ppxscal/embedding_network huggingface dataset:
Multipath traffic engineering in WDM optical burst switching networks
Authors: Yong Liu, Gurusamy Mohan, Kee Chaing Chua, Jia Lu
Venue: IEEE Transactions on Communications (2009)

In this paper, we investigate the problem of multipath traffic engineering in optical burst switching (OBS) networks. The main goal of this work is to minimize burst loss rate in the network by adaptively balancing the burst traffic among multiple paths based on the measurement and analysis of path congestion. We develop three distributed traffic splitting algorithms by considering the special features of OBS networks. Among these three algorithms, one algorithm considers burst level traffic distribution, and the other two algorithms consider flow level traffic distribution to avoid packet reordering problem. The proposed multipath traffic engineering algorithms achieve significant performance improvement in reducing burst loss probability in a distributed manner in OBS networks. Further, through theoretical analysis and simulations, we show that the proposed algorithms converge quickly on a sudden traffic increase in the network.
Auction Service Discovery Model - An Agent Based Approach
Authors: Nandini Sidnal, Sunilkumar S. Manvi
Venue: Proceedings of the 2009 Third International Conference on Multimedia and Ubiquitous Engineering (2009)

To support m-commerce applications such as mobile e-auctions, an efficient service discovery mechanism is required in a scenario where service directories are stored on distributed servers and users are mobile. E-auction services discovery in dynamic mobile environments poses many challenges such as dynamism in E-market, service access time, service filtering, lack of automated tools for searching and limitations of mobile devices.In this paper, we address the aforesaid challenges by using Belief Desire Intention (BDI) architecture based agents to achieve the following, 1) improve the service access time of the e-auction services search mechanism, 2) filtering the e-auction service list according to user and time context and 3)automate the e-auction service search process by using mobile agents. The partial simulation of the proposed work is done to analyze the performance parameters such as e-auction service request hit ratio and access time.
Lithuanian Virtual University as a construct for implementation of lifelong learning
Authors: Danguole Rutkauskiene, Aleksandras Targamadze, Egle Butkeviciene, Gvidas Rutkauskas
Venue: Proceedings of the 10th IASTED International Conference on Computers and Advanced Technology in Education (2007)

Nowadays, distance learning (DL) is run to meet important national and international needs based on economical, political, geographical and demographical conditions. It's the conditions of local and global societies that motivate utilization of DL, not only the strained economical conditions of the individual student [1]. Integral development of Lithuanian DL system is based on several integral programs and sub-programs. Lithuanian Distance Learning Network is established with the main goal - to develop and maintain Lithuanian Distance Education (DE) System and to assist in the preparation of DL courses. This is necessary in order to create better conditions for Lithuanian people in lifelong learning, as well as encourage higher education institutions to develop and apply DL. This paper analysis the situation of development of DL network, and problems of integration of this network into different vocational training sub-networks.
An advanced video-based system for monitoring active volcanoes
Authors: Bruno Andò, Emilio Pecora
Venue: Computers Geosciences (2006)

Video surveillance systems are consolidated techniques for monitoring eruptive phenomena in volcanic areas. Along with these systems, which use standard video cameras, people working in this field sometimes make use of infrared cameras providing useful information about the thermal evolution of eruptions. Real-time analysis of the acquired frames is required, along with image storing, to analyze and classify the activity of volcanoes. Human effort and large storing capabilities are hence required to perform monitoring tasks. In this paper we present a new strategy aimed at improving the performance of video surveillance systems in terms of human-independent image processing and storing optimization. The proposed methodology is based on real-time thermo-graphic analysis of the area considered. The analysis is performed by processing images acquired with an IR camera and extracting information about meaningful volcanic events. Two software tools were developed. The first provides information about the activity being monitored and automatically adapts the image storing rate. The second tool automatically produces useful information about the eruptive activity encompassed by a selected frame sequence. The software developed includes a suitable user interface allowing for convenient management of the acquired images and easy access to information about the volcanic activity monitored.
Uncertainty Optimization Model for Emergency Resource Scheduling
Authors: Di Li, Guangli Liu, Youjian Gao
Venue: Proceedings of the 2009 Second International Symposium on Knowledge Acquisition and Modeling - Volume 01 (2009)

