ppxscal/embedding_network huggingface dataset:
Infinitely Divisible Cascades to Model the Statistics of Natural Images
Authors: Pierre Chainais
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2007)

We propose to model the statistics of natural images thanks to the large class of stochastic processes called Infinitely Divisible Cascades (IDC). IDC were first introduced in one dimension to provide multifractal time series to model the socalled intermittency phenomenon in hydrodynamical turbulence. We have extended the definition of scalar infinitely divisible cascades from 1 to N dimensions and commented on the relevance of such a model in fully developed turbulence in [1]. In this article, we focus on the particular 2 dimensional case. IDC appear as good candidates to model the statistics of natural images. They share most of their usual properties and appear to be consistent with several independent theoretical and experimental approaches of the literature. We point out the interest of IDC for applications to procedural texture synthesis.
Spatial Clustering Method Based on Cloud Model
Authors: Haijun Wang, Yu Deng
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 02 (2007)

Spatial clustering is one of those major methods applying to spatial data mining and knowledge discovery. The purpose of this paper is to set forth a spatial clustering method based on cloud model, which can be widely applied to the research on classification and hierarchy in realm of spatial data mining and knowledge discovery. The implementation procedure of this method is advanced, and the feasibility of this method is proven through experiments effectively. Key wordsspatial clustering, cloud model, spatial data mining, knowledge discovery
Applying a Model-based Approach for Embedded System Development
Authors: Christian Bunse, Hans-Gerhard Gross, Christian Peper
Venue: Proceedings of the 33rd EUROMICRO Conference on Software Engineering and Advanced Applications (2007)

Model-based and component-oriented software development approaches are slowly superseding traditional ways of developing embedded systems. For investigating to which extent model-based development is feasible for embedded system development, we conducted a case study in which a small embedded system is developed using the MARMOT approach. In order to evaluate the degree of reuse that might be achieved, the components of the case study are used in the context of different small projects. Several aspects of reuse, application size, ease of adaptation, and development effort are quantified. This analysis reveals that model-based and component-oriented development performs well for small embedded systems, and it leads to the conclusion that model-driven/component-based development of embedded systems enables adaptable applications with higherthan- normal reuse rate.
Test Compression / Decompression Based on JPEG VLC Algorithm
Authors: Hideyuki Ichihara, Yukinori Setohara, Yusuke Nakashima, Tomoo Inoue
Venue: Proceedings of the 16th Asian Test Symposium (2007)

Test data compression / decompression schemes for testing SoCs can reduce test application cost. A drawback of the previous schemes, however, is that a decompressor must be embedded in an SoC under test. In this paper, we target the testing of SoCs with multimedia cores and introduce a scheme of test compression / decompression with the decoding function in the multimedia cores. This scheme can utilize the decoder and encoder in a multimedia core for compressing and decompressing test data, and consequently it requires slight hardware overhead. As an example of the proposed scheme, we focus on a lossless variable-length coding (VLC) in the JPEG algorithm, and propose a test compression / decompression method using the VLC decoder. We also propose a test generation method for this scheme. Experimental results show that the test compression with the VLC can achieve high compression ratio and the proposed test generation method can increase the compression ratio.
Post-release information privacy protection: A framework and next-generation privacy-enhanced operating system
Authors: Yanjun Zuo, Timothy O'Keefe
Venue: Information Systems Frontiers (2007)

In today's digital world, privacy issues have received widespread public attention. Current research on information privacy protection focuses on release control and subject identity obscurity. Little work has been done, however, to prevent a piece of private information from being misused after that information has been released to external entities. This paper focuses on information privacy protection in a post-release phase. Without entirely depending on the information collector, an information owner is provided with powerful means to control and audit how his/her released information will be used, by whom, and when. The goal is to minimize the asymmetry of information flow between an information owner and an information collector. A set of innovative owner-controlled privacy protection and violation detection techniques has been proposed: Self-destroying File, Mutation Engine System, Automatic Receipt Collection, and Honey Token-based Privacy Violation Detection. Next generation privacy-enhanced operating system, which supports the proposed mechanisms, is introduced. Such a privacy-enhanced operating system stands for a technical breakthrough, which offers new features to existing operating systems. We discuss the functionalities of such an operating system and the design guidelines. To our best knowledge, no similar technical work has been found to provide post-release information privacy protection.
Identity formation, learning styles and trust in virtual worlds
Authors: Iris A. Junglas, Norman A. Johnson, Douglas J. Steel, D. Chon Abraham, Paul Mac Loughlin
Venue: ACM SIGMIS Database (2007)

