ppxscal/embedding_network huggingface dataset:
A Data Fusion Approach in Protein Homology Detection
Authors: Aydin Can Polatkan, Hasan Ogul, Hayri Sever
Venue: Proceedings of the 2008 International Conference on Biocomputation, Bioinformatics, and Biomedical Technologies (2008)

The discriminative framework for protein remote homology detection based on support vector machines (SVMs) is reconstructed by the fusion of sequence based features. In this respect, n-peptide compositions are partitioned and fed into separate SVMs. The SVM outputs are evaluated with different techniques and tested to discern their ability for SCOP protein super family classification on a common benchmarking set. It reveals that the fusion approach leads to an improvement in prediction accuracy with a remarkable gain on computer memory usage.
The relative generalized Hamming weight of linear q-ary codes and their subcodes
Authors: Zihui Liu, Wende Chen, Yuan Luo
Venue: Designs, Codes and Cryptography (2008)

In this article, some properties of the relative generalized Hamming weight (RGHW) of linear codes and their subcodes are developed with techniques in finite projective geometry. The relative generalized Hamming weights of almost all 4-dimensional q-ary linear codes and their subcodes are determined.
Research on the DDS' CPLD Control to Generate Special Band Signal
Authors: Shi Yu Yan, Ji Zhou Li
Venue: Proceedings of the 2008 International Conference on BioMedical Engineering and Informatics - Volume 02 (2008)

Direct Digital Frequency Synthesis(DDS) in often used in RF(Radio Frequency) systems, such as MRI(Magnetic Resource Imaging). This paper describes a DDS chip AD9854’s structure and its essential program by a CPLD chip XC95288XL. It gives us material internal structure and how to program AD9854, and how to generate a radio frequency by AD9854 with CPLD’s control. The program code is written in VHDL, and all codes are simmulated through ModelSim SE 5.6d. At last, the paper gives conclusion that using CPLD control DDS chip to generate radio frequency is absolutely feasible.
An efficient kernel matrix evaluation measure
Authors: Canh Hao Nguyen, Tu Bao Ho
Venue: Pattern Recognition (2008)

We study the problem of evaluating the goodness of a kernel matrix for a classification task. As kernel matrix evaluation is usually used in other expensive procedures like feature and model selections, the goodness measure must be calculated efficiently. Most previous approaches are not efficient except for kernel target alignment (KTA) that can be calculated in O(n^2) time complexity. Although KTA is widely used, we show that it has some serious drawbacks. We propose an efficient surrogate measure to evaluate the goodness of a kernel matrix based on the data distributions of classes in the feature space. The measure not only overcomes the limitations of KTA but also possesses other properties like invariance, efficiency and an error bound guarantee. Comparative experiments show that the measure is a good indication of the goodness of a kernel matrix.
Structured Decomposition of Adaptive Applications
Authors: Justin Mazzola Paluska, Hubert Pham, Umar Saif, Grace Chau, Chris Terman, Steve Ward
Venue: Proceedings of the 2008 Sixth Annual IEEE International Conference on Pervasive Computing and Communications (2008)

We describe an approach to automate certain high-levelimplementation decisions in a pervasive application, allowingthem to be postponed until run time. Our system enables a modelin which an application programmer can specify the behavior of anadaptive application as a set of open-ended decision points. Weformalize decision points as Goals, each of which may besatisfied by a set of scripts called Techniques. The set ofTechniques vying to satisfy any Goal is additive and may beextended at runtime without needing to modify or remove anyexisting Techniques. Our system provides a framework in whichTechniques may compete and interoperate at runtime in order tomaintain an adaptive application. Technique development may bedistributed and incremental, providing a path for thedecentralized evolution of applications. Benchmarks show thatour system imposes reasonable overhead during application startupand adaptation.
A case study on STEP-enabled generic product modelling framework
Authors: Z. D. Zhou, S. Q. Xie, W. Z. Yang
Venue: International Journal of Computer Integrated Manufacturing (2008)

