ppxscal/embedding_network huggingface dataset:
Preservation DataStores: Architecture for Preservation Aware Storage
Authors: Michael Factor, Dalit Naor, Simona Rabinovici-Cohen, Leeat Ramati, Petra Reshef, Julian Satran, David L. Giaretta
Venue: Proceedings of the 24th IEEE Conference on Mass Storage Systems and Technologies (2007)

The volumes of digital information are growing continuously and most of today's information is "born digital". Alongside this trend, business, scientific, artistic and cultural needs require much of this information to be kept for decades, centuries or longer. The convergence of these two trends implies the need for storage systems that support very long term preservation for digital information. We describe Preservation DataStores, a novel storage architecture to support digital preservation. It is a layered architecture that builds upon open standards, along with the OAIS, XAM and OSD standards. This new architecture transforms the logical information-object, a basic concept in preservation systems, into a physical storage object. The transformation allows more robust and optimized implementations for preservation aware storage. The architecture of Preservation DataStores is being developed as an infrastructure component of the CASPAR project* and will be tested in the context of this project using scientific, cultural, and artistic data.
The design of neuro-fuzzy networks using particle swarm optimization and recursive singular value decomposition
Authors: Cheng-Jian Lin, Shang-Jin Hong
Venue: Neurocomputing (2007)

In this paper, a neuro-fuzzy network with novel hybrid learning algorithm is proposed. The novel hybrid learning algorithm is based on the fuzzy entropy clustering (FEC), the modified particle swarm optimization (MPSO), and the recursive singular value decomposition (RSVD). The FEC is used to partition the input data for performing structure learning. Then, we adopt the MPSO to adjust the antecedent parameters of fuzzy rules. Two strategies in the MPSO, called the effective local approximation method (ELAM) and the multi-elites strategy (MES), are proposed to improve the performance of the traditional PSO. Moreover, we will apply RSVD to obtain the optimal consequent parameters of fuzzy rules. The proposed hybrid learning algorithm achieves superior performance in learning speed and learning accuracy than those of some traditional genetic methods.
Feedback Directed Prefetching: Improving the Performance and Bandwidth-Efficiency of Hardware Prefetchers
Authors: Santhosh Srinath, Onur Mutlu, Hyesoon Kim, Yale N. Patt
Venue: Proceedings of the 2007 IEEE 13th International Symposium on High Performance Computer Architecture (2007)

High performance processors employ hardware data prefetching to reduce the negative performance impact of large main memory latencies. While prefetching improves performance substantially on many programs, it can significantly reduce performance on others. Also, prefetching can significantly increase memory bandwidth requirements. This paper proposes a mechanism that incorporates dynamic feedback into the design of the prefetcher to increase the performance improvement provided by prefetching as well as to reduce the negative performance and bandwidth impact of prefetching. Our mechanism estimates prefetcher accuracy, prefetcher timeliness, and prefetcher-caused cache pollution to adjust the aggressiveness of the data prefetcher dynamically. We introduce a new method to track cache pollution caused by the prefetcher at run-time. We also introduce a mechanism that dynamically decides where in the LRU stack to insert the prefetched blocks in the cache based on the cache pollution caused by the prefetcher. Using the proposed dynamic mechanism improves average performance by 6.5% on 17 memory-intensive benchmarks in the SPEC CPU2000 suite compared to the best-performing conventional stream-based data prefetcher configuration, while it consumes 18.7% less memory bandwidth. Compared to a conventional stream-based data prefetcher configuration that consumes similar amount of memory bandwidth, feedback directed prefetching provides 13.6% higher performance. Our results show that feedback-directed prefetching eliminates the large negative performance impact incurred on some benchmarks due to prefetching, and it is applicable to stream-based prefetchers, global-history-buffer based delta correlation prefetchers, and PC-based stride prefetchers.
Learning Bayesian Network Structure from Distributed Homogeneous Data
Authors: Kui Xiang Gou, Gong Xiu Jun, Zheng Zhao
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 03 (2007)

In this paper, we propose an algorithm: Parallel Three-Phase Dependency Analysis (P-TPDA), for learning the structure of Bayesian Network from distributed homogenous datasets: each of which has same variables. The algorithm has two steps: local learning and global learning. In local learning, we first obtain local Bayesian Networks on each dataset independently using Bayesian Network Power Constructor system. Then in global learning, we combine those local structures into the final structure with conditional independency (CI) test. The simulated experimental results for alarm networks indicate: when the number of records in dataset is more than 10000, the final structure obtained with P-TPDA algorithm is consistent with the structure obtained with centralized solution. But the running time in P-TPDA algorithm is shorter than the running time in centralized solution.
Explaining Debugging Strategies to End-User Programmers
Authors: Neeraja Subrahmaniyan, Cory Kissinger, Kyle Rector, Derek Inman, Jared Kaplan, Laura Beckwith, Margaret Burnett
Venue: Proceedings of the IEEE Symposium on Visual Languages and Human-Centric Computing (2007)

