ppxscal/embedding_network huggingface dataset:
Enterprise level IT risk management
Authors: Nadhirah Azizi, Khairuddin Hashim
Venue: Proceedings of the 8th conference on Applied computer scince (2008)

Increasing IT budget and over-dependence of business on IT infra-structure makes risk management a critical component of enterprise management. The creation and sustenance of an IT risk management framework is one of the crucial and challenging tasks of modern corporate enterprise management. This paper presents the risks that organizations face with respect to IT, discusses the key risks in IT related functions and proposes a framework to monitor the risks. Our framework organises IT risks into five categories: infrastructure development and support, operations and maintenance of business process, office level support, software development and outsourcing management. The framework becomes the basis for an enterprise risk assessment model.
Pattern analysis of dermoscopic images based on Markov random fields
Authors: Carmen Serrano, Begoña Acha
Venue: Pattern Recognition (2009)

In this paper a method for detecting different patterns in dermoscopic images is presented. In order to diagnose a possible skin cancer, physicians assess the lesion based on different rules. While the most famous one is the ABCD rule (asymmetry, border, colour, diameter), the new tendency in dermatology is to classify the lesion performing a pattern analysis. Due to the colour textured appearance of these patterns, this paper presents a novel method based on Markov random field (MRF) extended for colour images that classifies images representing different dermatologic patterns. First, each image plane in L^*a^*b^* colour space is modelled as a MRF following a finite symmetric conditional model (FSCM). Coupling of colour components is taken into account by supposing that features of the MRF in the three colour planes follow a multivariate Normal distribution. Performance is analysed in different colour spaces. The best classification rate is 86% on average.
Architecture Design of P2PSIP System
Authors: Yang Ji, Chunhong Zhang, Lichun Li, Yao Wang, Mao Tao
Venue: International Journal of Distributed Sensor Networks (2009)

P2PSIP (Peer-to-Peer Session Initiation Protocol) is proposed to construct fully distributed signaling architecture for multimedia communication systems. Instead of centralized SIP servers, P2PSIP overlays utilize distributed and dynamic nodes to support location and storage services. So far various design alternatives of overlay architectures have been proposed to describe the mechanism about how the user nodes are connected together to form an application layer topology. However, there appears to have been little research work on comprehensively comparing the performance properties of various P2PSIP architectures, and no study has been made to investigate how to select appropriate overlay architecture according to application requirements. In this paper, we investigate various P2PSIP architectures and compare their features mainly from the perspective of application performance. The query latency of overlay and call setup delay of SIP sessions are modeled as significant performance considerations for selection of suitable architecture for different usage scenarios. First, we comprehensively analyze implementations of P2PSIP architecture. Four typical P2PSIP architectures are described in detail: pure DHT, DHT-based SIP server farm, P2PSIP overlay formed by super nodes, and hierarchical P2PSIP overlay. Furthermore, we classify the nodes into peer and client according to their roles in the architecture. Then the performance model of query latency and call setup delay for P2PSIP overlay architectures is proposed. Several parameters to present features of the overlay architectures are defined. The analysis primarily focuses on the impact of possibility of packet loss caused by link error or network congestion and churn of overlay. Finally, an event-driven chord-based simulation to evaluate query latency and call setup delay for different P2PSIP architectures is developed. An analytical model and simulation showed that the average call setup delay is less than ten seconds for all the architectures, which could satisfy the requirements of multimedia session establishments in most cases. We advocate that the super node or hierarchical architecture might be appropriate options rather than pure DHT in terms of latency performance in heterogeneous network environments. The server farm approach is good at management as well as performance, which might be the best option for systems supported by service providers.
GaN membrane-supported UV photodetectors manufactured using nanolithographic processes
Authors: A. Müller, G. Konstantinidis, M. Dragoman, D. Neculoiu, A. Dinescu, M. Androulidaki, M. Kayambaki, A. Stavrinidis, D. Vasilache, C. Buiculescu, I. Petrini, A. Kostopoulos, D. Dascalu
Venue: Microelectronics Journal (2009)

Membrane GaN metal-semiconductor-metal (MSM) photodetector structures using nanolithographic techniques have been manufactured for the first time. Very low dark currents and unexpected high values for the responsivity have been obtained. It seems that the membrane together with the (submicronic) MSM structure increase the gain of the structure and responsivities in the range of 50-100A/W can be obtained.
Automated design and optimization of circuits in emerging technologies
Authors: Rajesh A. Thakker, Chaitanya Sathe, Angada B. Sachid, Maryam Shojaei Baghini, V. Ramgopal Rao, Mahesh B. Patil
Venue: Proceedings of the 2009 Asia and South Pacific Design Automation Conference (2009)

