ppxscal/embedding_network huggingface dataset:
Feature Selection and Combination Criteria for Improving Predictive Accuracy in Protein Structure Classification
Authors: Chun Yuan Lin, Ken-Li Lin, Chuen-Der Huang, Hsiu-Ming Chang, Chiao Yun Yang, Chin-Teng Lin, Chuan Yi Tang, D. Frank Hsu
Venue: Proceedings of the Fifth IEEE Symposium on Bioinformatics and Bioengineering (2005)

The classification of protein structures is essential for their function determination in bioinformatics. The success of the protein structure classification depends on two factors: the computational methods used and the features selected. In this paper, we use a combinatorial fusion analysis technique to facilitate feature selection and combination for improving predictive accuracy in protein structure classification. When applying these criteria to our previous work, the resulting classification has an overall prediction accuracy rate of 87% for four classes and 69.6% for 27 folding categories. These rates are significantly higher than our previous work and demonstrate that combinatorial fusion is a valuable method for protein structure classification.
Usable presentation of secure pseudonyms
Authors: Katrin Borcea-Pfitzmann, Elke Franz, Andreas Pfitzmann
Venue: Proceedings of the 2005 workshop on Digital identity management (2005)

Privacy-Enhancing Identity Management (PIM) enables us-ers to control which personal information they provide to their communication partner(s) by partitioning their personal information into partial identities for themselves. Since partial identities must not be linkable, they cannot share a global name. Therefore, pseudonyms are used as identifiers.We discuss in this paper that besides the frequency of their use also the (re)presentation of pseudonyms influences the achievable privacy. Particularly, we point out that conflicting requirements on privacy and usability cannot be sufficiently considered by a single type of representation of pseudonyms. Hence, a PIM system should generate digital pseudonyms which are used for communication, while users assign local mnemonics to these pseudonyms in order to simplify their use. We discuss possible solutions for the support of mnemonics and, thereby, propose some improvements to privacy-enhancing identity management tools.
Victor R. Basili's Contributions to Software Quality
Authors: Forrest Shull, Carolyn Seaman, Marvin Zelkowitz
Venue: IEEE Software (2006)

On 16 May 2005, the worldwide software engineering community honored Victor R. Basili of the University of Maryland and Fraunhofer Center for Experimental Software Engineering, Maryland, for his achievements in empirical software engineering. The authors take a look at Basili's contributions, which cover three broad areas: research in the 1970s and early 1980s on software measurement and the Goal Question Metric (GQM) model, research in the 1980s and 1990s on these measurement ideas' maturation into a software engineering model of empirical studies--including the development of the Quality Improvement Paradigm (QIP) and the influence of the NASA Goddard Space Flight Center Software Engineering Laboratoryand research since 1990 in the Experience Factory as a model for creating learning organizations for continuous software process improvement.
On Correlating Structural Tests with Functional Tests for Speed Binning of High Performance Design
Authors: J. Zeng, M. S. Abadir, G. Vandling, L.-C. Wang, S. Karako, J. A. Abraham
Venue: Proceedings of the Fifth International Workshop on Microprocessor Test and Verification (2004)

The use of functional vectors has been an industry standard for speed binning of high-performance ICs. This practice can be prohibitively expensive as ICs become faster and more complex. In comparison, structural patterns target performance related faults in a more systematic manner. To make structural testing an effective alternative for speed binning, this paper investigates the correlation between functional test frequency and the test frequencies of various types of structural patterns on MPC7455, a Motorola microprocessor compatible to PowerPC™ ¹ instruction set architecture
Neural Network Based Framework For Goal Event Detection In Soccer Videos
Authors: Kasun Wickramaratna, Min Chen, Shu-Ching Chen, Mei-Ling Shyu
Venue: Proceedings of the Seventh IEEE International Symposium on Multimedia (2005)

In this paper, a neural network based framework for semantic event detection in soccer videos is proposed. The framework provides a robust solution for soccer goal event detection by combining the strength of multimodal analysis and the ability of neural network ensembles to reduce the generalization error. Due to the rareness of the goal events, the bootstrapped sampling method on the training set is utilized to enhance the recall of goal event detection. Then a group of component networks are trained using all the available training data. The precision of the detection is greatly improved via the following two steps. First, a pre-filtering step is employed on the test set to reduce the noisy and inconsistent data, and then an advanced weighting scheme is proposed to intelligently traverse and combine the component network predictions by taking into consideration the prediction performance of each network. A set of experiments are designed to compare the performance of different bootstrapped sampling schemes, to present the strength of the proposed weighting scheme in event detection, and to demonstrate the effectiveness of our framework for soccer goal event detection.
Introduction to the special issue on the 2005 workshop on design, analysis, and simulation of chip multiprocessors (dasCMP'05)
Authors: Norman P. Jouppi, Rakesh Kumar, Dean Tullsen
Venue: ACM SIGARCH Computer Architecture News (2005)