There has been little research into how end-user programming environments can provide explanations that could fill a critical information gap for end-user debuggers -- help with debugging strategy. To address this need, we designed and prototyped a video-based approach for explaining debugging strategy, and accompanied it with a text-only approach. We then conducted a qualitative empirical study with end-user debuggers. The results reveal the influences of the explanations on end-user debuggers' decision making, how users reacted to the video versus textual media, and the information gaps the explanations closed. The results also reveal issues of particular importance to explanations of this type.
Security Analysis and Improvement of a (t, n) Threshold Proxy Signature Scheme
Authors: Fanyu Kong, Jia Yu, Baodong Qin, Ming Li, Daxing Li
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 03 (2007)

Recently, H. Jiang proposed a (t, n) threshold proxy signature scheme based on RSA cryptosystem, in which any t or more proxy signers can cooperatively generate a proxy signature while t - 1 or less of them can't do it. In this paper, we propose a security analysis of H. Jiang's threshold proxy signature scheme and show that when e \ge p + q, the original signer can compute the group proxy private key d and then generate any valid proxy signature. Therefore, this scheme doesn't satisfy the security properties of threshold proxy signatures when e \ge p + q. Fortunately, this security weakness can be easily repaired.
Cross-layer design of source rate control and congestion control for wireless video streaming
Authors: Peng Zhu, Wenjun Zeng, Chunwen Li
Venue: Advances in Multimedia (2007)

Cross-layer design has been used in streaming video over the wireless channels to optimize the overall system performance. In this paper, we extend our previous work on joint design of source rate control and congestion control for video streaming over the wired channel, and propose a cross-layer design approach for wireless video streaming. First, we extend the QoS-aware congestion control mechanism (TFRCC) proposed in our previous work to the wireless scenario, and provide a detailed discussion about how to enhance the overall performance in terms of rate smoothness and responsiveness of the transport protocol. Then, we extend our previous joint design work to the wireless scenario, and a thorough performance evaluation is conducted to investigate its performance. Simulation results show that by cross-layer design of source rate control at application layer and congestion control at transport layer, and by taking advantage of the MAC layer information, our approach can avoid the throughput degradation caused by wireless link error, and better support the QoS requirements of the application. Thus, the playback quality is significantly improved, while good performance of the transport protocol is still preserved.
Using Semantic Web Technologies to Analyze Learning Content
Authors: Jelena Jovanovic, Dragan Gasevic, Christopher Brooks, Vladan Devedzic, Marek Hatala, Timmy Eap, Griff Richards
Venue: IEEE Internet Computing (2007)

The authors demonstrate how to use Semantic Web technologies to improve the state-of-the-art in online learning environments and bridge the gap between students on the one hand, and authors or teachers on the other. The ontological framework presented here helps formalize learning object context as a complex interplay of different learning-related elements and shows how we can use semantic annotation to interrelate diverse learning artifacts. On top of this framework, the authors implemented several feedback channels for educators to improve the delivery of future Web-based courses.
On Determining Optimum Simple Golay Marking Transformations for Binary Image Processing
Authors: K. Preston
Venue: IEEE Transactions on Computers (1972)

A computer program has been written which is capable of evaluating all possible Golay marking transformations related to a particular pattern recognition task using an exhaustive search technique. Such evaluations are reported for separating two image data sets: one taken from biomedical microscopy; the other, aerial reconnaissance.
Architectural power models for SRAM and CAM structures based on hybrid analytical/empirical techniques
Authors: Xiaoyao Liang, Kerem Turgay, David Brooks
Venue: Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design (2007)

The need to perform power analysis in the early stages of the design process has become critical as power has become a major design constraint. Embedded and high-performance microprocessors incorporate large on-chip cache and similar SRAM-based or CAM-based structures, and these components can consume a significant fraction of the total chip power. Thus an accurate power modeling method for such structures is important in early architecture design studies. We present a unified architecture-level power modeling methodology for array structures which is highly-accurate, parameterizable, and technology scalable. We demonstrate the applicability of the model to different memory structures (SRAMs and CAMs) and include leakage-variability in advanced technologies. The power modeling approach is validated against HSPICE power simulation results, and we show power estimation accuracy within 5% of detailed circuit simulations.
Improving metabolic flux estimation via evolutionary optimization for convex solution space
Authors: Jiusheng Chen, Haoran Zheng, Haiyan Liu, Junqing Niu, Jianping Liu, Tie Shen, Bin Rui, Yunyu Shi
Venue: Bioinformatics (2007)

