ppxscal/embedding_network huggingface dataset:
Mining, modeling, and evaluation of subnetworks from large biomolecular networks and its comparison study
Authors: Xiaohua Hu, Michael Ng, Fang-Xiang Wu, Bahrad A. Sokhansanj
Venue: IEEE Transactions on Information Technology in Biomedicine (2009)

In this paper, we present a novel method to mine, model, and evaluate a regulatory system executing cellular functions that can be represented as a biomolecular network. Our method consists of two steps. First, a novel scale-free network clustering approach is applied to such a biomolecular network to obtain various subnetworks. Second, computational models are generated for the subnetworks and simulated to predict their behavior in the cellular context. We discuss and evaluate some of the advanced computational modeling approaches, in particular, state-spacemodeling, probabilisticBoolean network modeling, and fuzzy logic modeling. The modeling and simulation results represent hypotheses that are tested against high-throughput biological datasets (microarrays and/or genetic screens) under normal and perturbation conditions. Experimental results on time-series gene expression data for the human cell cycle indicate that our approach is promising for subnetwork mining and simulation from large biomolecular networks.
Multi-level Partition of Unity Algebraic Point Set Surfaces
Authors: Chunxia Xiao, Guangpu Feng, Yu Chu, Zhongyi Du, Xunhua Yang
Venue: Proceedings of the 2009 International Conference on Multimedia Information Networking and Security - Volume 01 (2009)

We present a multi-level partition of unity algebraic set surfaces (MPU-APSS) for surface reconstruction which can be represented by either a projection or in an implicit form. A algebraic point set surface (APSS) defines a smooth surface from a set of unorganized points using local moving least-squares (MLS) fitting of algebraic spheres. However, due to the local nature, APSS does not work well for geometry editing and modeling. Instead, our method builds a global implicit approximation function for the scattered pointset based on the partition of unity approach. By using an octree subdivision strategy, we first adaptively construct local algebraic spheres for the point set, and then apply weighting functions to blend together these local shape functions. Finally, we compute an error-controlled approximation of the signed distance function from the surface. In addition, we present an efficient projection operator which makes our representation suitable for point set filtering and dynamic point resampling. We demonstrate the effectiveness of our unified approach for both surface reconstruction and geometry modeling such as shape blending, surface completion and deformations. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
A Directed Labeled Graph Frequent Pattern Mining Algorithm Based on Minimum Code
Authors: Yuhua Li, Quan Lin, Gang Zhong, Dongsheng Duan, Yanan Jin, Wei Bi
Venue: Proceedings of the 2009 Third International Conference on Multimedia and Ubiquitous Engineering (2009)

Most of existing frequent subgraph mining algorithms are used to deal with undirected unlabeled marked graph. A few of them aim at directed graph or labeled graph. But in the real world ,a lot of connections have direction and label,so directed labeled graph mining is more meaningful. Now we are analyzing a financial network which can be modeled by a directed weighted graph. We are interested in the patterns which are frequent.The graph pattern means a uniform expression of graphs which has different marked nodes but same structure. In our application we consider direction and weight as part of the pattern. It’s different from subgraph because subgraph mining consider the labels of nodes. This paper proposes a new algorithm mSpan for directed labeled graph frequent pattern mining. Based on FP-growth, the algorithm gets a minimum edge code and an abstract node code sequence to indentify a directed graph pattern uniquely through minimum extension. It can solve the graph pattern isomorphic problem and the redundant extension problem. The experiment shows that mSpan can mine all frequent directed, labeled graph patterns.
Full vectoring optimal power allocation in xDSL channels under per-modem power constraints and spectral mask constraints
Authors: Vincent Le Nir, Marc Moonen, Jan Verlinden, Mamoun Guenach
Venue: IEEE Transactions on Communications (2009)

In xDSL systems, crosstalk can be separated into two categories, namely in-domain crosstalk and out-of-domain crosstalk. In-domain crosstalk is also refered to as self crosstalk. Out-of-domain crosstalk is crosstalk originating from outside the multi-pair system and is also denoted as external noise (alien crosstalk, radio frequency interference,...). While self crosstalk in itself can easily be canceled by a linear detector like the ZF detector, the presence of external noise requires a more advanced processing. Coordination between transmitters and receivers enables the self crosstalk and the external noise to be mitigated using MIMO signal processing, usually by means of a whitening filter and SVD. In this paper, we investigate the problem of finding the optimal power allocation in MIMO xDSL systems in the presence of self crosstalk and external noise. Optimal Tx/Rx structures and power allocation algorithms will be devised under practical limitations from xDSL systems, namely per-modem total power constraints and/or spectral mask constraints, leading to a generalized SVD-based transmission. Simulation results are given for bonded VDSL2 systems with external noise coming from ADSL2+ or VDSL2 disturbing lines, along with a comparison between algorithms with one-sided signal coordination either only at the transmit side or the receive side.
Randomized cooperation in asynchronous dispersive links
Authors: Matthew Sharp, Anna Scaglione, Birsen Sirkeci-Mergen
Venue: IEEE Transactions on Communications (2009)