A novel table-based environment for automatic design and optimization of FinFET circuits is demonstrated. A new accurate look-up table (LUT) technique is implemented in a circuit simulator and integrated with particle swarm optimization algorithm for efficient circuit designs in novel devices. Op-amp circuits are designed and optimized to demonstrate the accuracy and usefulness of the proposed platform. Further, it is shown that the proposed design methodology can take into account variations in process, supply voltage, and temperature.
Design of Teacher E-portfolio System for Teacher Professional Development
Authors: Duan Xinyu, Li Min
Venue: Proceedings of the 2009 Second International Workshop on Knowledge Discovery and Data Mining (2009)

The teacher e-portfolio based on network is a product of modern information technology, it can record the teacher’s growth of instruction, strengthen their personal knowledge management, and more important, it can enhance their instruction reflection. Teacher professional development is an issue of general concern in education field, particularly with the implementation of the new curriculum reform. In this paper, we propose a new view for teacher professional development, which is teacher e-portfolio system; we design the module and function of the system based on the requirement analysis.
Shrinkage estimation in the frequency domain of multivariate time series
Authors: Hilmar Böhm, Rainer von Sachs
Venue: Journal of Multivariate Analysis (2009)

In this paper on developing shrinkage for spectral analysis of multivariate time series of high dimensionality, we propose a new nonparametric estimator of the spectral matrix with two appealing properties. First, compared to the traditional smoothed periodogram our shrinkage estimator has a smaller L"2 risk. Second, the proposed shrinkage estimator is numerically more stable due to a smaller condition number. We use the concept of ''Kolmogorov'' asymptotics where simultaneously the sample size and the dimensionality tend to infinity, to show that the smoothed periodogram is not consistent and to derive the asymptotic properties of our regularized estimator. This estimator is shown to have asymptotically minimal risk among all linear combinations of the identity and the averaged periodogram matrix. Compared to existing work on shrinkage in the time domain, our results show that in the frequency domain it is necessary to take the size of the smoothing span as ''effective sample size'' into account. Furthermore, we perform extensive Monte Carlo studies showing the overwhelming gain in terms of lower L"2 risk of our shrinkage estimator, even in situations of oversmoothing the periodogram by using a large smoothing span.
Denial of service attacks and defenses in decentralized trust management
Authors: Jiangtao Li, Ninghui Li, XiaoFeng Wang, Ting Yu
Venue: International Journal of Information Security (2009)

Trust management is an approach to scalable and flexible access control in decentralized systems. In trust management, a server often needs to evaluate a chain of credentials submitted by a client; this requires the server to perform multiple expensive digital signature verifications. In this paper, we study low-bandwidth Denial-of-Service (DoS) attacks that exploit the existence of trust management systems to deplete server resources. Although the threat of DoS attacks has been studied for some application-level protocols such as authentication protocols, we show that it is especially destructive for trust management systems. Exploiting the delegation feature in trust management languages, an attacker can forge a long credential chain to force a server to consume a large amount of computing resource. Using game theory as an analytic tool, we demonstrate that unprotected trust management servers will easily fall prey to a witty attacker who moves smartly. We report our empirical study of existing trust management systems, which manifests the gravity of this threat. We also propose a defense technique using credential caching, and show that it is effective in the presence of intelligent attackers.
On the closure of pattern expressions languages under intersection with regular languages
Authors: Cezar C&#x00e2;mpeanu, Nicolae Santean
Venue: Acta Informatica (2009)

In this paper we address a standing question on pattern expressions (PE), namely whether the family of PE languages is closed under the intersection with regular languages. Since this family is not closed under complement, but is closed under reversal, another natural question has frequently been raised in the recent years, on whether particular languages such as the mirror language and the language of palindromes are PE languages. We give answers to these and other related questions as well, thus providing an insight on their descriptional power.
Hypergraph-Based Anomaly Detection of High-Dimensional Co-Occurrences
Authors: Jorge Silva, Rebecca Willett
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2009)

This paper addresses the problem of detecting anomalous multivariate co-occurrences using a limited number of unlabeled training observations. A novel method based on using a hypergraph representation of the data is proposed to deal with this very high-dimensional problem. Hypergraphs constitute an important extension of graphs which allow edges to connect more than two vertices simultaneously. A variational Expectation-Maximization algorithm for detecting anomalies directly on the hypergraph domain without any feature selection or dimensionality reduction is presented. The resulting estimate can be used to calculate a measure of anomalousness based on the False Discovery Rate. The algorithm has $O(np)$ computational complexity, where $n$ is the number of training observations and $p$ is the number of potential participants in each co-occurrence event. This efficiency makes the method ideally suited for very high-dimensional settings, and requires no tuning, bandwidth or regularization parameters. The proposed approach is validated on both high-dimensional synthetic data and the Enron email database, where $p &#x003E; 75,000$, and it is shown that it can outperform other state-of-the-art methods.
New worker-centric scheduling strategies for data-intensive grid applications
Authors: Steven Y. Ko, Ramsés Morales, Indranil Gupta
Venue: Proceedings of the ACM/IFIP/USENIX 2007 International Conference on Middleware (2007)