Avatars in virtual worlds exhibit many of the social behaviors found in real life. As such, we can learn much about our own behaviors from them based on prior theories. But social psychological theories that help researchers understand real life behaviors may not necessarily apply to virtual worlds. In fact, we know little about how human behaviors, as depicted by the actions of avatars, will be different than they are in real life. For insight into this, we look at how virtual worlds impact three behaviors: forming an identity, learning, and trusting. Each of these provides some insight into behavior in virtual worlds and suggests what we must work to understand in order to modify or adapt existing social psychological theories to apply to virtual worlds.
A cluster validity index for fuzzy clustering
Authors: Yunjie Zhang, Weina Wang, Xiaona Zhang, Yi Li
Venue: Information Sciences: an International Journal (2008)

A new cluster validity index is proposed for the validation of partitions of object data produced by the fuzzy c-means algorithm. The proposed validity index uses a variation measure and a separation measure between two fuzzy clusters. A good fuzzy partition is expected to have a low degree of variation and a large separation distance. Testing of the proposed index and nine previously formulated indices on well-known data sets shows the superior effectiveness and reliability of the proposed index in comparison to other indices and the robustness of the proposed index in noisy environments.
Proceedings of the 2006 IEEE/ACM/IFIP Workshop on Embedded Systems for Real Time Multimedia
Venue: Proceedings of the 2006 IEEE/ACM/IFIP Workshop on Embedded Systems for Real Time Multimedia (2006)

The following topics are dealt with: adaptation algorithm; multimedia architecture design methodology; power optimization and energy characterization; hardware and interface synthesis; embedded software techniques
Abstract Syntax Trees - and their Role in Model Driven Software Development
Authors: G. Fischer, J. Lusiardi, J. Wolff von Gudenberg
Venue: Proceedings of the International Conference on Software Engineering Advances (2007)

Abstract syntax trees (ASTs) are known from compiler construction where they build the intermediate data format which is passed from the analytic front-end to the synthetic back-end. In model driven software development ASTs are used as a model of the source code. The Object Management Group (OMG) has issued a request for proposals for AST models. Various levels of abstraction can be introduced. ASTs can be used for program analysis and for program transformation. In this paper we present an eclipse based representation framework for ASTs.
From Signatures of Algebraic Specifications to Collections of Object-Oriented Class Signatures
Authors: Bastian Dolle, Walter Dosch
Venue: Proceedings of the International Conference on Software Engineering Advances (2007)

This paper presents a formal method how to transform the structured signature of an algebraic specification into a collection of object-oriented class signatures. We discuss possible design decisions and formalize them as design mappings. The transformation of the signature forms the syntactic basis for relating algebraic specifications with object-oriented modeling in a profound way. The approach bridges the gap between functional specification concepts and objectoriented modeling techniques and contributes to a better understanding of object-oriented software construction. We illustrate the transformation with a characteristic example. All transformation procedures have been implemented in the ASIOS tool.
Event Detection in Sports Video Based on Multiple Feature Fusion
Authors: Hua-Yong Liu, Tingting He, Hui Zhang
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 02 (2007)

Semantic sports video analysis has attracted more and more attention recently. In this paper, we present a football event detection method by using multiple feature extraction and fusion. Instead of using low-level features, the proposed method is built upon visual, auditory features, text and au- dio keywords. Promising event detection results have been achieved. By using the proposed method, we have been able to detect the football events accurately. Experimental re- sults have shown our proposed method is effective for foot- ball event detection.
An Improved Algorithm for the Simplification of Switching Functions Using Unique Identifiers on a Karnaugh Map
Authors: A. B. Marcovitz
Venue: IEEE Transactions on Computers (1969)

The use of unique identifiers to indicate covered terms in a Karnaugh map minimization algorithm significantly improves the chances of obtaining a minimum cover for complex functions. This correspondence presents a technique that takes advantage of unique identifers.
Performance Improvement of Bankruptcy Prediction using Credit Card Sales Information of Small & Micro Business
Authors: Jongsik Yoon, Young S. Kwon, Tae Hyup Roh
Venue: Proceedings of the 5th ACIS International Conference on Software Engineering Research, Management & Applications (2007)

Due to the poor financial statements which represent credit risk of small and micro business, it's been difficult to develop the credit evaluation model that reflects both consumer credit risk and business credit risk of small and micro business. The purpose of this study is to develop the credit evaluation model for small and micro businesses using credit card sales information in lieu of poor financial information. In order to develop the model, we derive some variables and analyze the relationship between good and bad credits. We find out that twelve variables are significant in predicting good or bad risk for small and micro business, which are categorized into the business period, scale for sale, a fluctuation in sales, sales pattern and business category's bankruptcy ratio, etc. We employ the new statistical learning technique, support vector machines (SVM) as a classifier. We use grid search technique to find out better parameter for SVM. The experimental result shows that credit card sales information could be a good substitute for the financial data on business credit risk in predicting the bankruptcy for small-micro businesses. In addition, we also find out that SVM performs best, when compared with other classifiers such as neural networks, CART, C5.0, multivariate discriminant analysis (MDA), and logistic regression analysis(LRA).
A Real-Time Worm Outbreak Detection System Using Shared Counters
Authors: Miad Faezipour, Mehrdad Nourani, Rina Panigrahy
Venue: Proceedings of the 15th Annual IEEE Symposium on High-Performance Interconnects (2007)