Recently, we proposed a decentralized cooperative communication scheme [1]. In this paper we show that randomized decentralized schemes perform well even when the cooperating nodes are asynchronous. In particular we study the attainable diversity for frequency selective channels, and the coding gain in comparison to a centralized scheme.
Research on the application of content analysis to online learning
Authors: Jing Leng, Jian Liao, Ronghuai Huang
Venue: Proceedings of the 10th IASTED International Conference on Computers and Advanced Technology in Education (2007)

For the past ten years, computer-mediated communication has been a revolutionary tool to support instruction. Thus content analysis of computer-mediated communication needed to be employed to qualitatively analyze the electronic discourse. The paper describes a system that analyzes discussion content by combining word frequency counts with a key word in context analysis. In terms of the calculation of concept similarity, a formal concept lattice is implemented based on HowNet through mapping the concept, sememe and the relationship in HowNet into formal context. The application shows that it provides good foundation for the research of concept similarity based on the knowledge in HowNet.
An on-chip loopback block for RF transceiver built-in test
Authors: Marvin Onabajo, Jose Silva-Martinez, Felix Fernandez, Edgar Sánchez-Sinencio
Venue: IEEE Transactions on Circuits and Systems II: Express Briefs (2009)

This brief addresses the realization of an on-chip block for built-in testing of RF transceivers with the loopback method. Design issues and measurement results are discussed, giving practical insights into closing the signal path between transmitter (Tx) and receiver (Rx) sections. The circuit is intended for cost-efficient production testing of RF front-end blocks with on-chip power detectors and bit-error-rate analysis at baseband frequencies for integrated transceivers operating in the 1.9- to 2.4-GHz range. It can provide 40-200 MHz Tx-Rx frequency shifting and 26-42 dB continuous attenuation while consuming a 0.052-mm2 die area in 0.13-µm CMOS technology and ∼12 mW of power when activated in test mode.
An Approach for Database Intrusion Detection Based on the Event Sequence Clustering
Authors: Yinzhao Li, Dongxu Yang, Jiadong Ren, Changzhen Hu
Venue: Proceedings of the 2009 Fifth International Joint Conference on INC, IMS and IDC (2009)

Database intrusion detection technology is an important part of the database security. The paper presents a new database intrusion detection method based on the event sequence clustering. Firstly, aiming at computing the similarity of two SQL statement sequences, an improved edit distance function is defined. The corresponding clustering results are obtained by the computed similarity. Secondly, the attack sequences are detected by calculating the similarity between user’s operation sequences and cluster center. The association between two operation sequences is analyzed. At last, the experimental results show that our approach has lower false alarm rate and higher accuracy rate.
Medium access control priority mechanism for a DQMAN-based wireless network
Authors: J. Alonso-Zárate, D. Gregoratti, P. Giotis, C. Verikoukis, L. Alonso
Venue: IEEE Communications Letters (2009)

The analysis of an access priority mechanism for a high-performance Medium Access Control (MAC) protocol, the Distributed Queueing MAC protocol for wireless Ad Hoc Networks (DQMAN), is presented in this letter. DQMAN is comprised of a hierarchical, dynamic, and spontaneous master-slave clustering algorithm together with an embedded tree-splitting collision resolution algorithm based on access minislots. The responsibility of being master entails extra functionality, and thus extra energy consumption. Therefore, this responsibility must be shared in a dynamic manner among all the stations of the network in order to ensure fairness in the system. By allowing those stations acting as master stations to avoid contention to get access to the channel, their average packet transmission delay can be effectively reduced compared to that of slave stations. Consequently, stations may be encouraged to operate in master mode regardless of the extra functions they may have to carry out. We analyze in this letter the reduced average packet transmission delay for masters.
How replicated data management in the cloud can benefit from a data grid protocol: the Re:GRIDiT Approach
Authors: Laura Cristiana Voicu, Heiko Schuldt
Venue: Proceeding of the first international workshop on Cloud data management (2009)

