ppxscal/embedding_network huggingface dataset:
Generalized dynamic frame sizing algorithm for finite-internal-buffered networks
Authors: Ching-Min Lien, Cheng-Shang Chang
Venue: IEEE Communications Letters (2009)

In this paper, we generalize the Dynamic Frame Sizing (DFS) algorithm proposed in [2] for CICQ switches to a network of queues subject to multicast traffic flows. Under the assumption of Bernoulli arrival processes for the multicast flows, we show that the DFS algorithm guarantees 100% throughput and there are at most two packets in each internal queue.
Teseo: A vectoriser of historical seismograms
Authors: Stefano Pintore, Matteo Quintiliani, Diego Franceschi
Venue: Computers Geosciences (2005)

Historical seismograms contain a rich harvest of information useful for the study of past earthquakes. It is necessary to extract this information by digitising the analogue records if modern analysis is required. Teseo has been developed for quick and accurate digitisation of seismogram traces from raster files, introducing a vectorisation step based on piecewise cubic Bezier curves. The vectoriser can handle greyscale images stored in a suitable file format and it offers three concurrent vectorisation methods: manual, automatic by colour selection, and automatic by neural networks. The software that implements the methods described is distributed with open source license.
An Improved Adaptive Boosting Algorithm for Neural Network Ensemble Based on Multi-dimensional Cloud Model
Authors: Zhigang Gan, Nanfeng Xiao
Venue: Proceedings of the 2009 Second International Symposium on Knowledge Acquisition and Modeling - Volume 02 (2009)

AdaBoosting is widely used in neural network ensemble as a variety of boosting algorithm. However, with the learning pattern of focusing on hard sample, AdaBooting makes neural network fall into degradation easily. Additionally, in neural network ensemble the weight of individual neural network only takes into account the misclassifying rate. In fact, due to the characteristic of neural network's tendency of learning hard samples in Adaboosting algorithm, the predictive accuracy of individual neural network's training for a particular sample space is much higher than for the whole sample space. This paper proposes an improved AdaBoosting algorithm called Cloud-AdaBoosting. In this method, it is introduced the concept of cloud model and applied the technique of filling training set with similar samples generated by cloud generator to overcome the degradation phenomena resulted from the tendency of learning hard samples. Through calculating the certainty degree of each test sample relative to neural network, it is adjusted dynamically the weight of whole neural network output by individual neural network which can reflect the prediction ability of a part of samples in neural network ensemble, and then enhance the whole prediction performance of the ensemble. The experiment results show that the proposed algorithm is efficient to increase the prediction accuracy of neural network ensemble.
Mean velocity estimation of mobile stations by spatial correlation of channels in cellular systems
Authors: Woongsup Lee, Dong-Ho Cho
Venue: IEEE Communications Letters (2009)

We propose a velocity estimation scheme for mobile stations (MSs) in cellular communication systems that uses the azimuth spread (AS), delay spread (DS), and shadow fading of MSs. Due to the fact that the AS, DS, and shadow fading are correlated in the spatial domain, the variation of the AS, DS, and shadow fading of an MS is related to its velocity. And, we also consider the variation of velocity which was not considered in previous velocity estimation studies. Through analysis and numerical results, we show that we can estimate the velocity of an MS with lower estimation error compared to previous estimation schemes, despite of measurement error.
Implications of online learning: an analytical study
Authors: Khaled H. Daabaj, Shubat S. Ahmeda
Venue: Proceedings of the 10th IASTED International Conference on Computers and Advanced Technology in Education (2007)

The advancement of technology has led to the conversion of traditional courses into Web courses. This conversion is becoming easier and occurring more systematically in higher education. A growing demand for continuing education is changing the characteristic structure of the tertiary student population, with more students working full time and carrying family responsibilities. In addition, education is increasingly embracing active learning models over the traditional transmission mode of instruction. These factors are making Web-based courses easier to implement, more desirable, and pedagogically relevant. However, as the medium is relatively new, it is not yet precisely known what variables contribute more to students' learning. With the prospect of more Web-based courses being taken by an increasing number of students, it is important to gain a better understanding of how Web-based courses influence students learning [1]. Also, research is needed to obtain more understanding of the learning factors that influence student success in web-based learning. Web-based learning has been suggested to be the future of all types of distance learning [2].
Bursty topics extraction for web forums
Authors: You Chen, Sen Yang, XueQi Cheng
Venue: Proceeding of the eleventh international workshop on Web information and data management (2009)

Many bursty topics which are difficult to summarize and search exist in web forums. Most existing topic detection and tracking (TDT) methods deal with the news stories, but the language used in web forums are much casual, oral and informal compared with news data. In this paper, we present a noise-filtered model to extract bursty topics from web forums using terms and participations of users. Conducting experiments in ShuiMu community we demonstrate the efficiency of our model. Our model not only extracts bursty topics which are better organized for search and visualization, but also discoveries communities corresponding to these topics.
Iterative decoding of serially concatenated CPM in fading channels with noisy channel state information
Authors: Dhammika Bokolamulla, Teng Joon Lim, Tor Aulin
Venue: IEEE Transactions on Communications (2009)