This research proposes a STEP-enabled generic product modelling framework (GPMF) for efficient information exchange and sharing in support of rapid product development in a modern manufacturing environment. This framework consists of four functional components: an EXPRESS data model, namely EDM; a STEP-based modelling environment; a 'five-phase' modelling method; and three EDM data exchange and sharing methods. The focus of this research is placed on the modelling methodologies and the definition of schemas for various product development activities such as manufacturing, inspection, etc., and the integration of the schemas with other resources defined within STEP. There are 25 schemas defined to enable that the proposed GPMF is compatible and can be used in modelling various types of products. These aspects, to our best knowledge, are not studied extensively in the literature. The structure of framework will be discussed in the paper with the focus placed on the EDM as the core of the framework. Case studies are carried out to validate the proposed GPMF. Two products are chosen from different engineering disciplines. They are modelled into product models according to the GPMF. Each case utilizes one of the EDM data exchange and sharing methods and its corresponding software environment to obtain the product models that are presented as STEP Part 21 exchange files, STEP objects and a database object. A prototype system called product data management system (PDMS) is developed to test the GPMF. The case studies show that the product models built based on the GPMF are capable of integrating information in product design, manufacturing and assembly, and the GPMF is compatible, comprehensive and flexible.
A comprehensive empirical evaluation of missing value imputation in noisy software measurement data
Authors: Jason Van Hulse, Taghi M. Khoshgoftaar
Venue: Journal of Systems and Software (2008)

The handling of missing values is a topic of growing interest in the software quality modeling domain. Data values may be absent from a dataset for numerous reasons, for example, the inability to measure certain attributes. As software engineering datasets are sometimes small in size, discarding observations (or program modules) with incomplete data is usually not desirable. Deleting data from a dataset can result in a significant loss of potentially valuable information. This is especially true when the missing data is located in an attribute that measures the quality of the program module, such as the number of faults observed in the program module during testing and after release. We present a comprehensive experimental analysis of five commonly used imputation techniques. This work also considers three different mechanisms governing the distribution of missing values in a dataset, and examines the impact of noise on the imputation process. To our knowledge, this is the first study to thoroughly evaluate the relationship between data quality and imputation. Further, our work is unique in that it employs a software engineering expert to oversee the evaluation of all of the procedures and to ensure that the results are not inadvertently influenced by poor quality data. Based on a comprehensive set of carefully controlled experiments, we conclude that Bayesian multiple imputation and regression imputation are the most effective techniques, while mean imputation performs extremely poorly. Although a preliminary evaluation has been conducted using Bayesian multiple imputation in the empirical software engineering domain, this is the first work to provide a thorough and detailed analysis of this technique. Our studies also demonstrate conclusively that the presence of noisy data has a dramatic impact on the effectiveness of imputation techniques.
A synchronization-based multi-task communication mechanism for wireless sensor networks
Authors: Youssef Charfi, Naoki Wakamiya, Masayuki Murata
Venue: ACM SIGMOBILE Mobile Computing and Communications Review (2008)

A lot of work has been done to design wireless sensor networks (WSNs) that are distributed, self-organized, and energy-efficient. Most of these WSNs are designed to carry out a single task such as data gathering or diffusion and are not flexible enough to perform multiple tasks while keeping their self-organized behavior. In this paper, we show how a fully dis-tributed and self-organized data gathering mechanism that rely on pulse-coupled oscillator models to achieve synchronization can be extended to offer periodic two-way communica-tion between the base station and the sensor nodes. We also demonstrate the ability of the proposed mechanism to perform multiple functions such as data gathering and retasking without any disturbance in the synchronization of the WSN.
An accelerated Newton method for equations with semismooth Jacobians and nonlinear complementarity problems
Authors: Christina Oberlin, Stephen J. Wright
Venue: Mathematical Programming: Series A and B (2008)

