ppxscal/embedding_network huggingface dataset:
Area-efficient Reed-Solomon decoder design for optical communications
Authors: Bo Yuan, Zhongfeng Wang, Li Li, Minglun Gao, Jin Sha, Chuan Zhang
Venue: IEEE Transactions on Circuits and Systems II: Express Briefs (2009)

A high-speed low-complexity Reed-Solomon (RS) decoder architecture based on the recursive degree computationless modified Eudidean (rDCME) algorithm is presented in this brief. The proposed architecture has very low hardware complexity compared with the conventional modified Euclidean and degree computationless modified Euclidean (DCME) architectures, since it can reducethe degree computation circuitry and replace the conventional systolic architecture that uses many processing elements (PEs) with a recursive architecture using a single PE. A high-throughput data rate is also facilitated by employing a pipelining technique. The proposed rDCME architecture has been designed and implemented using SMIC 0.18-µm CMOS technology. Synthesized results show that the proposed RS (255, 239) decoder requires only about 18K gates and can operate at 640 MHz to achieve a throughput of 5.1 Gb/s, which meets the requirement of modern high-speed optical communications.
Coding for shared satellite channel communications
Authors: Philippa A. Martin, Marcel A. Ambroze, Desmond P. Taylor, Martin Tomlinson
Venue: IEEE Transactions on Communications (2009)

This paper investigates the design and performance of a two-user satellite communication system. Each user is independently encoded using a structured Turbo code with identical symbol interleavers. This permits Turbo decoding to be performed using the combined component code trellises, which provides significant gains over independent decoding. The design of the code-matched symbol interleavers is described. Both ideal and imperfect knowledge of the relative phase shift between users is considered. Performance is compared to the single user case and the performance degradation due to a third unknown user is considered. These investigations show that the proposed system performs well in a variety of conditions.
Evaluation of connection types in design for disassembly (DFD) using analytic network process
Authors: Aşkıner Güngör
Venue: Computers and Industrial Engineering (2006)

Design for disassembly (DFD) is an important design concept to make products more friendly for maintenance and remanufacturing practices. One of the important issues in DFD guidelines is related with the selection of the connectors used in the product. This paper evaluates the alternative connection types using the powerful analytic network process (ANP). The paper generates a complete ANP model, which includes all important aspects of connector selection. The model presented evaluates alternative connectors by including the three main concerns: (1) making product disassembly friendly; (2) making product assembly efficient; and (3) increasing the product performance when it is in-use. The results obtained from the model can benefit designers in making better decisions on selecting connectors to be used in the product. Benefits of the approach is detailed through illustrative example.
An experiment with conversation theory as a candidate for a meta learning theory
Authors: Balbir S. Barn, Hilary Dexter
Venue: Proceedings of the 10th IASTED International Conference on Computers and Advanced Technology in Education (2007)

This paper argues that educational theories are complex and it is their structural complexity that prevents understanding and easy application to learning design. In order to support e-learning, software tools to aid the understanding and application process are more likely to be successful if there is a formal model for describing educational theories -- a computer readable conceptual model which can act as a reference model and provide visual representations of their inherent complex nature. This paper suggests that before it is possible to describe a meta model for learning theories it is necessary to have a more detailed understanding of the nature and form of a meta learning theory. The paper reports on an experiment on using Gordon Pask's Cybernetics based Conversation Theory as a candidate meta learning theory. The paper contributes a UML representation of Conversation Theory and presents experimental comparison data with other theories using the model as the basis for comparison.
Parallel simulation of chip-multiprocessor by using multi-threading
Authors: Ya-shuai Lü, Li Shen, Zhi-ying Wang, Kui Dai
Venue: Proceedings of the IASTED Asian Conference on Modelling and Simulation (2007)

Multi-core on one chip becomes the current main trend of micro processors' architecture, and simulation plays an important role in evaluating new processor architectures. Traditional ways of sequential simulation for chip-multiprocessor (CMP) require lots of simulation time which can't be afford during processor design phase. Therefore, exploiting parallelism is necessary for speeding up the multi-core processor simulation. In this paper, we present a parallel CMP simulator, which is implemented by using POSIX threads, and also present the programming methodology for converting a sequential single core simulator to a parallel CMP simulator. Furthermore, the tradeoffs in parallel simulator implementation are also discussed. The experiments are carried out on a four-CPU dual core Xeon server. Under weak consistence order model, the parallel simulator achieves a speedup of 7.2X comparing with the sequential one.
A case study on model driven data integration for data centric software development
Authors: Hyeonsook Kim, Ying Zhang, Samia Oussena, Tony Clark
Venue: Proceeding of the ACM first international workshop on Data-intensive software management and mining (2009)

