ppxscal/embedding_network huggingface dataset:
Bittorrent peer identification based on behaviors of a choke algorithm
Authors: Wanchai Ngiwlay, Chalermek Intanagonwiwat, Yunyong Teng-amnuay
Venue: Proceedings of the 4th Asian Conference on Internet Engineering (2008)

Bittorrent is currently one of the most popular peer-to-peer (P2P) file sharing protocols. However, it incurs such excessive amount of traffic that it may adversely affect users of legacy internet applications. To limit this adverse impact, an efficient methodology for bittorrent identification may be needed. In this paper, we propose a novel approach to identify local bittorrent peers. Our approach is based on behaviors of the choke algorithm, a main algorithm used in bittorrent. An advantage of our approach is that we can identify bittorrent peers without examining the packet pay-load. Therefore, our approach is free from privacy issues and still effective even though the packet payload is encrypted. Unlike previous works, we identify bittorrent hosts at the peer level instead of the flow level. Given that we use only information from network layer instead of transport layer, our work maintains fewer states and achieves robustness to changes in the transport layer. Furthermore, our work is effective even in restricted environments such as networks equipped with NAT devices or firewalls without modifications to existing network equipments. Our experimental result indicates that our approach can efficiently identify most of excessive bandwidth-consuming peers (i.e., peers transfer a large amount of data in our traces) with a low false-positive rate.
Using data driven simulation to build inventory model
Authors: Minghui Yang
Venue: Proceedings of the 40th Conference on Winter Simulation (2008)

Many general-purpose simulation languages (such as ARENA, SLAM II, GPSS/H, SIMAN etc) have been the major simulation tools to simulate the demand-supply processes. They have made great contributions to the decision making. But in the recent years, followed by the fast development of WINDOW applications, powerful PC hardware and software, numerous applications have used different approaches to develop simulation applications. One rapidly developing area in simulation is dynamic data-driven simulation (DDDS) by using data manipulation and analysis packages. SAS is a powerful tool for data analysis and data manipulation. It can also be used to build simulation models in data driven applications. This article presents our research development in this area for demand forecast applications.
Linear modeling and simulation of low-voltage electric system for single-point vulnerability assessment of military installation
Authors: Edgar C. Portante, Thomas N. Taxon, James A. Kavicky, Tarek Abdallah, Timothy K. Perkins
Venue: Proceedings of the 40th Conference on Winter Simulation (2008)

This paper describes the formulation and development of a linear model to support the single-point vulnerability assessment of electric distribution systems at existing and future U.S. Department of Defense (DoD) military sites. The model uses flow sensitivity factors to rank candidates for designation as "critical components" and uses triggered cascading line outages to confirm the component's criticality. The model is written in Java and integrated in a package that employs a user-friendly graphical user interface (GUI) for convenient display of results. This paper describes the process used to formulate the model and presents a sample application.
Matching incomplete time series with dynamic time warping: an algorithm and an application to post-stroke rehabilitation
Authors: Paolo Tormene, Toni Giorgino, Silvana Quaglini, Mario Stefanelli
Venue: Artificial Intelligence in Medicine (2009)

Objective: The purpose of this study was to assess the performance of a real-time (''open-end'') version of the dynamic time warping (DTW) algorithm for the recognition of motor exercises. Given a possibly incomplete input stream of data and a reference time series, the open-end DTW algorithm computes both the size of the prefix of reference which is best matched by the input, and the dissimilarity between the matched portions. The algorithm was used to provide real-time feedback to neurological patients undergoing motor rehabilitation. Methods and materials: We acquired a dataset of multivariate time series from a sensorized long-sleeve shirt which contains 29 strain sensors distributed on the upper limb. Seven typical rehabilitation exercises were recorded in several variations, both correctly and incorrectly executed, and at various speeds, totaling a data set of 840 time series. Nearest-neighbour classifiers were built according to the outputs of open-end DTW alignments and their global counterparts on exercise pairs. The classifiers were also tested on well-known public datasets from heterogeneous domains. Results: Nonparametric tests show that (1) on full time series the two algorithms achieve the same classification accuracy (p-value =0.32); (2) on partial time series, classifiers based on open-end DTW have a far higher accuracy (@k=0.898 versus @k=0.447;p
Design and chip implementation of the ubiquitous processor HCgorilla
Authors: Masa-aki Fukase, Kazunori Noda, Atsuko Yokoyama, Tomoaki Sato
Venue: Proceedings of the 2009 Asia and South Pacific Design Automation Conference (2009)

