ppxscal/embedding_network huggingface dataset:
Modular parametric finite element modelling for reliability-studies in electronic and MEMS packaging
Authors: B. Wunderle, J. Auersperg, V. Grosser, E. Kaulfersch, O. Wittler, B. Michel
Venue: Proceedings of the Symposium on Design, Test, Integration and Packaging of MEMS/MOEMS (2003)

A modular and parametric approach to FE-modelling is presented which allows rapid virtual prototyping for MEMS and other microelectronics packages with respect to some topical reliability issues: Thermal management and thermo-mechanical fatigue. Thereby the method of automatic model generation by modular parametric modelling is outlined and some examples featuring the required solution techniques are given. This simulation procedure forms part of a comprehensive design optimisation process in the field of predictive engineering.
Development of System for the Automatic Generation of Unknown Virus Extermination Software
Authors: Ryuiti Koike, Naoshi Nakaya, Yuji Koi
Venue: Proceedings of the 2007 International Symposium on Applications and the Internet (2007)

In recent years, there has been a frequent occurrence of virus-related incidents, including cases where a virus infection has caused the unauthorized release of confidential information. Viruses should be considered a society-level security risk. However, the mainstream approach to addressing a virus is basically to implement countermeasures for the virus after the damage has occurred. Some of these countermeasures are unable to keep up with the current pace at which viruses are occurring. To address this problem, in this research, we developed a system to generate unknown virus extermination software automatically, without any manual operations. The developed system is designed to automatically generate software that detects and exterminates an unknown virus, by using both a dynamic heuristic that uses a virtual PC and a technique to automatically generate a signature from header data in the virus executable. We were able to verify the effectiveness of this system when we conducted experiments to check whether or not an actual virus could be exterminated by a vaccine that was automatically created for the virus with the developed system.
Essential Dimensions of Latent Semantic Indexing (LSI)
Authors: April Kontostathis
Venue: Proceedings of the 40th Annual Hawaii International Conference on System Sciences (2007)

Latent Semantic Indexing (LSI) is commonly used to match queries to documents in information retrieval applications. LSI has been shown to improve retrieval performance for some, but not all, collections, when compared to traditional vector space retrieval. In this paper, we first develop a model for understanding which values in the reduced dimensional space contain the term relationship (latent semantic) information. We then test this model by developing a modified version of LSI that captures this information, Essential Dimensions of LSI (EDLSI). EDLSI significantly improves retrieval performance on corpora that previously did not benefit from LSI, and offers improved runtime performance when compared with traditional LSI. Traditional LSI requires the use of a dimensionality reduction parameter which must be tuned for each collection. Applying our model, we have also shown that a small, fixed dimensionality reduction parameter (k=10) can be used to capture the term relationship information in a corpus.
Customized classification learning based on query projections
Authors: Yiqiu Han, Wai Lam, Charles X. Ling
Venue: Information Sciences: an International Journal (2007)

We develop a customized classification learning method QPL, which is based on query projections. Given an instance to be classified (query instance), QPL explores the projections of the query instance (QPs), which are essentially subsets of attribute values shared by the query and training instances. QPL investigates the associated training data distribution of a QP to decide whether it is useful. The final prediction for the query is made by combining some statistics of the selected useful QPs. Unlike existing instance-based learning, QPL does not need to compute a distance measure between instances. The utilization of QPs for learning can explore a richer hypothesis space and achieve a balance between precision and robustness. Another characteristic of QPL is that the target class may vary for different query instances in a given data set. We have evaluated our method with synthetic and benchmark data sets. The results demonstrate that QPL can achieve good performance and high reliability.
Flexible post-calculus engineering mathematics electives
Authors: M. J. Maron
Venue: Proceedings of the 28th Annual Frontiers in Education - Volume 03 (1998)

The University of Louisville offers six engineering degrees that are ABET-accredited at the advanced level. The mathematics course requirement for these programs, taught by Engineering Mathematics faculty within the engineering school, is well above the minimum required for advanced level accreditation. All engineering programs require 12 semester hours (SH) of calculus, 3 SH of ordinary differential equations, and 3 SH of probability/statistics; five of the six programs also require a 3 SH linear algebra course and/or a 3 SH numerical methods course. This paper describes how the nonprobability/statistics courses were revised in response to an accreditation-driven request to decrease the number of semester hours of basic mathematics. The revisions sought to do this while maintaining the students' high level of mathematical preparation and ensuring that they also have baseline computer algebra system skills early in their education. The revised curriculum will be phased in starting Fall 1998.
A method for fast revocation of public key certificates and security capabilities
Authors: Dan Boneh, Xuhua Ding, Gene Tsudik, Chi Ming Wong
Venue: Proceedings of the 10th conference on USENIX Security Symposium - Volume 10 (2001)