We use the sum-product algorithm (SPA) to propose a reduced-complexity detector for serially concatenated continuous phase modulated (SCCPM) signals with noisy channel state information (CSI) at the receiver. Two channel effects - phase noise (PN) and flat fading - are tackled using the statistical model and associated factor graph (FG) of the problem. Although optimal performance is not assured due to the loopy nature of the FG, as well as simplifying assumptions made in the algorithm development, simulations show that very significant performance gains are possible, and the gap between systems with noiseless and noisy CSI can be reduced to about 1 dB using the proposed methods. The increase in complexity compared to the conventional decoder, which treats CSI estimates as if they were equal to their true values, is small.
Application of an Uncertain Reasoning Approach to Software Aging Detection
Authors: QingE Wu, ZhenYu Han, TianSong Guo
Venue: Proceedings of the 2009 Fifth International Joint Conference on INC, IMS and IDC (2009)

In order to be able to better deal with uncertain information, this paper presents an uncertain reasoning approach, i.e., a reasoning approach of combination of rough set theory and other uncertainty theories. This paper studies mainly the basic algorithm of the reasoning approach, and through example and simulation, shows that the reasoning approach is more effective and feasible than the old reasoning approaches. Moreover, an example to software aging detection is discussed for displaying the application of the reasoning approach. Finally, some prospects for future research are given.
An Heuristic Genetic Algorithm Solve Test Point Selecting with Unreliable Test
Authors: Jia-Liang Pan, Xiao-Hui Ye, Qiang Xue
Venue: Proceedings of the 2009 Second International Workshop on Computer Science and Engineering - Volume 01 (2009)

A mathematical model of the test selection with unreliable test is created and a heuristic function of the test point are established based on the tolerances of the test point detection, coverage and reliance in this paper. In order to overcome the computational explosion, the genetic algorithm with heuristic function is proposed to settle the test selection problem with unreliable test. The algorithm is illustrated and tested using a range of a real-word system. The examples show that this algorithm is significantly better than simple genetic algorithm. It is also feasible and effective, especially in the large-scale system.
Design and performance analysis of a practical load-balanced switch
Authors: Yanming Shen, Shivendra S. Panwar, H. Jonathan Chao
Venue: IEEE Transactions on Communications (2009)

The load-balanced (LB) switch proposed by C.S. Chang et al. [1], [2] consists of two stages. First, a load-balancing stage converts arriving packets into uniform traffic. Then, a forwarding stage transfers packets from the linecards to their final output destination. Load-balanced switches do not need a centralized scheduler and can achieve 100% throughput for a broad class of traffic distributions. However, load-balanced switches may cause packets at the output port to be out of sequence. Several schemes have been proposed to tackle the out-of-sequence problem of the load-balanced switch. They are either too complex to implement, or introduce a large additional delay. In this paper, we present a practical load-balanced switch, called the Byte-Focal switch, which uses packet-by-packet scheduling to significantly improve the delay performance over switches of comparable complexity. We prove that the queues at the input need only finite buffering, and that the overall switch is stable under any traffic matrix. Our analysis shows that the average queuing delay is roughly linear with the switch size N, and although the worst case resequencing delay is N2, the average resequencing delay is much smaller. This means that we can reduce the required resequencing buffer size significantly.
Reliability of grid service systems
Authors: Y. S. Dai, M. Xie, K. L. Poh
Venue: Computers and Industrial Engineering (2006)

Grid computing system is different from conventional distributed computing systems by its focus on large-scale resource sharing, where remote accessing and information communication have great influence on grid computing. As an important metric for services, the grid service reliability is studied in this paper. There are some earlier studies on the reliability analysis of conventional small-scale distributed systems, which ignored the communication time and processing time when studying the reliability, but it is not practical in the reliability analysis of grid services due to the wide-area property of the network. Thus, this paper presents a model for the grid services and develops an approach to analyze the grid service reliability. Detailed algorithms to compute the grid service reliability are presented and a self-sensing technology is proposed for parameterization and monitoring. A numerical example is used for the purpose of illustration. Finally, the new model is compared with different types of conventional models, through which this model is verified more suitable for grid service reliability.
Genetic algorithm aided design of component codes for irregular variable length coding
Authors: R. G. Maunder, L. Hanzo
Venue: IEEE Transactions on Communications (2009)