Model Driven Data Integration is a data integration approach that proactively incorporates and utilizes metadata across the data integration process. By decoupling data and metadata, MDDI drastically reduces complexity of data integration; whilst also providing an integrated standard development method, which is associated with Model Driven Architecture. This paper introduces a case study to adopt MDA technology as an MDDI framework for data centric software development; including data merging and data customization for data mining. A data merging model is also proposed to define relationships between different models at a conceptual level which is then transformed into a physical model. In this case study we collect and integrate historical data from various universities into the Data Warehouse system in order to develop student intervention services through data mining.
New performance results for multiuser optimum combining in the presence of rician fading
Authors: Raymond H. Y. Louie, Matthew R. McKay, Iain B. Collings
Venue: IEEE Transactions on Communications (2009)

This paper analyzes the performance of multiuser optimum combining systems. We consider the practical scenario where the desired user undergoes Rician fading, and the received signals are corrupted by Rayleigh-faded interference and noise. We derive new closed-form expressions for the symbol error rate, ergodic capacity, level crossing rate, and average fade duration. These results are given as either accurate approximations or asymptotic (eg. high signal-to-noise ratio (SNR)) expressions, and are based on new closed-form statistical properties which we derive for the signal-to-interference noise ratio (SINR). Specifically, we derive exact first order expansions and accurate gamma approximations for the SINR distribution, as well as simplified exact expressions for the moments. We also present closed-form expressions for key performance parameters such as the diversity order and array gain, wideband slope, and high SNR power offset, and analyze the impact of the Rician K-factor, which is shown in all cases to yield a performance improvement.
Quasi-maximum-likelihood detector based on geometrical diversification greedy intensification
Authors: Amor Nafkha, Emmanuel Boutillon, Christian Roland
Venue: IEEE Transactions on Communications (2009)

This letter proposes a quasi optimum maximum likelihood detection technique based on Geometrical Diversification and Greedy Intensification (GDGI). The presented detector scheme is shown to achieve almost optimal performance for all signal-to-noise ratio (SNR) values and a cubic computation complexity in the problem dimension. It possesses a regular structure well suited for hardware implementation. Simulation results show that for a system with a high dimension of n = 60, the loss is approximately 0.35 dB at BER=10-5 compared to an optimal decoding.
Optimal decoding and performance analysis of a noisy channel network with network coding
Authors: Ming Xiao, Tor Aulin
Venue: IEEE Transactions on Communications (2009)

We investigate sink decoding approaches and performance analysis for a network with intermediate node encoding (coded network). The network consists of statistically independent noisy channels. The sink bit error probability (BEP) is the performance measure. First, we investigate soft-decision decoding without statistical information on the upstream channels (the channels not directly connected to the sink). Numerical results show that the decoder cannot significantly improve the performance from a hard-decision decoder. We develop union bounds for analysis. The bounds show the asymptotic (regarding SNR: signal-to-noise ratio) performance of the decoder. Using statistical information about the upstream channels, we can find the error patterns of final hop channels (channels directly connected to sinks). With the error patterns, maximum-likelihood (ML) decoding can be performed, and a significant improvement in the BEP is obtained. To evaluate the union bound for the ML decoder, we use an equivalent point procedure. It is reduced to the least-squares problem with a linear constraint in the medium-to-high SNR region. With deterministic knowledge of the errors in the upstream channels, a genie-aided decoder can further improve the performance. We give the union bound for the genie decoder, which is straightforward to evaluate. By analyzing these decoders, we find that knowledge about the upstream channels is essential for good sink decoding.
A game-theoretic framework for interference avoidance
Authors: R. Menon, A. B. MacKenzie, J. Hicks, R. M. Buehrer, J. H. Reed
Venue: IEEE Transactions on Communications (2009)

Various iterative algorithms for interference avoidance (IA) in networks with co-located receivers, suitable for distributed implementation, have been proposed in the literature. In this paper, the IA problem is cast in a game-theoretic framework and is formulated as a potential game. This formulation accommodates previously proposed algorithms and, in addition, gives us a framework that enables the design of new distributed and convergent algorithms for IA including algorithms with nonidentical utility functions for the users. Two new convergence results for potential games are then derived. The first result establishes the convergence of a class of potential games to the global solution while following best response iterations and when noise is added. The second result establishes the convergence of potential games to the Nash equilibria of the game while following random better response iterations. The first result combined with the potential game formulation allows us to show that for a large class of network scenarios, arbitrarily small noise assures the convergence of best response IA algorithms, including the eigen-iterations, to an arbitrarily small neighborhood of the globally optimal signature sequence set. The second result enables the design of reduced feedback mechanisms for IA that converge to desirable solutions.
Proceeding of the first international workshop on Cloud data management
Venue: Conference on Information and Knowledge Management (2009)