Motivation: Flux estimation by using 13 C-labeling pattern information of metabolites is currently the only method that can give accurate, detailed quantification of all intracellular fluxes in the central metabolism of a microorganism. In essence, it corresponds to a constrained optimization problem which minimizes a weighted distance between measured and simulated results. Characteristics, such as existence of multiple local minima, non-linear and non-differentiable make this problem a special difficulty. Results: In the present work, we propose an evolutionary-based global optimization algorithm taking advantage of the convex feature of the problem's solution space. Based on the characteristics of convex spaces, specialized initial population and evolutionary operators are designed to solve 13C-based metabolic flux estimation problem robustly and efficiently. The algorithm was applied to estimate the central metabolic fluxes in Escherichia coli and compared with conventional optimization technique. Experimental results illustrated that our algorithm is capable of achieving fast convergence to good near-optima and maintaining the robust nature of evolutionary algorithms at the same time. Availability: Available from the authors upon request. Contact: hrzheng@ustc.edu.cn Supplementary information: Colour versions of the figure are available online as a part of the Supplementary data.
NucPred—Predicting nuclear localization of proteins
Authors: Markus Brameier, Andrea Krings, Robert M. MacCallum
Venue: Bioinformatics (2007)

Summary: NucPred analyzes patterns in eukaryotic protein sequences and predicts if a protein spends at least some time in the nucleus or no time at all. Subcellular location of proteins represents functional information, which is important for understanding protein interactions, for the diagnosis of human diseases and for drug discovery. NucPred is a novel web tool based on regular expression matching and multiple program classifiers induced by genetic programming. A likelihood score is derived from the programs for each input sequence and each residue position. Different forms of visualization are provided to assist the detection of nuclear localization signals (NLSs). The NucPred server also provides access to additional sources of biological information (real and predicted) for a better validation and interpretation of results. Availability: The web interface to the NucPred tool is provided at http://www.sbc.su.se/~maccallr/nucpred. In addition, the Perl code is made freely available under the GNU Public Licence (GPL) for simple incorporation into other tools and web servers. Contact:brameier@birc.au.dk, r.maccallum@imperial.ac.uk
On the Compression of Markov Prediction Model
Authors: Lei Shi, Yao Yao, Lin Wei
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 01 (2007)

Markov prediction model is the basis of Web prefetching and personalized recommendation. The existence of a large amount of Web objects results in a vast increase in the number of states which represent the users visited transfer behavior, which also causes the problem of huge spatial complexity in prediction model. In view of the transition probability matrix in Markov prediction model, this paper proposes a measurement method based on row similarity and column similarity. First, the similarity matrix is calculated. Then the row similarity and column similarity are used to obtain similar pages simultaneously which can be compressed together. Thus the number of states can be reduced. The experimental results show that the model can not only have good overall performance and compression effect but also keeps relative higher prediction accuracy and recall.
A unified requirements model; integrating features, use cases, requirements, requirements analysis and hazard analysis
Authors: Brian Berenbach, Timo Wolf
Venue: Proceedings of the International Conference on Global Software Engineering (2007)

In global development projects, different modeling techniques are used to create and manage the requirements, analyze the problem domain, identify potential hazards and develop the system design. For each modeling technique, separate tools (e.g. UML case tool, requirements database, Word) are used. Each tool comes with its own meta-model, which hinders the interchange of models across tools and makes automated traceability and quality analysis across all models unmanageable. We propose the integration of different modeling techniques by adding new relationships. The integrated requirements model supports complete traceability across feature modeling, use case modeling, requirements and hazard analysis, detailed requirements and system design. We propose design rules and metrics for a formal and automated quality assurance, project monitoring and control. The model is implemented in a central repository, accessible from distributed sites. Synchronous online collaboration, asynchronous offline access and model-based configuration management is supported for the entire unified requirements model.
Natural-Language Interface for CAD: A First Step
Authors: Tariq Samad, Stephen Director
Venue: IEEE Design Test (1985)

Though the ubiquity of CAD tools in state-of-the-art VLSI design has forced the issue of user interfaces for CAD to prominence,one type of user interface that has not been investigated hitherto is the naturallanquage interface. The CAD domain is substantiallymore complex than the domains for which previous natural-language interfaces have been built. This implies that a natural-languageinterface for CAD cannot be based on previous approaches to language understanding; a new approach is required. Our approachemphasizes flexibility, parallelism, and redundancy, and is embodied in an interface called Cleopatra. Ultimately, Cleopatrawill be an interface for an ?integrated design environment.? As a first step towards that goal, but also as a useful toolin its own right, Cleopatra currently deals with circuit-simulation post-processing.
A Test and Diagnosis Methodology for RF Transceivers
Authors: Hung-kai Chen, Chauchin Su
Venue: Proceedings of the 16th Asian Test Symposium (2007)

