ppxscal/embedding_network huggingface dataset:
Modeling of network traffic with self-similar process
Authors: Evgeniya Gospodinova, Mitko Gospodinov
Venue: Proceedings of the 9th International Conference on Computer Systems and Technologies and Workshop for PhD Students in Computing (2008)

This paper presents three algorithms for modelling of self-similar network traffic, based on the fractional Gaussian noise (FGN). These algorithms use different manners to compute the power spectrum of FGN. In the paper was made comparative analysis between them in terms of the computation speed and the accuracy in generating self-similar traffic with given Hurst parameters. The obtained results shown that both of the algorithms are with high agree of accuracy and they can be used in practical computer simulation studies.
Equalisation of satellite mobile channels with neural network techniques
Authors: Steven Bouchired, Daniel Roviras, Francis Castanié
Venue: Space Communications (1999)

The use of non-linear amplifiers near saturation in satellite channels causes severe distortion of the transmitted signal. These distortions make the matter of power efficiency prevail over spectral efficiency in satellite communication systems. Nowadays, the use of satellite segments for applications requiring ever increasing data rates puts this principle in question. The present article proposes to fight non-linear distortion caused by satellite amplifiers by resorting to simple neural network equalisation devices in the receiving earth terminals. Several neural network equalisers are introduced, and applied to a satellite Universal Mobile Telecommunication System (S-UMTS) channel model. They are shown not only to outperform conventional equalisation techniques like the linear transversal equaliser, but also to have better performance than the non-linear Volterra equaliser. The performance improvement is all the more sensitive as the modulation scheme used is severely distorted. The case of 16-QAM transmission over a mobile satellite link is studied in details.
Hair self shadowing and transparency depth ordering using occupancy maps
Authors: Erik Sintorn, Ulf Assarsson
Venue: Proceedings of the 2009 symposium on Interactive 3D graphics and games (2009)

This paper presents a method for quickly constructing a high-quality approximate visibility function for high frequency semi-transparent geometry such as hair. We can then reconstruct the visibility for any fragment without the expensive compression needed by Deep Shadow Maps and with a quality that is much better than what is attainable at similar framerates using Opacity Maps or Deep Opacity Maps. The memory footprint of our method is also considerably lower than that of previous methods. We then use a similar method to achieve back-to-front sorted alpha blending of the fragments with results that are virtually indistinguishable from depth-peeling and an order of magnitude faster.
ZnO clusters: Laser ablation production and time-of-flight mass spectroscopic study
Authors: A. Dmytruk, I. Dmitruk, I. Blonskyy, R. Belosludov, Y. Kawazoe, A. Kasuya
Venue: Microelectronics Journal (2009)

Zinc oxide clusters have been produced by laser ablation of bulk powder zinc peroxide in vacuum and investigated by time-of-flight mass spectroscopy. Experimental results revealed unpredicted and hitherto unknown (ZnO)"n clusters of enhanced stability (''magic clusters'') at n=34, 60 and 78. Cage-like structures for the magic clusters have been suggested, supported by first-principles calculations.
Efficient Feature Selection in the Presence of Multiple Feature Classes
Authors: Paramveer S. Dhillon, Dean Foster, Lyle H. Ungar
Venue: Proceedings of the 2008 Eighth IEEE International Conference on Data Mining (2008)

We present an information theoretic approach to feature selection when the data possesses feature classes. Feature classes are pervasive in real data. For example, in gene expression data, the genes which serve as features may be divided into classes based on their membership in gene families or pathways. When doing word sense disambiguation or named entity extraction, features fall into classes including adjacent words, their parts of speech, and the topic and venue of the document the word is in. When predictive features occur predominantly in a small number of feature classes, our information theoretic approach significantly improves feature selection. Experiments on real and synthetic data demonstrate substantial improvement in predictive accuracy over the standard $L_0$ penalty-based stepwise and stream wise feature selection methods as well as over Lasso and Elastic Nets, all of which are oblivious to the existence of feature classes.
Marketing in a Random Network
Authors: Hamed Amini, Moez Draief, Marc Lelarge
Venue: Network Control and Optimization: Second Euro-NF Workshop, NET-COOP 2008 Paris, France, September 8-10, 2008. Revised Selected Papers (2009)

Viral marketing takes advantage of preexisting social networks among customers to achieve large changes in behaviour. Models of influence spread have been studied in a number of domains, including the effect of "word of mouth" in the promotion of new products or the diffusion of technologies. A social network can be represented by a graph where the nodes are individuals and the edges indicate a form of social relationship. The flow of influence through this network can be thought of as an increasing process of active nodes: as individuals become aware of new technologies, they have the potential to pass them on to their neighbours. The goal of marketing is to trigger a large cascade of adoptions. In this paper, we develop a mathematical model that allows to analyze the dynamics of the cascading sequence of nodes switching to the new technology. To this end we describe a continuous-time and a discrete-time models and analyse the proportion of nodes that adopt the new technology over time.
Methodology for successful undergraduate recruiting in computer science at comprehensive public universities
Authors: Patricia Morreale, Stan Kurkovsky, George Chang
Venue: ACM SIGCSE Bulletin (2009)