Chip multiprocessor architectures are becoming increasingly attractive as an option to provide high instruction throughput while keeping power and complexity under control. Such architectures have also been shown to have scalability and productivity advantages. Multi-core processors are fast becoming mainstream.
Toward a logical framework for cognitive effects-based operations: some empirical and computational results
Authors: Selmer Bringsjord
Venue:  (2005)

At present, military modeling and simulation technologies do not possess the representational expressivity needed in order to formally capture the notion of a fully functional organization. Collective, robust, purposive behavior which is typically associated with multiple human actors working in concert has been (largely) outside of the grasp of the military modeling and simulation community. In this thesis, the challenge of modeling organizational behavior will be explored in light of the Effects-based Operations (EBO) paradigm. EBO has manifested itself as a paradigmatic shift towards looking at military planning as fully understanding the causal linkages between taking action and the resultant cascading effects (both intended and unintended) which ripple through the battlespace. While a reasonable amount of research has been directed at understanding the dynamics of physical effects, relatively little attention has been paid to the psychological dimension of effects. The research presented here are the first steps toward a computational framework for a full-spectrum (physical and psychological) analysis of effects called CEBO, standing for Cognitive Effects-Based Operations. CEBO will begin to take shape through the exploration of organizations (multi-agent systems) using the machinery of deontic logic; a family of logical languages used to reason about norms. In order to establish the viability of deontic logic as a mechanism for simulating human-like organizational behavior with respect to norms, I have investigated deontic reasoning from the perspective of cognitive psychology, producing results concerning how humans may mentally represent, reason about, and take appropriate action with respect to norms. As the reasonability of deontic logic as an appropriate formalism for laying the foundations for CEBO is established, I present a computational model of socio-cognitive agency which is consistent with modern conceptions of agent-based normative reasoning, implemented using the Athena denotational proof language (DPL) [67]. Athena performs proof checking, inference; model-checking, and model-building (for counterexample generation) allowing us to reason about normative contingencies and requirements between agents within an organization. Finally, I present an extension to this formal language which allows agents to possess multiple, possibly conflicting sets of obligations, and the machinery by which they may be reasoned over.
An Efficient and Accurate Logarithmic Multiplier Based on Operand Decomposition
Authors: V. Mahalingam, N. Ranganathan
Venue: Proceedings of the 19th International Conference on VLSI Design held jointly with 5th International Conference on Embedded Systems Design (2006)

Logarithmic Number Systems (LNS) offer a viable alternative in terms of area, delay and power to binary number systems for multiplication and division operations in signal processing. The Mitchell Algorithm (MA) proposed in [9], is a simple and low cost approach commonly used for logarithmic multiplication. However, the method involves high error due to piecewise straight line approximation of the logarithm curve. Several methods have been proposed in the literature for improving the accuracy of Mitchell's Algorithm. In this paper, we propose a new method for improving the accuracy of MA using Operand Decomposition (OD). The OD process decreases the number of bits with the value of '1' in the multiplicands and reduces the amount of approximation. The proposed method decreases the error percentage of the Mitchell Algorithm by 44.7% on the average. Since the proposed method does not require any correction term it can be used in combination with other methods for improving the accuracy of the MA based multiplier. Experimental results are presented for random input data, signal and image processing applications, which clearly indicate that the proposed method significantly outperforms previous methods proposed in the literature.
Structured programming in Fortran
Authors: James M. Sakoda
Venue: ACM SIGSOC Bulletin (1974)

The basic spirit of structured programming is to write programs that are easy to read and debug. Students who are taught programming should be encouraged to use structured programming principles. Ingredients of structured programming include: The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Power Allocation and Scheduling for MAC Layer Design in UWB Networks
Authors: Jun Cai, Kuang-Hao Liu, Xuemin (Sherman) Shen, Jon W. Mark, Terence D. Todd
Venue: Proceedings of the Second International Conference on Quality of Service in Heterogeneous Wired/Wireless Networks (2005)

