ppxscal/embedding_network huggingface dataset:
Classification Using EO-1 Hyperion Hyperspectral and ETM Data
Authors: Jinguo Yuan, Zheng Niu
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 03 (2007)

Hyperspectral remote sensing technology demonstrates the capacity for accurate vegetation identification. Hyperion image acquired simultaneously in 356-2577nm narrow spectral bands with 10nm sampling interval allows the capture of vegetation types information. This paper employed Hyperion hyperspectral data and ETM+ data acquired over Xishuangbanna tropical vegetation area in Yunnan province, China to make agriculture land classification. Remote sensing data geometric correction and radiometric correction preprocessing were first made. Atmospheric correction of the Hyperion image was performed using Second Simulation of the Satellite Signal in the Solar Spectrum (6S) radiation transfer model. The first three principle components of Hyperion accounted for 99.3% of total information, which were selected to make unsupervised classification using ISODATA algorithm. Overall classification accuracy of Hyperion using spectral angle mapper (SAM) and unsupervised classification after principle component analysis were 52.3% and 65.7%, respectively.
Theoretical and Empirical Research on Dynamic Optimization Model of Structural Adjustment of International Reserves
Authors: Jie Ma, Fang Shu
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 02 (2007)

Considering the unreasonable currency structure of Chinese foreign reserve, this paper analyzed the optional asset sorts according to currency structure of trade and investment, as well as current status of global international reserves. The author took the hypothesis of interest rate parity to figure the dynamic return of different assets and its expected depreciation, and constructed a quadratic programming constrained model to analyze quantitatively how to adjust foreign reserve structure dynamically. Empirical results show that China needs not only to decrease dollar reserve to increase the reserve of Euro, Yen and Pound, but also to switch part of foreign reserve into gold reserve.
A privacy controller approach for privacy protection in web services
Authors: George O. M. Yee
Venue: Proceedings of the 2007 ACM workshop on Secure web services (2007)

The growth of the Internet has been accompanied by the growth of web services (e.g. e-commerce, e-health). This increased use of web services has meant that more and more user personal information is being shared with web service providers, leading to the need to protect the privacy of web service users, as evidenced by the enactment of privacy legislation in many jurisdictions. Existing privacy policy approaches for privacy protection, such as making the service provider's privacy policy known to the user, or the use of P3P privacy policies, are inadequate. In the former case, the user cannot know for sure whether or not the provider will honor its policy; in the latter case, there is no flexibility for the user to specify her own policy for governing her own personal information - the provider's policy is the only one offered. This paper proposes the use of privacy controllers together with user privacy policies to overcome the limitations in current privacy policy approaches. An example to illustrate the approach is also given.
Clustering and visualization approaches for human cell cycle gene expression data analysis
Authors: F. Napolitano, G. Raiconi, R. Tagliaferri, A. Ciaramella, A. Staiano, G. Miele
Venue: International Journal of Approximate Reasoning (2008)

In this work a comprehensive multi-step machine learning data mining and data visualization framework is introduced. The different steps of the approach are: preprocessing, clustering, and visualization. A preprocessing based on a Robust Principal Component Analysis Neural Network for feature extraction of unevenly sampled data is used. Then a Probabilistic Principal Surfaces approach combined with an agglomerative procedure based on Fisher's and Negentropy information is applied for clustering and labeling purposes. Furthermore, a Multi-Dimensional Scaling approach for a 2-dimensional data visualization of the clustered and labeled data is used. The method, which provides a user-friendly visualization interface in both 2 and 3 dimensions, can work on noisy data with missing points, and represents an automatic procedure to get, with no a priori assumptions, the number of clusters present in the data. Analysis and identification of genes periodically expressed in a human cancer cell line (HeLa) using cDNA microarrays is carried out as test case.
A Symbol Table Abstraction to Implement Languages with Explicit Scope Control
Authors: R. P. Cook
Venue: IEEE Transactions on Software Engineering (1983)

We are concerned with languages in which the programmer has explicit control over the referencing environment of a name. Several modern programming languages, including Ada, Euclid, Mesa, and Modula, implement these control capabilities. This paper describes a simple technique which uses the traditional concepts of a hashed symbol table and lexical level to solve many of the symbol table implemen-tation problems associated with explicit scope control. The primary ad-vantage of this technique is that a single symbol table abstraction can be used to simply and efficiently solve most problems in scope control.
A Novel Fast Mode Decision for the H.264/AVC Based on Local Macroblock Motion Activity
Authors: Huanqiang Zeng, Canhui Cai, Kai-Kuang Ma
Venue: Proceedings of the Fourth International Conference on Image and Graphics (2007)

