of wormholes (IVoW), to monitor and detect such attacks in large-scale wireless networks in real time. We characterize the topology features of a network under wormhole attacks through the node position changes and visualize the information at dynamically adjusted scales. We integrate an automatic detection algorithm with appropriate user interactions to handle complicated scenarios that include a large number of moving nodes and multiple wormhole attackers. Various visual forms have been adopted to assist in the understanding and analysis of reconstructed network topology and to improve the detection accuracy. Extended simulation has demonstrated that the proposed approach can effectively locate the fake neighbor connections without introducing many false alarms. IVoW does not require the wireless nodes to be equipped with any special hardware, thus avoiding any additional cost. We have performed user studies to evaluate the effectiveness of our approach and demonstrate that visual analysis can be successfully combined with network security mechanisms to greatly improve intrusion detection capabilities.
Support Vector Machine Based Assessment System on Shift Quality for Vehicles: Theory, Structure and Application
Authors: Jian Wang, Yulong Lei, Jianguo Zhang
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 05 (2007)

Support Vector Machine (SVM) is a new statistic method which could make a good prediction with limited instances. Compared with Artificial Neutral Network (ANN), SVM can provide better genetic ability. Shift quality is one of important vehicle performances, because it can be" felt" directly by the terminal customers. Therefore, how to make a correct assessment during the development is an important duty for vehicles manufacturing. The study provides an assessment system on shift quality based on SVM method. In order to verify the ability of the new method, the model trained by one automated manual transmission (AMT) car was applied on some other AMT vehicles, and the predicted results were compared with subjective rating results by expert drivers and analyzed to identify the potential of this new assessment system.
Dynamic Memories with Fast Random and Sequential Access
Authors: H. S. Stone
Venue: IEEE Transactions on Computers (1975)

This paper treats two dynamic memories, one proposed by Aho and Ullman and the other proposed by Stone. The first memory has the property that every item is accessible in 0 (log2 N) steps, and that after access to the first two items of a block of contiguous items, each successive item can be accessed in unit time. In this paper we give a new derivation of the properties, and indicate minor variations and improvements of the memory-access algorithm.
Rough Set Based Fuzzy Controller and Its Application to Load Control System in Power Plant
Authors: Fang Wang, Keming Xie, Jun Xie
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 02 (2007)

In this paper, we present the rough set-based algorithm of multi-layer fuzzy rules extraction. The idea comes from the limitation of human thinking. The dimension number of fuzzy rules from this algorithm is no more than 3. These rules are advantageous to being understood, compared and corrected. This algorithm improves C-D discernible matrices without attributes calculation between inconsistent objects and chooses the most important attribute gradually from core attributes as starting point. Information increment of decision D is used as heuristic information of attributes selection. This multilayer fuzzy controller is combined with conventional PID, applied to unit load control system of power plant. The simulation results show that the performance of the proposed rough set based fuzzy controller is satisfactory.
A stochastic grammar of images
Authors: Song-Chun Zhu, David Mumford
Venue: Foundations and Trends® in Computer Graphics and Vision (2006)

This exploratory paper quests for a stochastic and context sensitive grammar of images. The grammar should achieve the following four objectives and thus serves as a unified framework of representation, learning, and recognition for a large number of object categories. (i) The grammar represents both the hierarchical decompositions from scenes, to objects, parts, primitives and pixels by terminal and nonterminal nodes and the contexts for spatial and functional relations by horizontal links between the nodes. It formulates each object category as the set of all possible valid configurations produced by the grammar. (ii) The grammar is embodied in a simple And-Or graph representation where each Or-node points to alternative sub-configurations and an And-node is decomposed into a number of components. This representation supports recursive top-down/bottom-up procedures for image parsing under the Bayesian framework and make it convenient to scale up in complexity. Given an input image, the image parsing task constructs a most probable parse graph on-the-fly as the output interpretation and this parse graph is a subgraph of the And-Or graph after making choice on the Or-nodes. (iii) A probabilistic model is defined on this And-Or graph representation to account for the natural occurrence frequency of objects and parts as well as their relations. This model is learned from a relatively small training set per category and then sampled to synthesize a large number of configurations to cover novel object instances in the test set. This generalization capability is mostly missing in discriminative machine learning methods and can largely improve recognition performance in experiments. (iv) To fill the well-known semantic gap between symbols and raw signals, the grammar includes a series of visual dictionaries and organizes them through graph composition. At the bottom-level the dictionary is a set of image primitives each having a number of anchor points with open bonds to link with other primitives. These primitives can be combined to form larger and larger graph structures for parts and objects. The ambiguities in inferring local primitives shall be resolved through top-down computation using larger structures. Finally these primitives forms a primal sketch representation which will generate the input image with every pixels explained. The proposal grammar integrates three prominent representations in the literature: stochastic grammars for composition, Markov (or graphical) models for contexts, and sparse coding with primitives (wavelets). It also combines the structure-based and appearance based methods in the vision literature. Finally the paper presents three case studies to illustrate the proposed grammar.
Integer Programming via Chaotic Ant Swarm
Authors: Yuying Li, Lixiang Li, Qiaoyan Wen, Yixian Yang
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 04 (2007)