We discuss local convergence of Newton&#x2019;s method to a singular solution x * of the nonlinear equations F(x) =&#x00a0; 0, for $$F:{\mathbb{R}}^n \rightarrow {\mathbb{R}}^n$$. It is shown that an existing proof of Griewank, concerning linear convergence to a singular solution x * from a starlike domain around x * for F twice Lipschitz continuously differentiable and x * satisfying a particular regularity condition, can be adapted to the case in which F&#x2032; is only strongly semismooth at the solution. Further, Newton&#x2019;s method can be accelerated to produce fast linear convergence to a singular solution by overrelaxing every second Newton step. These results are applied to a nonlinear-equations reformulation of the nonlinear complementarity problem (NCP) whose derivative is strongly semismooth when the function f arising in the NCP is sufficiently smooth. Conditions on f are derived that ensure that the appropriate regularity conditions are satisfied for the nonlinear-equations reformulation of the NCP at x *.
Optimally fast parallel algorithms for preprocessing and pattern matching in one and two dimensions
Authors: R. Cole
Venue: Proceedings of the 1993 IEEE 34th Annual Foundations of Computer Science (1993)

All algorithms below are optimal alphabet-independent parallel CRCW PRAM algorithms. In one dimension: Given a pattern string of length m for the string-matching problem, we design an algorithm that computes a deterministic sample of a sufficiently long substring in constant time. This problem used to be a bottleneck in the pattern preprocessing for one- and two-dimensional pattern matching. The best previous time bound was O(log/sup 2/ m/log log m). We use this algorithm to obtain the following results. 1. Improving the preprocessing of the constant-time text search algorithm from O(log/sup 2/ m/log log m) to n(log log m), which is now best possible. 2. A constant-time deterministic string-matching algorithm in the case that the text length n satisfies n=/spl Omega/(m/sup 1+/spl epsiv//) for a constant /spl epsiv/>0. 3. A simple probabilistic string-matching algorithm that has constant time with high probability for random input. 4. A constant expected time Las-Vegas algorithm for computing the period of the pattern and all witnesses and thus string matching itself, solving the main open problem remaining in string matching.
Towards A Model-Based Autonomic Reliability Framework for Computing Clusters
Authors: Abhishek Dubey, Steve Nordstrom, Turker Keskinpala, Sandeep Neema, Ted Bapty, Gabor Karsai
Venue: Proceedings of the Fifth IEEE Workshop on Engineering of Autonomic and Autonomous Systems (2008)

One of the primary problems with computing clusters is to ensure that they maintain a reliable working state most of the time to justify economics of operation. In this paper, we introduce a model-based hierarchical reliability framework that enables periodic monitoring of vital health parameters across the cluster and provides for autonomic fault mitigation. We also discuss some of the challenges faced by autonomic reliability frameworks in cluster environments such as non-determinism in task scheduling in standard operating systems such as Linux and need for synchronized execution of monitoring sensors across the cluster. Additionally, we present a solution to these problems in the context of our framework, which utilizes a feedback controller based approach to compensate for the scheduling jitter in non real-time operating systems. Finally, we present experimental data that illustrates the effectiveness of our approach.
Spanning 3-colourable subgraphs of small bandwidth in dense graphs
Authors: Julia Böttcher, Mathias Schacht, Anusch Taraz
Venue: Journal of Combinatorial Theory Series B (2008)

A conjecture by Bollobas and Komlos states the following: For every@c>0and integersr>=2and @D, there exists@b>0with the following property. If G is a sufficiently large graph with n vertices and minimum degree at least(r-1r+@c)nand H is an r-chromatic graph with n vertices, bandwidth at most @bn and maximum degree at most @D, then G contains a copy of H. This conjecture generalises several results concerning sufficient degree conditions for the containment of spanning subgraphs. We prove the conjecture for the case r=3.
A framework for providing adaptive sports video to mobile devices
Authors: Cunxun Zang, Qingshan Liu, Xiaofeng Tong, Hanqing Lu
Venue: Proceedings of the 2nd international conference on Mobile multimedia communications (2006)