This paper describes the chip design and implementation of a special processor architecture, HCgorilla. It is a hardware cryptography-embedded multimedia mobile processor dedicated for ubiquitous computing. This is supported by multiple pipelines composed of media and cipher pipes. Media pipes are user friendly due to Java compatibility. Cipher pipes are suited to cryptographic streaming due to random number addressing. The chip design follows power conscious wave-pipelining and seeks test simplification. The chip implementation uses a CMOS standard cell technology.
BackSpace: formal analysis for post-silicon debug
Authors: Flavio M. De Paula, Marcel Gort, Alan J. Hu, Steven J. E. Wilton, Jin Yang
Venue: Proceedings of the 2008 International Conference on Formal Methods in Computer-Aided Design (2008)

Post-silicon debug is the problem of determining what's wrong when the fabricated chip of a new design behaves incorrectly. This problem now consumes over half of the overall verification effort on large designs, and the problem is growing worse. We introduce a new paradigm for using formal analysis, augmented with some on-chip hardware support, to automatically compute error traces that lead to an observed buggy state, thereby greatly simplifying the post-silicon debug problem. Our preliminary simulation experiments demonstrate the potential of our approach: we can "backspace" hundreds of cycles from randomly selected states of some sample designs. Our preliminary architectural studies propose some possible implementations and show that the on-chip overhead can be reasonable. We conclude by surveying future research directions.
Adaptive neuro-fuzzy inference system for classification of ECG signals using Lyapunov exponents
Authors: Elif Derya íbeyli
Venue: Computer Methods and Programs in Biomedicine (2009)

This paper describes the application of adaptive neuro-fuzzy inference system (ANFIS) model for classification of electrocardiogram (ECG) signals. Decision making was performed in two stages: feature extraction by computation of Lyapunov exponents and classification by the ANFIS trained with the backpropagation gradient descent method in combination with the least squares method. Four types of ECG beats (normal beat, congestive heart failure beat, ventricular tachyarrhythmia beat, and atrial fibrillation beat) obtained from the PhysioBank database were classified by four ANFIS classifiers. To improve diagnostic accuracy, the fifth ANFIS classifier (combining ANFIS) was trained using the outputs of the four ANFIS classifiers as input data. The proposed ANFIS model combined the neural network adaptive capabilities and the fuzzy logic qualitative approach. Some conclusions concerning the saliency of features on classification of the ECG signals were obtained through analysis of the ANFIS. The performance of the ANFIS model was evaluated in terms of training performance and classification accuracies and the results confirmed that the proposed ANFIS model has potential in classifying the ECG signals.
Swapped (OTIS) Networks Built of Connected Basis Networks Are Maximally Fault Tolerant
Authors: Weidong Chen, Wenjun Xiao, Behrooz Parhami
Venue: IEEE Transactions on Parallel and Distributed Systems (2009)

An optical transpose interconnection system (OTIS) network with n^2 nodes is a two-level swapped architecture built of n copies of an n-node basis network that constitute its clusters. A simple rule for intercluster connectivity (node j in cluster i connected to node i in cluster j) leads to regularity, modularity, packageability, fault tolerance, and algorithmic efficiency of the resulting networks. We prove that an OTIS (swapped) network with a connected basis network possesses maximal fault tolerance, regardless of whether its basis network is maximally fault tolerant. We also show how the corresponding maximal number of node-disjoint paths between two nodes of a swapped network can be algorithmically constructed in a manner that is independent of the existence and construction of node-disjoint paths within its basis network. Our results are stronger than previously published results and they replace a number of proofs and constructions in the literature for specific basis networks. Additionally, we use our parallel path constructions to establish that the fault diameter and wide diameter of an OTIS network is no more than 4 units greater than its diameter.
Directions in Network-Based Security Monitoring
Authors: Phillip Porras
Venue: IEEE Security and Privacy (2009)