We present a new approach to fast certificate revocation centered around the concept of an on-line semi-trusted mediator (SEM). The use of a SEM in conjunction with a simple threshold variant of the RSA cryptosystem (mediated RSA) offers a number of practical advantages over current revocation techniques. Our approach simplifies validation of digital signatures and enables certificate revocation within legacy systems. It also provides immediate revocation of all security capabilities. This paper discusses both the architecture and implementation of our approach as well as performance and compatibility with the existing infrastructure. Our results show that threshold cryptography is practical for certificate revocation.
Automated Generation of Test Cases Using Model-Driven Architecture
Authors: A. Z. Javed, P. A. Strooper, G. N. Watson
Venue: Proceedings of the 29th International Conference on Software Engineering Workshops (2007)

In this paper, we demonstrate a method that uses the model transformation technology of MDA to generate unit test cases from a platform-independent model of the system. The method we propose is based on sequence diagrams. First we model the sequence diagram and then this model is automatically transformed into a general unit test case model (an xUnit model which is independent of a particular unit testing framework), using model-to-model transformations. Then model-to-text transformations are applied on the xUnit model to generate platformspecific (JUnit, SUnit etc.) test cases that are concrete and executable. We have implemented the transformations in a prototype tool based on the Tefkat transformation tool and MOFScript. The paper gives details of the tool and the transformations that we have developed. We have applied the method to a small example (ATM Simulation).
Bi-Intervals for Backtracking on Temporal Constraint Networks
Authors: Jean-Francois Baget, Sebastien Laborie
Venue: Proceedings of the 14th International Symposium on Temporal Representation and Reasoning (2007)

Checking satisfiability of temporal constraint networks involves infinite variables domains. We explore a solution based upon finite partitions of infinite domains. Though a straightforward partition results in a sound and complete backtrack, its extension to forward checking is not complete. Using bi-intervals, we obtain sound and complete backtrack and forward checking algorithms. Moreover, we show that bi-intervals used in a hybrid algorithm which also instanti- ates constraints improve backtrack efficiency.
Using discriminant analysis to identify students at risk
Authors: E. W. Thomas
Venue: Proceedings of the 26th Annual Frontiers in Education - Volume 01 (1996)

In designing any educational intervention one often needs to determine what factors are related to success and failure in a course, identify students at risk, evaluate the impact of any new program on student performance. In this paper we will discuss the use of discriminant analysis as a technique for addressing all of these issues. Discriminant analysis is a statistical technique designed to investigate the differences between two or more groups of people with respect to several underlying variables. This technique is more appropriate than commonly used educational measures (correlations, regression weights, etc.) because the variable being predicted is categorical. Moreover, this approach results in a unit of analysis, predicted category membership, that is more useful in evaluating instructional interventions.
Verbal and non-verbal cues in the communication of emotions
Authors: T. S. Polzin
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 04 (2000)

Several studies have shown that humans extend their interpersonal behavioral patterns onto their interaction with computers. Based on this finding, research in human-computer interaction acknowledges the need to detect the users' expressions of emotion. However, we discovered that most of the current research is confined to emotion synthesis. In this investigation, we explored the role of verbal and non-verbal information in the communication of emotions. By training emotion-specific language and prosodic models on a corpus consisting of several thousands of sad, angry, or neutral speech segments from English movies, we showed that a classification system based on these models achieved an accuracy comparable to the accuracy of human listeners performing the same task.
Quaternion wavelet phase based stereo matching for uncalibrated images
Authors: Jun Zhou, Yi Xu, Xiaokang Yang
Venue: Pattern Recognition Letters (2007)

This paper proposes a quaternion wavelet phase based stereo matching (QWPSM) scheme for uncalibrated image pairs. In this scheme, we estimate the disparity by directly establishing correspondences between quaternionic phase structures of two quaternion wavelet filtered (QWF) images. Firstly, linear-phase quaternion wavelet filters (LPQWFs) are constructed from real biorthogonal wavelet bases. Then, quaternion phases are extracted under each scale through quaternion wavelet filtering of the multiscale transformed image pyramids. The disparity estimation is formed as a minimization process of a local energy weighted cost function, and propagated from coarse to fine scales. Costs can adaptively alleviate the negative effects of phase singularities, which are the main causes of mismatches in phase-based stereo matching. Multiscale matching strategy is used to avoid phase wrapping and improve convergence speed. Experimental results are promising in various image pairs.
Extending file systems using stackable templates
Authors: Erez Zadok, Ion Badulescu, Alex Shender
Venue: Proceedings of the annual conference on USENIX Annual Technical Conference (1999)