This PAPER uses chaotic ant swarm (CAS) to solve the problem of integer programming by embedding the search space Zl into Rl and truncating the real values to the nearest integers. Two novel methods based on the CAS, rounding the real solutions after every step (CAS-F) and after the final step (CAS-S), are given and numerical experiences show that in most cases the CAS-F outperforms the CAS-S. Finally the CAS-F is compared with the particle swarm optimization (PSO) on seven widely used integer programming test problems. Results not only indicate that the CAS-F can efficiently deal with this problem, but also the CAS-F is better than the PSO in low dimension.
Data allocation scheme based on term weight for P2P information retrieval
Authors: Hisashi Kurasawa, Hiromi Wakaki, Atsuhiro Takasu, Jun Adachi
Venue: Proceedings of the 9th annual ACM international workshop on Web information and data management (2007)

Many Peer-to-Peer information retrieval systems that use a global index have already been proposed that can retrieve documents relevant to a query. Since documents are allocated to peers regardless of the query, the system needs to connect many peers to gather the relevant documents. We propose a new data allocation scheme for P2P information retrieval that we call Concordia. Concordia uses a node to allocate a document based on the weight of each term in the document to efficiently assemble all the documents relevant to a query from the P2P Network. Moreover, the node encodes the binary data of a document with an erasure code, and Concordia produces an efficient redundancy for counteracting node failures.
Image Enhancement Using Elastic Manifolds
Authors: Vadim Ratner, Yehoshua Y. Zeevi
Venue: Proceedings of the 14th International Conference on Image Analysis and Processing (2007)

Image denoising and enhancement problems have many physical analogues that highlight new approaches to novel solutions. One such solution, based on viewing the image as elastic sheet, is presented. A processing scheme for grayscale images is outlined and further considered in the context of color images. Preliminary analysis and simulations on noisy images indicate that multidimensional manifold representation of combined space-color information incorporates the advantages of separate color channel representations. Experimental analysis reveals elastic sheet method to be a powerful and robust denoising tool, which preserves most meaningful details.
Non-invasive tumor localization by 3D registration of range sensor and computer tomography images.
Authors: Ruben Posada-Gomez, Gnier Alor-Hernandez, Mario Alberto Garcia-Martinez, Albino Martinez-Sibaja
Venue: Proceedings of the Eighth Mexican International Conference on Current Trends in Computer Science (2007)

This paper describes a patient positioning method that allows a non-invasive localization of tumors in the field of conformal radiotherapy for the treatment of cancers located in the head. The proposed methodology uses computer tomography and range sensor images of the patient's head; on the one hand tomography data has information of tumor localization related to the patient's head and on the other hand range sensor images has information of patient's face localization into the treatment's room. A 3D multimodality registration of computer tomography and range sensor images and the calibration of range sensor at radiotherapy treatment room avoid the use of stereotactic frame for patient's positioning. Tests performed with human data proved that the registration algorithm is accurate (0.1mm mean distance between homologous points) and robust even for facial expression changes.
Micro-CAP: An Analog Circuit Design System for Personal Computers
Authors: Andrew Thompson
Venue: IEEE Computer Graphics and Applications (1984)

The accuracy and speed of this circuit analysis program for PCs compare favorably with similar programs running on mainframes. 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
Color Image Restoration Based on Dynamic Recurrent RBF Neural Network
Authors: Hongwei Ge, Weinan Yang
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 03 (2007)

A kind of nearest neighbor classification (NNC) based on dynamic recurrent RBF Neural Network is used to restore color image. It combines a MLP and a RBF Neural Network, and allows for explicit representation of prototype patterns as network parameters. The system structure is self-adaptive, and the prototypes can be added or removed freely. The dynamic classification implemented by the network eliminates all comparisons, which are the vital steps of the conventional NNC process. Some results of image de-noising show the high performance of this model. Moreover, the new model also provides excellent robustness with respect to various percentages of noise in our testing examples.
Upgrading Web Search Queries
Authors: Suhail S. J. Owais, Pavel Kromer, Vaclav Snasel, S. Maleki-Dizaji, Henry O. Nyongesa
Venue: Proceedings of the 18th International Conference on Database and Expert Systems Applications (2007)

