ppxscal/embedding_network huggingface dataset:
Summer schools on the amateur radio computing
Authors: Miroslav S. Skoric
Venue: Proceedings of the 12th annual SIGCSE conference on Innovation and technology in computer science education (2007)

Summer schools in computer science dedicated for pre-university students and their teachers would increase the number of decisions for studying CS. With adding a variety of computer-related amateur radio communications, we introduce excitement for learning and having fun in CS profession.
A Two-stage Multi-view Analysis Framework for Human Activity and Interactions
Authors: Sangho Park, Mohan M. Trivedi
Venue: Proceedings of the IEEE Workshop on Motion and Video Computing (2007)

This paper presents a new framework for a multi-stage multi-view approach for human interactions and activity analysis. The analysis is performed in a distributed vision system that synergistically integrate track- and body-level representations across multiple cameras. Our system aims at versatile and easily-deployable system that does not require careful camera calibration. Main contributions of the paper are: (1) context-dependent camera handover for occlusion handling, (2) switching the multi-stage analysis between track- and body-level representations, and (3) a hypothesis-verification paradigm for top-down feedback exploiting spatio-temporal constraints inherent in human interaction. Experimental evaluation shows the efficacy of the proposed system for analyzing multi-person interactions. Current implementation uses two views, but extension to more views is straightforward.
Singular value analysis of space-time equalization in the GSM mobile system
Authors: A. L. van der Veen
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 02 (1996)

Singular value analysis of a GMSK-modulated signal such as employed by GSM reveals that it admits a reasonably accurate linear model, enabling the use of linear space-time equalizers to retrieve the data symbols. The analysis also shows that one antenna does not provide sufficient resolution to allow estimation of the channel length, so that the performance of the equalizers is limited. An algorithm is proposed for the blind space-time equalization and separation of multiple co-channel GMSK signals, based on their fixed symbol rate, finite alphabet and constant modulus properties.
Assessing hybrid classes in a flexible learning environment
Authors: M. Lawrence-Slater
Venue: Proceedings of the Frontiers in Education Conference, 2001. 31st Annual - Volume 02 (2001)

This paper describes the development of a regime comprising a teaching platform and associated assessment processes. The objective behind these is to enable the equitable assessment of student assignments in hybrid courses. In this paper, the term hybrid refers to courses where the student body comprises both campus-based and off-campus students. Additionally, in either of these groups students may elect to undertake their studies using online resources rather than attend in person. The paper commences with a background discussion on the problem and reasons for seeking alternative approaches to teaching and assessment in hybrid courses. This is followed by a detailed examination of the teaching processes, assessable components and the tools which are pivotal to the process. The paper describes the rationale and objectives behind each, the relationship between the different components and describes the relationship of each to the process as a whole. The paper concludes with some of the issues encountered during the evolution of the regime and discussion on further direction in respect to future research and development. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Valuing pilot projects in a learning by investing framework: An approximate dynamic programming approach
Authors: Eymen Errais, Jeffrey Sadowsky
Venue: Computers and Operations Research (2008)

We introduce a general discrete time dynamic framework to value pilot project investments that reduce idiosyncratic uncertainty with respect to the final cost of a project. The model generalizes different settings introduced previously in the literature by incorporating both market and technical uncertainty and differentiating between the commercial phase and the pilot phase of a project. In our model, the pilot phase requires N stages of investment for completion. With this distinction we are able to frame the problem as a compound perpetual Bermudan option. We work in an incomplete markets setting where market uncertainty is spanned by tradable assets and technical uncertainty is idiosyncratic to the firm. The value of the option to invest as well as the optimal exercise policy are solved by an approximate dynamic programming algorithm that relies on the independence of the state variables increments. We prove the convergence of our algorithm and derive a theoretical bound on how the errors compound as the number of stages of the pilot phase is increased. We implement the algorithm for a simplified version of the model where revenues are fixed, providing an economic interpretation of the effects of the main parameters driving the model. In particular, we explore how the value of the investment opportunity and the optimal investment threshold are affected by changes in market volatility, technical volatility, the learning coefficient, the drift rate of costs and the time to completion of a pilot stage.
Discrete transport system simulated by SSF for reliability and functional analysis
Authors: Tomasz Walkowiak, Jacek Mazurkiewicz
Venue: Proceedings of the 2nd International Conference on Dependability of Computer Systems (2007)