New networking applications such as Network Intrusion Detection Systems (NIDS) require finding the frequently repeated strings in a packet stream for further investigation. The strategy of finding frequently repeated strings within a given time frame of the packet stream has been quite efficient to detect the polymorphic worms. A novel real-time worm outbreak detection system using two-phase hashing is proposed in this paper. We use the concept of shared counters to minimize the memory cost while efficiently sifting through suspicious strings. We have simulated our system for various settings and packet stream sizes. Our system can support line speed of gigabit-rates with negligible false positive and negative.
Interactive 3D City Modeling using Google Earth and Ground Images
Authors: Weili Ding, Feng Zhu, Yingming Hao
Venue: Proceedings of the Fourth International Conference on Image and Graphics (2007)

A new interactive approach is presented and implemented for constructing 3D city models from Google Earth and ground images. Using the roof size provided by Google Earth and the image coordinates of the four corner points of the building rectangular facade, without any prior knowledge about the parameters of the camera, we show a method for obtaining the building height and facades textures from single ground image. Furthermore, we show an algorithm for computing the tree height using a known building height and shadows in the satellite image. Based on the height and texture acquisition methods presented in this paper and geographic information provided by Google Earth, the 3D model of a typical urban site is constructed and rendered using OpenGL. The modeling results indicate that our method has many good characteristics such as low cost, simple manipulation and satisfying resolution.
Observing local and global properties of metabolic pathways
Authors: Syed Asad Rahman, Dietmar Schomburg
Venue: Bioinformatics (2006)

Motivation: The local and global aspects of metabolic network analyses allow us to identify enzymes or reactions that are crucial for the survival of the organism(s), therefore directing us towards the discovery of potential drug targets. Results: We demonstrate a new method (‘load points’) to rank the enzymes/metabolites in the metabolic network and propose a model to determine and rank the biochemical lethality in metabolic networks (enzymes/metabolites) through ‘choke points’. Based on an extended form of the graph theory model of metabolic networks, metabolite structural information was used to calculate the k-shortest paths between metabolites (the presence of more than one competing path between substrate and product). On the basis of these paths and connectivity information, load points were calculated and used to empirically rank the importance of metabolites/enzymes in the metabolic network. The load point analysis emphasizes the role that the biochemical structure of a metabolite, rather than its connectivity (hubs), plays in the conversion pathway. In order to identify potential drug targets (based on the biochemical lethality of metabolic networks), the concept of choke points and load points was used to find enzymes (edges) which uniquely consume or produce a particular metabolite (nodes). A non-pathogenic bacterial strain Bacillus subtilis 168 (lactic acid producing bacteria) and a related pathogenic bacterial strain Bacillus anthracis Sterne (avirulent but toxigenic strain, producing the toxin Anthrax) were selected as model organisms. The choke point strategy was implemented on the pathogen bacterial network of B.anthracis Sterne. Potential drug targets are proposed based on the analysis of the top 10 choke points in the bacterial network. A comparative study between the reported top 10 bacterial choke points and the human metabolic network was performed. Further biological inferences were made on results obtained by performing a homology search against the human genome. Availability: The load and choke point modules are introduced in the Pathway Hunter Tool (PHT), the basic version of which is available on Contact: d.schomburg@uni-koeln.de Supplementary information: Supplementary data are available on Bioinformatics online.
An Analysis of Swapping Policies in Virtual Storage Systems
Authors: We-Min Chow
Venue: IEEE Transactions on Software Engineering (1977)

An important resource allocation mechanism in virtual storage operating systems is the maintainence of the multiprogramming level in main storage, especially when some form of working-set storage management strategy is employed. Swapping of programs in and out of main memory occurs when sufficient storage becomes available and when total storage demand exceeds capacity. In this paper, we propose a class of swapping algorithms that couples storage management parameters with swapping decisions. An analytic model is developed and numerical results are presented to compare the performance of these algorithms.
Analysing the Security Threats against Network Convergence Architectures
Authors: Patroklos Argyroudis, Robert McAdoo, Stephen Toner, Linda Doyle, Donal O'Mahony
Venue: Proceedings of the Third International Symposium on Information Assurance and Security (2007)