It is our great pleasure to welcome you to the 1st International Workshop on Cloud Data Management (CloudDB 2009). Cloud computing is set to revolutionize the IT industry, and database services are at the core of cloud computing, since no information system can be built without database services. Cloud data management holds many promises and challenges. It is our hope that CloudDB will bring together researchers and practitioners from a wide range of areas including services computing, data management, programming language, parallel and distributed systems, mobile computing, scientific and social systems, and brainstorm on the future of database centric cloud computing. CloudDB attracted 11 submissions from Asia, Europe, and North America. The program committee accepted 8 papers, including 5 full papers and 3 short papers. These papers cover a variety of topics, including Cloud-based indexing, query processing and Cloud system application. We hope that they will serve as a valuable start point for much brilliant thinking in cloud data management.
An ontology for breast radiologist training
Authors: Shanghua Sun, Paul Taylor, Louise Wilkinson, Lisanne Khoo
Venue: Proceedings of the 10th IASTED International Conference on Computers and Advanced Technology in Education (2007)

Computer-based tools are increasingly used in radiologists' training and numerous initiatives are attempting to compile large databases of annotated digital images for training purposes. We want to apply computational intelligence to support individualised learning in mammography, based on a set of annotated cases. We require not just a controlled set of radiological descriptors to be used in the annotation but rather an ontology to support reasoning about the educational content of a case. Previous research in biomedical ontologies has modelled normal anatomy, genetic processes and other clinical concepts. There has, however, been relatively little work on imaging or on modelling educational concepts. In this paper, we describe an ontology for breast radiologist training. The ontology is based on a thorough study of 400 cases, selected and annotated by experienced screening radiologists. In addition to the usual reporting information, annotations also include learning points, indicating their educational significance. We give a detailed description of our ontology, and of how the learning points are interpreted and represented. The novel ontology enables computerbased reasoning, allowing a teaching tool to deliver an individualised training programme.
Remote Laboratories Extending Access to Science and Engineering Curricular
Authors: Martyn Cooper, Jose M. M. Ferreira
Venue: IEEE Transactions on Learning Technologies (2009)

This paper draws on research, development, and deployment of remote laboratories undertaken by the authors since 2000. They jointly worked on the PEARL project (http://iet.open.ac.uk/pearl/) from 2000 to 2003 and have worked on further projects within their own institutions (the Open University, United Kingdom, and the University of Porto, Portugal, respectively) since then. The paper begins with a statement of the rationale for remote experiments, then offers a review of past work of the authors and highlights the key lessons for remote labs drawn from this. These lessons include 1) the importance of removing accessibility barriers, 2) the importance of a pedagogic strategy, 3) evaluation of pedagogic effectiveness, 4) the ease of automation or remote control, and 5) learning objectives and design decisions. The paper then discusses key topics including assessment issues, instructional design, pedagogical strategies, relations to industry, and cost benefits. A conclusion summarizes key points from the paper within a review of the current status of remote labs in education.
Doubly generalized LDPC codes over the AWGN channel
Authors: Yige Wang, Marc Fossorier
Venue: IEEE Transactions on Communications (2009)

In this paper, the design of doubly generalized low-density parity-check (DGLDPC) codes is proposed. This approach generalizes the structure of LDPC codes at both check and variable nodes. The performance of DGLDPC codes over the AWGN channel is analyzed using EXIT charts. Combined with differential evolution optimization, this analysis provides thresholds for DGLDPC codes that are better than that of LDPC and GLDPC codes with the same maximum variable degree. These theoretical thresholds are verified via simulations. Furthermore DGLDPC codes exhibit a lower error floor compared with their LDPC and GLDPC counterparts.
A simulated annealing approach to a bi-criteria sequencing problem in a two-stage supply chain
Authors: S. Afshin Mansouri
Venue: Computers and Industrial Engineering (2006)

In this paper, a multi-objective simulated annealing (MOSA) solution approach is proposed to a bi-criteria sequencing problem to coordinate required set-ups between two successive stages of a supply chain in a flow shop pattern. Each production batch has two distinct attributes and a set-up occurs in each stage when the corresponding attribute of the two successive batches are different. There are two objectives including: minimizing total set-ups and minimizing the maximum number of set-ups between the two stages that are both NP-hard problems. The MOSA approach starts with an initial set of locally non-dominated solutions generated by an initializing heuristic. The set is then iteratively updated through the annealing process in search for true Pareto-optimal frontier until a stopping criterion is met. Performance of the proposed MOSA was evaluated using true Pareto-optimal solutions of small problems found via total enumeration. It was also compared against a lower bound in large problems. Comparative experiments show that the MOSA is robust in finding true Pareto-optimal solutions in small problems. It was also shown that MOSA is very well-performing in large problems and that it outperforms an existing multi-objective genetic algorithm (MOGA) in terms of quality of solutions.
Delay-Dependent Robust Stability for Uncertain Neutral System with Discrete and Distributed Delays
Authors: Diankun Wang
Venue: Proceedings of the 2009 International Conference on Multimedia Information Networking and Security - Volume 02 (2009)