Emergency resource scheduling Optimization model with uncertainty is presented under the condition of disaster. Firstly, emergency resource scheduling problem is discussed in the transport path optimization. Then according to the actual situation of emergence decision-making, of chance-constrained model a model of fuzzy chance constrained programming (FCCP) based on the credibility theory is constructed with fuzzy times. And a hybrid intelligent algorithm for solving chance constrained programming models with fuzzy decisions was also designed. Due to the premature phenomenon of genetic algorithm (GA), the simulated annealing algorithm is introduced in which selection and mutation operator is modified,. So the convergent speed has been increased and premature phenomenon can be avoided. At last, data experiment verified the validity and rationality of the algorithm.
MSMOTE: Improving Classification Performance When Training Data is Imbalanced
Authors: Shengguo Hu, Yanfeng Liang, Lintao Ma, Ying He
Venue: Proceedings of the 2009 Second International Workshop on Computer Science and Engineering - Volume 02 (2009)

Learning from data sets that contain very few instances of the minority class usually produces biased classifiers that have a higher predictive accuracy over the majority class, but poorer predictive accuracy over the minority class. SMOTE (Synthetic Minority Over-sampling Technique) is specifically designed for learning from imbalanced data sets. This paper presents a modified approach (MSMOTE) for learning from imbalanced data sets, based on the SMOTE algorithm. MSMOTE not only considers the distribution of minority class samples, but also eliminates noise samples by adaptive mediation. The combination of MSMOTE and AdaBoost are applied to several highly and moderately imbalanced data sets. The experimental results show that the prediction performance of MSMOTE is better than SMOTEBoost in the minority class and F-values are also improved.
Linear model extraction of a launch vehicle by system identification based on six degrees of freedom simulation
Authors: M. Tayefi, J. Roshanian, M. Bahrami
Venue: Proceedings of the IASTED Asian Conference on Modelling and Simulation (2007)

The transfer functions of the aerospace launch vehicle can be extracted using well-known linearization methodology. This paper presents an alternative to obtain the transfer functions via closed-loop identification using six degrees of freedom nonlinear simulation software. The vehicle is characterized by high nonlinearity, open loop instability and time-varying behaviours. The model structure with some unknown parameters is obtained after mathematical modeling, thus the case of our problem is a parameter identification one. Time-variant parameters are estimated by Kalman filter approach with the aid of ARX model structure.
Optimized non-unitary linear precoding for orthogonal space-time block codes
Authors: Haiyang Huang, Gang Wu, Shaoqian Li
Venue: IEEE Communications Letters (2009)

This letter proposes a novel optimized nonunitary linear precoding design for orthogonal space-time block codes (OSTBCs). We dig out the transmission potentials by the analysis from eigen-space point of view according to the unique structure of OSTBCs. The proposed precoding form is proved to be theoretically optimized. Compared with the classical unitary Grassmannian codebook design, in the sense of restriction on the time average power of transmit signal, the proposed nonunitary codebook further improves the overall performance of practical systems. The new constraint on codebook size to guarantee full diversity order is given and proved. The advantages of our proposed design are verified in the numerical simulations.
Low-power CMOS synchronous counter with clock gating embedded into carry propagation
Authors: Young-Won Kim, Joo-Seong Kim, Jae-Hyuk Oh, Yoon-Suk Park, Jong-Woo Kim, Kwang-Il Park, Bai-Sun Kong, Young-Hyun Jun
Venue: IEEE Transactions on Circuits and Systems II: Express Briefs (2009)

A novel low-power CMOS synchronous counter whose clock-gating logic is embedded into a carry propagation circuit is proposed. The proposed synchronous counter operates with no redundant transitions and requires fewer transistors, minimizing tbe switching power consumption and silicon area as compared wlth conventional CMOS synchronous counters. The proposed synchronous counter consisting of 16 bits was fabricated in 0.18-µm CMOS technology. The experimental result indicates that the proposed synchronous counter achieves a power saving of 64% with 15% device count reduction.
A heuristic for minimizing the makespan in no-idle permutation flow shops
Authors: Pawel Jan Kalczynski, Jerzy Kamburowski
Venue: Computers and Industrial Engineering (2005)

The paper deals with the problem of finding a job sequence that minimizes the makespan in m-machine flow shops under the no-idle condition. This condition requires that each machine must process jobs without any interruption from the start of processing the first job to the completion of processing the last job. Since the problem is NP-hard, we propose a constructive heuristic for solving it that significantly outperforms heuristics known so far.
A strategy for fair coexistence of loss and delay-based congestion control algorithms
Authors: Łukasz Budzisz, Rade Stanojevic, Robert Shorten, Fred Baker
Venue: IEEE Communications Letters (2009)

Delay-based TCP variants have attracted a large amount of attention in the networking community because of their ability to efficiently use network resources, control queuing delays, exhibit virtually zero packet loss, etc. One major issue that discourages the wider deployment of delay-based TCP variants is their inability to co-exist fairly with standard loss-based TCP. In this note we propose a simple mechanism that allows delay-and loss-based (AIMD) TCP flows to compete fairly with each other. Further, our approach ensures that delay-based flows automatically (and swiftly) switch to a low-delay regime if no loss-based flows are present. We provide analytical and simulation results to validate presented algorithm.
Integrating web-based intelligence retrieval and decision-making from the twitter trends knowledge base
Authors: Marc Cheong, Vincent Lee
Venue: Proceeding of the 2nd ACM workshop on Social web search and mining (2009)

