ppxscal/embedding_network huggingface dataset:
Data mining logic explanations from numerical data
Authors: Klaus Truemper
Venue:  (2006)

The problem of finding compact logic explanations subsumes the separation problem of machine learning, where one desires a mathematical formula or, more generally, an algorithm that decides membership of the elements of two or more given data sets. We derive a solution to the problem where the explanations are represented as propositional logic clauses. These clauses act as separation rules uncovering hidden relationships in the underlying data. The method for finding the explanations consists of several steps including discretization, introduction of uncertainty, computation of importance functions, construction of explanation formulas, and validation. The first three steps rely on a new notion of alternate random process, which is essential for identification of salient features and relationships. In several tests, the process produced compact logic explanations that were easily understood and readily verified as correct or at least potentially correct by a field expert.
On the Accurate Calculation of Miller Effect
Authors: E. Gutierrez-Cortes, D. Baez-Lopez
Venue: Proceedings of the 17th International Conference on Electronics, Communications and Computers (2007)

Miller's theorem has proven its usefulness in analyzing feedback amplifiers [1-3]. However, it does not provide accurate results for either gain, input and output impedances.[3]. This paper presents an alternative analysis of a feedback amplifier by using the Extra Element Theorem (EET) [4] and the Unified Feedback Model (UFM)[7]. The results obtained are accurate when compared to direct analysisÞ The paper presents an introduction to the EET and the UFM. Then an analysis of gain, input and output impedance of a capacitive feedback amplifier using both the EET and the UFM is shown. The accuracy of both algorithms is demonstrated by comparison to the results obtained by direct analysis.
Language-Based Program Verification via Expressive Types
Authors: Martin Sulzmann, Răzvan Voicu
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2007)

Recent developments in the area of expressive types have the prospect to supply the ordinary programmer with a programming language rich enough to verify complex program properties. Program verification is made possible via tractable type checking. We explore this possibility by considering two specific examples; verifying sortedness and resource usage verification. We show that advanced type error diagnosis methods become essential to assist the user in case of type checking failure. Our results point out new research directions for the development of programming environments in which users can write and verify their programs.
Experience in using Electronics Workbench
Authors: M. H. Rashid
Venue: Proceedings of the Frontiers in Education Conference,1997. on 27th Annual Conference. Teaching and Learning in an Era of Change. - Volume 01 (1997)

This paper summarizes the usefulness of the circuit simulator Electronics Workbench in analysis and design verifications of electronic circuits. It simulates a real laboratory environment with meters, function generator, oscilloscope, and Bode plotter. It is illustrated through examples. 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
High-Rate Analysis of Systematic Lossy Error Protection of a Predictively Encoded Source
Authors: Shantanu Rane, David Rebollo-Monedero, Bernd Girod
Venue: Proceedings of the 2007 Data Compression Conference (2007)

We consider a first-order Markov source, which is predictively encoded using a DPCM-style encoder. The quantized compressed prediction residual is trans- mitted over an erasure channel. Additionally, a Wyner-Ziv encoded version of the prediction residual is transmitted in order to provide error resilience. When the symbols from the first transmission are erased by the channel, this second description is decoded, and limits the maximum distortion that can occur. Since the quantization step size used in the second description is, in general, larger than that used in the main transmission, error protection is lossy. Using high- rate quantization theory, we derive expressions for the rate and the end-to-end distortion incurred by this system. We show that, compared to conventional lossless forward error correction, this lossy error protection scheme is robust in the sense that it allows the received signal quality to degrade gracefully when the erasure probability increases.
An Ontology-Based Context Model for Home Health Monitoring and Alerting in Chronic Patient Care Networks
Authors: F. Paganelli, D. Giuli
Venue: Proceedings of the 21st International Conference on Advanced Information Networking and Applications Workshops - Volume 02 (2007)

New care models have been defined in order to manage the increasing impact of chronic conditions. These models pose several technology-oriented challenges for home-based continuous care, requiring assistance services based on collaboration among different stakeholders: health operators, patient relatives, as well as social community members. This work describes an ontology-based context model and a related context management middleware providing a reusable and extensible application framework for monitoring and assisting patients at home. It provides flexible instruments for patient health status and social context representation, as well as reasoning mechanisms for alarm situation handling.
Minimal resource allocation network (MRAN) for magnetic recording channel equalization
Authors: D. Jianping
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 200. on IEEE International Conference - Volume 02 (2001)

