ppxscal/embedding_network huggingface dataset:
Pareto-based Multi-Objective Machine Learning
Authors: Yaochu Jin
Venue: Proceedings of the 7th International Conference on Hybrid Intelligent Systems (2007)

Machine learning is inherently a multi-objective task. Traditionally, however, either only one of the objectives is adopted as the cost function or multiple objectives are aggregated to a scalar cost function. This can mainly attributed to the fact that most conventional learning algorithms can only deal with a scalar cost function. Over the last decade, efforts on solving machine learning problems using the Pareto-based multi-objective optimization methodology have gained increasing impetus, particularly thanks to the great success of multi-objective optimization using evolutionary algorithms and other population-based stochastic search methods. It has been shown that Pareto-based multi-objective learning approaches are more powerful compared to learning algorithms with a scalar cost functions in addressing various topics of machine learning, such as clustering, feature selection, improvement of generalization ability, knowledge extraction, and ensemble generation. This talk provides first a brief overview of Pareto-based multi-objective machine learning techniques. In addition, a number of case studies are provided to illustrate the major benefits of the Pareto-based approach to machine learning, e.g., how to identify interpretable models and models that can generalize on unseen data from the obtained Pareto-optimal solutions. Three approaches to Pareto-based multi-objective ensemble generation are compared and discussed in detail. Most recent results on multi-objective optimization of spiking neural networks will be presented.
Optimized Assignment Coverage Computation in Formal Verification of Digital Systems
Authors: Majid Nabi, Hamid Shojaei, Siamak Mohammadi
Venue: Proceedings of the 16th Asian Test Symposium (2007)

Model checking thoroughly verifies the design correctness with respect to a specification. When the verification process succeeds, we can only postulate the correctness of the design relative to the given specification. How far can we affirm the verified design implements all the behavior of the desired system? With this regard we need to estimate the completeness of the properties by using some coverage metrics. In this paper, we have proposed a new metric called assignment coverage and an optimized method to overcome the intensive computations required for the multiple transformations among the abstract layers in the verification tool. The proposed coverage computation method provides adequate information to complete the set of properties. Finally, we have applied the proposed metric to some verification benchmark to reveal the effectiveness of this metric in finding undetected coverage holes.
Using VPN technology to remove physical barriers in linux lab experiments
Authors: Lee W. Toderick, Philip J. Lunsford II
Venue: Proceedings of the 8th ACM SIGITE conference on Information technology education (2007)

The ability for students to perform computer laboratory experiments has traditionally been limited to a physical environment. Because of this restriction, lab experiments could be performed only during formal lab hours or open lab time. There are a number of negative consequences resulting from physical barriers, including administrative issues involving lab equipment and room support costs, and site access on weekends and after-hours. Student limitations involve inflexible lab room schedules, sometimes insufficient equipment, and possible late-night safety concerns. Recently we adopted an open source VPN solution that uses Openswan and the IPSec sub-system. This open source technology allows student computers to connect to the private lab LAN and perform experiments from home or the dorm, at any time of the day, night, or weekend. Based on student feedback and improved technologies, the solution was enhanced, expanded, and made more flexible. A locally developed and copyrighted software application, code name BroadReach, simplifies student VPN configuration and management of the VPN Gateway to the secure LAN and is discussed in this paper. Issues related to IPSec are identified and both industry and local solutions are presented. Finally, the future migration of a DE classroom into a single computer using Virtualization techniques is outlined.
Retrenchment and the Atomicity Pattern
Authors: Richard Banach, Czeslaw Jeske, Anthony Hall, Susan Stepney
Venue: Proceedings of the Fifth IEEE International Conference on Software Engineering and Formal Methods (2007)

The issues surrounding the question of atomicity, both in the past and nowadays, are briefly reviewed, and a picture of an ACID (atomic, consistent, isolated, durable) transaction as a refinement problem is presented. An example of a simple air traffic control system is introduced, and the discrepancies that can arise when read-only operations examine the state at atomic and finegrained levels are handled by retrenchment. Non-ACID timing aspects of the ATC example are also handled by retrenchment, and the treatment is generalised as the retrenchment Atomicity Pattern. The utility of the pattern is confirmed against a different case study, the Mondex Electronic Purse.
Evolutionary Optimization ofWavelet Feature Sets for Real-Time Pedestrian Classification
Authors: Jan Salmen, Thorsten Suttorp, Johann Edelbrunner, Christian Igel
Venue: Proceedings of the 7th International Conference on Hybrid Intelligent Systems (2007)