Distributed computations, dealing with large amounts of data, are scheduled in Grid clusters today using either a task-centric mechanism, or a worker-centric mechanism. Because of the large data sets, the execution time is bounded by the cost of data transfer. In this paper, we introduce new worker-centric scheduling strategies that are novel in that they aim to implicitly exploit the locality of interest in order to reduce the cost of data transfer. Many Grid applications are characterized by such a locality of interest, i.e., a file is often accessed by multiple tasks and, more importantly, a set of files that are accessed by one task are also likely to be accessed together by other tasks. Our new deterministic, as well as probabilistic, scheduling algorithms implicitly exploit this feature to improve running time. Our experiments are done with traces of a real Grid application (Coadd), and show that our algorithms are able to achieve utilization of over 90%, while reducing makespan significantly compared to task-centric approaches.
A stochastic gradient type algorithm for closed-loop problems
Authors: Kengy Barty, Jean-S&#x00e9;bastien Roy, Cyrille Strugarek
Venue: Mathematical Programming: Series A and B (2009)

We focus on the numerical solution of closed-loop stochastic problems, and propose a perturbed gradient algorithm to achieve this goal. The main hurdle in such problems is the fact that the control variables are infinite-dimensional, due to, e.g., the information constraints. Alternatively said, control variables are feedbacks, i.e., functions. Such controls have hence to be represented in a finite way in order to solve the problem numerically. In the same way, the gradient of the criterion is itself an infinite-dimensional object. Our algorithm replaces this exact (and unknown) gradient by a perturbed one, which consists of the product of the true gradient evaluated at a random point and a kernel function which extends this gradient to the neighbourhood of the random point. Proceeding this way, we explore the whole space iteration after iteration through random points. Since each kernel function is perfectly known by a small number of parameters, say N, the control at iteration k is perfectly known as an infinite-dimensional object by at most N&#x00a0;&#x00d7;&#x00a0;k parameters. The main strength of this method is that it avoids any discretization of the underlying space, provided that we can sample as many points as needed in this space. Moreover, our algorithm can take into account the possible measurability constraints of the problem in a new way. Finally, the randomized strategy implemented by the algorithm causes the most probable parts of the space to be the most explored ones, which is a priori an interesting feature. In this paper, we first prove two convergence results of this algorithm in the strongly convex and convex cases, and then give some numerical examples showing the interest of this method for practical stochastic optimization problems.
Symmetric reconstruction algorithms for incomplete 3D models
Authors: Lilit Yenokyan, Armen Zakarian, Pravansu Mohanty, Vahram Avagyan
Venue: International Journal of Computer Applications in Technology (2009)

this paper, a new approach and algorithms for 3D model reconstruction, based on the model symmetry, are presented. After the incomplete 3D model is introduced to the system, symmetry type and model parameters are established, an algorithm is developed for model alignment. Symmetry analysis algorithms are proposed for collecting information on the asymmetric/missing sections of the aligned model on a layer-by-layer basis. The outputs of these algorithms are used to generate the triangular mesh of missing sections of the model. The methodology developed in this paper is illustrated with the 3D model reconstruction examples.
Analysis for the characteristics of non-uniform sampled fiber grating
Authors: X. J. Zhang, Z. Q. Ye
Venue: Proceedings of the 2008 International Conference on Advanced Infocomm Technology (2008)

Based on coupled mode theory, the optic-spectral property of non-uniform sampled fiber grating are theoretically analyzed and numerically simulated using the transfer matrix method. We believe the finding presented here offer useful guideline to the design of the sampled fiber Bragg grating.
Implementation of the AES Algorithm for a Reconfigurable, Bit Serial, Fully Pipelined Architecture
Authors: Raphael Weber, Achim Rettberg
Venue: Proceedings of the 5th International Workshop on Reconfigurable Computing: Architectures, Tools and Applications (2009)

This paper describes the implementation of the Advanced Encryption Standard (AES) for a specific hardware architecture, which was developed based on the combination of different design paradigms. The architecture comprises synchronous and systematic bit---serial processing without a central controlling instance. To realize the AES cipher, we extended the architecture by designing specific elements. That means, we deeply analyzed the encryption algorithm and identified hardware characteristics leading to an optimal area and run---time efficient implementation. The implementation of AES is done with the developed synthesis tool of the hardware architecture in synthesizable VHDL code. For testing purposes, we simulated the generated VHDL code and ran some tests on an FPGA board.
Satisfiability of Formulas from the Standpoint of Object Classification: The RST Approach
Authors: Anna Gomolińska
Venue: Fundamenta Informaticae (2008)