Extending file system functionality is not a new idea, but a desirable one nonetheless[6, 14, 18]. In the several years since stackable file systems were first proposed, only a handful are in use[12, 19]. Impediments to writing new file systems include the complexity of operating systems, the difficulty of writing kernel-based code, the lack of a true stackable vnode interface[14], and the challenges of porting one file system to another operating system. We advocate writing new stackable file systems as kernel modules. As a starting point, we propose a portable, stackable template file system we call Wrapfs (wrapper file system). Wrapfs is a canonical, minimal stackable file system that can be used as a pattern across a wide range of operating systems and file systems. Given Wrapfs, developers can add or modify only that which is necessary to achieve the desired functionality. Wrapfs takes care of the rest, and frees developers from the details of operating systems. Wrapfs templates exist for several common operating systems (Solaris, Linux, and FreeBSD), thus alleviating portability concerns. Wrapfs can be ported to any operating system with a vnode interface that provides a private data pointer for each data structure used in the interface. The overhead imposed by Wrapfs is only 5-7%. This paper describes the design and implementation of Wrapfs, explores portability issues, and shows how the implementation was achieved without changing client file systems or operating systems. We discuss several examples of file systems written using Wrapfs.
Privacy-preserving sharing and correction of security alerts
Authors: Patrick Lincoln, Phillip Porras, Vitally Shmatikov
Venue: Proceedings of the 13th conference on USENIX Security Symposium - Volume 13 (2004)

We present a practical scheme for Internet-scale collaborative analysis of information security threats which provides strong privacy guarantees to contributors of alerts. Wide-area analysis centers are proving a valuable early warning service against worms, viruses, and other malicious activities. At the same time, protecting individual and organizational privacy is no longer optional in today's business climate. We propose a set of data sanitization techniques and correlation, while maintaining privacy for alert contributors. Our approach is practical, scalable, does not rely on trusted third parties or secure multiparty computation schemes, and does not require sophisticated schemes, and does not require sophisticated key management.
Transformer-Coupled Loopback Test for Differential Mixed-Signal Specifications
Authors: Byoungho Kim, Zhenhai Fu, Jacob A. Abraham
Venue: Proceedings of the 25th IEEE VLSI Test Symmposium (2007)

Loopback tests for a differential mixed-signal Device Under Test (DUT) have rarely been attempted, since any imbalance introduced by a Design for Test (DfT) circuitry on differential signaling delivers an imperfect sinusoidal wave to the DUT input, thereby degrading the DUT performance. In addition, this methodology inherently suffers from fault masking. These problems result in low test accuracy and serious yield loss. This paper presents a novel methodology for efficient prediction of individual DUT dynamic performance parameters with a Radio-Frequency (RF) transformer in loopback mode to overcome the imbalance problem of DfT circuitry. Cascaded RF transformer in loopback mode produces differently weighted loopback responses, which are used to characterize the DUT dynamic performance. Hardware measurement results show that this approach can be effectively used to predict the specifications of a DUT.
3D Vascular Shape Segmentation for Fluid-Structure Modeling
Authors: Najah Hraiech, Michael Carroll, Michel Rochette, Jean-Louis Coatrieux
Venue: Proceedings of the IEEE International Conference on Shape Modeling and Applications 2007 (2007)

Shape signatures are fundamental in medicine to characterize abnormal patterns and track their evolution over time. Beyond the diagnosis objective, they are critical to understand the relations between structures and functions as well as to design advanced image-guided therapy. One of the most critical steps in medical imaging remains segmentation, aimed at a fast, precise, robust and reproducible extraction of the organ boundaries. We present a 3D semi-automatic technique for segmenting the inner boundary of Abdominal Aortic Aneurysms (AAA). The method that is proposed makes use of recent developments from graph theory, the graph-cut algorithms. It requires a limited interaction with the user (for learning the object and background statistical features). Its performance is highlighted on multi-detector CT angiography data. Some perspectives are then sketched in order to show how this result could be improved to feed fluid-structure simulations.
Fast accent identification and accented speech recognition
Authors: D. Nelson
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 01 (1999)