Computer vision for object detection often relies on complex classifiers and large feature sets to achieve high detection rates. But when real-time constraints have to be met, for example in driver assistance systems, fast classifiers are required. Here we consider the design of a computationally efficient system for pedestrian detection. We propose an evolutionary algorithm for the optimization of a small set of wavelet features, which can be computed very efficiently. These features serve as input to a linear classifier. The classification performance of the optimized system is on par with recently published results obtained with support vector machines on large feature sets, while the computational time is lower by orders of magnitude.
Open Source Software: All You Do Is Put It Together
Authors: Zeljko Obrenovic, Dragan Gaševic
Venue: IEEE Software (2007)

The authors propose an infrastructure for rapidly prototyping applications from open source software components. The Adaptable Multi-Interface Communicator infrastructure (AMICO) is based on ideas of middleware platforms for component integration, but it focuses on pragmatic aspects of OSS integration, often absent from many existing integration platforms. The authors also identify the key requirements of middleware for rapid prototyping with OSS components and illustrate their approach through two examples in complex scenarios. Another article related to software composition also appears in this issue ("Dynamic Detection of COTS Component Incompatibility").
Sign Detection in Residue Number Systems
Authors: D. K. Banerji, J. A. Brzozowski
Venue: IEEE Transactions on Computers (1969)

This paper is concerned with the sign detection problem in residue number systems. The proposed solution is applicable only to nonredundant systems. It is shown that under rather general conditions an explicit, closed formula for the sign function can be obtained. In a special case, when one of the moduli is 2, the sign function becomes an EXCLUSIVE-OR function. A sign detection algorithm is proposed and methods of implementing the algorithm are presented.
Tutorials on Computer Systems Series Editors' Introduction
Authors: A. V. Pohm
Venue: Computer (1980)

Specially commissioned by the Computer Society, this series of tutorials examines the interrelationships among the various disciplines involved in the design of computer-based systems.
Music playlist generation by adapted simulated annealing
Authors: Steffen Pauws, Wim Verhaegh, Mark Vossen
Venue: Information Sciences: an International Journal (2008)

We present the design of an algorithm for use in an interactive music system that automatically generates music playlists that fit the music preferences of a user. To this end, we introduce a formal model, define the problem of automatic playlist generation (APG), and prove its NP-hardness. We use a local search (LS) procedure employing a heuristic improvement to standard simulated annealing (SA) to solve the APG problem. In order to employ this LS procedure, we introduce an optimization variant of the APG problem, which includes the definition of penalty functions and a neighborhood structure. To improve upon the performance of the standard SA algorithm, we incorporated three heuristics referred to as song domain reduction, partial constraint voting, and a two-level neighborhood structure. We evaluate the developed algorithm by comparing it to a previously developed approach based on constraint satisfaction (CS), both in terms of run time performance and quality of the solutions. For the latter we not only considered the penalty of the resulting solutions, but we also performed a conclusive user evaluation to assess the subjective quality of the playlists generated by both algorithms. In all tests, the LS algorithm was shown to be a dramatic improvement over the CS algorithm.
Reducing False Positives Based on Time Sequence Analysis
Authors: Dong Li, Zhitang Li, Li Wang
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 04 (2007)

Various IDS devices produce large number of alert, the majority of which are false positives. It is laborious for the security officers to find real intrusions. To find intrusions in real time, we should first remove false positives in the alerts. According to the experience of IDS alerts analysis, we find that there are some regularities in alert flow occurrence: power law, trend, periodicity. Based on these statistical regularities, we can operate it based on time sequence effectively. The results of real world data analysis demonstrate that the method can reduce massive false positives in real time effectively.
Bitmap Index Design Choices and Their Performance Implications
Authors: Elizabeth O'Neil, Patrick O'Neil, Kesheng Wu
Venue: Proceedings of the 11th International Database Engineering and Applications Symposium (2007)

Historically, bitmap indexing has provided an important database capability to accelerate queries. However, only a few database systems have implemented these indexes because of the difficulties of modifying fundamental assumptions in the lowlevel design of a database system and in the expectations of customers, both of which have developed in an environment that does not support bitmap indexes. Another problem that arises, and one that may more easily be addressed by a research article, is that there is no definitive design for bitmap indexes; bitmap index designs in Oracle, Sybase IQ, Vertica and MODEL 204 are idiosyncratic, and some of them were designed for older machine architectures. To investigate an efficient design on modern processors, this paper provides details of the Set Query benchmark and a comparison of two research implementations of bitmap indexes. One, called RIDBit, uses the N-ary storage model to organize table rows, and implements a strategy that gracefully switches between the well-known B-tree RID-list structure and a bitmap structure. The other, called FastBit is based on vertical organization of the table data, where all columns are individually stored. It implements a compressed bitmap index, with a linear organization of the bitmaps to optimize disk accesses. Through this comparison, we evaluate the pros and cons of various design choices. Our analysis adds a number of subtleties to the conventional indexing wisdom commonly quoted in the database community.
Detecting Cumulated Anomaly by a Dubiety Degree based detection Model
Authors: Gang Lu, Junkai Yi, Kevin Lu
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 03 (2007)