Twitter as a microblogging platform has vast potential to become a collective source of intelligence that can be used to obtain opinions, ideas, facts, and sentiments. This paper addresses the issue on collective intelligence retrieval with activated knowledge-base decision making. Our methodology differs from the existing literature in the sense that we are doing analysis on Twitter microblog messages as opposed to traditional blog analysis in the literature which deals with the conventional 'blogosphere'. Another key difference in our methodology is that we apply visualization techniques in conjunction with artificial intelligence-based data mining methods to classify messages dealing with the trend topic. Our methodology also analyzes demographics of the authors of such Twitter messages and attempt to map a Twitter trend into what's going on in the real world. Our findings reveal a pattern behind trends on Twitter, enabling us to see how it 'ticks' and evolves though visualization methods. Our findings also enable us to understand the underlying characteristics behind the 'trend setters', providing us a new perspective on the contributors of a trend.
On reliable communications over channels impaired by bursty impulse noise
Authors: Dario Fertonani, Giulio Colavolpe
Venue: IEEE Transactions on Communications (2009)

Digital communications over channels impaired by impulse noise are addressed. We adopt a two-state Markov model that allows to describe the typical bursty nature of the impulse noise, in contrast to the memoryless models generally considered in the literature. For this channel, we evaluate the achievable information rate and propose a couple of practical communication systems based on powerful codes and iterative receivers. Moreover, we discuss the effectiveness of the considered receivers in terms of performance/latency tradeoff as well as in terms of robustness to erroneous channel estimations. The proposed schemes are shown to perform fairly close to the theoretical limits, and significantly better than the conventional schemes employing memoryless detection.
A unified method for determining the weight enumerators of binary extended quadratic residue codes
Authors: Chong-Dao Lee, Yan-Haw Chen, Yaotsu Chang
Venue: IEEE Communications Letters (2009)

This letter proposes an improved and unified method to determine the weight enumerators of binary extended quadratic residue (EQR) codes. It is faster than the previous methods for some of binary EQR codes. Moreover, all the results for the weight enumerators of binary EQR codes are listed.
Performance of collaborative spectrum sensing for cognitive radio in the presence of Gaussian channel estimation errors
Authors: Yunfei Chen, Norman C. Beaulieu
Venue: IEEE Transactions on Communications (2009)

The performance of collaborative spectrum sensing for cognitive radio in a lognormal shadowing and Rayleigh fading channel is investigated. Unlike previous works that assume perfect knowledge of the average channel signal-to-noise ratio, this paper considers the realistic case where estimation of the average channel signal-to-noise ratio has error. Furthermore, while previous works have designed and examined estimators based on assuming that the channel samples used in the average signal-to-noise ratio estimators are noiseless, the present work assumes that the channel samples are noisy, as is the case in practical systems. Numerical results show that the probability of missed opportunity decreases as the estimation error decreases, as expected. Perhaps unexpectedly, the results also show that in the presence of noise, there exists a threshold phenomenon for the noise level. Below a particular threshold, the probability of missed opportunity increases as the noise level increases. Yet above this threshold, the probability of missed opportunity decreases as the noise level increases.
Transforming a teacher education method course through technology: effects on preservice teachers' technology competency
Authors: Charoula Angeli
Venue: Computers Education (2005)

In this study, an instructional design model was employed for restructuring a teacher education course with technology. The model was applied in a science education method course, which was offered in two different but consecutive semesters with a total enrollment of 111 students in the fall semester and 116 students in the spring semester. Using tools, such as multimedia authoring tools in the fall semester and modeling software in the spring semester, teacher educators designed high quality technology-infused lessons for science and, thereafter, modeled them in classroom for preservice teachers. An assessment instrument was constructed to assess preservice teachers' technology competency, which was measured in terms of four aspects, namely, (a) selection of appropriate science topics to be taught with technology, (b) use of appropriate technology-supported representations and transformations for science content, (c) use of technology to support teaching strategies, and (d) integration of computer activities with appropriate inquiry-based pedagogy in the science classroom. The results of a MANOVA showed that preservice teachers in the Modeling group outperformed preservice teachers' overall performance in the Multimedia group, F=21.534, p=0.000. More specifically, the Modeling group outperformed the Multimedia group on only two of the four aspects of technology competency, namely, use of technology to support teaching strategies and integration of computer activities with appropriate pedagogy in the classroom, F=59.893, p=0.000, and F=10.943, p=0.001 respectively. The results indicate that the task of preparing preservice teachers to become technology competent is difficult and requires many efforts for providing them with ample of opportunities during their education to develop the competencies needed to be able to teach with technology.
Multipath combining scheme in single-carrier transmission systems
Authors: Jieling Wang, Hong Yang, Kechu Yi
Venue: IEEE Communications Letters (2009)