A class of new model transformation and a corresponding Lyapunov-Krasovskii function is introduced to solve the stability problem of uncertain neutral system with Discrete and Distributed Delays. By using the theory of linear matrix inequality (LMI) and Jensen integral inequality, new delay-dependent criteria for nominal system and uncertain system are derived. The proposed criteria are less conservative than the other existing ones since they require fewer terms bounds.
Convolutional codes under a minimal trellis complexity measure
Authors: Bartolomeu F. Uchôa-Filho, Richard Demo Souza, Cecilio Pimentel, Marcel Jar
Venue: IEEE Transactions on Communications (2009)

We conduct a code search, restricted to the recently introduced class of generalized punctured convolutional codes, under the minimal trellis complexity measure defined by McEliece and Lin. For the same decoding complexity and the same code rate, new codes are compared to well-known existing classes of convolutional codes. Some of the best convolutional codes (in a distance spectrum sense) of existing and new trellis complexities are tabulated.
Two ant-colony algorithms for minimizing total flowtime in permutation flowshops
Authors: Chandrasekharan Rajendran, Hans Ziegler
Venue: Computers and Industrial Engineering (2005)

The problem of scheduling in flowshops with the objective of minimizing total flowtime is studied. For solving the problem two ant-colony algorithms are proposed and analyzed. The first algorithm refers to some extent to ideas by Stuetzle [Stuetzle, T. (1998). An ant approach for the flow shop problem. In: Proceedings of the sixth European Congress on intelligent techniques and soft computing (EUFIT '98) (Vol. 3) (pp. 1560-1564). Aachen: Verlag Mainz] and Merkle and Middendorf [Merkle, D., & Middendorf, M. (2000). An ant algorithm with a new pheromone evaluation rule for total tardiness problems. In: Proceedings of the EvoWorkshops 2000, lecture notes in computer science 1803 (pp. 287-296). Berlin: Springer]. The second algorithm is newly developed. The proposed ant-colony algorithms have been applied to 90 benchmark problems taken from Taillard [Taillard, E. (1993). Benchmarks for basic scheduling problems. European Journal of Operational Research, 64, 278-285]. A comparison of the solutions yielded by the ant-colony algorithms with the best heuristic solutions known for the benchmark problems up to now, as published in extensive studies by Liu and Reeves [Liu, J., & Reeves, C.R. (2001). Constructive and composite heuristic solutions to the P//@SC"i scheduling problem. European Journal of Operational Research, 132, 439-452, and Rajendran and Ziegler [Rajendran, C., & Ziegler, H. (2004). Ant-colony algorithms for permutation flowshop scheduling to minimize makespan/total flowtime of jobs. European Journal of Operational Research, 155, 426-438], shows that the presented ant-colony algorithms are better, on an average, than the heuristics analyzed by Liu and Reeves and Rajendran and Ziegler.
The parcel hub scheduling problem: A simulation-based solution approach
Authors: Douglas L. McWilliams, Paul M. Stanfield, Christopher D. Geiger
Venue: Computers and Industrial Engineering (2005)

This research presents an interesting scheduling problem common to freight consolidation terminals. This previously unstudied problem involves scheduling a set of inbound trailers to a fixed number of unload docks. The objective is to schedule the trailers to the unload docks to minimize the time span of the transfer operation. This study focuses on freight consolidation terminals in the parcel delivery industry. A simulation-based scheduling algorithm that uses a genetic algorithm to drive the search for new solutions is proposed. In addition to the introduction and discussion of the parcel hub scheduling problem, the contribution of this research is an approach that serves as the initial effort to solve this practical problem.
Research of Welch Arithmetic and Wavelet Transforms for Person Identification of EEG
Authors: Derong Jiang, Jianfeng Hu
Venue: Proceedings of the 2009 Second International Workshop on Computer Science and Engineering - Volume 02 (2009)

OBJECTIVE: To find a method which establish the identity of given person based on the EEG, and the rates of identification were satisfied. METHOD: Several signal processing methods were proposed to use for feature extraction, such as Welch arithmetic, Wavelet transform, and multi layer BP neural network was used for classification of person identification. RESULT: Satisfactory results were obtain with more than 80 percent identification rate for different participators, and identification of specific frequency was done, where with 21-30Hz of participators was highest in contribution. CONCLUSION: EEG which was proposed to used for person identification could be used by persons with Disabilities and the general public, so it have better adaptation.