ppxscal/embedding_network huggingface dataset:
WIER-implementing artifact reuse in an educational environment with real projects-work in progress
Authors: J. Ceddia
Venue: Proceedings of the Frontiers in Education Conference, 2001. 31st Annual - Volume 02 (2001)

Software reuse has been discussed in the literature for many years. As educators, the authors aim to foster the legitimate reuse of software artifacts such as specifications, designs, test cases, prototypes, documentation and templates. This paper describes a major project that attempts to encourage reuse in an undergraduate computing degree program by utilising these artifacts. The students are required to complete an industrial experience project as part of their course. Since 1995, over 170 projects have been undertaken and very quickly, project types were identified by the coordinators. Students, however, were only exposed to their own project and so could not easily benefit from the experience of past students. A Web based tool called WIER (Web Industrial Experience Resources) has been developed to: (a) provide a search and review facility for past projects; (b) ease the project administration workload for the students; (c) provide templates and examples of major documentation deliverables; and (d) provide a list of resources (books and URLs) that past students have found useful when researching a topic. A faceted classification scheme has been implemented in WIER to index past projects. Certain constraints of this environment such as the high turnover of programmers (students) and client copyright issues are considered A full evaluation of WIER will be carried out throughout 2001, including formal student feedback and tracking usage of the site's resources.
On the statistical nature of real sinusoids associated with rotating machinery
Authors: P. Sherman
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 06 (2000)

This paper represents the first phase of an ongoing investigation into the nature of sinusoidal types of random processes associated with real world phenomena. Some noteworthy results include the normality of amplitude and frequency, characterization of the same as stationary random processes, and potential to improve condition monitoring of rotating machinery.
A middleware independent service modeling and a model transformation framework
Authors: Ralph Johnson
Venue:  (2006)

One of the reasons enterprise software is difficult to change is because it relies on middleware services. Middleware makes the rest of the application simpler but then the application depends on the middleware. Migrating existing software to new middleware technology requires significant software redesign, rewriting and testing.This dissertation follows the Model Driven Architecture (MDA) initiative from the Object Management Group (OMG). The MDA separates business or application logic from underlying platform technology by defining application models at two levels; a Platform Independent Model (PIM) and a Platform Specific Model (PSM). The dissertation focuses on the middleware independent aspect of the platform. By specifying common services using UML profiles that do not depend on specific middleware technology and providing separate transformations for each service, it is possible to develop business software models at a middleware independent level and to use transformers to map a PIM onto a middleware specific implementation.The Mercator model transformation tool and framework help two kinds of developers. This first kind is modelers who use the tool to edit PIMs and use common object services packaged as profiles. The second kind is model compiler developers who define profiles and create transformers that translate the PIMs into middleware specific implementation. The framework provides the profile definition and transformation structure as well as model manipulation APIs that allow model compiler developers to plug in new object services and/or new transformations of existing services. PIMs no longer contain middleware specific information. This information is customizable and kept separately in annotation files.Our contributions in this research are: (1) A systematic method to define middleware independent object services. (2) Profiles for object persistence, naming, distribution, transaction and messaging services. These profiles contain stereotypes, APIs, annotations and model transformers. (3) A novel, lightweight, stereotype-triggered model transformation framework that allows object service transformers to plug-in to manipulate model elements. (4) A modeling language based on eMOF with support for UML profiles and viewpoints. (5) A Mercator tool that implements the framework.We believe that this research is a step towards the realization of the MDA approach.
A robust technique for harmonic analysis of speech
Authors: N. Abu-Shikhah
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 200. on IEEE International Conference - Volume 02 (2001)

A technique named least squares harmonic (LSH) is proposed for speech decomposition. The problem of harmonic estimation for speech is formulated as a solution to two sets of linear equations derived from minimising the mean squared error between original and estimated signals. The algorithm assumes that a good initial estimate of the pitch period is available. The performance of the algorithm is comparable to that of the total least square Prony method (TLSP) at high signal-to-noise ratios, however, at very low SNR, the proposed algorithm leads to a much more accurate harmonic representation. The approach used here has a great potential in coding and recognition applications.
Kernel Auto-Regressive Model with eXogenous Inputs for Nonlinear Time Series Prediction
Authors: Venkataramana B. Kini, C. Chandra Sekhar
Venue: Proceedings of the International Conference on Computing: Theory and Applications (2007)