In this paper we propose a novel Real-Valued Free Distance Metric (RV-FDM) for comparing the error correction capabilities of Variable Length Error Correction (VLEC) codebooks that have the same integer-valued free distance lower bounds. We demonstrate that VLEC codebooks having higher RV-FDMs tend to have EXtrinsic Information Transfer (EXIT) functions with more pronounced 'S'-shapes. Furthermore, we show that higher-accuracy EXIT chart matching can be achieved if the component EXIT functions of an irregular code exhibit more variety. This motivates the employment of our novel genetic algorithm for designing the component VLEC codes of irregular variable length coding, that have particular EXIT functions, in addition to exhibiting desirable bit entropies and decoding complexities.
From order to disorder: the role of computer-based electronics projects on fostering of higher-order cognitive skills
Authors: Moshe Barak
Venue: Computers Education (2005)

This research explored learning and thinking processes enhanced by integrating computers in secondary schools electronics projects. Electronics studies provide a sophisticated learning environment, where computers are simultaneously part of the subject matter learned (Technology Education), and a means for enhancing teaching and learning (Educational Technology), as seen in any other area of education. The follow-up on fifty students working on their final projects showed that students working on computer-based electronics projects tend to adopt flexible strategies, such as creating new ideas, risk-taking, improvisation, using trial and error methods for problem solving, and rapid transition from one design to another. In contrast, students working on non-computerized electronics projects are more likely to progress along a linear path: planning, construction, and troubleshooting. Computerized projects also promote the transfer of knowledge between students, and joint development of ideas. Students who exercise freedom in their project do not express the same independence in their documentation, and prepare portfolios that show how they, supposedly, developed their system in an orderly manner. It is important to educate students, and teachers, that creative design and problem solving requires a balance between openness, flexibility, and intuition, on the one hand, and systematic investigation, discipline, and hard work, on the other hand.
A recursive distributed topology discovery service for grid clients
Authors: Luca Valcarenghi, Francesco Paolucci, Filippo Cugini, Piero Castoldi
Venue: IEEE Communications Letters (2009)

Distributed application (e.g., grid-enabled application) performance can be improved by complementing the computational resource information advertised to the clients with network information (e.g., topology and link capacity). In this way, clients may choose the jointly optimal resources. This study focuses on how to provide clients with network information. The proposed method, namely the Recursive Distributed Topology Discovery Service (RD-TDS), utilizes a selected set of distributed beacons (i.e., measurement points) for network discovery. Each RD-TDS beacon recursively probes nodes that it has not discovered during its previous exploration steps but that have been discovered by other beacons. The exploration ends when each beacon does not have any new node to probe. The RD-TDS evaluation confirms the expected advantage of such method: closely approximating the full topology discovery with a limited number of active beacons. In addition, the proposed method rationale can be easily applied to many current network exploration tools.
An activity-subspace approach for estimating the integrated input function and relative distribution volume in PET parametric imaging
Authors: Peng Qiu, Z. Jane Wang, K. J. Ray Liu, Zsolt Szabo
Venue: IEEE Transactions on Information Technology in Biomedicine (2009)

Dynamic positron emission tomography (PET) imaging technique enables the measurement of neuroreceptor distributions corresponding to anatomic structures, and thus, allows image-wide quantification of physiological and biochemical parameters. Accurate quantification of the concentration of neuroreceptor has been the objective of many research efforts. Compartment modeling is the most widely used approach for receptor binding studies. However, current compartment-model-based methods often either require intrusive collection of accurate arterial blood measurements as the input function, or assume the existence of a reference region. To obviate the need for the input function or a reference region, in this paper, we propose to estimate the input function. We propose a novel concept of activity subspace, and estimate the input function by the analysis of the intersection of the activity subspaces. Then, the input function and the distribution volume (DV) parameter are refined and estimated iteratively. Thus, the underlying parametric image of the total DV is obtained. The proposed method is compared with a blind estimation method, iterative quadratic maximum-likelihood (IQML) via simulation, and the proposed method outperforms IQML. The proposed method is also evaluated in a brain PET dataset.
MAP decoding for multi-antenna systems with non-uniform sources: exact pairwise error probability and applications
Authors: Firouz Behnamfar, Fady Alajaji
Venue: IEEE Transactions on Communications (2009)