Cloud computing has recently received considerable attention both in industry and academia. Due to the great success of the first generation of Cloud-based services, providers have to deal with larger and larger volumes of data. Quality of service agreements with customers require data to be replicated across data centers in order to guarantee a high degree of availability. In this context, Cloud Data Management has to address several challenges, especially when replicated data are concurrently updated at different sites or when the system workload and the resources requested by clients change dynamically. Mostly independent from recent developments in Cloud Data Management, Data Grids have undergone a transition from pure file management with read-only access to more powerful systems. In our recent work, we have developed the Re:GRIDiT protocol for managing data in the Grid which provides concurrent access to replicated data at different sites without any global component and supports the dynamic deployment of replicas. Since it is independent from the underlying Grid middleware, it can be seamlessly transferred to other environments like the Cloud. In this paper, we compare Data Management in the Grid and the Cloud, briefly introduce the Re:GRIDiT protocol and show its applicability for Cloud Data Management.
An Intra Prediction Mode-Based Video Encryption Algorithm in H.264
Authors: Jianguo Jiang, Shiyi Xing, Meibin Qi
Venue: Proceedings of the 2009 International Conference on Multimedia Information Networking and Security - Volume 01 (2009)

H.264 is a new video encoding world standard, and the security of video based on H.264 is becoming a research focus. This paper analyses the security shortage of the intra prediction mode (IPM) encryption algorithm proposed by Ahn[1] from view of perception performance, plaintext scrambling space and key security and then presents an improved IPM encryption algorithm (IPMEA). It encrypts all the IPMs by chaotic pseudo-random sequence, scrambles them for the second time by circulating sequence controlled by key and gives a scheme of key distribution and synchronization. Performance analysis and experimental results show that IPMEA can exhibit higher security than the existing ones and has little impact on code length. Meanwhile, it has low complexity and good real-time property, so it is suitable for real-time video transferring on the network.
Extreme Learning Machine with Fuzzy Activation Function
Authors: Hieu Trung Huynh, Yonggwan Won
Venue: Proceedings of the 2009 Fifth International Joint Conference on INC, IMS and IDC (2009)

Recently, an efficient learning algorithm called extreme learning machine (ELM) has been proposed for single-hidden layer feed forward neural networks (SLFNs). Unlike the traditional gradient-descent based learning algorithms which determine network weights by iterative processes, the ELM algorithm analytically determines the output weights with random choice of input weights and hidden layer biases. This algorithm can achieve good performance with very high learning speed. In this paper, we propose a novel fuzzy-based activation function for SLFNs trained by ELM algorithm. This is a simple sigmoid-like nonlinear activation function and more suitable for hardware implementation. The experimental results for real applications show that this activation function offers good performance which is compatible to the sigmoidal activation function.
A comparison of solution procedures for two-machine flow shop scheduling with late work criterion
Authors: Jacek Blazewicz, Erwin Pesch, Malgorzata Sterna, Frank Werner
Venue: Computers and Industrial Engineering (2005)

In this paper we analyze different solution procedures for the two-machine flow shop scheduling problem with a common due date and weighted late work criterion, i.e. for problem F2|d"j=d|Y"w , which is known to be binary NP-hard. In computational experiments we compare the practical efficiency of a dynamic programming approach, an enumerative method and a heuristic list scheduling procedure. Test results show that each solution method has its advantages and none of them can be rejected from consideration a priori.
Novel web page classification techniques in contextual advertising
Authors: Jung-Jin Lee, Jung-Hyun Lee, JongWoo Ha, SangKeun Lee
Venue: Proceeding of the eleventh international workshop on Web information and data management (2009)

Contextual advertising seeks to place relevant ads to generic web pages based on their contents. Recently, it has been observed that classifying web pages into a well-organized taxonomy of topics is promising for matching topically relevant ads to web pages. Following the observation, in this paper we propose two methods to increase classification accuracy for web pages in the context of contextual advertising. Our strategy is to enhance the baseline classifier by reflecting unique features of web pages and the taxonomy. In particular, category tags extracted from web pages are utilized to augment term weights, and the hierarchical structure of the taxonomy is taken into account to categorize web pages with high confidence. We conduct a series of experiments to evaluate the proposed methods, and the results show that classification accuracy is increased up to 11% compared to the baseline classifier.
MATLAB functions to analyze directional (azimuthal) data-I: Single-sample inference
Authors: Thomas A. Jones
Venue: Computers Geosciences (2006)

Data that represent azimuthal directions cannot be analyzed statistically in the same manner as ordinary variables that measure, for example, size or quality. Many statistical techniques have been developed for dealing with directional data, but available software for the unique calculations is scarce. This paper describes a MATLAB script, located on the IAMG server, that calculates descriptive statistics and performs inference on azimuthal parameters. The calculations include tests for specific distributions, and tests on the preferred direction and concentration of vectors about this direction. The inference methods use large-sample approximations, plus resampling methods (bootstrap) for smaller sample sizes.
The Design of Evaluation Index System of Growth Capacity of Small & Medium-Sized Enterprises and Its Empirical Analysis
Authors: Bin Xu, Renjing Xu
Venue: Proceedings of the 2009 Second International Symposium on Knowledge Acquisition and Modeling - Volume 01 (2009)