In this paper we present a novel approach for nonlinear time series prediction using Kernel methods. The kernel methods such as Support Vector Machine(SVM) and Support Vector Regression(SVR) deal with nonlinear problems assuming independent and identically distributed (i.i.d.) data, without explicit notion of time. However, the problem of prediction necessitates temporal information. In this regard, we propose a novel time series modeling technique, Kernel Auto-Regressive model with eXogenous inputs (KARX) and associated estimation methods. Amongst others the advantage of KARX model compared to the widely used Nonlinear Auto-Regressive eXogenous (NARX) model (which is implemented using Artificial Neural Network (ANN)) is, implicit nonlinear mapping and better regularization capability. In this work, we make use of Kalman recursions instead of quadratic programming which is generally used in kernel methods. Also, we employ online estimation schemes for estimating model noise parameters. The efficacy of the approach is demonstrated on artificial time series as well as real world time series acquired from aircraft engines.
Irregular sampling with unknown locations
Authors: P. Marziliano
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 03 (1999)

This paper is concerned with finding the locations of an irregularly sampled finite discrete-time band-limited signal. First a geometrical approach is described and is transformed into an optimization problem. Due to the structure of the problem, multiple solutions exist and are shifts of each other. Three methods of solution are suggested: an exhaustive method which finds the exact set of locations; random search method and cyclic coordinate method, both descent methods, which find approximate or exact solutions. The cyclic coordinate method is less likely to fall in a local minimum and proves to be more satisfactory than the random search method in the presence of jitter. A practical example, where a signal is sampled several times with a regular spacing, is also described.
Software Engineering Education in Russia: A Comparative Study of People, Process and Technology a Four Year Perspective
Authors: Gil Taran, Mel Rosso-Llopart
Venue: Proceedings of the 20th Conference on Software Engineering Education & Training (2007)

The Master of Software Engineering Program at Carnegie Mellon University initiated in 2003 a software engineering education lecture series in Russia to introduce enduring principles and industry best practices for software development and software project management. Through a system of multi-day corporate/public workshops and a methodology for training local trainers to re-teach the material, the seminars have been successfully attended by practicing engineers from all over Russia, the Ukraine and Belarus. Our experiences of interacting with the Russian software industry provides an in-depth look at how software practitioners and executives in Russia approach issues of dealing with people, process and technology, and how the industry has changed from an educational perspective over the past four years since we had started.
Efficient user-level thread migration and checkpointing on windows NT clusters
Authors: Hazim Abdel-Shafi, Evan Speight, John K. Bennett
Venue: Proceedings of the 3rd conference on USENIX Windows NT Symposium - Volume 3 (1999)

Clusters of industry-standard multiprocessors are emerging as a competitive alternative for large-scale parallel computing. However, these systems have several disadvantages over large-scale multiprocessors, including complex thread scheduling and increased susceptibility to failure. This paper describes the design and implementation of two user-level mechanisms in the Brazos parallel programming environment that address these issues on clusters of multiprocessors running Windows NT: thread migration and checkpointing. These mechanisms offer several benefits: (1) The ability to tolerate the failure of multiple computing nodes with minimal runtime overhead and short recovery time. (2) The ability to add and remove computing nodes while applications continue to run, simplifying scheduled maintenance operations and facilitating load balancing. (3) The ability to tolerate power failures by performing a checkpoint before shutdown or by migrating computation threads to other stable nodes. Brazos is a distributed system that supports both shared memory and message passing parallel programming paradigms on networks of Intel x86-based multiprocessors running Windows NT. The performance of thread migration in Brazos is an order of magnitude faster than previously reported Windows NT implementations, and is competitive with implementations on other operating systems. The checkpoint facility exhibits low runtime overhead and fast recovery time.
American Electric Power's Project Probe/sup SM/-enhancing power engineering education through industrial-academic cooperation
Authors: D. J. Bayless
Venue: Proceedings of the 28th Annual Frontiers in Education - Volume 03 (1998)

Numerous concerns confronting engineering education in the next century will necessitate a greater level of cooperation between academia and industry. A model of such cooperation is Project Probe/sup SM/-an annual summer intern program offered by American Electric Power (AEP) to provide meaningful education and work experiences in power generation engineering for qualified engineering students. Project Probe supplements traditional engineering education that often lacks focus in areas of critical need for the power industry. Project Probe aims to foster communication and cooperation between academia and the power industry, support and educate engineering faculty with regard to the power industry, as well as enhance the education of future engineers. This paper presents the objectives, methodology and results of Project Probe since 1995, including student development, faculty enrichment and benefits to the host power plants and American Electric Power. Project Probe is shown intern or cooperative educational programs. Information is also presented to encourage implementation of aspects of Project Probe into university classroom work and to encourage educators and industry to seek suitable partners for sponsorship and development of similar programs. Recommendations are also presented to facilitate implementation of a program similar to Project Probe.
Digital Butterworth filter for subtracting noise from low magnitude surface electromyogram
Authors: Roger G. T. Mello, Liliam F. Oliveira, Jurandir Nadal
Venue: Computer Methods and Programs in Biomedicine (2007)