We study the maximum a posteriori (MAP) decoding of memoryless non-uniform sources over multiple-antenna channels. Our model is general enough to include space-time coding, BLAST architectures, and single-transmit multireceive antenna systems which employ any type of channel coding. We derive a closed-form expression for the codeword pairwise error probability (PEP) of general multi-antenna codes using moment generating function and Laplace transform arguments. We then consider space-time orthogonal block (STOB) coding and prove that, similar to the maximum likelihood (ML) decoding case, detection of symbols is decoupled in MAP decoding. We also derive the symbol PEP in closed-form for STOB codes. We apply these results in several scenarios. First, we design a binary antipodal signaling scheme which minimizes the system bit error rate (BER) under STOB coding. At a BER of 10-6, this constellation has a channel signal-to-noise ratio (CSNR) gain of 4.7 dB over conventional BPSK signaling for a binary non-uniform source with p0 Δ P(0) = 0.9. We next design space-time linear dispersion (LD) codes which are optimized for the source distribution under the criterion of minimizing the union upper bound on the frame error rate (FER). Two codes are given here: one outperforms V-BLAST by 3.5 dB and Alamouti's code by 12.3 dB at an FER of 10-2 for a binary source with p0 = 0.9, and the other outperforms V-BLAST by 4.2 dB at an FER of 10-3 for a uniform source. These codes also outperform the LD codes of [13] constructed under a different criteria. Finally, the problem of bit-to-signal mapping is studied. It is shown that for a binary source with p0 = 0.9, 64-QAM signaling, and SER = 10-3, a gain of 3.7 dB can be achieved using a better-than-Gray mapping. For a system with one transmit and two receive antennas that uses trellis coding with 16-QAM signaling, a 1.8 dB gain over quasi-Gray mapping and ML decoding is observed when MAP decoding is used for binary sources with p0 = 0.9.
Smart Environment Software Reference Architecture
Authors: A. Fernandez-Montes, J. A. Ortega, J. A. Alvarez, L. Gonzalez-Abril
Venue: Proceedings of the 2009 Fifth International Joint Conference on INC, IMS and IDC (2009)

Nowadays ubiquitous computing is spreading to all scopes of our lives. Smart environments are present at every location such us homes with automation and control devices, offices full of control networks to assist workers, or hotels with even more control devices in order to save energy and satisfy guests preferences.This paper focus on the proposal of a Reference Architecture for developing Smart Applications and deploy them in Smart Environments. The proposal consider three main process in the Software Architecture of these applications:a) perception, b) reasoning and c) acting.
Data Mining for Customer Queries in ERP Model A Case Study
Authors: Abdullah S. Al-Mudimigh, Zahid Ullah, Farrukh Saleem, Fahad N. Al-Aboud
Venue: Proceedings of the 2009 Fifth International Joint Conference on INC, IMS and IDC (2009)

Customers always play a key role for the establishment or mean of crisis for any organization. In this paper, we applied data mining techniques on MADAR data for the perfection and development of the organization as well as making their customers more and more satisfied and contented. In the presented model we specially kept customers on the top and emphasized and highlighted the role of customers for every organization. By using their characteristics and surroundings we clustered the data on the basis of action taken against the raised question. In addition, the clustered data employed on the Apriori algorithm and finally, we discovered new rules and patterns from the database for formulating the process in adequate and satisfactory milieu. For the best implementation we used two data mining techniques; Clustering and Association Mining, to get most valuable, informative and strong results for this organization. This is the way to have the best association and gratify their customer in future.
Epistemological beliefs and their impact on the practice of e-learning in companies
Authors: Christian Harteis, Hans Gruber, Herbert Hertramph
Venue: Proceedings of the 10th IASTED International Conference on Computers and Advanced Technology in Education (2007)

Epistemological beliefs comprise the individual understanding of the nature of knowledge and the creation of knowledge. Hence, they impact the perception of learning opportunities and professional learning activities. Many enterprises apply new media in order to support staff development through e-learning activities. However, a closer look at the practices of e-learning reveals that only rarely the potential of new media for professional learning is fully utilized. Frequently it is neglected that employees' subjectivity - in particular their epistemological beliefs - determines their ways of using new media for self-directed learning activities. This contribution reports and discusses empirical findings which indicate that employees' epistemological beliefs impact not the amount but probably the quality of learning with new media. The conclusions offer new impulses for the study of knowledge management.
Explorative learning and scientific writing: how to teach students control their own learning process
Authors: Alexander W. Hunziker, Rolf Hugi
Venue: Proceedings of the 10th IASTED International Conference on Computers and Advanced Technology in Education (2007)

A major problem in teaching business administration students is that they learn concepts and principles but do not sufficiently think and act themselves. They are socialized to repeat thoughts of others rather than to methodically develop new, original answers. This paper outlines an e-learning design that allows students to learn at the same time (1) basic knowledge about how to write a scientific paper and (2) how to structure an explorative learning process and (3) how to collaborate in a virtual environment. The project has been realized in the bachelor program's first semester. It's e-learning design is based on seven steps: Question, mental model one, research, mental model two, conclusion. And then: Presentation of own paper and critical discussion of peer paper. Face to face meetings are used as well as asynchronous interaction, both within groups and between groups as well as with teachers (coaches). Online elements provide necessary and optional information for students supporting them in completing their task. The quality of the self-controlled, explorative learning process is ensured by quality standards for each step. The standards include methodological and formal aspects only. The qualitative evaluation indicates that the project is very effective.