Current research trends in networks and telecommunications suggest that future architectures will aim for the convergence not only of fixed and mobile infrastructures, but also of different network layer technologies. Proposals like OCALA from UC Berkeley and our own TRANSIT can be used to converge different architectures and network layer overlays while supporting legacy applications. In this paper we analyse and assess the security threats against such systems. Our contribution constitutes the first step in designing security models for convergence architectures as part of their design and deployment phases, rather than as retrofitted mechanisms.
Decision support for dynamic greenhouse climate control strategies
Authors: O. Körner, G. Van Straten
Venue: Computers and Electronics in Agriculture (2008)

Earlier, different dynamic greenhouse climate regimes were designed with various aims as energy saving, biocide reduction or reduction of chemical growth retardants that are used for quality improvement. The aim of this research was to create a decision support tool in order to decide at which week of the year to use which climate control regime for the optimal gain of sustainability and plant quality. A combined greenhouse climate and control model was used to analyse separate and combined effects of six different regimes with increasing degrees of freedom for various climate variables. In this simulation study the model crop cut chrysanthemum was used. Temperature integration, dynamic humidity control, and negative DIF regimes were adapted from earlier papers (DIF=difference between average day and average night temperature, reduces the use of chemical growth regulators). Temperature integration with a regular 24-h averaging period (TI"2"4) and with two nested temperature averaging periods 24h and 6 days (TI"n, subscript 'n' for nested), and combinations of TI"2"4 and TI"n with the DIF concept (TI"2"4","D"I"F^x and TI"n","D"I"F^x, respectively) to control stem elongation were simulated. TI"2"4 and TI"n were also combined with a dynamic humidity control. All strategies were compared to a standard climate regime (BP, blueprint). The best choice of regimes regarding energy saving, plant quality and reductions of the use of chemicals was targeted for different seasons. In winter absolute energy saving compared to BP was highest when a DIF regime was applied, and the energy saving increased with decreasing DIF set point. In relative sense the largest energy saving can be obtained with TI"n (51% in a 4-week period), in spring or autumn (and then with TI"2"4 and the DIF regimes). In these seasons, however, TI"2"4","D"I"F^x or TI"n","D"I"F^x should be used to reduce chemical growth regulators. The decision whether to use TI"n, TI"2"4, or a DIF regime was therefore a decision between energy saving or saving of chemicals. The tool developed in this paper can be used to quantify the costs in energy or chemicals when using the one or other strategy.
Performance Analysis of Secure Call Admission Control in Heterogeneous Networks
Authors: A. Al-Haj, J. Mellor, I. Awan
Venue: Proceedings of the The 2007 International Conference on Next Generation Mobile Applications, Services and Technologies (2007)

The need for security is obviously growing very fast with the dramatic development in computer network communication. It is a fact, that sending information over any public network can be exposed to possible unauthorized access or malicious attacks. It becomes increasingly important to secure the data flow path. IPSec is a suite of protocols that adds security to communications at the IP level. Protocols within the IPSec suite make extensive use of cryptographic algorithms. Since these algorithms are computationally sophisticated, some hardware accelerators are needed to support high throughput. In this paper we propose an IPsec-based secure call admission control (SCAC) with multiple cryptographic accelerators. Our proposed IPsec-based Multifence Secure Call Admission Control in heterogeneous networks enhanced with Malicious Packets Filter (MPF), is a set of technologies and solutions. It enforces security policy and bandwidth compliance on all devices seeking to access network computing resources, in order to limit damage from emerging security threats and to allow network access only to compliant and trusted endpoint devices. This SCAC also provides support for quality of service. High-level simulations and the related results are provided to show the effectiveness of the SCAC.
A Theory of Refractive and Specular 3D Shape by Light-Path Triangulation
Authors: Kiriakos N. Kutulakos, Eron Steger
Venue: International Journal of Computer Vision (2008)

We investigate the feasibility of reconstructing an arbitrarily-shaped specular scene (refractive or mirror-like) from one or more viewpoints. By reducing shape recovery to the problem of reconstructing individual 3D light paths that cross the image plane, we obtain three key results. First, we show how to compute the depth map of a specular scene from a single viewpoint, when the scene redirects incoming light just once. Second, for scenes where incoming light undergoes two refractions or reflections, we show that three viewpoints are sufficient to enable reconstruction in the general case. Third, we show that it is impossible to reconstruct individual light paths when light is redirected more than twice. Our analysis assumes that, for every point on the image plane, we know at least one 3D point on its light path. This leads to reconstruction algorithms that rely on an "environment matting" procedure to establish pixel-to-point correspondences along a light path. Preliminary results for a variety of scenes (mirror, glass, etc.) are also presented.