This work presents a digital filter designed to delimitate the frequency band of surface electromyograms (EMG) and remove the mains noise and its harmonics, focusing the signal analysis during reduced muscle activity. A Butterworth filter was designed as the frequency-domain product of a second order, high-pass filter with cutoff frequency 10Hz, an eighth order low-pass filter, with cutoff at 400Hz and six stop-band filters, second order, centered at the 60Hz mains noise and its harmonics until 360Hz. The resulting filter was applied in both direct and reverse directions of the signals to avoid phase distortions. The performance was evaluated with a simulated EMG signal with additive noise in multiples of 60Hz. A qualitative assessment was made with real EMG data, acquired from 16 subjects, with age from 20 to 32 years. Subjects were positioned in orthostatic position during 21s, being only the last second analyzed to assure stationarity. EMG were collected by Ag/AgCl electrodes on right lateral gastrocnemius, amplified with gain 5000, filtered in the band from 10Hz to 1kHz, and thus digitized with 2ksamples/s. The filter effectively removed the mains noise components, with attenuations greater than 96.6%. The attenuation of the simulated signal at frequencies below 15Hz and at 60Hz caused only a small reduction of total power, preserving the original spectrum. Thus, the filter resulted suitable to the proposed application.
Prerequisites for Successful Architectural Knowledge Sharing
Authors: Rik Farenhorst, Patricia Lago, Hans van Vliet
Venue: Proceedings of the 2007 Australian Software Engineering Conference (2007)

Sharing knowledge pertaining to software architectures becomes increasingly important. If this knowledge is not explicitly stored or communicated, valuable knowledge dissipates. However, stakeholders will only share knowledge with each other if they are motivated to do so, or in other words if the necessary incentives are created. In this paper we identify three incentives for architectural knowledge sharing: the establishment of social ties, more efficient decision making, and knowledge internalization. Next, we discuss our experiences on how architectural knowledge is shared in a large software development organization. Based on these experiences we propose a set of prerequisites that need to be met to foster successful architectural knowledge sharing. The importance of these prerequisites is motivated by demonstrating that they create the identified incentives.
Software project economics: a roadmap
Authors: Martin Shepperd
Venue: 2007 Future of Software Engineering (2007)

The objective of this paper is to consider research progress in the field of software project economics with a view to identifying important challenges and promising research directions. I argue that this is an important sub-discipline since this will underpin any cost-benefit analysis used to justify the resourcing, or otherwise, of a software project. To accomplish this I conducted a bibliometric analysis of peer reviewed research articles to identify major areas of activity. My results indicate that the primary goal of more accurate cost prediction systems remains largely unachieved. However, there are a number of new and promising avenues of research including: how we can combine results from primary studies, integration of multiple predictions and applying greater emphasis upon the human aspects of prediction tasks. I conclude that the field is likely to remain very challenging due to the people-centric nature of software engineering, since it is in essence a design task. Nevertheless the need for good economic models will grow rather than diminish as software becomes increasingly ubiquitous. Keywords: cost models, effort prediction, empirical software engineering, software project management.
Using component metadata to regression test component-based software: Research Articles
Authors: Alessandro Orso, Hyunsook Do, Gregg Rothermel, Mary Jean Harrold, David S. Rosenblum
Venue: Software Testing, Verification Reliability (2007)

Increasingly, modern-day software systems are being built by combining externally-developed software components with application-specific code. For such systems, existing program-analysis-based software engineering techniques may not directly apply, due to lack of information about components. To address this problem, the use of component metadata has been proposed. Component metadata are metadata and metamethods provided with components, that retrieve or calculate information about those components. In particular, two component-metadata-based approaches for regression test selection are described: one using code-based component metadata and the other using specification-based component metadata. The results of empirical studies that illustrate the potential of these techniques to provide savings in re-testing effort are provided. Copyright &copy; 2006 John Wiley & Sons, Ltd. Based in part on &lsquo;Using component metacontents to support the regression testing of component-based software&rsquo; by A. Orso, M. J. Harrold, D. Rosenblum, G. Rothermel, M. L. Soffa and H. Do, which appeared in Proceedings of the International Conference on Software Maintenance, Florence, Italy, November 2001, pp. 716&ndash;725 [1]. &copy; 2001 IEEE. This revised and expanded version appears here with the permission of the IEEE.
Collective entity resolution in relational data
Authors: Lise Getoor
Venue:  (2006)