With the continuous development of market economy, the position of small & medium-sized enterprises (abbreviation: SMEs) became more and more important in Chinese national economy. However, as a result of the increasingly competitive market economy and the internal reasons of SMEs, the SMEs generally have shorter life expectancy. In order to grasp, in terms of whole, the growth status and development trends of SMEs, in this paper, we firstly proposed the necessity building the evaluation index system of growth capacity of SMEs, then we constructed the evaluation index system and introduced evaluation method. At last, we carried out an empirical analysis with above-mentioned methods and came to the relevant conclusions.
Fast centrality approximation in modular networks
Authors: Shu Yan Chan, Ian X.Y. Leung, Pietro Liò
Venue: Proceeding of the 1st ACM international workshop on Complex networks meet information & knowledge management (2009)

Measuring the centrality of nodes in real-world networks has remained an important task in the technological, social, and biological network paradigms carrying implications on their analysis and applications. Exact inference of centrality values is infeasible in large networks due to the need to solve the all-pairs shortest path problem. We introduce a framework to approximate node centralities in real-world networks that are known to exhibit modularity, i.e., the presence of dense subgraphs or communities, which are themselves sparsely connected. We also propose a novel centrality measure known as Community Inbetweenness that ranks nodes based solely on community information. In a modular network of size n with √n(1/2) evenly sized communities and m edges, our framework requires linear time O(m) and O(√nm) time for the approximation of closeness and betweenness respectively. Utilizing a recently proposed linear time method in community detection, our approximation techniques are faster than traditional sampling algorithms, applicable in real-time distributed environments, and offer highly comparable results.
On the attenuation of DAC aliases through multiphase clocking
Authors: Paul T. M. Van Zeijl, Manel Collados
Venue: IEEE Transactions on Circuits and Systems II: Express Briefs (2009)

L-fold" interpolation can be used to lower aliases of digital-to-analog converters (DACs). L-fold interpolation uses multiple DACs, each clocked with different phases of a single clock frequency with each DAC using the same signal data. The literature on this topic indicates that lowering the aliases can only be done by increasing the number of DACs and clock phases. This brief shows that by proper selection of clock phases, precise cancelling of certain aliases for a two-phase clock with two DACs is already possible. The cancellation of aliases helps reduce unwanted spurious emissions when DACs are used as amplitude modulators in polar transmitters.
A Method of Network Traffic Analysis Based on Multiple-Combination Model
Authors: Jing Wu, Yan-heng Liu, Rong Lv, Guo-xin Cao
Venue: Proceedings of the 2009 Fifth International Joint Conference on INC, IMS and IDC (2009)

The traditional stationary network traffic model (ARIMA) is incapable of describing non-stationary characteristics. In the process of predicting, the accuracy will weaken with the increase of step. As a non-stationary network traffic model, NN (neural network) could make up for the defect of stationary model, which can not describe the non-stationary qualities of the network traffic. However, the parameters choice of NN doesn’t have a specific theoretical foundation. According to the problems above, the paper proposes a method of multiple combinations. First, we compared the errors of ARIMA with those of Elman model, and then designed a multiple-combination model which applied to network traffic analysis. The result shows that the method is superior to a single model.
Statistical analysis of water-quality data containing multiple detection limits: S-language software for regression on order statistics
Authors: Lopaka Lee, Dennis Helsel
Venue: Computers Geosciences (2005)

Trace contaminants in water, including metals and organics, often are measured at sufficiently low concentrations to be reported only as values below the instrument detection limit. Interpretation of these ''less thans'' is complicated when multiple detection limits occur. Statistical methods for multiply censored, or multiple-detection limit, datasets have been developed for medical and industrial statistics, and can be employed to estimate summary statistics or model the distributions of trace-level environmental data. We describe S-language-based software tools that perform robust linear regression on order statistics (ROS). The ROS method has been evaluated as one of the most reliable procedures for developing summary statistics of multiply censored data. It is applicable to any dataset that has 0 to 80% of its values censored. These tools are a part of a software library, or add-on package, for the R environment for statistical computing. This library can be used to generate ROS models and associated summary statistics, plot modeled distributions, and predict exceedance probabilities of water-quality standards.
Approximate performance analysis of coded OSTBC-OFDM systems over arbitrary correlated generalized Ricean fading channels
Authors: Pavel Loskot, Norman C. Beaulieu
Venue: IEEE Transactions on Communications (2009)

A framework for analyzing the performance of coded OSTBC-OFDM systems over arbitrary correlated generalized Ricean fading channels is established. The moment generating function of the signal-to-noise ratio at the input to the channel decoder is derived assuming correlated transmitter and receiver antennas and correlated paths in frequency selective channels. The probability of outage, the pairwise error probability, and the bit error rate are then evaluated. Bit-interleaved and iteratively decoded turbo product codes, Gray encoded M-ary quadrature amplitude modulation, and other parameters of the IEEE 802.16 Standard are used to illustrate numerical results.