This paper proposes a practical joint power allocation and scheduling scheme for medium access control (MAC) layer design in ultra-wideband (UWB) networks. The scheme increases system spectral efficiency and reduces power consumption by fully considering the properties of the UWB, such as its capacity in supporting parallel transmission and providing accurate positioning, and its stringent constraint on computational complexity. Practical implementations of the proposed scheme is achieved by introducing a margin based power allocation scheme and an exclusive region based scheduling scheme. The margin based power allocation scheme is carried out based on each link's own information, and is simple to implement, while the exclusive region based scheduling scheme takes into account the interaction among different links. Simulation results show that the proposed power allocation and scheduling schemes exhibit good performance in terms of the average number of slots per frame and the power consumption reduction.
Defect Characterization and Tolerance of QCA Sequential Devices and Circuits
Authors: M. Momenzadeh, J. Huang, F. Lombardi
Venue: Proceedings of the 20th IEEE International Symposium on Defect and Fault Tolerance in VLSI Systems (2005)

This paper analyzes the defect tolerance of sequential devices and circuits implemented by molecular Quantum-dot Cellular Automata (QCA). Initially, a novel QCA SR-type flip-flop is proposed; this flip-flop is the first sequential device for QCA and it takes into account the timing issues associated with the adiabatic switching of this technology. Using a defect model by which single additional and missing cells are considered in a molecular implementation, simulation results are provided for a logic-level characterization of the defects. Also for sequential circuits, defect tolerance is pursued and shown to affect the functionality of basic QCA devices, resulting mostly in unwanted inversion and stuck-at faulty behavior at logic level.
Measurements for understanding the behavior of the genetic algorithm in dynamic environments: a case study using the Shaky Ladder Hyperplane-Defined Functions
Authors: William Rand, Rick Riolo
Venue: Proceedings of the 2005 workshops on Genetic and evolutionary computation (2005)

We describe a set of measures to examine the behavior of the Genetic Algorithm (GA) in dynamic environments. We describe how to use both average and best measures to look at performance, satisficability, robustness, and diversity. We use these measures to examine GA behavior with a recently devised dynamic test suite, the Shaky Ladder Hyperplane-Defined Functions (sl-hdf's). This test suite can generate random problems with similar levels of difficulty and provides a platform allowing systematic controlled observations of the GA in dynamic environments. We examine the results of these measures in two different versions of the sl-hdf's, one static and one regularly-changing. We provide explanations for the observations in these two different environments, and give suggestions as to future work.
Conversational Collaborative Recommendation --- An Experimental Analysis
Authors: Rachael Rafter, Barry Smyth
Venue: Artificial Intelligence Review (2005)

Traditionally, collaborative recommender systems have been based on a single-shot model of recommendation where a single set of recommendations is generated based on a user's (past) stored preferences. However, content-based recommender system research has begun to look towards more conversational models of recommendation, where the user is actively engaged in directing search at recommendation time. Such interactions can range from high-level dialogues with the user, possibly in natural language, to more simple interactions where the user is, for example, asked to indicate a preference for one of k suggested items. Importantly, the feedback attained from these interactions can help to differentiate between the user's long-term stored preferences, and her current (short-term) requirements, which may be quite different. We argue that such interactions can also be beneficial to collaborative recommendation and provide experimental evidence to support this claim.
A distributed shared object model based on a hierarchical consistency protocol for heterogeneous clusters
Authors: Xuli Liu, Hong Jiang, Leen-Kiat Soh
Venue: Proceedings of the 2004 IEEE International Symposium on Cluster Computing and the Grid (2004)

The significant performance-to-cost ratio advantage of clusters, combined with recent advances in middleware (programming environment) and networking technologies, has made them the single most popular and fastest growing platform for high performance computing in recent years. While the message passing interface (MPI) still dominates as a means of parallel programming in clusters, it is nevertheless desirable for programmers to program in a single address space, not only across a cluster but also among multiple, likely heterogeneous, clusters so as to significantly extend the computing power of a single cluster. In this paper we propose a distributed shared object (DSO) model based on a distributed hierarchical consistency model (DHCM) protocol for heterogeneous clusters. DHCM, inspired by but significantly improved over the local consistency, is designed to help maintain coherence and consistency in a DSO programming environment and to adapt to different levels of consistency. The notion of adaptive consistency is proposed and partially implemented to improve the efficiency in consistency control, and scalability is addressed as well through the hierarchical structure of the protocol design. We implemented this model purely in Java for portability and heterogeneity. The performance of DHCM is evaluated by executing the LU application chosen from the SPLASH-2 benchmark suite on a 128-node Linux cluster. The experimental results show that the protocol with a hierarchical structure significantly outperforms the protocol with a single-tier in terms of execution time, indicating higher scalability.
Recovery of a Drawing Order from Off-Line Isolated Letters Dedicated to On-Line Recognition
Authors: Laetitia Rousseau, Eric Anquetil, Jean Camillerapp
Venue: Proceedings of the Eighth International Conference on Document Analysis and Recognition (2005)