In this paper, we present a novel framework that serves adaptive sports video to mobile users. Our framework combines content-based sports highlights extraction and quality-domain video compression technologies in video server, capable of reducing wireless bandwidth consumption more effectively. We develop a robust replay-based highlights extraction method, and propose a content-based video streaming coding scheme to handle the problems of bandwidth and capacity of computation. To validate the practicality and effectiveness of our system, we conduct the experiments on several real soccer videos. The experimental results demonstrate the robustness of our highlights extraction method and more than 77.5% of the bandwidth consumption could be reduced.
The recovery of a schema mapping: bringing exchanged data back
Authors: Marcelo Arenas, Jorge Pérez, Cristian Riveros
Venue: Proceedings of the twenty-seventh ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems (2008)

A schema mapping is a specification that describes how data from a source schema is to be mapped to a target schema. Once the data has been transferred from the source to the target, a natural question is whether one can undo the process and recover the initial data, or at least part of it. In fact, it would be desirable to find a reverse schema mapping from target to source that specifies how to bring the exchanged data back. In this paper, we introduce the notion of a recovery of a schema mapping: it is a reverse mapping M' for a mapping M that recovers sound data with respect to M. We further introduce an order relation on recoveries. This allows us to choose mappings that recover the maximum amount of sound information. We call such mappings maximum recoveries. We study maximum recoveries in detail, providing a necessary and sufficient condition for their existence. In particular, we prove that maximum recoveries exist for the class of mappings specified by FO-to-CQ source-to-target dependencies. This class subsumes the class of source-to-target tuple-generating dependencies used in previous work on data exchange. For the class of mappings specified by FO-to-CQ dependencies, we provide an exponential-time algorithm for computing maximum recoveries, and a simplified version for full dependencies that works in quadratic time. We also characterize the language needed to express maximum recoveries, and we include a detailed comparison with the notion of inverse (and quasi-inverse) mapping previously proposed in the data exchange literature. In particular, we show that maximum recoveries strictly generalize inverses. We study the complexity of some decision problems related to the notions of recovery and maximum recovery. Finally, we report our initial results about a relaxed notion of maximal recovery, showing that it strictly generalizes the notion of maximum recovery.
Motion planning on a graph
Authors: C. H. Papadimitriou
Venue: Proceedings of the 35th Annual Symposium on Foundations of Computer Science (1994)

We are given a connected, undirected graph G on n vertices. There is a mobile robot on one of the vertices; this vertex is labeled s. Each of several other vertices contains a single movable obstacle. The robot and the obstacles may only reside at vertices, although they may be moved across edges. A vertex may never contain more than one object (robot/obstacle). In one step, we may move either the robot or one of the obstacles from its current position /spl upsi/ to a vacant vertex adjacent to v. Our goal is to move the robot to a designated vertex t using the smallest number of steps possible. The problem is a simple abstraction of a robot motion planning problem, with the geometry replaced by the adjacencies in the graph. We point out its connections to robot motion planning. We study its complexity, giving exact and approximate algorithms for several cases.
Privacy Preserving Shortest Path Computation in Presence of Convex Polygonal Obstacles
Authors: Ananda Swarup Das, Jitu Kumar Keshri, Kannan Srinathan, Vaibhav Srivastava
Venue: Proceedings of the 2008 Third International Conference on Availability, Reliability and Security (2008)

Shortest path computation in presence of obstacles has been a subject of study since long and so has been the study of privacy preserving algorithms. In this paper we design efficient privacy preserving algorithms for computing the shortest path circumventing convex polygonal obstacles. Specifically, we assume that a party A has source sand destination d while another party B has the list of convex polygonal obstacles and A wishes to find the shortest path from s to d without compromising each others’ privacy. That is, at the end of the protocol, A must not know anything else about the obstacles other that what may be revealed by the shortest path that is output and B must not know anything about A’s source/destination.
A classification scheme for the prediction of essential chemical and biological properties based on the classical neural network approach
Authors: Markus Borschbach
Venue: Proceedings of the 5th WSEAS/IASME International Conference on Systems Theory and Scientific Computation (2005)