The concept of Cumulated Anomaly is addressed in this paper, which describes a new type of database anomalies. A detection model, Dubiety-Determining Model (DDM), for Cumulated Anomaly, is proposed. This model is based on statistical theories and fuzzy set theories. The DDM can measure the dubiety degree of each database transaction quantitatively. We designed software system architecture to support the DDM for monitoring database transactions. We also implemented the system and tested it. Our experimental results show that the DDM method is feasible and effective.
An Investigation of Alternative Cache Organizations
Authors: J. Bell
Venue: IEEE Transactions on Computers (1974)

An investigation of the various cache schemes that are practical for a minicomputer has been found to provide considerable insight into cache organization. Simulations are used to obtain data on the performance and sensitivity of organizational parameters of various writeback and lookahead schemes. Hardware considerations in the construction of the actual cache-minicomputer are also noted and a simple cost/performance analysis is presented.
Scalable Query Dissemination in XPeer
Authors: Giovanni Conforti, Giorgio Ghelli, Paolo Manghi, Carlo Sartiani
Venue: Proceedings of the 11th International Database Engineering and Applications Symposium (2007)

This paper presents XPeer, a data sharing system for massively distributed XML data. XPeer allows users to publish and query heterogeneous information without any significant administration efforts. XPeer tries to dispatch any given query to all and only the potentially relevant peers, exploiting a superpeer network to this aim.
Reconfigurable Computing Cluster (RCC) Project: Investigating the Feasibility of FPGA-Based Petascale Computing
Authors: Ron Sass, William V. Kritikos, Andrew G. Schmidt, Srinivas Beeravolu, Parag Beeraka
Venue: Proceedings of the 15th Annual IEEE Symposium on Field-Programmable Custom Computing Machines (2007)

While medium- and large-sized computing centers have increasingly relied on clusters of commodity PC hardware to provide cost-effective capacity and capability, it is not clear that this technology will scale to the PetaFLOP range. It is expected that semiconductor technology will continue its exponential advancements over next fifteen years; however, new issues are rapidly emerging and the relative importance of current performance metrics are shifting. Future PetaFLOP architectures will require system designers to solve computer architecture problems ranging from how to house, power, and cool the machine, all the while remaining sensitive to cost. The Reconfigurable Computing Cluster (RCC) project is a multi-institution, multi-disciplinary project investigating the use of Platform FPGAs to build cost-effective petascale computers. This paper describes the nascent project's objectives and a 64-node prototype cluster. Specifically, the aim is to provide an detailed motivation for the project, describe the design principles guiding development, and present a preliminary performance assessment. Microbenchmark results are reported to answer several pragmatic questions about key subsystems, including the system software, network performance, memory bandwidth, power consumption of nodes in the cluster. Results suggest that the approach is sound.
Removing manually generated boilerplate from electronic texts: experiments with project Gutenberg e-books
Authors: Owen Kaser, Daniel Lemire
Venue: Proceedings of the 2007 conference of the center for advanced studies on Collaborative research (2007)

Collaborative work on unstructured or semi-structured documents, such as in literature corpora or source code, often involves agreed upon templates containing metadata. These templates are not consistent across users and over time. Rule-based parsing of these templates is expensive to maintain and tends to fail as new documents are added. Statistical techniques based on frequent occurrences have the potential to identify automatically a large fraction of the templates, thus reducing the burden on the programmers. We investigate the case of the Project Gutenberg&trade; corpus, where most documents are in ASCII format with preambles and epilogues that are often copied and pasted or manually typed. We show that a statistical approach can solve most cases though some documents require knowledge of English. We also survey various technical solutions that make our approach applicable to large data sets.
Multilevel Minimum Cross Entropy Threshold Selection Based on Quantum Particle Swarm Optimization
Authors: Yong Zhao, Zongde Fang, Kanwei Wang, Hui Pang
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 02 (2007)

The minimum cross entropy thresholding (MCET) has been proven as an efficient method in image segmentation for bilevel thresholding. However, this method is computationally intensive when extended to multilevel thresholding. This paper first employs a recursive programming technique which can reduce an order of magnitude for computing the MCET fitness function. Then, a quantum particle swarm optimization (QPSO) algorithm is proposed for searching the near-optimal MCET thresholds. The experimental results show that the proposed QPSO-based algorithm can get ideal segmentation result with less computation cost.
Workflow Similarity Measure for Process Clustering in Grid
Authors: Yi Wang, Minglu Li, Jian Cao, Xinhua Lin, Feilong Tang
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 04 (2007)