A method of reliability and functional analysis related to discrete transport systems is presented. The proposed analysis is based on modeling and simulating of the system behavior. Monte Carlo simulation is used for proper reliability and functional parameters calculation. The simulator is built using Scalable Simulation Framework (SSF). No restriction on the system structure and on a kind of distribution is the main advantage of the method. The paper presents some exemplar system modeling. The authors stress the problem of influence of the reliability parameters for final system functional measures (required time of delivery). They also propose to measure the economic quality of discrete transport system by "profit function. The presented problem is practically essential for defining an organization of vehicle maintenance and transport system logistics.
Direction finding for point and dispersed sources: VEC-MUSIC and its performance
Authors: Yan Meng
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 05 (1996)

A prime objective of array processing is to estimate the location of signal sources. The signals in many applications such as ocean exploration, radar and radio communications could appear to be from either point sources or spatially dispersed ones. Previously, a few methods have been proposed to estimate the DOA of dispersed sources. Among them, VEC-MUSIC [Wu et al. 1994] has the property of jointly estimating the DOA of point and dispersed sources. In this paper, the the unique ability of VEC-MUSIC to distinguish a point source from a dispersed source using different noise subspaces is demonstrated. The asymptotic performance of VEC-MUSIC is also analyzed.
Use Case Driven Approach to Self-Monitoring in Autonomic Systems
Authors: A. R. Haydarlou, M. A. Oey, B. J. Overeinder, F. M. T. Brazier
Venue: Proceedings of the Third International Conference on Autonomic and Autonomous Systems (2007)

Self-monitoring of autonomic distributed systems requires knowledge of the states and events of many different parts of a system. One of the main challenges is to determine which information is most crucial for analysis of a system's behaviour, and when. This paper proposes a modelbased approach to self-monitoring for which structural and behavioural models of a system are described at different levels: application, subsystem, component and class level. In this approach, a system's behaviour is monitored in the context of a hierarchy of use-cases related to these levels. The structural and behaviouralmodels are used to automatically instrument an existing distributed system. The proposed architecture of a self-monitoring engine is described as is the implementation. The models have been specified in the OntologyWeb Language (OWL) and the self-monitoring (as a part of our self-management framework) has been implemented in Java. The scenario used to illustrate the approach is that of authentication for a simplified version of a distributed portal application.
Multi-dimensional Robustness Optimization in Heterogeneous Distributed Embedded Systems
Authors: Arne Hamann, Razvan Racu, Rolf Ernst
Venue: Proceedings of the 13th IEEE Real Time and Embedded Technology and Applications Symposium (2007)

Embedded system optimization typically considers objectives such as cost, timing, buffer sizes, and power consumption. Robustness criteria, i.e. sensitivity of the system to property variations like execution and transmission delays, input data rates, CPU clock rates, etc., has found less attention despite its practical relevance. In this paper we present an approach for optimizing multi-dimensional robustness criteria in complex distributed embedded systems. The key novelty of our approach is a scalable stochastic multi-dimensional sensitivity analysis technique approximating the sought-after sensitivity front from two sides, i.e. coming from the space of working and from the space of non-working system property combinations. We utilize the proposed stochastic sensitivity analysis to derive multi-dimensional robustness metrics, which are capable of bounding the robustness of given system configurations with little computational effort. The proposed metrics can significantly speed up multi-dimensional robustness optimization by quickly identifying promising system configurations, whose in-depth robustness evaluation can be performed subsequently to the optimization process.
Antenna Load Mismatch Effects in EER-Based Transmitters for Digital Audio Broadcasting
Authors: Scott H. Melvin, Manmeet S. Goldy, Jacek Ilow
Venue: Proceedings of the Fifth Annual Conference on Communication Networks and Services Research (2007)