In this article we discuss judgment of satisfiability of formulas of a knowledge representation language as an object classification task. Our viewpoint is that of the rough set theory (RST), and the descriptor language for Pawlak's information systems of a basic kind is taken as the study case. We show how certain analogy-based methods can be employed to judge satisfiability of formulas of that language.
Discovery-oriented collaborative filtering for improving user satisfaction
Authors: Yoshinori Hijikata, Takuya Shimizu, Shogo Nishida
Venue: Proceedings of the 13th international conference on Intelligent user interfaces (2009)

Many recommender systems employed in commercial web sites use collaborative filtering. The main goal of traditional collaborative filtering techniques is improvement of the accuracy of recommendation. Nevertheless, such techniques present the problem that they include many items that the user already knows. These recommendations appear to be good when we consider accuracy alone. On the other hand, when we consider users' satisfaction, they are not necessarily good because of the lack of discovery. In our work, we infer items that a user does not know by calculating the similarity of users or items based on information about what items users already know. We seek to recommend items that the user would probably like and does not know by combining the above method and the most popular method of collaborative filtering.
A comparison of three educational robots: conference workshop
Authors: Tim DeClue, Phil Heeler, Scott Sigman
Venue: Journal of Computing Sciences in Colleges (2009)

This tutorial/workshop will demonstrate three programmable robots used in educational settings to teach computer science concepts. The platforms include: &bull; an older model LEGO robot kit using RoboLab software (price unavailable) &bull; the Paralax Scribbler as modified by the Institute for Personal Robotics Education at Georgia Robotics (cost around $200) &bull; the new LEGO Mindstorms NXT robot (cost is around $350) The LEGO robots have been used at Northwest Missouri State at the middle school level and at Drury University at the college level. The Scribbler was used in the fall of 2008 at Southwest Baptist University at both the high school and college level. The tutorial will consist of the presenters showing how the programming interface works for each of the robots. If time permits, the Scribblers will be used by up to 12 attendees (there will be 12 robots available) to gain hands-on experience.
Characterizing network traffic by means of the NetMine framework
Authors: Daniele Apiletti, Elena Baralis, Tania Cerquitelli, Vincenzo D'Elia
Venue: Computer Networks: The International Journal of Computer and Telecommunications Networking (2009)

The NetMine framework allows the characterization of traffic data by means of data mining techniques. NetMine performs generalized association rule extraction to profile communications, detect anomalies, and identify recurrent patterns. Association rule extraction is a widely used exploratory technique to discover hidden correlations among data. However, it is usually driven by frequency constraints on the extracted correlations. Hence, it entails (i) generating a huge number of rules which are difficult to analyze, or (ii) pruning rare itemsets even if their hidden knowledge might be relevant. To overcome these issues NetMine exploits a novel algorithm to efficiently extract generalized association rules, which provide a high level abstraction of the network traffic and allows the discovery of unexpected and more interesting traffic rules. The proposed technique exploits (user provided) taxonomies to drive the pruning phase of the extraction process. Extracted correlations are automatically aggregated in more general association rules according to a frequency threshold. Eventually, extracted rules are classified into groups according to their semantic meaning, thus allowing a domain expert to focus on the most relevant patterns. Experiments performed on different network dumps showed the efficiency and effectiveness of the NetMine framework to characterize traffic data.
A stochastic graph grammar for compositional object representation and recognition
Authors: Liang Lin, Tianfu Wu, Jake Porway, Zijian Xu
Venue: Pattern Recognition (2009)

This paper illustrates a hierarchical generative model for representing and recognizing compositional object categories with large intra-category variance. In this model, objects are broken into their constituent parts and the variability of configurations and relationships between these parts are modeled by stochastic attribute graph grammars, which are embedded in an And-Or graph for each compositional object category. It combines the power of a stochastic context free grammar (SCFG) to express the variability of part configurations, and a Markov random field (MRF) to represent the pictorial spatial relationships between these parts. As a generative model, different object instances of a category can be realized as a traversal through the And-Or graph to arrive at a valid configuration (like a valid sentence in language, by analogy). The inference/recognition procedure is intimately tied to the structure of the model and follows a probabilistic formulation consisting of bottom-up detection steps for the parts, which in turn recursively activate the grammar rules for top-down verification and searches for missing parts. We present experiments comparing our results to state of art methods and demonstrate the potential of our proposed framework on compositional objects with cluttered backgrounds using training and testing data from the public Lotus Hill and Caltech datasets.