This paper presents a methodology for increasing undergraduate Computer Science (CS) major enrollment at comprehensive public universities, particularly those that have first generation college students or students from underrepresented populations in professional computer science in the United States. While there has been significant prior discussion of undergraduate recruiting to increase major enrollment in CS, this is the first identification of a systematic approach to recruiting distinct undergraduate student populations into the CS major. Nationally, highly selective and selective universities and colleges have worked within their student populations to increase major enrollments, while CS departments at comprehensive public universities primarily focused on regional recruiting have also worked to identify and increase CS major enrollments. The approach outlined here addresses regional recruiting for undergraduate majors in CS and has been used at two public universities. The resulting methodology serves as a template for any department or faculty member seeking to increase undergraduate enrollment in CS.
Matrix approach to discrete fractional calculus II: Partial fractional differential equations
Authors: Igor Podlubny, Aleksei Chechkin, Tomas Skovranek, YangQuan Chen, Blas M. Vinagre Jara
Venue: Journal of Computational Physics (2009)

A new method that enables easy and convenient discretization of partial differential equations with derivatives of arbitrary real order (so-called fractional derivatives) and delays is presented and illustrated on numerical solution of various types of fractional diffusion equation. The suggested method is the development of Podlubny's matrix approach [I. Podlubny, Matrix approach to discrete fractional calculus, Fractional Calculus and Applied Analysis 3 (4) (2000) 359-386]. Four examples of numerical solution of fractional diffusion equation with various combinations of time-/space-fractional derivatives (integer/integer, fractional/integer, integer/fractional, and fractional/fractional) with respect to time and to the spatial variable are provided in order to illustrate how simple and general is the suggested approach. The fifth example illustrates that the method can be equally simply used for fractional differential equations with delays. A set of MATLAB routines for the implementation of the method as well as sample code used to solve the examples have been developed.
Learning on Weighted Hypergraphs to Integrate Protein Interactions and Gene Expressions for Cancer Outcome Prediction
Authors: TaeHyun Hwang, Ze Tian, Rui Kuangy, Jean-Pierre Kocher
Venue: Proceedings of the 2008 Eighth IEEE International Conference on Data Mining (2008)

Building reliable predictive models from multiple complementary genomic data for cancer study is a crucial step towards successful cancer treatment and a full understanding of the underlying biological principles. To tackle this challenging data integration problem, we propose a hypergraph-based learning algorithm called HyperGene to integrate microarray gene expressions and protein-protein interactions for cancer outcome prediction and biomarker identification. HyperGene is a robust two-step iterative method that alternatively finds the optimal outcome prediction and the optimal weighting of the marker genes guided by a protein-protein interaction network. Under the hypothesis that cancer-related genes tend to interact with each other, the HyperGene algorithm uses a protein-protein interaction network as prior knowledge by imposing a consistent weighting of interacting genes. Our experimental results on two large-scale breast cancer gene expression datasets show that HyperGene utilizing a curated protein-protein interaction network achieves significantly improved cancer outcome prediction. Moreover, HyperGene can also retrieve many known cancer genes as highly weighted marker genes.
Intelligent scheduling and replication: a synergistic approach
Authors: Ali Elghirani, Riky Subrata, Albert Y. Zomaya
Venue: Concurrency and Computation: Practice Experience (2009)

In large-scale data-intensive applications data play a pivotal role in the execution of these applications, and data transfer is a primary cause of job execution delay. In environments such as the data grids where execution of jobs that require large amounts of data is undertaken, a smart collaborative environment between the scheduling and data management services to achieve a synergistic effect on the performance of the grid becomes essential. This paper presents an intelligent data grid framework where job scheduling and data and replica management are coupled to provide an integrated environment for efficient access to data and job scheduling. The data management service predicts and estimates the appropriate locations of replica and proactively replicates the data sets in these locations while the intelligent tabu-search-based scheduler incorporating information about the data sets dispatches the jobs to the sites expected to facilitate minimum job execution time and better overall system utilization. Evaluation of the framework shows significant improvement in the performance of the grid and job execution time. Copyright &copy; 2008 John Wiley & Sons, Ltd.
A comparison of via-programmable gate array logic cell circuits
Authors: Thomas C.P. Chau, Philip H.W. Leong, Sam M.H. Ho, Brian P.W. Chan, Steve C.L. Yuen, Kong-Pang Pun, Oliver C.S. Choy, Xinan Wang
Venue: Proceeding of the ACM/SIGDA international symposium on Field programmable gate arrays (2009)