As terrestrial audio broadcasting is moving from the analog to the digital era, there is an interest from the broadcasting industry to re-examine the existing Amplitude Modulation (AM) and Frequency Modulation (FM) hardware. The objective is to identify potential problems which may arise when using digital signals with the existing systems. In particular, this paper analyzes the effects that an antenna impedance mismatch has on the spectrum regrowth of a hybrid analog-digital AM signal at the passband. The interest in this research stems from the difficulty in controlling the antenna impedance as it may vary with weather conditions e.g., icing on the antenna. Spectrum regrowth results are first presented in this paper when modelling the antenna load as a resonant circuit for both series and shunt load topologies when the inverse Chebychev reconstruction filter is deployed in the Envelope Elimination and Restoration (EER) amplifier. Different selectivity factors, Q, for antenna resonant circuit are considered. Following this, attempts to design more robust filters are offered that would be of the same order and would provide improved spectral performance when working with the antenna impedance deviations from the nominal resistive value of 50.
Reverse engineering the way humans rank textures
Authors: Maria Petrou, Alireza Talebpour, Alexander Kadyrov
Venue: Pattern Analysis Applications (2007)

We argue that in order to understand which features are used by humans to group textures, one must start by computing thousands of features of diverse nature, and select from those features those that allow the reproduction of perceptual groups or perceptual ranking created by humans. We use the Trace transform to produce such features here. We compare these features with those produced from the co-occurrence matrix and its variations. We show that when one is not interested in reproducing human behaviour, the elements of the co-occurrence matrix used as features perform best in terms of texture classification accuracy. However, these features cannot be &#x201c;trained&#x201d; or &#x201c;selected&#x201d; to imitate human ranking, while the features produced from the Trace transform can. We attribute this to the diverse nature of the features computed from the Trace transform.
Gaze-based infotainment agents
Authors: Helmut Prendinger, Tobias Eichner, Elisabeth André, Mitsuru Ishizuka
Venue: Proceedings of the international conference on Advances in computer entertainment technology (2007)

We propose an infotainment presentation system that relies on eyegaze as an intuitive and unobtrusive input modality. The system analyzes eye movements in real-time to infer users' attention, visual interest, and preference regarding interface objects. The application consists of a virtual showroom where a team of two highly realistic 3D agents presents product items in an entertaining and attractive way. The presentation flow adapts to the user's attentiveness and interest, or lack thereof, and thus provides a more personalized and user-attentive experience of the presentation.
Attribute-oriented fuzzy generalization in proximity- and similarity-based relational database systems: Research Articles
Authors: Rafal A. Angryk, Frederick E. Petry
Venue: International Journal of Intelligent Systems (2007)

In this article we investigate an attribute-oriented induction approach for acquisition of abstract knowledge from data stored in a fuzzy database environment. We utilize a proximity-based fuzzy database schema as the medium carrying the original information, where lack of precise information about an entity can be reflected via multiple attribute values, and the classical equivalence relation is replaced with the broader fuzzy proximity relation. We analyze in detail the process of attribute-oriented induction by concept hierarchies, utilizing the original properties of fuzzy databases to support this established data mining technique. In our approach we take full advantage of the implicit knowledge about the similarity of original attribute values, included by default in the investigated fuzzy database schemas. &copy; 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 763&ndash;779, 2007.
Minitrack "Virtual Communities"
Authors: Karine Barzilai-Nahon
Venue: Proceedings of the 40th Annual Hawaii International Conference on System Sciences (2007)