Prediction of biological and chemical features of a given chemical structure is a challenging problem for the existing nonlinear mapping performed by neural networks. In combinatorial chemistry, computational approaches are capable to significantly decrease the necessary amounts of synthesis for the development of a specific chemical or biological drug. Therefore, the main goal is to distinguish appropriate descriptors from insignificant ones. The experimental design for the classical nonlinear neural network mapping for the approximation of five descriptors and the corresponding reaction of the immune system for the drug development are reported briefly. The results for the different descriptors are presented in comparison.
Architecture of Qbox: a scalable first-principles molecular dynamics code
Authors: F. Gygi
Venue: IBM Journal of Research and Development (2008)

We describe the architecture of Qbox, a parallel, scalable first-principles molecular dynamics (FPMD) code. Qbox is a C++/ Message Passing Interface implementation of FPMD based on the plane-wave, pseudopotential method for electronic structure calculations. It is built upon well-optimized parallel numerical libraries, such as Basic Linear Algebra Communication Subprograms (BLACS) and Scalable Linear Algebra Package (ScaLAPACK), and also features an Extensible Markup Language (XML) interface built on the Apache Xerces-C library. We describe various choices made in the design of Qbox that led to excellent scalability on large parallel computers. In particular, we discuss the case of the IBM Blue Gene/L™ platform on which Qbox was run using up to 65,536 nodes. Future design challenges for upcoming petascale computers are also discussed. Examples of applications of Qbox to a variety of first-principles simulations of solid, liquids, and nanostructures are briefly described.
Extending PKI Interoperability in Computational Grids
Authors: Massimiliano Pala, Shreyas Cholia, Scott A. Rea, Sean W. Smith
Venue: Proceedings of the 2008 Eighth IEEE International Symposium on Cluster Computing and the Grid (2008)

One of the most successful working examples of virtualor ganizations, computational grids need authentication mechanisms that inter-operate across domain boundaries. Public Key Infrastructures (PKIs) provide sufficient flexibility to allow resource managers to securely grant access to their systems in such distributed environments. However, as PKIs grow and services are added to enhance both security and usability, users and applications must struggle to discover available resources—particularly when the Certification Authority (CA) is alien to the relying party. This paper presents how to overcome these limitations of the current grid authentication model by integrating the PKI Resource Query Protocol (PRQP) into the Grid Security Infrastructure (GSI).
A low damage Si3N4 sidewall spacer process for self-aligned sub-100nm III-V MOSFETs
Authors: X. Li, R. J. W. Hill, H. Zhou, C. D. W. Wilkinson, I. G. Thayne
Venue: Microelectronic Engineering (2008)

This paper investigates a low damage reactive ion etch (RIE) process to make thin silicon nitride sidewall spacers for the fabrication of self-aligned sub-100nm gate length III-V metal-oxide-semiconductor field-effect-transistors (MOSFETs). Self-alignment is essential to minimize the contribution to the parasitic series source/drain resistance (RSD) from the access region between the ohmic contact and the gate, whilst retaining the overall electrostatic integrity of the device. In this work, a blanket Si"3N"4 was deposited by room temperature inductively coupled plasma chemical vapour deposition (ICP-CVD) and etched by reactive ion etching in a SF"6/N"2 based chemistry. Conditions were optimised to ensure low damage to the underlying device layer stack. This process has successfully produced thin Si"3N"4 spacers for fabricating self-aligned GaAs MOSFETs. The sheet resistance of III-V MOSFET materials was monitored as a function of etch parameters to assess the impact of damage related effects on the electronic characteristics of the underlying material. The etching profile and the sheet resistance of the device layer structures were characterised by using scanning electronic microscope (SEM) and sonogage, respectively.