This paper presents the performance results of a minimal radial basis function neural network referred to as minimal resource allocation network (MRAN) for equalization of a highly nonlinear magnetic recording data storage channel. Using a realistic magnetic channel model, MRAN equalizer's performance has been studied in the presence of channel impairments like partial erasure, additive white Gaussian noise and jitter and width variance. Compared with the earlier neural equalizers, MRAN equalizer has better performance in terms of higher signal to distortion ratios (SDR).
Extended Abstract: Provable-Security Analysis of Authenticated Encryption in Kerberos
Authors: Alexandra Boldyreva, Virendra Kumar
Venue: Proceedings of the 2007 IEEE Symposium on Security and Privacy (2007)

Kerberos is a widely-deployed network authentication protocol that is being considered for standardization. Many works have analyzed its security, identifying flaws and often suggesting fixes, thus helping the protocol's evolution. Several recent results present successful formal-methodsbased verification of a significant portion of the current version 5, and some even imply security in the computational setting. For these results to hold, encryption in Kerberos should satisfy strong cryptographic security notions. However, neither currently deployed as part of Kerberos encryption schemes nor their proposed revisions are known to provably satisfy such notions. We take a close look at Kerberos' encryption and confirm that most of the options in the current version provably provide privacy and authenticity, some with slight modification that we suggest. Our results complement the formal-methods-based analysis of Kerberos that justifies its current design.
Robust estimation for rapid speaker adaptation using discounted likelihood techniques
Authors: A. Gunawardana
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 02 (2000)

The discounted likelihood procedure, which is a robust extension of the usual EM procedure, is presented, and two approximations which lead to two different variants of the usual maximum likelihood linear regression adaptation scheme are introduced. These schemes are shown to robustly estimate speaker adaptation transforms with very little data. The evaluation is carried out on the Switchboard corpus.
Multi-task reinforcement learning: a hierarchical Bayesian approach
Authors: Aaron Wilson, Alan Fern, Soumya Ray, Prasad Tadepalli
Venue: Proceedings of the 24th international conference on Machine learning (2007)

We consider the problem of multi-task reinforcement learning, where the agent needs to solve a sequence of Markov Decision Processes (MDPs) chosen randomly from a fixed but unknown distribution. We model the distribution over MDPs using a hierarchical Bayesian infinite mixture model. For each novel MDP, we use the previously learned distribution as an informed prior for modelbased Bayesian reinforcement learning. The hierarchical Bayesian framework provides a strong prior that allows us to rapidly infer the characteristics of new environments based on previous environments, while the use of a nonparametric model allows us to quickly adapt to environments we have not encountered before. In addition, the use of infinite mixtures allows for the model to automatically learn the number of underlying MDP components. We evaluate our approach and show that it leads to significant speedups in convergence to an optimal policy after observing only a small number of tasks.
Time-frequency mapping based on non-uniform smoothed spectral representations
Authors: P. Hatziantoniou
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 03 (1999)

For audio and acoustic system responses, the auditory system tends to smooth high frequency spectral regions and to register, mainly, low-frequency components of late echoes in the time domain. To model such processing, a theoretical model for non-uniform spectral smoothing is introduced allowing the choice of arbitrary frequency resolution profiles to match such auditory features. This generalized framework is extended to allow mapping of such smoothing spectra into the time domain.
Strategies for improving the modeling and interpretability of Bayesian networks
Authors: Ádamo L. de Santana, Carlos R. Francês, Cláudio A. Rocha, Solon V. Carvalho, Nandamudi L. Vijaykumar, Liviane P. Rego, João C. Costa
Venue: Data Knowledge Engineering (2007)

One of the main factors for the knowledge discovery success is related to the comprehensibility of the patterns discovered by applying data mining techniques. Amongst which we can point out the Bayesian networks as one of the most prominent when considering the easiness of knowledge interpretation achieved. Bayesian networks, however, present limitations and disadvantages regarding their use and applicability. This paper presents an extension for the improvement of Bayesian networks, treating aspects such as performance, as well as interpretability and use of their results; incorporating genetic algorithms in the model, multivariate regression for structure learning and temporal aspects using Markov chains.
Cooperative navigation of autonomous vehicles in a known environment
Authors: Shreecharan Kanchanavally
Venue:  (2006)