The performance of speech recognition systems degrades when speaker accent is different from that in the training set. Accent-independent or accent-dependent recognition both require collection of more training data. In this paper, we propose a faster accent classification approach using phoneme-class models. We also present our findings in acoustic features sensitive to a Cantonese accent, and possibly other Asian language accents. In addition, we show how we can rapidly transform a native accent pronunciation dictionary to that for accented speech by simply using knowledge of the native language of the foreign speaker. The use of this accent-adapted dictionary reduces recognition error rate by 13.5%, similar to the results obtained from a longer, data-driven process.
A Reduced Complexity Algorithm for Minimizing N-Detect Tests
Authors: Kalyana R. Kantipudi, Vishwani D. Agrawal
Venue: Proceedings of the 20th International Conference on VLSI Design held jointly with 6th International Conference: Embedded Systems (2007)

We give a new recursive rounding linear programming (LP) solution to the problem of N-detect test minimzation. This is a polynomial- time solution that closely approximates the exact but NP-hard integer linear programming (ILP) solution. In ILP, a test is represented by a [0; 1] integer variable and the sum of those variables is minimized. Constraints ensure that each fault has at least N tests with non-zero variables. Tra- ditionally, the problem has been transformed to less complex LP by treating the variables as real numbers, regarded as probabilities with which they can be rounded o to 0 or 1. This is known as the randomized rounding method. In the new method, the LP is recursively used, each time rounding the largest variable to 1 and reducing the size of the LP. The method is found to converge to a solution in just a few LP runs and the result is usually better than that of randomized rounding. Experimental results include ISCAS85 benchmarks and a set of multiplier circuits. N-detect tests for N = 1; 5 and 15 are considered. Also, a 10-vector single-detect sequence for c6288 is given.
Periodicity and unbordered words: A proof of the extended duval conjecture
Authors: Tero Harju, Dirk Nowotka
Venue: Journal of the ACM (JACM) (2007)

The relationship between the length of a word and the maximum length of its unbordered factors is investigated in this article. Consider a finite word w of length n. We call a word bordered if it has a proper prefix, which is also a suffix of that word. Let &mu;(w) denote the maximum length of all unbordered factors of w, and let &part;(w) denote the period of w. Clearly, &mu;(w) &le; &part;(w). We establish that &mu;(w) &equals; &part;(w), if w has an unbordered prefix of length &mu;(w) and n &ge; 2&mu;(w) &minus; 1. This bound is tight and solves the stronger version of an old conjecture by Duval [1983]. It follows from this result that, in general, n &ge; 3&mu;(w) &minus; 3 implies &mu;(w) &equals; &part;(w), which gives an improved bound for the question raised by Ehrenfeucht and Silberger in 1979.
Multiscale methods for the segmentation of images
Authors: M. E. C. Schneider
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 04 (1996)

This work presents a method for segmenting images based on gradients in the intensity function. Past approaches have centered on formulating the problem in the context of variational calculus as the minimization of a functional involving the image intensity and edge functions. Computational methods for finding the minima of such variational problems are prone to two shortfalls: they are often computationally intensive and almost always incapable of computing error statistics associated with the segmentation. Using a particular variational formulation as a starting point, this paper presents a derivation of an associated statistical formulation using multiscale models. The result is an algorithm which is fast and capable of computing error statistics.
Pedagogical Agents for Teacher Intervention in Educational Robotics Classes: Implementation Issues
Authors: Ilkka Jormanainen, Yuejun Zhang, Kinshuk Kinshuk, Erkki Sutinen
Venue: Proceedings of the The First IEEE International Workshop on Digital Game and Intelligent Toy Enhanced Learning (2007)

Teachers working in robotics classes face a major problem: how to keep track on individual students' or even small groups' progress in a class of 30-40 students. A multi-agent environment to help teachers with this problem is based on having pedagogical agents to monitor students' interaction, robots' movements, and the construction and programming process of robots. Mobile interaction agents move in local area network delivering other agents' observations to teacher's visualization agent. The implemented prototype system has revealed the strengths and the weakness of the proposed architecture.
A generic fuzzy rule based technique for image segmentation
Authors: G. C. Karmakar
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 03 (2001)

Many fuzzy clustering based techniques do not incorporate the spatial relationships of the pixels, while all fuzzy rule based image segmentation techniques tend to be very much application dependent. In most techniques, the structure of the membership functions are predefined and their parameters are either automatically or manually determined. This paper addresses the aforementioned problems by introducing a general fuzzy rule based image segmentation technique, which is application independent and can also incorporate the spatial relationships of the pixels. It also proposes the automatic defining of the structure of the membership functions. A qualitative comparison is made between the segmentation results using this method and the popular fuzzy c-means (FCM) applied to two types of images: light intensity (LI) and an X-ray of the human vocal tract. The results clearly show that this method exhibits significant improvements over FCM for both types of images.