The intra- and inter-prediction techniques have been effectively exploited in the H.264/AVC for significantly improving the coding efficiency. However, exhaustively searching for the optimal prediction mode vastly increases its computational complexity. To decrease the computational complexity of the mode decision process, a novel fast mode decision algorithm is proposed in this paper to speed up the encoding process by predicting the mode of the current macroblock based on the motion activity of the neighboring macroblocks. The proposed algorithm has two main stages. First, the SKIP mode is utilized as an early termination mechanism to terminate any further checking of other modes. This is quite effective for those regions with low-motion activity. If the SKIP mode is not met, the local macroblocks' motion activities will be identified in terms of motion-vector city-block length. Experimental results have shown that the proposed algorithm achieves a reduction of 56% computational complexity on average, while introducing only 0.059 dB loss in PSNR and 0.2% increment on the total bit rate compared with that of exhaustive trying out all possible modes, being set as the default in the original JM reference software.
Fault diagnosis using algorithmic redundancy
Authors: M. Ghetie, D. Sauter, H. Noura, M. Saif
Venue: Journal of Intelligent Fuzzy Systems: Applications in Engineering and Technology (2000)

This paper introduces the concept of algorithmic redundancy used in fault diagnosis. Its implementation is illustrated with three examples: a statistical limit checking test, a fault detection and isolation method based on balance equations, and a fuzzy alarm generator. These three methods are integrated in a hierarchical diagnostic architecture that is used to validate the concept with simulation results.
A Family of Locking Protocols for Database Systems that Are Modeled by Directed Graphs
Authors: A. Silberschatz
Venue: IEEE Transactions on Software Engineering (1982)

This paper is concerned with the problem of ensuring the integrity of database systems that are accessed concurrently by a number of independent asychronously running transactions. It is assumed that the database system is partitioned into small units that are referred to as the database entities. The relation between the entities is represented by a directed acyclic graph in which the vertices correspond to the database entities and the arcs correspond to certain access rights. We develop a family of non-two-phase locking protocols for such systems that will be shown to ensure serializability and deadlock-freedom. This family is sufficientdy general to encompass all the previously developed non-two-phase lose locking protocols as well as a number of new protocols. One of these new protocols that seems to be particularly useful is also presented in this paper.
A Comparison of the ACMIC3S and the IEEE/CSE Model Curriculum Subcommittee Recommendations
Authors: G. L. Engel
Venue: Computer (1977)

The year 1977 saw the independent development of two significant documents in the field of computer science and engineering education: "Curriculum Recommendations for the Undergraduate Program in Computer Science: A Report of the ACM Committee on Curriculum in Computer Science,"1and A Curriculum in Computer Science and Engineering2prepared by the Model Curricula Subcommittee of the IEEE Computer Society. The work leading to the publication of these reports was independent, though the commmittees did maintain liaison.
A Chaos-Based Predictive Algorithm for Continuous Aggregate Queries over Data Streams
Authors: Yaxin Yu, Guoren Wang, Can Chen, Chong Fu
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 03 (2007)

It is very important to predict the future value or trend of continuous aggregate queries over data streams. But so far, many research works over data streams, especially from database field, have been focusing mainly on the approximate query processing. Although there are a few literatures to discuss the prediction issues of continuous aggregate queries over data streams, none of them allow for the effect that inherent characteristics of stream data itself imposed on prediction. The chaotic property shows some inherent principle, which would influence the stream's future behaviors. Based on this, a novel chaos-based online predictive algorithm for continuous aggregate queries is proposed in this paper. This algorithm borrows local approximation prediction of chaotic time series to forecast the future values of stream data. The extensive experimental results show that the proposed algorithm has higher performance and provides better prediction of aggregate values over data streams.
Parametric design optimization of 2-DOF R-R planar manipulator-A design of experiment approach
Authors: B. K. Rout, R. K. Mittal
Venue: Robotics and Computer-Integrated Manufacturing (2008)

This work illustrates simulation approach for optimizing the parametric design and performance of a 2-DOF R-R planar manipulator. Using dynamic and kinematic models of a manipulator different performance measures for the manipulator are obtained for different combination of parameters with effect of noise incorporated to imitate the real time performance of the manipulator. A novel approach has been proposed to model, the otherwise difficult to model, noise effects. The data generated during simulation for various parameter combinations are utilized to analyze the statistical significance of kinematic and dynamic parameters on performance of manipulator using ANOVA technique. The parameter combinations, which give optimum performance measures obtained for different points in workspace, are compared and reported.
Similarity-Guided Streamline Placement with Error Evaluation
Authors: Yuan Chen
Venue: IEEE Transactions on Visualization and Computer Graphics (2007)