Virtual Communities have been studied from a variety of perspectives. Examples range from communities of interest to communities of practice, from gaming communities to communities of transaction. More specifically, community building and community management may be factors of key success in the digital economy. They may represent new business models in the digital economy, as well as being new venues of social interactions and social relationships.
A model of Frame and Verb Compliance in language acquisition
Authors: Rutvik Desai
Venue: Neurocomputing (2007)

Researchers studying word learning have discovered that the syntactic frame in which a word appears plays an important role in the interpretation of the word, and this importance diminishes gradually with increasing age. Interpretation of sentences based on the frame and the verb is known as Frame and Verb Compliance, respectively. Here, a connectionist model is presented that explains this shift from Frame of Verb Compliance in terms of competition between two cues-the frame and the verb-that predict causality. The model learns a miniature language by associating sentences with the corresponding ''scenes''. The most frequent cues, the frames, are learned first, resulting in frame compliance in the initial phase of learning. As the learning progresses, the less frequent but more powerful cues, the verbs, are learned and prevail over the frames resulting in verb compliance. It is argued that these phenomena can be attributed to the interaction between properties of the input and the learning mechanism, and it is not necessary to invoke specialized principles.
An Automated Framework for Validating Firewall Policy Enforcement
Authors: Adel El-Atawy, Taghrid Samak, Zein Wali, Ehab Al-Shaer, Frank Lin, Christopher Pham, Sheng Li
Venue: Proceedings of the Eighth IEEE International Workshop on Policies for Distributed Systems and Networks (2007)

The implementation of network security devices such as firewalls and IDSs are constantly being improved to accommodate higher security and performance standards. Using reliable and yet practical techniques for testing the functionality of firewall devices particularly after new filtering implementation or optimization becomes necessary to assure required security. Generating random traffic to test the functionality of firewall matching is inefficient and inaccurate as it requires an exponential number of test cases for a reasonable coverage. In addition, in most cases the policies used during testing are limited and manually generated representing fixed policy profiles. In this paper, we present a framework for automatic testing of the firewall policy enforcement or implementation using efficient random traffic and policy generation techniques. Our framework is a two-stage architecture that provides a satisfying coverage of the firewall operational states. A large variety of policies are randomly generated according to custom profiles and also based on the grammar of the access control list. Testing packets are then generated intelligently and proportional to the critical regions of the generated policies to validate the firewall enforcement for such policies. We describe our implementation of the framework based on Cisco IOS, which includes the policy generation, test cases generation, capturing and analyzing firewall output, and creating detailed test reports. Our evaluation results show that the automated security testing is not only achievable but it also offers a dramatically higher degree of confidence than random or manual testing.
Enhancements in Deterministic BIST Implementations for Improving Test of Complex SOCs
Authors: Sandeep Jain, Jais Abraham, Srinivas Kumar Vooka, Sumant Kale, Amit Dutta, Rubin Parekhji
Venue: Proceedings of the 20th International Conference on VLSI Design held jointly with 6th International Conference: Embedded Systems (2007)

Innovative solutions have been proposed to reduce the test cost of SOC designs. STUMPS (Self-Test Using PRPG and MISR Structures) architecture based logic BIST (Built-In Self- Test) is one such popular solution which attempts to reduce the cost of scan based tests by exploiting shorter scan chains in the design. To address the lower test coverage attainable through traditional random pattern logic BIST, several enhancements have been proposed. Deterministic BIST based on periodic re-seeding is one such. This paper discusses various enhancements that have been implemented in deterministic BIST, (using DBIST from SOC-BIST test suite from Synopsys, Inc.), on recent complex SOC designs in Texas Instruments (India). These include (i) controller support for internal high speed shift and self-test, (ii) programmable solution for dynamic handling of Xs, (iii) clock control methodology for reduced pattern volume of at-speed tests across multiple clock domains, and (iv) efficient diagnostics using DBIST patterns. Experimental results are presented on various designs where these features have been implemented, to illustrate the positive impact on test cost as well as test quality.
Near optimal multiple alignment within a band in polynomial time
Authors: Bin Ma, Lusheng Wang, Ming Li
Venue: Journal of Computer and System Sciences (2007)