This paper proposes an RF test and diagnosis methodology based on digital DFT structure and builtin DSP function of a SoC Chip. Constellation variation plots are proposed to identify the faulty component. Furthermore, linear interpolation is used to determine the amount of variation. The simulated test results show that the method is able to identify not only the faulty component but also the variation amount precise.
New Concepts in Display Technology
Authors: J. Adams
Venue: Computer (1977)

As the number of image processing applications and users increases, so does the need for a low-cost image processing system. This paper describes an approach to the implementation of a solid-state image display which provides the nucleus for such a system. Combining a powerful display processor with modern random access memory refresh technology, the system features a unique "image array processor" in which entire images, instead of single pixels, may be manipulated and displayed arithmetically at video frame rates. Built on a modest budget around an LSI-11 microprocessor (see Figure 1), this system can nevertheless provide complete image processing capabilities, using the display's refresh memories for temporary image storage (in lieu of magnetic disk devices).
Online Handwritten Kanji Recognition Based on Inter-stroke Grammar
Authors: I. Ota, R. Yamamoto, S. Sako, S. Sagayama
Venue: Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 02 (2007)

This paper presents a new approach to online recog- nition of handwritten Kanji characters focusing on their hierarchical structure. Stochastic context-free grammar (SCFG) is introduced to represent the Kanji character gen- erating process in combination with Hidden Markov Mod- els (HMM) representing Kanji substrokes and to improve the recognition accuracy of important and frequently used Kanji characters in which inter-stroke relative positions play important roles. Combining the stroke likelihood and the relative-position likelihood between character-parts in the parsing process is expected to compensate their ambi- guities. By modeling relative positions and share the models across distinct Kanji categories, a small training data can yield effective results and enables us to recognize Kanji sim- ply by defining the SCFG rules to represent their structures without training data. Experimental results on an online handwritten Kanji database from JAIST (Japan Advanced Institute of Science and Technology) showed significant im- provements in the recognition rates of some important Kanji with relatively fewer strokes and also showed little differ- ence between the trained- and the non-trained Kanji in recognition rates.
Heuristic Algorithm for Fixed Job Scheduling Problem
Authors: Jie Xu, Hong Sun, Wei Yang
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 05 (2007)

In view of the characteristics of the fixed job scheduling problem, by establishing the sequential network model among work pieces the fixed job scheduling is converted into the optimal directed path decomposition problem, and the minimal path assignment cost of the sequential network model is the optimization objective. Then a heuristic algorithm based on the simulated annealing is presented, and applied to simulate the airline aircraft dispatching problem. The result indicates that the algorithm can deal with the generally fixed job scheduling problem, whose computation complexity is O (M (m3+mn)).
XBenchMatch: a benchmark for XML schema matching tools
Authors: Fabien Duchateau, Zohra Bellahsène, Ela Hunt
Venue: Proceedings of the 33rd international conference on Very large data bases (2007)

We present XBenchMatch, a benchmark which uses as input the result of a schema matching algorithm (set of mappings and/or an integrated schema) and generates statistics about the quality of this input and the performance of the matching tool.
An Efficient Contributory Group Rekeying Scheme based on Hash Functions for MANETs
Authors: Depeng Li, Srinivas Sampalli
Venue: Proceedings of the 2007 IFIP International Conference on Network and Parallel Computing Workshops (2007)

The increasing popularity of secure group communications has been witnessed in collaborative environments for a long time. Contributory group key schemes are deployed to secure dynamic peer group communications. A number of group applications in resource-limited networks require that the group key scheme should be performance-efficient and failuretolerant. We present a Diffie-Hellman-based contributory group key management scheme which mostly utilizes hash functions. Performance analyses and experimental results show that our approach achieves a new performance minimum, while guaranteeing the same level of security as other approaches.
The Probabilistic Analysis of Distance Estimators in Wireless Sensor Network
Authors: Chuanzhi Zang, Wei Liang, Haibin Yu
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 05 (2007)

It is well known that localization plays an important role in wireless sensor network applications. There are two categories of localization approaches, such as range-based and range-free. RSSI(Received Signal Strength Indicator)-based method is in the first category. Three RSSI-based distance estimators, Biased Estimator (BE), Unbiased Estimator (UE) and Maximal Likelihood Estimator (MLE), are presented to calculate the distance. The biased estimator is the existing method which is used extensively in the literatures, while the unbiased estimator and maximal likelihood estimator are two new estimators developed in this paper. The probabilistic analysis of those estimators is done to compare the performance among them. The probabilistic analysis and simulations show that under some condition we should choose unbiased estimator and under some other condition we should choose MLE.