One of the critical goals in the robotics community is to create autonomous robots that interact with unknown environments and will execute high level tasks without human intervention. Developing the technology necessary for autonomous robots is a formidable undertaking with deep interweaved ramifications in automated reasoning, perception and control. It raises many important problems of which motion planning is one of them. Navigation or path planning means to determine how to move an object from its original location and orientation to a goal configuration while avoiding collision with obstacles. The main purpose of this dissertation is to propose cooperative path planning for a group of robots navigating in a known environment. We solve this problem of path planning by introducing a general theory for a set of interconnected Multi Input Multi Output feedback linearizable systems. We show how this theory can be implemented for the path planning of autonomous ground and aerial vehicles. Convergence of a vehicle to a invariant set around the target location is analyzed using the Lyapunov stability method. We propose an obstacle avoidance algorithm by considering the problem as steering the states of a dynamic system to a desired position while avoiding specific regions of state space. Sufficient analytical conditions for avoiding a forbidden region in terms of state trajectories and a set of barrier functions are derived using Lyapunov stability analysis. We then extend the concept of path planning to non feedback linearizable kinematic unicycle models possessing fixed speed and control saturation. The only available control sets the heading of the vehicle. It is shown that a suitable output function allows for convergence of the position states of the unicycle to a bounded neighborhood around a desired set point when the control input is subject to a saturation nonlinearity. Formation control for a group of such vehicles is studied in this dissertation. We also proposes a possible solution to the problem of tracking mobile targets by group of uninhabited autonomous aerial vehicle (UAV) with communication constraints when only the targets initial position is known. We introduce probabilistic based, time-varying Hospitability maps, which consider the UAV location as points of low hospitability, and extend the Past, Present and Predicted Future (PPP) search algorithm to deal with not only static, but also mobile targets. The practical feasibility of the proposed algorithms are studied by implementing them on Pioneer-3 robots.
Building a scalable and efficient component oriented system sing CORBA: active badge system case study
Authors: Jakub Szymaszek, Andrzej Uszok, Krzysztof Zielinski
Venue: Proceedings of the 4th conference on USENIX Conference on Object-Oriented Technologies and Systems - Volume 4 (1998)

This paper presents experience gathered when implementing the localization system for an office environment in CORBA. It describes methods which enable preserving fine-grained object-oriented structure of the system and achieving efficient performance at the same time. The presented study is a practical lesson about the implementation of a scalable system oriented towards information dissemination. The key idea is to represent a large observable collection of objects by a repository that provides access to them both as individual CORBA objects and data records. The proper usage of this duality may have substantial influence on the overall system performance. The repository is equipped with a scalable notification mechanism built around a notification dispatcher and notification tree concepts. Fundamental features of the proposed solution are illustrated by a performance study and a representative application.
Non-interactive key establishment in mobile ad hoc networks
Authors: Zhenjiang Li, J. J. Garcia-Luna-Aceves
Venue: Ad Hoc Networks (2007)

We present a new non-interactive key agreement and progression (NIKAP) scheme for mobile ad hoc networks (MANETs), which does not require an on-line centralized authority, can non-interactively establish and update pairwise keys between nodes, is configurable to operate synchronously or asynchronously, and supports differentiated security services w.r.t. the given security policies. NIKAP is valuable to scenarios where pairwise keys are desired to be established without explicit negotiation over insecure channels, and also need to be updated frequently.
Improving crossover operator for real-coded genetic algorithms using virtual parents
Authors: Domingo Ortiz-Boyer, César Hervás-Martínez, Nicolás García-Pedrajas
Venue: Journal of Heuristics (2007)

The crossover operator is the most innovative and relevant operator in real-coded genetic algorithms. In this work we propose a new strategy to improve the performance of this operator by the creation of virtual parents obtained from the population parameters of localisation and dispersion of the best individuals. The idea consists of mating these virtual parents with individuals of the population. In this way, the offspring are created in the most promising regions. This strategy has been incorporated into several crossover operators. After analysing the results we can conclude that this strategy significantly improves the performance of the algorithm in most problems analysed.
Prediction Models for a Smart Home Based Health Care System
Authors: Vikramaditya R. Jakkula, Diane J. Cook, Gaurav Jain
Venue: Proceedings of the 21st International Conference on Advanced Information Networking and Applications Workshops - Volume 02 (2007)

Technology holds great potential for improvements in the field of health care used in intelligent environments, with homes becoming the centers for proactive health care. Smart health care systems at home can be used to provide such solutions. A technology-assisted smart health care system would enable elderly people to lead their independent lifestyle away from hospitals and also avoid having expensive caregivers. In this paper, we present one such solution where a prediction model in an intelligent smart home system can be used for identifying health trends over time and enable prediction of future trends which can aid in providing preventive measures.
Evolutionary, developmental neural networks for robust robotic control
Authors: Rodney A. Brooks
Venue:  (2006)