The amount and variety of information sources, especially on the World Wide Web (WWW), grows and the requirements imposed on search applications are increasing. Search service should provide the users with accurate, sensible responses to their requests. It is difficult to provide information that accurately matches user information needs. Search effectiveness can be seen as the accuracy of matching user information needs against the retrieved information. There are problems emerging: users often do not present search queries in the form that optimally represents their information need, the measure of a document's relevance is often highly subjective between different users and information sources might contain heterogeneous documents, in multiple formats and the representation of documents is not unified. In this paper we present a proposal to improve web search effectiveness via evolutionary optimization of Boolean and vector search queries based on individual user models.
A Selection Model for MSNs of Overlay Network Based on Hybrid Algorithm
Authors: Deqiang Cheng, Jiansheng Qian
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 05 (2007)

After analyzing the characteristics of overlay network, a hybrid K-medoids genetic model (HKGM) is proposed based on the hybrid clustering algorithms, which is used to choose the multicast service nodes (MSNs) from network nodes. Compared with the traditional K-medoids model, HKGM not only avoids converging to local minimum value, but also is robust to initialization. Also, during the evolution, according to actual features of MSNs in overlay network, the evolutional control strategies including diverse gene and evolutionary elite reservation are used to enhance the local search ability of model, and to increase the convergent speed.
Testing Non-Functional Requirements with Aspects: An Industrial Case Study
Authors: Jani Metsa, Mika Katara, Tommi Mikkonen
Venue: Proceedings of the Seventh International Conference on Quality Software (2007)

Testing is regarded as one of the most resource consum- ing tasks of an average software project. A common goal of testing related activities is to make sure that requirements are satisfied by the implementation. Although existing tools are often effective in functional testing, emerging non- functional requirements set new demands. Aspect-oriented techniques offer a promising approach for capturing such issues under verification. However, prior to industrial adoption more pragmatic guidelines on applying aspects are required. In this paper, we evaluate aspect-oriented techniques in testing non-functional requirements of an industrial system. In addition, we discuss the types of requirements that lend themselves for more efficient testing using aspects than conventional techniques. Keywords: aspects, non-functional, testing.
Facilitating situation assessment through gir with multi-scale open source web documents
Authors: Brian M. Tomaszewski, Chi-Chun Pan, Prasenjit Mitra, Alan M. MacEachren
Venue: Proceedings of the 4th ACM workshop on Geographical information retrieval (2007)

In this paper, we present our preliminary work on a Geographic Information Retrieval (GIR) system that utilizes loosely coupled web services and Google Earth™(GE) to retrieve, extract, combine, and visualize situation information from multi-scale, open source web documents. Our intent with this work is to support situation assessment in the crisis management domain through tools that link and geographically contextualize information contained in text documents retrieved from multiple sources. In particular, our present work focuses on combining two data sources - The Federal Emergency Management Agency (FEMA) National Situation Updates and Google News"™.
Analysis of Power Supply Noise in the Presence of Process Variations
Authors: Praveen Ghanta, Sarma Vrudhula
Venue: IEEE Design Test (2007)

This article presents a comprehensive methodology for analyzing the impact of device and metal process variations on the power supply noise and hence the signal integrity of on-chip power grids. This approach models the power grid using modified nodal-analysis equations, and is based on representing the voltage response as an orthogonal polynomial series in the process variables. The series is truncated, and coefficients of the series are optimally obtained by using the Galerkin method. The authors thus obtain an analytical representation of the voltage response in the process variables that can be directly sampled to obtain the voltage response at different process corners. The authors have verified their analysis exhaustively on several industrial power grids as large as 1.3 million nodes, and considering up to 20 process variables. Results from their method demonstrate a very good match with those from Monte Carlo simulations, while providing significant speedups of the order of 100 to 1,000 times for comparable accuracy.
Supporting trust building in distributed groups by appropriate security technology
Authors: Wolfgang Appelt, Sanjin Pajo, Wolfgang Prinz
Venue: Proceedings of the 2007 international ACM conference on Supporting group work (2007)

In this paper, we discuss requirements for building trust in locally distributed groups whose members co-operate via shared workspace systems. We argue that appropriate security technology should be an intrinsic part of such systems and describe a conceptual model as well as a recent extension to an existing shared workspace system that provides the respective functionality based on PGP.