Most streamline generation algorithms either provide a particular density of streamlines across the domain or explicitly detect features, such as critical points, and follow customized rules to emphasize those features. However, the former generally includes many redundant streamlines, and the latter requires Boolean decisions on which points are features (and may thus suffer from robustness problems for real-world data). We take a new approach to adaptive streamline placement for steady vector fields in 2D and 3D. We define a metric for local similarity among streamlines and use this metric to grow streamlines from a dense set of candidate seed points. The metric considers not only Euclidean distance, but also a simple statistical measure of shape and directional similarity. Without explicit feature detection, our method produces streamlines that naturally accentuate regions of geometric interest. In conjunction with this method, we also propose a quantitative error metric for evaluating a streamline representation based on how well it preserves the information from the original vector field. This error metric reconstructs a vector field from points on the streamline representation and computes a difference of the reconstruction from the original vector field.
TextOntoEx: Automatic ontology construction from natural English text
Authors: Mohamed Yehia Dahab, Hesham A. Hassan, Ahmed Rafea
Venue: Expert Systems with Applications: An International Journal (2008)

Most of existing ontologies construction tools support construction of ontological relations (e.g., taxonomy, equivalence, etc.) but they do not support construction of domain relations, non-taxonomic conceptual relationships (e.g., causes, caused by, treat, treated by, has-member, contain, material-of, operated-by, controls, etc.). Domain relations are found mainly in text sources. TextOntoEx constructs ontology from natural domain text using semantic pattern-based approach. TextOntoEx is a chain between linguistic analysis and ontology engineering. TextOntoEx analyses natural domain text to extract candidate relations and then maps them into meaning representation to facilitate constructing ontology. The paper explains this approach in more details and discusses some experiments on deriving ontology from natural text.
On the Use of Lexeme Features for Writer Verification
Authors: A. Bhardwaj, A. Singh, H. Srinivasan, S. Srihari
Venue: Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 02 (2007)

Document examiners use a variety of features to analyze a given handwritten document for writer verification. The challenge in the automatic classification of a pair of doc- uments to belong to the same or different writer, are both (i)The task of proper selection and extraction of features from the handwritten document and (ii)The use of a proper model that is capable of utilizing the true discriminatory power of these features for classification. This paper de- scribes the use of content specific skeleton based features for characters and pairs of characters (bigrams) and as- certains their discriminatory power. A triangulation skele- tonisation procedure is first used to obtain the skeleton of the character(s), and features are computed from the skele- ton. Experiments and results are conducted on content spe- cific features extracted for two most frequently occurring bigrams (th, he), and characters (d and f). A neural net- work based on a Bayesian formulation was used to ascer- tain the discriminability power of these features. To com- bine these features with previously existing writer verifica- tion features, an alternative Naive Bayes model is also de- scribed and evaluated. From the results obtained, we con- clude that bigram th has the highest discriminatory power followed by character d, f and bigram he. Also the paper highlights the significant increase in performance of writer verification( 15% more) with the use of Bayesian neural networks as against the Naive Bayes model.
Identifying Long-range Dependent Network Traffic through Autocorrelation Functions
Authors: Karim Mohammed Rezaul, Vic Grout
Venue: Proceedings of the 32nd IEEE Conference on Local Computer Networks (2007)

For over a decade researchers have been reporting the impact of self-similar long-range dependent network traffic. Long-range dependence (LRD) is of great significance in traffic engineering problems such as measurement, queuing strategy, buffer sizing and admission and congestion control. In this research, in order to determine the existence of LRD, we apply three different robust versions of the autocorrelation function (ACF), namely weighted ACF (WACF), trimmed ACF (TACF) and variance-ratio of differences and sums, known as the D/S variance estimator (DACF), in conjunction with the sample ACF (which is moment based). Here we define the moment based ACF as MACF. In telecommunications, LRD traffic defines that a similar pattern of traffic persists for a longer span of time. Through ACF, it is possible to detect how long the traffic lasts. The aim of this research is to investigate the performance of ACF in identifying the existence of LRD traffic.
Evaluation and Application of MVFs in Coverage for Coverage-Based NHPP SRGM Frameworks
Authors: Takaji Fujiwara, Joong-Yang Park, Jae-Heung Park
Venue: Proceedings of the 5th ACIS International Conference on Software Engineering Research, Management & Applications (2007)