Multiple sequence alignment is a fundamental problem in computational biology. Because of its notorious difficulties, aligning sequences within a constant band (c-diagonal) is a popular practice in bioinformatics with good practical results [D. Sankoff, J. Kruskal, Time Warps, String Edits, and Macromolecules: The Theory and Practice of Sequence Comparison, Addison-Wesley, 1983; W.R. Pearson, D. Lipman, Improved tools for biological sequence comparison, Proc. Natl. Acad. Sci. USA 85 (1988) 2444-2448; W.R. Pearson, Rapid and sensitive sequence comparison with FASTP and FASTA, Methods Enzymol. 183 (1990) 63-98; W.R. Pearson, Searching protein sequence libraries: Comparison of the sensitivity and selectivity of the Smith-Waterman and FASTA algorithms, Genomics 11 (1991) 635-650; S. Altschul, D. Lipman, Trees, stars, and multiple sequence alignment, SIAM J. Appl. Math. 49 (1989) 197-209; K. Chao, W.R. Pearson, W. Miller, Aligning two sequences within a specified diagonal band, CABIOS 8 (1992) 481-487; J.W. Fickett, Fast optimal alignment, Nucleic Acids Res. 12 (1984) 175-180; E. Ukkonen, Algorithms for approximate string matching, Inform. Control 64 (1985) 100-118; J.L. Spouge, Fast optimal alignment, CABIOS 7 (1991) 1-7]. However, the problem is still NP-hard for multiple sequences. In this paper, we present a theoretical study of this problem. In particular, for arbitrarily small @e>0, we present polynomial time algorithms that produce a multiple alignment (not necessarily c-diagonal) with cost at most 1+@e times the cost of the optimal c-diagonal alignment, under standard models of both SP alignment and consensus (star) alignment. Our algorithms for consensus alignment allow very general score schemes. In order to prove our main results, we also present similar results for SP alignment and consensus alignment, allowing only constant number of insertion and deletion gaps (of arbitrary length) per sequence on the average. These results are interesting in their own rights and they improve some results in [M. Li, B. Ma, L. Wang, Finding similar regions in many sequences, in: Proc. 31st ACM Symp. Theory of Computing, Atlanta, 1999, pp. 473-482].
Global Biclustering of Microarray Data
Authors: Thomas Wolf, Benedikt Brors, Thomas Hofmann, Elisabeth Georgii
Venue: Proceedings of the Sixth IEEE International Conference on Data Mining - Workshops (2006)

We consider the problem of simultaneously clustering genes and conditions of a gene expression data matrix. A bicluster is defined as a subset of genes that show similar behavior within a subset of conditions. Finding biclusters can be useful for revealing groups of genes involved in the same molecular process as well as groups of conditions where this process takes place. Previous work either deals with local, bicluster-based criteria or assumes a very specific structure of the data matrix (e.g. checkerboard or block-diagonal) [11]. In contrast, our goal is to find a set of flexibly arranged biclusters which is optimal in regard to a global objective function. As this is a NP-hard combinatorial problem, we describe several techniques to obtain approximate solutions. We benchmarked our approach successfully on the Alizadeh B-cell lymphoma data set [1].
Quatronome: a stomp box for jam session with movies
Authors: Jun Usui, Hirotaka Hatayama, Naohito Okude
Venue: Proceedings of the international conference on Advances in computer entertainment technology (2007)

Quatronome is a stomp box to make user's room change into his/her own stage by connecting his/her instrument or microphone and playing it. There has been much equipment aiming for good sounds. However, we found another need for players to play music of one's taste and enjoy playing with others from some fieldworks. By using Quatronome, users can play music together with three movies, and can also record the sound and movie of their performance. Thus users can play music as if he/she were a member of the band.