Via-programmable gate arrays (VPGAs) offer a middle ground between application specific integrated circuits and field programmable gate arrays in terms of flexibility, manufactuing cost, speed, power and area. In this paper, we present a novel VPGA logic cell, the complementary universal logic gate (CULG) which can be used to implement both sequential and combinatorial elements. Its performance is compared with a number of other designs including transmission gate, differential cascode voltage switch with pass gate, and standard cell. The CULG is found to have comparable power-delay product and process variation sensitivity to the other designs while offering the lowest power consumption.
Robustness of complex communication networks under link attacks
Authors: Yubo Wang, Shi Xiao, Gaoxi Xiao, Xiuju Fu, Tee Hiang Cheng
Venue: Proceedings of the 2008 International Conference on Advanced Infocomm Technology (2008)

Recent research results show that some most important complex communication systems, which usually can be modeled as scale-free networks with a power-law nodal degree distribution, may be fragile under intentional attacks that take down network hubs. We study the robustness of these networks under deliberate attacks which remove network links. Specifically, we evaluate the extreme case where an efficient graph-partitioning algorithm is applied, based on accurate network-topology information, to decide on the links to be removed. Simulation results show that even such type of calculated link-removal attack cannot easily split a complex communication network. Moreover, among the two split parts, the larger one generally remains as a scale-free network with a very small network diameter. We also consider the case where a specific set of nodes have to be split away from the major part of the network. Simulation results show that applying a graph-partitioning algorithm generally does not lead to a significantly more cost-effective solution than simply removing the given set of nodes together with the links connected to them.
Extraction of Rectangular Boundaries from Aerial Image Data
Authors: Dong-Chul Park, Vu Thi Lan Huong, Dong-Min Woo, Yunsik Lee
Venue: Proceedings of the 2009 International Conference on Computer Engineering and Technology - Volume 02 (2009)

A novel approach for the extraction of rectangular boundaries from aerial image data is proposed and presented in this paper. In this approach, a Centroid Neural Network (CNN) with a metric of line segments is also proposed for connecting low-level linear structures or grouping similar objects. Extracting rectangular boundaries for building rooftops from an edge image without height information of buildings such as stereo pairs or digital elevation models is very challenging and difficult. We introduce an approach that involves a combination of many algorithms to identify rectangular boundaries in a bottom-up manner. After the straight lines are extracted from an edge image using the CNN, rectangular boundaries are then found by using an edge-based grouping approach originating from perceptual concepts. We present the steps of the proposed building rooftop recognition method and experimental results on an edge image.
An Approach to Enable Workflow in Mobile Work Scenarios
Authors: Andrés Neyem, Dario Franco, Sergio F. Ochoa, José A. Pino
Venue: Computer Supported Cooperative Work in Design IV: 11th International Conference, CSCWD 2007, Melbourne, Australia, April 26-28, 2007. Revised Selected Papers (2008)

This paper shows how to use workflows to model collaboration in ad-hoc mobile environments. Particularly, it introduces the concept of "active entity", which is a network-isolated subcomponent of a workflow process. This is shown how active entities overcome the challenges of an ad-hoc mobile environment and describes the support required for this workflow extension in terms of lightweight software architecture for mobile devices.
Adaptive on-chip power supply with robust one-cycle control technique
Authors: Dongsheng Ma, Janet Wang, Minkyu Song
Venue: IEEE Transactions on Very Large Scale Integration (VLSI) Systems (2008)

In this paper, an integrated adaptive-output switching converter is proposed. The design employs a one-cycle control for fast line regulation and a single outer loop for tight load regulation and fine tuning. A switched-capacitor integrator is introduced to the one-cycle control to obtain positive integration with a single positive power supply, allowing a standard low-cost CMOS fabrication process. To improve the efficiency, a dynamic loss control technique is presented. The converter was designed and fabricated with 0.35 µm N-well CMOS process. With a supply voltage of 3 V, a voltage ripple of less than ±20 mV is measured. The maximum efficiency is 92% with a load power of 475 mW. The converter exhibits a tracking speed of 23.75 µs/V for both start-up and reference voltage transitions. The recovery time for a 20% load change is approximately 9.5 µs.
Model order reduction of nonlinear systems via the trajectory piecewise linear approach application to transmission lines circuit
Authors: Z. Yacine, A. Benfdila, S. Djennoune
Venue: Proceedings of the 8th conference on Applied informatics and communications (2008)