In grid environment, workflow process can be seen as not only cooperative approach of grid services and resources, but also reusable and sharable knowledge to settle specific problem. The research of grid work- flow process clustering can promote knowledge dis- covery and reuse in grid. In this paper, we put forward a grid workflow process design method using Event- Condition-Action (ECA) rule, and propose a new proc- ess similarity measure approach. Then, we use a case to prove the feasibility of the approach and show how to revise present clustering algorithm with the similar- ity measure approach briefly.
Knowledge-Based Code Selection Methods in Retargetable Microcode Synthesis
Authors: Robert Mueller, Joseph Varghese
Venue: IEEE Design Test (1985)

We have presented a method for machine-independent synthesis of microcode using knowledge-based techniques. A high-level representationof the microprogram is translated into symbolic assertions and then converted by the synthesis system to microcode. Thus,a synthesis system can function as the back end of a microcode compiler. Since the knowledge base is machine-independent andrequires only a machine description to generate microcode for that machine, it can also be used as a retargetable microcodecompiler. The knowledge base is in procedural form and consists of transformation rules that reflect the effect of MOs onmachine states. Many of these rules simply restrict the transformations to acceptable behavior on the part of the synthesissystem. Others help to reduce the search by providing knowledge about desirable behavior in the form of heuristics, or helpthe synthesis system reason about different possible derivations for the same specification.
An Evaluation Method of Mechanical Equipment Health State on the Basis of Fuzzy Synthetic Evaluation
Authors: Xuejun Li, Guangfu Bin, Balbir S. Dhillon
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 03 (2007)

maintenance scheme for mechanical equipment, from the viewpoint of function structure of mechanical equipment, a new evaluation method of mechanical equipment running state using fuzzy synthetic evaluation theories is proposed. The concept of health of mechanical equipment is defined. The health value(HV) is employed for quantifying the health state of mechanical equipment. The weight vector and evaluation matrix are discussed as well as fuzzy transformation algorithm operators. The fuzzy synthesis evaluation model is built. The HV is obtained by means of "from bottom to top" to calculate hierarchical HVs of all sub-systems step by step. HV's database of whole mechanical equipment will be established. Based on the database, the health state of mechanical equipment is clear, which provides us with theoretical guide for seeking further optimization maintenance strategy. As an example of application, health state evaluation of rotary kiln used in cement industry has demonstrated. The results show proposed method is effective and feasible. Key words:fuzzy synthesis evaluation; mechanical equipment; health state; health value
An Algorithm of Similarity Mining in Time Series Data on the Basis of Grey Markov Scgm(1,1) Model
Authors: Guoqiang Xiong, Qingjing Gao
Venue: Proceedings of the 2007 IFIP International Conference on Network and Parallel Computing Workshops (2007)

Aiming at two pivotal difficulties involved by similarity data mining in time series, namely effective mining of time series data with arbitrary length and that have biggish stochastic volatility, an algorithm of similarity mining in time series data on the basis of grey Markov SCGM(1, 1) model is proposed in this paper. Grey SCGM(1, 1) model is applied to seek for available information from time series data themselves, and then general change trend has been researched. Markov chain is applied to reveal stochastic volatility regularity and entropy is applied to measure similarity degree of time series. So applicable data scope of similarity mining in time series data is extended and efficiency of data mining is improved.
Fast Texture Mapping from a Single Frontal Image
Authors: Junlan Nie, Li Zhang
Venue: Proceedings of the Fourth International Conference on Image and Graphics (2007)

This paper introduces an improved texture mapping method to meet the future requirement of palm equipment applications. In the case of a lower resource configuration, because there is no requirement of the exact matching between model and texture, the facial texture is extracted from a single frontal face image through a few simple interactions. According to the feature points manual- marked on the texture image, the local texture coordinates can be auto-adjusted alternatively by the algorithm. Experimental results show that the algorithm is rapid, real-time and robust; and that the output model is photo-realistic.
C1 Quadratic Interpolation over Arbitrary Point Sets
Authors: Zoltan Cendes, Steven Wong
Venue: IEEE Computer Graphics and Applications (1987)

New formulas for generating smooth surfaces over arbitrarily spaced data points are developed. The formulas are based on quadratic polynomials for the construction of derivative continuous surfaces rather than on the cubic polynomials generally used. The technique is based on a subdivision procedure, dividing each triangle in a triangulation of the data points into six subtriangles and fitting a quadratic Bezier surface patch over each subtriangle. THe formulas require only function and first derivative values at the data points and are easily evaluated in terms of the Bezier coefficients. Since two-dimensional quadratic polynomials contain only six terms, while 10 terms are required to evaluate a cubic, the new procedure significantly improves the efficiency of algorithms for drawing surfaces in computer-aided geometric design.