Many non-homogeneous Poisson process software reliability growth models are characterized by their mean value functions. Mean value functions of coverage-based models are usually obtained as composite functions of the coverage growth function and the function relating the number of detected faults to the coverage. This paper performs empirical evaluation of the relationships between the number of detected faults and the coverage embedded in the coverage-based software reliability growth models. It is also illustrated that integration of well-performing coverage growth functions and relationships between the number of detected faults and the coverage procduces well-performing mean value functions.
A Simple Hand/Eye Experimental Set-up for Computer Vision Research
Authors: R. A. Jarvis
Venue: Computer (1977)

A simple, low-cost gantry crane robotic platform for use in computer vision research has been developed recently in the Department of Computer Science at the Australian National University in Canberra. The device operates as a mechanical arm, manipulating elements of scenes being scanned by a video camera. Input from the camera is then subjected to computer analysis.
Implantable stimulator and recording device for artificial prosthesis control
Authors: Jordi Sacristán-Riquelme, M. Teresa Osés
Venue: Microelectronics Journal (2007)

This paper presents an application-specific integrated circuit (ASIC) consisting of both, a four-channel neural stimulator and a single-channel recording amplifier, along with their digital control and regulated voltage supplies. The ASIC has been designed to be compatible with different types of electrodes although the use of sieve electrodes was considered a priority. The main performances of this ASIC as stimulator are: fully programmability for several stimuli shapes (monophasic, biphasic, arbitrary amplitude/duration pairs for stimulation and recovery phases), wide frequency range (7Hz to more than 350Hz with 1Hz resolution) and high-current range (>1.5mA in two scales, with 6 bits resolution). Furthermore, any anode can be associated with any cathode, thus improving the spatial selectivity of some electrode types. From the recording viewpoint, the ASIC exhibits very low noise (5nV/Hz), high CMRR (94dB) and digitally programmable gain and bandwidth. The overall digital control is designed to control up to 16 stimulation channels and four recording amplifiers using a regular and modular implementation for the analog parts which gives rise to higher ASIC performances with a small increase in area. The system has been integrated using high voltage CMOS 0.7@mm technology. ''In vitro'' experimental results are also presented.
Investigating and modeling metadata use to support information architecture development in the statistical knowledge network
Authors: Carol A. Hert, Sheila O. Denn, Daniel W. Gillman, Jung Sun Oh, Maria Cristina Pattuelli, Naybell Hernández
Venue: Journal of the American Society for Information Science and Technology (2007)

Metadata and an appropriate metadata model are non-trivial components of information architecture conceptualization and implementation, particularly when disparate and dispersed systems are integrated. Metadata availability can enhance retrieval processes, improve information organization and navigation, and support management of digital objects. To support these activities efficiently, metadata need to be modeled appropriately for the tasks. The authors' work focuses on how to understand and model metadata requirements to support the work of end users of an integrative statistical knowledge network (SKN). They report on a series of user studies. These studies provide an understanding of metadata elements necessary for a variety of user-oriented tasks, related business rules associated with the use of these elements, and their relationship to other perspectives on metadata model development. This work demonstrates the importance of the user perspective in this type of design activity and provides a set of strategies by which the results of user studies can be systematically utilized to support that design.
Visual analytics: why now?
Authors: James J. Thomas
Venue: Information Visualization (2007)

An emerging field of study, visual analytics, is briefly described, including its motivations and the emerging partnerships that are bringing the best talents and technologies to missions such as homeland security and human health.
The Impact of Microcomputers on Devices to Aid the Handicapped
Authors: J. H. Aylor
Venue: Computer (1981)

Proven prototypes too often do not go into production because of economic factors. The authors are using microcomputers to make devices less expensive, more flexible, and more producible.
TTL Hardware Interface: A High-Level Interface for Streaming Multiprocessor Architectures
Authors: T. Henriksson, P. van der Wolf
Venue: Proceedings of the 2006 IEEE/ACM/IFIP Workshop on Embedded Systems for Real Time Multimedia (2006)

Digital chips for multimedia applications use function-specific hardware co-processors to achieve high performance at low power consumption. These co-processors are typically equipped with traditional address-based interfaces. Networks-on-chips (NoCs) are emerging as scalable interconnect for advanced digital chips. Integration of co-processors with NoCs requires load/store packetizing wrappers on the network interfaces. This leads to unnecessary address generation and address transportation over the NoC for streaming data. By using high-level message passing interfaces for the streaming data, the co-processors can be made simpler and better reusable and the NoCs are used more efficiently. We present the task transaction level (TTL) high-level hardware interface for streaming co-processors as a concrete proposal for such an interface. We present three case study implementations and conclude that a TTL high-level message passing interface is beneficial compared to an address-based interface because it offers a better match with NoCs and it allows for better reuse and simpler design of co-processors