Analyse, simulate and control systems is quite often a very hard and expensive task, because the models obtained by modelling are so complicate in one side by the nonlinear character and on the other one by the very high order due to the necessity to represent the behaviour of the system with precision, like models of MEMS (Micro Electro Mechanical Systems), circuits of interconnects and circuits of power electronic systems. The solution is to find approximations of such models reproducing the original behaviour accurately. For this purpose, several approaches have been developed, but often deal with local approximation which is insufficient to represent exactly the original model. In this paper we propose an approach to nonlinear model order reduction which guarantees a simplification and an accurate representation of the behaviour of strongly non linear systems handling local and global approximation ensuring a good quality of approximation. We illustrate the technique on a nonlinear circuit transmission lines.
Thermal-aware floorplanning for task migration enabled active sub-threshold leakage reduction
Authors: Hushrav D Mogal, Kia Bazargan
Venue: Proceedings of the 2008 IEEE/ACM International Conference on Computer-Aided Design (2008)

This paper presents a new approach to active sub-threshold leakage reduction using task migration. The main idea is to replicate a hot module in a design so as to actively migrate its computation at regular intervals, reducing the on-chip temperature and thereby the subthreshold leakage. We observe that choosing which blocks to migrate and their placement in a floorplan is a chicken-and-egg problem. To solve this, we propose a two step floorplanning methodology, wherein, given a base floorplan, we first choose the modules to replicate and then effectively utilize the deadspaces in it by exploiting the lateral conduction of heat in the floorplan to place a module's replica. With an optimized floorplan, using task migration we obtain an average savings of 29% in the active sub-threshold leakage at the expense of about 6% additional area.
Improving target detection by coupling it with tracking
Authors: Junxian Wang, George Bebis, Mircea Nicolescu, Monica Nicolescu, Ronald Miller
Venue: Machine Vision and Applications (2009)

Target detection and tracking represent two fundamental steps in automatic video-based surveillance systems where the goal is to provide intelligent recognition capabilities by analyzing target behavior. This paper presents a framework for video-based surveillance where target detection is integrated with tracking to improve detection results. In contrast to methods that apply target detection and tracking sequentially and independently from each other, we feed the results of tracking back to the detection stage in order to adaptively optimize the detection threshold and improve system robustness. First, the initial target locations are extracted using background subtraction. To model the background, we employ Support Vector Regression (SVR) which is updated over time using an on-line learning scheme. Target detection is performed by thresholding the outputs of the SVR model. Tracking uses shape projection histograms to iteratively localize the targets and improve the confidence level of detection. For verification, additional information based on size, color and motion information is utilized. Feeding back the results of tracking to the detection stage restricts the range of detection threshold values, suppresses false alarms due to noise, and allows to continuously detect small targets as well as targets undergoing perspective projection distortions. We have validated the proposed framework in two different application scenarios, one detecting vehicles at a traffic intersection using visible video and the other detecting pedestrians at a university campus walkway using thermal video. Our experimental results and comparisons with frame-based detection and kernel-based tracking methods illustrate the robustness of our approach.
Accuracy Refinement Algorithm for Mobile Target Location Tracking by Radio Signal Strength Indication Approach
Authors: Erin-Ee-Lin Lau, Wan-Young Chung
Venue: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences (2008)

A novel RSSI (Received Signal Strength Indication) refinement algorithm is proposed to enhance the resolution for indoor and outdoor real-time location tracking system. The proposed refinement algorithm is implemented in two separate phases. During the first phase, called the pre-processing step, RSSI values at different static locations are collected and processed to build a calibrated model for each reference node. Different measurement campaigns pertinent to each parameter in the model are implemented to analyze the sensitivity of RSSI. The propagation models constructed for each reference nodes are needed by the second phase. During the next phase, called the runtime process, real-time tracking is performed. Smoothing algorithm is proposed to minimize the dynamic fluctuation of radio signal received from each reference node when the mobile target is moving. Filtered RSSI values are converted to distances using formula calibrated in the first phase. Finally, an iterative trilateration algorithm is used for position estimation. Experiments relevant to the optimization algorithm are carried out in both indoor and outdoor environments and the results validated the feasibility of proposed algorithm in reducing the dynamic fluctuation for more accurate position estimation.
An assessment of rain attenuation impact on satellite communication: Matching service quality and system design to the time of the day
Authors: Emilio Matricciani
Venue: Space Communications (2000)

The paper presents long term probability distributions of rain attenuation exceeded in 0.5-h, 1-h, 2-h, 4-h, contiguous periods of the day, at 11.6 GHz, circular polarisation, over a 32Ž slant path from Spino d'Adda (Po Valley) in Northern Italy, compared to the usually considered long term results. The main findings are independent of frequency. These data can be useful in matching system design and service quality, which is affected very differently by rain attenuation to the time of the day. The results are applicable to communication satellites, and to TV and radio broadcasting. The data have been obtained by applying the synthetic storm technique to a large and statistical reliable set of 1233 rain rate time series collected in 10.6 years of continuous observation, thereby deriving 1233 rain attenuation time series.