The use of artificial evolution to synthesize controllers for physical robots is still in its infancy. Most applications are on very simple robots in artificial environments, and even these examples struggle to span the "reality gap," a name given to the difference between the performance of a simulated robot and the performance of a real robot using the same evolved controller. This dissertation describes three methods for improving the use of artificial evolution as a tool for generating controllers for physical robots. First, the evolutionary process must incorporate testing on the physical robot. Second, repeated structure on the robot should be exploited. Finally, prior knowledge about the robot and task should be meaningfully incorporated. The impact of these three methods, both in simulation and on physical robots, is demonstrated, quantified, and compared to hand-designed controllers. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)
Middleware for Ubiquitous Service-Oriented Spaces on the Web
Authors: Geert Vanderhulst, Kris Luyten, Karin Coninx
Venue: Proceedings of the 21st International Conference on Advanced Information Networking and Applications Workshops - Volume 02 (2007)

Web services are todays preferred vehicle for creating service-oriented architectures (SOA). Due to the boom of personal networked devices, the Web also found its way to the mobile space. This gives rise to device hosted mobile services that deliver functionality over a wireless network. There is potential to unite these services in a collaborative service space and exploit them as building blocks for distributed applications. This paper concentrates on a light-weight middleware layer to facilitate the integration, accessibility and orchestration of Web-based services in heterogeneous environments. Leveraging Web technology, this layer allows to interconnect serverless, peer-to-peer services deployed across federations of devices. We present its value in a ubiquitous application.
Spatial signature estimation in cyclic cumulant domain and multiuser signal separation in uplink SDMA
Authors: Qinye Yin
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 05 (1999)

In smart antenna systems (SAS), the most compelling research work is the space-division multiple-access (SDMA) which includes uplink source separation and downlink selective transmission. We propose a subspace-based spatial signature estimation algorithm of cochannel multiuser signals by jointly exploiting cumulant and cyclostationarity, and apply it to multiuser signal copy in uplink SDMA. Our method constructs a new matrix called the spatial signature matrix (SS matrix), and estimates the multiuser spatial signature through the eigen-decomposition of the SS matrix. Based on estimated spatial signature, a spatial filter bank is designed for cochannel multiuser waveform estimation. Computer simulations show that the spatial response of the filter bank can be used to find the direction-of-arrival (DOA) of the correlated multiuser signals.
The Architecture and Development Flow of the S5 Software Configurable Processor
Authors: Jeffrey M. Arnold
Venue: Journal of VLSI Signal Processing Systems (2007)

A software configurable processor (SCP) is a hybrid device that couples a conventional processor datapath with programmable logic to allow application programs to dynamically customize the instruction set. SCP architectures can offer significant performance gains by exploiting data parallelism, operator specialization and deep pipelines. The S5000 is a family of high performance software configurable processors for embedded applications. The S5000 consists of a conventional 32-bit RISC processor coupled with a programmable Instruction Set Extension Fabric (ISEF). To develop an application for the S5 the programmer identifies critical sections to be accelerated, writes one or more extension instructions as functions in a variant of the C programming language, and accesses those functions from the application program. Performance gains of more than an order of magnitude over the unaccelerated processor can be achieved.
Promoting Digital Forensics Awareness through the University of Alaska Fairbanks ASSERT Center
Authors: Kara Nance, Brian Hay, Christopher Hecker
Venue: Proceedings of the 40th Annual Hawaii International Conference on System Sciences (2007)

As a Center of Academic Excellence (CAE) in Information Assurance Education, the University of Alaska Fairbanks is committed to promoting a culture of awareness and advancement of the current state of knowledge in the field of information assurance in Alaska and beyond through dedicated research, education, training, and outreach. The Advanced System Security Education, Research, and Training (ASSERT) Center provides resources and education in information assurance within the University, and also to the Alaskan community, including schools, government, industry, and the general public. This paper presents a survey of the ASSERT Center digital forensics educational resources and outreach activities that are being used to identify and meet the needs of the State of Alaska with respect to the protection of digital assets. These include programs targeting K-12 students, K-12 teachers, business personnel, community members, and higher education audiences.
Architecting Pervasive Computing Systems for Privacy: A Survey
Authors: Roberto Speicys Cardoso, Valerie Issarny
Venue: Proceedings of the Sixth Working IEEE/IFIP Conference on Software Architecture (2007)

In pervasive computing systems, a higher number of interactions will be mediated by computers, amplifying the menace to privacy. Privacy protection in pervasive environments is still a big issue, despite the growing number of works on this subject as evidenced by this survey. In this paper, we propose a taxonomy for privacy invasion attacks, classify existing privacy enhancing technologies according to the protection provided for those attacks, and introduce a service-oriented privacy-enhanced architecture for pervasive computing.