This paper presents a method to generate an equivalent on-line signal of a letter image. To do this, an off-line drawing order has to be recovered using handwriting knowledge. Our approach consists in looking for several start and the end points. Then a reconstruction algorithm is applied and finally the best path is chosen. This approach has been validated on a database of handwritten letters including both on-line and off-line signals. An on-line recognition system has been used to recognize these letters.
A Context-Aware HTML/XML Document Transmission Process for Mobile Wireless Clients
Authors: Huamin Chen, Prasant Mohapatra
Venue: World Wide Web (2005)

Delivery and rendering of HTML/XML documents has been a core task in many contemporary networking applications. In mobile wireless networks, efficient handling of these types of documents is necessary due to the frequent disconnections, packet loss, and high bit error rate. One approach to address the challenge is the ability to process and reuse the partial data. Current application protocols like HTTP cannot support this approach due to the following constraints: TCP's in-order data uploading to the applications and tag matching. We propose a context-aware transmission process (CATP) to run on top of UDP. This protocol does not transmit HTML/XML files in-order. Instead, it reorganizes the files and transmit tags first before transporting their enclosed data. Conforming browsers receive the file structures and fill in with subsequent data packets in whatever sequence they arrive. As a result, lost and delayed packets do not hinder rendering of those that are logically behind but have already arrived at the client sides. Thus the retransmission of the lost frames can be concealed and overall user perceived performance improved. The user-perceivable performance is quantified in terms of silent time during which no activity is observed at the browser display. The protocol also facilitates partial content caching, amortizing network transmission overhead, and non-interactive applications of Web services. We validated this protocol through prototype implementation and compared the performance with TCP and in-order delivery UDP schemes. Our protocol provides better user-perceivable performance under various loss rates and document sizes.
Redundancy-based feature selection for high-dimensional data and application in bioinformatics
Authors: Huan Liu
Venue:  (2005)

This dissertation studies feature selection: the problem of selecting a subset of features from the original ones in a data set. In many applications such as genomic microarray analysis and text document categorization, data often contains thousands of features. Many of them can be irrelevant or redundant to classification tasks. In order for learning algorithms to perform efficiently and effectively on high-dimensional data, it is imperative to remove irrelevant and redundant features. The data characteristics of high-dimensional data hinder the success of many applications and pose severe challenges for existing feature selection methods focusing on feature relevance analysis. This dissertation describes solutions for efficiently handling redundant features. First, it shows that feature relevance alone is insufficient for efficient and effective feature selection for high-dimensional data. Next, it proposes a systematic framework to perform explicit redundancy analysis in feature selection. Under the framework, it further introduces three feature selection algorithms, Fast Correlation Based Filter (FCBF), Redundancy Based Filter (RBF), and Reporter Surrogate Variable Program (RSVP), handling various types of high-dimensional data. FCBF allows for efficient selection of relevant but non-redundant features. When applied to gene expression microarray data, RBF can efficiently identify a small set of discriminative genes for accurate classification of biological samples. Based on a real-world problem of glioma migration, this dissertation discusses results of RSVP that bridges the gap between statistically significant findings and biologically significant insights.
Effective Capacity Channel Model for Frequency-selective Fading Channels
Authors: Dapeng Wu, Rohit Negi
Venue: Proceedings of the Second International Conference on Quality of Service in Heterogeneous Wired/Wireless Networks (2005)

To efficiently support quality of service (QoS) in future wireless networks, it is important to model a wireless channel in terms of connection-level QoS metrics such as data rate, delay and delay-violation probability. To achieve this, in [7], we proposed and developed a link-layer channel model termed effective capacity (EC) for flat fading channels. In this paper, we apply the effective capacity technique to modeling frequency selective fading channels. Specifically, we utilize the duality between the distribution of a queue with superposition of N i.i.d. sources, and the distribution of a queue with a frequency-selective fading channel that consists of N i.i.d. sub-channels, to model a frequency selective fading channel. In the proposed model, a frequency selective fading channel is modeled by three EC functions; we also propose a simple and efficient algorithm to estimate these EC functions. Simulation results show that the actual QoS metric is closely approximated by the QoS metric predicted by the proposed EC channel model. The accuracy of the prediction using our model can translate into efficiency in admission control and resource reservation.