This article outlines some recently emerging research in network-based malicious software detection. The author discusses differences between traditional network intrusion detection and these new techniques, and highlights a new freely available tool called BotHunter.
Computation of the third-order partial derivatives from a digital elevation model
Authors: Igor V. Florinsky
Venue: International Journal of Geographical Information Science (2009)

Loci of extreme curvature of the topographic surface may be defined by the derivation function (T) depending on the first-, second-, and third-order partial derivatives of elevation. The loci may partially describe ridge and thalweg lines. The first-and second-order partial derivatives are commonly calculated from a digital elevation model (DEM) by fitting the second-order polynomial to a 3&times;3 window. This approach cannot be used to compute the third-order partial derivatives and T. We deduced formulae to estimate the first-, second-, and third-order partial derivatives from a DEM fitting the third-order polynomial to a 5&times;5 window. The polynomial is approximated to elevation values of the window. This leads to a local denoising that may enhance calculations. Under the same grid size of a DEM and root mean square error (RMSE) of elevation, calculation of the second-order partial derivatives by the method developed results in significantly lower RMSE of the derivatives than that using the second-order polynomial and the 3&times;3 window. An RMSE expression for the derivation function is deduced. The method proposed can be applied to derive any local topographic variable, such as slope gradient, aspect, curvatures, and T. Treatment of a DEM by the method developed demonstrated that T mapping may not substitute regional logistic algorithms to detect ridge/thalweg networks. However, the third-order partial derivatives of elevation can be used in digital terrain analysis, particularly, in landform classifications.
Fusion of Feature- and Area-Based Information for Urban Buildings Modeling from Aerial Imagery
Authors: Lukas Zebedin, Joachim Bauer, Konrad Karner, Horst Bischof
Venue: Proceedings of the 10th European Conference on Computer Vision: Part IV (2008)

Accurate and realistic building models of urban environments are increasingly important for applications, like virtual tourism or city planning. Initiatives like Virtual Earth or Google Earth are aiming at offering virtual models of all major cities world wide. The prohibitively high costs of manual generation of such models explain the need for an automatic workflow.This paper proposes an algorithm for fully automatic building reconstruction from aerial images. Sparse line features delineating height discontinuities and dense depth data providing the roof surface are combined in an innovative manner with a global optimization algorithm based on Graph Cuts. The fusion process exploits the advantages of both information sources and thus yields superior reconstruction results compared to the indiviual sources. The nature of the algorithm also allows to elegantly generate image driven levels of detail of the geometry.The algorithm is applied to a number of real world data sets encompassing thousands of buildings. The results are analyzed in detail and extensively evaluated using ground truth data.
Semi-Lagrangian semi-implicit time-splitting scheme for a regional model of the atmosphere
Authors: Andrei Bourchtein, Ludmila Bourchtein
Venue: Journal of Computational and Applied Mathematics (2009)

Semi-Lagrangian semi-implicit (SLSI) method is currently one of the most efficient approaches for numerical solution of the atmosphere dynamics equations. In this research we apply splitting techniques in the context of a two-time-level SLSI scheme in order to simplify the treatment of the slow physical modes and optimize the solution of the elliptic equations related to implicit part of the scheme. The performed numerical experiments show the accuracy and computational efficiency of the scheme.
HIPS: Hyper-Interaction within Physical Space
Authors: G. Benelli, A. Bianchi, P. Marti, D. Sennati, E. Not
Venue: Proceedings of the 1999 IEEE International Conference on Multimedia Computing and Systems - Volume 02 (1999)