Many databases contain imprecise references to real-world entities. For example, a social-network database records names of people. But different people can go by the same name and there may be different observed names referring to the same person. The goal of entity resolution is to determine the mapping from database references to discovered real-world entities. Traditional entity resolution approaches consider approximate matches between attributes of individual references, but this does not always work well. In many domains, such as social networks and academic circles, the underlying entities exhibit strong ties to each other, and as a result, their references often co-occur in the data. In this dissertation, I focus on the use of such co-occurrence relationships for jointly resolving entities. I refer to this problem as 'collective entity resolution'. First, I propose a relational clustering algorithm for iteratively discovering entities by clustering references taking into account the clusters of co-occurring references. Next, I propose a probabilistic generative model for collective resolution that finds hidden group structures among the entities and uses the latent groups as evidence for entity resolution. One of my contributions is an efficient unsupervised inference algorithm for this model using Gibbs Sampling techniques that discovers the most likely number of entities. Both of these approaches improve performance over attribute-only baselines in multiple real world and synthetic datasets. I also perform a theoretical analysis of how the structural properties of the data affect collective entity resolution and verify the predicted trends experimentally. In addition, I motivate the problem of query-time entity resolution. I propose an adaptive algorithm that uses collective resolution for answering queries by recursively exploring and resolving related references. This enables resolution at query-time, while preserving the performance benefits of collective resolution. Finally, as an application of entity resolution in the domain of natural language processing, I study the sense disambiguation problem and propose models for collective sense disambiguation using multiple languages that outperform other unsupervised approaches.
Understanding Consumers' Expectations of Mobile Data Services in Australia
Authors: Sherah Kurnia, Heejin Lee, Song Yang
Venue: Proceedings of the International Conference on the Management of Mobile Business (2007)

The Australian Mobile Telecommunication Industry has experienced a significant growth in the last few years. However, mobile data services which have the potential to increase the industry revenue significantly have not been used widely as predicted. At this stage, few studies have been conducted to explore the use of mobile data services in Australia. To better understand mobile phone users' expectations regarding mobile data services, this study explores the current use of mobile data services in Australia through a survey study. The findings indicate that there has been a positive trend towards a wider use of mobile data services in Australia. Price, usefulness and immediate availability of the services have been identified as important factors that can further encourage the use of mobile data services in Australia.
A new interpretation of the misadjustment in adaptive filtering
Authors: H. J. Butterweck
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 03 (1996)

An LMS type adaptive filter in a stationary environment does not converge to the Wiener solution, but exhibits small asymptotic fluctuations around it. These contribute to the output as an interfering signal, whose strength is conventionally designated by the term "misadjustment", defined as the normalized excess mean-squared error due to the weight fluctuations. Importantly, this definition makes sense only for a white reference signal. For a coloured reference signal the contribution of the weight fluctuations to the output signal is often correlated with the reference signal which forbids direct superposition of the partial powers. In that case the excess mean-squared error no longer serves as a measure of the deviation between the error signal and the reference signal. In a small-signal approximation the power of the partial output signal due to the weight fluctuations is then shown to represent an appropriate measure of the misadjustment.
The Zombie roundup: understanding, detecting, and disrupting botnets
Authors: Evan Cooke, Farnam Jahanian, Danny McPherson
Venue: Proceedings of the Steps to Reducing Unwanted Traffic on the Internet on Steps to Reducing Unwanted Traffic on the Internet Workshop (2005)

Global Internet threats are undergoing a profound transformation from attacks designed solely to disable infrastructure to those that also target people and organizations. Behind these new attacks is a large pool of compromised hosts sitting in homes, schools, businesses, and governments around the world. These systems are infected with a bot that communicates with a bot controller and other bots to form what is commonly referred to as a zombie army or botnet. Botnets are a very real and quickly evolving problem that is still not well understood or studied. In this paper we outline the origins and structure of bots and botnets and use data from the operator community, the Internet Motion Sensor project, and a honeypot experiment to illustrate the botnet problem today. We then study the effectiveness of detecting botnets by directly monitoring IRC communication or other command and control activity and show a more comprehensive approach is required. We conclude by describing a system to detect botnets that utilize advanced command and control systems by correlating secondary detection data from multiple sources.