In this letter, we introduce and investigate the RAKE combining receiver which is widely used in the code-division multiple access (CDMA) systems to the non-spectrum-spreading single-carrier transmission system. The initial estimate of the transmitted data is obtained by linear single-carrier equalizers, and then all the multipath signals are constructed from this initial solution and channel impulse response. By interference cancellation (IC) technique, we can acquire every multipath component in the received signal after cancelling the sum of all the other multipath signals constructed. Finally, all the components are combined together using selection combining (SC), equal gain combining (EGC) or maximal ratio combining (MRC), so that temporal diversity gain from the combined output can be obtained. Simulation results show that bit error rate (BER) performance of the new combining receiver based on zero forcing (ZF) and minimum mean square error (MMSE) equalizers can achieve the SNR gain dramatically in the SUI-5 wireless communication link.
Analysis of Improved Routing Algorithm in Wireless Sensor Networks
Authors: Jinghua Wang, Yuanyuan Chen, Huan He, Tingting Guan, Yuegu Zhou
Venue: Proceedings of the 2009 Second International Workshop on Computer Science and Engineering - Volume 01 (2009)

How to get high efficient data routing for the limited energy resource networks is an important problem in the study of the wireless sensor networks. An improved routing algorithm for data aggregation based on ant colony algorithm (IACAR) is presented. The ant colony system provides a natural and intrinsic way of exploring search space in determining data aggregation. Every ant will explore all possible paths from the source node to the sink node. Simulation results show that proposed algorithm can reduce significant energy costs.
Packing the most onto your cloud
Authors: Ashraf Aboulnaga, Ziyu Wang, Zi Ye Zhang
Venue: Proceeding of the first international workshop on Cloud data management (2009)

Parallel dataflow programming frameworks such as Map-Reduce are increasingly being used for large scale data analysis on computing clouds. It is therefore becoming important to automatically optimize the performance of these frameworks. In this paper, we deal with one particular optimization problem, namely scheduling sets of Map-Reduce jobs on a cluster of machines. We present a scheduler that takes job characteristics into account and finds a schedule that minimizes the total completion time of the set of jobs. Our scheduler decides on the number of machines to assign to each job, and it tries to pack as many jobs on the machines as the machine resources can support. To enable flexible assignment of jobs onto machines, we run the Map-Reduce jobs in virtual machines. Our scheduling problem is formulated as a constrained optimization problem, and we experimentally demonstrate using the Hadoop open source Map-Reduce implementation that the solution to this problem results in benefits up to 30%.
Cross-language linking of news stories on the web using interlingual topic modelling
Authors: Wim De Smet, Marie-Francine Moens
Venue: Proceeding of the 2nd ACM workshop on Social web search and mining (2009)

We have studied the problem of linking event information across different languages without the use of translation systems or dictionaries. The linking is based on interlingua information obtained through probabilistic topic models trained on comparable corpora written in two languages (in our case English and Dutch). The achieve this, we expand the Latent Dirichlet Allocation model to process documents in two languages. We demonstrate the validity of the learned interlingual topics in a document clustering task, where the evaluation is performed on Google News.
Efficient Image Feature Combination with Hierarchical Scheme for Content-Based Image Management System
Authors: Jaekyong Jeong, Hyeongyong Jeon, Chijung Hwang, Byeungwoo Jeon
Venue: Proceedings of the 2009 Third International Conference on Multimedia and Ubiquitous Engineering (2009)

This paper proposes efficient image feature combinations based on local descriptor and hierarchical indexing scheme obtained by clustering with global descriptor for content-based image management system such as image identification and identical image grouping. As features for the image retrieval, we consider both global feature which has general information of overall image for fast image retrieval and local feature which is based on feature points and has high matching accuracy for fine matching of images. The developed local feature is invariant to image scale and rotation, addition of noise, and change in illumination, thus, it sufficiently performs reliable matching between different views of scene across affine transformation. The method works with global feature among image clusters of database in advance and do fine searching only among image data in the cluster with local feature. In order to decrease computation time, we apply conventional clustering methods to group images similar in their characteristics together so that search can be made in a hierarchical manner by fine matching within partial database of candidate images. It can overcome the drawback of exhaustive matching time between similar images by using only local descriptor. 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