HIPS is a project recently funded by the European Commission within the I-Cube initiative whose main aim is to study new technologies and interaction modalities that allow people to navigate both a physical space and a related information space at the same time, with a minimal gap between the two. The project envisages a portable electronic tour guide (to exhibitions, museums, archaeological sites, expositions distributed over a city, and to cities themselves) which empowers visitors to determine themselves the structure of a tour, according to their own criteria, interests and needs and which allow different information delivery modalities.
Outlier Removal by Convex Optimization for L-Infinity Approaches
Authors: Yongduek Seo, Hyunjung Lee, Sang Wook Lee
Venue: Proceedings of the 3rd Pacific Rim Symposium on Advances in Image and Video Technology (2009)

This paper is about removing outliers without iterations in L &thinsp;&infin;&thinsp; optimization. Existing L &thinsp;&infin;&thinsp; outlier removal method requires iterative removal of the set of measurements with greatest residual during L &thinsp;&infin;&thinsp; minimization. In the method presented in this paper, on the other hand, a threshold is preset once for the maximum residual error in a manner similar to RANSAC, and the measurements yielding greater residuals than the threshold are taken to be outliers. We examine two feasibility test algorithms: 1) one that minimizes the maximum infeasibility and 2) the other that minimizes the sum of infeasibilities (SOI). Both of these can be used for feasibility test in conjunction with the bisection algorithm which attains the L &thinsp;&infin;&thinsp; optimum. We note that the SOI method has an interesting characteristic due to its L1-norm minimization nature. It tries to estimate a robust solution while maximizing the number of feasible constraints. The infeasible constraints are found to be due mostly to outliers. Once we set a threshold, the SOI algorithm sorts out outliers from the data set without any repetition and substantial reduction of computation time can be achieved compared to the iterative method. Experiments with synthetic as well as real objects demonstrate the effectiveness of the SOI method. We suggest that the SOI method precede the outlier-sensitive L &thinsp;&infin;&thinsp; optimization.
Linear-time certifying recognition algorithms and forbidden induced subgraphs
Authors: Pinar Heggernes, Dieter Kratsch
Venue: Nordic Journal of Computing (2007)

We give the first linear-time certifying algorithms to recognize split graphs, threshold graphs, chain graphs, co-chain graphs and trivially perfect graphs, with sublinear certificates for negative output. In case of membership in a given graph class our algorithms provide as certificate a structure for the input graph that characterizes the class, and in case of non-membership they provide as certificate a forbidden induced subgraph of the class. The certificates of membership can be authenticated in time O(n + m) and the certificates of non-membership can be authenticated in time O(1).
The Smallest Sendmail Book
Authors: John Ostrowick
Venue:  (2008)

Sendmail is a program which runs on Linux and other UNIX-like operating systems, and its function is, as its name suggests, to deliver email. It also receives email. Sendmail is also one of the oldest and most reliable programs out there; it is just very complicated. This book aims to tell you what you need to know to get Sendmail to work. It is therefore intended as a book for beginners. It is also useful for hurried system administrators who do not have time to trawl Internet for solutions to problems that need to be solved right now. Sendmail is particularly difficult to understand, and has many cryptic error messages. After reading through this book, however, you should be able to configure a Sendmail server, and you should be able to understand most of its error messages.
Incremental sequence-based frequent query pattern mining from XML queries
Authors: Guoliang Li, Jianhua Feng, Jianyong Wang, Lizhu Zhou
Venue: Data Mining and Knowledge Discovery (2009)

Existing algorithms of mining frequent XML query patterns (XQPs) employ a candidate generate-and-test strategy. They involve expensive candidate enumeration and costly tree-containment checking. Further, most of existing methods compute the frequencies of candidate query patterns from scratch periodically by checking the entire transaction database, which consists of XQPs transferred from user query logs. However, it is not straightforward to maintain such discovered frequent patterns in real XML databases as there may be frequent updates that may not only invalidate some existing frequent query patterns but also generate some new frequent query patterns. Therefore, a drawback of existing methods is that they are rather inefficient for the evolution of transaction databases. To address above-mentioned problems, this paper proposes an efficient algorithm ESPRIT to mine frequent XQPs without costly tree-containment checking. ESPRIT transforms XML queries into sequences using a one-to-one mapping technique and mines the frequent sequences to generate frequent XQPs. We propose two efficient incremental algorithms, ESPRIT-i and ESPRIT-i +, to incrementally mine frequent XQPs. We devise several novel optimization techniques of query rewriting, cache lookup, and cache replacement to improve the answerability and the hit rate of caching. We have implemented our algorithms and conducted a set of experimental studies on various datasets. The experimental results demonstrate that our algorithms achieve high efficiency and scalability and outperform state-of-the-art methods significantly.
SRV: A Virtual Reality Application to Electrical Substations Operation Training
Authors: Eder Arroyo, Jose Luis Los Arcos
Venue: Proceedings of the IEEE International Conference on Multimedia Computing and Systems - Volume 2 (1999)

The purpose of this paper si to present the SRV (Virtual Reality System), a virtual reality application to train personnel associated with the manual operation of electrical substations equipment. We present a low-cost PC-based application which allows the user both to know the basic elements of an electrical substation in terms of appearance, behaviour and functionality and to operate the substation interacting with the switching equipment and performing operations like in the real world. The SRV system is composed of a plant simulator (SGI Simulator), which is currently used by IBERDROLA in the training process of operators in the execution of local manoeuvres in those substations where there are no automation or remote control facilities, and the virtual reality environment, a set or realistic three dimensional models of different types of substations. The capability of generating automatically any substation from the single-line diagrams, the interaction facilities and the almost real appearance of the components, makes the SRV system a very good addition to the current operator training process.
Bijective proofs of partition identities arising from modular equations
Authors: Sun Kim
Venue: Journal of Combinatorial Theory Series A (2009)

We establish generalizations of certain partition theorems originating with modular equations and give bijective proofs for them. As a special case, we give a bijective proof of the Farkas and Kra partition theorem modulo 7.
Fusion of classifiers for illumination robust face recognition
Authors: Annalisa Franco, Loris Nanni
Venue: Expert Systems with Applications: An International Journal (2009)

In this paper the problem of face recognition under variable illumination conditions is considered. Most of the works in the literature exhibit good performance under strictly controlled acquisition conditions, but the performance drastically drop when changes in pose and illumination occur, so that recently a number of approaches have been proposed to deal with such variability. The aim of this work is twofold: first a survey on the existing techniques proposed to obtain an illumination robust recognition is given, and then a new method, based on the fusion of different classifiers, is proposed. The experiments carried out on different face databases confirm the effectiveness of the approach.
Adaptive model for user knowledge in the e-learning system
Authors: Todorka Glushkova
Venue: Proceedings of the 9th International Conference on Computer Systems and Technologies and Workshop for PhD Students in Computing (2008)

The paper presents a conceptual model and some ideas for realization of the e-learning system in the secondary school that is adaptive to the user knowledge. We propose the algorithm for evaluation of student's cognitions at three levels -- as general mark, as level of subject domain knowledge and as mark of each concept. According to this valuation and the stereotype information, the LMS starts and manages an appropriate training process.
CriAS: a performance-driven criticality-aware synthesis flow for on-chip multicycle communication architecture
Authors: Chia-I Chen, Juinn-Dar Huang
Venue: Proceedings of the 2009 Asia and South Pacific Design Automation Conference (2009)

In deep submicron era, wire delay is no longer negligible and is dominating the system performance. Several state-of-the-art architectural synthesis flows have been proposed for the distributed register architectures to cope with the increasing wire delay by allowing on-chip multicycle communication. In this paper, we present a new performance-driven criticality-aware synthesis flow CriAS targeting regular distributed register architectures. CriAS features a hierarchical binding strategy and a coarse-grained placer for minimizing the number of critical global data transfers. The key ideas are to take time criticality as the major concern at earlier binding stages before the detailed physical placement information is available, and to preserve the locality of closely related critical components in the later placement phase. The experimental results show that 19% overall performance improvement can be achieved on average as compared to the previous work.